Query: coronavirus under reporting [SEP] how has lack of testing availability led to underreporting of true incidence of Covid-19? [SEP] Looking for studies answering questions of impact of lack of complete testing for Covid-19 on incidence and prevalence of Covid-19.

title: The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: what lessons have we learned?
abstract: To provide an overview of the three major deadly coronaviruses and identify areas for improvement of future preparedness plans, as well as provide a critical assessment of the risk factors and actionable items for stopping their spread, utilizing lessons learned from the first two deadly coronavirus outbreaks, as well as initial reports from the current novel coronavirus (COVID-19) epidemic in Wuhan, China.  Utilizing the Centers for Disease Control and Prevention (CDC, USA) website, and a comprehensive review of PubMed literature, we obtained information regarding clinical signs and symptoms, treatment and diagnosis, transmission methods, protection methods and risk factors for Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS) and COVID-19. Comparisons between the viruses were made.  Inadequate risk assessment regarding the urgency of the situation, and limited reporting on the virus within China has, in part, led to the rapid spread of COVID-19 throughout mainland China and into proximal and distant countries. Compared with SARS and MERS, COVID-19 has spread more rapidly, due in part to increased globalization and the focus of the epidemic. Wuhan, China is a large hub connecting the North, South, East and West of China via railways and a major international airport. The availability of connecting flights, the timing of the outbreak during the Chinese (Lunar) New Year, and the massive rail transit hub located in Wuhan has enabled the virus to perforate throughout China, and eventually, globally.  We conclude that we did not learn from the two prior epidemics of coronavirus and were ill-prepared to deal with the challenges the COVID-19 epidemic has posed. Future research should attempt to address the uses and implications of internet of things (IoT) technologies for mapping the spread of infection.

title: Increased Detection coupled with Social Distancing and Health Capacity Planning Reduce the Burden of COVID-19 Cases and Fatalities: A Proof of Concept Study using a Stochastic Computational Simulation Model
abstract: In absence of any vaccine, the Corona Virus Disease 2019 (COVID-19) pandemic is being contained through a non-pharmaceutical measure termed Social Distancing (SD). However, whether SD alone is enough to flatten the epidemic curve is debatable. Using a Stochastic Computational Simulation Model, we investigated the impact of increasing SD, hospital beds and COVID-19 detection rates in preventing COVID-19 cases and fatalities.  The Stochastic Simulation Model was built using the EpiModel package in R. As a proof of concept study, we ran the simulation on Kasaragod, the most affected district in Kerala. We added 3 compartments to the SEIR model to obtain a SEIQHRF (Susceptible-Exposed-Infectious-Quarantined-Hospitalised-Recovered-Fatal) model.  Implementing SD only delayed the appearance of peak prevalence of COVID-19 cases. Doubling of hospital beds could not reduce the fatal cases probably due to its overwhelming number compared to the hospital beds. Increasing detection rates could significantly flatten the curve and reduce the peak prevalence of cases (increasing detection rate by 5 times could reduce case number to half).  An effective strategy to contain the epidemic spread of COVID-19 in India is to increase detection rates in combination with SD measures and increase in hospital beds.

title: COVID-19 related mortality and spread of disease in long-term care: first findings from a living systematic review of emerging evidence
abstract: Policy responses to mitigate the impact of the COVID-19 pandemic on long-term care (LTC) require robust and timely evidence on mortality and spread of the disease in these settings. The aim of this living systematic review is to synthesise early international evidence on mortality rates and incidence of COVID-19 among people who use and provide LTC.  We report the initial findings of a living systematic review (CRD42020183557), including studies identified through database searches up to 29 May 2020. We searched seven databases (MEDLINE; Embase; CINAHL Plus; Web of Science; Global Health; WHO COVID-19 Research Database; medRxiv) to identify all studies reporting primary data on COVID-19 related mortality and incidence of disease among LTC users and staff. We excluded studies not focusing on LTC. Included primary studies were critically appraised and results on number of deaths and COVID-19 related mortality rates, case fatality rates, and excess deaths (co-primary outcomes), as well as incidence of disease, hospitalisations, and ICU admissions were synthesised narratively. We further included official figures on number of deaths in LTC.  A total of 30 study reports for 27 unique primary studies or outbreak reports were included. Outbreak investigations in LTC facilities found COVID-19 incidence rates of between 0.0% and 71.7% among residents and between 1.5% and 64.0% among staff. Mortality rates varied from 0.0% to 9.9% of all residents at outbreak facilities, with case fatality rates between 0.0% and 33.7%. In included studies, no LTC staff members had died. LTC residents accounted for between 0% (Hong Kong) and 82% (Canada) of COVID-related deaths, according to official figures.  Long-term care users have been particularly vulnerable to the COVID-19 pandemic. However, we found wide variation in spread of disease and mortality rates between outbreaks at individual LTC facilities. Further research into the factors determining successful prevention and containment of COVID-19 outbreaks is needed to protect long-term care users and staff.

title: An outbreak of COVID‐19 caused by a new coronavirus: what we know so far

title: Special report: Early use of ICD-10-CM code "U07.1, COVID-19" to identify 2019 novel coronavirus cases in Military Health System administrative data.
abstract: This report describes early exploratory analysis of ICD-10-CM code U07.1 (2019-nCoV acute respiratory disease [COVID-19]) to assess the use of administrative data for case ascertainment, syndromic surveillance, and future epidemiological studies. Out of the 2,950 possible COVID-19 cases identified between 1 April 2020 and 4 May 2020, 600 (20.3%) were detected in the Defense Medical Surveillance System (DMSS) and not in the Disease Reporting System internet (DRSi) or in Health Level 7 laboratory data from the Composite Health Care System. Among the 150 out of 600 cases identified exclusively in the DMSS and selected for Armed Forces Health Longitudinal Technology Application (AHLTA) review, 16 (10.7%) had a certified positive lab result in AHLTA, 17 (11.3%) met Council of State and Territorial Epidemiologists (CSTE) criteria for a probable case, 46 (30.7%) were not cases based on CSTE criteria, and 71 (47.3%) had evidence of a positive lab result from an outside source. Lack of full capture of lab results may continue to be a challenge as the variety of available tests expands. Administrative data may provide an important stopgap measure for detecting lab positive cases, pending incorporation of new COVID-19 tests and standardization of test and result nomenclature.

title: Testing times in Coronavirus disease (Covid-19): A tale of two nations
abstract: The Coronavirus Disease (Covid-19) pandemic is caused by the severe acute respiratory syndrome virus 2 and was first identified in Wuhan, China, in December 2019. The disease spread globally, leading to the World Health Organization declaring it a pandemic in March 2020. The condition is often fatal in its severe form. As it is a previously unknown virus, no treatment is identified or any vaccine available. The burden of disease control and containment, therefore, falls upon a robust and geographically appropriate testing strategy. Testing policies are modified, in turn, by the rapidly evolving patterns of the disease in various nations and by the evolving nature of tests in development. It is, therefore, helpful to study different national models to learn from the experience of different countries. This article compares testing strategies in the UK and India as the two countries travel different paths in controlling the pandemic. The UK is one of the most severely affected countries in the world. Initially restricted to hospitalised patients, the UK has broadened the scope of testing to many categories of individuals. In contrast, India appears to have a lower prevalence of the infection. However, the large Indian population and relatively insufficient testing capacities so far have led India to adopt a different testing trajectory, with the testing currently focused on high-risk groups in the community and hospitals. Owing to the rapidly changing nature of the disease, there can be no ‘one-size-fits-all’ policy but should be based on country-specific circumstances.

title: Efficiency analysis of major cruise lines
abstract: Three major cruise lines account for 82% of the total market share. Their financial statements show different results between the operating incomes and net incomes over time. To examine the major causes of the differences, this study measured the efficiency of the top three cruise lines to develop a network DEA model to analyze the cruise operations at two stages, namely operating and non-operating stages. In addition, the determinants of the efficiencies were examined using a bootstrapped-truncated regression model. Overall, cruise lines were efficient at the operating stage, but varied widely in the efficiency of the non-operating stage. Cruise lines attempting high capacity expansion were relatively inefficient because of the heavy interest payments arising from the high debt-to-capital ratio. Moreover, the neglected hedging policy regarding the financial risks also contributed to the inefficiency.

title: Loss of Taste and Smell as Distinguishing Symptoms of COVID-19
abstract: Olfactory and taste dysfunctions have emerged as symptoms of COVID-19. Among individuals with COVID-19 enrolled in a household study, loss of taste and/or smell was the fourth most commonly reported symptom (26/42; 62%), and among household contacts, it had the highest positive predictive value (83%; 95% CI: 55-95%) for COVID-19. These findings support consideration of loss of taste and/or smell in possible case identification and testing prioritization for COVID-19.

title: Modelling the epidemiological trend and behavior of COVID-19 in Italy
abstract: As of March 16, 2020, over 185,000 across the world, Italy became the red hotspot for the COVID-19 pandemic after China. With over 35,000 cases and 2900 deaths reported in the month of March in Italy, it is necessary to stimulate epidemic trend to understand the behavior of COVID-19 in Italy. By S.E.I.R. simulation, we estimated the most representative epidemic parameters occurred from March 1 to 14, 2020, thus being able to evaluate the consistency of the containment rules and identify possible Sars-Cov-2 local mutations. Our estimations are based on some assumptions and limitations exited.

title: Full spectrum of COVID-19 severity still being depicted

title: Estimating Sensitivity of Laboratory Testing for Influenza in Canada through Modelling
abstract: The weekly proportion of laboratory tests that are positive for influenza is used in public health surveillance systems to identify periods of influenza activity. We aimed to estimate the sensitivity of influenza testing in Canada based on results of a national respiratory virus surveillance system.  The weekly number of influenza-negative tests from 1999 to 2006 was modelled as a function of laboratory-confirmed positive tests for influenza, respiratory syncytial virus (RSV), adenovirus and parainfluenza viruses, seasonality, and trend using Poisson regression. Sensitivity was calculated as the number of influenza positive tests divided by the number of influenza positive tests plus the model-estimated number of false negative tests. The sensitivity of influenza testing was estimated to be 33% (95%CI 32–34%), varying from 30–40% depending on the season and region.  The estimated sensitivity of influenza tests reported to this national laboratory surveillance system is considerably less than reported test characteristics for most laboratory tests. A number of factors may explain this difference, including sample quality and specimen procurement issues as well as test characteristics. Improved diagnosis would permit better estimation of the burden of influenza.

title: Predicting Whom to Test is More Important Than More Tests - Modeling the Impact of Testing on the Spread of COVID-19 Virus By True Positive Rate Estimation
abstract: I estimate plausible true positive (TP) rates for the number of COVID-19 tests per day, most relevant when the number of test is on the same order of magnitude as number of infected persons. I then modify a standard SEIR model to model current growth patterns and detection rates in South Korea and New York state. Although reducing transmission rates have the largest impact, increasing TP rates by ~10% in New York can have an impact equal to adding tens of thousands of new tests per day. Increasing both TP rates and tests per day together can have significant impacts and likely be more easily sustained than social distancing restrictions. Systematic and standardized data collection, even beyond contact tracking, should be ongoing and quickly made available for research teams to maximize the efficacy of testing.

title: Protecting Chinese healthcare workers while combating the 2019 novel coronavirus
abstract: Hospital-associated transmission is an important route of spreading the 2019 novel coronavirus (2019-nCoV) infection and pneumonia (Corona Virus Disease 2019, COVID-19) . Healthcare workers (HCWs) are at high risk while combating COVID-19 at the very frontline, and nosocomial outbreaks among HCWs are not unusual in similar settings; the 2003 severe acute respiratory syndrome (SARS) outbreak led to over 966 HCW infections with 1.4% deaths in mainland China . As of 11 February 2020, 3019 HCWs might have been infected with 2019-nCov in China, 1716 HCW cases were confirmed by nucleic acid testing[3], and at least 6 HCWs died, including the famous whistleblower Dr Li Wenliang. In view of this severe situation, we are recommending urgent interventions to help to protect HCWs.

title: Forecasting the cumulative number of COVID-19 deaths in China: a Boltzmann function-based modeling study
abstract: The COVID-19 outbreak is ongoing in China. Here, Boltzmann function-based analyses reveal the potential total numbers of COVID-19 deaths: 3,260 (95% confidence interval [CI], 3187–3394) in China; 110 (95% CI, 109–112) in Hubei Province; 3,174 (95% CI, 3095–3270) outside Hubei; 2,550 (95% CI, 2494–2621) in Wuhan City; and 617 (95% CI, 607–632) outside Wuhan.

title: A web-based Diagnostic Tool for COVID-19 Using Machine Learning on Chest Radiographs (CXR)
abstract: This paper reports the development and web deployment of an inference model for Coronavirus COVID-19 using machine vision on chest radiographs (CXR). The transfer learning from the Residual Network (RESNET-50) was leveraged for model development on CXR images from healthy individuals, bacterial and viral pneumonia, and COVID-19 positives patients. The performance metrics showed an accuracy of 99%, a recall valued of 99.8%, a precision of 99% and an F1 score of 99.8% for COVID-19 inference. The model was further successfully validated on CXR images from an independent repository. The implemented model was deployed with a web graphical user interface for inference (https://medics-inference.onrender.com ) for the medical research community; an associated cron job is scheduled to continue the learning process when novel and validated information becomes available

title: Understanding the emerging coronavirus: what it means for health security and infection prevention

title: Estimation of Unreported Novel Coronavirus (SARS-CoV-2) Infections from Reported Deaths: A Susceptible–Exposed–Infectious–Recovered–Dead Model
abstract: In the midst of the novel coronavirus (SARS-CoV-2) epidemic, examining reported case data could lead to biased speculations and conclusions. Indeed, estimation of unreported infections is crucial for a better understanding of the current emergency in China and in other countries. In this study, we aimed to estimate the unreported number of infections in China prior to the 23 January 2020 restrictions. To do this, we developed a Susceptible–Exposed–Infectious–Recovered–Dead (SEIRD) model that estimated unreported infections from the reported number of deaths. Our approach relied on the fact that observed deaths were less likely to be affected by ascertainment biases than reported infections. Interestingly, we estimated that the basic reproductive number (R(0)) was 2.43 (95%CI = 2.42–2.44) at the beginning of the epidemic and that 92.9% (95%CI = 92.5%–93.1%) of total cases were not reported. Similarly, the proportion of unreported new infections by day ranged from 52.1% to 100%, with a total of 91.8% (95%CI = 91.6%–92.1%) of infections going unreported. Agreement between our estimates and those from previous studies proves that our approach is reliable for estimating the prevalence and incidence of undocumented SARS-CoV-2 infections. Once it has been tested on Chinese data, our model could be applied to other countries with different surveillance and testing policies.

title: Hyperlocal Postcode Based Crowdsourced Surveillance Systems in the COVID-19 Pandemic Response
abstract: The SARS-CoV-2 pandemic has rapidly saturated healthcare resources across the globe and has led to a restricted screening process, hindering efforts at comprehensive case detection. This has not only facilitated community spread but has also resulted in an underestimation of the true incidence of disease, a statistic which is useful for policy making aimed at controlling the current pandemic and in preparing for future outbreaks. In this perspective, we present a crowdsourced platform developed by us for the true estimation of all SARS-CoV-2 infections in the community, through active self-reporting and layering other authentic datasets. The granularity of data captured by this system could prove to be useful in assisting governments to identify SARS-CoV-2 hotspots in the community facilitating lifting of restrictions in a controlled fashion.

title: Ascertainment rate of novel coronavirus disease (COVID-19) in Japan
abstract: We analyzed the epidemiological dataset of confirmed cases with COVID-19 in Japan as of 28 February 2020 and estimated the number of severe and non-severe cases, accounting for under-ascertainment. The ascertainment rate of non-severe cases was estimated at 0.44 (95% confidence interval: 0.37, 0.50), indicating that unbiased number of non-cases would be more than twice the reported count. Severe cases are twice more likely diagnosed and reported than other cases.

title: Angiotensin receptor blockers as tentative SARS‐CoV‐2 therapeutics
abstract: At the time of writing this commentary (February 2020), the coronavirus COVID‐19 epidemic has already resulted in more fatalities compared with the SARS and MERS coronavirus epidemics combined. Therapeutics that may assist to contain its rapid spread and reduce its high mortality rates are urgently needed. Developing vaccines against the SARS‐CoV‐2 virus may take many months. Moreover, vaccines based on viral‐encoded peptides may not be effective against future coronavirus epidemics, as virus mutations could make them futile. Indeed, new Influenza virus strains emerge every year, requiring new immunizations. A tentative suggestion based on existing therapeutics, which would likely be resistant to new coronavirus mutations, is to use available angiotensin receptor 1 (AT1R) blockers, such as losartan, as therapeutics for reducing the aggressiveness and mortality from SARS‐CoV‐2 virus infections. This idea is based on observations that the angiotensin‐converting enzyme 2 (ACE2) very likely serves as the binding site for SARS‐CoV‐2, the strain implicated in the current COVID‐19 epidemic, similarly to strain SARS‐CoV implicated in the 2002–2003 SARS epidemic. This commentary elaborates on the idea of considering AT1R blockers as tentative treatment for SARS‐CoV‐2 infections, and proposes a research direction based on datamining of clinical patient records for assessing its feasibility.

title: Estimate of COVID-19 case prevalence in India based on surveillance data of patients with severe acute respiratory illness
abstract: In absence of extensive testing for SARS-CoV-2, true prevalence of COVID-19 cases in India remain unknown. In this study, a conservative estimate of prevalence of COVID-19 is calculated based on the age wise COVID-19 positivity rate among patients with severe respiratory illness as reported by Indian Council of Medical Research. Calculations in the study estimates a cumulative number of 17151 COVID-19 positive cases by the end of April 2, 2020.

title: Epidemiology of viral respiratory tract infections in a prospective cohort of infants and toddlers attending daycare
abstract: The epidemiology of respiratory tract infections (RTIs) in a daycare cohort has not been explored using molecular techniques.  Determine the overall incidence of RTIs in a daycare cohort using real-time reverse transcriptase polymerase chain reaction (RT-PCR). (2) Determine the relative incidence and impact of specific respiratory viruses, and characterize and compare clinical features associated with these pathogens.  In this prospective cohort study conducted from February 2006 to April 2008, nasal swabs were obtained from symptomatic children ages 0–30 months enrolled in fulltime daycare. RT-PCR was performed to detect respiratory syncytial virus (RSV), human metapneumovirus (MPV), influenza (Flu) viruses A and B, parainfluenza (PIV), adenovirus (AdV), human coronaviruses (CoV) and rhinovirus (RhV). Symptom diaries were completed for each illness.  We followed 119 children (mean age 10 months; range 2–24 months) for 115 child years. The mean annual incidence of RTI per child was 4.2 the first year and 1.2 the second year of the study. At least 1 virus was identified in 67% RTIs. Co-infections were common (27% RTIs), with RhV, CoV, and AdV the most common co-pathogens. PIV was identified in 12% of RTIs with a high incidence of PIV4. The viruses with the greatest impact on our population were RSV, RhV and AdV.  Using molecular techniques, viruses were identified in approximately twice as many RTIs as previously reported in a daycare cohort. Infections with newly identified viruses, such as HMPV and CoV subtypes were less frequent and severe than infections with RSV, AdV and RhV.

title: Pharmacovigilance in Patients with Diabetes: A Data-Driven Analysis Identifying Specific RAS Antagonists with Adverse Pulmonary Safety Profiles That Have Implications for COVID-19 Morbidity and Mortality
abstract: Current demographic information from China reports that 10-19% of patients hospitalized with COVID-19 were diabetic. Angiotensin converting enzyme inhibitors (ACEIs) and angiotensin-II receptor blockers (ARBs) are considered first-line agents in diabetics due to their nephroprotective effects but administration of these drugs leads to upregulation of angiotensin-converting-enzyme-2 (ACE2), responsible for viral entry of severe-acute-respiratory-distress-syndrome, coronavirus-2 (SARS-CoV-2). Data is lacking to determine what pulmonary effects ACEIs/ARBs may have in patients with diabetes, which could be relevant in the management of patients infected with SARS-CoV-2. In this study, the aim was to assess the prevalence of pulmonary adverse drug effects (ADEs) in diabetic patients taking ACEI or ARBs to help provide guidance as to how these medications could affect outcomes in acute respiratory illness, such as SARS-CoV-2 infection.  1DATA, a unique data platform resulting from collaboration across veterinary and human healthcare, utilized an intelligent medicine recommender system (1DrugAssist) developed using several national and international databases, to evaluate all ADEs reported to the FDA for patients with diabetes taking ACEIs or ARBs.  Mining of this data elucidated the proportion of a cluster of pulmonary ADEs associated with specific medications in these classes, which may aid healthcare professionals in understanding how these medications could worsen or predispose patients with diabetes to infections affecting the respiratory system specifically, COVID-19. Based on this data mining, Captopril was found to have a statistically significantly higher incidence of pulmonary ADEs compared to other ACEIs (P = 0.005) as well as ARBs (P = 0.012), though other specific drugs also had important pulmonary ADEs associated with their use.  These analyses suggest that pharmacists and clinicians will need to consider specific medication’s adverse event profile, particularly captopril, and how this profile may affect infections and other acute disease states that alter pulmonary function, such as COVID-19.

title: The Challenge of Using Epidemiological Case Count Data: The Example of Confirmed COVID-19 Cases and the Weather
abstract: The publicly available data on COVID-19 cases provides an opportunity to better understand this new disease. However, strong attention needs to be paid to the limitations of the data to avoid making inaccurate conclusions. This article, which focuses on the relationship between the weather and COVID-19, raises the concern that the same factors influencing the spread of the disease might also affect the number of tests performed and who gets tested. For example, weather conditions impact the prevalence of respiratory diseases with symptoms similar to COVID-19, and this will likely influence the number of tests performed. This general limitation could severely undermine any similar analysis using existing COVID-19 data or similar epidemiological data, which could, therefore, mislead decision-makers on questions of great policy relevance.

title: Implications of SARSr-CoV 2 infection in thalassemias: Do patients fall into the "high clinical risk" category?
abstract: We're all flying blind regarding coronavirus, but it's fair to think if thalassemic patients are particularly vulnerable to SARS-COV-2 infection or are at potential higher risk of complications from COVID-19 than normal population, specially when they become older. The frustrating thing is that, right now, this virus is still new. It only came to the attention of the World Health Organization at the end of December. Very few cases in thalassemia have so far been reported; is this due to lack of testing or a true lack of infection/susceptibility? However, we believe that more data should be collected to better characterise the impact of SARS-CoV-2 infection in patients with thalassemias. Therefore, a multicenter registry and the collection of comprehensive data from both positive COVID-19 thalassemia major and non-transfusion dependent thalassemia are necessary to clarify debated issues. In the meantime an early and vigilant monitoring along with high quality supportive care are needed in thalassemic patients at high risk for SARS-CoV-2 infection.

title: ‘These are answers we need.’ WHO plans global study to discover true extent of coronavirus infections
abstract: In an effort to understand how many people have been infected with the new coronavirus, the World Health Organization (WHO) is planning a coordinated study to test blood samples for the presence of antibodies to the virus Called Solidarity II, the program, which will involve more than half a dozen countries around the globe, will launch in the coming days, says Maria Van Kerkhove, who is helping coordinate WHO’s COVID-19 response Knowing the true number of cases—including mild ones—will help pin down the prevalence and mortality rate of COVID-19 in different age groups It will also help policymakers decide how long shutdowns and quarantines should last “These are answers we need, and we need the right answers to drive policy,” WHO’s executive director for health emergencies, Michael Ryan, told a press briefing on 27 March

title: A Cautionary Tale of False-Negative Nasopharyngeal COVID-19 Testing
abstract: There remains diagnostic uncertainty regarding the sensitivity of reverse transcription polymerase chain reaction in detection of SARS-CoV-2 from nasopharyngeal specimens. We present a case where two nasopharyngeal specimens were negative, followed by a positive sputum sample. Serial testing for COVID-19 is indicated in patients with high pretest probability of disease.

title: Impact of virus testing on COVID-19 case fatality rate: estimate using a fixed-effects model
abstract: In response to the SARS-CoV2 pandemic, governments have adopted a variety of public health measures. There are variations in how much testing has been done across countries. South Korea, Germany, and Iceland take the bet of massive testing of their population. Whereas tests were not performed widely in southern European countries. As the former undergo a lower case-fatality rate due to the COVID-19 than the latter, the impact of the testing strategy must be investigated. In this study, we aimed to evaluate the impact of testing on the case fatality rate.  We use data on inpatients across French geographic areas and propose a novel methodology that exploits policy discontinuities at region borders to estimate the effect of COVID-19 tests on the case-fatality rate. In France, testing policies are determined locally. We compare all contiguous department pairs located on the opposite sides of a region border. The heterogeneity in testing rate between department pairs together with the similarities in other dimensions allow us to mimic the existence of treatment and control groups and to identify the impact of testing on mortality.  The increase of one percentage point in the test rate is associated with a decrease of 0.001 percentage point in the death rate. In other words, for each additional 1000 tests, one person would have remained alive.  Massive population testing could have a significant effect on mortality in different ways. Mass testing may help decision-makers to implement healthcare measures to limit the spread of the disease.

title: Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic
abstract: originating from China has rapidly crossed borders, infecting people throughout the whole world. This phenomenon has led to a massive public reaction; the media has been reporting continuously across borders to keep all informed about the pandemic situation. All these things are creating a lot of concern for people leading to heightened levels of anxiety. Pandemics can lead to heightened levels of stress; Anxiety is a common response to any stressful situation. This study attempted to assess the knowledge, attitude, anxiety experience, and perceived mental healthcare need among adult Indian population during the COVID-19 pandemic. An online survey was conducted using a semi-structured questionnaire using a non-probability snowball sampling technique. A total of 662 responses were received. The responders had a moderate level of knowledge about the COVID-19 infection and adequate knowledge about its preventive aspects. The attitude towards COVID-19 showed peoples' willingness to follow government guidelines on quarantine and social distancing. The anxiety levels identified in the study were high. More than 80 % of the people were preoccupied with the thoughts of COVID-19 and 72 % reported the need to use gloves, and sanitizers. In this study, sleep difficulties, paranoia about acquiring COVID-19 infection and distress related social media were reported in 12.5 %, 37.8 %, and 36.4 % participants respectively. The perceived mental healthcare need was seen in more than 80 % of participants. There is a need to intensify the awareness and address the mental health issues of people during this COVID-19 pandemic.

title: Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases
abstract: The COVID-19 outbreak is a global pandemic with community circulation in many countries, including the United States, with confirmed cases in all states. The course of this pandemic will be shaped by how governments enact timely policies and disseminate information and by how the public reacts to policies and information. Here, we examine information-seeking responses to the first COVID-19 case public announcement in a state. Using an event study framework for all US states, we show that such news increases collective attention to the crisis right away. However, the elevated level of attention is short-lived, even though the initial announcements are followed by increasingly strong policy measures. Specifically, searches for “coronavirus” increased by about 36% (95% CI: 27 to 44%) on the day immediately after the first case announcement but decreased back to the baseline level in less than a week or two. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms, and hand sanitizer. On the other hand, searches for information regarding community-level policies (e.g., quarantine, school closures, testing) or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are representative of the study period being relatively early in the epidemic, and more-elaborate policy responses were not yet part of the public discourse. Further analysis should track evolving patterns of responses to subsequent flows of public information.

title: COVID-19 data analysis and modeling in Palestine
abstract: We estimate an actual number of infected cases in Palestine based on the 18-day effect from infection to death. We find that the number of cases in April 22 varies between 506 and 2 026 infected cases. We also focus on the reproductive number in Palestine based on population dynamics with two SEIR models. Dataset is from 5 March to 22 April 2020. With a transmission rate equal to 4.55 106, on May 22, the simulations predict 11 014 total infected cases in the optimistic scenario and 113 171 in the worst one. The crest of the pandemic is from 22 to 27 May 2020. The reproductive number R0 is equal to 1.54 for a fixed fraction of 0.6 of symptomatic cases that are reported and for a removal rate of 7. Palestinian COVID-19 mortality number is equal to 6 per million. It is small compared to countries neighboring Palestine. The infected number is equal to 88.4 per million, which is less than most of its neighbors. The basic reproduction number is still greater than 1. Changes to the transmission rate (over time) would be advisable, to fall R0 below the critical threshold.

title: A six-year descriptive epidemiological study of human coronavirus infections in hospitalized patients in Hong Kong
abstract: We conducted a six-year epidemiological study on human coronaviruses (HCoVs) circulating in Hong Kong, using 8275 nasopharyngeal samples from patients with acute respiratory tract infections. HCoVs were detected in 77 (0.93%) of the samples by a pan-HCoV RT-PCR assay. The most frequently detected HCoV species was HCoV-OC43 (0.58%), followed by HCoV-229E (0.15%), HCoV-HKU1 (0.13%) and HCoV-NL63 (0.07%). HCoVs were detected throughout the study period (September 2008–August 2014), with the highest detection rate from September 2010 to August 2011 (22/1500, 1.47%). Different seasonal patterns of each HCoV species in Hong Kong were noted. HCoV-OC43 was predominant in the fall and winter, whereas HCoV-HKU1 showed peak activity in winter, with a few cases occurred in spring and summer. HCoV-229E mainly occurred in winter and spring, while HCoV-NL63 was predominant in summer and autumn. HCoVs most commonly infect the elderly and young children, with median age of 79.5 years (range, 22 days to 95 years). Intriguingly, the detection rate of HCoV-OC43 in the age group of > 80 years (26/2380, 1.09%) was significantly higher than that in the age group of 0–10 years (12/2529, 0.47%) (P < 0.05). These data provides new insight into the epidemiology of coronaviruses.

title: Impact of COVID-19 on endoscopy trainees: an international survey

title: Genetic diversity and evolution of SARS-CoV-2
abstract: Abstract COVID-19 is a viral respiratory illness caused by a new coronavirus called SARS-CoV-2. The World Health Organization declared the SARS-CoV-2 outbreak a global public health emergency. We performed genetic analyses of eighty-six complete or near-complete genomes of SARS-CoV-2 and revealed many mutations and deletions on coding and non-coding regions. These observations provided evidence of the genetic diversity and rapid evolution of this novel coronavirus.

title: A simplified model for expected development of the SARS-CoV-2 (Corona) spread in Germany and US after social distancing
abstract: Widespread opinions and discussion exist regarding the efficiency of social distancing after crucial spread of the SARS-CoV-2 virus during the actual Covid-19 pandemic. While Germany has released a federal law that prohibits any type of direct contact for more than 2 people other countries including the US released curfews. People are now wondering whether these measures are helpful to stop or hamper the Covid-19 pandemic and to limit the spread of the new corona virus. A quantitative statement on this question depends on many parameters that are difficult to grasp mathematically and cannot therefore be made conclusively (they include consistent adherence to the measures decided, the estimated number of unreported cases, the possible limitation by test capacities, possible mutations of the virus, etc ...). However, it turns out that a reduction in the actual daily new infection rate (actual daily growth rate of reported cases, in short: infection rate) from the current value of 30-35% in the US to 10% would be extremely effective in stopping the spread of the virus. The severe restrictions in Germany which closed any public events, schools and universities a week ago might already have contributed to a reduction of the growth rate of reported cases below 30%.

title: “Off-label” use of hydroxychloroquine, azithromycin, lopinavir-ritonavir and chloroquine in COVID-19: a survey of cardiac adverse drug reactions by the French Network of Pharmacovigilance Centers
abstract: COVID-19 is an unprecedented challenge for physicians and scientists. Several publicized drugs are being used with not much evidence of their efficacy such as hydroxychloroquine, azithromycin or lopinavir-ritonavir. Yet, the cardiac safety of these drugs in COVID-19 deserves scrutiny as they are known to foster cardiac adverse ADRs, notably QTc interval prolongation on the electrocardiogram and its arrhythmogenic consequences.  Since March 27th, 2020, the French Pharmacovigilance Network directed all cardiac adverse drug reactions associated with “off-label” use of hydroxychloroquine, azithromycin and lopinavir-ritonavir in COVID-19 to the Nice Regional Center of Pharmacovigilance. Each Regional Center of Pharmacovigilance first assessed causality of drugs. We performed a specific analysis of these cardiac adverse drug reactions amidst an array of risk factors, reassessed the electrocardiograms and estimated their incidence in coronavirus-disease-2019.  In one month, 120 reports of cardiac adverse drug reactions have been notified, 102 of which associated with hydroxychloroquine alone (85%), or associated with azithromycin (60%). Their estimated incidence is 0.77% to 1.54% of all patients, notwithstanding strong underreporting. Lopinavir-ritonavir came third with 17 reports (14%) and chloroquine fourth with 3 reports (2.5%). There were 8 sudden, unexplained or aborted deaths (7%), 8 ventricular arrhythmias (7 %), 90 reports of prolonged QTc (75%) most of them “serious” (64%), 48 of which proved ≥ 500 ms, 20 reports of severe conduction disorders (17%) and 5 reports of other cardiac causes (4%). Six reports derived from automedication.  “Off-label” use of treatments in COVID-19 increases the risk of cardiac ADRs, some of them avoidable. Even if these drugs are perceived as familiar, they are used in patients with added risk factors caused by infection. Precautions should be taken to mitigate the risk, even if they will be proven efficacious.

title: Update: Severe Respiratory Illness Associated with Middle East Respiratory Syndrome Coronavirus (MERS-CoV) — Worldwide, 2012–2013
abstract: CDC continues to work in consultation with the World Health Organization (WHO) and other partners to better understand the public health risk posed by the Middle East Respiratory Syndrome Coronavirus (MERS-CoV), formerly known as novel coronavirus, which was first reported to cause human infection in September 2012. The continued reporting of new cases indicates that there is an ongoing risk for transmission to humans in the area of the Arabian Peninsula. New reports of cases outside the region raise concerns about importation to other geographic areas. Nosocomial outbreaks with transmission to health-care personnel highlight the importance of infection control procedures. Recent data suggest that mild respiratory illness might be part of the clinical spectrum of MERS-CoV infection, and presentations might not initially include respiratory symptoms. In addition, patients with comorbidities or immunosuppression might be at increased risk for infection, severe disease, or both. Importantly, the incubation period might be longer than previously estimated. Finally, lower respiratory tract specimens (e.g., sputum, bronchoalveolar lavage, bronchial wash, or tracheal aspirate) should be collected in addition to nasopharyngeal sampling for evaluation of patients under investigation. An Emergency Use Authorization (EUA) was recently issued by the Food and Drug Administration (FDA) to allow for expanded availability of diagnostic testing in the United States.

title: BCG vaccine-induced protection from COVID-19 infection, wishful thinking or a game changer?
abstract: A series of epidemiological explorations have suggested a negative association between national BCG vaccination policy and the prevalence and mortality of COVID-19. Nevertheless, these comparisons are difficult to validate due to broad differences between countries such as socioeconomic status, demographic structure, rural vs. urban settings, time of arrival of the pandemic, number of diagnostic tests and criteria for testing, and national control strategies to limit the spread of COVID-19. We review evidence for the potential biological basis of BCG cross-protection from severe COVID-19 and refine the epidemiological analysis to mitigate effects of potentially confounding factors (e.g., stage of the COVID-19 epidemic, development, rurality, population density and age structure). Results fail to confirm the null hypothesis of no-association between BCG vaccination and COVID-19 mortality, and suggest that BCG could have a protective effect. Nevertheless, the analyses are restricted to coarse-scale signals and should be considered with caution. BCG vaccination clinical trials are required to corroborate the patterns detected here and to establish causality between BCG vaccination and protection from severe COVID-19. Public health implications of a plausible BCG cross-protection from severe COVID-19 are discussed.

title: Association of national Bacille Calmette-Guerin vaccination policy with COVID-19 epidemiology: an ecological study in 78 countries
abstract: A possible association between national Bacille Calmette-Guerin (BCG) vaccination policy and lower COVID-19 incidence has been suggested in some preprint papers. Using publicly accessible databases, I explored associations of national BCG vaccination policy with COVID-19 epidemiology in 78 countries. Data collection was conducted from April 25 to May 5, 2020. I compared countries that have a current universal BCG vaccination policy (BCG countries), with countries that currently lack such a policy (non-BCG countries). The mixed effect model revealed national BCG policy decreases in the country-specific risk of death by COVID-19, correspond to odds ratio of 0.446 (95% confidence intervals 0.323 - 0.614, P =1x10-5). In BCG countries, the case increase rate was attenuated marginally by 25.4% (95% CI 3.0 to 42.7, P=0.029) as compared with those of the non-BCG countries. Although the protective mechanism of BCG vaccination against COVID-19 remains unknown, further laboratory and clinical research should be warranted.

title: The Evolution of the WHO/NREVSS Influenza Surveillance System: The Challenges and Opportunities that Accompany Electronic Laboratory Data

title: Review of trials currently testing treatment and prevention of COVID-19
abstract: As COVID-19 cases continue to rise globally, evidence from large randomized controlled trials is still lacking. Currently, numerous trials testing potential treatment and preventative options are being undertaken all over the world.  We summarized all registered clinical trials examining treatment and prevention options for COVID-19. Additionally, we evaluated the quality of the retrieved studies.  Clinicaltrials.gov, the Chinese Clinical Trial Registry and the European Union Clinical Trials Register were systematically searched.  Registered clinical trials examining treatment and/or prevention options for COVID-19 were included. No language, country or study design restrictions were applied. We excluded withdrawn or cancelled studies and trials not reporting therapeutic or preventative strategies for COVID-19.  No restrictions in terms of participants' age and medical background or type of intervention were enforced.  The registries were searched using the term 'coronavirus' or 'COVID-19' from their inception until 26 March 2020. Additional manual search of the registries was also performed. Eligible studies were summarized and tabulated. Interventional trials were methodologically analysed, excluding expanded access studies and trials testing traditional Chinese medicine.  In total, 309 trials evaluating therapeutic management options, 23 studies assessing preventive strategies and three studies examining both were retrieved. Finally, 214 studies were methodologically reviewed. Interventional treatment studies were mostly randomized (n = 150/198, 76%) and open label (n = 73/198, 37%) with a median number of planned inclusions of 90 (interquartile range 40-200). Major categories of interventions that are currently being investigated are discussed.  Numerous clinical trials have been registered since the onset of the COVID-19 pandemic. Summarized data on these trials will assist physicians and researchers to promote patient care and guide future research efforts for COVID-19 pandemic containment.

title: Sex differences in the frequency of gastrointestinal symptoms and olfactory or taste disorders in 1942 nonhospitalized patients with coronavirus disease 2019 (COVID-19)
abstract: The coronavirus disease 2019 (COVID 19) is a communicable disease caused by a novel coronavirus.  This study aimed to assess self­reported frequency of gastrointestinal symptoms and olfactory or taste disorders in nonhospitalized patients with COVID­19 in Poland.  This cross­sectional survey was conducted between April 17 and 18, 2020, in 4516 nonhospitalized patients with COVID­19 in Poland. The questionnaire included 8 questions related to the health status, symptoms of COVID­19, comorbidities, and smoking status.  Completed questionnaires were obtained from 1942 patients with COVID­19 with a response rate of 43%. The median age of the respondents was 50 years; 60.2% were women. Among nonhospitalized patients with COVID­19, 21.3% had hypertension, 4.5% had diabetes, and 3.1% had a chronic respiratory disease. Regular tobacco use was declared by 11.2% of patients with COVID­19. At least one gastrointestinal symptom was reported by 53.6% of patients. Almost half of patients (47%) with COVID­19 reported lack of appetite and 24.2% reported diarrhea. Among 1942 interviewed patients, 54.2% reported at least 1 olfactory or taste disorder and 42.5% reported both alterations. Self­reported olfactory and taste disorders were 49.2% and 47.5%, respectively. Self­reported frequency of gastrointestinal symptoms and olfactory or taste disorders during COVID­19 was significantly higher (P <0.001) in women than men.  This study demonstrated that olfactory and taste disorders are frequent symptoms in patients with mild­to­moderate COVID­19. Moreover, our study indicated sex differences in the frequency of gastrointestinal symptoms and olfactory or taste disorders among nonhospitalized patients with COVID­19.

title: COVID-19 and treatment with NSAIDs and corticosteroids: should we be limiting their use in the clinical setting?
abstract: Given the current SARS-CoV-2 (COVID-19) pandemic, the availability of reliable information for clinicians and patients is paramount. There have been a number of reports stating that non-steroidal anti-inflammatory drugs (NSAIDs) and corticosteroids may exacerbate symptoms in COVID-19 patients. Therefore, this review aimed to collate information available in published articles to identify any evidence behind these claims with the aim of advising clinicians on how best to treat patients. This review found no published evidence for or against the use of NSAIDs in COVID-19 patients. Meanwhile, there appeared to be some evidence that corticosteroids may be beneficial if utilised in the early acute phase of infection, however, conflicting evidence from the World Health Organisation surrounding corticosteroid use in certain viral infections means this evidence is not conclusive. Given the current availability of literature, caution should be exercised until further evidence emerges surrounding the use of NSAIDs and corticosteroids in COVID-19 patients.

title: Prospective case-control analysis of the aetiologies of acute undifferentiated fever in Vietnam
abstract: Acute undifferentiated fever (AUF) is frequently observed in tropical settings, but diagnosing the cause of AUF is often a challenge for local physicians and the physicians treating returning travellers. We conducted a case-control study in central Vietnam in 2016. A total of 378 febrile adult patients (AUFs) with a fever for ≤21 days, no evidence of localized infection and negative screening tests for dengue and malaria, and 384 afebrile adult patients (Controls) were prospectively enrolled. Whole blood, plasma, eschar swab, throat swab and urine specimens were collected and analysed. Quantitative PCR and RT-PCR were used to test for 55 bacteria, viruses and their subtypes. Serological tests were also used to test for rickettsial agents. The most common aetiology was influenza virus (20.9% in AUFs vs. 0% in Controls), followed by rickettsial agents (mainly Orientia tsutsugamushi and Rickettsia typhi) (10.8% vs. 0.3%), dengue virus (7.7% vs. 0.5%), Leptospira (4.8% vs. 0.8%), adenovirus (4.8% vs. 1.0%), and enterovirus (2.1% vs. 0%) (p < .05). The real proportion of dengue in AUF cases was underestimated because patients with dengue-positive rapid diagnosis tests were excluded from the study. The emerging agent Rickettsia felis, which had not been previously observed in Vietnam, was detected in this study. In total, 216 patients (57.1%) were given causative diagnoses, comprising 143 (66.2%) monoinfections and 73 (33.8%) coinfections. The infections caused by these agents should be considered in clinical practice and further studies. Additionally, agents susceptible to doxycycline were detected in 15.6% of AUFs; thus, this drug should be included in the panel used to treat AUF patients.

title: Lessons from a rapid systematic review of early SARS-CoV-2 serosurveys
abstract: As the world grapples with the COVID-19 pandemic, there is increasing global interest in the role of serological testing for population monitoring and to inform public policy. However, limitations in serological study designs and test standards raise concerns about the validity of seroprevalence estimates and their utility in decision-making. There is now a critical window of opportunity to learn from early SARS-CoV-2 serology studies. We aimed to synthesize the results of SARS-CoV-2 serosurveillance projects from around the world and provide recommendations to improve the coordination, strategy, and methodology of future serosurveillance efforts.  This was a rapid systematic review of cross-sectional and cohort studies reporting seroprevalence outcomes for SARS-CoV 2. We included completed, ongoing, and proposed serosurveys. The search included electronic databases (PubMed, MedRXIV, BioRXIV, and WHO ICTPR); five medical journals (NEJM, BMJ, JAMA, The Lancet, Annals of Internal Medicine); reports by governments, NGOs, and health systems; and media reports (Google News) from December 1, 2019 to May 1, 2020. We extracted data on study characteristics and critically appraised prevalence estimates using Joanna Briggs Institute criteria.  Seventy records met inclusion criteria, describing 73 studies. Of these, 23 reported prevalence estimates: eight preprints, 14 news articles, and one government report. These studies had a total sample size of 35,784 and reported 42 prevalence estimates. Seroprevalence estimates ranged from 0.4% to 59.3%. No estimates were found to have a low risk of bias (43% high risk, 21% moderate risk, 36% unclear). Fifty records reported characteristics of ongoing or proposed serosurveys. Overall, twenty countries have completed, ongoing, or proposed serosurveys.  Study design, quality, and prevalence estimates of early SARS-CoV2 serosurveys are heterogeneous, suggesting that the urgency to examine seroprevalence may have compromised methodological rigour. Based on the limitations of included studies, future serosurvey investigators and stakeholders should ensure that: i) serological tests used undergo high-quality independent evaluations that include cross-reactivity; ii) all reports of serosurvey results, including media, describe the test used, sample size, and sampling method; and iii) initiatives are coordinated to prevent test fatigue, minimize redundant efforts, and encourage better study methodology. Other.  No third-party funding.

title: Impact of viral epidemic outbreaks on mental health of healthcare workers: a rapid systematic review
abstract: To examine the impact of providing healthcare during or after health emergencies caused by viral epidemic outbreaks on healthcare workers (HCWs) mental health, and to assess the available evidence base regarding interventions to reduce such impact.  Systematic rapid review and meta-analysis.  MEDLINE, Embase, and PsycINFO, searched up to 23 March 2020.  We selected observational and experimental studies examining the impact on mental health of epidemic outbreaks on HCWs. Titles and abstracts were screened by one reviewer, and full texts were evaluated by two reviewers independently. We extracted study characteristics, symptoms, prevalence of mental health problems, risk factors, mental health interventions, and its impact. We assessed risk of bias for each individual study. We conducted a narrative and tabulated synthesis of the results. We pooled data using random-effects meta-analyses to estimate the prevalence of specific mental health problems. We followed the GRADE approach to assess the certainty in the evidence.  We included 61 studies (56 examining impact on mental health and five about interventions to reduce such impact). Most were conducted in Asia (59%), examined the impact of the SARS epidemic (69%), and took place in the hospital setting (79%). The pooled prevalence was higher for anxiety (45%, 95% CI 21 to 69%; 6 studies, 3,373 participants), followed by depression (38%, 95% CI 15 to 60%; 7 studies, 3,636 participants), acute stress disorder (31%, 95% CI 0 to 82%, 3 studies , 2,587 participants), burnout (29%, 95% CI 25 to 32%; 3 studies; 1,168 participants) and post-traumatic stress disorder (19%, 95% CI 11 to 26%, 10 studies, 3,121 participants). Based on 37 studies, we identified a broad number of risk factors for these conditions, including sociodemographic: younger age and female gender; social factors: lack of social support, social rejection or isolation, stigmatization; and occupational: working in a high risk environment (frontline staff), specific occupational roles (e.g., nurse), and lower levels of specialized training, preparedness and job experience. Two out of five interventions identified were educational aimed to prevent mental health problems by increasing HCWs resilience. These interventions showed positive effects in confidence in support and training, pandemic self-efficacy and interpersonal problems solving (very low certainty). One multifaceted intervention (based on training and organisational changes) targeted at hospital nurses during the SARS epidemic produced statistically significant improvements in anxiety, depression, and sleep quality (very low certainty). The impact of the two remaining interventions (multifaceted and based on psychotherapy provision) was unreported.  The prevalence of anxiety, depression, acute and post-traumatic stress disorder, and burnout, was high both during and after the outbreaks. These problems not only have a long-lasting effect on the mental health of HCWs, but also hinder the urgent response to the current COVID-19 pandemic, by jeopardising attention and decision-making. Governments and healthcare authorities should take urgent actions to protect the mental health of HCWs. In light of the limited evidence regarding the impact of interventions to tackle mental health problems in HCWs, the risk factors identified in this study represent important targets for future interventions.

title: Inactivating porcine coronavirus before nuclei acid isolation with the temperature higher than 56 °C damages its genome integrity seriously
abstract: 2019-Novel Coronavirus (2019-nCoV) is the pathogen of Corona Virus Disease 2019. Nucleic acid detection of 2019-nCoV is one of the key indicators for clinical diagnosis. However, the positive rate is only 30-50%. Currently, fluorescent quantitative RT-PCR technology is mainly used to detect 2019-nCoV. According to “The Laboratory Technical Guidelines for Detection 2019-nCoV (Fourth Edition)” issued by National Health and Commission of China and “The Experts’ Consensus on Nucleic Acid Detection of 2019-nCoV” released by Chinese Society of Laboratory Medicine, the human samples must be placed under 56°C or higher to inactivate the viruses in order to keep the inspectors from virus infection before the nucleic acids were isolated as the template of qRT-PCR. In this study, we demonstrated that the virus inactivation treatment disrupts its genome integrity seriously when using porcine epidemic diarrhea virus (vaccine), a kind of coronavirus, as a model. Our results showed that only 50.11% of the detectable viral templates left after the inactivation of 56 °C for 30 minutes and only 3.36% left after the inactivation of 92 °C for 5 minutes when the samples were preserved by Hank’s solution, one of an isotonic salt solutions currently suggested. However, the detectable templates of viral nucleic acids can be unchanged after the samples were incubated at 56 °C or higher if the samples were preserved with an optimized solution to protect the RNA from being disrupted. We therefore highly recommend to carry out systematic investigation on the impact of high temperature inactivation on the integrity of 2019-nCoV genome and develop a sample preservation solution to protect the detectable templates of 2019-nCoV nucleic acids from high temperature inactivation damage.

title: ANTIQUE: A Non-factoid Question Answering Benchmark
abstract: Considering the widespread use of mobile and voice search, answer passage retrieval for non-factoid questions plays a critical role in modern information retrieval systems. Despite the importance of the task, the community still feels the significant lack of large-scale non-factoid question answering collections with real questions and comprehensive relevance judgments. In this paper, we develop and release a collection of 2,626 open-domain non-factoid questions from a diverse set of categories. The dataset, called ANTIQUE, contains 34k manual relevance annotations. The questions were asked by real users in a community question answering service, i.e., Yahoo! Answers. Relevance judgments for all the answers to each question were collected through crowdsourcing. To facilitate further research, we also include a brief analysis of the data as well as baseline results on both classical and neural IR models.

title: REPLY to “Self‐reported olfactory loss in COVID‐19: is it really a favorable prognostic factor?”

title: Early trends for SARS-CoV-2 infection in central and north Texas and impact on other circulating respiratory viruses
abstract: Rapid diagnosis and isolation are key to containing the quick spread of a pandemic agent like severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2), which has spread globally since its initial outbreak in Wuhan province in China. SARS-CoV-2 is novel and the effect on typically prevalent seasonal viruses is just becoming apparent. We present our initial data on the prevalence of respiratory viruses in the month of March 2020. This is a retrospective cohort study post launching of SARS-CoV-2 testing at Baylor Scott and White Hospital (BSWH), Temple, Texas. Testing for SARS-CoV-2 was performed by real-time reverse transcription polymerase chain reaction assay and results were shared with State public health officials for immediate interventions. More than 3500 tests were performed during the first 2 weeks of testing for SARS-CoV-2 and identified 168 (4.7%) positive patients. Sixty-two (3.2%) of the 1912 ambulatory patients and 106 (6.3%) of the 1659 emergency department/inpatients tested were positive. The highest rate of infection (6.9%) was seen in patients aged 25 to 34 years, while the lowest rate of infection was seen among patients aged <25 years old (2%). County-specific patient demographic information was shared with respective public health departments for epidemiological interventions. Incidentally, this study showed that there was a significant decrease in the occurrence of seasonal respiratory virus infections, perhaps due to increased epidemiological awareness about SARS-CoV-2 among the general public, as well as the social distancing measures implemented in response to SARS-CoV-2. Data extracted for BSWH from the Centers for Disease Control and Prevention's National Respiratory and Enteric Virus Surveillance System site revealed that Influenza incidence was 8.7% in March 2020, compared with 25% in March 2019. This study was intended to provide an initial experience of dealing with a pandemic and the role of laboratories in crisis management. This study provided SARS-CoV-2 testing data from ambulatory and inpatient population. Epidemiological interventions depend on timely availability of accurate diagnostic tests and throughput capacity of such systems during large outbreaks like SARS-CoV-2.

title: Counting Coronavirus Disease 2019 (COVID-19) Cases: Case Definitions, Screened Populations and Testing Techniques Matter
abstract: While counting cases of disease appears straightforward, there are issues to consider when enumerating disease counts during an epidemic. For example, for Coronavirus Disease-2019 (COVID-19), how is a case defined? Hubei province in China changed its case definition twice in a fortnight-from laboratory-confirmed cases to clinically-confirmed cases without laboratory tests, and back to laboratory-confirmed cases. This caused confusion in the reported number of cases. If a confirmed case requires laboratory testing, what is the population who are laboratory-tested? Due to limited laboratory testing capacity in the early phase of an emerging epidemic, only "suspected cases" are laboratory-tested in most countries. This will result in underdiagnosis of confirmed cases and also raises the question: how is a "suspect case" defined? With the passage of time and increased capability to perform laboratory tests, more people can be screened and the number of confirmed cases will increase. What are the technical considerations of laboratory testing? This includes specimen collection (variable collection methods), samples collected (upper or lower respiratory tract biospecimens), time of collection in relation to course of disease, different laboratory test methods and kits (not all of which may be standardised or approved by authorities such as the Food and Drug Administration). Are approved laboratory facilities and trained manpower available, and how are test results interpreted and false-negatives excluded? These issues will affect the accuracy of disease counts, which in turn will have implications on how we mount an appropriate response to the outbreak.

title: Oral presentations

title: The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society
abstract: With more than 900,000 confirmed cases worldwide and nearly 50,000 deaths during the first three months of 2020, the COVID-19 pandemic has emerged as an unprecedented healthcare crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, healthcare delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and healthcare workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. While mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography (CXR) and computed tomography (CT) are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pre-test probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing COVID-19 patients across a spectrum of healthcare environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based upon the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of CXR and CT in the management of COVID-19.

title: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges
abstract: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously provisionally named 2019 novel coronavirus or 2019-nCoV) disease (COVID-19) in China at the end of 2019 has caused a large global outbreak and is a major public health issue. As of 11 February 2020, data from the World Health Organization (WHO) have shown that more than 43 000 confirmed cases have been identified in 28 countries/regions, with >99% of cases being detected in China. On 30 January 2020, the WHO declared COVID-19 as the sixth public health emergency of international concern. SARS-CoV-2 is closely related to two bat-derived severe acute respiratory syndrome-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21. It is spread by human-to-human transmission via droplets or direct contact, and infection has been estimated to have mean incubation period of 6.4 days and a basic reproduction number of 2.24–3.58. Among patients with pneumonia caused by SARS-CoV-2 (novel coronavirus pneumonia or Wuhan pneumonia), fever was the most common symptom, followed by cough. Bilateral lung involvement with ground-glass opacity was the most common finding from computed tomography images of the chest. The one case of SARS-CoV-2 pneumonia in the USA is responding well to remdesivir, which is now undergoing a clinical trial in China. Currently, controlling infection to prevent the spread of SARS-CoV-2 is the primary intervention being used. However, public health authorities should keep monitoring the situation closely, as the more we can learn about this novel virus and its associated outbreak, the better we can respond.

title: Monitoring the Spread of Swine Enteric Coronavirus Diseases in the United States in the Absence of a Regulatory Framework
abstract: The reporting and monitoring of swine enteric coronavirus diseases (SECD), including porcine epidemic diarrhea virus and porcine delta coronavirus, in the United States have been challenging because of the initial absence of a regulatory framework and the emerging nature of these diseases. The National Animal Health Laboratory Network, the Emergency Management and Response System, and the Swine Health Monitoring Project were used to monitor the disease situation between May 2013 and March 2015. Important differences existed between and among them in terms of nature and extent of reporting. Here, we assess the implementation of these systems from different perspectives, including a description and comparison of collected data, disease metrics, usefulness, simplicity, flexibility, acceptability, representativeness, timeliness, and stability. This assessment demonstrates the limitations that the absence of premises identification imposes on certain animal health surveillance and response databases, and the importance of federally regulated frameworks in collecting accurate information in a timely manner. This study also demonstrates the value that the voluntary and producer-organized systems may have in monitoring emerging diseases. The results from all three data sources help to establish the baseline information on SECD epidemiological dynamics after almost 3 years of disease occurrence in the country.

title: A first study on the impact of current and future control measures on the spread of COVID-19 in Germany
abstract: The novel coronavirus (SARS-CoV-2), identified in China at the end of December 2019 and causing the disease COVID-19, has meanwhile led to outbreaks all over the globe, with about 571,700 confirmed cases and about 26,500 deaths as of March 28th, 2020. We present here the preliminary results of a mathematical study directed at informing on the possible application or lifting of control measures in Germany. The developed mathematical models allow to study the spread of COVID-19 among the population in Germany and to asses the impact of non-pharmaceutical interventions. The overall goal is to suggest strategies for the mitigation of the current outbreak, slowing down the spread of the virus and thus reducing the peak in daily diagnosed cases, the demand for hospitalization or intensive care units admissions, and eventually fatalities.

title: Severe Acute Respiratory Syndrome, Beijing, 2003
abstract: The largest outbreak of severe acute respiratory syndrome (SARS) struck Beijing in spring 2003. Multiple importations of SARS to Beijing initiated transmission in several healthcare facilities. Beijing’s outbreak began March 5; by late April, daily hospital admissions for SARS exceeded 100 for several days; 2,521 cases of probable SARS occurred. Attack rates were highest in those 20–39 years of age; 1% of cases occurred in children <10 years. The case-fatality rate was highest among patients >65 years (27.7% vs. 4.8% for those 20–64 years, p < 0.001). Healthcare workers accounted for 16% of probable cases. The proportion of case-patients without known contact to a SARS patient increased significantly in May. Implementation of early detection, isolation, contact tracing, quarantine, triage of case-patients to designated SARS hospitals, and community mobilization ended the outbreak.

title: Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020
abstract: The initial cluster of severe pneumonia cases that triggered the COVID-19 epidemic was identified in Wuhan, China in December 2019. While early cases of the disease were linked to a wet market, human-to-human transmission has driven the rapid spread of the virus throughout China. The Chinese government has implemented containment strategies of city-wide lockdowns, screening at airports and train stations, and isolation of suspected patients; however, the cumulative case count keeps growing every day. The ongoing outbreak presents a challenge for modelers, as limited data are available on the early growth trajectory, and the epidemiological characteristics of the novel coronavirus are yet to be fully elucidated. We use phenomenological models that have been validated during previous outbreaks to generate and assess short-term forecasts of the cumulative number of confirmed reported cases in Hubei province, the epicenter of the epidemic, and for the overall trajectory in China, excluding the province of Hubei. We collect daily reported cumulative confirmed cases for the 2019-nCoV outbreak for each Chinese province from the National Health Commission of China. Here, we provide 5, 10, and 15 day forecasts for five consecutive days, February 5th through February 9th, with quantified uncertainty based on a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model. Our most recent forecasts reported here, based on data up until February 9, 2020, largely agree across the three models presented and suggest an average range of 7409–7496 additional confirmed cases in Hubei and 1128–1929 additional cases in other provinces within the next five days. Models also predict an average total cumulative case count between 37,415 and 38,028 in Hubei and 11,588–13,499 in other provinces by February 24, 2020. Mean estimates and uncertainty bounds for both Hubei and other provinces have remained relatively stable in the last three reporting dates (February 7th – 9th). We also observe that each of the models predicts that the epidemic has reached saturation in both Hubei and other provinces. Our findings suggest that the containment strategies implemented in China are successfully reducing transmission and that the epidemic growth has slowed in recent days.

title: Estimates of the severity of COVID-19 disease
abstract: A range of case fatality ratio (CFR) estimates for COVID 19 have been produced that differ substantially in magnitude.  We used individual-case data from mainland China and cases detected outside mainland China to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the CFR by relating the aggregate distribution of cases by dates of onset to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for the demography of the population, and age and location-based under ascertainment. We additionally estimated the CFR from individual linelist data on 1,334 cases identified outside mainland China. We used data on the PCR prevalence in international residents repatriated from China at the end of January 2020 to obtain age-stratified estimates of the infection fatality ratio (IFR). Using data on age stratified severity in a subset of 3,665 cases from China, we estimated the proportion of infections that will likely require hospitalisation.  We estimate the mean duration from onset-of-symptoms to death to be 17.8 days (95% credible interval, crI 16.9,19.2 days) and from onset-of-symptoms to hospital discharge to be 22.6 days (95% crI 21.1,24.4 days). We estimate a crude CFR of 3.67% (95% crI 3.56%,3.80%) in cases from mainland China. Adjusting for demography and under-ascertainment of milder cases in Wuhan relative to the rest of China, we obtain a best estimate of the CFR in China of 1.38% (95% crI 1.23%,1.53%) with substantially higher values in older ages. Our estimate of the CFR from international cases stratified by age (under 60 or 60 and above) are consistent with these estimates from China. We obtain an overall IFR estimate for China of 0.66% (0.39%,1.33%), again with an increasing profile with age.  These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and demonstrate a strong age-gradient in risk.

title: Development of a United Kingdom National External Quality Assessment Scheme (UK NEQAS) for HIV point of care testing
abstract: The use of HIV point of care tests (POCTs) is increasing rapidly in both laboratory and other settings. These tests are often performed by non-laboratory trained staff. At the present time there are no external quality assessment (EQA) providers in the UK offering proficiency testing schemes for HIV point of care testing. The aim of this study is to develop such an EQA scheme. Firstly, a selection of the most widely used POCTs was selected and their performance assessed using existing HIV-positive serology EQA specimens. All assays produced the correct results however intensity of results observed for the same specimen differed greatly between POCT devices. In addition the effect of various sub-groups of HIV-1 serum samples on the HIV POCT assays was investigated and no difference between the results on the POCTs was observed. Ultimately four serum specimens, two HIV-1 and one HIV-2 positive, one HIV negative, were chosen and sent to NHS laboratories and sexual health clinics for testing as part of a pilot EQA scheme for HIV POCT. Results were excellent with 97% of participants reporting correct results (n= 20). The study highlighted a lack of awareness of EQA particularly in non-laboratory settings, although recommendations (ISO 22870:2006) are in place for the users of such devices. In conclusion, the need for EQA for providers of point of care testing is an integral part of ensuring reliability of results and quality of care for the patient.

title: First Complete Genome Sequence of Human Coronavirus HKU1 from a Nonill Bat Guano Miner in Thailand
abstract: Human coronavirus HKU1 (HCoV-HKU1) was first detected in a patient with viral pneumonia from Hong Kong in 2004. Here, we report the first complete genome sequence of HCoV-HKU1 from Thailand, obtained from a nonill person who worked in a bat cave. Phylogenetic tree analysis revealed it as a group B HCoV-HKU1.

title: COVID-19 projections for reopening Connecticut
abstract: Closure of schools and the statewide "Stay Safe, Stay Home" order have effectively reduced COVID-19 transmission in Connecticut, with model projections estimating incidence at about 1,300 new infections per day. If close interpersonal contact increases quickly in Connecticut following reopening on May 20, the state is at risk of a substantial increase of COVID-19 infections, hospitalizations, and deaths by late Summer 2020. Real-time metrics including case counts, hospitalizations, and deaths may fail to provide enough advance warning to avoid resurgence. Substantial uncertainty remains in our knowledge of cumulative COVID-19 incidence, the proportion of infected individuals who are asymptomatic, infectiousness of children, the effects of testing and contact tracing on isolation of infected individuals, and how contact patterns may change following reopening.

title: Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model
abstract: The daily incidence and deaths of coronavirus disease 2019 (COVID-19) in the USA are poorly understood. Internet search interest was found to be correlated with COVID-19 daily incidence in China, but has not yet been applied to the USA. Therefore, we examined the association of internet search-interest with COVID-19 daily incidence and deaths in the USA.  We extracted COVID-19 daily new cases and deaths in the USA from two population-based datasets, namely 1-point-3-acres.com and the Johns Hopkins COVID-19 data repository. The internet search-interest of COVID-19-related terms was obtained using Google Trends. The Pearson correlation test and general linear model were used to examine correlations and predict trends, respectively.  There were 636,282 new cases and,325 deaths of COVID-19 in the USA from March 1 to April 15, 2020, with a crude mortality of 4.45%. The daily new cases peaked at 35,098 cases on April 10, 2020 and the daily deaths peaked at 2,494 on April 15, 2020. The search interest of COVID, “COVID pneumonia” and “COVID heart” were correlated with COVID-19 daily incidence, with 12 or 14 days of delay (Pearson’s r = 0.978, 0.978 and 0.979, respectively) and deaths with 19 days of delay (Pearson’s r = 0.963, 0.958 and 0.970, respectively). The 7-day follow-up with prospectively collected data showed no significant correlations of the observed data with the predicted daily new cases or daily deaths, using search interest of COVID, COVID heart, and COVID pneumonia.  Search terms related to COVID-19 are highly correlated with the COVID-19 daily new cases and deaths in the USA.

title: Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults
abstract: RAPID COMMUNICATION 22 March 2020 Estimating excess 1- year mortality from COVID-19 according to underlying conditions and age in England: a rapid analysis using NHS health records in 3.8 million adults  The medical, health service, societal and economic impact of the COVID-19 emergency has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom (to date at least) have underlying conditions. Models have not incorporated information on high risk conditions or their longer term background (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence rates and differing mortality impacts.  Using population based linked primary and secondary care electronic health records in England (HDR UK - CALIBER), we report the prevalence of underlying conditions defined by UK Public Health England COVID-19 guidelines (16 March 2020) in 3,862,012 individuals aged ≥30 years from 1997-2017. We used previously validated phenotypes, openly available (https://caliberresearch.org/portal), for each condition using ICD-10 diagnosis, Read, procedure and medication codes. We estimated the 1-year mortality in each condition, and developed simple models of excess COVID-19-related deaths assuming relative risk (RR) of the impact of the emergency (compared to background mortality) of 1.2, 1.5 and 2.0.  20.0% of the population are at risk according to current PHE guidelines, of which; 13.7% were age>70 years and 6.3% aged ≤70 years with ≥1 underlying condition (cardiovascular disease (2.3%), diabetes (2.2%), steroid therapy (1.9%), severe obesity (0.9%), chronic kidney disease (0.6%) and chronic obstructive pulmonary disease, COPD (0.5%). Multimorbidity (co-occurrence of ≥2 conditions in an individual) was common (10.1%). The 1-year mortality in the at-risk population was 4.46%, and age and underlying conditions combine to influence background risk, varying markedly across conditions (5.9% in age>70 years, 8.6% for COPD and 13.1% in those with ≥3 or more conditions). In a suppression scenario (at SARS CoV2 rates of 0.001% of the UK population), there would be minimal excess deaths (3 and 7 excess deaths at relative risk, RR, 1.5 and 2.0 respectively). At SARS CoV2 rates of 10% of the UK population (mitigation) the model estimates the numbers of excess deaths as: 13791, 34479 and 68957 (at RR 1.2, 1.5 and 2.0 respectively). At SARS CoV2 rates of 80% in the UK population (do-nothing), the model estimates the number of excess deaths as 110332, 275,830 and 551,659 (at RR 1.2, 1.5 and 2.0) respectively.  We provide the public, researchers and policy makers a simple model to estimate the excess mortality over 1 year from COVID-19, based on underlying conditions at different ages. If the relative mortality impact of COVID-19 were to be about 20% (similar magnitude as the established winter vs summer mortality excess), then the excess deaths would be 0 when 1 in 100 000 (suppression), 13791 when 1 in 10 (mitigation) and 110332 when 8 in 10 are infected (do nothing) scenario. However, the relative impact of COVID-19 is unknown. If the emergency were to double the mortality risk, then we estimate 7, 68957 and 551,659 excess deaths in the same scenarios. These results may inform the need for more stringent suppression measures as well as efforts to target those at highest risk for a range of preventive interventions.

title: Surviving Sepsis Campaign: guidelines on the management of critically ill adults with Coronavirus Disease 2019 (COVID-19)
abstract: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, Coronavirus Disease 2019 (COVID-19), affecting thousands of people around the world. Urgent guidance for clinicians caring for the sickest of these patients is needed.  We formed a panel of 36 experts from 12 countries. All panel members completed the World Health Organization conflict of interest disclosure form. The panel proposed 53 questions that are relevant to the management of COVID-19 in the ICU. We searched the literature for direct and indirect evidence on the management of COVID-19 in critically ill patients in the ICU. We identified relevant and recent systematic reviews on most questions relating to supportive care. We assessed the certainty in the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach, then generated recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. Recommendations were either strong or weak, or in the form of best practice recommendations.  The Surviving Sepsis Campaign COVID-19 panel issued 54 statements, of which 4 are best practice statements, 9 are strong recommendations, and 35 are weak recommendations. No recommendation was provided for 6 questions. The topics were: (1) infection control, (2) laboratory diagnosis and specimens, (3) hemodynamic support, (4) ventilatory support, and (5) COVID-19 therapy.  The Surviving Sepsis Campaign COVID-19 panel issued several recommendations to help support healthcare workers caring for critically ill ICU patients with COVID-19. When available, we will provide new recommendations in further releases of these guidelines.  contains supplementary material, which is available to authorized users.

title: Prediction of the clinical outcome of COVID-19 patients using T lymphocyte subsets with 340 cases from Wuhan, China: a retrospective cohort study and a web visualization tool
abstract: Wuhan, China was the epicenter of the 2019 coronavirus outbreak. As a designated hospital, Wuhan Pulmonary Hospital has received over 700 COVID-19 patients. With the COVID-19 becoming a pandemic all over the world, we aim to share our epidemiological and clinical findings with the global community.  In this retrospective cohort study, we studied 340 confirmed COVID-19 patients from Wuhan Pulmonary Hospital, including 310 discharged cases and 30 death cases. We analyzed their demographic, epidemiological, clinical and laboratory data and implemented our findings into an interactive, free access web application.  Baseline T lymphocyte Subsets differed significantly between the discharged cases and the death cases in two-sample t-tests: Total T cells (p < 2.2e-16), Helper T cells (p < 2.2e-16), Suppressor T cells (p = 1.8-14), and TH/TS (Helper/Suppressor ratio, p = 0.0066). Multivariate logistic regression model with death or discharge as the outcome resulted in the following significant predictors: age (OR 1.05, p 0.04), underlying disease status (OR 3.42, p 0.02), Helper T cells on the log scale (OR 0.22, p 0.00), and TH/TS on the log scale (OR 4.80, p 0.00). The McFadden pseudo R-squared for the logistic regression model is 0.35, suggesting the model has a fair predictive power.  While age and underlying diseases are known risk factors for poor prognosis, patients with a less damaged immune system at the time of hospitalization had higher chance of recovery. Close monitoring of the T lymphocyte subsets might provide valuable information of the patients condition change during the treatment process. Our web visualization application can be used as a supplementary tool for the evaluation.

title: Emerging Viruses without Borders: The Wuhan Coronavirus
abstract: The recently emerged coronavirus in Wuhan, China has claimed at least six lives as of January 22 and infected hundreds if not thousands of individuals. The situation has drawn international attention, including from the virology community. We applaud the rapid release to the public of the genome sequence of the new virus by Chinese virologists, but we also believe that increased transparency on disease reporting and data sharing with international colleagues are crucial for curbing the spread of this newly emerging virus to other parts of the world.

title: Understanding the Renin-Angiotensin-Aldosterone-SARS-CoV-Axis: A Comprehensive Review
abstract: Coronavirus Disease 19 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic with significant morbidity and mortality since first appearing in Wuhan, China, in late 2019. As many countries are grappling with the onset of their epidemics, pharmacotherapeutics remain lacking. The window of opportunity to mitigate downstream morbidity and mortality is narrow but remains open. The renin-angiotensin-aldosterone system (RAAS) is crucial to the homeostasis of both the cardiovascular and respiratory systems. Importantly, SARS-CoV-2 utilises and interrupts this pathway directly, which could be described as the renin-angiotensin-aldosterone-SARS-CoV-2-axis (RAAS-SCoV-axis). There exists significant controversy and confusion surrounding how anti-hypertensive agents might function along this pathway. This review explores the current state of knowledge regarding the RAAS-SCoV-axis, informed by prior studies of SARS-CoV, how this relates to our currently evolving pandemic, and how these insights might guide our next steps in an evidence-based manner.  This review discusses the role of the RAAS-SCoV-axis in acute lung injury and the effects, risks, and benefits of pharmacologic modification of this axis. There may be an opportunity to leverage the different aspects of RAAS inhibitors to mitigate indirect viral-induced lung injury. Concerns have been raised that such modulation might exacerbate the disease. While relevant preclinical, experimental models to date favor a protective effect of RAAS-SCoV-axis inhibition on both lung injury and survival, clinical data related to the role of RAAS modulation in the setting of SARS-CoV-2 remains limited.  Proposed interventions for SARS-CoV-2 predominantly focus on viral microbiology and aim to inhibit viral cellular injury. While these therapies are promising, immediate use may not be feasible, and the time window of their efficacy remains a major unanswered question. An alternative approach is the modulation of the specific downstream pathophysiologic effects caused by virus that lead to morbidity and mortality. We propose a preponderance of evidence that supports clinical equipoise regarding the efficacy of RAAS-based interventions, and the imminent need for a multisite randomised controlled clinical trial to evaluate the inhibition of the RAAS-SCoV-axis on acute lung injury in COVID-19.

title: Key data for outbreak evaluation: building on the Ebola experience
abstract: Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

title: Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review.
abstract: Coronavirus disease 2019 (COVID-19) is a rapidly emerging disease that has been classified a pandemic by the World Health Organization (WHO). To support WHO with their recommendations on quarantine, we conducted a rapid review on the effectiveness of quarantine during severe coronavirus outbreaks.  We conducted a rapid review to assess the effects of quarantine (alone or in combination with other measures) of individuals who had contact with confirmed cases of COVID-19, who travelled from countries with a declared outbreak, or who live in regions with high transmission of the disease.  An information specialist searched PubMed, Ovid MEDLINE, WHO Global Index Medicus, Embase, and CINAHL on 12 February 2020 and updated the search on 12 March 2020. WHO provided records from daily searches in Chinese databases up to 16 March 2020.  CRITERIA Cohort studies, case-control-studies, case series, time series, interrupted time series, and mathematical modelling studies that assessed the effect of any type of quarantine to control COVID-19. We also included studies on SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome) as indirect evidence for the current coronavirus outbreak.  Two review authors independently screened 30% of records; a single review author screened the remaining 70%. Two review authors screened all potentially relevant full-text publications independently. One review author extracted data and assessed evidence quality with GRADE and a second review author checked the assessment. We rated the certainty of evidence for the four primary outcomes: incidence, onward transmission, mortality, and resource use.  We included 29 studies; 10 modelling studies on COVID-19, four observational studies and 15 modelling studies on SARS and MERS. Because of the diverse methods of measurement and analysis across the outcomes of interest, we could not conduct a meta-analysis and conducted a narrative synthesis. Due to the type of evidence found for this review, GRADE rates the certainty of the evidence as low to very low. Modeling studies consistently reported a benefit of the simulated quarantine measures, for example, quarantine of people exposed to confirmed or suspected cases averted 44% to 81% incident cases and 31% to 63% of deaths compared to no measures based on different scenarios (incident cases: 4 modelling studies on COVID-19, SARS; mortality: 2 modelling studies on COVID-19, SARS, low-certainty evidence). Very low-certainty evidence suggests that the earlier quarantine measures are implemented, the greater the cost savings (2 modelling studies on SARS). Very low-certainty evidence indicated that the effect of quarantine of travellers from a country with a declared outbreak on reducing incidence and deaths was small (2 modelling studies on SARS). When the models combined quarantine with other prevention and control measures, including school closures, travel restrictions and social distancing, the models demonstrated a larger effect on the reduction of new cases, transmissions and deaths than individual measures alone (incident cases: 4 modelling studies on COVID-19; onward transmission: 2 modelling studies on COVID-19; mortality: 2 modelling studies on COVID-19; low-certainty evidence). Studies on SARS and MERS were consistent with findings from the studies on COVID-19.  Current evidence for COVID-19 is limited to modelling studies that make parameter assumptions based on the current, fragmented knowledge. Findings consistently indicate that quarantine is important in reducing incidence and mortality during the COVID-19 pandemic. Early implementation of quarantine and combining quarantine with other public health measures is important to ensure effectiveness. In order to maintain the best possible balance of measures, decision makers must constantly monitor the outbreak situation and the impact of the measures implemented. Testing in representative samples in different settings could help assess the true prevalence of infection, and would reduce uncertainty of modelling assumptions. This review was commissioned by WHO and supported by Danube-University-Krems.

title: Progress in tuberculosis control and the evolving public-health system in China
abstract: China has the world's second largest tuberculosis epidemic, but progress in tuberculosis control was slow during the 1990s. Detection of tuberculosis had stagnated at around 30% of the estimated total of new cases, and multidrug-resistant tuberculosis was a major problem. These signs of inadequate tuberculosis control can be linked to a malfunctioning health system. The spread of severe acute respiratory syndrome (SARS) in 2003, brought to light substantial weaknesses in the country's public-health system. After the SARS epidemic was brought under control, the government increased its commitment and leadership to tackle public-health problems and, among other efforts, increased public-health funding, revised laws that concerned the control of infectious diseases, implemented the world's largest internet-based disease reporting system, and started a programme to rebuild local public-health facilities. These measures contributed to acceleration in efforts to control tuberculosis. By 2005, the detection of cases of tuberculosis had increased to 80% of the estimated total new cases, permitting China to achieve the 2005 global tuberculosis control targets. At the same time, specific efforts to improve tuberculosis control also contributed to strengthening of the public-health system. We examine how the strengthening of a disease control programme and the public-health system worked together to achieve a desired health outcome.

title: COVID-19, Australia: Epidemiology Report 15 (Reporting week to 23:59 AEST 10 May 2020).
abstract: Confirmed cases in Australia notified up to 10 May 2020: notifications = 6,971; deaths = 98. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. The reduction in international travel, social distancing measures and public health action have likely been effective in slowing the spread of the disease, in the Australian community. Cases of COVID-19 continue to be notified by jurisdictions, albeit at a slowed rate. Testing rates over the past week have increased markedly, with a very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. In the past reporting week new cases in Australia are mostly considered to be locally acquired, consistent with the drop in international travel. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years, with a third of these cases associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, cases continue to increase, with some areas such as Brazil and India showing a dramatic rise in reported cases. Although some low-income countries have currently reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of disease occurrence.

title: Using ILI surveillance to estimate state-specific case detection rates and forecast SARS-CoV-2 spread in the United States
abstract: Detection of SARS-CoV-2 infections to date has relied on RT-PCR testing. However, a failure to identify early cases imported to a country, bottlenecks in RT-PCR testing, and the existence of infections which are asymptomatic, sub-clinical, or with an alternative presentation than the standard cough and fever have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how publicly available CDC influenza-like illness (ILI) outpatient surveillance data can be repurposed to estimate the detection rate of symptomatic SARS-CoV-2 infections. We find a surge of non-influenza ILI above the seasonal average and show that this surge is correlated with COVID case counts across states. By quantifying the number of excess ILI patients in March relative to previous years and comparing excess ILI to confirmed COVID case counts, we estimate the syndromic case detection rate of SARS-CoV-2 in the US to be less than 13%. If only 1/3 of patients infected with SARS-CoV-2 sought care, the ILI surge would correspond to more than 8.7 million new SARS-CoV-2 infections across the US during the three week period from March 8 to March 28. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to be doubling slower than every 4 days. Together these results suggest a conceptual model for the COVID epidemic in the US in which rapid spread across the US are combined with a large population of infected patients with presumably mild-to-moderate clinical symptoms. We emphasize the importance of testing these findings with seroprevalence data, and discuss the broader potential to use syndromic time series for early detection and understanding of emerging infectious diseases.

title: Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29(th)–March 30(th), 2020.
abstract: The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15(th), 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6(th), 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30(th), 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.9 (95%CI: 0.9,1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

title: COVID-19: What Should Interventional Radiologists Know and What Can They Do?
abstract: The outbreak of coronavirus disease 2019 (COVID-19) in late December 2019 in Wuhan, China, has been characterized as a “pandemic” by the World Health Organization and has resulted in 81,603 confirmed cases in China, among the 334,981 cases confirmed in 189 countries as of 09:00 am, March 24, 2020 (China central standard time). During the past 3 months, hundreds of thousands of Chinese health care workers, including interventional radiologists (IRs), have been fighting this battle against the horrifying COVID-19 disease. As IRs, what should we know and what can we do when facing this challenge? This paper shares the experience we have gone through.

title: A review of the 2019 Novel Coronavirus (COVID-19) based on current evidence
abstract: The pneumonia caused by novel coronavirus (SARS-CoV-2) in Wuhan, China in December 2019 is a highly contagious disease. The World Health Organization (WHO) has declared the ongoing outbreak as a global public health emergency. Currently, the research on novel coronavirus is still in the primary stage. Based on the current published evidence, we systematically summarizes the epidemiology, clinical characteristics, diagnosis, treatment and prevention of knowledge surrounding COVID-19. This review in the hope of helping the public effectively recognize and deal with the 2019 novel coronavirus (SARS-CoV-2), and providing a reference for future studies.

title: Extremely low exposure of a community to severe acute respiratory syndrome coronavirus: false seropositivity due to use of bacterially derived antigens.
abstract: Estimates of seropositivity to a new infectious agent in a community are useful to public health. For severe acute respiratory syndrome (SARS), the figures are conflicting. Herein, we screened 12,000 people in a community stricken by SARS 10 months previously and found 53 individuals (0.44%) who had immunoglobulin G antibodies to the SARS coronavirus (SARS-CoV) nucleocapsid (N) produced in bacteria. However, only seven of these (group 1) had sera which also reacted with the native N antigen expressed in SARS-CoV-infected Vero cells, N-transfected 293T cells, and tissues of infected SARS patients. Of these, six individuals had had SARS previously. The remaining person, as well as the 46 other individuals (group 2), were healthy and had no history of SARS. Group 1 antibodies recognized epitopes located slightly differently in N from those of group 2 antibodies, and a mouse hybridoma antibody resembling the former type was generated. Unusually, group 2 antibodies appeared to recognize cross-reactive bacterial epitopes that presumably were posttranslationally modified in eukaryotes and hence were probably not induced by SARS-CoV or related coronaviruses but rather by bacteria. The N antigen is thus highly unique. The extremely low rate (0.008%) of asymptomatic SARS infection found attests to the high virulence of the SARS-CoV virus.

title: Optimal Allocation of COVID-19 Test Kits Among Accredited Testing Centers in the Philippines
abstract: Testing is crucial for early detection, isolation, and treatment of coronavirus disease (COVID-19)-infected individuals. However, in resource-constrained countries such as the Philippines, test kits have limited availability. As of 12 April 2020, there are 11 testing centers in the country that have been accredited by the Department of Health (DOH) to conduct testing. In this paper, we determine the optimal percentage allocation of COVID-19 test kits among accredited testing centers in the Philippines that gives an equitable chance to all infected individuals to be tested. Heterogeneity in testing accessibility, population density of municipalities, and the capacity of testing facilities are included in the model. Our results showed that the range of optimal allocation per testing center are: Research Institute for Tropical Medicine (4.17%-6.34%), San Lazaro Hospital (14.65%-24.03%), University of the Philippines-National Institutes of Health (16.25%-44.80%), Lung Center of the Philippines (15.8%-26.40%), Baguio General Hospital Medical Center (0.58%-0.76%), The Medical City, Pasig City (5.96%-25.51%), St. Luke's Medical Center, Quezon City (1.09%-6.70%), Bicol Public Health Laboratory (0.06%-0.08%), Western Visayas Medical Center (0.71%-4.52%), Vicente Sotto Memorial Medical Center (1.02%-2.61%), and Southern Philippines Medical Center (approx 0.01%). If there will be changes in the number of testing centers, our model can still be used to modify the test kit allocation. Our results can serve as a guide to the authorities in distributing the COVID-19 test kits. These can also be used to determine the capacity of testing centers and the effects of increasing its number. The model can also be used for proposing additional number and location of new testing centers.

title: SCALE19: A scalable and cost-efficient method for testing Covid-19 based on hierarchical group testing
abstract: Containment of Covid-19 requires an extensive testing of the affected population. Some propose global testing to effectively contain Covid-19. Current tests for Covid-19 are administered individually. These tests for Covid-19 are expensive and are limited due to the lack of resources and time. We propose a simple and efficient group testing method for Covid-19. We propose a group testing method where test subjects are grouped and tested. Depending on the result of the group test, subsequent sub groups are formed and tested recursively based on a quartery search algorithm. We designed and built an evaluation model that simulates test subject population, infected test subjects according to available Covid-19 statistics, and the group testing processes in SCALE19. We considered several population models including USA and the world. Our results show that we can significantly reduce the required number of tests up to 89% without sacrificing the accuracy of the individual test of the entire population. For USA, up to 280 million tests can be reduced from the total US population of 331 million and it would be equivalent saving of $28 billion assuming a cost of $100 per test. For the world, 6.96 billion tests can be reduced from the total population of 7.8 billion and it would be equivalent to saving $696 billion. We propose SCALE19 can significantly reduce the total required number of tests compared to individual tests of the entire population. We believe SCALE19 is efficient and simple to be deployed in containment of Covid-19.

title: Assessing the impact of structured education on the knowledge of hospital pharmacists about adverse drug reactions and reporting methods in Saudi Arabia: an open-label randomised controlled trial
abstract: Pharmacists have limited knowledge about adverse drug reactions (ADRs) in Saudi Arabia.  The aim of this study was to assess the impact of educational intervention on the knowledge of hospital pharmacists about ADRs.  This was a 3-month randomized controlled trial conducted in Saudi Arabia between January 2018 and March 2018. Participants in both groups were required to complete an online questionnaire at baseline and at 12-week follow-up. Participants in the intervention group received a structured information sheet about ADRs 2 weeks after the first assessment. The main outcome measure was difference in mean knowledge score about ADRs.  Difference in mean knowledge score about ADRs.  A total of 46 participants were included in the study. At the 12-week follow-up, there was a significant improvement in the mean knowledge score (± standard deviation) of intervention participants from 7.67 (± 2.1) at baseline to 11.22 (± 0.4) (95% CI −4.5 to −2.5; p < 0.0001). The mean knowledge score of control participants remained unchanged at 6.71 (± 2.3) during both baseline and follow-up assessments.  ADR-specific education was associated with a significant improvement in the knowledge and understanding of pharmacists about ADRs and their methods of reporting.

title: Ebola in the Eastern Democratic Republic of Congo: One Health approach to infectious disease control
abstract: The Democratic Republic of Congo (DRC) is facing its tenth outbreak of Ebola virus disease (EVD), in North-Kivu and Ituri provinces. This is the second most deadly EVD outbreak in history, after the one that occurred in West Africa in 2014. The DRC Ministry of Health (MoH), supported by the World Health Organization (WHO) and a range of regional and international partners, are implementing EVD response plans in these affected areas such as screening of suspect cases at points of entry, case detection, contact tracing, laboratory testing, case management and infection prevention and control, safe and dignified burials, ring vaccination (this involves vaccination of infected individuals, direct contacts of infected individuals and contacts of their contacts), and therapeutics, community mobilization and free access to healthcare services. Despite these efforts, there has been a sharp rise in the number of confirmed cases within the identified affected areas, and due to a number of challenges unique to DRC, there has been an expansion in the geographical extent of transmission. The significance of the proximity of these regions to wildlife and the Virunga National Park is questionable in the EVD transmission dynamics. The close interaction between human, animal, and environmental factors, in combination with high population movement due to regular rebel attacks in these regions, suggest the need for the integration of the One Health approach in the holistic response plans for control and prevention of EVD. This paper seeks to highlight the implications and importance of a One Health–based approach into the infectious diseases control program implementation in DRC.

title: A time series method to analyze incidence pattern and estimate reproduction number of COVID-19
abstract: The ongoing pandemic of Coronavirus disease (COVID-19) emerged in Wuhan, China in the end of 2019. It has already affected more than 300,000 people, with the number of deaths nearing 13000 across the world. As it has been posing a huge threat to global public health, it is of utmost importance to identify the rate at which the disease is spreading. In this study, we propose a time series model to analyze the trend pattern of the incidence of COVID-19 outbreak. We also incorporate information on total or partial lockdown, wherever available, into the model. The model is concise in structure, and using appropriate diagnostic measures, we showed that a time-dependent quadratic trend successfully captures the incidence pattern of the disease. We also estimate the basic reproduction number across different countries, and find that it is consistent except for the United States of America. The above statistical analysis is able to shed light on understanding the trends of the outbreak, and gives insight on what epidemiological stage a region is in. This has the potential to help in prompting policies to address COVID-19 pandemic in different countries.

title: Estimation of the basic reproduction number, average incubation time, asymptomatic infection rate, and case fatality rate forCOVID-19: Meta-analysis and sensitivity analysis
abstract: The coronavirus disease 2019 (COVID-19) has been found to be caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensive knowledge of COVID-19 remains incomplete and many important features are still unknown. This manuscripts conduct a meta-analysis and a sensitivity study to answer the questions: What is the basic reproduction number? How long is the incubation time of the disease on average? What portion of infections are asymptomatic? And ultimately, what is the case fatality rate? Our studies estimate the basic reproduction number to be 3.15 with the 95% interval (2.41, 3.90), the average incubation time to be 5.08 days with the 95% confidence interval (4.77, 5.39) (in day), the asymptomatic infection rate to be 46% with the 95% confidence interval (18.48%, 73.60%), and the case fatality rate to be 2.72% with 95% confidence interval (1.29%, 4.16%) where asymptomatic infections are accounted for.

title: Still puzzling questions in immunology (infection and immunity)

title: Understanding the early dynamics of the 2014 porcine epidemic diarrhea virus (PEDV) outbreak in Ontario using the incidence decay and exponential adjustment (IDEA) model
abstract: The United States swine industry was first confronted with porcine epidemic diarrhea virus (PEDV) in 2013. In young pigs, the virus is highly pathogenic and the associated morbidity and mortality has a significant negative impact on the swine industry. We have applied the IDEA model to better understand the 2014 PEDV outbreak in Ontario, Canada. Using our simple, 2-parameter IDEA model, we have evaluated the early epidemic dynamics of PEDV on Ontario swine farms.  We estimated the best-fit R(0) and control parameter (d) for the between farm transmission component of the outbreak by fitting the model to publically available cumulative incidence data. We used maximum likelihood to compare model fit estimates for different combinations of the R(0) and d parameters. Using our initial findings from the iterative fitting procedure, we projected the time course of the epidemic using only a subset of the early epidemic data. The IDEA model projections showed excellent agreement with the observed data based on a 7-day generation time estimate. The best-fit estimate for R(0) was 1.87 (95% CI: 1.52 – 2.34) and for the control parameter (d) was 0.059 (95% CI: 0.022 – 0.117). Using data from the first three generations of the outbreak, our iterative fitting procedure suggests that R(0) and d had stabilized sufficiently to project the time course of the outbreak with reasonable accuracy.  The emergence and spread of PEDV represents an important agricultural emergency. The virus presents a significant ongoing threat to the Canadian swine industry. Developing an understanding of the important epidemiological characteristics and disease transmission dynamics of a novel pathogen such as PEDV is critical for helping to guide the implementation of effective, efficient, and economically feasible disease control and prevention strategies that are able to help decrease the impact of an outbreak.

title: COVID-19: what is next for public health?

title: Metronomic oral vinorelbine and lung cancer therapy during the COVID 19 pandemic: a single-center experience
abstract: • Intravenous vinorelbine is a standard treatment for advanced NSCLC; • Oral vinorelbine is equally effective as compared to intravenous vinorelbine; • Metronomic oral formulation of vinorelbine is a safe and active treatment for advanced NSCLC; • No established treatment is a “gold standard” during COVID19 era; • Metronomic oral vinorelbine permitted to carry on active treatment during COVID Emergency; • Metronomic oral vinorelbine reduce side effects and hospital visits to lung cancer patients; • Management of lung cancer patients may be improved by metronomic oral vinorelbine.

title: Bacterial and fungal co-infection in individuals with coronavirus: A rapid review to support COVID-19 antimicrobial prescribing
abstract: To explore and describe the current literature surrounding bacterial/fungal co-infection in patients with coronavirus infection.  MEDLINE, EMBASE, and Web of Science were searched using broad based search criteria relating to coronavirus and bacterial co-infection. Articles presenting clinical data for patients with coronavirus infection (defined as SARS-1, MERS, SARS-COV-2, and other coronavirus) and bacterial/fungal co-infection reported in English, Mandarin, or Italian were included. Data describing bacterial/fungal co-infections, treatments, and outcomes were extracted. Secondary analysis of studies reporting antimicrobial prescribing in SARS-COV-2 even in the absence of co-infection was performed.  1007 abstracts were identified. Eighteen full texts reported bacterial/fungal co-infection were included. Most studies did not identify or report bacterial/fungal coinfection (85/140;61%). 9/18 (50%) studies reported on COVID-19, 5/18 (28%) SARS-1, 1/18 (6%) MERS, and 3/18 (17%) other coronavirus. For COVID-19, 62/806 (8%) patients were reported as experiencing bacterial/fungal co-infection during hospital admission. Secondary analysis demonstrated wide use of broad-spectrum antibacterials, despite a paucity of evidence for bacterial coinfection. On secondary analysis, 1450/2010 (72%) of patients reported received antimicrobial therapy. No antimicrobial stewardship interventions were described. For non-COVID-19 cases bacterial/fungal co-infection was reported in 89/815 (11%) of patients. Broad-spectrum antibiotic use was reported.  Despite frequent prescription of broad-spectrum empirical antimicrobials in patients with coronavirus associated respiratory infections, there is a paucity of data to support the association with respiratory bacterial/fungal co-infection. Generation of prospective evidence to support development of antimicrobial policy and appropriate stewardship interventions specific for the COVID-19 pandemic are urgently required.

title: Using viral genomics to estimate undetected infections and extent of superspreading events for COVID-19
abstract: Asymptomatic infections and limited testing capacity have led to under-reporting of SARS-CoV-2 cases. This has hampered the ability to ascertain true infection numbers, evaluate the effectiveness of surveillance strategies, determine transmission dynamics, and estimate reproductive numbers. Leveraging both viral genomic and time series case data offers methods to estimate these parameters. Using a Bayesian inference framework to fit a branching process model to viral phylogeny and time series case data, we estimated time-varying reproductive numbers and their variance, the total numbers of infected individuals, the probability of case detection over time, and the estimated time to detection of an outbreak for 12 locations in Europe, China, and the United States. The median percentage of undetected infections ranged from 13% in New York to 92% in Shanghai, China, with the length of local transmission prior to two cases being detected ranging from 11 days (95% CI: 4-21) in California to 37 days (9-100) in Minnesota. The probability of detection was as low as 1% at the start of local epidemics, increasing as the number of reported cases increased exponentially. The precision of estimates increased with the number of full-length viral genomes in a location. The viral phylogeny was informative of the variance in the reproductive number with the 32% most infectious individuals contributing 80% of total transmission events. This is the first study that incorporates both the viral genomes and time series case data in the estimation of undetected COVID-19 infections. Our findings suggest the presence of undetected infections broadly and that superspreading events are contributing less to observed dynamics than during the SARS epidemic in 2003. This genomics-informed modeling approach could estimate in near real-time critical surveillance metrics to inform ongoing COVID-19 response efforts.

title: Making sense of the Global Coronavirus Data: The role of testing rates in understanding the pandemic and our exit strategy
abstract: The Coronavirus disease 2019(COVID-19) outbreak has caused havoc across the world. Subsequently, research on COVID-19 has focused on number of cases and deaths and predicted projections have focused on these parameters. We propose that the number of tests performed is a very important denominator in understanding the COVID-19 data. We analysed the number of diagnostic tests performed in proportion to the number of cases and subsequently deaths across different countries and projected pandemic outcomes. We obtained real time COVID-19 data from the reference website Worldometer at 0900 BST on Saturday 4th April, 2020 and collated the information obtained on the top 50 countries with the highest number of COVID 19 cases. We analysed this data according to the number of tests performed as the main denominator. Country wise population level pandemic projections were extrapolated utilising three models - 1) inherent case per test and death per test rates at the time of obtaining the data (4/4/2020 0900 BST) for each country; 2) rates adjusted according to the countries who conducted at least 100000 tests and 3) rates adjusted according to South Korea. We showed that testing rates impact on the number of cases and deaths and ultimately on future projections for the pandemic across different countries. We found that countries with the highest testing rates per population have the lowest death rates and give us an early indication of an eventual COVID-19 mortality rate. It is only by continued testing on a large scale that will enable us to know if the increasing number of patients who are seriously unwell in hospitals across the world are the tip of the iceberg or not. Accordingly, obtaining this information through a rapid increase in testing globally is the only way which will enable us to exit the COVID-19 pandemic and reduce economic and social instability.

title: COVID-19: Should We Test Everyone?
abstract: Since the beginning of 2020, the coronavirus disease 2019 (COVID-19) has spread rapidly in the city of Wuhan, P.R. China, and subsequently, across the world. The swift spread of the virus is largely attributed to its stealth transmissions in which infected patients may be asymptomatic. Undetected transmissions present a remarkable challenge for the containment of the virus and pose an appalling threat to the public. An urgent question that has been asked by the public is"Should I be tested for COVID-19 if I am sick?". While different regions established their own criteria for screening infected cases, the screening criteria have been modified based on new evidence and understanding of the virus as well as the availability of resources. The shortage of test kits and medical personnel has considerably limited our ability to do as many tests as possible. Public health officials and clinicians are facing a dilemma of balancing the limited resources and unlimited demands. On one hand, they are striving to achieve the best outcome by optimizing the usage of the scant resources. On the other hand, they are challenged by the patients' frustrations and anxieties, stemming from the concerns of not being tested for COVID-19 for not meeting the definition of PUI (person under investigation). In this paper, we evaluate the situation from the statistical viewpoint by factoring into the considerations of the uncertainty and inaccuracy of the test, an issue that is often overlooked by the general public. We aim to shed light on the tough situation by providing evidence-based reasoning from the statistical angle, and we expect this examination will help the general public understand and assess the situation rationally. Most importantly, the development offers recommendations for physicians to make sensible evaluations to optimally use the limited resources for the best medical outcome.

title: Coronavirus Disease (COVID-19) and Pediatric Patients: A Review of Epidemiology, Symptomatology, Laboratory and Imaging Results to Guide the Development of a Management Algorithm
abstract: Coronavirus disease (COVID-19) has been declared a worldwide pandemic. Compared to adults, there has been a significantly smaller number of reported cases of COVID-19 in the pediatric population, although the incidence is increasing every day. This article looks to review specific epidemiological factors, symptomatology, laboratory and imaging workup, and other relevant metrics derived from the limited published literature that are specific to the pediatric population, to provide a review for the pediatric practitioner and guide, in part, the creation of a clinical algorithm for the management of COVID-19 in the pediatric population that can be utilized by pediatric institutions.

title: Daily Situation Report on Coronavirus disease (COVID-19) in Iran; March 25, 2020
abstract: After detection of the first confirmed cases of COVID-19 in Iran, the National Committee on COVID-19 Epidemiology in Ministry of Health and Medical Education was established. This Committee is official source of gathering, analyzing, and reporting the COVID-19 data in Iran. The data of all sources in the country including, medical care monitoring center (MCMC), Hospitals’ Information Systems (HIS), Laboratory portal, the data of the center for communicable disease control (MOH), as well as the data from community health centers are integrated and used in this regards. This factsheet contain daily situation report on coronavirus disease (covid-19) in Iran; March 25, 2020.

title: COVID-19, Australia: Epidemiology Report 2 (Reporting week ending 19:00 AEDT 8 February 2020).
abstract: This is the second epidemiological report for coronavirus disease (COVID-19), previously known as novel coronavirus (2019-nCoV), reported in Australia as at 19:00 Australian Eastern Daylight Time [AEDT] 8 February 2020. It includes data on Australian cases notified during the week ending 19:00 AEDT 8 February 2020, the international situation and current information on the severity, transmission and spread of the COVID-19 infection.

title: Study of Non-Pharmacological Interventions on COVID-19 Spread
abstract: COVID-19 disease has emerged as one of the life threatening threat to the society. It is caused by a novel beta coronavirus. It began as unidentified pneumonia of unknown aetiology in Wuhan City, Hubei province in China emerged in December 2019. No vaccine has been produced till now. Mathematical models are used to study impact of different measures used to decrease pandemic. Mathematical models have been designed to estimate the numbers of spreaders in different scenarios in the present manuscript. In the present manuscript, three different mathematical models have been proposed with different scenarios such as screening, quarantine and NPIs for estimating number of virus spreaders. the analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other countries. Since, every people suffering with COVID-19 disease are spreaders. The screening and quarantine with NPIs have been implemented to study their impact on the spreaders. It has been found that NPI measures are able to reduce number of spreaders. The NPI measures reduces the growth of the spread function and providing decision makers more time to prepare with in dealing of the disease.

title: Coronavirus: home testing pilot launched in London to cut hospital visits and ambulance use.

title: Post-exposure Prophylaxis or Preemptive Therapy for SARS-Coronavirus-2: Study Protocol for a Pragmatic Randomized Controlled Trial
abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 causing the coronavirus disease 2019 (COVID-19) pandemic. Currently, there are a lack of evidence-based therapies to prevent COVID-19 following exposure, or to prevent worsening of symptoms following confirmed infection. We describe the design of a clinical trial of hydroxychloroquine for post-exposure prophylaxis and pre-emptive therapy for COVID-19.  We will conduct two nested multicenter international double-blind randomized placebo-controlled clinical trials of hydroxychloroquine for: 1) post-exposure prophylaxis (PEP) of asymptomatic household contacts or healthcare workers exposed to COVID-19 within the past four days, and 2) pre-emptive therapy (PET) for symptomatic outpatients with COVID-19 with a total symptom duration of less than 4 days. We will recruit 1500 patients for each the PEP and PET trials. Participants will be randomized 1:1 to receive 5 days of hydroxychloroquine or placebo. The primary PEP trial outcome will be the incidence of symptomatic COVID-19 disease. The primary PET trial outcome will be an ordinal scale of disease severity (not hospitalized; hospitalized without intensive care, hospitalization with intensive care, or death). Participant screening, informed consent, and follow up will be exclusively internet-based with appropriate regulatory and research ethics board approvals in Canada and the United States.  These complementary randomized control trials are innovatively designed and adequately powered to rapidly answer urgent questions regarding the effectiveness of hydroxychloroquine to reduce transmission and disease severity of COVID-19 during a pandemic. In-person participant follow-up will not be conducted in order to facilitate social distancing strategies and reduce risks of exposure to study personnel. Innovative trial approaches are needed to urgently assess therapeutic options to mitigate the global impact of this pandemic.

title: Development of Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP) Assays Targeting SARS-CoV-2
abstract: Epidemics of Coronavirus Disease 2019 (COVID-19) now have more than 100,000 confirmed cases worldwide. Diagnosis of COVID-19 is currently performed by RT-qPCR methods, but the capacity of RT-qPCR methods is limited by its requirement of high-level facilities and instruments. Here, we developed and evaluated RT-LAMP assays to detect genomic RNA of SARS-CoV-2, the causative virus of COVID-19. RT-LAMP assays in this study can detect as low as 100 copies of SARS-CoV-2 RNA. Cross-reactivity of RT-LAMP assays to other human Coronaviruses was not observed. We also adapted a colorimetric detection method for our RT-LAMP assay so that the tests potentially performed in higher throughput.

title: The Rate of Underascertainment of Novel Coronavirus (2019-nCoV) Infection: Estimation Using Japanese Passengers Data on Evacuation Flights
abstract: From 29 to 31 January 2020, a total of 565 Japanese citizens were evacuated from Wuhan, China on three chartered flights. All passengers were screened upon arrival in Japan for symptoms consistent with novel coronavirus (2019-nCoV) infection and tested for presence of the virus. Assuming that the mean detection window of the virus can be informed by the mean serial interval (estimated at 7.5 days), the ascertainment rate of infection was estimated at 9.2% (95% confidence interval: 5.0, 20.0). This indicates that the incidence of infection in Wuhan can be estimated at 20,767 infected individuals, including those with asymptomatic and mildly symptomatic infections. The infection fatality risk (IFR)—the actual risk of death among all infected individuals—is therefore 0.3% to 0.6%, which may be comparable to Asian influenza pandemic of 1957–1958.

title: The role of institutional trust in preventive and treatment-seeking behaviors during the 2019 novel coronavirus (2019-nCoV) outbreak among residents in Hubei, China
abstract: Since December 2019, pneumonia associated with the 2019 novel coronavirus (2019-nCoV) has emerged in Wuhan, China. The exponential increase of the confirmed number of cases of 2019n-CoV is of great concern to the global community. The fears and panic among residents in the epicenters have prompted diverse responses, which are understudied. During such a crisis, community trust and support for the government and health authorities are important to contain the outbreak. We aimed to investigate the influence of institutional trust on public responses to the 2019-nCoV outbreak.  An anonymous Internet-based, cross-sectional survey was administered on January 29, 2020. The study population comprised all residents currently residing or working in the province of Hubei, where Wuhan is the capital city. The level of trust in information provision and preventive instructions, individual preventive behaviors and treatment-seeking behaviors were queried.  The majority of the participants expressed a great extent of trust in the information and preventive instructions provided by the central government than by the local government. A high uptake of 2019-nCoV preventive measures was found, particularly among people who had been placed under quarantine. Being under quarantine (adjusted odds ratio [OR] = 2.35, 95% confidence interval [CI] 1.80 to 3.08) and having a high institutional trust score (OR = 2.23, 95% CI 1.96 to 2.53) were both strong and significant determinants of higher preventive behavior scores. The majority of study participants (85.7%, n = 3,640) reported that they would seek hospital treatment if they suspected themselves to have been infected with 2019 n-CoV. Few of the participants from Wuhan (16.6%, n = 475) and those participants who were under quarantine (13.8%, n = 550) expressed an unwillingness to seek hospital treatment. Similarly, being under quarantine (OR = 2.36, 95% CI 1.80 to 3.09) and having a high institutional trust score (OR = 2.20, 95% CI 1.96 to 2.49) were two strong significant determinants of hospital treatment-seeking.  The results of this study suggest that institutional trust is an important factor influencing adequate preventive behavior and seeking formal medical care during an outbreak. In view of the 2019-nCoV being highly pathogenic and extremely contagious, our findings also underscore the importance of public health intervention to reach individuals with poor adherence to preventive measures and who are reluctant to seek treatment at formal health services.   2019-nCoV; institutional trust; preventive behaviors

title: Anesthesiologists' and intensive care providers' exposure to COVID-19 infection in a New York City academic center: a prospective cohort study assessing symptoms and COVID-19 antibody testing
abstract: Protecting first-line healthcare providers against work-related COVID-19 infection at the onset of the pandemic has been a crucial challenge in the United States. Anesthesiologists in particular are considered at risk, since aerosol-generating procedures, such as intubation and extubation, have been shown to significantly increase the odds for respiratory infections during severe acute respiratory syndrome (SARS) outbreaks. This study assessed the incidence of COVID-19-like symptoms and presence of COVID-19 antibodies after work-related COVID-19 exposures, among physicians working in a large academic hospital in New York City (NYC).  An e-mail survey was addressed to anesthesiologists and affiliated intensive care providers at Columbia University Irving Medical Center on April 15, 2020. The survey assessed 4 domains: 1) demographics and medical history, 2) community exposure to COVID-19 (e.g., use of NYC subway), 3) work-related exposure to COVID-19, and 4) development of COVID-19-like symptoms after work exposure. The first 100 survey responders were invited to undergo a blood test to assess antibody status (presence of IgM/IgG specific to COVID-19). Work-related exposure was defined as any episode where the provider was not wearing adequate personal protective equipment (airborne or droplet/contact protection depending on the exposure type). Based on the clinical scenario, work exposure was categorized as high-risk (e.g., exposure during intubation) or low-risk (e.g., exposure during doffing).  205 healthcare providers were contacted and 105 completed the survey (51%); 91 completed the serological test. Sixty-one of the respondents (58%) reported at least one work-related exposure and 54% of the exposures were high-risk. Among respondents reporting a work-related exposure, 16 (26.2%) reported post-exposure COVID-19-like symptoms. The most frequent symptoms were myalgia (9 cases), diarrhea (8 cases), fever (7 cases), and sore throat (7 cases). COVID-19 antibodies were detected in 11 of the 91 tested respondents (12.1%), with no difference between respondents with (11.8%) or without (12.5%) a work- related exposure, including high-risk exposure. Compared with antibody negative respondents, antibody positive respondents were more likely to use NYC subway to commute to work and report COVID-19-like symptoms in the last 90 days.  In the epicenter of the United States' pandemic and within 6-8 weeks of the COVID-19 outbreak, a small proportion of anesthesiologists and affiliated intensive care providers reported COVID-19-like symptoms after a work-related exposure and even fewer had detectable COVID-19 antibodies. Presence of COVID-19 antibodies appeared to be associated with community/environmental transmission rather than secondary to work-related exposures involving high risk procedures.

title: A deeper look at COVID-19 CFR: health care impact and roots of discrepancy
abstract: Intensive care capacity and proper testing play a paramount role in the COVID-19 Case Fatality Rate (CFR). Nevertheless, the real impact of such important measures has not been appreciated due to the lack of proper metrics. In this work, we have proposed a method for estimating a lower bound for the number of positive cases by using the reported data on the oldest age group and the regions' population distributions. The proposed estimation method improved the expected similarity between the age-distribution of positive cases and regions' population. Further, we have provided a quantitative measure for the impact of intensive care on the critical cases by comparing the CFR among those who did and did not receive intensive care. Our findings showed that the chance of living among non-ICU receivers is less than half of ICU receivers (~24% vs ~60%).

title: Herd‐level prevalence and incidence of porcine epidemic diarrhoea virus (PEDV) and porcine deltacoronavirus (PDCoV) in swine herds in Ontario, Canada
abstract: Porcine epidemic diarrhoea virus (PEDV) and porcine deltacoronavirus (PDCoV) were first identified in Canada in 2014. Surveillance efforts have been instrumental in controlling both diseases. In this study, we provide an overview of surveillance components for the two diseases in Ontario (Canada), as well as PEDV and PDCoV incidence and prevalence measures. Swine herds located in the Province of Ontario, of any type, whose owners agreed to participate in a voluntary industry‐led disease control programme (DCP) and with associated diagnostic or epidemiological information about the two swine coronaviruses, were eligible to be included for calculation of disease frequency at the provincial level. PEDV and PDCoV data stored in the industry DCP database were imported into the R statistical software and analysed to produce weekly frequency of incidence counts and prevalence counts, in addition to yearly herd‐level incidence risk and prevalence between 2014 and 2016. The yearly herd‐level incidence risk of PEDV, based on industry data, was 13.5%, 3.0% and 1.4% (95% CI: 11.1–16.2, 2.0–4.2, 0.8–2.3), while the yearly herd‐level incidence risk of PDCoV was 1.1%, 0.3%, and 0.1% (95% CI: 0.5–2.2, 0.1–0.9, 0.0–0.5), for 2014, 2015 and 2016, respectively. Herd‐level prevalence estimates for PEDV in the last week of 2014, 2015 and 2016 were 4.4%, 2.3% and 1.4%, respectively (95% CI: 3.1–6.0, 1.5–3.3, ), while herd‐level prevalence estimates for PDCoV in the last week of 2014, 2015 and 2016 were 0.5%, 0.2% and 0.2%, respectively (95% CI: 0.1–1.2, 0.0–0.6, 0.0–0.6). Collectively, our results point to low and decreasing incidence risk and prevalence for PEDV and PDCoV in Ontario, making both diseases possible candidates for disease elimination at the provincial level.

title: Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
abstract: This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19.

title: Initial human transmission dynamics of the pandemic (H1N1) 2009 virus in North America
abstract: Between 5 and 25 April 2009, pandemic (H1N1) 2009 caused a substantial, severe outbreak in Mexico, and subsequently developed into the first global pandemic in 41 years. We determined the reproduction number of pandemic (H1N1) 2009 by analyzing the dynamics of the complete case series in Mexico City during this early period.  We analyzed three mutually exclusive datasets from Mexico City Distrito Federal which constituted all suspect cases from 15 March to 25 April: confirmed pandemic (H1N1) 2009 infections, non‐pandemic influenza A infections and patients who tested negative for influenza. We estimated the initial reproduction number from 497 suspect cases identified prior to 20 April, using a novel contact network methodology incorporating dates of symptom onset and hospitalization, variation in contact rates, extrinsic sociological factors, and uncertainties in underreporting and disease progression. We tested the robustness of this estimate using both the subset of laboratory‐confirmed pandemic (H1N1) 2009 infections and an extended case series through 25 April, adjusted for suspected ascertainment bias.  The initial reproduction number (95% confidence interval range) for this novel virus is 1·51 (1·32–1·71) based on suspected cases and 1·43 (1·29–1·57) based on confirmed cases before 20 April. The longer time series (through 25 April) yielded a higher estimate of 2·04 (1·84–2·25), which reduced to 1·44 (1·38–1·51) after correction for ascertainment bias.  The estimated transmission characteristics of pandemic (H1N1) 2009 suggest that pharmaceutical and non‐pharmaceutical mitigation measures may appreciably limit its spread prior the development of an effective vaccine.

title: Will COVID-19 pandemic diminish by summer-monsoon in India? Lesson from the first lockdown
abstract: The novel Coronavirus (2019-nCoV) was identified in Wuhan, Hubei Province, China, in December 2019 and has created a medical emergency worldwide. It has spread rapidly to multiple countries and has been declared a pandemic by the World Health Organization. In India, it is already reported more than 18 thousand cases and more than 600 deaths due to Coronavirus disease 2019 (COVID-19) till April 20, 2020. Previous studies on various viral infections like influenza have supported an epidemiological hypothesis that the cold and dry (low absolute humidity) environments favor the survival and spread of droplet-mediated viral diseases. These viral transmissions found attenuated in warm and humid (high absolute humidity) environments. However, the role of temperature, humidity, and absolute humidity in the transmission of COVID-19 has not yet been well established. Therefore the study to investigate the meteorological condition for incidence and spread of COVID-19 infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease is required for India. In this work, we analyze the local weather patterns of the Indian region affected by the COVID-19 virus for March and April months, 2020. We have investigated the effect of meteorological parameters like Temperature, relative humidity, and absolute humidity on the rate of spread of COVID-19 using daily confirm cases in India. We have used daily averaged meteorological data for the last three years (2017-2019) for March and April month and the same for the year 2020 for March 1 to April 15. We found a positive association (Pearsons r=0.56) between temperature and daily COVID-19 cases over India. We found a negative association of humidity (RH and AH) with daily COVID-19 Cases (Persons r=-0.62, -0.37). We have also investigated the role of aerosol in spreading the pandemic across India because its possible airborne nature. For this, we have investigated the association of aerosols (AOD) and other pollutions (NO2) with COVID-19 cases during the study period and also during the first lockdown period (25 March-15 April) in India. We found a negative association in March when there were few cases, but in April, it shows positive association when the number of cases is more (for AOD it was r=-0.41 and r=0.28 respectively). During the lockdown period, aerosols (AOD) and other pollutants (NO2; an indicator of PM2.5) reduced sharply with a percentage drop of about 36 and 37, respectively. This reduction may have reduced the risk for COVID-19 through air transmission due to the unavailability of aerosol particles as a base. HYSPLIT forward trajectory model also shows that surface aerosols may travel up to 4 km according to wind and direction within three h of its generation. If coronavirus becomes airborne as suggested by many studies, then it may have a higher risk of transmission by aerosols particles. So relaxing in the lockdown and environmental rules in terms of pollutant emissions from power plants, factories, and other facilities would be a wrong choice and could result in more COVID-19 incidences and deaths in India. Therefore the current study, although limited, suggests that it is doubtful that the spread of COVID-19 would slow down in India due to meteorological factors, like high temperature and high humidity. Because a large number of cases have already been reported in the range of high Tem, high Relative, and high absolute humidity regions of India. Thus our results in no way suggest that COVID-19 would not spread in warm, humid regions or during summer/monsoon. So effective public health interventions should be implemented across India to slow down the transmission of COVID-19. If COVID-19 is indeed sensitive to environmental factors, it could be tested in the coming summer-monsoon for India. So the only summer is not going to help India until monsoon is coming. Only government mitigations strategies would be helpful, whether its lockdown, aggressive and strategic testing, medical facilities, imposing social distancing, encouraging to use face mask or monitoring by a mobile application (Aarogya Setu).

title: Adjusting Coronavirus prevalence estimates for laboratory test kit error
abstract: Testing representative populations to determine the prevalence or percent of the population with active SARS-Cov-2 (COVID-19) infection and/or antibodies to infection is being recommended as essential for making public policy decisions to open-up or to continue enforcing national, state and local government rules to shelter-in-place. However, all laboratory tests are imperfect and have estimates of sensitivity and specificity less than 100% - in some cases considerably less than 100%. That error will lead to biased prevalence estimates. If the true prevalence of COVID-19 is low, possibly in the range of 1-5%, then testing error will lead to a constant background of bias that will most likely be larger and possibly much larger than the true prevalence itself. As a result, what is needed is a method for adjusting prevalence estimates for testing error. In this paper we outline methods for adjusting prevalence estimates for testing error both prospectively in studies being planned and retrospectively in studies that have been conducted. The methods if employed would also help to harmonize study results within countries and around the world. Adjustment can lead to more accurate prevalence estimates and to better policy decisions.

title: Smell and Taste Dysfunction in Patients With COVID-19: A Systematic Review and Meta-analysis
abstract: To estimate the prevalence of olfactory and gustatory dysfunctions (OGDs) among patients infected with novel coronavirus disease 2019 (COVID-19).  A systematic review was conducted by searching MEDLINE, EMBASE, and the preprint server MedRxiv until 11 May 2020 using the terms ‘anosmia’ or ‘hyposmia’ or ‘dysosmia’ or ‘olfactory dysfunction’ or ‘olfaction disorder’ or ‘smell dysfunction’ or ‘ageusia’ or ‘hypogeusia’ or ‘dysgeusia’ or ‘taste dysfunction’ or ‘gustatory dysfunction’ or ‘neurological’ and ‘COVID-19’ or ‘2019 novel coronavirus’ or ‘2019-nCoV’ or ‘SARS-CoV-2’. References of included studies were also manually screened. Only studies involving diagnostic-confirmed patients with COVID-19 were included. Random-effects meta-analysis was performed.  A total of twenty-four studies with data from 8438 test-confirmed COVID-19 patients from thirteen countries were included. The pooled proportion of patients presenting with olfactory and gustatory dysfunctions was 41.0% (95% confidence interval [CI] 28.5% to 53.9) and 38.2% (95% CI 24.0 to 53.6%), respectively. Increasing mean age correlated with lower prevalence of olfactory (coefficient = -0.076; p=.02) and gustatory (coefficient = -0.073; p=.03) dysfunctions. There was a higher prevalence of olfactory dysfunctions with the use of objective measurements compared to self-reports (coefficient = 2.33; p=.01). No significant moderation of the prevalence of OGDs by gender was observed.  There is a high prevalence of OGDs among patients infected with COVID-19. Routine screening for these conditions could contribute to improved case detection in the ongoing COVID-19 pandemic. However, to better inform population screening measures, further studies are needed to establish causality.

title: Evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as coronavirus disease 2019 (COVID-19) pandemic: A global health emergency
abstract: According to data compiled by researchers at Johns Hopkins University in Baltimore, Maryland, more than two and half million cases of coronavirus disease 2019 (COVID-19), caused by a newly discovered virus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), have been confirmed on April 20, 2020 ( 2020b). Since the emergence of this infectious disease in Asia (Wuhan, China) late last year, it has been subsequently span to every continent of the world except Antarctica (Rodríguez-Morales et al., 2020). Along with a foothold in every country, the current disease pandemic is disrupting practically every aspect of life all over the world. As the outbreak are continuing to evolve, several research activities have been conducted for better understanding the origin, functions, treatments, and preventions of this novel coronavirus. This review will be a summa of the key features of novel coronavirus (nCoV), the virus causing disease 2019 and the present epidemic situation worldwide up to April 20, 2020. It is expected that this record will play an important role to take more preventive measures for overcoming the challenges faced during this current pandemic.

title: The within-host viral kinetics of SARS-CoV-2
abstract: In this work, we use a within-host viral dynamic model to describe the SARS-CoV-2 kinetics in host. Chest radiograph score data are used to estimate the parameters of that model. Our result shows that the basic reproductive number of SARS-CoV-2 in host growth is around 3.79. Using the same method we also estimate the basic reproductive number of MERS virus is 8.16 which is higher than SARS-CoV-2. The PRCC method is used to analyze the sensitivities of model parameters and the drug effects on virus growth are also implemented to analyze the model.

title: COVID-19 in Italy: impact of containment measures and prevalence estimates of infection in the general population
abstract: Since the beginning of the COVID-19 epidemic in Italy, the Italian Government implemented several restrictive measures to contain the spread of the infection. Data shows that, among these measures, the lockdown implemented as of 9 March had a positive impact, in particular the central and southern regions of Italy, while other actions appeared to be less effective. When the true prevalence of a disease is unknown, it is possible estimate it, based on mortality data and the assumptive case-fatality rate of the disease. Given these assumptions, the estimated period-prevalence of COVID-19 in Italy varies from 0.35% in Sicity to 13.3% in Lombardy.

title: Understanding the Anemic Global Response to COVID-19.
abstract: The COVID-19 outbreak is the most serious test of the international system since the 2008 global financial crisis. Rather than cooperate to contain and respond to a common threat, the world's leading powers, the United States and China, increasingly blamed each other through wildly speculative theories about the origins of the virus. The World Health Organization (WHO) sought to coordinate a global response but it has been hamstrung and come under attack. Given past cooperation between major powers to mobilize and eradicate smallpox and previous U.S. leadership to fight HIV/AIDS and the 2014 West African Ebola crisis, the limited cooperation and lack of leadership are puzzling. What explains the anemic global response to date? This paper draws from structural international relations theory to suggest a partial but somewhat dissatisfying answer. International organizations are inherently weak faced with opposition by major powers. The international system simultaneously incentivizes states to cooperate and address common threats but at the same time encourages countries to take care of themselves, potentially at the expense of others. Which of these motives dominates cannot be explained by structural theory, requiring us to look to other factors such as the attributes of states or of leaders themselves.

title: Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States
abstract: Detection of SARS-CoV-2 infections to date has relied heavily on RT-PCR testing. However, limited test availability, high false-negative rates, and the existence of asymptomatic or sub-clinical infections have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how influenza-like illness (ILI) outpatient surveillance data can be used to estimate the prevalence of SARS-CoV-2. We found a surge of non-influenza ILI above the seasonal average in March 2020 and showed that this surge correlated with COVID-19 case counts across states. If 1/3 of patients infected with SARS-CoV-2 in the US sought care, this ILI surge would have corresponded to more than 8.7 million new SARS-CoV-2 infections across the US during the three-week period from March 8 to March 28, 2020. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to have been doubling slower than every 4 days. Together these results suggest a conceptual model for the COVID-19 epidemic in the US characterized by rapid spread across the US with over 80% infected patients remaining undetected. We emphasize the importance of testing these findings with seroprevalence data and discuss the broader potential to use syndromic surveillance for early detection and understanding of emerging infectious diseases.

title: COVID-19 trend in Bangladesh: deviation from epidemiological model and critical analysis of the possible factors
abstract: Since its first report on March 08, COVID-19 positive cases and number of deaths are increasing in Bangladesh. In the first month of COVID-19 infection, incidence of daily positive cases did follow the susceptible, infected and recovered (SIR) based predictions we reported in April, but started to deviate in the following month. COVID-19 transmission and disease progression depends on multifaceted determinants e.g. viral genetics, host immunity, social distancing, co-morbidity, socio-demographic and environmental parameters. Therefore deviation in confirmed cases from predicted model may appear and warrant thorough investigation. In this short report, we tried to demonstrate and analyze the possible factors associated with the deviation which included preventive intervention strategies, socioeconomic capabilities, climatic and meteorological indexes, acquired immunity of Bangladeshi population, demographic characteristics, health indicators and food habits.  The key factor responsible for the deviation was found to be the number of tests performed. Having population with low median age, young age groups are being mostly infected. Low prevalence of non-communicable diseases among them and strong immunity compared to the elderly might have kept most of them asymptomatic with silent recovery. Warm temperature, humidity and UV index of Bangladesh during this summer period might have contributed to the slow progression of infection. Longer daylight mediated immunity, fresh air circulations and ventilation, less density in rural areas and certain food habits perhaps helped the large number of populations to restrict the infection.  Despite all these helpful determinants in Bangladesh, person to person contact is still the leading risk factor for COVID-19 transmission. Infection may increase rapidly if safe distance and preventive measures are not strictly followed while resuming the normal social and work life. A global second wave may hit in many countries in autumn and as well as in Bangladesh in mid-October when winter starts to approach. Strong collaborative action plans, strategies and implementation are needed immediately to prevent catastrophe.

title: Quantifying the effect of quarantine control in Covid-19 infectious spread using machine learning
abstract: Since the first recording of what we now call Covid-19 infection in Wuhan, Hubei province, China on Dec 31, 2019, the disease has spread worldwide and met with a wide variety of social distancing and quarantine policies. The effectiveness of these responses is notoriously difficult to quantify as individuals travel, violate policies deliberately or inadvertently, and infect others without themselves being detected. Moreover, the publicly available data on infection rates are themselves unreliable due to limited testing and even possibly under-reporting. In this paper, we attempt to interpret and extrapolate from publicly available data using a mixed first-principles epidemiological equations and data-driven neural network model. Leveraging our neural network augmented model, we focus our analysis on four locales: Wuhan, Italy, South Korea and the United States of America, and compare the role played by the quarantine and isolation measures in each of these countries in controlling the effective reproduction number Rt of the virus. Our results unequivocally indicate that the countries in which rapid government interventions and strict public health measures for quarantine and isolation were implemented were successful in halting the spread of infection and prevent it from exploding exponentially. In the case of Wuhan especially, where the available data were earliest available, we have been able to test the predicting ability of our model by training it from data in the January 24 till March 3 window, and then matching the predictions up to April 1. Even for Italy and South Korea, we have a buffer window of one week (25 March - 1 April) to validate the predictions of our model. In the case of the US, our model captures well the current infected curve growth and predicts a halting of infection spread by 20 April 2020. We further demonstrate that relaxing or reversing quarantine measures right now will lead to an exponential explosion in the infected case count, thus nullifying the role played by all measures implemented in the US since mid March 2020.

title: Trends in excess cancer and cardiovascular deaths in Scotland during the COVID-19 pandemic 30 December 2019 to 20 April 2020
abstract: Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks' of data, we found a peak in excess deaths between weeks 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had diminished around the time lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.

title: Thoughts on Higher Medical Education Under Major Public Health Emergencies: Thinking Ahead After COVID-19 Outbreak
abstract: To explore the most suitable teaching and learning pattern in medical school during COVID-19 Outbreak.  This study is a case-control study. We had tried to apply a new blended teaching model based on 5G network that combined team-based learning (TBL) and online interaction to the students before the outbreak and then universities responded to the COVID-19 outbreak by closing campuses and shifting to other forms of distance learning. In other word, the courses started using blended teaching model before COVID-19 outbreak and might last using other forms of distance learning throughout the pandemic. Five Point Likert Scale Questionnaires which contains 20 items were used, and the effect of the two kinds of teaching patterns was compared by evaluating the indicators of core competencies of students including professionalism, attitude towards learning, knowledge and learning skills, teamwork skills, motivation in learning, adaptability and acceptance of the courses and network environment.  Our study based on a single center.  Fifty fourth-year medical students receiving the 5+3 pattern courses regarding internal medicine were enrolled in the study. The teaching and learning patter started using blended teaching model before COVID-19 outbreak and might last using other forms of distance learning throughout the pandemic.  According to the descriptive statistical analysis of the first part of the questionnaire (question 1-16), the average score of adaptability and acceptance of the courses is 2.60 lower than 3, indicating that students are more adapted to other forms of distance learning during COVID-19 outbreak; the average score of the rest of the questions is higher than 3, indicating that blended teaching model based on 5G network is superior to other forms of distance learning. The number of male students who are inclined to the blended teaching model based on 5G network is 0.13 times as much as that of female students (95%CI:0.028~0.602, p=0.009).  Online forms of distance learning were accepted by the students. Female students had higher expectations on the course and were more likely to adapt well to the change during the COVID-19 outbreak. However, all students preferred the blended teaching model based on 5G network that combined team-based learning (TBL) and online interaction before the pandemic.  It indicates that medical education based on 5G network that combined team-based learning (TBL) and online interaction is a more suitable option to teach medical students online. China's experience in online higher medical education may serve as a reference to other countries during the pandemic.

title: Coronavirus 2019 and health systems affected by protracted conflict: the case of Syria
abstract: Two thirds of countries globally are unprepared to respond to a health emergency as per the International Health Regulations (2005) with conflict-affected countries like Syria particularly vulnerable. Political influences on outbreak preparedness, response and reporting may also adversely affect control of SARS-CoV-2 in Syria. Syria reported its first case on 22 March 2020 however concerns were raised that this was delayed and that underreporting continues. Main Syria's conflict has displaced more than half its pre-war population leaving 6.7 million people internally displaced; consequent overcrowding with insufficient water, sanitation and healthcare (including laboratory capacity) could lead to conditions which are ideal for spread of SARS-CoV-2 in Syria. Political changes have led to the formation of at least three health systems within Syria's borders, each with their own governance, capacity and planning. This fragmentation with little interaction between them could lead to poor resource allocation and adversely affect control. As such, COVID-19 could overwhelm the health systems (particularly intensive care capacity) leading to high deaths across the population, particularly for the most vulnerable such as detainees.  Locally implementable interventions which rapidly build WASH and health system capacity are required across Syria to ensure early detection and management of COVID-19 cases.

title: The proportion of deaths cases in confirmed patients of COVID-19 is still increasing for cumulative cases reported up to 25 April 2020
abstract: In this work I analyse how proportions of fatal cases after COVID-19 infection change since outbreak of the disease. Using publicity available data I model the change in deaths probability from day 30 of outbreak until 25 April 2020. The global trend is that the proportion of fatal cases is still increasing and that many countries have not yet reached the maximum deaths proportion. However, there are visual differences between countries and in some countries the proportions are clearly below or above the global trend. A positive correlation between deaths cases and recorded infections indicates that a higher infection number results in increased mortality numbers.

title: Global rheumatology in the time of COVID-19

title: Using Supervised Machine Learning and Empirical Bayesian Kriging to reveal Correlates and Patterns of COVID-19 Disease outbreak in sub-Saharan Africa: Exploratory Data Analysis
abstract: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide. Knowledge of coronavirus-related risk factors can help countries build more systematic and successful responses to COVID-19 disease outbreak. Here we used Supervised Machine Learning and Empirical Bayesian Kriging (EBK) techniques to reveal correlates and patterns of COVID-19 Disease outbreak in sub-Saharan Africa (SSA).  We analyzed time series aggregate data compiled by Johns Hopkins University on the outbreak of COVID-19 disease across SSA. COVID-19 data was merged with additional data on socio-demographic and health indicator survey data for 39 of SSA 48 countries that reported confirmed cases and deaths from coronavirus between February 28, 2020 through March 26, 2020. We used supervised machine learning algorithm, Lasso for variable selection and statistical inference. EBK was used to also create a raster estimating the spatial distribution of COVID-19 disease outbreak.  The lasso Cross-fit partialing out predictive model ascertained seven variables significantly associated with the risk of coronavirus infection (i.e. new HIV infections among pediatric, adolescent, and middle-aged adult PLHIV, time (days), pneumococcal conjugate-based vaccine, incidence of malaria and diarrhea treatment). Our study indicates, the doubling time in new coronavirus cases was 3 days. The steady three-day decrease in coronavirus outbreak rate of change (ROC) from 37% on March 23, 2020 to 23% on March 26, 2020 indicates the positive impact of countries' steps to stymie the outbreak. The interpolated maps show that coronavirus is rising every day and appears to be severely confined in South Africa. In the West African region (i.e. Burkina Faso, Ghana, Senegal, CotedIviore, Cameroon, and Nigeria), we predict that new cases and deaths from the virus are most likely to increase.  Integrated and efficiently delivered interventions to reduce HIV, pneumonia, malaria and diarrhea, are essential to accelerating global health efforts. Scaling up screening and increasing COVID-19 testing capacity across SSA countries can help provide better understanding on how the pandemic is progressing and possibly ensure a sustained decline in the ROC of coronavirus outbreak.

title: Incidence of Respiratory Viral Infections Detected by PCR and Real-Time PCR in Adult Patients with Community-Acquired Pneumonia: A Meta-Analysis
abstract: With the development of more rapid and sensitive detection methods based on PCR techniques, the contributions of respiratory viral infections to community-acquired pneumonia (CAP) in adult patients are being more and more recognized. Yet, up to now, there has been a lack of synthetic data that clearly demonstrates the incidence of respiratory viral infections in adult patients with CAP.  We intended to demonstrate the incidence of respiratory viral infections detected by PCR and real-time PCR in adult patients with CAP.  We searched PubMed and Embase for studies providing the incidence of respiratory viral infections in adult patients with CAP. We investigated potential sources of heterogeneity by a univariant metaregression analysis and calculated the combined incidence of viral infections, viral infections mixed with other pathogens and individual respiratory virus species.  We eventually identified 23 eligible reports with a total number of 6,404 patients. Incidences ranged from 8.6 to 56.2% for overall respiratory viral infections. We noted significant heterogeneity in incidence estimates for the incidence of viral infections (Cochran's χ(2) = 269.9, p < 0.0001, I(2) = 91.8%). The combined incidence of viral infections was 22.4% (95% CI = 19.0-25.7). Incidences of viral coinfections with other pathogens ranged from 3 to 28%. A high level of heterogeneity was identified as well during the estimates for incidences of coinfections (χ(2) = 200.9, p < 0.0001, I(2) = 91.5%). The combined incidence of viral coinfections with other pathogens was 12.4% (95% CI = 9.7-15.0). Our heterogeneity analyses suggested that a lower respiratory tract sample was associated with higher overall viral incidence. Moreover, the influenza virus, rhinovirus and coronavirus were the 3 most frequently detected viral pathogens in adult patients with CAP according to our study.  Respiratory viruses are probably crucial pathogens of adult patients with CAP, with the influenza virus being the most frequent viral pathogen identified. More than half of the viral infections are characterized as mixed infections with other pathogens.

title: I Just Can’t Get Enough (of Experts): The Numbers of COVID-19 and the Need for a European Approach to Testing
abstract: This article offers a reflection on the testing strategies deployed in the generation of epidemiological data in the European Union (EU). I will argue that, while in the early days of the pandemic, Member States proceeded to testing in a rather scattered way, the shortage of resources seems to have acted as a driver of coordination, which is now increasingly being discussed at EU level. I will examine the legal and institutional framework supporting such embryonic coordination efforts and offer a preliminary assessment of their implications for a European approach to epidemiological knowledge-making.

title: Epidemiologic features of Kawasaki disease in acute stages in Taiwan, 1997–2010: Effect of different case definitions in claims data analysis
abstract: Kawasaki disease is the leading cause of pediatric acquired cardiac disease in many industrialized countries. The aim of this study was to estimate the incidence of Kawasaki disease in acute stages in Taiwan, by linking the diagnosis code to medication and comparing the differences in epidemiological features with those of previous reports that used the diagnosis code alone.  We searched the National Health Insurance Research Database from 1997 to 2010. For the International Classification of Diseases, Ninth Revision (ICD-9) set, all inpatients with a main diagnosis of Kawasaki disease (ICD-9, 446.1) were retrieved. For the ICD-9 + intravenous immunoglobulin (IVIG) set, Kawasaki disease in acute stages was defined as the disease stages requiring IVIG. The epidemiologic features were calculated and compared by both methods.  The incidence rates for children under 5 years ranged from 21.5 to 68.5 per 100,000 person-years (average 49.1) for the ICD-9 + IVIG set and from 48.5 to 82.8 per 100,000 person-years (average 74.9) for the ICD-9 set. Significant discrepancy in peak season estimation occurred in summer. The 5-year recurrence rate was 1.1% for the ICD-9 + IVIG set and 4.5% for the ICD-9 set. The coronary complication rates were around 7.24% (ICD-9 + IVIG) and 6.48% (ICD-9).  Discrepancies occurred when different case definitions were used in claims data analysis. Previous reports might have overestimated the incidence, recurrence rate, and complication rate in older children. The new method might slightly underestimate them. The true incidence might lie in between.

title: COVID-19, Australia: Epidemiology Report 6 (Reporting week ending 19:00 AEDT 7 March 2020).
abstract: This is the sixth epidemiological report for coronavirus disease 2019 (COVID-19), reported in Australia as at 19:00 Australian Eastern Daylight Time [AEDT] 7 March 2020. It includes data on COVID-19 cases diagnosed in Australia, the international situation and a review of current evidence.

title: Psychological responses, behavioral changes and public perceptions during the early phase of the COVID-19 outbreak in China: a population based cross-sectional survey
abstract: To investigate psychological and behavioral responses to the threat of SARS-CoV-2 infections and their associations with public perceptions in China Design: Cross sectional population-based telephone survey via random digital dialing between 1 and 10 February, 2020  Wuhan (the epicentre and quarantined city), and Shanghai (a typical major city with close transportation link with Wuhan) Participants: Random sample of 510 residents in Wuhan and 501 residents in Shanghai aged above 18  Anxiety (measured by the 7-item generalized anxiety disorder [GAD-7] scale), recommended and avoidance behaviors (engaged in all six behaviors such as increasing surface cleaning and reducing going out).  The prevalence rates of moderate or severe anxiety (score ≥10 on GAD-7) were 32.7% (n=167) among Wuhan participants and 20.4% (n=102) among Shanghai participants. 78.6% (n=401) of Wuhan participants and 63.9% (n=320) of Shanghai participants had carried out all six precautionary behaviors. For both measures, Wuhan participants were more responsive to the outbreak (p<0.001). Controlling for personal characteristics, logistic regression results suggested that risks of moderate or severe anxiety were positively associated with perceived susceptibility (odds ratio 1.6, 95% confidence interval 1.3-1.8) and severity of the disease (1.6, 1.4-1.9) and confusion about information reliability (1.6, 1.5-1.9). Having confidence in taking measures to protect oneself against the disease was associated with a lower risk (0.6, 0.5-0.7). The strongest predictor of behavioral change was perceived severity (1.2, 1.1-1.4), followed by confusion about information reliability (1.1, 1.0-1.3).  Psychological and behavioral responses to COVID-19 have been dramatic during the rising phase of the outbreak. Our results support efforts for timely dissemination of accurate and reliable information to address the high anxiety level.

title: H7N9 influenza-the laboratory presentations: A letter to editor

title: The incidence of pneumonia in rural Thailand
abstract: Pneumonia continues to be a leading infectious disease killer, yet accurately measuring incidence remains a challenge. In 2002, Thailand began active, population-based surveillance for radiographically confirmed pneumonia in Sa Kaeo Province.  Full-time surveillance officers conducted active case ascertainment at every hospital, and routine audits and a community cluster survey promoted complete and accurate reporting. A case of pneumonia was defined as acute infection with signs or symptoms of lower respiratory tract infection and evidence of new infiltrates. An independent panel of radiologists reviewed digital images of all radiographs.  Between September 2002 and August 2003, 777 patients met the case definition. The measured minimum incidence was 177/100000 but the estimated incidence was as high as 580/100000 with full adjustment for incomplete chest radiography and access to health care. Seventy-two (9%) patients died and 28% were known to be HIV positive. Fifteen (2%) patients had pneumonia twice during the year. The average cost of hospitalization for an episode of pneumonia ranged from US$490.80 to $628.60.  Pneumonia is a significant and costly public health problem in Thailand. This surveillance system allows precise assessment and monitoring of radiologically confirmed pneumonia and lays the groundwork for the introduction of new vaccines against pneumonia pathogens.

title: To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic
abstract: Face mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial, though increasingly recommended, and the potential of this intervention is not well understood. We develop a compartmental model for assessing the community-wide impact of mask use by the general, asymptomatic public, a portion of which may be asymptomatically infectious. Model simulations, using data relevant to COVID-19 dynamics in the US states of New York and Washington, suggest that broad adoption of even relatively ineffective face masks may meaningfully reduce community transmission of COVID-19 and decrease peak hospitalizations and deaths. Moreover, mask use decreases the effective transmission rate in nearly linear proportion to the product of mask effectiveness (as a fraction of potentially infectious contacts blocked) and coverage rate (as a fraction of the general population), while the impact on epidemiologic outcomes (death, hospitalizations) is highly nonlinear, indicating masks could synergize with other non-pharmaceutical measures. Notably, masks are found to be useful with respect to both preventing illness in healthy persons and preventing asymptomatic transmission. Hypothetical mask adoption scenarios, for Washington and New York state, suggest that immediate near universal (80%) adoption of moderately (50%) effective masks could prevent on the order of 17--45% of projected deaths over two months in New York, while decreasing the peak daily death rate by 34--58%, absent other changes in epidemic dynamics. Even very weak masks (20% effective) can still be useful if the underlying transmission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24--65% (and peak deaths 15--69%), compared to 2--9% mortality reduction in New York (peak death reduction 9--18%). Our results suggest use of face masks by the general public is potentially of high value in curtailing community transmission and the burden of the pandemic. The community-wide benefits are likely to be greatest when face masks are used in conjunction with other non-pharmaceutical practices (such as social-distancing), and when adoption is nearly universal (nation-wide) and compliance is high.

title: SARS‐CoV‐2 viral spike G614 mutation exhibits higher case fatality rate
abstract: The COVID pandemic is caused by infection with the SARS‐CoV‐2 virus. The major mutation detected to date in the SARS‐CoV‐2 viral envelope spike protein, which is responsible for virus attachment to the host and is also the main target for host antibodies, is a mutation of an aspartate (D) at position 614 found frequently in Chinese strains to a glycine (G). We sought to infer health impact of this mutation.  Increased case fatality rate correlated strongly with the proportion of viruses bearing G614 on a country by country basis. The amino acid at position 614 occurs at an internal protein interface of the viral spike, and the presence of G at this position was calculated to destabilize a specific conformation of the viral spike, within which the key host receptor binding site is more accessible.  These results imply that G614 is a more pathogenic strain of SARS‐CoV‐2, which may influence vaccine design. The prevalence of this form of the virus should also be included in epidemiologic models predicting the COVID‐19 health burden and fatality over time in specific regions. Physicians should be aware of this characteristic of the virus to anticipate the clinical course of infection.

title: On Identifying and Mitigating Bias in the Estimation of the COVID-19 Case Fatality Rate
abstract: The relative case fatality rates (CFRs) between groups and countries are key measures of relative risk that guide policy decisions regarding scarce medical resource allocation during the ongoing COVID-19 pandemic. In the middle of an active outbreak when surveillance data is the primary source of information, estimating these quantities involves compensating for competing biases in time series of deaths, cases, and recoveries. These include time- and severity- dependent reporting of cases as well as time lags in observed patient outcomes. In the context of COVID-19 CFR estimation, we survey such biases and their potential significance. Further, we analyze theoretically the effect of certain biases, like preferential reporting of fatal cases, on naive estimators of CFR. We provide a partially corrected estimator of these naive estimates that accounts for time lag and imperfect reporting of deaths and recoveries. We show that collection of randomized data by testing the contacts of infectious individuals regardless of the presence of symptoms would mitigate bias by limiting the covariance between diagnosis and death. Our analysis is supplemented by theoretical and numerical results and a simple and fast open-source codebase at https://github.com/aangelopoulos/cfr-covid-19 .

title: How much is coronavirus spreading under the radar?

title: Reporting errors in infectious disease outbreaks, with an application to Pandemic Influenza A/H1N1
abstract: Effectively responding to infectious disease outbreaks requires a well-informed response. Quantitative methods for analyzing outbreak data and estimating key parameters to characterize the spread of the outbreak, including the reproductive number and the serial interval, often assume that the data collected is complete. In reality reporting delays, undetected cases or lack of sensitive and specific tests to diagnose disease lead to reporting errors in the case counts. Here we provide insight on the impact that such reporting errors might have on the estimation of these key parameters.  We show that when the proportion of cases reported is changing through the study period, the estimates of key epidemiological parameters are biased. Using data from the Influenza A/H1N1 outbreak in La Gloria, Mexico, we provide estimates of these parameters, accounting for possible reporting errors, and show that they can be biased by as much as 33%, if reporting issues are not accounted for.  Failure to account for missing data can lead to misleading and inaccurate estimates of epidemic parameters.

title: The confounded crude case-fatality rates for COVID-19 hide more than they reveal - a comparison of age-specific and age-adjusted rates between six countries
abstract: The reported crude case-fatality rates (CFRs) vary widely between countries. The serious limitations of using crude rates for comparisons are sometimes overlooked. In this paper we examined to what extent the age distribution of the cases is responsible for the differences in CFRs between countries.  Data on COVID-19 were extracted from the reports of individual countries. Overall and age-specific CFRs were available for six countries. The CFRs by country were adjusted for age using the direct method, using the combined age-specific number of cases of all six countries as the standard population.  The age distribution of the cases varied widely between countries. The crude CFRs varied between 1.6% and 11%. The differences in the age-specific CFRs were much smaller and the age-adjusted rates were much closer than the crude rates. The ratio of the crude CFR for the country with the highest to that with the lowest, was reduced substantially from 7.4 to 2.3 for the age-adjusted rates.  The age structure of the cases dramatically impacts on the differences in the crude CFRs between countries. Adjusting for age substantially reduces this variation. Other factors such as the differences in the definition of the denominators, the definition of a case and the standard of healthcare are likely to account for much of the residual variation. It is misleading to compare the crude COVID-19 CFRs between countries and should be avoided. Comparisons should be based on age-specific and age-adjusted rates.  COVID-19, case-fatality rates, age-specific rates, age-adjusted rates, confounding

title: Group Testing for Sars-Cov-2 to Enable Rapid Scale-Up of Testing and Real-Time Surveillance of Incidence
abstract: High-throughput molecular testing for SARS-CoV-2 may be enabled by group testing in which pools of specimens are screened, and individual specimens tested only after a pool tests positive. Several labs have recently published examples of pooling strategies applied to SARS-CoV-2 specimens, but overall guidance on efficient pooling strategies is lacking. Therefore we developed a model of the efficiency and accuracy of specimen pooling algorithms based on available data on SAR-CoV-2 viral dynamics. For a fixed number of tests, we estimate that programs using group testing could screen 2 to 20 times as many specimens compared to individual testing; increase the total number of true positive infections identified; and improve the positive predictive value of results. We compare outcomes that may be expected in different testing situations and provide general recommendations for group testing implementation. A free, publicly-available web calculator is provided to help inform laboratory decisions on SARS-CoV-2 pooling algorithms.

title: Worldwide and Regional Forecasting of Coronavirus (Covid-19) Spread using a Deep Learning Model
abstract: In December 2019, Covid-19 epidemic was identified in Wuhan, China. Covid-19 may cause fatality especially among elderly, and people with chronic health problems. After human to human transmissions of the disease, it has rapidly spread throughout China, and then the outbreak has reached to neighboring countries in Asia. Now, the spread of the virus is accelerating in the world, and increasing number of new cases has been reported daily in Europe, Middle East, Africa and America regions. Recently, World Health Organization (WHO) also announced Covid-19 as a Pandemic. As of 3 April, worldwide around more than 1 million cases and around 60,000 fatalities are reported. Thus, forecasting regional and worldwide outbreak size of Covid-19 is important in order to take necessary actions regarding to preparedness plans and mitigation interventions. In this work, we design a deep learning model, which is an effective artificial intelligence method, to provide regional and worldwide forecasts. Particularly for worldwide, our approach predicts the cumulative number of cases, cumulative number of deaths and daily new cases. For Europe and Middle East regions, we predict the cumulative number of cases, and for Mainland China we predict daily new cases and the cumulative number of deaths. We predict the next 10 days based on the previously reported actual time series data of Covid-19. For worldwide forecasts, we use the data provided by Worldometers. For Europe and Middle East forecasts, we use the data provided by World Health Organization, and for China Mainland forecasts, the data is obtained from Chinese Centre for Disease Control and Prevention. This is the first time that a deep learning model has been employed for Covid-19 spread prediction, solely based on the known reported cases of Covid-19. The proposed deep learning architecture consists of Long Short Term Memory (LSTM) layer, dropout layer, and fully connected layers to predict regional and worldwide forecasts. We evaluate our approach with Root Mean Square Error (RMSE) metric. For forecasting, we use the network models that give the minimum RMSE on the last 3 days of actual data. Networks, which achieves the minimum RMSE on the last 3 days, are used to predict the next 10 days. Every day, the spread and situations are changing. Our approach can take into account these real-time changes; the deep learning model can be re-trained with new daily data and perform real-time forecasting. Results show that the proposed deep learning model is promising, it can predict possible scenarios regionally and globally for the spread of Covid-19.

title: Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters
abstract: To evaluate the relative risk of COVID-19 death in people <65 years old versus older individuals in the general population, to provide estimates of absolute risk of COVID-19 death at the population level, and to understand what proportion of COVID-19 deaths occur in non-elderly people without underlying diseases in epicenters of the pandemic.  Countries and US states or major cities with at least 250 COVID-19 deaths as of 4/4/2020 and with information available on death counts according to age strata, allowing to calculate the number of deaths in people with age <65. Data were available for Belgium, Germany, Italy, Netherlands, Portugal, Spain, Sweden, and Switzerland, as well as Louisiana, Michigan, Washington states and New York City as of April 4, 2020.  Proportion of COVID-19 deaths that occur in people <65 years old; relative risk of COVID-19 death in people <65 versus ≥65 years old; absolute risk of death in people <65 and in those ≥80 years old in the general population as of 4/4/2020; absolute death risk expressed as equivalent of death risk from driving a motor vehicle.  Individuals with age <65 account for 5%-9% of all COVID-19 deaths in the 8 European epicenters, and approach 30% in three US hotbed locations. People <65 years old had 34- to 73-fold lower risk than those ≥65 years old in the European countries and 13- to 15-fold lower risk in New York City, Louisiana and Michigan. The absolute risk of COVID-19 death ranged from 1.7 per million for people <65 years old in Germany to 79 per million in New York City. The absolute risk of COVID-19 death for people ≥80 years old ranged from approximately 1 in 6,000 in Germany to 1 in 420 in Spain. The COVID-19 death risk in people <65 years old during the period of fatalities from the epidemic was equivalent to the death risk from driving between 9 miles per day (Germany) and 415 miles per day (New York City). People <65 years old and not having any underlying predisposing conditions accounted for only 0.3%, 0.7%, and 1.8% of all COVID-19 deaths in Netherlands, Italy, and New York City.  People <65 years old have very small risks of COVID-19 death even in the hotbeds of the pandemic and deaths for people <65 years without underlying predisposing conditions are remarkably uncommon. Strategies focusing specifically on protecting high-risk elderly individuals should be considered in managing the pandemic.

title: How many lives can be saved? A global view on the impact of testing, herd immunity and demographics on COVID-19 fatality rates
abstract: In this work, we assess the global impact of COVID-19 showing how demographic factors, testing policies and herd immunity are key for saving lives. We extend a standard epidemiological SEIR model in order to: (a) identify the role of demographics (population size and population age distribution) on COVID-19 fatality rates; (b) quantify the maximum number of lives that can be saved according to different testing strategies, different levels of herd immunity, and specific population characteristics; and (d) infer from the observed case fatality rates (CFR) what the true fatality rate might be. Different from previous SEIR model extensions, we implement a Bayesian Melding method in our calibration strategy which enables us to account for data limitation on the total number of deaths. We derive a distribution of the set of parameters that best replicate the observed evolution of deaths by using information from both the model and the data.

title: COVID-19, MERS and SARS with Concomitant Liver Injury—Systematic Review of the Existing Literature
abstract: The novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection has been predominantly linked to respiratory distress syndrome, but gastrointestinal symptoms and hepatic injury have also been reported. The mechanism of liver injury is poorly understood and may result as a consequence of viral hepatitis, systemic inflammatory response, gut barrier and microbiome alterations, intensive care treatment or drug toxicity. The incidence of hepatopathy among patients with coronavirus disease 2019 (COVID-19) is unclear, but studies have reported liver injury in patients with SARS and Middle East respiratory syndrome (MERS). We aimed to systematically review data on the prevalence of hepatic impairments and their clinical course in SARS and MERS Coronaviridae infections. A systematic literature search (PubMed/Embase/Cinahl/Web of Science) according to preferred reporting items for systematic review and meta-analysis protocols (PRISMA) was conducted from database inception until 17/03/2020 for studies that evaluated the incidence of hepatic abnormalities in SARS CoV-1, SARS CoV-2 and MERS infected patients with reported liver-related parameters. A total of forty-three studies were included. Liver anomalies were predominantly mild to moderately elevated transaminases, hypoalbuminemia and prolongation of prothrombin time. Histopathology varied between non-specific inflammation, mild steatosis, congestion and massive necrosis. More studies to elucidate the mechanism and importance of liver injury on the clinical course and prognosis in patients with novel SARS-CoV-2 infection are warranted.

title: Comparison of Hospitalized Patients With ARDS Caused by COVID-19 and H1N1
abstract: Since the outbreak of coronavirus disease 2019 (COVID-19) in China in December 2019, considerable attention has been focused on its elucidation. However, it is also important for clinicians and epidemiologists to differentiate COVID-19 from other respiratory infectious diseases such as influenza viruses.  The aim of this study was to explore the different clinical presentations between COVID-19 and influenza A (H1N1) pneumonia in patients with ARDS.  This analysis was a retrospective case-control study. Two independent cohorts of patients with ARDS infected with either COVID-19 (n = 73) or H1N1 (n = 75) were compared. Their clinical manifestations, imaging characteristics, treatments, and prognosis were analyzed and compared.  The median age of patients with COVID-19 was higher than that of patients with H1N1, and there was a higher proportion of male subjects among the COVID-19 cohort (P < .05). Patients with COVID-19 exhibited higher proportions of nonproductive coughs, fatigue, and GI symptoms than those of patients with H1N1 (P < .05). Patients with H1N1 had higher Sequential Organ Failure Assessment (SOFA) scores than patients with COVID-19 (P < .05). The Pao 2/Fio 2 of 198.2 mm Hg in the COVID-19 cohort was significantly higher than the Pao 2/Fio 2 of 107.0 mm Hg in the H1N1 cohort (P < .001). Ground-glass opacities was more common in patients with COVID-19 than in patients with H1N1 (P < .001). There was a greater variety of antiviral therapies administered to COVID-19 patients than to H1N1 patients. The in-hospital mortality of patients with COVID-19 was 28.8%, whereas that of patients with H1N1 was 34.7% (P = .483). SOFA score-adjusted mortality of H1N1 patients was significantly higher than that of COVID-19 patients, with a rate ratio of 2.009 (95% CI, 1.563-2.583; P < .001).  There were many differences in clinical presentations between patients with ARDS infected with either COVID-19 or H1N1. Compared with H1N1 patients, patients with COVID-19-induced ARDS had lower severity of illness scores at presentation and lower SOFA score-adjusted mortality.

title: Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: A modelling analysis based on overseas cases and air travel data
abstract: As of March 1, 2020, Iran had reported 987 novel coronavirus disease (COVID-19) cases, including 54 associated deaths. At least six neighboring countries (Bahrain, Iraq, Kuwait, Oman, Afghanistan, and Pakistan) had reported imported COVID-19 cases from Iran. In this study, air travel data and the numbers of cases from Iran imported into other Middle Eastern countries were used to estimate the number of COVID-19 cases in Iran. It was estimated that the total number of cases in Iran was 16 533 (95% confidence interval: 5925–35 538) by February 25, 2020, before the UAE and other Gulf Cooperation Council countries suspended inbound and outbound flights from Iran.

title: Decrease in Hospital Admissions for Transient Ischemic Attack, Mild, and Moderate Stroke During the COVID-19 Era
abstract: Since the onset of the coronavirus 2019 (COVID-19) pandemic, doctors and public authorities have demonstrated concern about the reduction in quality of care for other health conditions due to social restrictions and lack of resources. Using a population-based stroke registry, we investigated the impact of the onset of the COVID-19 pandemic in stroke admissions in Joinville, Brazil.  Patients admitted after the onset of COVID-19 restrictions in the city (defined as March 17, 2020) were compared with those admitted in 2019. We analyzed differences between stroke incidence, types, severity, reperfusion therapies, and time from stroke onset to admission. Statistical tests were also performed to compare the 30 days before and after COVID-19 to the same period in 2019.  We observed a decrease in total stroke admissions from an average of 12.9/100 000 per month in 2019 to 8.3 after COVID-19 (P=0.0029). When compared with the same period in 2019, there was a 36.4% reduction in stroke admissions. There was no difference in admissions for severe stroke (National Institutes of Health Stroke Scale score >8), intraparenchymal hemorrhage, and subarachnoid hemorrhage.  The onset of COVID-19 was correlated with a reduction in admissions for transient, mild, and moderate strokes. Given the need to prevent the worsening of symptoms and the occurrence of medical complications in these groups, a reorganization of the stroke-care networks is necessary to reduce collateral damage caused by COVID-19.

title: A Comprehensive Public Health Evaluation of Lockdown as a Non-pharmaceutical Intervention on COVID-19 Spread in India: National Trends Masking State Level Variations
abstract: India has been under four phases of a national lockdown from March 25 to May 31 in response to the COVID-19 pandemic. Unmasking the state-wise variation in the effect of the nationwide lockdown on the progression of the pandemic could inform dynamic policy interventions towards containment and mitigation.  Using data on confirmed COVID-19 cases across 20 states that accounted for more than 99% of the cumulative case counts in India till May 31, 2020, we illustrate the masking of state-level trends and highlight the variations across states by presenting evaluative evidence on some aspects of the COVID-19 outbreak: case-fatality rates, doubling times of cases, effective reproduction numbers, and the scale of testing.  The estimated effective reproduction number R for India was 3.36 (95% confidence interval (CI): [3.03, 3.71]) on March 24, whereas the average of estimates from May 25 - May 31 stands at 1.27 (95% CI: [1.26, 1.28]). Similarly, the estimated doubling time across India was at 3.56 days on March 24, and the past 7-day average for the same on May 31 is 14.37 days. The average daily number of tests have increased from 1,717 (March 19–25) to 131,772 (May 25–31) with an estimated testing shortfall of 4.58 million tests nationally by May 31. However, various states exhibit substantial departures from these national patterns.  Patterns of change over lockdown periods indicate the lockdown has been effective in slowing the spread of the virus nationally. The COVID-19 outbreak in India displays large state-level variations and identifying these variations can help in both understanding the dynamics of the pandemic and formulating effective public health interventions. Our framework offers a holistic assessment of the pandemic across Indian states and union territories along with a set of interactive visualization tools that are daily updated at covind19.org.

title: Modeling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories
abstract: Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.

title: Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales.
abstract: The Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as Covid-19-related has increased compared to what would have been expected in the absence of the pandemic. Reasons behind this might include Covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown. I used weekly ONS data on the number of deaths in England and Wales that did not officially involve Covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a difference-in-differences econometric approach to study whether there was a relative increase in deaths not registered as Covid-19-related during the pandemic, compared to a control. Results suggest that there were an additional 968 weekly deaths that officially did not involve Covid-19, compared to what would have otherwise been expected. It is possible that some people are dying from Covid-19 without being diagnosed, and/or that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.

title: "No test is better than a bad test": Impact of diagnostic uncertainty in mass testing on the spread of Covid-19
abstract: The cessation of lock-down measures will require an effective testing strategy. Much focus at the beginning of the UK's Covid-19 epidemic was directed to deficiencies in the national testing capacity. The quantity of tests may seem an important focus, but other characteristics are likely more germane. False positive tests are more probable than positive tests when the overall population has a low prevalence of the disease, even with highly accurate tests.  We modify an SIR model to include quarantines states and test performance using publicly accessible estimates for the current situation. Three scenarios for cessation of lock-down measures are explored: (1) immediate end of lock-down measures, (2) continued lock-down with antibody testing based immunity passports, and (3) incremental relaxation of lock-down measures with active viral testing. Sensitivity, specifcity, prevalence and test capacity are modified for both active viral and antibody testing to determine their population level effect on the continuing epidemic.  Diagnostic uncertainty can have a large effect on the epidemic dynamics of Covid-19 within the UK. The dynamics of the epidemic are more sensitive to test performance and targeting than test capacity. The quantity of tests is not a substitute for an effective strategy. Poorly targeted testing has the propensity to exacerbate the peak in infections.  The assessment that 'no test is better than a bad test' is broadly supported by the present analysis. Antibody testing is unlikely to be a solution to the lock-down, regardless of test quality or capacity. A well designed active viral testing strategy combined with incremental relaxation of the lock-down measures is shown to be a potential strategy to restore some social activity whilst continuing to keep infections low.

title: Identification of spatial variations in COVID-19 epidemiological data using K-Means clustering algorithm: a global perspective
abstract: Discerning spatial variations of COVID-19 through quantitative analysis operating on the geographically designated datasets relating to socio-demographics and epidemiological data facilitate strategy planning in curtailing the transmission of the disease and focus on articulation of necessary interventions in an informed manner.  K-means clustering was employed on the available country-specific COVID-19 epidemiological data and the influential background characteristics. Country-specific case fatality rates and the average number of people tested positive for COVID-19 per every 10,000 population in each country were derived from the WHO COVID-19 situation report 107, and were used for clustering along with the background characteristics of proportion of countrys population aged >65 years and percentage GDP spent as public health expenditure.  The algorithm grouped the 89 countries into cluster 1 and Cluster 2 of sizes 54 and 35, respectively. It is apparent that Americas, European countries, and Australia formed a major part of cluster 2 with high COVID-19 case fatality rate, higher proportion of countrys population tested COVID-19 positive, higher percentage of GDP spent as public health expenditure, and greater percentage of population being more than 65 years of age.  In spite of the positive correlation between high public health expenditure (%GDP) and COVID-19 incidence, case fatality rate, the immediate task ahead of most of the low and middle income countries is to strengthen their public health systems realizing that the correlation found in this study could be spurious in light of the underreported number of cases and poor death registration.

title: Impact of the COVID-19 pandemic on cancer treatment: the patients’ perspective
abstract: The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has inevitable consequences for medical care of non-COVID-19 patients. To assess the impact of this pandemic on oncological care, a nationwide survey was conducted among cancer patients in the Netherlands.  The patients’ perspective on oncological care was investigated using an online survey between March 29(th) 2020 and April 18(th) 2020. The survey consisted of 20 questions on four topics: patients’ characteristics, contact with the hospital, consequences of the COVID-19 pandemic, and concerns about COVID-19.  5302 cancer patients completed this nationwide survey. Overall, 30% of patients reported consequences for their oncological treatment or follow-up. In the majority of cases this resulted in conversion from hospital visit to consultation by phone or video. The most frequently adjusted treatments were chemotherapy (30%) and immunotherapy (32%). Among patients with delay and discontinuation of treatment, respectively 55% and 63% of patients were (very) concerned about these consequences of the COVID-19 pandemic. Consequences were independent of regional differences in COVID-19 incidence. However, patients in regions with high COVID-19 incidence were significantly more concerned.  This is the first study investigating perspectives of cancer patients during the COVID-19 pandemic. The study demonstrates the significant impact of the COVID-19 crisis on oncological care, indicating the need for psycho-oncological support during this pandemic.

title: Clinical features and the maternal and neonatal outcomes of pregnant women with coronavirus disease 2019
abstract: There is little information about the coronavirus disease 2019 (Covid-19) during pregnancy. This study aimed to determine the clinical features and the maternal and neonatal outcomes of pregnant women with Covid-19.  In this retrospective analysis from five hospitals, we included pregnant women with Covid-19 from January 1 to February 20, 2020. The primary composite endpoints were admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Secondary endpoints included the clinical severity of Covid-19, neonatal mortality, admission to neonatal intensive care unit (NICU), and the incidence of acute respiratory distress syndrome (ARDS) of pregnant women and newborns.  Thirty-three pregnant women with Covid-19 and 28 newborns were identified. One (3%) pregnant woman needed the use of mechanical ventilation. No pregnant women admitted to the ICU. There were no moralities among pregnant women or newborns. The percentages of pregnant women with mild, moderate, and severe symptoms were 13 (39.4%),19(57.6%), and 1(3%). One (3.6%) newborn developed ARDS and was admitted to the NICU. The rate of perinatal transmission of SARS-CoV-2 was 3.6%.  This report suggests that pregnant women are not at increased risk for severe illness or mortality with Covid-19 compared with the general population. The SARS-CoV-2 infection during pregnancy might not be associated with as adverse obstetrical and neonatal outcomes that are seen with the severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) infection during pregnancy. (Funded by the National Key Research and Development Program.

title: Searching for MERS and Novel Flu with Limited Resources

title: Covid-19: Deadline for roll out of UK's tracing app will be missed.

title: COVID-19 in a pediatric heart transplant recipient: Emergence of Donor Specific Antibodies

title: Bacterial resistance: A sensitive issue Complexity of the challenge and containment strategy in Europe
abstract: The development of antimicrobial agents has been a key achievement of modern medicine. However, their overuse has led to an increasing incidence of infections due to antibiotic-resistant microorganisms. Quantitative figures on the current economic and health impact of antimicrobial resistance are scant, but it is clearly a growing challenge that requires timely action. That action should be at the educational, ethical, economic and political level. An important first step would be to increase public awareness and willingness to take the necessary measures to curb resistance. Hence, studies are needed that would provide solid, quantitative data on the societal impact of antibiotic resistance. This review discusses the complexity of resistance, identifies its main drivers and proposes measures to contain it on a European scale.

title: COVID-19 in Bangladesh: Data deficiency to delayed decision

title: Continued and Serious Lockdown Could Minimize Many Newly Transmitted Cases of COVID-19 in the U.S.: Wavelets, Deterministic Models, and Data
abstract: All the newly reported COVID-19 cases of April in the U.S. have not acquired the virus in the same month. We estimate that there was an average of 29,000/day COVID-19 cases in the U.S. transmitted from infected to susceptible during April 1-24, 2020 after adjusting for under-reported and under-diagnosed. We have provided model-based predictions of COVID-19 for the low and high range of transmission rates and with varying degrees of preventive measures including the lockdowns. We predict that even if 10% of the susceptible and 20 % of the infected who were not identified as of April 23, 2020, do not adhere to proper care or do not obey lockdown, then by the end of May and by end of June 50,000 and 55,000 new cases will emerge, respectively. These values for the months of May and June with worse adherence rates of 50% by susceptible and infected (but not identified) will be 251,000 and 511,000, respectively. Continued and serious lockdown measures could bring this average daily new cases to a further low at 4,300/day to 8,000/day in May.

title: Impact of Social Vulnerability on COVID-19 Incidence and Outcomes in the United States
abstract: Prior pandemics have disparately affected socially vulnerable communities. Whether regional variations in social vulnerability to disasters influence COVID-19 outcomes and incidence in the U.S. is unknown.  To examine the association of Social Vulnerability Index (SVI), a percentile-based measure of county-level social vulnerability to disasters, and its sub-components (socioeconomic status, household composition, minority status, and housing type/transportation accessibility) with the case fatality rate (CFR) and incidence of COVID-19.  Ecological study of counties with at least 50 confirmed COVID-19 cases as of April 4th, 2020. Generalized linear mixed-effects models with state-level clustering were applied to estimate county-level associations of overall SVI and its sub-component scores with COVID-19 CFR (deaths/100 cases) and incidence (cases/1000 population), adjusting for population percentage aged >65 years, and for comorbidities using the average Hierarchical Condition Category (HCC) score. Counties with high SVI (≥median) and high CFR (≥median) were identified.  Population-based study of U.S. county-level data.  U.S. counties with at least 50 confirmed COVID-19 cases. Main outcomes and measures: COVID-19 CFR and incidence.  Data from 433 counties including 283,256 cases and 6,644 deaths were analyzed. Median SVI was 0.46 [Range: 0.01-1.00], and median CFR and incidence were 1.9% [Range: 0-13.3] and 1.2 per 1000 people [Range: 0.6-38.8], respectively. Higher SVI, indicative of greater social vulnerability, was associated with higher CFR (RR: 1.19 [1.05, 1.34], p=0.005, per-1% increase), an association that strengthened after adjustment for age>65 years and comorbidities (RR: 1.63 [1.38, 1.91], p<0.001), and was further confirmed in a sensitivity analysis limited to six states with the highest testing levels. Although the association between overall SVI and COVID-19 incidence was not significant, the SVI sub-components of socioeconomic status and minority status were both predictors of higher incidence and CFR. A combination of high SVI (≥0.46) and high adjusted CFR (≥2.3%) was observed in 28.9% of counties.  Social vulnerability is associated with higher COVID-19 case fatality. High social vulnerability and CFR coexist in more than 1 in 4 U.S. counties. These counties should be targeted by public policy interventions to help alleviate the pandemic burden on the most vulnerable population.

title: Mortality from COVID-19 in 12 countries and 6 states of the United States
abstract: Reliable estimates of COVID-19 mortality are crucial to aid control strategies and to assess the effectiveness of interventions.  Project COVID-19 mortality trends to October 1, 2020, in 12 countries or regions that constitute >90% of the global COVID-19 deaths reported as of April 12, 2020.  The Global COVID-19 Assessment of Mortality (GCAM) is an open, transparent, and continuously updated (www.cghr.org/covid) statistical model that combines actual COVID-19 mortality counts with Bayesian inference to forecast COVID-19 deaths, the date of peak deaths, and the duration of excess mortality. The analyses covered a total of 700 million population above age 20 in 12 countries or regions: USA; Italy; Spain; France; UK; Iran; Belgium; a province of China (Hubei, which accounted for 90% of reported Chinese deaths); Germany; the Netherlands; Switzerland; and Canada; and six US states: New York, New Jersey, Michigan, Louisiana, California, and Washington.  Forecasted deaths across the 12 current high-burden countries sum 167,000 to 593,000 (median 253,000). The trajectory of US deaths (49,000-249,000 deaths; median 86,000)- over half of which are expected in states beyond the initial six states analysed in this study- will have the greatest impact on the eventual total. Mortality ranges are 25,000-109,000 (median 46,000) in the UK; 23,000-31,000 (median 26,000) in Italy; 21,000-37,000 (median 26,000) in France and 21,000-32,000 (median 25,000) in Spain. Estimates are most precise for Hubei, China, where the epidemic curve is complete, and least precise in California, where it is ongoing. New York has the highest cumulative median mortality rate per million (1135), about 12-fold that of Germany. Mortality trajectories are notably flatter in Germany, California, and Washington State, each of which took physical distancing and testing strategies seriously. Using past country-specific mortality as a guide, GCAM predicts surge capacity needs, reaching more than twice existing capacity in a number of places., In every setting, the results might be sensitive to undercounts of COVID-19 deaths, which are already apparent.  Mortality from COVID-19 will be substantial across many settings, even in the best case scenario. GCAM will provide continually updated and increasingly precise estimates as the pandemic progresses.

title: How lethal is the novel coronavirus, and how many undetected cases there are? The importance of being tested.
abstract: There is big concern for estimating the lethality and the extent of undetected infections associated with the novel coronavirus SARS-CoV2 outbreak. While detailed epidemiological models are certainly needed, I suggest here an orthogonal approach based on a minimum number of parameters robustly fitted from the cumulative data easily accessible for all countries at the John Hopkins University database that became the worldwide reference for the pandemics. I show that, after few days from the beginning of the outbreak, the apparent death rate can be extrapolated to infinite time through regularized regression such as rescaled ridge regression. The variation from country to country of these extrapolated death rates appears to depend almost only (r^2=0.91) on the ratio between performed tests and detected cases even when the instantaneous apparent lethality rates are as different as 9% in Italy and 0.4% in Germany. Extrapolating to the limit of infinite number of tests, I obtain a death rate of 0.012+/- 0.012, in agreement with other estimates. The inverse relationship between the extrapolated death rate and the intensity tests allows estimating that more than 50% of cases were undetected in most countries, with more than 90% undetected cases in countries severely hit by the epidemics such as Italy. Finally, I propose to adopt the ratio between the cumulative number of recovered and deceased persons as an indicator that can anticipate the halting of the epidemics.

title: Neonatal Pertussis, an Under-Recognized Health Burden and Rationale for Maternal Immunization: A Systematic Review of South and South-East Asian Countries
abstract: Pertussis is an under-recognized cause of neonatal morbidity and mortality. To review information on the epidemiology and disease burden of neonatal pertussis in South and Southeast Asian countries, a systematic literature review of three bibliographic databases was undertaken. Peer-reviewed original studies on neonatal pertussis epidemiology and burden published since 2000, with a geographical scope limited to South and Southeast Asian countries, were included. Data were systematically extracted based on parameters defined a priori. Our findings show that the burden of neonatal pertussis and its complications is substantial. An increase in the number of pertussis cases has been noted since early 2000, ranging from 61 to 92.9% in infants 0–3 months old. The most common symptoms an infant is likely to present with are cough with or without paroxysms, cyanosis, apnea, tachypnea, difficulty in breathing and leukocytosis. In addition, it can lead to hospitalization (length of stay: 5–7 days), complications (e.g., pneumonia, seizures) and mortality ranging from 5.6 to 14.7%. Other observations indicate that diagnosis is challenging because of non-specific clinical symptoms. Specifically, for obstetricians and gynecologists, the information available for making informed decisions on the prevention of neonatal pertussis is unreliable. Maternal immunization against pertussis during late stages of pregnancy has proven to be efficacious and well tolerated. A high burden of neonatal pertussis, as well as its complications, is observed in South and Southeast Asian countries. There is a need to intensify efforts to protect this vulnerable population with maternal vaccination.

title: County-level factors influence the trajectory of Covid-19 incidence
abstract: With new cases of Covid-19 surging in the United States, we need to better understand how the spread of novel coronavirus varies across all segments of the population. We use hierarchical exponential growth curve modeling techniques to examine whether community social and economic characteristics uniquely influence the incidence of Covid-19 cases in the urban built environment. We show that, as of May 3, 2020, confirmed coronavirus infections are concentrated along demographic and socioeconomic lines in New York City and surrounding areas, the epicenter of the Covid-19 pandemic in the United States. Furthermore, we see evidence that, after the onset of the pandemic, timely enactment of physical distancing measures such as school closures is imperative in order to limit the extent of the coronavirus spread in the population. Public health authorities must impose nonpharmaceutical measures early on in the pandemic and consider community-level factors that associate with a greater risk of viral transmission.

title: Analysis of the sex ratio of reported gonorrhoea incidence in Shenzhen, China
abstract: To assess the clinical process of gonorrhoea diagnosis and report in China, and to determine the difference of sex ratio between reported incidence based on reporting data and true diagnosis rate based on reference tests of gonorrhoea.  A total of 26 dermatology and sexually transmitted disease (STD) departments, 34 obstetrics-gynaecology clinics and 28 urology outpatient clinics selected from 34 hospitals of Shenzhen regarded as our study sites.  A total of 2754 participants were recruited in this study, and 2534 participants completed the questionnaire survey and provided genital tract secretion specimens. There were 1106 male and 1428 female participants. Eligible participants were patients who presented for outpatient STD care at the selected clinics for the first time in October 2012 were at least 18 years old, and were able to give informed consent.  Untested rate, true-positive rate, false-negative rate and unreported rate of gonorrhoea, as well as reported gonorrhoea incidence sex ratio and true diagnosis sex ratio were calculated and used to describe the results.  2534 participants were enrolled in the study. The untested rate of gonorrhoea among females was significantly higher than that among males (female 88.1%, male 68.3%, p=0.001). The male-to-female sex ratios of untested rate, true-positive rate, false-negative rate and unreported rate were 1:1.3, 1.2:1, 1:1.6 and 1:1.4, respectively. The reported gonorrhoea incidence sex ratio of new diagnosed gonorrhoea was 19.8:1 (male vs female: 87/1106 vs 5/1420), while the true diagnosis sex ratio was 2.5:1 (male vs female: 161/1106 vs 84/1420). These data indicate that the sex ratio of reported gonorrhoea incidence has been overestimated by a factor of 7.9 (19.8/2.5).  We found the current reported gonorrhoea incidence and sex ratios to be inaccurate due to underestimations of gonorrhoea incidence, especially among women.

title: Potential interventions for novel coronavirus in China: A systematic review
abstract: An outbreak of a novel coronavirus (COVID‐19 or 2019‐CoV) infection has posed significant threats to international health and the economy. In the absence of treatment for this virus, there is an urgent need to find alternative methods to control the spread of disease. Here, we have conducted an online search for all treatment options related to coronavirus infections as well as some RNA‐virus infection and we have found that general treatments, coronavirus‐specific treatments, and antiviral treatments should be useful in fighting COVID‐19. We suggest that the nutritional status of each infected patient should be evaluated before the administration of general treatments and the current children's RNA‐virus vaccines including influenza vaccine should be immunized for uninfected people and health care workers. In addition, convalescent plasma should be given to COVID‐19 patients if it is available. In conclusion, we suggest that all the potential interventions be implemented to control the emerging COVID‐19 if the infection is uncontrollable.

title: Number of International Arrivals Predicts Severity of the first Global Wave of the COVID-19 Pandemic
abstract: Reported death rates from different countries during the COVID-19 pandemic vary. Lack of universal testing and death underreporting make between-country comparisons difficult. The country-level determinants of COVID-19 mortality are unknown.  Derive a measure of COVID-related death rates that is comparable across countries and identify its country-level predictors.  An ecological study design of publicly available data was employed. Countries reporting >25 COVID-related deaths until May 1, 2020 were included. The outcome was the mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential predictors assessed were most recently published Demographic parameters (population and population density, percentage population living in urban areas, median age, average body mass index, smoking prevalence), Economic parameters (Gross Domestic Product per capita; environmental parameters: pollution levels, mean temperature (January-April)), co-morbidities (prevalence of diabetes, hypertension and cancer), health systems parameters (WHO Health Index and hospital beds per 10,000 population and international arrivals). Multivariable linear regression was used to analyse the data.  Thirty-one countries were included. Of all country-level predictors included in the multivariable model, only total number of international arrivals was significantly associated with the mean death rate: Beta 0.3798 (95% Confidence Interval 0.2414, 0.5182), P <0.001.  International travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Stopping international travel, particularly from affected areas, may be the most effective strategy to control COVID outbreak and prevent related deaths.

title: Insights from early mathematical models of 2019-nCoV acute respiratory disease (COVID-19) dynamics
abstract: In December 2019, a novel coronavirus (SARS-CoV-2) has been identified to cause acute respiratory disease in humans. An outbreak of this disease has been reported in mainland China with the city of Wuhan as the recognized epicenter. The disease has also been exported to other countries, including the Philippines, but the level of spread is still under control (as of 08 February 2020). To describe and predict the dynamics of the disease, several preliminary mathematical models are formulated by various international study groups. Here, the insights that can be drawn from these models are discussed, especially as inputs for designing strategies to control the epidemics. Proposed model-based strategies on how to prevent the spread of the disease in local setting, such as during large social gatherings, are also presented. The model shows that the exposure time is a significant factor in spreading the disease. With a basic reproduction number equal to 2, and 14-day infectious period, an infected person staying more than 9 hours in the event could infect other people. Assuming the exposure time is 18 hours, the model recommends that attendees of the social gathering should have a protection with more than 70 percent effectiveness.

title: Estimating number of global importations of COVID-19 from Wuhan, risk of transmission outside mainland China and COVID-19 introduction index between countries outside mainland China
abstract: The emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China in early December 2019 has caused widespread transmission within the country, with over 1,000 deaths reported to date. Other countries have since reported coronavirus disease 2019 (COVID-19) importation from China, with some experiencing local transmission and even case importation from countries outside China. We aim to estimate the number of cases imported from Wuhan to each country or territory outside mainland China, and with these estimates assess the risk of onward local transmission and the relative potential of case importation between countries outside China.  We used the reported number of cases imported from Wuhan and flight data to generate an uncertainty distribution for the estimated number of imported cases from Wuhan to each location outside mainland China. This uncertainty was propagated to quantify the local outbreak risk using a branching process model. A COVID-19 introduction index was derived for each pair of donor and recipient countries, accounting for the local outbreak risk in the donor country and the between-country connectivity.  We identified 13 countries or territories outside mainland China that may have under-detected COVID-19 importation from Wuhan, such as Thailand and Indonesia. In addition, 16 countries had a local outbreak risk estimate exceeding 50%, including four outside Asia. The COVID-19 introduction index highlights potential locations outside mainland China from which cases may be imported to each recipient country.  As SARS-CoV-2 continues to spread globally, more epicentres may emerge outside China. Hence, it is important for countries to remain alert for the possibilities of viral introduction from other countries outside China, even before local transmission in a source country becomes known.

title: Presentation of new onset anosmia during the COVID-19 pandemic.
abstract: Anosmia has not been formally recognised as a symptom of COVID-19 infection. Growing anecdotal evidence suggests increasing incidence of cases of anosmia during the current pandemic, suggesting that COVID-19 may cause olfactory dysfunction. The objective was to characterise patients reporting new onset anosmia during the COVID-19 pandemic METHODOLOGY: Design: Survey of 2428 patients reporting new onset anosmia during the COVID-19 pandemic.  Volunteer sample of patients seeking medical advice of recent onset self-diagnosed loss of sense of smell  2428 surveys were completed within 7 days; 64% respondents were under 40. The majority of respondents reported onset of their anosmia in the last week. Of the cohort, 17% did not report any other symptom thought to be associated with COVID-19. In patients who reported other symptoms, 51% reported either cough or fever and therefore met current guidelines for self-isolation.  Anosmia is reported in conjunction with well-reported symptoms of coronas virus, but 1 in 6 patients with recent onset anosmia report this as an isolated symptom. This might help identify otherwise asymptomatic carriers of disease and trigger targeted testing. Further study with COVID-19 testing is required to identify the proportion of patients in whom new onset anosmia can be attributed to COVID-19.

title: Celiac and non-celiac gluten sensitivity: a review on the association with schizophrenia and mood disorders
abstract: An association between many psychiatric and gluten-related disorders has been known for some time. In the case of schizophrenia and mood disorders, the major psychiatric disorders, there is much evidence, not without contradictions, of a possible association between schizophrenia and celiac disease. The association between mood disorders and gluten-related disorders, especially celiac disease, has only been studied for depression, often coupled with anxiety, and very recently for bipolar disorder. Since non-celiac gluten sensitivity is now known to be different from celiac disease, many studies have shown that gluten sensitivity is also associated with major psychiatric disorders. Here we review the literature on the association between schizophrenia/mood disorders and celiac disease/gluten sensitivity, pointing out the differences between these associations.

title: A Well Infant With Coronavirus Disease 2019 With High Viral Load
abstract: A well 6-month-old infant with coronavirus disease 2019 (COVID-19) had persistently positive nasopharyngeal swabs up to day 16 of admission. This case highlights the difficulties in establishing the true incidence of COVID-19, as asymptomatic individuals can excrete the virus. These patients may play important roles in human-to-human transmission in the community.

title: The true case fatality of COVID19: An analytical solution
abstract: The exact risk of dying from COVID-19 has remained elusive and a topic of debate. The observed case fatality rates of 46 different countries are hypothesized to be dependent on their testing rates. An analytical test to this hypothesis suggests that the case fatality rate of COVID-19 could be consistent to a certain degree across all countries and states. The current global fatality rate is estimated to be around 1% and expected to converge between 1-3% when the pandemic ends. This model can be helpful to estimate the true infection rate for individual countries.

title: BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic
abstract: The coronavirus disease 2019 (COVID-19) has quickly grown from a regional outbreak in Wuhan, China to a global pandemic. Early estimates of the epidemic growth and incubation period of COVID-19 may have been biased due to sample selection. Using detailed case reports from 14 locations in and outside mainland China, we obtained 378 Wuhan-exported cases who left Wuhan before an abrupt travel quarantine. We developed a generative model we call BETS for four key epidemiological events---Beginning of exposure, End of exposure, time of Transmission, and time of Symptom onset (BETS)---and derived explicit formulas to correct for the sample selection. We gave a detailed illustration of why some early and highly influential analyses of the COVID-19 pandemic were severely biased. All our analyses, regardless of which subsample and model were being used, point to an epidemic doubling time of 2 to 2.5 days during the early outbreak in Wuhan. A Bayesian nonparametric analysis further suggests that about 5% of the symptomatic cases may not develop symptoms within 14 days of infection and that men may be much more likely than women to develop symptoms within 2 days of infection.

title: Glycan-Protein Interactions in Viral Pathogenesis
abstract: The surfaces of host cells and viruses are decorated by complex glycans, which play multifaceted roles in the dynamic interplay between the virus and the host including viral entry into host cell, modulation of proteolytic cleavage of viral proteins, recognition and neutralization of virus by host immune system. These roles are mediated by specific multivalent interactions of glycans with their cognate proteins (generally termed as glycan-binding proteins or GBPs or lectins). The advances in tools and technologies to chemically synthesize and structurally characterize glycans and glycan-GBP interactions have offered several insights into the role of glycan-GBP interactions in viral pathogenesis and have presented opportunities to target these interactions for novel antiviral therapeutic or vaccine strategies. This review covers aspects of role of host cell surface glycan receptors and viral surface glycans in viral pathogenesis and offers perspectives on how to employ various analytical tools to target glycan-GBP interactions.

title: Molecular Diagnosis of Severe Acute Respiratory Syndrome : The State of the Art
abstract: Severe acute respiratory syndrome (SARS) first appeared in Guangdong Province, China, in November 2002. Although virus isolation and serology were useful early in the SARS outbreak for diagnosing new cases, these tests are not generally useful because virus culture requires a BSL-3 laboratory and seroconversion is often delayed until 2 to 3 weeks after infection. The first qualitative reverse transcriptase-polymerase chain reaction tests for SARS-coronavirus (CoV) were sensitive and capable of detecting 1 to 10 genome equivalents. These assays were quickly supplemented with quantitative real-time assays that helped elucidate the natural history of SARS, particularly the initial presence of low viral loads in the upper respiratory tract and high viral loads in the lower respiratory tract. The unique natural history of SARS-CoV infection dictates the testing of both respiratory and nonrespiratory specimens, the testing of multiple specimens from the same patient, and sending out positives to be confirmed by a reference laboratory. Commercially available reverse transcriptase-polymerase chain reaction tests for SARS have recently appeared; however, meaningful evaluations of these assays have not yet been performed and their true performance has not been determined. These and other issues related to diagnosis of SARS-CoV infection are discussed in this review.

title: Emerging Animal Coronaviruses: First SARS and Now MERS
abstract: The first major pandemic of the new millennium that arose from southern China in 2002 was of zoonotic origin from wild game animals, called severe acute respiratory syndrome [SARS]. The culprit was determined to be a coronavirus of animal origin [SARS-CoV]. The discovery of the SARS-CoV, which caused an outbreak of >8000 people in >30 countries with fatality of about 10%, resulted in intense search for novel coronaviruses with potentially high pathogenicity. Ten years later after the SARS pandemic, another novel coronavirus crossed the species barrier from bats to humans through an intermediate camel host, to produce a severe lower respiratory infection labeled the Middle East respiratory syndrome [MERS]. A novel coronavirus [MERS-CoV] was first identified in September 2012, from patients who resided or traveled to Saudi Arabia. The MERS-CoV spread through contacts with camel and subsequently from human to human via droplet transmission. MERS cases occurred in several other countries including in Europe and the United States, mainly from residence or travel to the Arabian Peninsula, but was not of pandemic potential. However, in the spring of 2015, a MERS outbreak started in South Korea which was initiated by a returning traveler from Saudi Arabia, and subsequently secondary infection of over 186 local residents occurred. Recent estimate in May 2015 indicates that the MERS-CoV have afflicted 1167 patients with MERS worldwide with 479 deaths [41% fatality]. Thus MERS is more deadly than SARS but appears to be less contagious. However, unlike SARS which has not reappeared since 2002–2003, MERS-CoV have the potential to cause sporadic or local outbreaks for many years as the virus may now be entrenched endemically in dromedary camels of the Middle East.

title: Laboratory readiness and response for novel coronavirus (2019-nCoV) in expert laboratories in 30 EU/EEA countries, January 2020
abstract: Timely detection of novel coronavirus (2019-nCoV) infection cases is crucial to interrupt the spread of this virus. We assessed the required expertise and capacity for molecular detection of 2019-nCoV in specialised laboratories in 30 European Union/European Economic Area (EU/EEA) countries. Thirty-eight laboratories in 24 EU/EEA countries had diagnostic tests available by 29 January 2020. A coverage of all EU/EEA countries was expected by mid-February. Availability of primers/probes, positive controls and personnel were main implementation barriers.

title: Spreading of COVID-19 in Brazil: Impacts and uncertainties in social distancing strategies
abstract: Brazil's continental dimension poses a challenge to the control of the spread of COVID-19. Due to the country specific scenario of high social and demographic heterogeneity, combined with limited testing capacity, lack of reliable data, under-reporting of cases, and restricted testing policy, the focus of this study is twofold: (i) to develop a generalized SEIRD model that implicitly takes into account the quarantine measures, and (ii) to estimate the response of the COVID-19 spread dynamics to perturbations/uncertainties. By investigating the projections of cumulative numbers of confirmed and death cases, as well as the effective reproduction number, we show that the model parameter related to social distancing measures is one of the most influential along all stages of the disease spread and the most influential after the infection peak. Due to such importance in the outcomes, different relaxation strategies of social distancing measures are investigated in order to determine which strategies are viable and less hazardous to the population. The results highlight the need of keeping social distancing policies to control the disease spread. Specifically, the considered scenario of abrupt social distancing relaxation implemented after the occurrence of the peak of positively diagnosed cases can prolong the epidemic, with a significant increase of the projected numbers of confirmed and death cases. An even worse scenario could occur if the quarantine relaxation policy is implemented before evidence of the epidemiological control, indicating the importance of the proper choice of when to start relaxing social distancing measures.

title: Coronavirus in pregnancy and delivery: rapid review
abstract: There are limited case series reporting the impact on women affected by coronavirus during pregnancy. In women affected by severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), the case fatality rate appears higher in those affected in pregnancy compared with non-pregnant women. We conducted a rapid review to guide health policy and management of women affected by COVID-19 during pregnancy, which was used to develop the Royal College of Obstetricians and Gynaecologists' (RCOG) guidelines on COVID-19 infection in pregnancy.  Searches were conducted in PubMed and MedRxiv to identify primary case reports, case series, observational studies and randomized controlled trials describing women affected by coronavirus in pregnancy. Data were extracted from relevant papers. This review has been used to develop guidelines with representatives of the Royal College of Paediatrics and Child Health (RCPCH) and RCOG who provided expert consensus on areas in which data were lacking.  From 9965 search results in PubMed and 600 in MedRxiv, 21 relevant studies, all of which were case reports or case series, were identified. From reports of 32 women to date affected by COVID-19 in pregnancy, delivering 30 babies (one set of twins, three ongoing pregnancies), seven (22%) were asymptomatic and two (6%) were admitted to the intensive care unit (ICU), one of whom remained on extracorporeal membrane oxygenation. No maternal deaths have been reported to date. Delivery was by Cesarean section in 27 cases and by vaginal delivery in two, and 15 (47%) delivered preterm. There was one stillbirth and one neonatal death. In 25 babies, no cases of vertical transmission were reported; 15 were reported as being tested with reverse transcription polymerase chain reaction after delivery. Case fatality rates for SARS and MERS were 15% and 27%, respectively. SARS was associated with miscarriage or intrauterine death in five cases, and fetal growth restriction was noted in two ongoing pregnancies affected by SARS in the third trimester.  Serious morbidity occurred in 2/32 women with COVID-19, both of whom required ICU care. Compared with SARS and MERS, COVID-19 appears less lethal, acknowledging the limited number of cases reported to date and that one woman remains in a critical condition. Preterm delivery affected 47% of women hospitalized with COVID-19, which may put considerable pressure on neonatal services if the UK's reasonable worst-case scenario of 80% of the population being affected is realized. Based on this review, RCOG, in consultation with RCPCH, developed guidance for delivery and neonatal care in pregnancies affected by COVID-19, which recommends that delivery mode be determined primarily by obstetric indication and recommends against routine separation of affected mothers and their babies. We hope that this review will be helpful for maternity and neonatal services planning their response to COVID-19.  Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

title: Epidemiological and clinical characteristics of the early phase of the COVID-19 epidemic in Brazil
abstract: The first case of COVID-19 was detected in Brazil on February 25, 2020. We report the epidemiological, demographic, and clinical findings for confirmed COVID-19 cases during the first month of the epidemic in Brazil.  Individual-level and aggregated COVID-19 data were analysed to investigate demographic profiles, socioeconomic drivers and age-sex structure of COVID-19 tested cases. Basic reproduction numbers (R0) were investigated for Sao Paulo and Rio de Janeiro. Multivariate logistic regression analyses were used to identify symptoms associated with confirmed cases and risk factors associated with hospitalization. Laboratory diagnosis for eight respiratory viruses were obtained for 2,429 cases.  By March 25, 1,468 confirmed cases were notified in Brazil, of whom 10% (147 of 1,468) were hospitalised. Of the cases acquired locally (77.8%), two thirds (66.9% of 5,746) were confirmed in private laboratories. Overall, positive association between higher per capita income and COVID-19 diagnosis was identified. The median age of detected cases was 39 years (IQR 30-53). The median R0 was 2.9 for Sao Paulo and Rio de Janeiro. Cardiovascular disease/hypertension were associated with hospitalization. Co-circulation of six respiratory viruses, including influenza A and B and human rhinovirus was detected in low levels.  Socioeconomic disparity determines access to SARS-CoV-2 testing in Brazil. The lower median age of infection and hospitalization compared to other countries is expected due to a younger population structure. Enhanced surveillance of respiratory pathogens across socioeconomic statuses is essential to better understand and halt SARS-CoV-2 transmission.

title: Epidemiological characteristics of novel coronavirus infection: A statistical analysis of publicly available case data
abstract: Following the first report of coronavirus disease 2019 (COVID-19) in Sapporo City, Hokkaido Prefecture, Japan on 14 February 2020, a surge of cases was observed in Hokkaido during February and March. As of 6 March, 90 cases were diagnosed in Hokkaido. Unfortunately, many infected persons may not have been recognized as cases due to having mild or no symptoms. We therefore estimated the actual number of COVID-19 cases in (i) Hokkaido Prefecture and (ii) Sapporo City using data on cases diagnosed outside these areas. The estimated cumulative incidence in Hokkaido as of 27 February was 2297 cases (95% confidence interval [CI]: 382, 7091) based on data on travelers outbound from Hokkaido. The cumulative incidence in Sapporo City as of 28 February was estimated at 2233 cases (95% CI: 0, 4893) based on the count of confirmed cases within Hokkaido. Both approaches resulted in similar estimates, indicating higher incidence of infections in Hokkaido than were detected by the surveillance system. This quantification of the gap between detected and estimated cases can help inform public health response as it provides insight into the possible scope of undetected transmission.

title: Mapping inhibitor binding modes on an active cysteine protease via nuclear magnetic resonance spectroscopy.
abstract: Cruzain is a member of the papain/cathepsin L family of cysteine proteases, and the major cysteine protease of the protozoan Trypanosoma cruzi, the causative agent of Chagas disease. We report an autoinduction methodology that provides soluble cruzain in high yields (>30 mg/L in minimal medium). These increased yields provide sufficient quantities of active enzyme for use in nuclear magnetic resonance (NMR)-based ligand mapping. Using circular dichroism and NMR spectroscopy, we also examined the solution-state structural dynamics of the enzyme in complex with a covalently bound vinyl sulfone inhibitor (K777). We report the backbone amide and side chain carbon chemical shift assignments of cruzain in complex with K777. These resonance assignments were used to identify and map residues located in the substrate binding pocket, including the catalytic Cys25 and His162. Selective [(15)N]Cys, [(15)N]His, and [(13)C]Met labeling was performed to quickly assess cruzain-ligand interactions for a set of eight low-molecular weight compounds exhibiting micromolar binding or inhibition. Chemical shift perturbation mapping verified that six of the eight compounds bind to cruzain at the active site. Three different binding modes were delineated for the compounds, namely, covalent, noncovalent, and noninteracting. These results provide examples of how NMR spectroscopy can be used to screen compounds for fast evaluation of enzyme-inhibitor interactions to facilitate lead compound identification and subsequent structural studies.

title: An urgent call to address the nutritional status of women and children in Nepal during COVID-19 crises
abstract: Due to the ongoing nationwide lockdown in Nepal, women and children face a greater risk of malnutrition and eventually leading to mortality and morbidity. To harness the progress made so far in improving the nutritional status of women and children, a focus on nutrition should be a part of the COVID-19 response plan.

title: Characterization of the COVID-19 pandemic and the impact of uncertainties, mitigation strategies, and underreporting of cases in South Korea, Italy, and Brazil
abstract: By April 7th, 2020, the Coronavirus disease 2019 (COVID-19) has infected one and a half million people worldwide, accounting for over 80 thousand of deaths in 209 countries and territories around the world. The new and fast dynamics of the pandemic are challenging the health systems of different countries. In the absence of vaccines or effective treatments, mitigation policies, such as social isolation and lock-down of cities, have been adopted, but the results vary among different countries. Some countries were able to control the disease at the moment, as is the case of South Korea. Others, like Italy, are now experiencing the peak of the pandemic. Finally, countries with emerging economies and social issues, like Brazil, are in the initial phase of the pandemic. In this work, we use mathematical models with time-dependent coefficients, techniques of inverse and forward uncertainty quantification, and sensitivity analysis to characterize essential aspects of the COVID-19 in the three countries mentioned above. The model parameters estimated for South Korea revealed effective social distancing and isolation policies, border control, and a high number in the percentage of reported cases. In contrast, underreporting of cases was estimated to be very high in Brazil and Italy. In addition, the model estimated a poor isolation policy at the moment in Brazil, with a reduction of contact around 40%, whereas Italy and South Korea estimated numbers for contact reduction are at 75% and 90%, respectively. This characterization of the COVID-19, in these different countries under different scenarios and phases of the pandemic, supports the importance of mitigation policies, such as social distancing. In addition, it raises serious concerns for socially and economically fragile countries, where underreporting poses additional challenges to the management of the COVID-19 pandemic by significantly increasing the uncertainties regarding its dynamics.

title: Modelling fatality curves of COVID-19 and the effectiveness of intervention strategies
abstract: The main objective of the present paper is twofold: first, to model the fatality curves of the COVID-19 disease, as represented by the cumulative number of deaths as a function of time; and second, to use the corresponding mathematical model to study the effectiveness of possible intervention strategies. We applied the Richards growth model (RGM) to the COVID-19 fatality curves from several countries, where we used the data from the Johns Hopkins University database up to April 1, 2020. Countries selected for analysis were China, Italy, Spain, Iran, and Brazil. The RGM was shown to describe very well the fatality curves of China, which is in a late stage of the COVID-19 outbreak, as well as of Italy, Spain, and Iran, which supposedly are in the middle of the outbreak at the time of this writing. As for Brazil, which is still in the so-called exponential growth regime, we used the generalized growth model which is more appropriate for such cases. An analytic formula for the efficiency of intervention strategies within the context of the RGM is derived. Our findings show that there is only a narrow window of opportunity, after the onset of the epidemic, during which effective countermeasures can be taken. We applied our intervention model to the COVID-19 fatality curve of Italy to illustrate the effect of several possible interventions.

title: The Second Worldwide Wave of Interest in Coronavirus since the COVID-19 Outbreaks in South Korea, Italy and Iran: A Google Trends Study
abstract: The recent emergence of a new coronavirus, COVID-19, has gained extensive coverage in public media and global news. As of 24 March 2020, the virus has caused viral pneumonia in tens of thousands of people in Wuhan, China, and thousands of cases in 184 other countries and territories. This study explores the potential use of Google Trends (GT) to monitor worldwide interest in this COVID-19 epidemic. GT was chosen as a source of reverse engineering data, given the interest in the topic. Current data on COVID-19 is retrieved from (GT) using one main search topic: Coronavirus. Geographical settings for GT are worldwide, China, South Korea, Italy and Iran. The reported period is 15 January 2020 to 24 March 2020. The results show that the highest worldwide peak in the first wave of demand for information was on 31 January 2020. After the first peak, the number of new cases reported daily rose for 6 days. A second wave started on 21 February 2020 after the outbreaks were reported in Italy, with the highest peak on 16 March 2020. The second wave is six times as big as the first wave. The number of new cases reported daily is rising day by day. This short communication gives a brief introduction to how the demand for information on coronavirus epidemic is reported through GT.

title: The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran
abstract: To estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud, Northeast of Iran.  The R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The serial interval was fit with a gamma distribution. The probable incidence and cumulative incidence in the next 30 days were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using earlyR and projections packages in R software.  The maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1 to 3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI: 1.03 to 1.25) by the end of the day 41. The expected average number of new cases in Shahroud is 9.0 case/day with a standard deviation of 3.8, which means an estimated total of 271 (95% CI: 178-383) new cases in the next 30 days.  It is essential to reduce the R0 to values below one. Therefore, we strongly recommend enforcing and continuing the current preventive measures, restricting travel, and providing screening tests for a larger proportion of the population.

title: First two months of the 2019 Coronavirus Disease (COVID-19) epidemic in China: real-time surveillance and evaluation with a second derivative model
abstract: Similar to outbreaks of many other infectious diseases, success in controlling the novel 2019 coronavirus infection requires a timely and accurate monitoring of the epidemic, particularly during its early period with rather limited data while the need for information increases explosively.  In this study, we used a second derivative model to characterize the coronavirus epidemic in China with cumulatively diagnosed cases during the first 2 months. The analysis was further enhanced by an exponential model with a close-population assumption. This model was built with the data and used to assess the detection rate during the study period, considering the differences between the true infections, detectable and detected cases.  Results from the second derivative modeling suggest the coronavirus epidemic as nonlinear and chaotic in nature. Although it emerged gradually, the epidemic was highly responsive to massive interventions initiated on January 21, 2020, as indicated by results from both second derivative and exponential modeling analyses. The epidemic started to decelerate immediately after the massive actions. The results derived from our analysis signaled the decline of the epidemic 14 days before it eventually occurred on February 4, 2020. Study findings further signaled an accelerated decline in the epidemic starting in 14 days on February 18, 2020.  The coronavirus epidemic appeared to be nonlinear and chaotic, and was responsive to effective interventions. The methods used in this study can be applied in surveillance to inform and encourage the general public, public health professionals, clinicians and decision-makers to take coordinative and collaborative efforts to control the epidemic.

title: Impact of coronavirus disease 2019 (covid-19) outbreak on rehabilitation services and physical medicine and rehabilitation (PM&R) physicians' activities: perspectives from the Spanish experience

title: Sudden cardiac death in COVID-19 patients, a report of three cases
abstract: The mortality rate of coronavirus disease-19 (COVID-19) has been reported as 1–6% in most studies. The cause of most deaths has been acute pneumonia. Nevertheless, it has been noted that cardiovascular failure can also lead to death. Three COVID-19 patients were diagnosed based on reverse transcriptase-polymerase chain reaction of a nasopharyngeal swab test and radiological examinations in our hospital. The patients received medications at the discretion of the treating physician. In this case series, chest computed tomography scans and electrocardiograms, along with other diagnostic tests were used to evaluate these individuals. Sudden cardiac death in COVID-19 patients is not common, but it is a major concern. So, it is recommended to monitor cardiac condition in selected patients with COVID-19.

title: The Mathematics of Testing with Application to Prevalence of COVID-19
abstract: We formulate three basic assumptions that should ideally guide any well-designed COVID-19 prevalence study. We provide, on the basis of these assumptions alone, a full derivation of mathematical formulas required for statistical analysis of testing data. In particular, we express the disease prevalence in a population through those for its homogeneous subpopulations. Although some of these formulas are routinely employed in prevalence studies, the study design often contravenes the assumptions upon which these formulas vitally depend. We also designed a natural prevalence estimator from the testing data and studied some of its properties. The results are equally valid for diseases other than COVID-19 as well as in non-epidemiological settings.

title: Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study
abstract: A range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Hong Kong. We examined the effect of these interventions and behavioural changes of the public on the incidence of COVID-19, as well as on influenza virus infections, which might share some aspects of transmission dynamics with COVID-19.  We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (R(t)) for COVID-19 and influenza A H1N1 to estimate changes in transmissibility over time. Attitudes towards COVID-19 and changes in population behaviours were reviewed through three telephone surveys done on Jan 20–23, Feb 11–14, and March 10–13, 2020.  COVID-19 transmissibility measured by R(t) has remained at approximately 1 for 8 weeks in Hong Kong. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% CI 34–53%) reduction in transmissibility in the community, from an estimated R(t) of 1·28 (95% CI 1·26–1·30) before the start of the school closures to 0·72 (0·70–0·74) during the closure weeks. Similarly, a 33% (24–43%) reduction in transmissibility was seen based on paediatric hospitalisation rates, from an R(t) of 1·10 (1·06–1·12) before the start of the school closures to 0·73 (0·68–0·77) after school closures. Among respondents to the surveys, 74·5%, 97·5%, and 98·8% reported wearing masks when going out, and 61·3%, 90·2%, and 85·1% reported avoiding crowded places in surveys 1 (n=1008), 2 (n=1000), and 3 (n=1005), respectively.  Our study shows that non-pharmaceutical interventions (including border restrictions, quarantine and isolation, distancing, and changes in population behaviour) were associated with reduced transmission of COVID-19 in Hong Kong, and are also likely to have substantially reduced influenza transmission in early February, 2020.  Health and Medical Research Fund, Hong Kong.

title: Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms
abstract: India has taken strong and early public health measures for arresting the spread of the COVID-19 epidemic. With only 536 COVID-19 cases and 11 fatalities, India - a democracy of 1.34 billion people - took the historic decision of a 21-day national lockdown on March 25. The lockdown was further extended to May 3, soon after the analysis of this paper was completed.  To study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 cases in India compared to other less severe non-pharmaceutical interventions using epidemiological forecasting models and Bayesian estimation algorithms; to compare effects of hypothetical durations of lockdown from an epidemiological perspective; to study alternative explanations for slower growth rate of the virus outbreak in India, including exploring the association of the number of cases and average monthly temperature; and finally, to outline the pivotal role of reliable and transparent data, reproducible data science methods, tools and products as we reopen the country and prepare for a post lock-down phase of the pandemic.  We use the daily data on the number of COVID-19 cases, of recovered and of deaths from March 1 until April 7, 2020 from the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Additionally, we use COVID-19 incidence counts data from Kaggle and the monthly average temperature of major cities across the world from Wikipedia.  The current time-series data on daily proportions of cases and removed (recovered and death combined) from India are analyzed using an extended version of the standard SIR (susceptible, infected, and removed) model. The eSIR model incorporates time-varying transmission rates that help us predict the effect of lockdown compared to other hypothetical interventions on the number of cases at future time points. A Markov Chain Monte Carlo implementation of this model provided predicted proportions of the cases at future time points along with credible intervals (CI).  Our predicted cumulative number of COVID-19 cases in India on April 30 assuming a 1-week delay in people's adherence to a 21-day lockdown (March 25 - April 14) and a gradual, moderate resumption of daily activities after April 14 is 9,181 with upper 95% CI of 72,245. In comparison, the predicted cumulative number of cases under "no intervention" and "social distancing and travel bans without lockdown" are 358 thousand and 46 thousand (upper 95% CI of nearly 2.3 million and 0.3 million) respectively. An effective lockdown can prevent roughly 343 thousand (upper 95% CI 1.8 million) and 2.4 million (upper 95% CI 38.4 million) COVID-19 cases nationwide compared to social distancing alone by May 15 and June 15, respectively. When comparing a 21-day lockdown with a hypothetical lockdown of longer duration, we find that 28-, 42-, and 56-day lockdowns can approximately prevent 238 thousand (upper 95% CI 2.3 million), 622 thousand (upper 95% CI 4.3 million), 781 thousand (upper 95% CI 4.6 million) cases by June 15, respectively. We find some suggestive evidence that the COVID-19 incidence rates worldwide are negatively associated with temperature in a crude unadjusted analysis with Pearson correlation estimates [95% confidence interval] between average monthly temperature and total monthly incidence around the world being -0.185 [-0.548, 0.236] for January, -0.110 [-0.362, 0.157] for February, and -0.173 [-0.314, -0.026] for March.  The lockdown, if implemented correctly in the end, has a high chance of reducing the total number of COVID-19 cases in the short term, and buy India invaluable time to prepare its healthcare and disease monitoring system. Our analysis shows we need to have some measures of suppression in place after the lockdown for the best outcome. We cannot heavily rely on the hypothetical prevention governed by meteorological factors such as temperature based on current evidence. From an epidemiological perspective, a longer lockdown between 42-56 days is preferable. However, the lockdown comes at a tremendous price to social and economic health through a contagion process not dissimilar to that of the coronavirus itself. Data can play a defining role as we design post-lockdown testing, reopening and resource allocation strategies.  Our contribution to data science includes an interactive and dynamic app (covind19.org) with short- and long-term projections updated daily that can help inform policy and practice related to COVID-19 in India. Anyone can visualize the observed data for India and create predictions under hypothetical scenarios with quantification of uncertainties. We make our prediction codes freely available (https://github.com/umich-cphds/cov-ind-19) for reproducible science and for other COVID-19 affected countries to use them for their prediction and data visualization work.

title: A model to predict SARS-CoV-2 infection based on the first three-month surveillance data in Brazil.
abstract: COVID-19 diagnosis is a critical problem, mainly due to the lack or delay in the test results. We aimed to obtain a model to predict SARS-CoV-2 infection in suspected patients reported to the Brazilian surveillance system.  We analyzed suspected patients reported to the National Surveillance System that corresponded to the following case definition: patients with respiratory symptoms and fever, who traveled to regions with local or community transmission or who had close contact with a suspected or confirmed case. Based on variables routinely collected, we obtained a multiple model using logistic regression. The area under the receiver operating characteristic curve (AUC) and accuracy indicators were used for validation.  We described 1468 COVID-19 cases (confirmed by RT-PCR) and 4271 patients with other illnesses. With a data subset, including 80% of patients from Sao Paulo (SP) and Rio Janeiro (RJ), we obtained a function which reached an AUC of 95.54% (95% CI: 94.41% - 96.67%) for the diagnosis of COVID-19 and accuracy of 90.1% (sensitivity 87.62% and specificity 92.02%). In a validation dataset including the other 20% of patients from SP and RJ, this model exhibited an AUC of 95.01% (92.51% - 97.5%) and accuracy of 89.47% (sensitivity 87.32% and specificity 91.36%).  We obtained a model suitable for the clinical diagnosis of COVID-19 based on routinely collected surveillance data. Applications of this tool include early identification for specific treatment and isolation, rational use of laboratory tests, and input for modeling epidemiological trends.

title: Prevalence and Clinical Presentation of Health Care Workers With Symptoms of Coronavirus Disease 2019 in 2 Dutch Hospitals During an Early Phase of the Pandemic
abstract: On February 27, 2020, the first patient with coronavirus disease 2019 (COVID-19) was reported in the Netherlands. During the following weeks, at 2 Dutch teaching hospitals, 9 health care workers (HCWs) received a diagnosis of COVID-19, 8 of whom had no history of travel to China or northern Italy, raising the question of whether undetected community circulation was occurring.  To determine the prevalence and clinical presentation of COVID-19 among HCWs with self-reported fever or respiratory symptoms.  This cross-sectional study was performed in 2 teaching hospitals in the southern part of the Netherlands in March 2020, during the early phase of the COVID-19 pandemic. Health care workers employed in the participating hospitals who experienced fever or respiratory symptoms were asked to voluntarily participate in a screening for infection with the severe acute respiratory syndrome coronavirus 2. Data analysis was performed in March 2020.  The prevalence of severe acute respiratory syndrome coronavirus 2 infection was determined by semiquantitative real-time reverse transcriptase–polymerase chain reaction on oropharyngeal samples. Structured interviews were conducted to document symptoms for all HCWs with confirmed COVID-19.  Of 9705 HCWs employed (1722 male [18%]), 1353 (14%) reported fever or respiratory symptoms and were tested. Of those, 86 HCWs (6%) were infected with severe acute respiratory syndrome coronavirus 2 (median age, 49 years [range, 22-66 years]; 15 [17%] male), representing 1% of all HCWs employed. Most HCWs experienced mild disease, and only 46 (53%) reported fever. Eighty HCWs (93%) met a case definition of fever and/or coughing and/or shortness of breath. Only 3 (3%) of the HCWs identified through the screening had a history of travel to China or northern Italy, and 3 (3%) reported having been exposed to an inpatient with a known diagnosis of COVID-19 before the onset of symptoms.  Within 2 weeks after the first Dutch case was detected, a substantial proportion of HCWs with self-reported fever or respiratory symptoms were infected with severe acute respiratory syndrome coronavirus 2, likely as a result of acquisition of the virus in the community during the early phase of local spread. The high prevalence of mild clinical presentations, frequently not including fever, suggests that the currently recommended case definition for suspected COVID-19 should be used less stringently.

title: Predictive accuracy of a hierarchical logistic model of cumulative SARS-CoV-2 case growth
abstract: Infectious disease predictions models, including virtually all epidemiological models describing the spread of the SARS-CoV-2 pandemic up to June 2020, are rarely evaluated. The aim of the present study was to investigate the predictive accuracy of a prognostic model for forecasting the development of the cumulative number of reported SARS-CoV-2 cases in countries and administrative regions worldwide.  The cumulative number of reported SARS-CoV-2 cases was forecasted in 251 regions with a horizon of two weeks, one month, and two months using a previously described hierarchical logistic model at the end of March 2020. Forecasts were compared to actual observations by using a series of evaluation metrics.  On average, predictive accuracy was very high in nearly all regions at the two weeks forecast, high in most regions at the one month forecast, and notable in the majority of the regions at the two months forecast. Higher accuracy was associated with the availability of more data for estimation and with a more pronounced cumulative case growth from the first case to the date of estimation. In some strongly affected regions, cumulative case counts were considerably underestimated.  With keeping its limitations in mind, the investigated model can be used for the preparation and distribution of resources during the SARS-CoV-2 pandemic. Future research should primarily address the model's assumptions and its scope of applicability. In addition, establishing a relationship with known mechanisms and traditional epidemiological models of disease transmission would be desirable.

title: Is social connectedness a risk factor for the spreading of COVID-19 among older adults? The Italian paradox
abstract: Italy was one of the first European countries affected by the new coronavirus (COVID-19) pandemic, with over 105,000 infected people and close to 13,000 deaths, until March 31(st). The pandemic has hit especially hard because of the country's demographic structure, with a high percentage of older adults. The authors explore the possibility, recently aired in some studies, of extensive intergenerational contact as a possible determinant of the severity of the pandemic among the older Italian adults. We analyzed several variables to test this hypothesis, such as the percentage of infected patients aged >80 years, available nursing home beds, COVID-19 incidence rate, and the number of days from when the number of positive tests exceeded 50 (epidemic maturity). We also included in the analysis mean household size and percentage of households comprising one person, in the region. Paradoxically, the results are opposite of what was previously reported. The pandemic was more severe in regions with higher family fragmentation and increased availability of residential health facilities.

title: High incidence of venous thromboembolic events in anticoagulated severe COVID‐19 patients
abstract: Coagulopathy is a common abnormality in patients with COVID‐19. However, the exact incidence of venous thromboembolic event is unknown in anticoagulated, severe COVID‐19 patients.  Systematic assessment of venous thromboembolism (VTE) using complete duplex ultrasound (CDU) in anticoagulated COVID‐19 patients.  We performed a retrospective study in 2 French intensive care units (ICU) where CDU is performed as a standard of care. A CDU from thigh to ankle at selected sites with Doppler waveforms and images was performed early during ICU stay in patients admitted with COVID‐19. Anticoagulation dose was left to the discretion of the treating physician based on the individual risk of thrombosis. Patients were classified as treated with prophylactic anticoagulation or therapeutic anticoagulation. Pulmonary embolism was systematically searched in patients with persistent hypoxemia or secondary deterioration.  From March 19 to April 11, 2020, 26 consecutive patients with severe COVID‐19 were screened for VTE. Eight patients (31%) were treated with prophylactic anticoagulation, whereas 18 patients (69%) were treated with therapeutic anticoagulation. The overall rate of VTE in patients was 69%. The proportion of VTE was significantly higher in patients treated with prophylactic anticoagulation when compared with the other group (100% vs 56%, respectively, P = .03). Surprisingly, we found a high rate of thromboembolic events in COVID‐19 patients treated with therapeutic anticoagulation, with 56% of VTE and 6 pulmonary embolisms.  Our results suggest considering both systematic screening of VTE and early therapeutic anticoagulation in severe ICU COVID‐19 patients.

title: Uncertainty Quantification in Epidemiological Models for COVID-19 Pandemic
abstract: The main goal of this paper is to develop the forward and inverse modeling of the Coronavirus (COVID-19) pandemic using novel computational methodologies in order to accurately estimate and predict the pandemic. This leads to governmental decisions support in implementing effective protective measures and prevention of new outbreaks. To this end, we use the logistic equation and the SIR system of ordinary differential equations to model the spread of the COVID-19 pandemic. For the inverse modeling, we propose Bayesian inversion techniques, which are robust and reliable approaches, in order to estimate the unknown parameters of the epidemiological models. We use an adaptive Markov-chain Monte-Carlo (MCMC) algorithm for the estimation of a posteriori probability distribution and confidence intervals for the unknown model parameters as well as for the reproduction number. Furthermore, we present a fatality analysis for COVID-19 in Austria, which is also of importance for governmental protective decision making. We perform our analyses on the publicly available data for Austria to estimate the main epidemiological model parameters and to study the effectiveness of the protective measures by the Austrian government. The estimated parameters and the analysis of fatalities provide useful information for decision makers and makes it possible to perform more realistic forecasts of future outbreaks.

title: [Managing patients in dialysis and with kidney transplant infected with Covid-19].
abstract: We are in the midst of a health emergency that is totally new for us all and that requires a concerted effort, especially when it comes to safeguarding patients on hemodialysis, and kidney transplant recipients. Brescia is currently a very active cluster of infections (2918 cases on the 17/03/2020), second only to Bergamo. The way our structure is organised has allowed us to treat nephropathic patients directly within the Nephrology Unit, following of course a great deal of reshuffling; at the moment, we are treating 21 transplanted patients and 17 on hemodialysis. This has led us to adopt a systematic approach to handling this emergency, not only in managing inpatients, but also in researching the new disease. Our approach is mirrored in the guidelines attached to this article, originally intended for internal use only but potentially very useful to our colleagues, as they face the same exact problems. We have also started collecting data on our positive patients with the aim of understanding better the functioning of this disease and how best to manage it. If anyone is interested, we ask you to please get in touch with us, so we can coordinate our efforts.

title: COVID-19: Magnifying the Effect of Health Disparities

title: Case- fatality rate in COVID- 19 patients: A meta-analysis of publicly accessible database
abstract: A novel coronavirus was reported in Wuhan, China in December 2019 to cause severe acute respiratory symptoms (COVID- 19). In this meta-analysis, we estimated case fatality rate from COVID- 19 infection by random effect meta-analysis model with country level data. Publicly accessible web database WorldOMeter (https://www.worldometers.info/coronavirus/) was accessed on 24th March 2020 GMT and reported total number of cases, total death, active cases and seriously ill/ critically ill patients were retrieved. Primary outcome of this meta-analysis was case fatality rate defined by total number of deaths divided by total number of diagnosed cases. Pooled case fatality rate (95% CI) was 1.78 (1.34- 2.22) %. Between country heterogeneity was 0.018 (p<0.0001). Pooled estimate of composite poor outcome (95% CI) was 4.06 (3.24- 4.88) % at that point of time after exclusion of countries reported small number of cases. Pooled mortality rate (95% CI) was 33.97 (27.44- 40.49) % amongst closed cases (where patients have recovered or died) with. Meta regression analysis identified statistically significant association between health expenditure and mortality amongst closed cases (p=0.037).

title: Maybe not an overreaction

title: The COVID-19 infection in Italy: a statistical study of an abnormally severe disease
abstract: We statistically investigate the Coronavirus Disease 19 (hereinafter Covid-19) epidemics, which is particularly invasive in Italy. We show that the high apparent mortality (or Case Fatality Ratio, CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of infected cases. To give a more realistic estimate of the mortality of Covid-19, we use the most recent estimates of the IFR (Infection Fatality Ratio) of epidemic, based on the minimum observed CFR, and furthermore analyse data obtained from the ship Diamond Princess, a good representation of a laboratory case-study from an isolated system in which all the people have been tested. From such analyses we derive more realistic estimates of the real extension of the infection, as well as more accurate indicators of how fast the infection propagates. We then point out from the various explanations proposed, the dominant factors causing such an abnormal seriousness of the disease in Italy. Finally, we use the deceased data, the only ones estimated to be reliable enough, to predict the total number of infected people and the interval of time when the infection in Italy could stop.

title: Machine Learning Maps Research Needs in COVID-19 Literature
abstract: Manually assessing the scope of the thousands of publications on the COVID-19 (coronavirus disease 2019) pandemic is an overwhelming task. Shortcuts through metadata analysis (e.g., keywords) assume that studies are properly tagged. However, machine learning approaches can rapidly survey the actual text of coronavirus abstracts to identify research overlap between COVID-19 and other coronavirus diseases, research hotspots, and areas warranting exploration. We propose a fast, scalable, and reusable framework to parse novel disease literature. When applied to the COVID-19 Open Research Dataset (CORD-19), dimensionality reduction suggested that COVID-19 studies to date are primarily clinical-, modeling- or field-based, in contrast to the vast quantity of laboratory-driven research for other (non-COVID-19) coronavirus diseases. Topic modeling also indicated that COVID-19 publications have thus far focused primarily on public health, outbreak reporting, clinical care, and testing for coronaviruses, as opposed to the more limited number focused on basic microbiology, including pathogenesis and transmission.

title: Advantages and Limitations of Anticipating Laboratory Test Results from Regression- and Tree-Based Rules Derived from Electronic Health-Record Data
abstract: Laboratory testing is the single highest-volume medical activity, making it useful to ask how well one can anticipate whether a given test result will be high, low, or within the reference interval (“normal”). We analyzed 10 years of electronic health records—a total of 69.4 million blood tests—to see how well standard rule-mining techniques can anticipate test results based on patient age and gender, recent diagnoses, and recent laboratory test results. We evaluated rules according to their positive and negative predictive value (PPV and NPV) and area under the receiver-operator characteristic curve (ROC AUCs). Using a stringent cutoff of PPV and/or NPV≥0.95, standard techniques yield few rules for sendout tests but several for in-house tests, mostly for repeat laboratory tests that are part of the complete blood count and basic metabolic panel. Most rules were clinically and pathophysiologically plausible, and several seemed clinically useful for informing pre-test probability of a given result. But overall, rules were unlikely to be able to function as a general substitute for actually ordering a test. Improving laboratory utilization will likely require different input data and/or alternative methods.

title: COVID-19 in patients with HIV

title: Semiparametric Bayesian Inference for the Transmission Dynamics of COVID-19 with a State-Space Model
abstract: The outbreak of Coronavirus Disease 2019 (COVID-19) is an ongoing pandemic affecting over 200 countries and regions. Inference about the transmission dynamics of COVID-19 can provide important insights into the speed of disease spread and the effects of mitigation policies. We develop a novel Bayesian approach to such inference based on a probabilistic compartmental model using data of daily confirmed COVID-19 cases. In particular, we consider a probabilistic extension of the classical susceptible-infectious-recovered model, which takes into account undocumented infections and allows the epidemiological parameters to vary over time. We estimate the disease transmission rate via a Gaussian process prior, which captures nonlinear changes over time without the need of specific parametric assumptions. We utilize a parallel-tempering Markov chain Monte Carlo algorithm to efficiently sample from the highly correlated posterior space. Predictions for future observations are done by sampling from their posterior predictive distributions. Performance of the proposed approach is assessed using simulated datasets. Finally, our approach is applied to COVID-19 data from four states of the United States: Washington, New York, California, and Illinois. An R package BaySIR is made available at https://github.com/tianjianzhou/BaySIR for the public to conduct independent analysis or reproduce the results in this paper.

title: A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland
abstract: Since COVID-19 emerged in early December, 2019 in Wuhan and swept across China Mainland, a series of large-scale public health interventions, especially Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement, have been taken by the government to control the epidemic. Based on Baidu Migration data and the confirmed cases data, we identified two key factors affecting the later (e.g February 27, 2020) cumulative confirmed cases in non-Wuhan region (y). One is the sum travelers from Wuhan during January 20 to January 26 (x1), which had higher infected probability but lower transmission ability because the human-to-human transmission risk of COVID-19 was confirmed and announced on January 20. The other is the seed cases from Wuhan before January 19, which had higher transmission ability and could be represented with the confirmed cases before January 29 (x2) due to a mean 10-day delay between infection and detection. A simple yet effective regression model then was established as follow: y= 70.0916+0.0054*x1+2.3455*x2 (n = 44, R2 = 0.9330, P<10-7). Even the lock-down date only delay or in advance 3 days, the estimated confirmed cases by February 27 in non-Wuhan region will increase 35.21% or reduce 30.74% - 48.59%. Although the above interventions greatly reduced the human mobility, Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement do have a determining effect on the ongoing spread of COVID-19 across China Mainland. The strategy adopted by China has changed the fast-rising curve of newly diagnosed cases, the international community should learn from lessons of Wuhan and experience from China. Efforts of 29 Provinces and 44 prefecture-level cities against COVID-19 were also assessed preliminarily according to the interpretive model. Big data has played and will continue playing an important role in public health.

title: Amid COVID-19: the importance of developing an positive adverse drug reaction (ADR) and medical device incident (MDI) reporting culture for Global Health and public safety
abstract: Amid COVID-19 Crisis, reporting adverse drug reactions (ADRs) and medical device incidents (MDIs) to Health Canada or health authorities in every country is crucial for monitoring medication safety and improving public health. Health Canada, for example, through their online database, has facilitated the process of reporting side effects relating to drugs and medical devices. However, several patients and health care professionals still fail to voluntarily report adverse events. For health care providers, some barriers to reporting may include fear of negative feedback, apathy, legal concerns, and uncertainty about whether an incident qualifies as an ADR. In the current COVID-19 Crisis, it is especially important for health care providers to be diligent about reporting Adverse Drug Reactions (ADRs), since misinformation propagated by the media is causing patients to misuse certain medications. We need to shift the current thought process about ADR reporting in order to encourage a positive reporting culture by patients and health care providers.

title: Recent Aspects on the Pathogenesis Mechanism, Animal Models and Novel Therapeutic Interventions for Middle East Respiratory Syndrome Coronavirus Infections
abstract: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an emerging zoonotic virus considered as one of the major public threat with a total number of 2 298 laboratory-confirmed cases and 811 associated deaths reported by World Health Organization as of January 2019. The transmission of the virus was expected to be from the camels found in Middle Eastern countries via the animal and human interaction. The genome structure provided information about the pathogenicity and associated virulent factors present in the virus. Recent studies suggested that there were limited insight available on the development of novel therapeutic strategies to induce immunity against the virus. The severities of MERS-CoV infection highlight the necessity of effective approaches for the development of various therapeutic remedies. Thus, the present review comprehensively and critically illustrates the recent aspects on the epidemiology of the virus, the structural and functional features of the viral genome, viral entry and transmission, major mechanisms of pathogenesis and associated virulent factors, current animal models, detection methods and novel strategies for the development of vaccines against MERS-CoV. The review further illustrates the molecular and computational virtual screening platforms which provide insights for the identification of putative drug targets and novel lead molecules toward the development of therapeutic remedies.

title: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (COVID-19)
abstract: Estimation of the fraction and contagiousness of undocumented novel coronavirus (COVID-19) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Many mild infections are typically not reported and, depending on their contagiousness, may support stealth transmission and the spread of documented infection.  Here we use observations of reported infection and spread within China in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with the emerging coronavirus, including the fraction of undocumented infections and their contagiousness.  We estimate 86% of all infections were undocumented (95% CI: [82%−90%]) prior to the Wuhan travel shutdown (January 23, 2020). Per person, these undocumented infections were 52% as contagious as documented infections ([44%−69%]) and were the source of infection for two-thirds of documented cases. Our estimate of the reproductive number (2.23; [1.77–3.00]) aligns with earlier findings; however, after travel restrictions and control measures were imposed this number falls considerably.  A majority of COVID-19 infections were undocumented prior to implementation of control measures on January 23, and these undocumented infections substantially contributed to virus transmission. These findings explain the rapid geographic spread of COVID-19 and indicate containment of this virus will be particularly challenging. Our findings also indicate that heightened awareness of the outbreak, increased use of personal protective measures, and travel restriction have been associated with reductions of the overall force of infection; however, it is unclear whether this reduction will be sufficient to stem the virus spread.

title: Estimation of seroprevalence of novel coronavirus disease (COVID-19) using preserved serum at an outpatient setting in Kobe, Japan: A cross-sectional study.
abstract: Coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has been affecting many people on earth and our society. Japan is known to have relatively less number of infections as well as deaths among developed nations. However, accurate prevalence of COVID-19 in Japan remains unknown. Therefore, we conducted a cross-sectional study to estimate seroprevalence of SARS-CoV-2 infection.  We conducted a cross-sectional serologic testing for SARS-CoV-2 antibody using 1,000 samples from patients at outpatient settings who visited the clinic from March 31 to April 7, 2020, stratified by decade of age and sex.  There were 33 positive IgG among 1,000 serum samples (3.3%, 95%CI: 2.3-4.6%). By applying this figure to the census of Kobe City (poplation: 1,518,870), it is estimated that the number of people with positive IgG be 50,123 (95%CI: 34,934-69,868). Age and sex adjusted prevalence of positivity was 2.7% (95%CI 1.8-3.9%), and the estimated number of people with positive IgG was 40,999 (95%CI: 27,333-59,221). These numbers were 396 to 858 fold more than confirmed cases with PCR testing in Kobe City.  Our cross-sectional serological study suggests that the number of people with seropositive for SARS-CoV-2 infection in Kobe, Japan is far more than the confirmed cases by PCR testing.

title: Epidemiological Analysis of the First 1389 Cases of COVID-19 in Poland: A Preliminary Report
abstract: The World Health Organization has declared COVID-19 a global pandemic. This paper presents an epidemiological analysis of the first phase of the COVID-19 epidemic in Poland.  This cross-sectional study was carried out between 3 and 27 March 2020 on a sample of 1389 laboratory-confirmed COVID-19 cases in Poland. Data were obtained from epidemiological reports collected by the Chief Sanitary Inspectorate. Analysis includes the number of COVID-19 cases, number of deaths, number of hospitalizations, number of people quarantined, and number of laboratory tests performed.  The first case was confirmed on 4 March 2020. Over 24 days after the first case, the total number of confirmed infections rose to 1389 (34,000 laboratory tests were performed). The highest incidence rates (over 5 per 100,000) were observed in the 2 central administrative regions (Mazowieckie and Lódzkie) and in the south-western region of Dolnoslaskie, which borders the Czech Republic and Germany. Based on available data about age and sex, a clearly higher incidence was observed in the 20-29 years (4.0 per 100,000), 40-49 years (4.1 per 100,000), and 50-59 years (4.3 per 100,000) age groups. In the period analyzed (24 days), there were 16 confirmed deaths (average age 65.5 years; 81.2% males).  The proportion of women and men with confirmed COVID-19 infection was similar to the sex ratio in the general population. Infections were relatively less common in those aged under 20 years. The largest numbers of confirmed cases were detected in 3 of the 4 largest cities, each of which has an international airport.

title: It can be dangerous to take epidemic curves of COVID-19 at face value
abstract: During an epidemic with a new virus, we depend on modelling to plan the response: but how good are the data? The aim of our work was to better understand the impact of misclassification errors in identification of true cases of COVID-19 on epidemic curves. Data originated from Alberta, Canada (available on 28 May 2020). There is presently no information of sensitivity (Sn) and specificity (Sp) of laboratory tests used in Canada for the causal agent for COVID-19. Therefore, we examined best attainable performance in other jurisdictions and similar viruses. This suggested perfect Sp and Sn 60–95%. We used these values to re-calculate epidemic curves to visualize the potential bias due to imperfect testing. If the sensitivity improved, the observed and adjusted epidemic curves likely fall within 95% confidence intervals of the observed counts. However, bias in shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60–70% range. These issues are minor early in the epidemic, but hundreds of undiagnosed cases are likely later on. It is therefore hazardous to judge progress of the epidemic based on observed epidemic curves unless quality of testing is better understood.  The online version of this article (10.17269/s41997-020-00367-6) contains supplementary material, which is available to authorized users.

title: Paucity and disparity of publicly available sex-disaggregated data for the COVID-19 epidemic hamper evidence-based decision-making
abstract: COVID-19 has joined the long list of human disorders with sexually dimorphic expression. Increased lethality in men was evident in the first large reports from ChinaCDC and WHO-China, and the gender gap appeared even wider in the early Italian outbreak. Newspapers and scientific journals alike have commented on this finding and the preexisting conditions, biological processes, and gender role behavior differences that may underlie it. However, as for other diseases, and in spite of years of advocating for the collection of raw epidemiological data and the analysis of clinical trial data sets by sex, very little appeared to be released about sex differences in characteristics of the epidemics beyond infection and death rates, such as severity of disease, comorbidities, rate of recovery, length of hospital stay, or number of tests for the SARS-CoV-2 coronavirus. These data are critical not only for scientists to understand the pathophysiology of disease, but also to inform decision-making by countries and healthcare systems on how to prioritize testing and best allocate scarce resources and relief funds. Systematic analysis of official websites for the 20 countries and 6 US states reporting the highest number of cases on March 21, 2020, revealed a wide disparity in sex-disaggregated data made available to the public and scholars. Only a handful of the countries reported cases by sex separately. None of the other characteristics, including fatality rates, were stratified by sex at the time. Beyond suboptimal sex disaggregation, our analysis found a paucity of usable raw data sets and a generalized lack of standardization of captured data, making comparisons difficult. A second round of data capture in April found more complete, but even more disparate, information. Our analysis revealed a wide range of sex ratios among confirmed cases, which changed over time. In countries where a male-biased sex ratio was initially reported, the reported proportion of women among cases dramatically increased in under 3 weeks. In contrast, men were consistently over-represented in severe cases, intensive care admissions, and deaths. We also show that the sex ratio varies with age, with a complex pattern, reproduced across the 6 countries for which data were found. Accurate, peer-reviewed, statistical analysis of harmonized, sex-disaggregated data for other characteristics of epidemics, such as availability of testing, suspected source of infection, or comorbidities will be critical to understand where the observed disparities come from and to generate evidence-based recommendations for decision-making by institutions and governments around the world.

title: Evolving reporting criteria of COVID-19 in Taiwan during the epidemic

title: Modelling the COVID-19 epidemics in Brasil: Parametric identification and public health measures influence
abstract: A SIRU-type epidemic model is proposed for the prediction of COVID-19 spreading within Brasil, and analyse the influence of public health measures on simulating the control of this infectious disease. Since the reported cases are typically only a fraction of the total number of the symptomatic infectious individuals, the model accounts for both reported and unreported cases. Also, the model allows for the time variation of both the transmission rate and the fraction of asymptomatic infectious that become reported symptomatic individuals, so as to reflect public health interventions, towards its control, along the course of the epidemic evolution. An analytical exponential behaviour for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for parametric estimations employing the present direct problem model with the data from the known portion of the epidemics evolution, represented by the time series for the reported cases of infected individuals. The direct-inverse problem analysis is then employed with the actual data from China, with the first half been employed for the parametric estimation and the second half for validation of the predictive capability of the proposed approach. The full dataset for China is then employed in another parameter identification, including the average times that asymptomatic infectious individuals and that symptomatic individuals are infectious. Following this validation, the available data on reported cases in Brasil from February 15th till March 29th, 2020, is used for estimating parameters and then predict the epidemy evolution under these conditions. Finally, public health interventions are simulated, aimed at diminishing the effects of the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviours for these two parameters, usually assumed constant in epidemic evolutions without intervention. It is demonstrated that a combination of actions to affect both parameters can have a much faster and effective result in the control of the epidemy dynamics.

title: A Tale of Two Communities: Characterizing Reddit Response to COVID-19 through /r/China_Flu and /r/Coronavirus
abstract: The COVID-19 pandemic has deeply impacted people's lives around the globe. During the extended lockdowns caused by the pandemic, online communities are crucial for people to access information and share experiences. In particular, two"new"communities have emerged on Reddit: /r/China_flu and /r/Coronavirus. By studying activities and users in these two communities, we provide a characterization of people's responses to COVID-19 on Reddit. First, we find that user activity peaks around March 17, when the World Health Organization (WHO) announced COVID-19 as a pandemic. Shortly after that, the activity levels of both communities have been declining week by week. We further illustrate the central role of these two communities in the emergence of COVID-related communities. Second, we study the differences between these two communities. /r/Coronavirus is recommended as the official community for COVID-19 on Reddit, while /r/China_flu adopts a loose moderation practice. As a result, we observe that these two communities are gradually growing apart and more extremism is being found in /r/China_flu. Finally, we examine the spillover effect of the COVID-19 pandemic on user activity across the entire Reddit platform. Our results show significant changes in user activities outside COVID-related communities. In subreddits related to finance, food, and countries/cities, user activity is recovering to the pre-pandemic level in late April and May as countries reopen, but subreddits related to travel and sports remain highly impacted and show lower activity levels than the pre-pandemic period. Our work highlights the strength of Reddit as a source for understanding public reactions to COVID-19 and the importance of content moderation on the Internet during a pandemic.

title: Transmission Dynamics of COVID-19 and Impact on Public Health Policy
abstract: In this work we construct a mathematical model for the transmission and spread of coronavirus disease 2019 or COVID-19. Our model features delay terms to account for (a) the time lapse or latency period between contracting the disease and displaying symptoms, and (b) the time lag in testing patients for the virus due to the limited numbers of testing facilities currently available. We find that the delay introduces a significant disparity between the actual and reported time-trajectories of cases in a particular region. Specifically, the reported case histories lag the actual histories by a few days. Hence, to minimize the spread of the disease, lockdowns and similarly drastic social isolation measures need to be imposed some time before the reported figures are approaching their peak values. We then account for the social reality that lockdowns can only be of a limited duration in view of practical considerations. We find that the most effective interval for imposing such a limited-time lockdown is one where the midpoint of the lockdown period coincides with the actual peak of the spread of the disease in the absence of the lockdown. We further show that the true effectivity of imposing a lockdown may be misrepresented and grossly underestimated by the reported case trajectories in the days following the action.

title: Symptomatic COVID-19 Infection in Eye Professionals in Wuhan China

title: COVID-19 in India: State-wise Analysis and Prediction
abstract: Coronavirus disease 2019 (COVID-19), a highly infectious disease, was first detected in Wuhan, China, in December 2019. The disease has spread to 210 countries and territories around the world and infected (confirmed) more than two million people. In India, the disease was first detected on 30 January 2020 in Kerala in a student who returned from Wuhan. The total (cumulative) number of confirmed infected people is 17615 till now across India (19 April 2020). Most of the research and newspaper articles focus on the number of infected people in entire India. However, given the size and diversity of India, it may be a good idea to look at the spread of the disease in each state separately, along with the entire country. For example, currently, Maharashtra has more than 2500 confirmed cumulative infected cases, whereas West Bengal has less than 300 confirmed infected cases (16 April 2020). The approaches to address the pandemic in the two states must be different due to limited resources. In this article, we will focus the infected people in each state (restricting to only those states with enough data for prediction) and build three growth models to predict infected people for that state in the next 30 days. The impact of preventive measures on daily infected-rate is discussed for each state.

title: The Late Arrival of COVID-19 in Africa - Mitigating Pan-Continental Spread

title: Chest CT features and their role in COVID-19
abstract: Since December 2019, the novel coronavirus disease (COVID-19) has spread rapidly throughout China. This article reviews the chest CT features of COVID-19 and analyzes the role of chest CT in this health emergency.

title: High COVID-19 incidence among Norwegian travellers returned from Lombardy: implications for travel restrictions
abstract: On February 27th, three cases of COVID-19 were reported among Norwegians that had recently returned from Lombardy, Italy. Travellers from the region rapidly became the most common source of imported infections in the earliest stage of the Norwegian COVID-19 epidemic. The situation was exacerbated by the unfortunate temporal overlap between the Norwegian winter holidays and intense epidemic spread of COVID-19 in Northern Italy, resulting in a large number of infected travellers. Here we combined flight data on travels between Norway and Lombardy with patient-level data to determine the fraction of travellers returning to Norway that had been infected with SARS-CoV-2. Travellers returning to Norway from Lombardy contracted COVID-19 at incidence rates up to 0.02 per person-day in the period spanning February 21st and March 1st, with a clear uptick in transmission in the middle of the period. This shows an example of the infection risk in tourist destinations being several fold higher than elsewhere in the region. In Norway, this is also supported by high rates of infections among tourists returning from Austria in February and March, despite a low number of reported cases in the country at the time. The massive COVID-19 prevalence among travellers suggest that mandatory quarantine of returning travellers or suspension of non-essential international flights is essential if the aim is to control or suppress the COVID-19 pandemic.

title: Can the COVID-19 epidemic be controlled on the basis of daily test reports?
abstract: This paper studies if and to which extent COVID-19 epidemics can be controlled by authorities taking decisions on public health measures on the basis of daily reports of swab test results, active cases and total cases. A suitably simplified process model is derived to support the controllability analysis, highlighting the presence of very significant time delay; the model is validated with data from several outbreaks. The analysis shows that suppression strategies can be effective if strong enough and enacted early on. It also shows how mitigation strategies can fail because of the combination of delay, unstable dynamics, and uncertainty in the feedback loop; approximate conditions based on the theory of limitation of linear control are given for feedback control to be feasible.

title: Benchmarking the CoVID-19 pandemic across countries and states in the U.S.A. under heterogeneous testing
abstract: Public health officials need to make urgent decisions to reduce the potential impact of the CoVID-19 pandemic. Benchmarking based on the increase in total cases or case fatality rates is one way of comparing performance across countries or territories (such as states in the USA), and could inform policy decisions about COVID-19 mitigation strategies. But comparing cases and fatality across territories is challenging due to heterogeneity in testing and health systems. We show two complementary ways of benchmarking across countries or US states. First, we used multivariate regressions to estimate the test-elasticity-of-COVID-19-case-incidence. We found a 10% increase in testing yielded ~9% (95% CI:4.2-13.4%; p<0.001) increase in reported cases across countries, and ~2% (95%CI:0.1-3.4%; p=0.03) increase across US states during the week ending April 10th, 2020. We found comparable negative elasticities for fatality rates (across countries: beta;=-0.77, 95%CI:-1.40- -0.14; p=0.02; US states: beta;=-0.15, 95%CI:-0.30-0.01; p=0.06). Our results were robust to various model specifications. Second, we decomposed the growth in cases into test growth and positive test ratio (PTR) growth to intuitively visualize the components of case growth. We hope these results can help support evidence-based decisions by public health officials as more consistent data hopefully becomes available.

title: Choosing Wisely® in Hematology: Have We Made a Difference?
abstract: The Choosing Wisely® initiative, led by the American Board of Internal Medicine Foundation in collaboration with national professional medical societies, aims to help patients choose care that is essential, free from harm, and evidence-based. The American Society of Hematology has advocated practices specific to hematology for physicians and patients to examine carefully. Here, we summarize various barriers to adopting these practices, interventions used to improve adoption, and challenges in measuring the effectiveness of these interventions.  The Choosing Wisely® campaign has become an international effort with more than 20 countries worldwide having embraced it. Such widespread interest indicates that the campaign initiated an important dialog between patients and physicians about overutilization of resources. Evidence showing the positive impact of interventions on adopting these practices is accumulating, but their effect on improving clinical outcomes is uncertain.  Decreasing overuse of resources is a cultural change in perspective for practitioners and patients alike. We believe that healthcare delivery is transitioning from being volume-based to value-based. As we continue to support the Choosing Wisely® campaign, we need to implement strategies to document and measure the influence of our value-based recommendations on physician practices, patient care and attitudes, and healthcare costs.

title: Elementary time-delay dynamics of COVID-19 disease
abstract: An elementary model of COVID-19 dynamics, based on time-delay differential equations with a step-like survival function, is shown to be in good agreement with data from China and South Korea. The time-delal approach overcomes the major limitation of standard Susceptible-Exposed-Infected-Recovered (SEIR) models based on ordinary differential equations, namely their inability to predict the observed curve of infected individuals as a function of time. The model is also applied to countries where the epidemic is in earlier stages, such as Italy and Spain, to obtain estimates of the total number of cases and peak number of infected people that might be observed.

title: Laboratory Testing Methods for Novel Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2)
abstract: Following the first reports of coronavirus disease-19 (COVID-19) by China to the World Health Organization (WHO) on 31st December 2019, more than 4,302,774 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) cases have been reported by authorities in 212 countries and territories by 12th May 2020. The outbreak and spread of COVID-19 worldwide, highlights the critical need for developing rapid and accurate diagnostic testing methods for emerging human coronavirus (CoV) infections. Testing is crucial to track the spread of disease during a pandemic, and to swiftly permit public health interventions including isolation, quarantine, and appropriate clinical management of afflicted individuals. The key components of viral diagnostic tests are (1) collection of the appropriate sample (blood, nasal swab, and throat swab), (2) availability of the genetic and proteomic sequences of the novel virus for analysis, and (3) rapid and accurate laboratory testing methods. The current gold standard for the molecular diagnosis of SARS-CoV-2 infection is the real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for the qualitative and quantitative detection of viral nucleic acids. Other relevant laboratory methods include enzyme-linked immunoassays (EIA) for viral antibody and antigen detection, and serum viral neutralization (SVN) assays for antibody neutralization determination. The challenges faced in developing a diagnostic test for a novel pathogen are the ability to measure low viral loads for early detection, to provide low or no cross-reactivity with other viral strains and to deliver results rapidly. Several point-of-care molecular devices are currently being integrated for fast and accurate diagnosis of SARS-CoV-2 infections. This review discusses the current laboratory methods available to test for coronaviruses by focusing on the present COVID-19 outbreak.

title: The 45th Annual Meeting of the European Society for Blood and Marrow Transplantation: Physicians – Poster Session

title: Early Effects of COVID-19 on Oral and Maxillofacial Surgery Residency Training-Results From a National Survey.
abstract: The coronavirus disease 2019 (COVID-19) pandemic has had an immense impact on the healthcare industry. Oral and maxillofacial surgery (OMS) clinical practice uniquely exposes providers to COVID-19. The purpose of the present study was to understand the effect of the COVID-19 pandemic on OMS residency training programs (OMSRTPs): 1) training and education; 2) availability and use of personal protective equipment (PPE); 3) experience with, and use of, screening and viral testing; 4) resident experience; and 5) program director (PD) experience and observations of the immediate and future effects on OMSRTPs.  OMS residents and PDs in OMSRTPs in the United States were invited to participate in the present cross-sectional study from April 1, 2020 to May 1, 2020. A 51-question survey was used to evaluate the effects of COVID-19 on OMSRTPs and to assess the 5 specific aims of the present study.  A total of 160 residents and 13 PDs participated in the survey, representing 83% of US states or territories with OMSRTPs. Almost all residents (96.5%) reported modifications to their training program, and 14% had been reassigned to off-service clinical rotations (eg, medicine, intensive care unit). The use of an N95 respirator mask plus standard PPE precautions during aerosol-generating procedures varied by procedure location, with 36.8% reporting limited access to these respirators. Widespread screening practices were in use, with 83.6% using laboratory-based viral testing. Residents scheduled to graduate in 2022 were most concerned with the completion of the graduation requirements and with decreased operative experience. Most residents (94.2%) had moved to web-based didactics, and a plurality (47%) had found increased value in the didactics.  Sweeping alterations to OMS clinical practice have occurred for those in OMSRTPs during the COVID-19 pandemic. Although the overall OMSRTP response has been favorable, residents' concerns regarding the ubiquitous availability of appropriate PPE, operative experience, and completion of graduation requirements requires further deliberation.

title: The establishment of reference sequence for SARS‐CoV‐2 and variation analysis
abstract: Starting around December 2019, an epidemic of pneumonia, which was named COVID‐19 by the World Health Organization, broke out in Wuhan, China, and is spreading throughout the world. A new coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) by the Coronavirus Study Group of the International Committee on Taxonomy of Viruses was soon found to be the cause. At present, the sensitivity of clinical nucleic acid detection is limited, and it is still unclear whether it is related to genetic variation. In this study, we retrieved 95 full‐length genomic sequences of SARAS‐CoV‐2 strains from the National Center for Biotechnology Information and GISAID databases, established the reference sequence by conducting multiple sequence alignment and phylogenetic analyses, and analyzed sequence variations along the SARS‐CoV‐2 genome. The homology among all viral strains was generally high, among them, 99.99% (99.91%‐100%) at the nucleotide level and 99.99% (99.79%‐100%) at the amino acid level. Although overall variation in open‐reading frame (ORF) regions is low, 13 variation sites in 1a, 1b, S, 3a, M, 8, and N regions were identified, among which positions nt28144 in ORF 8 and nt8782 in ORF 1a showed mutation rate of 30.53% (29/95) and 29.47% (28/95), respectively. These findings suggested that there may be selective mutations in SARS‐COV‐2, and it is necessary to avoid certain regions when designing primers and probes. Establishment of the reference sequence for SARS‐CoV‐2 could benefit not only biological study of this virus but also diagnosis, clinical monitoring and intervention of SARS‐CoV‐2 infection in the future.

title: Mental health status among family members of health care workers in Ningbo, China during the Coronavirus Disease 2019 (COVID-19) outbreak: a Cross-sectional Study
abstract: So far, the psychological impact of COVID-19 epidemic among family members of Health care workers (HCWs) in China has been neglected. The present cross-sectional study aimed to investigate the mental health status and related factors of families of HCWs in Designated Hospitals in Ningbo, China.  Family members of HCWs working in five designated hospitals in Ningbo, China were recruited between February 10th and 20th, 2020. Information on demographic variables, the COVID-19-related events in the lives, knowledge of COVID-19 and the working status of family members (that is, HCWs) was collected using online self-administered questionnaires. The mental health status were assessed using the Chinese version of Patient Health Questionnare-9 (PHQ-9) and Chinese version of Generalized Anxiety Disorder-7 (GAD-7 ). Multivariable logistic regression analyses were conducted to identify the main factors associated with the mental health conditions.  A total of 822 participants completed questionnaires correctly. (response rate of 95.80% ). The overall prevalence of GAD and depressive symptoms were 33.73%, and 29.35%, respectively. More times (hours) to focus on the COVID-19 (OR=1.215, 95%CI:1.061-1.391), family members (that is, HCWs) directly contact with confirmed or suspected COVID-19 patients (OR=1.477, 95%CI:1.069-2.040) were risk factors for GAD, while higher participants self-reported safety score for protective equipment of HCWs (OR=0.807, 95%CI:0.700-0.930) was a protective factor. More times (hours) to focus on the COVID-19 (OR=1.215, 95%CI:1.061-1.391), longer average working times per week for family members (that is, HCWs) (OR=1.017, 95%CI:1.005-1.029), being parents and other next of kin of HCWs were risk factors for depressive symptoms (OR=3.526, 95%CI:1.609-7.728 and OR=1.639, 95%CI:1.096-2.451, respectively). In addition, compared with participants who were HCWs, participants who were enterprise workers and were more likely to develop depressive symptoms(OR=1.750, 95%CI:1.104-2.776), while who were government employees or institutions employees were less likely to suffer depressive symptoms (OR=0.529, 95%CI:0.286-0.977).  Psychological responses to COVID-19 have been dramatic among family members of HCWs during the rising phase of the outbreak. Our findings provide strong evidence to pay more attention on the mental health status of this vulnerable but often unseen populations during COVID-19 epidemic.

title: COVID-19 in England: spatial patterns and regional outbreaks
abstract: to investigate the spatiotemporal distribution of COVID-19 cases in England; to provide spatial quantification of risk at a high resolution; to provide information for prospective antigen and serological testing.  We fit a spatiotemporal Negative Binomial generalised linear model to Public Health England SARS-CoV-2 testing data at the Lower Tier Local Authority region level. We assume an order-1 autoregressive model for case progression within regions, coupling discrete spatial units via observed commuting data and time-varying measures of traffic flow. We fit the model via maximum likelihood estimation in order to calculate region-specific risk of ongoing transmission, as well as measuring regional uncertainty in incidence.  We detect marked heterogeneity across England in COVID-19 incidence, not only in raw estimated incidence, but in the characteristics of within-region and between-region dynamics of PHE testing data. There is evidence for a spatially diverse set of regions having a higher daily increase of cases than others, having accounted for current case numbers, population size, and human mobility. Uncertainty in model estimates is generally greater in rural regions.  A wide range of spatial heterogeneity in COVID-19 epidemic distribution and infection rate exists in England currently. Future work should incorporate fine-scaled demographic and health covariates, with continued improvement in spatially-detailed case reporting data. The method described here may be used to measure heterogeneity in real-time as behavioural and social interventions are relaxed, serving to identify "hotspots" of resurgent cases occurring in diverse areas of the country, and triggering locally-intensive surveillance and interventions as needed.  There is general concern over the ability of PHE testing data to capture the true prevalence of infection within the population, though this approach is designed to provide measures of spatial prevalence based on testing that can be used to guide further future testing effort. Now-casts of epidemic characteristics are presented based on testing data alone (as opposed to "true" prevalence in any one area). The model used in this analysis is phenomenological for ease and speed of principled parameter inference; we choose the model which best fits the current spatial case timeseries, without attempting to enforce "SIR"-type epidemic dynamics.

title: Ongoing outbreak of COVID-19 in Iran: challenges and signs of concern
abstract: Since the first outbreak in China, the Coronavirus Disease 2019 (COVID-19) has rapidly spread around the world. Iran was one of the first countries outside of China to report infections with COVID-19. With nearly 100 exported cases to various other countries, it has since been the epicentre of the outbreak in the Middle east. By examining the age-stratified COVID-19 case fatality rates across the country and 14 university hospitals in Tehran, we find that, in younger age groups, the reported cases on 13/03/2020 only capture less than 10% of symptomatic cases in the population. This indicates significant levels of under-reporting in Iran. Using the 18 full-genome sequences from cases with a travel history or link to Iran, as well as the one full genome sequence obtained from within the country, we estimate the time to the most recent common ancestor of sequences which suggests the likely start of the outbreak on 21/01/2020 (95% HPD: 05/12/2019 - 14/02/2020) with an approximate doubling time of 3.07 (95% HPD: 1.68 - 16.27). Also, based on known exported cases to Oman, Kuwait, Lebanon, and China, we estimate the outbreak size on 25 February and 6 March to be around 13,700 (95% CI: 7,600 - 33,300) and 60,500 (43,200 - 209,200), respectively. Knowing the size of the outbreak at two time points and the typical doubling times associated with the COVID-19 epidemics in countries across Europe and North America, we can independently verify that the likely start of epidemic in Iran is around 15/01/2020 (27/12/2019 - 24/01/2020). Our assessment of the fate of the epidemic based on current levels of non-pharmaceutical interventions implemented by the government suggests upward of 10 million cases (IQR: 6.7M - 18M) and 100,000 ICU beds required (IQR: 77K - 140K) during the peak of the epidemic with more than 100,000 cumulative deaths (IQR: 180K - 240K). We also predict a peak in demand for ICU beds on 21/04/2020 (IQR: 06/04/2020 - 23/05/2020). The large span of the peak of the ICU demand is a result of two separate peaks, with the first occurring at around 15/4/2020 and the second in approximately a months time. The latter is also expected to last longer and is based on the relatively relaxed social distancing measures in place. The exact magnitude and timing of the peaks strictly depends on levels of interventions and can change significantly upon new information or change of policy. We caution that a lack of, or relaxed, stringent intervention measures, during a period of highly under-reported spread, would likely lead to the healthcare system becoming overwhelmed in the next few months.

title: Draft Genome Sequence of the Bordetella bronchiseptica Swine Isolate KM22
abstract: Bordetella bronchiseptica swine isolate KM22 has been used in experimental infections of swine as a model of clinical B. bronchiseptica infections within swine herds and to study host-to-host transmission. Here we report the draft genome sequence of KM22.

title: Changes of CT findings in a 2019 novel coronavirus (2019-nCoV) pneumonia patient

title: Frequency of testing for COVID 19 infection and the presence of higher number of available beds per country predict outcomes with the infection, not the GDP of the country - A descriptive statistical analysis
abstract: The novel coronavirus epidemic which originated in late 2019 from China has wreaked havoc on millions across the world with illness, death and socioeconomic recession. As of now no valid treatment or preventative strategy has evolved worldwide and governments across the world have been forced to take the draconian step of social isolation in communities by enforcing lockdowns.  This study aims to correlate the rates of infection with the novel coronavirus and total deaths as the primary output variable. In addition the strength of association between infection rates and total death in comparison to GDP share of the respective countries, physicians, hospital beds and rates of testing for COVID 19 infection per thousand patients, is being assessed, in a bid to develop a model which would help to develop tools to reduce the impact of this disease.  Data relating to number of cases, severity, cases recovered and deaths worldwide and specifically for the top six countries affected was collected from the WHO COVID-19 situation report which is being updated on a daily basis till 22nd March 2020, the date of analysis. Additional data related to GDP, physician and hospital bed per 1000 patients were procured from the World Bank database. All data were collected in a file in CSV format. Analysis was conducted in Jupyter notebook with Python 3.8.2 software and also with XL-Stat statistical software for excel. The analytical strategy was descriptive with no inferential overtones.  COVID 19 infection strongly correlates with total deaths (r : 0.89), with a predicted death rate of 25 patients per 1000 affected. There was no correlation between the GDP growth of the country and number of treating physicians/1000 patient population with any COVID 19 related outcome. However there was a negative correlation between COVID 19-related deaths and the number of beds available per 1000 population [r=-0.34]. Importantly there is an inverse correlation between the number of tests conducted per million population with the rates of active infections [r=-0.12] , new cases [r=-0.38] and new deaths [r=-0.28] in COVID 19.  This is the first study to assess parameters other than age and sex and sets out a robust dataset which indicates an increased risk of worsening outcomes with lesser number of beds and testing, suggesting that the need of the hour is to increase available bed numbers and to increase rates of testing.

title: A Laboratory Risk Assessment during the Coronavirus (COVID-19) Pandemic

title: Laboratory practices to mitigate biohazard risks during the COVID-19 outbreak: an IFCC global survey
abstract: A global survey was conducted by the IFCC Task Force on COVID-19 to better understand how general biochemistry laboratories manage the pre-analytical, analytical and post-analytical processes to mitigate biohazard risks during the coronavirus disease 2019 (COVID-19) pandemic.  An electronic survey was developed to record the general characteristics of the laboratory, as well as the pre-analytical, analytical, post-analytical and operational practices of biochemistry laboratories that are managing clinical samples of patients with COVID-19.  A total of 1210 submissions were included in the analysis. The majority of responses came from hospital central/core laboratories that serve hospital patient groups and handle moderate daily sample volumes. There has been a decrease in the use of pneumatic tube transport, increase in hand delivery and increase in number of layers of plastic bags for samples of patients with clinically suspected or confirmed COVID-19. Surgical face masks and gloves are the most commonly used personal protective equipment (PPE). Just >50% of the laboratories did not perform an additional decontamination step on the instrument after analysis of samples from patients with clinically suspected or confirmed COVID-19. A fifth of laboratories disallowed add-on testing on these samples. Less than a quarter of laboratories autoclaved their samples prior to disposal.  The survey responses showed wide variation in pre-analytical, analytical and post-analytical practices in terms of PPE adoption and biosafety processes. It is likely that many of the suboptimal biosafety practices are related to practical local factors, such as limited PPE availability and lack of automated instrumentation.

title: Prevalence of Gastrointestinal Symptoms and Fecal Viral Shedding in Patients With Coronavirus Disease 2019: A Systematic Review and Meta-analysis
abstract: Coronavirus disease 2019 (COVID-19) is a global pandemic and can involve the gastrointestinal (GI) tract, including symptoms like diarrhea and shedding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in feces.  To provide a pooled estimate of GI symptoms, liver enzyme levels outside reference ranges, and fecal tests positive for SARS-CoV-2 among patients with COVID-19.  An electronic literature search was performed for published (using MEDLINE/PubMed and Embase) and  (using bioRxiv and medRxiv) studies of interest conducted from November 1, 2019, to March 30, 2020. Search terms included “COVID-19,” “SARS-Cov-2,” and/or “novel coronavirus.”  Eligible studies were those including patients with SARS-CoV-2 infection who reported GI symptoms.  Data on patients with GI symptoms (ie, diarrhea, nausea, or vomiting), liver enzyme level changes, and fecal shedding of virus were extracted. Quality of studies was examined using methodological index for nonrandomized studies. Pooled estimates (%) were reported with 95% CIs with level of heterogeneity (I(2)).  Study and patient characteristics with pooled detection rates for diarrhea, nausea or vomiting, liver enzyme levels outside reference ranges, and SARS-CoV-2 positivity in feces tests were analyzed.  Of 1484 records reviewed, 23 published and 6  studies were included in the analysis, with a total of 4805 patients (mean [SD] age, 52.2 [14.8] years; 1598 [33.2%] women) with COVID-19. The pooled rates were 7.4% (95% CI, 4.3%-12.2%) of patients reporting diarrhea and 4.6% (95% CI, 2.6%-8.0%) of patients reporting nausea or vomiting. The pooled rate for aspartate aminotransferase levels outside reference ranges was 20% (95% CI, 15.3%-25.6%) of patients, and the pooled rate for alanine aminotransferase levels outside reference ranges was 14.6% (95% CI, 12.8%-16.6%) of patients. Fecal tests that were positive for SARS-CoV-2 were reported in 8 studies, and viral RNA shedding was detected in feces in 40.5% (95% CI, 27.4%-55.1%) of patients. There was high level of heterogeneity (I(2) = 94%), but no statistically significant publication bias noted.  These findings suggest that that 12% of patients with COVID-19 will manifest GI symptoms; however, SAR-CoV-2 shedding was observed in 40.5% of patients with confirmed SARS-CoV-2 infection. This highlights the need to better understand what measures are needed to prevent further spread of this highly contagious pathogen.

title: Molecular and serological investigation of 2019-nCoV infected patients: implication of multiple shedding routes
abstract: In December 2019, a novel coronavirus (2019-nCoV) caused an outbreak in Wuhan, China, and soon spread to other parts of the world. It was believed that 2019-nCoV was transmitted through respiratory tract and then induced pneumonia, thus molecular diagnosis based on oral swabs was used for confirmation of this disease. Likewise, patient will be released upon two times of negative detection from oral swabs. However, many coronaviruses can also be transmitted through oral–fecal route by infecting intestines. Whether 2019-nCoV infected patients also carry virus in other organs like intestine need to be tested. We conducted investigation on patients in a local hospital who were infected with this virus. We found the presence of 2019-nCoV in anal swabs and blood as well, and more anal swab positives than oral swab positives in a later stage of infection, suggesting shedding and thereby transmitted through oral–fecal route. We also showed serology test can improve detection positive rate thus should be used in future epidemiology. Our report provides a cautionary warning that 2019-nCoV may be shed through multiple routes.

title: New Laparoscopic Technique of Hysteropexy for Uterine Retrodisplacement: Bologna Technique.
abstract: To show a new laparoscopic technique of hysteropexy for uterine retrodisplacement (retroversion and/or retroflexion).  Narrated step-by-step explanation of the Bologna hysteropexy technique using descriptive text and an educational video.  Tertiary referred center of minimally invasive gynecology, Sant'Orsola Hospital, Bologna University.  The Bologna hysteropexy is proposed as an additional procedure after surgical laparoscopic interventions for benign gynecologic disease. The technique consists of 2 semicontinuous absorbable sutures (Biosyn monofilament no. 1 [Covidien, Mansfield, MA] with 2/3 inch diameter needle, 36 mm) suspending the uterus to the anterior abdominal wall, through the plication and shortening of round ligaments. A knot is tied intracorporeally between the 2 free ends of the semicontinuous sutures, drawing a V shape figure and resulting in uterine ventrosuspension.  The Bologna technique hysteropexy is simple and quick to perform. It is effective in suspending the uterus in anteverted and anteflexed positions at 6-month ultrasound follow-up. No perioperative complications were recorded. It can be done with a standard surgical suture-passer and does not add additional cost to surgery. Furthermore, an absorbable suture is desirable for fertile women.

title: Test, test, test for COVID-19 antibodies: the importance of sensitivity, specificity and predictive powers
abstract: SARS-CoV-2 antibody tests of varying specificity and sensitivity are now available. For informing individuals whether they have had COVID-19, they need to be very accurate. For measuring population prevalence of past infection, the numbers of false positives and negatives need to be roughly equal. With a series of worked examples for a notional population of 100,000 people, we show that even test systems with a high specificity can yield a large number of false positive results, especially where the population prevalence is low. For example, at a true population prevalence of 5%, using a test with 99% sensitivity and specificity, 16% of positive results will be false and thus 950 people will be incorrectly informed they have had the infection. Further confirmatory testing may be needed. Giving false reassurance upon which personal or societal decisions might be based could be harmful for individuals, undermine public confidence and foster further outbreaks.

title: Antibody tests for identification of current and past infection with SARS-CoV-2.
abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection.  To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys.  We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020.  We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria).  We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs).  We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands.  The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.

title: Sterile Parts of Operating Gown during Lower Limb Joint Replacement Surgery.
abstract: The prevention of surgical site infection is one of the most concerning issues in operating rooms. Surgical gowns are worn as one of the intraoperative strategies for infection prevention. The present study investigated whether the gowns remained sterile during the surgical procedure. Furthermore, this study examined which parts of the surgical gown were more prone to contamination.  The sterility of the gowns was investigated during eight total joint arthroplasties all of which were performed by four surgeons. The samples were taken from the arms and frontal part of the sterile gowns pre- and postoperatively. In the anterior surface of the gown, the sampling was initiated at a strip with 50 cm height from the ground followed by the strips with 15 cm distances from caudal to cephalad. Furthermore, the frontal part of the gown was divided into three parts in relation to the operating room table. Finally, the contamination rate was evaluated in each part. A semiquantitative method was used for the analysis of bacterial culture.  Before the operation, there were four samples tested positive for bacterial culture (1.06%). All of these samples were taken from the most proximal strip near the neckline. After the surgery, the rate of contamination in the strips on the frontal part of the gown was reported as 3.1% to 53%. Based on the operating table, the contamination rate was 35.9%, 8.9%, and 47.3% in the distal, middle, and proximal parts of the gown, respectively. The contamination rate at the elbow crease was 23%, and at 5 and 10 cm above the creases were 24% and 36%, respectively.  The high rate of gown contamination during the operation is concerning. However, part of the gown that was in contact with the operating room table remained clean most of the time. More safe strategies should be used for infection prevention in operating rooms.

title: Estimation of local novel coronavirus (COVID-19) cases in Wuhan, China from off-site reported cases and population flow data from different sources
abstract: In December 2019, a novel coronavirus (COVID-19) pneumonia hit Wuhan, Hubei Province, China and spread to the rest of China and overseas. The emergence of this virus coincided with the Spring Festival Travel Rush in China. It is possible to estimate total number of cases of COVID-19 in Wuhan, by 23 January 2020, given the cases reported in other cities and population flow data between cities.  We built a model to estimate the total number of cases in Wuhan by 23 January 2020, based on the number of cases detected outside Wuhan city in China, with the assumption that if the same screening effort used in other cities applied in Wuhan. We employed population flow data from different sources between Wuhan and other cities/regions by 23 January 2020. The number of total cases was determined by the maximum log likelihood estimation.  From overall cities/regions data, we predicted 1326 (95% CI: 1177, 1484), 1151 (95% CI: 1018, 1292) and 5277 (95% CI: 4732, 5859) as total cases in Wuhan by 23 January 2020, based on different source of data from Changjiang Daily newspaper, Tencent, and Baidu. From separate cities/regions data, we estimated 1059 (95% CI: 918, 1209), 5214 (95% CI: 4659, 5808) as total cases in Wuhan in Wuhan by 23 January 2020, based on different sources of population flow data from Tencent and Baidu.  Sources of population follow data and methods impact the estimates of local cases in Wuhan before city lock down. Keyword: COVID-19; mobility; pneumonia; transportation; outbreaks

title: Coronavirus disease (COVID-19) Community Testing Team in Scotland: A 14-day review, 6 to 20 February 2020
abstract: In response to the outbreak of COVID-19, we set up a team to carry out sampling in the community. This enabled individuals to remain in self-isolation in their own homes and to prevent healthcare settings and services from being overwhelmed by admissions for sampling of suspected cases. There is evidence that this is a cost effective, safe and necessary service to complement COVID-19 testing in hospitals.

title: Now-casting the COVID-19 epidemic: The use case of Japan, March 2020
abstract: Reporting delays in disease surveillance impair the ability to assess the current dynamic of an epidemic. In continuously updated epidemic curves, case numbers for the most recent epidemic week or day usually appear to be lower than the previous, suggesting a decline of the epidemic. In reality, the epidemic curve may still be on the rise, because reporting delay prevents the most recent cases to appear in the case count. In context of the COVID-19 epidemic and for countries planning large international gatherings, such as the Summer Olympic Games in Japan 2020, the ability to assess the actual stage of an epidemic is of outmost importance.  We applied now-casting onto COVID-19 data provided by the nCoV-2019 Data Working Group to evaluate the .true count of cases, by taking into account reporting delays occurring between date of symptom onset and date of confirmation.  We calculated a decrease of reporting delay, from a median delay of ten days in calendar week four 2020 to six days in calendar week eight, resulting in an overall mean of 4.3 days. The confidence intervals of the now-casting indicated an increase of cases in the last reporting days, while case country in that same time period suggested a decline.  As a specific use case this tool may be of particular value for the challenging risk assessment and risk communication in the context of the Summer Olympic Games in Japan 2020 and similar situations elsewhere.

title: Venous Thromboembolism Complicated with COVID-19: What Do We Know So Far?
abstract: Coronavirus disease (COVID-19) is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is responsible for the ongoing 2019–2020 pandemic. Venous thromboembolism (VTE), a frequent cardiovascular and/or respiratory complication among hospitalized patients, is one of the known sequelae of the illness. Hospitalized COVID-19 patients are often elderly, immobile, and show signs of coagulopathy. Therefore, it is reasonable to assume a high incidence of VTE among these patients. Presently, the incidence of VTE is estimated at around 25% of patients hospitalized in the intensive care unit for COVID-19 even under anticoagulant treatment at prophylactic doses. In this review, we discuss present knowledge of the topic, the unique challenges of diagnosis and treatment of VTE, as well as some of the potential mechanisms of increased risk for VTE during the illness. Understanding the true impact of VTE on patients with COVID-19 will potentially improve our ability to reach a timely diagnosis and initiate proper treatment, mitigating the risk for this susceptible population during a complicated disease.

title: 2019-nCoV: The Identify-Isolate-Inform (3I) Tool Applied to a Novel Emerging Coronavirus
abstract: 2019 Novel Coronavirus (2019-nCoV) is an emerging infectious disease closely related to MERS-CoV and SARS-CoV that was first reported in Wuhan City, Hubei Province, China in December 2019. As of January 2020, cases of 2019-nCoV are continuing to be reported in other Eastern Asian countries as well as in the United States, Europe, Australia, and numerous other countries. An unusually high volume of domestic and international travel corresponding to the beginning of the 2020 Chinese New Year complicated initial identification and containment of infected persons. Due to the rapidly rising number of cases and reported deaths, all countries should be considered at risk of imported 2019-nCoV. Therefore, it is essential for prehospital, clinic, and emergency department personnel to be able to rapidly assess 2019-nCoV risk and take immediate actions if indicated. The Identify-Isolate-Inform (3I) Tool, originally conceived for the initial detection and management of Ebola virus and later adjusted for other infectious agents, can be adapted for any emerging infectious disease. This paper reports a modification of the 3I Tool for use in the initial detection and management of patients under investigation for 2019-nCoV. After initial assessment for symptoms and epidemiological risk factors, including travel to affected areas and exposure to confirmed 2019-nCoV patients within 14 days, patients are classified in a risk-stratified system. Upon confirmation of a suspected 2019-nCoV case, affected persons must immediately be placed in airborne infection isolation and the appropriate public health agencies notified. This modified 3I Tool will assist emergency and primary care clinicians, as well as out-of-hospital providers, in effectively managing persons with suspected or confirmed 2019-nCoV.

title: Estimating the Early Outbreak Cumulative Incidence of COVID-19 in the United States: Three Complementary Approaches
abstract: Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the weekly incidence of COVID-19. Unfortunately, a lack of systematic testing across the United States (US) due to equipment shortages and varying testing strategies has hindered the usefulness of the reported positive COVID-19 case counts. We introduce three complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 during the early outbreak in each state in the US as well as in New York City, using a combination of excess influenza-like illness reports, COVID-19 test statistics, and COVID-19 mortality reports. Instead of relying on an estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our three approaches, there is a consistent conclusion that estimated state-level COVID-19 symptomatic case counts from March 1 to April 4, 2020 varied from 5 to 50 times greater than the official positive test counts. Nationally, our estimates of COVID-19 symptomatic cases in the US as of April 4 have a likely range of 2.2 to 5.1 million cases, with possibly as high as 8.1 million cases, up to 26 times greater than the cumulative confirmed cases of about 311,000. Extending our method to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 6.0 to 12.2 million, which compares with 1.5 million positive test counts. Our approaches demonstrate the value of leveraging existing influenza-like-illness surveillance systems during the flu season for measuring the burden of new diseases that share symptoms with influenza-like-illnesses. Our methods may prove useful in assessing the burden of COVID-19 during upcoming flu seasons in the US and other countries with comparable influenza surveillance systems.

title: Current knowledge, attitude and behaviour of hand and food hygiene in a developed residential community of Singapore: a cross-sectional survey
abstract: Diarrhoea incidence has been increasing progressively over the past years in developed countries, including Singapore, despite the accessibility and availability to clean water, well-established sanitation infrastructures and regular hygiene promotion. The aim of this study is to determine the current knowledge, attitude and behaviour of hand and food hygiene, and the potential risk factors of diarrhoea in a residential community of Singapore.  A cross-sectional study was conducted within a residential area in the west of Singapore from June to August 2013. A total of 1,156 household units were randomly sampled and invited to participate in an interviewer-assisted survey using standardised questionnaires. Descriptive, univariate and multivariate analyses were performed using descriptive statistics, Fisher’s Exact test and multivariate logistic regression modelling, respectively. R program was used for all statistical analysis. All tests were conducted at 5 % level of significance with 95 % confidence intervals (CI) reported where applicable.  A total of 240 units (20.8 %) consented and responded to the survey invitation. About 77 % of the expected knowledge and attitude were observed in at least 80 % of the participants, compared to only about 31 % of the expected behaviours and practises. Being single [adjusted odds ratio (AOR) = 2.29; 95 % CI = 1.16-4.48], having flu in the past six month (AOR = 3.24; 95 % CI = 1.74-6.06), preferred self-medication (AOR = 2.07; 95 % CI = 1.06–4.12) were risk factors of diarrhoea. Washing hands with water before attending to children or sick persons (AOR = 0.30; 95 % CI = 0.11–0.82), washing hands with water (AOR = 0.16; 95 % CI = 0.05–0.45) and water with soap (AOR = 0.29; 95 % CI = 0.12–0.72) after attending to children or sick persons, and hand washing between 30 s to a minute (AOR = 0.44; 95 % CI = 0.20-0.90) were protective factors against diarrhoea.  Good knowledge and attitude of the participants did not positively translate into high compliance and motivation to perform good hygiene practices. This observation may have resulted in a significant extent on the increasing diarrhoea incidences. Current interventions may be improved with more active community partnership among the residents, schools and the relevant social organizations, to raise awareness on the importance of compliance to good hygiene practices, and the risk factors of diarrhoea. A large case–control study would be required to validate these findings in future.  contains supplementary material, which is available to authorized users.

title: Coronavirus disease 2019 during pregnancy: a systematic review of reported cases
abstract: This study aimed to conduct a systematic review of the clinical outcomes reported for pregnant patients with coronavirus disease 2019.  The PubMed, CINAHL, and Scopus databases were searched using a combination of key words such as "Coronavirus and/or pregnancy," "COVID and/or pregnancy," "COVID disease and/or pregnancy," and "COVID pneumonia and/or pregnancy." There was no restriction of language to allow collection of as many cases as possible.  All studies of pregnant women who received a coronavirus disease 2019 diagnosis using acid nucleic test, with reported data about pregnancy, and, in case of delivery, reported outcomes, were included.  All the studies included have been evaluated according to the tool for evaluating the methodological quality of case reports and case series described by Murad et al.  Six studies that involved 51 pregnant women were eligible for the systematic review. At the time of the report, 3 pregnancies were ongoing; of the remaining 48 pregnant women, 46 gave birth by cesarean delivery, and 2 gave birth vaginally; in this study, 1 stillbirth and 1 neonatal death were reported.  Although vertical transmission of severe acute respiratory syndrome coronavirus 2 infection has been excluded thus far and the outcome for mothers and neonates has been generally good, the high rate of preterm delivery by cesarean delivery is a reason for concern. Cesarean delivery was typically an elective surgical intervention, and it is reasonable to question whether cesarean delivery for pregnant patients with coronavirus disease 2019 was warranted. Coronavirus disease 2019 associated with respiratory insufficiency in late pregnancies certainly creates a complex clinical scenario.

title: Determination of daily reproduction numbers of SARS-CoV2 based on death cases suggests more rapid initial spread in Italy and the United States
abstract: Population density, behaviour and cultural habits strongly influence the spread of pathogens. Consequently, key epidemiological parameters may vary from country to country. Confirmed COVID-19 cases in in China have been used to estimate those parameters, that vary largely (reviewed in 1). The estimates also depend on testing frequency and case definitions that are prone to change during ongoing epidemics, providing additional uncertainties. The rise in fatal cases due to SARS-CoV2 could be a more reliable parameter, since missing of deaths is less likely. In the absence of changes in the management of severe COVID-19 cases, the rise in death cases should be proportional to the rise in virus infections. Although the fluctuating low numbers of fatal cases very early in the epidemic may lead to some uncertainty, more than 100 deaths per day are reported since 10.03.2020 in Italy and since 21.03.2020 in the US. Therefore, the dynamics of deaths were analysed to estimate the daily reproduction numbers (Rt) and the effectiveness of control measures. Thus, our analysis provides evidence that basic epidemiological parameters differ between countries to an extent compromising epidemiological predictions of the pandemic. It also suggests that suppression of spread in Italy and the US may be more difficult to achieve. Although we assume that variations in social behaviour are responsible for the different estimates of R0, selection of more rapidly spreading variants of SARS-CoV-2 cannot be excluded. Despite uncertainty in the reliability of the data used and lack of information on possible changes in the effectiveness of registration of COVID-19 deaths during the observation period, our findings should be considered as a working hypothesis demanding further investigations. As the number of deaths rapidly increases worldwide, we encourage more sophisticated modelling of the epidemic based on the dynamics of death cases by experts in the field.

title: Unknown unknowns – COVID-19 and potential global mortality
abstract: COVID-19 (SARS-CoV-2) is currently a global pandemic. This paper will attempt to estimate global infection rates and potential resultant mortality in the absence of effective treatment and/or vaccination. Calculations are based on World Health Organisation data from Wuhan in China: 14% of infected cases are severe, 5% require intensive care and 4% die. Estimated infection rates and mortality rates at the level of continents and some individual countries (when these are of sufficient size) are tabulated. This pandemic may cause close to half a billion deaths, i.e. 6% of the global population – and potentially more. At the risk of sounding sensational, but with a sober sense of realism, healthcare risks being plunged into the Middle-Ages if the public do not do their part. Infection cannot occur in the absence of contact. The only way to mitigate these numbers is to apply social distancing and take the standard precautions so frequently reiterated by Public Health: hand washing, avoid touching the face and so on. These measures are crucial as the human cost is going to be unthinkable even in the best-case scenarios that epidemiologists are modelling.

title: Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example
abstract: During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy. Motivated by the ongoing response to COVID-19, we provide a toolkit of statistical and mathematical models beyond the simple SIR-type differential equation models for analysing the early stages of an outbreak and assessing interventions. In particular, we focus on parameter estimation in the presence of known biases in the data, and the effect of non-pharmaceutical interventions in enclosed subpopulations, such as households and care homes. We illustrate these methods by applying them to the COVID-19 pandemic.

title: Persons Evaluated for 2019 Novel Coronavirus — United States, January 2020
abstract: In December 2019, a cluster of cases of pneumonia emerged in Wuhan City in central China's Hubei Province. Genetic sequencing of isolates obtained from patients with pneumonia identified a novel coronavirus (2019-nCoV) as the etiology (1). As of February 4, 2020, approximately 20,000 confirmed cases had been identified in China and an additional 159 confirmed cases in 23 other countries, including 11 in the United States (2,3). On January 17, CDC and the U.S. Department of Homeland Security's Customs and Border Protection began health screenings at U.S. airports to identify ill travelers returning from Wuhan City (4). CDC activated its Emergency Operations Center on January 21 and formalized a process for inquiries regarding persons suspected of having 2019-nCoV infection (2). As of January 31, 2020, CDC had responded to clinical inquiries from public health officials and health care providers to assist in evaluating approximately 650 persons thought to be at risk for 2019-nCoV infection. Guided by CDC criteria for the evaluation of persons under investigation (PUIs) (5), 210 symptomatic persons were tested for 2019-nCoV; among these persons, 148 (70%) had travel-related risk only, 42 (20%) had close contact with an ill laboratory-confirmed 2019-nCoV patient or PUI, and 18 (9%) had both travel- and contact-related risks. Eleven of these persons had laboratory-confirmed 2019-nCoV infection. Recognizing persons at risk for 2019-nCoV is critical to identifying cases and preventing further transmission. Health care providers should remain vigilant and adhere to recommended infection prevention and control practices when evaluating patients for possible 2019-nCoV infection (6). Providers should consult with their local and state health departments when assessing not only ill travelers from 2019-nCoV-affected countries but also ill persons who have been in close contact with patients with laboratory-confirmed 2019-nCoV infection in the United States.

title: Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem
abstract: As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.

title: Detection and genetic characterization of kobuvirus in cats: The first molecular evidence from Northeast China
abstract: Feline kobuvirus (FeKoV), a novel picornavirus of the genus kobuvirus, was initially identified in the feces of cats with diarrhea in South Korea in 2013. To date, there is only one report of the circulation of kobuvirus in cats in southern China. To investigate the presence and genetic variability of FeKoV in northeast China, 197 fecal samples were collected from 105 cats with obvious diarrhea and 92 asymptomatic cats in Shenyang, Jinzhou, Changchun, Jilin and Harbin regions, Northeast China, and viruses were detected by RT-PCR with universal primers targeting all kobuviruses. Kobuvirus was identified in 28 fecal samples with an overall prevalence of 14.2% (28/197) of which 20 samples were co-infected with feline parvovirus (FPV) and/or feline bocavirus (FBoV). Diarrhoeic cats had a higher kobuvirus prevalence (19.1%, 20/105) than asymptomatic cats (8.7%, 8/92). By genetic analysis based on partial 3D gene, all kobuvirus-positive samples were more closely related to previous FeKoV strains with high identities of 90.5%–97.8% and 96.6%–100% at the nucleotide and amino acid levels. Additionally, phylogenetic analysis based on the complete VP1 gene indicated that all FeKoV strains identified in this study were placed into a cluster, which separated from other reference strains previously reported, and three identical amino acid substitutions were present at the C-terminal of the VP1 protein for these FeKoV strains. Furthermore, two complete FeKoV polyprotein genomes were successfully obtained from two positive samples and designated 16JZ0605 and 17CC0811, respectively. The two strains shared 92.9%–94.9% nucleotide identities and 96.8%–98.4% amino acid identities to FeKoV prototype strains. Phylogenetic analysis indicated that FeKoVs were clustered according to their geographical regions, albeit with limited sequences support. This study provides the first molecular evidence that FeKoV circulates in cats in northeast China, and these FeKoVs exhibit genetic diversity and unique evolutionary trend.

title: Recognizing COVID-19-related myocarditis: the possible pathophysiology and proposed guideline for diagnosis and management
abstract: Human coronavirus-associated myocarditis is known, and a number of COVID-19-related myocarditis cases have been reported. The pathophysiology of COVID-19-related myocarditis is thought to be a combination of direct viral injury and cardiac damage due to the host’s immune response. COVID-19 myocarditis diagnosis should be guided by insights from previous coronavirus and other myocarditis experience. The clinical findings include changes in ECG, cardiac biomarkers, and impaired cardiac function. When cardiac MRI is infeasible, cardiac CT angiography with delayed myocardial imaging may serve to exclude significant coronary artery disease and identify myocardial inflammatory patterns. Because many COVID-19 patients have cardiovascular comorbidities, myocardial infarction should be considered. Where the diagnosis remains uncertain, an endomyocardial biopsy may help identify active cardiac infection through viral genome amplification and possibly refine the treatment risks of systemic immunosuppression. Arrhythmias are not uncommon in the COVID-19 patients; however, its pathophysiology is still speculative. Nevertheless, clinicians should be vigilant to provide prompt monitoring and treatments. The long-term impact of COVID-19 myocarditis, including in the majority of mild cases remains unknown.

title: The relationship of COVID-19 severity with cardiovascular disease and its traditional risk factors: A systematic review and meta-analysis
abstract: Whether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex.  We performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data (≥10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses.  Of the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >~5 in >60-65 vs. <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR=1.73, [95%CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ~2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19.  Despite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be used to inform objective decisions on COVID-19 testing, clinical management, and workforce planning.

title: A cascade of causes that led to the COVID-19 tragedy in Italy and in other European Union countries

title: How Does COVID-19 impact Students with Disabilities/Health Concerns?
abstract: The impact of COVID-19 on students has been enormous, with an increase in worries about fiscal and physical health, a rapid shift to online learning, and increased isolation. In addition to these changes, students with disabilities/health concerns may face accessibility problems with online learning or communication tools, and their stress may be compounded by additional risks such as financial stress or pre-existing conditions. To our knowledge, no one has looked specifically at the impact of COVID-19 on students with disabilities/health concerns. In this paper, we present data from a survey of 147 students with and without disabilities collected in late March to early April of 2020 to assess the impact of COVID-19 on these students' education and mental health. Our findings show that students with disabilities/health concerns were more concerned about classes going online than their peers without disabilities. In addition, students with disabilities/health concerns also reported that they have experienced more COVID-19 related adversities compared to their peers without disabilities/health concerns. We argue that students with disabilities/health concerns in higher education need confidence in the accessibility of the online learning tools that are becoming increasingly prevalent in higher education not only because of COVID-19 but also more generally. In addition, educational technologies will be more accessible if they consider the learning context, and are designed to provide a supportive, calm, and connecting learning environment.

title: Informational needs assessment of non‐Hodgkin lymphoma survivors and their physicians

title: Perceptions of Occupational Risk and Changes in Clinical Practice of U.S. Vitreoretinal Surgery Fellows during the COVID-19 Pandemic
abstract: To assess perceptions of occupational risk and changes to clinical practice of ophthalmology trainees in the United States during the COVID-19 pandemic.  An anonymous, non-validated, cross-sectional survey was conducted online. Data was collected from April 7-16, 2020. Participants 2019-2020 second year U.S. vitreoretinal surgery fellows in two-year vitreoretinal surgery training programs were invited to participate. Intervention Online survey.  Survey questions assessed policies guiding COVID-19 response, known or suspected exposure to SARS-CoV-2, changes in clinical duties and volume, and methods to reduce occupational risk including availability of personal protective equipment.  Completed responses were obtained from 62 of 87 eligible recipients (71.2% response rate). Training settings included academic (58.1%), hybrid academic/private practice (35.5%), and private practice only settings (6.5%). Overall, 19.4% of respondents reported an exposure to a COVID-19 positive patient, 14.5% reported self-quarantining due to possible exposure, and 11.3% reported being tested for COVID-19. In regards to PPE, N95 masks were available in the emergency room (n=40, 64.5%), office (n=35, 56.5%), and operating room settings (n=35, 56.5%). Perceived comfort level with PPE recommendations was significantly associated with availability of an N95 respirator mask in the clinic (p<0.001), emergency room (p<0.001) or operating room (p=0.002) settings. Additional risk mitigation methods outside of PPE were: reduction in patient volume (n=62, 100%), limiting patient companions (n=59, 95.2%), use of a screening process (n=59, 95.2%), use of a slit lamp face shield (n=57, 91.9%), temperature screening of all persons entering clinical space (n=34, 54.84%), and placement of face mask on patients (n=33, 53.2%). Overall, 16.1% reported additional clinical duties within the scope of ophthalmology, and 3.2% reported being re-deployed to non-ophthalmology services. 98.4% of respondents expected a reduction in surgical case volume. No respondents reported loss of employment or reduction in pay or benefits due to COVID-19.  Suspected or confirmed clinical exposure to COVID-19 positive patients occurred in approximately one-fifth of trainee respondents. Perceived comfort level with PPE standards was significantly associated with N95 respirator mask availability. As surgical training programs grapple with the COVID-19 pandemic, analysis of trainees’ concerns may inform development of mitigation strategies.

title: Characteristics and outcomes of pregnant women hospitalised with confirmed SARS-CoV-2 infection in the UK: a national cohort study using the UK Obstetric Surveillance System (UKOSS)
abstract: To describe a national cohort of pregnant women hospitalised with SARS-CoV-2 infection in the UK, identify factors associated with infection and describe outcomes, including transmission of infection, for mother and infant.  Prospective national population-based cohort study using the UK Obstetric Surveillance System (UKOSS).  All 194 obstetric units in the UK Participants: 427 pregnant women admitted to hospital with confirmed Sars-CoV-2 infection between 01/03/2020 and 14/04/2020. 694 comparison women who gave birth between 01/11/2017 and 31/10/2018.  Incidence of maternal hospitalisation, infant infection. Rates of maternal death, level 3 critical care unit admission, preterm birth, stillbirth, early neonatal death, perinatal death; odds ratios for infected versus comparison women.  Estimated incidence of hospitalisation with confirmed SARS-CoV-2 in pregnancy 4.9 per 1000 maternities (95%CI 4.5-5.4). The median gestation at symptom onset was 34 weeks (IQR 29-38). Black or other minority ethnicity (aOR 4.49, 95%CI 3.37-6.00), older maternal age (aOR 1.35, 95%CI 1.01-1.81 comparing women aged 35+ with those aged 30-34), overweight and obesity (aORs 1.91, 95%CI 1.37-2.68 and 2.20, 95%CI 1.56-3.10 respectively compared to women with a BMI<25kg/m2) and pre-existing comorbidities (aOR 1.52, 95%CI 1.12-2.06) were associated with admission with SARS-CoV-2 during pregnancy. 247 women (58%) gave birth or had a pregnancy loss; 180 (73%) gave birth at term. 40 (9%) hospitalised women required respiratory support. Twelve infants (5%) tested positive for SARS-CoV-2 RNA, six of these infants within the first 12 hours after birth.  The majority of pregnant women hospitalised with SARS-CoV-2 were in the late second or third trimester, supporting guidance for continued social distancing measures in later pregnancy. Most had good outcomes and transmission of SARS-CoV-2 to infants was uncommon. The strong association between admission with infection and black or minority ethnicity requires urgent investigation and explanation.

title: Reorganization of Medical Oncology Departments during COVID-19 Pandemic: a Nationwide Italian Survey
abstract: The novel severe acute respiratory syndrome coronavirus-2 (SARSCoV-2) pandemic is a global health problem, which started to affect China by the end of year 2019. In Europe, Italy has faced this novel disease entity (named COVID-19) first and severely. COVID-19 represents a significant hurdle for public health services and a potential harm for patients with cancer. The Collegio Italiano dei Primari Oncologi Medici (CIPOMO) is an Italian association of head physicians in oncology departments, which promotes working and research activities in oncology on a national basis. In the midst of the epidemic in Italy, the CIPOMO promoted a national survey aiming to evaluate the impact of COVID-19 on clinical activity of oncologists and the implementation of containment measures of COVID-19 diffusion. Overall, 122 head physicians participated in this survey, with a homogeneous distribution on the national territory. Results show that the following measures for oncologic patients have been promptly implemented through the whole country: use of protective devices, triage of patients accessing the hospital, delay of non-urgent visits, and use of telemedicine. Results of this survey suggest that Italian oncology departments have promptly set a proactive approach to the actual emergency. Oncologists need to preserve the continuum of care of patients, as the benefit of ensuring a well-delivered anti-cancer treatment plan outweighs the risk of COVID-19 infection. International cooperation is an important starting point, as heavily affected nations can serve as an example to find out ways to safely preserve health activity during pandemic.

title: Estimating unobserved SARS-CoV-2 infections in the United States
abstract: By March 2020, COVID-19 led to thousands of deaths and disrupted economic activity worldwide. As a result of narrow case definitions and limited capacity for testing, the number of unobserved SARS-CoV-2 infections during its initial invasion of the US remains unknown. We developed an approach for estimating the number of unobserved infections based on data that are commonly available shortly after the emergence of a new infectious disease. The logic of our approach is, in essence, that there are bounds on the amount of exponential growth of new infections that can occur during the first few weeks after imported cases start appearing. Applying that logic to data on imported cases and local deaths in the US through March 12, we estimated that 22,876 (95% posterior predictive interval: 7,451 - 53,044) infections occurred in the US by this date. By comparing the model's predictions of symptomatic infections to local cases reported over time, we obtained daily estimates of the proportion of symptomatic infections detected by surveillance. This revealed that detection of symptomatic infections decreased throughout February as exponential growth of infections outpaced increases in testing. Between February 21 and March 12, we estimated an increase in detection of symptomatic infections, which was strongly correlated (median: 0.97, 95% PPI: 0.85 - 0.98) with increases in testing. These results suggest that testing was a major limiting factor in assessing the extent of SARS-CoV-2 transmission during its initial invasion of the US.

title: National Institute for the Infectious Diseases “L. Spallanzani”, IRCCS. Recommendations for COVID-19 clinical management
abstract: On January 9 2020, the World Health Organization (WHO) declared the identification, by Chinese Health authorities, of a novel coronavirus, further classified as SARS-CoV-2 responsible of a disease (COVID-19) ranging from asymptomatic cases to severe respiratory involvement. On March 9 2020, WHO declared COVID-19 a global pandemic. Italy is the second most affected country by COVID-19 infection after China. The “L. Spallanzani” National Institute for the Infectious Diseases, IRCCS, Rome, Italy, has been the first Italian hospital to admit and manage patients affected by COVID-19. Hereby, we show our recommendations for the management of COVID-19 patients, based on very limited clinical evidences; they should be considered as expert opinions, which may be modified according to newly produced literature data.

title: Urologic Surgery and COVID-19: How the Pandemic Is Changing the Way We Operate
abstract: The coronavirus disease 2019 (COVID-19) pandemic has had a global impact on all aspects of health care, including surgical procedures. For urologists, it has affected and will continue to influence how we approach the care of patients preoperatively, intraoperatively, and postoperatively. A risk-benefit assessment of each patient undergoing surgery should be performed during the COVID-19 pandemic based on the urgency of the surgery and the risk of viral illness and transmission. Patients with advanced age and comorbidities have a higher incidence of mortality. Routine preoperative testing and symptom screening is recommended to identify those with COVID-19. Adequate personal protective equipment (PPE) for the surgical team is essential to protect health care workers and ensure an adequate workforce. For COVID-19 positive or suspected patients, the use of N95 respirators is recommended if available. The anesthesia method chosen should attempt to minimize aerosolization of the virus. Negative pressure rooms are strongly preferred for intubation/extubation and other aerosolizing procedures for COVID-19 positive patients or when COVID status is unknown. Although transmission has not yet been shown during laparoscopic and robotic procedures, efforts should be made to minimize the risk of aerosolization. Ultra-low particulate air filters are recommended for use during minimally invasive procedures to decrease the risk of viral transmission. Thorough cleaning and sterilization should be performed postoperatively with adequate time allowed for the operating room air to be cycled after procedures. COVID-19 patients should be separated from noninfected patients at all levels of care, including recovery, to decrease the risk of infection. Future directions will be guided by outcomes and infection rates as social distancing guidelines are relaxed and more surgical procedures are reintroduced. Recommendations should be adapted to the local environment and will continue to evolve as more data become available, the shortage of testing and PPE is resolved, and a vaccine and therapeutics for COVID-19 are developed.

title: The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States
abstract: In March and April 2020, public health authorities in the United States acted to mitigate transmission of and hospitalizations from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). These actions were not coordinated at the national level, which raises the question of what might have happened if they were. It also creates an opportunity to use spatial and temporal variation to measure their effect with greater accuracy.  We combine publicly available data sources on the timing of stay-at-home orders and daily confirmed COVID-19 cases at the county level in the United States (N = 132,048). We then derive from the classic SIR model a two-way fixed-effects model and apply it to the data with controls for unmeasured differences between counties and over time. This enables us to estimate the effect of stay-at-home orders while accounting for local variation in factors like health systems and demographics, and temporal variation in national mitigation actions, access to tests, or exposure to media reports that could influence the course of the disease.  Mean county-level daily growth in COVID-19 infections peaked at 17.2% just before stay-at-home orders were issued. Two way fixed-effects regression estimates suggest that orders were associated with a 3.8 percentage point (95% CI 0.7 to 8.6) reduction in the growth rate after one week and an 8.6 percentage point (3.0 to 14.1) reduction after two weeks. By day 22 the reduction (18.2 percentage points, 12.3 to 24.0) had surpassed the growth at the peak, indicating that growth had turned negative and the number of new daily infections was beginning to decline. A hypothetical national stay-at-home order issued on March 13, 2020 when a national emergency was declared might have reduced cumulative county infections by 62.3%, and might have helped to reverse exponential growth in the disease by April 5.  Although stay-at-home orders impose great costs to society, delayed responses and piecemeal application of these orders generate similar costs without obtaining the full potential benefits suggested by this analysis. The results here suggest that a coordinated nationwide stay-at-home order may have reduced by hundreds of thousands the current number of infections and by thousands the total number of deaths from COVID-19. Future efforts in the United States and elsewhere to control pandemics should coordinate stay-at-home orders at the national level, especially for diseases for which local spread has already occurred and testing availability is delayed. Since stay-at-home orders reduce infection growth rates, early implementation when infection counts are still low would be most beneficial.

title: Association of Vitamin D Deficiency and Treatment with COVID-19 Incidence
abstract: Vitamin D treatment has been found to decrease incidence of viral respiratory tract infection, especially in vitamin D deficiency. It is unknown whether COVID-19 incidence is associated with vitamin D deficiency and treatment.  To examine whether vitamin D deficiency and treatment are associated with testing positive for COVID-19.  Retrospective cohort study Setting: University of Chicago Medicine Participants: Patients tested for COVID-19 from 3/3/2020-4/10/2020. Vitamin D deficiency was defined by the most recent 25-hydroxycholecalciferol <20ng/ml or 1,25-dihydroxycholecalciferol <18pg/ml within 1 year before COVID-19 testing. Treatment was defined by the most recent vitamin D type and dose, and treatment changes between the time of the most recent vitamin D level and time of COVID-19 testing. Vitamin D deficiency and treatment changes were combined to categorize vitamin D status at the time of COVID-19 testing as likely deficient(last-level-deficient/treatment-not-increased), likely sufficient(last-level-not-deficient/treatment-not-decreased), or uncertain deficiency(last-level-deficient/treatment-increased or last-level-not-deficient/treatment-decreased).  The main outcome was testing positive for COVID-19. Multivariable analysis tested whether the most recent vitamin D level and treatment changes after that level were associated with testing positive for COVID-19 controlling for demographic and comorbidity indicators. Bivariate analyses of associations of treatment with vitamin D deficiency and COVID-19 were performed.  Among 4,314 patients tested for COVID-19, 499 had a vitamin D level in the year before testing. Vitamin D status at the time of COVID-19 testing was categorized as likely deficient for 127(25%) patients, likely sufficient for 291(58%) patients, and uncertain for 81(16%) patients. In multivariate analysis, testing positive for COVID-19 was associated with increasing age(RR(age<50)=1.05,p<0.021;RR(age[≥]50)=1.02,p<0.064)), non-white race(RR=2.54,p<0.01) and being likely vitamin D deficient (deficient/treatment-not-increased:RR=1.77,p<0.02) as compared to likely vitamin D sufficient(not-deficient/treatment-not-decreased), with predicted COVID-19 rates in the vitamin D deficient group of 21.6%(95%CI[14.0%-29.2%] ) versus 12.2%(95%CI[8.9%-15.4%]) in the vitamin D sufficient group. Vitamin D deficiency declined with increasing vitamin D dose, especially of vitamin D3. Vitamin D dose was not significantly associated with testing positive for COVID-19.  Vitamin D deficiency that is not sufficiently treated is associated with COVID-19 risk. Testing and treatment for vitamin D deficiency to address COVID-19 warrant aggressive pursuit and study.

title: COVID-19 testing.

title: Generic probabilistic modelling and non-homogeneity issues for the UK epidemic of COVID-19
abstract: Coronavirus COVID-19 spreads through the population mostly based on social contact. To gauge the potential for widespread contagion, to cope with associated uncertainty and to inform its mitigation, more accurate and robust modelling is centrally important for policy making. We provide a flexible modelling approach that increases the accuracy with which insights can be made. We use this to analyse different scenarios relevant to the COVID-19 situation in the UK. We present a stochastic model that captures the inherently probabilistic nature of contagion between population members. The computational nature of our model means that spatial constraints (e.g., communities and regions), the susceptibility of different age groups and other factors such as medical pre-histories can be incorporated with ease. We analyse different possible scenarios of the COVID-19 situation in the UK. Our model is robust to small changes in the parameters and is flexible in being able to deal with different scenarios. This approach goes beyond the convention of representing the spread of an epidemic through a fixed cycle of susceptibility, infection and recovery (SIR). It is important to emphasise that standard SIR-type models, unlike our model, are not flexible enough and are also not stochastic and hence should be used with extreme caution. Our model allows both heterogeneity and inherent uncertainty to be incorporated. Due to the scarcity of verified data, we draw insights by calibrating our model using parameters from other relevant sources, including agreement on average (mean field) with parameters in SIR-based models.

title: Phenomenological Modelling of COVID-19 epidemics in Sri Lanka, Italy and Hebei Province of China
abstract: The COVID-19 pandemic has resulted in increasing number of infections and deaths on a daily basis. There is no specific treatment or vaccine identified and the focus has been preventive measures based on statistical and mathematical models. These have relied on analyzing the behavior of populations and characteristics of the infection and applying modelling techniques. The analysis of epidemiological curve fitting on number of daily infections across affected countries could give useful insights on the characteristics of the epidemic. A variety of phenomenological models are available to capture dynamics of disease spread and growth. Data for this study used the number of daily new infections and cumulative number of infections in COVID-19 in three selected countries, Sri Lanka, Italy and Hebei province of China, from the first day of appearance of cases to 20th April 2020. In this study Gompertz, Logistic and Exponential growth curves were fitted on cumulative number of infections across countries. Akaikes information criteria (AIC) was used in determining the best fitting curve for each country. Results revealed that the most appropriate growth curves for Sri Lanka, Italy and China-Hebei are Exponential, Gompertz and Logistic curves respectively. The overall growth rate and final epidemic size evaluated from best models for the three countries and short-term forecasts were also generated. Log incidences over time in each country were regressed before and after the identified peak time of the respective outbreaks of countries. Hence, doubling time/halving time together with daily growth rates and predictions were estimated. Findings altogether demonstrate that outbreak seems extinct in Hebei-China whereas further transmissions are possible in Sri Lanka. In Italy, current outbreak transmits in a decreasing rate.  Novel Coronavirus (COVID-19), Phenomenological Models, Epidemiological Curve, Prediction

title: The time scale of asymptomatic transmission affects estimates of epidemic potential in the COVID-19 outbreak
abstract: The role of asymptomatic carriers in transmission poses challenges for control of the COVID-19 pandemic. Study of asymptomatic transmission and implications for surveillance and disease burden are ongoing, but there has been little study of the implications of asymptomatic transmission on dynamics of disease. We use a mathematical framework to evaluate expected effects of asymptomatic transmission on the basic reproduction number  see text] (i.e., the expected number of secondary cases generated by an average primary case in a fully susceptible population) and the fraction of new secondary cases attributable to asymptomatic individuals. If the generation-interval distribution of asymptomatic transmission differs from that of symptomatic transmission, then estimates of the basic reproduction number which do not explicitly account for asymptomatic cases may be systematically biased. Specifically, if asymptomatic cases have a shorter generation interval than symptomatic cases,  see text] will be over-estimated, and if they have a longer generation interval,  see text] will be under-estimated. Estimates of the realized proportion of asymptomatic transmission during the exponential phase also depend on asymptomatic generation intervals. Our analysis shows that understanding the temporal course of asymptomatic transmission can be important for assessing the importance of this route of transmission, and for disease dynamics. This provides an additional motivation for investigating both the importance and relative duration of asymptomatic transmission.

title: Controversies about COVID-19 and anticancer treatment with immune checkpoint inhibitors

title: Impact of school closures for COVID-19 on the US health-care workforce and net mortality: a modelling study
abstract: The coronavirus disease 2019 (COVID-19) pandemic is leading to social (physical) distancing policies worldwide, including in the USA. Some of the first actions taken by governments are the closing of schools. The evidence that mandatory school closures reduce the number of cases and, ultimately, mortality comes from experience with influenza or from models that do not include the effect of school closure on the health-care labour force. The potential benefits from school closures need to be weighed against costs of health-care worker absenteeism associated with additional child-care obligations. In this study, we aimed to measure child-care obligations for US health-care workers arising from school closures when these are used as a social distancing measure. We then assessed how important the contribution of health-care workers would have to be in reducing mortality for their absenteeism due to child-care obligations to undo the benefits of school closures in reducing the number of cases.  For this modelling analysis, we used data from the monthly releases of the US Current Population Survey to characterise the family structure and probable within-household child-care options of US health-care workers. We accounted for the occupation within the health-care sector, state, and household structure to identify the segments of the health-care workforce that are most exposed to child-care obligations from school closures. We used these estimates to identify the critical level at which the importance of health-care labour supply in increasing the survival probability of a patient with COVID-19 would undo the benefits of school closures and ultimately increase cumulative mortality.  Between January, 2018, and January, 2020, the US Current Population Survey included information on more than 3·1 million individuals across 1·3 million households. We found that the US health-care sector has some of the highest child-care obligations in the USA, with 28·8% (95% CI 28·5–29·1) of the health-care workforce needing to provide care for children aged 3–12 years. Assuming non-working adults or a sibling aged 13 years or older can provide child care, 15·0% (14·8–15·2) of the health-care workforce would still be in need of child care during a school closure. We observed substantial variation within the health-care system. We estimated that, combined with reasonable parameters for COVID-19 such as a 15·0% case reduction from school closings and 2·0% baseline mortality rate, a 15·0% decrease in the health-care labour force would need to decrease the survival probability per percent health-care worker lost by 17·6% for a school closure to increase cumulative mortality. Our model estimates that if the infection mortality rate of COVID-19 increases from 2·00% to 2·35% when the health-care workforce declines by 15·0%, school closures could lead to a greater number of deaths than they prevent.  School closures come with many trade-offs, and can create unintended child-care obligations. Our results suggest that the potential contagion prevention from school closures needs to be carefully weighted with the potential loss of health-care workers from the standpoint of reducing cumulative mortality due to COVID-19, in the absence of mitigating measures.

title: Iranian mental health during the COVID-19 epidemic

title: Commentary on ‘Interventions to improve antibiotic prescribing practices in ambulatory care’
abstract: This is a commentary on a Cochrane review, published in this issue of EBCH, first published as: Arnold SR, Straus SE. Interventions to improve antibiotic prescribing practices in ambulatory care. Cochrane Database of Systematic Reviews 2005, Issue 4. Art. No.: CD003539.  Further information for this Cochrane review is available in this issue of EBCH in the accompanying EBCH Summary and Characteristics and Key Findings Tables articles.

title: COVID-19: Modelling Local Transmission and Morbidity effects to provide an estimate of overall Relative Healthcare Resource Impact by General Practice Granularity
abstract: (SARS-CoV-2) is the name given to the 2019 novel coronavirus. COVID-19 is the name given to the disease associated with the virus. SARS-CoV-2 is a new strain of coronavirus that has not been previously identified in humans.  Two key factors were analysed which when multiplied together would give an estimate of relative demand on healthcare utilisation. These factors were case incidence and case morbidity. GP Practice data was used as this provided the most geographically granular source of published public population data. To analyse case incidence, the latest values for indicators that could be associated with infection transmission rates were collected from the Office of National Statistics (ONS) and Quality Outcome Framework (QOF) sources. These included population density, % age >16 at fulltime work/education, % age over 60, % BME ethnicity, social deprivation as IMD 2019, Location as latitude/longitude, and patient engagement as % self-confident in their own long term condition management. Average case morbidity was calculated by applying the international mortality Odds Ratio to the local population relevant age and disease prevalences and then summing and dividing by the equivalent national figure. To provide a comparative measure of overall healthcare resource impact, individual GP practice impact scores were compared against the median practice.  The case incidence regression is a dynamic situation with the significance of specific factors moderating over time as the balance between external infection, community transmission and impact of mitigation measures feeds through to the number of cases. It showed that currently Urban, % Working and age >60 were the strongest determinants of case incidence. The local population comorbidity remains unchanged. The range of relative HC impact was wide with 80% of practices falling between 20%-250% of the national median. Once practice population numbers were included it showed that the top 33% of GP practices supporting 45% of the patient population would require 68% of COVID-19 healthcare resources. The model provides useful information about the relative impact of Covid-19 on healthcare workload at GP practice granularity in all parts of England. Conclusion Covid-19 is impacting on the utilisation of health and social care resources across the country. This model provides a method for predicting relative local levels of disease burden based on defined criteria and thereby providing a method for targeting limited (and perhaps soon to be scarce) care resources to optimise national, regional and local responses to the COVID-19 outbreak.

title: Weather Conditions and COVID-19 Transmission: Estimates and Projections
abstract: Understanding and projecting the spread of COVID-19 requires reliable estimates of how weather components are associated with the transmission of the virus. Prior research on this topic has been inconclusive. Identifying key challenges to reliable estimation of weather impact on transmission we study this question using one of the largest assembled databases of COVID-19 infections and weather.  We assemble a dataset that includes virus transmission and weather data across 3,739 locations from December 12, 2019 to April 22, 2020. Using simulation, we identify key challenges to reliable estimation of weather impacts on transmission, design a statistical method to overcome these challenges, and validate it in a blinded simulation study. Using this method and controlling for location-specific response trends we estimate how different weather variables are associated with the reproduction number for COVID-19. We then use the estimates to project the relative weather-related risk of COVID-19 transmission across the world and in large cities.  We show that the delay between exposure and detection of infection complicates the estimation of weather impact on COVID-19 transmission, potentially explaining significant variability in results to-date. Correcting for that distributed delay and offering conservative estimates, we find a negative relationship between temperatures above 25 degrees Celsius and estimated reproduction number ([R]), with each degree Celsius associated with a 3.1% (95% CI, 1.5% to 4.8%) reduction in [R]. Higher levels of relative humidity strengthen the negative effect of temperature above 25 degrees. Moreover, one millibar of additional pressure increases [R] by approximately 0.8 percent (95% CI, 0.6% to 1%) at the median pressure (1016 millibars) in our sample. We also find significant positive effects for wind speed, precipitation, and diurnal temperature on [R]. Sensitivity analysis and simulations show that results are robust to multiple assumptions. Despite conservative estimates, weather effects are associated with a 43% change in [R] between the 5th and 95th percentile of weather conditions in our sample.  These results provide evidence for the relationship between several weather variables and the spread of COVID-19. However, the (conservatively) estimated relationships are not strong enough to seasonally control the epidemic in most locations.

title: An Epidemiological Study on COVID-19: A Rapidly Spreading Disease
abstract: The outbreak of the novel coronavirus disease in 2019 (COVID-19) caused a major public health crisis worldwide and challenged healthcare systems across the six continents. The high infectivity of the disease led many governments to adopt strict regulations and measures with the aim of containing its spread. The purpose of this study is to assess the incidence, severity, and territorial expansion of COVID-19.  Data from the World Health Organization was screened, and COVID-19 situation reports were extracted from January 21 up till March 14 (inclusive). Our data included the total number of cases, total number of new cases, total number of cured cases, and total number of related deaths. Percentage change of cases over the days of our study were calculated using the Joinpoint regression, with a significance level set at greater than 0.05.  The total number of COVID-19 cases reached 156,622, with 5,845 subsequent deaths. China, Italy, and Iran have the highest number of cases worldwide. During the first 22 days, the incidence rate of COVID-19 increased significantly to reach 1.81 cases per million persons (p<0.001). That was followed by a significant decrease over the next 11 days (p<0.001) to reach 0.071 cases per million persons. A steady rise then followed, which saw a significant increase in incidence rate to 1.429 cases per million persons (p<0.001). Percentages of death and cured cases varied across the different countries; nevertheless, death percentages have generally been decreasing since the start of the crisis.  Adopting precautionary regulations such as social isolation, increasing sanitation, and employing strict quarantine measures have proved to be beneficial in containing the virus. Further research needs to be conducted to help discover therapeutic modalities and improve outcomes.

title: An artificial intelligence-based first-line defence against COVID-19: digitally screening citizens for risks via a chatbot
abstract: To combat the pandemic of the coronavirus disease (COVID-19), numerous governments have established phone hotlines to prescreen potential cases. These hotlines have struggled with the volume of callers, leading to wait times of hours or, even, an inability to contact health authorities. Symptoma is a symptom-to-disease digital health assistant that can differentiate more than 20,000 diseases with an accuracy of more than 90%. We tested the accuracy of Symptoma to identify COVID-19 using a set of diverse clinical cases combined with case reports of COVID-19. We showed that Symptoma can accurately distinguish COVID-19 in 96.32% of clinical cases. When considering only COVID-19 symptoms and risk factors, Symptoma identified 100% of those infected when presented with only three signs. Lastly, we showed that Symptoma’s accuracy far exceeds that of simple “yes-no” questionnaires widely available online. In summary, Symptoma provides unparalleled accuracy in systematically identifying cases of COVID-19 while also considering over 20,000 other diseases. Furthermore, Symptoma allows free text input, furthered with disease-specific follow up questions,  Symptoma the potential to be a key tool in the global fight against COVID-19. The Symptoma predictor is freely available online at https://www.symptoma.com.

title: Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model
abstract: With the outbreak of coronavirus disease 2019 (COVID-19), a sudden case increase in late February 2020 led to deep concern globally. Italy, South Korea, Iran, France, Germany, Spain, the US and Japan are probably the countries with the most severe outbreaks. Collecting epidemiological data and predicting epidemic trends are important for the development and measurement of public intervention strategies. Epidemic prediction results yielded by different mathematical models are inconsistent; therefore, we sought to compare different models and their prediction results to generate objective conclusions.  We used the number of cases reported from January 23 to March 20, 2020, to estimate the possible spread size and peak time of COVID-19, especially in 8 high-risk countries. The logistic growth model, basic SEIR model and adjusted SEIR model were adopted for prediction. Given that different model inputs may infer different model outputs, we implemented three model predictions with three scenarios of epidemic development.  When comparing all 8 countries short-term prediction results and peak predictions, the differences among the models were relatively large. The logistic growth model estimated a smaller epidemic size than the basic SERI model did; however, once we added parameters that considered the effects of public health interventions and control measures, the adjusted SERI model results demonstrated a considerably rapid deceleration of epidemic development. Our results demonstrated that contact rate, quarantine scale, and the initial quarantine time and length are important factors in controlling epidemic size and length.  We demonstrated a comparative assessment of the predictions of the COVID-19 outbreak in eight high-risk countries using multiple methods. By forecasting epidemic size and peak time as well as simulating the effects of public health interventions, the intent of this paper is to help clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviors are critical to slow down the epidemic.

title: Internet Search Patterns Reveal Clinical Course of Disease Progression for COVID-19 and Predict Pandemic Spread in 32 Countries
abstract: Effective public health response to COVID-19 relies on accurate and timely surveillance of local pandemic spread, as well as rapid characterization of the clinical course of disease in affected individuals. De novo diagnostic testing methods developed for emergent pandemics are subject to significant development delays and capacity limitations. There is a critical need for complementary surveillance approaches that can function at population-scale to inform public health decisions in real-time. Internet search patterns provide a number of important advantages relative to laboratory testing. We conducted a detailed global study of Internet search patterns related to COVID-19 symptoms in multiple languages across 32 countries on six continents. We found that Internet search patterns reveal a robust temporal pattern of disease progression for COVID-19: Initial symptoms of fever, dry cough, sore throat and chills are followed by shortness of breath an average of 5.22 days [95% CI 3.30-7.14] after symptom onset, matching the precise clinical course reported in the medical literature. Furthermore, we found that increases in COVID-19-symptom-related searches predict increases in reported COVID-19 cases and deaths 18.53 days [95% CI 15.98-21.08] and 22.16 days [95% CI 20.33-23.99] in advance, respectively. This is the first study to show that Internet search patterns can be used to reveal the detailed clinical course of a disease. These data can be used to track and predict the local spread of COVID-19 before widespread laboratory testing becomes available in each country, helping to guide the current public health response.

title: COVID-19 Pneumonia in Asymptomatic Trauma Patients; Report of 8 Cases
abstract: We are currently involved in the novel coronavirus 2019 (COVID-19) pandemic. A considerable number of COVID-19 infected cases are asymptomatic but they can transmit the disease to others, especially healthcare workers. In this study, we reported 8 incidentally detected cases of COVID-19 pneumonia in chest computed tomography (CT) scan of patients referred to emergency department following multiple trauma without any respiratory symptoms.

title: Are Online Searches for the Novel Coronavirus (COVID-19) Related to Media or Epidemiology? A Cross-sectional Study
abstract: Previous studies on the novel Coronavirus (COVID-19) have found strong correlations between online searches and the epidemiology of the disease.  Our aim was to determine if online searches for COVID-19 related to international media announcements or national epidemiology.  Searches for “coronavirus” were made on Google Trends from December 31, 2019 to April 13, 2020 for 40 European countries. The online COVID-19 searches for all countries were correlated with each other. COVID-10 epidemiology (i.e. incidence and mortality) was correlated with the national online searches. Major announcements by the World Health Organization (WHO) were taken into consideration with peaks in online searches. Correlations were made using Spearman's rank correlation coefficient.  Overall, the online searches for COVID-19 were not correlated with the actual incidence and mortality of COVID-19. The mean Spearman correlation for incidence was 0.20 (range -0.66 to 0.76) and for mortality was 0.35 (range -0.75 to 0.85). Online searches in Europe were all strongly synchronized with each other; a mean Spearman correlation of 0.93 (range 0.62 to 0.99).  Online searches for COVID-19 in Europe are not correlated with epidemiology but strongly correlated with international WHO announcements. Our study challenges previous Google Trends studies and emphasizes the role of the WHO in raising awareness of a new disease.

title: TB infection and BCG vaccination: Are we protected from COVID-19?
abstract: The incidence of emerging COVID-19 disease is variable across the different parts of the world. Apart from travel patterns, other factors determining this difference may include host immune response. Aim of this study was to assess the effect of TB endemicity and BCG coverage on COVID-19.   We reviewed available data regarding tuberculosis incidence, BCG coverage (as per WHO), and COVID-19 incidence of 174 countries. We divided the countries into four cohorts depending upon annual TB incidence and BCG coverage.  Countries with high TB incidence had lower COVID-19 as compared to countries with low TB incidence. Similarly, countries with high BCG coverage had lower incidence of COVID-19 suggesting some protective mechanisms in TB endemic areas. Although, the ecological differences and different testing strategies between countries could not be accounted for in this analysis.  Higher TB incidence and BCG coverage were found to be associated with lesser incidence of COVID-19. This outcome paves the way for further research into pathogenesis and immune response in COVID-19.

title: Early analysis of the Australian COVID-19 epidemic
abstract: As of 18 April 2020, there had been 6,533 confirmed cases of COVID-19 in Australia. Of these, 67 had died from the disease. The daily count of new confirmed cases was declining. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors, such as the intensity and timing public health interventions, that contribute to individual country experiences of COVID-19 will assist in the next stage of response planning globally. Using data from the Australian national COVID-19 database, we describe how the epidemic and public health response unfolded in Australia up to 13 April 2020. We estimate that the effective reproduction number was likely below 1 (the threshold value for control) in each Australian state since mid-March and forecast that hospital ward and intensive care unit occupancy will remain below capacity thresholds over the next two weeks.

title: Abstracts from the 37th Annual Meeting of the Society of General Internal Medicine

title: Viral Diseases of New World Camelids
abstract: The increased popularity and population of New World camelids in the United States requires the development of a broader base of knowledge of the health and disease parameters for these animals by the veterinary livestock practitioner. Although our knowledge regarding infectious diseases of camelids has increased greatly over the past decade, the practice of camelid medicine is a relatively new field in North America, so it is important to seek out seasoned colleagues and diagnostic laboratories that are involved in camelid health treatment and diagnosis.

title: Are official confirmed cases and fatalities counts good enough to study the COVID-19 pandemic dynamics? A critical assessment through the case of Italy
abstract: As the COVID-19 outbreak is developing the two most frequently reported statistics seem to be the raw confirmed case and case fatalities counts. Focusing on Italy, one of the hardest hit countries, we look at how these two values could be put in perspective to reflect the dynamics of the virus spread. In particular, we find that merely considering the confirmed case counts would be very misleading. The number of daily tests grows, while the daily fraction of confirmed cases to total tests has a change point. It (depending on region) generally increases with strong fluctuations till (around, depending on region) 15th-22nd March and then decreases linearly after. Combined with the increasing trend of daily performed tests, the raw confirmed case counts are not representative of the situation and are confounded with the sampling effort. This we observe when regressing on time the logged fraction of positive tests and for comparison the logged raw confirmed count. Hence, calibrating model parameters for this virus's dynamics should not be done based only on confirmed case counts (without rescaling by the number of tests), but take also fatalities and hospitalization count under consideration as variables not prone to be distorted by testing efforts. Furthermore, reporting statistics on the national level does not say much about the dynamics of the disease, which are taking place at the regional level. These findings are based on the official data of total death counts up to 15th April 2020 released by ISTAT and up to 10th May 2020 for the number of cases. In this work we do not fit models but we rather investigate whether this task is possible at all. This work also informs about a new tool to collect and harmonize official statistics coming from different sources in the form of a package for the R statistical environment and presents the COVID-19 Data Hub.

title: Daily Situation Report on Coronavirus disease (COVID-19) in Iran; March 16, 2020
abstract: After detection of the first confirmed cases of COVID-19 in Iran, the National Committee on COVID-19 Epidemiology in Ministry of Health and Medical Education was established. This Committee is official source of gathering, analyzing, and reporting the COVID-19 data in Iran. The data of all sources in the country including, medical care monitoring center (MCMC), Hospitals’ Information Systems (HIS), Laboratory portal, the data of the center for communicable disease control (MOH), as well as the data from community health centers are integrated and used in this regards. This factsheet contain daily situation report on coronavirus disease (covid-19) in Iran; March 16, 2020.

title: Be Prepared

title: MERS-CoV infection: Mind the public knowledge gap
abstract: In August 2015, the Corona outbreak caused by Middle East respiratory syndrome coronavirus (MERS-CoV) was the 9th episode since June 2012 in Saudi Arabia. Little is known about the public awareness toward the nature or prevention of the disease. The aim of this work was to assess the knowledge of the adult population in Riyadh toward the MERS-CoV. In this cross-sectional survey, a self-administrated questionnaire was distributed to randomly selected participants visiting malls in Riyadh. The questionnaire contained measurable epidemiological and clinical MERS-CoV knowledge level variables and relevant source of information. The study included 676 participants. Mean age was 32.5 (±SD 8.6) years and 353 (47.8%) were males. Almost all participants heard about the corona disease and causative agent. The study showed a fair overall knowledge (66.0%), less knowledge on epidemiological features of the disease (58.3%), and good knowledge (90.7%) on the clinical manifestation of the MERS-CoV. Internet was the major (89.0%) source of disease information, and other sources including health care providers, SMS, television, magazines and books were low rated (all <25%). In a multivariate logistic regression analysis age ≤30 years (Odds Ratio (OR)=1.647, 95%CI 1.048–2.584, P =0.030), male gender (OR=1.536, 95%CI 1.105–2.134, P =0.01), and no tertiary education (OR=1.957, 95%CI 1.264–3.030, P =0.003) were independent significant predictors of poor epidemiological knowledge. This study concludes that there was inadequate epidemiological knowledge received by the public and the reliance mostly on the clinical manifestations to recognizing the MERS-CoV disease. Comprehensive public health education programs is important to increase awareness of simple epidemiological determinants of the disease is warranted.

title: COVID-19, Australia: Epidemiology Report 3 (Reporting week ending 19:00 AEDT 15 February 2020).
abstract: This is the third epidemiological report for coronavirus disease 2019 (COVID-19), previously known as novel coronavirus (2019-nCoV), from the virus now known as SARS-CoV-2, reported in Australia as at 19:00 Australian Eastern Daylight Time [AEDT] 15 February 2020. It includes data on the COVID-19 Australian cases, the international situation and current information on the severity, transmission and spread.

title: La grippe est-elle encore le modèle des infections virales émergentes ?
abstract: Emerging viral infections are a crucial challenge to the organization of human public health policies. In the past decades, numerous viral pathogens have barged into the field of medicine, being viruses either newly appeared in the population or newly identified or exhibiting unexpected epidemiological properties. Several factors have been reported to promote such emergences, including viral traffic from animals, ongoing viral genetic evolution, host factors, environmental and social changes. As an example, HIV-1 pandemic perfectly illustrates the evolutionary success of a simian retrovirus introduced into the human population as well as its dramatic impact both on the demographic and economic status of many countries. Influenza viruses remain a classic persisting model of emerging pathogens, which is supported by the coalescence of many contributing characteristics, particularly an animal reservoir consisting of birds and mammals and a segmented RNA genome prone to point mutations and reassortments. Two recent examples, the avian flu due to A/H5N1 virus and the pandemic flu due to A/H1N1 2009, show the difficulties both for predicting the outcome of flu emergences and defining the right strategy for their control. Despite their complexity, influenza virus infections provide a permanent incitement to improve our knowledge and monitoring of viral emergences.

title: Managing Febrile Respiratory Illnesses during a Hypothetical SARS Outbreak
abstract: Since the World Health Organization declared the global outbreak of severe acute respiratory syndrome (SARS) contained in July 2003, new cases have periodically reemerged in Asia. This situation has placed hospitals and health officials worldwide on heightened alert. In a future outbreak, rapidly and accurately distinguishing SARS from other common febrile respiratory illnesses (FRIs) could be difficult. We constructed a decision-analysis model to identify the most efficient strategies for managing undifferentiated FRIs within a hypothetical SARS outbreak in New York City during the season of respiratory infections. If establishing reliable epidemiologic links were not possible, societal costs would exceed $2.0 billion per month. SARS testing with existing polymerase chain reaction assays would have harmful public health and economic consequences if SARS made up <0.1% of circulating FRIs. Increasing influenza vaccination rates among the general population before the onset of respiratory season would save both money and lives.

title: Climate factors and incidence of Middle East respiratory syndrome coronavirus
abstract: Our understanding of climate factors and their links to the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreaks is incomplete. This study aimed to estimate the monthly incidence of MERS-CoV cases and to investigate their correlation to climate factors.  The study used aggregated monthly MERS-CoV cases that reported to the Saudi Center for Disease Prevention and Control from the Riyadh Region between November 1, 2012 and December 31, 2018. Data on the meteorological situation throughout the study period was calculated based on Google reports on the Riyadh Region (24.7136°N, 46.6753°E). The Poisson regression was used to estimate the incidence rate ratio (IRR) and its 95% confidence intervals (CI) for each climate factor.  A total of 712 MERS-CoV cases were included in the analysis (mean age 54.2±9.9 years), and more than half (404) (56.1%) MERS-CoV cases were diagnosed during a five-month period from April to August. The highest peak timing positioned in August 2015, followed by April 2014, June 2017, March 2015, and June 2016. High temperatures (IRR=1.054, 95% CI: 1.043–1.065) and a high ultraviolet index (IRR=1.401, 95% CI: 1.331–1.475) were correlated with a higher incidence of MERS-CoV cases. However, low relative humidity (IRR=0.956, 95% CI: 0.948–0.964) and low wind speed (IRR=0.945, 95% CI: 0.912–0.979) were correlated with a lower incidence of MERS-CoV cases.  The novel coronavirus, MERS-CoV, is influenced by climate conditions with increasing incidence between April and August. High temperature, high ultraviolet index, low wind speed, and low relative humidity are contributors to increased MERS-CoV cases. The climate factors must be evaluated in hospitals and community settings and integrated into guidelines to serve as source of control measures to prevent and eliminate the risk of infection.

title: Human coronavirus NL63, a new respiratory virus
abstract: From the mid-1960s onwards, it was believed that only two human coronavirus species infect humans: HCoV-229E and HCoV-OC43. Then, in 2003, a novel member of the coronavirus family was introduced into the human population: SARS-CoV, causing an aggressive lung disease. Fortunately, this virus was soon expelled from the human population, but it quickly became clear that the human coronavirus group contains more members then previously assumed, with HCoV-NL63 identified in 2004. Despite its recent discovery, ample results from HCoV-NL63 research have been described. We present an overview of the publications on this novel coronavirus.

title: The phenotypic changes of Î³Î´ T cells in COVID-19 patients
abstract: A novel pneumonia-associated respiratory syndrome named coronavirus disease-2019 (COVID-19), which caused by SARS-CoV-2 and broken in Wuhan, China in the end of 2019. Unfortunately, there is no specific antiviral agent or vaccine available to treat SARS-CoV-2 infections. Also, information regarding the immunological characteristics in COVID-19 patients remains limited. Here we collected the blood samples from 18 healthy donors (HD) and 38 COVID-19 patients to analyze changes in {gamma}{delta} T cells. In comparison to HD, the {gamma}{delta} T cells percentage was decreased. {gamma}{delta} T cells are able to immediately respond to SARS-CoV-2 infection and upregulate the activation marker CD25. In addition, the increased expression of CD4 in {gamma}{delta} T cells may serve as a biomarker for the assessment of SARS-CoV-2 infection.

title: The SARS-CoV-2 outbreak: What we know
abstract: There is a current worldwide outbreak of the novel coronavirus Covid-19 (coronavirus disease 2019; the pathogen called SARS-CoV-2; previously 2019-nCoV), which originated from Wuhan in China and has now spread to 6 continents including 66 countries, as of 24:00 on March 2, 2020. Governments are under increased pressure to stop the outbreak from spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak site and from laboratories supporting the investigation. This paper aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus.

title: Early trends for SARS-CoV-2 infection in central and north Texas and impact on other circulating respiratory viruses
abstract: Rapid diagnosis and isolation are key to containing the rapid spread of a pandemic agent like SARS-CoV-2, which has spread globally since its initial outbreak in Wuhan province in China. SARS-CoV-2 is novel to most parts of the world including USA and the effect on normally prevalent viruses is just becoming apparent. We present our initial data on the prevalence of respiratory viruses in the month of March, 2020.  This is a retrospective cohort study post launching of SARS-CoV-2 testing at BSWH, Temple TX. Testing for SARS-CoV-2 was performed by real-time RT-PCR assay and results were shared with State public health officials for immediate interventions.  More than 3500 tests were performed during the first two weeks of testing for SARS-CoV-2 and identified 168 (4.7%) positive patients. Sixty-two (3.2%) of the 1,912 ambulatory patients and 106 (6.3%) of the 1,659 ED/inpatients were tested positive. Higher rate of infection (6.9%) were noted in the patients belonging to age group 25-34 years and least number of positive cases were noted in <25 years old (2%) group. The TX State county specific patient demographic information was shared with respective public health departments for epidemiological interventions. Incidentally, this study showed that there was a sudden decrease in the occurrence of other infections due to seasonal viruses, perhaps due to increased epidemiological awareness, about SARS-CoV-2, among general public. Authors would also like to share a small study on SARS-CoV-2 serological assay for the detection of IgG antibodies.  This study was intended to provide an initial experience of dealing with a pandemic and the role of laboratories in crisis management. Epidemiological interventions depend on timely availability of accurate diagnostic tests and throughput capacity of such systems during large outbreaks like SARS-CoV-2.

title: The current state of COVID-19 in Australia: importation and spread
abstract: The rapid global spread of coronavirus disease (COVID-19) is unprecedented. The outbreak has quickly spread to more than 100 countries reporting over 100,000 confirmed cases. Australia reported its first case of COVID-19 on 25th January 2020 and has since implemented travel restrictions to stop further introduction of the virus.  We analysed daily global COVID-19 data published by the World Health Organisation to investigate the spread of the virus thus far. To assess the current risk of COVID-19 importation and local spread in Australia we predict international passenger flows into Australia during 2020.  Our analysis of global data shows that Australia can expect a similar growth rate of reported cases as observed in France and the United States. We identify travel patterns of Australian citizens/residents and foreign travellers that can inform the implementation of new and the alteration of existing travel restrictions related to COVID-19.  Our findings identify the risk reduction potential of current travel bans, based on the proportion of returning travellers to Australia that are residents or visitors. The similarity of the exponential growth in the epidemic curve in Australia to other countries guides forecasts of COVID-19 growth in Australia, and opportunities for drawing lessons from other countries with more advanced outbreaks.

title: COVID-19: Abnormal liver function tests
abstract: Recent data on the coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has begun to shine light on the impact of the disease on the liver. But no studies to date have systematically described liver test abnormalities in patients with COVID-19. We evaluated the clinical characteristics of COVID-19 in patients with abnormal liver test results.  Clinical records and laboratory results were obtained from 417 patients with laboratory-confirmed COVID-19 who were admitted to the only referral hospital in Shenzhen, China from January 11 to February 21, 2020 and followed up to March 7, 2020. Information on clinical features of patients with abnormal liver tests were collected for analysis.  Of 417 patients with COVID-19, 318 (76.3%) had abnormal liver test results and 90 (21.5%) had liver injury during hospitalization. The presence of abnormal liver tests became more pronounced during hospitalization within 2 weeks, with 49 (23.4%), 31 (14.8%), 24 (11.5%) and 51 (24.4%) patients having alanine aminotransferase, aspartate aminotransferase, total bilirubin and gamma-glutamyl transferase levels elevated to more than 3× the upper limit of normal, respectively. Patients with abnormal liver tests of hepatocellular type or mixed type at admission had higher odds of progressing to severe disease (odds ratios [ORs] 2.73; 95% CI 1.19–6.3, and 4.44, 95% CI 1.93–10.23, respectively). The use of lopinavir/ritonavir was also found to lead to increased odds of liver injury (OR from 4.44 to 5.03, both p <0.01).  Patients with abnormal liver tests were at higher risk of progressing to severe disease. The detrimental effects on liver injury mainly related to certain medications used during hospitalization, which should be monitored and evaluated frequently.  Data on liver tests in patients with COVID-19 are scarce. We observed a high prevalence of liver test abnormalities and liver injury in 417 patients with COVID-19 admitted to our referral center, and the prevalence increased substantially during hospitalization. The presence of abnormal liver tests and liver injury were associated with the progression to severe pneumonia. The detrimental effects on liver injury were related to certain medications used during hospitalization, which warrants frequent monitoring and evaluation for these patients.

title: Outcome of a public consultation on the Draft Opinion of the EFSA Panel on Dietetic Products, Nutrition, and Allergies (NDA) on a guidance on the scientific requirements for health claims related to gut and immune function

title: A sporadic COVID-19 pneumonia treated with extracorporeal membrane oxygenation in Tokyo, Japan: A case report
abstract: An ongoing outbreak of a novel coronavirus disease (coronavirus disease 2019, COVID-19) has become a global threat. While clinical reports from China to date demonstrate that the majority of cases remain relatively mild and recover with supportive care, it is also crucial to be well prepared for severe cases warranting intensive care. Initiating appropriate infection control measures may not always be achievable in primary care or in acute-care settings. Case A 45-year-old man was admitted to the intensive care unit due to severe pneumonia, later confirmed as COVID-19. His initial evaluation in the resuscitation room and treatments in the intensive care unit was performed under droplet and contact precaution with additional airborne protection using the N95 respirator mask. He was successfully treated in the intensive care unit with mechanical ventilation and extracorporeal membrane oxygenation for respiratory support; and antiretroviral treatment with lopinavir/ritonavir. His total intensive care unit stay was 15 days and was discharged on hospital day 24.  Strict infection control precautions are not always an easy task, especially under urgent care in an intensive care unit. However, severe cases of COVID-19 pneumonia, or another novel infectious disease, could present at any moment and would be a continuing challenge to pursue appropriate measures. We need to be well prepared to secure healthcare workers from exposure to infectious diseases and nosocomial spread, as well as to provide necessary intensive care.

title: Rotavirus incidence in hospitalised Hong Kong children: 1 July 1997 to 31 March 2011
abstract: Sentinel laboratory surveillance from one hospital and passive discharge diagnosis (Clinical Management System, CMS) data from all public Hospital Authority (HA) hospitals were used to estimate disease burden and incidence of rotavirus in hospitalised Hong Kong children over 14 rotavirus seasons (1 July 1997 to 31 March 2011). A primary diagnosis of a gastroenteritis-related disorder was noted in 9.8% of children aged below 5 years, and a primary or secondary diagnosis in 11.8%. Any CMS diagnosis of rotavirus (ICD 008.61) was initially used to derive incidence estimates of rotavirus by age group. Rotavirus was recorded as any primary or any secondary diagnosis in 1.6% of children below 5 years of age. The unadjusted incidence rates per 100,000 person-years based on any CMS diagnosis of rotavirus were: 249 (0 to <1m); 612 (1 to <2m); 1066 (2 to <6m); 1383 (6 to <11m); 959 (1 to <2y); 406 (2 to <3y); 233 (3 to <4y); 124 (4 to <5y). Overall the rotavirus incidence was 1071 in children below 2 years and 542 in children below 5 years of age, with the incidence rates trending up during the time period (p = 0.001). A similar but less marked upward trend (p = 0.046) was noted for the incidence of all-cause gastroenteritis. Laboratory results from a single surveillance hospital (1 July 2000 to 31 March 2011) were then linked to these CMS codes to derive adjustment factors for possible over- and under-diagnosis of rotavirus based on CMS codes alone. This analysis suggested that a CMS diagnosis of rotavirus alone likely under-reported true incidence by a factor of between 1.59 and 2.02 in children below 5 years of age. Despite the availability of rotavirus vaccines in the private sector since 2006, no reduction in the incidence of hospitalisation for either rotavirus or all-cause gastroenteritis was noted in Hong Kong children below 5 years of age over 14 rotavirus seasons (1997–2011).

title: Efficient prevalence estimation and infected sample identification with group testing for SARS-CoV-2
abstract: The ongoing pandemic of SARS-CoV-2, a novel coronavirus, caused over 3 million reported cases of coronavirus disease 2019 (COVID-19) and 200,000 reported deaths between December 2019 and April 2020(1). Cases and deaths will increase as the virus continues its global march outward. In the absence of effective pharmaceutical interventions or a vaccine, wide-spread virological screening is required to inform where restrictive isolation measures should be targeted and when they can be lifted(2–6). However, limitations on testing capacity have restricted the ability of governments and institutions to identify individual clinical cases, appropriately measure community prevalence, and mitigate transmission. Group testing offers a way to increase efficiency, by combining samples and testing a small number of pools(7–9). Here, we evaluate the effectiveness of group testing designs for individual identification or prevalence estimation of SARS-CoV-2 infection when testing capacity is limited. To do this, we developed mathematical models for epidemic spread, incorporating empirically measured individual-level viral kinetics to simulate changing viral loads in a large population over the course of an epidemic. We used these to construct representative populations and assess pooling strategies for community screening, accounting for variability in viral load samples, dilution effects, changing prevalence and resource constraints. We confirmed our group testing framework through pooled tests on de-identified human nasopharyngeal specimens with viral loads representative of the larger population. We show that group testing designs can both accurately estimate overall prevalence using a small number of measurements and substantially increase the identification rate of infected individuals in resource-limited settings.

title: Abdominal and testicular pain: An atypical presentation of COVID-19

title: Risk of COVID-19 among frontline healthcare workers and the general community: a prospective cohort study
abstract: Data for frontline healthcare workers (HCWs) and risk of SARS-CoV-2 infection are limited and whether personal protective equipment (PPE) mitigates this risk is unknown. We evaluated risk for COVID-19 among frontline HCWs compared to the general community and the influence of PPE.  We performed a prospective cohort study of the general community, including frontline HCWs, who reported information through the COVID Symptom Study smartphone application beginning on March 24 (United Kingdom, U.K.) and March 29 (United States, U.S.) through April 23, 2020. We used Cox proportional hazards modeling to estimate multivariate-adjusted hazard ratios (aHRs) of a positive COVID-19 test.  Among 2,035,395 community individuals and 99,795 frontline HCWs, we documented 5,545 incident reports of a positive COVID-19 test over 34,435,272 person-days. Compared with the general community, frontline HCWs had an aHR of 11·6 (95% CI: 10·9 to 12·3) for reporting a positive test. The corresponding aHR was 3·40 (95% CI: 3·37 to 3·43) using an inverse probability weighted Cox model adjusting for the likelihood of receiving a test. A symptom-based classifier of predicted COVID-19 yielded similar risk estimates. Compared with HCWs reporting adequate PPE, the aHRs for reporting a positive test were 1·46 (95% CI: 1·21 to 1·76) for those reporting PPE reuse and 1·31 (95% CI: 1·10 to 1·56) for reporting inadequate PPE. Compared with HCWs reporting adequate PPE who did not care for COVID-19 patients, HCWs caring for patients with documented COVID-19 had aHRs for a positive test of 4·83 (95% CI: 3·99 to 5·85) if they had adequate PPE, 5·06 (95% CI: 3·90 to 6·57) for reused PPE, and 5·91 (95% CI: 4·53 to 7·71) for inadequate PPE.  Frontline HCWs had a significantly increased risk of COVID-19 infection, highest among HCWs who reused PPE or had inadequate access to PPE. However, adequate supplies of PPE did not completely mitigate high-risk exposures.  Alzheimer’s Society, NIH, NIOSH, Massachusetts Consortium on Pathogen Readiness

title: Pulmonary enterovirus infections in stem cell transplant recipients
abstract: In recent years, it has been recognised that the community respiratory viruses are a frequent cause of upper and lower respiratory tract infections in immunocompromised hosts such as bone marrow transplant recipients. By contrast, infections by non-polio enteroviruses have rarely been reported after stem cell transplantation. We present four cases of acute respiratory illness with enterovirus isolated as the sole pathogen from bronchoalveolar lavage. All four patients developed pneumonia and three died of progressive pneumonia, which reflects the severity of this complication. We conclude that enteroviral pulmonary infections may be a cause of severe pneumonia in immunocompromised hosts.

title: Multi-Stage Group Testing Improves Efficiency of Large-Scale COVID-19 Screening
abstract: SARS-CoV-2 test kits are in critical shortage in many countries. This limits large-scale population testing and hinders the effort to identify and isolate infected individuals.  Herein, we developed and evaluated multi-stage group testing schemes that test samples in groups of various pool sizes in multiple stages. Through this approach, groups of negative samples can be eliminated with a single test, avoiding the need for individual testing and achieving considerable savings of resources.  We designed and parameterized various multi-stage testing schemes and compared their efficiency at different prevalence rates using computer simulations.  We found that three-stage testing schemes with pool sizes of maximum 16 samples can test up to three and seven times as many individuals with the same number of test kits for prevalence rates of around 5% and 1%, respectively. We propose an adaptive approach, where the optimal testing scheme is selected based on the expected prevalence rate.  These group testing schemes could lead to a major reduction in the number of testing kits required and help improve large-scale population testing in general and in the context of the current COVID-19 pandemic.

title: Interactive Real-time Image Analysis System for Distant Operation
abstract: This paper reports on the development and implementation of an integrated and interactive system for cell analysis featuring remote operation and real-time analysis for generating analytical data from microscopic images. The system consists of a number of image processing modules implemented in a virtual instrumentation environment, combined with novel techniques developed for thinning and local edge-gap filling in the cell image segmentation process. These approaches, integrated with advances in networking, have been initially applied to viral feature analysis in SARS-CoV microscopy. Real-time operation through the user-interface of the proposed system generates quantitative results for remote clients. The rapidity and viability of operation permit the investigation of mutant viral agents on the basis of their morphological cell features.

title: Daily Situation Report on Coronavirus disease (COVID-19) in Iran; March 23, 2020
abstract: After detection of the first confirmed cases of COVID-19 in Iran, the National Committee on COVID-19 Epidemiology in Ministry of Health and Medical Education was established. This Committee is official source of gathering, analyzing, and reporting the COVID-19 data in Iran. The data of all sources in the country including, medical care monitoring center (MCMC), Hospitals’ Information Systems (HIS), Laboratory portal, the data of the center for communicable disease control (MOH), as well as the data from community health centers are integrated and used in this regards. This factsheet contain daily situation report on coronavirus disease (covid-19) in Iran; March 23, 2020.

title: Group testing as a strategy for the epidemiologic monitoring of COVID-19
abstract: Sample pooling consists in combining samples from multiple individuals into a single pool that is then tested using a unique test-kit. A positive test means that at least one individual within the pool is infected. Here, we propose an analysis and applications of sample pooling to the epidemiologic monitoring of COVID-19. We first introduce a model of the RT-qPCR process used to test for the presence of virus in a sample and construct a statistical model for the viral load in a typical infected individual inspired by the clinical data from Jones et. al. (2020). We then propose a method for the measure of the prevalence in a population, based on group testing, taking into account the increased number of false negatives associated with this method. Finally, we present an application of sample pooling for the prevention of epidemic outbreak in closed connected communities (e.g. nursing homes).

title: Clinical Characteristics of Hospitalized Patients with SARS-CoV-2 and Hepatitis B virus Co-infection
abstract: The coronavirus disease 2019 (COIVD-19) caused by SARS-CoV-2 has been characterized as a pandemic, which causes a serious public health challenge in the world. A very large group of patients infected by HBV has been reported worldwide, especially in China. In order to answer whether specific treatment strategy on the patients coinfected with HBV and SARS-CoV-2, it requires profound understanding of the clinical characteristics on those patients. However, the impacts of SARS-CoV-2 infection on HBV patients remain largely unknown.  In this retrospective investigation, we included 123 COVID-19 patients admitted to Zhongnan Hospital of Wuhan University, Wuhan, China, from January 5 to March 7, 2020. All enrolled patients are the laboratory confirmed COVID-19 pneumonia cases according to the criteria reported previously. A total of 123 patients were analyzed for their Clinical records, laboratory results including the diagnosis of HBV infection and liver function. Among 123 confirmed COVID-19 patients, the mean age was 51 years old and 59.3% were females (73/123). Fifteen were previously HBV infected patients, 66.7% of them were males (10/15), patients with HBV infection appeared to have a higher incidence of liver cirrhosis and an increased level of total bilirubin. Seven (46.7%) patients with HBV infection were defined as severe cases, while the severity rate was 24.1% for the patients without HBV infection (26/108). The mortality of patients with HBV infection was 13.3% (2/15) compared to 2.8% (3/108) for the patients without HBV infection.  SARS-CoV-2 infection may cause liver function damage in COVID-19 cases and the patients with HBV infection are likely to have more severe disease outcome.

title: Modeling infectious disease dynamics in the complex landscape of global health.
abstract: Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health.

title: Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
abstract: As of March 31, 2020, the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued.  Here we estimate the effective reproduction number, R(t), of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts.  The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI 0.3, 1.0) during the first transmission wave by February 14, 2020, while the overall R based on the cluster size distribution as of March 17, 2020, was estimated at 0.6 (95% CI 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p < 0.001).  The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.

title: Chapter 24 Coronaviridae
abstract: Publisher Summary Coronavirus and coronavirus-like infections are described in swine, cattle, horses, cats, dogs, rats, birds, bats, rabbits, ferrets, mink, and various wildlife species, although many coronavirus infections are subclinical or asymptomatic. In humans, coronaviruses are included in the spectrum of viruses that cause the common cold and, recently, severe acute respiratory syndrome (SARS), which is a zoonosis. This chapter explains that the family Coronaviridae is included with the families Arteriviridae and Roniviridae in the order nidovirales; viruses in these three families share a distinctive replication strategy. The genus Coronavirus contains a substantial number of pathogens of mammals and birds that individually cause a remarkable variety of diseases, including pneumonia, reproductive disease, enteritis, polyserositis, sialodacryoadenitis, hepatitis, encephalomyelitis, nephritis, and various other disorders. The genus Coronavirus can be subdivided into at least three cluster groups on the basis of genetic and serologic properties, with subgroups in two of these. Group 1a includes transmissible gastroenteritis virus of swine, porcine respiratory coronavirus, canine coronavirus, feline enteric coronavirus, ferret and mink coronaviruses, and spotted hyena coronavirus. Group 1b includes certain human coronaviruses, porcine epidemic diarrhea virus, and bat coronavirus. Group 2a includes mouse hepatitis virus, bovine coronavirus, sialodacryoadenitis virus of rats, porcine hemagglutinating encephalomyelitis virus, canine respiratory coronavirus, and other human coronaviruses. Group 2b includes human SARS coronavirus and civet cat, raccoon dog, and horseshoe bat coronaviruses. Group 3 includes avian infectious bronchitis virus, turkey coronavirus, and several potential but still largely uncharacterized new species from ducks, geese, and pigeons.

title: Covid-19: "Illogical" lack of testing is causing healthy staff to self-isolate, BMA chief warns.

title: A systematic review of lopinavir therapy for SARS coronavirus and MERS coronavirus—A possible reference for coronavirus disease‐19 treatment option
abstract: In the past few decades, coronaviruses have risen as a global threat to public health. Currently, the outbreak of coronavirus disease‐19 (COVID‐19) from Wuhan caused a worldwide panic. There are no specific antiviral therapies for COVID‐19. However, there are agents that were used during the severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) epidemics. We could learn from SARS and MERS. Lopinavir (LPV) is an effective agent that inhibits the protease activity of coronavirus. In this review, we discuss the literature on the efficacy of LPV in vitro and in vivo, especially in patients with SARS and MERS, so that we might clarify the potential for the use of LPV in patients with COVID‐19.

title: Group testing performance evaluation for SARS-CoV-2 massive scale screening and testing
abstract: The capacity of the current molecular testing convention does not allow high-throughput and community level scans of COVID-19 infections. The diameter in the current paradigm of shallow tracing is unlikely to reach the silent clusters that might be as important as the symptomatic cases in the spread of the disease. Group testing is a feasible and promising approach when the resources are scarce and when a relatively low prevalence regime is observed on the population.  We employed group testing with a sparse random pooling scheme and conventional group test decoding algorithms both for exact and inexact recovery.  Our simulations showed that significant reduction in per case test numbers (or expansion in total test numbers preserving the number of actual tests conducted) for very sparse prevalence regimes is available. Currently proposed COVID-19 group testing schemes offer a gain up to 15X-20X scale-up. There is a good probability that the required scale up to achieve massive scale testing might be greater in certain scenarios. We investigated if further improvement is available, especially in sparse prevalence occurrence where outbreaks are needed to be avoided by population scans.  Our simulations show that sparse random pooling can provide improved efficiency gains compared to conventional group testing or Reed-Solomon error correcting codes. Therefore, we propose that special designs for different scenarios could be available and it is possible to scale up testing capabilities significantly.

title: Is Increased Sleep Responsible for Reductions in Myocardial Infarction During the COVID-19 Pandemic?
abstract: The COVID-19 pandemic caused by the highly contagious SARS-CoV-2 virus has had devastating consequences across the globe. However, multiple clinics and hospitals have experienced a decrease in rates of acute myocardial infarction and corresponding cardiac catheterization lab activations, raising the question: Has the risk of myocardial infarction decreased during COVID? Sleep deprivation is known to be an independent risk factor for myocardial infarction, and sleep has been importantly impacted during the pandemic, possibly due to the changes in work-home life leading to a lack of structure. We conducted a social media-based survey to assess potential mechanisms underlying the observed improvement in risk of myocardial infarction. We used validated questionnaires to assess sleep patterns, tobacco consumption and other important health outcomes to test the hypothesis that increases in sleep duration may be occurring which have a beneficial impact on health. We found that the COVID-19 pandemic led to shifts in circadian rhythm, with subjects waking up 105 minutes later during the pandemic (p < 0.0001). Subjects also reported going to sleep 41 minutes later during the pandemic (p < 0.0001). These shifts led to longer duration of sleep during the COVID-19 pandemic. Before the pandemic, subjects reported sleeping 6.8 hours per night, which rose to 7.5 hours during the pandemic, a 44 minute or 11% increase (p < 0.0001). We acknowledge the major negative health impact of the global pandemic but would advocate for using this crisis to improve the work and sleep habits of the general population, which may lead to overall health benefits for our society.

title: Transmission dynamics of the COVID-19 epidemic in India, and evaluating the impact of asymptomatic carriers and role of expanded testing in the lockdown exit strategy: a modelling approach
abstract: The coronavirus disease 2019 (COVID-19) has caused over 3 200 000 cases and 230 000 deaths as on 2 May 2020, and has quickly become an unprecedented global health threat. India, with its unique challenges in fighting this pandemic, imposed one of the worlds strictest and largest population-wide lockdown on 25 March 2020. Here, we estimated key epidemiological parameters and evaluated the effect of control measures on the COVID-19 epidemic in India and its states. Through a modeling approach that accounted for asymptomatics, we assessed the impact of lockdown relaxation and increased testing.  We estimated the basic reproduction number and effective reproduction number at a national and state level in India after adjusting for imported cases and reporting lag using established statistical methods, using time-series data from 4 March to 25 April 2020. Using a dynamic SEIR-QDPA model fitted to data from India, we forecasted the size and temporality of the ongoing first wave while accounting for the interventions in place. We used the model to simulate lockdown relaxation under various scenarios to evaluate its effect on the size and temporality of the second wave. We also evaluated the feasibility of increased testing as a containment strategy after restrictions are relaxed and its impact on the epidemic size and resumption of socio-economic activities, while taking into account the changes in transmission dynamics brought about by asymptomatic carriers.  The median delay from symptom onset to detection (reporting lag) was estimated to be 2{middle dot}68 days (95% CI 2{middle dot}00-3{middle dot}00) with an IQR of 2{middle dot}03 days (95% CI 1{middle dot}00-3{middle dot}00). The R0 for India was estimated to be 2{middle dot}083 (95% CI 2{middle dot}044-2{middle dot}122 ; R2 = 0{middle dot}972), while the Rt gradually down trended from 1{middle dot}665 (95%CI 1{middle dot}539-1{middle dot}789) on 30 March to 1{middle dot}159 (95% CI 1{middle dot}128-1{middle dot}189) on 21 April. 60{middle dot}7% of confirmed COVID-19 cases in our sample were found to be asymptomatic. We observed that delaying the lockdown relaxation increases the time to new rise in active cases after the relaxation in a linear fashion. If lockdown was reintroduced after a fixed relaxation period, the magnitude of the second peak could be reduced by delaying the relaxation and decreasing the duration of relaxation. These benefits were greater in case of a gradual relaxation as compared to a sudden lifting of lockdown. We found that detecting a higher proportion of cases through testing significantly decreases the total infections. This positive impact of testing progressively increased at higher transmission rates when restrictions were relaxed. We found that similar containment targets could be achieved by both, a combination of high testing and less social restrictions, and a combination of lower testing with intensive social distancing.  The nationwide social distancing interventions in India since 25 March have reduced the effective transmission levels, though sub-threshold Rt remains to be achieved. If lockdown is to be extended, additional benefits for mitigating the second wave can be achieved if it is extended farther after the peak of active cases has passed. Intensive social distancing is inherently enough to contain the epidemic, however, testing will play a pivotal role in the lockdown exit strategy by impeding the epidemic growth enough to allow for a greater resumption of socio-economic activities, thus minimizing the social and economic fallout resulting from severe restrictions. Considering that asymptomatics play an undeniable role in the transmission of COVID-19, dependence on presence of symptoms for control strategies, behavioural changes and testing should be reduced.

title: World governments should protect their population from COVID-19 pandemic using Italy and Lombardy as precursor
abstract: The COVID-19 pandemic is spreading worldwide. Italy emerged early on as the country with the largest outbreak outside Asia. The outbreak in Northern Italy demonstrates that it is fundamental to contain the virus' spread at a very early stage of diffusion. At later stages, no containment measure, even if strict, can prevent the saturation of the hospitals and of the intensive care units in any country. Here we show that it is possible to predict when the intensive care units will saturate, within a few days from the first cases of COVID-19 intensive care patients. Using early counts of intensive care patients, we predict the saturation for Lombardy, Italy. Governments should use the Italian precursor to control the outbreak of COVID-19 and prevent the saturation of their intensive care units to protect their population.

title: Hindsight is 2020 vision: Characterisation of the global response to the COVID-19 pandemic
abstract: Since the initial outbreak in Wuhan (Hubei, China) in December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), has rapidly spread to cause one of the most pressing challenges facing our world today: the COVID-19 pandemic. Within four months of the first reported cases, more than two and a half million cases were confirmed with over two hundred thousand deaths globally, and many countries had taken extreme measures to stop the spread. In this work, we analyse the response to the COVID-19 outbreak for 103 countries over the period 22 January to 13 April 2020. We utilise a novel stochastic epidemiological model that includes a regulatory mechanism that captures the level of tolerance to rising confirmed cases within the response behaviour. Using approximate Bayesian computation, we identify that the top ten outbreaks as of 31 March are characterised by a high tolerance to rising cases tallies, whereas countries that avoided severe outbreak have a low tolerance. Countries that recovered rapidly also have a higher identification rate. As of 13 April, almost all countries show declines in transmission rates and basic reproductive numbers. Furthermore, countries approaching recovery also increased their identification rate between 31 March and 13 April. We also demonstrate that uncertainty in undocumented infections dramatically impacts uncertainty in predictions. Overall, we recommend that broader testing is required to understand the magnitude of undocumented infections.

title: Will novel virus go pandemic or be contained?

title: Self-screening to reduce medical resource consumption facing the COVID-19 pandemic

title: [Several suggestion of operation for colorectal cancer under the outbreak of Corona Virus Disease 19 in China].
abstract: Pneumonia caused by SARS-Cov-2 infection has been reported in Wuhan since December 2019, and spread rapidly across the country. The radical operation of colorectal cancer is confine operation. Patients with colorectal cancer should receive operation as soon as possible after elective operation is resumed in each hospital. SARS-Cov-2 virus can be transmitted by asymptomatic infectors, and it has been confirmed to be transmitted by droplets and contact. However, fecal-oral transmission and aerosol transmission have not been excluded. Based onLaparoscopic colorectal operation experiences, the author suggests that the surgery strategy for colorectal cancer patients under the COVID-19 situation. Recommending laparoscopy-assisted radical surgery for colorectal cancer patients. The aerosols need to be strictly managed during operation. NOSES and TaTME should be carried out with cautious during the epidemic period. Protective stoma should be carried out scientifically and reasonably, and the protection of operating room personnel should be strengthened.

title: Ocular manifestations and clinical characteristics of 534 cases of COVID-19 in China: A cross-sectional study
abstract: The novel coronavirus disease (COVID-19) was first reported in Wuhan, China in December 2019 and is now pandemic all over the world. Previous study has reported several COVID-19 cases with conjunctivitis. However, the complete profiling of COVID-19 related ocular symptoms and diseases are still missing. We aim to investigate the ocular manifestations and clinical characteristics of COVID-19 patients.  A total of five hundred and thirty-four patients were recruited at Mobile Cabin Hospital and Tongji Hospital. We collected information on demographic characteristics, exposure history, ocular symptoms, systemic concomitant symptoms, eye drop medication, eye protections, radiologic findings, and SARS-CoV-2 detection in nasopharyngeal swabs by RT-PCR from questionnaires and electronic medical records.  The median age of patients was 40 and 50 years at Mobile Cabin Hospital and Tongji Hospital, respectively. Of 534 COVID-19 patients, 25 patients (4.68%) presented with conjunctival congestion and 3 patients had conjunctival congestion as the initial symptom. The average duration of conjunctival congestion was 4.9 {+/-} 2.6 days (mean [SD]), ranging from 2 to 10 days. Dry eye (112, 20.97%), blurred vision (68, 12.73%), and foreign body sensation (63, 11.80%) ranked as the top three COVID-19 related ocular symptoms. Notably, a total of 332 COVID-19 patients (62%) had a hand-eye contact history. We also found that some COVID-19 patients had a history of eye disease, including conjunctivitis (33, 6.18%), dry eye (24, 4.49%), keratitis (14, 2.62%), cataract (9, 1.69%), and diabetic retinopathy (5, 0.94%). In consistent with previous studies, the most common clinical symptoms were fever, cough, and fatigue. Patients, 60.5% in Mobile Cabin Hospital and 67.5% in Tongji Hospital, respectively were confirmed with positive SARS-CoV-2 detection.  Conjunctival congestion was one of the COVID-19 related ocular symptoms, which may have clinical diagnostic significance. It is essential to provide eye-care equipment and strengthen education on eye protection, as dirty hand-eye contact might be a high risk factor of COVID-19. Further detailed and comprehensive ophthalmological guidance is needed for COVID-19 control.

title: Estimation of COVID-19 burden in Egypt

title: Use of the Demographic and Health Survey framework as a population surveillance strategy for COVID-19

title: Post-exposure prophylaxis or pre-emptive therapy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): study protocol for a pragmatic randomized-controlled trial
abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 causing the coronavirus disease (COVID-19) pandemic. Currently, there is a lack of evidence-based therapies to prevent COVID-19 following exposure to the virus, or to prevent worsening of symptoms following confirmed infection. We describe the design of a clinical trial of hydroxychloroquine for post-exposure prophylaxis (PEP) and pre-emptive therapy (PET) for COVID-19.  We will conduct two nested multicentre international double-blind randomized placebo-controlled clinical trials of hydroxychloroquine for: 1) PEP of asymptomatic household contacts or healthcare workers exposed to COVID-19 within the past four days, and 2) PET for symptomatic outpatients with COVID-19 showing symptoms for less than four days. We will recruit 1,500 patients each for the PEP and PET trials. Participants will be randomized 1:1 to receive five days of hydroxychloroquine or placebo. The primary PEP trial outcome will be the incidence of symptomatic COVID-19. The primary PET trial outcome will be an ordinal scale of disease severity (not hospitalized, hospitalized without intensive care, hospitalization with intensive care, or death). Participant screening, informed consent, and follow-up will be exclusively internet-based with appropriate regulatory and research ethics board approvals in Canada and the United States.  These complementary randomized-controlled trials are innovatively designed and adequately powered to rapidly answer urgent questions regarding the effectiveness of hydroxychloroquine to reduce virus transmission and disease severity of COVID-19 during a pandemic. In-person participant follow-up will not be conducted to facilitate social distancing strategies and reduce risks of exposure to study personnel. Innovative trial approaches are needed to urgently assess therapeutic options to mitigate the global impact of this pandemic.

title: Immunology of COVID-19: current state of the science
abstract: The coronavirus disease 2019 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has affected millions of people worldwide, igniting an unprecedented effort from the scientific community to understand the biological underpinning of COVID19 pathophysiology. In this review, we summarize the current state of knowledge of innate and adaptive immune responses elicited by SARS-CoV-2 infection and the immunological pathways that likely contribute to disease severity and death. We also discuss the rationale and clinical outcome of current therapeutic strategies as well as prospective clinical trials to prevent or treat SARS-CoV-2 infection.

title: COVID-19-New Insights on a Rapidly Changing Epidemic.

title: Standardization and Age-Distribution of COVID-19: Implications for Variability in Case Fatality and Outbreak Identification
abstract: Epidemiological data from the COVID-19 pandemic has demonstrated variability in attack rates by age, and country-to-country variability in case fatality ratio (CFR).  To use direct and indirect standardization for insights into the impact of age-specific under-reporting on between-country variability in CFR, and apparent size of COVID-19 epidemics.  Post-hoc secondary data analysis (case studies), and mathematical modeling.  China, global.  None.  Data were extracted from a sentinel epidemiological study by the Chinese Center for Disease Control (CCDC) that describes attack rates and CFR for COVID-19 in China prior to February 12, 2020. Standardized morbidity ratios (SMR) were used to impute missing cases and adjust CFR. Age-specific attack rates and CFR were applied to different countries with differing age structures (Italy, Japan, Indonesia, and Egypt), in order to generate estimates for CFR, apparent epidemic size, and time to outbreak recognition for identical age-specific attack rates.  SMR demonstrated that 50-70% of cases were likely missed during the Chinese epidemic. Adjustment for under-recognition of younger cases decreased CFR from 2.4% to 0.8% (assuming 50% case ascertainment in older individuals). Standardizing the Chinese epidemic to countries with older populations (Italy, and Japan) resulted in larger apparent epidemic sizes, higher CFR and earlier outbreak recognition. The opposite effect was demonstrated for countries with younger populations (Indonesia, and Egypt).  Secondary data analysis based on a single country at an early stage of the COVID-19 pandemic, with no attempt to incorporate second order effects (ICU saturation) on CFR.  Direct and indirect standardization are simple tools that provide key insights into between-country variation in the apparent size and severity of COVID-19 epidemics.

title: Counting Coronavirus Disease 2019 (COVID-19) Cases: Case Definitions, Screened Populations and Testing Techniques Matter.
abstract: While counting cases of disease appears straightforward, there are issues to consider when enumerating disease counts during an epidemic. For example, for Coronavirus Disease-2019 (COVID-19), how is a case defined? Hubei province in China changed its case definition twice in a fortnight-from laboratory-confirmed cases to clinically-confirmed cases without laboratory tests, and back to laboratory-confirmed cases. This caused confusion in the reported number of cases. If a confirmed case requires laboratory testing, what is the population who are laboratory-tested? Due to limited laboratory testing capacity in the early phase of an emerging epidemic, only "suspected cases" are laboratory-tested in most countries. This will result in underdiagnosis of confirmed cases and also raises the question: how is a "suspect case" defined? With the passage of time and increased capability to perform laboratory tests, more people can be screened and the number of confirmed cases will increase. What are the technical considerations of laboratory testing? This includes specimen collection (variable collection methods), samples collected (upper or lower respiratory tract biospecimens), time of collection in relation to course of disease, different laboratory test methods and kits (not all of which may be standardised or approved by authorities such as the Food and Drug Administration). Are approved laboratory facilities and trained manpower available, and how are test results interpreted and false-negatives excluded? These issues will affect the accuracy of disease counts, which in turn will have implications on how we mount an appropriate response to the outbreak.

title: Final 2013 Reports of Nationally Notifiable Infectious Diseases

title: COVID-19 epidemic in Malaysia: Impact of lock-down on infection dynamics
abstract: COVID-19 epidemic in Malaysia started as a small wave of 22 cases in January 2020 through imported cases. It was followed by a bigger wave mainly from local transmissions resulting in 651 cases. The following wave saw unexpectedly three digit number of daily cases following a mass gathering urged the government to choose a more stringent measure. A limited lock-down approach called Movement Control Order (MCO) was immediately initiated to the whole country as a way to suppress the epidemic trajectory. The lock-down causes a major socio-economic disruption thus the ability to forecast the infection dynamic is urgently required to assist the government on timely decisions. Limited testing capacity and limited epidemiological data complicate the understanding of the future infection dynamic of the COVID-19 epidemic. Three different epidemic forecasting models was used to generate forecasts of COVID-19 cases in Malaysia using daily reported cumulative case data up until 1st April 2020 from the Malaysia Ministry of Health. The forecasts were generated using a Curve Fitting Model with Probability Density Function and Skewness Effect, the SIR Model, and a System Dynamic Model. Method one based on curve fitting with probability density function estimated that the peak will be on 19th April 2020 with an estimation of 5,637 infected persons. Method two based on SIR Model estimated that the peak will be on 20th - 31st May 2020 if Movement Contro (MCO) is in place with an estimation of 630,000 to 800,000 infected persons. Method three based on System Dynamic Model estimated that the peak will be on 17th May 2020 with an estimation of 22,421 infected persons. Forecasts from each of model suggested the epidemic may peak between middle of April to end of May 2020.  COVID-19, Infection dynamic, Prediction Modeling, SIR, System Learning, Lock-down

title: Covid-19 Incidence Rate Evolution Modeling using Dual Wave Gaussian-Lorentzian Composite Functions
abstract: Modeling the evolution of Covid-19 incidence rate is critical to deciding and assessing non-medical intervention strategies that can lead to successful containment of the pandemic. This research presents a mathematical model to empirically assess measures related to various pandemic containment strategies, their similarities and a probabilistic estimate on the evolution of Covid-19 incidence rates. The model is built on the principle that, the exponential rise and decay of the number of confirmed Covid-19 infections can be construed as a set of concurrent non-linear waves. These waves can be characterized by a linear combination of Gaussian and Cauchy Lorentz functions collectively termed as Gaussian-Lorentzian Composite (GLC) function. The GLC function is used for non-linear approximation of officially confirmed Covid-19 incidence rates in each country. Results of fitting GLC based models to incidence rate trends of 20 different countries proves that the models can empirically explain the growth and decay trajectory Covid-19 infections in a given population.

title: Application and optimization of RT-PCR in diagnosis of SARS-CoV-2 infection
abstract: Coronavirus Disease 2019 (COVID-19) caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat to public health. Aiming to construct an efficient screening pattern, we comprehensively evaluated the performances of RT-PCR and chest CT in diagnosing COVID-19.  The records including demographics, RT-PCR, and CT from 87 confirmed COVID-19 cases and 481 exclusion cases were collected. The diagnostic accuracy of the pharyngeal swab RT-PCR, CT, combination with the second pharyngeal swab RT-PCR or with CT were evaluated individually. Besides, all the stool RT-PCR results were plotted by time to explore the value of stool RT-PCR.  Combination of RT-PCR and CT has the higher sensitivity (91.9%,79/86) than RT-PCR alone (78.2%，68/87) or CT alone (66.7%, 54 of 81) or combination of two RT-PCR tests (86.2%,75/87). There was good agreement between RT-PCR and CT (kappa-value, 0.430). In 34 COVID-19 cases with inconsistent results, 94.1% (n=32) are mild infection, 62.5% of which (20/32) showed positive RT-PCR. 46.7% (35/75) COVID-19 patients had at least one positive stool during the course. Two cases had positive stool earlier than the pharyngeal swabs. Importantly, one patient had consecutive positive stool but negative pharyngeal swabs.  Combination of RT-PCR and CT with the highest sensitivity is an optimal pattern to screen COVID-19. RT-PCR is superior to CT in diagnosing mild infections. Stool RT-PCR should be considered as an item for improving discovery rate and hospital discharge. This study shed light for optimizing scheme of screening and monitoring of SARS-CoV-2 infection.

title: Can COVID-19 present unusual GI symptoms?

title: Nelfinavir inhibits replication of severe acute respiratory syndrome coronavirus 2 in vitro
abstract: In December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, Hubei Province, China. No specific treatment has been established against coronavirus disease-2019 (COVID-19) so far. Therefore, it is urgently needed to identify effective antiviral agents for the treatment of this disease, and several approved drugs such as lopinavir have been evaluated. Here, we report that nelfinavir, an HIV-1 protease inhibitor, potently inhibits replication of SARS-CoV-2. The effective concentrations for 50% and 90% inhibition (EC50 and EC90) of nelfinavir were 1.13 µM and 1.76 µM respectively, the lowest of the nine HIV-1 protease inhibitors including lopinavir. The trough and peak serum concentrations of nelfinavir were three to six times higher than EC50 of this drug. These results suggest that nelfinavir is a potential candidate drug for the treatment of COVID-19 and should be assessed in patients with COVID-19.

title: A Literature Review and Survey of Childhood Pneumonia Etiology Studies: 2000–2010
abstract: The Pneumonia Etiology Research for Child Health (PERCH) project is the largest multicountry etiology study of childhood pneumonia since the Board on Science and Technology in International Development studies of the 1980s. However, it is not the only recent or ongoing pneumonia etiology study, and even with seven sites, it cannot capture all epidemiologic settings in the developing world. Funding providers, researchers and policymakers rely on the best available evidence to strategically plan programs, new research directions and interventions. We aimed to describe the current landscape of recent pneumonia etiology studies in children under 5 years of age in the developed and developing world, as ascertained by a literature review of relevant studies with data since the year 2000 and a survey of researchers in the field of childhood pneumonia. We collected information on the study population, study design, case definitions, laboratory samples and methods and identified pathogens. A literature review identified 88 studies with child pneumonia etiology results. As of June 2010, our survey of researchers identified an additional 65 ongoing and recently completed child pneumonia etiology studies. This demonstrates the broad existing context into which the PERCH study must be placed. However, the landscape analysis also reveals a multiplicity of case definitions, levels of clinician involvement, facility types, specimen collection, and laboratory techniques. It reinforces the need for the standardization of methods and analyses for present and future pneumonia etiology studies in order to optimize their cumulative potential to accurately describe the microbial causes of childhood pneumonia.

title: Lack of Antiviral Activity of Darunavir against SARS-CoV-2
abstract: Given the high need and the absence of specific antivirals for treatment of COVID-19 (the disease caused by severe acute respiratory syndrome-associated coronavirus-2 [SARS-CoV-2]), human immunodeficiency virus (HIV) protease inhibitors are being considered as therapeutic alternatives. Prezcobix/Rezolsta is a fixed-dose combination of 800 mg of the HIV protease inhibitor darunavir (DRV) and 150 mg cobicistat, a CYP3A4 inhibitor, which is indicated in combination with other antiretroviral agents for the treatment of HIV infection. There are currently no definitive data on the safety and efficacy of DRV/cobicistat for treatment of COVID-19. The in vitro antiviral activity of darunavir against a clinical isolate from a patient infected with SARS-CoV-2 was assessed. DRV showed no activity against SARS-CoV-2 at clinically relevant concentrations (EC50 >100 μM). Remdesivir, used as a positive control, showed potent antiviral activity (EC50 = 0.38 μM). Overall, the data do not support the use of DRV for treatment of COVID-19.

title: JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation
abstract: Recently, the novel coronavirus 2019 (COVID-19) has caused a pandemic disease over 200 countries, influencing billions of humans. To control the infection, the first and key step is to identify and separate the infected people. But due to the lack of Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests, it is essential to discover suspected COVID-19 patients via CT scan analysis by radiologists. However, CT scan analysis is usually time-consuming, requiring at least 15 minutes per case. In this paper, we develop a novel Joint Classification and Segmentation (JCS) system to perform real-time and explainable COVID-19 diagnosis. To train our JCS system, we construct a large scale COVID-19 Classification and Segmentation (COVID-CS) dataset, with 144,167 CT images of 400 COVID-19 patients and 350 uninfected cases. 3,855 CT images of 200 patients are annotated with fine-grained pixel-level labels, lesion counts, infected areas and locations, benefiting various diagnosis aspects. Extensive experiments demonstrate that, the proposed JCS diagnosis system is very efficient for COVID-19 classification and segmentation. It obtains an average sensitivity of 95.0% and a specificity of 93.0% on the classification test set, and 78.3% Dice score on the segmentation test set, of our COVID-CS dataset. The online demo of our JCS diagnosis system will be available soon.

title: Genetic relatedness of the novel human group C betacoronavirus to Tylonycteris bat coronavirus HKU4 and Pipistrellus bat coronavirus HKU5
abstract: The recent outbreak of severe respiratory infections associated with a novel group C betacoronavirus (HCoV-EMC) from Saudi Arabia has drawn global attention to another highly probable “SARS-like” animal-to-human interspecies jumping event in coronavirus (CoV). The genome of HCoV-EMC is most closely related to Tylonycteris bat coronavirus HKU4 (Ty-BatCoV HKU4) and Pipistrellus bat coronavirus HKU5 (Pi-BatCoV HKU5) we discovered in 2006. Phylogenetically, HCoV-EMC is clustered with Ty-BatCoV HKU4/Pi-BatCoV HKU5 with high bootstrap supports, indicating that HCoV-EMC is a group C betaCoV. The major difference between HCoV-EMC and Ty-BatCoV HKU4/Pi-BatCoV HKU5 is in the region between S and E, where HCoV-EMC possesses five ORFs (NS3a-NS3e) instead of four, with low (31%–62%) amino acid identities to Ty-BatCoV HKU4/Pi-BatCoV HKU5. Comparison of the seven conserved replicase domains for species demarcation shows that HCoV-EMC is a novel CoV species. More intensive surveillance studies in bats and other animals may reveal the natural host of HCoV-EMC.

title: Utilization and Appropriateness of Transthoracic Echocardiography In Response to the COVID-19 Pandemic

title: Which Kind of Provider’s Operation Volumes Matters? Associations between CABG Surgical Site Infection Risk and Hospital and Surgeon Operation Volumes among Medical Centers in Taiwan
abstract: Volume-infection relationships have been examined for high-risk surgical procedures, but the conclusions remain controversial. The inconsistency might be due to inaccurate identification of cases of infection and different methods of categorizing service volumes. This study takes coronary artery bypass graft (CABG) surgical site infections (SSIs) as an example to examine whether a relationship exists between operation volumes and SSIs, when different SSIs case identification, definitions and categorization methods of operation volumes were implemented.  A population-based cross-sectional multilevel study was conducted. A total of 7,007 patients who received CABG surgery between 2006 and 2008 from19 medical centers in Taiwan were recruited. SSIs associated with CABG surgery were identified using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9 CM) codes and a Classification and Regression Trees (CART) model. Two definitions of surgeon and hospital operation volumes were used: (1) the cumulative CABG operation volumes within the study period; and (2) the cumulative CABG operation volumes in the previous one year before each CABG surgery. Operation volumes were further treated in three different ways: (1) a continuous variable; (2) a categorical variable based on the quartile; and (3) a data-driven categorical variable based on k-means clustering algorithm. Furthermore, subgroup analysis for comorbidities was also conducted.  This study showed that hospital volumes were not significantly associated with SSIs, no matter which definitions or categorization methods of operation volume, or SSIs case identification approaches were used. On the contrary, the relationships between surgeon’s volumes varied. Most of the models demonstrated that the low-volume surgeons had higher risk than high-volume surgeons.  Surgeon volumes were more important than hospital volumes in exploring the relationship between CABG operation volumes and SSIs in Taiwan. However, the relationships were not robust. Definitions and categorization methods of operation volume and correct identification of SSIs are important issues for future research.

title: Prevalence of acute liver injury and hypertransaminemia in patients with COVID-19: a protocol for a systematic review
abstract: COVID-19 has spread rapidly in China and around the world. Published studies have revealed that some patients with COVID-19 had abnormal liver function in laboratory tests. However, the results were inconsistent and the analysis of epidemiological data stratified by the severity of COVID-19 was not available in previous meta-analyses. Furthermore, these meta-analyses were suspected of overestimating the incidence of liver injury in patients with COVID-19 because some studies considered transaminase elevation as liver injury, which might partially result from cardiac and muscle injury. This systematic review aims to enrol published literatures related to COVID-19 without language restriction, analyse the data based on the severity of the COVID-19 and explore the impact of varied definitions of liver injury on the incidence of liver injury.  We have conducted a preliminary search on PubMed and Excerpta Medica Database on 13 April 2020, for the studies published after December 2019 on the prevalence of acute liver injury and hypertransaminemia in patients with COVID-19. Two reviewers will independently screen studies, extract data and assess the risk of bias. We will estimate the pooled incidence of hypertransaminemia and acute liver injury in patients with COVID-19 by using the random-effects model. The I(²) test will be used to identify the extent of heterogeneity. Publication bias will be assessed by funnel plot and performing the Begg’s and Egger’s test if adequate studies are available. We will perform a risk of bias assessment using the Joanna Briggs Institute’s critical appraisal checklist.  Since this study will be based on the published data, it does not require ethical approval. The final results of this study will be published in a peer-reviewed journal.

title: Detection of Middle East respiratory syndrome coronavirus using reverse transcription loop-mediated isothermal amplification (RT-LAMP)
abstract: The first documented case of Middle East Respiratory Syndrome coronavirus (MERS-CoV) occurred in 2012, and outbreaks have continued ever since, mainly in Saudi Arabia. MERS-CoV is primarily diagnosed using a real-time RT-PCR assay, with at least two different genomic targets required for a positive diagnosis according to the case definition of The World Health Organization (WHO) as of 3 July 2013. Therefore, it is urgently necessary to develop as many specific genetic diagnostic methods as possible to allow stable diagnosis of MERS-CoV infections.  Reverse transcription-loop-mediated isothermal amplification (RT-LAMP) is a genetic diagnostic method used widely for the detection of viral pathogens, which requires only a single temperature for amplification, and can be completed in less than 1 h. This study developed a novel RT-LAMP assay for detecting MERS-CoV using primer sets targeting a conserved nucleocapsid protein region.  The RT-LAMP assay was capable of detecting as few as 3.4 copies of MERS-CoV RNA, and was highly specific, with no cross-reaction to other respiratory viruses. Pilot experiments to detect MERS-CoV from medium containing pharyngeal swabs inoculated with pre-titrated viruses were also performed. The RT-LAMP assay exhibited sensitivity similar to that of MERS-CoV real-time RT-PCR.  These results suggest that the RT-LAMP assay described here is a useful tool for the diagnosis and epidemiologic surveillance of human MERS-CoV infections.

title: A novel comprehensive metric to assess COVID-19 testing outcomes: Effects of geography, government, and policy response
abstract: Testing and case identification are key strategies in controlling the COVID-19 pandemic. Contact tracing and isolation are only possible if cases have been identified. The effectiveness of testing must be tracked, but a single comprehensive metric is not available to assess testing effectiveness, and no timely estimates of case detection rate are available globally, making inter-country comparisons difficult. The purpose of this paper was to propose a single, comprehensive metric, called the COVID-19 Testing Index (CovTI) scaled from 0 to 100, that incorporated several testing metrics. The index was based on case-fatality rate, test positivity rate, active cases, and an estimate of the detection rate. It used parsimonious modeling to estimate the true total number of COVID-19 cases based on deaths, testing, health system capacity, and government transparency. Publicly reported data from 188 countries and territories were included in the index. Estimates of detection rates aligned with previous estimates in literature (R2=0.97). As of June 3, 2020, the states with the highest CovTI included Iceland, Australia, New Zealand, Hong Kong, and Thailand, and some island nations. Globally, CovTI increased from April 20 ([x]=43.2) to June 3 ([x]=52.2) but declined in ca. 10% of countries. Bivariate analyses showed the average in countries with open public testing policies (59.7, 95% CI 55.6-63.8) were significantly higher than countries with no testing policy (30.2, 95% CI 18.1-42.3) (p<0.0001). A multiple linear regression model assessed the association of independent grouping variables with CovTI. Open public testing and extensive contact tracing were shown to significantly increase CovTI, after adjusting for extrinsic factors, including geographic isolation and centralized forms of government. This tool may be useful for policymakers to assess testing effectiveness, inform decisions, and identify model countries. It may also serve as a tool for researchers in analyses by combining it with other databases.

title: Host response-based screening to identify undiagnosed cases of COVID-19and expand testing capacity
abstract: The COVID-19 pandemic has created unprecedented challenges in diagnostic testing. At the beginning of the epidemic, a confluence of factors resulted in delayed deployment of PCR-based diagnostic tests, resulting in lack of testing of individuals with symptoms of the disease. Although these tests are now more widely available, it is estimated that a three- to ten-fold increase in testing capacity will be required to ensure adequate surveillance as communities reopen(1). In response to these challenges, we evaluated potential roles of host-response based screening in the diagnosis of COVID-19. Previous work from our group showed that the nasopharyngeal (NP) level of CXCL10, a protein produced as part of the host response to viral infection, is a sensitive predictor of respiratory virus infection across a wide spectrum of viruses(2). Here, we show that NP CXCL10 is elevated during SARS-CoV-2 infection and use a CXCL10-based screening strategy to identify four undiagnosed cases of COVID-19 in Connecticut in early March. In a second set of samples tested at the Yale New Haven Hospital, we show that NP CXCL10 had excellent performance as a rule-out test (NPV 0.99, 95% C.I. 0.985-0.997). Our results demonstrate how biomarker-based screening could be used to leverage existing PCR testing capacity to rapidly enable widespread testing for COVID-19.

title: Hundreds of severe pediatric COVID-19 infections in Wuhan prior to the lockdown
abstract: Before January 22, 2020, only one pediatric case of COVID-19 was reported in mainland China. However, a retrospective surveillance study identified six children who had been hospitalized for COVID-19 in one of three central Wuhan hospitals between January 7th and January 15th. Given that Wuhan has over 395 other hospitals, there may have been far more severe pediatric cases than reported. There were six and 43 children out of 336 who tested positive for COVID-19 and influenza, respectively among all pediatric admissions during the 9-day period. By using this ratio in a detailed analysis of influenza surveillance data and COVID-19 epidemic dynamics , we estimate that there were 313 [95% CI: 171-520] children hospitalized for COVID-19 in Wuhan during January 7-15, 2020 . Under an epidemic doubling time of 7.31 days4, we estimate that there were 1105 [95% CI: 592, 1829] cumulative pediatric COVID-19 hospitalizations prior to the January 23rd lockdown, which far surpasses the 425 confirmed cases reported across all age groups, none of which were children under age 15. Children are strikingly absent from COVID-19 reports and limited data suggest that pediatric infections are overwhelmingly mild5. Thus, our estimates for hundreds of severe pediatric cases likely translates to thousands or even tens of thousands of mildly infected children, suggesting that the force of infection from children may be grossly underestimated and the infection fatality rate overestimated from confirmed case counts alone. This highlights the urgent need for more robust surveillance to gauge the true extent and severity of COVID-19 in all ages.

title: SARS-CoV-2 infection in 86 healthcare workers in two Dutch hospitals in March 2020
abstract: On February 27, 2020, the first patient with COVID-19 was reported in the Netherlands. During the following weeks, nine healthcare workers (HCWs) were diagnosed with COVID-19 in two Dutch teaching hospitals, eight of whom had no history of travel to China or Northern-Italy. A low-threshold screening regimen was implemented to determine the prevalence and clinical presentation of COVID-19 among HCWs in these two hospitals.  HCWs who suffered from fever or respiratory symptoms were voluntarily tested for SARS-CoV-2 by real-time reverse-transcriptase PCR on oropharyngeal samples. Structured interviews were conducted to document symptoms for all HCWs with confirmed COVID-19.  Thirteen-hundred fifty-three (14%) of 9,705 HCWs employed were tested, 86 (6%) of whom were infected with SARS-CoV-2. Most HCWs suffered from relatively mild disease and only 46 (53%) reported fever. Seventy-nine (92%) HCWs met a case definition of fever and/or coughing and/or shortness of breath. None of the HCWs identified through the screening reported a travel history to China or Northern Italy, and 3 (3%) reported to have been exposed to an inpatient known with COVID-19 prior to the onset of symptoms.  Within two weeks after the first Dutch case was detected, a substantial proportion of HCWs with fever or respiratory symptoms were infected with SARS-CoV-2, probably caused by acquisition of the virus in the community during the early phase of local spread. The high prevalence of mild clinical presentations, frequently not including fever, asks for less stringent use of the currently recommended case-definition for suspected COVID-19.

title: POOLING FOR SARS-CoV-2 CONTROL IN CARE INSTITUTIONS
abstract: Workers and residents in Care Homes are considered at special risk for the acquisition of SARS-CoV-2 infection, due to the infectivity and high mortality rate in the case of residents, compared to other containment areas. The aims of the present study, based in our local experience, were (a) to describe SARS-CoV-2 prevalence in institutionalized people in Galicia (Spain) during the Coronavirus pandemic and (b) to evaluate the expected performance of a pooling strategy using RT-PCR for the next rounds of screening of institutionalized people. Distribution of SARS-CoV-2 infection at Care Houses was uneven. As the virus circulation global rate was low in our area, the number of people at risk of acquiring the infection continues to be very high. In this work, we have successfully demonstrated that pooling of different groups of samples at low prevalence clusters, can be done with a small average delay on quantification cycle (Cq) values. A new surveillance system with guaranteed protection is required for small clusters, previously covered with individual testing. Our proposal for Care Houses, once prevalence zero is achieved, would include successive rounds of testing using a pooling solution for transmission control preserving testing resources. Scale-up of this method may be of utility to confront larger clusters to avoid the viral circulation and keeping them operative.

title: Influenza-Negative Influenza-Like Illness (fnILI) Z-Score as a Proxy for Incidence and Mortality of COVID-19
abstract: Though ideal for determining the burden of disease, SARS-CoV2 test shortages preclude its implementation as a robust surveillance system in the US. We correlated the use of the derivative influenza-negative influenza-like illness (fnILI) z-score from the CDC as a proxy for incident cases and disease-specific deaths. For every unit increase of fnILI z-score, the number of cases increased by 70.2 (95%CI[5.1,135.3]) and number of deaths increased by 2.1 (95%CI[1.0,3.2]). FnILI data may serve as an accurate outcome measurement to track the spread of the and allow for informed and timely decision-making on public health interventions.

title: Testing for COVID-19: a few points to remember.
abstract: Diagnostic approaches to COVID-19 include clinical history, PCR tests for the presence of SARS-CoV-2 virus and detection of antibodies. By combining these three approaches, the seroprevalence of anti-SARS-CoV-2 antibodies can be examined in healthcare teams. The aim of the study was to examine the seroprevalence of anti-SARS-CoV-2 antibodies in a population of healthcare professionals 6 - 8 weeks after the first COVID-19 case was detected in the Czech Republic. A total of 269 subjects were enrolled in the study (187 women, 82 men) with a median age of 45.9 years (21 - 71 years). We used a questionnaire to ascertain travel history and clinical signs of any respiratory tract infection. Blood samples were collected, and IgG levels were analysed in all samples. The level of IgA antibodies was analysed in those positive for IgG. PCR testing was performed in cases testing positive for presence of antibodies. The enzyme-linked immunosorbent assay (ELISA) test system for SARS-CoV-2 from Euroimmun (Germany) was used to analyse immunoglobulin levels. 17 % of the tested cohort reported symptoms compatible with COVID-19 and 35.8 % reported history of international travel. There were 5 subjects positive IgG cases (of 269; 1.85 %), and one IgA positive and IgG borderline positive subject (0.37 %). There was only one PCR positive subject. Anti SARS-CoV-2 antibodies were thus detected in 2.22% of participating health professionals. This article shows the pitfalls of the testing methods and highlights the necessity of using a correct testing algorithm, considering the character of the tested population and the expected low prevalence.

title: Outdoor Air Pollutant Concentration and COVID-19 Infection in Wuhan, China
abstract: COVID-19 infection, first reported in Wuhan, China in December 2019, has become a global pandemic, causing significantly high infections and mortalities in Italy, the UK, the US, and other parts of the world. Based on the statistics reported by John Hopkins University, 4.7M people worldwide and 84,054 people in China have been confirmed positive and infected with COVID-19, as of 18 May 2020. Motivated by the previous studies which show that the exposures to air pollutants may increase the risk of influenza infection, our study examines if such exposures will also affect Covid-19 infection. To the best of our understanding, we are the first group in the world to rigorously explore the effects of outdoor air pollutant concentrations, meteorological conditions and their interactions, and lockdown interventions, on Covid-19 infection in China. Since the number of confirmed cases is likely to be under-reported due to the lack of testing capacity, the change in confirmed case definition, and the undiscovered and unreported asymptotic cases, we use the rate of change in the daily number of confirmed infection cases instead as our dependent variable. Even if the number of reported infections is under-reported, the rate of change will still accurately reflect the relative change in infection, provided that the trend of under-reporting remains the same. In addition, the rate of change in daily infection cases can be distorted by the government imposed public health interventions, including the lockdown policy, inter-city and intra-city mobility, and the change in testing capacity and case definition. Hence, the effects of the lockdown policy and the inter-city and intra-city mobility, and the change in testing capacity and case definition are all taken into account in our statistical modelling. Furthermore, we adopt the generalized linear regression models covering both the Negative Binomial Regression and the Poisson Regression. These two regression models, when combined with different time-lags (to reflect the COVID-19 incubation period and delay due to official confirmation) in air pollutant exposure (PM2.5), are used to fit the COVID-19 infection model. Our statistical study has shown that higher PM2.5 concentration is significantly correlated with a higher rate of change in the daily number of confirmed infection cases in Wuhan, China (p < 0.05). We also determine that a higher dew point interacting with a higher PM2.5 concentration is correlated with a higher rate of change in the daily number of confirmed infection cases, while a higher UV index and a higher PM2.5 concentration are correlated with a lower rate of change. Furthermore, we find that PM2.5 concentration eight days ago has the strongest predictive power for COVID-19 Infection. Our study bears significance to the understanding of the effect of air pollutant (PM2.5) on COVID-19 infection, the interaction effects of both the air pollutant concentration (PM2.5) and the meteorological conditions on the rate of change in infection, as well as the insights into whether lockdown should have an effect on COVID-19 infection.

title: Preparing for the Unthinkable: Emergency Preparedness for the Hematopoietic Cell Transplant Program
abstract: Emergencies come at the most inopportune times. Some are totally unexpected, others come with short warnings. Although rare, an emergency comes with the potential to wreak disaster and pose serious risk to the services provided to hematopoietic cell transplant (HCT) patients. Yet, the consequences of an emergency can be mitigated by thinking the unthinkable and having a plan for emergency preparedness in place. Each HCT center should develop a plan containing steps of mitigation, preparedness, response and recovery. This report provides the framework for a HCT-specific emergency preparedness plan that can be used by individual centers to develop customized guidelines on preparing for, responding to, and recovering from an emergency.

title: The effect of inter-city travel restrictions on geographical spread of COVID-19: Evidence from Wuhan, China
abstract: To contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020, restricting travel to other parts of China. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China.  We estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to March 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios representing the effect of local non-pharmaceutical interventions.  In the four cities, given the potentially high prevalence of COVID-19 in Wuhan between Dec 2019 and early Jan 2020, local transmission may have been seeded as early as 2 - 8 January 2020. By the time the cordon sanitaire was imposed, simulated case counts were likely in the hundreds. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities.  Our results indicate that the cordon sanitaire may not have prevented COVID-19 spread in major Chinese cities; local non-pharmaceutical interventions were likely more important for this.

title: Rapid Detection of Novel Coronavirus (COVID-19) by Reverse Transcription-Loop-Mediated Isothermal Amplification
abstract: Novel Corona virus (COVID-19 or 2019-nCoV) is an emerging global health concern that requires a rapid diagnostic test. Quantitative reverse transcription PCR (qRT-PCR) is currently the standard for COVID-19 detection; however, Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) may allow for faster and cheaper field based testing at point-of-risk. The objective of this study was to develop a rapid screening diagnostic test that could be completed in under 30 minutes. Simulated patient samples were generated by spiking serum, urine, saliva, oropharyngeal swabs, and nasopharyngeal swabs with a portion of the COVID-19 nucleic sequence. The samples were tested using RT-LAMP as well as by conventional qRT-PCR. Specificity of the RT-LAMP was evaluated by also testing against other related coronaviruses. RT-LAMP specifically detected COVID-19 in simulated patient samples. This test was performed in under 30 minutes. This approach could be used for monitoring of exposed individuals or potentially aid with screening efforts in the field and potential ports of entry.

title: COVID-19 control in China during mass population movements at New Year

title: COVID19 - The need for Public Health in a time of emergency

title: Alignment using genetic programming with causal trees for identification of protein functions
abstract: A hybrid evolutionary model is used to propose a hierarchical homology of protein sequences to identify protein functions systematically. The proposed model offers considerable potentials, considering the inconsistency of existing methods for predicting novel proteins. Because some novel proteins might align without meaningful conserved domains, maximizing the score of sequence alignment is not the best criterion for predicting protein functions. This work presents a decision model that can minimize the cost of making a decision for predicting protein functions using the hierarchical homologies. Particularly, the model has three characteristics: (i) it is a hybrid evolutionary model with multiple fitness functions that uses genetic programming to predict protein functions on a distantly related protein family, (ii) it incorporates modified robust point matching to accurately compare all feature points using the moment invariant and thin-plate spline theorems, and (iii) the hierarchical homologies holding up a novel protein sequence in the form of a causal tree can effectively demonstrate the relationship between proteins. This work describes the comparisons of nucleocapsid proteins from the putative polyprotein SARS virus and other coronaviruses in other hosts using the model.

title: Analytical sensitivity and efficiency comparisons of SARS-COV-2 qRT-PCR primer-probe sets
abstract: The recent spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exemplifies the critical need for accurate and rapid diagnostic assays to prompt clinical and public health interventions. Currently, several quantitative reverse-transcription polymerase chain reaction (qRT-PCR) assays are being used by clinical, research, and public health laboratories. However, it is currently unclear if results from different tests are comparable. Our goal was to evaluate the primer-probe sets used in four common diagnostic assays available on the World Health Organization (WHO) website. To facilitate this effort, we generated RNA transcripts to be used as assay standards and distributed them to other laboratories for internal validation. We then used (1) RNA transcript standards, (2) full-length SARS-CoV-2 RNA, (3) pre-COVID-19 nasopharyngeal swabs, and (4) clinical samples from COVID-19 patients to determine analytical efficiency and sensitivity of the qRT-PCR primer-probe sets. We show that all primer-probe sets can be used to detect SARS-CoV-2 at 500 virus copies per reaction, except for the RdRp-SARSr (Charite) confirmatory primer-probe set which has low sensitivity. Our findings characterize the limitations of currently used primer-probe sets and can assist other laboratories in selecting appropriate assays for the detection of SARS-CoV-2.

title: Statistical and network-based analysis of Italian COVID-19 data: communities detection and temporal evolution
abstract: Coronavirus disease (COVID-19) outbreak started at Wuhan, China, and it has rapidly spread across China and many other countries. Italy is one of the European countries most affected by the COVID-19 disease, and it has registered high COVID-19 death rates and the death toll. In this article, we analyzed different Italian COVID-19 data at the regional level for the period February 24 to March 29, 2020. The analysis pipeline includes the following steps. After individuating groups of similar or dissimilar regions with respect to the ten types of available COVID-19 data using statistical test, we built several similarity matrices (reported in Supplementary file). Then, we mapped those similarity matrices into networks where nodes represent Italian regions and edges represent similarity relationships (edge length is inversely proportional to similarity). Then, network-based analysis was performed mainly discovering communities of regions that show similar behaviour. Then, network-based analysis was performed by running several community detection algorithms on those networks and by underlying communities of regions that show similar behaviour. The network-based analysis of Italian COVID-19 data is able to elegantly show how regions form communities, i.e. how they join and leave them, along time and how community consistency changes along time and with respect to the different available data.

title: Should We Be Screening for SARS-CoV-2 in IBD Patients Before Initiation of Biologic Therapy?

title: Reporting of D-dimer data in COVID-19: some confusion and potential for misinformation.
abstract: Coronavirus disease 2019 (COVID-19) represents a new pandemic caused by severe acute respiratory syndrome virus coronavirus 2 (SARS-CoV-2). A previous pooled analysis clearly identified elevated D-dimer levels as being associated with severity of COVID-19. Since then, several other studies have provided clearer support for this initial evidence. However, potentially under-recognized by those reporting on D-dimer is the considerable variation in reporting units for D-dimer, and thus also the potential for misreporting of D-dimer data based on poor or incomplete reporting. A PubMed search was used to identify recent papers reporting on D-dimers in COVID-19-based studies. We report that: (1) most publications did not identify either the manufacturer or D-dimer product used; (2) most did not identify whether D-dimer values were reported as D-dimer units (DDU) or fibrinogen equivalent units (FEU) (~2 × differences); (3) nearly half did not identify normal cut-off values; (4) some did not report numerical findings or units for D-dimer; (5) where reported, most identified units as either mg/L or μg/mL; (6) we identified at least four errors in reporting from 21 papers. It may not be possible to truly standardize D-dimer assays, but it should be feasible to harmonize D-dimer assays to a single unit of measurement.

title: Transmission potential of influenza A/H7N9, February to May 2013, China
abstract: On 31 March 2013, the first human infections with the novel influenza A/H7N9 virus were reported in Eastern China. The outbreak expanded rapidly in geographic scope and size, with a total of 132 laboratory-confirmed cases reported by 3 June 2013, in 10 Chinese provinces and Taiwan. The incidence of A/H7N9 cases has stalled in recent weeks, presumably as a consequence of live bird market closures in the most heavily affected areas. Here we compare the transmission potential of influenza A/H7N9 with that of other emerging pathogens and evaluate the impact of intervention measures in an effort to guide pandemic preparedness.  We used a Bayesian approach combined with a SEIR (Susceptible-Exposed-Infectious-Removed) transmission model fitted to daily case data to assess the reproduction number (R) of A/H7N9 by province and to evaluate the impact of live bird market closures in April and May 2013. Simulation studies helped quantify the performance of our approach in the context of an emerging pathogen, where human-to-human transmission is limited and most cases arise from spillover events. We also used alternative approaches to estimate R based on individual-level information on prior exposure and compared the transmission potential of influenza A/H7N9 with that of other recent zoonoses.  Estimates of R for the A/H7N9 outbreak were below the epidemic threshold required for sustained human-to-human transmission and remained near 0.1 throughout the study period, with broad 95% credible intervals by the Bayesian method (0.01 to 0.49). The Bayesian estimation approach was dominated by the prior distribution, however, due to relatively little information contained in the case data. We observe a statistically significant deceleration in growth rate after 6 April 2013, which is consistent with a reduction in A/H7N9 transmission associated with the preemptive closure of live bird markets. Although confidence intervals are broad, the estimated transmission potential of A/H7N9 appears lower than that of recent zoonotic threats, including avian influenza A/H5N1, swine influenza H3N2sw and Nipah virus.  Although uncertainty remains high in R estimates for H7N9 due to limited epidemiological information, all available evidence points to a low transmission potential. Continued monitoring of the transmission potential of A/H7N9 is critical in the coming months as intervention measures may be relaxed and seasonal factors could promote disease transmission in colder months.

title: COVID-19, Australia: Epidemiology Report 17 (Fortnightly reporting period ending 24 May 2020).
abstract: Confirmed cases in Australia notified up to 24 May 2020: notifications = 7,135; deaths = 102. The incidence of COVID-19 has markedly reduced since a peak in mid-March. There have been no cases reported in SA, the NT or the ACT in the last four weeks. The numbers of new cases reported from other jurisdictions continue to be very low. Testing rates have been higher across all jurisdictions, with Victoria reporting an 85% testing rate increase and NSW a 40% increase over this period. The positivity rate nationally continues to remain very low at less than 0.1% over the reporting period. Continued high rates of testing are necessary to detect and mitigate the spread of COVID-19 in the community. Over the past fortnight, 45% of cases acquired their infection overseas. Of cases considered to be locally acquired over this period, most were associated with contacts of confirmed cases or were associated with known outbreaks. The highest rate of COVID-19 continues to be among people aged 65-79 years. Three-quarters of all cases in this age group have been associated with overseas travel, including several outbreaks linked to cruise ships. The lowest rate of disease is in children under 18, a pattern reflected in international reports. A small proportion of cases overall have experienced severe disease, requiring hospitalisation or intensive care with some fatalities. The crude case fatality rate amongst Australian cases is 1.4%. People who are older and have one or more comorbidities are more likely to experience severe disease. A combination of early case identification, physical distancing, public health measures and a reduction in international travel have likely been effective in slowing the spread of the disease in Australia. In addition, the median number of days between symptom onset and diagnostic testing has improved considerably from 7 days in the early phase of the outbreak to 1 day in the latest phase of the epidemic. Internationally, as at 24 May 2020, there have been recent increases in the number of daily cases reported globally. The largest numbers of both cases and deaths have been reported in the United States. Of the confirmed cases reported globally, the case fatality rate is approximately 6.5%. Countries in South America are starting to see rapid acceleration, while the United States is seeing a very slow decline in its daily new case numbers. In the South East Asia region, India and Bangladesh are seeing accelerating epidemics, compounded by the recovery from Cyclone Amphan. Increasing numbers of cases are also being reported in Africa, although the numbers are much smaller. In the Pacific there are very few daily new cases reported.

title: A rate equation approach to model the denaturation or replication behavior of the SARS coronavirus
abstract: As a newly emerging virus, little is known about the SARS coronavirus, whose outbreak has brought away several hundred people’s lives over the world in the year of 2003 and is seriously imperiling the human health. Revealing the denaturation and replication mechanisms of SARS coronavirus has great importance for successfully fighting SARS. However, experiments related to SARS coronavirus are extremely dangerous and therefore restricted only to certain specific labs with high safety standard. Clearly, predicting the behaviors of SARS coronavirus in a wide variety of environmental conditions, which are not easily accessible, are thus critically necessary. In this study, we proposed to quantify the survival time of SARS coronavirus either in vitro or in vivo, through introducing thermal rate process models established from the well-known Arrhenius law. The complex physical and chemical behaviors of the SARS coronavirus can then be attributed to its activation energy, frequency factor, damage function as well as the surrounding environmental conditions. Based on the first data on stability and resistance of SARS coronavirus measured by members of WHO laboratory network, the rate coefficients involved in the above equations were estimated for the first time. Predictions on the survival time of SARS coronavirus in different temperature scale were then performed. It was found theoretically that, such survival time falls in an extremely wide range, say from several seconds in high temperature to an almost infinitely long time in a low temperature environment, which has already or is being supported by the currently available tests data. Applications of the present theory to interpret several existing phenomena were presented and their implementations in developing new technical ways for SARS prevention and clinical therapy were discussed. Uncertainties involved in the theoretical models were also analyzed and predicted. Parametric studies were performed to test the effects of the rate coefficients to the survival time of SARS coronavirus. Some important factors, which can significantly vary the denaturation or replication process of SARS coronavirus were pointed out. Through regulating the parameters involved in the equation, certain potential therapies either through drug delivery or engineering approach to treat the SARS disease can possibly be established. Extension of the present model for further studies was also suggested. This study opens a new theoretical way for probing into the complex behaviors of SARS coronavirus. Modellierung der Denaturierung oder Repliziryng von SARS-Korona-Viren Zusammenfassung Der Kenntnisstand über die Eigenschaften des in 2003 neu aufgetretenen SARS Korona Virus, der einige Hundert Menschenleben gekostet hat, ist relativ gering. Die Ermittlung des Denaturierungs- und Replizierungsmechanismuses des SARS Virus ist für seine Bekämpfung von hoher Bedeutung. Experimentelle Untersuchungen an diesem extrem gefährlichen Virus dürfen nur durch Laboratorien mit einem hohen Sicherheitsstandard erfolgen. Die Vorhersage des Verhaltens des SARS Virus in unterschiedlichen Umgebungsbedingungen ist dabei erforderlich. In der vorliegenden Studie wird die überlebensdauer des Virus unter Labor- und realen Bedingungen durch Anwendung der bekannten Arrhenius-Beziehung für temperaturabhängige Vorgänge ermittelt. Das physikalische und chemische Verhalten des SARS Virus wird anhand der zugrundeliegenden Modell- Parameter beschrieben. Basierend auf den ersten Messungen von Mitgliedern des WHO-laboratory-network über die Stabilität und Widerstandsfähigkeit des Virus wurden erstmalig die Geschwindigkeitskoeffizienten des Berechnungsmodells bestimmt. Vorhersagen der Überlebensdauer des SARS-Virus unter unterschiedlichen Temperaturbedingungen wurden ausgeführt. Das sich hieraus ergebende, sehr unterschiedliche Ausmaß der Überlebensfähigkeit in Abhängigkeit der Umgebungstemperatur ist durch den Vergleich mit verfügbaren experimentellen Ergebnissen bestätigt worden. Die Anwendung der vorgestellten Modellierung zur Interpretation realer Phänomene und zur Entwicklung technischer Maßnahmen zur Vorbeugung und klinischen Therapierung von SARS wird diskutiert. Der Einfluß von Unsicherheiten des Modells wird analysiert und abgeschätzt. Parametrische Studien sind durchgeführt worden, um den Einfluß der Geschwindigkeitskoeffizienten auf die Überlebensdauer des SARS Virus darzustellen. Einige wichtige Einflußgrößen auf die Denaturierung und Replikationsfähigkeit des SARS Virus werden aufgezeigt. Durch eine Variation der Modellparameter kann die potentielle Wirksamkeit medikamentöser oder physikalischer Therapien abgeschätzt werden. Erweiterungsmöglichkeiten des vorgestellten Modells werden vorgeschlagen. Die vorliegende Studie ermöglicht neue, theoretische Vorgehensweisen zur Untersuchung des komplexen Verhaltensmusters des SARS Virus.

title: CT Scans of Patients with 2019 Novel Coronavirus (COVID-19) Pneumonia
abstract: The increasing speed of confirmed 2019 novel coronavirus (COVID-19) cases is striking in China. The purpose of this study is to summarize the outcomes of patients with novel COVID-19 pneumonia (NCP) at our institution.  In this single-center study, we retrospectively included 118 cases of NCP, from January 16, 2020 to February 4, 2020. The clinical outcomes were monitored up to February 11, 2020. The outcomes of NCP patients were phase summarized at our institution. Three kinds of responses to clinical treatment were defined and evaluated: 1) good, symptoms continually improved; 2) fair, symptoms not improved or relapsed; 3) poor, symptoms aggravated. The risk factors, including basal clinical characteristics, CT imaging features, and follow-up CT changes (no change, progress, and improvement) related to poor/fair outcomes, were also investigated.  Six patients were improved to no-emergency type, 2 remained the same, and 2 progressed to fatal type. Besides, 13 patients progressed from the common type group to the emergency group (3 in fatal type and 10 in severe type). Forty-two (35.6%) patients were discharged with a median hospital stay of 9.5 days (range, 4.0-15.0 days). Thus, the numbers in different responses were, 73 patients in good response group (4 emergency cases, 69 no-emergency cases), 28 in fair response group (3 emergency cases, 25 no-emergency cases), and 17 in poor response group (3 emergency cases, 14 no-emergency cases). No patient has died in our hospital to date. The median duration of progress observed from CT scans was 6 days (range, 2-14 days). The progression in abnormal imaging findings indicate a poor/fair response, whereas the alleviated symptoms seen from CT suggest a good response.  Most cases are no-emergency type and have a favorable response to clinical treatment. Follow-up CT changes during the treatment can help evaluate the treatment response of patients with NCP.

title: Level of underreporting including underdiagnosis before the first peak of COVID-19 in various countries: Preliminary retrospective results based on wavelets and deterministic modeling

title: Smart Pooled sample Testing for COVID-19: A Possible Solution for Sparsity of Test Kits
abstract: There is an exponential growth of COVID-19. The adaptation of preventive measures to limit the spread of infection among the people is the best solution to this health issue. The identification of infected cases and their isolation from healthy people is one of the most important preventive measures. In this regard, screening of the samples from a large number of people is needed which requires a lot of reagent kits for the detection of SARS-CoV-2. The use of smart pooled sample testing with the help of algorithms may be a quite useful strategy in the current prevailing scenario of the COVID-19 pandemic. With the help of this strategy, the optimum number of samples to be pooled for a single test may be determined based on the total positivity rate of the particular community.

title: The incidence of the novel coronavirus SARS-CoV-2 among asymptomatic patients: a systematic review
abstract: the recent outbreak of the coronavirus disease 2019 (COVID-19) has quickly spread globally since its discovery in Wuhan, China, in December 2019. A comprehensive strategy, including surveillance, diagnostics, research, and clinical treatment is urgently needed to win the battle against COVID-19. Recently, numerous studies reported the incidence of SARS-CoV-2 in asymptomatic patients. Yet, the incidence and viral transmission from the asymptomatic cases are not apparent yet.  this study aims to systematically review the published literature on SARS-CoV-2 in the asymptomatic patients to estimate the incidence of COVID-19 among asymptomatic cases, as well as describe its epidemiological and clinical significance.  the literature was searched through four scientific databases: PubMed, Web of Science, Scopus, and Science Direct.  a total of 63 studies satisfied the inclusion criteria where the majority of the reported studies were from China. However, there was a lack of SARS-CoV-2 epidemiological studies from several countries worldwide, tracing the actual incidence of COVID-19, especially in asymptomatic patients. Studies with a large sample size (n>1000) estimated that percentage of people contracting SARS-CoV-2 and are likely to be asymptomatic ranges from 1.2-12.9%. However, the other studies with a smaller sample size reported a much higher incidence and indicated that up to 87.9% of COVID-19 infected individuals could be asymptomatic. Most of these studies indicated that asymptopatics are a potential source of infection to the community.  this review highlighted the need for more robust and well-designed studies to better estimate COVID-19 incidence among asymptomatic patients worldwide. The early identification of the asymptomatic cases, as well as monitoring and tracing close contact, could help in mitigating the spread of COVID-19.

title: COVID-19 and Italy: what next?
abstract: The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions, affecting over 100 countries in a matter of weeks. A global response to prepare health systems worldwide is imperative. Although containment measures in China have reduced new cases by more than 90%, this reduction is not the case elsewhere, and Italy has been particularly affected. There is now grave concern regarding the Italian national health system's capacity to effectively respond to the needs of patients who are infected and require intensive care for SARS-CoV-2 pneumonia. The percentage of patients in intensive care reported daily in Italy between March 1 and March 11, 2020, has consistently been between 9% and 11% of patients who are actively infected. The number of patients infected since Feb 21 in Italy closely follows an exponential trend. If this trend continues for 1 more week, there will be 30 000 infected patients. Intensive care units will then be at maximum capacity; up to 4000 hospital beds will be needed by mid-April, 2020. Our analysis might help political leaders and health authorities to allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks. If the Italian outbreak follows a similar trend as in Hubei province, China, the number of newly infected patients could start to decrease within 3–4 days, departing from the exponential trend. However, this cannot currently be predicted because of differences between social distancing measures and the capacity to quickly build dedicated facilities in China.

title: Monitoring trends and differences in COVID-19 case fatality rates using decomposition methods: Contributions of age structure and age-specific fatality
abstract: The population-level case fatality rate (CFR) associated with COVID-19 varies substantially, both across countries and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, France, Germany, Italy, South Korea, Spain, and the United States. We calculate the CFR for each country at the latest data point and for Italy also over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. CFRs vary from 0.7% in Germany and 1.6% in South Korea to 8.6% in Spain and 10.6% in Italy. The age-structure of detected cases can explain a substantial proportion of cross-country variation in the CFR. For example, 57% of Spain's difference with respect to South Korea is explained by the observed cases being older. In Italy, the CFR increased from 4.2% to 10.6% between March 9 and March 29, 2020, and more than 95% of the change was due to increasing age-specific case fatality rates. The importance of the age-structure of infected cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case fatality rates indicate the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.

title: Prevalence of coronavirus

title: Estimation of SARS-CoV-2 Infection Prevalence in Santa Clara County
abstract: To reliably estimate the demand on regional health systems and perform public health planning, it is necessary to have a good estimate of the prevalence of infection with SARS-CoV-2 (the virus that causes COVID-19) in the population. In the absence of wide-spread testing, we provide one approach to infer prevalence based on the assumption that the fraction of true infections needing hospitalization is fixed and that all hospitalized cases of COVID-19 in Santa Clara are identified. Our goal is to estimate the prevalence of SARS-CoV-2 infections, i.e. the true number of people currently infected with the virus, divided by the total population size. Our analysis suggests that as of March 17, 2020, there are 6,500 infections (0.34% of the population) of SARS-CoV-2 in Santa Clara County. Based on adjusting the parameters of our model to be optimistic (respectively pessimistic), the number of infections would be 1,400 (resp. 26,000), corresponding to a prevalence of 0.08% (resp. 1.36%). If the shelter-in-place led to R0 < 1, we would expect the number of infections to remain about constant for the next few weeks. However, even if this were true, we expect to continue to see an increase in hospitalized cases of COVID-19 in the short term due to the fact that infection of SARS-CoV-2 on March 17th can lead to hospitalizations up to 14 days later.

title: Impact of non-pharmaceutical interventions on documented cases of COVID-19
abstract: The novel coronavirus (SARS-CoV-2) has rapidly evolved into a global epidemic. To control its spread, countries have implemented non pharmaceutical interventions (NPIs), such as school or border closures, while others have even enforced complete lockdowns. Here we study the impact of NPIs in reducing documented cases of COVID-19. Documented case numbers are selected because they are essential for decision-makers in the area of health-policy when monitoring and evaluating current control mechanisms.  We empirically estimate the relative reduction in the number of new cases attributed to each NPI. A cross-country analysis is performed using documented cases through April 15, 2020 from n=20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland).  As of April 15, venue closures were associated with a reduction in the number of new cases by 36 % (95% credible interval [CrI] 20-48 %), closely followed by gathering bans (34 %; 95% CrI 21-45 %), border closures (31 %; 95% CrI 19-42 %), and work bans on non-essential business activities (31 %; 95% CrI 16-44 %). Event bans lead to a slightly less pronounced reduction (23 %; 95% CrI 8-35 %). School closures (8 %; 95% CrI 0-23 %) and lockdowns (5 %; 95% CrI 0-14 %) appeared to be the least effective among the NPIs considered in this analysis.  With this cross-country analysis, we provide early estimates regarding the impact of different NPIs for controlling the COVID-19 epidemic. These findings are relevant for evaluating current health-policies.  COVID-19, coronavirus, non-pharmaceutical interventions, policy measures, health-policy, public health, health services research

title: COVID-19: the medium is the message

title: Novel Coronavirus (COVID-19) Knowledge and Perceptions: A Survey of Healthcare Workers
abstract: During the first week of March, the surge of coronavirus disease 2019 (COVID-19) cases reached over 100 countries with more than 100,000 cases. Healthcare authorities have already initiated awareness and preparedness activities beyond borders. A poor understanding of the disease among healthcare workers (HCWs) may result in delayed treatment and the rapid spread of infection. This study aimed to investigate the knowledge and perceptions of HCWs about COVID-19.  A cross-sectional, web-based study was conducted among HCWs about COVID-19 during the first week of March 2020. A 23-item survey instrument was developed and distributed randomly to HCWs using social media; it required 5 minutes to complete. A chi-square test was used to investigate the level of association among variables at the significance level of p<0.05.  Of 529 participants, a total of 453 HCWs completed the survey (response rate: 85.6%); 51.6% were males, 32.1% were aged 25-34 years, and most were doctors (30.2%) and medical students (29.6%). Regarding COVID-19, most of the participants used social media to obtain information (61%), and a significant proportion of HCWs had poor knowledge of its transmission (61%) and symptom onset (63.6%) and showed positive perceptions of COVID-19 prevention and control. Factors such as age and profession were associated with inadequate knowledge and poor perception of COVID-19.  As the global threat of COVID-19 continues to emerge, it is critical to improve the knowledge and perceptions of HCWs. Educational interventions are urgently needed to reach HCWs beyond borders, and further studies are warranted.

title: Impact of COVID-19 Outbreak on Healthcare Workers in Italy: Results from a National E-Survey
abstract: Italy has been the first-hit European country to face the outbreak of coronavirus disease 2019 (COVID-19). Aim of this survey was to assess in depth the impact of the outbreak on healthcare workers (HCW). A 40-item online survey was disseminated via social media inviting Italian HCW, with questions exploring demographics, health status and work environment of respondents. A total of 527 were invited to take part in March 2020, of whom 74% (n = 388) responded to the survey. Of these, 235 (61%) were women. HCW were mostly physicians (74%), from high-prevalence regions (52%). 25% experienced typical symptoms during the last 14 days prior to survey completion, with only 45% of them being tested for COVID-19. Among the tested population, 18 (18%) resulted positive for COVID-19, with 33% being asymptomatic. Only 22% of HCW considered personal protective equipment adequate for quality and quantity. Females and respondents working in high-risk sectors were more likely to rate psychological support as useful (OR, 1.78 [CI 95% 1.14–2.78] P = 0.012, and 2.02 [1.12–3.65] P = 0.020, respectively) and workload as increased (mean increase, 0.38 [0.06–0.69] P = 0.018; and 0.54 [0.16–0.92] P = 0.005, respectively). The insights from this survey may help authorities in countries where COVID-19 epidemic has not yet broken out. Management strategies should be promptly undertaken in order to enhance safety and optimise resource allocation.

title: Prevalence of COVID-19 Infection and Outcomes Among Symptomatic Healthcare Workers in Seattle, Washington
abstract: Healthcare workers (HCW) serving on the front lines of the coronavirus disease 2019 (COVID-19) pandemic have been at increased risk for infection due to SARS-CoV-2 in some settings. Healthcare-acquired infection has been reported in similar epidemics, but there are limited data on the prevalence of COVID-19 among HCWs and their associated clinical outcomes in the United States.  We established two high-throughput employee testing centers in Seattle, Washington with drive-through and walk-through options for symptomatic employees in the University of Washington Medicine system and its affiliated organizations. Using data from these testing centers, we report the prevalence of SARS-CoV-2 infection among symptomatic employees and describe the clinical characteristics and outcomes among employees with COVID-19.  Between March 12 and April 23, a total of 3,477 symptomatic employees were tested for COVID-19 at two employee testing centers; 185 (5.3%) employees tested positive for COVID-19. The prevalence of SARS-CoV-2 was similar when comparing frontline HCWs (5.2%) to non-frontline staff (5.5%). Among 174 positive employees reached for follow-up at least 14 days after diagnosis, 6 reported COVID-related hospitalization; all recovered.  During the study period, we observed that the prevalence of positive SARS-CoV-2 tests among symptomatic HCWs was comparable to that of symptomatic non-frontline staff. Reliable and rapid access to testing for employees is essential to preserve the health, safety, and availability of the healthcare workforce during this pandemic and to facilitate the rapid return of SARS-CoV-2 negative employees to work.

title: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)
abstract: Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2)] infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82-90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46-62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.

title: SARS-CoV-2 epidemiology and control, different scenarios for Turkey
abstract: Coronavirus Infectious Disease 2019 (COVID-19) is now a pandemic spreading in most countries including Turkey.  The current knowledge of COVID-19 and the virus causing it, SARS-CoV-2, was reviewed. The epidemiology and control in different countries was compared and the differences discussed.  The population attack rates and case fatality rates vary from country to country with Lombardy in northern Italy reporting an attack rate in the general population of 0.37% compared to 0.004% in Hong Kong. The differences are caused by different testing strategies and reporting systems.  Turkey is early in the outbreak. Different control strategies are available with South Korea, Hong Kong and Singapore being models to follow.

title: Chapter 27 Emergence and Reemergence of Viral Zoonotic Diseases: Concepts and Factors of Emerging and Reemerging Globalization of Health Threats
abstract: The unpredictable emergence of new zoonotic diseases with viral etiology is currently a hot issue in the scientific and political circles. Viral emergence and reemergence, as a sanitary event, are only the visible part of the iceberg, while the hidden one corresponds to a multitude of complex and interrelated factors, including societal and environmental factors favoring the advent of the state of viral emergence and reemergence. According to the World Health Organization, 60% of the agents recognized as human pathogens come from the animal kingdom, and 75% of the pathogens responsible for emerging and reemerging animal diseases present a potential transgression of interface between interspecies establishing favorable conditions for genetic exchange leading to the emergence of new highly pathogenic variants and strains of which the animal is often the host reservoir. Therefore any public health prophylactic strategy requires a holistic approach to the health problem, taking into account the interaction between the triad elements of the human, animal, and environment. This globalized approach has been realized by the international community through the new recently established concept of “One Health, One World,” making the old bipolar concept of separated human and animal health issues avoided and obsolete. The extreme diversity of emerging and reemerging viral pathogens, the change of human lifestyle, the globalization of travel, business exchanges, and tourism potentiate the risk of emergence of highly pathogenic zoonotic diseases. Promoting intersectorial collaboration will allow to unify the health and safety policies. The cross-cutting ecological and health data at the national and global scales are effective means for sustaining good health in human, animal, and ecosystem (in particular the viral ecology).

title: Communicating the Risk of Death from Novel Coronavirus Disease (COVID-19)
abstract: To understand the severity of infection for a given disease, it is common epidemiological practice to estimate the case fatality risk, defined as the risk of death among cases. However, there are three technical obstacles that should be addressed to appropriately measure this risk. First, division of the cumulative number of deaths by that of cases tends to underestimate the actual risk because deaths that will occur have not yet observed, and so the delay in time from illness onset to death must be addressed. Second, the observed dataset of reported cases represents only a proportion of all infected individuals and there can be a substantial number of asymptomatic and mildly infected individuals who are never diagnosed. Third, ascertainment bias and risk of death among all those infected would be smaller when estimated using shorter virus detection windows and less sensitive diagnostic laboratory tests. In the ongoing COVID-19 epidemic, health authorities must cope with the uncertainty in the risk of death from COVID-19, and high-risk individuals should be identified using approaches that can address the abovementioned three problems. Although COVID-19 involves mostly mild infections among the majority of the general population, the risk of death among young adults is higher than that of seasonal influenza, and elderly with underlying comorbidities require additional care.

title: Integrated Disease Surveillance and Response (IDSR) in Malawi: Implementation gaps and challenges for timely alert
abstract: The recent 2014 Ebola Virus Disease (EVD) outbreaks rang the bell to call upon global efforts to assist resource-constrained countries to strengthen public health surveillance system for early response. Malawi adopted the Integrated Disease Surveillance and Response (IDSR) strategy to develop its national surveillance system since 2002 and revised its guideline to fulfill the International Health Regulation (IHR) requirements in 2014. This study aimed to understand the state of IDSR implementation and differences between guideline and practice for future disease surveillance system strengthening.  This was a mixed-method research study. Quantitative data were to analyze completeness and timeliness of surveillance system performance from national District Health Information System 2 (DHIS2) during October 2014 to September 2016. Qualitative data were collected through interviews with 29 frontline health service providers from the selected district and 7 key informants of the IDSR system implementation and administration at district and national levels.  The current IDSR system showed relatively good completeness (73.1%) but poor timeliness (40.2%) of total expected monthly reports nationwide and zero weekly reports during the study period. Major implementation gaps were lack of weekly report and trainings. The challenges of IDSR implementation revealed through qualitative data included case identification, compiling reports for timely submission and inadequate resources.  The differences between IDSR technical guideline and actual practice were huge. The developing information technology infrastructure in Malawi and emerging mobile health (mHealth) technology can be opportunities for the country to overcome these challenges and improve surveillance system to have better timeliness for the outbreaks and unusual events detection.

title: Use of a Supplemental Oxygen Protocol to Suppress Progression of Retinopathy of Prematurity.
abstract: To compare progression of retinopathy of prematurity (ROP) before and after institution of an oxygen therapy protocol to inhibit active proliferation and progression of ROP in premature infants.  A retrospective cohort study was performed of premature infants undergoing ROP screening before (cohort A) and after (cohort B) implementation of an oxygen therapy protocol to inhibit further progression for those with stage 2 ROP or worse. Statistical analysis with χ2, Fisher's exact test, or Wilcoxon rank sum test was performed; and logistic regression models were created to determine the odds ratio of cohort B developing ROP progression beyond stage 2, compared to cohort A, adjusting for other risk factors for ROP.  In cohort A, without oxygen therapy protocol (2002-2007), 44% (54/122) of infants progressed beyond stage 2, compared to 23% (24/103) of infants after protocol implementation (cohort B, 2008-2012) (P = 0.001). No significant differences between cohort A and B were found for gestational age, birth weight, survival, sepsis, bronchopulmonary dysplasia, oxygen at discharge, or need for diuretics. Infants with stage 2 ROP in cohort B, with oxygen therapy protocol, had significantly decreased risk of ROP beyond stage 2 (odds ratio 0.37, 95% confidence interval 0.20-0.67; P = 0.0013), compared to cohort A, correcting for differences in birth weight and necrotizing enterocolitis.  Progression from stage 2 to stage 3 ROP in premature infants was significantly decreased after implementation of an oxygen therapy protocol, without a corresponding increase in pulmonary morbidity. This study suggests that appropriate oxygen therapy may play a role in inhibiting progression of stage 2 ROP, potentially decreasing the risk of lifelong visual loss in this vulnerable population.

title: The COVID-19 pandemic: Important considerations for contact lens practitioners
abstract: A novel coronavirus (CoV), the Severe Acute Respiratory Syndrome Coronavirus - 2 (SARS-CoV-2), results in the coronavirus disease 2019 (COVID-19). As information concerning the COVID-19 disease continues to evolve, patients look to their eye care practitioners for accurate eye health guidance. There is currently no evidence to suggest an increased risk of contracting COVID-19 through contact lens (CL) wear compared to spectacle lens wear and no scientific evidence that wearing standard prescription spectacles provides protection against COVID-19 or other viral transmissions. During the pandemic there will potentially be significant changes in access to local eyecare. Thus, it is imperative CL wearers are reminded of the steps they should follow to minimise their risk of complications, to reduce their need to leave isolation and seek care. Management of adverse events should be retained within optometric systems if possible, to minimise the impact on the wider healthcare service, which will be stretched. Optimal CL care behaviours should be the same as those under normal circumstances, which include appropriate hand washing (thoroughly with soap and water) and drying (with paper towels) before both CL application and removal. Daily CL cleaning and correct case care for reusable CL should be followed according to appropriate guidelines, and CL exposure to water must be avoided. Where the availability of local clinical care is restricted, practitioners should consider advising patients to reduce or eliminate sleeping in their CL (where patients have the appropriate knowledge about correct daily care and access to suitable lens-care products) or consider the option of moving patients to daily disposable lenses (where patients have appropriate lens supplies available). Patients should also avoid touching their face, including their eyes, nose and mouth, with unwashed hands and avoid CL wear altogether if unwell (particularly with any cold or flu-like symptoms).

title: Excess registered deaths in England and Wales during the COVID-19 pandemic, March 2020 to May 2020
abstract: Official counts of COVID-19 deaths have been criticized for potentially including people who did not die of COVID-19 but merely died with COVID-19. I address that critique by fitting a generalized additive model to weekly counts of all deaths registered in England and Wales during the 2010s. The model produces baseline rates of death registrations expected without the COVID-19 pandemic, and comparing those baselines to recent counts of registered deaths exposes the emergence of excess deaths late in March 2020. By April's end, England and Wales registered 45,300 $\pm$ 3200 excess deaths of adults aged 45+. Through 22 May, the last day of available all-deaths data, 56,600 $\pm$ 4400 were registered (about 53% of which were of men). Both the ONS's corresponding count of 43,205 death certificates which mention COVID-19, and the Department of Health and Social Care's count of 33,671 deaths, are appreciably less, implying that their counting methods have underestimated, not overestimated, the pandemic's true death toll. If underreporting rates have held steady during May, about 59,000 direct and indirect COVID-19 deaths might have been registered through the end of May but not yet publicly reported in full.

title: COVID- 19 Infection in Children: Estimating Pediatric Morbidity and Mortality
abstract: Estimates of pediatric morbidity and mortality from COVID-19 are vital for planning optimal use of human and material resources throughout this pandemic.  Government websites from countries with minimum 1000 cases in adults and children on April 13, 2020 were searched to find the number of cases confirmed in children, the age range, and the number leading to hospitalization, intensive care unit (ICU) admission or death. A systematic literature search was performed April 13, 2020 to find additional data from cases series.  Data on pediatric cases were available from government websites for 23 of the 70 countries with minimum 1000 cases by April 13, 2020. Of 424 978 cases in these 23 countries, 8113 (1.9%) occurred in children. Nine publications provided data from 4251 cases in 4 additional countries. Combining data from the websites and the publications, 330 of 2361 cases required admission (14%). The ICU admission rate was 2.2 % of confirmed cases (44 of 2031) and 7.2% of admitted children (23 of 318). Death was reported for 15 cases.  Children accounted for 1.9% of confirmed cases. The true incidence of pediatric infection and disease will only be known once testing is expanded to individuals with less severe or no symptoms. Admission rates vary from 0.3 to 10% of confirmed cases (presumably varying with the threshold for testing) with about 7% of admitted children requiring ICU care. Death is rare in middle and high income countries.

title: Coronavirus cases have dropped sharply in South Korea. What’s the secret to its success?
abstract: Europe is now the epicenter of the COVID-19 pandemic Case counts and deaths are soaring in Italy, Spain, France, and Germany, and many countries have imposed lockdowns and closed borders Meanwhile, the United States, hampered by a fiasco with delayed and faulty test kits, is just guessing at its COVID-19 burden, though experts believe it is on the same trajectory as countries in Europe

title: New York City COVID-19 resident physician exposure during exponential phase of pandemic
abstract: BackgroundFrom March 2-April 12, 2020, New York City (NYC) experienced exponential growth of the COVID-19 pandemic due to novel coronavirus (SARS-CoV-2). Little is known regarding how physicians have been affected. We aimed to characterize COVID-19 impact on NYC resident physicians.MethodsIRB-exempt and expedited cross-sectional analysis through survey to NYC residency program directors (PDs) April 3-12, 2020, encompassing events from March 2-April 12, 2020.ResultsFrom an estimated 340 residency programs around NYC, recruitment yielded 91 responses, representing 24 specialties and 2,306 residents. 45.1% of programs reported at least one resident with confirmed COVID-19: 101 resident physicians were confirmed COVID-19-positive, with an additional 163 residents presumed positive for COVID-19 based on symptoms but awaiting or unable to obtain testing. Two COVID-19-positive residents were hospitalized, with one in intensive care. Among specialties with >100 residents represented, negative binomial regression indicated that infection risk differed by specialty (p=0.039). 80% of programs reported quarantining a resident. 90/91 programs reported reuse or extended mask use, and 43 programs reported that personal protective equipment (PPE) was suboptimal. 65 programs (74.7%) have redeployed residents elsewhere to support COVID-19 efforts.ConclusionMany resident physicians around NYC have been affected by COVID-19 through direct infection, quarantine, or redeployment. Lack of access to testing and concern regarding suboptimal PPE are common among residency programs. Infection risk may differ by specialty.FundingAHA, MPB, RWSC, CGM, LRDG, JDH: NEI Core Grant P30EY019007, RPB Unrestricted Grant. ACP and JS: Parker Family Chair.  University of Pennsylvania.

title: Systematic Comparison of Two Animal-to-Human Transmitted Human Coronaviruses: SARS-CoV-2 and SARS-CoV
abstract: After the outbreak of the severe acute respiratory syndrome (SARS) in the world in 2003, human coronaviruses (HCoVs) have been reported as pathogens that cause severe symptoms in respiratory tract infections. Recently, a new emerged HCoV isolated from the respiratory epithelium of unexplained pneumonia patients in the Wuhan seafood market caused a major disease outbreak and has been named the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus causes acute lung symptoms, leading to a condition that has been named as “coronavirus disease 2019” (COVID-19). The emergence of SARS-CoV-2 and of SARS-CoV caused widespread fear and concern and has threatened global health security. There are some similarities and differences in the epidemiology and clinical features between these two viruses and diseases that are caused by these viruses. The goal of this work is to systematically review and compare between SARS-CoV and SARS-CoV-2 in the context of their virus incubation, originations, diagnosis and treatment methods, genomic and proteomic sequences, and pathogenic mechanisms.

title: SARS-CoV-2 turned positive in a discharged patient with COVID-19 arouses concern regarding the present standard for discharge
abstract: An outbreak of COVID-19 in Wuhan, China caused by SARS-CoV-2 has led to a serious epidemic in China and other countries, resulting in worldwide concern. With the active efforts from prevention and control, the quantity of discharged patients is escalating. How to manage these patients normatively is still challenging. We hereby reported an asymptomatic discharged patient with COVID-19 who was retested positive for SARS-CoV-2, which arouses concern regarding the present discharge standard of COVID-19.

title: Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing
abstract: Extensive physical distancing measures are currently the primary intervention against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing measures, with the timing of these measures informed by survey data on attitudes to distancing and COVID-19.We fit our model to reported COVID-19 cases in British Columbia, Canada, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimate the impact that physical distancing (also known as social distancing)has had on the contact rate and examine the projected impact of relaxing distancing measures. We find that distancing has had a strong impact, consistent with declines in reported cases and in hospitalization and intensive care unit numbers. We estimate that approximately 0.78 (0.66-0.89 90% CI) of contacts have been removed for individuals in British Columbia practising physical distancing and that this fraction is above the threshold of 0.45 at which prevalence is expected to grow. However, relaxing distancing measures beyond this threshold re-starts rapid exponential growth. Because the extent of underestimation is unknown, the data are consistent with a wide range in the prevalence of COVID-19 in the population; changes to testing criteria over time introduce additional uncertainty. Our projections indicate that intermittent distancing measures - if sufficiently strong and robustly followed - could control COVID-19 transmission, but that if distancing measures are relaxed too much, the epidemic curve would grow to high prevalence.

title: [Cause analysis and treatment strategies of "recurrence" with novel coronavirus pneumonia (covid-19) patients after discharge from hospital].
abstract: With a large number of COVID-19 patients discharging from hospital, some had showed re-fever and positive nucleic acid test after discharge from hospital. This might be due to the biological characteristics of 2019-nCoV, and might also be related to the basic disease, clinical status, glucocorticoid using, sample sampling, processing and detecting of patients, and some even related to the re-infection or secondary bacterial virus infection. Therefore, we suggest that in view of this phenomenon, further stratified management of discharge from hospital should be carried out on the basis of guidelines, especially for patients with advanced age, underlying diseases or severe or critical pneumonia. For those patients who can't completely deoxygenate for a long time after hospitalization, individualized treatment methods and different discharge evaluation criteria should be adopted to ensure the complete cure of patients and prevent recurrencing after discharge from hospital.

title: International Expert Consensus Statement on Chest Imaging in Pediatric COVID-19 Patient Management: Imaging Findings, Imaging Study Reporting and Imaging Study Recommendations
abstract: The coronavirus disease 2019 (COVID-19) has quickly spread since it was first detected in December of 2019 to a global pandemic with over 1.7 million confirmed cases in over 200 countries around the world at the time this document is being prepared. Due to the novel nature of the virus and the rapidly evolving understanding of the disease, there is a great deal of uncertainty surrounding the diagnosis and management of COVID-19 pneumonia in pediatric patients. Chest imaging plays an important role in evaluation of pediatric patients with COVID-19, however there is currently little information available describing imaging manifestations of pediatric COVID-19 and even less discussing utilization of imaging studies in pediatric patients. To specifically address these concerns, a group of international experts in pediatric thoracic imaging from 5 continents convened to create a consensus statement describing the imaging manifestations of COVID-19 in the pediatric population, discussing the potential utility of structured reporting during the coronavirus 2019 pandemic, and generating consensus recommendations for utilization of chest radiographs (CXR) and computed tomography (CT) in the evaluation of pediatric patients with COVID-19. The results were compiled into 2 structured reporting algorithms (one for CXR and one for chest CT) and 8 consensus recommendations for utilization of chest imaging in pediatric COVID-19 infection.

title: Changes in testing rates could mask the novel coronavirus disease (COVID-19) growth rate
abstract: Since the novel coronavirus disease (COVID-19) emerged in December 2019 in China, it has rapidly spread around the world, leading to one of the most significant pandemic events of recent history. Deriving reliable estimates of the COVID-19 epidemic growth rate is quite important to guide the timing and intensity of intervention strategies. Indeed, many studies have quantified the epidemic growth rate using time-series of reported cases during the early phase of the outbreak to estimate the basic reproduction number, R0. Using daily time series of COVID-19 incidence, we illustrate how epidemic curves of reported cases may not always reflect the true epidemic growth rate due to changes in testing rates, which could be influenced by limited diagnostic testing capacity during the early epidemic phase.

title: COVID-19 pneumonia in Taiwan

title: How Reliable are Test Numbers for Revealing the COVID-19 Ground Truth and Applying Interventions?
abstract: The number of confirmed cases of COVID-19 is often used as a proxy for the actual number of ground truth COVID-19 infected cases in both public discourse and policy making. However, the number of confirmed cases depends on the testing policy, and it is important to understand how the number of positive cases obtained using different testing policies reveals the unknown ground truth. We develop an agent-based simulation framework in Python that can simulate various testing policies as well as interventions such as lockdown based on them. The interaction between the agents can take into account various communities and mobility patterns. A distinguishing feature of our framework is the presence of another `flu'-like illness with symptoms similar to COVID-19, that allows us to model the noise in selecting the pool of patients to be tested. We instantiate our model for the city of Bengaluru in India, using census data to distribute agents geographically, and traffic flow mobility data to model long-distance interactions and mixing. We use the simulation framework to compare the performance of three testing policies: Random Symptomatic Testing (RST), Contact Tracing (CT), and a new Location Based Testing policy (LBT). We observe that if a sufficient fraction of symptomatic patients come out for testing, then RST can capture the ground truth quite closely even with very few daily tests. However, CT consistently captures more positive cases. Interestingly, our new LBT, which is operationally less intensive than CT, gives performance that is comparable with CT. In another direction, we compare the efficacy of these three testing policies in enabling lockdown, and observe that CT flattens the ground truth curve maximally, followed closely by LBT, and significantly better than RST.

title: Guidance for rebooting electrophysiology through the COVID-19 pandemic from the Heart Rhythm Society and the American Heart Association Electrocardiography and Arrhythmias Committee of the Council on Clinical Cardiology Endorsed by the American College of Cardiology
abstract: Coronavirus disease 2019 (COVID-19) has presented substantial challenges to patient care and impacted health care delivery, including cardiac electrophysiology practice throughout the globe. Based upon the undetermined course and regional variability of the pandemic, there is uncertainty as to how and when to resume and deliver electrophysiology services for arrhythmia patients. This joint document from representatives of the Heart Rhythm Society, American Heart Association, and American College of Cardiology seeks to provide guidance for clinicians and institutions reestablishing safe electrophysiological care. To achieve this aim, we address regional and local COVID-19 disease status, the role of viral screening and serologic testing, return-to-work considerations for exposed or infected health care workers, risk stratification and management strategies based on COVID-19 disease burden, institutional preparedness for resumption of elective procedures, patient preparation and communication, prioritization of procedures, and development of outpatient and periprocedural care pathways.

title: Estimation of COVID-19 under-reporting in Brazilian States through SARI
abstract: Due to its impact, COVID-19 has been stressing the academy to search for curing, mitigating, or controlling it. However, when it comes to controlling, there are still few studies focused on under-reporting estimates. It is believed that under-reporting is a relevant factor in determining the actual mortality rate and, if not considered, can cause significant misinformation. Therefore, the objective of this work is to estimate the under-reporting of cases and deaths of COVID-19 in Brazilian states using data from the Infogripe on notification of Severe Acute Respiratory Infection (SARI). The methodology is based on the concepts of inertia and the use of event detection techniques to study the time series of hospitalized SARI cases. The estimate of real cases of the disease, called novelty, is calculated by comparing the difference in SARI cases in 2020 (after COVID-19) with the total expected cases in recent years (2016 to 2019) derived from a seasonal exponential moving average. The results show that under-reporting rates vary significantly between states and that there are no general patterns for states in the same region in Brazil.

title: Seroprevalence of COVID-19 virus infection in Guilan province, Iran
abstract: The extent of infection by coronavirus disease 2019 has not been well documented. In this study we aimed to determine seropositivity of COVID-19 virus infection in population of a highly affected area in north of Iran.  In a population-based cluster random sampling design through phone call invitation, a total of 196 household including 552 subjects agreed to participate in this study. Each participant were taken 50ml blood sample at health care center. Rapid test kits were used to detect antibody against COVID-19. Crude, population-weight adjusted and test performance adjusted prevalence of antibody seropositivity to SARS-CoV-2 were reported.  The prevalence of antibody seropositivity was 0.22 (95%CI: 0.19-0.26). The population weight adjusted estimate was 0.21 (95%CI: 0.14-0.29) and test performance adjusted prevalence was 0.33 (95%CI: 0.28-0.39). Based on these estimates the range of infected people in this province would be between 518000 and 777000.  The population seropositivity prevalence of COVID-19 virus infection indicated that the asymptomatic infection is much higher than the number of confirmed cases of COVID-19. This estimate can be used to better detect infection fatality rate and decide for public policy guidelines.

title: Remdesivir, lopinavir, emetine, and homoharringtonine inhibit SARS-CoV-2 replication in vitro
abstract: An escalating pandemic by the novel SARS-CoV-2 virus is impacting global health and effective therapeutic options are urgently needed. We evaluated the in vitro antiviral effect of compounds that were previously reported to inhibit coronavirus replication and compounds that are currently under evaluation in clinical trials for SARS-CoV-2 patients. We report the antiviral effect of remdesivir, lopinavir, homorringtonine, and emetine against SARS-CoV-2 virus in Vero E6 cells with the estimated 50% effective concentration at 23.15 μM, 26.63 μM, 2.55 μM and 0.46 μM, respectively. Ribavirin or favipiravir that are currently evaluated under clinical trials showed no inhibition at 100 μM. Synergy between remdesivir and emetine was observed, and remdesivir at 6.25 μM in combination with emetine at 0.195 μM may achieve 64.9% inhibition in viral yield. Combinational therapy may help to reduce the effective concentration of compounds below the therapeutic plasma concentrations and provide better clinical benefits.

title: Initial evidence of higher morbidity and mortality due to SARS-CoV-2 in regions with lower air quality
abstract: COVID-19 has spread in all continents in a span of just over three months, escalating into a pandemic that poses several humanitarian as well as scientific challenges. We here investigated the geographical expansion of the infection and correlate it with the annual indexes of air quality observed from the Sentinel-5 satellite orbiting around China, Italy and the U.S.A. Controlling for population size, we find more viral infections in those areas afflicted by Carbon Monoxide (CO) and Nitrogen Dioxide (NO2). Higher mortality was also correlated with poor air quality, namely with high PM2.5, CO and NO2 values. In Italy, the correspondence between poor air quality and SARS-CoV-2 appearance and induced mortality was the starkest. Similar to smoking, people living in polluted areas are more vulnerable to SARS-CoV-2 infections and induced mortality. This further suggests the detrimental impact climate change will have on the trajectory of future epidemics.

title: Variable pool testing for infection spread estimation
abstract: We present a method for efficient estimation of the prevalence of infection in a population with high accuracy using only a small number of tests. The presented approach uses pool testing with a mix of pool sizes of various sizes. The test results are then combined to generate an accurate estimation over a wide range of infection probabilities. This method does not require an initial guess on the infection probability. We show that, using the suggested method, even a set of only $50$ tests with a total of only $1000$ samples can produce reasonable estimation over a wide range of probabilities. A measurement set with only $100$ tests is shown to achieve $25\%$ accuracy over infection probabilities from $0.001$ to $0.5$. The presented method is applicable to COVID-19 testing.

title: COVID-19 and homelessness in England: a modelling study of theCOVID-19 pandemic among people experiencing homelessness, and theimpact of a residential intervention to isolate vulnerable people andcare for people with symptoms
abstract: There is an ongoing pandemic of the viral respiratory disease COVID-19. People experiencing homelessness are vulnerable to infection and severe disease. Health and housing authorities in England have developed a residential intervention that aims to isolate those vulnerable to severe disease (COVID-PROTECT) and care for people with symptoms (COVID CARE).  We used a discrete-time Markov chain model to forecast COVID-19 infections among people experiencing homelessness, given strong containment measures in the general population and some transmission among 35,817 people living in 1,065 hostels, and 11,748 people sleeping rough (the 'do nothing' scenario). We then estimated demand for beds if those eligible are offered COVID-PROTECT and COVID-CARE. We estimated the reduction in the number of COVID-19 cases, deaths, and hospital admissions that could be achieved by these interventions. We also conducted sensitivity and scenario analyses to identify programme success factors.  In a 'do nothing' scenario, we estimate that 34% of the homeless population could get COVID-19 between March and August 2020, with 364 deaths, 4,074 hospital admissions and 572 critical care admissions. In our 'base intervention' scenario, demand for COVID-PROTECT peaks at 9,934 beds, and demand for COVID-CARE peaks at 1,366 beds. The intervention could reduce transmission by removing symptomatic individuals from the community, and preventing vulnerable individuals from being infected. This could lead to a reduction of 164 deaths, 2,624 hospital admissions, and 248 critical care admissions over this period. Sensitivity analyses showed that the number of deaths is sensitive to transmission of COVID-19 in COVID-PROTECT. If COVID-PROTECT capacity is limited, scenario analyses show the benefit of prioritising people who are vulnerable to severe disease.  Supportive accommodation can mitigate the impact of the COVID-19 pandemic on the homeless population of England, and reduce the burden on acute hospitals.

title: On Answering the Call to Action for COVID-19: Continuing a Bold Legacy of Health Advocacy
abstract: The disproportionately high burden of death and disability observed for racial and ethnic minorities under the Coronavirus pandemic necessitates sustained advocacy by the medical and public health communities around critical determinants of population health. Prompting our advocacy should be the understanding that our collective ability to rebound from such crises may ultimately hinge on protecting and equipping our most vulnerable racial-ethnic minority groups and any susceptible individuals within those populations. If proven effective, recent historic firsts by the U.S. Department of Health and Human Services (HHS), through the Health Resources and Services Administration (HRSA), the Office of Minority Health (OMH) and the Centers for Disease Control and Prevention (CDC) in response to COVID-19 should be championed for permanency within policy, practice and funding. In addition, given the complex history of Black Americans in this country and persistent and substantial Black-white disparities on health and economic measures across the board, some kind of reparations for this group may serve as a logical starting point for further advocacy. Nevertheless, we remain supportive allies of all organizations concerned with communities who suffer the weight of this pandemic and any future world health disasters. Let us as human clinicians and public health professionals capture this moment of challenge and engage in thoughtful unification of effort and commit to measurable progress for as long as the need exists and certainly for the foreseeable future.

title: Therapeutic Options for Middle East Respiratory Syndrome Coronavirus (MERS-CoV) – possible lessons from a systematic review of SARS-CoV therapy
abstract: The Middle East Respiratory Syndrome coronavirus (MERS-CoV) has been detected in a number of countries in the Middle East and Europe with an apparently high mortality rate. It is phylogenetically related to the SARS coronavirus and has also been associated with severe respiratory illness as well as nosocomial transmission in healthcare settings. Current international recommendations do not support any specific therapies; however, there are a number of agents, which were used during the SARS epidemic of 2003. It is possible that these might be active against the related MERS coronavirus. We have reviewed the literature on the safety and efficacy of therapies used in patients with SARS with a view to their potential use in patients with MERS-CoV infections.

title: Underestimation of COVID-19 cases in Japan: an analysis of RT-PCR testing for COVID-19 among 47 prefectures in Japan.
abstract: Under the unique Japanese policy to restrict reverse transcriptase-polymerase chain reaction (RT-PCR) testing against severe acute respiratory syndrome coronavirus 2, a nationwide number of its confirmed cases and mortality remains to be low. Yet the information is lacking on geographical differences of these measures and their associated factors.  Evaluation of prefecture-based geographical differences and associated predictors for the incidence and number of RT-PCR tests for COVID-19.   We retrieved domestic laboratory-confirmed cases, deaths, and the number of RT-PCR testing for COVID-19 from January 15 to April 6, 2020 in 47 prefectures in Japan, using publicly-available data by the Ministry of Health, Labour and Welfare. We did descriptive analyses of these three measures and identified significant predictors for the incidence and RT-PCR testing through multiple regression analyses and correlates with the number of deaths through correlation analysis.  The median prefectural-level incidence and number of RT-PCR testing per 100,000 population were 1.14 and 38.6, respectively. Multiple regression analyses revealed that significant predictors for the incidence were prefectural-level population (p < 0.001) and the number of RT-PCR testing (p = 0.03); and those for RT-PCR testing were the incidence (p = 0.025), available beds (p = 0.045) and cluster infections (p = 0.034).  Considering bidirectional association between the incidence and RT-PCR testing, there may have been an underdiagnosed population for the infection. The restraint policy for RT-PCR testing should be revisited to meet the increasing demand under the COVID-19 epidemic.

title: Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset
abstract: Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for diagnosis quickly. This paper explores how useful chest X-ray images can be in diagnosing COVID-19 disease. We have obtained 122 chest X-rays of COVID-19 and over 4,000 chest X-rays of viral and bacterial pneumonia. A pretrained deep convolutional neural network has been tuned on 102 COVID-19 cases and 102 other pneumonia cases in a 10-fold cross validation. The results were all 102 COVID-19 cases were correctly classified and there were 8 false positives resulting in an AUC of 0.997. On a test set of 20 unseen COVID-19 cases all were correctly classified and more than 95% of 4171 other pneumonia examples were correctly classified. This study has flaws, most critically a lack of information about where in the disease process the COVID-19 cases were and the small data set size. More COVID-19 case images will enable a better answer to the question of how useful chest X-rays can be for diagnosing COVID-19 (so please send them).

title: Positive tracheal SARS-CoV-2 RNA test after three negative SARS-CoV-2 RNA tests in a patient with COVID-19

title: COVID-19 outbreak in Algeria: A mathematical Model to predict cumulative cases
abstract: Since December 29, 2019 a pandemic of new novel coronavirus-infected pneumonia named COVID-19 has started from Wuhan, China, has led to 254 996 confirmed cases until midday March 20, 2020. Sporadic cases have been imported worldwide, in Algeria, the first case reported on February 25, 2020 was imported from Italy, and then the epidemic has spread to other parts of the country very quickly with 139 confirmed cases until March 21, 2020.  It is crucial to estimate the cases number growth in the early stages of the outbreak, to this end, we have implemented the Alg-COVID-19 Model which allows to predict the incidence and the reproduction number R0 in the coming months in order to help decision makers. The Alg-COVIS-19 Model initial equation 1, estimates the cumulative cases at t prediction time using two parameters: the reproduction number R0 and the serial interval SI.  We found R0=2.55 based on actual incidence at the first 25 days, using the serial interval SI= 4,4 and the prediction time t=26. The herd immunity HI estimated is HI=61%. Also, The Covid-19 incidence predicted with the Alg-COVID-19 Model fits closely the actual incidence during the first 26 days of the epidemic in Algeria Fig. 1.A. which allows us to use it.

title: Estimation of the number of general anesthesia cases based on a series of nationwide surveys on Twitter during COVID-19 in Japan: A statistical analysis
abstract: Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first reported in Wuhan, Hubei, China, and has since spread to more than 200 other countries at the time of writing. In light of this situation, the Japanese Government declared a state of emergency in seven regions of Japan on the April 7, 2020 under the provisions of the law. The medical care delivery system has been under pressure. Although various surgical societies have published guidelines on which to base their surgical decisions, it is not clear how general anesthesia has been performed and will be performed in Japan. Social networks such as Twitter are becoming a part of society, as various information is accumulated on the web. One of the services provided by Twitter is a voting function-Twitter Polls-through which anonymous surveys can be conducted. We analyzed the results of a series of surveys on Twitter on the status of operating restrictions using a mathematical model, and public data provided by the Japanese Government were used to estimate the current and future changes in the number of general anesthesia performed in Japan. The number of general anesthesia was estimated as 2.77*104 cases per week on 2nd May 2020 and 0.68*104 cases in 24 weeks.

title: COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures
abstract: Cruise ships carry a large number of people in confined spaces with relative homogeneous mixing. On 3 February, 2020, an outbreak of COVID-19 on cruise ship Diamond Princess was reported with 10 initial cases, following an index case on board around 21-25(th) January. By 4(th) February, public health measures such as removal and isolation of ill passengers and quarantine of non-ill passengers were implemented. By 20(th) February, 619 of 3,700 passengers and crew (17%) were tested positive.  We estimated the basic reproduction number from the initial period of the outbreak using SEIR models. We calibrated the models with transient functions of countermeasures to incidence data. We additionally estimated a counterfactual scenario in absence of countermeasures, and established a model stratified by crew and guests to study the impact of differential contact rates among the groups. We also compared scenarios of an earlier versus later evacuation of the ship.  The basic reproduction rate was initially 4 times higher on-board compared to the  see text] in the epicentre in Wuhan, but the countermeasures lowered it substantially. Based on the modeled initial  see text] of 14.8, we estimated that without any interventions within the time period of 21 January to 19 February, 2920 out of the 3700 (79%) would have been infected. Isolation and quarantine therefore prevented 2307 cases, and lowered the  see text] to 1.78. We showed that an early evacuation of all passengers on 3 February would have been associated with 76 infected persons in their incubation time.  The cruise ship conditions clearly amplified an already highly transmissible disease. The public health measures prevented more than 2000 additional cases compared to no interventions. However, evacuating all passengers and crew early on in the outbreak would have prevented many more passengers and crew from infection.

title: On the assessment of more reliable COVID-19 infected number: the italian case.
abstract: COVID-19 (SARS-CoV-2) is the most recent pandemic disease the world is currently managing. It started in China at the end of 2019, and it is diffusing throughout Italy, one of the most affected countries, and it is currently spreading through European countries and USA. Patients affected by COVID-19 are identified employing medical swabs applied mainly to (i) citizens with COVID-19 symptoms such as flu or high temperature, or (ii) citizens that had contacts with COVID-19 patients. A percentage of COVID-19 affected patients needs hospitalisation, whereas a portion needs to be treated in Intensive Care Units (ICUs). Nevertheless, it is a matter of current intuition that COVID-19 infected citizens are more than those detected, and sometime the infection is detected too late. Thus there are many efforts in both tracking people activities as well as diffusing low cost reliable COVID-19 tests for early detection. Starting from mortality rates of diseases caused by viruses in the same family (e.g. MERS, SARS, H1N1), we study the relations between the number of COVID-19 infections and the number of deaths, through Italian regions. We thus assess several infections being higher than the ones currently measured. We thus focus on the characterisation of the pandemic diffusion by estimating the infected number of patients versus the number of death. We use such an estimated number of infections, to foresee the effects of restriction actions adopted by governments to constrain virus diffusion. We finally think that our model can support the healthcare system to react when COVID-19 is increasing.

title: Utilization of Nucleic Acid Amplification Assays for the Detection of Respiratory Viruses
abstract: Viruses are major contributors to morbidity and mortality from acute respiratory infections in all age groups worldwide. Accurate identification of the etiologic agent of respiratory tract infections is important for proper patient management. Diagnosis can be problematic, because a range of potential pathogens can cause similar clinical symptoms. Nucleic acid amplification testing is emerging as the preferred method of diagnostic testing. Real-time technology and the ability to perform multiplex testing have facilitated this emergence. Commercial platforms for nucleic acid amplification testing of respiratory viruses include real-time polymerase chain reaction (PCR), nucleic acid sequence-based amplification, and loop-mediated isothermal amplification. Multiplex PCR with fluidic microarrays or DNA chips are the most recent diagnostic advance. These assays offer significant advantages in sensitivity over antigen detection methods and in most cases also over traditional culture methods. A limited number of assays, however, are commercially available, thus laboratory developed assays frequently are used. This article reviews the performance of commercially available assays and discusses issues relevant to the development of in-house assays.

title: Cruise Ships, Nursing Homes and Prisons as COVID-19 Epicenters: A ‘Wicked Problem” with Breakthrough Solutions?

title: Comorbidities in COVID-19: Outcomes in hypertensive cohort and controversies with renin angiotensin system blockers
abstract: and aims COVID-19 is already a pandemic. Emerging data suggest an increased association and a heightened mortality in patients of COVID-19 with comorbidities. We aimed to evaluate the outcome in hypertensive patients with COVID-19 and its relation to the use of renin-angiotensin system blockers (RASB).  We have systematically searched the medical database up to March 27, 2020 and retrieved all the published articles in English language related to our topic using MeSH key words.  From the pooled data of all ten available Chinese studies (n = 2209) that have reported the characteristics of comorbidities in patients with COVID-19, hypertension was present in nearly 21%, followed by diabetes in nearly 11%, and established cardiovascular disease (CVD) in approximately 7% of patients. Although the emerging data hints to an increase in mortality in COVID-19 patients with known hypertension, diabetes and CVD, it should be noted that it was not adjusted for multiple confounding factors. Harm or benefit in COVID-19 patients receiving RASB has not been typically assessed in these studies yet, although mechanistically and plausibly both, benefit and harm is possible with these agents, given that COVID-19 expresses to tissues through the receptor of angiotensin converting enzyme-2.  Special attention is definitely required in patients with COVID-19 with associated comorbidities including hypertension, diabetes and established CVD. Although the role of RASB has a mechanistic equipoise, patients with COVID-19 should not stop these drugs at this point of time, as recommended by various world organizations and without the advice of health care provider.

title: COVID-19 DYNAMICS: A HETEROGENEOUS MODEL
abstract: The ongoing Coronavirus disease 2019 (COVID-19) epidemic is different from the previous epidemic of severe acute respiratory syndrome (SARS), which demands a rigorous analysis for the selection of anti-epidemic measures and their lifting when the epidemic subsides. Here we estimate the basic reproductive number for COVID-19 and propose a dynamical model for the time course of infection number. With this model, we assessed the effects of different measures for infection risk control. The model is different from the previous ones as it models the population as heterogeneous, with subpopulations having different infection risks. Our analyses showed that after this heterogeneity is incorporated in the model, several characteristics of the epidemic are estimated more accurately: the total number of cases and peak number of cases are lower compared to the homogeneous case, the early-stage growth rate in the number of infection cases is little affected, and the decrease in the number of infections slows down during the epidemic late stage. The comparison of our model results with the available data for COVID-19 indicates that the anti-epidemic measures undertaken in China and the rest of the world managed to decrease the basic reproductive number but did not assure an accumulation of sufficient collective immunity. Thus, the epidemic has a high likelihood to restart, which necessitates a careful approach to lifting the quarantine measures.

title: Impact of coronavirus pandemic crisis in endoscopic clinical practice: Results from a national survey in Brazil
abstract: In March 2020, the World Health Organization declared coronavirus disease of 2019 (COVID-19) as a pandemic, mobilizing all countries to contain the disease spread. Activity in endoscopy centers globally was severely affected. We conducted a national survey aiming to assess the impact of the COVID-19 outbreak on endoscopic clinical practice in Brazil.  In April 2020, 3,719 associate members of SOBED (Brazilian Society of Digestive Endoscopy) were invited to respond to an electronic survey. An Internet link was established to provide access to the online questionnaire with 40 questions regarding personal profile, endoscopy unit logistics and schedule, availability and use of personal protective equipment (PPE), financial impact, and exposure to COVID-19.  A total of 2,131 individuals (67 %) accessed the questionnaire and 1155 responses were received. After review, 980 responses were considered valid. According to almost 90 % of respondents, endoscopy activity was restricted to urgent procedures, in both public and private hospitals. All respondents increased PPE use after the outbreak, however, institutions provided adequate PPE to only 278 responders (28.7 %). Significant income loss was universally reported. A total of 10 practitioners (1 %) reported COVID-19 infection and attributed the contamination to endoscopic procedures.  Based on this nationwide survey with almost 1,000 respondents, the COVID-19 pandemic substantially reduced the activity of endoscopy units in private and public settings. The pandemic increased awareness of PPE use, but its availability was not universal and 1 % of the respondents became infected with COVID-19, allegedly due to exposure during endoscopic procedures.

title: Estimating Risk for Death from Coronavirus Disease, China, January–February 2020
abstract: Since December 2019, when the first case of coronavirus disease (COVID-19) was identified in the city of Wuhan in the Hubei Province of China, the epidemic has generated tens of thousands of cases throughout China. As of February 28, 2020, the cumulative number of reported deaths in China was 2,858. We estimated the time-delay adjusted risk for death from COVID-19 in Wuhan, as well as for China excluding Wuhan, to assess the severity of the epidemic in the country. Our estimates of the risk for death in Wuhan reached values as high as 12% in the epicenter of the epidemic and ≈1% in other, more mildly affected areas. The elevated death risk estimates are probably associated with a breakdown of the healthcare system, indicating that enhanced public health interventions, including social distancing and movement restrictions, should be implemented to bring the COVID-19 epidemic under control.

title: What we do when a COVID-19 patient needs an operation: operating room preparation and guidance

title: Preliminary Results of Initial Testing for Coronavirus (COVID-19) in the Emergency Department
abstract: On March 10, 2020, the World Health Organization declared a global pandemic due to widespread infection of the novel coronavirus 2019 (COVID-19). We report the preliminary results of a targeted program of COVID-19 infection testing in the ED in the first 10 days of its initiation at our institution.  We conducted a review of prospectively collected data on all ED patients who had targeted testing for acute COVID-19 infection at two EDs during the initial 10 days of testing (March 10–19, 2020). During this initial period with limited resources, testing was targeted toward high-risk patients per Centers for Disease Control and Prevention guidelines. Data collected from patients who were tested included demographics, clinical characteristics, and test qualifying criteria. We present the data overall and by test results with descriptive statistics.  During the 10-day study period, the combined census of the study EDs was 2157 patient encounters. A total of 283 tests were ordered in the ED. The majority of patients were 18–64 years of age, male, non-Hispanic white, had an Emergency Severity Index score of three, did not have a fever, and were discharged from the ED. A total of 29 (10.2%) tested positive. Symptoms-based criteria most associated with COVID-19 were the most common criteria identified for testing (90.6%). All other criteria were reported in 5.51–43.0% of persons being tested. Having contact with a person under investigation was significantly more common in those who tested positive compared to those who tested negative (63% vs 24.5%, respectively). The majority of patients in both results groups had at least two qualifying criteria for testing (75.2%).  In this review of prospectively collected data on all ED patients who had targeted testing for acute COVID-19 infection at two EDs in the first 10 days of testing, we found that 10.2% of those tested were identified as positive. The continued monitoring of testing and results will help providers understand how COVID-19 is progressing in the community.

title: First cases of coronavirus disease 2019 (COVID-19) in the WHO European Region, 24 January to 21 February 2020
abstract: A cluster of pneumonia of unknown origin was identified in Wuhan, China, in December 2019  On 12 January 2020, Chinese authorities shared the sequence of a novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolated from some clustered cases  Since then, the disease caused by SARS-CoV-2 has been named coronavirus disease 2019 (COVID-19) As at 21 February 2020, the virus had spread rapidly mostly within China but also to 28 other countries, including in the World Health Organization (WHO) European Region [3-5] Here we describe the epidemiology of the first cases of COVID-19 in this region, excluding cases reported in the United Kingdom (UK), as at 21 February 2020 The study includes a comparison between cases detected among travellers from China and cases whose infection was acquired due to subsequent local transmission %R doi:https://doi org/10 2807/1560-7917 ES 2020 25 9 2000178

title: An IDEA for Short Term Outbreak Projection: Nearcasting Using the Basic Reproduction Number
abstract: Communicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth.  The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R(0), along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts).  Compared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R(0) is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1(th) serial interval using data from the i(th) serial interval within an average of 20% of actual incidence.  This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists.

title: The race to unravel the United States’ biggest coronavirus outbreak
abstract: Rohit Shankar left the virology laboratory at 2 a m on Wednesday, and was back at the lab bench by 7 a m the same day “It’s okay,” he says, “I had a doughnut and a coffee ” Shankar, a medical scientist, and his colleagues at the University of Washington in Seattle are poised to exponentially drive up the number of confirmed cases of the coronavirus disease COVID-19 around the city, in western Washington state That’s because this week, they began analysing a mountain of nose and throat swabs collected from hospitals in the region Already, the researchers are seeing clear signs that the virus has infected vastly more people than have been formally detected Scientists fear coronavirus spread in countries least able to contain it Washington state has become the United States’ ground zero for COVID-19, which has now spread to more than 90 countries worldwide in what seems to be a new and dangerous phase of the outbreak Washington has declared a state emergency, and ten people there have died from the disease But the number of confirmed cases in Washington — 70 — is still an underestimate resulting from a lack of testing, researchers agree A genomic analysis posted online on 29 February suggested that hundreds of people in western Washington might already be infected Academic scientists have mostly been prevented from measuring the extent of the US outbreak because of federal rules restricting the number of labs qualified to run diagnostic tests But that is changing now, and helps account for why the state's caseload jumped from 10 to 70 this week Dozens of virologists and genomicists have now kicked into high gear in Seattle, dropping or adapting projects to devote resources to the outbreak Researchers are working around the clock to find out how many people have the disease in the area Others are analysing genomes to reveal how the virus is transmitted or developing new therapies The scientists are racing to help Washington avoid the fate of Hubei province in China, where more than 2,900 people have died of COVID-19 so far The coronavirus emerged in the province’s city Wuhan in December, and the initial response from officials was slow “We are past the point of containment,” says Helen Chu, an infectious-disease specialist at the University of Washington School of Medicine (UW Medicine) in Seattle “So now we need to keep the people who are vulnerable from getting sick ”

title: Covid-19: Como Transformar Un Ventilador De No Invasiva En Un Ventilador De Criticos
abstract: COVID-19 pandemic caused not only many deaths around the world but also made evident technical limitations of hospital and intensive care units (ICU). The growing demand of ICU ventilators in a short lapse of time constitutes one of the main community concerns. The main goal of this communication is to give simple solutions to transform a noninvasive ventilator in an invasive one for intubated patients. The proposal can be applied in two well defined strategies for the COVID-19 pandemic: To replace anesthesia workstations, leaving those machines to be used in patients. To apply this option in COVID-19 patients by way of a therapeutic "bridge", waiting for the release of a ventilator in the ICU.

title: COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth
abstract: In December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. We aimed to build a mathematical model to capture the global trend of epidemics outside China.  In this retrospective, outside-China diagnosis number reported from Jan 21 to Feb 28, 2020 was downloaded from WHO website. We develop a simple regression model on these numbers: log10 (Nt+34)=0.0515*t+2.075 where Nt is the total diagnosed patient till the ith day, t=1 at Feb 1.  Based on this model, we estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days.

title: Covid-19: the medical students responding to the pandemic.

title: Comorbidity and its impact on 1,590 patients with COVID-19 in China: A Nationwide Analysis
abstract: To evaluate the spectrum of comorbidities and its impact on the clinical outcome in patients with coronavirus disease 2019 (COVID-19).  Retrospective case studies Setting: 575 hospitals in 31 province/autonomous regions/provincial municipalities across China Participants: 1,590 laboratory-confirmed hospitalized patients. Data were collected from November 21st, 2019 to January 31st, 2020.  Epidemiological and clinical variables (in particular, comorbidities) were extracted from medical charts. The disease severity was categorized based on the American Thoracic Society guidelines for community-acquired pneumonia. The primary endpoint was the composite endpoints, which consisted of the admission to intensive care unit (ICU), or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared among patients with COVID-19 according to the presence and number of comorbidities.  Of the 1,590 cases, the mean age was 48.9 years. 686 patients (42.7%) were females. 647 (40.7%) patients were managed inside Hubei province, and 1,334 (83.9%) patients had a contact history of Wuhan city. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. 269 (16.9%), 59 (3.7%), 30 (1.9%), 130 (8.2%), 28 (1.8%), 24 (1.5%), 21 (1.3%), 18 (1.1%) and 3 (0.2%) patients reported having hypertension, cardiovascular diseases, cerebrovascular diseases, diabetes, hepatitis B infections, chronic obstructive pulmonary disease, chronic kidney diseases, malignancy and immunodeficiency, respectively. 130 (8.2%) patients reported having two or more comorbidities. Patients with two or more comorbidities had significantly escalated risks of reaching to the composite endpoint compared with those who had a single comorbidity, and even more so as compared with those without (all P<0.05). After adjusting for age and smoking status, patients with COPD (HR 2.681, 95%CI 1.424-5.048), diabetes (HR 1.59, 95%CI 1.03-2.45), hypertension (HR 1.58, 95%CI 1.07-2.32) and malignancy (HR 3.50, 95%CI 1.60-7.64) were more likely to reach to the composite endpoints than those without. As compared with patients without comorbidity, the HR (95%CI) was 1.79 (95%CI 1.16-2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61-4.17) among patients with two or more comorbidities.  Comorbidities are present in around one fourth of patients with COVID-19 in China, and predispose to poorer clinical outcomes.

title: Estimating the number of SARS-CoV-2 infections in the United States
abstract: We apply a model developed by The COVID-19 Response Team [S. Flaxman, S. Mishra, A. Gandy, et al., ''Estimating the number of infections and the impact of non- pharmaceutical interventions on COVID-19 in 11 European countries,'' tech. rep., Imperial College London, 2020.] to estimate the total number of SARS-CoV-2 infections in the United States. Across the United States we estimate as of April 18, 2020 the fraction of the population infected was 4.6% [3.6%, 5.8%], 21 times the portion of the population with a positive test result. Excluding New York state, which we estimate accounts for over half of infections in the United States, we estimate an infection rate of 2.3% [2.1%, 2.8%]. We include the timing of each state's implementation of interventions including encouraging social distancing, closing schools, banning public events, and a lockdown / stay-at-home order. We assume fatalities are reported correctly and infer the number and timing of infections based on the infection fatality rate measured in populations that were tested universally for SARS-CoV-2. Underreporting of deaths would drive our estimates to be too low. Reporting of deaths on the wrong day could drive errors in either direction. This model does not include effects of herd immunity; in states where the estimated infection rate is very high - namely, New York - our estimates may be too high.

title: Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020
abstract: This ecological analysis investigates the spatial patterns of the COVID‐19 epidemic in the United States in relation to socioeconomic variables that characterize US counties.  Data on confirmed cases and deaths from COVID‐19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state‐level measure of the percent of the population that has been tested for COVID‐19 was used to control for the impact of testing.  The impact of COVID‐19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID‐19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested.  Knowledge about the spatial aspects of the COVID‐19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to “shelter‐in‐place” should continue to stem the spread of COVID‐19.

title: Does active smoking worsen Covid-19?
abstract: Probably it does.

title: Potential roles of social distancing in mitigating the spread of coronavirus disease 2019 (COVID-19) in South Korea
abstract: On January 20, 2020, the first COVID-19 case was confirmed in South Korea. After a rapid outbreak, the number of incident cases has been consistently decreasing since early March; this decrease has been widely attributed to its intensive testing. We report here on the likely role of social distancing in reducing transmission in South Korea. Our analysis suggests that transmission may still be persisting in some regions.

title: Vitrification after multiple rounds of sample application and blotting improves particle density on cryo-electron microscopy grids
abstract: Single particle cryo-electron microscopy (cryoEM) is becoming widely adopted as a tool for structural characterization of biomolecules at near-atomic resolution. Vitrification of the sample to obtain a dense distribution of particles within a single field of view remains a major bottleneck for the success of such experiments. Here, we describe a simple and cost-effective method to increase the density of frozen-hydrated particles on grids with holey carbon support films. It relies on performing multiple rounds of sample application and blotting prior to plunge freezing in liquid ethane. We show that this approach is generally applicable and significantly increases particle density for a range of samples, such as small protein complexes, viruses and filamentous assemblies. The method is versatile, easy to implement, minimizes sample requirements and can enable characterization of samples that would otherwise resist structural studies using single particle cryoEM.

title: Use of Rapid Online Surveys to Assess People's Perceptions During Infectious Disease Outbreaks: A Cross-sectional Survey on COVID-19
abstract: Given the extensive time needed to conduct a nationally representative household survey and the commonly low response rate of phone surveys, rapid online surveys may be a promising method to assess and track knowledge and perceptions among the general public during fast-moving infectious disease outbreaks.  This study aimed to apply rapid online surveying to determine knowledge and perceptions of coronavirus disease 2019 (COVID-19) among the general public in the United States and the United Kingdom.  An online questionnaire was administered to 3000 adults residing in the United States and 3000 adults residing in the United Kingdom who had registered with Prolific Academic to participate in online research. Prolific Academic established strata by age (18-27, 28-37, 38-47, 48-57, or ≥58 years), sex (male or female), and ethnicity (white, black or African American, Asian or Asian Indian, mixed, or “other”), as well as all permutations of these strata. The number of participants who could enroll in each of these strata was calculated to reflect the distribution in the US and UK general population. Enrollment into the survey within each stratum was on a first-come, first-served basis. Participants completed the questionnaire between February 23 and March 2, 2020.  A total of 2986 and 2988 adults residing in the United States and the United Kingdom, respectively, completed the questionnaire. Of those, 64.4% (1924/2986) of US participants and 51.5% (1540/2988) of UK participants had a tertiary education degree, 67.5% (2015/2986) of US participants had a total household income between US $20,000 and US $99,999, and 74.4% (2223/2988) of UK participants had a total household income between £15,000 and £74,999. US and UK participants’ median estimate for the probability of a fatal disease course among those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was 5.0% (IQR 2.0%-15.0%) and 3.0% (IQR 2.0%-10.0%), respectively. Participants generally had good knowledge of the main mode of disease transmission and common symptoms of COVID-19. However, a substantial proportion of participants had misconceptions about how to prevent an infection and the recommended care-seeking behavior. For instance, 37.8% (95% CI 36.1%-39.6%) of US participants and 29.7% (95% CI 28.1%-31.4%) of UK participants thought that wearing a common surgical mask was “highly effective” in protecting them from acquiring COVID-19, and 25.6% (95% CI 24.1%-27.2%) of US participants and 29.6% (95% CI 28.0%-31.3%) of UK participants thought it was prudent to refrain from eating at Chinese restaurants. Around half (53.8%, 95% CI 52.1%-55.6%) of US participants and 39.1% (95% CI 37.4%-40.9%) of UK participants thought that children were at an especially high risk of death when infected with SARS-CoV-2.  The distribution of participants by total household income and education followed approximately that of the US and UK general population. The findings from this online survey could guide information campaigns by public health authorities, clinicians, and the media. More broadly, rapid online surveys could be an important tool in tracking the public’s knowledge and misperceptions during rapidly moving infectious disease outbreaks.

title: Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases
abstract: Chest CT is used for diagnosis of 2019 novel coronavirus disease (COVID-19), as an important complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests.  To investigate the diagnostic value and consistency of chest CT as compared with comparison to RT-PCR assay in COVID-19.  From January 6 to February 6, 2020, 1014 patients in Wuhan, China who underwent both chest CT and RT-PCR tests were included. With RT-PCR as reference standard, the performance of chest CT in diagnosing COVID-19 was assessed. Besides, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative, respectively) was analyzed as compared with serial chest CT scans for those with time-interval of 4 days or more.  Of 1014 patients, 59% (601/1014) had positive RT-PCR results, and 88% (888/1014) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95%CI, 95-98%, 580/601 patients) based on positive RT-PCR results. In patients with negative RT-PCR results, 75% (308/413) had positive chest CT findings; of 308, 48% were considered as highly likely cases, with 33% as probable cases. By analysis of serial RT-PCR assays and CT scans, the mean interval time between the initial negative to positive RT-PCR results was 5.1 ± 1.5 days; the initial positive to subsequent negative RT-PCR result was 6.9 ± 2.3 days). 60% to 93% of cases had initial positive CT consistent with COVID-19 prior (or parallel) to the initial positive RT-PCR results. 42% (24/57) cases showed improvement in follow-up chest CT scans before the RT-PCR results turning negative.  Chest CT has a high sensitivity for diagnosis of COVID-19. Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. A translation of this abstract in Farsi is available in the supplement. - ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

title: Foodborne Diseases: Prevalence of Foodborne Diseases in Europe
abstract: Official estimates of the prevalence of foodborne disease are highly biased, failing to account for underdiagnosis and underreporting of laboratory-confirmed clinical disease in people. To overcome the biases inherent in routine surveillance there has been a burgeoning in methods used to assess the prevalence of foodborne disease in Europe. These show that prevalence of foodborne illness across Europe is very high no matter what method is used to measure it. Salmonella and Campylobacter are consistently found to be the leading foodborne pathogens in Europe.

title: The Essential Facts of Wuhan Novel Coronavirus Outbreak in China and Epitope-based Vaccine Designing against COVID-19
abstract: Wuhan Novel Coronavirus disease (COVID-19) outbreak has become a global outbreak which has raised the concern of scientific community to design and discover a definitive cure against this deadly virus which has caused deaths of numerous infected people upon infection and spreading. To date, no antiviral therapy or vaccine is available which can effectively combat the infection caused by this virus. This study was conducted to design possible epitope-based subunit vaccines against the SARS-CoV-2 virus using the approaches of reverse vaccinology and immunoinformatics. Upon continual computational experimentation three possible vaccine constructs were designed and one vaccine construct was selected as the best vaccine based on molecular docking study which is supposed to effectively act against SARS-CoV-2. Later, molecular dynamics simulation and in silico codon adaptation experiments were carried out in order to check biological stability and find effective mass production strategy of the selected vaccine. Hopefully, this study will contribute to uphold the present efforts of the researches to secure a definitive treatment against this lethal virus.

title: Haplotype networks of SARS-CoV-2 infections in the Diamond Princess cruise ship outbreak
abstract: The Diamond Princess (DP) cruise ship was put under quarantine offshore Yokohama, Japan, after a passenger who disembarked in Hong Kong was confirmed as a COVID-19 case. We performed whole genome sequencing of SARS-CoV-2 directly from PCR-positive clinical specimens and conducted a haplotype network analysis of the outbreak. All tested isolates exhibited a transversion at G11083T, suggesting that SARS-CoV-2 dissemination on the DP originated from a single introduction event before the quarantine started. Although further spreading might have been prevented by quarantine, some progeny clusters were linked to transmission through mass-gathering events in the recreational areas and direct transmission among passengers who shared cabins during the quarantine. This study demonstrates the usefulness of haplotype network analysis in identifying potential infection routes.

title: Protocol of a population-based prospective COVID-19 cohort study Munich, Germany (KoCo19)
abstract: The SARS-CoV-2 pandemic is leading to the global introduction of public health interventions to prevent the spread of the virus and avoid the overload of health care systems, especially for the most severely affected patients. Scientific studies to date have focused primarily on describing the clinical course of patients, identifying treatment options and developing vaccines. In Germany, as in many other regions, current tests for SARS-CoV2 are not being conducted on a representative basis and in a longitudinal design. Furthermore, knowledge about the immune status of the population is lacking. Yet these data are needed to understand the dynamics of the pandemic and to thus appropriately design and evaluate interventions. For this purpose, we recently started a prospective population-based cohort in Munich, Germany, with the aim to better understand the state and dynamics of the pandemic.  In 100, randomly selected constituencies out of 755, 3,000 Munich households are identified via random route and offered enrollment into the study. All household members are asked to complete a baseline questionnaire and subjects [≥]14 years of age are asked to provide a venous blood sample of [≤]3 ml for the determination of SARS-CoV-2 IgG/IgA status. The residual plasma and the blood pellet are preserved for later genetic and molecular biological investigations. For twelve months, each household member is asked to keep a diary of daily symptoms, whereabouts and contacts via WebApp. If symptoms suggestive for COVID-19 are reported, family members, including children <14 years, are offered a pharyngeal swab taken at the Division of Infectious Diseases and Tropical Medicine, LMU University Hospital Munich, for molecular testing for SARS-CoV-2. In case of severe symptoms, participants will be transferred to a Munich hospital. For one year, the study teams re-visits the households for blood sampling every six weeks.  With the planned study we will establish a reliable epidemiological tool to improve the understanding of the spread of SARS-CoV-2 and to better assess the effectiveness of public health measures as well as their socio-economic effects. This will support policy makers in managing the epidemic based on scientific evidence.

title: The performance and professionalism of nurses in the fight against the new outbreak of COVID-19 epidemic is laudable

title: More than just smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis
abstract: Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, generally lacked quantitative measurements, and were mostly restricted to data from single countries. Here, we report the development, implementation and initial results of a multi-lingual, international questionnaire to assess self-reported quantity and quality of perception in three distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, 8 other, ages 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change {+/-}100) revealed a mean reduction of smell (-79.7{+/-}28.7, mean{+/-}SD), taste (-69.0{+/-}32.6), and chemesthetic (-37.3{+/-}36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell, but also affects taste and chemesthesis. The multimodal impact of COVID-19 and lack of perceived nasal obstruction suggest that SARS-CoV-2 infection may disrupt sensory-neural mechanisms.

title: The socio-economic determinants of the coronavirus disease (COVID-19) pandemic
abstract: The magnitude of the coronavirus disease (COVID-19) pandemic has an enormous impact on the social life and the economic activities in almost every country in the world. Besides the biological and epidemiological factors, a multitude of social and economic criteria also govern the extent of the coronavirus disease spread in the population. Consequently, there is an active debate regarding the critical socio-economic determinants that contribute to the resulting pandemic. In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 35 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome.

title: Political Intrusions into the International Health Regulations Treaty and Its Impact on Management of Rapidly Emerging Zoonotic Pandemics: What History Tells Us
abstract: For a large number of health care providers world-wide, the coronavirus disease 2019 (COVID-19) pandemic is their first experience in population-based care. In past decades, lower population densities, infectious disease outbreaks, epidemics, and pandemics were rare and driven almost exclusively by natural disasters, predatory animals, and war. In the early 1900s, Sir William Osler first advanced the knowledge of zoonotic diseases that are spread from reservoir animals to human animals. Once rare, they now make up 71% or more of new diseases. Globally, zoonotic spread occurs for many reasons. Because the human population has grown in numbers and density, the spread of these diseases accelerated though rapid unsustainable urbanization, biodiversity loss, and climate change. Furthermore, they are exacerbated by an increasing number of vulnerable populations suffering from chronic deficiencies in food, water, and energy. The World Health Organization (WHO) and its International Health Regulation (IHR) Treaty, organized to manage population-based diseases such as Influenza, severe acute respiratory syndrome (SARS), H1N1, Middle East respiratory syndrome (MERS), HIV, and Ebola, have failed to meet population-based expectations. In part, this is due to influence from powerful political donors, which has become most evident in the current COVID-19 pandemic. The global community can no longer tolerate an ineffectual and passive international response system, nor tolerate the self-serving political interference that authoritarian regimes and others have exercised over the WHO. In a highly integrated globalized world, both the WHO with its IHR Treaty have the potential to become one of the most effective mechanisms for crisis response and risk reduction world-wide. Practitioners and health decision-makers must break their silence and advocate for a stronger treaty, a return of the WHO’s singular global authority, and support highly coordinated population-based management. As Osler recognized, his concept of “one medicine, one health” defines what global public health is today.

title: Metagenomic analysis of viromes of dromedary camel fecal samples reveals large number and high diversity of circoviruses and picobirnaviruses
abstract: The recent discovery of Middle East Respiratory Coronavirus and another novel dromedary camel coronavirus UAE-HKU23 in dromedaries has boosted interest in search of novel viruses in dromedaries. In this study, fecal samples of 203 dromedaries in Dubai were pooled and deep sequenced. Among the 7330 assembled viral contigs, 1970 were assigned to mammalian viruses. The largest groups of these contigs matched to Picobirnaviridae, Circoviridae, Picornaviridae, Parvoviridae, Astroviridae and Hepeviridae. Many of these viral families were previously unknown to dromedaries. In addition to the high abundance of contigs from Circoviridae (n=598 with 14 complete genomes) and Picobirnaviridae (n=1236), a high diversity of contigs from these two families was found, with the 14 Circoviridae complete genomes forming at least five clusters and contigs from both genogroup I and genogroup II potentially novel picobirnaviruses. Further studies comparing the incidence of these viral families in healthy and sick dromedaries will reveal their pathogenic potential.

title: Estimating the global spread of COVID-19
abstract: Limited and inconsistent testing and differences in age distribution, health care resources, social distancing, and policies have caused large variations in the extent and dynamics of the COVID-19 pandemic across nations, complicating the estimation of prevalence, the infection fatality rate (IFR), and other factors important to care providers and policymakers. Using data for all 84 countries with reliable testing data (spanning 4.75 billion people) we develop a dynamic epidemiological model integrating data on cases, deaths, excess mortality and other factors to estimate how asymptomatic transmission, disease acuity, hospitalization, and behavioral and policy responses to risk condition prevalence and IFR across nations and over time. For these nations we estimate IFR averages 0.68% (0.64%-0.7%). Cases and deaths through June 18, 2020 are estimated to be 11.8 and 1.48 times official reports, respectively, at 88.5 (85-95.3) million and 600 (586-622) thousand. Prevalence and IFR vary substantially, e.g., Ecuador (18%; 0.61%), Chile (15.5%; 0.57%), Mexico (8.8%; 0.69%), Iran (7.9%; 0.44%), USA (5.3%; 0.99%), UK (5.2%; 1.59%), Iceland (1.65%, 0.56%), New Zealand (0.1%, 0.64%), but all nations remain well below the level needed for herd immunity. By alerting the public earlier and reducing contacts, extensive testing when the pandemic was declared could have averted 35.3 (32.7-42.7) million cases and 197 (171-232) thousand deaths. However, future outcomes are less dependent on testing and more contingent on the willingness of communities and governments to reduce transmission. Absent breakthroughs in treatment or vaccination and with mildly improved responses we project 249 (186-586) million cases and 1.75 (1.40-3.67) million deaths in the 84 countries by Spring 2021.

title: Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics
abstract: Newly emerging pandemics like COVID-19 call for better predictive models to implement early and precisely tuned responses to their deep impact on society. Standard epidemic models provide a theoretically well-founded description of dynamics of disease incidence. For COVID-19 with infectiousness peaking before and at symptom onset, the SEIR model explains the hidden build-up of exposed individuals which challenges containment strategies, in particular, due to delayed epidemic responses to non-pharmaceutical interventions. However, spatial heterogeneity questions the adequacy of modeling epidemic outbreaks on the level of a whole country. Here we show that sequential data assimilation of a stochastic version of the standard SEIR epidemic model captures dynamical behavior of outbreaks on the regional level. Such regional modeling of epidemics with relatively low numbers of infected and realistic demographic noise accounts for both spatial heterogeneity and stochasticity. Based on adapted regional models, population level short-term predictions can be achieved. More realistic epidemic models that include spatial heterogeneity are within reach via sequential data assimilation methods.

title: Fast spread of COVID-19 in Europe and the US suggests the necessity of early, strong and comprehensive interventions
abstract: The COVID-19 pandemic caused more than 800,000 infections and 40,000 deaths by the end of March 2020. However, some of the basic epidemiological parameters, such as the exponential epidemic growth rate and R(0) are debated. We developed an inference approach to control for confounding factors in data collection, such as underreporting and changes in surveillance intensities, and fitted a mathematical model to infection and death count data collected from eight European countries and the US. In all countries, the early epidemic grew exponentially at rates between 0.19–0.29/day (epidemic doubling times between 2.4–3.7 days). This suggests a highly infectious virus with an R(0) likely between 4.0 and 7.1. We show that similar levels of intervention efforts are needed, no matter the goal is mitigation or containment. Early, strong and comprehensive intervention efforts to achieve greater than 74–86% reduction in transmission are necessary.

title: Test performance evaluation of SARS-CoV-2 serological assays
abstract: Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data.  We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system.  Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8–100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3–100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7–94.8%. No consistent cross-reactivity was observed.  Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.

title: An empirical estimate of the infection fatality rate of COVID-19 from the first Italian outbreak
abstract: The coronavirus 2019 (COVID-19) pandemic has been spread-ing globally for months, yet the infection fatality ratio of the disease is still uncertain. This is partly because of inconsistencies in testing and death reporting standards across countries. Our purpose is to provide accurate estimates which do not rely on testing and death count data directly but only use population level statistics.  We collected demographic and death records data from the Italian Institute of Statistics. We focus on the area in Italy that experienced the initial outbreak of COVID-19 and estimated a Bayesian model fitting age-stratified mortality data from 2020 and previous years. We also assessed the sensitivity of our estimates to alternative assumptions on the proportion of population infected.  We estimate an overall infection fatality rate of 1.29% (95% credible interval [CrI] 0.89 - 2.01), as well as large differences by age, with a low infection fatality rate of 0.05% for under 60 year old (CrI 0-.19) and a substantially higher 4.25% (CrI 3.01-6.39) for people above 60 years of age. In our sensitivity analysis, we found that even under extreme assumptions, our method delivered useful information. For instance, even if only 10% of the population were infected, the infection fatality rate would not rise above 0.2% for people under 60.  Our empirical estimates based on population level data show a sharp difference in fatality rates between young and old people and firmly rule out overall fatality ratios below 0.5% in populations with more than 30% over 60 years old.

title: Coronavirus Disease-19: The First 7,755 Cases in the Republic of Korea
abstract: We report the first 7,755 patients with confirmed COVID-19 in Korea as of March 12(th), 2020. A total of 66 deaths have been recorded, giving a case fatality proportion of 0.9%. Older people, and those with comorbidities were at a higher risk of a fatal outcome. The highest number of cases of COVID-19 were in Daegu, followed by Gyeongbuk. This summary may help to understand the disease dynamics in the early phase of the COVID-19 outbreaks, and may therefore, guide future public health measures.

title: American Indian Reservations and COVID-19: Correlates of Early Infection Rates in the Pandemic
abstract: To determine the household and community characteristics most closely associated with variation in COVID-19 incidence on American Indian reservations in the lower 48 states.  Multivariate analysis with population weights.  Two hundred eighty-seven American Indian Reservations and tribal homelands (in Oklahoma) and, as of April 10, 2020, 861 COVID-19 cases on these reservation lands.  The relationship between rate per 1000 individuals of publicly reported COVID-19 cases at the tribal reservation and/or community level and average household characteristics from the 2018 5-Year American Community Survey records.  By April 10, 2020, in regression analysis, COVID-19 cases were more likely by the proportion of homes lacking indoor plumbing (10.83, P = .001) and were less likely according to the percentage of reservation households that were English-only (−2.43, P = .03). Household overcrowding measures were not statistically significant in this analysis (−6.40, P = .326).  Failure to account for the lack of complete indoor plumbing and access to potable water in a pandemic may be an important determinant of the increased incidence of COVID-19 cases. Access to relevant information that is communicated in the language spoken by many reservation residents may play a key role in the spread of COVID-19 in some tribal communities. Household overcrowding does not appear to be associated with COVID-19 infections in our data at the current time. Previous studies have identified household plumbing and overcrowding, and language, as potential pandemic and disease infection risk factors. These risk factors persist. Funding investments in tribal public health and household infrastructure, as delineated in treaties and other agreements, are necessary to protect American Indian communities.

title: A tug-of-war between severe acute respiratory syndrome coronavirus 2 and host antiviral defence: lessons from other pathogenic viruses
abstract: World Health Organization has declared the ongoing outbreak of coronavirus disease 2019 (COVID-19) a Public Health Emergency of International Concern. The virus was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses. Human infection with SARS-CoV-2 leads to a wide range of clinical manifestations ranging from asymptomatic, mild, moderate to severe. The severe cases present with pneumonia, which can progress to acute respiratory distress syndrome. The outbreak provides an opportunity for real-time tracking of an animal coronavirus that has just crossed species barrier to infect humans. The outcome of SARS-CoV-2 infection is largely determined by virus-host interaction. Here, we review the discovery, zoonotic origin, animal hosts, transmissibility and pathogenicity of SARS-CoV-2 in relation to its interplay with host antiviral defense. A comparison with SARS-CoV, Middle East respiratory syndrome coronavirus, community-acquired human coronaviruses and other pathogenic viruses including human immunodeficiency viruses is made. We summarize current understanding of the induction of a proinflammatory cytokine storm by other highly pathogenic human coronaviruses, their adaptation to humans and their usurpation of the cell death programmes. Important questions concerning the interaction between SARS-CoV-2 and host antiviral defence, including asymptomatic and presymptomatic virus shedding, are also discussed.

title: COVID-19 and pets: When pandemic meets panic
abstract: As the novel coronavirus outbreak spreads globally with devastating effects on human health, pets are also becoming unnecessary victims amidst the pandemic panic. Many have been reluctantly left home alone by owners who have been forced to temporarily evacuate their homes. And, although no evidence exists to indicate that they can either transmit the virus or develop its associated coronavirus disease 2019 (COVID-19), fear among the public that pets might play a role in spreading COVID-19 has resulted in pets being abandoned or even killed. This article outlines some of the ways in which the current pandemic has negatively impacted the welfare of pets. It also highlights the relationships between animal, human, and environmental health, as well as the importance of taking a collaborative transdisciplinary One Health approach to help prevent future COVID-19 outbreaks.

title: Excess cases of influenza-like illnesses synchronous with coronavirus disease (COVID-19) epidemic, France, March 2020
abstract: Several French regions where coronavirus disease (COVID-19) has been reported currently show a renewed increase in ILI cases in the general practice-based Sentinelles network. We computed the number of excess cases by region from 24 February to 8 March 2020 and found a correlation with the number of reported COVID-19 cases so far. The data suggest larger circulation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the French population than apparent from confirmed cases.

title: COVID-19, Australia: Epidemiology Report 16 (Reporting week to 23:59 AEST 17 May 2020).
abstract: Confirmed cases in Australia notified up to 17 May 2020: notifications = 7,075; deaths = 100. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. Social distancing measures, public health action and the reduction in international travel have likely been effective in slowing the spread of the disease, in the Australian community. Testing rates over the past week have increased markedly, with a continued very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. New cases of COVID-19 are currently being reported by by only some jurisdictions, albeit at relatively low rates. Although case numbers are low, new cases tend to still be a mix of overseas-acquired and locally-acquired infections. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of new cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years. One third of all cases in this age group have been associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, while the number of new cases each day remains relatively stable at the global level, some areas such as Brazil and India are showing a dramatic rise in reported cases. Although some low-income countries have so far reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of true disease incidence.

title: The COVID-19 (SARS-CoV-2) Uncertainty Tripod in Brazil: Assessments on model-based predictions with large under-reporting
abstract: The COVID-19 pandemic (SARS-CoV-2 virus) is the defying global health crisis of our time. The absence of mass testing and the relevant presence of asymptomatic individuals causes the available data of the COVID-19 pandemic in Brazil to be largely under-reported regarding the number of infected individuals and deaths. We propose an adapted Susceptible-Infected-Recovered (SIR) model which explicitly incorporates the under-reporting and the response of the population to public policies (such as confinement measures, widespread use of masks, etc) to cast short-term and long-term predictions. Large amounts of uncertainty could provide misleading models and predictions. In this paper, we discuss the role of uncertainty in these prediction, which is illustrated regarding three key aspects. First, assuming that the number of infected individuals is under-reported, we demonstrate an anticipation regarding the peak of infection. Furthermore, while a model with a single class of infected individuals yields forecasts with increased peaks, a model that considers both symptomatic and asymptomatic infected individuals suggests a decrease of the peak of symptomatic. Second, considering that the actual amount of deaths is larger than what is being register, then demonstrate the increase of the mortality rates. Third, when consider generally under-reported data, we demonstrate how the transmission and recovery rate model parameters change qualitatively and quantitatively. We also investigate the effect of the"COVID-19 under-reporting tripod", i.e. the under-reporting in terms of infected individuals, of deaths and the true mortality rate. If two of these factors are known, the remainder can be inferred, as long as proportions are kept constant. The proposed approach allows one to determine the margins of uncertainty by assessments on the observed and true mortality rates.

title: Phylogenetic network analysis of SARS-CoV-2 genomes
abstract: In a phylogenetic network analysis of 160 complete human severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) genomes, we find three central variants distinguished by amino acid changes, which we have named A, B, and C, with A being the ancestral type according to the bat outgroup coronavirus. The A and C types are found in significant proportions outside East Asia, that is, in Europeans and Americans. In contrast, the B type is the most common type in East Asia, and its ancestral genome appears not to have spread outside East Asia without first mutating into derived B types, pointing to founder effects or immunological or environmental resistance against this type outside Asia. The network faithfully traces routes of infections for documented coronavirus disease 2019 (COVID-19) cases, indicating that phylogenetic networks can likewise be successfully used to help trace undocumented COVID-19 infection sources, which can then be quarantined to prevent recurrent spread of the disease worldwide.

title: Lack of Antiviral Activity of Darunavir against SARS-CoV-2
abstract: Given the high need and the absence of specific antivirals for treatment of COVID-19 (the disease caused by severe acute respiratory syndrome-associated coronavirus-2 [SARS-CoV-2]), human immunodeficiency virus (HIV) protease inhibitors are being considered as therapeutic alternatives.  Prezcobix/Rezolsta is a fixed-dose combination of 800mg of the HIV protease inhibitor darunavir (DRV) and 150mg cobicistat, a CYP3A4 inhibitor, which is indicated in combination with other antiretroviral agents for the treatment of HIV infection. There are currently no definitive data on the safety and efficacy of DRV/cobicistat for treatment of COVID-19. The in vitro antiviral activity of darunavir against a clinical isolate from a patient infected with SARS-CoV-2 was assessed.  DRV showed no activity against SARS-CoV-2 at clinically relevant concentrations (EC50 >100μM). Remdesivir, used as a positive control, showed potent antiviral activity (EC50 =0.38μM).  Overall, the data do not support the use of DRV for treatment of COVID-19.

title: Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions
abstract: This paper provides a formal evaluation of the predictive performance of a model (and its various updates) developed by the Institute for Health Metrics and Evaluation (IHME) for predicting daily deaths attributed to COVID19 for each state in the United States. The IHME models have received extensive attention in social and mass media, and have influenced policy makers at the highest levels of the United States government. For effective policy making the accurate assessment of uncertainty, as well as accurate point predictions, are necessary because the risks inherent in a decision must be taken into account, especially in the present setting of a novel disease affecting millions of lives. To assess the accuracy of the IHME models, we examine both forecast accuracy as well as the predictive performance of the 95% prediction intervals provided by the IHME models. We find that the initial IHME model underestimates the uncertainty surrounding the number of daily deaths substantially. Specifically, the true number of next day deaths fell outside the IHME prediction intervals as much as 70% of the time, in comparison to the expected value of 5%. In addition, we note that the performance of the initial model does not improve with shorter forecast horizons. Regarding the updated models, our analyses indicate that the later models do not show any improvement in the accuracy of the point estimate predictions. In fact, there is some evidence that this accuracy has actually decreased over the initial models. Moreover, when considering the updated models, while we observe a larger percentage of states having actual values lying inside the 95% prediction intervals (PI), our analysis suggests that this observation may be attributed to the widening of the PIs. The width of these intervals calls into question the usefulness of the predictions to drive policy making and resource allocation.

title: Prevalence and impact of diabetes among people infected with SARS-CoV-2

title: COVID-19 Fatality Rate and Performed Swabs in Italy: a Misleading Perception.
abstract: Disease 2019 (COVID-19) fatality rate in Italy is controversial and is largely affecting discussion on the impact of containment measures that are straining the world's social and economic fabric, such as large-scale use of isolation and quarantine, closing borders, imposing limits on public gatherings, and implementing nationwide lockdowns.  The scientific community, citizens, politicians and mass media are arguing over data that seem to suggest that Italy has a significantly higher number of COVID-19-related deaths than in the rest of the world. Moreover, Italian citizens have a misleading perception related to the number of actually performed swab tests. Citizens and mass media denounce that the coverage obtained by COVID-19 swab testing in Italy is not in line with other countries all over the world.  In this paper, we try to clarify, with a set of statistical analysis conducted world-wide, both aspects by highlighting the actual numbers and by comparing them with the official data available.  The analysis clearly shows that the Italian COVID-19 fatality and mortality rate are in line with the official world scenario, and these findings are true also for the number of COVID-19 swabs performed in Italy and in Lombardy Region.  Up-to-date analysis of this type may simplify the understanding of the pandemic evolution.

title: Age-dependent effects in the transmission and control of COVID-19 epidemics
abstract: The COVID-19 pandemic has shown a markedly low proportion of cases among children. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms, or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from six countries. We estimate that clinical symptoms occur in 25% (95% CrI: 19-32%) of infections in 10-19-year-olds, rising to 76% (68-82%) in over-70s, and that susceptibility to infection in under-20s is approximately half that of older adults. Accordingly, we find that interventions aimed at children may have a relatively small impact on total cases, particularly if the transmissibility of subclinical infections is low. The age-specific clinical fraction and susceptibility we have estimated has implications for the expected global burden of COVID-19 because of demographic differences across settings: in younger populations, the expected clinical attack rate would be lower, although it is likely that comorbidities in low-income countries will affect disease severity. Without effective control measures, regions with older populations may see disproportionally more clinical cases, particularly in the later stages of the pandemic.

title: Loss of smell and taste in combination with other symptoms is a strong predictor of COVID-19 infection
abstract: A strategy for preventing further spread of the ongoing COVID-19 epidemic is to detect infections and isolate infected individuals without the need of extensive bio-specimen testing.  Here we investigate the prevalence of loss of smell and taste among COVID-19 diagnosed individuals and we identify the combination of symptoms, besides loss of smell and taste, most likely to correspond to a positive COVID-19 diagnosis in non-severe cases.  Community survey.  Subscribers of RADAR COVID-19, an app that was launched for use among the UK general population asking about COVID-19 symptoms.  Loss of smell and taste.  COVID-19.  Between 24 and 29 March 2020, 1,573,103 individuals reported their symptoms via the app; 26% reported suffering from one or more symptoms of COVID-19. Of those, n=1702 reported having had a RT-PCR COVID-19 test and gave full report on symptoms including loss of smell and taste; 579 were positive and 1123 negative. In this subset, we find that loss of smell and taste were present in 59% of COVID-19 positive individuals compared to 18% of those negative to the test, yielding an odds ratio (OR) of COVID-19 diagnosis of OR[95%CI]=6.59[5.25; 8.27], P= 1.90x10-59 . We also find that a combination of loss of smell and taste, fever, persistent cough, fatigue, diarrhoea, abdominal pain and loss of appetite is predictive of COVID-19 positive test with sensitivity 0.54[0.44; 0.63], specificity 0.86[0.80; 0.90], ROC-AUC 0.77[0.72; 0.82] in the test set, and cross-validation ROC-AUC 0.75[0.72; 0.77]. When applied to the 410,598 individuals reporting symptoms but not formally tested, our model predicted that 13.06%[12.97%;13.15] of these might have been already infected by the virus.  Our study suggests that loss of taste and smell is a strong predictor of having been infected by the COVID-19 virus. Also, the combination of symptoms that could be used to identify and isolate individuals includes anosmia, fever, persistent cough, diarrhoea, fatigue, abdominal pain and loss of appetite. This is particularly relevant to healthcare and other key workers in constant contact with the public who have not yet been tested for COVID-19.

title: A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coasts
abstract: The ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to make a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coasts. The model is then fitted to current data and implemented using Runge-Kutta methods. Our computation results predict that the number of new cases would peak around mid-April and begin to abate by July, and that the number of cases of COVID-19 might be significantly mitigated by having greater numbers of functional testing kits available for screening. The model also showed how small changes in variables can make large differences in outcomes and highlights the importance of healthcare preparedness during pandemics.

title: Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review
abstract: Rapid diagnostics, vaccines and therapeutics are important interventions for the management of the 2019 novel coronavirus (2019-nCoV) outbreak. It is timely to systematically review the potential of these interventions, including those for Middle East respiratory syndrome-Coronavirus (MERS-CoV) and severe acute respiratory syndrome (SARS)-CoV, to guide policymakers globally on their prioritization of resources for research and development. A systematic search was carried out in three major electronic databases (PubMed, Embase and Cochrane Library) to identify published studies in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Supplementary strategies through Google Search and personal communications were used. A total of 27 studies fulfilled the criteria for review. Several laboratory protocols for confirmation of suspected 2019-nCoV cases using real-time reverse transcription polymerase chain reaction (RT-PCR) have been published. A commercial RT-PCR kit developed by the Beijing Genomic Institute is currently widely used in China and likely in Asia. However, serological assays as well as point-of-care testing kits have not been developed but are likely in the near future. Several vaccine candidates are in the pipeline. The likely earliest Phase 1 vaccine trial is a synthetic DNA-based candidate. A number of novel compounds as well as therapeutics licensed for other conditions appear to have in vitro efficacy against the 2019-nCoV. Some are being tested in clinical trials against MERS-CoV and SARS-CoV, while others have been listed for clinical trials against 2019-nCoV. However, there are currently no effective specific antivirals or drug combinations supported by high-level evidence.

title: Socioeconomic disparities in subway use and COVID-19 outcomes in New York City
abstract: The United States CDC has reported that racial and ethnic disparities in the COVID-19 pandemic may in part be due to socioeconomic disadvantages that require individuals to continue to work outside their home and a lack of paid sick leave. However, data-driven analyses of the socioeconomic determinants of COVID-19 burden are still needed. Using data from New York City (NYC), we aimed to determine how socioeconomic factors impact human mobility and COVID-19 burden.  New York City has a large amount of heterogeneity in socioeconomic status (SES) and demographics among neighborhoods. We used this heterogeneity to conduct a cross-sectional spatial analysis of the associations between human mobility (i.e., subway ridership), sociodemographic factors, and COVID-19 incidence as of April 26, 2020. We also conducted a secondary analysis of NYC boroughs (which are equivalent to counties in the city) to assess the relationship between the decline in subway use and the time it took for each borough to end the exponential growth period of COVID-19 cases.  Areas with the lower median income, a greater percentage of individuals who identify as non-white and/or Hispanic/Latino, a greater percentage of essential workers, and a greater percentage of healthcare workers had more subway use during the pandemic. The positive associations between subway use and median income, and between subway use and percent non-white and/or Hispanic/Latino do not remain when adjusted for the percent of essential workers. This suggests essential work is what drives subway use in lower SES zip codes and communities of color. Increased subway use was associated with a higher rate of COVID-19 cases per 100,000 population when adjusted for testing effort (aRR=1.11; 95% CI: 1.03 - 1.19), but this association was weaker once we adjusted for median income (aRR=1.06; 95% CI: 1.00 - 1.12). All sociodemographic variables were significantly associated with the rate of positive cases per 100,000 population when adjusting for testing effort (except percent uninsured) and adjusting for both income and testing effort. The risk factor with the strongest association with COVID-19 was the percent of individuals in essential work (aRR = 1.59, 95% CI: 1.36 - 1.86). We found that subway use declined prior to any executive order, and there was an estimated 28-day lag between the onset of reduced subway use and the end of the exponential growth period of SARS-CoV-2 within New York City boroughs.  Our results suggest that the ability to stay home during the pandemic has been constrained by SES and work circumstances. Poorer neighborhoods are not afforded the same reductions in mobility as their richer counterparts. Furthermore, lower SES neighborhoods have higher disease burdens, which may be due to inequities in ability to shelter-in-place, and/or due to the plethora of other existing health disparities that increase vulnerability to COVID-19. Furthermore, the extended lag time between the dramatic fall in subway ridership and the end of the exponential growth phase for COVID-19 cases is important for future policy, because it demonstrates that if there is a resurgence, and stay-at-home orders are re-issued, then cities can expect to wait a month before reported cases will plateau.

title: Considerations for Drug Interactions on QTc in Exploratory COVID-19 (Coronavirus Disease 2019) Treatment

title: Severity of coronavirus respiratory tract infections in adults admitted to acute care in Toronto, Ontario
abstract: The World Health Organization has highlighted the need for improved surveillance and understanding of the health burden imposed by non-influenza RNA respiratory viruses. Human coronaviruses (CoVs) are a major cause of respiratory and gastrointestinal tract infections with associated morbidity and mortality.  The objective of our study was to characterize the epidemiology of CoVs in our tertiary care centre, and identify clinical correlates of disease severity.  A cross-sectional study was performed of 226 patients admitted with confirmed CoV respiratory tract infection between 2010 and 2016. Variables consistent with a severe disease burden were evaluated including symptoms, length of stay, intensive care unit (ICU) admission and mortality.  CoVs represented 11.3% of all positive respiratory virus samples and OC43 was the most commonly identified CoV. The majority of infections were community-associated while 21.6% were considered nosocomial. The average length of stay was 11.8 days with 17.3% of patients requiring ICU admission and an all-cause mortality of 7%. In a multivariate model, female gender and smoking were associated with increased likelihood of admission to ICU or death.  This study highlights the significant burden of CoVs and justifies the need for surveillance in the acute care setting.

title: Analysis of the Worldwide Corona Virus (COVID-19) Pandemic Trend;A Modelling Study to Predict Its Spread
abstract: The Coronavirus (COVID-19) has advanced into 197 countries and territories leaving behind a total of 372,757 confirmed cases and 16231 deaths.  One the basis of WHO situation reports data of COVID-19 along with daily official reports from the Japan, China and the Korea we modeled the spread of COVID19 by using the Successive Approximation Method. We defined the two state of data to find the mean ratio (η) of the present cases count to the sum of previous and present cases. This ratio further predicts the future state of COVID-19 pandemic.  The mean ratio (η) of expected cases were found 0.485, while the mean ratio for deaths was found to be 0.49. We calculated worldwide expected lower bound value for confirmed cases 247007 cases with maximum limit of 1667719 cases and minimum deaths count 8660 with upper limit of 117397 deaths in next 30 days. While in the case of Iran, a large increase in the number of deaths are expected in the upcoming 30 days with lower bound value of 1140 deaths and maximum value of 598478 deaths.  Iran whole population is on risk.

title: Coast-to-coast spread of SARS-CoV-2 in the United States revealed by genomic epidemiology
abstract: Since its emergence and detection in Wuhan, China in late 2019, the novel coronavirus SARS-CoV-2 has spread to nearly every country around the world, resulting in hundreds of thousands of infections to date. The virus was first detected in the Pacific Northwest region of the United States in January, 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the U.S., we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated impacts of federal travel restrictions. This study provides evidence for widespread, sustained transmission of SARS-CoV-2 within the U.S. and highlights the critical need for local surveillance.

title: Serial interval of novel coronavirus (COVID-19) infections
abstract: To estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs.  We collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset (n = 28) and a subset of pairs with highest certainty in reporting (n = 18). In addition, we adjust for right truncation of the data as the epidemic is still in its growth phase.  Accounting for right truncation and analyzing all pairs, we estimated the median serial interval at 4.0 days (95% credible interval [CrI]: 3.1, 4.9). Limiting our data to only the most certain pairs, the median serial interval was estimated at 4.6 days (95% CrI: 3.5, 5.9).  The serial interval of COVID-19 is close to or shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 serial interval is also shorter than the serial interval of severe acute respiratory syndrome (SARS), indicating that calculations made using the SARS serial interval may introduce bias.

title: Confirmation of the high cumulative incidence of thrombotic complications in critically ill ICU patients with COVID-19: An updated analysis
abstract: We recently reported a high cumulative incidence of thrombotic complications in critically ill patients with COVID-19 admitted to the intensive care units (ICUs) of three Dutch hospitals. In answering questions raised regarding our study, we updated our database and repeated all analyses.  We re-evaluated the incidence of the composite outcome of symptomatic acute pulmonary embolism (PE), deep-vein thrombosis, ischemic stroke, myocardial infarction and/or systemic arterial embolism in all COVID-19 patients admitted to the ICUs of 2 Dutch university hospitals and 1 Dutch teaching hospital from ICU admission to death, ICU discharge or April 22nd 2020, whichever came first.  We studied the same 184 ICU patients as reported on previously, of whom a total of 41 died (22%) and 78 were discharged alive (43%). The median follow-up duration increased from 7 to 14 days. All patients received pharmacological thromboprophylaxis. The cumulative incidence of the composite outcome, adjusted for competing risk of death, was 49% (95% confidence interval [CI] 41–57%). The majority of thrombotic events were PE (65/75; 87%). In the competing risk model, chronic anticoagulation therapy at admission was associated with a lower risk of the composite outcome (Hazard Ratio [HR] 0.29, 95%CI 0.091–0.92). Patients diagnosed with thrombotic complications were at higher risk of all-cause death (HR 5.4; 95%CI 2.4–12). Use of therapeutic anticoagulation was not associated with all-cause death (HR 0.79, 95%CI 0.35–1.8).  In this updated analysis, we confirm the very high cumulative incidence of thrombotic complications in critically ill patients with COVID-19 pneumonia.

title: 2019-novel Coronavirus (2019-nCoV): estimating the case fatality rate - a word of caution.

title: Reagents hold up European COVID-19 tests
abstract: Politicians in the UK and the Netherlands claim that delays in the rollout of COVID-19 testing are because of a shortage of reagents—typically enzymes and buffers—used in antigen tests to determine the presence of the coronavirus that causes COVID-19 Politicians in the Netherlands have accused Roche of withholding the latest chemical formula for a buffer used in its polymerase chain reaction–based COVID-19 tests And Dutch media outlets say Roche is keeping reagents for its tests within its home country of Switzerland The company tells C&EN that it is doing all it can to provide COVID-19 test kits, as well as the required reagents, in Europe and beyond In the UK, “a critical constraint on the ability to rapidly increase testing capacity is the availability of the chemical reagents,” UK government minister Michael Gove told journalists March 31 UK politicians are under scrutiny because the country’s testing lags Germany’s as well

title: Emergency Caesarean delivery in a patient with confirmed COVID-19 under spinal anaesthesia

title: Identification of a Severe Acute Respiratory Syndrome Coronavirus-Like Virus in a Leaf-Nosed Bat in Nigeria
abstract: Bats are reservoirs for emerging zoonotic viruses that can have a profound impact on human and animal health, including lyssaviruses, filoviruses, paramyxoviruses, and severe acute respiratory syndrome coronaviruses (SARS-CoVs). In the course of a project focused on pathogen discovery in contexts where human-bat contact might facilitate more efficient interspecies transmission of viruses, we surveyed gastrointestinal tissue obtained from bats collected in caves in Nigeria that are frequented by humans. Coronavirus consensus PCR and unbiased high-throughput pyrosequencing revealed the presence of coronavirus sequences related to those of SARS-CoV in a Commerson’s leaf-nosed bat (Hipposideros commersoni). Additional genomic sequencing indicated that this virus, unlike subgroup 2b CoVs, which includes SARS-CoV, is unique, comprising three overlapping open reading frames between the M and N genes and two conserved stem-loop II motifs. Phylogenetic analyses in conjunction with these features suggest that this virus represents a new subgroup within group 2 CoVs.

title: Temperature and precipitation associate with Covid-19 new daily cases: A correlation study between weather and Covid-19 pandemic in Oslo, Norway
abstract: This study aims to analyze the correlation between weather and covid-19 pandemic in the capital city of Norway, Oslo. This study employed a secondary data analysis of covid-19 surveillance data from the Norwegian public health institute and weather data from the Norwegian Meteorological institute. The components of weather include minimum temperature (°C), maximum temperature (°C), temperature average (°C), normal temperature (°C), precipitation level (mm) and wind speed (m/s). Since normality was not fulfilled, a non-parametric correlation test was used for data analysis. Maximum temperature (r = 0.347; p = .005), normal temperature(r = 0.293; p = .019), and precipitation level (r = −0.285; p = .022) were significantly correlated with covid-19 pandemic. The finding serves as an input to a strategy making against the prevention of covid-19 as the country prepare to enter into a new weather season.

title: How best to use limited tests? Improving COVID-19 surveillance in long-term care
abstract: Long-term care facilities (LTCFs) are particularly vulnerable to nosocomial outbreaks of coronavirus disease 2019 (COVID-19), with high rates of transmission and mortality. Timely epidemiological surveillance is essential to detect and respond to outbreaks, but testing resources are highly limited in the current pandemic context.  We used an individual-based transmission model to simulate COVID-19 spread along inter-individual contact networks in the LTCF setting. A range of surveillance strategies were evaluated for their ability to detect simulated outbreaks, assuming limited availability of standard RT-PCR tests. Various epidemiological scenarios were considered, including COVID-19 importation from patient transfers or staff members infected in the community.  We estimated a median delay of 7 (95% uncertainty interval: 2-15) days from importation of an asymptomatic COVID-19-infected patient to first presentation of COVID-19 symptoms among any patients or staff, at which point an additional 7 (0-25) individuals were infected but did not (yet) show symptoms. Across a range of scenarios, the reference surveillance strategy (testing individuals with COVID-like symptoms with signs of severity) took a median 11-21 days to detect an outbreak. Group testing (pooling specimens from multiple individuals for a single RT-PCR test) patients and staff with any COVID-like symptoms was both the most timely and efficient strategy, detecting outbreaks up to twice as quickly as the reference, and more quickly than other considered strategies while using fewer tests. Maximizing use of available tests via testing cascades was more effective than group testing only when substantial testing resources were available (on the order of 1 test/20 beds/day). Including not merely those with symptoms but also newly admitted patients in group tests and testing cascades reduced delays in outbreak detection for LTCFs actively admitting patients potentially already infected with COVID-19.  Improving COVID-19 surveillance can alert healthcare institutions to emerging outbreaks before they escalate, informing a need for urgent public health intervention in settings with ongoing nosocomial transmission.

title: Isolation of and Characterization of Neutralizing Antibodies to Covid-19 from a Large Human Naïve scFv Phage Display Library
abstract: SARS-CoV-2 (Covid-19) has caused currently ongoing global plague and imposed great challenges to health managing systems all over the world, with millions of infections and hundreds of thousands of deaths. In addition to racing to develop vaccines, neutralizing antibodies (nAbs) to this virus have been extensively sought and are expected to provide another prevention and therapy tool against this frantic pandemic. To offer fast isolation and shortened early development, a large human naïve phage display antibody library, was built and used to screen specific nAbs to the receptor-binding domain, RBD, the key for Covid-19 virus entry through a human receptor, ACE2. The obtained RBD-specific antibodies were characterized by epitope mapping, FACS and neutralization assay. Some of the antibodies demonstrated spike-neutralizing property and ACE2-competitiveness. Our work proved that RBD-specific neutralizing binders from human naïve antibody phage display library are promising candidates to for further Covid-19 therapeutics development.

title: Discovering drugs to treat coronavirus disease 2019 (COVID-19).
abstract: The SARS-CoV-2 virus emerged in December 2019 and then spread rapidly worldwide, particularly to China, Japan, and South Korea. Scientists are endeavoring to find antivirals specific to the virus. Several drugs such as chloroquine, arbidol, remdesivir, and favipiravir are currently undergoing clinical studies to test their efficacy and safety in the treatment of coronavirus disease 2019 (COVID-19) in China; some promising results have been achieved thus far. This article summarizes agents with potential efficacy against SARS-CoV-2.

title: A Multicentre Study of 2019 Novel Coronavirus Disease Outcomes of Cancer Patients in Wuhan, China
abstract: At present, there is a global pandemic of coronavirus disease 2019 (COVID-19) pneumonia. Two previous case series from China have suggested that cancer patients are at a higher risk of COVID-19 pneumonia, but the reports were limited by small numbers and few clinical information.  To study clinical characteristics and outcomes of cancer patients infected with COVID-19.  Retrospective study.  Four designated COVID-16 hospitals in Wuhan, Hubei province, China.  Medical records of 67 cancer patients admitted to hospitals between Jan 5, 2020 to Feb 18, 2020 were included.  Demographic, clinical, laboratory, radiological and treatment data were collected. Survival data of the cohort was cut-off on Mar 10, 2020.  Of the 67 patients (median age: 66 years), the median age of patients who had severe illness was older than that of patients who had mild symptoms (P<0.001). Forty-three (64.2%) patients had other concurrent chronic diseases, and the proportion of severe patients had co-morbidities was higher than patients with mild disease (P=0.004). Twenty-three (34.3%) patients were still at the anticancer treatment phase, but no tumour progression and recurrence was observed for all the patients during the treatment of COVID-19 pneumonia. About 70% of these patients had fever (n=53, 79.1%) and/or cough (n=50, 74.6%). Lymphocytopenia was the main laboratory finding accompanying increased C-reactive protein and procalcitonin in cancer patients, especially in severe cases. By Mar 10, 2020, 18 (26.9%) patients died from COVID-19, and 39 (58.2%) patients have been discharged. The median age of survivors was younger than that of deaths (P=0.014). Lung cancer (n=15, 22.4%) with COVID-19 was the most common cancer type and accounted for the highest proportion COVID-19 resulted deaths (33.3%, 5/15). We observed a tendency that patients at the follow-up phase had a better prognosis than that at anticancer treatment phase (P=0.095).  This is a retrospective study with only 67 cases from four hospitals. And some specific clinical information was insufficient.  This study showed COVID-19 patients with cancer seem to have a higher proportion of severe cases and poorer prognosis. The tendency of poor prognosis was more obvious in patients at anticancer treatment phase. We should pay more intensive attentions to cancer patients infected with COVID-19.

title: Estimating the COVID-19 infection rate: Anatomy of an inference problem
abstract: As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Illinois, New York, and Italy is substantially lower than reported.

title: Date of origin of the SARS coronavirus strains
abstract: A new respiratory infectious epidemic, severe acute respiratory syndrome (SARS), broke out and spread throughout the world. By now the putative pathogen of SARS has been identified as a new coronavirus, a single positive-strand RNA virus. RNA viruses commonly have a high rate of genetic mutation. It is therefore important to know the mutation rate of the SARS coronavirus as it spreads through the population. Moreover, finding a date for the last common ancestor of SARS coronavirus strains would be useful for understanding the circumstances surrounding the emergence of the SARS pandemic and the rate at which SARS coronavirus diverge.  We propose a mathematical model to estimate the evolution rate of the SARS coronavirus genome and the time of the last common ancestor of the sequenced SARS strains. Under some common assumptions and justifiable simplifications, a few simple equations incorporating the evolution rate (K) and time of the last common ancestor of the strains (T(0)) can be deduced. We then implemented the least square method to estimate K and T(0 )from the dataset of sequences and corresponding times. Monte Carlo stimulation was employed to discuss the results.  Based on 6 strains with accurate dates of host death, we estimated the time of the last common ancestor to be about August or September 2002, and the evolution rate to be about 0.16 base/day, that is, the SARS coronavirus would on average change a base every seven days. We validated our method by dividing the strains into two groups, which coincided with the results from comparative genomics.  The applied method is simple to implement and avoid the difficulty and subjectivity of choosing the root of phylogenetic tree. Based on 6 strains with accurate date of host death, we estimated a time of the last common ancestor, which is coincident with epidemic investigations, and an evolution rate in the same range as that reported for the HIV-1 virus.

title: Chinese and Italian COVID-19 outbreaks can be correctly described by a modified SIRD model
abstract: The COVID-19 disease is rapidly spreading in whole globe, affecting millions of people and pushing governments to take drastic measures to contain the outbreaks. The understanding of the dynamics of the epidemic is of great interest for the governments and health authorities that are facing COVID-19 outbreaks. The scarce presence of epidemiologic data, due to the still ongoing outbreaks, makes prediction difficult and mainly based on heuristic (fitting) models. However, these models with non-physical based parameters, can only give limited insight in the evolution of the outbreaks. In this work a SIRD compartmental model was developed to describe and predict the evolution of the Chinese and Italian outbreaks. Exploiting the similarities of the measures taken by the governments to contain the virus and of the total population number of Hubei province and Italy, the model was tuned on the Chinese outbreak (almost extinguished) and by perturbation the Italian outbreak was describe and predicted.

title: A simulation-based procedure to estimate base rates from Covid-19 antibody test results I: Deterministic test reliabilities
abstract: We design a procedure (the complete Python code may be obtained at: https://github.com/abhishta91/antibody_montecarlo) using Monte Carlo (MC) simulation to establish the point estimators described below and confidence intervals for the base rate of occurrence of an attribute (e.g., antibodies against Covid-19) in an aggregate population (e.g., medical care workers) based on a test. The requirements for the procedure are the test's sample size (N) and total number of positives (X), and the data on test's reliability. The modus is the prior which generates the largest frequency of observations in the MC simulation with precisely the number of test positives (maximum-likelihood estimator). The median is the upper bound of the set of priors accounting for half of the total relevant observations in the MC simulation with numbers of positives identical to the test's number of positives. Our rather preliminary findings are: The median and the confidence intervals suffice universally; The estimator X/N may be outside of the two-sided 95% confidence interval; Conditions such that the modus, the median and another promising estimator which takes the reliability of the test into account, are quite close; Conditions such that the modus and the latter estimator must be regarded as logically inconsistent; Conditions inducing rankings among various estimators relevant for issues concerning over- or underestimation.

title: Comorbidity and its impact on 1590 patients with Covid-19 in China: A Nationwide Analysis
abstract: The coronavirus disease 2019 (Covid-19) outbreak is evolving rapidly worldwide.  To evaluate the risk of serious adverse outcomes in patients with coronavirus disease 2019 (Covid-19) by stratifying the comorbidity status.  We analysed the data from 1590 laboratory-confirmed hospitalised patients 575 hospitals in 31 province/autonomous regions/provincial municipalities across mainland China between December 11(th), 2019 and January 31(st), 2020. We analyse the composite endpoints, which consisted of admission to intensive care unit, or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared according to the presence and number of comorbidities.  The mean age was 48.9 years. 686 patients (42.7%) were females. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD [hazards ratio (HR) 2.681, 95% confidence interval (95%CI) 1.424–5.048], diabetes (HR 1.59, 95%CI 1.03–2.45), hypertension (HR 1.58, 95%CI 1.07–2.32) and malignancy (HR 3.50, 95%CI 1.60–7.64) were risk factors of reaching to the composite endpoints. The HR was 1.79 (95%CI 1.16–2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61–4.17) among patients with two or more comorbidities.  Among laboratory-confirmed cases of Covid-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.

title: Direct Measurement of Rates of Asymptomatic Infection and Clinical Care-Seeking for Seasonal Coronavirus
abstract: The pandemic potential of the novel coronavirus (nCoV) that emerged in Wuhan, China, during December 2019 is strongly tied to the number and contagiousness of undocumented human infections. Here we present findings from a proactive longitudinal sampling study of acute viral respiratory infections that documents rates of asymptomatic infection and clinical care seeking for seasonal coronavirus. We find that the majority of infections are asymptomatic by most symptom definitions and that only 4% of individuals experiencing a seasonal coronavirus infection episode sought medical care for their symptoms. These numbers indicate that a very high percentage of seasonal coronavirus infections are undocumented and provide a reference for understanding the spread of the emergent nCoV.

title: Assessment of adverse events related to anti-influenza neuraminidase inhibitors using the FDA adverse event reporting system and online patient reviews
abstract: The recommended antiviral drugs available for the treatment and prevention of influenza are neuraminidase inhibitors (NAIs). The aim of this study was to evaluate age-related clinical manifestations of adverse events (AEs) related to NAIs. FAERS and WebMD data were downloaded. The available NAIs selected for the analysis were oseltamivir, peramivir, zanamivir, and laninamivir. Disproportionality was analyzed using the proportional reporting ratio (PRR), the reporting odds ratio (ROR), and the information component (IC) methods. In total, 16729 AEs from 4598 patients and 575 AEs from 440 patients in the FAERS and WebMD, respectively, were included in the analysis. In the FAERS, AEs were more common among those who were younger (<19 years) for zanamivir, while for those who were older (>65 years) for peramivir. A disproportionality analysis showed that signals for vomiting and hallucinations were detected in younger patients given oseltamivir, while an abnormal hepatic function, cardiac failure, shock, and cardio-respiratory arrest were detected in older patients given peramivir. Psychiatric disorders were most common in younger and older patients, while gastrointestinal disorders were most common in adult given oseltamivir in the WebMD. Adverse symptoms related to NAIs varied and depended on the drugs used and the age of the patient.

title: Relative Coronavirus Disease 2019 Mortality: A Swiss Population-based Study
abstract: Severity of the coronavirus disease 2019 (covid-19) has been assessed in terms of absolute mortality in SARS-CoV-2 positive cohorts. An assessment of mortality relative to mortality in the general population is presented.  Retrospective population-based study.  Individual information on symptomatic confirmed SARS-CoV-2 patients and subsequent deaths from any cause were compared to the all-cause mortality in the Swiss population of 2018. Starting February 23, 2020, mortality in covid-19 patients was monitored for 80 days and compared to the population mortality observed in the same time-of-year starting February 23, 2018.  5 160 595 inhabitants of Switzerland aged 35 to 95 without covid-19 (general population in spring 2018) and 20 769 persons tested positively for covid-19 (spring 2020).  Sex- and age-specific mortality rates were estimated using Cox proportional hazards models. Absolute probabilities of death were predicted and risk was assessed in terms of relative mortality by taking the ratio between the sex- and age-specific absolute mortality in covid19 patients and the corresponding mortality in the 2018 general population.  A confirmed SARS-CoV-2 infection substantially increased the probability of death across all patient groups, ranging from nine (6 to 15) times the population mortality in 35-year old infected females to a 53-fold increase (46 to 59) for 95 year old infected males. The highest relative risks were observed among males and older patients. The magnitude of these effects was smaller compared to increases observed in absolute mortality risk. Male covid-19 patients exceeded the population hazard for males (hazard ratio 1.20, 1.00 to 1.44). Each additional year of age increased the population hazard in covid-19 patients (hazard ratio 1.04, 1.03 to 1.05).  Information about the distribution of relevant comorbidities was not available on population level and the associated risk was not quantified.  Health care professionals, decision makers, and societies are provided with an additional population-adjusted assessment of covid-19 mortality risk. In combination with absolute measures of risk, the relative risks presented here help to develop a more comprehensive understanding of the actual impact of covid-19.

title: Disparities in COVID-19 Reported Incidence, Knowledge, and Behavior
abstract: Data from the COVID-19 pandemic in the United States show large differences in hospitalizations and mortality across race and geography. However, there is limited data on health information, beliefs, and behaviors that might indicate different exposure to risk.  A sample of 5,198 respondents in the United States (80% population representative, 20% oversample of hotspot areas in New York City, Seattle, New Orleans, and Detroit) was conducted from March 29th to April 13th to measure differences in knowledge, beliefs and behavior regarding COVID-19. Linear regression was used to understand racial, geographic, political, and socioeconomic differences in COVID-19 reported incidence knowledge, and behaviors after adjusting for state-specific and survey date fixed effects.  The largest differences in COVID-19 knowledge and behaviors are associated with race/ethnicity, gender, and age. African-Americans, men, and people <55 years old are less likely to know how the disease is spread, less likely to know symptoms of COVID-19, wash their hands less frequently, and leave the home more often. Differences by income, political orientation, and living in a hotspot area are much smaller.  There are wide gaps in COVID-19 reported incidence, knowledge regarding disease spread and symptoms, and in social distancing behavior. The findings suggest more effort is needed to increase accurate information and encourage appropriate behaviors among minority communities, men, and younger people.

title: Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020.
abstract: Importance Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19.  To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020.  This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020.  Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data.  There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths.  Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

title: Pre-outbreak determinants of perceived risks of corona infection and preventive measures taken. A prospective population-based study
abstract: Assess how people perceive the risks of coronavirus infection, whether people take preventive measures, and which (pre-outbreak) factors contribute to the perceived risks and measures taken, such as (pre-outbreak) respiratory problems, heart problems, diabetes, anxiety and depression symptoms, loneliness, age, gender, marital status and education level.  Data were collected in the longitudinal LISS panel, based on a random sample of the Dutch population. The coronavirus survey started on March 2, and the data collection ended on March 17 2020. Data were linked with surveys on health and social integration conducted at the end of 2019 (Nstudy sample=3,540).  About 15% perceived the risk of infection as high, and 11% the risk becoming ill when infected. Multivariate logistic regression analyses showed the following. Older age-groups perceived the risk for coronavirus infection as lower (all adjusted Odd Ratios [aOR] smaller than .058). In total, 43.8% had taken preventive measures, especially females (aOR=1.47, 95% CI=1.27-1.69). Those with lower education levels less often used preventive measures (aOR=0.56, 95% CI=0.46-0.69). Those with pre-outbreak respiratory problems (aOR=2.89, 95% CI=2.24-3.73), heart problems (aOR=2.17, 95% CI=1.49-3.16) and diabetes (aOR=3.10, 95% CI=2.02-4.74) perceived the risk becoming ill when infected as higher than others. However, respondents with pre-outbreak respiratory problems and diabetes did not more often take preventive measures.  Vulnerable patients more often recognize that they are at risk becoming ill when infected by the coronavirus, but many do not take preventive measures. Interventions to stimulate the use of preventive measures should pay additional attention to physically vulnerable patients, men and those with lower education levels.

title: Redundancy in reporting on COVID‐19
abstract: Additional to the problems described very well by Dr. Ioannidis1 , there is another issue that became highlighted during this pandemic: redundancy in research and reporting. Redundant articles repeat already known information and are mostly published just for the sake of publishing. By searching through Pubmed, one can easily see that the number of publications related to COVID-19 is growing exponentially (Figure).

title: Neglected and endemic zoonoses.
abstract: Endemic zoonoses are found throughout the developing world, wherever people live in close proximity to their animals, affecting not only the health of poor people but often also their livelihoods through the health of their livestock. Unlike newly emerging zoonoses that attract the attention of the developed world, these endemic zoonoses are by comparison neglected. This is, in part, a consequence of under-reporting, resulting in underestimation of their global burden, which in turn artificially downgrades their importance in the eyes of administrators and funding agencies. The development of cheap and effective vaccines is no guarantee that these endemic diseases will be eliminated in the near future. However, simply increasing awareness about their causes and how they may be prevented-often with very simple technologies-could reduce the incidence of many endemic zoonoses. Sustainable control of zoonoses is reliant on surveillance, but, as with other public-sector animal health services, this is rarely implemented in the developing world, not least because of the lack of sufficiently cheap diagnostics. Public-private partnerships have already provided advocacy for human disease control and could be equally effective in addressing endemic zoonoses.

title: Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China
abstract: We described the epidemiological features of the coronavirus disease 2019 (Covid-19) outbreak, and evaluated the impact of non-pharmaceutical interventions on the epidemic in Wuhan, China.  Individual-level data on 25,961 laboratory-confirmed Covid-19 cases reported through February 18, 2020 were extracted from the municipal Notifiable Disease Report System. Based on key events and interventions, we divided the epidemic into four periods: before January 11, January 11-22, January 23 - February 1, and February 2-18. We compared epidemiological characteristics across periods and different demographic groups. We developed a susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions.  The median age of the cases was 57 years and 50.3% were women. The attack rate peaked in the third period and substantially declined afterwards across geographic regions, sex and age groups, except for children (age <20) whose attack rate continued to increase. Healthcare workers and elderly people had higher attack rates and severity risk increased with age. The effective reproductive number dropped from 3.86 (95% credible interval 3.74 to 3.97) before interventions to 0.32 (0.28 to 0.37) post interventions. The interventions were estimated to prevent 94.5% (93.7 to 95.2%) infections till February 18. We found that at least 59% of infected cases were unascertained in Wuhan, potentially including asymptomatic and mild-symptomatic cases.  Considerable countermeasures have effectively controlled the Covid-19 outbreak in Wuhan. Special efforts are needed to protect vulnerable populations, including healthcare workers, elderly and children. Estimation of unascertained cases has important implications on continuing surveillance and interventions.

title: Modeling COVID 19 in the Basque Country: from introduction to control measure response
abstract: In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque Health managers and the Basque Government during the COVID-19 responses. BMTF is a modeling team, working on different approaches, including statistical methods and artificial intelligence. In this paper we describe and present the results obtained by one of the modeling approaches developed within the BMTF, a stochastic SHARUCD-type models able to describe the disease incidence data, provided by the Basque Health Service, with a single parameter set. Data inspection has shown that the partial lockdown measures were effective to slowdown disease transmission in the Basque Country. Short and longer-term predictions are tested with good results adjusted to the current epidemiological data. The growth rate {lambda} is calculated from the model and from the data and the implications for the reproduction ratio r are shown. At the moment, the reproduction ratio r is estimated to be below the threshold behavior of r = 1, but still close to 1, meaning that although the number of new cases are decelerating, a careful monitoring of the development of the outbreak is required. Besides projections on the national health system needs during the increased population demand on hospital admissions, models were able to describe COVID-19 epidemic in the Basque Country, from introduction to control measure response and are now being used to monitor disease transmission when the country lockdown is gradually lifted. These are the first made public available modeling results for the Basque Country and the efforts will be continued taking into consideration the updated data and new information that are generated over time.

title: On the Coronavirus (COVID-19) Outbreak and the Smart City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence (AI) to Benefit Urban Health Monitoring and Management
abstract: As the Coronavirus (COVID-19) expands its impact from China, expanding its catchment into surrounding regions and other countries, increased national and international measures are being taken to contain the outbreak. The placing of entire cities in ‘lockdown’ directly affects urban economies on a multi-lateral level, including from social and economic standpoints. This is being emphasised as the outbreak gains ground in other countries, leading towards a global health emergency, and as global collaboration is sought in numerous quarters. However, while effective protocols in regard to the sharing of health data is emphasised, urban data, on the other hand, specifically relating to urban health and safe city concepts, is still viewed from a nationalist perspective as solely benefiting a nation’s economy and its economic and political influence. This perspective paper, written one month after detection and during the outbreak, surveys the virus outbreak from an urban standpoint and advances how smart city networks should work towards enhancing standardization protocols for increased data sharing in the event of outbreaks or disasters, leading to better global understanding and management of the same.

title: Any possible role of phosphodiesterase type 5 inhibitors in the treatment of severe COVID19 infections? A lesson from urology

title: The novel coronavirus (2019-nCoV) in pregnancy: What we need to know

title: SARS-CoV-2 specific antibody responses in COVID-19 patients
abstract: A new coronavirus, SARS-CoV-2, has recently emerged to cause a human pandemic. Whereas molecular diagnostic tests were rapidly developed, serologic assays are still lacking, yet urgently needed. Validated serologic assays are important for contact tracing, identifying the viral reservoir and epidemiological studies. Here, we developed serological assays for the detection of SARS-CoV-2 neutralizing, spike- and nucleocapsid-specific antibodies. Using serum samples from patients with PCR-confirmed infections of SARS-CoV-2, other coronaviruses, or other respiratory pathogenic infections, we validated and tested various antigens in different in-house and commercial ELISAs. We demonstrate that most PCR-confirmed SARS-CoV-2 infected individuals seroconverted, as revealed by sensitive and specific in-house ELISAs. We found that commercial S1 IgG or IgA ELISAs were of lower specificity while sensitivity varied between the two, with IgA showing higher sensitivity. Overall, the validated assays described here can be instrumental for the detection of SARS-CoV-2-specific antibodies for diagnostic, seroepidemiological and vaccine evaluation studies.

title: Modeling and Forecasting Trend of COVID-19 Epidemic in Iran
abstract: COVID-19 is an emerging disease and precise data are not available in the world and Iran. this study aimed to determine the epidemic trend and prediction of COVID-19 in Iran.  This study is a secondary data analysis and modeling. We used the daily reports of definitive COVID-19 patients (sampling of severe cases and hospitalization) released by Iran Ministry of Health and Medical Education. Epidemic projection models of Gompertz, Von Bertalanffy and least squared error (LSE) were used to predict the number of cases at April 3, 2020 until May 13, 2020.  R0 in Iran was estimated to be 4.7 that has now fallen to below 2. Given the three different scenarios, the prediction of the patients on April 3, 2020 by Von Bertalanffy, Gompertz and LSE were estimated at 48200, 52500 and 58000, respectively. The number of deceased COVID-19 patients was also estimated to be 3600 individuals using the Von growth model, 4200 ones by Gompertz's model and 4850 ones according to the LSE method. To predict and estimate the number of patients and deaths in the end of epidemic based on Von and Gompertz models, we will have 87000 cases, 4900 and 11000 deaths until 13 May and 1 June, respectively.  The process of controlling the epidemic is tangible. If enforcement and public behavior interventions continue with current trends, the control and reduction of the COVID-19 epidemic in Iran will be flat from April 28, until July, 2020 and new cases are expected to decline from the following Iranian new year.

title: Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world
abstract: the COVID-19 has been successfully contained in China but is spreading all over the world. We use phenomenological models to dissect the development of the epidemics in China and the impact of the drastic control measures both at the aggregate level and within each province. We use the experience from China to analyze the calibration results on Japan, South Korea, Iran, Italy and Europe, and make future scenario projections.  we calibrate the logistic growth model, the generalized logistic growth model, the generalized growth model and the generalized Richards model to the reported number of infected cases from Jan. 19 to March 10 for the whole of China, 29 provinces in China, four severely affected countries and Europe as a whole. The different models provide upper and lower bounds of our scenario predictions.  We quantitatively document four phases of the outbreak in China with a detailed analysis on the heterogenous situations across provinces. Based on Chinese experience, we identify a high risk in Japan with estimated total confirmed cases as of March 25 being 1574 (95% CI: [880, 2372]), and 5669 (95% CI: [988, 11340]) by June. For South Korea, we expect the number of infected cases to approach the ceiling, 7928 (95% CI: [6341, 9754]), in 20 days. We estimate 0.15% (95% CI: [0.03%, 0.30%]) of Italian population to be infected in a positive scenario. We would expect 114867 people infected in Europe in 10 days, in a negative but probable scenario, corresponding to 0.015% European population.  The extreme containment measures implemented by China were very effective with some instructive variations across provinces. For other countries, it is almost inevitable to see the continuation of the outbreak in the coming months. Japan and Italy are in serious situations with no short-term end to the outbreak to be expected. There is a significant risk concerning the upcoming July 2020 Summer Olympics in Tokyo. Iran's situation is highly uncertain with unclear and negative future scenarios, while South Korea is approaching the end of the outbreak. Both Europe and the USA are at early stages of the outbreak, posing significant health and economic risks to the world in absence of serious measures.

title: Similarities and Differences in COVID-19 Awareness, Concern, and Symptoms by Race and Ethnicity in the United States: Cross-Sectional Survey
abstract: Existing health disparities based on race and ethnicity in the United States are contributing to disparities in morbidity and mortality during the coronavirus disease (COVID-19) pandemic. We conducted an online survey of American adults to assess similarities and differences by race and ethnicity with respect to COVID-19 symptoms, estimates of the extent of the pandemic, knowledge of control measures, and stigma.  The aim of this study was to describe similarities and differences in COVID-19 symptoms, knowledge, and beliefs by race and ethnicity among adults in the United States.  We conducted a cross-sectional survey from March 27, 2020 through April 1, 2020. Participants were recruited on social media platforms and completed the survey on a secure web-based survey platform. We used chi-square tests to compare characteristics related to COVID-19 by race and ethnicity. Statistical tests were corrected using the Holm Bonferroni correction to account for multiple comparisons.  A total of 1435 participants completed the survey; 52 (3.6%) were Asian, 158 (11.0%) were non-Hispanic Black, 548 (38.2%) were Hispanic, 587 (40.9%) were non-Hispanic White, and 90 (6.3%) identified as other or multiple races. Only one symptom (sore throat) was found to be different based on race and ethnicity (P=.003); this symptom was less frequently reported by Asian (3/52, 5.8%), non-Hispanic Black (9/158, 5.7%), and other/multiple race (8/90, 8.9%) participants compared to those who were Hispanic (99/548, 18.1%) or non-Hispanic White (95/587, 16.2%). Non-Hispanic White and Asian participants were more likely to estimate that the number of current cases was at least 100,000 (P=.004) and were more likely to answer all 14 COVID-19 knowledge scale questions correctly (Asian participants, 13/52, 25.0%; non-Hispanic White participants, 180/587, 30.7%) compared to Hispanic (108/548, 19.7%) and non-Hispanic Black (25/158, 15.8%) participants.  We observed differences with respect to knowledge of appropriate methods to prevent infection by the novel coronavirus that causes COVID-19. Deficits in knowledge of proper control methods may further exacerbate existing race/ethnicity disparities. Additional research is needed to identify trusted sources of information in Hispanic and non-Hispanic Black communities and create effective messaging to disseminate correct COVID-19 prevention and treatment information.

title: Deep Learning-Based Recognizing COVID-19 and other Common Infectious Diseases of the Lung by Chest CT Scan Images
abstract: COVID-19 has become global threaten. CT acts as an important method of diagnosis. However, human-based interpretation of CT imaging is time consuming. More than that, substantial inter-observer-variation cannot be ignored. We aim at developing a diagnostic tool for artificial intelligence (AI)-based classification of CT images for recognizing COVID-19 and other common infectious diseases of the lung.  In this study, images were retrospectively collected and prospectively analyzed using machine learning. CT scan images of the lung that show or do not show COVID-19 were used to train and validate a classification framework based on convolutional neural network. Five conditions including COVID-19 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, pulmonary tuberculosis, and normal lung were evaluated. Training and validation set of images were collected from Wuhan Jin Yin-Tan Hospital whereas test set of images were collected from Zhongshan Hospital Xiamen University and the fifth Hospital of Wuhan.  Accuracy, sensitivity, and specificity of the AI framework were reported. For test dataset, accuracies for recognizing normal lung, COVID-19 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, and pulmonary tuberculosis were 99.4%, 98.8%, 98.5%, 98.3%, and 98.6%, respectively. For the test dataset, accuracy, sensitivity, specificity, PPV, and NPV of recognizing COVID-19 were 98.8%, 98.2%, 98.9%, 94.5%, and 99.7%, respectively.  The performance of the proposed AI framework has excellent performance of recognizing COVID-19 and other common infectious diseases of the lung, which also has balanced sensitivity and specificity.

title: Rapid clinical diagnosis in fatal swine influenza (H1N1) pneumonia in an adult with negative rapid influenza diagnostic tests (RIDTs): Diagnostic swine influenza triad
abstract: The “herald wave” of the H1N1 pandemic spread from Mexico to the United States in spring 2009. Initially, the epicenter of H1N1 in the United States was in the New York area. Our hospital, like others, was inundated with large numbers of patients who presented at the Emergency Department (ED) with influenza-like illnesses (ILIs) for swine influenza testing and evaluation.  The Winthrop-University Hospital ED used rapid influenza (QuickVue A/B) tests to screen for H1N1 infection. Patients who were rapid influenza A test-positive were also reverse transcription-polymerase chain reaction (RT-PCR) positive for H1N1. In our ED, 30% of patients with ILIs and possible H1N1 pneumonia had negative rapid influenza A screening tests. Because H1N1 RT-PCR testing was restricted, there was no laboratory test to confirm or rule out H1N1. Other rapid influenza diagnostic tests (RIDTs), e.g., the respiratory fluorescent antibody (FA) viral panel test, were used to identify H1N1 patients with negative RIDTs.  Unfortunately, there was not a good correlation between RIDT results and RT-PCR results. There was a critical need to develop a clinical syndromic approach for diagnosing hospitalized adults with probable H1N1 pneumonia with negative RIDTs. Early in the pandemic, the Winthrop-University Hospital Infectious Disease Division developed a diagnostic weighted point score system to diagnose H1N1 pneumonia clinically in RIDT-negative adults. The point score system worked well, but was time-consuming. As the “herald wave” of the pandemic progressed, our ED staff needed a rapid, simplified method to diagnose probable H1N1 pneumonia in hospitalized adults with negative RIDTs. A rapid and simplified diagnosis was based on the diagnostic weighted point score system, which we simplified into a triad of key, nonspecific laboratory indicators. In adults hospitalized with an ILI, a fever >102°F with severe myalgias, and a chest x-ray without focal segmental/lobar infiltrates, the presence of three indicators, i.e., otherwise unexplained relative lymphopenia, elevated serum transaminases, and an elevated creatinine phosphokinase, constituted the diagnostic swine influenza triad. The Infectious Disease Division's diagnostic swine flu triad was used effectively as the pandemic progressed, and was not only useful in correctly diagnosing probable H1N1 pneumonia in hospitalized adults with negative RIDTs, but was also in ruling out mimics of swine influenza, e.g., exacerbations of chronic bronchitis, asthma, or congestive heart failure, as well as bacterial community-acquired pneumonias (CAPs), e.g., legionnaire's disease.  Clinicians can use the Winthrop-University Hospital Infectious Disease Division's Diagnostic swine influenza triad to make a rapid clinical diagnosis of probable H1N1 pneumonia in hospitalized adult patients with negative RIDTs.

title: Final 2012 Reports of Nationally Notifiable Infectious Diseases

title: Cancer Surgery During COVID-19: How We Move Forward

title: Lies, Gosh Darn Lies, and Not Enough Good Statistics: Why Epidemic Model Parameter Estimation Fails
abstract: An opportunity exists in exploring epidemic modeling as a novel way to determine physiological and demic parameters for genetic association studies on a population/environmental (quasi) epidemiological study level. First, the spread of SARS-COV-2 has produced population specific lineages; second, epidemic spread model parameters are tied directly to these physiological and demic rates (e. g. incubation time, recovery time, transmission rate); and third, these parameters may serve as novel phenotypes to associate with region-specific genetic mutations as well as demic characteristics (e. g. age structure, cultural observance of personal space, crowdedness). Therefore, we sought to understand whether the parameters of epidemic models could be determined from the trajectory of infections, recovery, and hospitalizations prior to peak, and also to evaluate the quality and comparability of data between jurisdictions reporting their statistics necessary for the analysis of model parameters across populations. We found that, analytically, the pre-peak growth of an epidemic is limited by a subset of the model variates, and that the rate limiting variables are dominated by the expanding eigenmode of their equations. The variates quickly converge to the ratio of eigenvector components of the positive growth rate, which determines the doubling time. There are 9 parameters and 4 independent components in the eigenmode, leaving 5 undetermined parameters. Those parameters can be strikingly population dependent, and can have significant impact on estimates of hospital loads downstream. Without a sound framework, measurements of infection rates and other parameters are highly corrupted by uneven testing rates to uneven counting and reporting of relevant values. From the standpoint of phenotype parameters, this means that structured experiments must be performed to estimate these parameters in order to perform genetic association studies, or to construct viable models that accurately predict critical quantities such as hospitalization loads.

title: Factors associated with country-variation in COVID-19 morbidity and mortality worldwide: an observational geographic study
abstract: The world is threatened by the outbreak of coronavirus disease 19 (COVID-19) since December 2019. The number of cases and deaths increased dramatically in some countries from March 2020. The objective of our study was to examine potential associated factors with country-variation in COVID-19 morbidity and mortality in the world.  We performed a retrospective geographic study including all countries with the most recent available data on free access on the web. We analyzed univariate and multivariable correlation between both the number of reported cases and deaths by country and demographic, socioeconomic characteristics, lockdown as major control measure, average annual temperature and relative humidity. We performed simple linear regression, independent t test and ANOVA test for univariate analyses and negative binomial regression model for multivariable analyses.  We analyzed data of 186 countries from all world regions. As of 13th April 2020, a total of 1 804 302 COVID-19 cases and 113 444 deaths were reported. The reported number of COVID-19 cases and deaths by countries was associated with the number of days between the first case and lockdown, the number of cases at lockdown, life expectancy at birth, average annual temperature and the socio-economic level. Countries which never implemented BCG vaccination reported higher mortality than others.  The pandemic is still ongoing and poses a global health threat as there is no effective antiviral treatment or vaccines. Thus, timing of control measure implementation is a crucial factor in determining the spread of the epidemic. It should be a lesson for this pandemic and for the future.

title: The impact of early social distancing at COVID-19 Outbreak in the largest Metropolitan Area of Brazil.
abstract: We evaluated the impact of early social distancing on the COVID-19 transmission in the Sao Paulo metropolitan area. Using an age-stratified SEIR model, we determined the time-dependent reproductive number, and forecasted the ICU beds necessary to tackle this epidemic. Within 60 days, these measures might prevent 89,133 deaths.

title: Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study
abstract: The coronavirus disease (COVID-19) pandemic is a global health emergency with over 6 million cases worldwide as of the beginning of June 2020. The pandemic is historic in scope and precedent given its emergence in an increasingly digital era. Importantly, there have been concerns about the accuracy of COVID-19 case counts due to issues such as lack of access to testing and difficulty in measuring recoveries.  The aims of this study were to detect and characterize user-generated conversations that could be associated with COVID-19-related symptoms, experiences with access to testing, and mentions of disease recovery using an unsupervised machine learning approach.  Tweets were collected from the Twitter public streaming application programming interface from March 3-20, 2020, filtered for general COVID-19-related keywords and then further filtered for terms that could be related to COVID-19 symptoms as self-reported by users. Tweets were analyzed using an unsupervised machine learning approach called the biterm topic model (BTM), where groups of tweets containing the same word-related themes were separated into topic clusters that included conversations about symptoms, testing, and recovery. Tweets in these clusters were then extracted and manually annotated for content analysis and assessed for their statistical and geographic characteristics.  A total of 4,492,954 tweets were collected that contained terms that could be related to COVID-19 symptoms. After using BTM to identify relevant topic clusters and removing duplicate tweets, we identified a total of 3465 (<1%) tweets that included user-generated conversations about experiences that users associated with possible COVID-19 symptoms and other disease experiences. These tweets were grouped into five main categories including first- and secondhand reports of symptoms, symptom reporting concurrent with lack of testing, discussion of recovery, confirmation of negative COVID-19 diagnosis after receiving testing, and users recalling symptoms and questioning whether they might have been previously infected with COVID-19. The co-occurrence of tweets for these themes was statistically significant for users reporting symptoms with a lack of testing and with a discussion of recovery. A total of 63% (n=1112) of the geotagged tweets were located in the United States.  This study used unsupervised machine learning for the purposes of characterizing self-reporting of symptoms, experiences with testing, and mentions of recovery related to COVID-19. Many users reported symptoms they thought were related to COVID-19, but they were not able to get tested to confirm their concerns. In the absence of testing availability and confirmation, accurate case estimations for this period of the outbreak may never be known. Future studies should continue to explore the utility of infoveillance approaches to estimate COVID-19 disease severity.

title: Flash Survey on SARS-CoV-2 Infections in Pediatric Patients on anti-Cancer Treatment
abstract: Since the beginning of COVID-19 pandemics, it is known that the severe course of the disease occurs mostly among elderly, whereas it is rare among children and young adults. Comorbidities, in particular diabetes and hypertension, clearly associated with age, besides obesity and smoke are strongly associated with the need of intensive treatment and a dismal outcome. A weaker immunity of the elderly has been proposed as a possible explanation of this uneven age distribution. Along the same line, anecdotal information from Wuhan, China mentioned a severe course of COVID-19 in a child treated for leukemia.  We made a flash survey on COVID19 incidence and severity among children on anticancer treatment. Respondents were asked by email to fill in a short web based survey.  We received reports from 25 countries, where approximately 10,000 patients at risk are followed. At the time of the survey, over 200 of these children were tested, nine of whom were positive for COVID-19. Eight of the nine cases had asymptomatic to mild disease and one was just diagnosed with COVID-19. We also discuss preventive measures that are in place or should be taken as well as treatment options in immunocompromised children with COVID-19.  Thus, even children receiving anti-cancer chemotherapy may have a mild or asymptomatic course of COVID-19. While we should not underestimate the risk of developing a more severe course of COVID-19 than observed here, the intensity of preventive measures should not cause delays or obstructions in oncological treatment.

title: Outbreak of SARS-CoV2: Pathogenesis of infection and cardiovascular involvement
abstract: Since the new coronavirus SARS (SARS-CoV2) has emerged from china, the infection (COVID-19) has affected many countries and led to many deaths worldwide. Like SARS-CoV, ACE2 as a functional receptor for SARS-CoV2 is essential for virus to entry to the cell. ACE2 is a part of RAS which is expressed in several organs that opposes the AngII functions by converting Ang II to Ang (1-7), the one with vasodilation effects. The death rate of COVID-19 is estimated about 3.4%, however, some comorbid conditions like underlying cardiovascular disease, hypertension, and diabetes increase the risk of mortality. In addition, cardiovascular involvement by SARS-CoV2 could be direct through either ACE2 receptors which are expressed tremendously in heart, or by the surge of different cytokines or by ARDS-induced hypoxia. Traditional risk factors could aggravate the process of COVID-19 infection that urges the triage of these high risk patients for SARS-CoV2. Currently, there is no effective, proven treatment or vaccination for COVID-19, but many investigators are struggling to find a treatment strategy as soon as possible. Some potential medications like chloroquine by itself or in combination with azithromycin, and some protease inhibitors used for the treatment of COVID-19 have cardiovascular adverse effects that should be kept in mind in order to close monitor of the patients receiving these medications.

title: Letter to the Editor: Three cases of re‐detectable positive SARS‐CoV‐2 RNA in recovered COVID‐19 patients with antibodies
abstract: The number of hospitalized cases has declined significantly in Wuhan. However, there have been reports that several cases of re‐detectable positive SARS‐CoV‐2 RNA in recovered COVID‐19 patients, the potential reasons of re‐detectable positive patients remained elusive. Here, we report three confirmed cases of COVID‐19 whose IgM was negative and IgG was positive before the first discharge, while nasopharyngeal swab test of SARS‐CoV‐2 RNA turned positive again during hotel isolation. In addition, all three cases presented negative results for IgM antibodies and positive results for IgG antibodies during re‐admission period. These cases suggested that the reasons for re‐detectable positive patients with profile of antibodies may be related to several factors. It is necessary to quarantine COVID‐19 patients for 14 days after discharge, and the role of antibodies in anti‐SARS‐CoV‐2 warrants further investigation. This article is protected by copyright. All rights reserved.

title: Analysis and Prediction of False Negative Results for SARS-CoV-2 Detection with Pharyngeal Swab Specimen in COVID-19 Patients: A Retrospective Study
abstract: False negative results of SARS-CoV-2 nucleic acid detection pose threats to COVID-19 patients and medical workers alike.  To develop multivariate models to determine clinical characteristics that contribute to false negative results of SARS-CoV-2 nucleic acid detection, and use them to predict false negative results as well as time windows for testing positive.  Retrospective Cohort Study (Ethics number of Tongji Hospital: No.  A database of outpatients in Tongji Hospital (University Hospital) from 15 January 2020 to 19 February 2020.  1,324 outpatients with COVID-19  Clinical information on CT imaging reports, blood routine tests, and clinic symptoms were collected. A multivariate logistic regression was used to explain and predict false negative testing results of SARS-CoV-2 detection. A multivariate accelerated failure model was used to analyze and predict delayed time windows for testing positive.  Of the 1,324 outpatients who diagnosed of COVID-19, 633 patients tested positive in their first SARS-CoV-2 nucleic acid test (47.8%), with a mean age of 51 years (SD=14.9); the rest, which had a mean age of 47 years (SD=15.4), tested negative in the first test. Ground glass opacity in a CT imaging report was associated with a lower chance of false negatives (aOR, 0.56), and reduced the length of time window for testing positive by 26%. Consolidation was associated with a higher chance of false negatives (aOR, 1.57), and extended the length of time window for testing positive by 44%. In blood routine tests, basophils (aOR, 1.28) and eosinophils (aOR, 1.29) were associated with a higher chance of false negatives, and were found to extend the time window for testing positive by 23% and 41%, respectively. Age and gender also affected the significantly.  Data were generated in a large single-center study.  Testing outcome and positive window of SARS-CoV-2 detection for COVID-19 patients were associated with CT imaging results, blood routine tests, and clinical symptoms. Taking into account relevant information in CT imaging reports, blood routine tests, and clinical symptoms helped reduce a false negative testing outcome. The predictive AFT model, what we believe to be one of the first statistical models for predicting time window of SARS-CoV-2 detection, could help clinicians improve the accuracy and efficiency of the diagnosis, and hence, optimizes the timing of nucleic acid detection and alleviates the shortage of nucleic acid detection kits around the world.

title: First Pediatric Case of Coronavirus Disease 2019 in Korea
abstract: The large outbreak of coronavirus disease 2019 (COVID-19) that started in Wuhan, China has now spread to many countries worldwide. Current epidemiologic knowledge suggests that relatively few cases are seen among children, which limits opportunities to address pediatric specific issues on infection control and the children's contribution to viral spread in the community. Here, we report the first pediatric case of COVID-19 in Korea. The 10-year-old girl was a close contact of her uncle and her mother who were confirmed to have COVID-19. In this report, we present mild clinical course of her pneumonia that did not require antiviral treatment and serial viral test results from multiple specimens. Lastly, we raise concerns on the optimal strategy of self-quarantine and patient care in a negative isolation room for children.

title: Deep Impact of COVID-19 in the HealthCare of Latin America: the case of Brazil

title: Novel Coronavirus COVID-19 Strike on Arab Countries and Territories: A Situation Report I
abstract: The novel Coronavirus (COVID-19) is an infectious disease caused by a new virus called COVID-19 or 2019-nCoV that first identified in Wuhan, China. The disease causes respiratory illness (such as the flu) with other symptoms such as a cough, fever, and in more severe cases, difficulty breathing. This new Coronavirus seems to be very infectious and has spread quickly and globally. In this work, information about COVID-19 is provided and the situation in Arab countries and territories regarding the COVID-19 strike is presented. The next few weeks main expectations is also given.

title: Considerations of coronavirus (COVID-19) impact and the management of the dead in Brazil
abstract: During a pandemic such as COVID-19, the forensic community plays a key role in the management of the crisis, both nationally and internationally. Much has been written and disseminated regarding protocols for death investigation, infection mitigation and risks, and management of dead. However, in many contexts, the ability of forensic practitioners to follow best-practice procedures is limited by the resources available to them. This article examines some of the impact of the novel coronavirus (COVID-19) in Brazil, with emphasis on management of the dead and challenges faced by medicolegal services.

title: Pre-Procedural Surveillance Testing for SARS-CoV-2 in an Asymptomatic Population Shows Low Rates of Positivity
abstract: Seattle region hospitals have been severely impacted for several months by ongoing community spread of the novel coronavirus 2019 disease. (1,2) Although testing was initially focused on the diagnosis and treatment of symptomatic patients, this effort has now expanded to include surveillance of asymptomatic patients in order to protect health care workers and prevent nosocomial infections. There is an urgent need to understand best practices for the delivery of routine medical care during an ongoing outbreak. (3) Here we report the rates of SARS-CoV-2 infection in asymptomatic patients screened prior to admission or a surgical or aerosolizing procedure.  Beginning March 30, 2020, our hospital began screening all asymptomatic patients prior to needed surgeries and aerosolizing procedures (n=350). On April 13, 2020, we expanded this practice to universal surveillance screening of all patients prior to admission (n=349). Testing was performed on nasopharyngeal swabs using the Washington state emergency use authorized University of Washington CDC-based laboratory-developed test or FDA authorized DiaSorin Simplexa SARS-CoV-2, Hologic Panther Fusion SARS-CoV-2, or Roche cobas SARS-CoV-2 tests. This study was approved by the Institutional Review Board of University of Washington Medical Center (STUDY00009734). Informed consent was not required.  For patients undergoing surgical or aerosolizing procedures, 3 of 350 patients (0.9%) were positive for SARS-CoV-2. For patients who were asymptomatic and tested at the time of admission, 3 of 349 patients (0.9%) were positive and 2 of 349 (0.6%) were inconclusive; inconclusive results were treated as low-level positives. For asymptomatic patients tested for any other reason (e.g. exposure risk), 12 of 157 patients (7.6%) were positive and 1 of 157 (0.6%) were inconclusive. Meanwhile, of the 473 inpatients in this period who had any symptom concerning for COVID-19, 68 of 473 patients (14.3%) were positive. There was a variety of ordering services and locations in all indication categories, with no particular predominating medical service or location. During this time period the outpatient prevalence of SARS-CoV-2 active infection in our region was 3-5% (manuscript in review).  The application of universal surveillance testing for SARS-CoV-2 in patients prior to surgery or aerosolizing procedure shows that the positivity rate for SARS-CoV-2 is low (<1%) in asymptomatic patients without known exposure risk factors. The positivity rate for asymptomatic patients on admission screen was similar; both measures were notably lower than recently reported measurements during an outbreak in New York City that found a positivity rate of 13.7% in asymptomatic pregnant women. (4) The rate of sub-clinical infection likely varies with the scale of the community outbreak. Even in the context of a community-wide outbreak, our data show a low prevalence of COVID-19 infection in the urgent pre-procedural setting. These data reflect the prevalence of asymptomatic SARS-CoV-2 infection in a population of individuals who use medical services and provide an assessment of exposure risk to other patients and healthcare workers around the time of admission. The Greater Seattle Coronavirus Assessment Network (SCAN) also recently published results from the first 18 days of home-based testing and reported no positive tests in 1392 patients reporting no COVID-19-like illness. (5) Although other studies support a large proportion of asymptomatic infections, the data from this metropolitan outbreak do not support a similar pattern. Clinical providers, especially those involved in performing procedures that have a risk of aerosolization, are asking for methods to risk-assess patients prior to the procedure. Pre-procedure testing is one option to accomplish this goal. Importantly, in the midst of an outbreak, testing prior to procedures can decrease the use of PPE, identify appropriate precautions for patients, and reduce the risk of nosocomial infection.

title: A new threat from an old enemy: Re-emergence of coronavirus (Review)
abstract: The new outbreak of coronavirus from December 2019 has brought attention to an old viral enemy and has raised concerns as to the ability of current protection measures and the healthcare system to handle such a threat. It has been known since the 1960s that coronaviruses can cause respiratory infections in humans; however, their epidemic potential was understood only during the past two decades. In the present review, we address current knowledge on coronaviruses from a short history to epidemiology, pathogenesis, clinical manifestation of the disease, as well as treatment and prevention strategies. Although a great amount of research and efforts have been made worldwide to prevent further outbreaks of coronavirus-associated disease, the spread and lethality of the 2019 outbreak (COVID-19) is proving to be higher than previous epidemics on account of international travel density and immune naivety of the population. Only strong, joint and coordinated efforts of worldwide healthcare systems, researchers, and pharmaceutical companies and receptive national leaders will succeed in suppressing an outbreak of this scale.

title: Significance of Coronavirus Mutants in Feces and Diseased Tissues of Cats Suffering from Feline Infectious Peritonitis
abstract: The internal FECV→FIPV mutation theory and three of its correlates were tested in four sibs/half-sib kittens, a healthy contact cat, and in four unrelated cats that died of FIP at geographically disparate regions. Coronavirus from feces and extraintestinal FIP lesions from the same cat were always >99% related in accessory and structural gene sequences. SNPs and deletions causing a truncation of the 3c gene product were found in almost all isolates from the diseased tissues of the eight cats suffering from FIP, whereas most, but not all fecal isolates from these same cats had intact 3c genes. Other accessory and structural genes appeared normal in both fecal and lesional viruses. Deliterious mutations in the 3c gene were unique to each cat, indicating that they did not originate in one cat and were subsequently passed horizontally to the others. Compartmentalization of the parental and mutant forms was not absolute; virus of lesional type was sometimes found in feces of affected cats and virus identical to fecal type was occasionally identified in diseased tissues. Although 3c gene mutants in this study were not horizontally transmitted, the parental fecal virus was readily transmitted by contact from a cat that died of FIP to its housemate. There was a high rate of mutability in all structural and accessory genes both within and between cats, leading to minor genetic variants. More than one variant could be identified in both diseased tissues and feces of the same cat. Laboratory cats inoculated with a mixture of two closely related variants from the same FIP cat developed disease from one or the other variant, but not both. Significant genetic drift existed between isolates from geographically distinct regions of the Western US.

title: Severe acute respiratory syndrome coronavirus 7a accessory protein is a viral structural protein.
abstract: Severe acute respiratory syndrome coronavirus (SCoV) 7a protein is one of the viral accessory proteins. In expressing cells, 7a protein exhibits a variety of biological activities, including induction of apoptosis, activation of the mitogen-activated protein kinase signaling pathway, inhibition of host protein translation, and suppression of cell growth progression. Analysis of SCoV particles that were purified by either sucrose gradient equilibrium centrifugation or a virus capture assay, in which intact SCoV particles were specifically immunoprecipitated by anti-S protein monoclonal antibody, demonstrated that 7a protein was associated with purified SCoV particles. Coexpression of 7a protein with SCoV S, M, N, and E proteins resulted in production of virus-like particles (VLPs) carrying 7a protein, while 7a protein was not released from cells expressing 7a protein alone. Although interaction between 7a protein and another SCoV accessory protein, 3a, has been reported, 3a protein was dispensable for assembly of 7a protein into VLPs. S protein was not required for the 7a protein incorporation into VLPs, and yet 7a protein interacted with S protein in coexpressing cells. These data established that, in addition to 3a protein, 7a protein was a SCoV accessory protein identified as a SCoV structural protein.

title: Dynamics of the COVID-19 pandemic in India
abstract: Understanding the dynamics of the COVID-19 pandemic is crucial for improved control and social distancing strategies. To that effect, we have employed the susceptible-exposed-infectious-recovered model, refined by contact tracing and hospitalization data from Indian provinces Kerala, Delhi, Maharashtra, and West Bengal, as well as from overall India. We have performed a sensitivity analysis to identify the most crucial input parameters, and we have calibrated the model to describe the data as best as possible. Short-term predictions reveal an increasing and worrying trend of COVID-19 cases for all four provinces and India as a whole, while long-term predictions also reveal the possibility of oscillatory dynamics. Our research thus leaves the option open that COVID-19 might become a seasonal occurrence. We also simulate and discuss the impact of media on the dynamics of the COVID-19 pandemic.

title: An SEIR Model for Assessment of Current COVID-19 Pandemic Situation in the UK
abstract: The ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long incubation period, high fatality ratio and non-specific symptoms, making this novel coronavirus far different from common seasonal influenza. In this note, we present a modified SEIR model which takes into account the time lag effect and probability distribution of model states. Based on the proposed model, it is estimated that the actual total number of infected people by 1 April in the UK might have already exceeded 610,000. Average fatality rates under different assumptions at the beginning of April 2020 are also estimated. Our model also reveals that the R0 value is between 7.5-9 which is much larger than most of the previously reported values. The proposed model has a potential to be used for assessing future epidemic situations under different intervention strategies.

title: Humanity tested
abstract: The world needs mass at-home serological testing for antibodies elicited by SARS-CoV-2, and rapid and frequent point-of-care testing for the presence of the virus’ RNA in selected populations.

title: The Application of the Haddon Matrix to Public Health Readiness and Response Planning
abstract: State and local health departments continue to face unprecedented challenges in preparing for, recognizing, and responding to threats to the public’s health. The attacks of 11 September 2001 and the ensuing anthrax mailings of 2001 highlighted the public health readiness and response hurdles posed by intentionally caused injury and illness. At the same time, recent natural disasters have highlighted the need for comparable public health readiness and response capabilities. Public health readiness and response activities can be conceptualized similarly for intentional attacks, natural disasters, and human-caused accidents. Consistent with this view, the federal government has adopted the all-hazards response model as its fundamental paradigm. Adoption of this paradigm provides powerful improvements in efficiency and efficacy, because it reduces the need to create a complex family of situation-specific preparedness and response activities. However, in practice, public health preparedness requires additional models and tools to provide a framework to better understand and prioritize emergency readiness and response needs, as well as to facilitate solutions; this is particularly true at the local health department level. Here, we propose to extend the use of the Haddon matrix—a conceptual model used for more than two decades in injury prevention and response strategies—for this purpose.

title: Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020)
abstract: Rates of Covid-19 infection have declined in many countries, but outbreaks persist in residents of long-term care facilities (LTCFs) who are at high risk of severe outcomes. Epidemiological data from LTCFs are scarce. We used population-level active surveillance to estimate incidence of, and risk factors for Covid-19, and attributable mortality in elderly residents of LTCFs.  Cohort study using individual-level electronic health records from 8,713 residents and daily counts of infection for 9,339 residents and 11,604 staff across 179 UK LTCFs. We modelled risk factors for infection and mortality using Cox proportional hazards and estimated attributable fractions.  2,075/9,339 residents developed Covid-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory confirmed infections. Confirmed infection incidence in residents and staff respectively was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days. 121/179 (67.6%) LTCFs had at least one Covid-19 infection or death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection. 1,694 all-cause deaths occurred in 8,713 (19.4% [18.6%; 20.3%]) residents. 217 deaths occurred in 607 residents with confirmed infection (case-fatality rate: 35.7% [31.9%; 39.7%]). 567/1694 (33.5%) of all-cause deaths were attributable to Covid-19, 28.0% of which occurred in residents with laboratory-confirmed infection. The remainder of excess deaths occurred in asymptomatic or symptomatic residents in the context of limited testing for infection, suggesting substantial under-ascertainment.  1 in 5 residents had symptoms of infection during the pandemic, but many cases were not tested. Higher occupancy and lower staffing levels increase infection risk. Disease control measures should integrate active surveillance and testing with fundamental changes in staffing and care home occupancy to protect staff and residents from infection.

title: A two-wave epidemiological model of COVID-19 outbreaks using MS-Excel(R)
abstract: The emergence of the coronavirus SARS-CoV-2 has raised a global issue and a pandemic disease outbreak, COVID-19, was declared by the World Health Organization on March 12th, 2020. The new virus is rapidly spreading in humans and cases of severe acute respiratory syndromes are being reported worldwide. Health authority advisors and governments from small towns to large countries need to quickly manage and deal with growing epidemiological data on a daily basis. In this work, current available data from reported cases and deaths over time were analyzed and treated. Lethality has been calculated by finding linearization of death cases against reported ones, using a time-delayed data transposition. A two-wave statistical model, 2WM, based on the superposition of normal distributions was used to fit current data and to estimate the evolution of infections and deaths, using Microsoft Excel(R). The model showed good agreement even for apparent single wave behavior in some countries and can easily be extended to any number of waves. A gamma distribution was used as a risk function to estimate death probability from patient admission to reported death. Evolution of fatality cases over time can then be estimated from the model with reasonable accuracy. Data from South Korea, China, Australia, Germany, Italy and Spain were used to validate the model. Data from The United States, United Kingdom and Brazil were used to study the epidemiology as the pandemic progresses. Additionally, the 2WM was applied to world data and to the Brazilian state of Santa Catarina. The model was implemented in MS-Excel, a popular and easy to use analytical tool. A template spreadsheet is provided as supplementary material. Constant lethality can be determined from the initial stage of the pandemic wave. Values ranged from 1.7% to 15.3%, depending on the degree of possible sub notification cases. Even for places with low testing, a linear relationship can be found. The two-wave model can be fine-tuned to properly adjust the data. The second wave pattern was estimated according to the first wave parameter. The accuracy for estimating COVID-19 evolution was compared to the classic SIR model with good agreement. According to the model, based on current trends, health protocols and policies, approximately 10,000,000 cases and 860,000 deaths will be recorded worldwide. Approximately 99% of that number would be reached by the end of July 2020 given constant conditions.

title: Scoping review of prevalence of neurologic comorbidities in patients hospitalized for COVID-19
abstract: The emergence of coronavirus disease 2019 (COVID-19) presents a challenge for neurologists caring for patients with preexisting neurologic conditions hospitalized for COVID-19 or for evaluation of patients who have neurologic complications during COVID-19 infection. We conducted a scoping review of the available literature on COVID-19 to assess the potential effect on neurologists in terms of prevalent comorbidities and incidence of new neurologic events in patients hospitalized with COVID-19.  We searched MEDLINE/PubMed, CINAHL (EBSCO), and Scopus databases for adult patients with preexisting neurologic disease who were diagnosed and hospitalized for COVID-19 or reported incidence of secondary neurologic events following diagnosis of COVID-19. Pooled descriptive statistics of clinical data and comorbidities were examined.  Among screened articles, 322 of 4,014 (8.0%) of hospitalized patients diagnosed and treated for COVID-19 had a preexisting neurologic illness. Four retrospective studies demonstrated an increased risk of secondary neurologic complications in hospitalized patients with COVID-19 (incidence of 6%, 20%, and 36.4%, respectively). Inconsistent reporting and limited statistical analysis among these studies did not allow for assessment of comparative outcomes.  Emerging literature suggests a daunting clinical relationship between COVID-19 and neurologic illness. Neurologists need to be prepared to reorganize their consultative practices to serve the neurologic needs of patients during this pandemic.

title: [Management and clinical thinking of Coronavirus Disease 2019].
abstract: In December 2019, the 2019 novel coronavirus pneumonia (NCP, officially named Coronavirus Disease 2019(COVID-19) by the World Health Organization) broke out in Wuhan, Hubei, and it quickly spread to the whole country and abroad. The situation was at stake. The sudden and serious COVID-19 epidemic has brought us a lot of urgent problems. How to effectively control the spread of COVID-19? When does the population infection rate rise to its peak? What will eventually be the number of infected patients? How to make early diagnosis? What effective antiviral drugs are available? How to effectively treat with existing drugs? Can it successfully improve the survival rate of critically patients? In response to the above questions, we put forward corresponding suggestions and reflections from the perspective of the infectious clinician.

title: Bayesian analysis of tests with unknown specificity and sensitivity
abstract: When testing for a rare disease, prevalence estimates can be highly sensitive to uncertainty in the specificity and sensitivity of the test. Bayesian inference is a natural way to propagate these uncertainties, with hierarchical modeling capturing variation in these parameters across experiments. Another concern is the people in the sample not being representative of the general population. Statistical adjustment cannot without strong assumptions correct for selection bias in an opt-in sample, but multilevel regression and poststratification can at least adjust for known differences between sample and population. We demonstrate these models with code in R and Stan and discuss their application to a controversial recent study of COVID-19 antibodies in a sample of people from the Stanford University area. Wide posterior intervals make it impossible to evaluate the quantitative claims of that study regarding the number of unreported infections. For future studies, the methods described here should facilitate more accurate estimates of disease prevalence from imperfect tests performed on non-representative samples.

title: Pharmacotherapy in COVID-19; A narrative review for emergency providers
abstract: The COVID-19 pandemic has been particularly challenging due to a lack of established therapies and treatment guidelines. With the rapid transmission of disease, even the off-label use of available therapies has been impeded by limited availability. Several antivirals, antimalarials, and biologics are being considered for treatment at this time. The purpose of this literature review is to synthesize the available information regarding treatment options for COVID-19 and serve as a resource for health care professionals.  This narrative review was conducted to summarize the effectiveness of current therapy options for COVID-19 and address the controversial use of non-steroidal anti-inflammatory drugs (NSAIDs), angiotensin converting enzyme (ACE) inhibitors, and angiotensin receptor blockers (ARBs). PubMed and SCOPUS were queried using a combination of the keywords “COVID 19,” “SARS-CoV-2,” and “treatment.” All types of studies were evaluated including systematic reviews, case-studies, and clinical guidelines.  There are currently no therapeutic drugs available that are directly active against SARS-CoV-2; however, several antivirals (remdesivir, favipiravir) and antimalarials (chloroquine, hydroxychloroquine) have emerged as potential therapies. Current guidelines recommend combination treatment with hydroxychloroquine/azithromycin or chloroquine, if hydroxychloroquine is unavailable, in patients with moderate disease, although these recommendations are based on limited evidence. Remdesivir and convalescent plasma may be considered in critical patients with respiratory failure; however, access to these therapies may be limited. Interleukin-6 (IL-6) antagonists may be used in patients who develop evidence of cytokine release syndrome (CRS). Glucocorticoids should be avoided unless there is evidence of refractory septic shock, acute respiratory distress syndrome (ARDS), or another compelling indication for their use. ACE inhibitors and ARBs should not be discontinued at this time and ibuprofen may be used for fever.  There are several ongoing clinical trials that are testing the efficacy of single and combination treatments with the drugs mentioned in this review and new agents are under development. Until the results of these trials become available, we must use the best available evidence for the prevention and treatment of COVID-19. Additionally, we can learn from the experiences of healthcare providers around the world to combat this pandemic.

title: A prospect on the use of antiviral drugs to control local outbreaks of COVID-19
abstract: Current outbreaks of COVID-19 are threatening the health care systems of several countries around the world. Control measures, based on isolation and quarantine, have been shown to decrease and delay the burden of the ongoing epidemic. With respect to the ongoing COVID-19 epidemic, recent modelling work shows that this intervention technique may be inadequate to control local outbreaks, even when perfect isolation is assumed. Furthermore, the effect of infectiousness prior to symptom onset combined with a significant proportion of asymptomatic infectees further complicates the use of contact tracing. Antivirals, which decrease the viral load and reduce the infectiousness, could be integrated in the control measures in order to augment the feasibility of controlling the epidemic.  Using a simulation-based model of viral transmission we tested the efficacy of different intervention measures for the control of COVID-19. For individuals that were identified through contact tracing, we evaluate two procedures: monitoring individuals for symptoms onset and testing of individuals. Moreover, we investigate the effect of a potent antiviral compound on the contact tracing process.  The use of an antiviral drug, in combination with contact tracing, quarantine and isolation, results in a significant decrease of the final size, the peak incidence, and increases the probability that the outbreak will fade out.  For an infectious disease in which presymptomatic infections are plausible, an intervention measure based on contact tracing performs better when realized together with testing instead of monitoring, provided that the test is able to detect infections during the incubation period. In addition, in all tested scenarios, the model highlights the benefits of the administration of an antiviral drug in addition to quarantine, isolation and contact tracing. The resulting control measure, could be an effective strategy to control local and re-emerging outbreaks of COVID-19.

title: Estimation of risk factors for COVID-19 mortality - preliminary results
abstract: Since late December 2019 a new epidemic outbreak has emerged from Whuhan, China. Rapidly the new coronavirus has spread worldwide. China CDC has reported results of a descriptive exploratory analysis of all cases diagnosed until the 11th February 2020, presenting the epidemiologic curves and geo-temporal spread of COVID-19 along with case fatality rate according to some baseline characteristics, such as age, gender and several well-established high prevalence comorbidities. Despite this, we intend to increase even further the predictive value of that manuscript by presenting the odds ratio for mortality due to COVID-19 adjusted for the presence of those comorbidities and baseline characteristics such as age and gender. Besides, we present a way to determine the risk of each particular patient, given his characteristics. We found that age is the variable that presents higher risk of COVID-19 mortality, where 60 or older patients have an OR = 18.8161 (CI95%[7.1997; 41.5517]). Regarding comorbidities, cardiovascular disease appears to be the riskiest (OR=12.8328 CI95%[10.2736; 15.8643], along with chronic respiratory disease (OR=7.7925 CI95%[5.5446; 10.4319]). Males are more likely to die from COVID-19 (OR=1.8518 (CI95%[1.5996; 2.1270]). Some limitations such as the lack of information about the correct prevalence of gender per age or about comorbidities per age and gender or the assumption of independence between risk factors are expected to have a small impact on results. A final point of paramount importance is that the equation presented here can be used to determine the probability of dying from COVID-19 for a particular patient, given its age interval, gender and comorbidities associated.

title: COVID-19 infection and rheumatoid arthritis: Faraway, so close!
abstract: The outbreak of the new coronavirus infections COVID-19 in December 2019 in China has quickly become a global health emergency. Given the lack of specific anti-viral therapies, the current management of severe acute respiratory syndrome coronaviruses (SARS-CoV-2) is mainly supportive, even though several compounds are now under investigation for the treatment of this life-threatening disease. COVID-19 pandemic is certainly conditioning the treatment strategy of a complex disorder as rheumatoid arthritis (RA), whose infectious risk is increased compared to the general population because of an overall impairment of immune system typical of autoimmune diseases combined with the iatrogenic effect generated by corticosteroids and immunosuppressive drugs. However, the increasing knowledge about the pathophysiology of SARS-CoV-2 infection is leading to consider some anti-rheumatic drugs as potential treatment options for the management of COVID-19. In this review we will critically analyse the evidences on either positive or negative effect of drugs commonly used to treat RA in this particular scenario, in order to optimize the current approach to RA patients.

title: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Children and Adolescents: A Systematic Review
abstract: The current rapid worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection justifies the global effort to identify effective preventive strategies and optimal medical management. While data are available for adult patients with coronavirus disease 2019 (COVID-19), limited reports have analyzed pediatric patients infected with SARS-CoV-2.  To evaluate currently reported pediatric cases of SARS-CoV-2 infection.  An extensive search strategy was designed to retrieve all articles published from December 1, 2019, to March 3, 2020, by combining the terms coronavirus and coronavirus infection in several electronic databases (PubMed, Cochrane Library, and CINAHL), and following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Retrospective cross-sectional and case-control studies, case series and case reports, bulletins, and national reports about the pediatric SARS-CoV-2 infection were included. The risk of bias for eligible observational studies was assessed according to the Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.  A total of 815 articles were identified. Eighteen studies with 1065 participants (444 patients were younger than 10 years, and 553 were aged 10 to 19 years) with confirmed SARS-CoV-2 infection were included in the final analysis. All articles reflected research performed in China, except for 1 clinical case in Singapore. Children at any age were mostly reported to have mild respiratory symptoms, namely fever, dry cough, and fatigue, or were asymptomatic. Bronchial thickening and ground-glass opacities were the main radiologic features, and these findings were also reported in asymptomatic patients. Among the included articles, there was only 1 case of severe COVID-19 infection, which occurred in a 13-month-old infant. No deaths were reported in children aged 0 to 9 years. Available data about therapies were limited.  To our knowledge, this is the first systematic review that assesses and summarizes clinical features and management of children with SARS-CoV-2 infection. The rapid spread of COVID-19 across the globe and the lack of European and US data on pediatric patients require further epidemiologic and clinical studies to identify possible preventive and therapeutic strategies.

title: Artificial infectious disease optimization: A SEIQR epidemic dynamic model-based function optimization algorithm
abstract: To solve some complicated function optimization problems, an artificial infectious disease optimization algorithm based on the SEIQR epidemic model is constructed, it is called as the SEIQR algorithm, or SEIQRA in short. The algorithm supposes that some human individuals exist in an ecosystem; each individual is characterized by a number of features; an infectious disease (SARS) exists in the ecosystem and spreads among individuals, the disease attacks only a part of features of an individual. Each infected individual may pass through such states as susceptibility (S), exposure (E), infection (I), quarantine (Q) and recovery (R). State S, E, I, Q and R can automatically and dynamically divide all people in the ecosystem into five classes, it provides the diversity for SEIQRA; that people can be attacked by the infectious disease and then transfer it to other people can cause information exchange among people, information exchange can make a person to transit from one state to another; state transitions can be transformed into operators of SEIQRA; the algorithm has 13 legal state transitions, which corresponds to 13 operators; the transmission rules of the infectious disease among people is just the logic to control state transitions of individuals among S, E, I, Q and R, it is just the synergy of SEIQRA, the synergy can be transformed into the logic structure of the algorithm. The 13 operators in the algorithm provide a native opportunity to integrate many operations with different purposes; these operations include average, differential, expansion, chevy, reflection and crossover. The 13 operators are executed equi-probably; a stable heart rhythm of the algorithm is realized. Because the infectious disease can only attack a small part of organs of a person when it spreads among people, the part variables iteration strategy (PVI) can be ingeniously applied, thus enabling the algorithm to possess of high performance of computation, high suitability for solving some kinds of complicated optimization problems, especially high dimensional optimization problems. Results show that SEIQRA has characteristics of strong search capability and global convergence, and has a high convergence speed for some complicated functions optimization problems.

title: Olfactory and Gustatory Dysfunction as an Early Identifier of COVID-19 in Adults and Children: An International Multicenter Study
abstract: To evaluate the prevalence and characteristics of olfactory or gustatory dysfunction in coronavirus disease 2019 (COVID-19) patients.  Multicenter case series.  Five tertiary care hospitals (3 in China, 1 in France, 1 in Germany).  In total, 394 polymerase chain reaction (PCR)–confirmed COVID-19-positive patients were screened, and those with olfactory or gustatory dysfunction were included. Data including demographics, COVID-19 severity, patient outcome, and the incidence and degree of olfactory and/or gustatory dysfunction were collected and analyzed. The Questionnaire of Olfactory Disorders (QOD) and visual analog scale (VAS) were used to quantify olfactory and gustatory dysfunction, respectively. All subjects at 1 hospital (Shanghai) without subjective olfactory complaints underwent objective testing.  Of 394 screened subjects, 161 (41%) reported olfactory and/or gustatory dysfunction and were included. Incidence of olfactory and/or gustatory disorders in Chinese (n = 239), German (n = 39), and French (n = 116) cohorts was 32%, 69%, and 49%, respectively. The median age of included subjects was 39 years, 92 of 161 (57%) were male, and 10 of 161 (6%) were children. Of included subjects, 10% had only olfactory or gustatory symptoms, and 19% had olfactory and/or gustatory complaints prior to any other COVID-19 symptom. Of subjects with objective olfactory testing, 10 of 90 demonstrated abnormal chemosensory function despite reporting normal subjective olfaction. Forty-three percent (44/102) of subjects with follow-up showed symptomatic improvement in olfaction or gustation.  Olfactory and/or gustatory disorders may represent early or isolated symptoms of severe acute respiratory syndrome coronavirus 2 infection. They may serve as a useful additional screening criterion, particularly for the identification of patients in the early stages of infection.

title: Multilevel Integrated Model with a Novel Systems Approach (MIMANSA) for Simulating the Spread of COVID-19
abstract: Abstract COVID-19 has affected people's lives all over the world. It has created a perplexing situation about what actions one should and should not take. Mathematical modeling of biological systems is challenging and gives a different perspective, especially in decision making under multiple complex scenarios. Public health officials grapple with multiple issues such as recommending a lockdown, contact tracing, promoting the mask usage, social distancing, and frequent handwashing, as well as keeping the families of patients in isolation for the incubation period. It is even more challenging to find the optimal combination of all of the above without the use of a suitable mathematical model. There are many different approaches to modeling the spread of SARS-CoV-2, the virus that causes COVID-19. Some models are easy to use, while others need extensive use of high-end computers. However, models to assist public health official's decision making are hard to find. In this paper, we discuss a novel systems approach to building a model for simulating the spread of COVID-19. The model, MIMANSA, divides an individual's in-person social interactions into three areas, namely home, workplace, and public places. While tracking the in-person interactions, the model follows the virus spread. Internally, the model labels healthy people who turn into silent carriers, virus-infected patients, or healthy carriers. It tracks down to the smallest level of a single day interaction. As and when a new silent carrier is created, the model automatically expands and builds a network of virus spread. All single-day blocks are integrated to get the final result. MIMANSA is novel due to its ability to build a virus spread network as a multilevel, integrated model, and in the end, enable one to make complex decisions with ease. MIMANSA is trained and validated using the data from the www.COVID-19India.org website. It does not use any arbitrary constants. All its parameters have a physical significance and are measurable. Once trained, the parameter estimation is complete, and the model is ready to run multiple scenarios. MIMANSA has four control mechanisms that a user can use. It helps one simulate the what-if scenarios. The first one is to control the exposure level to the virus depending on the number of hours spent with a silent carrier. The second provides control over the infection rate or the probability of a healthy person getting infected in the presence of a silent carrier. The third one allows the user to control lockdown effectiveness percentage, and the fourth one gives control over quarantine percentage. Inside the model, MIMANSA differentiates between virus-infected patients, silent carriers, and healthy carriers. MIMANSA has the capability to consider variations in virus activity levels of every asymptomatic patient, varying the exposure to the virus, and varying the infection rate depending on the person's immunity. MIMANSA can simulate scenarios to study the impact of many different conditions simultaneously. MIMANSA assists public health officials in complex decision making, enables scientists in projecting the SARS-CoV-2 virus spread, and aids hospital administrators in management. MIMANSA will play a significant role in finding the balance between the effect of strict lockdown on the economy vs. the marginally high number of COVID-19 patients with a bit relaxed lockdown.

title: Three adjacent nucleotide changes spanning two residues in SARS-CoV-2 nucleoprotein: possible homologous recombination from the transcription-regulating sequence
abstract: The COVID-19 pandemic is caused by the single-stranded RNA virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus of zoonotic origin that was first detected in Wuhan, China in December 2019. There is evidence that homologous recombination contributed to this cross-species transmission. Since that time the virus has demonstrated a high propensity for human-to-human transmission. Here we report two newly identified adjacent amino acid polymorphisms in the nucleocapsid at positions 203 and 204 (R203K/G204R) due to three adjacent nucleotide changes across the two codons (i.e. AGG GGA to AAA CGA). This new strain within the LGG clade may have arisen by a form of homologous recombination from the core sequence (CS-B) of the transcription-regulating sequences of SAS-CoV-2 itself and has rapidly increased to approximately one third of reported sequences from Europe during the month of March 2020. We note that these polymorphisms are predicted to reduce the binding of an overlying putative HLA-C*07-restricted epitope and that HLA-C*07 is prevalent in Caucasians being carried by >40% of the population. The findings suggest that homologous recombination may have occurred since its introduction into humans and be a mechanism for increased viral fitness and adaptation of SARS-CoV-2 to human populations.

title: Coronavirus disease 2019 in pregnancy: early lessons
abstract: The worldwide incidence of coronavirus disease 2019 (COVID-19) infection is rapidly increasing, but there exists limited information on coronavirus disease 2019 in pregnancy. Here, we present our experience with 7 confirmed cases of coronavirus disease 2019 in pregnancy presenting to a single large New York City tertiary care hospital. Of the 7 patients, 5 presented with symptoms of coronavirus disease 2019, including cough, myalgias, fevers, chest pain, and headache. Of the 7 patients, 4 were admitted to the hospital, including 2 who required supportive care with intravenous hydration. Of note, the other 2 admitted patients who were asymptomatic on admission to the hospital, presenting instead for obstetrically indicated labor inductions, became symptomatic after delivery, each requiring intensive care unit admission.

title: Heterogeneity in District-Level Transmission of Ebola Virus Disease during the 2013-2015 Epidemic in West Africa
abstract: The Ebola virus disease (EVD) epidemic in West Africa in 2013–2015 spread heterogeneously across the three hardest-hit countries Guinea, Liberia and Sierra Leone and the estimation of national transmission of EVD provides little information about local dynamics. To investigate district-level transmissibility of EVD, we applied a statistical modelling approach to estimate the basic reproduction number (R(0)) for each affected district and each country using weekly incident case numbers. We estimated growth rates during the early exponential phase of the outbreak using exponential regression of the case counts on the first eight weeks since onset. To take into account the heterogeneity between and within countries, we fitted a mixed effects model and calculated R(0) based on the predicted individual growth rates and the reported serial interval distribution. At district level, R(0) ranged from 0.36 (Dubréka) to 1.72 (Beyla) in Guinea, from 0.53 (Maryland) to 3.37 (Margibi) in Liberia and from 1.14 (Koinadugu) to 2.73 (Western Rural) in Sierra Leone. At national level, we estimated an R(0) of 0.97 (95% CI 0.77–1.18) for Guinea, 1.26 (95% CI 0.98–1.55) for Liberia and 1.66 (95% CI 1.32–2.00) for Sierra Leone. Socio-demographic variables related to urbanisation such as high population density and high wealth index were found positively associated with R(0) suggesting that the consequences of fast urban growth in West Africa may have contributed to the increased spread of EVD.

title: Predicting the number of reported and unreported cases for the COVID-19 epidemic in South Korea, Italy, France and Germany
abstract: We model the COVID-19 coronavirus epidemic in South Korea, Italy, France, and Germany. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.

title: COVID-19: Recovering estimates of the infected fatality rate during an ongoing pandemic through partial data
abstract: In an ongoing epidemic, the case fatality rate is not a reliable estimate of a disease's severity. This is particularly so when a large share of asymptomatic or pauci-symptomatic patients escape testing, or when overwhelmed healthcare systems are forced to limit testing further to severe cases only. By leveraging data on COVID-19, we propose a novel way to estimate a disease's infected fatality rate, the true lethality of the disease, in the presence of sparse and partial information. We show that this is feasible when the disease has turned into a pandemic and data comes from a large number of countries, or regions within countries, as long as testing strategies vary sufficiently. For Italy, our method estimates an IFR of 1.1% (95% CI: 0.2% - 2.1%), which is strongly in line with other methods. At the global level, our method estimates an IFR of 1.6% (95% CI: 1.1% - 2.1%). This method also allows us to show that the IFR varies according to each country's age structure and healthcare capacity.

title: National UK programme of community health workers for COVID-19 response

title: PCR sequencing of the spike genes of geographically and chronologically distinct human coronaviruses 229E
abstract: A reverse transcription nested PCR (RT-PCR) sequencing methodology was developed and used to generate sequence data from the spike genes of three geographically and chronologically distinct human coronaviruses 229E. These three coronaviruses were isolated originally from the USA in the 1960s (human coronavirus 229E strain ATCC VR-74), the UK in the 1990s (human coronavirus 229E LRI 281) and Ghana (human coronavirus 229E A162). Upon translation and alignment with the published spike protein sequence of human coronavirus 229E ‘LP’ (isolated in the UK in the 1970s), it was found that variation within the translated protein sequences was rather limited. In particular, minimal variation was observed between the translated spike protein sequence of human coronaviruses 229E LP and ATCC VR-74 (1/1012 amino acid differences), whilst most variation was observed between the translated spike protein sequence of human coronaviruses 229E LP and A162 (47/1012 amino acid changes). Further, the translated spike protein sequence of human coronavirus 229E A162 showed three clusters of amino acid changes, situated within the 5′ half of the translated spike protein sequence.

title: Comparative analyses revealed reduced spread of COVID-19 in malaria endemic countries
abstract: In late 2019, SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) infection started in Hubei province of China and now it has spread like a wildfire in almost all parts of the world except some. WHO named the disease caused by SARS-CoV-2 as COVID-19 (CoronaVirus Disease-2019). It is very intriguing to see a mild trend of infection in some countries which could be attributed to mitigation efforts, lockdown strategies, health infrastructure, demographics and cultural habits. However, the lower rate of infection and death rates in mostly developing countries, which are not placed at higher levels in terms of healthcare facilities, is a very surprising observation. To address this issue, we hypothesize that this lower rate of infection is majorly been observed in countries which have a higher transmission/prevalence of protozoan parasite borne disease, malaria. We compared the COVID-19 spread and malaria endemicity of 108 countries which have shown at least 200 cases of COVID-19 till 18th April 2020. We found that the number of COVID-19 cases per million population correlates negatively with the malaria endemicity of respective countries. The malaria free countries not only have higher density of COVID-19 infections but also the higher case fatality rates as compared to highly malaria endemic countries. We also postulate that this phenomenon is due to natural immune response against malaria infection, which is providing a heterologous protection against the virus. Unfortunately, there is no licensed vaccine against SARS-CoV-2 yet, but this information will be helpful in design of future strategies against fast spreading COVID-19 disease.

title: First 12 patients with coronavirus disease 2019 (COVID-19) in the United States
abstract: More than 93,000 cases of coronavirus disease (COVID-19) have been reported worldwide. We describe the epidemiology, clinical course, and virologic characteristics of the first 12 U.S. patients with COVID-19.  We collected demographic, exposure, and clinical information from 12 patients confirmed by CDC during January 20-February 5, 2020 to have COVID-19. Respiratory, stool, serum, and urine specimens were submitted for SARS-CoV-2 rRT-PCR testing, virus culture, and whole genome sequencing.  Among the 12 patients, median age was 53 years (range: 21-68); 8 were male, 10 had traveled to China, and two were contacts of patients in this series. Commonly reported signs and symptoms at illness onset were fever (n=7) and cough (n=8). Seven patients were hospitalized with radiographic evidence of pneumonia and demonstrated clinical or laboratory signs of worsening during the second week of illness. Three were treated with the investigational antiviral remdesivir. All patients had SARS-CoV-2 RNA detected in respiratory specimens, typically for 2-3 weeks after illness onset, with lowest rRT-PCR Ct values often detected in the first week. SARS-CoV-2 RNA was detected after reported symptom resolution in seven patients. SARS-CoV-2 was cultured from respiratory specimens, and SARS-CoV-2 RNA was detected in stool from 7/10 patients.  In 12 patients with mild to moderately severe illness, SARS-CoV-2 RNA and viable virus were detected early, and prolonged RNA detection suggests the window for diagnosis is long. Hospitalized patients showed signs of worsening in the second week after illness onset.

title: Who is more susceptible to Covid-19 infection and mortality in the States?
abstract: A novel coronavirus was detected in Wuhan, China and reported to WHO on 31 December 2019. WHO declared a global pandemic on 11 March 2020. The first case in the US was reported in January 2020. Since mid-March 2020, the number of confirmed cases has increased exponentially in the States, with 1.1 million confirmed cases, and 57.4 thousand deaths as of 30 April 2020. Even though some believe that this new lethal coronavirus does not show any partiality to the rich, previous epidemiological studies find that the poor in the US are more susceptible to the epidemics due to their limited access to preventive measures and crowded living conditions. In this study, we postulate that the rich is more susceptible to Covid-19 infection during the early stage before social distancing measures have been introduced. This may be attributed to the higher mobility (both inter- and intra-city), given their higher tendency to travel for business/education, and to more social interactions. However, we postulate after the lockdown/social distancing has been imposed, the infection among the rich may be reduced due to better living conditions. Further, the rich may be able to afford better medical treatment once infected, hence a relatively lower mortality. In contrast, without proper medical insurance coverage, the poor may be prevented from receiving timely and proper medical treatment, hence a higher mortality.  We will collect the number of confirmed Covid-19 cases in the US during the period of Jan 2020 to Apr 2020 from Johns Hopkins University, also the number of Covid-19 tests in the US from the health departments across the States. County-level socio-economic status (SES) including age, sex, race/ethnicity, income, education, occupation, employment status, immigration status, and housing price, will be collected from the US Census Bureau. State/county-level health conditions including the prevalence of chronic diseases will be collected from the US CDC. State/county-level movement data including international and domestic flights will be collected from the US Bureau of Transportation Statistics. We will also collect the periods of lockdown/social distancing. Regression models are constructed to examine the relationship between SES, and Covid-19 infection and mortality at the state/county-level before and after lockdown/social distancing, while accounting for Covid-19 testing capacities and co-morbidities.  We expect that there is a positive correlation between Covid-19 infection and SES at the state/county-level in the US before social distancing. In addition, we expect a negative correlation between Covid-19 mortality and SES.

title: Coronavirus Disease (COVID-19) in Children: Indian Perspectives

title: [Standardized diagnosis and treatment of colorectal cancer during the outbreak of novel coronavirus pneumonia in Renji hospital].
abstract: Novel coronavirus pneumonia (NCP) is currently raging in China. It has been proven that NCP can be transmitted from human to human and cause hospital infection, which seriously threatens surgical staffs and inpatients. Although colorectal surgery is not a front-line subject in the fight against the epidemic, but in this special situation, now it is a difficult task that with the premise of how to maximize the protection for patients and their families, health of medical staff, and the safety of wards and hospitals, we can provide the highest quality medical services to ensure the orderly development of previous clinical work. Referring to the "Diagnosis and Treatment Scheme for NCP (Trial Version 4 and 5)" and combining the actual practice situation in our hospital with the "Summary of New Coronavirus Files of Shanghai Renji Hospital", we summarize how to carry out the clinical practice of colorectal surgery under the situation of the prevention and control of the NCP epidemiology, meanwhile under such situation aiming the procedure of diagnose and treatment for emergency patients with colorectal tumor, we share the experiences of the diagnosis of colorectal tumor, the management of patients with colorectal cancer who are scheduled to be admitted for surgery, the protection of wards, the perioperative management. More importantly, we introduce in detail the operative management and perioperative management of colorectal surgery patients suspected or diagnosed with new coronary pneumonia, including prevention and control measures for medical staff, operating rooms and surgical instruments. The main points are as follows: (1) Multidisciplinary team (MDT) must be run through the diagnosis and treatment of colorectal cancer. The members include not only routine departments, but also respiratory department and infectious department. (2) Colonoscopy examination may cause cross infection of NCP to patients and doctors. Therefore, it is prior to examine the emergency cases and life-threatening patients (bleeding, obstruction, gastrointestinal foreign bodies, etc.). If the emergent patients (intestinal obstruction) with suspected or confirmed NCP, the surgeons must perform emergency surgery, and intestinal decompressive tube through colonoscopy is not recommended. (3) The colorectal cancer patients with suspected or confirmed NCP should be placed in the isolated room with separate medical devices, and the operative room with negative pressure (under-5 Pa) must be separated. All disposable medical items, body fluids and feces of the patients in perioperative periods must be unified disposed according to the medical waste standard. (4) The surgical medical workers who process colorectal cancer patients with NCP must be protected by three-level. After operation, the medical workers must receive medical observation and be isolated for 14 days. We hope our "Renji experience" will be beneficial to colleagues.

title: Improved inference of time-varying reproduction numbers during infectious disease outbreaks
abstract: Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

title: P441 – P678

title: COVID-19 attack rate increases with city size
abstract: The current outbreak of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health and economic threat to interconnected human societies. Until a vaccine is developed, strategies for controlling the outbreak rely on aggressive social distancing. These measures largely disconnect the social network fabric of human societies, especially in urban areas. Here, we estimate the growth rates and reproductive numbers of COVID-19 in US cities from March 14th through March 19th to reveal a power-law scaling relationship to city population size. This means that COVID-19 is spreading faster on average in larger cities with the additional implication that, in an uncontrolled outbreak, larger fractions of the population are expected to become infected in more populous urban areas. We discuss the implications of these observations for controlling the COVID-19 outbreak, emphasizing the need to implement more aggressive distancing policies in larger cities while also preserving socioeconomic activity.

title: Genetic evolution analysis of 2019 novel coronavirus and coronavirus from other species
abstract: The Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a Public Health Emergency of International Concern. However, so far, there are still controversies about the source of the virus and its intermediate host. Here, we found the novel coronavirus was closely related to coronaviruses derived from five wild animals, including Paguma larvata, Paradoxurus hermaphroditus, Civet, Aselliscus stoliczkanus and Rhinolophus sinicus, and was in the same branch of the phylogenetic tree. However, genome and ORF1a homology show that the virus is not the same coronavirus as the coronavirus derived from these five animals, whereas the virus has the highest homology with Bat coronavirus isolate RaTG13.

title: Ascertainment rate of novel coronavirus disease (COVID-19) in Japan
abstract: To estimate the ascertainment rate of novel coronavirus (COVID-19).  We analyzed the epidemiological dataset of confirmed cases with COVID-19 in Japan as of 28 February 2020. A statistical model was constructed to describe the heterogeneity of reporting rate by age and severity. We estimated the number of severe and non-severe cases, accounting for under-ascertainment.  The ascertainment rate of non-severe cases was estimated at 0.44 (95% confidence interval: 0.37, 0.50), indicating that unbiased number of non-cases would be more than twice the reported count.  Severe cases are twice more likely diagnosed and reported than other cases. Considering that reported cases are usually dominated by non-severe cases, the adjusted total number of cases is also about a double of observed count. Our finding is critical in interpreting the reported data, and it is advised to interpret mild case data of COVID-19 as always under-ascertained.

title: Localising an asset-based COVID-19 response in Ecuador

title: Kidney impairment is associated with in-hospital death of COVID-19 patients
abstract: Information on kidney impairment in patients with coronavirus disease 2019 (COVID-19) is limited. This study aims to assess the prevalence and impact of abnormal urine analysis and kidney dysfunction in hospitalized COVID-19 patients in Wuhan.  We conducted a consecutive cohort study of COVID-19 patients admitted in a tertiary teaching hospital with 3 branches following a major outbreak in Wuhan in 2020. Hematuria, proteinuria, serum creatinine concentration and other clinical parameters were extracted from the electronic hospitalization databases and laboratory databases. Incidence rate for acute kidney injury (AKI) was examined during the study period. Association between kidney impairment and in-hospital death was analyzed.  We included 710 consecutive COVID19 patients, 89 (12.3%) of whom died in hospital. The median age of the patients was 63 years (inter quartile range, 51-71), including 374 men and 336 women. On admission, 44% of patients have proteinuria hematuria and 26.9% have hematuria, and the prevalence of elevated serum creatinine and blood urea nitrogen were 15.5% and 14.1% respectively. During the study period, AKI occurred in 3.2% patients. Kaplan-Meier analysis demonstrated that patients with kidney impairment have higher risk for in-hospital death. Cox proportional hazard regression confirmed that elevated serum creatinine, elevated urea nitrogen, AKI, proteinuria and hematuria was an independent risk factor for in-hospital death after adjusting for age, sex, disease severity, leukocyte count and lymphocyte count.  The prevalence of kidney impairment (hematuria, proteinuria and kidney dysfunction) in hospitalized COVID-19 patients was high. After adjustment for confounders, kidney impairment indicators were associated with higher risk of in-hospital death. Clinicians should increase their awareness of kidney impairment in hospitalized COVID-19 patients.

title: Translating COVID-19 Pandemic Surge Theory to Practice in the Emergency Department: How to Expand Structure
abstract: Multiple professional societies, nongovernment and government agencies have studied the science of sudden onset disaster mass casualty incidents to create and promote surge response guidelines. The COVID-19 pandemic has presented the health-care system with challenges that have limited science to guide the staff, stuff, and structure surge response.This study reviewed the available surge science literature specifically to guide an emergency department's surge structural response using a translational science approach to answer the question: How does the concept of sudden onset mass casualty incident surge capability apply to the process to expand COVID-19 pandemic surge structure response?The available surge structural science literature was reviewed to determine the application to a pandemic response. The on-line ahead of print and print COVID-19 scientific publications, as well as gray literature were studied to learn the best available COVID-19 surge structural response science. A checklist was created to guide the emergency department team's COVID-19 surge structural response.

title: Global coronavirus disease 2019: what has daily cumulative index taught us?
abstract: In addition to the absolute case number, a rapid increase in the number of COVID-19 cases within a short time was supposed to result in insufficiency of the healthcare system and further negatively affect patients’ outcomes. This study was conducted to investigate the association between the outcomes of COVID-19 patients and daily cumulative index (DCI), which was defined as the average daily number of new cases of COVID-19 and calculated by cumulative cases/number of days between the first reported case and March 6, 2020 by country. Spearman's rank correlation analyses were conducted to evaluate the relationship between mortality, incidence, and DCI. In this study, we found that DCI was positively correlated with incidence (adjusted risk ratio [aRR] = 1.01, 95% [confidence interval, CI] = 1.00-1.02, p < 0.01). Higher correlation between mortality and DCI (mortality rate: r = 0.397, p = 0.018; mortality per 1,000,000 people: r = 0.0.428, p = 0.004) was observed than disease incidence. DCI remained statistically associated with mortality per 1,000,000 people after adjustment of Health Care Index (aRR = 1.02, 95% CI = 1.01-1.03, p < 0.001) or Healthcare Access and Quality Index (aRR = 1.02, 95% CI = 1.01-1.04, p < 0.01. Reducing DCI through strict infection control measures can help slow the increasing number of COVID-19 cases and further improve outcome in COVID-19 patients.

title: Global analysis of daily new COVID-19 cases reveals many static-phase countries including US and UK potentially with unstoppable epidemics
abstract: The COVID-19 epidemics are differentially progressing in different countries. Here, comparative analyses of daily new cases reveal that 61 most affected countries can be classified into four types: downward (22), upward (20), static-phase (12) and uncertain ones (7). In particular, the 12 static-phase countries including US and UK are characterized by largely constant numbers of daily new cases in the past over 14 days. Furthermore, these static-phase countries are overall significantly lower in testing density but higher in the level of positive COVID-19 tests than downward countries. These findings suggest that the testing capacity in static-phase countries is lagging behind the spread of the outbreak, i.e., daily new cases (confirmed) are likely less than daily new infections and the remaining undocumented infections are thus still expanding, resulting in unstoppable epidemics. As such, increasing the testing capacity and/or reducing the COVID-19 transmission are urgently needed to stop the severing crisis in static-phase countries.

title: Epidemiology of Covid-19 in a Long-Term Care Facility in King County, Washington
abstract: Long-term care facilities are high-risk settings for severe outcomes from outbreaks of Covid-19, owing to both the advanced age and frequent chronic underlying health conditions of the residents and the movement of health care personnel among facilities in a region.  After identification on February 28, 2020, of a confirmed case of Covid-19 in a skilled nursing facility in King County, Washington, Public Health–Seattle and King County, aided by the Centers for Disease Control and Prevention, launched a case investigation, contact tracing, quarantine of exposed persons, isolation of confirmed and suspected cases, and on-site enhancement of infection prevention and control.  As of March 18, a total of 167 confirmed cases of Covid-19 affecting 101 residents, 50 health care personnel, and 16 visitors were found to be epidemiologically linked to the facility. Most cases among residents included respiratory illness consistent with Covid-19; however, in 7 residents no symptoms were documented. Hospitalization rates for facility residents, visitors, and staff were 54.5%, 50.0%, and 6.0%, respectively. The case fatality rate for residents was 33.7% (34 of 101). As of March 18, a total of 30 long-term care facilities with at least one confirmed case of Covid-19 had been identified in King County.  In the context of rapidly escalating Covid-19 outbreaks, proactive steps by long-term care facilities to identify and exclude potentially infected staff and visitors, actively monitor for potentially infected patients, and implement appropriate infection prevention and control measures are needed to prevent the introduction of Covid-19.

title: CT in relation to RT-PCR in diagnosing COVID-19 in the Netherlands: a prospective study
abstract: Early differentiation between emergency department (ED) patients with and without corona virus disease (COVID-19) is very important. Chest CT scan may be helpful in early diagnosing of COVID-19. We investigated the diagnostic accuracy of CT using RT-PCR for SARS-CoV-2 as reference standard and investigated reasons for discordant results between the two tests.  In this prospective single centre study in the Netherlands, all adult symptomatic ED patients had both a CT scan and a PCR upon arrival at the ED. CT results were compared with PCR test(s). Diagnostic accuracy was calculated. Discordant results were investigated using discharge diagnoses.  Between March 13th and March 24th 2020, 193 symptomatic ED patients were included. In total, 43.0% of patients had a positive PCR and 56.5% a positive CT, resulting in a sensitivity of 89.2%, specificity 68.2%, likelihoodratio (LR) + 2.81 and LR- 0.16. Sensitivity was higher in patients with high risk pneumonia (CURB-65 score ≥3; n=17, 100%) and with sepsis (SOFA score ≥2; n=137, 95.5%). Of the 35 patients (31.8%) with a suspicious CT and a negative PCR, 9 had another respiratory viral pathogen, and in 7 patients, COVID-19 was considered likely. One of nine patients with a non-suspicious CT and a positive PCR had developed symptoms within 48 hours before scanning.  The accuracy of chest CT in symptomatic ED patients is high, but used as a single diagnostic test, CT can not safely diagnose or exclude COVID-19. However, CT can be used as a quick first screening tool.

title: Covid-19: Africa's case numbers are rising rapidly, WHO warns.

title: Geographic Differences in COVID-19 Cases, Deaths, and Incidence - United States, February 12-April 7, 2020
abstract: Community transmission of coronavirus disease 2019 (COVID-19) was first detected in the United States in February 2020. By mid-March, all 50 states, the District of Columbia (DC), New York City (NYC), and four U.S. territories had reported cases of COVID-19. This report describes the geographic distribution of laboratory-confirmed COVID-19 cases and related deaths reported by each U.S. state, each territory and freely associated state,* DC, and NYC during February 12-April 7, 2020, and estimates cumulative incidence for each jurisdiction. In addition, it projects the jurisdiction-level trajectory of this pandemic by estimating case doubling times on April 7 and changes in cumulative incidence during the most recent 7-day period (March 31-April 7). As of April 7, 2020, a total of 395,926 cases of COVID-19, including 12,757 related deaths, were reported in the United States. Cumulative COVID-19 incidence varied substantially by jurisdiction, ranging from 20.6 cases per 100,000 in Minnesota to 915.3 in NYC. On April 7, national case doubling time was approximately 6.5 days, although this ranged from 5.5 to 8.0 days in the 10 jurisdictions reporting the most cases. Absolute change in cumulative incidence during March 31-April 7 also varied widely, ranging from an increase of 8.3 cases per 100,000 in Minnesota to 418.0 in NYC. Geographic differences in numbers of COVID-19 cases and deaths, cumulative incidence, and changes in incidence likely reflect a combination of jurisdiction-specific epidemiologic and population-level factors, including 1) the timing of COVID-19 introductions; 2) population density; 3) age distribution and prevalence of underlying medical conditions among COVID-19 patients (1-3); 4) the timing and extent of community mitigation measures; 5) diagnostic testing capacity; and 6) public health reporting practices. Monitoring jurisdiction-level numbers of COVID-19 cases, deaths, and changes in incidence is critical for understanding community risk and making decisions about community mitigation, including social distancing, and strategic health care resource allocation.

title: Hazardous Postoperative Outcomes of Unexpected COVID-19 Infected Patients: A Call for Global Consideration of Sampling all Asymptomatic Patients Before Surgical Treatment
abstract: In December 2019, a novel coronavirus was identified as the cause of many pneumonia cases in China and eventually declared as a pandemic as the virus spread globally. Few reports were published on the outcome of surgical procedures in diagnosed COVID-19 patients and even fewer on the surgical outcomes of asymptomatic undiagnosed COVID-19 surgical patients. We aimed to review all published data regarding surgical outcomes of preoperatively asymptomatic untested coronavirus disease 2019 (COVID-19) patients.  This report is a review on the perioperative period in COVID-19 patients who were preoperatively asymptomatic and not tested for COVID-19. Searches were conducted in PubMed April 4th, 2020. All publications, of any design, were considered for inclusion.  Four reports were identified through our literature search, comprising 64 COVID-19 carriers, of them 51 were diagnosed only in the postoperative period. Synthesis of these reports, concerning the postoperative outcomes of patients diagnosed with COVID-19 during the perioperative period, suggested a 14/51 (27.5%) postoperative mortality rate and severe mostly pulmonic complications, as well as medical staff exposure and transmission.  COVID-19 may have potential hazardous implications on the perioperative course. Our review presents results of unacceptable mortality rate and a high rate of severe complications. These observations warrant further well-designed studies, yet we believe it is time for a global consideration of sampling all asymptomatic patients before surgical treatment.

title: Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study
abstract: The coronavirus disease (COVID-19) is the latest pandemic of the digital age. With the internet harvesting large amounts of data from the general population in real time, public databases such as Google Trends (GT) and the Baidu Index (BI) can be an expedient tool to assist public health efforts.  The aim of this study is to apply digital epidemiology to the current COVID-19 pandemic to determine the utility of providing adjunctive epidemiologic information on outbreaks of this disease and evaluate this methodology in the case of future pandemics.  An epidemiologic time series analysis of online search trends relating to the COVID-19 pandemic was performed from January 9, 2020, to April 6, 2020. BI was used to obtain online search data for China, while GT was used for worldwide data, the countries of Italy and Spain, and the US states of New York and Washington. These data were compared to real-world confirmed cases and deaths of COVID-19. Chronologic patterns were assessed in relation to disease patterns, significant events, and media reports.  Worldwide search terms for shortness of breath, anosmia, dysgeusia and ageusia, headache, chest pain, and sneezing had strong correlations (r>0.60, P<.001) to both new daily confirmed cases and deaths from COVID-19. GT COVID-19 (search term) and GT coronavirus (virus) searches predated real-world confirmed cases by 12 days (r=0.85, SD 0.10 and r=0.76, SD 0.09, respectively, P<.001). Searches for symptoms of diarrhea, fever, shortness of breath, cough, nasal obstruction, and rhinorrhea all had a negative lag greater than 1 week compared to new daily cases, while searches for anosmia and dysgeusia peaked worldwide and in China with positive lags of 5 days and 6 weeks, respectively, corresponding with widespread media coverage of these symptoms in COVID-19.  This study demonstrates the utility of digital epidemiology in providing helpful surveillance data of disease outbreaks like COVID-19. Although certain online search trends for this disease were influenced by media coverage, many search terms reflected clinical manifestations of the disease and showed strong correlations with real-world cases and deaths.

title: Pangolin homology associated with 2019-nCoV
abstract: To explore potential intermediate host of a novel coronavirus is vital to rapidly control continuous COVID-19 spread. We found genomic and evolutionary evidences of the occurrence of 2019-nCoV-like coronavirus (named as Pangolin-CoV) from dead Malayan Pangolins. Pangolin-CoV is 91.02% and 90.55% identical at the whole genome level to 2019-nCoV and BatCoV RaTG13, respectively. Pangolin-CoV is the lowest common ancestor of 2019-nCoV and RaTG13. The S1 protein of Pangolin-CoV is much more closely related to 2019-nCoV than RaTG13. Five key amino-acid residues involved in the interaction with human ACE2 are completely consistent between Pangolin-CoV and 2019-nCoV but four amino-acid mutations occur in RaTG13. It indicates Pangolin-CoV has similar pathogenic potential to 2019-nCoV, and would be helpful to trace the origin and probable intermediate host of 2019-nCoV.

title: Estimating cases of COVID-19 from Daily Death Data in Italy
abstract: COVID-19 is an emerging infectious disease which has been declared a pan- demic by the World Health Organisation. Due to limited testing capacity for this new virus, variable symptomatology the majority of infected showing non-specific mild or no symptoms it is likely current prevalence data is an underestimate.  We present an estimate of the number of cases of COVID-19 com- pared to the number of confirmed case in Italy based on the daily reported deaths and information about the incubation period, time from symptom on- set to death and reported case fatality rate.  Our model predicts that on the 31st of January 2020 when the first 3 infected cases had been identified by Italian authorise there were already nearly 30 cases in Italy, and by the 24th of February 2020 only 0.5% cases had been detected and confirmed by Italian authorities. While official statistics had 132 confirmed case we believe a more accurate estimate would be closer to 26000. With a case-doubling period of about 2.5 days.

title: Stochastic discrete epidemic modeling of COVID-19 transmission in the Province of Shaanxi incorporating public health intervention and case importation
abstract: Before the lock-down of Wuhan/Hubei/China, on January 23rd 2020, a large number of individuals infected by COVID-19 moved from the epicenter Wuhan and the Hubei province due to the Spring Festival, resulting in an epidemic in the other provinces including the Shaanxi province. The epidemic scale in Shaanxi was comparatively small and with half of cases being imported from the epicenter. Based on the complete epidemic data including the symptom onset time and transmission chains, we calculate the control reproduction number (1.48-1.69) in Xian. We could also compute the time transition, for each imported or local case, from the latent, to infected, to hospitalized compartment, as well as the effective reproduction number. This calculation enables us to revise our early deterministic transmission model to a stochastic discrete epidemic model with case importation and parameterize it. Our model-based analyses reveal that the newly generated infections decay to zero quickly; the cumulative number of case-driven quarantined individuals via contact tracing stabilize at a manageable level, indicating that the intervention strategies implemented in the Shaanxi province have been effective. Risk analyses, important for the consideration of resumption of work, show that a large second outbreak is expected if the level of case importation remains at the same level as between January 10th and February 4th 2020. However, if the case importation decreases by 30%, 60% and 90%, the second outbreak if happening will be of small-scale assuming contact tracing and quarantine/isolation remain as effective as before. Finally, we consider the effects of intermittent inflow with a Poisson distribution on the likelihood of multiple outbreaks. We believe the developed methodology and stochastic model provide an important model framework for the evaluation of revising travel restriction rules in the consideration of resuming social-economic activities while managing the disease control with potential case importation.

title: Efficacy of remdesivir versus placebo for the treatment of COVID-19: A protocol for systematic review and meta-analysis of randomized controlled trials
abstract: In spite of the global containment on prevention efforts, the spread of coronavirus disease 2019 (COVID-19) is continuing to rise, with 1.1 million confirmed cases and 60,124 deaths recorded worldwide since 04 April 2020. The outbreak has a significant threat to international health and economy. At present, there is no approved vaccine or treatment for the disease, while efforts are underway. Remdesivir, a nucleotide-analogue antiviral drug developed for Ebola, is determined to prevent and stop infections with COVID-19, while results are yet controversial. Here, we aim to conduct a systematic review and meta-analysis of randomized controlled trials to compare the effectiveness of remdesivir and placebo in patients with COVID-19.  We will search MEDLINE-PubMed, Embase, Cochrane Library, ClinicalTrials.gov, and Google scholar databases without restriction in year of publication. We will include randomized controlled trials that assessed the effectiveness of remdesivir versus placebo for patients confirmed with COVID-19. We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA 2015) guidelines for the design and reporting of the results. The primary endpoint will be time to clinical recovery. The secondary endpoints will be all cause mortality, discharged date, frequency of respiratory progression, and treatment-emergent adverse events. Two independent authors will perform study selection, data extraction, and methodology quality assessment. RevMan 5.3 software will be used for statistical analysis. Random/fixed effect model will be carried out to calculate mean differences for continuous outcomes and risk ratio for dichotomous outcomes between remdesivir and placebo. Ethics and dissemination: This study does not require ethical approval, because no participants data will be involved in this systematic review and meta-analysis. The findings of this study will be published in reputable and peer-reviewed journal.  This review protocol is submitted in PROSPERO database for registration and we will include the registration number in the revised version of the manuscript.  2019 novel coronavirus, 2019-nCoV, Coronavirus diseases 2019, COVID-19, SARS-cov-2, Remdesivir, Randomized Controlled Trials. Systematic review, Meta-analysis,

title: Side by side comparison of three fully automated SARS-CoV-2 antibody assays with a focus on specificity
abstract: In the context of the COVID-19 pandemic, numerous new serological test systems for the detection of anti-SARS-CoV-2 antibodies have become available quickly. However, the clinical performance of many of them is still insufficiently described. Therefore we compared three commercial, CE-marked, SARS-CoV-2 antibody assays side by side.  We included a total of 1,154 specimens from pre-COVID-19 times and 65 samples from COVID-19 patients ([≥]14 days after symptom onset) to evaluate the test performance of SARS-CoV-2 serological assays by Abbott, Roche, and DiaSorin.  All three assays presented with high specificities: 99.2% (98.6-99.7) for Abbott, 99.7% (99.2-100.0) for Roche, and 98.3% (97.3-98.9) for DiaSorin. In contrast to the manufacturers' specifications, sensitivities only ranged from 83.1% to 89.2%. Although the three methods were in good agreement (Cohen's Kappa 0.71-0.87), McNemar's test revealed significant differences between results obtained from Roche and DiaSorin. However, at low seroprevalences, the minor differences in specificity resulted in profound discrepancies of positive predictability at 1% seroprevalence: 52.3% (36.2-67.9), 77.6% (52.8-91.5), and 32.6% (23.6-43.1) for Roche, Abbott, and DiaSorin, respectively.  We find diagnostically relevant differences in specificities for the anti-SARS-CoV-2 antibody assays by Abbott, Roche, and DiaSorin that have a significant impact on the positive predictability of these tests.

title: Availability of Internationally Controlled Essential Medicines in the COVID-19 Pandemic
abstract: Section 2 of the 2019 World Health Organization (WHO) Model List of Essential Medicines includes opioid analgesics formulations commonly used for the control of pain and respiratory distress, as well as sedative and anxiolytic substances such as midazolam and diazepam. These medicines, essential to palliative care, are regulated under the international drug control conventions overseen by United Nations (UN) specialized agencies and treaty bodies and under national drug control laws. Those national laws and regulations directly affect bedside availability of Internationally Controlled Essential Medicines (ICEMs). The complex interaction between national regulatory systems and global supply chains (now impacted by COVID-19 pandemic) directly affects bedside availability of ICEMs and patient care. Despite decades of global civil society advocacy in the UN system, ICEMs have remained chronically unavailable, inaccessible and unaffordable in Lower-and-Middle Income Countries, and there are recent reports of shortages in High Income Countries as well. The most prevalent symptoms in COVID-19 are breathlessness, cough, drowsiness, anxiety, agitation and delirium. Frequently used medicines include opioids such as morphine or fentanyl and midazolam, all of them listed as ICEMs. This paper describes the issues related to the lack of availability and limited access to ICEMs during the COVID-19 pandemic in both intensive and palliative care patients in countries of all income levels and makes recommendations for improving access.

title: Genome-Wide Analysis of Protein-Protein Interactions and Involvement of Viral Proteins in SARS-CoV Replication
abstract: Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV) and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp) 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12) provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.

title: Measuring Icebergs: Using Different Methods to Estimate the Number of COVID-19 Cases in Portugal and Spain
abstract: The world is suffering from a pandemic called COVID-19, caused by the SARS-CoV-2 virus. The different national governments have problems evaluating the reach of the epidemic, having limited resources and tests at their disposal. Hence, any means to evaluate the number of persons with symptoms compatible with COVID-19 with reasonable level of accuracy is useful. In this paper we present the initial results of the @CoronaSurveys project. The objective of this project is the collection and publication of data concerning the number of people that show symptoms compatible with COVID-19 in different countries using open anonymous surveys. While this data may be biased, we conjecture that it is still useful to estimate the number of infected persons with the COVID-19 virus at a given point in time in these countries, and the evolution of this number over time. We show here the initial results of the @CoronaSurveys project in Spain and Portugal.

title: Malaria from hyperendemicity to elimination in Hekou County on China–Vietnam border: an ecological study
abstract: Malaria control and elimination are challenged by diversity and complexity of the determinants on the international border in the Great Mekong Sub-region. Hekou, a Chinese county on the China–Vietnam border, was used to document Chinese experiences and lessons for malaria control and elimination.  The design was an ecological study. Malaria burden before 1951 and procedures of 64 years (1952–2015) from malaria hyperendemicity to elimination are described. Single and bilinear regression analysis was utilized to analyse the relationship between the annual malaria incidence (AMI) and gross domestic product (GDP), urbanization rate, and banana planting area (BPA).  There was a huge malaria burden before 1951. AMI was reduced from 358.62 per 1000 person-years in 1953 to 5.69 per 1000 person-years in 1960. A system of primary health services, comprising three levels of county township hospitals and village health stations maintained malaria control and surveillance activities in changing political and social-economic settings. However, potential under-reported of malaria and market-oriented healthcare led to a malaria epidemic in 1987. Strong political commitment reoriented malaria from a control to an elimination programme. High coverage of malaria intervention and population access to intervention was crucial for malaria control and elimination; meanwhile, AMI was closely associated with socio-economic development, correlation coefficients (R) −0.6845 (95% CI −0.7978, −0.6845) for national GDP, −0.7014 (−0.8093, −0.7014) for national urbanization rate and −0.5563 (−0.7147, −0.3437) for BPA.  Multifactor, including political commitment, effective interventions, social and economic development and changing ecological environment, and the complicated interactions between these factors contribute to malaria elimination in Hekou County.  The online version of this article (doi:10.1186/s12936-017-1709-z) contains supplementary material, which is available to authorized users.

title: Bridging a false dichotomy in the COVID-19 response: a public health approach to the ‘lockdown’ debate

title: COVID-19 pandemic in the African continent: forecasts of cumulative cases, new infections, and mortality
abstract: Africa is the last major region to capitulate to the SARS-CoV-2 (COVID-19) pandemic. The first confirmed COVID-19 case in the region was reported on February 14, but what lies ahead in terms of the course and magnitude of infection remains speculative. To the best of our knowledge, no study, using a robust methodology, provides the immediate and long-term trajectory of COVID-19 for the entire region or accounts for its local context. This paper is the first systematic attempt to provide estimates on how many people would contract the virus and how many would die in the coming few months across Africa.  The forecasts on caseloads and incidences are from a co-variate-based instrumental variable regression model. Fatality rates from Italy and China were further applied to generate mortality estimates after adjustments were made for differences in age-structure, health service quality, and living standards between each of the African countries and those of the reference population. We cover all countries that reported a confirmed case as of March 31, 2020.  By the end of June, 16,283,085 people will contract COVID-19 (95% CI 718,403 to 98, 358, 799). With a cumulative caseload of 5,413,4517 (95% CI 1,332,953 to 8,489,940) and 906,625 (95% CI 173, 821 to 4,742,917) Northern and Eastern Africa will respectively be the most and least affected sub-regions in the continent. Cumulative COVID-19 cases on June 30, 2020 are expected to reach 2,912, 864 (95% CI 465,028 to 18,286,358) in Southern Africa, 2,787, 913 (95% CI 517, 489 to 15,056,314) in Western Africa, and 1,185,742 (95% CI 229, 111 to 6,138,692) in Central Africa. New infections (incidence) for the month of April are expected to be the highest in Djibouti, 32.8 per 1000 (95% CI 6.25 to 171.77), while Morocco 1045 (95% CI 167 to 6,547) will register the highest number of deaths.  Our study shows that countries that are least urbanized and have a low level of socio-economic development, hence least connected to the outside world, are likely to register lower and slower transmissions, at least at the early stage of the epidemic. However, the same set of enabling factors that worked for their benefit are likely to go against them in implementing interventions that have lessened the impact of the disease elsewhere.

title: Incidence of novel coronavirus (2019-nCoV) infection among people under home quarantine in Shenzhen, China
abstract: Since the outbreak of 2019-nCoV in December, Chinese government has implemented various measures including travel bans, centralized treatments, and home quarantines to slowing the transmission across the country. In this study, we aimed to estimate the incidence of 2019-nCoV infection among people under home quarantine in Shenzhen, China.  We used a stratified multistage random sampling method to recruit participants and collected demographic information and laboratory results of people under home quarantine. We conducted descriptive analysis to estimate the basic characteristics and to calculate the incidence in out study population.  A total of 2004 people under home quarantine participated in this study, of which 1637 participants finished the questionnaire with a response rate of 81.7%. Mean age of the participants was 33.7 years, ranging from 0.3 to 80.2 years. Of people who provided clear travel history, 129 people have traveled to Wuhan city and 1,046 people have traveled to other cities in Hubei province within 14 days before the home quarantine. Few (less than 1%) participants reported contact history with confirmed or suspected cases during their trip and most of these arrived at Shenzhen between Jan 24, 2020 to Jan 27, 2020. The incidence of COVID-19 in the sample was 1.5 (95% CI: 0.31-4.37).  Home quarantine has been effective in preventing the early transmission of COVID-19, but that more needs to be done to improve early detection of COVID-19 infection.

title: Management of the Clinical and Academic Mission in an Urban Otolaryngology Department During the COVID-19 Global Crisis
abstract: The objective of this study was to assess the strategic changes implemented in the departmental mission to continue safe delivery of otolaryngology care and to support the broader institutional mission during the COVID-19 pandemic response.  Retrospective assessment was performed to the response and management strategy developed to transform the clinical and academic enterprise.  Large urban tertiary care referral center.  The departmental structure was reorganized along new clinical teams to effectively meet the system directives for provision of otolaryngology care and support for inpatient cases of COVID-19. A surge deployment schedule was developed to assist frontline colleagues with clinical support as needed. Outpatient otolaryngology was consolidated across the system with conversion of the majority of visits to telehealth. Operative procedures were prioritized to ensure throughput for emergent and time-critical urgent procedures. A tracheostomy protocol was developed to guide management of emergent and elective airways. Educational and research efforts were redirected to focus on otolaryngology care in the clinical context of the COVID-19 crisis.  Emergence of the COVID-19 global health crisis has challenged delivery of otolaryngology care in an unparalleled manner. The concerns for preserving health of the workforce while ethically addressing patient career needs in a timely manner has created significant dilemmas. A proactive, thoughtful approach that reorganizes the overall departmental effort through provider and staff engagement can facilitate the ability to meet the needs of otolaryngology patients and to support the greater institutional mission to combat the pandemic.

title: Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases
abstract: The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.

title: COVID-19 (Novel Coronavirus 2019) - recent trends.
abstract: The World Health Organization (WHO) has issued a warning that, although the 2019 novel coronavirus (COVID-19) from Wuhan City (China), is not pandemic, it should be contained to prevent the global spread. The COVID-19 virus was known earlier as 2019-nCoV. As of 12 February 2020, WHO reported 45,171 cases and 1115 deaths related to COVID-19. COVID-19 is similar to Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) virus in its pathogenicity, clinical spectrum, and epidemiology. Comparison of the genome sequences of COVID-19, SARS-CoV, and Middle East Respiratory Syndrome coronavirus (MERS-CoV) showed that COVID-19 has a better sequence identity with SARS-CoV compared to MERS CoV. However, the amino acid sequence of COVID-19 differs from other coronaviruses specifically in the regions of 1ab polyprotein and surface glycoprotein or S-protein. Although several animals have been speculated to be a reservoir for COVID-19, no animal reservoir has been already confirmed. COVID-19 causes COVID-19 disease that has similar symptoms as SARS-CoV. Studies suggest that the human receptor for COVID-19 may be angiotensin-converting enzyme 2 (ACE2) receptor similar to that of SARS-CoV. The nucleocapsid (N) protein of COVID-19 has nearly 90% amino acid sequence identity with SARS-CoV. The N protein antibodies of SARS-CoV may cross react with COVID-19 but may not provide cross-immunity. In a similar fashion to SARS-CoV, the N protein of COVID-19 may play an important role in suppressing the RNA interference (RNAi) to overcome the host defense. This mini-review aims at investigating the most recent trend of COVID-19.

title: A Review of Salivary Diagnostics and Its Potential Implication in Detection of Covid-19
abstract: Saliva is an exocrine secretion produced from the salivary glands and has numerous functions, such as cleansing and protection of the oral cavity, antimicrobial effects and aids in digestion. Due to the speedy development in the field of salivaomics, saliva is now well accepted as a pool of biological markers that vary from changes in biochemicals, nucleic acids and proteins to the microflora. Saliva has an immense potential as a diagnostic fluid and offers an edge over other biological fluids as its collection method does not require invasive procedure, economical and is useful for monitoring systemic health. Development of sensitive and precise salivary diagnostic tools and the formulation of defined guidelines following meticulous testing will allow salivary diagnostics to be utilised as chair side tests for various oral and systemic diseases in the near future. The coronavirus disease (Covid-19) pandemic is the biggest challenge and global health crisis for the world since World War Two. Rapid and accurate diagnosis of Covid-19 is crucial in controlling the outbreak in the community and in hospitals. Nasopharyngeal and oropharyngeal swabs are the recommended specimen types for Covid-19 diagnostic testing. The collection of these specimen types requires close contact between healthcare workers and patients and poses a risk of transmission of the virus, causes discomfort and may cause bleeding, especially in patients with condition such as thrombocytopenia. Hence, nasopharyngeal or oropharyngeal swabs are not desirable for sequential monitoring of viral load. Saliva specimens can be obtained easily as the patient is asked to spit into a sterile bottle. The collection of saliva is non-invasive and greatly minimizes the exposure of healthcare workers to Covid-19. Saliva has a high consistency rate of greater than 90% with nasopharyngeal specimens in the detection of respiratory viruses, including coronaviruses. Saliva has also been used in screening respiratory viruses among hospitalized patients without pyrexia or respiratory symptoms. SARS-CoV can be detected in saliva at high titers. Salivary diagnostics is a dynamic field that is being incorporated as part of disease diagnosis, clinical monitoring of systemic health and to make significant clinical decisions for patient care. More research is required to analyze the potential diagnostic of Covid-19 in saliva to develop rapid chair side tests for the detection of Covid-19 and it is also pivotal to improve and develop successful strategies for prevention, especially for dentists and healthcare professionals who are involved in performing aerosol-generating procedures.

title: Analysis of SARS-CoV-2 Antibodies in COVID-19 Convalescent Plasma using a Coronavirus Antigen Microarray
abstract: The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates complete discrimination of these two groups. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes.

title: Estimation of COVID-19 prevalence in Italy, Spain, and France
abstract: At the end of December 2019, coronavirus disease 2019 (COVID-19) appeared in Wuhan city, China. As of April 15, 2020, >1.9 million COVID-19 cases were confirmed worldwide, including >120,000 deaths. There is an urgent need to monitor and predict COVID-19 prevalence to control this spread more effectively. Time series models are significant in predicting the impact of the COVID-19 outbreak and taking the necessary measures to respond to this crisis. In this study, Auto-Regressive Integrated Moving Average (ARIMA) models were developed to predict the epidemiological trend of COVID-19 prevalence of Italy, Spain, and France, the most affected countries of Europe. The daily prevalence data of COVID-19 from 21 February 2020 to 15 April 2020 were collected from the WHO website. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (0,2,1), ARIMA (1,2,0), and ARIMA (0,2,1) models with the lowest MAPE values (4.7520, 5.8486, and 5.6335) were selected as the best models for Italy, Spain, and France, respectively. This study shows that ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. The results of the analysis can shed light on understanding the trends of the outbreak and give an idea of the epidemiological stage of these regions. Besides, the prediction of COVID-19 prevalence trends of Italy, Spain, and France can help take precautions and policy formulation for this epidemic in other countries.

title: Serial interval in determining the estimation of reproduction number of the novel coronavirus disease (COVID-19) during the early outbreak

title: Coronavirus threat to Indian population: risk factors, transmission dynamics and preparedness to prevent the spread of the virus
abstract: Recent novel coronavirus outbreak in Wuhan City of Hubei province in China infected nearly 70,000 individuals and killed more than 1700 people within a short span of time leading to global pandemic. The disease is now spread to 26 countries in Asia, North America, Europe and Australasia. The virus is spreading rapidly to Asia-pacific and Southeast Asian countries. The disease is posing a serious threat to human population and has devastating impact on public health and economy. So far 3 Indians are infected and India is at risk of rapid spread of the disease because of its geographical location and other favorable conditions. With a poorer global health security index compared to China (India-57 and China-51), any such situation will have worse outcome. In near future there are also possibilities of similar kind of disease outbreak caused by new strains of coronaviruses due to factors like species jump of new viruses, high population density and inadequate medical facilities. In this short review we have highlighted the risk factors and transmission dynamics of coronaviruses that may pose a serious threat to India. We have also discussed about the possible preventive measure our country should take to control any such outbreak situation.

title: Structural, glycosylation and antigenic variation between 2019 novel coronavirus (2019-nCoV) and SARS coronavirus (SARS-CoV)
abstract: The emergence of 2019 novel coronavirus (2019-nCoV) is of global concern and might have emerged from RNA recombination among existing coronaviruses. CoV spike (S) protein which is crucial for receptor binding, membrane fusion via conformational changes, internalization of the virus, host tissue tropism and comprises crucial targets for vaccine development, remain largely uncharacterized. Therefore, the present study has been planned to determine the sequence variation, structural and antigenic divergence of S glycoprotein which may be helpful for the management of 2019-nCoV infection. The sequences of spike glycoprotein of 2019-nCoV and SARS coronavirus (SARS-CoV) were used for the comparison. The sequence variations were determined using EMBOSS Needle pairwise sequence alignment tools. The variation in glycosylation sites was predicted by NetNGlyc 1.0 and validated by N-GlyDE server. Antigenicity was predicted by NetCTL 1.2 and validated by IEDB Analysis Resource server. The structural divergence was determined by using SuperPose Version 1.0 based on cryo-EM structure of the SARS coronavirus spike glycoprotein. Our data suggests that 2019-nCoV is newly spilled coronavirus into humans in China is closely related to SARS-CoV, which has only 12.8% of difference with SARS-CoV in S protein and has 83.9% similarity in minimal receptor-binding domain with SARS-CoV. Addition of a novel glycosylation sites were observed in 2019-nCoV. In addition, antigenic analysis proposes that great antigenic differences exist between both the viral strains, but some of the epitopes were found to be similar between both the S proteins. In spite of the variation in S protein amino acid composition, we found no significant difference in their structures. Collectively, for the first time our results exhibit the emergence of human 2019-nCoV is closely related to predecessor SARS-CoV and provide the evidence that 2019-nCoV uses various novel glycosylation sites as SARS-CoV and may have a potential to become pandemic owing its antigenic discrepancy. Further, demonstration of novel Cytotoxic T lymphocyte epitopes may impart opportunities for the development of peptide based vaccine for the prevention of 2019-nCoV.

title: Current status and progress of 2019 novel coronavirus pneumonia/ 中华危重病急救医学
abstract: Recently, the 2019 novel coronavirus (2019-nCoV) pneumonia outbroke in Wuhan and rapidly spread to all over China and even the world. Because of the strong infectivity and various clinical symptoms, it has brought certain difficulties to the epidemic prevention and control. Currently there is no specific drug for 2019-nCoV. Previous drugs used to treat other coronaviruses may be effective, but further clinical trials remain needed. We reviewed literature on the epidemiology, etiology, clinical manifestations, imaging manifestations, laboratory examination, diagnosis, complications, treatment and outcome of 2019-nCoV pneumonia.

title: Flattening the curve before it flattens us: hospital critical care capacity limits and mortality from novel coronavirus (SARS-CoV2) cases in US counties
abstract: As of March 26, 2020, the United States had the highest number of confirmed cases of Novel Coronavirus (COVID-19) of any country in the world. Hospital critical care is perhaps the most important medical system choke point in terms of preventing deaths in a disaster scenario such as the current COVID-19 pandemic. We therefore brought together previously established disease modeling estimates of the growth of the COVID-19 epidemic in the US under various social distancing contact reduction assumptions, with local estimates of the potential critical care surge response across all US counties.  Estimates of spatio-temporal COVID-19 demand and medical system critical care supply were calculated for all continental US counties. These estimates were statistically summarized and mapped for US counties, regions and urban versus non-urban areas. Estimates of COVID-19 infections and patients needing critical care were calculated from March 24, 2020 to April 24, 2020 for three different estimated population levels - 0%, 25%, and 50% - of contact reduction (through actions such as social distancing). Multiple national public and private datasets were linked and harmonized in order to calculate county-level critical care bed counts that included currently available beds and those that could be made available under four surge response scenarios - very low, low, medium, and high - as well as excess deaths stemming from inaccessible critical care.  Surge response scenarios ranged from a very low total supply 77,588 critical care beds to a high total of 278,850 critical care beds. Over the four week study period, excess deaths from inaccessible critical care ranged from 24,688 in the very low response scenario to 13,268 in the high response scenario. Northeastern and urban counties were projected to be most affected by excess deaths due to critical care shortages, and counties in New York, Colorado, and Virginia were projected to exceed their critical care bed limits despite high levels of COVID-19 contact reduction. Over the four week study period, an estimated 12,203-19,594 excess deaths stemming from inaccessible critical care could be averted through greater preventive actions such as travel restrictions, publicly imposed contact precautions, greater availability of rapid testing for COVID-19, social distancing, self-isolation when sick, and similar interventions. An estimated 4,029-11,420 excess deaths stemming from inaccessible critical care could be averted through aggressive critical care surge response and preparations, including high clearance of ICU and non-ICU critical care beds and extraordinary measures like using a single ventilator for multiple patients.  Unless the epidemic curve of COVID-19 cases is flattened over an extended period of time, the US COVID-19 epidemic will cause a shortage of critical care beds and drive up otherwise preventable deaths. The findings here support value of preventive actions to flatten the epidemic curve, as well as the value of exercising extraordinary surge capacity measures to increase access to hospital critical care for severely ill COVID-19 patients.

title: Portable chest X-ray in coronavirus disease-19 (COVID-19): A pictorial review
abstract: As the global pandemic of coronavirus disease-19 (COVID-19) progresses, many physicians in a wide variety of specialties continue to play pivotal roles in diagnosis and management. In radiology, much of the literature to date has focused on chest CT manifestations of COVID-19 (Zhou et al. ; Chung et al. ). However, due to infection control issues related to patient transport to CT suites, the inefficiencies introduced in CT room decontamination, and lack of CT availability in parts of the world, portable chest radiography (CXR) will likely be the most commonly utilized modality for identification and follow up of lung abnormalities. In fact, the American College of Radiology (ACR) notes that CT decontamination required after scanning COVID-19 patients may disrupt radiological service availability and suggests that portable chest radiography may be considered to minimize the risk of cross-infection (American College of Radiology ). Furthermore, in cases of high clinical suspicion for COVID-19, a positive CXR may obviate the need for CT. Additionally, CXR utilization for early disease detection may also play a vital role in areas around the world with limited access to reliable real-time reverse transcription polymerase chain reaction (RT-PCR) COVID testing. The purpose of this pictorial review article is to describe the most common manifestations and patterns of lung abnormality on CXR in COVID-19 in order to equip the medical community in its efforts to combat this pandemic.

title: Partially latent class models for case–control studies of childhood pneumonia aetiology
abstract: In population studies on the aetiology of disease, one goal is the estimation of the fraction of cases that are attributable to each of several causes. For example, pneumonia is a clinical diagnosis of lung infection that may be caused by viral, bacterial, fungal or other pathogens. The study of pneumonia aetiology is challenging because directly sampling from the lung to identify the aetiologic pathogen is not standard clinical practice in most settings. Instead, measurements from multiple peripheral specimens are made. The paper introduces the statistical methodology designed for estimating the population aetiology distribution and the individual aetiology probabilities in the Pneumonia Etiology Research for Child Health study of 9500 children for seven sites around the world. We formulate the scientific problem in statistical terms as estimating the mixing weights and latent class indicators under a partially latent class model (PLCM) that combines heterogeneous measurements with different error rates obtained from a case–control study. We introduce the PLCM as an extension of the latent class model. We also introduce graphical displays of the population data and inferred latent class frequencies. The methods are tested with simulated data, and then applied to Pneumonia Etiology Research for Child Health data. The paper closes with a brief description of extensions of the PLCM to the regression setting and to the case where conditional independence between the measures is relaxed.

title: Structure-Based Design, Synthesis and Biological Evaluation of Peptidomimetic Aldehydes as a Novel Series of Antiviral Drug Candidates Targeting the SARS-CoV-2 Main Protease
abstract: SARS-CoV-2 is the etiological agent responsible for the COVID-19 outbreak in Wuhan. Specific antiviral drug are urgently needed to treat COVID-19 infections. The main protease (Mpro) of SARS-CoV-2 is a key CoV enzyme that plays a pivotal role in mediating viral replication and transcription, which makes it an attractive drug target. In an effort to rapidly discover lead compounds targeting Mpro, two compounds (11a and 11b) were designed and synthesized, both of which exhibited excellent inhibitory activity with an IC50 value of 0.05 μM and 0.04 μM respectively. Significantly, both compounds exhibited potent anti-SARS-CoV-2 infection activity in a cell-based assay with an EC50 value of 0.42 μM and 0.33 μM, respectively. The X-ray crystal structures of SARS-CoV-2 Mpro in complex with 11a and 11b were determined at 1.5 Å resolution, respectively. The crystal structures showed that 11a and 11b are covalent inhibitors, the aldehyde groups of which are bound covalently to Cys145 of Mpro. Both compounds showed good PK properties in vivo, and 11a also exhibited low toxicity which is promising drug leads with clinical potential that merits further studies.

title: QT Interval and Arrhythmic Safety of Hydroxychloroquine Monotherapy in Coronavirus Disease 2019
abstract: Observational studies have suggested increased arrhythmic and cardiovascular risk with the combination use of hydroxychloroquine (HCQ) and azithromycin in patients with coronavirus disease 2019 (COVID-19).  The arrhythmic safety profile of HCQ monotherapy, which remains under investigation as a therapeutic and prophylactic agent in COVID-19, is less established and we sought to evaluate this.  In 245 consecutive patients with COVID-19 admitted to the University of Washington hospital system between March 9 and May 10, 2020, we identified 111 treated with HCQ monotherapy. Patients treated with HCQ underwent a systematic arrhythmia and QT interval surveillance protocol including serial electrocardiograms (ECG) (baseline, following second HCQ dose). The primary endpoint was in-hospital sustained ventricular arrhythmia or arrhythmic cardiac arrest. Secondary endpoints included clinically significant QTc prolongation.  A total of 111 patients with COVID-19 underwent treatment with HCQ monotherapy (mean age 62±16 years, 44 women [39%], serum creatinine 0.9 [interquartile range 0.4] mg/dL). There were no instances of sustained ventricular arrythmia or arrhythmic cardiac arrest. In 75 patients with serial ECGs, clinically significant QTc prolongation was observed in a minority (N=5 [7%]). In patients with serial ECGs, there was no significant change in the QTc interval in pre-specified subgroups of interest, including those with prevalent cardiovascular disease or baseline use of renin-angiotensin-aldosterone axis inhibitors.  In the context of a systematic monitoring protocol, HCQ monotherapy in hospitalized COVID-19 patients was not associated with malignant ventricular arrhythmia. A minority of patients demonstrated clinically significant QTc prolongation during HCQ therapy.

title: Perspectives on monoclonal antibody therapy as potential therapeutic intervention for Coronavirus disease-19 (COVID-19).
abstract: Last decade witnessed the outbreak of many life-threatening human pathogens including Nipah, Ebola, Chikungunya, Zika, Middle East respiratory syndrome coronavirus (MERS-CoV), Severe Acute respiratory syndrome coronavirus (SARS-CoV) and more recently novel coronavirus (2019-nCoV or SARS-CoV-2). The disease condition associated with novel coronavirus, referred to as Coronavirus disease (COVID-19). The emergence of novel coronavirus in 2019 in Wuhan, China marked the third highly pathogenic coronavirus infecting humans in the 21st century. The continuing emergence of coronaviruses at regular intervals poses a significant threat to human health and economy. Ironically, even after a decade of research on coronavirus, still there are no licensed vaccines or therapeutic agents to treat coronavirus infection which highlights an urgent need to develop effective vaccines or post-exposure prophylaxis to prevent future epidemics. Several clinical, genetic and epidemiological features of COVID-19 resemble SARS-CoV infection. Hence, the research advancements on SARS-CoV treatment might help scientific community in quick understanding of this virus pathogenesis and develop effective therapeutic/prophylactic agents to treat and prevent this infection. Monoclonal antibodies represent the major class of biotherapeutics for passive immunotherapy to fight against viral infection. The therapeutic potential of monoclonal antibodies has been well recognized in the treatment of many diseases. Here, we summarize the potential monoclonal antibody based therapeutic intervention for COVID-19 by considering the existing knowledge on the neutralizing monoclonal antibodies against similar coronaviruses SARS-CoV and MERS-CoV. Further research on COVID-19 pathogenesis could identify appropriate therapeutic targets to develop specific anti-virals against this newly emerging pathogen.

title: Frequency of diarrhea in novel coronavirus 2019 infection

title: The many estimates of the COVID-19 case fatality rate

title: Evolving status of the 2019 novel coronavirus infection: Proposal of conventional serologic assays for disease diagnosis and infection monitoring

title: COVID-19: The unreasonable effectiveness of simple models
abstract: When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the comprehensiveness of many widely established models, the official figures that recount the course of the outbreak still sketch a largely elusive and intimidating picture. Here we show unambiguously that the dynamics of the COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. Our analysis naturally leads us to establish that there exists a fundamental limitation to any theoretical approach, namely the unpredictable non-stationarity of the testing frames behind the reported figures. However, we show how such bias can be quantified self-consistently and employed to mine useful and accurate information from the data. In particular, we describe how the time evolution of the reporting rates controls the occurrence of the apparent epidemic peak, which typically follows the true one in countries that were not vigorous enough in their testing at the onset of the outbreak. The importance of testing early and resolutely appears as a natural corollary of our analysis, as countries that tested massively at the start clearly had their true peak earlier and less deaths overall.

title: Microbiological safety of drinking water: United States and global perspectives.
abstract: Waterborne disease statistics only begin to estimate the global burden of infectious diseases from contaminated drinking water. Diarrheal disease is dramatically underreported and etiologies seldom diagnosed. This review examines available data on waterborne disease incidence both in the United States and globally together with its limitations. The waterborne route of transmission is examined for bacterial, protozoal, and viral pathogens that either are frequently associated with drinking water (e.g., Shigella spp.), or for which there is strong evidence implicating the waterborne route of transmission (e.g., Leptospira spp.). In addition, crucial areas of research are discussed, including risks from selection of treatment-resistant pathogens, importance of environmental reservoirs, and new methodologies for pathogen-specific monitoring. To accurately assess risks from waterborne disease, it is necessary to understand pathogen distribution and survival strategies within water distribution systems and to apply methodologies that can detect not only the presence, but also the viability and infectivity of the pathogen.

title: Dynamic change process of target genes by RT-PCR testing of SARS-Cov-2 during the course of a Coronavirus Disease 2019 patient
abstract: We report the dynamic change process of target genes by RT-PCR testing of SARS-Cov-2 during the course of a COVID-19 patient: from successive negative results to successive single positive nucleocapsid gene, to two positive target genes (orf1ab and nucleocapsid) by RT-PCR testing of SARS-Cov-2, and describe the diagnosis, clinical course, and management of the case. In this case, negative results of RT-PCR testing was not excluded to diagnose a suspected COVID-19 patient, clinical signs and symptoms, other laboratory findings, and chest CT images should be taken into account for the absence of enough positive evidence. This case highlights the importance of successive sampling and testing SARS-Cov-2 by RT-PCR as well as the increased value of single positive target gene from pending to positive in two specimens to diagnose laboratory-confirmed COVID-19.

title: What Should Gastroenterologists and Patients Know About COVID-19?

title: Excess cases of Influenza like illnesses in France synchronous with COVID19 invasion.
abstract: Several French regions where COVID19 has been reported currently show a renewed increase in ILI cases in the general practice based Sentinelles network. Here we computed the number of excess cases by region and found correlation with the number of reported COVID19 cases so far. These data suggest larger circulation of SARS-CoV-2 in the French population than apparent from confirmed cases.

title: The effects of injection of bovine vaccine into a human digit: a case report
abstract: The incidence of needlestick injuries in farmers and veterinary surgeons is significant and the consequences of such an injection can be serious.  We report accidental injection of bovine vaccine into the base of the little finger. This resulted in increased pressure in the flexor sheath causing signs and symptoms of ischemia. Amputation of the digit was required despite repeated surgical debridement and decompression.  There have been previous reports of injection of oil-based vaccines into the human hand resulting in granulomatous inflammation or sterile abscess and causing morbidity and tissue loss. Self-injection with veterinary vaccines is an occupational hazard for farmers and veterinary surgeons. Injection of vaccine into a closed compartment such as the human finger can have serious sequelae including loss of the injected digit. These injuries are not to be underestimated. Early debridement and irrigation of the injected area with decompression is likely to give the best outcome. Frequent review is necessary after the first procedure because repeat operations may be required.

title: Efficacy of hydroxychloroquine for post-exposure prophylaxis to prevent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among adults exposed to coronavirus disease (COVID-19): a structured summary of a study protocol for a randomised controlled trial
abstract: To test the efficacy of Hydroxychloroquine (HCQ) (400 mg orally daily for 3 days then 200 mg orally daily for an additional 11 days, to complete 14 days) to prevent incident SARS-CoV-2 infection, compared to ascorbic acid among contacts of persons with SARS-CoV-2 infection Secondary objectives • To determine the safety and tolerability of HCQ as SARS-CoV-2 Post-exposure Prophylaxis (PEP) in adults • To test the efficacy of HCQ (400 mg orally daily for 3 days then 200 mg orally daily for an additional 11 days, to complete 14 days) to prevent incident SARS-CoV-2 infection 2 weeks after completing therapy, compared to ascorbic acid among contacts of persons with SARS-CoV-2 infection • To test the efficacy of HCQ to shorten the duration of SARS-CoV-2 shedding among those with SARS-CoV-2 infection in the HCQ PEP group • To test the efficacy of HCQ to prevent incident COVID-19  This is a randomized, multi-center, placebo-equivalent (ascorbic acid) controlled, blinded study of HCQ PEP for the prevention of SARS-CoV-2 infection in adults exposed to the virus.  This study will enroll up to 2000 asymptomatic adults 18 to 80 years of age (inclusive) at baseline who are close contacts of persons with polymerase chain reaction (PCR)-confirmed SARS-CoV-2 or clinically suspected COVID-19 and a pending SARS-CoV-2 PCR test. This multisite trial will be conducted at seven sites in Seattle (UW), Los Angeles (UCLA), New Orleans (Tulane), Baltimore (UMB), New York City (NYU), Syracuse (SUNY-Upstate), and Boston (BMC).  Men or women 18 to 80 years of age inclusive, at the time of signing the informed consent. 2. Willing and able to provide informed consent. 3. Had a close contact of a person (index) with known PCR-confirmed SARS-CoV-2 infection or index who is currently being assessed for COVID-19. a. Household contact (i.e., residing with the index case in the 14 days prior to index diagnosis or prolonged exposure within a residence/vehicle/enclosed space without maintaining social distance). b. Medical staff, first responders, or other care persons who cared for the index case without personal protection (mask and gloves): 4. Less than 4 days since last exposure (close contact with a person with SARS-CoV-2 infection) to the index case; 5. Access to device and internet for Telehealth visits; 6. Not planning to take HCQ in addition to the study medication. Exclusion criteria 1. Known hypersensitivity to HCQ or other 4-aminoquinoline compounds. 2. Currently hospitalized. 3. Symptomatic with subjective fever, cough, or shortness of breath. 4. Current medications exclude concomitant use of HCQ. 5. Concomitant use of other anti-malarial treatment or chemoprophylaxis, including chloroquine, mefloquine, artemether, or lumefantrine. 6. History of retinopathy of any etiology. 7. Psoriasis. 8.  Known bone marrow disorders with significant neutropenia (polymorphonuclear leukocytes <1500) or thrombocytopenia (<100 K). 10. Concomitant use of digoxin, cyclosporin, cimetidine, amiodarone, or tamoxifen. 11. Known moderate or severe liver disease. 12. Known long QT syndrome. 13. Severe renal impairment. 14. Use of any investigational or non-registered drug or vaccine within 30 days preceding the first dose of the study drugs or planned use during the study period.  Households will be randomized 1:1 (at the level of household), with close contact participants receiving one of the following therapies: •HCQ 400 mg orally daily for 3 days then 200 mg orally daily for an additional 11 days •Placebo-like control (ascorbic acid) 500 mg orally daily for 3 days then 250 mg orally daily for 11 days MAIN OUTCOMES: The primary outcome of the study is the incidence of SARS-CoV-2 infection through day 14 among participants who are SARS-CoV-2 negative at baseline by randomization group.  Participants will be randomized in a 1:1 ratio to HCQ or ascorbic acid at the level of the household (all eligible participants in 1 household will receive the same intervention). The randomization code and resulting allocation list will be generated and maintained by the Study Statistician. The list will be blocked and stratified by site and contact type (household versus healthcare worker). BLINDING (MASKING): This is a blinded study. HCQ and ascorbic acid will appear similar, and taste will be partially masked as HCQ can be bitter and ascorbic acid will be sour. The participants will be blinded to their randomization group once assigned. Study team members, apart from the Study Pharmacist and the unblinded statistical staff, will be blinded. Laboratory staff are blinded to the group allocation. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): The sample size for the study is N=2 000 participants randomized 1:1 to either HCZ (n=1 000) and ascorbic acid (n=1 000).   In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

title: Estimate of Covid-19 prevalence using imperfect data
abstract: The real number of people who were truly infected with SARS-CoV-2, is certainly significantly larger than the official record. Few countries have tracking and testing procedures that are sufficiently robust to discover nearly all infections. In most countries they are inadequate, hence the true extent of the pandemic is unknown. The current study proposes the estimate of the COVID-19 extent for countries with sufficiently high number of deaths and cases. The estimate is based on a simple model of mortality. This model was developed for a reference country with a large number of cases and high intensity of COVID-19 testing. The model is then applied to compute apparent mortality in the target and reference countries. The number of cases in the target country is then estimated assuming constant underlying true mortality. The estimate of cases in most countries is significantly higher than the official record. As of April 12, 2020, the global estimate is 5.2 million compared to 1.8 million in the official record. The models developed in this study are available at covid-model.net. The model ignores several factors that are known to influence mortality, such as the demographics and health condition of population, state of epidemic and sociological differences between countries. While the model is rough, it nevertheless provides a unified approach to producing a systematic global estimate of the extent of the COVID-19 epidemic and can be useful for its monitoring.

title: COVID-19, Australia: Epidemiology Report 15 (Reporting week to 23:59 AEST 10 May 2020)
abstract: Confirmed cases in Australia notified up to 10 May 2020: notifications = 6,971; deaths = 98. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. The reduction in international travel, social distancing measures and public health action have likely been effective in slowing the spread of the disease, in the Australian community. Cases of COVID-19 continue to be notified by jurisdictions, albeit at a slowed rate. Testing rates over the past week have increased markedly, with a very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. In the past reporting week new cases in Australia are mostly considered to be locally acquired, consistent with the drop in international travel. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years, with a third of these cases associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, cases continue to increase, with some areas such as Brazil and India showing a dramatic rise in reported cases. Although some low-income countries have currently reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of disease occurrence.

title: Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China
abstract: An outbreak of clusters of viral pneumonia due to a novel coronavirus (2019-nCoV/SARS-CoV-2) happened in Wuhan, Hubei Province in China in December 2019. Since the outbreak, several groups reported estimated R(0) of Coronavirus Disease 2019 (COVID-19) and generated valuable prediction for the early phase of this outbreak. After implementation of strict prevention and control measures in China, new estimation is needed. An infectious disease dynamics SEIR (Susceptible, Exposed, Infectious, and Removed) model was applied to estimate the epidemic trend in Wuhan, China under two assumptions of R(t). In the first assumption, R(t) was assumed to maintain over 1. The estimated number of infections would continue to increase throughout February without any indication of dropping with R(t) = 1.9, 2.6, or 3.1. The number of infections would reach 11,044, 70,258, and 227,989, respectively, by 29 February 2020. In the second assumption, R(t) was assumed to gradually decrease at different phases from high level of transmission (R(t) = 3.1, 2.6, and 1.9) to below 1 (R(t) = 0.9 or 0.5) owing to increasingly implemented public health intervention. Several phases were divided by the dates when various levels of prevention and control measures were taken in effect in Wuhan. The estimated number of infections would reach the peak in late February, which is 58,077–84,520 or 55,869–81,393. Whether or not the peak of the number of infections would occur in February 2020 may be an important index for evaluating the sufficiency of the current measures taken in China. Regardless of the occurrence of the peak, the currently strict measures in Wuhan should be continuously implemented and necessary strict public health measures should be applied in other locations in China with high number of COVID-19 cases, in order to reduce R(t) to an ideal level and control the infection.

title: Mortality rate and estimate of fraction of undiagnosed COVID-19 cases in the US in March and April 2020
abstract: We use a simple model to derive a mortality probability distribution for a patient as a function of days since diagnosis (considering diagnoses made between 25 February and 29 March 2020). The peak of the mortality probability is the 13th day after diagnosis. The overall shape and peak location of this probability curve are similar to the onset-to-death probability distribution in a case study using Chinese data. The total mortality probability of a COVID-19 patient in the US diagnosed between 25 February and 29 March is about 21%. We speculate that this high value is caused by severe under-testing of the population to identify all COVID-19 patients. With this probability, and an assumption that the true probability is 2.4%, we estimate that 89% of all SARS-CoV-2 infection cases were not diagnosed during this period. When the same method is applied to data extended to 25 April, we found that the total mortality probability of a patient diagnosed in the US after 1 April is about 6.4%, significantly lower than for the earlier period. We attribute this drop to increasingly available tests. Given the assumption that the true mortality probability is 2.4%, we estimate that 63% of all SARS-CoV-2 infection cases were not diagnosed during this period (1 - 25 April).

title: Recombination and lineage-specific mutations led to the emergence of SARS-CoV-2
abstract: The recent outbreak of a new coronavirus (SARS-CoV-2) in Wuhan, China, underscores the need for understanding the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. Here, we show that recombination in betacoronaviruses, including human-infecting viruses like SARS-CoV and MERS-CoV, frequently encompasses the Receptor Binding Domain (RBD) in the Spike gene. We find that this common process likely led to a recombination event at least 11 years ago in an ancestor of the SARS-CoV-2 involving the RBD. As a result of this recombination event, SARS-CoV and SARS-CoV-2 share a similar genotype in RBD, including two insertions (positions 432-436 and 460-472), and alleles 427N and 436Y. Both 427N and 436Y belong to a helix that interacts with the human ACE2 receptor. Ancestral state analyses revealed that SARS-CoV-2 differentiated from its most recent common ancestor with RaTG13 by accumulating a significant number of amino acid changes in the RBD. In sum, we propose a two-hit scenario in the emergence of the SARS-CoV-2 virus whereby the SARS-CoV-2 ancestors in bats first acquired genetic characteristics of SARS-CoV by incorporation of a SARS-like RBD through recombination before 2009, and subsequently, the lineage that led to SARS-CoV-2 accumulated further, unique changes specifically in the RBD.

title: Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States
abstract: Real-time estimates of the true size and trajectory of local COVID-19 epidemics are key metrics to guide policy responses. We developed a Bayesian nowcasting approach that explicitly accounts for reporting delays and secular changes in case ascertainment to generate real-time estimates of COVID-19 epidemiology on the basis of reported cases and deaths. Using this approach, we estimate time trends in infections, symptomatic cases, and deaths for all 50 US states and the District of Columbia from early-March through June 11, 2020. At the beginning of June, our best estimates of the effective reproduction number (Rt) are close to 1 in most states, indicating a stabilization of incidence, but there is considerable variability in the level of incidence and the estimated proportion of the population that has already been infected.

title: COVID-19: Developing from an Outbreak to A Pandemic

title: An age-structured epidemiological model of the Belgian COVID-19 epidemic
abstract: COVID-19 has prompted many countries to implement extensive social distancing to stop the rapid spread of the virus, in order to prevent overloading health care systems. Yet, the main epidemic parameters of this virus are not well understood. In the absence of broad testing or serological surveillance, it is hard to evaluate or predict the impact of different strategies to exit implemented lock-down measures. An age-structured epidemiological model was developed, which distinguishes between the younger versus older population (e.g. < 65 and >= 65). Because the illness severity is markedly different for these two populations, such a separation is necessary then estimating the model based on death and hospitalization incidence data. The model was applied to data of the Belgian epidemic and used to predict how the epidemic would react to a relaxing of social distancing measures.

title: Evaluation of Group Testing for SARS-CoV-2 RNA
abstract: During the current COVID-19 pandemic, testing kit and RNA extraction kit availability has become a major limiting factor in the ability to determine patient disease status and accurately quantify prevalence. Current testing strategies rely on individual tests of cases matching restrictive diagnostic criteria to detect SARS-CoV-2 RNA, limiting testing of asymptomatic and mild cases. Testing these individuals is one effective way to understand and reduce the spread of COVID-19. Here, we develop a pooled testing strategy to identify these low-risk individuals. Drawing on the well-studied group testing literature, modeling suggests practical changes to testing protocols which can reduce test costs and stretch a limited test kit supply. When most tests are negative, pooling reduces the total number of tests up to four-fold at 2% prevalence and eight-fold at 0.5% prevalence. At current SARS-CoV-2 prevalence, randomized group testing optimized per country could double the number of tested individuals from 1.8M to 3.6M using only 672k more tests. This strategy is well-suited to supplement testing for asymptomatic and mild cases who would otherwise go untested, and enable them to adopt behavioral changes to slow the spread of COVID-19.

title: Statistics based predictions of coronavirus 2019-nCoV spreading in mainland China
abstract: The epidemic outbreak cased by coronavirus 2019-nCoV is of great interest to researches because of the high rate of spread of the infection and the significant number of fatalities. A detailed scientific analysis of the phenomenon is yet to come, but the public is already interested in the questions of the duration of the epidemic, the expected number of patients and deaths. For long time predictions, the complicated mathematical models are necessary which need many efforts for unknown parameters identification and calculations. In this article, some preliminary estimates will be presented.  Since the reliable long time data are available only for mainland China, we will try to predict the epidemic characteristics only in this area. We will estimate some of the epidemic characteristics and present the most reliable dependences for victim numbers, infected and removed persons versus time.  In this study we use the known SIR model for the dynamics of an epidemic, the known exact solution of the linear equations and statistical approach developed before for investigation of the children disease, which occurred in Chernivtsi (Ukraine) in 1988-1989.  The optimal values of the SIR model parameters were identified with the use of statistical approach. The numbers of infected, susceptible and removed persons versus time were predicted.  Simple mathematical model was used to predict the characteristics of the epidemic caused by coronavirus 2019-nCoV in mainland China. The further research should focus on updating the predictions with the use of fresh data and using more complicated mathematical models.

title: Preliminary Results of Initial Testing for Coronavirus (COVID-19) in the Emergency Department
abstract: On March 10, 2020, the World Health Organization declared a global pandemic due to widespread infection of the novel coronavirus 2019 (COVID-19). We report the preliminary results of a targeted program of COVID-19 infection testing in the ED in the first 10 days of its initiation at our institution.  We conducted a review of prospectively collected data on all ED patients who had targeted testing for acute COVID-19 infection at two EDs during the initial 10 days of testing (March 10-19, 2020). During this initial period with limited resources, testing was targeted toward high-risk patients per Centers for Disease Control and Prevention guidelines. Data collected from patients who were tested included demographics, clinical characteristics, and test qualifying criteria. We present the data overall and by test results with descriptive statistics.  During the 10-day study period, the combined census of the study EDs was 2157 patient encounters. A total of 283 tests were ordered in the ED. The majority of patients were 18-64 years of age, male, non-Hispanic white, had an Emergency Severity Index score of three, did not have a fever, and were discharged from the ED. A total of 29 (10.2%) tested positive. Symptoms-based criteria most associated with COVID-19 were the most common criteria identified for testing (90.6%). All other criteria were reported in 5.51-43.0% of persons being tested. Having contact with a person under investigation was significantly more common in those who tested positive compared to those who tested negative (63% vs 24.5%, respectively). The majority of patients in both results groups had at least two qualifying criteria for testing (75.2%).  In this review of prospectively collected data on all ED patients who had targeted testing for acute COVID-19 infection at two EDs in the first 10 days of testing, we found that 10.2% of those tested were identified as positive. The continued monitoring of testing and results will help providers understand how COVID-19 is progressing in the community.

title: Development of a fluorescence based, high-throughput SARS-CoV-2 3CLpro reporter assay
abstract: In late 2019 a human coronavirus, now known as SARS-CoV-2, emerged, likely from a zoonotic reservoir. This virus causes COVID-19 disease, has infected millions of people, and has led to hundreds of thousands of deaths across the globe. While the best interventions to control and ultimately stop the pandemic are prophylactic vaccines, antiviral therapeutics are important to limit morbidity and mortality in those already infected. At this time, only one FDA approved anti-SARS-CoV-2 antiviral drug, remdesivir, is available and unfortunately, its efficacy appears to be limited. Thus, the identification of new and efficacious antivirals is of highest importance. In order to facilitate rapid drug discovery, flexible, sensitive, and high-throughput screening methods are required. With respect to drug targets, most attention is focused on either the viral RNA-dependent RNA polymerase or the main viral protease, 3CLpro. 3CLpro is an attractive target for antiviral therapeutics as it is essential for processing newly translated viral proteins, and the viral lifecycle cannot be completed without protease activity. In this work, we present a new assay to identify inhibitors of the SARS-CoV-2 main protease, 3CLpro. Our reporter is based on a GFP-derived protein that only fluoresces after cleavage by 3CLpro. This experimentally optimized reporter assay allows for antiviral drug screening in human cell culture at biosafety level-2 (BSL2) with high-throughput compatible protocols. Using this screening approach in combination with existing drug libraries may lead to the rapid identification of novel antivirals to suppress SARS-CoV-2 replication and spread.  The COVID-19 pandemic has already led to more than 400,000 deaths and innumerable changes to daily life worldwide. Along with development of a vaccine, identification of effective antivirals to treat infected patients is of the highest importance. However, rapid drug discovery requires efficient methods to identify novel compounds that can inhibit the virus. In this work, we present a method for identifying inhibitors of the SARS-CoV-2 main protease, 3CLpro. This reporter-based assay allows for antiviral drug screening in human cell culture at biosafety level-2 (BSL2) with high-throughput compatible sample processing and analysis. This assay may help identify novel antivirals to control the COVID-19 pandemic.

title: Brazil Health Care System preparation against COVID-19
abstract: The coronavirus disease outbreak from 2019 (COVID-19) is associated with a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a highly contagious virus that claimed thousands of lives around the world and disrupted the health system in many countries. The assessment of emergency capacity in every country is a necessary part of the COVID-19 response efforts. Thus, it is extremely recommended to evaluate the health care system to prepare the country to tackle COVID-19 challenges.  A retrospective and ecological study was performed with data retrieved from the public national healthcare database (DATASUS). Numbers of intensive care unit and infirmary beds, general or intensivists physicians, nurses, nursing technicians, and ventilators from each Regional Health Unity were extracted, and the beds per health professionals and ventilators per population rates were assessed. The accessibility to health services was also performed using a spatial overlay approach to verify regions that lack assistance. It was found that Brazil lacks equity, integrity, and may struggle to assist with high complexity for the COVID-19 patients in many regions of the country.  Brazilian health system is insufficient to tackle the COVID-19 in some regions of the country where the coronavirus may be responsible for high rates of morbidity and mortality.

title: Development of Reverse Transcription Loop-Mediated Isothermal Amplification Assays Targeting SARS-CoV-2
abstract: Epidemics of coronavirus disease 2019 (COVID-19) now have >100,000 confirmed cases worldwide. Diagnosis of COVID-19 is currently performed by quantitative RT-PCR methods, but the capacity of quantitative RT-PCR methods is limited by their requirement of high-level facilities and instruments. Herein, reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays to detect genomic RNA of SARS-CoV-2, the causative virus of COVID-19, were developed and evaluated. RT-LAMP assays in this study can detect as low as 100 copies of SARS-CoV-2 RNA. Cross-reactivity of RT-LAMP assays to other human coronaviruses was not observed. A colorimetric detection method was adapted for this RT-LAMP assay so that the tests potentially performed in higher throughput.

title: Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations
abstract: Accurate forecasts for COVID-19 are necessary for better preparedness and resource management. Specifically, deciding the response over months or several months requires accurate long-term forecasts which is particularly challenging as the model errors accumulate with time. A critical factor that can hinder accurate long-term forecasts, is the number of unreported/asymptomatic cases. While there have been early serology tests to estimate this number, more tests need to be conducted for more reliable results. To identify the number of unreported/asymptomatic cases, we take an epidemiology data-driven approach. We show that we can identify lower bounds on this ratio or upper bound on actual cases as a factor of reported cases. To do so, we propose an extension of our prior heterogeneous infection rate model, incorporating unreported/asymptomatic cases. We prove that the number of unreported cases can be reliably estimated only from a certain time period of the epidemic data. In doing so, we construct an algorithm called Fixed Infection Rate method, which identifies a reliable bound on the learned ratio. We also propose two heuristics to learn this ratio and show their effectiveness on simulated data. We use our approaches to identify the upper bounds on the ratio of actual to reported cases for New York City and several US states. Our results demonstrate with high confidence that the actual number of cases cannot be more than 35 times in New York, 40 times in Illinois, 38 times in Massachusetts and 29 times in New Jersey, than the reported cases.

title: Impact of coronavirus disease 2019 (covid-19) outbreak on rehabilitation services and physical medicine and rehabilitation (PM&R) physicians' activities: perspectives from the Spanish experience.

title: Emerging WuHan (COVID-19) coronavirus: glycan shield and structure prediction of spike glycoprotein and its interaction with human CD26
abstract: The recent outbreak of pneumonia-causing COVID-19 in China is an urgent global public health issue with an increase in mortality and morbidity. Here we report our modelled homo-trimer structure of COVID-19 spike glycoprotein in both closed (ligand-free) and open (ligand-bound) conformation, which is involved in host cell adhesion. We also predict the unique N- and O-linked glycosylation sites of spike glycoprotein that distinguish it from the SARS and underlines shielding and camouflage of COVID-19 from the host the defence system. Furthermore, our study also highlights the key finding that the S1 domain of COVID-19 spike glycoprotein potentially interacts with the human CD26, a key immunoregulatory factor for hijacking and virulence. These findings accentuate the unique features of COVID-19 and assist in the development of new therapeutics.

title: Chapter 2 Anatomical Uniqueness of the Mucosal Immune System (GALT, NALT, iBALT) for the Induction and Regulation of Mucosal Immunity and Tolerance
abstract: Mucosal surfaces lining the lung and the gut are constantly exposed to environmental antigens, commensal organisms, and pathogens. Consequently, the host’s immune system devotes enormous resources to the defense of these tissues. Although mucosal immune responses must be sufficiently strong to eliminate pathogens, they must also have mechanisms to prevent excessive inflammation and initiate epithelial repair. Importantly, mucosal immune responses are initiated and regulated by a variety of mucosal lymphoid tissues, collectively known as mucosa-associated lymphoid tissue (MALT). This chapter describes the unique developmental, architectural, and functional features of the MALT and how those features facilitate the local immune response at each site.

title: Stop playing with data: there is no sound evidence that Bacille Calmette-Guérin may avoid SARS-CoV-2 infection (for now)
abstract: Since the beginning of the COVID-19 epidemic, a possible explanation for the high heterogeneity of infection/mortality rates across involved countries was hinted in the prevalence of tuberculosis vaccination with Bacille Calmette-Guérin (BCG). A systematic review was therefore performed on May 2, 2020. A total of 13 articles were ultimately retrieved, 12 of them as preprint papers. All articles were ecological studies of low quality. Most of them did not include main confounding factors (i.e. demographic of the assessed countries, share of peo- ple residing in urban settings, etc.), and simply assessed the differences among incidence/mortality of COVID-19 with vaccination rates or by having vs. having not any vaccination policy for BCG. Even though all studies shared the very same information sources (i.e. international registries for BCG vaccination rates and open source data for COVID-19 epidemics), results were conflicting, with later studies apparently denying any true correlation between COVID-19 occurrence and BCG vaccination rates and/or policies. As a consequence, there is no sound evidence to recommend BCG vaccination for the prevention of COVID-19.

title: Modeling the COVID-19 outbreaks and the effectiveness of the containment measures adopted across countries
abstract: On March 11, 2020, the World Health Organization declared the COVID-19 outbreak, originally started in China, a global pandemic. Since then, the outbreak has indeed spread across all continents, threatening the public health of numerous countries. Although the Case Fatality Rate (CFR) of COVID-19 is relatively low when optimal level of healthcare is granted to the patients, the high percentage of severe cases developing severe pneumonia and thus requiring respiratory support is worryingly high, and could lead to a rapid saturation of Intensive Care Units (ICUs). To overcome this risk, most countries enacted COVID-19 containment measures. In this study, we use a Bayesian SEIR epidemiological model to perform a parametric regression over the COVID-19 outbreaks data in China, Italy, Belgium, and Spain, and estimate the effect of the containment measures on the basic reproduction ratio R_0. We find that the effect of these measures is detectable, but tends to be gradual, and that a progressive strengthening of these measures usually reduces the R_0 below 1, granting a decay of the outbreak. We also discuss the biases and inconsistencies present in the publicly available data on COVID-19 cases, providing an estimate for the actual number of cases in Italy on March 12, 2020. Lastly, despite the data and model's limitations, we argue that the idea of "flattening the curve" to reach herd immunity is likely to be unfeasible.

title: Comparison of the spatiotemporal characteristics of the COVID-19 and SARS outbreaks in mainland China
abstract: Both coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS) are caused by coronaviruses and have infected people in China and worldwide. We aimed to investigate whether COVID-19 and SARS exhibited similar spatial and temporal features at the provincial level in mainland China.  The number of people infected by COVID-19 and SARS were extracted from daily briefings on newly confirmed cases during the epidemics, as of Mar. 4, 2020 and Aug. 3, 2003, respectively. We depicted the spatiotemporal patterns of the COVID-19 and SARS epidemics using spatial statistics such as Moran's I and the local indicators of spatial association (LISA).  Compared to SARS, COVID-19 had a higher incidence. We identified 3 clusters (predominantly located in south-central China, highest RR=135.08) for COVID-19 and 4 clusters (mainly in Northern China, highest RR=423.51) for SARS. Fewer secondary clusters were identified after the “Wuhan lockdown”. The LISA cluster map detected a significantly high-low (Hubei) and low-high spatial clustering (Anhui, Hunan, and Jiangxi, in Central China) for COVID-19. Two significant high-high (Beijing and Tianjin) and low-high (Hebei) clusters were detected for SARS, although the global Moran's I value was not significant.  The different spatiotemporal clustering patterns between COVID-19 and SARS could point to changes in social and demographic factors, local government containment strategies or differences in transmission mechanisms between these coronaviruses.

title: QT prolongation in a diverse, urban population of COVID-19 patients treated with hydroxychloroquine, chloroquine, or azithromycin
abstract: Hydroxychloroquine, chloroquine, and azithromycin have been used for treatment of COVID-19, but may cause QT prolongation. Minority populations are disproportionately impacted by COVID-19. This study evaluates the risk of QT prolongation and subsequent outcomes after administration of these medications in largely underrepresented minority COVID-19 patients.  We conducted an observational study on hospitalized COVID-19 patients in the Montefiore Health System (Bronx, NY). We examined electrocardiograms (ECG) pre/post-medication initiation to evaluate QTc, HR, QRS duration, and presence of other arrhythmias.  One hundred five patients (mean age 67 years; 44.8% F) were analyzed. The median time from the first dose of any treatment to post-medication ECG was 2 days (IQR: 1–3). QTc in men increased from baseline (440 vs 455 ms, p < 0.001), as well as in women (438 vs 463 ms, p < 0.001). The proportion of patients with QT prolongation increased significantly (14.3% vs 34.3%, p < 0.001) even when adjusted for electrolyte abnormalities. The number of patients whose QTc > 500 ms was significantly increased after treatment (16.2% vs. 4.8%, p < 0.01). Patients with either QTc > 500 ms or an increase of 60 ms had a higher frequency of death (47.6% vs. 22.6%, p = 0.02) with an odds ratio of 3.1 (95% CI: 1.1–8.7). Adjusting for race/ethnicity yielded no significant associations.  Hydroxychloroquine, chloroquine, and/or azithromycin were associated with QTc prolongation but did not result in fatal arrhythmias. Our findings suggest that any harm is unlikely to outweigh potential benefits of treatment. Careful risk-benefit analyses for individual patients should guide the use of these medications. Randomized control trials are necessary to evaluate their efficacies.

title: Coronavirus and Other Respiratory Illnesses Comparing Older with Young Adults
abstract: Study of human coronavirus and other virus-associated respiratory illnesses is needed to describe their clinical effects on chronically ill, older adults.  A prospective study during 2009 to 2013 clinically assessed acute respiratory illnesses soon after onset and 3 to 4 weeks later in patients aged ≥60 years with chronic lung and heart diseases (group 1, 100 subjects) and healthy adults aged 18 to 40 years (group 2, 101 subjects). Respiratory secretions were tested for nucleic acids of a panel of respiratory viruses. An increase in antibody titer was assessed for 4 coronavirus strains.  Virus-associated illnesses (29 [39.1%] of 74 illnesses in group 1 and 59 [48.7%] of 121 illnesses in group 2) occurred in all calendar quarters, most commonly in the first and fourth quarters. Coronaviruses (group 1: 14 [18.9%] illnesses; group 2: 26 [21.5%] illnesses) and enteroviruses/rhinoviruses (group 1: 14 [18.9%] illnesses; group 2: 37 [30.6%] illnesses) were most common. Virus co-infections occurred in 10 illnesses. Illnesses with 9 to 11 symptoms were more common in group 1 (17 [23.0%]) than in group 2 (15 [12.4%]) (P < .05). Compared with group 2, more group 1 subjects reported dyspnea, more severe disease of longer duration, and treatment for acute illness with prednisone and antibiotics. Coronavirus-associated illnesses (percent of illnesses, group 1 vs group 2) were characterized by myalgias (21% vs 68%, P < .01), chills (50% vs 52%), dyspnea (71% vs 24%, P < .01), headache (64% vs 72%), malaise (64% vs 84%), cough (86% vs 68%), sputum production (86% vs 60%), sore throat (64% vs 80%), and nasal congestion (93% vs 96%).  Respiratory illnesses were commonly associated with coronaviruses and enteroviruses/rhinoviruses affecting chronically ill, older patients more than healthy, young adults.

title: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Children and Adolescents: A Systematic Review.
abstract: The current rapid worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection justifies the global effort to identify effective preventive strategies and optimal medical management. While data are available for adult patients with coronavirus disease 2019 (COVID-19), limited reports have analyzed pediatric patients infected with SARS-CoV-2.  To evaluate currently reported pediatric cases of SARS-CoV-2 infection.  An extensive search strategy was designed to retrieve all articles published from December 1, 2019, to March 3, 2020, by combining the terms coronavirus and coronavirus infection in several electronic databases (PubMed, Cochrane Library, and CINAHL), and following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Retrospective cross-sectional and case-control studies, case series and case reports, bulletins, and national reports about the pediatric SARS-CoV-2 infection were included. The risk of bias for eligible observational studies was assessed according to the Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.  A total of 815 articles were identified. Eighteen studies with 1065 participants (444 patients were younger than 10 years, and 553 were aged 10 to 19 years) with confirmed SARS-CoV-2 infection were included in the final analysis. All articles reflected research performed in China, except for 1 clinical case in Singapore. Children at any age were mostly reported to have mild respiratory symptoms, namely fever, dry cough, and fatigue, or were asymptomatic. Bronchial thickening and ground-glass opacities were the main radiologic features, and these findings were also reported in asymptomatic patients. Among the included articles, there was only 1 case of severe COVID-19 infection, which occurred in a 13-month-old infant. No deaths were reported in children aged 0 to 9 years. Available data about therapies were limited.  To our knowledge, this is the first systematic review that assesses and summarizes clinical features and management of children with SARS-CoV-2 infection. The rapid spread of COVID-19 across the globe and the lack of European and US data on pediatric patients require further epidemiologic and clinical studies to identify possible preventive and therapeutic strategies.

title: Gastrointestinal tract symptoms in coronavirus disease 2019: Analysis of clinical symptoms in adult patients
abstract: To investigate the clinical presentation of coronavirus disease 2019 (COVID-19), particularly the incidence of gastrointestinal tract symptoms.  We enrolled adult COVID-19 patients from a mobile cabin hospital in Wuhan with a definitive diagnosis by SARS-CoV-2 nucleic acid testing. Face-to-face interviews were conducted in which the patient selected COVID-19-related symptoms and report the time of onset and duration of symptoms.  A total of 212 adults were enrolled in this study, of which 127 (59.9%) were females, mean age was 48.50 (range: 17-79) years, and mean disease course was 26.78 (3-60) days. Fever and cough were the most common and earliest clinical symptoms of COVID-19. Diarrhoea occurred in 43.8% (93/212) of patients, of which 86.0% (80/93) had mushy stools. Nausea and vomiting were also common (20.7%). Diarrhoea lasted for 4.00(2.00-8.85) days and mostly occurred 5.00(0.25-11.00) days after the emergence of the first symptoms. Multiple logistic regression analysis found that diarrhoea was significantly correlated with fatigue [OR2.900,95%CI (1.629-5.164), p<0.0001].  Gastrointestinal tract symptoms are common in COVID-19 and most occur during the middle stage of the disease and lasts for a short period of time. Clinicians need to pay greater attention to gastrointestinal tract symptoms of COVID-19.

title: Neuropsychiatric adverse events of chloroquine: A real-world pharmacovigilance study using the FAERS database
abstract: In early April 2020, the antimalarial drug, chloroquine, has been approved as an emergency treatment for the coronavirus disease 2019 (COVID-19) in the United States and in Europe. Although infrequent, neuropsychiatric symptoms have been reported in patients who received chloroquine for the treatment of malaria or autoimmune diseases. In this study, we investigated these adverse events (AEs) using a large self-reporting database.  We conducted a disproportionality analysis for the detection of neuropsychiatric AE signals associated with the use of chloroquine (or hydroxychloroquine), reported to FAERS database between the fourth quarter of 2012 and the fourth quarter of 2019. Adjusted reporting odds ratio (ROR) for the development of each of the neuropsychiatric AEs following the use of chloroquine was calculated using a multilevel model.  We included 2,389,474 AE cases, among which 520 cases developed neuropsychiatric AE following the use of chloroquine. Exposure to chloroquine was associated with a statistically significant high reporting of amnesia, delirium, hallucinations, depression, and loss of consciousness, (lower 95% confidence interval of the adjusted ROR > 1), although the degree of increase in their ROR was limited. There was no statistically significant high reporting of any other neuropsychiatric AE, including suicide, psychosis, confusion, and agitation.  Current pharmacovigilance study results did not suggest any potential link between the use of chloroquine and an increased risk of suicide, psychosis, confusion, and agitation, which would be informative during the emergency use of chloroquine for the treatment of COVID-19.

title: Early estimation of the case fatality rate of COVID-19 in mainland China: a data-driven analysis.
abstract: An ongoing outbreak of pneumonia caused by a novel coronavirus [severe acute respiratory syndrome coronavirus (SARS-CoV)-2], named COVID-19, hit a major city of China, Wuhan in December 2019 and subsequently spread to other provinces/regions of China and overseas. Several studies have been done to estimate the basic reproduction number in the early phase of this outbreak, yet there are no reliable estimates of case fatality rate (CFR) for COVID-19 to date.  In this study, we used a purely data-driven statistical method to estimate the CFR in the early phase of the COVID-19 outbreak. Daily numbers of laboratory-confirmed COVID-19 cases and deaths were collected from January 10 to February 3, 2020 and divided into three clusters: Wuhan city, other cities of Hubei province, and other provinces of mainland China. Simple linear regression model was applied to estimate the CFR from each cluster.  We estimated that CFR during the first weeks of the epidemic ranges from 0.15% (95% CI: 0.12-0.18%) in mainland China excluding Hubei through 1.41% (95% CI: 1.38-1.45%) in Hubei province excluding the city of Wuhan to 5.25% (95% CI: 4.98-5.51%) in Wuhan.  Our early estimates suggest that the CFR of COVID-19 is lower than the previous coronavirus epidemics caused by SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV).

title: Animal models of mechanisms of SARS‐CoV‐2 infection and COVID‐19 pathology
abstract: The coronavirus disease 2019 (COVID‐19) pandemic caused by SARS‐CoV‐2 infections has led to substantial unmet need for treatments, many of which will require testing in appropriate animal models of this disease. Vaccine trials are already underway, but there remains an urgent need to find other therapeutic approaches to either target SARS‐CoV‐2 or the complications arising from viral infection, particularly the dysregulated immune response and systemic complications which have been associated with progression to severe COVID‐19. At the time of writing, in vivo studies of SARS‐CoV‐2 infection have been described using macaques, cats, ferrets, hamsters, and transgenic mice expressing human angiotensin I converting enzyme 2 (ACE2). These infection models have already been useful for studies of transmission and immunity, but to date only partially model the mechanisms implicated in human severe COVID‐19. There is therefore an urgent need for development of animal models for improved evaluation of efficacy of drugs identified as having potential in the treatment of severe COVID‐19. These models need to recapitulate key mechanisms of COVID‐19 severe acute respiratory distress syndrome and reproduce the immunopathology and systemic sequelae associated with this disease. Here, we review the current models of SARS‐CoV‐2 infection and COVID‐19‐related disease mechanisms and suggest ways in which animal models can be adapted to increase their usefulness in research into COVID‐19 pathogenesis and for assessing potential treatments.

title: COVID-19, hypertension and cardiovascular diseases: Should we change the therapy?
abstract: The coronavirus disease (COVID-19) has spread all around the world in a very short period of time. Recent data are showing significant prevalence of arterial hypertension and cardiovascular diseases (CVD) among patients with COVID-19, which raised many questions about higher susceptibility of patients with these comorbidities to the novel coronavirus, as well as the role of hypertension and CVD in progression and the prognosis of COVID-19 patients. There is a very limited amount of data, usually obtained from a small population, regarding the effect of the underlying disease on the outcome in patients with COVID-19. The evaluation of the treatment of these comorbidities at baseline and during COVID-19 is scarce and the results are conflicting. Hypertension and CVD, after the adjustment for other clinical and demographic parameters, primarily age, did not remain independent predictors of the lethal outcome in COVID-19 patients. Some investigations speculated about the association between the renin-angiotensin-aldosterone system (RAAS) and susceptibility to COVID-19, as well as the relationship between RAAS inhibitors and the adverse outcome in these patients. Withdrawing or switching RAAS inhibitors would have uncertain benefits, but it would definitely have many disadvantages such as uncontrolled hypertension, cardiac function deterioration and renal function impairment, which could potentially induce more complications in patients with COVID-19 than the infection of coronavirus itself. The aim of this review article was to summarize the prevalence of hypertension and CVD in patients with COVID-19, their influence on the outcome and the effect of treatment of hypertension and CVD in COVID-19 patients.

title: Effectiveness of isolation, testing, contact tracing and physical distancing on reducing transmission of SARS-CoV-2 in different settings
abstract: Isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures - including novel digital tracing approaches and less intensive physical distancing - may be required to reduce transmission. Using a model of individual-level transmission stratified by setting (household, work, school, other) based on BBC Pandemic data from 40,162 UK participants, we simulated the impact of a range of different testing, isolation, tracing and physical distancing scenarios. As well as estimating reduction in effective reproduction number, we estimated, for a given level of COVID-19 incidence, the number of contacts that would be newly quarantined each day under different strategies. Under optimistic but plausible assumptions, we estimated that combined testing and tracing strategies would reduce transmission more than mass testing or self-isolation alone (50-65% compared to 2-30%). If limits are placed on gatherings outside of home/school/work (e.g. maximum of 4 daily contacts in other settings), then manual contact tracing of acquaintances only could have a similar effect on transmission reduction as detailed contact tracing. In a scenario where there were 10,000 new symptomatic cases per day, we estimated in most contact tracing strategies, 140,000 to 390,000 contacts would be newly quarantined each day. Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimates that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number that is below one in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control.

title: Caution Warranted: Using the Institute for Health Metrics and Evaluation Model for Predicting the Course of the COVID-19 Pandemic
abstract: The Institute for Health Metrics and Evaluation model for predicting the course of the coronavirus disease 2019 pandemic has attracted considerable attention, including from the U.S. government. The appearance of certainty of model estimates is seductive when the world is desperate to know what lies ahead, but caution is warranted regarding the validity and usefulness of the model projections for policymakers.

title: Global, Regional and National Incidence and Case-fatality rates of Novel Coronavirus (COVID-19) across 154 countries and territories: A systematic assessment of cases reported from January to March 16, 2020
abstract: The 2019 novel coronavirus disease (COVID-19) outbreak turned into a pandemic, with hundreds of thousands of cases reported globally. The number of cases dramatically increased beginning in early March 2020.  We assessed the cumulative change in the incidence and case-fatality rates of COVID-19 at the global, regional, and national levels from January to March 16, 2020, in 154 affected countries and territories globally.  We collected data of COVID-19 cases using the GitHub repository, which provided real-time surveillance information developed by the Center for Systems Science and Engineering (CSSE), Johns Hopkins University (USA). Information such as confirmed COVID-19 cases, deaths, and recoveries reported across all affected countries was collected from January 22 to March 16, 2020. We estimated the change in the incidence rate, case-fatality rate, and recovery rate from January 22 to February 29 and from March 1 to March 16, 2020.  From January 22 to March 16, 2020, globally, the number of incident COVID-19 cases increased by 276.2%, and Europe recorded 65,281 new cases from March 1 to 16, 2020. Overall, the case-fatality rate was 3.92%, with a high COVID-19 fatality rate in Italy (7.7%), Iran (5.7%), China (4.2%) and the United Kingdom (3.6%). The estimated percentage change in COVID-19 cases from March 1 to 16, 2020, was highest in Belgium (105.8/100,000 population), followed by Qatar (439/100,000 population) and Portugal (331/100,000 population). The overall recovery rate of COVID-19 was 43%; China (35.5%) had the highest recovery rate, while the United States of America recorded a recovery rate of 0.3%.  Overall, all the COVID-19-affected countries showed an upward trend in incidence, with little change in the incidence rate of -0.20% from January to Mid-March. The case-fatality rate was found to be 3.92%, and the recovery rate was observed to be less than half (43%) among COVID-19 patients. Italy, Iran, and Spain had the largest numbers of new cases of COVID-19 from March 1 to 16, 2020.

title: Connecting BCG Vaccination and COVID-19: Additional Data
abstract: The reasons for a wide variation in severity of coronavirus disease 2019 (COVID-19) across the affected countries of the world are not known. Two recent studies have suggested a link between the BCG vaccination policy and the morbidity and mortality due to COVID-19. In the present study we compared the impact of COVID-19 in terms of case fatality rates (CFR) between countries with high disease burden and those with BCG revaccination policies presuming that revaccination practices would have provided added protection to the population against severe COVID-19. We found a significant difference in the CFR between the two groups of countries. Our data further supports the view that universal BCG vaccination has a protective effect on the course of COVID-19 probably preventing progression to severe disease and death. Clinical trials of BCG vaccine are urgently needed to establish its beneficial role in COVID-19 as suggested by the epidemiological data, especially in countries without a universal BCG vaccination policy.  COVID-19, BCG vaccination, case fatality ratio, mortality, low resource countries

title: Testing for COVID-19

title: On the impact of early non-pharmaceutical interventions as containment strategies against the COVID-19 pandemic
abstract: The novel coronavirus SARS-CoV-2 (COVID-19) emerged in December 2019 in Wuhan, China and has spread since then to around 210 countries and territories by April 2020. Consequently, countries have adopted physical distance measures in an attempt to mitigate the uncontrolled spread of the virus. A critical question for policymakers to inform evidence-based practice is if and how physical distance measures slowed the propagation of COVID-19 in the early phase of the pandemic.  This study aims to quantify the effects of physical distance mitigation measures on the propagation of the COVID-19 pandemic. Data from John Hopkins University on confirmed cases and testing data from the Our World in Data were used in an interrupted time series analysis to estimate the effects of physical distance measures on the growth rates of the pandemic in 12 countries of Asia, Africa, and Europe.  We found that physical distance measures produced a significant decrease in the growth rates of the COVID-19 pandemic in five countries (Austria, Belgium, Italy, Malaysia, and South Korea). The test-positivity rate was significant in understanding the slowing growth rate of COVID-19 cases caused by the mitigation measures, as it provides important context that is missing from analysis based only on confirmed case data.  Physical distance interventions effectively slowed the progression of the COVID-19 pandemic. The results of this study could inform infectious disease mitigation policies based on physical distance measures by quantifying the differential health outcomes of a pandemic with and without physical distance interventions.

title: COVID-19, Australia: Epidemiology Report 18 (Fortnightly reporting period ending 7 June 2020).
abstract: Notified cases of COVID-19 and associated deaths reported to the National Notifiable Diseases Surveillance System (NNDSS) to 7 June 2020. Confirmed cases in Australia notified up to 7 June 2020: notifications = 7,277; deaths = 102. Over the past fortnightly reporting period, the number of new cases in all jurisdictions continues to decline, or remain very low, and testing rates continue to be high across all jurisdictions, with the positivity rate remaining very low at less than 0.1%. The incidence of COVID-19 has markedly reduced since a peak in mid-March. A combination of early case identification, physical distancing, public health measures and a reduction in international travel have been effective in slowing the spread of disease in Australia. Of the 147 cases notified between 25 May and 7 June, 63% acquired their infection overseas. The proportion of cases locally acquired has dropped substantially to 28% of new cases this period compared with 50% and greater observed since 30 March 2020. Of the cases considered to be locally-acquired over this period, most were associated with contacts of confirmed cases or were associated with known outbreaks. A small proportion of overall cases have experienced severe disease, requiring hospitalisation or intensive care with some fatalities. The crude case fatality rate amongst Australian cases is 1.4%. People who are older and have one or more comorbidities are more likely to experience severe disease. The highest rate of COVID-19 continues to be among people aged 65-79 years. Three-quarters of all cases in this age group have been associated with overseas travel, including several outbreaks linked to cruise ships. The lowest rate of disease is in children under 18, a pattern reflected in international reports. Internationally, as of 7 June 2020, the largest numbers of both cases and deaths have been reported in the United States. Of the confirmed cases reported globally, the case fatality rate is approximately 5.8%. Countries in South America are seeing rapid growth in case numbers, while the United States is seeing a steady decline in its daily new case numbers. Case numbers in Europe remain relatively steady, with several countries in Eastern Europe experiencing rapid growth. In the South East Asia region, India and Bangladesh are seeing accelerating epidemics, compounded by the recovery from Cyclone Amphan. Reported cases are increasing in Africa, although the numbers are much smaller. In the Pacific there are few new cases reported daily.

title: Incorrect Reporting of Statistical Tests

title: Cumulative incidence and diagnosis of SARS-CoV-2 infection in New York
abstract: New York State (NYS) is an epicenter of the SARS-CoV-2 pandemic in the United States. Reliable estimates of cumulative incidence in the population are critical to tracking the extent of transmission and informing policies.  We conducted a statewide seroprevalence study among a 15,101 patron convenience sample at 99 grocery stores in 26 counties throughout NYS. SARS-CoV-2 cumulative incidence was estimated from antibody reactivity by first post-stratification weighting then adjusting by antibody test characteristics. The percent diagnosed was estimated by dividing diagnoses by estimated infection-experienced adults.  Based on 1,887 of 15,101 reactive results (12.5%), estimated cumulative incidence through March 29 was 14.0% (95% CI: 13.3-14.7%), corresponding to 2,139,300 (95% CI: 2,035,800-2,242,800) infection-experienced adults. Cumulative incidence was highest in New York City (NYC) 22.7% (95% CI: 21.5-24.0%) and higher among Hispanic/Latino (29.2%), non-Hispanic black/African American (20.2%), and non-Hispanic Asian (12.4%) than non-Hispanic white adults (8.1%, p<.0001). An estimated 8.9% (95% CI: 8.4-9.3%) of infections in NYS were diagnosed, with diagnosis highest among adults ≥55 years (11.3%, 95% CI: 10.4-12.2%).  From the largest US serosurvey to date, we estimated > 2 million adult New York residents were infected through late March, with substantial disparities, although cumulative incidence remained below herd immunity thresholds. Monitoring, testing, and contact tracing remain essential public health strategies.

title: Characteristics of patients with coronavirus disease (COVID‐19) confirmed using an IgM‐IgG antibody test
abstract: Coronavirus disease (COVID‐19), caused by a novel betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has rapidly developed into a pandemic since it was first reported in December 2019. Nucleic acid testing is the standard method for the diagnosis of viral infections. However, this method reportedly has a low positivity rate. To increase the sensitivity of COVID‐19 diagnoses, we developed an IgM‐IgG combined assay and tested it in patients with suspected SARS‐CoV‐2 infection. In total, 56 patients were enrolled in this study and SARS‐CoV‐2 was detected by using both IgM‐IgG antibody and nucleic acid tests. Clinical and laboratory data were collected and analyzed. Our findings suggest that patients who develop severe illness might experience longer virus exposure times and develop a more severe inflammatory response. The IgM‐IgG test is an accurate and sensitive diagnostic method. A combination of nucleic acid and IgM‐IgG testing is a more sensitive and accurate approach for diagnosis and early treatment of COVID‐19.

title: Coronavirus disease 2019 (COVID-19) imaging reporting and data system (COVID-RADS) and common lexicon: a proposal based on the imaging data of 37 studies
abstract: In the vast majority of the laboratory-confirmed coronavirus disease 2019 (COVID-19) patients, computed tomography (CT) examinations yield a typical pattern and the sensitivity of this modality has been reported to be 97% in a large-scale study. Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care.  To compose a comprehensive lexicon for description of the imaging findings and propose a grading system and structured reporting format for CT findings in COVID-19.  We updated our published systematic review on imaging findings in COVID-19 to include 37 published studies pertaining to diagnostic features of COVID-19 in chest CT. Using the reported imaging findings of 3647 patients, we summarized the typical chest CT findings, atypical features, and temporal changes of COVID-19 in chest CT. Subsequently, we extracted a list of descriptive terms and mapped it to the terminology that is commonly used in imaging literature.  We composed a comprehensive lexicon that can be used for documentation and reporting of typical and atypical CT imaging findings in COVID-19 patients. Using the same data, we propose a grading system with five COVID-RADS categories. Each COVID-RADS grade corresponds to a low, moderate, or high level of suspicion for pulmonary involvement of COVID-19.  The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients.  • Chest CT has high sensitivity in diagnosing the coronavirus disease 2019 (COVID-19). • Structured reporting systems simplify the interpretation and reporting of imaging examinations, serve as a framework for consistent generation of recommendations, and improve the quality of patient care. • The proposed COVID-RADS and common lexicon would improve the communication of findings to other healthcare providers, thus facilitating the diagnosis and management of COVID-19 patients.

title: Traditional Chinese Medicine in the Treatment of Patients Infected with 2019-New Coronavirus (SARS-CoV-2): A Review and Perspective
abstract: Currently, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, formerly known as 2019-nCoV, the causative pathogen of Coronavirus Disease 2019 (COVID-19)) has rapidly spread across China and around the world, causing an outbreak of acute infectious pneumonia. No specific anti-virus drugs or vaccines are available for the treatment of this sudden and lethal disease. The supportive care and non-specific treatment to ameliorate the symptoms of the patient are the only options currently. At the top of these conventional therapies, greater than 85% of SARS-CoV-2 infected patients in China are receiving Traditional Chinese Medicine (TCM) treatment. In this article, relevant published literatures are thoroughly reviewed and current applications of TCM in the treatment of COVID-19 patients are analyzed. Due to the homology in epidemiology, genomics, and pathogenesis of the SARS-CoV-2 and SARS-CoV, and the widely use of TCM in the treatment of SARS-CoV, the clinical evidence showing the beneficial effect of TCM in the treatment of patients with SARS coronaviral infections are discussed. Current experiment studies that provide an insight into the mechanism underlying the therapeutic effect of TCM, and those studies identified novel naturally occurring compounds with anti-coronaviral activity are also introduced.

title: Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys
abstract: Establishing how many people have already been infected by SARS-CoV-2 is an urgent priority for controlling the COVID-19 pandemic. Patchy virological testing has hampered interpretation of confirmed case counts, and unknown rates of asymptomatic and mild infections make it challenging to develop evidence-based public health policies. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies has been unclear. Here, we used a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across tested subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that serological positivity indicates immune protection, we propagated these estimates and uncertainty through dynamical models to assess the uncertainty in the epidemiological parameters needed to evaluate public health interventions. We examined the relative accuracy of convenience samples versus structured surveys to estimate population seroprevalence, and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize the design of serological surveys given particular test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions.

title: Gestión Y Liderazgo De Los Servicios De Enfermería En El Plan De Emergencia De La Pandemia Covid-19: La Experiencia Del Hospital Clínic De Barcelona./ [management and Leadership of Nursing Services in the Emergency Plan for the Pandemic Covid-19: the Experience of the Clinic Hospital of Barcelona]
abstract: At the international level, the enormous demand to manage the COVID-19 pandemic has posed a challenge both in the provision of personnel and in supplies and sanitary material. There is no precedent or publication related to the management and leadership of nursing services in Spain within the emergency plan for the COVID-19 pandemic. This article describes the experience of the Hospital Clinico de Barcelona in the current extraordinary circumstances that undoubtedly constitute a nursing management of enormous magnitude and unprecedented due to the high number of people affected and the extraordinary risk of healthcare personnel. Following national and international guidelines to alleviate the pandemic, protect health and prevent the spread of the outbreak. The ability to work as a team, emotional management and respect for organizational decisions have made it possible to face the challenges that the pandemic has put in place and that the Nursing Department can lead in a calm and orderly manner the different actions to perform. Lastly, it will be necessary to continue with an in-depth analysis of the situation and of the actions carried out in order to identify the areas for improvement as well as to evaluate the overall nature of the process.

title: The outbreak of COVID-19: An overview
abstract: In late December 2019, a previous unidentified coronavirus, currently named as the 2019 novel coronavirus#, emerged from Wuhan, China, and resulted in a formidable outbreak in many cities in China and expanded globally, including Thailand, Republic of Korea, Japan, United States, Philippines, Viet Nam, and our country (as of 2/6/2020 at least 25 countries). The disease is officially named as Coronavirus Disease-2019 (COVID-19, by WHO on February 11, 2020). It is also named as Severe Pneumonia with Novel Pathogens on January 15, 2019 by the Taiwan CDC, the Ministry of Health and is a notifiable communicable disease of the fifth category. COVID-19 is a potential zoonotic disease with low to moderate (estimated 2%–5%) mortality rate. Person-to-person transmission may occur through droplet or contact transmission and if there is a lack of stringent infection control or if no proper personal protective equipment available, it may jeopardize the first-line healthcare workers. Currently, there is no definite treatment for COVID-19 although some drugs are under investigation. To promptly identify patients and prevent further spreading, physicians should be aware of the travel or contact history of the patient with compatible symptoms.

title: The role of asymptomatic SARS-CoV-2 infections: rapid living systematic review and meta-analysis
abstract: There is substantial disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a population. The disagreement results, in part, from the interpretation of studies that report a proportion of asymptomatic people with SARS-CoV-2 detected at a single point.  1. Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? 2. Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? 3. What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection, or pre-symptomatic?  Rapid living systematic review (protocol https://osf.io/9ewys/). We searched Pubmed, Embase, bioRxiv and medRxiv using a living evidence database of SARS-CoV-2 literature on 25.03.2020. We included studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR (RT-PCR) that documented follow-up and symptom status at the beginning and end of follow-up and modelling studies. Study selection, data extraction and bias assessment were done by one reviewer and verified by a second, with disagreement resolved by discussion or a third reviewer. We used a common-effect model to synthesise proportions from comparable studies.  We screened 89 studies and included 11. We estimated an upper bound for the proportion of asymptomatic SARS-CoV-2 infections of 29% (95% confidence interval 23 to 37%) in eight studies. Selection bias and likely publication bias affected the family case investigation studies. One statistical modelling study estimated the true proportion of asymptomatic infections at 18% (95% credibility interval 16 to 20%). Estimates of the proportions of pre-symptomatic individual in four studies were too heterogeneous to combine. In modelling studies, 40-60% of all SARS-CoV-2 infections are the result of transmission from pre-symptomatic individuals, with a smaller contribution from asymptomatic individuals.  An intermediate contribution of pre-symptomatic and asymptomatic infections to overall SARS-CoV-2 transmission means that combination prevention, with enhanced hand and respiratory hygiene, testing tracing and isolation strategies and social distancing, will continue to be needed. The findings of this systematic review of publications early in the pandemic suggests that most SARS-CoV-2 infections are not asymptomatic throughout the course of infection.

title: Deep learning COVID-19 detection bias: accuracy through artificial intelligence
abstract: Detection of COVID-19 cases’ accuracy is posing a conundrum for scientists, physicians, and policy-makers. As of April 23, 2020, 2.7 million cases have been confirmed, over 190,000 people are dead, and about 750,000 people are reported recovered. Yet, there is no publicly available data on tests that could be missing infections. Complicating matters and furthering anxiety are specific instances of false-negative tests.  We developed a deep learning model to improve accuracy of reported cases and to precisely predict the disease from chest X-ray scans. Our model relied on convolutional neural networks (CNNs) to detect structural abnormalities and disease categorization that were keys to uncovering hidden patterns. To do so, a transfer learning approach was deployed to perform detections from the chest anterior-posterior radiographs of patients. We used publicly available datasets to achieve this.  Our results offer very high accuracy (96.3%) and loss (0.151 binary cross-entropy) using the public dataset consisting of patients from different countries worldwide. As the confusion matrix indicates, our model is able to accurately identify true negatives (74) and true positives (32); this deep learning model identified three cases of false-positive and one false-negative finding from the healthy patient scans.  Our COVID-19 detection model minimizes manual interaction dependent on radiologists as it automates identification of structural abnormalities in patient’s CXRs, and our deep learning model is likely to detect true positives and true negatives and weed out false positive and false negatives with > 96.3% accuracy.

title: Predicting the receptor-binding domain usage of the coronavirus based on kmer frequency on spike protein

title: How much of SARS-CoV-2 Infections is India detecting? A model-based estimation
abstract: Amid SARS-CoV-2 outbreak, the low number of infections for a population size of 1.38 billion is widely discussed, but with no definite answers.  We used the model proposed by Bommer and Vollmer to assess the quality of official case records. The infection fatality rates were taken from Verity et al (2020). Age distribution of the population for India and states are taken from the Census of India (2011). Reported number of deaths and SARS-CoV-2 confirmed cases from https://www.covid19india.org. The reported numbers of samples tests were collected from the reports of the Indian Council for Medical Research (ICMR).  The findings suggest that India is detecting just 3.6% of the total number of infections with a huge variation across its states. Among 13 states which have more than 100 COVID-19 cases, the detection rate varies from 81.9% (of 410 estimated infections) in Kerala to 0.8% (of 35487 estimated infections) in Madhya Pradesh and 2.4% (of 7431 estimated infections) in Gujarat.  As the study reports a lower number of deaths and higher recovery rates in the states with a high detection rate, thus suggest that India must enhance its testing capacity and go for widespread testing. Late detection puts patients in greater need of mechanical ventilation and ICU care, which imposes greater costs on the health system. The country should also adopt population-level random testing to assess the prevalence of the infection.

title: Trends in Notifiable Infectious Diseases in China: Implications for Surveillance and Population Health Policy
abstract: This study aimed to analyse trends in notifiable infectious diseases in China, in their historical context. Both English and Chinese literature was searched and diseases were categorised according to the type of disease or transmission route. Temporal trends of morbidity and mortality rates were calculated for eight major infectious diseases types. Strong government commitment to public health responses and improvements in quality of life has led to the eradication or containment of a wide range of infectious diseases in China. The overall infectious diseases burden experienced a dramatic drop during 1975–1995, but since then, it reverted and maintained a gradual upward trend to date. Most notifiable diseases are contained at a low endemic level; however, local small-scale outbreaks remain common. Tuberculosis, as a bacterial infection, has re-emerged since the 1990s and has become prevalent in the country. Sexually transmitted infections are in a rapid, exponential growth phase, spreading from core groups to the general population. Together human immunodeficiency virus (HIV), they account for 39% of all death cases due to infectious diseases in China in 2008. Zoonotic infections, such as severe acute respiratory syndrome (SARS), rabies and influenza, pose constant threats to Chinese residents and remain the most deadly disease type among the infected individuals. Therefore, second-generation surveillance of behavioural risks or vectors associated with pathogen transmission should be scaled up. It is necessary to implement public health interventions that target HIV and relevant coinfections, address transmission associated with highly mobile populations, and reduce the risk of cross-species transmission of zoonotic pathogens.

title: Fever and mobility data indicate social distancing has reduced incidence of communicable disease in the United States
abstract: In March of 2020, many U.S. state governments encouraged or mandated restrictions on social interactions to slow the spread of COVID-19, the disease caused by the novel coronavirus SARS-CoV-2 that has spread to nearly 180 countries. Estimating the effectiveness of these social-distancing strategies is challenging because surveillance of COVID-19 has been limited, with tests generally being prioritized for high-risk or hospitalized cases according to temporally and regionally varying criteria. Here we show that reductions in mobility across U.S. counties with at least 100 confirmed cases of COVID-19 led to reductions in fever incidences, as captured by smart thermometers, after a mean lag of 6.5 days ($90\%$ within 3--10 days) that is consistent with the incubation period of COVID-19. Furthermore, counties with larger decreases in mobility subsequently achieved greater reductions in fevers ($p<0.01$), with the notable exception of New York City and its immediate vicinity. These results indicate that social distancing has reduced the transmission of influenza like illnesses, including COVID 19, and support social distancing as an effective strategy for slowing the spread of COVID-19.

title: Prevalence of COVID-19 among patients with rheumatic diseases: the need to await results from large collaborative studies. Response to: 'COVID-19 pneumonia in a large cohort of patients treated with biological and targeted synthetic antirheumatic drugs' by Conticini et al

title: Modeling the Impact of Nationwide BCG Vaccine Recommendations on COVID-19 Transmission, Severity, and Mortality
abstract: COVID-19 was declared as pandemic on 11th March 2020  There are apparent dissimilarities in incidence and mortality of COVID-19 cases in different parts of world. Developing countries in Asia and Africa with fragile health system have shown lower incidence and mortality compared to developed countries with superior health system in Europe and America. Most countries in Asia and Africa have national BCG vaccination program while Europe and America do not have such program, or have ceased it. At present, there is no known therapy to treat COVID-19 disease. There is no vaccine available currently to prevent COVID- 19 disease. As mathematical modelling is ideal for predicting the rate of disease transmission as well as evaluating efficacy of possible public health prevention measures, we have created a mathematical model with seven compartments to understand nationwide BCG vaccine recommendation on COVID-19 transmission, severity and mortality. We have computed two basic reproduction number, one at vaccine free equilibrium point and other at non-vaccine free equilibrium point and carried out local stability, sensitivity and numerical analysis. Our result showed that individuals with BCG vaccinations have lower risk of getting COVID-19 infection, shorter hospital stays, and increased rate of recovery. Furthermore, countries with long-standing universal BCG vaccination policies have reduced incidence, mortality, and severity of COVID-19. Further research will focus on exploring the immediate benefits of vaccination to healthcare workers and patients as well as benefits of BCG re-vaccination.

title: Performance & Quality Evaluation of Marketed COVID-19 RNA Detection Kits
abstract: Compared to other coronaviruses, COVID-19 has a longer incubation period and features asymptomatic infection at a high rate (>25%). Therefore, early detection of infection is the key to early isolation and treatment. Direct detection of the virus itself has advantages over indirect detection. Currently, the most sensitive and commercially validated method for COVID-19 testing is RT-qPCR, designed to detect amplified virus-specific RNA. Reliable testing has proven to be a bottleneck in early diagnosis of virus infection in all countries dealing with the pandemic. Significant performance and quality issues with available testing kits have caused confusion and serious health risks. In order to provide better understanding of the Quality and performance of COVID-19 RNA detection kits on the market, we designed a system to evaluate the specificity (quantitation), sensitivity (LOD) and robustness of the kits using positive RNA and pseudovirus controls based on COVID-19 genomic sequence. We evaluated 8 Nucleic Acid qPCR Kits approved in China, some of which are also approved in the US and EU. Our study showed that half of these 8 kits lack 1:1 linear relationship for virus RNA copy: qPCR signal. Of the 4 with linear response, 2 demonstrated sensitivity at 1 Copy viral RNA/Reaction, suitable for early detection of virus infection. Furthermore, we established the best RNA extraction, handling and qPCR procedures allowing highly sensitive and consistent performance using BGI qPCR kits. Our study provides an effective method to assess and compare performance quality of all COVID-19 nucleic acid testing kits, globally.

title: An interactome map of the nucleocapsid protein from a highly pathogenic North American porcine reproductive and respiratory syndrome virus strain generated using SILAC‐based quantitative proteomics
abstract: Positive strand RNA viruses replicate in the cytoplasm of an infected cell and encode nucleocapsid proteins. These proteins function to promote encapsidation of the RNA genome and virus particle assembly as well as playing potential roles in viral RNA synthesis. Nucleocapsid proteins can also associate with cellular proteins and signaling cascades. The arterivirus nucleocapsid (N) protein is no exception and localizes to both the cytoplasm and the nucleolus in virus‐infected cells. This study generated an interactome map of the N protein from a highly virulent North American strain of porcine reproductive and respiratory syndrome virus (PRRSV). This is a major pathogen of swine resulting in significant morbidity and mortality. Crucial to the study was the use of SILAC coupled to affinity purification using GFP‐traps and LC‐MS/MS. This approach has not been applied before to the investigation of host/viral protein interactomes and this study revealed that the PRRSV N protein interacts with the host cell protein synthesis machinery especially at the level of translation initiation as well as with the RNA post‐transcriptional modification machinery. Applications of the dataset can include studies of virus/host interactions and the design of live attenuated recombinant vaccines.

title: Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria
abstract: On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

title: Prevalence of COVID-19 among patients with rheumatic diseases: the need to await results from large collaborative studies. Response to: 'COVID-19 pneumonia in a large cohort of patients treated with biological and targeted synthetic antirheumatic drugs' by Conticini et al.

title: CDC’s coronavirus test runs into early problems
abstract: Early batches of a kit developed by the US government to diagnose the novel coronavirus infection have been plagued by problems that initially limited their use and cast doubt on their accuracy The problems were first reported by the Washington Post, and C&EN learned soon after that the kits contained faulty reagents that led to inconclusive readouts The Centers for Disease Control and Prevention (CDC) has started an investigation into what exactly went wrong with the tests The CDC designed and manufactured the test kit, which detects the RNA genome of the virus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) The US Food and Drug Administration has approved its use in public health departments nationwide As of March 5, SARS-CoV-2 has killed 10 people in the US and infected nearly 100 Several hundred people have been tested, but the CDC has now stopped reporting testing numbers in favor of [truncated]

title: TUBERCULOUS SARCOIDOSIS: DOES IT EXIST?

title: Acute care issues in internationally adopted children
abstract: Over the past decade there has been a dramatic increase in international adoptions in the United States. While most adopted children will have common illnesses, others may have unique medical issues as a result of the conditions in their birth country requiring a broadened differential diagnosis. Knowledge of these issues is essential in the management of these patients. This review will predominately focus on infectious disease issues commonly seen in international adoptees but will also discuss other medical conditions and some of the psychosocial issues which may be encountered by caregivers in the emergency department.

title: Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT?
abstract: To evaluate the diagnostic value of computed tomography (CT) and real-time reverse-transcriptase-polymerase chain reaction (rRT-PCR) for COVID-19 pneumonia.  This retrospective study included all patients with COVID-19 pneumonia suspicion, who were examined by both CT and rRT-PCR at initial presentation. The sensitivities of both tests were then compared. For patients with a final confirmed diagnosis, clinical and laboratory data, in addition to CT imaging findings were evaluated.  A total of 36 patients were finally diagnosed with COVID-19 pneumonia. Thirty-five patients had abnormal CT findings at presentation, whereas one patient had a normal CT. Using rRT-PCR, 30 patients were tested positive, with 6 cases initially missed. Amongst these 6 patients, 3 became positive in the second rRT-PCR assay(after 2 days, 2 days and 3 days respectively), and the other 3 became positive only in the third round of rRT-PCR tests(after 5 days, 6 days and 8 days respectively). At presentation, CT sensitivity was therefore 97.2%, whereas the sensitivity of initial rRT-PCR was only 83.3%.  rRT-PCR may produce initial false negative results. We suggest that patients with typical CT findings but negative rRT-PCR results should be isolated, and rRT-PCR should be repeated to avoid misdiagnosis.

title: Otorhinolaryngologists and Coronavirus Disease 2019 (COVID-19)

title: National Governance of Public Health Responses in a Pandemic?
abstract: The world is currently facing the worst pandemic in a century and we were caught unprepared. COVID-19 has proven highly contagious and with severe consequences that are still unfolding. As of 16 April 2020, there were over 2 million confirmed cases and over 136,000 related deaths reported worldwide. Over 1 million of those confirmed cases were in the preceding 14 days, with the USA accounting for nearly half of those. Furthermore, the International Monetary Fund (IMF) is now warning that the world is about to suffer the worst economic recession since the Great Depression in the 1920s.

title: The Novel Coronavirus: A Bird's Eye View
abstract: The novel coronavirus (2019-nCoV) outbreak, which initially began in China, has spread to many countries around the globe, with the number of confirmed cases increasing every day. With a death toll exceeding that of the SARS-CoV outbreak back in 2002 and 2003 in China, 2019-nCoV has led to a public health emergency of international concern, putting all health organizations on high alert. Herein, we present on an overview of the currently available information on the pathogenesis, epidemiology, clinical presentation, diagnosis, and treatment of this virus.

title: A Covid-19 case mortality rate without time delay systematics
abstract: Concerning the two approaches to the Covid-19 case mortality rate published in the literature, namely computing the ratio of (a) the daily number of deaths to a time delayed daily number of confirmed infections; and (b) the cumulative number of deaths to confirmed infections up to a certain time, both numbers having been acquired in the middle of an outbreak, it is shown that each suffers from systematic error of a different source. We further show that in the absence of detailed knowledge of the time delay distribution of (a), the true case mortality rate is obtained by pursuing method (b) at the end of the outbreak when the fate of every case has decisively been rendered. The approach is then employed to calculate the mean case mortality rate of 13 regions of China where every case has already been resolved. This leads to a mean rate of 0.527 +/- 0.001 %.

title: Examining the Complex Relationship Between Tuberculosis and Other Infectious Diseases in Children
abstract: Millions of children are exposed to tuberculosis (TB) each year, many of which become infected with Mycobacterium tuberculosis. Most children can immunologically contain or eradicate the organism without pathology developing. However, in a minority, the organism overcomes the immunological constraints, proliferates and causes TB disease. Each year a million children develop TB disease, with a quarter dying. While it is known that young children and those with immunodeficiencies are at increased risk of progression from TB infection to TB disease, our understanding of risk factors for this transition is limited. The most immunologically disruptive process that can happen during childhood is infection with another pathogen and yet the impact of co-infections on TB risk is poorly investigated. Many diseases have overlapping geographical distributions to TB and affect similar patient populations. It is therefore likely that infection with viruses, bacteria, fungi and protozoa may impact on the risk of developing TB disease following exposure and infection, although disentangling correlation and causation is challenging. As vaccinations also disrupt immunological pathways, these may also impact on TB risk. In this article we describe the pediatric immune response to M. tuberculosis and then review the existing evidence of the impact of co-infection with other pathogens, as well as vaccination, on the host response to M. tuberculosis. We focus on the impact of other organisms on the risk of TB disease in children, in particularly evaluating if co-infections drive host immune responses in an age-dependent way. We finally propose priorities for future research in this field. An improved understanding of the impact of co-infections on TB could assist in TB control strategies, vaccine development (for TB vaccines or vaccines for other organisms), TB treatment approaches and TB diagnostics.

title: MATHEMATICAL PREDICTIONS FOR COVID-19 AS A GLOBAL PANDEMIC
abstract: This study shows that the disease free equilibrium (E_0 ) for COVID-19 coronavirus does not satisfy the criteria for a locally or globally asymptotic stability. This implies that as a pandemic as declared by WHO (2020) the COVID-19 coronavirus does not have a curative vaccine yet and precautionary measures are advised through quarantine and observatory procedures. Also, the Basic Reproductive number (R_0<1) by Equation (33) shows that there is a chance of decline of secondary infections when the ratio between the incidence rate in the population and the total number of infected population quarantined with observatory procedure. The effort to evaluate the disease equilibrium shows that unless there is a dedicated effort from government, decision makers and stakeholders, the world would hardly be reed of the COVID-19 coronavirus and further spread is eminent and the rate of infection will continue to increase despite the increased rate of recovery because of the absence of vaccine at the moment.

title: Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters
abstract: With continuous global COVID-19 outbreak, differing case numbers and mortality rates are observed. While actual case numbers appear vague, mortality numbers related to COVID-19 seem more precise. In this study, we used the mortality rate as the main indicator to evaluate the extent of underreporting and underdetection of COVID-19 cases.  We have analyzed all available data provided by the World Health Organization on the development of international COVID-19 cases and mortality numbers on March 17th, 2020. A crude case-fatality risk (cCFR) and adjusted case-fatality risk (aCFR) was calculated for China, South Korea, Japan, Italy, France, Spain, Germany, Iran and the United States. Additionally, a fold-change (FC) was derived for each country.  The highest aCFR and FC were detected for Spain. Based on their FC values, an extremely high number of undetected COVID-19 cases was displayed in France, the United States, Italy and Spain. For these countries, our findings indicate a detection rate of only 1-2% of total actual COVID-19 cases.  Due to limited testing capacities, mortality numbers may serve as a better indicator for COVID-19 case spread in many countries. Our data indicate that countries like France, Italy, the United States, Iran and Spain have extremely high numbers of undetected and underreported cases. Differences in testing availability and capacity, containment as well as overall health care and medical infrastructure result in significantly different mortality rates and COVID-19 case numbers for each respective country.

title: Resumption of activity in gastroenterology departments. Recommendations by SEPD, AEEH, GETECCU and AEG
abstract: The set of measures proposed by SEPD, AEEH, GETECCU and AEG are aimed to help departments in their resumption of usual activity. We have prepared a number of practical recommendations regarding patient management and the stepwise resumption of healthcare activity. These recommendations are based on the sparse, changing evidence available, and will be updated in the future according to daily needs and the availability of expendable materials to suit them; in each department they will be implemented depending upon the cumulative incidence of SARS-CoV-2 infection in each region, and the burden the pandemic has represented for each hospital. The general objectives of these recommendations include: • To protect our patients against the risks of infection with SARS-CoV-2 and to provide them with high-quality care.  To protect all healthcare professionals against the risks of infection with SARS-CoV-2. • To resume normal functioning of our departments in a setting of ongoing risk for infection with SARS-CoV-2.

title: First Complete Genome Sequence of a Feline Alphacoronavirus 1 Strain from Brazil
abstract: We identified a strain of Alphacoronavirus 1, FCoV-SB22, from a pool of fecal samples from domestic cats from a rural settlement in the municipality of Santa Bárbara, Pará, Brazil. The nucleotide identity with feline coronavirus was 91.5%. The present study reports the first complete genome sequence of a feline coronavirus from Brazil.

title: Prevalence and Severity of Coronavirus Disease 2019 (COVID-19) Illness in Symptomatic Pregnant and Postpartum Women Stratified by Hispanic Ethnicity.

title: Optimal timing for social distancing during an epidemic
abstract: Social distancing is an effective way to contain the spread of a contagious disease, particularly when facing a novel pathogen and no pharmacological interventions are available. In such cases, conventional wisdom suggests that social distancing measures should be introduced as soon as possible after the beginning of an outbreak to more effectively mitigate the spread of the disease. Using a simple epidemiological model we show that, however, there is in fact an optimal time to initiate a temporal social distancing intervention if the goal is to reduce the final epidemic size or flatten the epidemic curve. The optimal timing depends strongly on the effective reproduction number (R0) of the disease, such that as the R0 increases, the optimal time decreases non-linearly. Additionally, if pharmacological interventions (e.g., a vaccine) become available at some point during the epidemic, the sooner these interventions become available the sooner social distancing should be initiated to maximize its effectiveness. Although based on a simple model, we hope that these insights inspire further investigations within the context of more complex and data-driven epidemiological models, and can ultimately help decision makers to improve temporal social distancing policies to mitigate the spread of epidemics.

title: Practical insights for paediatric otolaryngology surgical cases and performing microlaryngobronchoscopy during the COVID-19 pandemic
abstract: Paediatric otolaryngology practice involves examining and operating in anatomical locations with high levels of aerosol generation and transmission of COVID-19 to treating clinicians, especially from the asymptomatic patient populations including children. During the COVID-19 pandemic all emergent otolaryngological conditions affecting the airway, oral, and nasal cavities should be managed medically where possible and any operating deferred. We present guidelines for operating on paediatric otolaryngological patients when necessary during the COVID-19 pandemic, and incorporate experience gathered during microlaryngobronchoscopy on a COVID-19 positive infant at our institution.

title: Comparison of risk factors for viral and nonviral asthma exacerbations

title: Difference of coagulation features between severe pneumonia induced by SARS-CoV2 and non-SARS-CoV2
abstract: Severe coronavirus disease 2019 (COVID-19) is commonly complicated with coagulopathy, the difference of coagulation features between severe pneumonia induced by SARS-CoV2 and non-SARS-CoV2 has not been analyzed. Coagulation results and clinical features of consecutive patients with severe pneumonia induced by SARS-CoV2 (COVID group) and non-SARS-CoV2 (non-COVID group) in Tongji hospital were retrospectively analyzed and compared. Whether patients with elevated D-dimer could benefit from anticoagulant treatment was evaluated. There were 449 COVID patients and 104 non-COVID patients enrolled into the study. The 28-day mortality in COVID group was approximately twofold of mortality in non-COVID group (29.8% vs. 15.4%, P = 0.003), COVID group were older (65.1 ± 12.0 vs. 58.4 ± 18.0, years, P < 0.001) and with higher platelet count (215 ± 100 vs. 188 ± 98, ×10(9)/L, P = 0.015), comparing to non-COVID group. The 28-day mortality of heparin users were lower than nonusers In COVID group with D-dimer > 3.0 μg/mL (32.8% vs. 52.4%, P = 0.017). Patients with severe pneumonia induced by SARS-CoV2 had higher platelet count than those induced by non-SARS-CoV2, and only the former with markedly elevated D-dimer may benefit from anticoagulant treatment.

title: A novel coronavirus capable of lethal human infections: an emerging picture
abstract: In September 2012, a novel coronavirus was isolated from a patient in Saudi Arabia who had died of an acute respiratory illness and renal failure. The clinical presentation was reminiscent of the outbreak caused by the SARS-coronavirus (SARS-CoV) exactly ten years ago that resulted in over 8000 cases. Sequence analysis of the new virus revealed that it was indeed a member of the same genus as SARS-CoV. By mid-February 2013, 12 laboratory-confirmed cases had been reported with 6 fatalities. The first 9 cases were in individuals resident in the Middle East, while the most recent 3 cases were in family members resident in the UK. The index case in the UK family cluster had travel history to Pakistan and Saudi Arabia. Although the current evidence suggests that this virus is not highly transmissible among humans, there is a real danger that it may spread to other parts of the world. Here, a brief review of the events is provided to summarize the rapidly emerging picture of this new virus.

title: Severe acute respiratory syndrome-associated coronavirus infection in Toronto children: a second look.
abstract: During the severe acute respiratory syndrome outbreak of 2003, there was an impetus to provide clinical information to the medical community in a timely manner. Accordingly, a preliminary report of our experience of suspected severe acute respiratory syndrome-associated coronavirus infections in children was published without microbiological findings. This report provides an update on pediatric severe acute respiratory syndrome-associated coronavirus infections in Toronto, Ontario, Canada, that includes microbiological findings.  All of the children admitted to the Hospital for Sick Children between March 14 and June 15, 2003, with suspect severe acute respiratory syndrome-associated coronavirus infection were included. A proven case was defined as one that fulfilled the clinical criteria for suspect severe acute respiratory syndrome-associated coronavirus infection and demonstrated a serologic response to severe acute respiratory syndrome-associated coronavirus. Serology results, from a neutralizing antibody assay, were considered positive if the sera inhibited the development of a severe acute respiratory syndrome-associated coronavirus-specific cytopathic effect at a dilution of > or =1:8.  Neutralizing antibody to severe acute respiratory syndrome-associated coronavirus was demonstrated in 8 of 25 children admitted with suspect severe acute respiratory syndrome-associated coronavirus infection. In 3 of these 8 children, severe acute respiratory syndrome-associated coronavirus was also detected by reverse-transcription polymerase chain reaction in the stool. All 8 had documented exposure to > or =1 severe acute respiratory syndrome-associated coronavirus-infected adults residing in the same household. Exposure that was limited to visiting a Toronto hospital at which severe acute respiratory syndrome-associated coronavirus-infected patients were admitted or travel from a country in which severe acute respiratory syndrome had been reported did not result in documented infection in any of our cases. On the basis of our clinical case definition, 6 of 8 microbiologically confirmed case had been classified as having probable severe acute respiratory syndrome-associated coronavirus infection. Clinical disease was mild, nonspecific, and self-limited and was indistinguishable from that reported with other common respiratory viruses.  The factor most strongly associated with severe acute respiratory syndrome-associated coronavirus infection in Toronto children was a history of close contact with an adult severe acute respiratory syndrome-associated coronavirus case. This serves to reinforce the importance of routinely obtaining a thorough epidemiologic travel and exposure history for all subjects with suspected infectious diseases.

title: Knowledge and practices of isolation precautions among nurses in Jordan
abstract: Implementation of isolation precautions from the Centers for Disease Control and Prevention (CDC) has been justified through research and clinical evidence. However, nurses' understanding and compliance with these precautions is still unknown. The aim of this study was to assess nurses' knowledge and practices in relation to isolation precautions in Jordan.  A cross-sectional, descriptive design was used. The study took place in 8 hospitals in Jordan. A self-reported questionnaire and an observational checklist were developed based on the CDC (2007) isolation precautions guidelines.  A total of 247 questionnaires were returned out of 400, for a response rate of 61.7%. The results show that most nurses (90%) have good knowledge of isolation precautions. However, only 65% of nurses reported good compliance with isolation precautions. The results of a t test revealed that nurses with Bachelor's degrees perform better in knowledge examinations than nurses with 2-year diplomas (P < .001). However, there was no significant difference in knowledge and self-report practices scores based on nurses' previous training and existence of isolation guidelines in their units or wards (P > .05). The results of the checklists confirm that there is a low compliance with standard isolation practice. In addition, the checklist shows that a high percentage of units and wards do not use isolation signs (46.4%) and posters (34.5%).  This study revealed that educating nurses about isolation is not enough strategy to improve their compliance. It is important to adapt other strategies, such as supporting nurses by giving them a manageable workload, and providing more supplies and reminders of isolation precautions in the hospitals.

title: Prevalence and clinical features of 2019 novel coronavirus disease (COVID-19) in the Fever Clinic of a teaching hospital in Beijing: a single-center, retrospective study
abstract: With the spread of COVID-19 from Wuhan, Hubei Province to other areas of the country, medical staff in Fever Clinics faced the challenge of identifying suspected cases among patients with respiratory infections manifested with fever. We aimed to describe the prevalence and clinical features of COVID-19 as compared to pneumonias of other etiologies in a Fever Clinic in Beijing.  In this single-center, retrospective study, 342 cases of pneumonia were diagnosed in Fever Clinic in Peking University Third Hospital between January 21 to February 15, 2020. From these patients, 88 were reviewed by panel discussion as possible or probable cases of COVID-19, and received 2019-nCoV detection by RT-PCR. COVID-19 was confirmed by positive 2019-nCoV in 19 cases, and by epidemiological, clinical and CT features in 2 cases (the COVID-19 Group, n=21), while the remaining 67 cases served as the non-COVID-19 group. Demographic and epidemiological data, symptoms, laboratory and lung CT findings were collected, and compared between the two groups.  The prevalence of COVID-19 in all pneumonia patients during the study period was 6.14% (21/342). Compared with the non-COVID-19 group, more patients with COVID-19 had an identified epidemiological history (90.5% versus 32.8%, P<0.001). The COVID-19 group had lower WBC [5.19×10^9/L (±1.47) versus 7.21×10^9/L (±2.94), P<0.001] and neutrophil counts [3.39×10^9/L (±1.48) versus 5.38×10^9/L (±2.85), P<0.001] in peripheral blood. However, the percentage and count of lymphocytes were not different. On lung CT scans, involvement of 4 or more lobes was more common in the COVID-19 group (45% versus 16.4%, P=0.008).  In the period of COVID-19 epidemic outside Hubei Province, the prevalence of COVID-19 in patients with pneumonia visiting to our Fever Clinic in Beijing was 6.14%. Epidemiological evidence was important for prompt case finding, and lower blood WBC and neutrophil counts may be useful for differentiation from pneumonia of other etiologies.

title: Emerging Polynomial Growth Trends in COVID-19 Pandemic Data and Their Reconciliation with Compartment Based Models
abstract: We study the reported data from the COVID-19 pandemic outbreak in January - May 2020 in 119 countries. We observe that the time series of active cases in individual countries (the difference of the total number of confirmed infections and the sum of the total number of reported deaths and recovered cases) display a strong agreement with polynomial growth and at a later epidemic stage also with a combined polynomial growth with exponential decay. Our results are also formulated in terms of compartment type mathematical models of epidemics. Within these models the universal scaling characterizing the observed regime in an advanced epidemic stage can be interpreted as an algebraic decay of the relative reproduction number $R_0$ as $T_M/t$, where $T_M$ is a constant and $t$ is the duration of the epidemic outbreak. We show how our findings can be applied to improve predictions of the reported pandemic data and estimate some epidemic parameters. Note that although the model shows a good agreement with the reported data we do not make any claims about the real size of the pandemics as the relation of the observed reported data to the total number of infected in the population is still unknown.

title: Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study
abstract: Middle East respiratory syndrome (MERS) is a new human disease caused by a novel coronavirus (CoV). Clinical data on MERS-CoV infections are scarce. We report epidemiological, demographic, clinical, and laboratory characteristics of 47 cases of MERS-CoV infections, identify knowledge gaps, and define research priorities.  We abstracted and analysed epidemiological, demographic, clinical, and laboratory data from confirmed cases of sporadic, household, community, and health-care-associated MERS-CoV infections reported from Saudi Arabia between Sept 1, 2012, and June 15, 2013. Cases were confirmed as having MERS-CoV by real-time RT-PCR. Findings 47 individuals (46 adults, one child) with laboratory-confirmed MERS-CoV disease were identified; 36 (77%) were male (male:female ratio 3·3:1). 28 patients died, a 60% case-fatality rate. The case-fatality rate rose with increasing age. Only two of the 47 cases were previously healthy; most patients (45 [96%]) had underlying comorbid medical disorders, including diabetes (32 [68%]), hypertension (16 [34%]), chronic cardiac disease (13 [28%]), and chronic renal disease (23 [49%]). Common symptoms at presentation were fever (46 [98%]), fever with chills or rigors (41 [87%]), cough (39 [83%]), shortness of breath (34 [72%]), and myalgia (15 [32%]). Gastrointestinal symptoms were also frequent, including diarrhoea (12 [26%]), vomiting (ten [21%]), and abdominal pain (eight [17%]). All patients had abnormal findings on chest radiography, ranging from subtle to extensive unilateral and bilateral abnormalities. Laboratory analyses showed raised concentrations of lactate dehydrogenase (23 [49%]) and aspartate aminotransferase (seven [15%]) and thrombocytopenia (17 [36%]) and lymphopenia (16 [34%]).  Disease caused by MERS-CoV presents with a wide range of clinical manifestations and is associated with substantial mortality in admitted patients who have medical comorbidities. Major gaps in our knowledge of the epidemiology, community prevalence, and clinical spectrum of infection and disease need urgent definition.

title: The Efficacy and Safety of Fecal Microbiota Transplant for Recurrent Clostridiumdifficile Infection: Current Understanding and Gap Analysis
abstract: The leading risk factor for Clostridioides (Clostridium) difficile infection (CDI) is broad-spectrum antibiotics, which lead to low microbial diversity, or dysbiosis. Current therapeutic strategies for CDI are insufficient, as they do not address the key role of the microbiome in preventing C. difficile spore germination into toxin-producing vegetative bacteria, which leads to symptomatic disease. Fecal microbiota transplant (FMT) appears to reduce the risk of recurrent CDI through microbiome restoration. However, a wide range of efficacy rates have been reported, and few placebo-controlled trials have been conducted, limiting our understanding of FMT efficacy and safety. We discuss the current knowledge gaps driven by questions around the quality and consistency of clinical trial results, patient selection, diagnostic methodologies, use of suppressive antibiotic therapy, and methods for adverse event reporting. We provide specific recommendations for future trial designs of FMT to provide improved quality of the clinical evidence to better inform treatment guidelines.

title: 2018 ACCP Global Conference on Clinical Pharmacy: October 20–23, 2018

title: COVID-19 Drug Discovery Using Intensive Approaches
abstract: Since the infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reported in China during December 2019, the coronavirus disease 2019 (COVID-19) has spread on a global scale, causing the World Health Organization (WHO) to issue a warning. While novel vaccines and drugs that target SARS-CoV-2 are under development, this review provides information on therapeutics which are under clinical trials or are proposed to antagonize SARS-CoV-2. Based on the information gained from the responses to other RNA coronaviruses, including the strains that cause severe acute respiratory syndrome (SARS)-coronaviruses and Middle East respiratory syndrome (MERS), drug repurposing might be a viable strategy. Since several antiviral therapies can inhibit viral replication cycles or relieve symptoms, mechanisms unique to RNA viruses will be important for the clinical development of antivirals against SARS-CoV-2. Given that several currently marketed drugs may be efficient therapeutic agents for severe COVID-19 cases, they may be beneficial for future viral pandemics and other infections caused by RNA viruses when standard treatments are unavailable.

title: Syndromic Surveillance for COVID-19 in Canada
abstract: Syndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada.  Data sources consisted of two distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups.  We found that 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month over March-April 2020. Across the three surveys, SARS-CoV-2-testing was reported in 2-9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Metis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath.  The low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of current SARS-CoV-2 testing rates.

title: Coronavirus Infection Among Children and Adolescents
abstract: Coronavirus infection is a global emergency. Over the past few months, there is a rapid increase in the number of cases and deaths due to coronavirus infection. It has been observed that elderly individuals and those with medical co-morbidities are maximally affected. In children and adolescents, coronavirus infection has low mortality as well as the severity of symptoms are less. Children and adolescents with immunocompromised state, malnutrition, medical co-morbidities and poor hygiene are at higher risk of contracting coronavirus infection. Minimizing this risk factors and adopting appropriate prevention measures will be helpful in limiting the spread of infection as there is no specific treatment and immunization available to date to address this serious issue. This chapter highlights the issues and challenges of coronavirus infection in children and adolescents.

title: How many are at increased risk of severe COVID-19 disease? Rapid global, regional and national estimates for 2020
abstract: The risk of severe COVID-19 disease is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 illness, and how this varies between countries may inform the design of possible strategies to shield those at highest risk.  We estimated the number of individuals at increased risk of severe COVID-19 disease by age (5-year age groups), sex and country (n=188) based on prevalence data from the Global Burden of Disease (GBD) study for 2017 and United Nations population estimates for 2020. We also calculated the number of individuals without an underlying condition that could be considered at-risk because of their age, using thresholds from 50-70 years. The list of underlying conditions relevant to COVID-19 disease was determined by mapping conditions listed in GBD to the guidelines published by WHO and public health agencies in the UK and US. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity.  We estimate that 1.7 (1.0 - 2.4) billion individuals (22% [15-28%] of the global population) are at increased risk of severe COVID-19 disease. The share of the population at increased risk ranges from 16% in Africa to 31% in Europe. Chronic kidney disease (CKD), cardiovascular disease (CVD), diabetes and chronic respiratory disease (CRD) were the most prevalent conditions in males and females aged 50+ years. African countries with a high prevalence of HIV/AIDS and Island countries with a high prevalence of diabetes, also had a high share of the population at increased risk. The prevalence of multimorbidity (>1 underlying conditions) was three times higher in Europe than in Africa (10% vs 3%).  Based on current guidelines and prevalence data from GBD, we estimate that one in five individuals worldwide has a condition that is on the list of those at increased risk of severe COVID-19 disease. However, for many of these individuals the underlying condition will be undiagnosed or not severe enough to be captured in health systems, and in some cases the increase in risk may be quite modest. There is an urgent need for robust analyses of the risks associated with different underlying conditions so that countries can identify the highest risk groups and develop targeted shielding policies to mitigate the effects of the COVID-19 pandemic.

title: Scaling features in the spreading of COVID-19
abstract: Since the outbreak of COVID-19, many data analyses have been done. Some of them are based on the classical epidemiological approach that assumes an exponential growth, but a few studies report that a power-law scaling may provide a better fit to the currently available data. Hereby, we examine the data in China (01/20/2020--02/24/2020), and indeed find that the growth closely follows a power-law kinetics over a significantly wide time period. The exponents are $2.48(20)$, $2.21(6)$ and $4.26(12)$ for the number of confirmed infections, deaths and cured cases, respectively, indicating an underlying small-world network structure in the pandemic. While no obvious deviations from the power-law growth can be seen yet for the number of deaths and cured cases, negative deviations have clearly appeared in the number of infections, particularly that for the region outside Hubei. This suggests the beginning of the slowing-down of the virus spreading due to the huge containment effort. Meanwhile, we find that despite the dramatic difference in magnitudes, the growth kinetics of the infection number exhibits much similarity for Hubei province and the region outside Hubei. On this basis, in log-log plot, we rescale the infection number for the region outside Hubei such that it overlaps as much as possible with the total infection number in China, from which an approximate extrapolation yields the maximum of the pandemic around March 3, 2020, with the number of infections about $83,000$. Further, by analyzing the kinetics of the mortality in log-log scale, we obtains a rough estimate that near March 3, the death rate of COVID-19 would be about $4.7\%\thicksim 5.0\%$ for Hubei province and $0.7\%\thicksim1.0\%$ for the region outside Hubei. We emphasize that our predictions may be quantitatively unreliable, since the data analysis is purely empirical and various assumptions are used.

title: Estimation of true number of COVID-19 infected people in Japan using LINE questionnaire
abstract: The authors estimated the true number of COVID-19 infected people in Japan using the LINE questionnaire data and the PCR test results. A statistically significant correlation was observed between the infection rate per prefecture with PCR test and the rate of high fever. Using this correlation, true number of COVID-19 infected people in Japan was estimated approximately twenty thousand (+/− ten thousand) as of April 1, 2020.

title: Testing COVID-19 tests faces methodological challenges
abstract: In battling the COVID-19 pandemic, testing is essential. The detection of viral RNA allows the identification of infected persons, while the detection of antibodies may reveal a response to a previous infection. Tests for coronavirus should be rigorously evaluated in terms of their analytical and clinical performance. This poses not only logistic challenges, but also methodological ones. Some of these are generic for the diagnostic accuracy paradigm, while others are more specific for tests for viruses. Problematic for evaluations of the clinical performance of tests for viral RNA is the absence of an independent reference standard. Many studies lack rigor in terms of the recruitment of study participants. Study reports are often insufficiently informative, which makes it difficult to assess the applicability of study findings. Attempts to summarize the performance of these tests in terms of a single estimate of the clinical sensitivity fails to do justice to the identifiable sources of the large heterogeneity in mechanisms for generating false negative results.

title: Spatial and Temporal Epidemiology of Lumpy Skin Disease in the Middle East, 2012–2015
abstract: Lumpy skin disease virus (LSDV) is an infectious disease of cattle that can have severe economic implications. New LSD outbreaks are currently circulating in the Middle East (ME). Since 2012, severe outbreaks were reported in cattle across the region. Characterizing the spatial and temporal dynamics of LSDV in cattle populations is prerequisite for guiding successful surveillance and control efforts at a regional level in the ME. Here, we aim to model the ecological niche of LSDV and identify epidemic progression patterns over the course of the epidemic. We analyzed publically available outbreak data from the ME for the period 2012–2015 using presence-only maximum entropy ecological niche modeling and the time-dependent method for the estimation of the effective reproductive number (R-TD). High-risk areas (probability >0.60) for LSDV identified by ecological niche modeling included parts of many northeastern ME countries, though Israel and Turkey were estimated to be the most suitable locations for occurrence of LSDV outbreaks. The most important environmental predictors that contributed to the ecological niche of LSDV included annual precipitation, land cover, mean diurnal range, type of livestock production system, and global livestock densities. Average monthly effective R-TD was equal to 2.2 (95% CI: 1.2, 3.5), whereas the largest R-TD was estimated in Israel (R-TD = 22.2, 95 CI: 15.2, 31.5) in September 2013, which indicated that the demographic and environmental conditions during this period were suitable to LSDV super-spreading events. The sharp drop of Isreal’s inferred R-TD in the following month reflected the success of their 2013 vaccination campaign in controlling the disease. Our results identified areas in which underreporting of LSDV outbreaks may have occurred. More epidemiological information related to cattle populations are needed to further improve the inferred spatial and temporal characteristics of currently circulating LSDV. However, the methodology presented here may be useful in guiding the design of risk-based surveillance and control programs in the region as well as aid in the formulation of epidemic preparedness plans in neighboring LSDV-free countries.

title: Endemic Melioidosis in Southern China: Past and Present
abstract: Melioidosis is a severe tropical infectious disease caused by the soil-dwelling bacterium Burkholderia pseudomallei, predominantly endemic to Southeast Asia and northern Australia. Between the 1970s and the 1990s, the presence of B. pseudomallei causing melioidosis in humans and other animals was demonstrated in four coastal provinces in southern China: Hainan, Guangdong, Guangxi, and Fujian, although indigenous cases were rare and the disease failed to raise concern amongst local and national health authorities. In recent years, there has been a rise in the number of melioidosis cases witnessed in the region, particularly in Hainan. Meanwhile, although China has established and maintained an effective communicable disease surveillance system, it has not yet been utilized for melioidosis. Thus, the overall incidence, social burden and epidemiological features of the disease in China remain unclear. In this context, we present a comprehensive overview of both historical and current information on melioidosis in Southern China, highlighting the re-emergence of the disease in Hainan. Surveillance and management strategies for melioidosis should be promoted in mainland China, and more research should be conducted to provide further insights into the present situation.

title: Level of underreporting including underdiagnosis before the first peak of COVID-19 in various countries: Preliminary retrospective results based on wavelets and deterministic modeling

title: Estimation of the actual disease occurrence based on official case numbers during a COVID outbreak in Germany 2020
abstract: Since the beginning of March 2020, the cumulative numbers of cases of infection with the novel coronavirus SARS-CoV-2 in Germany have been reported on a daily basis. The reports originate from national laws, according to which positive test findings must be submitted to the Federal Health Authorities, the Robert Koch Institute, via the local health authorities. Since an enormous number of unreported cases can be expected, the question of how widespread the disease has been in the population cannot be answered based on these administrative reports. Using mathematical modeling, however, estimates can be made. These estimates indicate that the small numbers of diagnostic tests carried out at the beginning of the outbreak overlooked considerable parts of the infection. In order to cover the initial phase of future waves of the disease, wide-spread and comprehensive tests are recommended.

title: Propagation, inactivation, and safety testing of SARS-CoV-2
abstract: In late 2019, a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, the capital of the Chinese province Hubei. Since then, SARS-CoV-2 has been responsible for a worldwide pandemic resulting in over 4 million infections and over 250,000 deaths. The pandemic has instigated widespread research related to SARS-CoV-2 and the disease that it causes, COVID-19. Research into this new virus will be facilitated by the availability of clearly described and effective procedures that enable the propagation and quantification of infectious virus. Because work with the virus is recommended to be performed at biosafety level 3, validated methods to effectively inactivate the virus to enable safe study of RNA, DNA and protein from infected cells are also needed. Here, we report methods used to grow SARS-CoV-2 in multiple cell lines and to measure virus infectivity by plaque assay using either agarose or microcrystalline cellulose as an overlay as well as a SARS-CoV-2 specific focus forming assay. We also demonstrate effective inactivation by TRIzol, 10% neutral buffered formalin, beta propiolactone, and heat.

title: Doubling time tells how effective Covid-19 prevention works
abstract: Covid-19 (coronavirus disease 2019) is a rapidly spreading pandemic in many countries. The total confirmed cases of Covid-19 are exponentially increasing and many countries are fighting Covid-19 with all strategies. However, there is still lacking consensus for effective strategies. Here, I demonstrate the time dependence of the doubling time in the Covid-19 exponential growths. Tracking the time-dependent doubling time tells how well Covid-19 prevention works, giving an index for successful fighting.

title: Comparative Analysis of COVID-19 Transmission Patterns in Three Chinese Regions vs. South Korea,Italy and Iran
abstract: The outbreak of Coronavirus 2019 (COVID-19) began in January 2020 in the city of Wuhan (Hubei province, China). It took about 2 months for China to get this infectious disease under control in its epicenter at Wuhan. Since February 2020, COVID-19 has been spreading around the world, becoming widespread in a number of countries. The timing and nature of government actions in response to the pandemic has varied from country to country, and their role in affecting the spread of the disease has been debated.  The present study proposed a modified susceptible-exposed-infected-removed model (SEIR) model to perform a comparative analysis of the temporal progress of disease spread in six regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). For each region we developed detailed timelines of reported infections and outcomes, along with government-implemented measures to enforce social distancing. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries.  The main results of this study are as follows: (a) an empirical COVID-19 growth law provides an excellent fit to the disease data in all study regions and potentially could be of more general validity; (b) significant differences exist in the spread characteristics of the disease among the three regions of China and between the three regions of China and the three countries; (c) under the control measures implemented in the Chinese regions (including the immediate quarantine of infected patients and their close contacts, and considerable restrictions on social contacts), the transmission rate of COVID-19 followed a modified normal distribution function, and it reached its peak after 1 to 2 days and then was reduced to zero 11, 11 and 18 days after a 1st-Level Response to Major Public Health Emergency was declared in Zhejiang, Guangdong and Xinjiang, respectively; moreover, the epidemic control times in Zhejiang, Guangdong and Xinjiang showed that the epidemic reached an "inflection point" after 9, 12 and 17 days, respectively, after a 1st-Level Response was issued; (d) an empirical COVID-19 law provided an excellent fit to the disease data in the six study regions, and the law can be potentially of more general validity; and (e) the curves of infected cases in South Korea, Italy and Iran would had been significantly flattened and shrunken at a relatively earlier stage of the epidemic if similar preventive measures as in the Chinese regions had been also taken in the above three countries on February 25th, February 25th and March 8th, respectively: the simulated maximum number of infected individuals in South Korea, Italy and Iran would had been 4480 cases (March 9th, 2020), 2335 cases (March 10th) and 6969 cases (March 20th), instead of the actual (reported) numbers of 7212 cases (March 9th), 8514 cases (March 10th, 2020) and 11466 cases (March 20th), respectively; moreover, up to March 29th, the simulated reduction in the accumulated number of infected cases would be 1585 for South Korea, 93490 for Italy and 23213 for Iran, respectively, accounting for 16.41% (South Korea), 95.70% (Italy) and 60.59% (Iran) of the accumulated number of actual reported infected cases.  The implemented measures in China were very effective for controlling the spread of COVID-19. These measures should be taken as early as possible, including the early identification of all infection sources and eliminating transmission pathways. Subsequently, the number of infected cases can be controlled at a low level, and existing medical resources could be sufficient for maintaining higher cure rates and lower mortality rate compared to the current situations in these countries. The proposed model can account for these prevention and control measures by properly adjusting its parameters, it computes the corresponding variations in disease transmission rate during the outbreak period, and it can provide valuable information for public health decision-making purposes.

title: Multiple drivers of the COVID-19 spread: role of climate, international mobility, and region-specific conditions
abstract: The novel Coronavirus Disease 2019 (COVID-19) has spread quickly across the globe. Here, we evaluated the role of climate (temperature and precipitation), region-specific susceptibility (BCG vaccination, malaria infection, and elderly population) and international traveller population (human mobility) in shaping the geographical patterns of COVID-19 cases across 1,055 countries/regions, and examined the sequential shift of multiple drivers of the accumulated cases from December, 2019 to April 12, 2020. The accumulated numbers of COVID-19 cases (per 1 million population) were well explained by a simple regression model. The explanatory power (R2) of the model increased up to > 70% in April 2020 as the COVID-19 spread progressed. Climate, host mobility, and host susceptibility largely explained the variance of the COVID-19 cases (per 1 million population), and their explanatory power improved as the pandemic progressed; the relative importance of host mobility and host susceptibility have been greater than that of climate. The number of days from outbreak onset showed greater explanatory power in the earlier stages of COVID-19 spread but rapidly lost its influence. Our findings demonstrate that the COVID-19 pandemic is deterministically driven by climate suitability, cross-border human mobility, and region-specific susceptibility. The present distribution of COVID-19 cases has not reached an equilibrium and is changing daily, especially in the Southern Hemisphere. Nevertheless, the present results, based on mapping the spread of COVID-19 and identifying multiple drivers of this outbreak trajectory, may contribute to a better understanding of the COVID-19 disease transmission risk and the measures against long-term epidemic.

title: Emergency Medical Services resource capacity and competency amid COVID-19 in the United States: Preliminary findings from a national survey
abstract: This study aimed to investigate available resources, Personal Protective Equipment (PPE) availability, sanitation practices, institutional policies, and opinions among EMS professionals in the United States amid the COVID-19 pandemic using a self-report survey questionnaire.  An online 42-question multiple choice survey was randomly distributed between April 1, 2020, and April 16, 2020 to various active Emergency Medical Services (EMS) paid personnel in all 50 U.S. states including the District of Columbia (n=192). We approximate a 95% confidence interval (± 0.07).  An overwhelming number of EMS providers report having limited access to N95 respirators, receiving little or no benefits from COVID-19 related work, and report no institutional policy on social distancing practices despite CDC recommendations. For providers who do have access to N95 respirators, 31% report having to use the same mask for 1 week or longer. Approximately ⅓ of the surveyed participants were unsure of when a COVID-19 patient is infectious. The data suggests regular decontamination of EMS equipment after each patient contact is not a regular practice.  Current practices to educate EMS providers on appropriate response to the novel coronavirus may not be sufficient, and future patients may benefit from a nationally established COVID-19 EMS response protocol. Further investigation on whether current EMS practices are contributing to the spread of infection is warranted. The data reveals concerning deficits in COVID-19 related education and administrative protocols which pose as a serious public health concern that should be urgently addressed.

title: Application of pooled testing in screening and estimating the prevalence of Covid-19
abstract: The recent emergence of the COVID-19 pandemic has posed an unprecedented healthcare challenge and catastrophic economic and social consequences to the countries across the world. The situation is even worse for emerging economies like India. WHO recommends mass scale testing as one of the most effective ways to contain its spread and fight the pandemic. But, due to the high cost and shortage of test kits, specifically in India, the testing is restricted to only those who are symptomatic. In this context, pooled testing is recommended by some experts as a partial solution to overcome this problem. In this article, we explain the basic statistical theory behind the pooled testing procedure for screening as well as prevalence estimation. In real world situations, the tests are imperfect, and lead to false positive and false negative results. We provide theoretical explanation of the impact of these diagnostic errors on the performances of individual testing and pooled testing procedures. Finally, we study the effect of misspecification of sensitivity and specificity of tests on the estimate of prevalence, an issue, which is debated a lot among the scientists in the context of COVID-19. Our theoretical investigations lead to some interesting and precise understanding of some of these issues.

title: Early recovery following new onset anosmia during the COVID-19 pandemic – an observational cohort study
abstract: A rapidly evolving evidence suggests that smell and taste disturbance are common symptoms in COVID-19 infection. As yet there are no reports on duration and recovery rates. We set out to characterise patients reporting new onset smell and taste disturbance during the COVID-19 pandemic and report on early recovery rates.  Online Survey of patients reporting self-diagnosed new onset smell and taste disturbance during the COVID-19 pandemic, with 1 week follow-up.  Three hundred eighty-two patents completed bot an initial and follow-up survey. 86.4% reported complete anosmia and a further 11.5% a very severe loss of smell at the time of completing the first survey. At follow-up 1 week later, there is already significant improvement in self-rating of severity of olfactory loss. 80.1% report lower severity scores at follow-up, 17.6% are unchanged and 1.9% are worse. 11.5% already report compete resolution at follow up, while 17.3% report persistent complete loss of smell, with reported duration being 1 to over 4 weeks. This is reflected in the overall cumulative improvement rate of 79% patients overall in the interval between surveys.  A review of the growing evidence base supports the likelihood that out cohort have suffered olfactory loss as part of COVID-19 infection. While early recovery rates are encouraging, long term rates will need to be further investigated and there may be an increase in patients with persistent post-viral loss as a result of the pandemic. We further call for loss of sense of smell to be formerly recognised as a marker of COVID-19 infection.

title: Case fatality rate in COVID-19: a systematic review and meta-analysis
abstract: Estimating the prevalence of severe or critical illness and case fatality of COVID-19 outbreak in December, 2019 remains a challenge due to biases associated with surveillance, data synthesis and reporting. We aimed to address this limitation in a systematic review and meta-analysis and to examine the clinical, biochemical and radiological risk factors in a meta-regression.  PRISMA guidelines were followed. PubMed, Scopus and Web of Science were searched using pre-specified keywords on March 07, 2020. Peer-reviewed empirical studies examining rates of severe illness, critical illness and case fatality among COVID-19 patients were examined. Numerators and denominators to compute the prevalence rates and risk factors were extracted. Random-effects meta-analyses were performed. Results were corrected for publication bias. Meta-regression analyses examined the moderator effects of potential risk factors.  The meta-analysis included 29 studies representing 2,090 individuals. Pooled rates of severe illness, critical illness and case fatality among COVID-19 patients were 15%, 5% and 0.8% respectively. Adjusting for potential underreporting and publication bias, increased these estimates to 26%, 16% and 7.4% respectively. Increasing age and elevated LDH consistently predicted severe / critical disease and case fatality. Hypertension; fever and dyspnea at presentation; and elevated CRP predicted increased severity.  Risk factors that emerged in our analyses predicting severity and case fatality should inform clinicians to define endophenotypes possessing a greater risk. Estimated case fatality rate of 7.4% after correcting for publication bias underscores the importance of strict adherence to preventive measures, case detection, surveillance and reporting.

title: Prevalence and Severity of Coronavirus Disease 2019 (COVID-19) Illness in Symptomatic Pregnant and Postpartum Women Stratified by Hispanic Ethnicity

title: Acute‐onset smell and taste disorders in the context of COVID‐19: a pilot multicentre polymerase chain reaction based case–control study
abstract: Specific respiratory tract infections, including COVID‐19, may cause smell and/or taste disorders (STDs) with increased frequency. The aim was to determine whether new‐onset STDs are more frequent amongst COVID‐19 patients than influenza patients.  This was a case–control study including hospitalized patients of two tertiary care centres. Consecutive patients positive for COVID‐19 polymerase chain reaction (cases) and patients positive for influenza polymerase chain reaction (historical control sample) were assessed during specific periods, employing a self‐reported STD questionnaire.  Seventy‐nine cases and 40 controls were included. No significant differences were found in basal features between the two groups. New‐onset STDs were significantly more frequent amongst cases (31, 39.2%) than in the control group (5, 12.5 %) [adjusted odds ratio 21.4 (2.77–165.4, P = 0.003)]. COVID‐19 patients with new‐onset STDs were significantly younger than COVID‐19 patients without STDs (52.6 ± 17.2 vs. 67.4 ± 15.1, P < 0.001). Amongst COVID‐19 patients who presented STDs, 22 (70.9%) recalled an acute onset and it was an initial manifestation in 11 (35.5%). Twenty‐five (80.6%) presented smell disorders (mostly anosmia, 14, 45.2%) and 28 (90.3%) taste disorders (mostly ageusia, 14, 45.2%). Only four (12.9 %) reported concomitant nasal obstruction. The mean duration of STD was 7.5 ± 3.2 days and 12 patients (40%) manifested complete recovery after 7.4 ± 2.3 days of onset.  New‐onset STDs were significantly more frequent amongst COVID‐19 patients than influenza patients; they usually had an acute onset and were commonly an initial manifestation. The use of STD assessment in anamnesis as a hint for COVID‐19 and to support individuals’ self‐isolation in the current epidemic context is suggested.

title: Network structure of COVID-19 spread and the lacuna in India's testing strategy
abstract: We characterize the network of COVID-19 spread in India and find that the transmission rate is 0.43, with daily case growth driven by individuals who contracted the virus abroad. We explore the question of whether this represents exponentially decaying dynamics or is simply an artefact of India's testing strategy. Testing has largely been limited to individuals travelling from high-risk countries and their immediate contacts, meaning that the network reflects positive identifications from a biased testing sample. Given generally low levels of testing and an almost complete absence of testing for community spread, there is significant risk that we may be missing out on the actual nature of outbreak. India still has an apparently low current caseload, with possibly a small window of time to act, and should therefore aggressively and systematically expand random testing for community spread, including for asymptomatic cases. This will help understand true transmission characteristics and plan appropriately for the immediate future.

title: Estimating the number of SARS-CoV-2 infections and the impact of social distancing in the United States
abstract: Understanding the number of individuals who have been infected with the novel coronavirus SARS-CoV-2, and the extent to which social distancing policies have been effective at limiting its spread, are critical for effective policy going forward. Here we present estimates of the extent to which confirmed cases in the United States undercount the true number of infections, and analyze how effective social distancing measures have been at mitigating or suppressing the virus. Our analysis uses a Bayesian model of COVID-19 fatalities with a likelihood based on an underlying differential equation model of the epidemic. We provide analysis for four states with significant epidemics: California, Florida, New York, and Washington. Our short-term forecasts suggest that these states may be following somewhat different trajectories for growth of the number of cases and fatalities.

title: Major testing issues in US
abstract: Delays and restrictions on who can be tested for the covid-19 virus in the US have raised the risk that it is spreading undetected, reports Colin Barras

title: L’apnée du sommeil : une maladie ou un syndrome ?

title: A glance at the prevalence of coronavirus disease 19 (COVID-19) in Iran: Strengths and weaknesses

title: Risks of Novel Coronavirus Disease (COVID-19) in Pregnancy; a Narrative Review
abstract: The outbreak of the new Coronavirus in China in December 2019 and subsequently in various countries around the world has raised concerns about the possibility of vertical transmission of the virus from mother to fetus. The present study aimed to review published literature in this regard.  In this narrative review, were searched for all articles published in various databases including PubMed, Scopus, Embase, Science Direct, and Web of Science using MeSH-compliant keywords including COVID-19, Pregnancy, Vertical transmission, Coronavirus 2019, SARS-CoV-2 and 2019-nCoV from December 2019 to March 18, 2020 and reviewed them. All type of articles published about COVID-19 and vertical transmission in pregnancy were included.  A review of 13 final articles published in this area revealed that COVID-19 can cause fetal distress, miscarriage, respiratory distress and preterm delivery in pregnant women but does not infect newborns. There has been no report of vertical transmission in pregnancy, and it has been found that clinical symptoms of COVID-19 in pregnant women are not different from those of non-pregnant women.  Overall, due to lack of appropriate data about the effect of COVID-19 on pregnancy, it is necessary to monitor suspected pregnant women before and after delivery. For confirmed cases both the mother and the newborn child should be followed up comprehensively.

title: SEROEPIDEMIOLOGIC STUDIES OF CORONAVIRUS INFECTION IN ADULTS AND CHILDREN(1)
abstract: McIntosh, K. A. Z. Kapikian, H. C Turner, J. W. Hartley, R. H. Parrott and R. M. Chanock. A seroepidemiologic study of infection by coronavirus strains 229E, OC38, OC43, and mouse hepatitis virus (MHV) strain A-59, is described. In adults with upper respiratory disease, two “outbreaks” of coronavirus infection occurred, one during the winter of 1965–1966 associated with complement fixing (CF) antibody responses to OC38, OC43 and MHV, and the other during the following winter associated with CF antibody responses to 229E. In hospitalized children, infection with 229E was rare; infection with OC38, OC43, and MHV occurred less often in hospitalized children with lower respiratory tract disease (3.5%) than in a control group with non-respiratory tract disease (8.2%). The limitations of the CF test using available coronavirus antigens are discussed.

title: Can N95 respirators be reused after disinfection? And for how many times?
abstract: The Coronavirus Disease 2019 (COVID-19) pandemic has led to a major shortage of N95 respirators, which protect healthcare professionals and the public who may come into contact with the virus. It is necessary to determine the conditions that would allow the safe reuse respirators and personal protection in this crisis. We found that heating (<100 {degrees}C) under various humidities (up to 100% RH at 75 {degrees}C) and ultraviolet (UV) irradiation were the most promising candidates for mask reuse in the modern hospital infrastructure (up to 20 cycles), when tested on a fabric with particle filtration efficiency [≥]95%. Treatments involving certain liquids and vapors may require caution, as steam, alcohol, and bleach all led to degradation in filtration efficiency, leaving the user vulnerable to viral aerosols.

title: Ultrasound-Assisted Versus Landmark-Guided Spinal Anesthesia in Patients With Abnormal Spinal Anatomy: A Randomized Controlled Trial.
abstract: Spinal anesthesia using a surface landmark-guided technique can be challenging in patients with anatomical alterations of the lumbar spine; however, it is unclear whether using ultrasonography can decrease the technical difficulties in these populations. We assessed whether an ultrasound-assisted technique could reduce the number of needle passes required for block success compared with the landmark-guided technique in patients with abnormal spinal anatomy.  Forty-four patients with abnormal spinal anatomy including documented lumbar scoliosis and previous spinal surgery were randomized to receive either surface landmark-guided or preprocedural ultrasound-assisted spinal anesthesia. All spinal procedures were performed by 1 of 3 experienced anesthesiologists. The primary outcome was the number of needle passes required for successful dural puncture. Secondary outcomes included the success rate on the first pass, total procedure time, periprocedural pain scores, and the incidences of radicular pain, paresthesia, and bloody tap during the neuraxial procedure. Intergroup difference in the primary outcome was assessed for significance using Mann-Whitney U test.  The median (interquartile range [IQR; range]) number of needle passes was significantly lower in the ultrasound group than in the landmark group (ultrasound 1.5 [1-3 {1-5}]; landmark 6 [2-9.3 {1-15}]; P < .001). First-pass success was achieved in 11 (50.0%) and 2 (9.1%) patients in the ultrasound and landmark groups, respectively (P = .007). The total procedure time, defined as the sum of the time for identifying landmarks and performing spinal anesthesia, did not differ significantly between the 2 groups (ultrasound 141 seconds [115-181 seconds {101-336 seconds}]; landmark 146 seconds [90-295 seconds {53-404 seconds}]; P = .888). The ultrasound group showed lower periprocedural pain scores compared with the landmark group (ultrasound 3.5 [1-5 {0-7}]; landmark 5.5 [3-8 {0-9}]; P = .012). The incidences of complications during the procedure showed no significant differences between the 2 groups.  For anesthesiologists with experience in neuraxial ultrasonography, the use of ultrasound significantly reduces the technical difficulties of spinal anesthesia in patients with abnormal spinal anatomy compared with the landmark-guided technique. Our results can lead to practical suggestions that encourage the use of neuraxial ultrasonography for spinal anesthesia in such patients.

title: Objective sensory testing methods reveal a higher prevalence of olfactory loss in COVID-19 positive patients compared to subjective methods: A systematic review and meta-analysis
abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has currently infected over 6.5 million people worldwide. In response to the pandemic, numerous studies have tried to identify the causes and symptoms of the disease. Emerging evidence supports recently acquired anosmia (complete loss of smell) and hyposmia (partial loss of smell) as symptoms of COVID-19, but studies of olfactory dysfunction show a wide range of prevalence, from 5% to 98%. We undertook a search of Pubmed/Medline and Google Scholar with the keywords 'COVID-19', 'smell', and/or 'olfaction'. We included any study that quantified olfactory loss as a symptom of COVID%[minus]19. Studies were grouped and compared based on the type of method used to measure smell loss - subjective measures such as self-reported smell loss versus objective measures using rated stimuli - to determine if prevalence rate differed by method type. For each study, 95% confidence intervals (CIs) were calculated from point estimates of olfactory disturbance rates. We identified 34 articles quantifying anosmia as a symptom of COVID-19, collected from cases identified from January 16 to April 30, 2020. The pooled prevalence estimate of smell loss was 77% when assessed through objective measurements (95% CI of 61.4-89.2%) and 45% with subjective measurements (95% CI of 31.1-58.5%). Objective measures are a more sensitive method to identify smell loss as a result of infection with SARS-CoV-2. The use of subjective measures, while expedient during the early stages of the pandemic, underestimates the true prevalence of smell loss.

title: Under-reporting of TB cases and associated factors: a case study in China
abstract: Tuberculosis is a leading cause of death worldwide and has become a high global health priority. Accurate country level surveillance is critical to ending the pandemic. Effective routine reporting systems which track the course of the epidemic are vital in addressing TB. China, which has the third largest TB epidemic in the world and has developed a reporting system to help with the control and prevention of TB, this study examined its effectiveness in Eastern China.  The number of TB cases reported internally in two hospitals in Eastern China were compared to the number TB cases reported by these same hospitals in the national reporting systems in order to assess the accuracy of reporting. Qualitative data from interviews with key health officials and researcher experience using the TB reporting systems were used to identify factors affecting the accuracy of TB cases being reported in the national systems.  This study found that over a quarter of TB cases recorded in the internal hospital records were not entered into the national TB reporting systems, leading to an under representation of national TB cases. Factors associated with underreporting included unqualified and overworked health personnel, poor supervision and accountability at local and national levels, and a complicated incohesive health information management system.  This study demonstrates that TB in Eastern China is being underreported. Given that Eastern China is a developed province, one could assume similar problems may be found in other parts of China with fewer resources as well as many low- and middle-income countries. Having an accurate account of the number of national TB cases is essential to understanding the national and global burden of the disease and in managing TB prevention and control efforts. As such, factors associated with underreporting need to be addressed in order to reduce underreporting.

title: Evidence of recombination in coronaviruses implicating pangolin origins of nCoV-2019
abstract: A novel coronavirus (nCoV-2019) was the cause of an outbreak of respiratory illness detected in Wuhan, Hubei Province, China in December of 2019. Genomic analyses of nCoV-2019 determined a 96% resemblance with a coronavirus isolated from a bat in 2013 (RaTG13); however, the receptor binding motif (RBM) of these two genomes share low sequence similarity. This divergence suggests a possible alternative source for the RBM coding sequence in nCoV-2019. We identified high sequence similarity in the RBM between nCoV-2019 and a coronavirus genome reconstructed from a viral metagenomic dataset from pangolins possibly indicating a more complex origin for nCoV-2019.

title: Prospects for detecting early warning signals in discrete event sequence data: application to epidemiological incidence data
abstract: Early warning signals (EWS) identify systems approaching a critical transition, where the system undergoes a sudden change in state. For example, monitoring changes in variance or autocorrelation offers a computationally inexpensive method which can be used in real-time to assess when an infectious disease transitions to elimination. EWS have a promising potential to not only be used to monitor infectious diseases, but also to inform control policies to aid disease elimination. Previously, potential EWS have been identified for prevalence data, however the prevalence of a disease is often not known directly. In this work we identify EWS for incidence data, the standard data type collected by the Centers for Disease Control and Prevention (CDC) or World Health Organization (WHO). We show, through several examples, that EWS calculated on simulated incidence time series data exhibit vastly different behaviours to those previously studied on prevalence data. In particular, the variance displays a decreasing trend on the approach to disease elimination, contrary to that expected from critical slowing down theory; this could lead to unreliable indicators of elimination when calculated on real-world data. We derive analytical predictions which can be generalised for many epidemiological systems, and we support our theory with simulated studies of disease incidence. Additionally, we explore EWS calculated on the rate of incidence over time, a property which can be extracted directly from incidence data. We find that although incidence might not exhibit typical critical slowing down properties before a critical transition, the rate of incidence does, presenting a promising new data type for the application of statistical indicators.  The threat posed by infectious diseases has a huge impact on our global society. It is therefore critical to monitor infectious diseases as new data become available during control campaigns. One obstacle in observing disease emergence or elimination is understanding what influences noise in the data and how this fluctuates when near to zero cases. The standard data type collected is the number of new cases per day/month/year but mathematical modellers often focus on data such as the total number of infectious people, due to its analytical properties. We have developed a methodology to monitor the standard type of data to inform whether a disease is approaching emergence or disease elimination. We have shown computationally how fluctuations change as disease data get closer towards a tipping point and our insights highlight how these observed changes can be strikingly different when calculated on different types of data.

title: The Role of Thailand in the International Trade in CITES-Listed Live Reptiles and Amphibians
abstract: International wildlife trade is one of the leading threats to biodiversity conservation. The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) is the most important initiative to monitor and regulate the international trade of wildlife but its credibility is dependent on the quality of the trade data. We report on the performance of CITES reporting by focussing on the commercial trade in non-native reptiles and amphibians into Thailand as to illustrate trends, species composition and numbers of wild-caught vs. captive-bred specimens.  Based on data in the WCMC-CITES trade database, we establish that a total of 75,594 individuals of 169 species of reptiles and amphibians (including 27 globally threatened species) were imported into Thailand in 1990–2007. The majority of individuals (59,895, 79%) were listed as captive-bred and a smaller number (15,699, 21%) as wild-caught. In the 1990s small numbers of individuals of a few species were imported into Thailand, but in 2003 both volumes and species diversity increased rapidly. The proportion of captive-bred animals differed greatly between years (from 0 to >80%). Wild-caught individuals were mainly sourced from African countries, and captive-bred individuals from Asian countries (including from non-CITES Parties). There were significant discrepancies between exports and imports. Thailand reports the import of >10,000 individuals (51 species) originating from Kazakhstan, but Kazakhstan reports no exports of these species. Similar discrepancies, involving smaller numbers (>100 individuals of 9 species), can be seen in the import of reptiles into Thailand via Macao.  While there has been an increase in imports of amphibian and reptiles into Thailand, erratic patterns in proportions of captive-bred specimens and volumes suggests either capricious markets or errors in reporting. Large discrepancies with respect to origin point to misreporting or possible violations of the rules and intentions of CITES.

title: Using early data to estimate the actual infection fatality ratio from COVID-19 in France
abstract: The number of screening tests carried out in France and the methodology used to target the patients tested do not allow for a direct computation of the actual number of cases and the infection fatality ratio (IFR). The main objective was to estimate the actual number of people infected with COVID-19 during the observation window in France and to deduce the IFR.  We develop a 'mechanistic-statistical' approach coupling a SIR epidemiological model describing the unobserved epidemiological dynamics, a probabilistic model describing the data acquisition process and a statistical inference method.  The actual number of infected cases in France is probably higher than the observations: we find here a factor x 8 (95%-CI: 5-12) which leads to an IFR in France of 0.5% (95%-CI: 0.3-0.8) based on hospital death counting data. Adjusting for the number of deaths in nursing homes, we obtain an IFR of 0.8% (95%-CI: 0.45-1.25).  This IFR is consistent with previous findings in China (0.66%) and in the UK (0.9%) and lower than the value previously computed on the Diamond Princess cruse ship data (1.3%).

title: Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV
abstract: Since 2002, beta coronaviruses (CoV) have caused three zoonotic outbreaks, SARS-CoV in 2002–2003, MERS-CoV in 2012, and the newly emerged SARS-CoV-2 in late 2019. However, little is currently known about the biology of SARS-CoV-2. Here, using SARS-CoV-2 S protein pseudovirus system, we confirm that human angiotensin converting enzyme 2 (hACE2) is the receptor for SARS-CoV-2, find that SARS-CoV-2 enters 293/hACE2 cells mainly through endocytosis, that PIKfyve, TPC2, and cathepsin L are critical for entry, and that SARS-CoV-2 S protein is less stable than SARS-CoV S. Polyclonal anti-SARS S1 antibodies T62 inhibit entry of SARS-CoV S but not SARS-CoV-2 S pseudovirions. Further studies using recovered SARS and COVID-19 patients’ sera show limited cross-neutralization, suggesting that recovery from one infection might not protect against the other. Our results present potential targets for development of drugs and vaccines for SARS-CoV-2.

title: Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak
abstract: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R 0, of 2019-nCoV in the early phase of the outbreak.  Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R 0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.  The early outbreak data largely follows the exponential growth. We estimated that the mean R 0 ranges from 2.24 (95%CI: 1.96–2.55) to 3.58 (95%CI: 2.89–4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R 0.  The mean estimate of R 0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.

title: Preliminary evidence that higher temperatures are associated with lower incidence of COVID-19, for cases reported globally up to 29th February 2020
abstract: Seasonal variation in COVID-19 incidence could impact the trajectory of the pandemic. Using global line-list data on COVID-19 cases reported until 29th February 2020 and global gridded temperature data, and after adjusting for surveillance capacity and time since first imported case, higher average temperature was strongly associated with lower COVID-19 incidence for temperatures of 1°C and higher. However, temperature explained a relatively modest amount of the total variation in COVID-19 incidence. These preliminary findings support stringent containment efforts in Europe and elsewhere.

title: Hormone replacement therapy after surgery for epithelial ovarian cancer.
abstract: Women who have undergone surgical treatment for epithelial ovarian cancer (EOC) may develop menopausal symptoms due to immediate loss of ovarian function following surgery and chemotherapy. Women may experience vasomotor symptoms, sleep disturbance, difficulty concentrating, sexual dysfunction, vaginal symptoms and accelerated osteoporosis. Although hormone replacement therapy (HRT) is the most effective treatment to relieve these symptoms, its safety has been questioned for women with EOC.  To assess the safety and efficacy of HRT for menopausal symptoms in women surgically treated for EOC.  We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2019, Issue 6), MEDLINE via Ovid (1946 to 12 June 2019) and Embase via Ovid (1980 to 2019, week 23). We also handsearched conference reports and trial registries. There was no language restriction.  We included randomized controlled trials (RCTs) with participants of any age and menopausal status who had undergone surgery for EOC and, after diagnosis and treatment, used any regimen and duration of HRT compared with placebo or no hormone therapy. We also included trials comparing different regimens or duration of administration of HRT.  Two review authors independently identified studies that met the inclusion criteria. They used Covidence to extract study characteristics, outcome data and to assess methodological quality of the included studies. MAIN RESULTS Our search strategy identified 2617 titles, of which 2614 titles were excluded. Three studies, involving 350 women, met our inclusion criteria. Two of the studies included pre and postmenopausal women, and the third only included premenopausal women. The overall age range of those women included in the studies was 20 to 89.6 years old, with a median follow-up ranging from 31.4 months to 19.1 years. The geographical distribution of participants included Europe, South Africa and China. All stages and histological subtypes were included in two of the studies, but stage IV disease had been excluded in the third. The three included studies used a variety of HRT regimens (conjugated oestrogen with or without medroxyprogesterone and with or without nylestriol) and HRT administrations (oral, patch and implant), In all studies, the comparisons were made versus women who had not received HRT. The studies were at low or unclear risk of selection and reporting bias, and at high risk of performance, detection and attrition bias. The certainty of the evidence was low for overall survival and progression-free survival, and very low for quality-of-life assessment, incidence of breast cancer, transient ischaemic attack (TIA), cerebrovascular accident (CVA) and myocardial infarction (MI). Meta-analysis of these studies showed that HRT may improve overall survival (hazard ratio (HR) 0.71, 95% confidence interval (CI) 0.54 to 0.93; 350 participants, 3 studies; low-certainty evidence). Quality-of-life assessment by use of the EORTC-C30 questionnaire was performed only in one study. We are uncertain whether HRT improves or reduces quality of life as the certainty of the evidence was assessed as very low (mean difference (MD) 13.67 points higher, 95% CI 9.26 higher to 18.08 higher; 1 study; 75 participants; very low-certainty evidence). Likewise, HRT may make little or no difference to progression-free survival (HR 0.76, 95% CI 0.57 to 1.01; 275 participants, 2 studies; low-certainty evidence). We are uncertain whether HRT improves or reduces the incidence of breast cancer (risk ratio (RR) 2.00, 95% CI 0.19 to 21.59; 225 participants, 2 studies; very low-certainty evidence); TIA (RR 5.00, 95% CI 0.24 to 102.42; 150 participants, 1 study; very low-certainty evidence); CVA (RR 0.67, 95% CI 0.11 to 3.88; 150 participants, 1 study; very low-certainty evidence); and MI (RR 0.20, 95% CI 0.01 to 4.10; 150 participants, 1 study; very low-certainty evidence). The incidence of gallstones was not reported in the included studies. AUTHORS' CONCLUSIONS Hormone replacement therapy may slightly improve overall survival in women who have undergone surgical treatment for EOC, but the certainty of the evidence is low. HRT may make little or no difference to quality of life, incidence of breast cancer, TIA, CVA and MI as the certainty of the evidence has been assessed as very low. There may be little or no effect of HRT use on progression-free survival. The evidence in this review is limited by imprecision and incompleteness of reported relevant outcomes and therefore the results should be interpreted with caution. Future well-designed RCTs are required as this is an important area to women experiencing menopausal symptoms following surgical treatment for ovarian cancer, especially as doctors are often reluctant to prescribe HRT in this scenario. The evidence in this review is too limited to support or refute that HRT is very harmful in this population.

title: Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019
abstract: The novel coronavirus SARS-CoV-2 is a newly emerging virus. The antibody response in infected patient remains largely unknown, and the clinical values of antibody testing have not been fully demonstrated.  A total of 173 patients with SARS-CoV-2 infection were enrolled. Their serial plasma samples (n=535) collected during the hospitalization were tested for total antibodies (Ab), IgM and IgG against SARS-CoV-2. The dynamics of antibodies with the disease progress was analyzed.  Among 173 patients, the seroconversion rate for Ab, IgM and IgG was 93.1%, 82.7% and 64.7%, respectively. The reason for the negative antibody findings in 12 patients might due to the lack of blood samples at the later stage of illness. The median seroconversion time for Ab, IgM and then IgG were day-11, day-12 and day-14, separately. The presence of antibodies was <40% among patients within 1-week since onset, and rapidly increased to 100.0% (Ab), 94.3% (IgM) and 79.8% (IgG) since day-15 after onset. In contrast, RNA detectability decreased from 66.7% (58/87) in samples collected before day-7 to 45.5% (25/55) during day 15-39. Combining RNA and antibody detections significantly improved the sensitivity of pathogenic diagnosis for COVID-19 (p<0.001), even in early phase of 1-week since onset (p=0.007). Moreover, a higher titer of Ab was independently associated with a worse clinical classification (p=0.006).  The antibody detection offers vital clinical information during the course of SARS-CoV-2 infection. The findings provide strong empirical support for the routine application of serological testing in the diagnosis and management of COVID-19 patients.

title: The COVID-19 outbreak and psychiatric hospitals in China: managing challenges through mental health service reform
abstract: Recently, more than 300 Chinese patients with psychiatric disorders were diagnosed with the 2019 novel coronavirus disease (COVID-19). Possible reasons quoted in the report were the lack of caution regarding the COVID-19 outbreak in January and insufficient supplies of protective gear. We outlined major challenges for patients with psychiatric disorders and mental health professionals during the COVID-19 outbreak, and also discussed how to manage these challenges through further mental health service reform in China.

title: Serum xanthophyll carotenoids are associated with estimated glomerular filtration rate in an aged cohort.
abstract: Progressive renal decline is associated with increasing oxidative stress. However, the majority of studies have investigated endogenous antioxidants in predominantly advanced stages of kidney disease. Many traditional risk factors associated with renal dysfunction have been linked with cognitive decline as the kidneys and brain share comparable anatomic and haemodynamic characteristics that leave them susceptible to common pathogenic mechanisms. The objective of this study was to examine serum dietary antioxidants and their association with renal function characterised by estimated glomerular filtration rate (eGFR) in a cross-sectional analysis of 570 participants. High performance liquid chromatography quantified serum levels of retinol, α-tocopherol, γ-tocopherol and six carotenoids (α-carotene, β-carotene, β-cryptoxanthin, lutein, lycopene and zeaxanthin) in participants. Multiple regression analyses were used to evaluate associations while adjusting for potential confounders. A sensitivity analysis was performed in cognitively-intact participants only. Serum levels of the xanthophyll carotenoid lutein were positively associated with eGFR in analyses adjusted for age (years), gender, smoking, APOE4 status and Alzheimer's disease. Retinol was inversely associated with eGFR, although was no longer significant in the smaller sensitivity analysis. Our findings identify significant associations between the xanthophyll carotenoids and eGFR. Further investigations are required to confirm these findings.

title: Prevention of Experimental Coronavirus Colds with Intranasal α-2b Interferon
abstract: Fifty-five volunteers treated with either intranasal recombinant interferon (rIFN; 2 × 10(6) IU/day) or placebo for 15 days were exposed to coronavirus by direct intranasal inoculation on the eighth day of treatment. Symptom scores were recorded, and cultures of virus were taken daily for all volunteers for seven days after inoculation. Nineteen (73%) of the 26 placebo recipients met symptom-score criteria for a cold, compared with 12 (41%) of the IFN recipients (P = .02). The mean nasal symptom scores in the placebo and IFN groups were 9.2 and 5.4, respectively (P = .03), and the mean total symptom scores in the two groups were 23.2 and 9.4, respectively (P = .003). The mean number of days with a total symptom score >4 was 1.6 in the placebo recipients and 0.5 in the rIFN recipients (P = .02). Prophylactic intranasal rIFN effectively shortened the duration and reduced the severity of coronavirus cold symptoms.

title: Characterization of the COVID-19 pandemic and the impact of uncertainties, mitigation strategies, and underreporting of cases in South Korea, Italy, and Brazil
abstract: By April 7th, 2020, the Coronavirus disease 2019 (COVID-19) has infected one and a half million people worldwide, accounting for over 80 thousand of deaths in 209 countries and territories around the world. The new and fast dynamics of the pandemic are challenging the health systems of different countries. In the absence of vaccines or effective treatments, mitigation policies, such as social isolation and lock-down of cities, have been adopted, but the results vary among different countries. Some countries were able to control the disease at the moment, as is the case of South Korea. Others, like Italy, are now experiencing the peak of the pandemic. Finally, countries with emerging economies and social issues, like Brazil, are in the initial phase of the pandemic. In this work, we use mathematical models with time-dependent coefficients, techniques of inverse and forward uncertainty quantification, and sensitivity analysis to characterize essential aspects of the COVID-19 in the three countries mentioned above. The model parameters estimated for South Korea revealed effective social distancing and isolation policies, border control, and a high number in the percentage of reported cases. In contrast, underreporting of cases was estimated to be very high in Brazil and Italy. In addition, the model estimated a poor isolation policy at the moment in Brazil, with a reduction of contact around 40%, whereas Italy and South Korea estimated numbers for contact reduction are at 75% and 90%, respectively. This characterization of the COVID-19, in these different countries under different scenarios and phases of the pandemic, supports the importance of mitigation policies, such as social distancing. In addition, it raises serious concerns for socially and economically fragile countries, where underreporting poses additional challenges to the management of the COVID-19 pandemic by significantly increasing the uncertainties regarding its dynamics.

title: Group Testing for Sars-Cov-2 to Enable Rapid Scale-Up of Testing and Real-Time Surveillance of Incidence
abstract: High-throughput molecular testing for SARS-CoV-2 may be enabled by group testing in which pools of specimens are screened, and individual specimens tested only after a pool tests positive. Several labs have recently published examples of pooling strategies applied to SARS-CoV-2 specimens, but overall guidance on efficient pooling strategies is lacking. Therefore we developed a model of the efficiency and accuracy of specimen pooling algorithms based on available data on SAR-CoV-2 viral dynamics. For a fixed number of tests, we estimate that programs using group testing could screen 2 to 20 times as many specimens compared to individual testing; increase the total number of true positive infections identified; and improve the positive predictive value of results. We compare outcomes that may be expected in different testing situations and provide general recommendations for group testing implementation. A free, publicly-available web calculator is provided to help inform laboratory decisions on SARS-CoV-2 pooling algorithms.

title: Cremation based estimates suggest significant under- and delayed reporting of COVID-19 epidemic data in Wuhan and China
abstract: Epidemiological data provide important information for decision making. COVID-19 statistics from China fall outside of recognized and accepted medical norms. As the epicenter of the COVID-19 initial outbreak, the epidemiological information from Wuhan affects the response and preparation of other parts of China and rest of the world. Here we estimated the incidence, death and starting time of the COVID-19 outbreak in Wuhan and China based on medical literature from China, official and non-official Chinese data sources.  Data sources included literature on COVID-19 in China, official Chinese government figures, state-run and non state-run media reports. Our estimates are based on investigative media reports of crematory operations in Wuhan, which is considered as a common data end point to life. A range of estimates is presented by an exponential growth rate model from lockdown (Jan 23,2020) until the intervention started to show effects, which was estimated 14.5 days after lockdown.  For the cumulative infections and total deaths, under different assumptions of death rates (from 2.5% to 10%) and doubling time 6.4 days, the estimates projected on February 7, 2020 in Wuhan range from 305,000 to 1,272,000 for infections and from 6,811 to 7,223 for deaths - on the order of at least 10 times the official figures (13,603 and 545). The implied starting time of the outbreak is October 2019. Under the assumption of the official 3.14% death rate and doubling time of 2.54 days (which was derived based on Chinese official data), the infection cases reached 2.2 million on February 7. The estimates of cumulative deaths, based on both funeral urns distribution and continuous full capacity operation of cremation services up to March 23, 2020, give results around 36,000, more than 10 times of the official death toll of 2,524.  Our study indicates a significant under-reporting in Chinese official data on the COVID-19 epidemic in Wuhan. The magnitude of discrepancy between our estimates based on cremation related data and Chinese official figures in early February, the critical time for response to the COVID-19 pandemic, suggests the need to reevaluate official statistics from China and consider all available and reasonable data sources for a better understanding of the COVID-19 pandemic.

title: Demographic, etiological, and histological pulmonary analysis of patients with acute respiratory failure: a study of 19 years of autopsies
abstract: Acute respiratory failure has been one of the most important causes of death in intensive care units, and certain aspects of its pulmonary pathology are currently unknown.  The objective was to describe the demographic data, etiology, and pulmonary histopathological findings of different diseases in the autopsies of patients with acute respiratory failure.  Autopsies of 4,710 patients with acute respiratory failure from 1990 to 2008 were reviewed, and the following data were obtained: age, sex, and major associated diseases. The pulmonary histopathology was categorized as diffuse alveolar damage, pulmonary edema, alveolar hemorrhage, and lymphoplasmacytic interstitial pneumonia. The odds ratio of the concordance between the major associated diseases and specific autopsy findings was calculated using logistic regression.  Bacterial bronchopneumonia was present in 33.9% of the cases and cancer in 28.1%. The pulmonary histopathology showed diffuse alveolar damage in 40.7% (1,917) of the cases. A multivariate analysis showed a significant and powerful association between diffuse alveolar damage and bronchopneumonia, HIV/AIDS, sepsis, and septic shock, between liver cirrhosis and pulmonary embolism, between pulmonary edema and acute myocardial infarction, between dilated cardiomyopathy and cancer, between alveolar hemorrhage and bronchopneumonia and pulmonary embolism, and between lymphoplasmacytic interstitial pneumonia and HIV/AIDS and liver cirrhosis.  Bronchopneumonia was the most common diagnosis in these cases. The most prevalent pulmonary histopathological pattern was diffuse alveolar damage, which was associated with different inflammatory conditions. Further studies are necessary to elucidate the complete pathophysiological mechanisms involved with each disease and the development of acute respiratory failure.

title: Changes in testing rates could mask the novel coronavirus disease (COVID-19) growth rate
abstract: Since the novel coronavirus disease (COVID-19) emerged in December 2019 in China, it has rapidly propagated to around the world, leading to one of the most significant pandemic events of recent history. Deriving reliable estimates of the COVID-19 epidemic growth rate is quite important to guide the timing and intensity of intervention strategies. Indeed, many studies have quantified the epidemic growth rate using time-series of reported cases during the early phase of the outbreak to estimate the basic reproduction number, R 0. Using daily time series of COVID-19 incidence, we illustrate how epidemic curves of reported cases may not always reflect the true epidemic growth rate due to changes in testing rates, which could be influenced by limited diagnostic testing capacity during the early epidemic phase.

title: Editorial Commentary: Still Learning From the Earliest Known MERS Outbreak, Zarqa, Jordan, April 2012

title: CoronaSurveys: Using Surveys with Indirect Reporting to Estimate the Incidence and Evolution of Epidemics
abstract: The world is suffering from a pandemic called COVID-19, caused by the SARS-CoV-2 virus. National governments have problems evaluating the reach of the epidemic, due to having limited resources and tests at their disposal. This problem is especially acute in low and middle-income countries (LMICs). Hence, any simple, cheap and flexible means of evaluating the incidence and evolution of the epidemic in a given country with a reasonable level of accuracy is useful. In this paper, we propose a technique based on (anonymous) surveys in which participants report on the health status of their contacts. This indirect reporting technique, known in the literature as network scale-up method, preserves the privacy of the participants and their contacts, and collects information from a larger fraction of the population (as compared to individual surveys). This technique has been deployed in the CoronaSurveys project, which has been collecting reports for the COVID-19 pandemic for more than two months. Results obtained by CoronaSurveys show the power and flexibility of the approach, suggesting that it could be an inexpensive and powerful tool for LMICs.

title: À propos de chirurgie et COVID-19 : quelques précautions complémentaires. Réponse à : « Stratégie pour la pratique de la chirurgie digestive et oncologique en situation d’épidémie de COVID-19 »()

title: Is ethnicity linked to incidence or outcomes of covid-19?

title: Setting healthcare priorities in hospitals: a review of empirical studies
abstract: Priority setting research has focused on the macro (national) and micro (bedside) level, leaving the meso (institutional, hospital) level relatively neglected. This is surprising given the key role that hospitals play in the delivery of healthcare services and the large proportion of health systems resources that they absorb. To explore the factors that impact upon priority setting at the hospital level, we conducted a thematic review of empirical studies. A systematic search of PubMed, EBSCOHOST, Econlit databases and Google scholar was supplemented by a search of key websites and a manual search of relevant papers’ reference lists. A total of 24 papers were identified from developed and developing countries. We applied a policy analysis framework to examine and synthesize the findings of the selected papers. Findings suggest that priority setting practice in hospitals was influenced by (1) contextual factors such as decision space, resource availability, financing arrangements, availability and use of information, organizational culture and leadership, (2) priority setting processes that depend on the type of priority setting activity, (3) content factors such as priority setting criteria and (4) actors, their interests and power relations. We observe that there is need for studies to examine these issues and the interplay between them in greater depth and propose a conceptual framework that might be useful in examining priority setting practices in hospitals.

title: COVID-19 pandemic: examining the faces of spatial differences in the morbidity and mortality in sub-Saharan Africa, Europe and USA.
abstract: COVID-19, the disease associated with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is currently a global pandemic with several thousands of confirmed cases of infection and death. However, the death rate across affected countries shows variation deserving of critical evaluation.  In this study, we evaluated differentials in COVID-19 confirmed cases of infection and associated deaths of selected countries in Sub-Sahara Africa (Nigeria and Ghana), South Africa, Europe (Italy, Spain, Sweden and UK) and USA. Data acquired for various standard databases on mutational shift of the SARS-CoV-2 virus based on geographical location, BCG vaccination policy, malaria endemicity, climatic conditions (temperature), differential healthcare approaches were evaluated over a period of 45 days from the date of reporting the index case.  The number of confirmed cases of infection and associated deaths in Sub-Sahara Africa were found to be very low compared to the very high values in Europe and USA over the same period. Recovery rate from COVID-19 is not correlated with the mutational attributes of the virus with the sequenced strain from Nigeria having no significant difference (p>0.05) from other geographical regions. Significantly higher (p<0.05) infection rate and mortality from COVID-19 were observed in countries (Europe and USA) without a current universal BCG vaccination policy compared to those with one (Sub-Sahara African countries). Countries with high malaria burden had significantly lower (p<0.05) cases of COVID-19 than those with low malaria burden. A strong negative correlation (-0.595) between mean annual temperature and COVID-19 infection and death was observed with 14.8% variances between temperature and COVID-19 occurrence among the countries. A clear distinction was observed in the COVID-19 disease management between the developed countries (Europe and USA) and Sub-Sahara Africa.  The study established that the wide variation in the outcome of the COVID-19 disease burden in the selected countries are attributable largely to climatic condition (temperature) and differential healthcare approaches to management of the disease. We recommend consideration and mainstreaming of these findings for urgent intervention and management of COVID-19 across these continents.

title: The impact of changes in diagnostic testing practices on estimates of COVID-19 transmission in the United States
abstract: Estimates of the reproductive number for novel pathogens such as SARS-CoV-2 are essential for understanding the potential trajectory of the epidemic and the level of intervention that is needed to bring the epidemic under control. However, most methods for estimating the basic reproductive number (R(0)) and time-varying effective reproductive number (R(t)) assume that the fraction of cases detected and reported is constant through time. We explore the impact of secular changes in diagnostic testing and reporting on estimates of R(0) and R(t) using simulated data. We then compare these patterns to data on reported cases of COVID-19 and testing practices from different United States (US) states. We find that changes in testing practices and delays in reporting can result in biased estimates of R(0) and R(t). Examination of changes in the daily number of tests conducted and the percent of patients testing positive may be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of COVID-19.

title: Chapter 3 Measuring, Monitoring, and Evaluating the Health of a Population
abstract: Public health depends on information derived from monitoring population health status to identify community health problems, and to diagnose and investigate health problems and hazards in the community. These depend on vital statistics and disease reporting systems, including for non-communicable diseases, injuries, risk factors, health care resources, utilization of resources, and special disease registries such as for cancer, birth defects, and many others. Information technology and computerization allow data systems to be linked to assess the impact of health conditions and utilization of services providing vital information for epidemiological and economic analyses for policy development. Epidemiology and its associated quantitative disciplines of biostatistics and demography are augmented by social and behavioral qualitative research methods. The disciplines of health systems research provide evidence from population health monitoring crucial to policy and priority determination. This introductory chapter is augmented in subsequent chapters, and by specialized courses in public health education programs.

title: SARS-CoV-2 and gastrointestinal tract: the dark side of the pandemic

title: KCDC Risk Assessments on the Initial Phase of the COVID-19 Outbreak in Korea
abstract: This study aims to evaluate the risk assessments of coronavirus 2019 (COVID-19) in the Korea Centers for Disease Control and Prevention (KCDC), from the point of detection to the provision of basic information to the relevant public health authorities.  To estimate the overall risk of specific public health events, probability, and impact at the country-level were evaluated using available information. To determine the probability of particular public health events, the risk of importation and risk of transmission were taken into consideration. KCDC used 5 levels (“very low,” “low,” “moderate,” “high,” and “very high”) for each category and overall risk was eventually decided.  A total of 8 risk assessments were performed on 8 separate occasions between January 8(th) to February 28(th), 2020, depending on the detection and report of COVID-19 cases in other countries. The overall risk of the situation in each assessment increased in severity over this period: “low” (first), “moderate” (second), “high” (third), “high” (fourth), “high” (fifth), “high” (sixth), “high” (seventh), and “very high” (eighth).  The KCDC’s 8 risk assessments were utilized to activate national emergency response mechanisms and eventually prepare for the pandemic to ensure the containment and mitigation of COVID-19 with non-pharmaceutical public health measures.

title: Coronavirus Disease (COVID-19) Pandemic: An Overview of Systematic Reviews
abstract: Navigating the rapidly growing body of scientific literature on the SARS-CoV-2 pandemic is challenging and ongoing critical appraisal of this output is essential. We aimed to collate and summarize all published systematic reviews on the coronavirus disease (COVID-19).  Nine databases (Medline, EMBASE, Cochrane Library, CINAHL, Web of Sciences, PDQ-Evidence, WHO's Global Research, LILACS and Epistemonikos) were searched from December 1, 2019 to March 24, 2020. Systematic reviews analyzing primary studies of COVID-19 were included. Two authors independently undertook screening, selection, extraction (data on clinical symptoms, prevalence, pharmacological and non-pharmacological interventions, diagnostic test assessment, laboratory and radiological findings) and quality assessment (AMSTAR 2). Meta-analysis on prevalence of clinical outcomes was performed.  Eighteen systematic reviews were included; one was empty. Using AMSTAR 2, confidence in the results of 13 reviews was rated as "critically low", one as "low", one as "moderate" and two as "high". Symptoms of COVID-19 were (range values of point estimates): fever (82-95%), cough with or without sputum (58-72%), dyspnea (26-59%), myalgia or muscle fatigue (29-51%), sore throat (10-13%), headache (8-12%) and gastrointestinal complaints (5-9%). Severe symptoms were more common in men. Elevated C-reactive protein (associated with lymphocytopenia) and lactate dehydrogenase, and slightly elevated aspartate and alanine aminotransferase, were commonly described. Thrombocytopenia and elevated levels of procalcitonin and cardiac troponin I were associated with severe disease. Chest imaging described a frequent pattern of uni- or bilateral multilobar ground-glass opacity. Only one review investigated the impact of medication (chloroquine) but found no verifiable clinical data. All-cause mortality ranged from 0.3% to 14%.  Confidence in the results of most reviews was "critically low". Future studies and systematic reviews should adhere to established methodologies. The majority of included systematic reviews were hampered by imprecise search strategy and no previous protocol submission.

title: COVID-19 mathematical model reopening scenarios for Sao Paulo - Brazil
abstract: The objective of the current investigation was to produce a generalized computational model to predict consequences of various reopening scenarios on COVID-19 infections rates and available hospital resources in Sao Paulo - Brazil. We were able to use the Susceptible-Exposed-Infected-Recovered (SEIR) model to fit both accumulated death data and corrected accumulated cases data associated with COVID-19 for both Brazil and the state of Sao Paulo. In addition, we were able to simulate the consequences of reopening under different possible scenarios in Brazil, in special for the state of Sao Paulo. The model was able to provide a predicted scenario in which reopening could occur with minimal impact on human life considering people careful behavior in combination with continued social distancing measures.

title: Microbicides and the environmental control of nosocomial viral infections
abstract: Viruses are important causes of acute and chronic diseases in humans. Newer viruses are still being discovered and those that are already known are being incriminated in the aetiology of clinical conditions with hitherto unknown causes. Apart from frequently causing infections in the general community, many types of viruses are also significant nosocomial pathogens. While it is generally agreed that we underestimate the proportion of nosocomial infections that are viral, due to a lack of routine monitoring, viruses easily account for more than 30% of the cases of hospital-acquired infections in many paediatric settings. Indeed, the relative importance of viruses in this respect is increasing due to a number of societal and demographic changes as well as alterations in healthcare practices. Safe vaccines against many common nosocomial viral agents are currently unavailable while there is also a virtual lack of effective and affordable chemotherapy against them. There is, therefore, renewed emphasis on preventive strategies by better understanding of the relative importance of various vehicles in the nosocomial spread of viruses and by infection control using microbicides. This, in turn, has stimulated considerable interest in the development of formulations that are not only safer but which also have demonstrated activity against major types of nosocomial viral pathogens. Further, much work is now underway to design better methods to assess the virucidal activity of microbicides used to decontaminate hands, reusable medical devices and environmental surfaces in critical areas of healthcare settings. It is anticipated that these approaches will result in reducing the health and economic impact of nosocomial infections due to viruses.

title: Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia
abstract: The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP.  We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number.  Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9).  On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk.

title: The International Health Regulations 10 years on: the governing framework for global health security

title: Guidance for rebooting electrophysiology through the COVID-19 pandemic from the Heart Rhythm Society and the American Heart Association Electrocardiography and Arrhythmias Committee of the Council on Clinical Cardiology
abstract: Coronavirus disease 2019 (COVID-19) has presented substantial challenges to patient care and impacted health care delivery, including cardiac electrophysiology practice throughout the globe. Based upon the undetermined course and regional variability of the pandemic, there is uncertainty as to how and when to resume and deliver electrophysiology services for arrhythmia patients. This joint document from representatives of the Heart Rhythm Society, American Heart Association, and American College of Cardiology seeks to provide guidance for clinicians and institutions reestablishing safe electrophysiological care. To achieve this aim, we address regional and local COVID-19 disease status, the role of viral screening and serologic testing, return-to-work considerations for exposed or infected health care workers, risk stratification and management strategies based on COVID-19 disease burden, institutional preparedness for resumption of elective procedures, patient preparation and communication, prioritization of procedures, and development of outpatient and periprocedural care pathways.

title: Analytical Validation of a COVID-19 qRT-PCR Detection Assay Using a 384-well Format and Three Extraction Methods
abstract: The COVID-19 global pandemic is an unprecedented health emergency. Insufficient access to testing has hampered effective public health interventions and patient care management in a number of countries. Furthermore, the availability of regulatory-cleared reagents has challenged widespread implementation of testing. We rapidly developed a qRT-PCR SARS-CoV-2 detection assay using a 384-well format and tested its analytic performance across multiple nucleic acid extraction kits. Our data shows robust analytic accuracy on residual clinical biospecimens. Limit of detection sensitivity and specificity was confirmed with currently available commercial reagents. Our methods and results provide valuable information for other high-complexity laboratories seeking to develop effective, local, laboratory-developed procedures with high-throughput capability to detect SARS-CoV-2.

title: New blood tests for antibodies could show true scale of coronavirus pandemic
abstract: How many COVID-19 cases have gone undetected? And are those who had mild cases of the disease—perhaps so mild they dismissed it as a cold or allergies—immune to new infections? If so, they could slow the spread of the burgeoning pandemic Labs and companies around the world have raced to develop antibody tests, and a few have been used in small studies and received commercial approval, including several from China But so far, large-scale data from such tests—for example showing what fraction of people in the hard-hit city of Wuhan, China, might now be immune—is still lacking or at least not public Scientists hope that will soon change as more tests become available

title: Infección grave por coronavirus SARS-CoV-2: experiencia en un hospital de tercer nivel con pacientes afectados por COVID-19 durante la pandemia 2020./ Infección grave por coronavirus SARS-CoV-2: experiencia en un hospital de tercer nivel con pacientes afectados por COVID-19 durante la pandemia 2020./ Severe infection due to the SARS-CoV-2 coronavirus: Experience of a tertiary hospital with COVID-19 patients during the 2020 pandemic
abstract: To describe the clinical and respiratory characteristics of a cohort of 43 patients with COVID-19 after an evolutive period of 28 days.  A prospective, single-center observational study was carried out.  Intensive care.  Patients admitted due to COVID-19 and respiratory failure.  None.  Automatic recording was made of demographic variables, severity parameters, laboratory data, assisted ventilation (HFO: high-flow oxygen therapy and IMV: invasive mechanical ventilation), oxygenation (PaO2, PaO2/FiO2) and complications. The patients were divided into three groups: survivors (G1), deceased (G2) and patients remaining under admission (G3). The chi-squared test or Fisher exact test (categorical variables) was used, along with the Mann-Whitney U-test or Wilcoxon test for analyzing the differences between medians. Statistical significance was considered for p<0.05.  A total of 43 patients were included (G1=28 [65.1%]; G2=10 [23.3%] and G3=5 [11.6%]), with a mean age of 65 years (range: 52-72), 62% males, APACHE II 18 (15-24), SOFA 6 (4-7). Arterial hypertension (30.2%) and obesity (25.6%) were the most frequent comorbidities. High-flow oxygen therapy was used in 62.7% of the patients, with failure in 85%. In turn, 95% of the patients required IMV and 85% received ventilation in prone decubitus. In the general population, initial PaO2/FiO2 improved after 7 days (165 [125-210] vs.194 [153-285]; p=0.02), in the same way as in G1 (164 [125-197] vs. 207 [160-294]; p=0.07), but not in G2 (163 [95-197] vs. 135 [85-177]). No bacterial coinfection was observed. The incidence of IMV-associated pneumonia was high (13 episodes/1000 days of IMV).  Patients with COVID-19 require early IMV, a high frequency of ventilation in prone decubitus, and have a high incidence of failed HFO. The lack of improvement of PaO2/FiO2 at 7 days could be a prognostic marker. .

title: Forecasting the Impact of Coronavirus Disease During Delivery Hospitalization: An Aid for Resources Utilization
abstract: The ongoing Coronavirus disease (COVID-19) pandemic has severely impacted the United States. In cases of infectious disease outbreak, forecasting models are often developed for resources utilization. Pregnancy and delivery pose unique challenges, given the altered maternal immune system and the fact that the majority of American women choose to deliver in the hospital setting.  The aim of our study is to forecast the incidence of COVID-19 in general population and to forecast the overall incidence, severe cases, critical cases and fatal COVID-19 cases during delivery hospitalization in the United States.  We use a phenomenological model with generalized logistic growth models to forecast the incidence of COVID-19 in the United States from 4/15/2020 – 12/31/2020. Incidence data from 3/1/2020 – 4/14/2020 were used to provide best-fit model solution. Subsequently, Monte-Carlo simulation was performed for each week from 3/1/2020 – 12/31/2020 to estimate the incidence of COVID-19 in delivery hospitalizations using the available data estimate.  From 3/1/2020 – 12/31/2020, our model forecasted a total of 860,475 cases of COVID-19 in general population across the United States. The cumulative incidence for COVID-19 during delivery hospitalization is anticipated to be 16,601 (95% CI, 9,711 – 23,491) cases. Among those, 3,308 (95% CI, 1,755 – 4,861) cases are expected to be severe, 681 (95% CI, 1324 – 1,038) critical and 52 (95% CI, 23 – 81) maternal mortality. Assuming similar baseline maternal mortality rate as the year of 2018, we projected an increase in maternal mortality rate in the US to at least 18.7 (95% CI, 18.0 – 19.5) deaths per 100,000 live birth as a direct result of COVID-19. Conclusions COVID-19 infection in pregnant women is expected to severely impact obstetrical care. From 3/1/2020 – 12/31/2020, we project 3,308 severe and 681 critical cases, with about 52 COVID-19 related maternal mortalities during delivery hospitalization in the United States. These data might be helpful for counseling and resource allocation.

title: Estimation of testing bias in covid-19
abstract: COVID-19 testing studies have become a standard approach for estimating prevalence and fatality rates which then assist in public health decision making to contain and mitigate the spread of the disease. The sampling designs used are often biased in that they do not reflect the true underlying populations. For instance, individuals with strong symptoms are more likely to be tested than those with no symptoms. This results in biased estimates of prevalence (too high) and over-estimation of fatality rates. Typical post-sampling corrections are not always possible. Here we present a simple bias correction methodology derived and adapted from a correction for publication bias in meta analysis studies. The methodology is general enough to allow a wide variety of customization making it more useful in practice. Implementation is easily done using already collected information. We show via an example that the bias corrections can provide dramatic reductions in estimation error.

title: Perception of emergent epidemic of COVID-2019 / SARS CoV-2 on the Polish Internet
abstract: Due to the spread of SARS CoV-2 virus infection and COVID-2019 disease, there is an urgent need to analyze COVID-2019 epidemic perception in Poland. This would enable authorities for preparation of specific actions minimizing public health and economic risks.  We study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet (on Twitter, Google, YouTube, Wikipedia and electronic media represented by Event Registry) from January 2020 to 12.03.2020 (before and after official introduction to Poland on 04.03.2020). To this end we utilize data mining, social network analysis, natural language processing techniques. Each examined internet platform was analyzed for representativeness and composition of the target group.  We identified three major cluster of the interest before disease introduction on the topic COVID-2019: China- and Italy-related peaks on all platforms, as well as a peak on social media related to the recent special law on combating COVID-2019. Besides, there was a peak in interest on the day of officially confirmed introduction as well as an exponential increase of interest when the Polish government declared war against disease with a massive mitigation program. From sociolingistic perspective, we found that concepts and issues of threat, fear and prevention prevailed before introduction. After introduction, practical concepts about disease and epidemic dominate. Twitter reflected the clear, structural division of the Polish political sphere. We were able to identify potential sources of misinformation as well as key actors (especially early adopters) and influencers.  Traditional and social media not only reflect reality, but also create it. Polish authorities, having a reliable analysis of the perception of the problem, could optimally prepare and manage the social dimension of the current epidemic and future ones. Due to filter bubbles observed on Twitter, public information campaigns might have less impact on society than expected. For greater penetration, it might be necessary to diversify information channels to reach as many people as possible which might already be happening. Moreover, it might be necessary to prevent the spread of disinformation, which is now possible due to the special law on combating COVID-2019.

title: Trends in Transmissibility of 2019 Novel Coronavirus-infected Pneumonia in Wuhan and 29 Provinces in China
abstract: The 2019 novel coronavirus infected pneumonia (COVID- 19) represents a significant public health threat. The COVID-19 emerged in December 2019 in Wuhan, China and rapidly spread to other regions and countries. The variation in transmission patterns and disease spread in regard to time or among different locations, partially reflecting the public health in- tervention effects, remains to be quantified. As most transmissibility-related epidemic parameters are unknown, we sought, with minimal assumptions, to estimate real-time transmissibility and forecast new cases using dynamic modelling.  Using the cases reported from the National Health Commission of China and transportation data, including the total number of travelling hours through railway, airplane, and car outbound from Wuhan, we have built a time-series model to estimate real-time underlying transmission rates of newly generated cases sequentially from January 20, 2020 to Feb 13, 2020 in Wuhan, Hubei province and other 28 provinces in China. We quantified the instantaneous transmission rate and relative reproduction number (R_t) of COVID-19, and evaluated whether public health intervention affected the case transmissibility in each province. Based on the current estimates, we have predicted the trend of disease spread with a high level of certainty.  We estimated that R_t declined from the range of 4 to 5 towards 1 and remained below unity, while there was an initial growth followed by a decline in a shorter period in Hubei and other provinces. The ratio of transmission rates decreased dramatically from January 23 to 27 likely due to the rigorous public health intervention implemented by the government beginning on January 23, 2020. The mean duration of the infectious period was 6 to 9 days. We have predicted the trend of infection sizes which be- came stable in provinces around February 19 to 24, 2020, and the date of containment would be one-week later in Wuhan.  Public health interventions implemented at both the so- cial and personal levels are effective in preventing outbreaks of COVID-19 in Wuhan and other provinces. Model prediction results suggested that COVID- 19 will be contained around the end of February 2020 in China.  Coronavirus, COVID-19, transmissibility, dynamic reproduction number R, statistical modelling, pneumonia outbreak

title: Rotaviral and Coronaviral Diarrhea
abstract: Rotaviruses and coronaviruses are very common causes of calfhood diarrhea throughout the world. Rotaviral and coronaviral infections in neonatal calves can produce a severe diarrhea of high morbidity but of variable mortality depending upon secondary bacterial infections and electrolyte imbalances. Laboratory diagnosis of rotaviral and coronaviral diarrhea is mostly done by detection of virus particles or virus antigens in fecal specimens. The sample of choice for these diagnostic tests is a fresh fecal sample collected directly from the calf as close as possible to the onset of diarrhea.

title: Docetaxel induces moderate ovarian toxicity in mice, primarily affecting granulosa cells of early growing follicles
abstract: Advances in cancer therapy have focused attention on the quality of life of cancer survivors. Since infertility is a major concern following chemotherapy, it is important to characterize the drug-specific damage to the reproductive system to help find appropriate protective strategies. This study investigates the damage on neonatal mouse ovary maintained in vitro for 6 days, and exposed for 24 h (on Day 2) to clinically relevant doses of Docetaxel (DOC; low: 0.1 µM, mid: 1 µM, high: 10 µM). Furthermore, the study explores the putative protective action exerted by Tri-iodothyronine (T3; 10(−7) M). At the end of culture, morphological analyses and follicle counts showed that DOC negatively impacts on early growing follicles, decreasing primary follicle number and severely affecting health at the transitional and primary stages. Poor follicle health was mainly due to effects on granulosa cells, indicating that the effects of DOC on oocytes were likely to be secondary to granulosa cell damage. DOC damages growing follicles specifically, with no direct effect on the primordial follicle reserve. Immunostaining and western blotting showed that DOC induces activation of intrinsic, type II apoptosis in ovarian somatic cells; increasing the levels of cleaved caspase 3, cleaved caspase 8, Bax and cleaved poly(ADP-ribose) polymerase, while also inducing movement of cytochrome C from mitochondria into the cytosol. T3 did not prevent the damage induced by the low dose of DOC. These results demonstrated that DOC induces a gonadotoxic effect on the mouse ovary through induction of somatic cell apoptosis, with no evidence of direct effects on the oocyte, and that the damaging effect is not mitigated by T3.

title: Video Conferencing Impact on Facial Appearance: Looking Beyond the COVID-19 Pandemic.

title: COVID‐19 and rationally layered social distancing
abstract: I would like to thank Dr. Thomson for the very pertinent and relevant points that he raised in his thoughtful letter Where are we now with COVID-19? . As my response will illustrate, and in what probably will become a defining feature of conversations surrounding COVID-19 for quite some time, attempts to answer will only make room for more questions. As COVID-19 is unfolding, every day is marked by novel developments. Since the editorial went to press , the outbreak has expanded considerably. Over 128,000 individuals were infected worldwide as of March 13, 2020, leading to 4720 deaths . In early March, while the outbreak in China appeared to start to subside , it started to amplify in Europe and the United States. The first fatality in the United States occurred on February 29, 2020 in a suburb of Seattle. On March 4m the first death was reported outside WA state, in CA, and was the 11th death in the United States. On March 6, the first two fatalities were reported in Florida. On March 11, 2020, the World Health Organization declared the outbreak a pandemic [5].

title: The First 75 Days of Novel Coronavirus (SARS-CoV-2) Outbreak: Recent Advances, Prevention, and Treatment
abstract: The recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously known as 2019-nCoV) outbreak has engulfed an unprepared world amidst a festive season. The zoonotic SARS-CoV-2, believed to have originated from infected bats, is the seventh member of enveloped RNA coronavirus. Specifically, the overall genome sequence of the SARS-CoV-2 is 96.2% identical to that of bat coronavirus termed BatCoV RaTG13. Although the current mortality rate of 2% is significantly lower than that of SARS (9.6%) and Middle East respiratory syndrome (MERS) (35%), SARS-CoV-2 is highly contagious and transmissible from human to human with an incubation period of up to 24 days. Some statistical studies have shown that, on average, one infected patient may lead to a subsequent 5.7 confirmed cases. Since the first reported case of coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 on December 1, 2019, in Wuhan, China, there has been a total of 60,412 confirmed cases with 1370 fatalities reported in 25 different countries as of February 13, 2020. The outbreak has led to severe impacts on social health and the economy at various levels. This paper is a review of the significant, continuous global effort that was made to respond to the outbreak in the first 75 days. Although no vaccines have been discovered yet, a series of containment measures have been implemented by various governments, especially in China, in the effort to prevent further outbreak, whilst various medical treatment approaches have been used to successfully treat infected patients. On the basis of current studies, it would appear that the combined antiviral treatment has shown the highest success rate. This review aims to critically summarize the most recent advances in understanding the coronavirus, as well as the strategies in prevention and treatment.

title: The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19: an individual-based modelling study
abstract: The rising COVID-19 pandemic caused many governments to impose policies restricting social interactions. These policies have slowed down the spread of the SARS-CoV-2 virus to the extent that restric- tions can be gradually lifted. Models can be useful to assess the consequences of deconfinement strategies with respect to business, school and leisure activities.  We adapted the individual-based model "STRIDE" to simulate interactions between the 11 million inhabitants of Belgium at the levels of households, workplaces, schools and communities. We calibrated our model to observed hospital incidence and seroprevalence data. STRIDE can explore contact tracing options and account for repetitive leisure contacts in extended household settings (so called "household bubbles") with varying levels of connectivity.  Household bubbles have the potential to reduce the number of COVID-19 hospital admissions by up to 90%. The effectiveness of contact tracing depends on its timing, as it becomes futile more than 4 days after the index case developed symptoms. Assuming that children have a lower level of susceptibility and lower probability to experience symptomatic SARS-CoV-2 infection, (partial) school closure options have relatively little impact on COVID-19 burden.  Not only the absolute number and intensity of physical contacts drive the transmission dynamics and COVID-19 burden, also their repetitiveness is influential. Contact tracing seems essential for a controlled and persistent release of lockdown measures, but requires timely compliance to testing, reporting and self-isolation. Rapid tracing and testing, and communication ensuring continued involvement of the population are therefore essential.

title: Diagnostic Imaging of Chest
abstract: Influenza A(H1N1) is caused by the conflict of interest between giant organisms and microorganisms. Influenza A and B viruses are single stranded RNA envelope virus composed of 890–2,341 nucleic acids in eight segmented genomes. Presently, only the virus subtypes of H1N1 and H3N2 still spread from human to human. The viruses spread and replicate under the following conditions: (1) the viruses enter the human body and duplicate there; (2) the viruses cause diseases; and (3) the viruses can easily spread from person to person. The H1N1 influenza viruses replicate is within only respiratory epithelial cells. The virus entering into the cells causes complex pathological changes of the cells. The columnar epithelial cells stop the self-synthesis of cellular component proteins. Therefore, the cells die due to their lack of necessary cell component proteins.

title: The spread of the COVID‐19 coronavirus: Health agencies worldwide prepare for the seemingly inevitability of the COVID‐19 coronavirus becoming endemic
abstract: While it is too late to confine the COVID‐19 coronovirus outbreak to China, a wealth of data spurs epidemiological and vaccine research.

title: Substantial underestimation of SARS-CoV-2 infection in the United States due to incomplete testing and imperfect test accuracy
abstract: Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Current confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Using a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy, we estimated 6,275,072 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) as of April 18, 2020. Accounting for uncertainty, the number of infections was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference was due to incomplete testing, while 14% (0.3-36%) was due to imperfect test accuracy. Estimates of SARS-CoV-2 infections that transparently account for testing practices and diagnostic accuracy reveal that the pandemic is larger than confirmed case counts suggest.

title: The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
abstract: Recent outbreak of a novel coronavirus disease 2019 (COVID-19) has led a rapid global spread around the world. For controlling COVID-19 outbreaks, many countries have implemented two non-pharmaceutical interventions: suppression like immediate lock-downsin cities at epicentre of outbreak; or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both interventions have apparent pros and cons; the effectiveness of any one intervention in isolation is limited. It is crucial but hard to know how and when to take which level of interventions tailored to the specific situation in each country. We aimed to conduct a feasibility study for robustly accessing the effect of multiple interventions to control the number and distribution of infections, growth of deaths, peaks and lengths of COVID-19 breakouts in the UK and other European countries, accounting for balance of healthcare demand.  We developed a model to attempt to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in the UK. Our model assumed that each intervention has equivalent effect on the reproduction number R across countries and over time; where its intensity was presented by average-number contacts with susceptible individuals as infectious individuals; early immediate intensive intervention led to increased health need and social anxiety. We considered two important features: direct link between Exposed and Recovered population, and practical healthcare demand by separation of infections into mild, moderate and critical cases. Our model was fitted and calibrated with date on cases of COVID-19 in Wuhan to estimate how suppression intervention impacted on the number and distribution of infections, growth of deaths over time during January 2020, and April 2020. We combined the calibrated model with data on the cases of COVID-19 in London and non-London regions in the UK during February 2020 and April 2020 to estimate the number and distribution of infections, growth of deaths, and healthcare demand by using multiple interventions. We applied the calibrated model to the prediction of infection and healthcare resource changes in other 6 European countries based on actual measures they have implemented during this period.  We estimated given that 1) By the date (5th March 2020) of the first report death in the UK, around 7499 people would have already been infected with the virus. After taking suppression on 23rd March, the peak of infection in the UK would have occurred between 28th March and 4th April 2020; the peak of death would have occurred between 18th April and 24th April 2020. 2) By 29th April, no significant collapse of health system in the UK have occurred, where there have been sufficient hospital beds for severe and critical cases. But in the Europe, Italy, Spain and France have experienced a 3 weeks period of shortage of hospital beds for severe and critical cases, leading to many deaths outside hospitals. 3) One optimal strategy to control COVID-19 outbreaks in the UK is to take region-level specific intervention. If taking suppression with very high intensity in London from 23rd March 2020 for 100 days, and 3 weeks rolling intervention between very high intensity and high intensity in non-London regions. The total infections and deaths in the UK were limited to 9.3 million and 143 thousand; the peak time of healthcare demand was due to the 96th day (12th May, 2020), where it needs hospital beds for 68.9 thousand severe and critical cases. 4) If taking a simultaneous 3 weeks rolling intervention between very high intensity and high intensity in all regions of the UK, the total infections and deaths increased slightly to 10 million and 154 thousand; the peak time of healthcare occurs at the 97th day (13th May, 2020), where it needs equivalent hospital beds for severe and critical cases of 73.5 thousand. 5) If too early releasing intervention intensity above moderate level and simultaneously implemented them in all regions of the UK, there would be a risk of second wave, where the total infections and deaths in the UK possibly reached to 23.4 million and 897 thousand.  Considering social and economic costs in controlling COVID-19 outbreaks, long-term suppression is not economically viable. Our finding suggests that rolling intervention is an optimal strategy to effectively and efficiently control COVID-19 outbreaks in the UK and potential other countries for balancing healthcare demand and morality ratio. As for huge difference of population density and social distancing between different regions in the UK, it is more appropriate to implement regional level specific intervention with varied intensities and maintenance periods. We suggest an intervention strategy to the UK that take a consistent suppression in London for 100 days and 3 weeks rolling intervention in other regions. This strategy would reduce the overall infections and deaths of COVID-19 outbreaks, and balance healthcare demand in the UK.

title: Guide to Understanding the 2019 Novel Coronavirus

title: [Covid-19 - radiologic and histologic features]
abstract: We here describe the current knowledge about the radiologic and histologic pulmonary features of covid-19, caused by SARS-CoV-2, and present lung histology from a case with fatal disease Initial findings on computed tomography (CT) typically include peripheral multifocal bilateral ground-glass opacities, and correspondingly microscopic alveolar edema This is followed by peripheral consolidations with air bronchogram and perilobular pattern on CT, signs of organizing pneumonia, corresponding to loose (potentially reversible) fibrosis The posterior parts of the lungs and the lower lobes are typically more markedly affected In severe disease with acute respiratory distress syndrome, thickened interlobular septa and crazy paving pattern appear on CT, which corresponds to histologic diffuse alveolar damage with, depending on the stage of the disease, features such as edema, hyaline membranes, reactive epithelium, inflammation, and fibrosis

title: Positional Bias of MHC Class I Restricted T-Cell Epitopes in Viral Antigens Is Likely due to a Bias in Conservation
abstract: The immune system rapidly responds to intracellular infections by detecting MHC class I restricted T-cell epitopes presented on infected cells. It was originally thought that viral peptides are liberated during constitutive protein turnover, but this conflicts with the observation that viral epitopes are detected within minutes of their synthesis even when their source proteins exhibit half-lives of days. The DRiPs hypothesis proposes that epitopes derive from Defective Ribosomal Products (DRiPs), rather than degradation of mature protein products. One potential source of DRiPs is premature translation termination. If this is a major source of DRiPs, this should be reflected in positional bias towards the N-terminus. By contrast, if downstream initiation is a major source of DRiPs, there should be positional bias towards the C-terminus. Here, we systematically assessed positional bias of epitopes in viral antigens, exploiting the large set of data available in the Immune Epitope Database and Analysis Resource. We show a statistically significant degree of positional skewing among epitopes; epitopes from both ends of antigens tend to be under-represented. Centric-skewing correlates with a bias towards class I binding peptides being over-represented in the middle, in parallel with a higher degree of evolutionary conservation.

title: Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020
abstract: The world is under pressure from the novel COVID-19 pandemic. Indonesia is the fourth most populous country in the world and predicted to be affected significantly over a longer time period. Our paper aims to provide detailed reporting and analyses of the present rapid responses to COVID-19, between January and March 2020, in Indonesia. We particularly highlight responses taken by the governments, non-government organisations and the community. We outline gaps and limitations in the responses, based on our rapid analysis of media contents, from government speeches and reports, social and mass media platforms. We present five recommendations toward more rapid, effective, and comprehensive responses.

title: The development and application of Laboratory Animal Science in China

title: Mobility traces and spreading of COVID-19
abstract: We use human mobility models, for which we are experts, and attach a virus infection dynamics to it, for which we are not experts but have taken it from the literature, including recent publications. This results in a virus spreading dynamics model. The results should be verified, but because of the current time pressure, we publish them in their current state. Recommendations for improvement are welcome. We come to the following conclusions: 1. Complete lockdown works. About 10 days after lockdown, the infection dynamics dies down. This assumes that lockdown is complete, which can be guaranteed in the simulation, but not in reality. Still, it gives strong support to the argument that it is never too late for complete lockdown. 2. As a rule of thumb, we would suggest complete lockdown no later than once 10% of hospital capacities available for COVID-19 are in use, and possibly much earlier. This is based on the following insights: a. Even after lockdown, the infection dynamics continues at home, leading to another tripling of the cases before the dynamics is slowed. b. There will be many critical cases coming from people who were infected before lockdown. Because of the exponential growth dynamics, their number will be large. c. Researchers with more detailed disease progression models should improve upon these statements. 3. Our simulations say that complete removal of infections at child care, primary schools, workplaces and during leisure activities will not be enough to sufficiently slow down the infection dynamics. It would have been better, but still not sufficient, if initiated earlier. 4. Infections in public transport play an important role. In the simulations shown later, removing infections in the public transport system reduces the infection speed and the height of the peak by approximately 20%. Evidently, this depends on the infection parameters, which are not well known.  This does not point to reducing public transport capacities as a reaction to the reduced demand, but rather use it for lower densities of passengers and thus reduced infection rates. 5. In our simulations, removal of infections at child care, primary schools, workplaces, leisure activities, and in public transport may barely have been sufficient to control the infection dynamics if implemented early on. Now according to our simulations it is too late for this, and (even) harsher measures will have to be initiated until possibly a return to such a restrictive, but still somewhat functional regime will again be possible. Evidently, all of these results have to be taken with care. They are based on preliminary infection parameters taken from the literature, used inside a model that has more transport/movement details than all others that we are aware of but still not enough to describe all aspects of reality, and suffer from having to write computer code under time pressure. Optimally, they should be confirmed independently. Short of that, given current knowledge we believe that they provide justification for "complete lockdown" at the latest when about 10% of available hospital capacities for COVID-19 are in use (and possibly earlier; we are no experts of hospital capabilities). What was not investigated in detail in our simulations was contact tracing, i.e. tracking down the infection chains and moving all people along infection chains into quarantine. The case of Singapore has so far shown that this may be successful. Preliminary simulation of that tactic shows that it is difficult to implement for COVID-19, since the incubation time is rather long, people are contagious before they feel sick, or maybe never feel sufficiently sick at all. We will investigate in future work if and how contact tracing can be used together with a restrictive, but not totally locked down regime. When opening up after lockdown, it would be important to know the true fraction of people who are already immune, since that would slow down the infection dynamics by itself. For Wuhan, the currently available numbers report that only about 0.1% of the population was infected, which would be very far away from "herd immunity". However, there have been and still may be many unknown infections.

title: Novel Coronavirus Disease 2019 (COVID-19): An Emerging Infectious Disease in the 21st Century
abstract: At the beginning of the New Year 2020, China alerted the world health organization (WHO) to a cluster of unusual pneumonia cases in Wuhan After extensive speculation, eventually a new species of coronavirus introduced as the causative pathogen of the disease Coronavirus disease 2019 (COVID-19) is a name for the disease, and the virus that causes it is known SARS-CoV-2 The very rapid spread of the COVID-19 in China and in many other countries has caused fear among people across the world The novel coronavirus outbreak declared a Public Health Emergency of International Concern on 30 January 2020  Several databases such as PubMed, Scopus, Google scholar, and BioRxiv were searched for publications reporting on the novel coronavirus up to 29 February 2020 Literature searches were performed using keywords including “Coronavirus 2019”, “2019-nCoV”, “COVID-19”, and “SARS-CoV-2” Moreover, websites such as the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) were searched to retrieve updated data and statistics regarding the novel coronavirus We extracted data on the epidemiology, pathogenesis, virology, clinical manifestations, transmission routes, diagnosis, treatment, and prevention measures  From the 1416 articles identified in the initial search, 53 were remained after title and abstract screening After full-text review, 37 articles were eligible to include in our study Incubation period for COVID-19 is between 2-10 days, according to the World Health Organization (WHO) The case fatality rate in patients infected with SARC-CoV-2 is 4 3%, and the results indicate that the mortality is higher in elderly individuals and patients with chronic conditions including patients with coronary artery disease, diabetes, chronic pulmonary disease, and hypertension The mortality rate in healthy subjects is less than 1%  The outbreak caused by the novel coronavirus is larger than the previous human coronaviruses, showing that the SARS-CoV-2 is an extremely contagious virus However, the mortality rate of COVID-19 is lower than that of other coronaviruses diseases such as SARS or MERS and other viruses like HIV and Ebola Currently, due to the lack of an effective treatment and vaccine, the best way to deal with the COVID-19 disease is to prevent transmission and spread of the virus and to execute personal protective measures

title: Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020
abstract: On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking. As at 20 February, 634 persons on board tested positive for the causative virus. We conducted statistical modelling to derive the delay-adjusted asymptomatic proportion of infections, along with the infections’ timeline. The estimated asymptomatic proportion was 17.9% (95% credible interval (CrI): 15.5–20.2%). Most infections occurred before the quarantine start.

title: When Stay-at-Home Orders Leave Victims Unsafe at Home: Exploring the Risk and Consequences of Intimate Partner Violence during the COVID-19 Pandemic
abstract: The novel coronavirus pandemic (hereafter COVID-19) is likely to have unprecedented impacts on the incidence and impacts of crime and violence globally. This includes impacts to the risk, consequences, and decision-making of women experiencing violence by an intimate partner (hereafter IPV). Most importantly, the COVID-19 pandemic, and its impact on the risk of IPV is likely to differentially impact vulnerable populations, including minority women and those with long histories of victimization and mental health issues. This review paper explores the potential short- and long-term implications of COVID-19 on the risk of IPV, highlighting some of the most recent preliminary data. The economic impact of the COVID-19 pandemic, record levels of male unemployment, added stressors in the home, including the care and home schooling of children, and the social distancing measures required by the epidemiological response, may serve to undermine the decades of progress made in keeping women and children safe at home. Victim police reporting, help-seeking decisions, and social service utilization during the pandemic are likely to be impacted by stay-at-home orders and social distancing requirements. The paper concludes with a discussion of the implications for providing safety planning and self-care for victims and their children.

title: Explaining the Bomb-Like Dynamics of COVID-19 with Modeling and the Implications for Policy
abstract: Using a Bayesian approach to epidemiological compartmental modeling, we demonstrate the bomb-like behavior of exponential growth in COVID-19 cases can be explained by transmission of asymptomatic and mild cases that are typically unreported at the beginning of pandemic events due to lower prevalence of testing. We studied the exponential phase of the pandemic in Italy, Spain, and South Korea, and found the R0 to be 2.56 (95% CrI, 2.41-2.71), 3.23 (95% CrI, 3.06-3.4), and 2.36 (95% CrI, 2.22-2.5) if we use Bayesian priors that assume a large portion of cases are not detected. Weaker priors regarding the detection rate resulted in R0 values of 9.22 (95% CrI, 9.01-9.43), 9.14 (95% CrI, 8.99-9.29), and 8.06 (95% CrI, 7.82-8.3) and assumes nearly 90% of infected patients are identified. Given the mounting evidence that potentially large fractions of the population are asymptomatic, the weaker priors that generate the high R0 values to fit the data required assumptions about the epidemiology of COVID-19 that do not fit with the biology, particularly regarding the timeframe that people remain infectious. Our results suggest that models of transmission assuming a relatively lower R0 value that do not consider a large number of asymptomatic cases can result in misunderstanding of the underlying dynamics, leading to poor policy decisions and outcomes.

title: Accelerated infection testing at scale: a proposal for inference with single test on multiple patients
abstract: In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals, both to determine the line of treatment as well as to know the spread of infection to plan containment, mitigation and future responses. However, the lack of adequate testing kits could be a bottleneck, especially in the case of unanticipated new diseases, such as COVID-19, where the testing technology, manufacturing capability, distribution, human skills and laboratories might be unavailable or in short supply. In addition, the cost of the standard PCR test is approximately USD 48, which is prohibitive for poorer patients and most governments. We address this bottleneck by proposing a test methodology that pools the sample from two (or more) patients in a single test. The key insight is that a single negative result from a pooled sample likely implies negative infection of all the individual patients. and It thereby rules out further tests for the patients. This protocol, therefore, requires significantly fewer tests. This may, however, result in somewhat increased false negatives. Our simulations show that combining samples from two patients with 7% underlying likelihood of infection implies that 36% fewer test kits are required, with 14% additional units of time for testing.

title: Consistent Detection of 2019 Novel Coronavirus in Saliva
abstract: The 2019 novel coronavirus (2019-nCoV) was detected in the self-collected saliva of 91.7% (11/12) of patients. Serial saliva viral load monitoring generally showed a declining trend. Live virus was detected in saliva by viral culture. Saliva is a promising noninvasive specimen for diagnosis, monitoring, and infection control in patients with 2019-nCoV infection.

title: Chapter Four Structural insights into coronavirus entry
abstract: Coronaviruses (CoVs) have caused outbreaks of deadly pneumonia in humans since the beginning of the 21st century. The severe acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and was responsible for an epidemic that spread to five continents with a fatality rate of 10% before being contained in 2003 (with additional cases reported in 2004). The Middle-East respiratory syndrome coronavirus (MERS-CoV) emerged in the Arabian Peninsula in 2012 and has caused recurrent outbreaks in humans with a fatality rate of 35%. SARS-CoV and MERS-CoV are zoonotic viruses that crossed the species barrier using bats/palm civets and dromedary camels, respectively. No specific treatments or vaccines have been approved against any of the six human coronaviruses, highlighting the need to investigate the principles governing viral entry and cross-species transmission as well as to prepare for zoonotic outbreaks which are likely to occur due to the large reservoir of CoVs found in mammals and birds. Here, we review our understanding of the infection mechanism used by coronaviruses derived from recent structural and biochemical studies.

title: COVID-19 Fatality and Comorbidity Risk Factors among Confirmed Patients in Mexico
abstract: As of April 18, 2020, 2.16 million patients in the world had been tested positive with Coronavirus (COVID-19) and 146,088 had died, which accounts for a case fatality rate of 6.76%. In Mexico, according to official statistics (April 18), 7,497 cases have been confirmed with 650 deaths, for a case fatality rate of 8.67%. These estimates, however, may not reflect the final fatality risk among COVID-19 confirmed patients, because they are based on cross-sectional counts of diagnosed and deceased patients, and therefore are not adjusted by time of exposure and right-censorship. In this paper we estimate fatality risks based on survival analysis methods, calculated from individual-level data on symptomatic patients confirmed with COVID-19 recently released by the Mexican Ministry of Health. The estimated fatality risk after 35 days of onset of symptoms is 12.38% (95% CI: 11.37-13.47). Fatality risks sharply rise with age, and significantly increase for males (59%) and individuals with comorbidities (38%-168%, depending on the disease). Two reasons may explain the high COVID-19 related fatality risk observed in Mexico, despite its younger age structure: the high selectivity and self-selectivity in testing and the high prevalence of chronic-degenerative diseases.

title: Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020
abstract: An outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ~11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

title: Do Weather Temperature and Median-age affect COVID-19 Transmission?
abstract: It was observed that the coldest countries and the eldest in terms of median-age were most distressed by COVID-19 pandemic, while the warmest countries and that have younger-aged population were the least affected. Therefore, this study utilized the non-linear least squares method to estimate the impact of weather temperatures and median age on COVID-19 cases per million in thirty-nine countries divided into two groups. The first group composed of twenty-four countries that announced the first COVID-19 case in January 2020, while the second group contains fifteen countries that witnessed the pandemic for the first time in February of the same year. The study revealed some major findings, which are: COVID-19 cases per million were not significantly affected by weather temperature or the median age in “January-group” countries (after 72.67 days on average), while COVID-19 cases per million increased significantly by decreasing temperatures, and increasing the median age in case of “February-group” countries (after an average of 44.80 days). This means that weather temperature and median age may influence the transmission rates of COVID-19 in its early stages, while weather temperature or median age no longer have effects in the advanced stages of the pandemic.

title: Middle East respiratory syndrome coronavirus: quantification of the extent of the epidemic, surveillance biases, and transmissibility
abstract: The novel Middle East respiratory syndrome coronavirus (MERS-CoV) had, as of Aug 8, 2013, caused 111 virologically confirmed or probable human cases of infection worldwide. We analysed epidemiological and genetic data to assess the extent of human infection, the performance of case detection, and the transmission potential of MERS-CoV with and without control measures.  We assembled a comprehensive database of all confirmed and probable cases from public sources and estimated the incubation period and generation time from case cluster data. Using data of numbers of visitors to the Middle East and their duration of stay, we estimated the number of symptomatic cases in the Middle East. We did independent analyses, looking at the growth in incident clusters, the growth in viral population, the reproduction number of cluster index cases, and cluster sizes to characterise the dynamical properties of the epidemic and the transmission scenario.  The estimated number of symptomatic cases up to Aug 8, 2013, is 940 (95% CI 290–2200), indicating that at least 62% of human symptomatic cases have not been detected. We find that the case-fatality ratio of primary cases detected via routine surveillance (74%; 95% CI 49–91) is biased upwards because of detection bias; the case-fatality ratio of secondary cases was 20% (7–42). Detection of milder cases (or clinical management) seemed to have improved in recent months. Analysis of human clusters indicated that chains of transmission were not self-sustaining when infection control was implemented, but that R in the absence of controls was in the range 0·8–1·3. Three independent data sources provide evidence that R cannot be much above 1, with an upper bound of 1·2–1·5.  By showing that a slowly growing epidemic is underway either in human beings or in an animal reservoir, quantification of uncertainty in transmissibility estimates, and provision of the first estimates of the scale of the epidemic and extent of case detection biases, we provide valuable information for more informed risk assessment.  Medical Research Council, Bill & Melinda Gates Foundation, EU FP7, and National Institute of General Medical Sciences.

title: Report on the Epidemiological Features of Coronavirus Disease 2019 (COVID-19) Outbreak in the Republic of Korea from January 19 to March 2, 2020
abstract: Since the first case of coronavirus disease19 (COVID-19) was reported in Wuhan, China, as of March 2, 2020, the total number of confirmed cases of COVID-19 was 89,069 cases in 67 countries and regions. As of 0 am, March 2, 2020, the Republic of Korea had the second-largest number of confirmed cases (n = 4,212) after China (n = 80,026). This report summarizes the epidemiologic features and the snapshots of the outbreak in the Republic of Korea from January 19 and March 2, 2020.

title: The epidemic of 2019-novel-coronavirus (2019-nCoV) pneumonia and insights for emerging infectious diseases in the future
abstract: At the end of December 2019, a novel coronavirus, 2019-nCoV, caused an outbreak of pneumonia spreading from Wuhan, Hubei province, to the whole country of China, which has posed great threats to public health and attracted enormous attention around the world. To date, there are no clinically approved vaccines or antiviral drugs available for these human coronavirus infections. Intensive research on the novel emerging human infectious coronaviruses is urgently needed to elucidate their route of transmission and pathogenic mechanisms, and to identify potential drug targets, which would promote the development of effective preventive and therapeutic countermeasures. Herein, we describe the epidemic and etiological characteristics of 2019-nCoV, discuss its essential biological features, including tropism and receptor usage, summarize approaches for disease prevention and treatment, and speculate on the transmission route of 2019-nCoV.

title: MERS-CoV geography and ecology in the Middle East: analyses of reported camel exposures and a preliminary risk map
abstract: Middle Eastern respiratory syndrome coronavirus (MERS-CoV) has spread rapidly across much of the Middle East, but no quantitative mapping of transmission risk has been developed to date. Moreover, details of the transmission cycle of the virus remain unclear, particularly regarding the role of camels as a reservoir host for human infections.  We present a first analysis of the environmental circumstances under which MERS-CoV cases have occurred in the Middle East, covering all case occurrences through May 2015, using ecological niche modeling approaches to map transmission risk. We compare the environmental breadth of conditions under which cases have reported camel contacts with that of the broader population of all cases, to assess whether camel-associated cases occur under a more restricted set of environmental circumstances.  We documented geographic and environmental distributions of MERS-CoV cases across the Middle East, and offer preliminary mapping of transmission risk. We confirm the idea that climatic dimensions of camel-associated cases are more constrained and less variable than the broader suite of case occurrences; hence, camel exposure may be a key limiting element in MERS-CoV transmission.  This study offers a first detailed geographic and environmental analysis of MERS-CoV distributions across the Middle East. Results indicated that camel-exposed cases occur under a narrower suite of environmental conditions than non-camel-exposed cases, suggesting perhaps a key role for camels in the transmission of the disease, and perhaps a narrower area of risk for ‘primary,’ camel-derived cases of MERS.

title: Simulating the infected population and spread trend of 2019-nCov under different policy by EIR model
abstract: Chinese government has taken strong measures in response to the epidemic of new coronavirus (2019-nCoV) from Jan.23, 2020. The number of confirmed infected individuals are still increasing rapidly. Estimating the accurate infected population and the future trend of epidemic spreading under control measures is significant and urgent. There have been reports external icon of spread from an infected patient with no symptoms to a close contact, which means the incubation individuals may has the possibility of infectiousness. However, the traditional transmission model, Susceptible-Exposed-Infectious-Recovered (SEIR) model, assumes that the exposed individual is being infected but without infectiousness. Thus, the estimating infected populations based on SEIR model from the existing literatures seems too far more than the official reported data. Here, we inferred that the epidemic could be spread by exposed (incubation) individuals. Then, we provide a new Exposed-identified-Recovered (EIR) model, and simulated the epidemic spreading processes from free propagation phase to extremely control phase. Then, we estimate of the size of the epidemic and forecast the future development of the epidemics under strong prevention interventions. According to the spread characters of 2019-nCov, we construct a novel EIR compartment system dynamics model. This model integrates two phases of the epidemic spreading: before intervention and after intervention. We assume that 2019-nCov is firstly spread without intervention then the government started to take strong quarantine measures. Use the latest reported official data, we estimate the basic parameters of the model and the basic reproduction number of 2019-nCov. Then, based on this model, we simulate the future spread of the epidemics. Both the infected population and the spreading trend of 2019-nCov under different prevention policy scenarios are estimated. The epidemic spreading trends under different quarantine rate and action starting date of prevention policy are simulated and compared.

title: Clinical Characteristics of COVID-19 Patients With Digestive Symptoms in Hubei, China: A Descriptive, Cross-Sectional, Multicenter Study
abstract: Since the outbreak of Coronavirus Disease 2019 (COVID-19) in December 2019, various digestive symptoms have been frequently reported in patients infected with the virus. In this study, we aimed to further investigate the prevalence and outcomes of COVID-19 patients with digestive symptoms.  In this descriptive, cross-sectional, multicenter study, we enrolled confirmed patients with COVID-19 who presented to 3 hospitals from January 18, 2020, to February 28, 2020. All patients were confirmed by real-time polymerase chain reaction and were analyzed for clinical characteristics, laboratory data, and treatment. Data were followed up until March 18, 2020.  In the present study, 204 patients with COVID-19 and full laboratory, imaging, and historical data were analyzed. The average age was 52.9 years (SD ± 16), including 107 men and 97 women. Although most patients presented to the hospital with fever or respiratory symptoms, we found that 103 patients (50.5%) reported a digestive symptom, including lack of appetite (81 [78.6%] cases), diarrhea (35 [34%] cases), vomiting (4 [3.9%] cases), and abdominal pain (2 [1.9%] cases). If lack of appetite is excluded from the analysis (because it is less specific for the gastrointestinal tract), there were 38 total cases (18.6%) where patients presented with a gastrointestinal-specific symptom, including diarrhea, vomiting, or abdominal pain. Patients with digestive symptoms had a significantly longer time from onset to admission than patients without digestive symptoms (9.0 days vs 7.3 days). In 6 cases, there were digestive symptoms, but no respiratory symptoms. As the severity of the disease increased, digestive symptoms became more pronounced. Patients with digestive symptoms had higher mean liver enzyme levels, lower monocyte count, longer prothrombin time, and received more antimicrobial treatment than those without digestive symptoms.  We found that digestive symptoms are common in patients with COVID-19. Moreover, these patients have a longer time from onset to admission, evidence of longer coagulation, and higher liver enzyme levels. Clinicians should recognize that digestive symptoms, such as diarrhea, are commonly among the presenting features of COVID-19 and that the index of suspicion may need to be raised earlier in at-risk patients presenting with digestive symptoms. However, further large sample studies are needed to confirm these findings.

title: Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible?
abstract: Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.

title: Asymptomatic cases with SARS‐CoV‐2 infection
abstract: On 31 March 2020, Chinese Health Authorization announced that numbers of asymptomatic cases with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection will be made to the public daily. This was a very important step since different counties have different capacities for the detection of SARS‐CoV‐2 infection and control strategy for the Coronavirus Disease 2019 outbreak. We summarized the characteristics of asymptomatic SARS‐CoV‐2 infections and the transmission potential of asymptomatic cases. Then we provided guidelines for the management of asymptomatic cases through quarantine and nucleic acid/serology tests.

title: Bioinformatics and evolutionary insight on the spike glycoprotein gene of QX-like and Massachusetts strains of infectious bronchitis virus
abstract: Infectious bronchitis virus (IBV) is a Gammacoronavirus of the family Coronaviridae and is a causative agent of an economically important disease in poultry. The spike glycoprotein of IBV is essential for host cell attachment, neutralization, and is involved in the induction of protective immunity. Previously obtained sequence data of the spike gene of IBV QX-like and Massachusetts strains were subjected to bioinformatics analysis.  On analysis of potential phosphorylation sites, the Ser542 and Ser563 sites were not present in Massachusetts strains, while QX-like isolates did not have the Ser534 site. Massachusetts and QX-like strains showed different cleavage site motifs. The N-glycosylation sites ASN-XAA-SER/THR-55, 147, 200 and 545 were additionally present in QX-like strains. The leucine-rich repeat regions in Massachusetts strains consisted of stretches of 63 to 69 amino acids, while in the QX-like strains they contained 59 amino acids in length. An additional palmitoylation site was observed in CK/SWE/082066/2010 a QX-like strain. Primary structure data showed difference in the physical properties and hydrophobic nature of both genotypes. The comparison of secondary structures revealed no new structural domains in the genotypic variants. The phylogenetic analyses based on avian and mammalian coronaviruses showed the analysed IBV as closely related to turkey coronaviruses and distantly related to thrush and munia coronaviruses.  The study demonstrated that spike glycoprotein of the Massachusetts and the QX-like variants of IBV are molecularly distinct and that this may reflect in differences in the behavior of these viruses in vivo.

title: Quantifying the prevalence of SARS-CoV-2 long-term shedding among non-hospitalized COVID-19 patients
abstract: With anecdotal reports of viral shedding from COVID-19 patients for several weeks, there is a need to quantify the prevalence of long-term SARS-CoV-2 shedding. Here, we characterize the temporal distribution of diagnostic SARS-CoV-2 PCR outcomes from nasopharyngeal swabs and associated EHR-derived features over two months for 874 COVID-19 patients with longitudinal data. Among a cohort of 379 COVID-19 patients with at least one positive follow-up SARS-CoV-2 PCR test, 53 patients remain SARS-CoV-2-positive after four weeks of initial diagnosis. Surprisingly, a majority of COVID-19 patients with long-term viral shedding are not hospitalized (40 of 53 patients), and have no enrichments among symptoms, demographics, or medical history. In a cohort of 370 COVID-19 patients that transition to a confirmed negative status, the upper bound of viral shedding duration has a mean of 21.2 days with standard deviation of 9.3 days. Of the 81 PCR-confirmed COVIDpos patients who have undergone serologic testing, 68 patients have developed anti-SARS-CoV-2 IgG to date, with a mean upper bound of time to seroconversion of 38.1 days (95% C.I. = 35.2-41.1 days). Given that SARS-CoV-2 PCR testing may detect replication incompetent virus and that serologic tests do not imply neutralizing immunity, we suggest that the development of novel assays for measuring infectious viral load in non-hospitalized long-term shedders may help mitigate community transmission. This study motivates a platform that can link longitudinal diagnostic and serologic testing with real-time epidemiological data, towards proactively identifying and managing emerging hotspots of COVID-19.

title: Infección por coronavirus (COVID-19) en Anales de Pediatría

title: Coronavirus close-up, faded star and orchestral operation - February's best science images.

title: Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model
abstract: The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment  see text] was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

title: Evolving status of the 2019 novel coronavirus infection: Proposal of conventional serologic assays for disease diagnosis and infection monitoring
abstract: The novel coronavirus (nCoV-2019) outbreak in Wuhan, China has spread rapidly nationwide, with some cases occurring in other parts of the world. Although most patients present with mild febrile illness with patchy pulmonary inflammation, a significant portion develop severe acute respiratory distress syndrome (ARDS), with a current case fatality of 2.3-3%. Diagnosis is based on clinical history and laboratory and chest radiographic findings, but confirmation currently relies on nucleic acid-based assays. The latter are playing an important role in facilitating patient isolation, treatment and assessment of infectious activities. However, due to their limited capacity to handle an epidemic of the current scale and insufficient supply of assay kits, only a portion of suspected cases can be tested, leading to incompleteness and inaccuracy in updating new cases, as well as delayed diagnosis. Furthermore, there has not been enough time to assess specificity and sensitivity. Conventional serological assays, such as enzyme-linked immunoassay (ELISA) for specific IgM and IgG antibodies, should offer a high-throughput alternative, which allows for uniform tests for all suspected patients, and can facilitate more complete identification of infected cases and avoidance of unnecessary cross infection among unselected patients. This article is protected by copyright. All rights reserved.

title: An update on COVID-19 for the radiologist - A British society of Thoracic Imaging statement

title: Associations between psychiatric disorders, COVID-19 testing probability and COVID-19 testing results: Findings from a population-based study
abstract: The novel COVID-19 pandemic has affected over 2.4 million people worldwide. Little is known about COVID-19 testing rates and COVID-19 test outcomes in people with mental illness. We hypothesized that people with psychiatric disorders are less likely to undergo COVID-19 testing and more likely to test positive.  We used data on COVID-19 testing in the UK Biobank (UKB) cohort to compare the prevalence of COVID-19 testing and test outcomes among individuals with psychiatric disorders to those without such diagnoses. We further investigated associations of testing probability and outcome with psychiatric diagnostic categories.  Individuals with psychiatric disorders were overrepresented among the 1 474 UKB participants with test data: 23% of the COVID-19 test sample had a psychiatric diagnosis compared to 10% in the full cohort (p<0.0001). This overrepresentation persisted for each of the specific psychiatric disorders tested. Furthermore, individuals with a psychiatric disorder (p=0.01), particularly with substance use disorder (p<0.005), had negative test results significantly more often than individuals without psychiatric disorders. Sensitivity analyses confirmed our results.  In contrast with our hypotheses, UKB participants with psychiatric disorders have been tested for COVID-19 more frequently than individuals without a psychiatric history, pleading against the notion that limited health care access is preventing them from undergoing testing. Among those tested, test outcomes were more frequently negative for UKB participants with psychiatric disorders than in others, countering arguments that people with mental illness are more prone to contract the virus.

title: COVID-19 and Thrombotic or Thromboembolic Disease: Implications for Prevention, Antithrombotic Therapy, and Follow-up
abstract: Coronavirus disease 2019 (COVID-19), a viral respiratory illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may predispose patients to thrombotic disease, both in the venous and arterial circulations, due to excessive inflammation, platelet activation, endothelial dysfunction, and stasis. In addition, many patients receiving antithrombotic therapy for thrombotic disease may develop COVID-19, which can have implications for choice, dosing, and laboratory monitoring of antithrombotic therapy. Moreover, during a time with much focus on COVID-19, it is critical to consider how to optimize the available technology to care for patients without COVID-19 who have thrombotic disease. Herein, we review the current understanding of the pathogenesis, epidemiology, management and outcomes of patients with COVID-19 who develop venous or arterial thrombosis, and of those with preexisting thrombotic disease who develop COVID-19, or those who need prevention or care for their thrombotic disease during the COVID-19 pandemic.

title: Measures of frequency: calculating prevalence and incidence in the era of COVID-19.

title: A demographic scaling model for estimating the total number of COVID-19 infections
abstract: The total number of COVID-19 infections is critical information for decision makers when assessing the progress of the pandemic, its implications, and policy options. Despite efforts to carefully monitor the COVID-19 pandemic, the reported number of confirmed cases is likely to underestimate the actual number of infections. We aim to estimate the total number of COVID-19 infections in a straightforward manner using a demographic scaling approach based on life tables.  We use data on total number of COVID-19 attributable deaths, population counts, and life tables as well as information on infection fatality rates as reported in Verity et al. (2020) for Hubei, China. We develop a scaling approach based on life tables and remaining life expectancy to map infection fatality rates between two countries to account for differences in their age structure, health status, and the health care system. The scaled infection fatality rates can be used in combination with COVID-19 attributable deaths to calculate estimates of the total number of infected. We also introduce easy to apply formulas to quantify the bias that would be required in death counts and infection fatality rates in order to reproduce a certain estimate of infections.  Across the 10 countries with most COVID-19 deaths as of April 17, 2020, our estimates suggest that the total number of infected is approximately 4 times the number of confirmed cases. The uncertainty, however, is high, as the lower bound of the 95% prediction interval suggests on average twice as many infections than confirmed cases, and the upper bound 10 times as many. Country-specific variation is high. For Italy, our estimates suggest that the total number of infected is approximately 1 million, or almost 6 times the number of confirmed cases. For the U.S., our estimate of 1.4 million is close to being twice as large as the number of confirmed cases, and the upper bound of 3 million is more than 4 times the number of confirmed cases. For Germany, where testing has been comparatively extensive, we estimate that the total number of infected is only 1.2 times (upper bound: 3 times) than the number of confirmed cases. Comparing our results with findings from local seroprevalence studies and applying our bias formulas shows that some of their infection estimates would only be possible if just a small fraction of COVID-19 related deaths were recorded, indicating that these seroprevalence estimates might not be representative for the total population.  As many countries lack population based seroprevalence studies, straightforward demographic adjustment can be used to deliver useful estimates of the total number of infected cases. Our results imply that the total number COVID-19 cases may be approximately 4 times (95%: 2 to 10 times) that of the confirmed cases. Although these estimates are uncertain and vary across countries, they indicate that the COVID-19 pandemic is much more broadly spread than what confirmed cases would suggest, and the number of asymptomatic cases or cases with mild symptoms may be high. In cases in which estimates from local seroprevalence studies or from simulation models exist, our approach can provide a simple benchmark to assess the quality of those estimates.

title: Is reporting many cases of COVID-19 in Iran due to strength or weakness of iran’s health system?

title: From China: hope and lessons for COVID-19 control

title: Assessing the interactions between COVID-19 and influenza in the United States
abstract: The 2019–2020 influenza sentinel surveillance data exhibits unexpected trends. Typical influenza seasons have a small herald wave, followed by a decrease due to school closure during holidays, and then a main post-holiday peak that is significantly larger than the pre-holiday wave. During the 2019–2020 influenza season, influenza-like illness data in the United States appears to have a markedly lower main epidemic peak compared to what would be expected based on the pre-holiday peak. We hypothesize that the 2019–2020 influenza season does have a lower than expected burden and that this deflation is due to a behavioral or ecological interaction with COVID-19. We apply an intervention analysis to assess if this influenza season deviates from expectations, then we compare multiple hypothesized drivers of the decrease in influenza in a spatiotemporal regression model. Lastly, we develop a mechanistic metapopulation model, incorporating transmission reduction that scales with COVID-19 risk perception. We find that the 2019–2020 ILI season is smaller and decreases earlier than expected based on prior influenza seasons, and that the increase in COVID-19 risk perception is associated with this decrease. Additionally, we find that a 5% average reduction in transmission is sufficient to reproduce the observed flu dynamics. We propose that precautionary behaviors driven by COVID-19 risk perception or increased isolation driven by undetected COVID-19 spread dampened the influenza season. We suggest that when surveillance for a novel pathogen is limited, surveillance streams of co-circulating infections may provide a signal.

title: Analysis of early renal injury in COVID-19 and diagnostic value of multi-index combined detection
abstract: The aim of the study was to analyze the incidence of COVID-19 with early renal injury, and to explore the value of multi-index combined detection in diagnosis of early renal injury in COVID-19.  The study was an observational, descriptive study.  This study was carried out in a tertiary hospital in Guangdong, China. Participants 12 patients diagnosed with COVID-19 from January 20, 2020 to February 20, 2020. Primary and secondary outcome measures The primary outcome was to evaluate the incidence of early renal injury in COVID-19. In this study, the estimated glomerular filtration rate (eGFR), endogenous creatinine clearance (Ccr) and urine microalbumin / urinary creatinine ratio (UACR) were calculated to assess the incidence of early renal injury. Secondary outcomes were the diagnostic value of urine microalbumin (UMA), 1-microglobulin (A1M), urine immunoglobulin-G (IGU), urine transferring (TRU) alone and in combination in diagnosis of COVID-19 with early renal injury.  While all patients had no significant abnormalities in serum creatinine (Scr) and blood urea nitrogen (BUN), the abnormal rates of eGFR, Ccr, and UACR were 66.7%, 41.7%, and 41.7%, respectively. Urinary microprotein detection indicated that the area under curve (AUC) of multi-index combined to diagnose early renal injury in COVID-19 was 0.875, which was higher than UMA (0,813), A1M (0.813), IGU (0.750) and TRU (0.750) alone. Spearman analysis showed that the degree of early renal injury was significantly related to C-reactive protein (CRP) and neutrophil ratio (NER), suggesting that the more severe the infection, the more obvious the early renal injury. Hypokalemia and hyponatremia were common in patients with COVID-19, and there was a correlation with the degree of renal injury.  Early renal injury was common in patients with COVID-19. Combined detection of UMA, A1M, IGU, and TRU was helpful for the diagnosis of early renal injury in COVID-19.

title: Modeling the Corona Virus Outbreak in IRAN
abstract: As the outbreak of coronavirus disease 2019 (COVID19) is a worldwide pandemic it is rapidly expanding in Iran realtime analyses of epidemiological data are needed to increase situational awareness and inform interventions. In this study we built a predictive model based on the cumulative trend of new cases and deaths for the top five provinces. we will also look at modeling the trends for confirmed cases deaths and recovered for the whole country.  In this study we have chosen to apply the exponential smoothing model to iteratively forecast future values of a regular time seires from weighted averages of past daily values of the series. This method is exponential because the value of each level is influenced by every preceeding actual value to an exponentially decreasing degree more recent values are given a greater weight. The available data is too small to identify seasonal patterns and make predictable variation in value, such as annual fluctuation in temperature relative to the season. Trend is a tendency in the data to increase or decrease over time.  If no control measures are put in place it is expected that over 40000 would be infected in Tehran around the middle of June. However if control measures were implemented with a high degree of success one would expect the spread of the COV19 virus would peak at the start of April with a downward trend dropping off by the end of May (70 days). In the scenario that no further measures are implemented, one would expect the spread of COVID19 to continue on a gentle incline reaching 21000 by mid-June. The same process has been applied to review the confirmed deaths and recovered dataset. The forecast has been carried out for the next 30 days a shorter timeframe has been selected as there is a high probability that the Iranian New Years celebration Farvardin first month of Spring (30th March in Western calendar) will have an impact on the infection rate following the event. The best predictive model predicts the confirmed cases to be in the range of 35000 70000 with the number of reported COVDI-19 deaths to be between 3000 5000 and 5000 30000 of recovered cases.  Modeling outbreak ofCovid19 shows that the number of patients and deaths is still increasing. Contagious diseases follow an exponential model and the same be Haves this one. This is because the virus can spread to others and finally each person turns into a carrier of the virus and transmit it to another person. Disease control depends on disconnection and social distancing. In addition many factors are effective in stopping the disease. These include citizens participation in the prevention process health education the effectiveness of instructive traditions environmental conditions and so on.

title: Projecting the transmission dynamics of SARS-CoV-2 through the post-pandemic period
abstract: There is an urgent need to project how transmission of the novel betacoronavirus SARS-CoV-2 will unfold in coming years. These dynamics will depend on seasonality, the duration of immunity, and the strength of cross-immunity to/from the other human coronaviruses. Using data from the United States, we measured how these factors affect transmission of human betacoronaviruses HCoV-OC43 and HCoV-HKU1. We then built a mathematical model to simulate transmission of SARS-CoV-2 through the year 2025. We project that recurrent wintertime outbreaks of SARS-CoV-2 will probably occur after an initial pandemic wave. We summarize the full range of plausible transmission scenarios and identify key data still needed to distinguish between them, most importantly longitudinal serological studies to determine the duration of immunity to SARS-CoV-2.

title: Response to "Lupus anticoagulant is frequent in patients with Covid-19" (JTH-2020-00483)

title: Case Report: The Importance of Novel Coronavirus Disease (COVID-19) and Coinfection with Other Respiratory Pathogens in the Current Pandemic
abstract: The early shortage of novel coronavirus disease (COVID-19) tests in the United States led many hospitals to first screen for common respiratory pathogens, and only if this screen was negative to proceed with COVID-19 testing. We report a case of a 56-year-old woman with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) coinfection with group A Streptococcus. The initial testing strategy resulted in delays in both diagnosis and implementation of appropriate precautions. Underlined is the importance of testing for both SARS-CoV-2 and other common respiratory pathogens during the current pandemic.

title: Prevalence of comorbid asthma in COVID-19 patients

title: Stem Cells and Cell Therapy Approaches in Lung Biology and Diseases
abstract: Cell-based therapies with embryonic or adult stem cells, including induced pluripotent stem cells, have emerged as potential novel approaches for several devastating and otherwise incurable lung diseases including emphysema, pulmonary fibrosis, pulmonary hypertension, and the acute respiratory distress syndrome. Although initial studies suggested engraftment of exogenously administered stem cells in lung, this is now generally felt to be a rare occurrence of uncertain physiologic significance. However, more recent studies have demonstrated paracrine effects of administered cells, including stimulation of angiogenesis and modulation of local inflammatory and immune responses in mouse lung disease models. Based on these studies and on safety and initial efficacy data from trials of adult stem cells in other diseases, groundbreaking clinical trials of cell-based therapy have been initiated for pulmonary hypertension and for chronic obstructive pulmonary disease. In parallel, the identity and role of endogenous lung progenitor cells in development and in repair from injury and potential contribution as lung cancer stem cells continue to be elucidated. Most recently, novel bioengineering approaches have been applied to develop functional lung tissue ex vivo. Advances in each of these areas will be described in this review with particular reference to animal models.

title: Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020
abstract: Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19.  To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020.  This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020.  Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data.  There were approximately 781â¯000 total deaths in the United States from March 1 to May 30, 2020, representing 122â¯300 (95% prediction interval, 116â¯800-127â¯000) more deaths than would typically be expected at that time of year. There were 95â¯235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths.  Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

title: The effect of travel restrictions on the spread of the 2019 novel coronavirus (2019-nCoV) outbreak
abstract: Motivated by the rapid spread of a novel coronavirus (2019-nCoV) in Mainland China, we use a global metapopulation disease transmission model to project the impact of both domestic and international travel limitations on the national and international spread of the epidemic. The model is calibrated on the evidence of internationally imported cases before the implementation of the travel quarantine of Wuhan. By assuming a generation time of 7.5 days, the reproduction number is estimated to be 2.4 [90% CI 2.2–2.6]. The median estimate for number of cases before the travel ban implementation on January 23, 2020 is 58,956 [90% CI 40,759 – 87,471] in Wuhan and 3,491 [90% CI 1,924 – 7,360] in other locations in Mainland China. The model shows that as of January 23, most Chinese cities had already received a considerable number of infected cases, and the travel quarantine delays the overall epidemic progression by only 3 to 5 days. The travel quarantine has a more marked effect at the international scale, where we estimate the number of case importations to be reduced by 80% until the end of February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

title: Incidence, clinical outcomes, and transmission dynamics of hospitalized 2019 coronavirus disease among 9,596,321 individuals residing in California and Washington, United States: a prospective cohort study
abstract: The United States is now the country reporting the highest number of 2019 coronavirus disease (COVID-19) cases and deaths. However, little is known about the epidemiology and burden of severe COVID-19 to inform planning within healthcare systems and modeling of intervention impact.  We assessed incidence, duration of hospitalization, and clinical outcomes of acute COVID-19 inpatient admissions in a prospectively-followed cohort of 9,596,321 individuals enrolled in comprehensive, integrated healthcare delivery plans from Kaiser Permanente in California and Washington state. We also estimated the effective reproductive number (RE) describing transmission in the study populations.  Data covered 1277 hospitalized patients with laboratory- or clinically-confirmed COVID-19 diagnosis by April 9, 2020. Cumulative incidence of first COVID-19 acute inpatient admission was 10.6-12.4 per 100,000 cohort members across the study regions. Mean censoring-adjusted duration of hospitalization was 10.7 days (2.5-97.5%iles: 0.8-30.1) among survivors and 13.7 days (2.5-97.5%iles: 1.7-34.6) among non-survivors. Among all hospitalized confirmed cases, censoring-adjusted probabilities of ICU admission and mortality were 41.9% (95% confidence interval: 34.1-51.4%) and 17.8% (14.3-22.2%), respectively, and higher among men than women. We estimated RE was 1.43 (1.17-1.73), 2.09 (1.63-2.69), and 1.47 (0.07-2.59) in Northern California, Southern California, and Washington, respectively, for infections acquired March 1, 2020. RE declined to 0.98 (0.76-1.27), 0.89 (0.74-1.06), and 0.92 (0.05-1.55) respectively, for infections acquired March 20, 2020.  We identify high probability of ICU admission, long durations of stay, and considerable mortality risk among hospitalized COVID-19 cases in the western United States. Reductions in RE have occurred in conjunction with implementation of non-pharmaceutical interventions.

title: Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study
abstract: As the outbreak of coronavirus disease 2019 (COVID-19) progresses, epidemiological data are needed to guide situational awareness and intervention strategies. Here we describe efforts to compile and disseminate epidemiological information on COVID-19 from news media and social networks.  In this population-level observational study, we searched DXY.cn, a health-care-oriented social network that is currently streaming news reports on COVID-19 from local and national Chinese health agencies. We compiled a list of individual patients with COVID-19 and daily province-level case counts between Jan 13 and Jan 31, 2020, in China. We also compiled a list of internationally exported cases of COVID-19 from global news media sources (Kyodo News, The Straits Times, and CNN), national governments, and health authorities. We assessed trends in the epidemiology of COVID-19 and studied the outbreak progression across China, assessing delays between symptom onset, seeking care at a hospital or clinic, and reporting, before and after Jan 18, 2020, as awareness of the outbreak increased. All data were made publicly available in real time.  We collected data for 507 patients with COVID-19 reported between Jan 13 and Jan 31, 2020, including 364 from mainland China and 143 from outside of China. 281 (55%) patients were male and the median age was 46 years (IQR 35–60). Few patients (13 [3%]) were younger than 15 years and the age profile of Chinese patients adjusted for baseline demographics confirmed a deficit of infections among children. Across the analysed period, delays between symptom onset and seeking care at a hospital or clinic were longer in Hubei province than in other provinces in mainland China and internationally. In mainland China, these delays decreased from 5 days before Jan 18, 2020, to 2 days thereafter until Jan 31, 2020 (p=0·0009). Although our sample captures only 507 (5·2%) of 9826 patients with COVID-19 reported by official sources during the analysed period, our data align with an official report published by Chinese authorities on Jan 28, 2020.  News reports and social media can help reconstruct the progression of an outbreak and provide detailed patient-level data in the context of a health emergency. The availability of a central physician-oriented social network facilitated the compilation of publicly available COVID-19 data in China. As the outbreak progresses, social media and news reports will probably capture a diminishing fraction of COVID-19 cases globally due to reporting fatigue and overwhelmed health-care systems. In the early stages of an outbreak, availability of public datasets is important to encourage analytical efforts by independent teams and provide robust evidence to guide interventions.

title: Geographic Differences in COVID-19 Cases, Deaths, and Incidence - United States, February 12-April 7, 2020.
abstract: Community transmission of coronavirus disease 2019 (COVID-19) was first detected in the United States in February 2020. By mid-March, all 50 states, the District of Columbia (DC), New York City (NYC), and four U.S. territories had reported cases of COVID-19. This report describes the geographic distribution of laboratory-confirmed COVID-19 cases and related deaths reported by each U.S. state, each territory and freely associated state,* DC, and NYC during February 12-April 7, 2020, and estimates cumulative incidence for each jurisdiction. In addition, it projects the jurisdiction-level trajectory of this pandemic by estimating case doubling times on April 7 and changes in cumulative incidence during the most recent 7-day period (March 31-April 7). As of April 7, 2020, a total of 395,926 cases of COVID-19, including 12,757 related deaths, were reported in the United States. Cumulative COVID-19 incidence varied substantially by jurisdiction, ranging from 20.6 cases per 100,000 in Minnesota to 915.3 in NYC. On April 7, national case doubling time was approximately 6.5 days, although this ranged from 5.5 to 8.0 days in the 10 jurisdictions reporting the most cases. Absolute change in cumulative incidence during March 31-April 7 also varied widely, ranging from an increase of 8.3 cases per 100,000 in Minnesota to 418.0 in NYC. Geographic differences in numbers of COVID-19 cases and deaths, cumulative incidence, and changes in incidence likely reflect a combination of jurisdiction-specific epidemiologic and population-level factors, including 1) the timing of COVID-19 introductions; 2) population density; 3) age distribution and prevalence of underlying medical conditions among COVID-19 patients (1-3); 4) the timing and extent of community mitigation measures; 5) diagnostic testing capacity; and 6) public health reporting practices. Monitoring jurisdiction-level numbers of COVID-19 cases, deaths, and changes in incidence is critical for understanding community risk and making decisions about community mitigation, including social distancing, and strategic health care resource allocation.

title: Small Solitary Ground-Glass Nodule on CT as an Initial Manifestation of Coronavirus Disease 2019 (COVID-19) Pneumonia
abstract: The 2019 novel coronavirus (2019-nCoV) outbreak in Wuhan, Hubei Province, China in 2019 led to large numbers of people being infected and developing atypical pneumonia (coronavirus disease 2019, COVID-19). Typical imaging manifestations of patients infected with 2019-nCoV has been reported, but we encountered an atypical radiological manifestation on baseline computed tomography (CT) images in three patients from Wuhan, China infected with the 2019-nCoV. Surprisingly, the only similar CT finding was a solitary sub-centimeter ground-glass nodule adjacent to bronchovascular bundles, which could be easily overlooked. In addition, the follow-up images in these patients showed how COVID-19 pneumonia evolved from these small nodules. The radiologic manifestation of the three cases will expand contemporary understanding of COVID-19.

title: Development of a dual-gene loop-mediated isothermal amplification (LAMP) detection assay for SARS-CoV-2: A preliminary study
abstract: Severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) has emerged as a rapidly spreading global pathogen stressing the need for development of rapid testing protocols ever than before. The aim of present study was to develop a SARS-CoV-2 detection protocol which can be performed within minimal resources and timeframe. For this purpose, we implemented the reverse transcription loop-mediated isothermal amplification (RT-LAMP) methodology for the qualitative detection of SARS-CoV-2 RNA. In order to improve the detection capability, the RT-LAMP assay was developed to simultaneously amplify two viral genes: ORF1a and N. A total of 45 SARS-CoV-2 associated coronavirus disease 2019 (COVID-19) cases were enrolled. Viral RNA was extracted from the nasopharyngeal swab samples and analyzed simultaneously using PCR and RT-LAMP protocols. Overall, our SARS-CoV-2 dual gene RT-LAMP assay was found to be 95% accurate in detecting positive cases and showed no cross-reactivity or false-positive result in non-COVID-19 samples. Further evaluation on larger and multi-centric cohorts is currently underway to establish the diagnostic accuracy and subsequent implementation into clinical practice and at point-of-care settings.

title: COVID-19, Australia: Epidemiology Report 5 (Reporting week ending 19:00 AEDT 29 February 2020).
abstract: This is the fifth epidemiological report for coronavirus disease 2019 (COVID-19), reported in Australia as at 19:00 Australian Eastern Daylight Time [AEDT] 29 February 2020. It includes data on COVID-19 cases diagnosed in Australia, the international situation and a review of current evidence.

title: Fear, Access, and the Real-Time Estimation of Etiological Parameters for Outbreaks of Novel Pathogens
abstract: Early analysis of outbreaks of novel pathogens to evaluate their likely public health impact depends on fitting predictive models to data gathered and updated in real-time. Both transmission rates and the critical threshold (i.e. the pathogen's 'reproductive number') are inferred by finding the values that provide the best model fit to reported case incidence. These models and inferred results are then the basic tools used for public health planning: how many people expected to be infected, at what scales of time and space, and whether potential intervention strategies impact disease transmission and spread. An underlying assumption, however, is that the ability to observe new cases is either constant, or at least constant relative to diagnostic test availability. We present a demonstration, discussion, and mathematical analysis of how this assumption of predictable observability in disease incidence can drastically impact model accuracy. We also demonstrate how to tailor estimations of these parameters to a few examples of different types of shifting influences acting on detection, depending on the likely sensitivity of surveillance systems to errors from sources such as clinical testing rates and differences in healthcare-seeking behavior from the public over time. Finally, we discuss the implications of these corrections for both historical and current outbreaks.

title: SARS‐CoV‐2 Testing and Outcomes in the First 30 Days after the First Case of COVID‐19 at an Australian Children’s Hospital
abstract: International studies describing COVID‐19 in children have shown low proportions of paediatric cases and generally a mild clinical course. We aimed to present early data on children tested for SARS‐CoV‐2 at a large Australian tertiary children’s hospital according to the state health department guidelines, which varied over time.  We conducted a retrospective cohort study at The Royal Children’s Hospital, Melbourne, Australia. It included all paediatric patients (aged 0–18 years) who presented to the Emergency Department (ED) or the Respiratory Infection Clinic (RIC) and were tested for SARS‐CoV‐2. The 30‐day study period commenced after the first confirmed positive case was detected at the hospital on 21(st) March 2020, until 19(th) April 2020. We recorded epidemiological and clinical data.  There were 433 patients in whom SARS‐CoV‐2 testing was performed in ED (331 (76%)) or RIC (102 (24%)). There were 4 (0.9%) who had positive SARS‐CoV‐2 detected, none of whom were admitted to hospital or developed severe disease. Of these SARS‐CoV‐2 positive patients, 1/4 (25%) had a comorbidity, which was asthma. Of the SARS‐CoV‐2 negative patients, 196/429 (46%) had comorbidities. Risk factors for COVID‐19 were identified in 4/4 SARS‐CoV‐2 positive patients and 47/429 (11%) SARS‐CoV‐2 negative patients.  Our study identified a very low rate of SARS‐CoV‐2 positive cases in children presenting to a tertiary ED or RIC, none of whom were admitted to hospital. A high proportion of patients who were SARS‐CoV‐2 negative had comorbidities.

title: Dynamic Estimation of Epidemiological Parameters of COVID-19 Outbreak and Effects of Interventions on Its Spread
abstract: A key challenge for estimating the epidemiological parameters of the COVID-19 outbreak in Wuhan is the discrepancy between the officially reported number of infections and the true number of infections. A common approach to tackling the challenge is to use the number of infections exported from Wuhan to infer the true number in the city. This approach can only provide a static estimate of the epidemiological parameters before Wuhan lockdown on January 23, 2020, because there are almost no exported cases thereafter. Here, we propose a method to dynamically estimate the epidemiological parameters of the COVID-19 outbreak in Wuhan by recovering true numbers of infections from day-to-day official numbers. Using the method, we provide a comprehensive retrospection on how the disease had progressed in Wuhan from January 19 to March 5, 2020. Particularly, we estimate that the outbreak sizes by January 23 and March 5 were 11,239 [95% CI 4,794--22,372] and 124,506 [95% CI 69,526--265,113], respectively. The effective reproduction number attained its maximum on January 24 (3.42 [95% CI 3.34--3.50]) and became less than 1 from February 7 (0.76 [95% CI 0.65--0.92]). We also estimate the effects of two major government interventions on the spread of COVID-19 in Wuhan. In particular, transportation suspension and large scale hospitalization respectively prevented 33,719 and 90,072 people from getting infected in the nine-day time period right after its implementation.

title: Epidemic Surveillance of Covid-19: Considering Uncertainty and Under-Ascertainment
abstract: Epidemic surveillance is a fundamental part of public health practice. Addressing under-ascertainment of cases is relevant in most surveillance systems, especially in pandemics of new diseases with a large spectrum of clinical presentations as it may influence timings of policy implementation and public risk perception. From this perspective, this article presents and discusses early evidence on under-ascertainment of COVID-19 and its motifs, options for surveillance, and reflections around their importance to tailor public health measures. In the case of COVID-19, systematically addressing and estimating under-ascertainment of cases is essential to tailor timely public health measures, and communicating these findings is of the utmost importance for policy making and public perception.

title: Abstract for the 8th International congress, Molecular Epidemiology and Evolutionary Genetics of Infectious Diseases

title: Invasive Aspergillosis in the Intensive Care Unit: Beyond the Typical Haematological Patient
abstract: Data about incidence of invasive aspergillosis in intensive care units (ICU) are scarce and variable. Incidences ranging from 2 to 24% have been reported, which might reflect different autopsy policies amongst centres. Recent studies have shown that many patients with invasive aspergillosis do not have a haematological diagnosis. Instead, conditions such as chronic obstructive pulmonary disease and liver failure became recognized as important risk factors. The diagnosis remains difficult in these patients, since diagnostic tests have not been widely validated outside the haematological boundaries. Mechanical ventilation precludes the interpretation of clinical signs and radiological diagnosis is clouded by underlying lung pathology. Respiratory cultures lack sensitivity and specificity. At the moment, diagnosis is best made by testing for galactomannan in bronchoalveolar fluid samples (sensitivity and specificity of > 87%). Testing galactomannan in sera has limited sensitivity for the non-neutropenic. Modern diagnostic tests such as PCR and beta-glucan have never been validated in an ICU population. Due mostly to major delays in the diagnosis, mortality exceeds 50%. Although our therapeutic armamentarium against invasive aspergillosis has improved in recent years, data concerning safety and efficacy of new antifungal agents in the ICU setting are lacking.

title: Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification from CT Images
abstract: An outbreak of a novel coronavirus disease (i.e., COVID-19) has been recorded in Wuhan, China since late December 2019, which subsequently became pandemic around the world. Although COVID-19 is an acutely treated disease, it can also be fatal with a risk of fatality of 4.03% in China and the highest of 13.04% in Algeria and 12.67% Italy (as of 8th April 2020). The onset of serious illness may result in death as a consequence of substantial alveolar damage and progressive respiratory failure. Although laboratory testing, e.g., using reverse transcription polymerase chain reaction (RT-PCR), is the golden standard for clinical diagnosis, the tests may produce false negatives. Moreover, under the pandemic situation, shortage of RT-PCR testing resources may also delay the following clinical decision and treatment. Under such circumstances, chest CT imaging has become a valuable tool for both diagnosis and prognosis of COVID-19 patients. In this study, we propose a weakly supervised deep learning strategy for detecting and classifying COVID-19 infection from CT images. The proposed method can minimise the requirements of manual labelling of CT images but still be able to obtain accurate infection detection and distinguish COVID-19 from non-COVID-19 cases. Based on the promising results obtained qualitatively and quantitatively, we can envisage a wide deployment of our developed technique in large-scale clinical studies.

title: Impact of city and residential unit lockdowns on prevention and control of COVID-19
abstract: With respect to the asymptomatic transmission characteristics of the novel coronavirus that appeared in 2019 (COVID-19), a susceptible-asymptomatic-infected-recovered-death (SAIRD) model that considered human mobility was constructed in this study. The dissemination of COVID-19 was simulated using computational experiments to identify the mechanisms underlying the impact of city and residential lockdowns on controlling the spread of the epidemic.  The implementation of measures to lock down cities led to higher mortality rates in these cities, due to reduced mobility. Moreover, implementing city lockdown along with addition of hospital beds led to improved cure and reduced mortality rates. Stringent implementation and early lockdown of residential units effectively controlled the spread of the epidemic, and reduced the number of hospital bed requirements. Collectively, measures to lock down cities and residential units should be taken to prevent the spread of COVID-19. In addition, medical resources should be increased in cities under lockdown. Implementation of these measures would reduce the spread of the virus to other cities and allow appropriate treatment of patients in cities under lockdown.

title: Novel Coronavirus (2019-nCoV) in Disguise
abstract: Novel coronavirus (2019-nCoV) pandemic is currently one of the most influential topics as it not only impacts the field of medicine but most importantly, it affects the lives of many individuals throughout the world. We report an interesting 2019-nCoV case in a tertiary community hospital with the initial concern of acute pyelonephritis without respiratory symptoms that ultimately led to the quarantine of a number of healthcare providers. This case emphasizes the importance of radiological evidence in diagnosing 2019-nCoV in the setting of an initial atypical presentation. It also serves as an example of how healthcare providers may need to increase their suspicion for COVID-19 to ensure self-protection and prompt diagnosis in the era of an ongoing pandemic.

title: COVID-19 diagnostic process in mainland China: the math beyond pneumonia

title: Covid-19 pandemic by the "real-time" monitoring: the Tunisian case and lessons for global epidemics in the context of 3PM strategies
abstract: Covid-19 is neither the first nor the last viral epidemic which societies around the world are, were and will be affected by. Which lessons should be taken from the current pandemic situation? The Covid-19 disease is still not well characterised, and many research teams all over the world are working on prediction of the epidemic scenario, protective measures to populations and sub-populations, therapeutic and vaccination issues, amongst others. Contextually, countries with currently low numbers of Covid-19-infected individuals such as Tunisia are intended to take lessons from those countries which already reached the exponential phase of the infection distribution as well as from those which have the exponential phase behind them and record a minor number of new cases such as China. To this end, in Tunisia, the pandemic wave has started with a significant delay compared with Europe, the main economic partner of the country. In this paper, we do analyse the current pandemic situation in this country by studying the infection evolution and considering potential protective strategies to prevent a pandemic scenario. The model is predictive based on a large number of undetected Covid-19 cases that is particularly true for some country regions such as Sfax. Infection distribution and mortality rate analysis demonstrate a highly heterogeneous picture over the country. Qualitative and quantitative comparative analysis leads to a conclusion that the reliable "real-time" monitoring based on the randomised laboratory tests is the optimal predictive strategy to create the most effective evidence-based preventive measures. In contrast, lack of tests may lead to incorrect political decisions causing either unnecessary over-protection of the population that is risky for a long-term economic recession, or under-protection of the population leading to a post-containment pandemic rebound. Recommendations are provided in the context of advanced predictive, preventive and personalised (3P) medical approach.

title: Use of excess mortality associated with the COVID-19 epidemic as an epidemiological surveillance strategy - preliminary results of the evaluation of six Brazilian capitals
abstract: In early 2020, the World Health Organization (WHO) recognized the pandemic situation of the new coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2), which causes Coronavirus Disease-2019 (COVID-19). In Brazil by the end of April 2020, another 110 thousand cases and 5,000 deaths had been confirmed. The scarcity of laboratory resources and overload of the care network, added to the broad clinical spectrum of the disease, can make it difficult to capture all mortality from this disease through epidemiological surveillance based on individual notification of cases. The aim of this study was to evaluate the excess of deaths in Brazilian capitals with the highest incidence of COVID-19, as a way of validating the method, we also evaluated a capital with low incidence. We assessed weekly mortality from all causes during the year 2020, up to the epidemiological week 17, compared with the previous year. The data were obtained through the National Civil Registry Information Center (CNIRC, acronym in Portuguese). We estimate the expected mortality and the 95% confidence interval by projecting the observed mortality in 2019 for the population of 2020. In the five capitals with the highest incidences it was possible to identify excess deaths in the pandemic period, the age group most affected were those over 60 years old, 31% of the excess deaths occurred in the population between 20 and 59 years old. There was a strong correlation (r = 0.94) between the excess of deaths in each city and the number of deaths confirmed by epidemiological surveillance. There was no excess of deaths in the capital with the lowest incidence, nor among the population under 20 years old. We estimate that epidemiological surveillance managed to capture only 52% of all mortality associated with the COVID-19 pandemic in the cities studied. Considering the simplicity of the method, its low cost and reliability for assessing the real burden of the disease, we believe that the assessment of excess mortality associated with the COVID-19 pandemic should be widely used as a complementary tool to regular epidemiological surveillance and its use should be encouraged by WHO.

title: Estimating the incidence reporting rates of new influenza pandemics at an early stage using travel data from the source country
abstract: During the surveillance of influenza pandemics, underreported data are a public health challenge that complicates the understanding of pandemic threats and can undermine mitigation efforts. We propose a method to estimate incidence reporting rates at early stages of new influenza pandemics using 2009 pandemic H1N1 as an example. Routine surveillance data and statistics of travellers arriving from Mexico were used. Our method incorporates changes in reporting rates such as linearly increasing trends due to the enhanced surveillance. From our results, the reporting rate was estimated at 0·46% during early stages of the pandemic in Mexico. We estimated cumulative incidence in the Mexican population to be 0·7% compared to 0·003% reported by officials in Mexico at the end of April. This method could be useful in estimation of actual cases during new influenza pandemics for policy makers to better determine appropriate control measures.

title: COVID-19 and spinal cord injury and disease: results of an international survey
abstract: An online survey.  To query the international spinal cord medicine community’s engagement with and response to the novel coronavirus (COVID-19) pandemic and to assess pandemic-specific information needs and patient concerns.  An international collaboration of authors and participants.  Two near-identical surveys (one English and one Spanish language) were distributed via the internet. Responses from those questions shared between the surveys were pooled then analyzed; four questions’ responses (those not shared) were analyzed separately.  A total of 783 responses were submitted from six continents. Few participants (5.8%) had tested their outpatients with SCI/D for COVID-19; only 4.4% reported having a patient with SCI/D with the virus. Of respondents who worked at an inpatient facility, 53.3% reported that only individuals with symptoms were being screened and 29.9% said that no screening was occurring. Participants relayed several concerns offered by their patients with SCI/D, including vulnerability to infection (76.9%) and fragility of caretaker supply (42%), and those living in countries with guaranteed health care were more likely to report widespread availability of COVID-19 testing than were those living in countries without universal care, χ(2) (3, N = 625) = 46.259, p < 0.001.  There is substantial variability in the rehabilitation medicine community in COVID-19 screening practices and availability of screening kits. People living with SCI/D are expressing legitimate and real concerns about their vulnerability to COVID-19. More and rapid work is needed to address these concerns and to standardize best-practice protocols throughout the rehabilitation community.

title: Retrospective serological investigation of severe acute respiratory syndrome coronavirus antibodies in recruits from mainland China.
abstract: Different assays were used to analyze 1,621 serum specimens collected from military recruits from the People's Republic of China in 2002 for severe acute respiratory syndrome (SARS) coronavirus antibodies. The results demonstrated that the subjects either had rarely been exposed to the virus before the 2003 SARS outbreak or had not been exposed but the nucleocapsid protein cross-reacted with other antibodies in humans.

title: Risks of Death and Severe Disease in Patients With Middle East Respiratory Syndrome Coronavirus, 2012–2015
abstract: Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging pathogen, first recognized in 2012, with a high case fatality risk, no vaccine, and no treatment beyond supportive care. We estimated the relative risks of death and severe disease among MERS-CoV patients in the Middle East between 2012 and 2015 for several risk factors, using Poisson regression with robust variance and a bootstrap-based expectation maximization algorithm to handle extensive missing data. Increased age and underlying comorbidity were risk factors for both death and severe disease, while cases arising in Saudi Arabia were more likely to be severe. Cases occurring later in the emergence of MERS-CoV and among health-care workers were less serious. This study represents an attempt to estimate risk factors for an emerging infectious disease using open data and to address some of the uncertainty surrounding MERS-CoV epidemiology.

title: Moderate mutation rate in the SARS coronavirus genome and its implications
abstract: The outbreak of severe acute respiratory syndrome (SARS) caused a severe global epidemic in 2003 which led to hundreds of deaths and many thousands of hospitalizations. The virus causing SARS was identified as a novel coronavirus (SARS-CoV) and multiple genomic sequences have been revealed since mid-April, 2003. After a quiet summer and fall in 2003, the newly emerged SARS cases in Asia, particularly the latest cases in China, are reinforcing a wide-spread belief that the SARS epidemic would strike back. With the understanding that SARS-CoV might be with humans for years to come, knowledge of the evolutionary mechanism of the SARS-CoV, including its mutation rate and emergence time, is fundamental to battle this deadly pathogen. To date, the speed at which the deadly virus evolved in nature and the elapsed time before it was transmitted to humans remains poorly understood.  Sixteen complete genomic sequences with available clinical histories during the SARS outbreak were analyzed. After careful examination of multiple-sequence alignment, 114 single nucleotide variations were identified. To minimize the effects of sequencing errors and additional mutations during the cell culture, three strategies were applied to estimate the mutation rate by 1) using the closely related sequences as background controls; 2) adjusting the divergence time for cell culture; or 3) using the common variants only. The mutation rate in the SARS-CoV genome was estimated to be 0.80 – 2.38 × 10(-3 )nucleotide substitution per site per year which is in the same order of magnitude as other RNA viruses. The non-synonymous and synonymous substitution rates were estimated to be 1.16 – 3.30 × 10(-3 )and 1.67 – 4.67 × 10(-3 )per site per year, respectively. The most recent common ancestor of the 16 sequences was inferred to be present as early as the spring of 2002.  The estimated mutation rates in the SARS-CoV using multiple strategies were not unusual among coronaviruses and moderate compared to those in other RNA viruses. All estimates of mutation rates led to the inference that the SARS-CoV could have been with humans in the spring of 2002 without causing a severe epidemic.

title: Estimating the number of COVID-19-related infections, deaths and hospitalizations in Iran under different physical distancing and isolation scenarios: A compartmental mathematical modeling
abstract: Iran is one of the countries that has been overwhelmed with COVID-19. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios.  We developed a Susceptible-Exposed-Infected-Removed (SEIR) model, parameterized to the COVID-19 pandemic in Iran. We used the model to quantify the magnitude of the outbreak in Iran and assess the effectiveness of isolation and physical distancing under five different scenarios (A: 0% isolation, through E: 40% isolation of all infected cases). We used Monte-Carlo simulation to calculate the 95% uncertainty intervals (UI).  Under scenario A, we estimated 5,196,000 (UI 1,753,000 - 10,220,000) infections to happen till mid-June with 966,000 (UI 467,800 - 1,702,000) hospitalizations and 111,000 (UI 53,400 - 200,000) deaths. Successful implantation of scenario E would reduce the number of infections by 90% (i.e. 550,000) and change the epidemic peak from 66,000 on June 9th to 9,400 on March 1st. Scenario E also reduces the hospitalizations by 92% (i.e. 74,500), and deaths by 93% (i.e. 7,800).  With no approved vaccination or therapy, we found physical distancing and isolation that includes public awareness and case-finding/isolation of 40% of infected people can reduce the burden of COVID-19 in Iran by 90% by mid-June.

title: The Impact of Infection on Population Health: Results of the Ontario Burden of Infectious Diseases Study
abstract: Evidence-based priority setting is increasingly important for rationally distributing scarce health resources and for guiding future health research. We sought to quantify the contribution of a wide range of infectious diseases to the overall infectious disease burden in a high-income setting.  We used health-adjusted life years (HALYs), a composite measure comprising premature mortality and reduced functioning due to disease, to estimate the burden of 51 infectious diseases and associated syndromes in Ontario using 2005–2007 data. Deaths were estimated from vital statistics data and disease incidence was estimated from reportable disease, healthcare utilization, and cancer registry data, supplemented by local modeling studies and national and international epidemiologic studies. The 51 infectious agents and associated syndromes accounted for 729 lost HALYs, 44.2 deaths, and 58,987 incident cases per 100,000 population annually. The most burdensome infectious agents were: hepatitis C virus, Streptococcus pneumoniae, Escherichia coli, human papillomavirus, hepatitis B virus, human immunodeficiency virus, Staphylococcus aureus, influenza virus, Clostridium difficile, and rhinovirus. The top five, ten, and 20 pathogens accounted for 46%, 67%, and 75% of the total infectious disease burden, respectively. Marked sex-specific differences in disease burden were observed for some pathogens. The main limitations of this study were the exclusion of certain infectious diseases due to data availability issues, not considering the impact of co-infections and co-morbidity, and the inability to assess the burden of milder infections that do not result in healthcare utilization.  Infectious diseases continue to cause a substantial health burden in high-income settings such as Ontario. Most of this burden is attributable to a relatively small number of infectious agents, for which many effective interventions have been previously identified. Therefore, these findings should be used to guide public health policy, planning, and research.

title: Power-law distribution in the number of confirmed COVID-19 cases
abstract: COVID-19 is an emerging respiratory infectious disease caused by the coronavirus SARS-CoV-2. It was first reported on in early December 2019 in Wuhan, China and within three month spread as a pandemic around the whole globe. Here, we study macro-epidemiological patterns along the time course of the pandemic. We compute the distribution of confirmed COVID-19 cases and deaths for countries worldwide and for counties in the US, and show that both distributions follow a truncated power-law over five orders of magnitude. We are able to explain the origin of this scaling behavior as a dual-scale process: the large-scale spread of the virus between countries and the small-scale accumulation of case numbers within each country. Assuming exponential growth on both scales, the critical exponent of the power-law is determined by the ratio of large-scale to small-scale growth rates. We confirm this theory in numerical simulations in a simple meta-population model, describing the epidemic spread in a network of interconnected countries. Our theory gives a mechanistic explanation why most COVID-19 cases occurred within a few epicenters, at least in the initial phase of the outbreak. Assessing how well a simple dual-scale model predicts the early spread of epidemics, despite the huge contrasts between countries, could help identify critical temporal and spatial scales of response in which to mitigate future epidemic threats.

title: Modeling COVID-19: Forecasting and analyzing the dynamics of the outbreak in Hubei and Turkey
abstract: As the pandemic of Coronavirus Disease 2019 (COVID-19) rages throughout the world, accurate modeling of the dynamics thereof is essential. However, since the availability and quality of data varies dramatically from region to region, accurate modeling directly from a global perspective is difficult, if not altogether impossible. Nevertheless, via local data collected by certain regions, it is possible to develop accurate local prediction tools, which may be coupled to develop global models. In this study, we analyze the dynamics of local outbreaks of COVID-19 via a coupled system of ordinary differential equations (ODEs). Utilizing the large amount of data available from the ebbing outbreak in Hubei, China as a testbed, we estimate the basic reproductive number, R0 of COVID-19 and predict the total cases, total deaths, and other features of the Hubei outbreak with a high level of accuracy. Through numerical experiments, we observe the effects of quarantine, social distancing, and COVID-19 testing on the dynamics of the outbreak. Using knowledge gleaned from the Hubei outbreak, we apply our model to analyze the dynamics of outbreak in Turkey. We provide forecasts for the peak of the outbreak and the total number of cases/deaths in Turkey, for varying levels of social distancing, quarantine, and COVID-19 testing.

title: COVID-19, Australia: Epidemiology Report 17 (Fortnightly reporting period ending 24 May 2020)
abstract: Confirmed cases in Australia notified up to 24 May 2020: notifications = 7,135; deaths = 102. The incidence of COVID-19 has markedly reduced since a peak in mid-March. There have been no cases reported in SA, the NT or the ACT in the last four weeks. The numbers of new cases reported from other jurisdictions continue to be very low. Testing rates have been higher across all jurisdictions, with Victoria reporting an 85% testing rate increase and NSW a 40% increase over this period. The positivity rate nationally continues to remain very low at less than 0.1% over the reporting period. Continued high rates of testing are necessary to detect and mitigate the spread of COVID-19 in the community. Over the past fortnight, 45% of cases acquired their infection overseas. Of cases considered to be locally acquired over this period, most were associated with contacts of confirmed cases or were associated with known outbreaks. The highest rate of COVID-19 continues to be among people aged 65-79 years. Three-quarters of all cases in this age group have been associated with overseas travel, including several outbreaks linked to cruise ships. The lowest rate of disease is in children under 18, a pattern reflected in international reports. A small proportion of cases overall have experienced severe disease, requiring hospitalisation or intensive care with some fatalities. The crude case fatality rate amongst Australian cases is 1.4%. People who are older and have one or more comorbidities are more likely to experience severe disease. A combination of early case identification, physical distancing, public health measures and a reduction in international travel have likely been effective in slowing the spread of the disease in Australia. In addition, the median number of days between symptom onset and diagnostic testing has improved considerably from 7 days in the early phase of the outbreak to 1 day in the latest phase of the epidemic. Internationally, as at 24 May 2020, there have been recent increases in the number of daily cases reported globally. The largest numbers of both cases and deaths have been reported in the United States. Of the confirmed cases reported globally, the case fatality rate is approximately 6.5%. Countries in South America are starting to see rapid acceleration, while the United States is seeing a very slow decline in its daily new case numbers. In the South East Asia region, India and Bangladesh are seeing accelerating epidemics, compounded by the recovery from Cyclone Amphan. Increasing numbers of cases are also being reported in Africa, although the numbers are much smaller. In the Pacific there are very few daily new cases reported.

title: COVID-19 outbreak in Italy: estimation of reproduction numbers over two months toward the Phase 2
abstract: After two months from the first case in COVID-19 outbreak, Italy counts more than 190,000 confirmed positive cases. From the beginning of April 2020, the nationwide lockdown started to show early effects by reducing the total cumulative incidence reached by the epidemic wave. This allows the government to program the measures to loosen lockdown restrictions for the so called "Phase 2". Here we provided the reproduction number estimation both in space and in time from February 24th to April 24th, 2020 across two months into the epidemic. Our estimates suggest basic reproduction number averaged over all the regions of 3.29, confirming that epidemiological figures of the SARS-CoV-2 epidemic in Italy are higher than those observed at the early stage of Wuhan (China) outbreak. Based on the SARS-CoV-2 transmission dynamics reported here, we gave a quantitative evaluation of the efficiency of the government measures to low the reproduction number under the unity (control regime). We estimated that among the worst hit regions in Italy, Lombardy reached the control regime on March 22nd followed by Emilia-Romagna (March 23th), Veneto (March 25th) and Piemonte (March 26th). Overall, we found that the mean value of time to reach the control regime in all the country is about 31 days from the February 24th and about 14 days from the first day of nationwide lockdown (March 12th). Finally, we highlighted the interplay between the reproduction number and two demographic indices in order to probe the "state of activity" of the epidemic for each Italian region in the control regime. We believe that this approach can provide a tool in the management of "Phase 2", potentially helping in challenging decision to continue, ease or tighten up restrictions.

title: Measures of frequency: calculating prevalence and incidence in the era of COVID-19

title: Syndromic Surveillance

title: Tracing DAY-ZERO and Forecasting the Fade out of the COVID-19 Outbreak in Lombardy, Italy: A Compartmental Modelling and Numerical Optimization Approach.
abstract: Italy currently constitutes the epicenter of the novel coronavirus disease (COVID-19) pandemic, having surpassed China's death toll. The disease is sweeping through Lombardy, which remains in lockdown since the 8th of March. As of the same day, the isolation measures taken in Lombardy have been extended to the entire country. Here, we provide estimates for: (a) the DAY-ZERO of the outbreak in Lombardy, Italy; (b) the actual number of exposed/infected cases in the total population; (c) the basic reproduction number (R0); (d) the "effective" per-day disease transmission; and, importantly, (e) a forecast for the fade out of the outbreak, on the basis of the COVID-19 Community Mobility Reports released by Google on March 29.  To deal with the uncertainty in the number of actual exposed/ infected cases in the total population, we address a compartmental Susceptible/ Exposed/ Infectious/ Recovered/ Dead (SEIRD) model with two compartments of infectious persons: one modelling the total cases in the population and another modelling the confirmed cases. The parameters of the model corresponding to the recovery period, the time from the onset of symptoms to death, the case fatality ratio, and the time from exposure to the time that an individual starts to be infectious, have been set as reported from clinical studies on COVID-19. For the estimation of the DAY-ZERO of the outbreak in Lombardy, as well as of the ``effective" per-day transmission rate for which no clinical data are available, we have used the SEIRD simulator to fit the numbers of new daily cases from February 21 to the 8th of March, the lockdown day of Lombardy and of all Italy. This was accomplished by solving a mixed-integer optimization problem with the aid of genetic algorithms. Based on the computed values, we also provide an estimation of the basic reproduction number $R_0$. Furthermore, based on an estimation for the reduction in the "effective" transmission rate of the disease as of March 8 that reflects the suspension of almost all activities in Italy, we ran the simulator to forecast the fade out of the epidemic. For this purpose, we considered the reduction in mobility in Lombardy as released on March 29 by Google COVID-19 Community Mobility Reports, the effect of social distancing, and the draconian measures taken by the government on March 20 and March 21, 2020.  Based on the proposed methodological procedure, we estimated that the DAY-ZERO was most likely between January 5 and January 23 with the most probable date the 15th of January 2020. The actual cumulative number of exposed cases in the total population in Lombardy on March 8 was of the order of 15 times the confirmed cumulative number of infected cases. The "effective" per-day disease transmission rate for the period until March 8 was found to be 0.686 (95% CI:0.660, 0.713), while the basic reproduction number R0 was found to be 4.51 (95% CI: 4.14, 4.90). Importantly, simulations show that the COVID-19 pandemic in Lombardy is expected to fade out by the end of May - early June, 2020, if the draconian, as of March 20 and March 21, measures are maintained.

title: Presence of SARS-Coronavirus-2 RNA in Sewage and Correlation with Reported COVID-19 Prevalence in the Early Stage of the Epidemic in The Netherlands
abstract: see text] In the current COVID-19 pandemic, a significant proportion of cases shed SARS-Coronavirus-2 (SARS-CoV-2) with their faeces. To determine if SARS-CoV-2 RNA was present in sewage during the emergence of COVID-19 in The Netherlands, sewage samples of six cities and the airport were tested using four qRT-PCR assays, three targeting the nucleocapsid gene (N1–N3) and one the envelope gene (E). No SARS-CoV-2 RNA was detected on February 6, 3 weeks before the first Dutch case was reported. On March 4/5, one or more gene fragments were detected in sewage of three sites, in concentrations of 2.6–30 gene copies per mL. In Amersfoort, N3 was detected in sewage 6 days before the first cases were reported. As the prevalence of COVID-19 in these cities increased in March, the RNA signal detected by each qRT-PCR assay increased, for N1–N3 up to 790–2200 gene copies per mL. This increase correlated significantly with the increase in reported COVID-19 prevalence. The detection of the virus RNA in sewage, even when the COVID-19 prevalence is low, and the correlation between concentration in sewage and reported prevalence of COVID-19, indicate that sewage surveillance could be a sensitive tool to monitor the circulation of the virus in the population.

title: Maternal and neonatal outcomes associated with COVID-19 infection: A systematic review
abstract: COVID-19 has created an extraordinary global health crisis. However, with limited understanding of the effects of COVID-19 during pregnancy, clinicians and patients are forced to make uninformed decisions.  To systematically evaluate the literature and report the maternal and neonatal outcomes associated with COVID-19. SEARCH STRATEGY: PubMed, MEDLINE, and EMBASE were searched from November 1(st), 2019 and March 28(th), 2020.  Primary studies, reported in English, investigating COVID-19-positive pregnant women and reporting their pregnancy and neonatal outcomes.  Data in relation to clinical presentation, investigation were maternal and neonatal outcomes were extracted and analysed using summary statistics. Hypothesis testing was performed to examine differences in time-to-delivery. Study quality was assessed using the ICROMS tool.  Of 73 identified articles, nine were eligible for inclusion (n = 92). 67.4% (62/92) of women were symptomatic at presentation. RT-PCR was inferior to CT-based diagnosis in 31.7% (26/79) of cases. Maternal mortality rate was 0% and only one patient required intensive care and ventilation. 63.8% (30/47) had preterm births, 61.1% (11/18) fetal distress and 80% (40/50) a Caesarean section. 76.92% (11/13) of neonates required NICU admission and 42.8% (40/50) had a low birth weight. There was one indeterminate case of potential vertical transmission. Mean time-to-delivery was 4.3±3.08 days (n = 12) with no difference in outcomes (p>0.05).  COVID-19-positive pregnant women present with fewer symptoms than the general population and may be RT-PCR negative despite having signs of viral pneumonia. The incidence of preterm births, low birth weight, C-section, NICU admission appear higher than the general population.

title: Toward understanding the 2019 Coronavirus and its impact on the heart

title: Evaluation of Sample Pooling for Screening of SARS-CoV-2
abstract: The coronavirus disease (COVID-19) pandemic has revealed the global public health importance of robust diagnostic testing. To overcome the challenge of nucleic acid (NA) extraction and testing kit availability efficient method is urgently needed.  To establish an efficient, time and resource-saving and cost-effective methods, and to propose an ad hoc pooling approach for mass screening of SARS-CoV-2  Direct clinical sample and NA pooling approach was used for the standard reverse transcriptase polymerase chain reaction (RT-PCR) test of the SARS CoV-2 targeting the envelop (E) and open reading frame (ORF1ab) genomic region of the virus. In this approach, experimental pools were created using SARS CoV-2 positive clinical samples spiked with up to 9 negative samples prior to NA extraction step to have a final extraction volume of 200L (maximum dilution factor of 10). Viral NA was also subsequently extracted from each pool and tested using the SARS CoV-2 RT-PCR assay.  We found that a single positive sample can be amplified and detected in pools of up to 7 samples depending on the ct value of the original sample, corresponding to high, medium, and low SARS CoV-2 viral copies/reaction. However, to minimize false negativity of the assay with pooling strategies and with unknown false negativity rate of the assay under validation, we recommend poling of 4 in 1 using the standard protocols of the assay, reagents and equipment. The predictive algorithm indicated a pooling ratio of 4 in 1 was expected to retain accuracy of the test irrespective of the ct value (relative RNA copy number) of the sample spiked and result in a 237% increase in testing efficiency.  The approaches showed its concept in easily customized and resource-saving manner and would allow expanding of current screening capacities and enable the expansion of detection in the community.

title: Analysis of clinical characteristics and laboratory findings of 95 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a retrospective analysis
abstract: Since December 2019, 2019 novel coronavirus pneumonia emerged in Wuhan city and rapidly spread throughout China and even the world. We sought to analyse the clinical characteristics and laboratory findings of some cases with 2019 novel coronavirus pneumonia .  In this retrospective study, we extracted the data on 95 patients with laboratory-confirmed 2019 novel coronavirus pneumonia in Wuhan Xinzhou District People’s Hospital from January 16th to February 25th, 2020. Cases were confirmed by real-time RT-PCR and abnormal radiologic findings. Outcomes were followed up until March 2th, 2020.  Higher temperature, blood leukocyte count, neutrophil count, neutrophil percentage, C-reactive protein level, D-dimer level, alanine aminotransferase activity, aspartate aminotransferase activity, α - hydroxybutyrate dehydrogenase activity, lactate dehydrogenase activity and creatine kinase activity were related to severe 2019 novel coronavirus pneumonia and composite endpoint, and so were lower lymphocyte count, lymphocyte percentage and total protein level. Age below 40 or above 60 years old, male, higher Creatinine level, and lower platelet count also seemed related to severe 2019 novel coronavirus pneumonia and composite endpoint, however the P values were greater than 0.05, which mean under the same condition studies of larger samples are needed in the future.  Multiple factors were related to severe 2019 novel coronavirus pneumonia and composite endpoint, and more related studies are needed in the future.

title: Olfactory and Gustatory Dysfunction as An Early Identifier of COVID-19 in Adults and Children: An International Multicenter Study
abstract: Evaluate the prevalence and characteristics of olfactory or gustatory dysfunction in COVID-19 patients  5 tertiary care hospitals (3 in China, 1 in France, 1 in Germany) Subjects and Methods: 394 PCR confirmed COVID-19 positive patients were screened, and those with olfactory or gustatory dysfunction were included. Data including demographics, COVID-19 severity, patient outcome, and the incidence and degree of olfactory and/or gustatory dysfunction were collected and analyzed. The Questionnaire of Olfactory Disorders (QOD) and Visual Analogue Scale (VAS) were used to quantify olfactory and gustatory dysfunction respectively. All subjects at one hospital (Shanghai) without subjective olfactory complaints underwent objective testing.  Of 394 screened subjects, 161 (41%) reported olfactory and/or gustatory dysfunction and were included. Incidence of olfactory and/or gustatory disorders in Chinese (n=239), German (n=39) and French (n=116) cohorts were 32%, 69%, and 49% 138 respectively. The median age of included subjects was 39 years old, 92/161 (57%) were male, and 10/161 (6%) were children. Of included subjects, 10% had only olfactory or gustatory symptoms, and 19% had olfactory and/or gustatory complaints prior to any other COVID-19 symptom. Of subjects with objective olfactory testing, 10/90 demonstrated abnormal chemosensory function despite reporting normal subjective olfaction. 43% (44/102) of subjects with follow-up showed symptomatic improvement in olfaction or gustation.  Olfactory and/or gustatory disorders may represent early or isolated symptoms of SARS-CoV-2 infection. They may serve as a useful additional screening criterion, particularly for the identification of patients in the early stages of infection.

title: The use of convalescent plasma therapy and remdesivir in the successful management of a critically ill obstetric patient with novel coronavirus 2019 infection: A case report
abstract: Remdesivir is a novel therapeutic with known activity against SARS CoV-2 and related coronaviruses. Remdesivir, as well as convalescent plasma therapy, are currently under investigation as potential therapies for patients with Coronavirus Disease 19 (COVID-19). In this case report we summarize the use of convalescent plasma therapy and then remdesivir as a late addition in the treatment of a critically ill obstetric patient with COVID-19. The patient subsequently improved, was extubated 5 days after initiation of remdesivir, was transitioned to room air 24 h later, and discharged at the completion of remdesivir therapy.

title: Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases
abstract: Chest CT is used for diagnosis of 2019 novel coronavirus disease (COVID-19), as an important complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests.  To investigate the diagnostic value and consistency of chest CT as compared with comparison to RT-PCR assay in COVID-19.  From January 6 to February 6, 2020, 1014 patients in Wuhan, China who underwent both chest CT and RT-PCR tests were included. With RT-PCR as reference standard, the performance of chest CT in diagnosing COVID-19 was assessed. Besides, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative, respectively) was analyzed as compared with serial chest CT scans for those with time-interval of 4 days or more.  Of 1014 patients, 59% (601/1014) had positive RT-PCR results, and 88% (888/1014) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95%CI, 95-98%, 580/601 patients) based on positive RT-PCR results. In patients with negative RT-PCR results, 75% (308/413) had positive chest CT findings; of 308, 48% were considered as highly likely cases, with 33% as probable cases. By analysis of serial RT-PCR assays and CT scans, the mean interval time between the initial negative to positive RT-PCR results was 5.1 ± 1.5 days; the initial positive to subsequent negative RT-PCR result was 6.9 ± 2.3 days). 60% to 93% of cases had initial positive CT consistent with COVID-19 prior (or parallel) to the initial positive RT-PCR results. 42% (24/57) cases showed improvement in follow-up chest CT scans before the RT-PCR results turning negative.  Chest CT has a high sensitivity for diagnosis of COVID-19. Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas.

title: Knowledge, Awareness, and Compliance of Disease Surveillance and Notification Among Jordanian Physicians in Residency Programs
abstract: Health professionals’ knowledge and awareness of the disease surveillance is essential for reporting diseases to health departments. This study aimed to assess the knowledge and attitudes of Jordanian physicians toward public health surveillance of communicable disease. A cross-sectional study was conducted among resident doctors who were working in 4 main Ministry of Health hospitals and 2 teaching hospitals in Jordan in September 2017. A self-administered paper-based questionnaire was used to collect the data. The questionnaire collected information about sociodemographic and practice-related characteristics of physicians and included items to assess their knowledge of surveillance and reporting practices. This study included 223 physicians (152 males and 71 females). About 60.1% of the residents were graduates from medical schools in Jordan and the remaining (39.9%) were graduates from medical schools in other countries. Approximately two thirds of residents (62.3%) were doing their residency in Ministry of Health hospitals and the rest (37.7%) in 2 teaching hospitals. Only 44.8% of physicians had defined surveillance correctly. Only 27.4% of physicians had been educated or trained on surveillance. About 39.5% of physicians had filled at least one report form during their practice. The main reasons for not reporting mandatory diseases were high workload (49.8%) and being not trained on reporting diseases (46.6%). A relatively high percentage of physicians have insufficient knowledge of surveillance and reporting of notifiable communicable diseases. Training of physicians on surveillance and diseases notification is highly needed. The practice of disease notification should be enforced in Jordanian hospitals.

title: Diagnosing COVID-19: Did We Miss Anything?
abstract: In late 2019, a mass of patients showing symptoms of a pneumonia-like disease of unknown origin emerged in Wuhan, China. Little did the world know it was the prelude of what would be a devastating pandemic. Samples were collected from these patients and the use of unbiased sequencing, and subsequent isolation of the pathogen using human airway epithelial cells led to the discovery of a novel coronavirus, named 2019-nCoV by the World Health Organization (WHO) and Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses. The disease caused by this virus is officially called the coronavirus disease 2019 (COVID-19).

title: Afectación clínica y sintomatológica en pacientes mayores de 65 años por COVID-19

title: SARS-CoV-2 inflames the heart. The importance of awareness of myocardial injury in COVID-19 patients

title: Coronavirus spreads
abstract: The deadly virus that emerged in Wuhan, China, may be much more contagious than initially thought. Jessica Hamzelou reports

title: Utility of Substandard Face Mask Options for Health Care Workers During the COVID-19 Pandemic

title: Adjusting confirmed COVID-19 case counts for testing volume
abstract: When assessing the relative prevalence of the novel coronavirus (COVID-19), observers often point to the number of COVID-19 cases that have been confirmed through viral testing. However, comparisons based on confirmed case counts alone can be misleading since a higher case count may reflect either a higher disease prevalence or a better rate of disease detection. Using weekly records of viral test results for each state in the US, I demonstrate how confirmed case counts can be adjusted based on the percentage of COVID-19 tests that come back positive. A regression analysis indicates that case counts track better with future hospitalizations and deaths when employing this simple adjustment for testing coverage. Viral testing results can be used as a leading indicator of COVID-19 prevalence, but data reporting standards should be improved, and care should be taken to account for testing coverage when comparing confirmed case counts.

title: Clinical Trials and Novel Pathogens: Lessons Learned from SARS
abstract: During the recent global outbreak of severe acute respiratory syndrome (SARS), thousands of patients received treatments of uncertain efficacy and known toxicity such as ribavirin and corticosteroids. Despite this, no controlled clinical trials assessing the efficacy of these agents were conducted. If a second global SARS outbreak occurred, clinicians would not have controlled data on which to base therapeutic decisions. We discuss the unique methodologic and logistical challenges faced by researchers who attempt to conduct controlled trials of therapeutic agents during an outbreak of a novel or unknown infectious pathogen. We draw upon our own experience in attempting to conduct a randomized controlled trial (trial) of ribavirin therapy for SARS and discuss the lessons learned. Strategies to facilitate future clinical trials during outbreaks of unknown or novel pathogens are also presented.

title: Prescription Surveillance and Polymerase Chain Reaction Testing to Identify Pathogens during Outbreaks of Infection
abstract: Syndromic surveillance, including prescription surveillance, offers a rapid method for the early detection of agents of bioterrorism and emerging infectious diseases. However, it has the disadvantage of not considering definitive diagnoses. Here, we attempted to definitively diagnose pathogens using polymerase chain reaction (PCR) immediately after the prescription surveillance system detected an outbreak. Specimens were collected from 50 patients with respiratory infections. PCR was used to identify the pathogens, which included 14 types of common respiratory viruses and Mycoplasma pneumoniae. Infectious agents including M. pneumoniae, respiratory syncytial virus (RSV), rhinovirus, enterovirus, and parainfluenza virus were detected in 54% of patients. For the rapid RSV diagnosis kit, sensitivity was 80% and specificity was 85%. For the rapid adenovirus diagnosis kit, no positive results were obtained; therefore, sensitivity could not be calculated and specificity was 100%. Many patients were found to be treated for upper respiratory tract infections without the diagnosis of a specific pathogen. In Japan, an outbreak of M. pneumoniae infection began in 2011, and our results suggested that this outbreak may have included false-positive cases. By combining syndromic surveillance and PCR, we were able to rapidly and accurately identify causative pathogens during a recent respiratory infection outbreak.

title: Evidence that higher temperatures are associated with lower incidence of COVID-19 in pandemic state, cumulative cases reported up to March 27, 2020
abstract: Seasonal temperature variation may impact the trajectories of COVID-19 in different global regions. Cumulative data reported by the World Health Organization, for dates up to March 27, 20201, show association between COVID-19 incidence and regions at or above 30° latitude. Historic climate data also show significant reduction of case rates with mean maximum temperature above approximately 22.5 degrees Celsius. Variance at the local level, however, could not be well explained by geography and temperature. These preliminary findings support continued countermeasures and study of SARS-CoV-2/COVID-19 transmission rates by temperature and humidity.

title: [Managing patients in dialysis and with kidney transplant infected with Covid-19]
abstract: We are in the midst of a health emergency that is totally new for us all and that requires a concerted effort, especially when it comes to safeguarding patients on hemodialysis, and kidney transplant recipients Brescia is currently a very active cluster of infections (2918 cases on the 17/03/2020), second only to Bergamo The way our structure is organised has allowed us to treat nephropathic patients directly within the Nephrology Unit, following of course a great deal of reshuffling;at the moment, we are treating 21 transplanted patients and 17 on hemodialysis This has led us to adopt a systematic approach to handling this emergency, not only in managing inpatients, but also in researching the new disease Our approach is mirrored in the guidelines attached to this article, originally intended for internal use only but potentially very useful to our colleagues, as they face the same exact problems We have also started collecting data on our positive patients with the aim of understanding better the functioning of this disease and how best to manage it If anyone is interested, we ask you to please get in touch with us, so we can coordinate our efforts

title: WeChat, a Chinese social media, may early detect the SARS-CoV-2 outbreak in 2019
abstract: We plotted daily data on the frequencies of keywords related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from WeChat, a Chinese social media. Using 'Feidian', Chinese abbreviation for SARS, may detect the SARS-CoV-2 outbreak in 2019 two weeks earlier. WeChat offered a new approach to early detect disease outbreaks.

title: Estimation of Tunisia COVID-19 infected cases based on mortality rate
abstract: Estimating the number of people affected by COVID-19 is crucial in deciding which public health policies to follow. The authorities in different countries carry out mortality counts. We propose that the mortality reported in each country can be used to create an index of the number of actual cases at a given time. The specificity of whether or not deaths are rapid or not by COVID-19 also affects the number of actual cases. The number of days between the declaration of illness and death varies between 12 and 18 days. For a delay of 18 days, and using an estimated mortality rate of 2%, the number of cases in April 2020 in Tunisia would be 5 580 people. The pessimistic scenario predicts 22 320 infected people, and the most optimistic predicts 744 (which is the number of reported cases on April 12, 2020). Modeling the occurrence of COVID-19 cases is critical to assess the impact of policies to prevent the spread of the virus.

title: COVID-19 Testing, Epidemic Features, Hospital Outcomes, and Household Prevalence, New York State-March 2020
abstract: The United States' COVID-19 epidemic has grown extensively since February 2020, with substantial associated hospitalizations and mortality; New York State (NYS) has emerged as the national epicenter. We report on the extent of testing and test results during the month of March in NYS, along with risk factors, outcomes, and household prevalence among initial cases subject to in-depth investigations.  Specimen collection for COVID-19 testing was conducted in healthcare settings, community-based collection sites, and by home testing teams. Information on demographics, risk factors, and hospital outcomes of cases was obtained through epidemiological investigations and an electronic medical records match, and summarized descriptively. Active testing of initial case's households enabled estimation of household prevalence.  During March In NYS, outside of New York City, a total of 47,326 persons tested positive for SARS-CoV-2, out of 141,495 tests (33% test-positive), with the highest number of cases located in the metropolitan region counties. Among 229 initial cases diagnosed through March 12, by March 30 13% were hospitalized and 2% died. Testing conducted among 498 members of these case's households found prevalent infection among 57%; excluding first-reported cases 38%. In these homes, we found a significant age gradient in prevalence, from 23% among those <5 years to 68% among those &#8805;65 years (p<.0001).  New York State faced a substantial and increasing COVID-19 outbreak during March 2020. The earliest cases had high levels of infection in their households and by the end of the month, the risks of hospitalization and death were high.

title: Suitability and Sufficiency of Telehealth Clinician-Observed, Participant-Collected Samples for SARS-CoV-2 Testing: The iCollect Cohort Pilot Study
abstract: The severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic calls for expanded opportunities for testing, including novel testing strategies such as home-collected specimens.  We aimed to understand whether oropharyngeal swab (OPS), saliva, and dried blood spot (DBS) specimens collected by participants at home and mailed to a laboratory were sufficient for use in diagnostic and serology tests of SARS-CoV-2.  Eligible participants consented online and were mailed a participant-collection kit to support collection of three specimens for SARS-CoV-2 testing: saliva, OPS, and DBS. Participants performed the specimen collection procedures during a telehealth video appointment while clinical observers watched and documented the suitability of the collection. The biological sufficiency of the specimens for detection of SARS-CoV-2 by reverse transcriptase–polymerase chain reaction and serology testing was assessed by laboratorians using visual inspection and quantification of the nucleic acid contents of the samples by ribonuclease P (RNase P) measurements.  Of the enrolled participants,153/159 (96.2%) returned their kits, which were included in this analysis. All these participants attended their video appointments. Clinical observers assessed that of the samples collected, 147/153 (96.1%) of the saliva samples, 146/151 (96.7%) of the oropharyngeal samples, and 135/145 (93.1%) of the DBS samples were of sufficient quality for submission for laboratory testing; 100% of the OPS samples and 98% of the saliva samples had cycle threshold values for RNase P <30, indicating that the samples contained sufficient nucleic acid for RNA-PCR testing for SARS-CoV-2.  These pilot data indicate that most participant-collected OPS, saliva, and DBS specimens are suitable and sufficient for testing for SARS-CoV-2 RNA and serology. Clinical observers rated the collection of specimens as suitable for testing, and visual and quantitative laboratory assessment indicated that the specimens were biologically sufficient. These data support the utility of participant-collected and mailed-in specimens for SARS-CoV-2 testing.

title: Scenario analysis of non-pharmaceutical interventions on global COVID-19 transmissions
abstract: This paper introduces a dynamic panel SIR (DP-SIR) model to investigate the impact of non-pharmaceutical interventions (NPIs) on the COVID-19 transmission dynamics with panel data from 9 countries across the globe. By constructing scenarios with different combinations of NPIs, our empirical findings suggest that countries may avoid the lockdown policy with imposing school closure, mask wearing and centralized quarantine to reach similar outcomes on controlling the COVID-19 infection. Our results also suggest that, as of April 4th, 2020, certain countries such as the U.S. and Singapore may require additional measures of NPIs in order to control disease transmissions more effectively, while other countries may cautiously consider to gradually lift some NPIs to mitigate the costs to the overall economy.

title: Results of an online questionnaire to survey calf management practices on dairy cattle breeding farms in Austria and to estimate differences in disease incidences depending on farm structure and management practices
abstract: Calf disease may result in great economic losses. To implement prevention strategies it is important to gain information on management and to point out risk factors. The objective of this internet based survey was to describe calf management practices on registered dairy breeding farms in Austria and to estimate differences in calf disease incidences depending on farm structure and management practices.  A total of 1287 questionnaires were finally analysed (response rate 12.2 %). Herd characteristics and regional distribution of farms indicated that this survey gives a good overview on calf management practices on registered dairy farms in Austria. The median number of cows per farm was 20 (interquartile range 13–30). Significant differences regarding farm characteristics and calf management between small and large farms (≤20 vs >20 cows) were present. Only 2.8 % of farmers tested first colostrum quality by use of a hydrometer. Storing frozen colostrum was more prevalent on large farms (80.8 vs 64.2 %). On 85.1 % of the farms, whole milk, including waste milk, was fed to the calves. Milk replacer and waste milk were more often used on large farms. In accordance with similar studies from other countries, calf diarrhoea was indicated as the most prevalent disease. Multivariable logistic regression analysis revealed that herd size was associated with calf diarrhoea and calf respiratory tract disease, with higher risk of disease on large farms. Furthermore, feeding waste milk to the calves was associated with increasing calf diarrhoea incidence on farm. In the final model with calf respiratory tract disease as outcome, respondents from organic farms reported less often a respiratory tract disease incidence of over 10 % compared with conventional farms [odds ratio (OR) 0.40, 95 % confidence interval (CI) 0.21–0.75] and farmers that housed calves individually or in groups after birth significantly reported more often to have an incidence of respiratory tract disease >10 % compared with farms where all calves were housed individually (OR 2.28, 95 % CI 1.16–4.48).  The results obtained in this study provide an overview on calf management on dairy breeding farms in Austria and may help to further point out areas to be improved on farm.

title: Gestión Y Liderazgo De Los Servicios De Enfermería En El Plan De Emergencia De La Pandemia Covid-19: La Experiencia Del Hospital Clínic De Barcelona./ [management and Leadership of Nursing Services in the Emergency Plan for the Pandemic Covid-19: the Experience of the Clinic Hospital of Barcelona]
abstract: At the international level, the enormous demand to manage the COVID-19 pandemic has posed a challenge both in the provision of personnel and in supplies and sanitary material. There is no precedent or publication related to the management and leadership of nursing services in Spain within the emergency plan for the COVID-19 pandemic. This article describes the experience of the Hospital Clinico de Barcelona in the current extraordinary circumstances that undoubtedly constitute a nursing management of enormous magnitude and unprecedented due to the high number of people affected and the extraordinary risk of healthcare personnel. Following national and international guidelines to alleviate the pandemic, protect health and prevent the spread of the outbreak. The ability to work as a team, emotional management and respect for organizational decisions have made it possible to face the challenges that the pandemic has put in place and that the Nursing Department can lead in a calm and orderly manner the different actions to perform. Lastly, it will be necessary to continue with an in-depth analysis of the situation and of the actions carried out in order to identify the areas for improvement as well as to evaluate the overall nature of the process.

title: New York City COVID-19 resident physician exposure during exponential phase of pandemic.
abstract: BackgroundFrom March 2-April 12, 2020, New York City (NYC) experienced exponential growth of the COVID-19 pandemic due to novel coronavirus (SARS-CoV-2). Little is known regarding how physicians have been affected. We aimed to characterize COVID-19 impact on NYC resident physicians.MethodsIRB-exempt and expedited cross-sectional analysis through survey to NYC residency program directors (PDs) April 3-12, 2020, encompassing events from March 2-April 12, 2020.ResultsFrom an estimated 340 residency programs around NYC, recruitment yielded 91 responses, representing 24 specialties and 2,306 residents. 45.1% of programs reported at least one resident with confirmed COVID-19: 101 resident physicians were confirmed COVID-19-positive, with an additional 163 residents presumed positive for COVID-19 based on symptoms but awaiting or unable to obtain testing. Two COVID-19-positive residents were hospitalized, with one in intensive care. Among specialties with >100 residents represented, negative binomial regression indicated that infection risk differed by specialty (p=0.039). 80% of programs reported quarantining a resident. 90/91 programs reported reuse or extended mask use, and 43 programs reported that personal protective equipment (PPE) was suboptimal. 65 programs (74.7%) have redeployed residents elsewhere to support COVID-19 efforts.ConclusionMany resident physicians around NYC have been affected by COVID-19 through direct infection, quarantine, or redeployment. Lack of access to testing and concern regarding suboptimal PPE are common among residency programs. Infection risk may differ by specialty.FundingAHA, MPB, RWSC, CGM, LRDG, JDH: NEI Core Grant P30EY019007, RPB Unrestricted Grant. ACP and JS: Parker Family Chair.  University of Pennsylvania.

title: FALSE-NEGATIVE RESULTS OF INITIAL RT-PCR ASSAYS FOR COVID-19: A SYSTEMATIC REVIEW
abstract: Cases with negative reverse transcription-polymerase chain reaction (RT-PCR) results at initial testing for suspicion of SARS-CoV-2 infection, and found to be positive in a subsequent test, are considered as RT-PCR false-negative cases. False-negative cases have important implications for COVID-19 management, isolation, and risk of transmission. We aimed to review and critically appraise evidence about the proportion of RT-PCR false-negatives at initial testing for COVID-19.  We performed a systematic review and critical appraisal of literature with high involvement of stakeholders in the review process. We searched on MEDLINE, EMBASE, LILACS, the WHO database of COVID-19 publications, the EPPI-Centre living systematic map of evidence about COVID-19, and the living systematic review developed by the University of Bern (ISPM). Two authors screened and selected studies according to the eligibility criteria and collected data of included studies (no-independent verification). Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We calculated the false-negative proportion with the corresponding 95% CI using a multilevel mixed-effect logistic regression model using STATA 16. Certainty of the evidence about false-negative cases was rated using the GRADE approach for tests and strategies. The information is current up to 6 April 2020.  Five studies enrolling 957 patients were included. All studies were affected by several biases and applicability concerns. Pooled estimation of false-negative proportion was 0.085 (95% CI= 0.034 to 0.196; tau-squared = 1.08; 95% CI= 0.27 to 8.28; p<0.001); however, this estimation is highly affected by unexplained heterogeneity, and its interpretation should be avoided. The certainty of the evidence was judged as very low, due to the risk of bias, indirectness, and inconsistency issues.  The collected evidence has several limitations, including risk of bias issues, high heterogeneity, and concerns about its applicability. Nonetheless, our findings reinforce the need for repeated testing in patients with suspicion of SARS-Cov-2 infection given that up to 29% of patients could have an initial RT-PCR false-negative result.

title: Multi-parametric disease dynamics study and analysis of the COVID-19 epidemic and implementation of population-wide intrusions: The Indian perspective
abstract: The outbreak of COVID-19 had spread at a deadly rate since its onset at Wuhan, China and is now spread across 216 countries and has affected more than 6 million people all over the world. The global response throughout the world has been primarily the implementation of lockdown measures, testing and contact tracing to minimise the spread of the disease. The aim of the present study was to predict the COVID-19 prevalence and disease progression rate in Indian scenario in order to provide an analysis that can shed light on comprehending the trends of the outbreak and outline an impression of the epidemiological stage for each state of a diverse country like India. In addition, the forecast of COVID-19 incidence trends of these states can help take safety measures and policy design for this epidemic in the days to come. In order to achieve the same, we have utilized an approach where we test modelling choices of the spatially unambiguous kind, proposed by the wave of infections spreading from the initial slow progression to a higher curve. We have estimated the parameters of an individual state using factors like population density and mobility. The findings can also be used to strategize the testing and quarantine processes to manipulate the spread of the disease in the future. This is especially important for a country like India that has several limitations about healthcare infrastructure, diversity in socioeconomic status, high population density, housing conditions, health care coverage that can be important determinants for the overall impact of the pandemic. The results of our 5-phase model depict a projection of the state wise infections/disease over time. The model can generate live graphs as per the change in the data values as the values are automatically being fetched from the crowd-sourced database.

title: Corona Viruses and the Chemical Senses: Past, Present, and Future
abstract: A wealth of rapidly evolving reports suggests that olfaction and taste disturbances may be manifestations of the novel COVID-19 pandemic. While otolaryngological societies worldwide have started to consider chemosensory evaluation as a screening tool for COVID-19 infection, the true nature of the relationship between the changes in chemosensory ability and COVID-19 is unclear. Our goal with this review is to provide a brief overview of published and archived literature, as well as the anecdotal reports and social trends related to this topic up to April 29, 2020. We also aim to draw parallels between the clinical/chemosensory symptomology reported in association to past coronavirus pandemics (such as SARS and MERS) and the novel COVID-19. This review also highlights current evidence on persistent chemosensory disturbances after the infection has resolved. Overall, our analysis pinpoints the need for further studies: 1) to better quantify olfaction and taste disturbances associated with SARS-CoV-2 infection, compared to those of other viral and respiratory infections, 2) to understand the relation between smell, taste, and chemesthesis disturbances in COVID-19, and 3) to understand how persistent are these disturbances after the infection has resolved.

title: Comparative Global Epidemiological Investigation of SARS-CoV-2 and SARS-CoV Diseases Using Meta-MUMS Tool Through Incidence, Mortality, and Recovery Rates
abstract: COVID-19 is a novel coronavirus that was reported by the world health organization in late December 2019. As an unexplained respiratory disease epidemic, which is similar to respiratory syndrome coronavirus SARS-CoV, it rapidly spread all over the world. The study aims to compare several parameters of COVID-19 and SARS-CoV infectious diseases in terms of incidence, mortality, and recovery rates. The publicly available dataset Worldometer (extracted on April 5, 2020) confirmed by WHO report was available for meta-analysis purposes using the Meta-MUMS tool. And, the reported outcomes of the analysis used a random-effects model to evaluate the event rate, and risk ratios thorough subgroup analysis forest plots. Seventeen countries for COVID-19 and eight countries of SARS infections, including COVID-19 group n = 1124243, and SARS-CoV group n = 8346, were analyzed. In this meta-analysis, a random effect model of relations of incidence, mortality, and recovery rates of COVID-19 and SARS world infections were determined. The meta-analysis and forest plots of two viral world infections showed that the incidence rate of COVID-19 infection is more than SARS infections, while recovery and mortality event rates of SARS-CoV are more than COVID-19 infection. And subgroup analysis showed that the mortality and recovery rates were higher in both SARS-CoV wand COVID-19 in comparison to incidence and mortality rates, respectively. In conclusion, the meta-analysis approach on the abovementioned dataset revealed the epidemiological and statistical analyses for comparing COVID-19 and SARS-CoV outbreaks.

title: What does “crisis” education look like?

title: Estimating the Global Infection Fatality Rate of COVID-19
abstract: COVID-19 has become a global pandemic, resulting in nearly three hundred thousand deaths distributed heterogeneously across countries. Estimating the infection fatality rate (IFR) has been elusive due to the presence of asymptomatic or mildly symptomatic infections and lack of testing capacity. We analyze global data to derive the IFR of COVID-19. Estimates of COVID-19 IFR in each country or locality differ due to variable sampling regimes, demographics, and healthcare resources. We present a novel statistical approach based on sampling effort and the reported case fatality rate of each country. The asymptote of this function gives the global IFR. Applying this asymptotic estimator to cumulative COVID-19 data from 139 countries reveals a global IFR of 1.04% (CI: 0.77%,1.38%). Deviation of countries' reported CFR from the estimator does not correlate with demography or per capita GDP, suggesting variation is due to differing testing regimes or reporting guidelines by country. Estimates of IFR through seroprevalence studies and point estimates from case studies or sub-sampled populations are limited by sample coverage and cannot inform a global IFR, as mortality is known to vary dramatically by age and treatment availability. Our estimated IFR aligns with many previous estimates and is the first attempt at a global estimate of COVID-19 IFR.

title: Back-projection of COVID-19 diagnosis counts to assess infection incidence and control measures: analysis of Australian data
abstract: Back-projection is an epidemiological analysis method that was developed to estimate HIV incidence using surveillance data on AIDS diagnoses. It was used extensively during the 1990s for this purpose as well as in other epidemiological contexts. Surveillance data on COVID-19 diagnoses can be analysed by the method of back-projection using information about the probability distribution of the time between infection and diagnosis, which is primarily determined by the incubation period. This paper demonstrates the value of such analyses using daily diagnoses from Australia. It is shown how back-projection can be used to assess the pattern of COVID-19 infection incidence over time and to assess the impact of control measures by investigating their temporal association with changes in incidence patterns. For Australia, these analyses reveal that peak infection incidence coincided with the introduction of border closures and social distancing restrictions, while the introduction of subsequent social distancing measures coincided with a continuing decline in incidence to very low levels. These associations were not directly discernible from the daily diagnosis counts, which continued to increase after the first stage of control measures. It is estimated that a one week delay in peak incidence would have led to a fivefold increase in total infections. Furthermore, at the height of the outbreak, half to three-quarters of all infections remained undiagnosed. Automated data analytics of routinely collected surveillance data are a valuable monitoring tool for the COVID-19 pandemic and may be useful for calibrating transmission dynamics models.

title: Novel coronavirus: how things are in Wuhan

title: Explaining national differences in the mortality of Covid-19: individual patient simulation model to investigate the effects of testing policy and other factors on apparent mortality.
abstract: There has been extensive speculation on the apparent differences in mortality between countries reporting on the confirmed cases and deaths due to Covid-19. A number of explanations have been suggested, but there is no clear evidence about how apparent fatality rates may be expected to vary with the different testing regimes, admission policies and other variables. An individual patient simulation model was developed to address this question. Parameters and sensitivity analysis based upon recent international data sources for Covid-19 and results were averaged over 100 iterations for a simulated cohort of over 500,000 patients. Different testing regimes for Covid-19 were considered; testing admitted patients only, various rates of community testing of symptomatic cases and active contact-tracing and screening. In the base case analysis, apparent mortality ranged from 10.5% under a policy of testing only admitted patients to 0.4% with intensive contact tracing and community testing. These findings were sensitive to assumptions regarding admission rates and the rate of spread, with more selective admission policies and suppression of spread increasing the apparent mortality and the potential for apparent mortality rates to exceed 18% under some circumstances. Under all scenarios the proportion of patients tested in the community had the greatest impact on apparent mortality. Whilst differences in mortality due to health service and demographic factors cannot be excluded, the current international differences in reported mortality are all consistent with differences in practice regarding screening, community testing and admission policies.

title: Awareness, attitudes, and practices related to the swine influenza pandemic among the Saudi public
abstract: During an infectious disease outbreak, it is critical to learn as much as possible about the concerns, knowledge, attitudes, and behavior of the public. Such information can be crucial to the improvement of communication efforts by public health officials and clinicians. The aim of this study was to identify awareness, attitudes, and practices related to influenza A (H1N1) among the Saudi public.  A cross-sectional study of 1,548 adult subjects recruited from various shopping malls in Riyadh and Jeddah was conducted. All of the subjects were interviewed using a questionnaire that tested their knowledge, attitudes, and use of precautionary measures in relation to the H1N1 influenza pandemic.  More than half (54.3%, 840/1548) of the participants showed high concern, 43.7%(677/1548) showed a low level of knowledge, and 60.8%(941/1548) had taken minimal or no precautionary measures. After adjusting for other variables, education level was the only significant predictor of the level of concern (p < 0.001), while greater precautionary measures were taken by participants who were male (p < 0.001), older (p = 0.047), better educated (p = 0.04), and more knowledgeable (p < 0.001). More than one-third (38.3%) of participants were not convinced that the MOH reports about the disease were true, and only 16.1% of the participants reported receiving information from health providers.  High concern did not translate into a higher compliance with precautionary recommendations, possibly due to the low level of knowledge about the disease among the public. Frequent communication between physicians and the public is recommended to help dispel myths about the disease and to spread better information about the role that the public can play in limiting the spread of the disease.

title: Is there a link between temperatures and COVID-19 contagions? Evidence from Italy
abstract: This study analyzes the link between temperatures and COVID-19 contagions in a sample of Italian regions during the period ranging from February 24 to April 15. To that end, Bayesian Model Averaging techniques are used to analyze the relevance of the temperatures together with a set of additional climate, environmental, demographic, social and policy factors. The robustness of individual covariates is measured through posterior inclusion probabilities. The empirical analysis provides conclusive evidence on the role played by the temperatures given that it appears as the most relevant determinant of contagions. This finding is robust to (i) the prior distribution elicitation, (ii) the procedure to assign weights to the regressors, (iii) the presence of measurement errors in official data due to under-reporting, (iv) the employment of different metrics of temperatures or (v) the inclusion of additional correlates. In a second step, relative importance metrics that perform an accurate partitioning of the R2 of the model are calculated. The results of this approach support the evidence of the model averaging analysis, given that temperature is the top driver explaining 45% of regional contagion disparities. The set of policy-related factors appear in a second level of importance, whereas factors related to the degree of social connectedness or the demographic characteristics are less relevant.

title: Risk of secondary infection waves of COVID-19 in an insular region: the case of the Balearic Islands, Spain
abstract: The Spanish government declared the lockdown on March 14th, 2020 to tackle the fast-spreading of COVID-19. As a consequence the Balearic Islands remained almost fully isolated due to the closing of airports and ports, These isolation measures and the home-based confinement have led to a low incidence of COVID-19 in this region. We propose a compartmental model for the spread of COVID-19 including five compartments (Susceptible, Latent, Infected, Diseased, and Recovered), and the mobility between municipalities. The model parameters are calibrated with the temporal series of confirmed cases provided by the Spanish Ministry of Health. After calibration, the proposed model captures the trend of the official confirmed cases before and after the lockdown. We show that the estimated number of cases depends strongly on the initial dates of the local outbreak onset and the number of imported cases before the lockdown. Our estimations indicate that the population has not reached the level of herd immunization necessary to prevent future outbreaks. While the low incidence, in comparison to mainland Spain, has prevented the saturation of the health system, this low incidence translates into low immunization rates, therefore facilitating the propagation of new outbreaks that could lead to secondary waves of COVID-19 in the region. These findings warn about scenarios regarding after-lockdown-policies and the risk of second outbreaks, emphasize the need for widespread testing, and could potentially be extrapolated to other insular and continental regions.

title: Surveillance for Hepatitis C
abstract: Hepatitis C is a global public health problem. Globally, an estimated 170 million persons (3 % of the world’s population) have been infected with the hepatitis C virus, and an estimated 350,000 persons die annually from complications of chronic hepatitis C. Furthermore, an increasing trend in hepatitis C mortality in the USA was observed over the last decade; in 2007, mortality associated with hepatitis C surpassed mortality associated with HIV. As the hepatitis C epidemic continues, it is increasingly important to accurately measure hepatitis C-related morbidity and mortality in order to inform public health programs and policies and prioritize and evaluate prevention efforts. This chapter provides an overview of hepatitis C surveillance and methods used in the USA with some examples from other countries.

title: Early dynamics of transmission and control of COVID-19: a mathematical modelling study
abstract: An outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.  We combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas.  We estimated that the median daily reproduction number, Rt , declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.  Our results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.

title: Editor’s Perspectives – June 2020

title: Estimates of the ongoing need for social distancing and control measures post-“lockdown” from trajectories of COVID-19 cases and mortality
abstract: By 21st May 2020, SARS-CoV-2 had caused more than 5 million cases of COVID-19 across more than 200 countries. Most countries with significant outbreaks have introduced social distancing or “lockdown” measures to reduce viral transmission. So the key question now is when, how, and to what extent, these measures can be lifted. Publically available data, on daily numbers of newly-confirmed cases and mortality, were used to fit regression models estimating trajectories, doubling times and the reproduction number (R(0)) of the disease, before and under the control measures. These data ran up to 21st May 2020, and were sufficient for analysis in 89 countries. The estimates of R(0), before lockdown, based on these data were broadly consistent with those previously published: between 2.0 and 3.7 in the countries with the largest number of cases available for analysis (USA, Italy, Spain, France and UK). There was little evidence to suggest that the restrictions had reduced R far below 1 in many places, with France having the most rapid reductions – R(0) 0.76 (95%CI 0.72–0.82), based on cases and 0.77 (95%CI 0.73–0.80) based on mortality. Intermittent lockdown has been proposed as a means of controlling the outbreak while allowing periods of increase freedom and economic activity. These data suggest that few countries could have even 1 week per month unrestricted without seeing resurgence of the epidemic. Similarly, restoring 20% of the activity that has been prevented by the lockdowns looks difficult to reconcile with preventing the resurgence of the disease in most countries.

title: A systematic review of the prophylactic role of chloroquine and hydroxychloroquine in coronavirus disease‐19 (COVID‐19)
abstract: The pandemic coronavirus disease‐19 (COVID‐19) has pushed the global healthcare system to a crisis and amounted to a huge economic burden. Different drugs for prophylaxis against COVID‐19 including chloroquine (CQ) or hydroxychloroquine (HCQ) have been tried. This study was performed to systematically review the role of CQ and HCQ in preventing the spread of COVID‐19.  PubMed, EMBASE, ClinicalTrials.gov, International Clinical Trials Registry Platform and Cochrane Library databases were searched for studies that evaluated the prophylactic role of CQ or HCQ on SARS‐CoV‐2 (pre‐clinical studies) or COVID‐19 (clinical studies) until 30 March 2020. The available literature was critically appraised.  A total of 45 articles were screened and 5 (3 in vitro pre‐clinical studies and 2 clinical opinions) were included. The pre‐clinical studies showed the prophylactic effects of CQ and HCQ against SARS‐CoV‐2. On the other hand, the clinical opinions advocated the prophylactic use of CQ and HCQ against COVID‐19. However, no original clinical studies on the prophylactic role of CQ or HCQ on COVID‐19 were available.  Although pre‐clinical results are promising, to date there is a dearth of evidence to support the efficacy of CQ or HCQ in preventing COVID‐19. Considering potential safety issues and the likelihood of imparting a false sense of security, prophylaxis with CQ or HCQ against COVID‐19 needs to be thoroughly evaluated in observational studies or high‐quality randomized controlled studies.

title: EEG findings in acutely ill patients investigated for SARS‐CoV‐2/COVID‐19: A small case series preliminary report
abstract: Acute encephalopathy may occur in COVID‐19‐infected patients. We investigated whether medically indicated EEGs performed in acutely ill patients under investigation (PUIs) for COVID‐19 report epileptiform abnormalities and whether these are more prevalent in COVID‐19 positive than negative patients.  In this retrospective case series, adult COVID‐19 inpatient PUIs underwent EEGs for acute encephalopathy and/or seizure‐like events. PUIs had 8‐channel headband EEGs (Ceribell; 20 COVID‐19 positive, 6 COVID‐19 negative); 2 more COVID‐19 patients had routine EEGs. Overall, 26 Ceribell EEGs, 4 routine and 7 continuous EEG studies were reviewed. EEGs were interpreted by board‐certified clinical neurophysiologists (n = 16). EEG findings were correlated with demographic data, clinical presentation and history, and medication usage. Fisher's exact test was used.  We included 28 COVID‐19 PUIs (30‐83 years old), of whom 22 tested positive (63.6% males) and 6 tested negative (33.3% male). The most common indications for EEG, among COVID‐19‐positive vs COVID‐19‐negative patients, respectively, were new onset encephalopathy (68.2% vs 33.3%) and seizure‐like events (14/22, 63.6%; 2/6, 33.3%), even among patients without prior history of seizures (11/17, 64.7%; 2/6, 33.3%). Sporadic epileptiform discharges (EDs) were present in 40.9% of COVID‐19‐positive and 16.7% of COVID‐19‐negative patients; frontal sharp waves were reported in 8/9 (88.9%) of COVID‐19‐positive patients with EDs and in 1/1 of COVID‐19‐negative patient with EDs. No electrographic seizures were captured, but 19/22 COVID‐19‐positive and 6/6 COVID‐19‐negative patients were given antiseizure medications and/or sedatives before the EEG.  This is the first preliminary report of EDs in the EEG of acutely ill COVID‐19‐positive patients with encephalopathy or suspected clinical seizures. EDs are relatively common in this cohort and typically appear as frontal sharp waves. Further studies are needed to confirm these findings and evaluate the potential direct or indirect effects of COVID‐19 on activating epileptic activity.

title: Estimation of COVID-19-induced depletion of hospital resources in Ontario, Canada.
abstract: The global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing substantial strain to health care systems. The purpose of our study was to predict the effect of the COVID-19 pandemic on patient outcomes and use of hospital resources in Ontario, Canada.  We developed an individuallevel simulation to model the flow of patients with COVID-19 through the hospital system in Ontario. We simulated different combined scenarios of epidemic trajectory and hospital health care capacity. Our outcomes included the number of patients who needed admission to the ward or to the intensive care unit (ICU) with or without the need for mechanical ventilation, number of days to resource depletion, number of patients awaiting resources and number of deaths.  We found that with effective early public health measures, hospital system resources would not be depleted. For scenarios with late or ineffective implementation of physical distancing, hospital resources would be depleted within 14-26 days, and in the worst case scenario, 13 321 patients would die while waiting for needed resources. Resource depletion would be avoided or delayed with aggressive measures to increase ICU, ventilator and acute care hospital capacities.  We found that without aggressive physical distancing measures, the Ontario hospital system would have been inadequately equipped to manage the expected number of patients with COVID-19 despite a rapid increase in capacity. This lack of hospital resources would have led to an increase in mortality. By slowing the spread of the disease using public health measures and by increasing hospital capacity, Ontario may have avoided catastrophic stresses to its hospitals.

title: A glance at the prevalence of coronavirus disease 19 (COVID-19) in Iran: Strengths and weaknesses

title: Video Conferencing Impact on Facial Appearance: Looking Beyond the COVID-19 Pandemic

title: Special report: Early use of ICD-10-CM code "U07.1, COVID-19" to identify 2019 novel coronavirus cases in Military Health System administrative data
abstract: This report describes early exploratory analysis of ICD-10-CM code U07.1 (2019-nCoV acute respiratory disease [COVID-19]) to assess the use of administrative data for case ascertainment, syndromic surveillance, and future epidemiological studies. Out of the 2,950 possible COVID-19 cases identified between 1 April 2020 and 4 May 2020, 600 (20.3%) were detected in the Defense Medical Surveillance System (DMSS) and not in the Disease Reporting System internet (DRSi) or in Health Level 7 laboratory data from the Composite Health Care System. Among the 150 out of 600 cases identified exclusively in the DMSS and selected for Armed Forces Health Longitudinal Technology Application (AHLTA) review, 16 (10.7%) had a certified positive lab result in AHLTA, 17 (11.3%) met Council of State and Territorial Epidemiologists (CSTE) criteria for a probable case, 46 (30.7%) were not cases based on CSTE criteria, and 71 (47.3%) had evidence of a positive lab result from an outside source. Lack of full capture of lab results may continue to be a challenge as the variety of available tests expands. Administrative data may provide an important stopgap measure for detecting lab positive cases, pending incorporation of new COVID-19 tests and standardization of test and result nomenclature.

title: The Effect of Large-Scale Anti-Contagion Policies on the Coronavirus (COVID-19) Pandemic
abstract: Governments around the world are responding to the novel coronavirus (COVID-19) pandemic with unprecedented policies designed to slow the growth rate of infections. Many actions, such as closing schools and restricting populations to their homes, impose large and visible costs on society. In contrast, the benefits of these policies, in the form of infections that did not occur, cannot be directly observed and are currently understood through process-based simulations. Here, we compile new data on 1,659 local, regional, and national anti-contagion policies recently deployed in the ongoing pandemic across localities in China, South Korea, Iran, Italy, France, and the United States (US). We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of any policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of roughly 42% per day. We find that anti-contagion policies collectively have had significant effects slowing this growth. Our results suggest that similar policies may have different impacts on different populations, but we obtain consistent evidence that the policy packages now deployed are achieving large, beneficial, and measurable health outcomes. We estimate that, to date, current policies have already prevented or delayed on the order of 62 million infections across these six countries. These findings may help inform whether or when these ongoing policies should be lifted or intensified, and they can support decision-making in the other 180+ countries where COVID-19 has been reported.

title: Correcting under-reported COVID-19 case numbers: estimating the true scale of the pandemic
abstract: The COVID-19 virus has spread worldwide in a matter of a few months, while healthcare systems struggle to monitor and report current cases. Testing results have struggled with the relative capabilities, testing policies and preparedness of each affected country, making their comparison a non-trivial task. Since severe cases, which more likely lead to fatal outcomes, are detected at a higher rate than mild cases, the reported virus mortality is likely inflated in most countries. Lockdowns and changes in human behavior modulate the underlying growth rate of the virus. Under-sampling of infection cases may lead to the under-estimation of total cases, resulting in systematic mortality estimation biases. For healthcare systems worldwide it is important to know the expected number of cases that will need treatment. In this manuscript, we identify a generalizable growth rate decay reflecting behavioral change. We propose a method to correct the reported COVID-19 cases and death numbers by using a benchmark country (South Korea) with near-optimal testing coverage, with considerations on population demographics. We extrapolate expected deaths and hospitalizations with respect to observations in countries that passed the exponential growth curve. By applying our correction, we predict that the number of cases is highly under-reported in most countries and a significant burden on worldwide hospital capacity.

title: Age-dependent risks of Incidence and Mortality of COVID-19 in Hubei Province and Other Parts of China
abstract: New coronavirus SARS-CoV-2 poses a big challenge for global public health in early 2020. Coronavirus Disease 2019 (COVID-19) caused by the virus rapidly spreads all over the world and takes thousands of lives in just two months. It is critical to refine the incidence and mortality risks of COVID-19 for the effective management of the general public and patients in the outbreak. In this report, we investigate the incidence and mortality risks of the infection by analyzing the age composition of 5319 infected patients, 76 fatal cases, and 1,144,648 individuals of the general public in China. Our result shows a relatively low incidence risk for young people but a very high mortality risk for seniors. Notably, mortality risk could be as high as 0.48 for people older than 80 years. Furthermore, our study suggests that a good medical service can effectively reduce the mortality rate of the viral infection to 1% or less.

title: Pernio-like skin lesions associated with COVID-19: a case series of 318 patients from 8 countries
abstract: Increasing evidence suggests pernio-like lesions are cutaneous manifestations of COVID-19.  To describe clinical and pathologic findings of pernio-like lesions in confirmed or suspected COVID-19 cases.  An international dermatology registry was circulated to healthcare providers worldwide through the American Academy of Dermatology (AAD), International League of Dermatologic Societies (ILDS), and other organizations.  We documented 505 patients with dermatologic manifestations associated with COVID-19, including 318 (63%) with pernio-like lesions. Patients with pernio-like lesions were generally young and healthy, with relatively mild COVID-19. Of 318 cases confirmed or suspected as COVID-19 by providers, twenty-three cases (7%) were laboratory-confirmed COVID-19 positive, and 20 others (6%) were close contacts of confirmed COVID-19 cases. Given current testing criteria, many patients lacked COVID-19 testing access. For 55% of patients, pernio-like lesions were their only symptom. In patients with other COVID-19 symptoms, pernio-like lesions typically appeared after other symptoms. Pernio-like lesions lasted a median of 14 days (IQR 10-21).  A case series cannot estimate population level incidence or prevalence. Additionally, there may be confirmation bias in reporting. We cannot exclude an epiphenomenon.  Pernio-like skin changes of the feet and hands, without another explanation, may suggest COVID-19 infection and should prompt confirmatory testing.

title: Racial segregation, testing sites access, and COVID-19 incidence rate in Massachusetts, USA
abstract: The U.S. has merely 4% of the world population but 25% of the world's COVID-19 cases. Massachusetts has been in the leading position of total cases since the outbreak in the U.S. Racial residential segregation is a fundamental cause of racial disparities in health. Moreover, disparities of access to health care have a large impact on COVID-19 cases. Thus, this study estimates racial segregation and disparities in testing sites access and employs economic, demographic, and transportation variables at the city/town level in Massachusetts. Spatial regression models are applied to evaluate the relationships between COVID-19 incidence rate and related variables. This is the first study to apply spatial analysis methods across neighborhoods in the U.S. to examine the COVID-19 incidence rate. The findings are: 1) residential segregations of Hispanic and Non-Hispanic Black/African Americans have a significantly positive association with COVID-19 incidence rate, indicating the higher susceptibility of COIVD-19 infections among minority; 2) The Black has the shortest drive time to testing sites, followed by Hispanic, Asian, and Whites. The drive time to testing sites is significantly negatively associated with the COVID-19 incidence rate, implying the importance of testing location being accessed by all populations; 3) Poverty rate and road density are significant explanatory variables. Importantly, overcrowding represented by more than one person per room is a significant variable found to be positively associated with COVID-19 incidence rate, suggesting the effectiveness of social distancing for reducing infection; 4) Different from previous studies, elderly population rate is not statistically significant with incidence rate because the elderly population in Massachusetts is less distributed in the hot spot regions of COVID-19 infections. The findings in this study provide useful insights for policymakers to propose new strategies to contain the COVID-19 transmissions in Massachusetts.

title: Resident physician exposure to novel coronavirus (2019-nCoV, SARS-CoV-2) within New York City during exponential phase of COVID-19 pandemic: Report of the New York City Residency Program Directors COVID-19 Research Group
abstract: From March 2-April 12, 2020, New York City (NYC) experienced exponential growth of the COVID-19 pandemic due to novel coronavirus (SARS-CoV-2). Little is known regarding how physicians have been affected. We aimed to characterize COVID-19 impact on NYC resident physicians.  IRB-exempt and expedited cross-sectional analysis through survey to NYC residency program directors (PDs) April 3-12, 2020, encompassing events from March 2-April 12, 2020.  From an estimated 340 residency programs around NYC, recruitment yielded 91 responses, representing 24 specialties and 2,306 residents. 45.1% of programs reported at least one resident with confirmed COVID-19: 101 resident physicians were confirmed COVID-19-positive, with additional 163 residents presumed positive for COVID-19 based on symptoms but awaiting or unable to obtain testing. 56.5% of programs had a resident waiting for, or unable to obtain, COVID-19 testing. Two COVID-19-positive residents were hospitalized, with one in intensive care. Among specialties with >100 residents represented, negative binomial regression indicated that infection risk differed by specialty (p=0.039). Although most programs (80%) reported quarantining a resident, with 16.8% of residents experiencing quarantine, 14.9% of COVID-19-positive residents were not quarantined. 90 programs, encompassing 99.2% of the resident physicians, reported reuse or extended mask use, and 43 programs, encompassing 60.4% of residents, felt that personal protective equipment (PPE) was suboptimal. 65 programs (74.7%) have redeployed residents elsewhere to support COVID-19 efforts.  Many resident physicians around NYC have been affected by COVID-19 through direct infection, quarantine, or redeployment. Lack of access to testing and concern regarding suboptimal PPE are common among residency programs. Infection risk may differ by specialty.

title: Risk-adapted Treatment Strategy For COVID-19 Patients
abstract: There are no clear expert consensus or guidelines on how to treat 2019 coronavirus disease (COVID-19). The objective of this study is to investigate the short-term effect of risk-adapted treatment strategy on patients with COVID-19.  We collected the medical records of 55 COVID-19 patients for analysis. We divided these patients into mild, moderate and severe groups, and risk-adapted treatment approaches were given according to the illness severity.  Twelve patients were in mild group and 22 were in moderate group (non-severe group, n = 34), and 21 patients were in severe group. At the end of the first two weeks after admission, clinical manifestations had completely despeared in 31(91.2%)patients in non-severe group, and 18(85.7%) patients in severe group (p = 0.85). Both groups had a satisfied chest CT imaging recovery, which includes 22(64.7%) patients in non-severe group and 12(57.1%) patients in severe group recovered at least 50% of the whole leisions in the first week, and 28(82.4%) and 16(76.2%) recovered at least 75% in the second week, respectively. There were no significant differences in SARS-CoV-2 nucleic acid negativity (p = 0.92). There were also no significant differences in the levels of SARS-CoV-2-IgM and IgG antibody production between the two groups (p = 0.13, 0.62). There were 45 cases were discharged from the hospital, and no patients died at the time of this clinical analysis.  Risk-adapted treatment strategy was associated with significant clinical manifestations alleviation and clinical imaging recovery. In severe COVID-19 patients, early and short-term use of low-dose methylprednisolone was beneficial and did not delay SARS-CoV-2 nucleic acid clearance and influence IgG antibody production.

title: Age- and sex-specific total mortality impacts of the early weeks of the Covid-19 pandemic in England and Wales: Application of a Bayesian model ensemble to mortality statistics
abstract: The Covid-19 pandemic affects mortality directly through infection as well as through changes in the social, environmental and healthcare determinants of health. The impacts on mortality are likely to vary, in both magnitude and timing, by age and sex. Our aim was to estimate the total mortality impacts of the pandemic, by sex, age group and week.  We developed an ensemble of 16 Bayesian models that probabilistically estimate the weekly number of deaths that would be expected had the Covid-19 pandemic not occurred. The models account for seasonality of death rates, medium-long-term trends in death rates, the impact of temperature on death rates, association of death rates in each week on those in preceding week(s), and the impact of bank holidays. We used data from January 2010 through mid-February 2020 (i.e., week starting 15th February 2020) to estimate the parameters of each model, which was then used to predict the number of deaths for subsequent weeks as estimates of death rates if the pandemic had not occurred. We subtracted these estimates from the actual reported number of deaths to measure the total mortality impact of the pandemic.  In the week that began on 21st March, the same week that a national lockdown was put in place, there was a >92% probability that there were more deaths in men and women aged [≥]45 years than would occur in the absence of the pandemic; the probability was 100% from the subsequent week. Taken over the entire period from mid-February to 8th May 2020, there were an estimated [~] 49,200 (44,700-53,300) or 43% (37-48) more deaths than would be expected had the pandemic not taken place. 22,900 (19,300-26,100) of these deaths were in females (40% (32-48) higher than if there had not been a pandemic), and 26,300 (23,800-28,700) in males (46% (40-52) higher). The largest number of excess deaths occurred among women aged >85 years (12,400; 9,300-15,300), followed by men aged >85 years (9,600; 7,800-11,300) and 75-84 years (9,000; 7,500-10,300). The cause of death assigned to the majority (37,295) of these excess deaths was Covid-19. There was nonetheless a >99.99% probability that there has been an increase in deaths assigned to other causes in those aged [≥]45 years. However, by the 8th of May, the all-cause excess mortality had become virtually equal to deaths assigned to Covid-19, and non-Covid excess deaths had diminished to close to zero, or possibly become negative, in all age-sex groups.  The death toll of Covid-19 pandemic, in middle and older ages, is substantially larger than the number of deaths reported as a result of confirmed infection, and was visible in vital statistics when the national lockdown was put in place. When all-cause mortality is considered, the mortality impact of the pandemic on men and women is more similar than when comparing deaths assigned to Covid-19 as underlying cause of death.

title: Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers
abstract: Risk of COVID-19 infection in Wuhan has been estimated using imported case counts of international travelers, often under the assumption that all cases in travelers are ascertained. Recent work indicates variation among countries in detection capacity for imported cases. Singapore has historically had very strong epidemiological surveillance and contact-tracing capacity and has shown in the COVID-19 epidemic evidence of a high sensitivity of case detection. We therefore used a Bayesian modeling approach to estimate the relative imported case detection capacity for other countries compared to that of Singapore. We estimate that the global ability to detect imported cases is 38% (95% HPDI 22% – 64%) of Singapore’s capacity. Equivalently, an estimate of 2.8 (95% HPDI 1.5 – 4.4) times the current number of imported cases, could have been detected, if all countries had had the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify likely case-detection capacities, we found that the ability to detect imported cases relative to Singapore among high surveillance locations is 40% (95% HPDI 22% – 67%), among intermediate surveillance locations it is 37% (95% HPDI 18% – 68%), and among low surveillance locations it is 11% (95% HPDI 0% – 42%). Using a simple mathematical model, we further find that treating all travelers as if they were residents (rather than accounting for the brief stay of some of these travelers in Wuhan) can modestly contribute to underestimation of prevalence as well. We conclude that estimates of case counts in Wuhan based on assumptions of perfect detection in travelers may be underestimated by several fold, and severity correspondingly overestimated by several fold. Undetected cases are likely in countries around the world, with greater risk in countries of low detection capacity and high connectivity to the epicenter of the outbreak.

title: Estimating the COVID-19 infection rate: Anatomy of an inference problem
abstract: As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of cumulative population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Illinois, New York, and Italy is substantially lower than reported.

title: Continued high incidence of children with severe influenza A(H1N1)pdm09 admitted to paediatric intensive care units in Germany during the first three post-pandemic influenza seasons, 2010/11–2012/13
abstract: Previous influenza surveillance at paediatric intensive care units (PICUs) in Germany indicated increased incidence of PICU admissions for the pandemic influenza subtype A(H1N1)pdm09. We investigated incidence and clinical characteristics of influenza in children admitted to PICUs during the first three post-pandemic influenza seasons, using active screening.  We conducted a prospective surveillance study in 24 PICUs in Bavaria (Germany) from October 2010 to September 2013. Influenza cases among children between 1 month and 16 years of age admitted to these PICUs with acute respiratory infection were confirmed by PCR analysis of respiratory secretions.  A total of 24/7/20 influenza-associated PICU admissions were recorded in the post-pandemic seasons 1/2/3; incidence estimates per 100,000 children were 1.72/0.76/1.80, respectively. Of all 51 patients, 80 % had influenza A, including 65 % with A(H1N1)pdm09. Influenza A(H1N1)pdm09 was almost absent in season 2 (incidence 0.11), but dominated PICU admissions in seasons 1 (incidence 1.35) and 3 (incidence 1.17). Clinical data was available for 47 influenza patients; median age was 4.8 years (IQR 1.6–11.0). The most frequent diagnoses were influenza-associated pneumonia (62 %), bronchitis/bronchiolitis (32 %), secondary bacterial pneumonia (26 %), and ARDS (21 %). Thirty-six patients (77 %) had underlying medical conditions. Median duration of PICU stay was 3 days (IQR 1–11). Forty-seven per cent of patients received mechanical ventilation, and one patient (2 %) extracorporeal membrane oxygenation; 19 % were treated with oseltamivir. Five children (11 %) had pulmonary sequelae. Five children (11 %) died; all had underlying chronic conditions and were infected with A(H1N1)pdm09. In season 3, patients with A(H1N1)pdm09 were younger than in season 1 (p = 0.020), were diagnosed more often with bronchitis/bronchiolitis (p = 0.004), and were admitted to a PICU later after the onset of influenza symptoms (p = 0.041).  Active screening showed a continued high incidence of A(H1N1)pdm09-associated PICU admissions in the post-pandemic seasons 1 and 3, and indicated possible underestimation of incidence in previous German studies. The age shift of severe A(H1N1)pdm09 towards younger children may be explained by increasing immunity in the older paediatric population. The high proportion of patients with underlying chronic conditions indicates the importance of consistent implementation of the current influenza vaccination recommendations for risk groups in Germany.

title: Early Reflection on the Global Impact of COVID19, and Implications for Physiotherapy

title: Aerodynamic Characteristics and RNA Concentration of SARS-CoV-2 Aerosol in Wuhan Hospitals during COVID-19 Outbreak
abstract: The ongoing outbreak of COVID-19 has spread rapidly and sparked global concern. While the transmission of SARS-CoV-2 through human respiratory droplets and contact with infected persons is clear, the aerosol transmission of SARS-CoV-2 has been little studied.  Thirty-five aerosol samples of three different types (total suspended particle, size segregated and deposition aerosol) were collected in Patient Areas (PAA) and Medical Staff Areas (MSA) of Renmin Hospital of Wuhan University (Renmin) and Wuchang Fangcang Field Hospital (Fangcang), and Public Areas (PUA) in Wuhan, China during COVID-19 outbreak. A robust droplet digital polymerase chain reaction (ddPCR) method was employed to quantitate the viral SARS-CoV-2 RNA genome and determine aerosol RNA concentration.  The ICU, CCU and general patient rooms inside Renmin, patient hall inside Fangcang had undetectable or low airborne SARS-CoV-2 concentration but deposition samples inside ICU and air sample in Fangcang patient toilet tested positive. The airborne SARS-CoV-2 in Fangcang MSA had bimodal distribution with higher concentration than those in Renmin during the outbreak but turned negative after patients number reduced and rigorous sanitization implemented. PUA had undetectable airborne SARS-CoV-2 concentration but obviously increased with accumulating crowd flow.  Room ventilation, open space, proper use and disinfection of toilet can effectively limit aerosol transmission of SARS-CoV-2. Gathering of crowds with asymptomatic carriers is a potential source of airborne SARS-CoV-2. The virus aerosol deposition on protective apparel or floor surface and their subsequent resuspension is a potential transmission pathway and effective sanitization is critical in minimizing aerosol transmission of SARS-CoV-2.

title: A systematic review on the efficacy and safety of chloroquine for the treatment of COVID-19
abstract: COVID-19 (coronavirus disease 2019) is a public health emergency of international concern. As of this time, there is no known effective pharmaceutical treatment, although it is much needed for patient contracting the severe form of the disease. The aim of this systematic review was to summarize the evidence regarding chloroquine for the treatment of COVID-19.  PubMed, EMBASE, and three trial Registries were searched for studies on the use of chloroquine in patients with COVID-19.  We included six articles (one narrative letter, one in-vitro study, one editorial, expert consensus paper, two national guideline documents) and 23 ongoing clinical trials in China. Chloroquine seems to be effective in limiting the replication of SARS-CoV-2 (virus causing COVID-19) in vitro.  There is rationale, pre-clinical evidence of effectiveness and evidence of safety from long-time clinical use for other indications to justify clinical research on chloroquine in patients with COVID-19. However, clinical use should either adhere to the Monitored Emergency Use of Unregistered Interventions (MEURI) framework or be ethically approved as a trial as stated by the World Health Organization. Safety data and data from high-quality clinical trials are urgently needed.

title: Transmission risk of SARS-CoV-2 to healthcare workers -observational results of a primary care hospital contact tracing.
abstract: The coronavirus disease (COVID)-19 epidemic is evolving rapidly. Healthcare workers are at increased risk for infection, and specific requirements for their protection are advisable to ensure the functioning of the basic healthcare system, including the availability of general practitioners (GPs). Understanding the transmission risk is particularly important for guiding evidence-based protective measures in the primary healthcare setting.  Healthcare worker contacts of an initially undiagnosed COVID-19 case, who were without personal protective equipment, in particular not wearing facemasks, were screened with nasopharyngeal swabs and polymerase chain reaction tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), irrespective of respiratory symptoms or fever seven days after initial contact. The details of exposure to the index case were obtained during routine contact investigation after unintentional pathogen exposure.  Twenty-one healthcare workers reported contacts with the index case. Three healthcare workers reported respiratory symptoms (cough) or low-grade fever within 4 days. None of them tested positive for SARS-CoV-2 at the time of symptom onset. All 21 healthcare workers tested SARS-CoV-2 negative 7 days after initial index case contact, including the three healthcare workers with previous symptoms. Ten of the 21 healthcare workers reported a cumulative exposure time of >15 minutes. Longer cumulative contact times were associated with more individual contacts, reduced contact time per contact and activities with physical patient contact. The closest relative of the index patient tested SARS-CoV-2 positive 2 days after the index case presented at the hospital emergency department.  We found a low risk of SARS-CoV-2 transmission in a primary care setting. These findings are compatible with previous reports of the highest transmission probability in household settings with prolonged close contacts. The current protective measures for healthcare workers, including strict adherence to basic standard hygiene and facemasks, offer considerable protection during short periods of contact with symptomatic COVID-19 cases by diminishing the risk of direct and indirect transmission.

title: Successful containment of Covid‐19 outbreak in a large maternity and perinatal center while continuing clinical service
abstract: With increasing number of SARS‐CoV‐2 infections and COVID‐19 patients to be taken care of by the health system, more and more health workers become affected by the disease. It has been reported that right from the beginning of the outbreak in Lombardy up to 20% of the doctors and nurses became infected. Under these circumstances, the regular operation of health institutions already suffering from a shortage of staff becomes difficult. This has led to complete or partial shutdowns of hospitals, either due to a lack of uninfected personnel or because of uncontrollable chains of infection endangering patients. In one of the largest university perinatal center in Bavaria with more than 3000 births per year, an outbreak of COVID‐19 occurred in March 2020, affecting 36 staff members, including doctors, nurses, and midwives. Here, we describe the outbreak and present the measures contributing to the successful containment of the outbreak within three weeks. At the same time, clinical services could be maintained, however, not without deployment of personnel exposed to employees infected with SARS‐CoV‐2. Apart from massive testing of personnel in pre‐defined phases and increased hygiene measures, including a general obligation to wear surgical face masks, we identified the need to monitor cases of illness across all groups of employees, to ensure social distancing within personnel and to evaluate contacts of clinical personnel outside of the hospital environment, in order to be able to interpret chains of infections and to disrupt them. Overall, only a bundle of measures is needed to contain such an outbreak.

title: Universal Screening for SARS-CoV-2 in Women Admitted for Delivery

title: COVID-19 infection in Italian people with diabetes: Lessons learned for our future (an experience to be used)

title: Confidence in the dynamic spread of epidemics under biased sampling conditions
abstract: The interpretation of sampling data plays a crucial role in policy response to the spread of a disease during an epidemic, such as the COVID-19 epidemic of 2020. However, this is a non-trivial endeavor due to the complexity of real world conditions and limits to the availability of diagnostic tests, which necessitate a bias in testing favoring symptomatic individuals. A thorough understanding of sampling confidence and bias is necessary in order make accurate conclusions. In this manuscript, we provide a stochastic model of sampling for assessing confidence in disease metrics such as trend detection, peak detection, and disease spread estimation. Our model simulates testing for a disease in an epidemic with known dynamics, allowing us to use Monte-Carlo sampling to assess metric confidence. We use this method to show that trends in the disease may be identified using under $10000$ biased samples each day, and an estimate of disease spread can be made with additional $1000-2000$ unbiased samples each day. We also demonstrate that the model can be used to assess more advanced metrics by finding the precision and recall of a strategy for finding peaks in the dynamics.

title: Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study
abstract: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to analyze epidemics. Utilizing data mining methods on electronic resources' data might provide a better insight into the COVID-19 outbreak to manage the health crisis in each country and worldwide.  This study aimed to predict the incidence of COVID-19 in Iran.  Data were obtained from the Google Trends website. Linear regression and long short-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases. All models were evaluated using 10-fold cross-validation, and root mean square error (RMSE) was used as the performance metric.  The linear regression model predicted the incidence with an RMSE of 7.562 (SD 6.492). The most effective factors besides previous day incidence included the search frequency of handwashing, hand sanitizer, and antiseptic topics. The RMSE of the LSTM model was 27.187 (SD 20.705).  Data mining algorithms can be employed to predict trends of outbreaks. This prediction might support policymakers and health care managers to plan and allocate health care resources accordingly.

title: Covid-19 and the Hopeless University at the End of the End of History

title: Cutaneous Manifestations of COVID-19: A Preliminary Review

title: Chapter Three Epidemiology and Biostatistics
abstract: Epidemiology and biostatistics are the cornerstone of public health and preventive medicine. These practices use mathematical, scientific, and social methods to monitor disease trends and provide intervention to prevent future disease.

title: Is the discovery of the novel human betacoronavirus 2c EMC/2012 (HCoV-EMC) the beginning of another SARS-like pandemic?
abstract: Fouchier et al. reported the isolation and genome sequencing of a novel coronavirus tentatively named “human betacoronavirus 2c EMC/2012 (HCoV-EMC)” from a Saudi patient presenting with pneumonia and renal failure in June 2012. Genome sequencing showed that this virus belongs to the group C species of the genus betacoronavirus and phylogenetically related to the bat coronaviruses HKU4 and HKU5 previously found in lesser bamboo bat and Japanese Pipistrelle bat of Hong Kong respectively. Another patient from Qatar with similar clinical presentation and positive RT-PCR test was reported in September 2012. We compare and contrast the clinical presentation, laboratory diagnosis and management of infection due to this novel coronavirus and that of SARS coronavirus despite the paucity of published information on the former. Since 70% of all emerging infectious pathogens came from animals, the emergence of this novel virus may represent another instance of interspecies jumping of betacoronavirus from animals to human similar to the group A coronavirus OC43 possibly from a bovine source in the 1890s and the group B SARS coronavirus in 2003 from bat to civet and human. Despite the apparently low transmissibility of the virus at this stage, research preparedness against another SARS-like pandemic is an important precautionary strategy.

title: An Invited Commentary on “The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review”

title: Clinical characteristics of refractory COVID-19 pneumonia in Wuhan, China
abstract: Since December 2019, novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) occurred in Wuhan, and rapidly spread throughout China. This study aimed to clarify the characteristics of patients with refractory COVID-19.  In this retrospective single-center study, we included 155 consecutive patients with confirmed COVID-19 in Zhongnan Hospital of Wuhan University from January 1(st) to February 5(th). The cases were divided into general and refractory COVID-19 groups according to the clinical efficacy after hospitalization, and the difference between groups were compared.  Compared with general COVID-19 patients (45.2%), refractory patients had an older age, male sex, more underlying comorbidities, lower incidence of fever, higher levels of maximum temperature among fever cases, higher incidence of breath shortness and anorexia, severer disease assessment on admission, high levels of neutrophil, aspartate aminotransferase (AST), lactate dehydrogenase (LDH) and C-reactive protein, lower levels of platelets and albumin, and higher incidence of bilateral pneumonia and pleural effusion (P<0.05). Refractory COVID-19 patients were more likely to receive oxygen, mechanical ventilation, expectorant, and adjunctive treatment including corticosteroid, antiviral drugs and immune enhancer (P<0.05). After adjustment, those with refractory COVID-19 were also more likely to have a male sex and manifestations of anorexia and fever on admission, and receive oxygen, expectorant and adjunctive agents (P<0.05) when considering the factors of disease severity on admission, mechanical ventilation, and ICU transfer.  Nearly 50% COVID-19 patients could not reach obvious clinical and radiological remission within 10 days after hospitalization. The patients with male sex, anorexia and no fever on admission predicted poor efficacy.

title: The CoRisk-Index: A data-mining approach to identify industry-specific risk assessments related to COVID-19 in real-time
abstract: While the coronavirus spreads, governments are attempting to reduce contagion rates at the expense of negative economic effects. Market expectations plummeted, foreshadowing the risk of a global economic crisis and mass unemployment. Governments provide huge financial aid programmes to mitigate the economic shocks. To achieve higher effectiveness with such policy measures, it is key to identify the industries that are most in need of support. In this study, we introduce a data-mining approach to measure industry-specific risks related to COVID-19. We examine company risk reports filed to the U.S. Securities and Exchange Commission (SEC). This alternative data set can complement more traditional economic indicators in times of the fast-evolving crisis as it allows for a real-time analysis of risk assessments. Preliminary findings suggest that the companies' awareness towards corona-related business risks is ahead of the overall stock market developments. Our approach allows to distinguish the industries by their risk awareness towards COVID-19. Based on natural language processing, we identify corona-related risk topics and their perceived relevance for different industries. The preliminary findings are summarised as an up-to-date online index. The CoRisk-Index tracks the industry-specific risk assessments related to the crisis, as it spreads through the economy. The tracking tool is updated weekly. It could provide relevant empirical data to inform models on the economic effects of the crisis. Such complementary empirical information could ultimately help policymakers to effectively target financial support in order to mitigate the economic shocks of the crisis.

title: Is there evidence that BCG vaccination has non-specific protective effects for COVID 19 infections or is it an illusion created by lack of testing?
abstract: The goal of this paper is to showcase that the COVID-19 disease pattern is evolving and to study the relationship between mandatory BCG policy and caseload/million or death/per million. We analyze seven recent publications on the impact of BCG vaccinations on the development of COVID19 illness and extend presented findings using the latest data from April 10, 2020. We analyze data from 98 countries and we extend existing models by adding the dimension of COVID-19-related testing conducted by the analyzed countries. Similarly to prior studies, we find that COVID-19 attributable case and death incidences across countries share a relationship with the BCG vaccination inclusion in the national immunization program of a country when testing is not taken into consideration. However, this relationship vanishes when we add the dimension of testing. We observe that case and death incidences conditional on testing do not get affected by the BCG vaccination inclusion in the national immunization program of a country. Therefore, we show that there is no statistical evidence to support the assertion that inclusion of BCG vaccination in national immunization program (NIP) has any impact of COVID 19 infections (cases) or mortality.

title: Cross-Country Comparison of Case Fatality Rates of COVID-19/SARS-COV-2
abstract: Case fatality rates (CFR) and recovery rates are important readouts during epidemics and pandemics. In this article, an international analysis was performed on the ongoing coronavirus disease 2019 (COVID-19) pandemic.  Data were retrieved from accurate databases according to the user’s guide of data sources for patient registries, CFR and recovery rates were calculated for each country. A comparison of CFR between countries with total cases ≥ 1,000 was observed for 12(th) and 23(rd) March.  Italy’s CFR was the highest of all countries studied for both time points (12(th) March, 6.22% versus 23(rd) March, 9.26%). The data showed that even though Italy was the only European country reported on 12(rd) March, Spain and France had the highest CFR of 6.16 and 4.21%, respectively, on 23(rd) March, which was strikingly higher than the overall CFR of 3.61%.  Obtaining detailed and accurate medical history from COVID-19 patients, and analyzing CFR alongside the recovery rate, may enable the identification of the highest risk areas so that efficient medical care may be provided. This may lead to the development of point-of-care tools to help clinicians in stratifying patients based on possible requirements in the level of care, to increase the probabilities of survival from COVID-19 disease.

title: SEIR and Regression Model based COVID-19 outbreak predictions in India
abstract: COVID-19 pandemic has become a major threat to the country. Till date, well tested medication or antidote is not available to cure this disease. According to WHO reports, COVID-19 is a severe acute respiratory syndrome which is transmitted through respiratory droplets and contact routes. Analysis of this disease requires major attention by the Government to take necessary steps in reducing the effect of this global pandemic. In this study, outbreak of this disease has been analysed for India till 30th March 2020 and predictions have been made for the number of cases for the next 2 weeks. SEIR model and Regression model have been used for predictions based on the data collected from John Hopkins University repository in the time period of 30th January 2020 to 30th March 2020. The performance of the models was evaluated using RMSLE and achieved 1.52 for SEIR model and 1.75 for the regression model. The RMSLE error rate between SEIR model and Regression model was found to be 2.01. Also, the value of R0 which is the spread of the disease was calculated to be 2.02. Expected cases may rise between 5000-6000 in the next two weeks of time. This study will help the Government and doctors in preparing their plans for the next two weeks. Based on the predictions for short-term interval, these models can be tuned for forecasting in long-term intervals.

title: COVID-19 incidence and R decreased on the Isle of Wight after the launch of the Test, Trace, Isolate programme
abstract: In May 2020 the UK introduced a Test, Trace, Isolate programme in response to the COVID-19 pandemic. The programme was first rolled out on the Isle of Wight and included Version 1 of the NHS contact tracing app. We used COVID-19 daily case data to infer incidence of new infections and estimate the reproduction number R for each of 150 Upper Tier Local Authorities in England, and at the National level, before and after the launch of the programme on the Isle of Wight. We used Bayesian and Maximum-Likelihood methods to estimate R, and compared the Isle of Wight to other areas using a synthetic control method. We observed significant decreases in incidence and R on the Isle of Wight immediately after the launch. These results are robust across each of our approaches. Our results show that the sub-epidemic on the Isle of Wight was controlled significantly more effectively than the sub-epidemics of most other Upper Tier Local Authorities, changing from having the third highest reproduction number R (of 150) before the intervention to the tenth lowest afterwards. The data is not yet available to establish a causal link. However, the findings highlight the need for further research to determine the causes of this reduction, as these might translate into local and national non-pharmaceutical intervention strategies in the period before a treatment or vaccination becomes available.

title: SARS-CoV-2 and COVID-19: The most important research questions
abstract: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an ongoing global health emergency. Here we highlight nine most important research questions concerning virus transmission, asymptomatic and presymptomatic virus shedding, diagnosis, treatment, vaccine development, origin of virus and viral pathogenesis.

title: What is the true incidence of COVID-19 in patients with rheumatic diseases?

title: Anosmia in COVID-19 patients
abstract: Coronaviruses (CoVs) have a neuroinvasive propensity, and the frequently reported symptoms of smelling and taste dysfunction in many COVID-19 patients may be related to the respective capability of SARS-CoV2, the cause of the current pandemic. In this study we objecti-fied and quantified the magnitude and underreporting of the smelling dysfunction caused by COVID-19 using a standardized test.  We conducted a prospective cross-sectional study comparing the proportion of anos-mia using Sniffin-sticks in those reporting a loss of smell, in those who did not as well as in unin-fected controls. The outcome of anosmic versus not anosmic patients were recorded during hospital stay and at day 15 on a six-category ordinal scale. The study was approved by the insti-tutional review board, all participants consented to the study.  40% of 45 consecutive hospitalized COVID-19 patients and 0% of 45 uninfected con-trols consenting were diagnosed with anosmia. 44% of anosmic and 50% of hyposmic patients did not report having smelling problems. Anosmia or hyposmia was not predictive of a severe COVID-19 manifestation.  The majority of COVID-19 patients have an objective anosmia and hyposmia, which often occurs unnoticed. These symptoms may be related to the neuroinvasive propensity of SARS-COV-2 and the unusual presentation of COVID-19 disease manifestations.

title: CoViD--19: An Automatic, Semiparametric Estimation Method for the Population Infected in Italy
abstract: To date, official data on the number of people infected with the SARS-CoV-2 , responsible for the CoViD19 , have been released by the Italian Government just on the basis of a non representative sample of population which tested positive for the swab. However a reliable estimation of the number of infected, including asymptomatic people, turns out to be crucial in the preparation of operational schemes and to estimate the future number of people, who will require, to different extents, medical attentions. In order to overcome the current data shortcoming, this paper proposes a bootstrap driven, estimation procedure for the number of people infected with the SARSCoV2. This method is designed to be robust, automatic and suitable to generate estimations at regional level. Obtained results show that, while official data at March the 12th report 12.839 cases in Italy, people infected wiyh the SARSCoV2 could be as high as 105.789.

title: Modeling behavioral change and COVID-19 containment in Mexico: A trade-off between lockdown and compliance
abstract: Emergency Measures (SEM) were implemented in Mexico on March 30th, 2020 requiring the suspension of non-essential activities. This action followed a Healthy Distance Sanitary action on March 23rd, 2020. The aim of both measures was to reduce community transmission of COVID-19 in Mexico by lowering the effective contact rate. Using a modification of the Kermack-McKendrick SEIR model we explore the effect of behavioral changes required to lower community transmission by introducing a time-varying contact rate, and the consequences of disease spread in a population subject to suspension of non-essential activities. Our study shows that there exists a trade-off between the proportion of the population under SEM and the average time an individual is committed to all the behavioral changes needed to achieve an effective social distancing. This trade-off generates an optimum value for the proportion of the population under strict mitigation measures, significantly below 1 in some cases, that minimizes maximum COVID-19 incidence. We study the population-level impact of three key factors: the implementation of behavior change control measures, the time horizon necessary to reduce the effective contact rate and the proportion of people under SEM in combating COVID-19. Our model is fitted to the available data. The initial phase of the epidemic, from February 17th to March 23rd, 2020, is used to estimate the contact rates, infectious periods and mortality rate using both confirmed cases (by date of symptoms initiation), and daily mortality. Data on deaths after march 23rd, 2020 is used to estimate the mortality rate after the mitigation measures are implemented. Our simulations indicate that the most likely dates for maximum incidence are between late May and early June, 2020 under a scenario of high SEM compliance and low SEM abandonment rate.

title: The basic reproduction number of novel coronavirus (2019-nCoV) estimation based on exponential growth in the early outbreak in China from 2019 to 2020: A reply to Dhungana

title: Chapter 6 Sources of Harm Prescription Drugs, Surgery, and Infections
abstract: Most medical harm is from prescription drugs, surgery, and healthcare-acquired infections. Although the full extent of medical harm remains to be accurately gauged, estimates of incidence have tended to grow larger with each successive detailed assessment. Estimates of the extent of harm in the United States published by the Institutes of Medicine in 2000, which at the time were so shocking as to be disbelieved by some authorities, have since been consistently eclipsed by further detailed analyses. Recent studies show that harm from drugs and infections individually exceeds estimates of what was previously thought to be the total of healthcare-related harm from all causes. The emergence of antibiotic-resistant microorganisms, due primarily to the use, misuse, and overuse of antibiotics, is a particularly ominous threat to future personal and population health.

title: Coronavirus disease 2019 in children: Surprising findings in the midst of a global pandemic
abstract: Question Coronavirus disease 2019 (COVID-19) is affecting millions of people worldwide. It seems that it affects mostly adults older than 40 years of age, and the death rate is highest for older individuals in the population. What should I tell parents worried about their children contracting the coronavirus (SARS-CoV-2) causing COVID-19, and what symptoms should I look for to determine if there is a need to test for the virus?Answer The COVID-19 global pandemic affects all ages. Severe respiratory manifestations have been the mainstay of illness in adults, with what seems to be rapid deterioration necessitating mechanical ventilation. Only 5% of those tested and found to have COVID-19 have been younger than 19 years, possibly owing to limited testing, as the symptoms in children are usually mild. Symptoms in children include fever, dry cough, rhinorrhea, sore throat, and fatigue, and in 10% diarrhea or vomiting. Rarely dyspnea or hypoxemia were also described. Blood tests and imaging have been shown to be of little value in children and should only be ordered for those in whom you would normally order these investigations for viral-like illness. No specific therapy is available and supportive care with rest, fluids, and antipyretics for children is the recommended approach. Ibuprofen or acetaminophen for fever and pain can be given. Antiviral and immunomodulatory treatment is not recommended at this time for otherwise healthy children, and corticosteroids should also not be used. Children with immunocompromised states should be isolated and avoid contact with others.

title: Endoscopy during the Covid-19 outbreak: experience and recommendations from a single center in a high-incidence scenario
abstract: A dramatic SARS-Cov-2 outbreak is hitting Italy hard. To face the new scenario all the hospitals have been re-organised in order to reduce all the outpatient services and to devote almost all their personnel and resources to the management of Covid-19 patients. As a matter of fact, all the services have undergone a deep re-organization guided by: the necessity to reduce exams, to create an environment that helps reduce the virus spread, and to preserve the medical personnel from infection. In these days a re-organization of the endoscopic unit, sited in a high-incidence area, has been adopted, with changes to logistics, work organization and patients selection. With the present manuscript, we want to support gastroenterologists and endoscopists in the organization of a “new” endoscopy unit that responds to the “new” scenario, while remaining fully aware that resources availability and local circumstances may extremely vary from unit to unit.

title: Neoplasia

title: Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters
abstract: With continuous global COVID-19 outbreak, differing case numbers and mortality rates are observed. While actual case numbers appear vague, mortality numbers related to COVID-19 seem more precise. In this study, we used the mortality rate as the main indicator to evaluate the extent of underreporting and underdetection of COVID-19 cases.  We have analyzed all available data provided by the World Health Organization on the development of international COVID-19 cases and mortality numbers on March 17th, 2020. A crude case-fatality risk (cCFR) and adjusted case-fatality risk (aCFR) was calculated for China, South Korea, Japan, Italy, France, Spain, Germany, Iran and the United States. Additionally, a fold-change (FC) was derived for each country.  The highest aCFR and FC were detected for Spain. Based on their FC values, an extremely high number of undetected COVID-19 cases was displayed in France, the United States, Italy and Spain. For these countries, our findings indicate a detection rate of only 1-2% of total actual COVID-19 cases.  Due to limited testing capacities, mortality numbers may serve as a better indicator for COVID-19 case spread in many countries. Our data indicate that countries like France, Italy, the United States, Iran and Spain have extremely high numbers of undetected and underreported cases. Differences in testing availability and capacity, containment as well as overall health care and medical infrastructure result in significantly different mortality rates and COVID-19 case numbers for each respective country.

title: Epidemiological, Clinical Characteristics and Outcome of Medical Staff Infected with COVID-19 in Wuhan, China: A Retrospective Case Series Analysis
abstract: Since December 2019, a novel coronavirus epidemic has emerged in Wuhan city, China and then rapidly spread to other areas. As of 20 Feb 2020, a total of 2,055 medical staff confirmed with coronavirus disease 2019 (COVID-19) caused by SARS-Cov-2 in China had been reported. We sought to explore the epidemiological, clinical characteristics and prognosis of novel coronavirus-infected medical staff.  In this retrospective study, 64 confirmed cases of novel coronavirus-infected medical staff admitted to Union Hospital, Wuhan between 16 Jan, 2020 to 15 Feb, 2020 were included. Two groups concerned were extracted from the subjects based on duration of symptoms: group 1 (<= 10 days) and group 2 (>10 days). Epidemiological and clinical data were analyzed and compared across groups. The Kaplan-Meier plot was used to inspect the change in hospital discharge rate. The Cox regression model was utilized to identify factors associated with hospital discharge.  The median age of medical staff included was 35 years old. 64% were female and 67% were nurses. None had an exposure to Huanan seafood wholesale market or wildlife. A small proportion of the cohort had contact with specimens (5%) as well as patients in fever clinics (8%) and isolation wards (5%). Fever (67%) was the most common symptom, followed by cough (47%) and fatigue (34%). The median time interval between symptoms onset and admission was 8.5 days. On admission, 80% of medical staff showed abnormal IL-6 levels and 34% had lymphocytopenia. Chest CT mainly manifested as bilateral (61%), subpleural (80%) and ground-glass (52%) opacities. During the study period, no patients was transferred to intensive care unit or died, and 34 (53%) had been discharged. Higher body mass index (BMI) (HR 0.14; 95% CI 0.03-0.73), fever (HR 0.24; 95% CI 0.09-0.60) and higher levels of IL-6 on admission (HR 0.31; 95% CI 0.11-0.87) were unfavorable factors for discharge.  In this study, medical staff infected with COVID-19 have relatively milder symptoms and favorable clinical course, which may be partly due to their medical expertise, younger age and less underlying diseases. Smaller BMI, absence of fever symptoms and normal IL-6 levels on admission are favorable for discharge for medical staff. Further studies should be devoted to identifying the exact patterns of SARS-CoV-2 infection among medical staff.

title: Diagnostic Testing for Severe Acute Respiratory Syndrome–Related Coronavirus-2: A Narrative Review
abstract: Diagnostic testing to identify persons infected with severe acute respiratory syndrome–related coronavirus-2 (SARS–CoV-2) infection is central to control the global pandemic of COVID-19 that began in late 2019. In a few countries, the use of diagnostic testing on a massive scale has been a cornerstone of successful containment strategies. In contrast, the United States, hampered by limited testing capacity, has prioritized testing for specific groups of persons. Real-time reverse transcriptase polymerase chain reaction–based assays performed in a laboratory on respiratory specimens are the reference standard for COVID-19 diagnostics. However, point-of-care technologies and serologic immunoassays are rapidly emerging. Although excellent tools exist for the diagnosis of symptomatic patients in well-equipped laboratories, important gaps remain in screening asymptomatic persons in the incubation phase, as well as in the accurate determination of live viral shedding during convalescence to inform decisions to end isolation. Many affluent countries have encountered challenges in test delivery and specimen collection that have inhibited rapid increases in testing capacity. These challenges may be even greater in low-resource settings. Urgent clinical and public health needs currently drive an unprecedented global effort to increase testing capacity for SARS–CoV-2 infection. Here, the authors review the current array of tests for SARS–CoV-2, highlight gaps in current diagnostic capacity, and propose potential solutions.

title: Synthesis and activity of an octapeptide inhibitor designed for SARS coronavirus main proteinase
abstract: The outbreak of SARS, a life-threatening disease, has spread over many countries around the world. So far there is no effective drug for the treatment of SARS. Stimulated by the binding mechanism of SARS-CoV M(pro) with the octapeptide AVLQSGFR reported recently as well as the “Chou's distorted key” theory, we synthesized the octapeptide AVLQSGFR for conducting various biochemical experiments to investigate the antiviral potential of the octapeptide against SARS coronavirus (BJ-01). The results demonstrate that, compared with other compounds reported so far, AVLQSGFR is the most active in inhibiting replication of the SARS coronavirus, and that no detectable toxicity is observed on Vero cells under the condition of experimental concentration.

title: Review of Airline-within-Airline strategy: Case studies of the Singapore Airlines Group and Qantas Group
abstract: The growth of the aviation industry has seen a rapid increase in low-cost carriers (LCCs) commencing operations, threatening the sustainability of a number of legacy airlines. The response to this challenge and threat has been for legacy airlines to create an airline-within-airline (AWA). This study reviews prior literature regarding the hotel industry and multi-brand strategy, and also uses case studies to examine the evolution of the AWA strategy at the Singapore Airlines Group and the Qantas Group between 2000 and 2016 in order to identify why these airlines operate AWAs successfully. High levels of autonomy, clear strategies, complimentary route networks, appropriate resources and minimal cannibalisation are identified as the primary attributes required for a successful AWA operation. Legacy airlines whose AWA strategy failed in the past often did not operate with all these essential attributes, which resulted in their AWAs undermining and competing directly with their own operations.

title: Serological tests facilitate identification of asymptomatic SARS‐CoV‐2 infection in Wuhan, China
abstract: The Wuhan City has ended the lockdown and people have been allowed to resume working since April 8 if meeting a set of COVID‐19‐associated tests including SARS‐CoV‐2 nucleic acid test (NAT) of nasopharyngeal swabs, chest CT scan or a SARS‐CoV‐2‐specific serological test. Here, we reported the positive rate of COVID‐19 tests based on NAT, chest CT scan and a serological SARS‐CoV‐2 test, from April 3 to 15 in one hospital in Qingshan Destrict, Wuhan. We observed a ~10% SARS‐CoV‐2‐specific IgG positive rate from 1,402 tests. Combination of SARS‐CoV‐2 NAT and a specific serological test might facilitate the detection of COVID‐19 infection, or the asymptomatic SARS‐CoV‐2‐infected subjects. Large‐scale investigation is required to evaluate the herd immunity of the city, for the resuming people and for the re‐opened city. This article is protected by copyright. All rights reserved.

title: Temporal relationship between outbound traffic from Wuhan and the 2019 coronavirus disease (COVID-19) incidence in China
abstract: The city of Wuhan is the epicenter of the 2019 coronavirus disease (COVID-19) outbreak and a central Chinese hub for transportation and industry. Mass migration prior to the Chinese New Year may have accelerated the spread of COVID-19 across China. This analysis investigated the temporal relationship between daily outbound traffic from Wuhan and the incidence of COVID-19 in 31 Chinese provinces during January-February 2020.  We collected incidence of confirmed COVID-19 cases from National and Provincial Health Committee reports from January 10 to February 29, 2020. Volume of outbound traffic from Wuhan to other provinces was measured by Baidu Migration Index, a widely used metric that tracks migration based on cellphone location. We used cross-correlation function and autoregressive integrated moving average (ARIMA) model to examine time-lagged association between traffic volume and COVID-19 incidence by province. Contributors to the provincial variation in the temporal associations were investigated. Additionally, we estimated the reduction in cumulative incidence of COVID-19 cases following the travel ban for Wuhan.  Cross-correlation function analyses suggested that the volume of outbound traffic from Wuhan was positively associated with COVID-19 incidence in all provinces, with correlation coefficients between 0.22-0.78 (all P<0.05). Approximately 42% of provinces showed <1 week of lag between traffic volume and COVID-19 incidence, 39% with 1 week, and 19% with 2-3 weeks. Migration had more prolonged impacts in provinces closer to Wuhan and with more passenger influx from Wuhan, but affected economically advantaged provinces to a lesser extent. We further estimated that the travel ban may have prevented approximately 19,768 COVID-19 cases (95% CI: 13,589, 25,946) outside of Wuhan by February 29, 2020.  Outflowing migration from Wuhan facilitated the COVID-19 transmission to other parts of China with varying time-lagged effects dependent on provincial characteristics. The travel ban led to a significant reduction in COVID-19 outside of Wuhan.

title: Pandemic preparedness of community pharmacies for COVID-19: A cross-sectional survey
abstract: Community pharmacies provide an important healthcare service, which is broadly established, and constitutes the preferred and initial contact for members of the community. The significant value of community pharmacies was further highlighted during the COVID-19 pandemic crisis.  The assessment of community pharmacies preparedness for the COVID-19 pandemic.  A cross‐sectional interview survey of 1018 community pharmacies working in four regions of Egypt (South, East, Centre, and North). Data collection was conducted from 8–19 April 2020.  Availability of personal protective equipment (PPE) and medication was better than alcohol (70% conc.). Home delivery services were available in 49.1% of pharmacies. Infection control measures covering interactions between staff were in place in up to 99.5% of pharmacies. Conversely, there was less frequent availability of contactless payment (29.1%), hand sanitizers (62.1%) or masks (86.5%) for customer use, or a separate area for patients with suspected COVID-19 (64%). Verbal customer education (90.4%) was used preferably to written (81.3%). Despite high clinical knowledge and awareness (97.6%–99.2%), only 8.8% of pharmacists had reported suspected COVID-19 cases, however this varied significantly with pharmacist demographics (geographic region P < 0.001; pandemic training p < 0.001; position p = 0.019; age p = 0.046).  Government and policymakers strive to mitigate the shortage of PPE and medication. More attention should be given to infection control measures around interactions between staff and customers to ensure community pharmacists are fit and able to provide continuity in their important role. Educating customers using regularly-updated posters, banners or signs will contribute to decreasing contact with patients, and reducing the number and duration of visits to the pharmacy. Pandemic preparedness of community pharmacists must also extend to reporting procedures. By avoiding under-reporting or over-reporting, community pharmacists will contribute to accurate monitoring of the national spread of infection.

title: Basic prediction methodology for covid-19: estimation and sensitivity considerations
abstract: The purpose of the present paper is to present simple estimation and prediction methods for basic quantities in an emerging epidemic like the ongoing covid-10 pandemic. The simple methods have the advantage that relations between basic quantities become more transparent, thus shedding light to which quantities have biggest impact on predictions, with the additional conclusion that uncertainties in these quantities carry over to high uncertainty also in predictions. A simple non-parametric prediction method for future cumulative case fatalities, as well as future cumulative incidence of infections (assuming a given infection fatality risk f), is presented. The method uses cumulative reported case fatalities up to present time as input data. It is also described how the introduction of preventive measures of a given magnitude ρ will affect the two incidence predictions, using basic theory of epidemic models. This methodology is then reversed, thus enabling estimation of the preventive magnitude ρ, and of the resulting effective reproduction number RE. However, the effects of preventive measures only start affecting case fatalities some 3-4 weeks later, so estimates are only available after this time has elapsed. The methodology is applicable in the early stage of an outbreak, before, say, 10% of the community have been infected. Beside giving simple estimation and prediction tools for an ongoing epidemic, another important conclusion lies in the observation that the two quantities f (infection fatality risk) and ρ (the magnitude of preventive measures) have very big impact on predictions. Further, both of these quantities currently have very high uncertainty: current estimates of f lie in the range 0.2% up to 2% (, ), and the overall effect of several combined preventive measures is clearly very uncertain. The two main findings from the paper are hence that, a) any prediction containing f, and/or some preventive measures, contain a large amount of uncertainty (which is usually not acknowledged well enough), and b) obtaining more accurate estimates of in particular f, should be highly prioritized. Seroprevalence testing of random samples in a community where the epidemic has ended are urgently needed.

title: Exercising caution in correlating COVID-19 incidence and mortality rates with BCG vaccination policies due to variable rates of SARS CoV-2 testing
abstract: TThe Bacillus Calmette-Guerin (BCG) vaccine provides protection against tuberculosis (TB), and is proposed to provide protection to non-TB infectious diseases. The COVID-19 outbreak results from infection with the novel coronavirus SARS-CoV-2 (CoV-2) and was declared a pandemic on March 11th, 2020. We queried whether the BCG vaccine offers protection against CoV-2 infection. We observed that countries with a current universal BCG vaccination policy have a significantly lower COVID-19 incidence than countries which never had a universal BCG policy or had one in the past. However, population density, median age, TB incidence, urban population, and, most significantly, CoV-2 testing rate, were also connected with BCG policy and could potentially confound the analysis. By limiting the analysis to countries with high CoV-2 testing rates, defined as greater than 2,500 tests per million inhabitants, these parameters were no longer statistically associated with BCG policy. When analyzing only countries with high testing rates, there was no longer a significant association between the number of COVID-19 cases per million inhabitants and the BCG vaccination policy. Although preliminary, our analyses indicate that the BCG vaccination may not offer protection against CoV-2 infection. While reporting biases may confound our observations, our findings support exercising caution in determining potential correlation between BCG vaccination and COVID-19 incidence, in part due significantly lower rates of CoV-2 testing per million inhabitants in countries with current universal BCG vaccination policy.

title: Inbred Strain Variant Database (ISVdb): A Repository for Probabilistically Informed Sequence Differences Among the Collaborative Cross Strains and Their Founders
abstract: The Collaborative Cross (CC) is a panel of recently established multiparental recombinant inbred mouse strains. For the CC, as for any multiparental population (MPP), effective experimental design and analysis benefit from detailed knowledge of the genetic differences between strains. Such differences can be directly determined by sequencing, but until now whole-genome sequencing was not publicly available for individual CC strains. An alternative and complementary approach is to infer genetic differences by combining two pieces of information: probabilistic estimates of the CC haplotype mosaic from a custom genotyping array, and probabilistic variant calls from sequencing of the CC founders. The computation for this inference, especially when performed genome-wide, can be intricate and time-consuming, requiring the researcher to generate nontrivial and potentially error-prone scripts. To provide standardized, easy-to-access CC sequence information, we have developed the Inbred Strain Variant Database (ISVdb). The ISVdb provides, for all the exonic variants from the Sanger Institute mouse sequencing dataset, direct sequence information for CC founders and, critically, the imputed sequence information for CC strains. Notably, the ISVdb also: (1) provides predicted variant consequence metadata; (2) allows rapid simulation of F1 populations; and (3) preserves imputation uncertainty, which will allow imputed data to be refined in the future as additional sequencing and genotyping data are collected. The ISVdb information is housed in an SQL database and is easily accessible through a custom online interface (http://isvdb.unc.edu), reducing the analytic burden on any researcher using the CC.

title: Impact of temperature on the dynamics of the COVID-19 outbreak in China
abstract: A COVID-19 outbreak emerged in Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. The effects of temperature on the dynamics of the COVID-19 epidemic in China are unknown. Data on COVID-19 daily confirmed cases and daily mean temperatures were collected from 31 provincial-level regions in mainland China between Jan. 20 and Feb. 29, 2020. Locally weighted regression and smoothing scatterplot (LOESS), distributed lag nonlinear models (DLNMs), and random-effects meta-analysis were used to examine the relationship between daily confirmed cases rate of COVID-19 and temperature conditions. The daily number of new cases peaked on Feb. 12, and then decreased. The daily confirmed cases rate of COVID-19 had a biphasic relationship with temperature (with a peak at 10 °C), and the daily incidence of COVID-19 decreased at values below and above these values. The overall epidemic intensity of COVID-19 reduced slightly following days with higher temperatures with a relative risk (RR) was 0.96 (95% CI: 0.93, 0.99). A random-effect meta-analysis including 28 provinces in mainland China, we confirmed the statistically significant association between temperature and RR during the study period (Coefficient = −0.0100, 95% CI: −0.0125, −0.0074). The DLNMs in Hubei Province (outside of Wuhan) and Wuhan showed similar patterns of temperature. Additionally, a modified susceptible-exposed-infectious-recovered (M-SEIR) model, with adjustment for climatic factors, was used to provide a complete characterization of the impact of climate on the dynamics of the COVID-19 epidemic.

title: Untangling factors associated with country-specific COVID-19 incidence, mortality and case fatality rates during the first quarter of 2020
abstract: At early stages of the COVID-19 pandemic which we are experiencing, the publicly reported incidence, mortality and case fatality rates (CFR) vary significantly between countries. Here we aim to untangle factors that are associated with the differences during the first quarter of the year 2020. Number of performed COVID-19 tests has a strong correlation with country-specific incidence (p <2×10-16) and mortality rate (p = 5.1×10-8). Using multivariate linear regression we show that incidence and mortality rates correlate significantly with GDP per capita (p = 2.6×10-15 and 7.0×10-4, respectively), country-specific duration of the outbreak (2.6×10-4 and 0.0019), fraction of citizens over 65 years old (p = 0.0049 and 3.8×10-4) and level of press freedom (p = 0.021 and 0.019) which cumulatively explain 80% of variability of incidence and more than 60% of variability of mortality of the disease during the period analyzed. Country hemisphere demonstrated significant correlation only with mortality (p = 0.17 and 0.036) whereas population density (p = 0.94 and p = 0.75) and latitude (p = 0.61 and 0.059) did not reach significance in our model. Case fatality rate is shown to rise as the outbreak progresses (p = 0.028). We rank countries by COVID-19 mortality corrected for incidence and the factors that were shown to affect it, and by CFR corrected for outbreak duration, yielding very similar results. Among the countries where the outbreak started after the 15th of February and with at least 1000 registered patients during the period analyzed, the lowest corrected CFR are seen in Israel, South Africa and Chile. The ranking results should be considered with caution as they do not consider all confounding factors or data reporting biases.

title: Radiation therapy considerations during the COVID-19 Pandemic: Literature review and expert opinions

title: Importations of COVID-19 into African countries and risk of onward spread
abstract: The emergence of a novel coronavirus (SARS-CoV-2) in Wuhan, China, at the end of 2019 has caused widespread transmission around the world. As new epicentres in Europe and America have arisen, of particular concern is the increased number of imported coronavirus disease 2019 (COVID-19) cases in Africa, where the impact of the pandemic could be more severe. We aim to estimate the number of COVID-19 cases imported from 12 major epicentres in Europe and America to each African country, as well as the probability of reaching 10,000 infections in total by the end of March, April, and May following viral introduction.  We used the reported number of cases imported from the 12 major epicentres in Europe and America to Singapore, as well as flight data, to estimate the number of imported cases in each African country. Under the assumption that Singapore has detected all the imported cases, the estimates for Africa were thus conservative. We then propagated the uncertainty in the imported case count estimates to simulate the onward spread of the virus, until 10,000 infections are reached or the end of May, whichever is earlier. Specifically, 1,000 simulations were run separately under two scenarios, where the reproduction number under the stay-at-home order was assumed to be 1.5 and 1.0 respectively.  We estimated Morocco, Algeria, South Africa, Egypt, Tunisia, and Nigeria as having the largest number of COVID-19 cases imported from the 12 major epicentres. Based on our 1,000 simulation runs, Morocco and Algeria's estimated probability of reaching 10,000 infections by end of March was close to 100% under both scenarios. In particular, we identified countries with less than 100 cases in total reported by end of April whilst the estimated probability of reaching 10,000 infections by then was higher than 50% even under the more optimistic scenario.  Our study highlights particular countries that are likely to reach (or have reached) 10,000 infections far earlier than the reported data suggest, calling for the prioritization of resources to mitigate the further spread of the epidemic.

title: Estimating the infection and case fatality ratio for COVID-19 using age-adjusted data from the outbreak on the Diamond Princess cruise ship
abstract: Adjusting for delay from confirmation-to-death, we estimated case and infection fatality ratios (CFR, IFR) for COVID-19 on the Diamond Princess ship as 2.3% (0.75%-5.3%) and 1.2% (0.38-2.7%). Comparing deaths onboard with expected deaths based on naive CFR estimates using China data, we estimate IFR and CFR in China to be 0.5% (95% CI: 0.2-1.2%) and 1.1% (95% CI: 0.3-2.4%) respectively.

title: FOCIS abstract supplement

title: Estimation of COVID-19 burden in Egypt – Authors' reply

title: Geo temporal distribution of 1,688 Chinese healthcare workers infected with COVID-19 in severe conditions, a secondary data analysis
abstract: The COVID 19 outbreak is posing an unprecedented challenge to healthcare workers. This study analyzes the geo temporal effects on disease severity for the 1,688 Chinese healthcare workers infected with COVID 19.  Using the descriptive results recently reported by the Chinese CDC, we compare the percentage of infected healthcare workers in severe conditions over time and across three areas in China, and the fatality rate of infected healthcare workers with all the infected individuals in China aged 22 to 59 years.  Among the infected Chinese healthcare workers whose symptoms onset appeared during the same ten day period, the percentage of those in severe conditions decreased statistical significantly from 19.7% (Jan 11 to 20) to 14.4% (Jan 21 to 31) to 8.7% (Feb 1 to 11). Across the country, there was also a significant difference in the disease severity among patients symptoms onset during the same period, with Wuhan being the most severe (17%), followed by Hubei Province (10.4%), and the rest of China (7.0%). The case fatality rate for the 1,688 infected Chinese healthcare workers was significantly lower than that for the 29,798 infected patients aged 20 to 59 years 0.3% (5/1,688) vs. 0.65% (193/29,798), respectively.  The disease severity improved considerably over a short period of time in China. The more severe conditions in Wuhan compared to the rest of the country may be attributable to the draconian lockdown. The clinical outcomes of infected Chinese healthcare workers may represent a more accurate estimation of the severity of COVID 19 for those who have access to quality healthcare.

title: Exit strategies: optimising feasible surveillance for detection, elimination and ongoing prevention of COVID-19 community transmission
abstract: Following successful implementation of strong containment measures by the community, Australia is now close to the point of eliminating detectable community transmission of COVID-19. We aimed to develop an efficient, rapid and scalable surveillance strategy for detecting all remaining COVID-19 community transmission through exhaustive identification of every active transmission chain. We also identified measures to enable early detection and effective management of any reintroduction of transmission once containment measures are lifted to ensure strong containment measures do not need to be reinstated.  We compared efficiency and sensitivity to detect community transmission chains through testing of: hospital cases; primary care fever and cough patients; or asymptomatic community members, using surveillance evaluation methods and mathematical modelling, varying testing capacities and prevalence of COVID-19 and non-COVID-19 fever and cough, and the reproduction number. System requirements for increasing testing to allow exhaustive identification of all transmission chains, and then enable complete follow-up of all cases and contacts within each chain, were assessed per million population.  Assuming 20% of cases are asymptomatic and all symptomatic COVID-19 cases present to primary care, with high transmission (R=2.2) there are a median of 13 unrecognised community cases (5 infectious) when a transmission chain is identified through hospital surveillance versus 3 unrecognised cases (1 infectious) through primary care surveillance. 3 unrecognised community upstream community cases themselves are estimated to generate a further 22-33 contacts requiring follow-up. The unrecognised community cases rise to 5 if only 50% of symptomatic cases present to primary care. Screening for asymptomatic disease in the community cannot exhaustively identify all transmission under any of the scenarios assessed. The additional capacity required to screen all fever and cough primary care patients would be approximately 2,000 tests/million population per week using 1/16 pooling of samples.  Screening all syndromic fever and cough primary care presentations, in combination with exhaustive and meticulous case and contact identification and management, enables appropriate early detection and elimination of community transmission of COVID-19. If testing capacity is limited, interventions such as pooling allow increased case detection, even given reduced test sensitivity. Wider identification and testing of all upstream contacts, (i.e. potential sources of infection for identified cases, and their related transmission chains) is critical, and to be done exhaustively requires more resources than downstream contact tracing. The most important factor in determining the performance of such a surveillance system is community participation in screening and follow up, and as such, appropriate community engagement, messaging and support to encourage presentation and compliance is essential. We provide operational guidance on implementing such a system.

title: Test, test, test for COVID-19 antibodies: the importance of sensitivity, specificity and predictive powers
abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests of varying specificity and sensitivity are now available. For informing individuals whether they have had coronavirus disease 2019 (COVID-19), they need to be very accurate. For measuring population prevalence of past infection, the numbers of false positives and negatives need to be roughly equal. With a series of worked examples for a notional population of 100,000 people, we show that even test systems with a high specificity can yield a large number of false positive results, especially where the population prevalence is low. For example, at a true population prevalence of 5%, using a test with 99% sensitivity and specificity, 16% of positive results will be false and thus 950 people will be incorrectly informed they have had the infection. Further confirmatory testing may be needed. Giving false reassurance on which personal or societal decisions might be based could be harmful for individuals, undermine public confidence and foster further outbreaks.

title: Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study
abstract: The coronavirus disease (COVID-19) is the latest pandemic of the digital age. With the internet harvesting large amounts of data from the general population in real time, public databases such as Google Trends (GT) and the Baidu Index (BI) can be an expedient tool to assist public health efforts.  The aim of this study is to apply digital epidemiology to the current COVID-19 pandemic to determine the utility of providing adjunctive epidemiologic information on outbreaks of this disease and evaluate this methodology in the case of future pandemics.  An epidemiologic time series analysis of online search trends relating to the COVID-19 pandemic was performed from January 9, 2020, to April 6, 2020. BI was used to obtain online search data for China, while GT was used for worldwide data, the countries of Italy and Spain, and the US states of New York and Washington. These data were compared to real-world confirmed cases and deaths of COVID-19. Chronologic patterns were assessed in relation to disease patterns, significant events, and media reports.  Worldwide search terms for shortness of breath, anosmia, dysgeusia and ageusia, headache, chest pain, and sneezing had strong correlations (r>0.60, P<.001) to both new daily confirmed cases and deaths from COVID-19. GT COVID-19 (search term) and GT coronavirus (virus) searches predated real-world confirmed cases by 12 days (r=0.85, SD 0.10 and r=0.76, SD 0.09, respectively, P<.001). Searches for symptoms of diarrhea, fever, shortness of breath, cough, nasal obstruction, and rhinorrhea all had a negative lag greater than 1 week compared to new daily cases, while searches for anosmia and dysgeusia peaked worldwide and in China with positive lags of 5 days and 6 weeks, respectively, corresponding with widespread media coverage of these symptoms in COVID-19.  This study demonstrates the utility of digital epidemiology in providing helpful surveillance data of disease outbreaks like COVID-19. Although certain online search trends for this disease were influenced by media coverage, many search terms reflected clinical manifestations of the disease and showed strong correlations with real-world cases and deaths.

title: COVID-19 presenting as acute pancreatitis
abstract: The ongoing pandemic of Coronavirus disease-2019 (COVID-19) has spread over 200 countries worldwide, affecting >2 million people and >120,000 deaths. COVID-19 is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The most common symptoms include cough, shortness of breath, and fever. However, gastrointestinal manifestations of COVID-19 are increasingly being recognized. Herein, we report a case of COVID-19 who presented with acute pancreatitis (AP) without any other risk factors.

title: COVID-19 in India: Predictions, Reproduction Number and Public Health Preparedness
abstract: The COVID-19 has emerged as a global concern for public health due to large scale outbreak. The number of confirmed cases has also been increased in India in the past few weeks. The predictions for the COVID-19 can provide insights into the epidemiology of the disease, which helps policymakers to check health system capacities.  We obtained data on daily confirmed, recovered and death cases for a period of 21 days and have implemented the exponential growth model to predict future cases for all the three components. The mathematical model was used to calculate the average reproduction number and herd immunity. We estimated the number of active cases till the 30th of April. We have also tried to analyze the public health capacity to combat COVID-19 in India.  If the exponential growth in the number of cases continues then the total number of active cases will be 2,49,635 until the end of April. The reproduction number for COVID-19 in India was found to be 2.56 and herd immunity as 61%. The cumulative cases predicted by the mathematical model was 1,20,203.  This prediction provides an alarming situation for India in terms of public health preparedness. The number of tests is needed to increase to detect all the cases of COVID-19 in India. Though some serious preventive measures have been implemented, but India should be ready to face any sudden community outbreak.  COVID-19, India, predictions, reproduction number, public health capacity

title: Coronavirus disease 2019 during pregnancy: a systematic review of reported cases
abstract: This study aimed to conduct a systematic review of the clinical outcomes reported for pregnant patients with coronavirus disease 2019.  The PubMed, CINAHL, and Scopus databases were searched using a combination of key words such as "Coronavirus and/or pregnancy," "COVID and/or pregnancy," "COVID disease and/or pregnancy," and "COVID pneumonia and/or pregnancy." There was no restriction of language to allow collection of as many cases as possible.  All studies of pregnant women who received a coronavirus disease 2019 diagnosis using acid nucleic test, with reported data about pregnancy, and, in case of delivery, reported outcomes, were included.  All the studies included have been evaluated according to the tool for evaluating the methodological quality of case reports and case series described by Murad et al.  Six studies that involved 51 pregnant women were eligible for the systematic review. At the time of the report, 3 pregnancies were ongoing; of the remaining 48 pregnant women, 46 gave birth by cesarean delivery, and 2 gave birth vaginally; in this study, 1 stillbirth and 1 neonatal death were reported.  Although vertical transmission of severe acute respiratory syndrome coronavirus 2 infection has been excluded thus far and the outcome for mothers and neonates has been generally good, the high rate of preterm delivery by cesarean delivery is a reason for concern. Cesarean delivery was typically an elective surgical intervention, and it is reasonable to question whether cesarean delivery for pregnant patients with coronavirus disease 2019 was warranted. Coronavirus disease 2019 associated with respiratory insufficiency in late pregnancies certainly creates a complex clinical scenario.

title: Importance of untested infectious individuals for the suppression of COVID-19 epidemics
abstract: A mathematical model which accounts for tested and untested infectious individuals is calibrated during the early stages of COVID-19 outbreaks in Germany, the Hubei province, Italy, Spain and the UK. The predicted percentage of untested infected individuals depends on the specific outbreak but we found that they typically represent 50% to 80% of the infected individuals. Even when unreported cases are taken into account, we estimate that less than 8% of the population would have been exposed to SARS-CoV-2 by 09/04/2020 in the analysed outbreaks. These levels are far from the 70-85% needed to ensure herd immunity and we predict a resurgence of infection if ongoing lockdowns in the analysed outbreaks are fully lifted. We propose that partially lifted lockdowns together with fast and thorough testing allowing for quick isolation of both symptomatic and asymptomatic cases could lead to suppression of secondary waves of COVID-19 epidemics.

title: Forecasting ultra-early intensive care strain from COVID-19 in England
abstract: The COVID-19 pandemic has led to unprecedented strain on intensive care unit (ICU) admission in parts of the world. Strategies to create surge ICU capacity requires complex local and national service reconfiguration and reduction or cancellation of elective activity. Theses measures require time to implement and have an inevitable lag before additional capacity comes on-line. An accurate short-range forecast would be helpful in guiding such difficult, costly and ethically challenging decisions. At the time this work began, cases in England were starting to increase. Here we present an attempt at an agile short-range forecast based on published real-time COVID-19 case data from the seven National Health Service commissioning regions in England (East of England, London, Midlands, North East and Yorkshire, North West, South East and South West). We use a Monte Carlo approach to model the likely impact of current diagnoses on regional ICU capacity over a 14 day horizon. Our model is designed to be parsimonious and based on plausible epidemiological data from the literature available. On the basis of the modelling assumptions made, ICU occupancy is likely to increase dramatically in the the days following the time of modelling. If the current exponential growth continues, 5 out of 7 commissioning regions will have more critically ill COVID-19 patients than there are ICU beds within two weeks\todo{last thing to do}. Despite variable growth in absolute patients, all commissioning regions are forecast to be heavily burdened under the assumptions used. Whilst, like any forecast model, there remain uncertainties both in terms of model specification and robust epidemiological data in this early prospective phase, it would seem that surge capacity will be required in the very near future. We hope that our model will help policy decision makers with their preparations. The uncertainties in the data highlight the urgent need for ongoing real-time surveillance to allow forecasts to be constantly updated using high quality local patient-facing data as it emerges.

title: Complete Genome of Avian coronavirus Vaccine Strains Ma5 and BR-I
abstract: Avian coronavirus (AvCoV) is a ubiquitous multiple-serotype pathogen of poultry, and its control is mainly based on the use of vaccines. We report here the previously unknown full genomes of the Ma5 (27,652 nucleotides [nt]) and BR-I (27,618 nt) AvCoV vaccine strains of the GI-1 (Massachusetts) and GI-11 (Brazil) types.

title: Quantitative trace analysis of a broad range of antiviral drugs in poultry muscle using column-switch liquid chromatography coupled to tandem mass spectrometry
abstract: A liquid chromatography–tandem mass spectrometry method for the analysis of seven antiviral drugs, zanamivir, ribavirin, oseltamivir, oseltamivir carboxylate, amantadine, rimantadine and arbidol, in poultry muscle is reported. The antiviral drugs were extracted from the homogenized poultry muscle sample using methanol. The extract was purified using tandem solid-phase extraction combining a cation exchange cartridge and a phenylboronic acid cartridge. To prevent excessive matrix effects, the analytes were separated from the matrix constituents using a column-switch liquid chromatography system combining a reversed-phase and a Hypercarb analytical column. Detection was carried out using tandem mass spectrometry. The method was fully validated according to 2002/657/EC  and proved to be adequate for quantification and confirmation of zanamivir and ribavirin at 10 μg kg(−1), oseltamivir, oseltamivir carboxylate, amantadine and rimantadine at levels below 1.0 μg kg(−1) and for qualitative confirmatory analysis of arbidol at levels below 1 μg kg(−1).  The online version of this article (doi:10.1007/s00216-011-5581-3) contains supplementary material, which is available to authorized users.

title: Pernio-like skin lesions associated with COVID-19: a case series of 318 patients from 8 countries
abstract: Increasing evidence suggests pernio-like lesions are cutaneous manifestations of COVID-19.  To describe clinical and pathologic findings of pernio-like lesions in confirmed or suspected COVID-19 cases.  An international dermatology registry was circulated to healthcare providers worldwide through the American Academy of Dermatology (AAD), International League of Dermatologic Societies (ILDS), and other organizations.  We documented 505 patients with dermatologic manifestations associated with COVID-19, including 318 (63%) with pernio-like lesions. Patients with pernio-like lesions were generally young and healthy, with relatively mild COVID-19. Of 318 cases confirmed or suspected as COVID-19 by providers, twenty-three cases (7%) were laboratory-confirmed COVID-19 positive, and 20 others (6%) were close contacts of confirmed COVID-19 cases. Given current testing criteria, many patients lacked COVID-19 testing access. For 55% of patients, pernio-like lesions were their only symptom. In patients with other COVID-19 symptoms, pernio-like lesions typically appeared after other symptoms. Pernio-like lesions lasted a median of 14 days (IQR 10-21).  A case series cannot estimate population level incidence or prevalence. Additionally, there may be confirmation bias in reporting. We cannot exclude an epiphenomenon.  Pernio-like skin changes of the feet and hands, without another explanation, may suggest COVID-19 infection and should prompt confirmatory testing.

title: 2019 Novel Coronavirus Disease (COVID‐19) in patients with Inflammatory Bowel Diseases
abstract: Data on patients with inflammatory bowel diseases (IBD) who have had 2019 novel coronavirus (SARS‐CoV‐2) disease (COVID‐19) are lacking.  To report the clinical characteristics, including gastrointestinal symptoms, of COVID‐19 in IBD patients, and to assess the risk of COVID‐19 in IBD.  This case series included consecutive IBD patients with laboratory‐confirmed COVID‐19. Age‐adjusted cumulative incidences were compared with the general population in the Madrid region.  Through April 8, 12 patients of 1918 IBD patients were diagnosed of COVID‐19. The average age was 52 years, 75% of the patients were female, and 58.3% had Crohn’s disease. Seven patients (58%) were on maintenance treatment with immunomodulators/biologics, of these 4 with combined therapy (33%). Eight patients (66%) required hospitalization (1 intensive care unit admission, and 2 deaths), and 4 patients were isolated at home. Nine patients had diarrhoea ranging between 4‐10 loose stools per day (mean 5.4, SD 1.6). In 5 patients (42%) diarrhoea was a presenting symptom. In 2 patients, diarrhoea was the only symptom at debut. Cumulative incidence of COVID‐19 was 6.1 per 1000 IBD patients. IBD patients had a lower adjusted incidence ratio of COVID‐19 (OR 0.74, 95% CI 0.70‐0.77; p<0.001), and a similar associated mortality ratio (OR 0.95, 95% CI: 0.84‐1.06; p=0.36), compared with the general population.  IBD patients do not have an increased risk of COVID‐19 and associated mortality compared with the general population. In many IBD patients diarrhoea was a presenting symptom, and sometimes, was the only symptom at onset of COVID‐19.

title: An evidence-based framework for priority clinical research questions for COVID-19
abstract: On 31 December, 2019, the World Health Organization China Country Office was informed of cases of pneumonia of unknown aetiology. Since then, there have been over 75 000 cases globally of the 2019 novel coronavirus (COVID-19), 2000 deaths, and over 14 000 cases recovered. Outbreaks of novel agents represent opportunities for clinical research to inform real-time public health action. In 2018, we conducted a systematic review to identify priority research questions for Severe Acute Respiratory Syndrome-related coronavirus (SARS-CoV) and Middle East Respiratory Syndrome-related coronavirus (MERS-CoV). Here, we review information available on COVID-19 and provide an evidenced-based framework for priority clinical research in the current outbreak.  Three bibliographic databases were searched to identify clinical studies published on SARS-CoV and MERS-CoV in the outbreak setting. Studies were grouped thematically according to clinical research questions addressed. In February 2020, available information on COVID19 was reviewed and compared to the results of the SARS-CoV and MERS-CoV systematic review.  From the research objectives for SARS-CoV and MERS-CoV, ten themes in the literature were identified: Clinical characterisation, prognosis, diagnosis, clinical management, viral pathogenesis, epidemiological characterisation, infection prevention and control/transmission, susceptibility, psychosocial, and aetiology. For COVID19, some information on clinical presentation, diagnostic testing, and aetiology is available but many clinical research gaps have yet to be filled.  Based on a systematic review of other severe coronaviruses, we summarise the state of clinical research for COVID-19, highlight the research gaps, and provide recommendations for the implementation of standardised protocols. Data based on internationally standardised protocols will inform clinical practice real-time.

title: Understanding Unreported Cases in the COVID-19 Epidemic Outbreak in Wuhan, China, and the Importance of Major Public Health Interventions
abstract: We develop a mathematical model to provide epidemic predictions for the COVID-19 epidemic in Wuhan, China. We use reported case data up to 31 January 2020 from the Chinese Center for Disease Control and Prevention and the Wuhan Municipal Health Commission to parameterize the model. From the parameterized model, we identify the number of unreported cases. We then use the model to project the epidemic forward with varying levels of public health interventions. The model predictions emphasize the importance of major public health interventions in controlling COVID-19 epidemics.

title: A model for COVID-19 transmission in Connecticut
abstract: To support public health policymakers in Connecticut as they begin phased lifting of social distancing restrictions, we developed a county-structured compartmental SEIR-type model of SARS-CoV-2 transmission and COVID-19 disease progression. We calibrated this model to the local dynamics of deaths and hospitalizations and the exact timing of state interventions, including school closures and stay-at-home order. In this technical report, we describe the details of the model design, implementation and calibration, and show projections of epidemic development through the Summer of 2020 under different assumptions about the increase in contact rates following partial state reopening. Our model results are consistent with high effectiveness of state lockdown measures, but changes in human interaction patterns during the coming months are unknown. In addition, a lot of uncertainty remains with respect to several key epidemiological parameters and the effectiveness of increased testing and contact tracing capacity. As more information becomes available, we will update the projections presented in this report.

title: COVID-19: Are Africa’s diagnostic challenges blunting response effectiveness?
abstract: Since its emergence in Wuhan, China in December 2019, novel Coronavirus disease - 2019 (COVID-19) has rapidly spread worldwide, achieving pandemic status on 11 (th) March, 2020. As of 1 (st) April 2020, COVID-19, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), had infected over 800,000 people and caused over 40,000 deaths in 205 countries and territories. COVID-19 has had its heaviest toll on Europe, United States and China. As of 1 (st) of April 2020, the number of confirmed COVID-19 cases in Africa was relatively low, with the highest number registered by South Africa, which had reported 1,380 confirmed cases. On the same date (also the date of this review), Africa had reported 5,999 confirmed cases, of which 3,838 (almost 65%) occurred in South Africa, Algeria, Egypt, Morocco and Tunisia, with the remaining 2,071 cases distributed unevenly across the other African countries. We speculate that while African nations are currently experiencing much lower rates of COVID-19 relative to other continents, their significantly lower testing rates may grossly underestimate incidence rates. Failure to grasp the true picture may mean crucial windows of opportunity shut unutilized, while limited resources are not deployed to maximum effect. In the absence of extensive testing data, an overestimation of spread may lead to disproportionate measures being taken, causing avoidable strain on livelihoods and economies. Here, based on the African situation, we discuss COVID-19 diagnostic challenges and how they may blunt responses.

title: A Randomized Trial of Hydroxychloroquine as Postexposure Prophylaxis for Covid-19
abstract: Coronavirus disease 2019 (Covid-19) occurs after exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For persons who are exposed, the standard of care is observation and quarantine. Whether hydroxychloroquine can prevent symptomatic infection after SARS-CoV-2 exposure is unknown.  We conducted a randomized, double-blind, placebo-controlled trial across the United States and parts of Canada testing hydroxychloroquine as postexposure prophylaxis. We enrolled adults who had household or occupational exposure to someone with confirmed Covid-19 at a distance of less than 6 ft for more than 10 minutes while wearing neither a face mask nor an eye shield (high-risk exposure) or while wearing a face mask but no eye shield (moderate-risk exposure). Within 4 days after exposure, we randomly assigned participants to receive either placebo or hydroxychloroquine (800 mg once, followed by 600 mg in 6 to 8 hours, then 600 mg daily for 4 additional days). The primary outcome was the incidence of either laboratory-confirmed Covid-19 or illness compatible with Covid-19 within 14 days.  We enrolled 821 asymptomatic participants. Overall, 87.6% of the participants (719 of 821) reported a high-risk exposure to a confirmed Covid-19 contact. The incidence of new illness compatible with Covid-19 did not differ significantly between participants receiving hydroxychloroquine (49 of 414 [11.8%]) and those receiving placebo (58 of 407 [14.3%]); the absolute difference was -2.4 percentage points (95% confidence interval, -7.0 to 2.2; P = 0.35). Side effects were more common with hydroxychloroquine than with placebo (40.1% vs. 16.8%), but no serious adverse reactions were reported.  After high-risk or moderate-risk exposure to Covid-19, hydroxychloroquine did not prevent illness compatible with Covid-19 or confirmed infection when used as postexposure prophylaxis within 4 days after exposure.

title: Daily Situation Report on Coronavirus disease (COVID-19) in Iran; March 15, 2020
abstract: After detection of the first confirmed cases of COVID-19 in Iran, the National Committee on COVID-19 Epidemiology in Ministry of Health and Medical Education was established. This Committee is official source of gathering, analyzing, and reporting the COVID-19 data in Iran. The data of all sources in the country including, medical care monitoring center (MCMC), Hospitals’ Information Systems (HIS), Laboratory portal, the data of the center for communicable disease control (MOH), as well as the data from community health centers are integrated and used in this regards. This factsheet contain daily situation report on coronavirus disease (covid-19) in Iran; March 15, 2020.

title: Assessment of Specimen Pooling to Conserve SARS CoV-2 Testing Resources
abstract: To establish the optimal parameters for group testing of pooled specimens for the detection of SARS-CoV-2.  The most efficient pool size was determined to be 5 specimens using a web-based application. From this analysis, 25 experimental pools were created using 50 microliter from one SARS-CoV-2 positive nasopharyngeal specimen mixed with 4 negative patient specimens (50 microliter each) for a total volume of 250 microliter l. Viral RNA was subsequently extracted from each pool and tested using the CDC SARS-CoV-2 RT-PCR assay. Positive pools were consequently split into individual specimens and tested by extraction and PCR. This method was also tested on an unselected group of 60 nasopharyngeal specimens grouped into 12-pools.  All 25 pools were positive with Cycle threshold (Ct) values within 0 and 5.03 Ct of the original individual specimens. The analysis of 60 specimens determined that two pools were positive followed by identification of two individual specimens among the 60 tested. This testing was accomplished while using 22 extractions/PCR tests, a savings of 38 reactions.  When the incidence rate of SARS-CoV-2 infection is 10% or less, group testing will result in the saving of reagents and personnel time with an overall increase in testing capability of at least 69%.

title: Assessment of Lockdown Effect in Some States and Overall India: A Predictive Mathematical Study on COVID-19 Outbreak
abstract: In the absence of neither an effective treatment or vaccine and with an incomplete understanding of the epidemiological cycle, Govt. has implemented a nationwide lockdown to reduce COVID-19 transmission in India. To study the effect of social distancing measure, we considered a new mathematical model on COVID-19 that incorporates lockdown effect. By validating our model to the data on notified cases from five different states and overall India, we estimated several epidemiologically important parameters as well as the basic reproduction number ($R_{0}$). Combining the mechanistic mathematical model with different statistical forecast models, we projected notified cases in the six locations for the period May 17, 2020, till May 31, 2020. A global sensitivity analysis is carried out to determine the correlation of two epidemiologically measurable parameters on the lockdown effect and also on $R_{0}$. Our result suggests that lockdown will be effective in those locations where a higher percentage of symptomatic infection exists in the population. Furthermore, a large scale COVID-19 mass testing is required to reduce community infection. Ensemble model forecast suggested a high rise in the COVID-19 notified cases in most of the locations in the coming days. Furthermore, the trend of the effective reproduction number ($R_{t}$) during the projection period indicates if the lockdown measures are completely removed after May 17, 2020, a high spike in notified cases may be seen in those locations. Finally, combining our results, we provided an effective lockdown policy to reduce future COVID-19 transmission in India.

title: Low serum 25-hydroxyvitamin D levels are associated with increased risk of viral coinfections in wheezing children

title: Incidence of COVID-19 and Connections with Air Pollution Exposure: Evidence from the Netherlands
abstract: The fast spread of severe acute respiratory syndrome coronavirus 2 has resulted in the emergence of several hot-spots around the world. Several of these are located in areas associated with high levels of air pollution. This study investigates the relationship between exposure to particulate matter and COVID-19 incidence in 355 municipalities in the Netherlands. The results show that atmospheric particulate matter with diameter less than 2.5 is a highly significant predictor of the number of confirmed COVID-19 cases and related hospital admissions. The estimates suggest that expected COVID-19 cases increase by nearly 100 percent when pollution concentrations increase by 20 percent. The association between air pollution and case incidence is robust in the presence of data on health-related preconditions, proxies for symptom severity, and demographic control variables. The results are obtained with ground-measurements and satellite-derived measures of atmospheric particulate matter as well as COVID-19 data from alternative dates. The findings call for further investigation into the association between air pollution and SARS-CoV-2 infection risk. If particulate matter plays a significant role in COVID-19 incidence, it has strong implications for the mitigation strategies required to prevent spreading.

title: Lack of coordination and medical disinformation in Canadian self-assessment tools for COVID-19
abstract: As SARS-CoV-2 threatens to overwhelm health systems in Canada, it is imperative that provinces are able to plan and manage an effective and reduced risk response. For this response to be most effective, it must reflect an evidence-based, pan-Canadian response. We designed four different prototypical patients with a combination of common COVID-19 symptoms and opportunities for exposure who were made to self-assess using the 10 provincial COVID-19 self-assessment tools on 1 April. These tools were developed to allow individuals to self-triage, allowing health systems direct capacity to testing and care. We assessed the consistency of the self-assessment tools and of the guidance provided to the patients. While the tools generally screen in three areas, the scope of included COVID-19 associated symptoms as well as the opportunities for exposure, and therefore transmission, vary between provinces such that no two provinces screened in the same way. This was, in turn, reflected in the inconsistency in guidance found. A patient with cough who had travelled abroad or had close contact with a confirmed case within 14 days received the most consistent guidance, with remaining patients receiving guidance ranging from mandatory quarantine or self-isolation to being told they did not have COVID-19 symptoms, guidance at odds with medical evidence. Thus, there is not a single, evidence-based Canadian standard of care simply for self-assessment. Without consistency in public health guidance, Canadians cannot appropriately self-isolate to mitigate community transmission, nor can the necessary valid and reliable data be collected to inform critical epidemiological models that help guide pandemic response. If federal and provincial governments are unable to coordinate a response, Parliament must use its available jurisdiction to legislate a duty on both to follow national standards, so as to improve coordination on COVID-19 in coming months.

title: Characterizing the Impact of COVID-19 on Men Who Have Sex with Men Across the United States in April, 2020
abstract: The COVID-19 pandemic is reinforcing health inequities among vulnerable populations, including men who have sex with men (MSM). We conducted a rapid online survey (April 2 to April 13, 2020) of COVID-19 related impacts on the sexual health of 1051 US MSM. Many participants had adverse impacts to general wellbeing, social interactions, money, food, drug use and alcohol consumption. Half had fewer sex partners and most had no change in condom access or use. Some reported challenges in accessing HIV testing, prevention and treatment services. Compared to older MSM, those 15–24 years were more likely to report economic and service impacts. While additional studies of COVID-19 epidemiology among MSM are needed, there is already evidence of emerging interruptions to HIV-related services. Scalable remote solutions such as telehealth and mailed testing and prevention supplies may be urgently needed to avert increased HIV incidence among MSM during the COVID-19 pandemic era.  The online version of this article (10.1007/s10461-020-02894-2) contains supplementary material, which is available to authorized users.

title: On the evolutionary epidemiology of SARS-CoV-2
abstract: There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how selection might be acting upon the virus during the COVID-19 pandemic. While there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued, evidence-based, analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.

title: An Overview of Severe Acute Respiratory Syndrome–Coronavirus (SARS-CoV) 3CL Protease Inhibitors: Peptidomimetics and Small Molecule Chemotherapy
abstract: see text] Severe acute respiratory syndrome (SARS) is caused by a newly emerged coronavirus that infected more than 8000 individuals and resulted in more than 800 (10–15%) fatalities in 2003. The causative agent of SARS has been identified as a novel human coronavirus (SARS-CoV), and its viral protease, SARS-CoV 3CL(pro), has been shown to be essential for replication and has hence been recognized as a potent drug target for SARS infection. Currently, there is no effective treatment for this epidemic despite the intensive research that has been undertaken since 2003 (over 3500 publications). This perspective focuses on the status of various efficacious anti-SARS-CoV 3CL(pro) chemotherapies discovered during the last 12 years (2003–2015) from all sources, including laboratory synthetic methods, natural products, and virtual screening. We describe here mainly peptidomimetic and small molecule inhibitors of SARS-CoV 3CL(pro). Attempts have been made to provide a complete description of the structural features and binding modes of these inhibitors under many conditions.

title: 89 Severe Acute Respiratory Syndrome (SARS)
abstract: Severe acute respiratory syndrome (SARS) first appeared in November 2002 and ultimately resulted in 8096 probable human infections and 774 deaths worldwide. By July 2003, the global outbreak was declared over. A new coronavirus, SARS-associated coronavirus (SARS-CoV), was identified as the causative agent; this virus appeared to have a zoonotic origin, as genetically similar coronaviruses have been identified in several animal species. The global response to the outbreak was extensive. Within a short period, the pathogen had been identified, new diagnostic tests were developed, surveillance systems were created, infection control and prevention measures were instituted, and transmission among humans stopped. It is unclear if and when person-to-person SARS-CoV transmission will reappear. However, procedures have been established by public health organizations, including the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC), to help guide diagnosis, reporting, surveillance, and prevention.

title: One-step RNA extraction for RT-qPCR detection of 2019-nCoV
abstract: The global outbreak of coronavirus disease 2019 (COVID-19) has placed an unprecedented burden on healthcare systems as the virus spread from the initial 27 reported cases in the city of Wuhan, China to a global pandemic in under three months1. Resources essential to monitoring virus transmission have been challenged with a demand for expanded surveillance. The CDC 2019-nCoV Real-Time Diagnostic Panel uses a real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) consisting of two TaqMan probe and primer sets specific for the 2019-nCoV N gene, which codes for the nucleocapsid structural protein that encapsulates viral RNA, for the qualitative detection of 2019-nCoV viral RNA in respiratory samples. To isolate RNA from respiratory samples, the CDC lists RNA extraction kits from three manufacturers. In anticipation of a limited supply chain of RNA extraction kits and the need for test scalability, we sought to identify alternative RNA extraction methods. Here we show that direct lysis of respiratory samples can be used in place of RNA extraction kits to run the CDC 2019-nCoV Real-Time Diagnostic assay with the additional benefits of higher throughput, lower cost, faster turnaround and possibly higher senitivity and improved saftey.

title: Incorporating and Addressing Testing Bias Within Estimates of Epidemic Dynamics for SARS-CoV-2
abstract: The disease burden of SARS-CoV-2 as measured by tests from various countries present varying estimates of infection and fatality rates. Models based on these acquired data may suffer from systematic errors and large estimation variances due to the biases associated with testing and lags between the infection and death counts. Here, we present an augmented compartment model to predict epidemic dynamics while explicitly modeling for the sampling bias involved in testing. Our simulations show that sampling biases in favor of patients with higher disease manifestation could significantly affect direct estimates of infection and fatality rates calculated from the numbers of confirmed cases and deaths, and serological testing can partially mitigate these biased estimates. We further recommend a strategy to obtain unbiased estimates, calculating the dependence of expected confidence on a randomized sample size, showing that relatively small sample sizes can provide statistically significant estimates for SARS-CoV-2 related death rates.

title: Laboratory diagnosis of emerging human coronavirus infections – the state of the art
abstract: The three unprecedented outbreaks of emerging human coronavirus (HCoV) infections at the beginning of the twenty-first century have highlighted the necessity for readily available, accurate and fast diagnostic testing methods. The laboratory diagnostic methods for human coronavirus infections have evolved substantially, with the development of novel assays as well as the availability of updated tests for emerging ones. Newer laboratory methods are fast, highly sensitive and specific, and are gradually replacing the conventional gold standards. This presentation reviews the current laboratory methods available for testing coronaviruses by focusing on the coronavirus disease 2019 (COVID-19) outbreak going on in Wuhan. Viral pneumonias typically do not result in the production of purulent sputum. Thus, a nasopharyngeal swab is usually the collection method used to obtain a specimen for testing. Nasopharyngeal specimens may miss some infections; a deeper specimen may need to be obtained by bronchoscopy. Alternatively, repeated testing can be used because over time, the likelihood of the SARS-CoV-2 being present in the nasopharynx increases. Several integrated, random-access, point-of-care molecular devices are currently under development for fast and accurate diagnosis of SARS-CoV-2 infections. These assays are simple, fast and safe and can be used in the local hospitals and clinics bearing the burden of identifying and treating patients.

title: A case report of neonatal COVID-19 infection in China ;Clinical Infectious Diseases ;Oxford Academic
abstract: In December 2019, the 2019 novel coronavirus disease (COVID-19) caused by SARS-CoV-2 emerged in China and now has spread in many countries Pregnant women are susceptible population of COVID-19 which are more likely to have complications and even progresse to severe illness We report a case of neonatal COVID-19 infection in China with pharyngeal swabs tested positive by rRT-PCR assay 36 hours after birth However, whether the case is a vertical transmission from mother to child remains to be confirmed

title: Mechanistic Models of Infectious Disease and Their Impact on Public Health
abstract: From the 1930s through the 1940s, Lowell Reed and Wade Hampton Frost used mathematical models and mechanical epidemic simulators as research tools and to teach epidemic theory to students at the Johns Hopkins Bloomberg School of Public Health (then the School of Hygiene and Public Health). Since that time, modeling has become an integral part of epidemiology and public health. Models have been used for explanatory and inferential purposes, as well as in planning and implementing public health responses. In this article, we review a selection of developments in the history of modeling of infectious disease dynamics over the past 100 years. We also identify trends in model development and use and speculate as to the future use of models in infectious disease dynamics.

title: Clinical meanings of rapid serological assay in patients tested for SARS-Co2 RT-PCR
abstract: PCR test for identifiction of viral nucleic acid is the current standard diagnostic method for the diagnosis of COVID-19 disease but technical reasons limit the utilization of this assay on large scale screenings.  We verified in a consecutive series of 191 symptomatic patients the clinical information that new rapid serological colorimetric test qualitatively analyzing IgM/IgG expression can provide with respect to standard assay and with respect to clinical outcome of patients.  Rapid serological test showed a sensitivity of 30% and a specificity of 89% with respect to the standard assay but, interestingly, these performances improve after 8 days of symptoms appearance. After 10 days of symptoms the predictive value of rapid serological test is higher than that of standard assay. When the behaviour of the two immunoglobulins was evaluated with respect to time length of symptoms appearance, no significant difference in immunoglobulins behaviour was shown.  The rapid serological test analyzed in the present study is candidate to provide information on immunoreaction of the subject to COVID-19 exposure.

title: Epidemiological and genetic analysis of severe acute respiratory syndrome
abstract: The severe acute respiratory syndrome (SARS) epidemics in 2002–2003 showed how quickly a novel infectious disease can spread both within communities and internationally. We have reviewed the epidemiological and genetic analyses that have been published both during and since these epidemics, and show how quickly data were collected and analyses undertaken. Key factors that determine the speed and scale of transmission of an infectious disease were estimated using statistical and mathematical modelling approaches, and phylogenetic analyses provided insights into the origin and evolution of the SARS-associated coronavirus. The SARS literature continues to grow, and it is hoped that international collaboration in the analysis of epidemiological and contact-network databases will provide further insights into the spread of this newly emergent infectious disease.

title: Scoping review of prevalence of neurologic comorbidities in patients hospitalized for COVID-19.
abstract: The emergence of coronavirus disease 2019 (COVID-19) presents a challenge for neurologists caring for patients with preexisting neurologic conditions hospitalized for COVID-19 or for evaluation of patients who suffer neurologic complications during COVID-19 infection. We conducted a scoping review of available literature on COVID-19 to assess the potential impact on neurologists in terms of prevalent comorbidities and incidence of new neurologic events in patients hospitalized with COVID-19.  We searched Medline/PubMed, CINAHL (EBSCO), and SCOPUS databases for adult patients with preexisting neurologic disease that were diagnosed and hospitalized for COVID-19, or reported incidence of secondary neurologic events following diagnosis of COVID-19. Pooled descriptive statistics of clinical data and comorbidities were examined.  Among screened articles, 322 of 4,014 (8.0%) of hospitalized patients diagnosed and treated for COVID-19 had a preexisting neurologic illness. Four retrospective studies demonstrated an increased risk of secondary neurologic complications in hospitalized patients with COVID-19 (incidence of 6%, 20% and 36.4%, respectively). Inconsistent reporting and limited statistical analysis among these studies did not allow for assessment of comparative outcomes.  Emerging literature suggests a daunting clinical relationship between COVID-19 and neurologic illness. Neurologists need to be prepared to reorganize their consultative practices to serve the neurologic needs of patients during this pandemic.

title: Cumulative Subject Index for 2009

title: Estimates of the severity of coronavirus disease 2019: a model-based analysis
abstract: In the face of rapidly changing data, a range of case fatality ratio estimates for coronavirus disease 2019 (COVID-19) have been produced that differ substantially in magnitude. We aimed to provide robust estimates, accounting for censoring and ascertainment biases.  We collected individual-case data for patients who died from COVID-19 in Hubei, mainland China (reported by national and provincial health commissions to Feb 8, 2020), and for cases outside of mainland China (from government or ministry of health websites and media reports for 37 countries, as well as Hong Kong and Macau, until Feb 25, 2020). These individual-case data were used to estimate the time between onset of symptoms and outcome (death or discharge from hospital). We next obtained age-stratified estimates of the case fatality ratio by relating the aggregate distribution of cases to the observed cumulative deaths in China, assuming a constant attack rate by age and adjusting for demography and age-based and location-based under-ascertainment. We also estimated the case fatality ratio from individual line-list data on 1334 cases identified outside of mainland China. Using data on the prevalence of PCR-confirmed cases in international residents repatriated from China, we obtained age-stratified estimates of the infection fatality ratio. Furthermore, data on age-stratified severity in a subset of 3665 cases from China were used to estimate the proportion of infected individuals who are likely to require hospitalisation.  Using data on 24 deaths that occurred in mainland China and 165 recoveries outside of China, we estimated the mean duration from onset of symptoms to death to be 17·8 days (95% credible interval [CrI] 16·9–19·2) and to hospital discharge to be 24·7 days (22·9–28·1). In all laboratory confirmed and clinically diagnosed cases from mainland China (n=70 117), we estimated a crude case fatality ratio (adjusted for censoring) of 3·67% (95% CrI 3·56–3·80). However, after further adjusting for demography and under-ascertainment, we obtained a best estimate of the case fatality ratio in China of 1·38% (1·23–1·53), with substantially higher ratios in older age groups (0·32% [0·27–0·38] in those aged <60 years vs 6·4% [5·7–7·2] in those aged ≥60 years), up to 13·4% (11·2–15·9) in those aged 80 years or older. Estimates of case fatality ratio from international cases stratified by age were consistent with those from China (parametric estimate 1·4% [0·4–3·5] in those aged <60 years [n=360] and 4·5% [1·8–11·1] in those aged ≥60 years [n=151]). Our estimated overall infection fatality ratio for China was 0·66% (0·39–1·33), with an increasing profile with age. Similarly, estimates of the proportion of infected individuals likely to be hospitalised increased with age up to a maximum of 18·4% (11·0–7·6) in those aged 80 years or older.  These early estimates give an indication of the fatality ratio across the spectrum of COVID-19 disease and show a strong age gradient in risk of death.

title: Umifenovir treatment is not associated with improved outcomes in patients with coronavirus disease 2019: A retrospective study
abstract: Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Umifenovir (Arbidol®) is an antiviral drug being used to treat influenza in Russia and China. This study aimed to investigate the effectiveness and safety of umifenovir for COVID-19.  A retrospective study was performed in non-ICU Ward in Jinyintan Hospital from February 2, 2020 to March 20, 2020. COVID-19 was confirmed by real-time reverse-transcriptase polymerase-chain-reaction (RT-PCR) assay for pharyngeal swab specimens. The confirmed patients were divided into umifenovir group and control group according to the use of umifenovir. The main outcomes were the negative rate of pharyngeal swab’s test for SARS-CoV-2 within 1 week after admission, as well as the duration for virus turning negative. The negativity time of SARS-CoV-2 was defined as the first day of a negative test if the nucleid acid of SARS-CoV-2 was negative for 2 consecutive tests.  A total of 81 COVID-19 patients were included, with 45 in umifenovir group and 36 in control group. Baseline clinical, laboratory characteristics were comparable between two groups. 33/45 (73.3%) patients in umifenovir group were tested negative in SARS-CoV-2 within 7 days after admission, the number was 28/36 (77.8%) in control group (p=0.19). The median time from onset of symtoms to SARS-CoV-2 turning negative were 18 days (interquartile range [IQR] 12-21) in umifenovir group and 16 days (IQR, 11-21) in control group (p= 0.42). Patients in umifenovir group had longer hospital stay than patients in control group (13 days [IQR, 9-17] vs 11 days [IQR, 9-14], p=0.04). No deaths or severe adverse reaction were found in both groups.  Umifenovir might not improve the prognosis or accelerate the SARS-CoV-2 clearance in non-ICU patients. A randomized control clinical trial is needed to assess the efficacy of umifenovir.

title: Respiratory Infections in the U.S. Military: Recent Experience and Control.
abstract: This comprehensive review outlines the impact of military-relevant respiratory infections, with special attention to recruit training environments, influenza pandemics in 1918 to 1919 and 2009 to 2010, and peacetime operations and conflicts in the past 25 years. Outbreaks and epidemiologic investigations of viral and bacterial infections among high-risk groups are presented, including (i) experience by recruits at training centers, (ii) impact on advanced trainees in special settings, (iii) morbidity sustained by shipboard personnel at sea, and (iv) experience of deployed personnel. Utilizing a pathogen-by-pathogen approach, we examine (i) epidemiology, (ii) impact in terms of morbidity and operational readiness, (iii) clinical presentation and outbreak potential, (iv) diagnostic modalities, (v) treatment approaches, and (vi) vaccine and other control measures. We also outline military-specific initiatives in (i) surveillance, (ii) vaccine development and policy, (iii) novel influenza and coronavirus diagnostic test development and surveillance methods, (iv) influenza virus transmission and severity prediction modeling efforts, and (v) evaluation and implementation of nonvaccine, nonpharmacologic interventions.

title: COVID-19 polymerase chain reaction testing before endoscopy: an economic analysis
abstract: The COVID-19 pandemic has limited endoscopy utilization, causing significant health and economic losses. We aim to model the impact of PCR testing into resuming endoscopy practice.  We performed a retrospective review of endoscopy utilization during the COVID-19 pandemic for a baseline reference. A computer model compared 3 approaches―Strategy 1: endoscopy for urgent indications only; Strategy 2: testing for semi-urgent indications; and Strategy 3: testing all patients. Analysis was made under current COVID-19 prevalence, and projected prevalence of 5% and 10%. Primary outcomes were number of procedures performed/cancelled. Secondary outcomes were direct costs, reimbursement, personal protective equipment used and personnel infected. Disease prevalence, testing accuracy, and costs were obtained from literature.  During the COVID-19 pandemic, endoscopy volume was 12.7% of expected. Strategy 2 and 3 were safe and effective interventions to resume endoscopy in semi-urgent and elective cases. Investing 22USD and 105USD in testing per patient allowed completing 19.4% and 95.3% of baseline endoscopies respectively. False negative results were seen after testing 4,700 patients (or 3 months applying Strategy 2 in our practice). Implementing PCR testing over 1 week in United States would require 13 and 64 million USD, with a return of 165 and 767 million USD to providers, leaving 65 and 325 health care workers infected.  PCR testing is an effective strategy to restart endoscopic practice in United States. PCR screening should be implemented during the second phase of the pandemic, once the healthcare system is able to test and isolate all suspected COVID-19 cases.

title: Clinical Testing For Covid-19
abstract: As the novel coronavirus SARS-CoV-2 caused COVID-19 cases in the United States the initial test was developed and performed at the Center for Disease Control (CDC). As the number of cases increased the demand for tests multiplied, leading the CDC to utilize the Emergency Utilization Authorization to allow clinical and commercial laboratories to develop tests to detect the presence of the virus. Many nucleic acid tests based on reverse transcriptase-polymerase chain reaction (RT-PCR) were developed, each with different techniques, specifications and turnaround time. As the illnesses turned into a pandemic, testing became more crucial. The test supply became inadequate to meet the need that it had to be prioritized according to guidance. For surveillance, the need for serologic tests emerged. Here we review the timeline of test development, the turn-around times, the various approved tests and compare them as regards the genes they detect. We concentrate on the point-of-care tests and discuss the basis for new serologic tests. We discuss the testing guidance for prioritization and their application in a hospital setting. As SARS-CoV-2 virus arrived in the USA causing the COVID-19 illness, one of the most talked about issues in the management of the disease and the resulting pandemic has been clinical testing. A unique situation arose of a communicable and highly contagious disease necessitating the rapid diagnosis of patients and the identification of non-symptomatic infected persons. Unfortunately, the USA did not have a Food and Drug Administration (FDA) approved laboratory test for the illness. The FDA ultimately utilized its Emergency Use Authorizations (EUA) on February 4, 2020 to allow for more rapid and widespread development and implementation of in-vitro  Indeed, companies and organizations utilized the EUA to file applications for new tests based on different methodologies, amounting to 48 applications in the span of 3 months from the beginning of February to the end of April 2020. In addition, multiple other tests were put in place under a separate authorization by a Presidential memorandum in early March allowing laboratories that carry Clinical Laboratory Improvement Amendment (CLIA) certification to put tests in place without an EUA from the FDA. This created an unprecedented situation where the medical community and the public may not be familiar with the various new tests for COVID-19 that are offered to patients and hospitals. The purpose of this review is to provide information, up-to-date as of the date of submission of the manuscript to the journal, on the various tests that have been developed, their scientific basis and their interpretation. We give a real-world example demonstrating the time lag in the return of test results and review testing prioritization guidance since the supply of tests remains below the perceived need.

title: Linking Statistics With Testing Policy to Manage COVID-19 in the Community
abstract: To determine the public health surveillance severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing volume needed, both for acute infection and seroprevalence.  Required testing volumes were developed using standard statistical methods based on test analytical performance, disease prevalence, desired precision, and population size.  Widespread testing for individual health management cannot address surveillance needs. The number of people who must be sampled for public health surveillance and decision making, although not trivial, is potentially in the thousands for any given population or subpopulation, not millions.  While the contributions of diagnostic testing for SARS-CoV-2 have received considerable attention, concerns abound regarding the availability of sufficient testing capacity to meet demand. Different testing goals require different numbers of tests and different testing strategies; testing strategies for national or local disease surveillance, including monitoring of prevalence, receive less attention. Our clinical laboratory and diagnostic infrastructure are capable of incorporating required volumes for many local, regional, and national public health surveillance studies into their current and projected testing capacity. However, testing for surveillance requires careful design and randomization to provide meaningful insights.

title: World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19)
abstract: An unprecedented outbreak of pneumonia of unknown aetiology in Wuhan City, Hubei province in China emerged in December 2019. A novel coronavirus was identified as the causative agent and was subsequently termed COVID-19 by the World Health Organization (WHO). Considered a relative of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), COVID-19 is caused by a betacoronavirus named SARS-CoV-2 that affects the lower respiratory tract and manifests as pneumonia in humans. Despite rigorous global containment and quarantine efforts, the incidence of COVID-19 continues to rise, with 90,870 laboratory-confirmed cases and over 3,000 deaths worldwide. In response to this global outbreak, we summarise the current state of knowledge surrounding COVID-19.

title: Preventing respiratory illness in older adults aged 60 years and above living in long-term care: A rapid overview of reviews
abstract: The overall objective of this rapid overview of reviews (overview hereafter) was to identify evidence from systematic reviews (SRs) for infection control and prevention practices for adults aged 60 years and older in long-term care settings.  Comprehensive searches in MEDLINE, EMBASE, the Cochrane Library, biorxiv.org/medrxiv.org, clinicaltrials.gov and the Global Infectious Disease Epidemiology Network (GIDEON) were carried out in early March 2020. Title/abstract and full-text screening, data abstraction, and quality appraisal (AMSTAR 2) were carried out by single reviewers.  A total of 6 SRs published between 1999 and 2018 were identified and included in the overview. The SRs included between 1 and 37 primary studies representing between 140 to 908 patients. All of the primary studies included in the SRs were carried out in long-term care facilities (LTCF) and examined pharmacological, non-pharmacological, or combined interventions. One high quality SR found mixed results for the effectiveness of hand hygiene to prevent infection (2 studies statistically significant positive results, 1 study non-statistically significant results). One moderate quality SR with meta-analysis found a moderate non-statistically significant effect for personal protective equipment (PPE) in preventing infection and found no statistically significant results for the effectiveness of social isolation. One moderate quality SR reported statically significant evidence for the effectiveness of amantadine and amantadine + PPE to prevent infection with respiratory illness in LTCF.  The current evidence suggests that with antiviral chemoprophylaxis with adamantine is effective in managing respiratory illness in residents of long-term care facilities. The rest of the strategies can be used in long-term care facilities, yet have limited evidence supporting their use from systematic reviews.

title: COVID-19: $R_0$ is lower where outbreak is larger
abstract: We use daily data from Lombardy, the Italian region most affected by the COVID-19 outbreak, to calibrate a SIR model individually on each municipality. These are all covered by the same health system and, in the post-lockdown phase we focus on, all subject to the same social distancing regulations. We find that municipalities with a higher number of cases at the beginning of the period analyzed have a lower rate of diffusion, which cannot be imputed to herd immunity. In particular, there is a robust and strongly significant negative correlation between the estimated basic reproduction number ($R_0$) and the initial outbreak size, in contrast with the role of $R_0$ as a \emph{predictor} of outbreak size. We explore different possible explanations for this phenomenon and conclude that a higher number of cases causes changes of behavior, such as a more strict adoption of social distancing measures among the population, that reduce the spread. This result calls for a transparent, real-time distribution of detailed epidemiological data, as such data affects the behavior of populations in areas affected by the outbreak.

title: Implications for forensic death investigations from first Swiss post-mortem CT in a case of non-hospital treatment with COVID-19
abstract: A case of a 50-year old HIV-positive man is presented, with focus on visualization of post-mortem computed tomography (PMCT) of the lungs, in comparison to a forensic control case. He had been found dead at home, a day after his nasopharyngeal swab had returned positive for SARS-COV-2, three days after the sample had been taken as an outpatient, over five weeks after first exhibiting possible symptoms. 3D-visualization was performed by visually discriminating correlates for aerated, poorly aerated and non-aerated lung regions. The visual side-by-side comparison with a control case shows the deterioration beyond any ”normal” post-mortem finding, however. The PMCT findings in the lungs resemble those of patients with acute respiratory distress syndrome (ARDS), while histologically identified inflammation also shows, in part binuclear, lymphocytes. In addition, acute liver dystrophy and acute tubular necrosis in the kidneys were found. Except coronary artery atherosclerosis, there appeared to be no remarkable pathology of the heart.  With the pandemic impact of SARS-COV-2, a range of issues unfolds, also for medicolegal investigations into deaths, as we report the first Swiss case with post-mortem CT where death had occurred due to a SARS-COV-2 infection, with features of a severe acute respiratory distress syndrome, as an outpatient. As this pandemic from the view of risk assessment does constitute a black swan, underestimated fat tails as technical reason should be addressed by also analyzing apparent extreme single observations. This case of an outpatient (without hospital or intensive-care treatment) shows a pulmonary progression beyond the typical findings of COVID-19, to a non-specific picture of ARDS, where histologically, in part binuclear lymphocytes were remarked. What appeared to be an initially slow progression with final rapid escalation raises the question whether nasopharyngeal swabs alone or added pulmonary CT might be better for screening high-risk patients. The reported symptoms and relatively late medical consultation in this case appeared to contrast with the extensive pathology, raising the question whether any search for super-spreaders should not just focus on asymptomatic but under-reported symptomatic patients, and whether their prolonged circulation in everyday life would justify measures such as for example more extensive face mask policies. As post-mortem testing for SARS-COV-2 may not be available for every case, PMCT may provide sensitive testing for lung changes related to COVID-19. In order to allow for more precise medicolegal investigations in the context of COVID-19, however, any more specific extra tests may have to be financed by stakeholders in epidemiology, infectious disease or policy.

title: Systematic Review of the Registered Clinical Trials of Coronavirus Disease 2019 (COVID-19)
abstract: Since the outbreak of coronavirus disease 2019 (COVID-19), many researchers in China have immediately carried out clinical research scheme of the COVID-19. But, there is still a lack of systematic review of registered clinical trials. Therefore, we conducted a systematic review of the clinical trials of COVID-19 to summarize the characteristics of the COVID-19 registered clinical trials.  This study is based on the recommendations of the PRISMA in the Cochrane handbook. The databases from the Chinese Clinical Registration Center and the ClinicalTrials.gov were searched to collect the registered clinical trials of COVID-19. The retrieval inception date is February 9, 2020. Two researchers independently selected the literature based on inclusion and exclusion criteria, extracted data and evaluated the risk of bias.  A total of 75 registered clinical trials (63 interventional studies and 12 observational studies) of COVID-19 were obtained. A majority of clinical trials were sponsored by Chinese hospitals. Only 11 trials have begun to recruit patients, and none of the registered clinical trials had been completed; 34 trials were early clinical exploratory trials or in a pre-experiment stage, 15 trials belonged to phrase Ⅲ and 4 trials were phrase Ⅳ. The methods of intervention included traditional Chinese medicine involving 26 trials, Western medicine involving 30 trials, and integrated traditional Chinese medicine and Western medicine involving 19 trials. The subjects were mainly non-critical adult patients (≥ 18 years old). The median sample size of the trials was 100 (IQR: 60 - 200), and the median execute time of the trials was 179 d (IQR: 94 - 366 d). The main outcomes were clinical observation and examinations. Overall, both the methodology quality of interventional trials and observational studies were low.  Disorderly and intensive clinical trials of COVID-19 using traditional Chinese medicine and western medicine are ongoing or will being carried out in China. However, based on the low methodology quality and small sample size and long studies execute time, we will not be able to obtain reliable, high-quality clinical evidence about COVID-19 treatment in the near future. Improving the quality of study design, prioritizing promising drugs, and using different designs and statistical methods are worth advocating and recommending for the clinical trials of COVID-19 in China.

title: Spread of SARS-CoV-2 in the Icelandic Population
abstract: During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was first diagnosed in Iceland at the end of February. However, data are limited on how SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population.  We targeted testing to persons living in Iceland who were at high risk for infection (mainly those who were symptomatic, had recently traveled to high-risk countries, or had contact with infected persons). We also carried out population screening using two strategies: issuing an open invitation to 10,797 persons and sending random invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples.  As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening.  In a population-based study in Iceland, children under 10 years of age and females had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males. The proportion of infected persons identified through population screening did not change substantially during the screening period, which was consistent with a beneficial effect of containment efforts. (Funded by deCODE Genetics–Amgen.

title: Potential Maternal and Infant Outcomes from Coronavirus 2019-nCoV (SARS-CoV-2) Infecting Pregnant Women: Lessons from SARS, MERS, and Other Human Coronavirus Infections
abstract: In early December 2019 a cluster of cases of pneumonia of unknown cause was identified in Wuhan, a city of 11 million persons in the People’s Republic of China. Further investigation revealed these cases to result from infection with a newly identified coronavirus, initially termed 2019-nCoV and subsequently SARS-CoV-2. The infection moved rapidly through China, spread to Thailand and Japan, extended into adjacent countries through infected persons travelling by air, eventually reaching multiple countries and continents. Similar to such other coronaviruses as those causing the Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS), the new coronavirus was reported to spread via natural aerosols from human-to-human. In the early stages of this epidemic the case fatality rate is estimated to be approximately 2%, with the majority of deaths occurring in special populations. Unfortunately, there is limited experience with coronavirus infections during pregnancy, and it now appears certain that pregnant women have become infected during the present 2019-nCoV epidemic. In order to assess the potential of the Wuhan 2019-nCoV to cause maternal, fetal and neonatal morbidity and other poor obstetrical outcomes, this communication reviews the published data addressing the epidemiological and clinical effects of SARS, MERS, and other coronavirus infections on pregnant women and their infants. Recommendations are also made for the consideration of pregnant women in the design, clinical trials, and implementation of future 2019-nCoV vaccines.

title: Defining high-value information for COVID-19 decision-making
abstract: Initial projections from the first generation of COVID-19 models focused public attention on worst-case scenarios in the absence of decisive policy action. These underscored the imperative for strong and immediate measures to slow the spread of infection. In the coming weeks, however, as policymakers continue enlisting models to inform decisions on COVID-19, answers to the most difficult and pressing policy questions will be much more sensitive to underlying uncertainties. In this study, we demonstrate a model-based approach to assessing the potential value of reducing critical uncertainties most salient to COVID-19 decision-making and discuss priorities for acquiring new data to reduce these uncertainties. We demonstrate how information about the impact of non-pharmaceutical interventions could narrow prediction intervals around hospitalizations over the next few weeks, while information about the prevalence of undetected cases could narrow prediction intervals around the timing and height of the peak of the epidemic.

title: Impact of COVID-19 on clinical practice, income, health and lifestyle behavior of Brazilian urologists
abstract: To evaluate the impact of COVID-19 on clinical practice, income, health and lifestyle behavior of Brazilian urologists during the month of April 2020.  A 39-question, web-based survey was sent to all urologist members of the Brazilian Society of Urology. We assessed socio-demographic, professional, health and behavior parameters. The primary goal was to evaluate changes in urologists ' clinical practice and income after two months of COVID-19. We also looked at geographical differences based on the incidence rates of COVID-19 in different states.  Among 766 urologists who completed the survey, a reduction [≥] 50% of patient visits, elective and emergency surgeries was reported by 83.2%, 89.6% and 54.8%, respectively. An income reduction of [≥] 50% was reported by 54.3%. Measures to reduce costs were implemented by most. Video consultations were performed by 38.7%. Modifications in health and lifestyle included weight gain (32.9%), reduced physical activity (60.0%), increased alcoholic intake (39.9%) and reduced sexual activity (34.9%). Finally, 13.5% of Brazilian urologists were infected with SARS-CoV-2 and about one third required hospitalization. Urologists from the highest COVID-19 incidence states were at a higher risk to have a reduction of patient visits and non-essential surgeries (OR=2.95, 95% CI 1.86 - 4.75; p < 0.0001) and of being infected with SARS-CoV-2 (OR=4.36 95% CI 1.74 - 10.54, p = 0.012).  COVID-19 produced massive disturbances in Brazilian urologists' practice, with major reductions in patient visits and surgical procedures. Distressing consequences were also observed on physicians' income, health and personal lives. These findings are probably applicable to other medical specialties.

title: Offline Digital Education for Postregistration Health Professions: Systematic Review and Meta-Analysis by the Digital Health Education Collaboration.
abstract: The shortage and disproportionate distribution of health care workers worldwide is further aggravated by the inadequacy of training programs, difficulties in implementing conventional curricula, deficiencies in learning infrastructure, or a lack of essential equipment. Offline digital education has the potential to improve the quality of health professions education.  The primary objective of this systematic review was to evaluate the effectiveness of offline digital education compared with various controls in improving learners' knowledge, skills, attitudes, satisfaction, and patient-related outcomes. The secondary objectives were (1) to assess the cost-effectiveness of the interventions and (2) to assess adverse effects of the interventions on patients and learners.  We searched 7 electronic databases and 2 trial registries for randomized controlled trials published between January 1990 and August 2017. We used Cochrane systematic review methods.  A total of 27 trials involving 4618 individuals were included in this systematic review. Meta-analyses found that compared with no intervention, offline digital education (CD-ROM) may increase knowledge in nurses (standardized mean difference [SMD]=1.88; 95% CI 1.14 to 2.62; participants=300; studies=3; I2=80%; low certainty evidence). A meta-analysis of 2 studies found that compared with no intervention, the effects of offline digital education (computer-assisted training [CAT]) on nurses and physical therapists' knowledge were uncertain (SMD 0.55; 95% CI -0.39 to 1.50; participants=64; I2=71%; very low certainty evidence). A meta-analysis of 2 studies found that compared with traditional learning, a PowerPoint presentation may improve the knowledge of patient care personnel and pharmacists (SMD 0.76; 95% CI 0.29 to 1.23; participants=167; I2=54%; low certainty evidence). A meta-analysis of 4 studies found that compared with traditional training, the effects of computer-assisted training on skills in community (mental health) therapists, nurses, and pharmacists were uncertain (SMD 0.45; 95% CI -0.35 to 1.25; participants=229; I2=88%; very low certainty evidence). A meta-analysis of 4 studies found that compared with traditional training, offline digital education may have little effect or no difference on satisfaction scores in nurses and mental health therapists (SMD -0.07; 95% CI -0.42 to 0.28, participants=232; I2=41%; low certainty evidence). A total of 2 studies found that offline digital education may have little or no effect on patient-centered outcomes when compared with blended learning. For skills and attitudes, the results were mixed and inconclusive. None of the studies reported adverse or unintended effects of the interventions. Only 1 study reported costs of interventions. The risk of bias was predominantly unclear and the certainty of the evidence ranged from low to very low.  There is some evidence to support the effectiveness of offline digital education in improving learners' knowledge and insufficient quality and quantity evidence for the other outcomes. Future high-quality studies are needed to increase generalizability and inform use of this modality of education.

title: Laboratory practices to mitigate biohazard risks during the COVID-19 outbreak: an IFCC global survey
abstract: A global survey was conducted by the IFCC Task Force on COVID-19 to better understand how general biochemistry laboratories manage the pre-analytical, analytical and post-analytical processes to mitigate biohazard risks during the coronavirus disease 2019 (COVID-19) pandemic.  An electronic survey was developed to record the general characteristics of the laboratory, as well as the pre-analytical, analytical, post-analytical and operational practices of biochemistry laboratories that are managing clinical samples of patients with COVID-19.  A total of 1210 submissions were included in the analysis. The majority of responses came from hospital central/core laboratories that serve hospital patient groups and handle moderate daily sample volumes. There has been a decrease in the use of pneumatic tube transport, increase in hand delivery and increase in number of layers of plastic bags for samples of patients with clinically suspected or confirmed COVID-19. Surgical face masks and gloves are the most commonly used personal protective equipment (PPE). Just >50% of the laboratories did not perform an additional decontamination step on the instrument after analysis of samples from patients with clinically suspected or confirmed COVID-19. A fifth of laboratories disallowed add-on testing on these samples. Less than a quarter of laboratories autoclaved their samples prior to disposal.  The survey responses showed wide variation in pre-analytical, analytical and post-analytical practices in terms of PPE adoption and biosafety processes. It is likely that many of the suboptimal biosafety practices are related to practical local factors, such as limited PPE availability and lack of automated instrumentation.

title: An overview of coronaviruses including the SARS-2 coronavirus – Molecular biology, epidemiology and clinical implications
abstract: Coronavirus infections have emerged as epidemic and pandemic threats in last two decades. After the H1N1 influenza pandemic in 2009, recently diagnosed novel betacoronavirus or severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has spread across 203 countries and territories in all 5 major continents. World Health Organization (WHO) declared this as a public health emergency of international concern on January 30, 2020. Subsequently on February 11, 2020 a new name was given to this disease i.e. COVID-19 by an expert group from WHO. As of April 12, 2020, 10:00 CET, GMT+2:00, 1,696,588 confirmed cases and 105,952 confirmed deaths have been reported to the WHO. (Coronavirus disease 2019, situation report 83). It possibly originated from a small animal market in Wuhan, China. A cluster of patients were admitted with unusual pneumonia not responding to treatment in various hospitals. Epidemiological, genomic analysis and correlation with other coronaviruses led to the isolation of new coronavirus, closely resembling the bat coronaviruses, from such patients in Wuhan. They were identified as the SARS-CoV-2. This virus infection presents as influenza like illness in the affected people. Fever, cough, respiratory distress with fatigue, diarrhea, nausea and vomiting are common symptoms seen in adults. This may progress on to respiratory distress, hypoxia, need for oxygen supplementation and ventilator support as seen in patients in the SARS-CoV-1 epidemic (2003) in Guangdong, China. The transmissibility of SARS-CoV-1 was less as compared to SARS-CoV-2 infection, and it was well controlled with good public health efforts. The present COVID-19 epidemic is still in the acceleration phase of 3 and 4 in various countries. Without any effective antiviral agents available at present, the need of the hour is early case detection, isolation of cases, use of good preventive care measures by the household contacts and in the hospital set up. The results of ongoing clinical trials on hydroxychloroquine, azithromycin alone or in combination and a new antiviral agent remdesivir may help to treat some of the infections. A need for effective vaccine is being seen an as good preventive strategy in this pandemic. However the results of clinical trials and incorporation of vaccines in public health programs is a long way to go.

title: Coronaviruses and their therapy
abstract: Coronaviruses may cause respiratory, enteric and central nervous system diseases in many species, including humans. Until recently, the relatively low burden of disease in humans caused by few of these viruses hampered development of coronavirus specific therapeutics. However, the emergence of severe acute respiratory syndrome coronavirus (SARS-CoV) has prompted the discovery of such drugs. Subsequent studies in animal models demonstrated the efficacy of SARS-CoV specific monoclonal antibodies, pegylated-interferon-α and siRNAs against SARS-CoV. Furthermore, several antivirals shown to be effective against other viruses were tested in vitro. Because of availability and shown efficacy, the use of interferons may be considered should SARS-CoV or a related coronavirus (re)-emerge. The more recent design of wide-spectrum inhibitors targeting the coronavirus main proteases may lead to the discovery of new antivirals against multiple coronavirus induced diseases.

title: Cats, coronaviruses and coronavirus antibody tests
abstract: Feline infectious peritonitis and other coronavirus infections of cats are briefly reviewed. Interpretation and applications of feline coronavirus antibody tests are described, and general recommendations are provided for practitioners. Some of the major unresolved questions regarding coronavirus infections of cats are delineated.

title: Ascertaining the 2004–2006 HIV type 1 CRF07_BC outbreak among injecting drug users in Taiwan
abstract: To ascertain the explosive 2004–2006 outbreak of HIV-1 CRF07_BC among intravenous drug users (IDU) in Taiwan, which more than doubled the total number of reported HIV cases in less than 3 years, resulting in a 45-fold increase in cumulative IDU/HIV cases and a 40-fold increase in previously seldom-reported female IDU/HIV cases.  A mathematical model was utilized to fit the monthly case data, in order to estimate the turning points (peak incidence) and the reproduction number R of the outbreak. Furthermore, correlation analysis was carried out to assess the correlation between infections among the male and female IDUs.  Model fit revealed a two-wave epidemic during April 2004–March 2007. The larger second wave started shortly after May 2005 and peaked in October 2005 before gradually subsiding. R was estimated to be 3.15 (3.14–3.16) and 27.21 (26.73–28.05) for the two respective waves. The time series of monthly differences in male and female case data were found to be most significantly correlated at lag 0 (i.e., r >0.7) with r =0.906 and 0.804, respectively in each direction. The Granger causality test indicated that the male time series caused the corresponding female time series with a lag of 2 months or less.  The modeling results revealed the presence of a small first wave in 2004, before an explosion of cases after May 2005. Furthermore, a harm reduction program implemented in August 2005 contributed to the downturn in the epidemic after October. Correlation results also suggest that the upsurge in male HIV cases led to the subsequent drastic surge in female cases.

title: Pre exposure Hydroxychloroquine use is associated with reduced COVID19 risk in healthcare workers
abstract: While several trials are ongoing for treatment of COVID-19, scientific research on chemoprophylaxis is still lacking even though it has potential to delay the pandemic allowing us time to complete research on vaccines.  We have conducted a cohort study amongst Health Care Workers (HCW) exposed to COVID-19 patients, at a tertiary care center in India where there was an abrupt cluster outbreak within on duty personnel. HCWs who had voluntarily taken hydroxychloroquine (HCQ) prior to exposure were considered one cohort while those who had not were considered to be another. All participants with a verifiable contact history were tested for COVID-19 by rtPCR. The two cohorts were comparable in terms of age, gender, comorbidities and exposure. The primary outcome was incidence rates of rtPCR positive COVID-19 infection amongst HCQ users and non - users.  106 healthcare workers were examined in this cohort study of whom 54 were HCQ users and rest were not. The comparative analysis of incidence of infection between the two groups demonstrated that voluntary HCQ usage was associated with lesser likelihood of developing SARS-CoV-2 infection, compared to those who were not on it, X2=14.59, p<0.001. None of the HCQ users noted any serious adverse effects.  This study demonstrated that voluntary HCQ consumption as pre-exposure prophylaxis by HCWs is associated with a statistically significant reduction in risk of SARS-CoV-2. These promising findings therefore highlight the need to examine this association in greater detail among a larger sample using Randomised Controlled Trials (RCT).

title: Radiation therapy considerations during the COVID‐19 Pandemic: Literature review and expert opinions
abstract: COVID-19 is an unprecedented pandemic that has already reached over 2 million confirmed cases globally, with at least 140,000 deaths as reported by the World Health Organization (WHO) as of April 16, 2020 1 . More than 662,000 cases have been reported in the United States with more than 29,000 deaths2 . The overall crude mortality rate now stands at 6.6% (may possibly be lower due to under-testing and under-reporting of total confirmed cases), and is highly dependent on age group, comorbidities, and the locoregional resources medically1 . A report from the United States presented age-stratified COVID-19 associated hospitalization rates among 1,482 patients during March 1-28, 2020, highlighting an alarmingly high rate of 74.5% at age > 50 years with underlining medical conditions3 . Based on a data summary report provided by New York City Health, as of April 14, 2020, the shares of a total of 6839 deaths reached 0.04%, 4.5%, 23.1%, 24.6%, and 47.7% for the age groups of 0-17, 18-44, 45-64, 65-74, and 75+ years old4 . All data suggest that adults at a more advanced age group are facing higher morbidity and mortality risks.

title: Human rhinoviruses: The cold wars resume
abstract: Human rhinoviruses (HRVs) are the most common cause of viral illness worldwide but today, less than half the strains have been sequenced and only a handful examined structurally. This viral super-group, known for decades, has still to face the full force of a molecular biology onslaught. However, newly identified viruses (NIVs) including human metapneumovirus and bocavirus and emergent viruses including SARS-CoV have already been exhaustively scrutinized. The clinical impact of most respiratory NIVs is attributable to one or two major strains but there are 100+ distinct HRVs and, because we have never sought them independently, we must arbitrarily divide the literature's clinical impact findings among them. Early findings from infection studies and use of inefficient detection methods have shaped the way we think of ‘common cold’ viruses today.  To review past HRV-related studies in order to put recent HRV discoveries into context.  HRV infections result in undue antibiotic prescriptions, sizable healthcare-related expenditure and exacerbation of expiratory wheezing associated with hospital admission.  The finding of many divergent and previously unrecognized HRV strains has drawn attention and resources back to the most widespread and frequent infectious agent of humans; providing us the chance to seize the advantage in a decades-long cold war.

title: Risk of hospitalization and death from COVID-19 infection in patients with chronic plaque psoriasis receiving a biological treatment and renal transplanted recipients in maintenance immunosuppressive treatment

title: Unknown Unknowns: Surgical Consent during the COVID-19 Pandemic

title: Incidence trend of 2019 novel coronavirus diseases (COVID-19) in China/ 上海预防医学
abstract: To investigate the epidemical characteristics and analyze the incidence trend of 2019 novel coronavirus diseases (COVID-19) in China.  The daily new confirmed cases of 2019 novel coronavirus diseases (COVID-19) in China from January 25 to February 8,2020 were collected for epidemiological descriptive analysis.  During the period from January 25 to February 8, 2020, the number of daily new confirmed cases fell for five consecutive days, from 890 cases on February 3 to 509 cases on February 8.  The incidence of 2019 novel coronavirus diseases (COVID-19) slowed down in 30 provinces (autonomous regions and municipalities directly under the central government) except Hubei and Xinjiang production and construction corps , but the overall situation is still not optimistic. It is imperative to pay close attention to the origin and destination of migrant workers and the incidence of disease in various areas, and take targeted measures to strengthen prevention and control of the disease.

title: Preliminary epidemiological analysis on children and adolescents with novel coronavirus disease 2019 outside Hubei Province, China: an observational study utilizing crowdsourced data
abstract: The outbreak of coronavirus disease 2019 (COVID-19) continues to expand across the world. Though both the number of cases and mortality rate in children and adolescents is reported to be low in comparison to adults, limited data has been reported on the outbreak with respect to pediatric patients. To elucidate information, we utilized crowdsourced data to perform a preliminary epidemiologic analysis of pediatric patients with COVID-19  In this observational study, data was collected from two open-access, line list crowdsourced online databases. Pediatric cases of COVID-19 were defined as patients ≤19 years of age with a laboratory confirmed diagnosis. The primary outcomes were case counts and cumulative case counts. Secondary outcomes included days between symptoms onset and first medical care and days between first medical care and reporting. Tertiary outcomes were rate of travel to Wuhan, rate of infected family members and rates of symptoms.  A total of 82 patients were included. The median age was 10 [IQR: 5-15] years. Patients from mainland China (outside Hubei) accounted for 46.3% of cases, while the remaining 53.7% of cases were international. Males and females accounted for 52.4% and 32.9% of cases, respectively, with the remaining 14.6% being designated as unknown. A male skew persisted across subgroup analyses by age group (p=1.0) and location (inside/outside China) (p=0.22). While the number of reported international cases has been steadily increasing over the study period, the number of reported cases in China rapidly decreased from the start point. The median reporting delay was 3 [IQR: 2-4.8] days. The median delay between symptom onset and first seeking medical care was 1 [IQR: 0-3.25] day. In international cases, time to first seeking medical care was a median of 2.5 days longer than in China (p=0.04). When clinical features were reported, fever was the most common presentation (68.0%), followed by cough (36.0%).  The number of reported international pediatric COVID-19 cases is rapidly increasing. COVID-19 infections are, to-date, more common in males than females in both the children and adolescent age groups. Additionally, this male predominance remains the case both inside and outside of China. Crowdsourced data enabled early analysis of epidemiologic variables in pediatric patients with COVID-19. Further data sharing is required to enable analyses that are required to understand the course of this infection in children.

title: Connecting clusters of COVID-19: an epidemiological and serological investigation
abstract: Elucidation of the chain of disease transmission and identification of the source of coronavirus disease 2019 (COVID-19) infections are crucial for effective disease containment. We describe an epidemiological investigation that, with use of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serological assays, established links between three clusters of COVID-19.  In Singapore, active case-finding and contact tracing were undertaken for all COVID-19 cases. Diagnosis for acute disease was confirmed with RT-PCR testing. When epidemiological information suggested that people might have been nodes of disease transmission but had recovered from illness, SARS-CoV-2 IgG serology testing was used to establish past infection.  Three clusters of COVID-19, comprising 28 locally transmitted cases, were identified in Singapore; these clusters were from two churches (Church A and Church B) and a family gathering. The clusters in Church A and Church B were linked by an individual from Church A (A2), who transmitted SARS-CoV-2 infection to the primary case from Church B (F1) at a family gathering they both attended on Jan 25, 2020. All cases were confirmed by RT-PCR testing because they had active disease, except for A2, who at the time of testing had recovered from their illness and tested negative. This individual was eventually diagnosed with past infection by serological testing. ELISA assays showed an optical density of more than 1·4 for SARS-CoV-2 nucleoprotein and receptor binding domain antigens in titres up to 1/400, and viral neutralisation was noted in titres up to 1/320.  Development and application of a serological assay has helped to establish connections between COVID-19 clusters in Singapore. Serological testing can have a crucial role in identifying convalescent cases or people with milder disease who might have been missed by other surveillance methods.

title: Modeling COVID-19 latent prevalence to assess a public health intervention at a state and regional scale
abstract: Emergence of COVID-19 caught the world off-guard and unprepared, initiating a global pandemic. In the absence of evidence, individual communities had to take timely action to reduce the rate of disease spread and avoid overburdening their healthcare systems. Although a few predictive models have been published to guide these decisions, most have not taken into account spatial differences and have included assumptions that do not match the local realities. Access to reliable information that is adapted to local context is critical for policymakers to make informed decisions during a rapidly evolving pandemic.  The goal of this study was to develop an adapted susceptible-infected-removed (SIR) model to predict the trajectory of the COVID-19 pandemic in North Carolina and the Charlotte metropolitan region and to incorporate the effect of a public health intervention to reduce disease spread, while accounting for unique regional features and imperfect detection.  Three SIR models were fit to prevalence data from the state and the greater Charlotte region and then rigorously compared. One of these models (SIR-Int) accounted for a stay-at-home intervention and imperfect detection of COVID-19 cases.  Presently, the COVID-19 outbreak is rapidly decelerating in NC and the Charlotte region. Infection curves are flattening at both the state and regional level. Relatively speaking, the greater Charlotte region has responded more favorably to the stay-at-home intervention than NC as a whole. While an initial basic SIR model served the purpose of informing decision making in the early days of the pandemic, its forecast increasingly did not fit the data over time. However, as the pandemic and local conditions evolved, the SIR-Int model provided a good fit to the data.  Using local data and continuous attention to model adaptation, our findings have enabled policymakers, public health officials and health systems to do capacity planning and evaluate the impact of a public health intervention. Our SIR-Int model for estimated latent prevalence was reasonably flexible, highly accurate, and demonstrated the efficacy of a stay-at-home order at both the state and regional level. Our results highlight the importance of incorporating local context into pandemic forecast modeling, as well as the need to remain vigilant and informed by the data as we enter into a critical period of the outbreak.

title: Effectiveness of interventions targeting air travellers for delaying local outbreaks of SARS-CoV-2
abstract: We evaluated if interventions aimed at air travellers can delay local SARS-CoV-2 community transmission in a previously unaffected country.  We simulated infected air travellers arriving into countries with no sustained SARS-CoV-2 transmission or other introduction routes from affected regions. We assessed the effectiveness of syndromic screening at departure and/or arrival & traveller sensitisation to the COVID-2019-like symptoms with the aim to trigger rapid self-isolation and reporting on symptom onset to enable contact tracing. We assumed that syndromic screening would reduce the number of infected arrivals and that traveller sensitisation reduces the average number of secondary cases. We use stochastic simulations to account for uncertainty in both arrival and secondary infections rates, and present sensitivity analyses on arrival rates of infected travellers and the effectiveness of traveller sensitisation. We report the median expected delay achievable in each scenario and an inner 50% interval.  Under baseline assumptions, introducing exit and entry screening in combination with traveller sensitisation can delay a local SARS-CoV-2 outbreak by 8 days (50% interval: 3–14 days) when the rate of importation is 1 infected traveller per week at time of introduction. The additional benefit of entry screening is small if exit screening is effective: the combination of only exit screening and traveller sensitisation can delay an outbreak by 7 days (50% interval: 2–13 days). In the absence of screening, with less effective sensitisation, or a higher rate of importation, these delays shrink rapidly to less than 4 days.  Syndromic screening and traveller sensitisation in combination may have marginally delayed SARS-CoV-2 outbreaks in unaffected countries.

title: Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors
abstract: The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural languages, a platform for the real-time synthesis of the exponentially growing biomedical literature and its comprehensive triangulation with deep omic insights is not available. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations extracted from unstructured biomedical text, and their triangulation with Single Cell RNA-sequencing based insights from over 25 tissues. Using this platform, we identify intersections between the pathologic manifestations of COVID-19 and the comprehensive expression profile of the SARS-CoV-2 receptor ACE2. We find that tongue keratinocytes, airway club cells, and ciliated cells are likely underappreciated targets of SARS-CoV-2 infection, in addition to type II pneumocytes and olfactory epithelial cells. We further identify mature small intestinal enterocytes as a possible hotspot of COVID-19 fecal-oral transmission, where an intriguing maturation-correlated transcriptional signature is shared between ACE2 and the other coronavirus receptors DPP4 (MERS-CoV) and ANPEP (α-coronavirus). This study demonstrates how a holistic data science platform can leverage unprecedented quantities of structured and unstructured publicly available data to accelerate the generation of impactful biological insights and hypotheses. The nferX Platform Single-cell resource -

title: Periodic COVID-19 Testing in Emergency Department Staff
abstract: As the number of COVID-19 cases in the US continues to rise and hospitals are experiencing personal protective equipment (PPE) shortages, healthcare workers have been disproportionately affected by COVID-19 infection. Since COVID-19 testing is now available, some have raised the question of whether we should be routinely testing asymptomatic healthcare workers.  Using publicly available data on COVID-19 infections and emergency department visits, as well as internal hospital staffing information, we generated a mathematical model to predict the impact of periodic COVID-19 testing in asymptomatic members of the emergency department staff in regions affected by COVID-19 infection. We calculated various transmission constants based on the Diamond Princess cruise ship data, used a logistic model to calculate new infections, and we created a Markov model according to average COVID-19 incubation time.  Our model predicts that after 30 days, with a transmission constant of 1.219e-4 new infections per person2, weekly COVID-19 testing of healthcare workers (HCW) would reduce new HCW and patient infections by 5.1% and bi-weekly testing would reduce both by 2.3%. At a transmission constant of 3.660e-4 new infections per person,2 weekly testing would reduce infections by 21.1% and bi-weekly testing would reduce infections by 9.7-9.8%. For a lower transmission constant of 4.067e-5 new infections per person2, weekly and biweekly HCW testing would result in a 1.54% and 0.7% reduction in infections respectively.  Periodic COVID-19 testing for emergency department staff in regions that are heavily-affected by COVID-19 and/or facing resource constraints may reduce COVID-19 transmission significantly among healthcare workers and previously-uninfected patients.

title: Influence of blood pressure on pneumonia risk: Epidemiological association and Mendelian randomisation in the UK Biobank
abstract: To determine whether elevated blood pressure influences risk for respiratory infection.  Prospective, population-based epidemiological and Mendelian randomisation studies.  UK Biobank.  377,143 self-identified British descent (54% women; median age 58 years) participants in the UK Biobank.  First incident pneumonia over an average of 8 follow-up years.  107,310 (30%) participants had hypertension at UK Biobank enrolment, and 9,969 (3%) developed a pneumonia during follow-up. Prevalent hypertension at baseline was significantly associated with increased risk for incident respiratory disease including pneumonia (hazard ratio 1.36 (95% confidence interval 1.29 to 1.43), P<0.001), acute respiratory distress syndrome or respiratory failure (1.43 (1.29 to 1.59), P<0.001), and chronic lower respiratory disease (1.30 (1.25 to 1.36), P<0.001), independent of age, age2, sex, smoking status, BMI, prevalent diabetes mellitus, prevalent coronary artery disease, and principal components of ancestry. Mendelian randomisation analyses indicated that genetic predisposition to a 5 mmHg increase in blood pressure was associated with increased risk of incident pneumonia for SBP (1.08, (1.04 to 1.13), P<0.001) and DBP (1.11 (1.03 to 1.20), P=0.005). Additionally, consistent with epidemiologic associations, increase in blood pressure genetic risk was significantly associated with reduced forced expiratory volume in the first second, forced vital capacity, and the ratio of the two (P<0.001 for all).  These results strongly suggest that elevated blood pressure independently increases risk for pneumonia and reduces pulmonary function. Maintaining adequate blood pressure control, in addition to other measures, may reduce risk for pneumonia. Whether the present findings are generalizable to novel coronavirus disease 2019 (COVID-19) require further study.

title: Treatment options for COVID-19: the reality and challenges
abstract: An outbreak related to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in Wuhan, China in December 2019. An extremely high potential for dissemination resulted in the global coronavirus disease 2019 (COVID-19) pandemic in 2020. Despite the worsening trends of COVID-19, no drugs are validated to have significant efficacy in clinical treatment of COVID-19 patients in large-scale studies. Remdesivir is considered the most promising antiviral agent; it works by inhibiting the activity of RNA-dependent RNA polymerase (RdRp). A large-scale study investigating the clinical efficacy of remdesivir (200 mg on day 1, followed by 100 mg once daily) is on-going. The other excellent anti-influenza RdRp inhibitor favipiravir is also being clinically evaluated for its efficacy in COVID-19 patients. The protease inhibitor lopinavir/ritonavir (LPV/RTV) alone is not shown to provide better antiviral efficacy than standard care. However, the regimen of LPV/RTV plus ribavirin was shown to be effective against SARS-CoV in vitro. Another promising alternative is hydroxychloroquine (200 mg thrice daily) plus azithromycin (500 mg on day 1, followed by 250 mg once daily on day 2-5), which showed excellent clinical efficacy on Chinese COVID-19 patients and anti-SARS-CoV-2 potency in vitro. The roles of teicoplanin (which inhibits the viral genome exposure in cytoplasm) and monoclonal and polyclonal antibodies in the treatment of SARS-CoV-2 are under investigation. Avoiding the prescription of non-steroidal anti-inflammatory drugs, angiotensin converting enzyme inhibitors, or angiotensin II type I receptor blockers is advised for COVID-19 patients.

title: A comparative multi-centre study on the clinical and imaging features of comfirmed and uncomfirmed patients with COVID-19
abstract: Previous studies had described the differences in clinical characteristics between ICU and non-ICU patients. However, seldom study focused on confirmed and unconfirmed groups. Our aim was to compare clinical and imaging characteristics of COVID-19 patients outside Hubei province between confirmed and unconfirmed group.  We retrospectively enrolled 163 consecutive adult patients with suspected COVID-19 from three tertiary hospitals in two provinces outside Hubei province from January 12, 2020 to February 13, 2020 and the differences in epidemiological, clinical, laboratory and imaging characteristics between the two groups were compared.  This study enrolled 163 patients with 62 confirmed cases and 101 unconfirmed cases. Most confirmed patients were clustered (31, 50.0%) and with definite epidemiological exposure. Symptoms of COVID-19 were nonspecific, largely fever and dry cough. Laboratory findings in confirmed group were characterized by normal or reduced white blood cell count, reduced the absolute value of lymphocytes, and elevated levels of C-reactive protein (CRP) and accelerated Erythrocyte sedimentation rate (ESR). The typical chest CT imaging features of patients with confirmed COVID-19 were peripherally distributed multifocal GGO with predominance in the lower lung lobe. Compared with unconfirmed patients, confirmed patients had significantly higher proportion of dry cough, leucopenia, lymphopenia and accelerated ESR (P<0.05); but not with alanine aminotransferase, aspartate aminotransferase, D-dimer, lactic dehydrogenase, and myoglobin (P>0.05). Proportion of peripheral, bilateral or lower lung distribution and multi-lobe involvement, GGO, crazy-paving pattern, air bronchogram and pleural thickening in the confirmed group were also higher (P<0.05).  Symptoms of COVID-19 were nonspecific. Leukopenia, lymphopenia and ESR, as well as chest CT could be used as a clue for clinical diagnosis of COVID-19.

title: Acute complications and mortality in hospitalized patients with coronavirus disease 2019: a systematic review and meta-analysis
abstract: The incidence of acute complications and mortality associated with COVID-19 remains poorly characterized. The aims of this systematic review and meta-analysis were to summarize the evidence on clinically relevant outcomes in hospitalized patients with COVID-19.  MEDLINE, EMBASE, PubMed, and medRxiv were searched up to April 20, 2020, for studies including hospitalized symptomatic adult patients with laboratory-confirmed COVID-19. The primary outcomes were all-cause mortality and acute respiratory distress syndrome (ARDS). The secondary outcomes included acute cardiac or kidney injury, shock, coagulopathy, and venous thromboembolism. The main analysis was based on data from peer-reviewed studies. Summary estimates and the corresponding 95% prediction intervals (PIs) were obtained through meta-analyses.  A total of 44 peer-reviewed studies with 14,866 COVID-19 patients were included. In general, risk of bias was high. All-cause mortality was 10% overall (95% PI, 2 to 39%; 1687/14203 patients; 43 studies), 34% in patients admitted to intensive care units (95% PI, 8 to 76%; 659/2368 patients; 10 studies), 83% in patients requiring invasive ventilation (95% PI, 1 to 100%; 180/220 patients; 6 studies), and 75% in patients who developed ARDS (95% PI, 35 to 94%; 339/455 patients; 11 studies). On average, ARDS occurred in 14% of patients (95% PI, 2 to 59%; 999/6322 patients; 23 studies), acute cardiac injury in 15% (95% PI, 5 to 38%; 452/2389 patients; 10 studies), venous thromboembolism in 15% (95% PI, 0 to 100%; patients; 3 studies), acute kidney injury in 6% (95% PI, 1 to 41%; 318/4682 patients; 15 studies), coagulopathy in 6% (95% PI, 1 to 39%; 223/3370 patients; 9 studies), and shock in 3% (95% PI, 0 to 61%; 203/4309 patients; 13 studies).  Mortality was very high in critically ill patients based on very low-quality evidence due to striking heterogeneity and risk of bias. The incidence of clinically relevant outcomes was substantial, although reported by only one third of the studies suggesting considerable underreporting.

title: [An increased neutrophil/lymphocyte ratio is an early warning signal of severe COVID-19].
abstract: To identify the biomarkers as early warning signals for severe COVID-19.  We retrospectively analyzed the clinical data of 63 patients with COVID- 19 from Hubei Provincial Hospital of Integrated Chinese and Western Medicine, including 32 moderate cases and 31 severe cases. The demographic data, underlying diseases, clinical manifestations and laboratory test results were compared between the two groups. Logistic regression analysis was performed to identify the factors that predicted the severity of COVID-19. The receiver- operating characteristic curve (ROC) of neutrophil/lymphocyte ratio (NLR) was calculated, and the area under the curve (AUC) was determined to estimate the optimal threshold of NLR for predicting severe cases of COVID-19.  The patients with moderate and server COVID-19 showed significant differences in the rate of diabetes, NLR, serum amyloid A (SSA), C-reactive protein (CRP) and serum albumin (ALB) levels (P < 0.05). The co- morbidity of diabetes, NLR, SSA and CRP were found to positively correlate and ALB to inversely correlate with the severity of COVID-19 (P < 0.05). Multivariate logistic regression analysis showed that NLR was an independent risk factor for severe COVID-19 (OR=1.264, 95% CI: 1.046-1.526, P=0.015) with an AUC of 0.831 (95% CI: 0.730-0.932), an optimal diagnostic threshold of 4.795, a sensitivity of 0.839, and a specificity of 0.750.  An increased NLR can serve as an early warning signal of severe COVID-19.

title: The Impact of Coronavirus Disease 2019 (COVID-19) on Liver Injury in China: A Systematic Review and Meta-analysis
abstract: The evidence for the incidence and severity of liver injury in Chinese patients with COVID-19 is still controversial.  The purpose of this study was to summarize the incidence of liver injury and the differences between liver injury markers among different patients with COVID-19 in China.  Computer searches of PubMed, Embase, CNKI and medRxiv were used to obtain reports on the incidence and markers of liver injury in Chinese patients with COVID-19, from January 1, 2020 to April 10, 2020.  A total of 57 reports from China were included, including 9889 confirmed cases of COVID-19 infection. The results of the meta-analysis showed that among the patients with early COVID-19 infection in China, the incidence of liver injury events was 24.7% (95% CI, 23.4%-26.4%). Liver injury in severe patients was more common than that in non-severe patients, with a risk ratio of 2.07 (95% CI, 1.77 to 2.43). Quantitative analysis showed that the severe the coronavirus infection, the higher the level of AST, ALT, TB, ALP, GGT and the lower the level of ALB. The changing trend of the appeal index was similar in ICU patients and dead patients.  There is a certain risk of liver injury in Chinese patients with COVID-19, and the risk and degree of liver injury are related to the severity of COVID-19.

title: Coronavirus disease 2019 (COVID-19): current status and future perspectives
abstract: Coronavirus disease 2019 (COVID-19) originated in the city of Wuhan, Hubei Province, Central China, and has spread quickly to 72 countries to date. COVID-19 is caused by a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [previously provisionally known as 2019 novel coronavirus (2019-nCoV)]. At present, the newly identified SARS-CoV-2 has caused a large number of deaths with tens of thousands of confirmed cases worldwide, posing a serious threat to public health. However, there are no clinically approved vaccines or specific therapeutic drugs available for COVID-19. Intensive research on the newly emerged SARS-CoV-2 is urgently needed to elucidate the pathogenic mechanisms and epidemiological characteristics and to identify potential drug targets, which will contribute to the development of effective prevention and treatment strategies. Hence, this review will focus on recent progress regarding the structure of SARS-CoV-2 and the characteristics of COVID-19, such as the aetiology, pathogenesis and epidemiological characteristics.

title: Suppression of innate antiviral response by severe acute respiratory syndrome coronavirus M protein is mediated through the first transmembrane domain
abstract: Coronaviruses have developed various measures to evade innate immunity. We have previously shown that severe acute respiratory syndrome (SARS) coronavirus M protein suppresses type I interferon (IFN) production by impeding the formation of functional TRAF3-containing complex. In this study, we demonstrate that the IFN-antagonizing activity is specific to SARS coronavirus M protein and is mediated through its first transmembrane domain (TM1) located at the N terminus. M protein from human coronavirus HKU1 does not inhibit IFN production. Whereas N-linked glycosylation of SARS coronavirus M protein has no influence on IFN antagonism, TM1 is indispensable for the suppression of IFN production. TM1 targets SARS coronavirus M protein and heterologous proteins to the Golgi apparatus, yet Golgi localization is required but not sufficient for IFN antagonism. Mechanistically, TM1 is capable of binding with RIG-I, TRAF3, TBK1 and IKKε, and preventing the interaction of TRAF3 with its downstream effectors. Our work defines the molecular architecture of SARS coronavirus M protein required for suppression of innate antiviral response.

title: Expression of SARS-coronavirus envelope protein in Escherichia coli cells alters membrane permeability
abstract: To promote viral entry, replication, release, and spread to neighboring cells, many cytolytic animal viruses encode proteins responsible for modification of host cell membrane permeability and for formation of ion channels in host cell membranes during their life cycles. In this study, we show that the envelope (E) protein of severe acute respiratory syndrome-associated coronavirus can induce membrane permeability changes when expressed in Escherichia coli. E protein expressed in bacterial and mammalian cells under reducing conditions existed as monomers, but formed homodimer and homotrimer under non-reducing conditions. Site-directed mutagenesis studies revealed that two cysteine residues of the E protein were essential for oligomerization, leading to induction of membrane permeability. This is the first report demonstrating that a coronavirus-encoded protein could modify membrane permeability in E. coli cells.

title: Important Steps to Control COVID-19/SARS-CoV-2 Infection
abstract: Elderly patients are having high mortality rates from COVID-19/SARS-CoV-2 infection compared to younger patients. The SARS-CoV-2 virus uses the ACE2 receptor as the entry point to the host cells. ARBs/ACEIs which are widely used in elderly patients, have been found to be associated with overexpression of ACE2.To decrease the severity of COVID-19 infection, ARB/ACEI should be switched to another class drug not known to cause a rise in ACE2 until the COVID-19 infection subsides. Specific human immunoglobulin can be tried for COVID-19 patients with critical conditions under supervision.

title: COVID-19 Growth Rate Decreases with Social Capital
abstract: Social capital has been associated with many public health variables including mortality, obesity, diabetes, and sexually-transmitted disease rates. However, the relationship of social capital to the spread of infectious disease like COVID-19 is lacking. The COVID-19 pandemic presents an unprecedented threat to global health and economy, for which control strategies have relied on aggressive social distancing. However, an understanding of how social capital is related to changes in human mobility patterns for adherence to social distancing is lacking.  This study examines the association between state- and county-level social capital indices and community health indices in the United States, and the growth rate of COVID-19 cases. It also examines changes in human mobility.  Using publicly available state- and county-specific time series data for COVID-19 cases from March 13 to March 31, we used exponential fits to determine growth rate. We obtained publicly available mobility change data, originally measured from GPS-enabled mobile devices. The design was then state- and county-level correlation analysis with social capital and community health indices from the Social Capital Project (United States Senate).  In bivariate linear correlation analyses, we find social capital and community health indices were negatively associated with COVID-19 growth rates at both the state and county levels. The correlation was strongest at the county level for the community health index: a one-unit increase in the county community health index was associated with a decrease in the COVID-19 growth rate exponent by 0.045. In further bivariate correlation analyses, we find that social capital indices were negatively associated with retail/recreation movement and positively associated with residential movement. That is, an increase in social capital is correlated with slower COVID-19 infection spread and more adherence to social distancing protocols.  Our results indicate the potential benefit of incorporating social capital concepts in planning policies to control the spread of COVID-19, e.g. different social distancing requirements in different communities. The results also indicate a need for further research into this potentially causal relationship, including examining interventions to increase social capital, community health, and institutional health.

title: Preparedness and response to Pediatric CoVID-19 in European Emergency Departments: a survey of the REPEM and PERUKI networks
abstract: We aimed to describe the variability and identify gaps in preparedness and response to the COVID-19 pandemic in European EDs caring for children.  A cross-sectional point prevalence survey, was developed and disseminated through the pediatric emergency medicine research networks for Europe (REPEM) and the United Kingdom and Ireland (PERUKI). We aimed to include ten EDs for countries with > 20 million inhabitants and five EDs for less populated countries, unless the number of eligible EDs was below five. ED directors or their delegates completed the survey between March 20th and 21st to report practice at that time. We used descriptive statistics to analyse data.  Overall 102 centers from 18 countries (86% response rate) completed the survey: 34% did not have an ED contingency plan for pandemics and 36% had never had simulations for such events. Wide variation on PPE items was shown for recommended PPE use at pre-triage and for patient assessment, with 62% of centers experiencing shortage in one or more PPE items, most frequently FFP2/N95 masks. Only 17% of EDs had negative pressure isolation rooms. COVID-19 positive ED staff was reported in 25% of centers.  We found variation and identified gaps in preparedness and response to the COVID-19 epidemic across European referral EDs for children. A lack in early availability of a documented contingency plan, provision of simulation training, appropriate use of PPE, and appropriate isolation facilities emerged as gaps that should be optimized to improve preparedness and inform responses to future pandemics.

title: Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
abstract: We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.

title: The impact of COVID-19 control measures on social contacts and transmission in Kenyan informal settlements
abstract: Many low- and middle-income countries have implemented control measures against coronavirus disease 2019 (COVID-19). However, it is not clear to what extent these measures explain the low numbers of recorded COVID-19 cases and deaths in Africa. One of the main aims of control measures is to reduce respiratory pathogen transmission through direct contact with others. In this study we collect contact data from residents of informal settlements around Nairobi, Kenya to assess if control measures have changed contact patterns, and estimate the impact of changes on the basic reproduction number (R0).  We conducted a social contact survey with 213 residents of five informal settlements around Nairobi in early May 2020, four weeks after the Kenyan government introduced enhanced physical distancing measures and a curfew between 7pm and 5am. Respondents were asked to report all direct physical and non-physical contacts made the previous day, alongside a questionnaire asking about the social and economic impact of COVID-19 and control measures. We examined contact patterns by demographic factors, including socioeconomic status. We described the impact of COVID-19 and control measures on income and food security. We compared contact patterns during control measures to patterns from non-pandemic periods to estimate the change in R0.  We estimate that control measures reduced physical and non-physical contacts, reducing the R0 from around 2.6 to between 0.5 and 0.7, depending on the pre-COVID-19 comparison matrix used. Masks were worn by at least one person in 92% of contacts. Respondents in the poorest socioeconomic quintile reported 1.5 times more contacts than those in the richest. 86% of respondents reported a total or partial loss of income due to COVID-19, and 74% reported eating less or skipping meals due to having too little money for food. Interpretation COVID-19 control measures have had a large impact on direct contacts and therefore transmission, but have also caused considerable economic and food insecurity. Reductions in R0 are consistent with the linear epidemic growth in Kenya and other sub-Saharan African countries that implemented similar, early control measures. However, negative and inequitable impacts on economic and food security may mean control measures are not sustainable in the longer term.

title: Massive and rapid COVID-19 testing is feasible by extraction-free SARS-CoV-2 RT-qPCR
abstract: Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The most widely used method of COVID-19 diagnostics is a reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay, detecting the presence of SARS-CoV-2 RNA in patient samples, typically from nasopharyngeal swabs. The RNA extraction is a major bottleneck in current COVID-19 testing, in terms of turn-around, logistics, component availability and cost, which delays or completely precludes COVID-19 diagnostics in many settings. Efforts to simplify the current methods are important, as increased diagnostic availability and efficiency is expected to benefit patient care and infection control. Here, we describe methods to circumvent RNA extraction in COVID-19 testing by performing RT-qPCR directly on heat-inactivated subject samples as well as samples lysed with readily available detergents. Our data, including cross-comparisons with clinically diagnosed patient samples, suggest that direct RT-qPCR is a viable option to extraction-based COVID-19 diagnostics. We argue that significant savings in terms of time and cost can be achieved by embracing RNA-extraction-free protocols, that feeds directly into the established PCR-based testing pipeline. This could aid the expansion of COVID-19 testing.

title: Determination of host cell proteins constituting the molecular microenvironment of coronavirus replicase complexes by proximity-labeling
abstract: Positive-sense RNA viruses hijack intracellular membranes that provide niches for viral RNA synthesis and a platform for interactions with host proteins. However, little is known about host factors at the interface between replicase complexes and the host cytoplasm. We engineered a biotin ligase into a coronaviral replication/transcription complex (RTC) and identified >500 host proteins constituting the RTC microenvironment. siRNA-silencing of each RTC-proximal host factor demonstrated importance of vesicular trafficking pathways, ubiquitin-dependent and autophagy-related processes, and translation initiation factors. Notably, detection of translation initiation factors at the RTC was instrumental to visualize and demonstrate active translation proximal to replication complexes of several coronaviruses. Collectively, we establish a spatial link between viral RNA synthesis and diverse host factors of unprecedented breadth. Our data may serve as a paradigm for other positive-strand RNA viruses and provide a starting point for a comprehensive analysis of critical virus-host interactions that represent targets for therapeutic intervention.

title: Inferring Infection Patterns Based on a Connectivity Map of Host Transcriptional Responses
abstract: Host responses to infections represent an important pathogenicity determiner, and delineation of host responses can elucidate pathogenesis processes and inform the development of anti-infection therapies. Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust “HTR communities” (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens.

title: Molecular mechanisms of severe acute respiratory syndrome (SARS)
abstract: Severe acute respiratory syndrome (SARS) is a new infectious disease caused by a novel coronavirus that leads to deleterious pulmonary pathological features. Due to its high morbidity and mortality and widespread occurrence, SARS has evolved as an important respiratory disease which may be encountered everywhere in the world. The virus was identified as the causative agent of SARS due to the efforts of a WHO-led laboratory network. The potential mutability of the SARS-CoV genome may lead to new SARS outbreaks and several regions of the viral genomes open reading frames have been identified which may contribute to the severe virulence of the virus. With regard to the pathogenesis of SARS, several mechanisms involving both direct effects on target cells and indirect effects via the immune system may exist. Vaccination would offer the most attractive approach to prevent new epidemics of SARS, but the development of vaccines is difficult due to missing data on the role of immune system-virus interactions and the potential mutability of the virus. Even in a situation of no new infections, SARS remains a major health hazard, as new epidemics may arise. Therefore, further experimental and clinical research is required to control the disease.

title: Prevalence and predictors of PTSS during COVID-19 outbreak in China hardest-hit areas: Gender differences matter
abstract: The outbreak of COVID-19 in China in December 2019 has been identified as a pandemic and a health emergency of global concern. Our objective was to investigate the prevalence and predictors of posttraumatic stress symptoms (PTSS) in China hardest-hit areas during COVID-19 outbreak, especially exploring the gender difference existing in PTSS. One month after the December 2019 COVID-19 outbreak in Wuhan China, we surveyed PTSS and sleep qualities among 285 residents in Wuhan and surrounding cities using the PTSD Checklist for DSM-5 (PCL-5) and 4 items from the Pittsburgh Sleep Quality Index (PSQI). Hierarchical regression analysis and non-parametric test were used to analyze the data. Results indicated that the prevalence of PTSS in China hardest-hit areas a month after the COVID-19 outbreak was 7%. Women reported significant higher PTSS in the domains of re-experiencing, negative alterations in cognition or mood, and hyper-arousal. Participants with better sleep quality or less frequency of early awakenings reported lower PTSS. Professional and effective mental health services should be designed in order to aid the psychological wellbeing of the population in affected areas, especially those living in hardest-hit areas, females and people with poor sleep quality.

title: What is the true incidence of COVID-19 in patients with rheumatic diseases?

title: AKI during COVID-19 infection: low incidence, high risk of death
abstract: Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide and seriously threatens human health since December 2019. However, information about acute kidney injury (AKI) during COVID-19 infection is limited. Some studies thought that presence of AKI is very common and cannot be ignored, while some studies pointed that AKI only is a rare incident during COVID-19 infection. This meta-analysis aimed to find out the truth of COVID-19 related AKI and to provide stronger evidence.  Two authors independently performed a literature search using PubMed, Web of Science, Embase, and Cochrane Library fulfilled the pre-specified criteria until April 25, 2020 to include studies reported the necessary clinic characteristics, then the incidence of AKI, incidence of required RRT, the mortality with AKI and the death risk with AKI during COVID-19 infection were pooled for statistical analysis by Open Meta-Analyst software to get conclusions.  It was found that the incidence of AKI in hospitalized patients with COVID-19 infection is low, only about 3.8%; the in-hospital mortality with AKI in COVID-19 infected patients is reach up to 32.6%; the death risk with AKI in COVID-19 infected patients is about 16.1 times higher than those without AKI.  This meta-analysis indicated AKI during COVID-19 infection should be pay more attention, it maybe a strong red flag to death risk. It is still need additional studies to support the conclusions and to explore the AKI mechanism during COVID-19 infection.

title: Using psychoneuroimmunity against COVID-19
abstract: The worldwide outbreak of coronavirus disease 2019 (COVID-19) raises concerns of widespread panic and anxiety in individuals subjected to the real or perceived threat of the virus. Compared to general populations, patients who are institutionalized in a closed unit are also very vulnerable to COVID-19 infection and complications. This crisis touched on difficult issues of not only psychiatric care and ethics, but also psychological impacts to psychiatric care givers. In this Viewpoint, we address both physical and biopsychosocial aspects of this infection, as well as the psychoneuroimmunity of preventive strategies of healthy lifestyle, regular exercise, balanced nutrition, quality sleep and a strong connection with people. Social distancing and wearing masks might help us from pathogen exposure, yet such these measures also prevent us from expressing compassion and friendliness. Therefore, all forms of psychological support should be routinely implemented not only to consider psychological resilience but also to enhance psychoneuroimmunity against COVID-19.

title: Modes of contact and risk of transmission in COVID-19 among close contacts
abstract: Rapid spread of SARS-CoV-2 in Wuhan prompted heightened surveillance in Guangzhou and elsewhere in China. Modes of contact and risk of transmission among close contacts have not been well estimated.  We included 4950 closes contacts from Guangzhou, and extracted data including modes of contact, laboratory testing, clinical characteristics of confirmed cases and source cases. We used logistic regression analysis to explore the risk factors associated with infection of close contacts.  Among 4950 closes contacts, the median age was 38.0 years, and males accounted for 50.2% (2484). During quarantine period, 129 cases (2.6%) were diagnosed, with 8 asymptomatic (6.2%), 49 mild (38.0%), and 5 (3.9%) severe to critical cases. The sensitivity of throat swab was 71.32% and 92.19% at first to second PCR test. Among different modes of contact, household contacts were the most dangerous in catching with infection of COVID-19, with an incidence of 10.2%. As the increase of age for close contacts and severity of source cases, the incidence of COVID-19 presented an increasing trend from 1.8% (0-17 years) to 4.2% (60 or over years), and from 0.33% for asymptomatic, 3.3% for mild, to 6.2% for severe and critical source cases, respectively. Manifestation of expectoration in source cases was also highly associated with an increased risk of infection in their close contacts (13.6%). Secondary cases were in general clinically milder and were less likely to have common symptoms than those of source cases.  In conclusion, the proportion of asymptomatic and mild infections account for almost half of the confirmed cases among close contacts. The household contacts were the main transmission mode, and clinically more severe cases were more likely to pass the infection to their close contacts. Generally, the secondary cases were clinically milder than those of source cases.

title: A model to forecast regional demand for COVID-19 related hospital beds
abstract: COVID-19 threatens to overwhelm hospital facilities throughout the United States. We created an interactive, quantitative model that forecasts demand for COVID-19 related hospitalization based on county-level population characteristics, data from the literature on COVID-19, and data from online repositories. Using this information as well as user inputs, the model estimates a time series of demand for intensive care beds and acute care beds as well as the availability of those beds. The online model is designed to be intuitive and interactive so that local leaders with limited technical or epidemiological expertise may make decisions based on a variety of scenarios. This complements high-level models designed for public consumption and technically sophisticated models designed for use by epidemiologists. The model is actively being used by several academic medical centers and policy makers, and we believe that broader access will continue to aid community and hospital leaders in their response to COVID-19. Link to online model: https://surf.stanford.edu/covid-19-tools/covid-19/

title: Atti del 52° Congresso Nazionale: Società Italiana di Igiene, Medicina Preventiva e Sanità Pubblica (SItI)

title: Indications for healthcare surge capacity in European countries facing an exponential increase in COVID19 cases
abstract: European healthcare systems face extreme pressure from COVID-19. We estimate such pressure by relating both country-specific accumulated COVID-19 deaths (intensity-approach) and active COVID-19 cases (magnitude-approach) to measures of healthcare system capacity: hospital beds, healthcare workers and healthcare expenditure. On March 25, 2020 - relative to Italy on March 11- we found Spain, The Netherlands and France to experience the highest pressure using the intensity-approach with a composite measure for healthcare capacity. For  see

title: Ability to replicate in the cytoplasm predicts zoonotic transmission of livestock viruses
abstract: Understanding viral factors that promote cross-species transmission is important for evaluating the risk of zoonotic emergence. Weconstructed a database of viruses of domestic artiodactyls and examined the correlation between traits linked in the literature to cross-species transmission and the ability of viruses to infect humans. Among these traits-genomic material, genome segmentation, and replication without nuclear entry-the last is the strongest predictor of cross-species transmission. This finding highlights nuclear entry as a barrier to transmission and suggests that the ability to complete replication in the cytoplasm may prove to be a useful indicator of the threat of cross-species transmission.

title: Is Nigeria prepared and ready to respond to the COVID-19 pandemic in its conflict-affected northeastern states?
abstract: Northeastern Nigeria has over the decade suffered from the Boko Haram insurgency and is still in the process of recovery from the complex humanitarian crisis that has displaced and subjected millions of vulnerable children, women and elderly population to poverty, disease outbreaks, hunger and malnutrition. Yet, the conflict-affected states in Northeastern Nigeria is not far away from being the worse-hit by the COVID-19 pandemic if urgent public health preventive measures are not taken to contain the spread of the deadly and highly infectious virus. The question arises, “what is Nigeria doing to tackle the burden of a COVID-19 spread and an ongoing humanitarian crisis?

title: iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking
abstract: With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results.

title: ‘Promoted by Hong Tao, the Chlamydia Hypothesis Had Become Well Established...': Understanding the 2003 Severe Acute Respiratory Syndrome (SARS) Epedemic - But Which One?
abstract: The aims of this chapter are twofold – first, to develop an understanding of the ways in which primary historical data come to be transformed across generations of popular science histories of emerging epidemics; and second, to develop an understanding of the ways in which those transformations impact on our ability to know what really happened during those epidemics.  The chapter begins with a rhetorical analysis of one particularly influential account of the 2003 severe acute respiratory syndrome (SARS) outbreak. Therein, we learn that the race to discover the outbreak's aetiology was tainted by scientific malpractice; that an esteemed Chinese microbiologist, Dr. Hong, apparently promoted his own, patently false, aetiological discovery, stifled debate on the matter and, in doing so, held the international response to the outbreak back by a number of weeks. But how was this account rhetorically constructed? And how did it engage with Dr. Hong's own research work?  Does Hong deserve to be remembered as an inept scientist? Subsequent accounts have been quick to repeat this one, founding text's account, suggesting that ‘yes, he does’. This chapter, however, returns to the primary data, examines the ways in which the original account troped those data and moves to suggest that ‘no, he does not’. Contributions to the field – Teasing out the more general implications of this particular case study, the chapter concludes with a discussion of the analytical gains that might accrue if other popular scientific histories of emerging epidemics were approached as ‘topics’ rather than ‘resources’.

title: Estimation in emerging epidemics: biases and remedies
abstract: When analysing new emerging infectious disease outbreaks, one typically has observational data over a limited period of time and several parameters to estimate, such as growth rate, the basic reproduction number R(0), the case fatality rate and distributions of serial intervals, generation times, latency and incubation times and times between onset of symptoms, notification, death and recovery/discharge. These parameters form the basis for predicting a future outbreak, planning preventive measures and monitoring the progress of the disease outbreak. We study inference problems during the emerging phase of an outbreak, and point out potential sources of bias, with emphasis on: contact tracing backwards in time, replacing generation times by serial intervals, multiple potential infectors and censoring effects amplified by exponential growth. These biases directly affect the estimation of, for example, the generation time distribution and the case fatality rate, but can then propagate to other estimates such as R(0) and growth rate. We propose methods to remove or at least reduce bias using statistical modelling. We illustrate the theory by numerical examples and simulations.

title: Viral Diseases
abstract: This chapter focuses on the naturally occurring viral diseases of rabbits. Poxviruses cause several important diseases in domestic and wild mammals and birds. Infection with poxviruses usually results in relatively mild disease involving the skin of the infected animals, however, generalized and often fatal disease may also occur, for example, in myxomatosis in rabbits. Close antigenic relationships exist among many poxviruses derived from different animal species. In spite of close antigenic relationships, the poxviruses of rabbits that produce distinct disease syndromes are discussed as separate entities. Virus of the genus Papillomavirus cause papillomas in various animal species and includes two rabbit viruses, the cottontail rabbit papillomavirus and the rabbit oral papillomavirus. The genus Polyomavirus contains one virus of rabbits, the rabbit kidney vacuolating virus. Papillomatosis of wild cottontail rabbits is characterized by the presence of horny warts, usually on the neck, shoulders, or abdomen. The warts begin as red raised areas at the site of infection, grow to become typical papillomas with rough rounded surfaces, and may later develop into large, keratinized horny growths. The rabbit kidney vacuolating virus was isolated in primary rabbit kidney cell cultures from papillomas of cottontail rabbits collected in Kansas. This virus causes vacuolar cytopathic effects in cell cultures. The virus resembles the cottontail rabbit (Shope) papil lomavirus but is a distinct virus. It does not produce papillomas when inoculated into rabbits and does not immunize rabbits against rabbit papillomavirus.

title: Insight into 2019 novel coronavirus — an updated intrim review and lessons from SARS-CoV and MERS-CoV
abstract: The rapid spread of the coronavirus disease 2019 (COVID-19), caused by a zoonotic beta-coronavirus entitled 2019 novel coronavirus (2019-nCoV), has become a global threat. Awareness of the biological features of 2019-nCoV should be updated in time and needs to be comprehensively summarized to help optimize control measures and make therapeutic decisions.  Based on recently published literatures, official documents and selected up-to-date preprint studies, we reviewed the virology and origin, epidemiology, clinical manifestations, pathology and treatment of 2019-nCoV infection, in comparison with severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV) infection.  The genome of 2019-nCoV partially resembled SARS-CoV and MERS-CoV, and indicating a bat origin. The COVID-19 generally had a high reproductive number, a long incubation period, a short serial interval and a low case fatality rate (much higher in patients with comorbidities) than SARS and MERS. Clinical presentation and pathology of COVID-19 greatly resembled SARS and MERS, with less upper respiratory and gastrointestinal symptoms, and more exudative lesions in post-mortems. Potential treatments included remdesivir, chloroquine, tocilizumab, convalescent plasma and vaccine immunization (when possible).  The initial experience from the current pandemic and lessons from the previous two pandemics can help improve future preparedness plans and combat disease progression.

title: The clinical and epidemiological features and hints of 82 confirmed COVID-19 pediatric cases aged 0-16 in Wuhan, China
abstract: Although COVID-19 pediatric patients just account for 1% of the overall cases, they are nonnegligible invisible infection sources. We quantitatively analyzed the clinical and epidemiological features of 82 confirmed cases aged 0-16 admitted to Wuhan Children's Hospital, which are expected to shed some lights onto the pediatric diagnosis and therapy.

title: Fighting the Coronavirus Outbreak

title: Using Digital Surveillance Tools for Near Real-Time Mapping of the Risk of International Infectious Disease Spread: Ebola as a Case Study
abstract: In our increasingly interconnected world, it is crucial to understand the risk of an outbreak originating in one country or region and spreading to the rest of the world. Digital disease surveillance tools such as ProMED and HealthMap have the potential to serve as important early warning systems as well as complement the field surveillance during an ongoing outbreak. Here we present a flexible statistical model that uses data produced from digital surveillance tools (ProMED and HealthMap) to forecast short term incidence trends in a spatially explicit manner. The model was applied to data collected by ProMED and HealthMap during the 2013-2016 West African Ebola epidemic. The model was able to predict each instance of international spread 1 to 4 weeks in advance. Our study highlights the potential and limitations of using publicly available digital surveillance data for assessing outbreak dynamics in real-time.

title: Analyzing Vaccine Trials in Epidemics With Mild and Asymptomatic Infection
abstract: Vaccine efficacy against susceptibility to infection (VE(S)), regardless of symptoms, is an important endpoint of vaccine trials for pathogens with a high proportion of asymptomatic infection, because such infections may contribute to onward transmission and long-term sequelae, such as congenital Zika syndrome. However, estimating VE(S) is resource-intensive. We aimed to identify approaches for accurately estimating VE(S) when limited information is available and resources are constrained. We modeled an individually randomized vaccine trial by generating a network of individuals and simulating an epidemic. The disease natural history followed a “susceptible-exposed-infectious/symptomatic (or infectious/asymptomatic)-recovered” model. We then used 7 approaches to estimate VE(S), and we also estimated vaccine efficacy against progression to symptoms (VE(P)). A corrected relative risk and an interval-censored Cox model accurately estimate VE(S) and only require serological testing of participants once, while a Cox model using only symptomatic infections returns biased estimates. Only acquiring serological endpoints in a 10% sample and imputing the remaining infection statuses yields unbiased VE(S) estimates across values of the basic reproduction number (R(0)) and accurate estimates of VE(P) for higher R(0) values. Identifying resource-preserving methods for accurately estimating VE(S) and VE(P) is important in designing trials for diseases with a high proportion of asymptomatic infection.

title: Innovative screening tests for COVID-19 in South Korea.
abstract: Recently, the number of Corona Virus Disease 2019 (COVID-19) cases has increased remarkably in South Korea, so the triage clinics and emergency departments (ED) are expected to be overcrowded with patients with presumed infection. As of March 21st, there was a total of 8,799 confirmed cases of COVID-19 and 102 related deaths in South Korea that was one of the top countries with high incidence rates . This sharp increase in infection is associated with 1) outbreaks in individual provinces, 2) deployment of rapid and aggressive screening tests, 3) dedicated healthcare staffs for virus screening tests, 4) quarantine inspection data transparency and accurate data reporting, and 5) public health lessons from previous Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) outbreaks. This commentary introduces innovative screening tests that are currently used in South Korea for COVID-19, e.g., Drive-Through and Walk-Through tests, and compare the advantages and disadvantages of both methods.

title: Synchronized travel restrictions across cities can be effective in COVID-19 control
abstract: Mobility control measures are of crucial importance for public health planning in combating the COVID-19 pandemic. Previous studies established the impact of population outflow from Wuhan on the spatial spread of coronavirus in China and hinted the impact of the other three mobility patterns, i.e., population outflow from Hubei province excluding Wuhan, population inflow from cities outside Hubei, and intra-city population movement. However, the overall impact of all mobility patterns, or the impact of the different timing of mobility restriction intervention, are not systematically analyzed. Here we apply the cumulative confirmed cases and mobility data of 350 Chinese cities outside Hubei to explore the relationships between all mobility patterns and epidemic spread, and estimate the impact of local travel restrictions, both in terms of level and timing, on the epidemic control based on mobility change. The relationships were identified by using Pearson correlation analysis and stepwise multivariable linear regression, while scenario simulation was used to estimate the mobility change caused by local travel restrictions. Our analysis shows that: (1) all mobility patterns correlated with the spread of the coronavirus in Chinese cities outside Hubei, while the corrleations droppd with the implemetation of travel restrictions; (2) the cumulative confirmed cases in two weeks after the Wuhan lockdown was mainly brought by three patterns of inter-city population movement, while those in the third and fourth weeks after was significantly influenced by the number of intra-city population movement; (3) the local travel restrictions imposed by cities outside Hubei have averted 1,960 (95%PI: 1,474-2,447) more infections, taking 22.4% (95%PI: 16.8%-27.9%) of confirmed ones, in two weeks after the Wuhan lockdown, while more synchronized implementation would further decrease the number of confirmed cases in the same period by 15.7% (95%PI:15.4%-16.0%) or 1,378 (95%PI: 1,353-1,402) cases; and (4) local travel restrictions on different mobility patterns have different degrees of protection on cities with or without initial confirmed cases until the Wuhan lockdown. Our results prove the effectiveness of local travel restrictions and highlight the importance of synchronized implementation of mobility control across cities in mitigating the COVID-19 transmission.

title: 2264. The Burden of Respiratory Viral Illness in HIV-Infected Patients
abstract: Among individuals living with human immunodeficiency virus (HIV), pulmonary complications are the most frequent cause of morbidity and mortality. Although bacterial and fungal pathogens are well-described etiologies of lung disease, the role of respiratory viruses remains poorly understood. We sought to describe the burden of respiratory viral illness in HIV-infected inpatients admitted to our tertiary care center.  All HIV-infected inpatients from August 2015 to March 2018 were approached if they presented with respiratory symptoms, defined as cough, dyspnea, sore throat, rhinorrhea, wheezing, or stridor. Eighty patients were enrolled. After obtaining informed consent, nasopharyngeal swabs and blood were collected. If the subject underwent bronchoscopy per the treating physician, excess bronchoalveolar lavage (BAL) sample was collected. Demographic and clinical data were recorded for each subject. Multiplex PCR testing of all respiratory samples was performed.  Of the 70 HIV-infected patients that have undergone complete analysis, 23 (33%) tested positive for respiratory viruses. Of these, 11 (48%) were positive for rhinovirus, 3 were positive for influenza A (13%), 2 for parainfluenza 3 (9%), 2 for coronavirus (9%), and one each tested positive for adenovirus, parainfluenza 4, respiratory syncytial virus and influenza B. One patient had co-infection with rhinovirus and human metapneumovirus. Patients infected with a respiratory virus had severe illness as nearly half (10/23; 48%) required intensive care, 5 (22%) required mechanical ventilation, 4 (17%) were discharged to a higher level of care, and 3 (13%) died.  The role of respiratory viruses on the lung health of HIV-infected patients is poorly defined. In this study, respiratory viruses were identified in over a third of HIV-infected inpatients, representing a substantial disease burden. Moreover, these patients demonstrated significant disease severity. Given these findings, there is a need for future studies of viral infections in HIV-infected individuals to elucidate mechanisms of susceptibility to reduce the burden of pulmonary morbidity in this vulnerable population.  No reported disclosures.

title: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in Children and Adolescents: A Systematic Review
abstract: The current rapid worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection justifies the global effort to identify effective preventive strategies and optimal medical management. While data are available for adult patients with coronavirus disease 2019 (COVID-19), limited reports have analyzed pediatric patients infected with SARS-CoV-2.  To evaluate currently reported pediatric cases of SARS-CoV-2 infection.  An extensive search strategy was designed to retrieve all articles published from December 1, 2019, to March 3, 2020, by combining the terms coronavirus and coronavirus infection in several electronic databases (PubMed, Cochrane Library, and CINAHL), and following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Retrospective cross-sectional and case-control studies, case series and case reports, bulletins, and national reports about the pediatric SARS-CoV-2 infection were included. The risk of bias for eligible observational studies was assessed according to the Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.  A total of 815 articles were identified. Eighteen studies with 1065 participants (444 patients were younger than 10 years, and 553 were aged 10 to 19 years) with confirmed SARS-CoV-2 infection were included in the final analysis. All articles reflected research performed in China, except for 1 clinical case in Singapore. Children at any age were mostly reported to have mild respiratory symptoms, namely fever, dry cough, and fatigue, or were asymptomatic. Bronchial thickening and ground-glass opacities were the main radiologic features, and these findings were also reported in asymptomatic patients. Among the included articles, there was only 1 case of severe COVID-19 infection, which occurred in a 13-month-old infant. No deaths were reported in children aged 0 to 9 years. Available data about therapies were limited.  To our knowledge, this is the first systematic review that assesses and summarizes clinical features and management of children with SARS-CoV-2 infection. The rapid spread of COVID-19 across the globe and the lack of European and US data on pediatric patients require further epidemiologic and clinical studies to identify possible preventive and therapeutic strategies.

title: Development and Evaluation of an AI System for COVID-19
abstract: Early detection of COVID-19 based on chest CT will enable timely treatment of patients and help control the spread of the disease. With rapid spreading of COVID-19 in many countries, however, CT volumes of suspicious patients are increasing at a speed much faster than the availability of human experts. Here, we propose an artificial intelligence (AI) system for fast COVID-19 diagnosis with an accuracy comparable to experienced radiologists. A large dataset was constructed by collecting 970 CT volumes of 496 patients with confirmed COVID-19 and 260 negative cases from three hospitals in Wuhan, China, and 1,125 negative cases from two publicly available chest CT datasets. Trained using only 312 cases, our diagnosis system, which is based on deep convolutional neural network, is able to achieve an accuracy of 94.98%, an area under the receiver operating characteristic curve (AUC) of 97.91%, a sensitivity of 94.06%, and a specificity of 95.47% on an independent external verification dataset of 1,255 cases. In a reader study involving five radiologists, only one radiologist is slightly more accurate than the AI system. The AI system is two orders of magnitude faster than radiologists and the code is available at https://github.com/ChenWWWeixiang/diagnosis_covid19.

title: The accuracy of nurses' estimates of their absenteeism
abstract: gaudine a & gregory c (2010) Journal of Nursing Management 18, 599–605 The accuracy of nurses' estimates of their absenteeism  The purpose of the present study was to determine the accuracy of nurses’ self‐reports of absence by examining: (1) the correlation, intra‐class correlation, and Cronbach’s alpha for self‐reported absence and absence as reported in organizational records, (2) difference in central tendency for the two measures of absence and (3) the percentage of nurses who underestimate their absence.  Research on nurses’ absenteeism has often relied on self‐reports of absence. However, nurses may not be aware of their actual absenteeism, or they may underestimate it.  Self‐reported absence from questionnaires completed by 215 Canadian nurses was compared with their absence from organizational records.  There is a strong positive correlation, a strong intra‐class correlation and Cronbach’s alpha for the two measures of absence. However, there is a difference in central tendency that is related to the majority of nurses in this study (51.1%) underestimating their days absent from work.  Research examining the predictors of absence may consider measuring absence with self‐reports. Nevertheless, nurses demonstrated a bias to underestimate their absence. Implications for nursing management Feedback interventions to reduce absenteeism can be developed to include providing nurses with accurate information about their absence.

title: Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study
abstract: Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described.  In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death.  191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days.  The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.  The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

title: Bat coronavirus phylogeography in the Western Indian Ocean
abstract: Bats provide key ecosystem services such as crop pest regulation, pollination, seed dispersal, and soil fertilization. Bats are also major hosts for biological agents responsible for zoonoses, such as coronaviruses (CoVs). The islands of the Western Indian Ocean are identified as a major biodiversity hotspot, with more than 50 bat species. In this study, we tested 1,013 bats belonging to 36 species from Mozambique, Madagascar, Mauritius, Mayotte, Reunion Island and Seychelles, based on molecular screening and partial sequencing of the RNA-dependent RNA polymerase gene. In total, 88 bats (8.7%) tested positive for coronaviruses, with higher prevalence in Mozambican bats (20.5% ± 4.9%) as compared to those sampled on islands (4.5% ± 1.5%). Phylogenetic analyses revealed a large diversity of α- and β-CoVs and a strong signal of co-evolution between CoVs and their bat host species, with limited evidence for host-switching, except for bat species sharing day roost sites. These results highlight that strong variation between islands does exist and is associated with the composition of the bat species community on each island. Future studies should investigate whether CoVs detected in these bats have a potential for spillover in other hosts.

title: Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach
abstract: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment.  The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China.  We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling.  After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively.  Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

title: Characteristics of COVID-19 infection in Beijing
abstract: Since the first case of a novel coronavirus (COVID-19) infection pneumonia was detected in Wuhan, China, a series of confirmed cases of the COVID-19 were found in Beijing. We analyzed the data of 262 confirmed cases to determine the clinical and epidemiological characteristics of COVID-19 in Beijing.  We collected patients who were transferred by Beijing Emergency Medical Service to the designated hospitals. The information on demographic, epidemiological, clinical, laboratory test for the COVID-19 virus, diagnostic classification, cluster case and outcome were obtained. Furthermore we compared the characteristics between severe and common confirmed cases which including mild cases, no-pneumonia cases and asymptomatic cases, and we also compared the features between COVID-19 and 2003 SARS.  By Feb 10, 2020, 262 patients were transferred from the hospitals across Beijing to the designated hospitals for special treatment of the COVID-19 infected by Beijing emergency medical service. Among of 262 patients, 46 (17.6%) were severe cases, 216 (82.4%) were common cases, which including 192 (73.3%) mild cases, 11(4.2%) non-pneumonia cases and 13 (5.0%) asymptomatic cases respectively. The median age of patients was 47.5 years old and 48.5% were male. 192 (73.3%) patients were residents of Beijing, 50 (26.0%) of which had been to Wuhan, 116 (60.4%) had close contact with confirmed cases, 21 (10.9%) had no contact history. The most common symptoms at the onset of illness were fever (82.1%), cough (45.8%), fatigue (26.3%), dyspnea (6.9%) and headache (6.5%). The median incubation period was 6.7 days, the interval time from between illness onset and seeing a doctor was 4.5 days. As of Feb 10, 17.2% patients have discharged and 81.7% patients remain in hospital in our study, the fatality of COVID-19 infection in Beijing was 0.9%.  On the basis of this study, we provided the ratio of the COVID-19 infection on the severe cases to the mild, asymptomatic and non-pneumonia cases in Beijing. Population was generally susceptible, and with a relatively low fatality rate. The measures to prevent transmission was very successful at early stage, the next steps on the COVID-19 infection should be focused on early isolation of patients and quarantine for close contacts in families and communities in Beijing. Funding Beijing Municipal Science and Technology Commission and Ministry of Science and Technology.

title: A spatial model to optimise predictions of COVID-19 incidence risk in Belgium using symptoms as reported in a large-scale online survey
abstract: Although COVID-19 has been spreading throughout Belgium since February, 2020, its spatial dynamics in Belgium remain poorly understood, due to the limited testing of suspected cases. We analyse data of COVID-19 symptoms, as self-reported in a weekly online survey, which is open to all Belgian citizens. We predict symptoms' incidence using binomial models for spatially discrete data, and we introduce these as a covariate in the spatial analysis of COVID-19 incidence, as reported by the Belgian government during the days following a survey round. The symptoms' incidence predictions explain a significant proportion of the variation in the relative risks based on the confirmed cases, and exceedance probability maps of the symptoms' incidence and the confirmed cases' relative risks pinpoint the same high-risk region. We conclude that these results can be used to develop public monitoring tools in scenarios with limited lab testing capacity, and to supplement test-based information otherwise.

title: Are antibodies tests accurate? Understanding predictive values and uncertainty of serology tests for the novel coronavirus.
abstract: Antibodies testing in the coronavirus era is frequently promoted, but the underlying statistics behind their validation has come under more scrutiny in recent weeks. We provide calculations, interpretations, and plots of positive and negative predictive values under a variety of scenarios. Prevalence, sensitivity, and specificity are estimated within ranges of values from researchers and antibodies manufacturers. Illustrative examples are highlighted, and interactive plots are provided in the Supplementary Material. Implications are discussed for society overall and across diverse locations with different levels of disease burden. Specifically, the proportion of positive serology tests that are false can differ drastically from up to 3% to 88% for people from different places with different proportions of infected people in the populations while the false negative rate is typically under 10%.

title: Knowledge and practice of preventive measures against COVID-19 infection among pregnant women in a low-resource African setting
abstract: Coronavirus disease pandemic has resulted in death of thousands of people across several countries. Several preventive measures have been recommended to halt the spread of the disease and its associated mortality. However, the level knowledge and practice of these preventive measures against COVID-19 infection among pregnant women, which constitute vulnerable groups, are yet to be evaluated.  To determine the knowledge and practice of preventive measures against COVID-19 infection among pregnant women in Abakaliki.  This was a self-administered questionnaire-based cross-sectional study conducted from February 1, 2020 to March 31, 2020 among 284 antenatal clinic attendees at Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Ebonyi State. A pretested and validated questionnaire was used to collect the data. Data analysis was done using SPSS version 22.  Of 284 participants, 60.9% (n=173) had adequate knowledge of the preventive measures against COVID-19 infection. However, the overall practice of these preventive measures among the participants were poor as 69.7% of the participants were not practicing the preventive measures against the coronavirus. The determinants of poor practice of the preventive measures among the participants were being in age group 31-40 years (AOR=2.04, 95%CI: 1.26 - 5.37, p=0.022), married (AOR=2.99, 95%CI: 1.40 - 6.33, p=0.035) grandmultiparous (AOR=3.11, 95%CI: 1.32 - 6.56, p=0.021), residing in rural area (AOR=2.08, 95%CI: 1.32 - 4.05, p=0.031), and having no formal education (AOR=6.73, 95%CI: 2.66 - 18.34, p=0.002).  The study showed that most of the participants had adequate knowledge of preventive measures against COVID-19 infection but the practice of these preventive measures were poor among the participants.

title: Crimean-Congo haemorrhagic fever in travellers: A systematic review
abstract: The recent Ebola epidemic has increased public awareness of the risk of travel associated viral haemorrhagic fever (VHF). International preparedness to manage imported cases Ebola virus infection was inadequate, highlighted by cases of nosocomial transmission. Crimean-Congo haemorrhagic fever (CCHF) is a re-emerging tick-borne VHF centred in the Eurasian region, affecting a large geographical area and with human-to-human transmission reported, especially in the healthcare setting.  To systematically review the characteristics of travel associated Crimean-Congo haemorrhagic fever.  A systematic review of travel-associated cases of CCHF was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement protocol. PubMed, SCOPUS, Science Citation Index (SCI) and ProMED databases were searched for reports published between January 1960 and January 2016. Three independent reviewers selected and reviewed studies and extracted data.  21 cases of travel associated CCHF were identified, of which 12 died (3 outcome unknown) and 4 secondary (nosocomial) infections were reported. Risk occupations or activities for CCHF infection were reported in 8/12 cases when data were available. Travel from Asia to Asia occurred in 9 cases, Africa to Africa occurred in 5 cases, Africa to Europe in 3 cases, Asia to Europe in 2 cases and Europe to Europe in 2 cases.  CCHF related to travel is rare, is generally associated with at risk activities/occupation and is frequently fatal. Key to early diagnosis and prevention of nosocomial transmission is an understanding of CCHF risk factors and the geographical distribution of CCHF. International travel to CCHF endemic areas is increasing and clinicians and laboratory personnel managing returning travellers should maintain a high index of suspicion.

title: Modelling the Effect of Area-deprivation on COVID-19 Incidences: A Study of Chennai Megacity, India
abstract: Socioeconomic inequalities may affect COVID-19 incidence. The goal of the research was to explore the association between deprivation of socioeconomic status (SES) and spatial patterns of COVID-19 incidence in Chennai megacity for unfolding the disease epidemiology.  Ecological (or contextual) study for electoral wards (sub-cities) of Chennai megacity.  Using data of confirmed COVID-19 cases from May 15, 2020, to May 21, 2020, for 155 electoral wards obtained from the official website of the Chennai municipal corporation, we examined the incidence of COVID-19 diseases using two count regression models namely, Poisson Regression (PR) and Negative Binomial Regression (NBR). As explanatory factors, we considered area-deprivation that represented the deprivation of socioeconomic status (SES). An index of multiple deprivations (IMD) developed to measure the area-deprivation using an advanced local statistic, Geographically Weighted Principal Component Analysis (GWPCA). Based on the availability of appropriately scaled data, five domains (i.e. poor housing condition, low asset possession, poor availability of WaSH services, lack of household amenities and services, and gender disparity) were selected as components of the IMD in this study.  The Hot-spot analysis revealed that area-deprivation was significantly associated with higher incidences of COVID-19 in Chennai megacity. The high variations (adj. R2: 72.2%) with the lower BIC (124.34) and AIC (112.12) for the NBR compared to PR suggests that the NBR model better explains the relationship between area-deprivation and COVID-19 incidences in Chennai megacity. NBR with two-sided tests, and p<0.05 was considered statistically significant. The outcome of the PR and NBR suggests that when all other variables were constant, according to NBR, the relative risk (RR) of COVID-19 incidences was 2.19 for the wards with high housing deprivation or in other words, the wards with high housing deprivation having 119% higher probability (RR= e0.786=2.19, 95% CI=1.98 to 2.40) compared to areas with low deprivation. Similarly, in the wards with poor availability of WaSH services, chances of having COVID-19 incidence was 90% higher compared to the wards with good WaSH services (RR= e0.642=1.90, 95% CI=1.79 to 2.00). Spatial risks of COVID-19 infections were predominantly concentrated in the wards with higher levels of area-deprivation which were mostly located in the north-eastern parts of Chennai megacity.  We formulated an area-based IMD, which was substantially related to COVID-19 incidences in the Chennai megacity. This study highlights that the risks of COVID-19 infections tend to be higher in more deprived areas of SES and the north-eastern part of Chennai megacity was predominantly high-risk areas. Our results can guide measures of COVID-19 control and prevention by considering spatial risks and area-deprivation.

title: Fatalism in the context of COVID-19: Perceiving coronavirus as a death sentence predicts reluctance to perform recommended preventative behaviors()
abstract: To manage the spread of coronavirus, health entities have urged the public to take preventative measures such as social distancing and handwashing. Yet, many appear reluctant to take these measures. Research is needed to understand factors underlying such reluctance, with the aim of developing targeted health interventions. We identify associating coronavirus with death as one such factor. 590 participants completed surveys in mid-March 2020, which included attitudes toward coronavirus, preventative behavioral intentions, and sociodemographic factors. Associating coronavirus with death negatively predicted intentions to perform preventative behaviors. Further, associating coronavirus with death was not evenly distributed throughout the sample and was related with a number of sociodemographic factors including age, race, and availability of sick leave. Following recommended preventative measures to slow the spread of coronavirus appears to relate to the degree to which people associate coronavirus with death. These findings can be used by public health researchers and practitioners to identify those for whom targeted health communication and interventions would be most beneficial, as well as to frame health messaging in ways that combat fatalism.

title: [Epidemic trend of corona virus disease 2019 (COVID-19) in mainland China].
abstract: In order to master the epidemic trend of corona virus disease 2019 (COVID-19) and evaluate the effect of prevention and control, we evaluate the epidemic dynamics of COVID-19 in mainland China, Hubei province, Wuhan city and other provinces outside Hubei from January 16 to February 14, 2020.  We collected the daily number of new confirmed COVID-19 cases by nucleic acid detection reported by the National Health Commission from January 16, 2020 to February 14, 2020. The analysis includes the epidemic curve of the new confirmed cases, multiple of the new confirmed cases for period-over-period, multiple of the new confirmed cases for fixed-base, and the period-over-period growth rate of the new confirmed cases.  From January 16 to February 14, 2020, the cumulative number of new confirmed cases of COVID-19 in mainland China was 50 031, including 37 930 in Hubei province, 22 883 in Wuhan city and 12 101 in other provinces outside Hubei. The peak of the number of new confirmed cases in other provinces outside Hubei was from January 31 to February 4, 2020, and the peak of new confirmed cases in Wuhan city and Hubei province was from February 5 to February 9, 2020. The number of new confirmed cases in other provinces outside Hubei showed a significant decline (23% compared with the peak) from February 5 to February 9, 2020, while the number of new confirmed cases in Wuhan city (30% compared with the peak) and Hubei Province (37% compared with the peak) decreased significantly from February 10 to February 14, 2020.  The epidemic prevention and control measures taken by the state and governments at all levels have shown very significant effects, effectively curbing the spread of the COVID-19 epidemic in China.

title: Letter to the editor: Headline stress disorder caused by Netnews during the outbreak of COVID‐19

title: Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study
abstract: The coronavirus disease (COVID-19) pandemic is a global health emergency with over 6 million cases worldwide as of the beginning of June 2020. The pandemic is historic in scope and precedent given its emergence in an increasingly digital era. Importantly, there have been concerns about the accuracy of COVID-19 case counts due to issues such as lack of access to testing and difficulty in measuring recoveries.  The aims of this study were to detect and characterize user-generated conversations that could be associated with COVID-19-related symptoms, experiences with access to testing, and mentions of disease recovery using an unsupervised machine learning approach.  Tweets were collected from the Twitter public streaming application programming interface from March 3-20, 2020, filtered for general COVID-19-related keywords and then further filtered for terms that could be related to COVID-19 symptoms as self-reported by users. Tweets were analyzed using an unsupervised machine learning approach called the biterm topic model (BTM), where groups of tweets containing the same word-related themes were separated into topic clusters that included conversations about symptoms, testing, and recovery. Tweets in these clusters were then extracted and manually annotated for content analysis and assessed for their statistical and geographic characteristics.  A total of 4,492,954 tweets were collected that contained terms that could be related to COVID-19 symptoms. After using BTM to identify relevant topic clusters and removing duplicate tweets, we identified a total of 3465 (<1%) tweets that included user-generated conversations about experiences that users associated with possible COVID-19 symptoms and other disease experiences. These tweets were grouped into five main categories including first- and secondhand reports of symptoms, symptom reporting concurrent with lack of testing, discussion of recovery, confirmation of negative COVID-19 diagnosis after receiving testing, and users recalling symptoms and questioning whether they might have been previously infected with COVID-19. The co-occurrence of tweets for these themes was statistically significant for users reporting symptoms with a lack of testing and with a discussion of recovery. A total of 63% (n=1112) of the geotagged tweets were located in the United States.  This study used unsupervised machine learning for the purposes of characterizing self-reporting of symptoms, experiences with testing, and mentions of recovery related to COVID-19. Many users reported symptoms they thought were related to COVID-19, but they were not able to get tested to confirm their concerns. In the absence of testing availability and confirmation, accurate case estimations for this period of the outbreak may never be known. Future studies should continue to explore the utility of infoveillance approaches to estimate COVID-19 disease severity.

title: Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China
abstract: As an emerging infectious disease, the 2019 coronavirus disease (COVID-19) has developed into a global pandemic. During the initial spreading of the virus in China, we demonstrated the ensemble Kalman filter performed well as a short-term predictor of the daily cases reported in Wuhan City. Second, we used an individual-level network-based model to reconstruct the epidemic dynamics in Hubei Province at its early stage and examine the effectiveness of non-pharmaceutical interventions on the epidemic spreading with various scenarios. Our simulation results show that without continued control measures, the epidemic in Hubei Province could have become persistent. Only by continuing to decrease the infection rate through 1) protective measures and 2) social distancing can the actual epidemic trajectory that happened in Hubei Province be reconstructed in simulation. Finally, we simulate the COVID-19 transmission with non-Markovian processes and show how these models produce different epidemic trajectories, compared to those obtained with Markov processes. Since recent studies show that COVID-19 epidemiological parameters do not follow exponential distributions leading to Markov processes, future works need to focus on non-Markovian models to better capture the COVID-19 spreading trajectories. In addition, shortening the infectious period via early case identification and isolation can slow the epidemic spreading significantly.

title: Extrapolation of Infection Data for the CoVid-19 Virus and Estimate of the Pandemic Time Scale.
abstract: Predictions about the further development of the Corona pandemic are widely diverging. Here, a simple yet powerful algorithm is introduced for extrapolating infection rate and number of total infections from available data. The calculation predicts that under present conditions the infection rate in Germany will culminate in a few weeks and decrease to low values by mid-June 2020. Total number of infections will reach several 100,000 though.

title: Modelling the evolution of COVID-19 in high-incidence European countries and regions: estimated number of infections and impact of past and future intervention measures
abstract: A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease had major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcome. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the afterwards reproduction number from current study. More challenging is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help planning changes in the implementation of control measures in a given country or region.

title: Infectious Disease Outbreak Response: Mind the Rights Gap
abstract: The international organization responsible for international coordinated response to disease outbreaks—the World Health Organization (WHO)—was given permission to receive reports from sources other than the state in revisions to the International Health Regulations (IHR) in 2005. However, the organization struggles to protect its corresponding right to receive reports from non-state actors on outbreak events. This article examines the consequences of this implementation gap between what is stated in the IHR—the right of WHO to receive reports from non-state actors on outbreak events—and the reality that states remain able and willing to act to ensure that this right is not exercised. The article examines two recent cases: the first detection of Middle East Respiratory Syndrome (MERS) outbreak in Saudi Arabia, and the first months of the Ebola outbreak in Guinea. Both cases demonstrate how the WHO has struggled to balance states’ concern with managing risk communication against WHO’s right to receive reports from non-state actors. The article argues that to realize the full potential of a transparent disease outbreak reporting process, there is a need for a human rights framework that expressly articulates its right to receive reports and outlines appropriate behaviour for the WHO, states, and non-state actors.

title: Understanding Economic and Health Factors Impacting the Spread of COVID-19 Disease
abstract: The rapid spread of the Coronavirus 2019 disease (COVID-19) had drastically impacted life all over the world. While some economies are actively recovering from this pestilence, others are experiencing fast and consistent disease spread, compelling governments to impose social distancing measures that have put a halt on routines, especially in densely-populated areas. Aiming at bringing more light on key economic and public health factors affecting the disease spread, this initial study utilizes a quantitative statistical analysis based on the most recent publicly-available COVID-19 datasets. The study had shown and explained multiple significant relationships between the COVID-19 data and other country-level statistics. We have also identified and statistically profiled four major country-level clusters with relation to different aspects of COVID-19 development and country-level economic and health indicators. Specifically, this study has identified potential COVID-19 under-reporting traits as well as various economic factors that impact COVID-19 Diagnosis, Reporting, and Treatment. Based on the country clusters, we have also described the four disease development scenarios, which are tightly knit to country-level economic and public health factors. Finally, we have highlighted the potential limitation of reporting and measuring COVID-19 and provided recommendations on further in-depth quantitative research.

title: COVID-19: Unique public health issues facing Black, Asian and minority ethnic communities
abstract: The 2019 coronavirus disease is a serious public health emergency, with serious adverse implications for populations, healthcare systems, and economies globally. Recently, concerns have been raised about possible association between ethnicity, incidence and outcomes of COVID-19 arisen from early government data. In this review, we will explore the possible association using both recent COVID-19 studies and studies of previous pandemics. We call for data on ethnicity to be routinely collected by governments, as part of international collaboration, alongside other patient demographics and further research to robustly determine magnitude of association. Moreover, governments must learn from previous pandemics and recommended strategies to mitigate risks on minority ethnicities due to socioeconomic disadvantages.

title: Early epidemiological assessment of the transmission potential and virulence of coronavirus disease 2019 (COVID-19) in Wuhan City: China, January-February, 2020
abstract: Since the first cluster of cases was identified in Wuhan City, China, in December, 2019, coronavirus disease 2019 (COVID-19) has rapidly spread across China, causing multiple introductions in 109 countries/territories/areas as of March 10th. Despite the scarcity of publicly available data, scientists around the world have made strides in estimating the magnitude of the epidemic, the basic reproduction number, and transmission patterns. Recently more evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which suggest the need to reassess the transmission potential of this emerging disease. In this study, we derive estimates of the transmissibility and virulence of COVID-19 in Wuhan City, China, by reconstructing the underlying transmission dynamics using multiple data sources.  We employ statistical methods and publicly available epidemiological datasets to jointly derive estimates of transmissibility and severity associated with the novel coronavirus. For this purpose, the daily series of laboratory-confirmed COVID-19 cases and deaths in Wuhan City and epidemiological data of Japanese evacuees from Wuhan City on board government-chartered flights were integrated into our analysis.  Our posterior estimates of basic reproduction number (R) in Wuhan City, China in 2019-2020 reached values as high as 5.20 (95%CrI: 5.04-5.47) and the enhanced public health intervention after January 23rd in 2020 was associated with a declined R at 0.58 (95%CrI: 0.51-0.64), with the total number of infections (i.e. cumulative infections) estimated at 1905526 (95%CrI: 1350283-2655936) in Wuhan City, raising the proportion of infected individuals to 19.1% (95%CrI: 13.5-26.6%). We also found that most recent crude infection fatality ratio (IFR) and time-delay adjusted IFR is estimated to be 0.04% (95% CrI: 0.03-0.06%) and 0.12% (95%CrI: 0.08-0.17%), which is several orders of magnitude smaller than the crude CFR estimated at 4.19%  We have estimated key epidemiological parameters of the transmissibility and virulence of COVID-19 in Wuhan, China during January-February, 2020 using an ecological modelling approach. The power of our approach lies in the ability to infer epidemiological parameters with quantified uncertainty from partial observations collected by surveillance systems.

title: Anticoagulation Practice Patterns in COVID‐19: A Global Survey
abstract: Best practice for prevention, diagnosis, and management of venous thromboembolism (VTE) in patients with SARS‐CoV‐2 disease 2019 (COVID‐19) is unknown due to limited published data in this population.  We aimed to assess current global practice and experience in management of COVID‐19 associated coagulopathy to identify information to guide prospective and randomized studies.  Physicians were queried about their current approach to prophylaxis, diagnosis, and treatment of VTE in patients with COVID‐19 using an online survey tool distributed through multiple international organizations between April 10 and 14, 2020.  515 physicians responded from 41 countries. The majority of respondents (78%) recommended prophylactic anticoagulation for all hospitalized patients with COVID‐19 with most recommending use of low‐molecular‐weight heparin or unfractionated heparin. Significant practice variation was found regarding need for dose escalation of anticoagulation outside the setting of confirmed or suspected VTE. Respondents reported the use of bedside testing when unable to perform standard diagnostic imaging for diagnosis of VTE. 291 respondents reported observing thrombotic complications in their patients with 64% noting that the complication was pulmonary embolism (PE). Of the 44% of respondents that estimated incidence of thrombosis in patients with COVID‐19 in their hospital, estimates ranged widely from 1 to 50%. 174 respondents noted bleeding complications (34% minor bleeding, 14% clinically relevant non‐major bleeding, and 12% major bleeding).  Well‐designed epidemiologic studies are urgently needed to understand the incidence and risk factors of VTE and bleeding complications in COVID‐19 patients. Randomized clinical trials addressing use of anticoagulation are also needed.

title: First known person-to-person transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the USA
abstract: Coronavirus disease 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in China in December, 2019. In January, 2020, state, local, and federal public health agencies investigated the first case of COVID-19 in Illinois, USA.  Patients with confirmed COVID-19 were defined as those with a positive SARS-CoV-2 test. Contacts were people with exposure to a patient with COVID-19 on or after the patient's symptom onset date. Contacts underwent active symptom monitoring for 14 days following their last exposure. Contacts who developed fever, cough, or shortness of breath became persons under investigation and were tested for SARS-CoV-2. A convenience sample of 32 asymptomatic health-care personnel contacts were also tested.  Patient 1—a woman in her 60s—returned from China in mid-January, 2020. One week later, she was hospitalised with pneumonia and tested positive for SARS-CoV-2. Her husband (Patient 2) did not travel but had frequent close contact with his wife. He was admitted 8 days later and tested positive for SARS-CoV-2. Overall, 372 contacts of both cases were identified; 347 underwent active symptom monitoring, including 152 community contacts and 195 health-care personnel. Of monitored contacts, 43 became persons under investigation, in addition to Patient 2. These 43 persons under investigation and all 32 asymptomatic health-care personnel tested negative for SARS-CoV-2.  Person-to-person transmission of SARS-CoV-2 occurred between two people with prolonged, unprotected exposure while Patient 1 was symptomatic. Despite active symptom monitoring and testing of symptomatic and some asymptomatic contacts, no further transmission was detected.

title: Chest CT in patients suspected of COVID-19 infection: A reliable alternative for RT-PCR

title: Clinical Characteristics of Coronavirus Pneumonia 2019 (COVID-19): An Updated Systematic Review
abstract: Clinical characteristics of novel coronavirus pneumonia (COVID-19) have been described in numerous studies but yielded varying results. We aimed to conduct a systematic review on scientific literatures and to synthesize critical data on clinical traits of COVID-19 from its initial outbreak to pandemic.  Systematic searches were conducted to identify retrospective observational study that contained clinical characteristics on COVID-19 through multiple databases. Two reviewers independently evaluated eligible publications. Data on clinical characteristics of COVID-19 were extracted and analyzed.  Seventy-two retrospective studies demonstrating the clinical characteristics of COVID-19 were included. A total of 3470 COVID-19 patients were synthesized to the final analysis in an unbiased manner. The most common symptom was fever (2878 [83.0%]), and 63.4% of the patients presented fever as onset symptom. There were 2528 [88.2%] of 2866 cases had abnormal lung findings on chest CT scan. Laboratory findings showed that 1498 [62.8%] of 2387 cases had lymphopenia, and 1354 [64.8%] of 2091 cases had an increased level of C-reactive protein (CRP). A total of 185 [11.5%] patients were admitted to intensive care unit (ICU) while the overall case fatality rate (CFR) was 3.7%. Compared to patients admitted outside of Hubei, China, those from Hubei had a significant higher ICU admission rate (21.9% vs. 2.5%, p<0.001). Also, CFR attributed to COVID-19 was significantly higher in Hubei than that of non-Hubei admissions (10.4% vs. 0.6%, p<0.001).  This large patient-based systematic review presents a more precise profiling of the COVID-19 from its outbreak to current pandemic. Dynamic evolvements of COVID-19 are needed to be characterized in future studies.

title: The response of Milan's Emergency Medical System to the COVID-19 outbreak in Italy

title: Rapid and accurate identification of COVID-19 infection through machine learning based on clinical available blood test results
abstract: Since the sudden outbreak of coronavirus disease 2019 (COVID-19), it has rapidly evolved into a momentous global health concern. Due to the lack of constructive information on the pathogenesis of COVID-19 and specific treatment, it highlights the importance of early diagnosis and timely treatment. In this study, 11 key blood indices were extracted through random forest algorithm to build the final assistant discrimination tool from 49 clinical available blood test data which were derived by commercial blood test equipments. The method presented robust outcome to accurately identify COVID-19 from a variety of suspected patients with similar CT information or similar symptoms, with accuracy of 0.9795 and 0.9697 for the cross-validation set and test set, respectively. The tool also demonstrated its outstanding performance on an external validation set that was completely independent of the modeling process, with sensitivity, specificity, and overall accuracy of 0.9512, 0.9697, and 0.9595, respectively. Besides, 24 samples from overseas infected patients with COVID-19 were used to make an in-depth clinical assessment with accuracy of 0.9167. After multiple verification, the reliability and repeatability of the tool has been fully evaluated, and it has the potential to develop into an emerging technology to identify COVID-19 and lower the burden of global public health. The proposed tool is well-suited to carry out preliminary assessment of suspected patients and help them to get timely treatment and quarantine suggestion. The assistant tool is now available online at http://lishuyan.lzu.edu.cn/COVID2019_2/.

title: ACE2 receptor polymorphism: susceptibility to SARS-CoV-2, hypertension, multi-organ failure, and COVID-19 disease outcome
abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged in Chinese people in December 2019 and has currently spread worldwide causing the COVID-19 pandemic with more than 150,000 deaths. In order for a SARS-CoV like virus circulating in wild life for a very long time to infect the index case-patient, a number of conditions must be met, foremost among which is the encounter with humans and the presence in homo sapiens of a cellular receptor allowing the virus to bind. Recently it was shown that the SARS-CoV-2 spike protein, binds to the human angiotensin I converting enzyme 2 (ACE2). This molecule is a peptidase expressed at the surface of lung epithelial cells and other tissues, that regulates the renin-angiotensin-aldosterone system. Humans are not equal with respect to the expression levels of the cellular ACE2. Moreover, ACE2 polymorphisms were recently described in human populations. Here we review the most recent evidence that ACE2 expression and/or polymorphism could influence both the susceptibility of people to SARS-CoV-2 infection and the outcome of the COVID-19 disease. Further exploration of the relationship between the virus, the peptidase function of ACE2 and the levels of angiotensin II in SARS-CoV-2 infected patients should help to better understand the pathophysiology of the disease and the multi-organ failures observed in severe COVID-19 cases, particularly heart failure.

title: Decrease in Hospital Admissions for Transient Ischemic Attack, Mild, and Moderate Stroke During the COVID-19 Era
abstract: Since the onset of the coronavirus 2019 (COVID-19) pandemic, doctors and public authorities have demonstrated concern about the reduction in quality of care for other health conditions due to social restrictions and lack of resources. Using a population-based stroke registry, we investigated the impact of the onset of the COVID-19 pandemic in stroke admissions in Joinville, Brazil.  Patients admitted after the onset of COVID-19 restrictions in the city (defined as March 17, 2020) were compared with those admitted in 2019. We analyzed differences between stroke incidence, types, severity, reperfusion therapies, and time from stroke onset to admission. Statistical tests were also performed to compare the 30 days before and after COVID-19 to the same period in 2019.  We observed a decrease in total stroke admissions from an average of 12.9/100 000 per month in 2019 to 8.3 after COVID-19 (P=0.0029). When compared with the same period in 2019, there was a 36.4% reduction in stroke admissions. There was no difference in admissions for severe stroke (National Institutes of Health Stroke Scale score >8), intraparenchymal hemorrhage, and subarachnoid hemorrhage.  The onset of COVID-19 was correlated with a reduction in admissions for transient, mild, and moderate strokes. Given the need to prevent the worsening of symptoms and the occurrence of medical complications in these groups, a reorganization of the stroke-care networks is necessary to reduce collateral damage caused by COVID-19.

title: COVID-19 and ischemic stroke: a systematic review and meta-summary of the literature
abstract: Acute ischemic stroke (AIS) is a life-threatening complication of coronavirus disease 2019 (COVID-19) infection. Increasing reports suggest an association between COVID-19 and AIS, although the underlying mechanism remains uncertain. We performed a systematic review to characterize the clinical characteristics, neuroimaging findings, and outcomes of AIS in COVID-19 patients. A literature search was performed in PubMed and Embase using a suitable keyword search strategy from 1st December 2019 to 29th May 2020. All studies reporting AIS occurrence in COVID-19 patients were included. A total of 39 studies comprising 135 patients were studied. The pooled incidence of AIS in COVID-19 patients from observational studies was 1.2% (54/4466) with a mean age of 63.4 ± 13.1 years. The mean duration of AIS from COVID-19 symptoms onset was 10 ± 8 days, and the mean NIHSS score was 19 ± 8. Laboratory investigations revealed an elevated mean d-dimer (9.2 ± 14.8 mg/L) and fibrinogen (5.8 ± 2.0 g/L). Antiphospholipid antibodies were detected in a significant number of cases. The majority of AIS neuroimaging patterns observed was large vessel thrombosis, embolism or stenosis (62.1%, 64/103), followed by multiple vascular territory (26.2%, 27/103). A high mortality rate was reported (38.0%, 49/129). We report the pooled incidence of AIS in COVID-19 patients to be 1.2%, with a high mortality rate. Elevated d-dimer, fibrinogen and the presence of antiphospholipid antibodies appear to be prominent in COVID-19 patients with concomitant AIS, but further mechanistic studies are required to elucidate their role in pathogenesis.

title: A mathematical model for the spatiotemporal epidemic spreading of COVID19
abstract: An outbreak of a novel coronavirus, named SARS-CoV-2, that provokes the COVID-19 disease, was first reported in Hubei, mainland China on 31 December 2019. As of 20 March 2020, cases have been reported in 166 countries/regions, including cases of human-to-human transmission around the world. The proportions of this epidemics is probably one of the largest challenges faced by our interconnected modern societies. According to the current epidemiological reports, the large basic reproduction number, R_0 ~ 2.3, number of secondary cases produced by an infected individual in a population of susceptible individuals, as well as an asymptomatic period (up to 14 days) in which infectious individuals are undetectable without further analysis, pave the way for a major crisis of the national health capacity systems. Recent scientific reports have pointed out that the detected cases of COVID19 at young ages is strikingly short and that lethality is concentrated at large ages. Here we adapt a Microscopic Markov Chain Approach (MMCA) metapopulation mobility model to capture the spread of COVID-19. We propose a model that stratifies the population by ages, and account for the different incidences of the disease at each strata. The model is used to predict the incidence of the epidemics in a spatial population through time, permitting investigation of control measures. The model is applied to the current epidemic in Spain, using the estimates of the epidemiological parameters and the mobility and demographic census data of the national institute of statistics (INE). The results indicate that the peak of incidence will happen in the first half of April 2020 in absence of mobility restrictions. These results can be refined with improved estimates of epidemiological parameters, and can be adapted to precise mobility restrictions at the level of municipalities. The current estimates largely compromises the Spanish health capacity system, in particular that for intensive care units, from the end of March. However, the model allows for the scrutiny of containment measures that can be used for health authorities to forecast with accuracy their impact in prevalence of COVID--19. Here we show by testing different epidemic containment scenarios that we urge to enforce total lockdown to avoid a massive collapse of the Spanish national health system.

title: Covid-19: GPs can stop health checks for over 75s and routine medicine reviews
abstract: GPs can stop or postpone some routine work to free them up to deal with covid-19, NHS England and NHS Improvement has said In a letter sent to GPs and commissioners Nikita Kanani, medical director for primary care, and Ed Waller, director of primary care strategy, set out a list of activities that GPs could stop doing or postpone 1 It included health checks for people over 75, which it said GPs could stop doing “if in their judgment that is not the right priority ” The letter also said that routine medical reviews could be deferred until October if necessary, “unless they can be viably conducted remotely and/or in exceptional cases in person or by home visit as per local clinical discretion ” Key medicine reviews where a patient is being regularly monitored should continue, it advised The letter added that practices’ Quality Outcomes Framework (QOF) income in 2020-21 would be protected “as necessary to respond to covid-19” and that one-off adjustments would be made for practices that earned less from QOF payments in 2019-20 than in 2018-19 as a result of covid-19 activities However, practices would be asked to consider stopping any private work they were doing to help free up capacity, the letter said

title: Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods
abstract: A major open question, affecting the policy makers decisions, is the estimation of the true size of COVID-19 infections. Most of them are undetected, because of a large number of asymptomatic cases. We provide an efficient, easy to compute and robust lower bound estimator for the number of undetected cases. A "modified" version of the Chao estimator is proposed, based on the cumulative time-series distribution of cases and deaths. Heterogeneity has been accounted for by assuming a geometrical distribution underlying the data generation process. An (approximated) analytical variance formula has been properly derived to compute reliable confidence intervals at 95%. An application to Austrian situation is provided and results from other European Countries are mentioned in the discussion.

title: Perspectives on the death investigation during the COVID-19 pandemic
abstract: The pandemic of COVID-19 caused by 2019-nCoV outbreaks in most of the countries, which has subsequently spread rapidly and become a pandemic worldwide. Due to the strong infectivity of COVID-19 and lack of experience of performing an autopsy to infectious disease-induced death, the pandemic created some challenges for forensic practitioners. In this article, we summarize the experience of how we handle the confirmed or suspected infectious cases, and give some perspectives for the future.

title: Interspecies transmission and emergence of novel viruses: lessons from bats and birds
abstract: As exemplified by coronaviruses and influenza viruses, bats and birds are natural reservoirs for providing viral genes during evolution of new virus species and viruses for interspecies transmission. These warm-blooded vertebrates display high species biodiversity, roosting and migratory behavior, and a unique adaptive immune system, which are favorable characteristics for asymptomatic shedding, dissemination, and mixing of different viruses for the generation of novel mutant, recombinant, or reassortant RNA viruses. The increased intrusion of humans into wildlife habitats and overcrowding of different wildlife species in wet markets and farms have also facilitated the interspecies transmission between different animal species.

title: Coronavirus epidemic and geriatric mental healthcare in China: how a coordinated response by professional organizations helped older adults during an unprecedented crisis

title: Innovative screening tests for COVID-19 in South Korea
abstract: Recently, the number of Corona Virus Disease 2019 (COVID-19) cases has increased remarkably in South Korea, so the triage clinics and emergency departments (ED) are expected to be overcrowded with patients with presumed infection. As of March 21st, there was a total of 8,799 confirmed cases of COVID-19 and 102 related deaths in South Korea that was one of the top countries with high incidence rates . This sharp increase in infection is associated with 1) outbreaks in individual provinces, 2) deployment of rapid and aggressive screening tests, 3) dedicated healthcare staffs for virus screening tests, 4) quarantine inspection data transparency and accurate data reporting, and 5) public health lessons from previous Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) outbreaks. This commentary introduces innovative screening tests that are currently used in South Korea for COVID-19, e.g., Drive-Through and Walk-Through tests, and compare the advantages and disadvantages of both methods.

title: SARS-CoV-2 Isolation and Propagation from Turkish COVID-19 patients
abstract: The novel coronavirus pneumonia, which was named later as Coronavirus Disease 2019 (COVID-19), is caused by the Severe Acute Respiratory Syndrome Coronavirus 2, namely SARS-CoV-2. It is a positive-strand RNA virus that is the seventh coronavirus known to infect humans. The COVID-19 outbreak presents enormous challenges for global health behind the pandemic outbreak. The first diagnosed patient in Turkey has been reported by the Republic of Turkey Ministry of Health on March 11, 2020. Today, over ninety thousand cases in Turkey, and two million cases around the world have been declared. Due to the urgent need for vaccine and anti-viral drug, isolation of the virus is crucial. Here, we report one of the first isolation and characterization studies of SARS-CoV-2 from nasopharyngeal and oropharyngeal specimens of diagnosed patients in Turkey. This study provides an isolation and replication methodology, and cell culture tropism of the virus that will be available to the research communities.  Scientists have isolated virus from Turkish COVID-19 patients. The isolation, propagation, and plaque and immune response assays of the virus described here will serve in following drug discovery and vaccine testing.

title: Localization to the nucleolus is a common feature of coronavirus nucleoproteins, and the protein may disrupt host cell division.
abstract: The subcellular localization of transmissible gastroenteritis virus (TGEV) and mouse hepatitis virus (MHV) (group I and group II coronaviruses, respectively) nucleoproteins (N proteins) were examined by confocal microscopy. The proteins were shown to localize either to the cytoplasm alone or to the cytoplasm and a structure in the nucleus. This feature was confirmed to be the nucleolus by using specific antibodies to nucleolin, a major component of the nucleolus, and by confocal microscopy to image sections through a cell expressing N protein. These findings are consistent with our previous report for infectious bronchitis virus (group III coronavirus) (J. A. Hiscox et al.,  2001), indicating that nucleolar localization of the N protein is a common feature of the coronavirus family and is possibly of functional significance. Nucleolar localization signals were identified in the domain III region of the N protein from all three coronavirus groups, and this suggested that transport of N protein to the nucleus might be an active process. In addition, our results suggest that the N protein might function to disrupt cell division. Thus, we observed that approximately 30% of cells transfected with the N protein appeared to be undergoing cell division. The most likely explanation for this is that the N protein induced a cell cycle delay or arrest, most likely in the G(2)/M phase. In a fraction of transfected cells expressing coronavirus N proteins, we observed multinucleate cells and dividing cells with nucleoli (which are only present during interphase). These findings are consistent with the possible inhibition of cytokinesis in these cells.

title: iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking
abstract: Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks.

title: Serologic and behavioral risk survey of workers with wildlife contact in China
abstract: We report on a study conducted in Guangdong Province, China, to characterize behaviors and perceptions associated with transmission of pathogens with pandemic potential in highly exposed human populations at the animal-human interface. A risk factor/exposure survey was administered to individuals with high levels of exposure to wildlife. Serological testing was performed to evaluate prior infection with several wildlife viral pathogens. Follow up serology was performed on a subset of the cohort as well as close contacts of individuals. 1,312 individuals were enrolled in the study. Contact with a wide range of wildlife species was reported in both occupational and occasional contexts. The overall proportion of individuals seropositive to any of the tested wildlife pathogens was approximately 4.0%. However, persons employed as butchers demonstrated a seropositivity of 9.0% to at least one pathogen of interest. By contrast, individuals working as hunters had lower rates of seropositivity. Among the study population, a number of other behaviors showed correlation with seropositivity, including contact with particular wildlife species such as field rats. These results demonstrate the need to further explore zoonotic risks of particular activities regarding wildlife contact, and to better understand risks of persons working as butchers with wildlife species.

title: Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study
abstract: The first case of COVID-19 atypical pneumonia was reported in Wuhan, China on December 1, 2019. Since then, at least 33 other countries have been affected and there is a possibility of a global outbreak. A tremendous amount of effort has been made to understand its transmission dynamics; however, the temporal and spatial transmission heterogeneity and changing epidemiology have been mostly ignored. The epidemic mechanism of COVID-19 remains largely unclear.  Epidemiological data on COVID-19 in China and daily population movement data from Wuhan to other cities were obtained and analyzed. To describe the transmission dynamics of COVID-19 at different spatio-temporal scales, we used a three-stage continuous-time Susceptible-Exposed-Infectious-Recovered (SEIR) meta-population model based on the characteristics and transmission dynamics of each stage: 1) local epidemic from December 1, 2019 to January 9, 2020; 2) long-distance spread due to the Spring Festival travel rush from January 10 to 22, 2020; and 3) intra-provincial transmission from January 23, 2020 when travel restrictions were imposed. Together with the basic reproduction number (R_0) for mathematical modelling, we also considered the variation in infectivity and introduced the controlled reproduction number (R_c) by assuming that exposed individuals to be infectious; we then simulated the future spread of COVID across Wuhan and all the provinces in mainland China. In addition, we built a novel source tracing algorithm to infer the initial exposed number of individuals in Wuhan on January 10, 2020, to estimate the number of infections early during this epidemic.  The spatial patterns of disease spread were heterogeneous. The estimated controlled reproduction number (R_c) in the neighboring provinces of Hubei province were relatively large, and the nationwide reproduction number (except for Hubei) ranged from 0.98 to 2.74 with an average of 1.79 (95% CI 1.77-1.80). Infectivity was significantly greater for exposed than infectious individuals, and exposed individuals were predicted to have become the major source of infection after January 23. For the epidemic process, most provinces reached their epidemic peak before February 10, 2020. It is expected that the maximum number of infections will be approached by the end of March. The final infectious size is estimated to be about 58,000 for Wuhan, 20,800 for the rest of Hubei province, and 17,000 for the other provinces in mainland China. Moreover, the estimated number of the exposed individuals is much greater than the officially reported number of infectious individuals in Wuhan on January 10, 2020.  The transmission dynamics of COVID-19 have been changing over time and were heterogeneous across regions. There was a substantial underestimation of the number of exposed individuals in Wuhan early in the epidemic, and the Spring Festival travel rush played an important role in enhancing and accelerating the spread of COVID-19. However, China's unprecedented large-scale travel restrictions quickly reduced R_c. The next challenge for the control of COVID-19 will be the second great population movement brought by removing these travel restrictions.

title: Underreporting of death by COVID-19 in Brazil's second most populous state
abstract: The COVID-19 pandemic brings to light the reality of the Brazilian health system. The underreporting of COVID-19 deaths in the state of Minas Gerais (MG), where is concentrated the second largest population of the country, reveals government unpreparedness, as there is a low capacity of testing in the population, which prevents the real understanding of the general panorama of Sars-Cov-2 dissemination. The goals of this research are to analyze the causes of deaths in the different Brazilian government databases (ARPEN and SINAN) and to assess whether there are sub-records shown by the unexpected increase in the frequency of deaths from causes clinically similar to COVID-19. A descriptive and quantitative analysis of the number of COVID-19 deaths and similar causes was made in different databases. Ours results demonstrate that the different official sources had a discrepancy of 209.23% between these data referring to the same period. There was also a 648.61% increase in SARS deaths in 2020, when compared to the average of previous years. Finally, it was shown that there was an increase in the rate of pneumonia and respiratory insufficiency (RI) by 5.36% and 5.72%, respectively. In conclusion, there is an underreporting of COVID-19 deaths in MG due to the unexplained excess of SARS deaths, Respiratory insufficiency and pneumonia compared to previous years.

title: Coronavirus Disease 2019: Coronaviruses and Blood Safety
abstract: With the outbreak of unknown pneumonia in Wuhan, China, in December 2019, a new coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), aroused the attention of the entire world. The current outbreak of infections with SARS-CoV-2 is termed Coronavirus Disease 2019 (COVID-19). The World Health Organization declared COVID-19 in China as a Public Health Emergency of International Concern. Two other coronavirus infections—SARS in 2002-2003 and Middle East Respiratory Syndrome (MERS) in 2012—both caused severe respiratory syndrome in humans. All 3 of these emerging infectious diseases leading to a global spread are caused by β-coronaviruses. Although coronaviruses usually infect the upper or lower respiratory tract, viral shedding in plasma or serum is common. Therefore, there is still a theoretical risk of transmission of coronaviruses through the transfusion of labile blood products. Because more and more asymptomatic infections are being found among COVID-19 cases, considerations of blood safety and coronaviruses have arisen especially in endemic areas. In this review, we detail current evidence and understanding of the transmission of SARS-CoV, MERS–CoV, and SARS-CoV-2 through blood products as of February 10, 2020, and also discuss pathogen inactivation methods on coronaviruses.

title: Mitigation and herd immunity strategy for COVID-19 is likely to fail
abstract: On the basis of a semi-realistic SIR microsimulation for Germany and Poland, we show that the R0 parameter interval for which the COVID-19 epidemic stays overcritical but below the capacity limit of the health care system to reach herd immunity is so narrow that a successful implementation of this strategy is likely to fail. Our microsimulation is based on official census data and involves household composition and age distribution as the main population structure variables. Outside household contacts are characterised by an out-reproduction number R* which is the only free parameter of the model. For a subcritical domain we compute the time till extinction and prevalence as a function of the initial number of infected individuals and R*. For the Polish city of Wroclaw we also discuss the combined impact of testing coverage and contact reduction. For both countries we estimate R* for disease progression until 20th of March 2020.

title: Estimated inequities in COVID-19 infection fatality rates by ethnicity for Aotearoa New Zealand
abstract: There is limited evidence as to how COVID-19 infection fatality rates (IFR) may vary by ethnicity. We combine demographic and health data for ethnic groupings in Aotearoa New Zealand with international data on IFR for different age groups to estimate inequities in IFR by ethnicity. We find that, if age is the dominant factor determining IFR, estimated IFR for Māori is around 50% higher than non-Māori. If underlying health conditions are more important than age per se, then estimated IFR for Māori is more than 2.5 times that of New Zealand European, and estimated IFR for Pasifika is almost double that of New Zealand European. IFRs for Māori and Pasifika are likely to be increased above these estimates by racism within the healthcare system and other inequities not reflected in official data. IFR does not account for differences among ethnicities in COVID-19 incidence, which could be higher in Māori and Pasifika as a result of crowded housing and higher inter-generational contact rates. These factors should be included in future disease incidence modelling. The communities at the highest risk will be those with elderly populations, and Māori and Pasifika communities, where the compounded effects of underlying health conditions, socioeconomic disadvantage, and structural racism result in imbricated risk of contracting COVID-19, becoming unwell, and death.

title: Featuring COVID-19 cases via screening symptomatic patients with epidemiologic link during flu season in a medical center of central Taiwan
abstract: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CO-V-2), was first reported in Wuhan, Hubei province, China has now rapidly spread over 50 countries. For the prevention and control of infection, Taiwan Centers for Disease Control initiated testing of SARS-CoV-2 on January 24th 2020 for persons suspected with this disease. Until February 28th, 43 flu-like symptomatic patients were screened in China Medical University Hospital.  Two patients were confirmed positive for SARS-CoV-2 infection by rRT-PCR as COVID-19 patients A and B. Causative pathogens for included patients were detected using FilmArray™ Respiratory Panel. We retrospectively analyzed the clinical presentations, laboratory data, radiologic findings, and travel and exposure contact histories, of the COVID-19 patients in comparison to those with other respiratory infections.  Through contact with Taiwan No. 19 case patient on 27th January, COVID-19 patients A and B were infected. Both patients had no identified comorbidities and developed mild illness with temporal fever, persistent cough, and lung interstitial infiltrates. Owing to the persistence of positive SARS-CoV-2 in respiratory specimen, the two COVID-19 patients are still in the isolation rooms despite recovery until 10th of March. The results of FilmArrayTM Respiratory Panel revealed 22 of the 41 non-COVID-19 patients were infected by particular pathogens. In general, seasonal respiratory pathogens are more prevalent than SARS-CoV-2 in symptomatic patients in non- COVID-19 endemic area during the flu season. Since all patients shared similar clinical and laboratory findings, expanded surveillance of detailed exposure history for suspected patients and application of rapid detection tools are highly recommended.

title: The Effects of Stringent Interventions for Coronavirus Pandemic
abstract: The pandemic of COVID-19 has caused severe public health consequences around the world. Many interventions of COVID-19 have been implemented. It is of great public health and societal importance to evaluate the effects of interventions in the pandemic of COVID-19. In this paper, with help of synthetic control method, regression discontinuity and a Susceptible-Infected and infectious without isolation-Hospitalized in isolation-Removed (SIHR) model, we evaluate the horizontal and longitudinal effects of stringent interventions implemented in Wenzhou, a representative urban city of China, where stringent interventions were enforced to curb its own epidemic situation with rapidly increasing newly confirmed cases. We found that there were statistically significant treatment effects of those stringent interventions which reduced the cumulative confirmed cases of COVID-19. Those reduction effects would increase over time. Also, if the stringent interventions were delayed by 2 days or mild interventions were implemented instead, the expected number of cumulative confirmed cases would have been nearly 2 times or 5 times of the actual number. The effects of stringent interventions are significant in mitigating the epidemic situation of COVID-19. The slower the interventions were implemented, the more severe the epidemic would have been, and the stronger the interventions would have been required.

title: Internationally lost COVID-19 cases
abstract: With its epicenter in Wuhan, China, the COVID-19 outbreak was declared a pandemic by the World Health Organization (WHO). While many countries have implemented flight restrictions to China, an increasing number of cases with or without travel background to China are confirmed daily. These developments support concerns on possible unidentified and unreported international COVID-19 cases, which could lead to new local disease epicenters.  We have analyzed all available data on the development of international COVID-19 cases from January 20th, 2020 until February 18th, 2020. COVID-19 cases with and without travel history to China were divided into cohorts according to the Healthcare Access and Quality Index (HAQ-Index) of each country. Chi-square and Post-hoc testing were performed.  While COVID-19 cases with travel history to China seem to peak for each HAQ-cohort, the number of non-travel related COVID-19 cases seem to continuously increase in the HAQ-cohort of countries with higher medical standards. Further analyses demonstrate a significantly lower proportion of reported COVID-19 cases without travel history to China in countries with lower HAQ (HAQ I vs. HAQ II, posthoc p < 0.01).  Our data indicate that countries with lower HAQ-index may either underreport COVID-19 cases or are unable to adequately detect them. Although our data may be incomplete and must be interpreted with caution, inconsistencies in reporting COVID-19 cases is a serious problem which might sabotage efforts to contain the virus.

title: Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review
abstract: Coronavirus disease 2019 (COVID-19) is a rapidly emerging disease that has been classified a pandemic by the World Health Organization (WHO). To support WHO with their recommendations on quarantine, we conducted a rapid review on the effectiveness of quarantine during severe coronavirus outbreaks.  We conducted a rapid review to assess the effects of quarantine (alone or in combination with other measures) of individuals who had contact with confirmed cases of COVID-19, who travelled from countries with a declared outbreak, or who live in regions with high transmission of the disease.  An information specialist searched PubMed, Ovid MEDLINE, WHO Global Index Medicus, Embase, and CINAHL on 12 February 2020 and updated the search on 12 March 2020. WHO provided records from daily searches in Chinese databases up to 16 March 2020.  We also included studies on SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome) as indirect evidence for the current coronavirus outbreak.  Two review authors independently screened 30% of records; a single review author screened the remaining 70%. Two review authors screened all potentially relevant full-text publications independently. One review author extracted data and assessed evidence quality with GRADE and a second review author checked the assessment. We rated the certainty of evidence for the four primary outcomes: incidence, onward transmission, mortality, and resource use.  We included 29 studies; 10 modelling studies on COVID-19, four observational studies and 15 modelling studies on SARS and MERS. Because of the diverse methods of measurement and analysis across the outcomes of interest, we could not conduct a meta-analysis and conducted a narrative synthesis. Due to the type of evidence found for this review, GRADE rates the certainty of the evidence as low to very low. Modeling studies consistently reported a benefit of the simulated quarantine measures, for example, quarantine of people exposed to confirmed or suspected cases averted 44% to 81% incident cases and 31% to 63% of deaths compared to no measures based on different scenarios (incident cases: 4 modelling studies on COVID-19, SARS; mortality: 2 modelling studies on COVID-19, SARS, low-certainty evidence). Very low-certainty evidence suggests that the earlier quarantine measures are implemented, the greater the cost savings (2 modelling studies on SARS). Very low-certainty evidence indicated that the effect of quarantine of travellers from a country with a declared outbreak on reducing incidence and deaths was small (2 modelling studies on SARS). When the models combined quarantine with other prevention and control measures, including school closures, travel restrictions and social distancing, the models demonstrated a larger effect on the reduction of new cases, transmissions and deaths than individual measures alone (incident cases: 4 modelling studies on COVID-19; onward transmission: 2 modelling studies on COVID-19; mortality: 2 modelling studies on COVID-19; low-certainty evidence). Studies on SARS and MERS were consistent with findings from the studies on COVID-19.  Current evidence for COVID-19 is limited to modelling studies that make parameter assumptions based on the current, fragmented knowledge. Findings consistently indicate that quarantine is important in reducing incidence and mortality during the COVID-19 pandemic. Early implementation of quarantine and combining quarantine with other public health measures is important to ensure effectiveness. In order to maintain the best possible balance of measures, decision makers must constantly monitor the outbreak situation and the impact of the measures implemented. Testing in representative samples in different settings could help assess the true prevalence of infection, and would reduce uncertainty of modelling assumptions. This review was commissioned by WHO and supported by Danube-University-Krems.

title: Should biologics for psoriasis be interrupted in the era of COVID-19?

title: Cardiovascular Collapse in COVID-19 Infection: The Role of Veno-Arterial Extracorporeal Membrane Oxygenation (VA-ECMO)
abstract: ABSTRACT COVID-19 has been associated with cardiovascular complications including acute cardiac injury, heart failure and cardiogenic shock. The role of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) in the event of COVID-19-associated cardiovascular collapse has not yet been established. We reviewed existing literature surrounding the role of VA-ECMO in the treatment of coronavirus-related cardiovascular collapse. COVID-19 is associated with higher incidence of cardiovascular complications compared to previous coronavirus outbreaks (SARS-CoV, MERS-CoV). We found only one case report from China where COVID-19-associated fulminant myocarditis and cardiogenic shock (CS) was successfully rescued using VA-ECMO as a bridge to recovery (BTR). We identified potential clinical scenarios (cardiac injury, myocardial infarction with and without obstructive coronary artery disease, viral myocarditis, and decompensated heart failure) leading to CS and risk factors for poor/uncertain benefit (age, sepsis, mixed/predominantly vasodilatory shock, prothrombotic state and/or coagulopathy, severe acute respiratory distress syndrome, multi-organ failure or high-risk prognostic scores) specific to using VA-ECMO as BTR in COVID-19 infection. Additional considerations and proposed recommendations specific to the COVID-19 pandemic were formulated with guidance from published data and expert consensus. A small subset of patients with cardiovascular complications from COVID-19 infection may progress to refractory CS. Accepting that resource scarcity may be the overwhelming concern for healthcare systems during this pandemic, VA-ECMO can be considered in highly selected cases of refractory CS and echocardiographic evidence of biventricular failure. The decision to initiate this therapy should take into consideration availability of resources, perceived benefit as well as risks of transmitting disease.

title: [The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China].
abstract: An outbreak of 2019 novel coronavirus diseases (COVID-19) in Wuhan, China has spread quickly nationwide. Here, we report results of a descriptive, exploratory analysis of all cases diagnosed as of February 11, 2020.  All COVID-19 cases reported through February 11, 2020 were extracted from China's Infectious Disease Information System. Analyses included: 1) summary of patient characteristics; 2) examination of age distributions and sex ratios; 3) calculation of case fatality and mortality rates; 4) geo-temporal analysis of viral spread; 5) epidemiological curve construction; and 6) subgroup analysis.  A total of 72 314 patient records-44 672 (61.8%) confirmed cases, 16 186 (22.4%) suspected cases, 10567 (14.6%) clinical diagnosed cases (Hubei only), and 889 asymptomatic cases (1.2%)-contributed data for the analysis. Among confirmed cases, most were aged 30-79 years (86.6%), diagnosed in Hubei (74.7%), and considered mild (80.9%). A total of 1 023 deaths occurred among confirmed cases for an overall case-fatality rate of 2.3%. The COVID-19 spread outward from Hubei sometime after December 2019 and by February 11, 2020, 1 386 counties across all 31 provinces were affected. The epidemic curve of onset of symptoms peaked in January 23-26, then began to decline leading up to February 11. A total of 1 716 health workers have become infected and 5 have died (0.3%).  The COVID-19 epidemic has spread very quickly. It only took 30 days to expand from Hubei to the rest of Mainland China. With many people returning from a long holiday, China needs to prepare for the possible rebound of the epidemic.

title: Adjusting to the new reality: Evaluation of early practice pattern adaptations to the COVID-19 pandemic
abstract: We aim to define national practice patterns to assess current clinical practice, anticipated delays and areas of concern that potentially could lead to deviations from the normal standard of care.  Anonymous surveys were emailed to members of the Society of Gynecologic Oncology (SGO). The spread of COVID-19 and its impact on gynecologic oncology care in terms of alterations to normal treatment patterns and anticipated challenges were assessed. The Wilcoxon rank sum test was performed to determine risk factors for COVID-19 infection.  We analyzed the responses of 331 gynecologic oncology providers. COVID-19 is present in 99.1% of surveyed communities with 99.7% reporting mitigation efforts in effect. The infection rate differs significantly between regions (p≪0.001) with the Northeast reporting the highest number of COVID-19 cases. Practice volume has dropped by 61.6% since the start of the pandemic with most cancellations being provider initiated. A majority of responders (52.8%) believed that ovarian cancer will be the most affected cancer by COVID-19. >94% of responders are proceeding with gynecologic cancer surgeries with exception of grade 1, endometrioid endometrial adenocarcinoma (36.3%). Surgical backlog (58.6%), delayed cancer diagnosis (43.2%) and re-establishing normal care with delayed patient (37.8%) were identified as the top 3 challenges after COVID-19 has abated.  COVID-19 is widespread and has radically altered normal practice patterns. Despite COVID-19 related concerns, most gynecologic oncology care is proceeding. However, the steep decline in clinical volume shows there is a large group of patients who are not being diagnosed or are deferring care.

title: Update: Public Health Response to the Coronavirus Disease 2019 Outbreak - United States, February 24, 2020.
abstract: An outbreak of coronavirus disease 2019 (COVID-19) caused by the 2019 novel coronavirus (SARS-CoV-2) began in Wuhan, Hubei Province, China in December 2019, and has spread throughout China and to 31 other countries and territories, including the United States (1). As of February 23, 2020, there were 76,936 reported cases in mainland China and 1,875 cases in locations outside mainland China (1). There have been 2,462 associated deaths worldwide; no deaths have been reported in the United States. Fourteen cases have been diagnosed in the United States, and an additional 39 cases have occurred among repatriated persons from high-risk settings, for a current total of 53 cases within the United States. This report summarizes the aggressive measures (2,3) that CDC, state and local health departments, multiple other federal agencies, and other partners are implementing to slow and try to contain transmission of COVID-19 in the United States. These measures require the identification of cases and contacts of persons with COVID-19 in the United States and the recommended assessment, monitoring, and care of travelers arriving from areas with substantial COVID-19 transmission. Although these measures might not prevent widespread transmission of the virus in the United States, they are being implemented to 1) slow the spread of illness; 2) provide time to better prepare state and local health departments, health care systems, businesses, educational organizations, and the general public in the event that widespread transmission occurs; and 3) better characterize COVID-19 to guide public health recommendations and the development and deployment of medical countermeasures, including diagnostics, therapeutics, and vaccines. U.S. public health authorities are monitoring the situation closely, and CDC is coordinating efforts with the World Health Organization (WHO) and other global partners. Interim guidance is available at https://www.cdc.gov/coronavirus/index.html. As more is learned about this novel virus and this outbreak, CDC will rapidly incorporate new knowledge into guidance for action by CDC, state and local health departments, health care providers, and communities.

title: A graph-based evidence synthesis approach to detecting outbreak clusters: An application to dog rabies
abstract: Early assessment of infectious disease outbreaks is key to implementing timely and effective control measures. In particular, rapidly recognising whether infected individuals stem from a single outbreak sustained by local transmission, or from repeated introductions, is crucial to adopt effective interventions. In this study, we introduce a new framework for combining several data streams, e.g. temporal, spatial and genetic data, to identify clusters of related cases of an infectious disease. Our method explicitly accounts for underreporting, and allows incorporating preexisting information about the disease, such as its serial interval, spatial kernel, and mutation rate. We define, for each data stream, a graph connecting all cases, with edges weighted by the corresponding pairwise distance between cases. Each graph is then pruned by removing distances greater than a given cutoff, defined based on preexisting information on the disease and assumptions on the reporting rate. The pruned graphs corresponding to different data streams are then merged by intersection to combine all data types; connected components define clusters of cases related for all types of data. Estimates of the reproduction number (the average number of secondary cases infected by an infectious individual in a large population), and the rate of importation of the disease into the population, are also derived. We test our approach on simulated data and illustrate it using data on dog rabies in Central African Republic. We show that the outbreak clusters identified using our method are consistent with structures previously identified by more complex, computationally intensive approaches.

title: Thème : Infections virales

title: SARS-CoV-2 diagnostic testing in Africa: needs and challenges

title: Epidemiology, virology, and clinical features of severe acute respiratory syndrome -coronavirus-2 (SARS-CoV-2; Coronavirus Disease-19)
abstract: A cluster of severe pneumonia of unknown etiology in Wuhan City, Hubei province in China emerged in December 2019. A novel coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was isolated from lower respiratory tract sample as the causative agent. The current outbreak of infections with SARS-CoV-2 is termed Coronavirus Disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 rapidly spread into at least 114 countries and killed more than 4,000 people by March 11 2020. WHO officially declared COVID-19 a pandemic on March 11, 2020. There have been 2 novel coronavirus outbreaks in the past 2 decades. The outbreak of severe acute respiratory syndrome (SARS) in 2002–2003 caused by SARS-CoV had a case fatality rate of around 10% (8,098 confirmed cases and 774 deaths), while Middle East respiratory syndrome (MERS) caused by MERS-CoV killed 861 people out of a total 2,502 confirmed cases between 2012 and 2019. The purpose of this review is to summarize known-to-date information about SARS-CoV-2, transmission of SARS-CoV-2, and clinical features.

title: Disentangling Increased Testing From Covid-19 Epidemic Spread
abstract: To design effective disease control strategies, it is critical to understand the incidence of diseases. In the Covid-19 epidemic in the United States (caused by outbreak of the SARS-CoV-2 virus), testing capacity was initially very limited and has been increasing at the same time as the virus has been spreading. When estimating the incidence, it can be difficult to distinguish whether increased numbers of positive tests stem from increases in the spread of the virus or increases in testing. This has made it very difficult to identify locations in which the epidemic poses the largest public health risks. Here, we use a probabilistic model to quantify beliefs about testing strategies and understand implications regarding incidence. We apply this model to estimate the incidence in each state of the United States, and find that: (1) the Covid-19 epidemic is likely to be more widespread than reported by limited testing, (2) the Covid-19 epidemic growth in the summer months is likely smaller than it was during the spring months, and (3) the regions which are at highest risk of Covid-19 epidemic outbreaks are not always those with the largest number of positive test results.

title: Abstracts from the 36th Annual Meeting of the Society of General Internal Medicine

title: Characterization and Pathogenicity of the Porcine Deltacoronavirus Isolated in Southwest China
abstract: Porcine deltacoronavirus (PDCoV) is a newly emerging enteric pathogen in swine that causes diarrhea in neonatal piglets and creates an additional economic burden on porcine industries in Asia and North America. In this study, a PDCoV isolate, CHN-SC2015, was isolated from Sichuan Province in southwest China. The isolate was characterized by a cytopathic effect, immunofluorescence, and electron microscopy. CHN-SC2015 titers in LLC-PK cells ranged from 10(4.31) to 10(8.22) TCID(50)/mL during the first 30 passages. During serial passage, 11 nucleotide mutations occurred in the S gene, resulting in nine amino acid changes. A whole genome sequencing analysis demonstrated that CHN-SC2015 shares 97.5%–99.1% identity with 59 reference strains in GenBank. Furthermore, CHN-SC2015 contained 6-nt deletion and 9-nt insertion in the ORF1ab gene, 3-nt deletion in the S gene and 11-nt deletion in its 3′UTR compared with other reference strains available in GenBank. A phylogenetic analysis showed that CHN-SC2015 is more closely related to other PDCoV strains in China than to the strains from Southeast Asia, USA, Japan, and South Korea, indicating the diversity of genetic relationships and regional and epidemic characteristics among these strains. A recombination analysis indicated that CHN-SC2015 experienced recombination events between SHJS/SL/2016 and TT-1115. In vivo infection demonstrated that CHN-SC2015 is highly pathogenic to sucking piglets, causing diarrhea, vomiting, dehydration, and death. Virus was shed daily in the feces of infected piglets and upon necropsy, was found distributed in the gastrointestinal tract and in multiple organs. CHN-SC2015 is the first systematically characterized strain from southwest China hitherto reported. Our results enrich the body of information on the epidemiology, pathogenicity and molecular evolution associated with PDCoV.

title: Identification and control are the priority.

title: Estimating the prevalence and risk of COVID-19 among international travelers and evacuees of Wuhan through modeling and case reports
abstract: Coronavirus disease 2019 (COVID-19) started in Wuhan, China and has spread through other provinces and countries through infected travelers. On January 23(rd), 2020, China issued a quarantine and travel ban on Wuhan because travelers from Wuhan were thought to account for the majority of exported COVID-19 cases to other countries. Additionally, countries evacuated their citizens from Wuhan after institution of the travel ban. Together, these two populations account for the vast majority of the “total cases with travel history to China” as designated by the World Health Organization (WHO). The current study aims to assess the prevalence and risk of COVID-19 among international travelers and evacuees of Wuhan. We first used case reports from Japan, Singapore, and Korea to investigate the date of flights of infected travelers. We then used airline traveler data and the number of infected exported cases to correlate the cases with the number of travelers for multiple countries. Our findings suggest that the risk of COVID-19 infection is highest among Wuhan travelers between January 19(th) and 22(nd), 2020, with an approximate infection rate of up to 1.3% among international travelers. We also observed that evacuee infection rates varied heavily between countries and propose that the timing of the evacuation and COVID-19 testing of asymptomatic evacuees played significant roles in the infection rates among evacuees. These findings suggest COVID-19 cases and infectivity are much higher than previous estimates, including numbers from the WHO and the literature, and that some estimates of the infectivity of COVID-19 may need re-assessment.

title: Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak
abstract: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R(0), of 2019-nCoV.  We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R(0).  We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403–540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18–25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R(0) of 2019-nCoV at 2.56 (95% CI: 2.49–2.63).  The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation.

title: Prevalence of Chemosensory Dysfunction in COVID-19 Patients: A Systematic Review and Meta-analysis Reveals Significant Ethnic Differences
abstract: A significant fraction of people who test positive for COVID-19 have chemosensory deficits. However, the reported prevalence of these deficits in smell and/or taste varies widely, and the reason for the differences between studies is unclear. We determined the pooled prevalence of such chemosensory deficits in a systematic review. We searched the COVID-19 portfolio of the National Institutes of Health for all studies that reported the prevalence of smell and/or taste deficits in patients diagnosed with COVID-19. Forty-two studies reporting on 23,353 patients qualified and were subjected to a systematic review and meta-analysis. Estimated random prevalence of olfactory dysfunction was 38.5%, of taste dysfunction was 30.4% and of overall chemosensory dysfunction was 50.2%. We examined the effects of age, disease severity, and ethnicity on chemosensory dysfunction. The effect of age did not reach significance, but anosmia/hypogeusia decreased with disease severity, and ethnicity was highly significant: Caucasians had a 3-6 times higher prevalence of chemosensory deficits than East Asians. The finding of ethnic differences points to genetic, ethnicity-specific differences of the virus-binding entry proteins in the olfactory epithelium and taste buds as the most likely explanation, with major implications for infectivity, diagnosis and management of the COVID-19 pandemic.

title: COVID-19 is not just a flu. Learn from Italy and act now

title: How will country-based mitigation measures influence the course of the COVID-19 epidemic?

title: Smoking and the risk of COVID-19 in a large observational population study
abstract: Smokers are generally more susceptible to infectious respiratory diseases and are at higher risk of developing severe complications from these infections. Conflicting reports exist regarding the impact of smoking on the risk of Coronavirus disease 2019 (COVID-19) infection.  We carried out a population-based study among over 3,000,000 adult members of Clalit Health Services, the largest health provider in Israel. Since the beginning of the disease outbreak, 114,545 individuals underwent RT-PCR testing for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and 4.0% had positive results. We performed a case-control study among patients who underwent SARS-CoV-2 testing, to assess the impact of smoking on infection incidence and severity. Individuals with positive tests were matched in a 1:5 ratio to individuals tested negative, of the same sex, age, and ethnicity/religion. Conditional logistic regressions were performed to evaluate odds ratios for current and previous smoking on the risk of testing positive. Multivariable logistic regressions were performed among patients infected with COVID-19 to estimate the association between smoking and fatal or severe disease requiring ventilation. Regressions were performed with and without adjustment for preexisting medical conditions.  In the matched cohort, current smokers (9.8%) were significantly less prevalent among members tested positive compared to the general population, and to matched members tested negative (19.4%, P<0.001). Current smoking was associated with significantly reduced odds ratio (OR) for testing positive OR=0.457 (95% confidence interval (CI) 0.407-0.514). Among patients tested positive, there was no evidence of significantly increased risk of developing severe or fatal disease.  The risk of infection by COVID-19 appears to be reduced by half among current smokers. This intriguing finding may reveal unique infection mechanisms present for COVID-19 which may be targeted to combat the disease and reduce its infection rate.

title: COVID-19 coronavirus vaccine design using reverse vaccinology and machine learning
abstract: To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole virus, as well as the spike (S) protein, nucleocapsid (N) protein, and membrane protein, have been tested for vaccine development against SARS and MERS. We further used the Vaxign reverse vaccinology tool and the newly developed Vaxign-ML machine learning tool to predict COVID-19 vaccine candidates. The N protein was found to be conserved in the more pathogenic strains (SARS/MERS/COVID-19), but not in the other human coronaviruses that mostly cause mild symptoms. By investigating the entire proteome of SARS-CoV-2, six proteins, including the S protein and five non-structural proteins (nsp3, 3CL-pro, and nsp8–10) were predicted to be adhesins, which are crucial to the viral adhering and host invasion. The S, nsp3, and nsp8 proteins were also predicted by Vaxign-ML to induce high protective antigenicity. Besides the commonly used S protein, the nsp3 protein has not been tested in any coronavirus vaccine studies and was selected for further investigation. The nsp3 was found to be more conserved among SARS-CoV-2, SARS-CoV, and MERS-CoV than among 15 coronaviruses infecting human and other animals. The protein was also predicted to contain promiscuous MHC-I and MHC-II T-cell epitopes, and linear B-cell epitopes localized in specific locations and functional domains of the protein. Our predicted vaccine targets provide new strategies for effective and safe COVID-19 vaccine development.

title: Is Group Testing Ready for Prime-time in Disease Identification?
abstract: Large scale disease screening is a complicated process in which high costs must be balanced against pressing public health needs. When the goal is screening for infectious disease, one approach is group testing in which samples are initially tested in pools and individual samples are retested only if the initial pooled test was positive. Intuitively, if the prevalence of infection is small, this could result in a large reduction of the total number of tests required. Despite this, the use of group testing in medical studies has been limited, largely due to skepticism about the impact of pooling on the accuracy of a given assay. While there is a large body of research addressing the issue of testing errors in group testing studies, it is customary to assume that the misclassification parameters are known from an external population and/or that the values do not change with the group size. Both of these assumptions are highly questionable for many medical practitioners considering group testing in their study design. In this article, we explore how the failure of these assumptions might impact the efficacy of a group testing design and, consequently, whether group testing is currently feasible for medical screening. Specifically, we look at how incorrect assumptions about the sensitivity function at the design stage can lead to poor estimation of a procedure's overall sensitivity and expected number of tests. Furthermore, if a validation study is used to estimate the pooled misclassification parameters of a given assay, we show that the sample sizes required are so large as to be prohibitive in all but the largest screening programs

title: Cardiovascular Risks in Patients with COVID-19: Potential Mechanisms and Areas of Uncertainty
abstract: COronaVirus Disease 2019 (COVID-19) has spread at unprecedented speed and scale into a global pandemic with cardiovascular risk factors and complications emerging as important disease modifiers. We aim to review available clinical and biomedical literature on cardiovascular risks of COVID-19.  SARS-CoV2, the virus responsible for COVID-19, enters the cell via ACE2 expressed in select organs. Emerging epidemiological evidence suggest cardiovascular risk factors are associated with increased disease severity and mortality in COVID-19 patients. Patients with a more severe form of COVID-19 are also more likely to develop cardiac complications such as myocardial injury and arrhythmia. The true incidence of and mechanism underlying these events remain elusive.  Cardiovascular diseases appear intricately linked with COVID-19, with cardiac complications contributing to the elevated morbidity/mortality of COVID-19. Robust epidemiologic and biologic studies are urgently needed to better understand the mechanism underlying these associations to develop better therapies.

title: Zoonotic origins of human coronaviruses
abstract: Mutation and adaptation have driven the co-evolution of coronaviruses (CoVs) and their hosts, including human beings, for thousands of years. Before 2003, two human CoVs (HCoVs) were known to cause mild illness, such as common cold. The outbreaks of severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) have flipped the coin to reveal how devastating and life-threatening an HCoV infection could be. The emergence of SARS-CoV-2 in central China at the end of 2019 has thrusted CoVs into the spotlight again and surprised us with its high transmissibility but reduced pathogenicity compared to its sister SARS-CoV. HCoV infection is a zoonosis and understanding the zoonotic origins of HCoVs would serve us well. Most HCoVs originated from bats where they are non-pathogenic. The intermediate reservoir hosts of some HCoVs are also known. Identifying the animal hosts has direct implications in the prevention of human diseases. Investigating CoV-host interactions in animals might also derive important insight on CoV pathogenesis in humans. In this review, we present an overview of the existing knowledge about the seven HCoVs, with a focus on the history of their discovery as well as their zoonotic origins and interspecies transmission. Importantly, we compare and contrast the different HCoVs from a perspective of virus evolution and genome recombination. The current CoV disease 2019 (COVID-19) epidemic is discussed in this context. In addition, the requirements for successful host switches and the implications of virus evolution on disease severity are also highlighted.

title: Cumulative incidence and diagnosis of SARS-CoV-2 infection in New York
abstract: New York State (NYS) is an epicenter of the United States' COVID-19 epidemic. Reliable estimates of cumulative incidence of SARS-CoV-2 infection in the population are critical to tracking the extent of transmission and informing policies, but US data are lacking, in part because societal closure complicates study conduct.  To estimate the cumulative incidence of SARS-CoV-2 infection and percent of infections diagnosed in New York State, overall and by region, age, sex, and race and ethnicity.  Statewide cross-sectional seroprevalence study, conducted April 19-28, 2020.  Grocery stores (n=99) located in 26 counties throughout NYS, which were essential businesses that remained open during a period of societal closure and attract a heterogenous clientele.  Convenience sample of patrons >=18 years and residing in New York State, recruited consecutively upon entering stores and via an in-store flyer.  Region (New York City, Westchester/Rockland, Long Island, Rest of New York State), age, sex, race and ethnicity.  cumulative incidence of SARS-CoV-2 infection, based on dry-blood spot (DBS) SARS-CoV-2 antibody reactivity; secondary outcome: percent of infections diagnosed.  Among 15,101 adults with suitable DBS specimens, 1,887 (12.5%) were reactive using a validated SARS-CoV-2 IgG microsphere immunoassay (sensitivity 87.9%, specificity 99.75%). Following post-stratification weighting on region, sex, age, and race and ethnicity and adjustment for assay characteristics, estimated cumulative incidence through March 29 was 14.0% (95% CI: 13.3-14.7%), corresponding to 2,139,300 (95% CI: 2,035,800-2,242,800) infection-experienced adults. Cumulative incidence was higher among Hispanic/Latino (29.2%, 95% CI: 27.2-31.2%), non-Hispanic black/African American (20.2% 95% CI, 18.1-22.3%), and non-Hispanic Asian (12.4%, 95% CI: 9.4-15.4%) adults than non-Hispanic white adults (8.1%, 95% CI: 7.4-8.7%, p<.0001). Cumulative incidence was highest in New York City (NYC) 22.7% (95% CI: 21.5%-24.0). Dividing diagnoses reported to NYS by estimated infection-experienced adults, an estimated 8.9% (95% CI: 8.4-9.3%) of infections were diagnosed, with those [≥]55 years most likely to be diagnosed (11.3%, 95% CI: 10.4-12.2%).  Over 2 million adults were infected through late March 2020, with substantial variations by subpopulations. As this remains below herd immunity thresholds, monitoring, testing, and contact tracing remain essential public health strategies.

title: The incidence of the novel coronavirus SARS-CoV-2 among asymptomatic patients: a systematic review
abstract: the recent outbreak of the coronavirus disease 2019 (COVID‐19) has quickly spread globally since its discovery in Wuhan, China, in December 2019. A comprehensive strategy, including surveillance, diagnostics, research, and clinical treatment is urgently needed to win the battle against COVID-19. Recently, numerous studies reported the incidence of SARS-CoV-2 in asymptomatic patients. Yet, the incidence and viral transmission from the asymptomatic cases are not apparent yet.  this study aims to systematically review the published literature on SARS-CoV-2 in the asymptomatic patients to estimate the incidence of COVID-19 among asymptomatic cases, as well as describe its epidemiological and clinical significance.  the literature was searched through four scientific databases: PubMed, Web of Science, Scopus, and Science Direct.  a total of 63 studies satisfied the inclusion criteria where the majority of the reported studies were from China. However, there was a lack of SARS-CoV-2 epidemiological studies from several countries worldwide, tracing the actual incidence of COVID-19, especially in asymptomatic patients. Studies with a large sample size (n>1000) estimated that percentage of people contracting SARS-CoV-2 and are likely to be asymptomatic ranges from 1.2-12.9%. However, the other studies with a smaller sample size reported a much higher incidence and indicated that up to 87.9% of COVID-19 infected individuals could be asymptomatic. Most of these studies indicated that asymptopatics are a potential source of infection to the community.  this review highlighted the need for more robust and well-designed studies to better estimate COVID-19 incidence among asymptomatic patients worldwide. The early identification of the asymptomatic cases, as well as monitoring and tracing close contact, could help in mitigating the spread of COVID-19.

title: A survey of UK acute clinicians' knowledge of personal protective requirements for infectious diseases and chemical, biological, and radiological warfare agents

title: Estimating the extent of true asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis
abstract: The prevalence of true asymptomatic COVID-19 cases is critical to policy makers considering the effectiveness of mitigation measures against the SARS-CoV-2 pandemic. We aimed to synthesize all available research on the asymptomatic rates and transmission rates where possible.  We searched PubMed, Embase, Cochrane COVID-19 trials, and European PMC for pre-print platforms such as MedRxiv. We included primary studies reporting on asymptomatic prevalence where: (a) the sample frame includes at-risk population, and (b) there was sufficiently long follow up to identify pre-symptomatic cases. Meta-analysis used fixed effect and random effects models.  We screened 571 articles and included five low risk-of-bias studies from three countries (China (2), USA (2), Italy (1)) that tested 9,242 at-risk people, of which 413 were positive and 65 were asymptomatic. Diagnosis in all studies was confirmed using a RT-qPCR test. The proportion of asymptomatic cases ranged from 6% to 41%. Meta-analysis (fixed effect) found that the proportion of asymptomatic cases was 16% (95% CI: 12% - 20%) overall; higher in non-aged care 19% (15% - 24%), and lower in long-term aged care 8% (4% - 14%). Two studies provided direct evidence of forward transmission of the infection by asymptomatic cases but suggested lower rates than symptomatic cases.  Our estimates of the prevalence of asymptomatic COVID-19 cases are lower than many highly publicized studies, but still substantial. Further robust epidemiological evidence is urgently needed, including in sub-populations such as children, to better understand the importance of asymptomatic cases for driving spread of the pandemic.

title: Early trends for SARS‐CoV‐2 infection in central and north Texas and impact on other circulating respiratory viruses
abstract: Rapid diagnosis and isolation are key to containing the quick spread of a pandemic agent like severe acute respiratory syndrome‐related coronavirus 2 (SARS‐CoV‐2), which has spread globally since its initial outbreak in Wuhan province in China. SARS‐CoV‐2 is novel and the effect on typically prevalent seasonal viruses is just becoming apparent. We present our initial data on the prevalence of respiratory viruses in the month of March 2020. This is a retrospective cohort study post launching of SARS‐CoV‐2 testing at Baylor Scott and White Hospital (BSWH), Temple, Texas. Testing for SARS‐CoV‐2 was performed by real‐time reverse transcription polymerase chain reaction assay and results were shared with State public health officials for immediate interventions. More than 3500 tests were performed during the first 2 weeks of testing for SARS‐CoV‐2 and identified 168 (4.7%) positive patients. Sixty‐two (3.2%) of the 1912 ambulatory patients and 106 (6.3%) of the 1659 emergency department/inpatients tested were positive. The highest rate of infection (6.9%) was seen in patients aged 25 to 34 years, while the lowest rate of infection was seen among patients aged <25 years old (2%). County‐specific patient demographic information was shared with respective public health departments for epidemiological interventions. Incidentally, this study showed that there was a significant decrease in the occurrence of seasonal respiratory virus infections, perhaps due to increased epidemiological awareness about SARS‐CoV‐2 among the general public, as well as the social distancing measures implemented in response to SARS‐CoV‐2. Data extracted for BSWH from the Centers for Disease Control and Prevention's National Respiratory and Enteric Virus Surveillance System site revealed that Influenza incidence was 8.7% in March 2020, compared with 25% in March 2019. This study was intended to provide an initial experience of dealing with a pandemic and the role of laboratories in crisis management. This study provided SARS‐CoV‐2 testing data from ambulatory and inpatient population. Epidemiological interventions depend on timely availability of accurate diagnostic tests and throughput capacity of such systems during large outbreaks like SARS‐CoV‐2.

title: A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys
abstract: Coronavirus infection spreads in clusters and therefore early identification of these clusters is critical for slowing down the spread of the virus. Here, we propose that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters to inform epidemiologists, public health officials, and policy makers. We show preliminary results from a survey of over 38,000 Israelis and call for an international consortium to extend this concept in order to develop predictive models. We expect such data to allow: Faster detection of spreading zones and patients; Obtaining a current snapshot of the number of people in each area who have developed symptoms; Predicting future spreading zones several days before an outbreak occurs; Evaluating the effectiveness of the various social distancing measures taken, and their contribution to reduce the number of symptomatic people. Such information can provide a valuable tool for decision makers to decide which areas need strengthening of social distancing measures and which areas can be relieved. Researchers from the U.S, Spain, and Italy have adopted our approach and we are collaborating to further improve it. We call with urgency for other countries to join this international consortium, and to share methods and data collected from these daily, simple, one-minute surveys.

title: Population age structure only partially explains the large number of COVID-19 deaths at the oldest ages
abstract: To date any attention paid to the age shape of COVID-19 deaths has been mostly in relation to attempts to understand the differences in case fatality rates between countries. The aim of this paper is to explore differences in age distribution of deaths from COVID-19 among European countries which have old age structures. We do this by way of a cross-country comparison and put forward some reasons for potential differences.

title: Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran
abstract: Iran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020.  We developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay adjusted case fatality ratio based on the distribution of the delay from hospitalization to death.  Our estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60-1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available.  The series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak.

title: Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label
abstract: Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 detection on chest CT is helpful to counter the outbreak of SARS-CoV-2. A weakly-supervised deep learning-based software system was developed using 3D CT volumes to detect COVID-19. For each patient, the lung region was segmented using a pre-trained UNet; then the segmented 3D lung region was fed into a 3D deep neural network to predict the probability of COVID-19 infectious. 499 CT volumes collected from Dec. 13, 2019, to Jan. 23, 2020, were used for training and 131 CT volumes collected from Jan 24, 2020, to Feb 6, 2020, were used for testing. The deep learning algorithm obtained 0.959 ROC AUC and 0.976 PR AUC. There was an operating point with 0.907 sensitivity and 0.911 specificity in the ROC curve. When using a probability threshold of 0.5 to classify COVID-positive and COVID-negative, the algorithm obtained an accuracy of 0.901, a positive predictive value of 0.840 and a very high negative predictive value of 0.982. The algorithm took only 1.93 seconds to process a single patient's CT volume using a dedicated GPU. Our weakly-supervised deep learning model can accurately predict the COVID-19 infectious probability in chest CT volumes without the need for annotating the lesions for training. The easily-trained and high-performance deep learning algorithm provides a fast way to identify COVID-19 patients, which is beneficial to control the outbreak of SARS-CoV-2. The developed deep learning software is available at \url{https://github.com/sydney0zq/covid-19-detection}.

title: Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection
abstract: Deep Learning has achieved state of the art performance in medical imaging. However, these methods for disease detection focus exclusively on improving the accuracy of classification or predictions without quantifying uncertainty in a decision. Knowing how much confidence there is in a computer-based medical diagnosis is essential for gaining clinicians trust in the technology and therefore improve treatment. Today, the 2019 Coronavirus (SARS-CoV-2) infections are a major healthcare challenge around the world. Detecting COVID-19 in X-ray images is crucial for diagnosis, assessment and treatment. However, diagnostic uncertainty in the report is a challenging and yet inevitable task for radiologist. In this paper, we investigate how drop-weights based Bayesian Convolutional Neural Networks (BCNN) can estimate uncertainty in Deep Learning solution to improve the diagnostic performance of the human-machine team using publicly available COVID-19 chest X-ray dataset and show that the uncertainty in prediction is highly correlates with accuracy of prediction. We believe that the availability of uncertainty-aware deep learning solution will enable a wider adoption of Artificial Intelligence (AI) in a clinical setting.

title: COVID-19 outbreak: less stethoscope, more ultrasound

title: Testing Case Number of Coronavirus Disease 2019 in China with Newcomb-Benford Law
abstract: The coronavirus disease 2019 bursted out about two months ago in Wuhan has caused the death of more than a thousand people. China is fighting hard against the epidemics with the helps from all over the world. On the other hand, there appear to be doubts on the reported case number. In this article, we propose a test of the reported case number of coronavirus disease 2019 in China with Newcomb-Benford law. We find a $p$-value of $92.8\%$ in favour that the cumulative case numbers abide by the Newcomb-Benford law. Even though the reported case number can be lower than the real number of affected people due to various reasons, this test does not seem to indicate the detection of frauds.

title: Using random testing in a feedback-control loop to manage a safe exit from the COVID-19 lockdown
abstract: We argue that frequent sampling of the fraction of infected people (either by random testing or by analysis of sewage water), is central to managing the COVID-19 pandemic because it both measures in real time the key variable controlled by restrictive measures, and anticipates the load on the healthcare system due to progression of the disease. Knowledge of random testing outcomes will (i) significantly improve the predictability of the pandemic, (ii) allow informed and optimized decisions on how to modify restrictive measures, with much shorter delay times than the present ones, and (iii) enable the real-time assessment of the efficiency of new means to reduce transmission rates. Here we suggest, irrespective of the size of a suitably homogeneous population, a conservative estimate of 15000 for the number of randomly tested people per day which will suffice to obtain reliable data about the current fraction of infections and its evolution in time, thus enabling close to real-time assessment of the quantitative effect of restrictive measures. Still higher testing capacity permits detection of geographical differences in spreading rates. Furthermore and most importantly, with daily sampling in place, a reboot could be attempted while the fraction of infected people is still an order of magnitude higher than the level required for a relaxation of restrictions with testing focused on symptomatic individuals. This is demonstrated by considering a feedback and control model of mitigation where the feed-back is derived from noisy sampling data.

title: Biophysical characterization of the SARS-CoV-2 spike protein binding with the ACE2 receptor and implications for infectivity
abstract: SARS-CoV-2 is a novel highly virulent pathogen which gains entry to human cells by binding with the cell surface receptor – angiotensin converting enzyme (ACE2). We computationally contrasted the binding interactions between human ACE2 and coronavirus spike protein receptor binding domain (RBD) of the 2002 epidemic-causing SARS-CoV-1, SARS-CoV-2, and bat coronavirus RaTG13 using the Rosetta energy function. We find that the RBD of the spike protein of SARS-CoV-2 is highly optimized to achieve very strong binding with human ACE2 (hACE2) which is consistent with its enhanced infectivity. SARS-CoV-2 forms the most stable complex with hACE2 compared to SARS-CoV-1 (23% less stable) or RaTG13 (11% less stable) while occupying the greatest number of residues in the ATR1 binding site. Notably, the SARS-CoV-2 RBD out-competes the angiotensin 2 receptor type I (ATR1) which is the native binding partner of ACE2 by 35% in terms of the calculated binding affinity. Strong binding is mediated through strong electrostatic attachments with every fourth residue on the N-terminus alpha-helix (starting from Ser19 to Asn53) as the turn of the helix makes these residues solvent accessible. By contrasting the spike protein SARS-CoV-2 Rosetta binding energy with ACE2 of different livestock and pet species we find strongest binding with bat ACE2 followed by human, feline, equine, canine and finally chicken. This is consistent with the hypothesis that bats are the viral origin and reservoir species. These results offer a computational explanation for the increased infectivity of SARS-CoV-2 and allude to therapeutic modalities by identifying and rank-ordering the ACE2 residues involved in binding with the virus.

title: News from the front: Excess mortality and life expectancy in two major epicentres of the COVID-19 pandemic in Italy
abstract: Existing studies commonly rely on national official reports to estimate the impact of COVID-19 on population health and human life. However, relying on national reports is problematic because classification and estimation of COVID-19 mortality are not consistent across countries. Likewise, delay coronavirus test results and shortage of testing kits can result in undercounting of coronavirus deaths. To overcome these problems, this study exploits all cause daily death registrations data provide by the Italian Statistical Office (ISTAT) from 1st January to 4th April 2020. This allows us to: 1) calculate excess mortality in 2020 compared to the years 2015 to 2019; and 2) estimate life expectancy on a seasonal and annual basis. We focus our analysis on Bergamo and Brescia, the two hardest hit provinces in Lombardy, northern Italy. Given the clustering nature of the epidemic, focusing on the areas with high concentration of severe illness and deaths allows us to capture the true impact of COVID-19 on mortality and life expectancy, which are likely to be underestimated in the national level data. We find that on the period 1 Jan to 4 April 2020, seasonal life expectancy in Bergamo reduced by around 8.1 and 6.5 years compared to 2019 for men and women respectively (4.5 and 3.4 years in Brescia). The drop in period life expectancy for 2020 may total up to 3 years in the case of men and 2 years in the case of women. Such a sharp decrease in life expectancy has not been experienced in modern history since the Second World War. This study shows that, in the absence of public health interventions to reduce the spread of the virus, COVID-19 has set life expectancy in Bergamo and Brescia back to the Italian life expectancy of 15 years ago.

title: The Response of An Orthopedic Department and Specialty Hospital at the Epicenter of a Pandemic: The NYU Langone Health Experience
abstract: As the world grapples with the COVID-19 pandemic, we as healthcare professionals thrive to continue to help our patients, and as orthopedic surgeons this goal is ever more challenging. As part of a major academic tertiary medical center in New York City, the orthopedic department at New York University (NYU) Langone health has evolved and adapted to meet the challenges of the COVID pandemic. In our report, we will detail the different aspects and actions taken by NYU Langone Health as well as NYU Langone orthopedic Hospital and the Orthopedic Department in particular. Among the steps taken, the department has reconfigured its staff’s assignments to help both with the institution’s efforts and our patients’ needs, from reassigning operating room nurses to medical COVID floors to having attending surgeons cover urgent care locations. We have reorganized our residency and fellowship rotations and assignments as well as adapting our educational programs to online learning. While constantly evolving to meet the institution’s and our patient demands, our leadership starts planning for the return to a new “normal”.

title: Mapping the Landscape of Artificial Intelligence Applications against COVID-19
abstract: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of April 23, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales including molecular, clinical, and societal applications. We also review datasets, tools, and resources needed to facilitate AI research. Finally, we discuss strategic considerations related to the operational implementation of projects, multidisciplinary partnerships, and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.

title: Is Hydroxychloroquine a Possible Postexposure Prophylaxis Drug to Limit the Transmission to Healthcare Workers Exposed to Coronavirus Disease 2019?

title: Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status
abstract: It has been 2 months since the first case of coronavirus disease 2019 (COVID-19) was reported in Wuhan, China. So far, COVID-19 has affected 85 403 patients in 57 countries/territories and has caused 2924 deaths in 9 countries. However, epidemiological data differ between countries. Although China had higher morbidity and mortality than other sites, the number of new daily cases in China has been lower than outside of China since 26 February 2020. The incidence ranged from 61.44 per 1 000 000 people in the Republic of Korea to 0.0002 per 1 000 000 people in India. The daily cumulative index (DCI) of COVID-19 (cumulative cases/no. of days between the first reported case and 29 February 2020) was greatest in China (1320.85), followed by the Republic of Korea (78.78), Iran (43.11) and Italy (30.62). However, the DCIs in other countries/territories were <10 per day. Several effective measures including restricting travel from China, controlling the distribution of masks, extensive investigation of COVID-19 spread, and once-daily press conferences by the government to inform and educate people were aggressively conducted in Taiwan. This is probably the reason why there was only 39 cases (as of 29 February 2020) with a DCI of 1 case per day in Taiwan, which is much lower than that of nearby countries such as the Republic of Korea and Japan. In addition, the incidence and mortality were correlated with the DCI. However, further study and continued monitoring are needed to better understand the underlying mechanism of COVID-19.

title: Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China
abstract: The incidence of coronavirus disease 2019 (COVID-19) in Wuhan, China, has been estimated using imported case counts of international travellers, generally under the assumptions that all cases of the disease in travellers have been ascertained and that infection prevalence in travellers and residents is the same. However, findings indicate variation among locations in the capacity for detection of imported cases. Singapore has had very strong epidemiological surveillance and contact tracing capacity during previous infectious disease outbreaks and has consistently shown high sensitivity of case-detection during the COVID-19 outbreak.  We used a Bayesian modelling approach to estimate the relative capacity for detection of imported cases of COVID-19 for 194 locations (excluding China) compared with that for Singapore. We also built a simple mathematical model of the point prevalence of infection in visitors to an epicentre relative to that in residents.  The weighted global ability to detect Wuhan-to-location imported cases of COVID-19 was estimated to be 38% (95% highest posterior density interval [HPDI] 22–64) of Singapore's capacity. This value is equivalent to 2·8 (95% HPDI 1·5–4·4) times the current number of imported and reported cases that could have been detected if all locations had had the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify likely case-detection capacities, the ability to detect imported cases relative to Singapore was 40% (95% HPDI 22–67) among locations with high surveillance capacity, 37% (18–68) among locations with medium surveillance capacity, and 11% (0–42) among locations with low surveillance capacity. Treating all travellers as if they were residents (rather than accounting for the brief stay of some of these travellers in Wuhan) contributed modestly to underestimation of prevalence.  Estimates of case counts in Wuhan based on assumptions of 100% detection in travellers could have been underestimated by several fold. Furthermore, severity estimates will be inflated several fold since they also rely on case count estimates. Finally, our model supports evidence that underdetected cases of COVID-19 have probably spread in most locations around the world, with greatest risk in locations of low detection capacity and high connectivity to the epicentre of the outbreak.

title: Adjusted fatality rates of COVID19 pandemic: a comparison across countries
abstract: A key impact measure of COVID-19 pandemic is the case fatality rate (CFR), but estimating it during an epidemic is challenging as the true number of cases may remain elusive.  To estimate the CFR applying a delay-adjusted method across countries, exploring differences to simple methods and potential correlation to country level variables.  Secondary analysis of publicly available data from countries with [≥]500 cases by April 30th. We calculated CFR adjusting for delay time from diagnosis to death and using simple methods for comparison. We performed a random effects meta-analysis to pooling CFRs for all countries and for those with high testing coverage and low positivity rate. We explored correlation of adjusted CFR with age structure and health care resources at country level.  We included 107 countries and the Diamond Princess cruise-ship. The overall delay adjusted CFR was 2.8% (95%CI: 2.1 to 3.1) while naive CFR was 5.1% (95%CI: 4.1 to 6.2). In countries with high testing coverage/low positivity rate the pooled adjusted CFR was 2.1% (95%CI: 1.5 to 3.0), there was a correlation with age over 65 years ({beta} = 0.12; 95%CI: 0.06 to 0.18), but not with number of physician or critical care beds. Naive method underestimated the CFR of the CFR with a median of 1.3% across countries.  Our best estimation of CFR across countries is 2% and varies according to the aged population size. Modelers and policy makers may consider these results to assess the impact of lockdowns or other mitigation policies.

title: Public health measures to slow community spread of COVID-19 ;The Journal of Infectious Diseases ;Oxford Academic
abstract: COVID-19 was initially identified in an outbreak of viral pneumonia in Wuhan in December 2019, and has now been recognized in 77 countries with over 90,000 laboratory-confirmed cases and over 3,000 deaths as of 3 March 2020  The epidemiology of COVID-19 has recently become clearer as incident cases continue to rise and researchers refine estimates of the severity, transmissibility, and populations affected Based on available data, COVID-19 is efficiently transmitted in the community, and the proportion of infections leading to severe illness is particularly high among adults ≥50 years of age and among individuals with comorbid health conditions Although rare, severe cases have also been reported among younger individuals Thus far, the estimated basic reproductive number (R0) of COVID-19 is higher than that of influenza , as is the case fatality risk for adults and older individuals An estimated 80% of COVID-19 cases are mild  This is not a glass half full statistic, as 20% of infections result in clinically severe cases that have the potential to overwhelm already overburdened health facilities Given the lack of vaccines and effective antivirals, nonpharmaceutical interventions (NPIs) are the most effective available interventions for local and global control and mitigation of COVID-19 To date, measures aimed at slowing introduction of infection globally have included travel restrictions, isolation of confirmed cases, and quarantine of exposed persons In the United States, NPIs have reduced the number of infected persons entering the country, but recent outbreaks in multiple US states make it clear that these measures have delayed but not prevented community transmission In 2009, NPIs were able to delay large epidemic waves of pandemic influenza A(H1N1)pdm09 in some locations until after the summer, since influenza transmission tends to be reduced by higher temperatures and humidity It is unclear whether COVID-19 transmission will be heavily affected by seasonal weather variation, given that transmission is now occurring in multiple tropical and sub-tropical locations

title: 2019-novel coronavirus outbreak: A new challenge
abstract: Following the public health emergency declared by the World Health Organization and the recent outbreak by 2019-nCoV in China and through other 29 countries, we aimed to summarize the clinical aspects of novel beta-coronavirus infection and its possible clinical presentations together with suggested therapeutic algorithms for patients who may require antibiotic treatment.  We reviewed the currently available literature of microbiologically confirmed infections by 2019-ConV (or COVID-19) occurred at the time of writing (13 February 2020). A literature search was performed using the PubMed database and the Cochrane library. Search terms included "novel coronavirus" or "2019-nCoV" or “COVID-19”.  Published cases occurred mostly in males (age ranged from 8 to 92). Cardiovascular, digestive and endocrine system diseases were commonly reported, except previous chronic pulmonary diseases (e.g., COPD, asthma, bronchiectasis) that were surprisingly underreported. Fever was presented in all the case series available, flanked by cough, dyspnea, myalgias and fatigue. Multiple bilateral lobular and subsegmental areas of consolidation or bilateral ground-glass opacities were the main reported radiological features of 2019-nCoV, at least in the early phases of disease.  The new 2019-nCoV epidemics is mainly associated with respiratory disease and few extrapulmonary signs. However, there is a low rate of associated pre-existing respiratory comorbidities.

title: Estimating the daily trend in the size of the COVID-19 infected population in Wuhan
abstract: There has been an outbreak of coronavirus disease (COVID-19) in Wuhan city, Hubei province, China since December 2019. Cases have been exported to other parts of China and more than 20 countries. We provide estimates of the daily trend in the size of the epidemic in Wuhan based on detailed information of 10,940 confirmed cases outside Hubei province.

title: Analysis of Serologic Cross-Reactivity Between Common Human Coronaviruses and SARS-CoV-2 Using Coronavirus Antigen Microarray
abstract: The current practice for diagnosis of SARS-CoV-2 infection relies on PCR testing of nasopharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk. This testing strategy likely underestimates the true prevalence of infection, creating the need for serologic methods to detect infections missed by the limited testing to date. Here, we describe the development of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A preliminary study of human sera collected prior to the SARS-CoV-2 pandemic demonstrates overall high IgG reactivity to common human coronaviruses and low IgG reactivity to epidemic coronaviruses including SARS-CoV-2, with some cross-reactivity of conserved antigenic domains including S2 domain of spike protein and nucleocapsid protein. This array can be used to answer outstanding questions regarding SARS-CoV-2 infection, including whether baseline serology for other coronaviruses impacts disease course, how the antibody response to infection develops over time, and what antigens would be optimal for vaccine development.

title: The effects of border control and quarantine measures on global spread of COVID-19
abstract: The rapid expansion of coronavirus (COVID-19) has been observed in many parts of the world. Many newly reported cases of this new coronavirus during early outbreak phases have been associated with travel history from an epidemic region (identified as imported cases). For those cases without travel history, the risk of wider spreads through community contact is even higher. However, most population models assume a homogeneous infected population without considering that the imported and secondary cases contracted by the imported cases can pose a different risk to community spread. We have developed an “easy-to-use” mathematical framework extending from a meta-population model embedding city-to-city connections to stratify the dynamics of transmission waves caused by imported, secondary, and others from an outbreak source region when control measures are considered. Using the dynamics of the secondary cases, we are able to determine the probability of community spread. Using the top 10 visiting cities from Wuhan in China as an example, we first demonstrated that the arrival time and the dynamics of the outbreaks at these cities can be successfully predicted under the reproductive number R0 = 2.92 and latent period τ = 5.2 days. Next, we showed that although control measures can gain extra 32.5 and 44.0 days in arrival time through a high intensive border control measure and a shorter time to quarantine under a low R0 (1.4), if the R0 is higher (2.92), only 10 extra days can be gained for each of the same measures. This suggests the importance of lowering the incidence at source regions together with infectious disease control measures in susceptible regions. The study allows us to assess the effects of border control and quarantine measures on the emergence and the global spread in a fully connected world using the dynamics of the secondary cases.

title: The COVID-19 pandemic: implications for the cytology laboratory
abstract: The coronavirus disease 2019 (COVID-19) is a pandemic caused by the SARS-CoV-2 virus. The infection has predominantly respiratory transmission and is transmitted through large droplets or aerosols, and less commonly by contact with infected surfaces or fomites. The alarming spread of the infection and the severe clinical disease that it may cause have led to the widespread institution of social distancing measures. Because of repeated exposure to potentially infectious patients and specimens, health care and laboratory personnel are particularly susceptible to contract COVID-19. This review paper provides an assessment of the current state of knowledge about the disease and its pathology, and the potential presence of the virus in cytology specimens. It also discusses the measures that cytology laboratories can take to function during the pandemic, and minimize the risk to their personnel, trainees, and pathologists. In addition, it explores potential means to continue to educate trainees during the COVID-19 pandemic.

title: Estimates of the Undetected Rate among the SARS-CoV-2 Infected using Testing Data from Iceland
abstract: Testing for SARS-CoV-2 in the United States is currently targeted to individuals whose symptoms and/or jobs place them at a high presumed risk of infection. An open question is, what is the share of infections that are undetected under current testing guidelines? To answer this question, we turn to COVID-19 testing data from Iceland. The criteria for testing within the Icelandic medical system, processed by the National University Hospital of Iceland (NUHI), have also been targeted at high-risk individuals, but additionally most Icelanders qualify for voluntary testing through the biopharmaceutical company deCODE genetics. We use results from Iceland's two testing programs to estimate the share of infections that are undetected under standard (NUHI) testing guidelines. Because of complications in the deCODE testing regime, it is not possible to estimate a single value for this this undetected rate; however, a range can be estimated. Our primary estimates for the fraction of infections that are undetected range from 88.7% to 93.6%.

title: Open Data Resources for Fighting COVID-19
abstract: We provide an insight into the open data resources pertinent to the study of the spread of Covid-19 pandemic and its control. We identify the variables required to analyze fundamental aspects like seasonal behaviour, regional mortality rates, and effectiveness of government measures. Open data resources, along with data-driven methodologies, provide many opportunities to improve the response of the different administrations to the virus. We describe the present limitations and difficulties encountered in most of the open-data resources. To facilitate the access to the main open-data portals and resources, we identify the most relevant institutions, at a world scale, providing Covid-19 information and/or auxiliary variables (demographics, mobility, etc.). We also describe several open resources to access Covid-19 data-sets at a country-wide level (i.e. China, Italy, Spain, France, Germany, U.S., etc.). In an attempt to facilitate the rapid response to the study of the seasonal behaviour of Covid-19, we enumerate the main open resources in terms of weather and climate variables.  The authors of this paper belong to the CONtrol COvid-19 Team, which is composed of different researches from universities of Spain, Italy, France, Germany, United Kingdom and Argentina. The main goal of CONCO-Team is to develop data-driven methods for the better understanding and control of the pandemic.

title: Unprecedented disruptions of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak
abstract: We assess the health and wellbeing of normal adults living and working after one month of confinement to contain the COVID-19 outbreak in China. On Feb 20 and 21, 2020, we surveyed 369 adults in 64 cities in China that varied in their rates of confirmed coronavirus cases on their health conditions, distress and life satisfaction. 27% of the participants worked at the office, 38% resorted to working from home, and 25% stopped working due to the outbreak. Those who stopped working reported worse mental and physical health conditions as well as distress. The severity of COVID-19 in a location predicts life satisfaction, and this relationship is contingent upon the existing chronic health issues and hours of exercise of the individuals. Our evidence supports the need to pay attention to the health of people who were not affected by the virus epidemiologically, especially for people who stopped working during the outbreak. Our results highlight that physically active people might be more susceptible to wellbeing issues during the lockdown. Policymakers who are considering introducing restrictive measures to contain COVID-19 may benefit from understanding such health and wellbeing implications.

title: [Management and clinical thinking of Coronavirus Disease 2019]
abstract: In December 2019, the 2019 novel coronavirus pneumonia (NCP, officially named Coronavirus Disease 2019(COVID-19) by the World Health Organization) broke out in Wuhan, Hubei, and it quickly spread to the whole country and abroad. The situation was at stake. The sudden and serious COVID-19 epidemic has brought us a lot of urgent problems. How to effectively control the spread of COVID-19? When does the population infection rate rise to its peak? What will eventually be the number of infected patients? How to make early diagnosis? What effective antiviral drugs are available? How to effectively treat with existing drugs? Can it successfully improve the survival rate of critically patients? In response to the above questions, we put forward corresponding suggestions and reflections from the perspective of the infectious clinician.

title: Modelling transmission and control of the COVID-19 pandemic in Australia
abstract: We develop an agent-based model for a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to reproduce key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits, unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13--14 weeks, when coupled with effective case isolation and international travel restrictions.

title: Incidence of novel coronavirus (2019-nCoV) infection among people under home quarantine in Shenzhen, China
abstract: Since the outbreak of 2019-nCoV in December, Chinese government has implemented various measures including travel bans, centralized treatments, and home quarantines to slowing the transmission across the country. In this study, we aimed to estimate the incidence of 2019-nCoV infection among people under home quarantine in Shenzhen, China.  We used a stratified multistage random sampling method to recruit participants and collected demographic information and laboratory results of people under home quarantine. We conducted descriptive analysis to estimate the basic characteristics and to calculate the incidence in out study population.  A total of 2004 people under home quarantine participated in this study, of which 1637 participants finished the questionnaire with a response rate of 81.7%. Mean age of the participants was 33.7 years, ranging from 0.3 to 80.2 years. Of people who provided clear travel history, 129 people have traveled to Wuhan city and 1,046 people have traveled to other cities in Hubei province within 14 days before the home quarantine. Few (less than 1%) participants reported contact history with confirmed or suspected cases during their trip and most of these arrived at Shenzhen between Jan 24, 2020 to Jan 27, 2020. The incidence of COVID-19 in the sample was 1.5‰ (95% CI: 0.31‰–4.37‰).  Home quarantine has been effective in preventing the early transmission of COVID-19, but that more needs to be done to improve early detection of COVID-19 infection.

title: Estimating the early death toll of COVID-19 in the United States
abstract: Efforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19.  We evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data.  There were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5–3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I.  Excess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity.

title: The value of mitigating epidemic peaks of COVID-19 for more effective public health responses

title: Genomic Characterization of a Newly Discovered Coronavirus Associated with Acute Respiratory Distress Syndrome in Humans
abstract: A novel human coronavirus (HCoV-EMC/2012) was isolated from a man with acute pneumonia and renal failure in June 2012. This report describes the complete genome sequence, genome organization, and expression strategy of HCoV-EMC/2012 and its relation with known coronaviruses. The genome contains 30,119 nucleotides and contains at least 10 predicted open reading frames, 9 of which are predicted to be expressed from a nested set of seven subgenomic mRNAs. Phylogenetic analysis of the replicase gene of coronaviruses with completely sequenced genomes showed that HCoV-EMC/2012 is most closely related to Tylonycteris bat coronavirus HKU4 (BtCoV-HKU4) and Pipistrellus bat coronavirus HKU5 (BtCoV-HKU5), which prototype two species in lineage C of the genus Betacoronavirus. In accordance with the guidelines of the International Committee on Taxonomy of Viruses, and in view of the 75% and 77% amino acid sequence identity in 7 conserved replicase domains with BtCoV-HKU4 and BtCoV-HKU5, respectively, we propose that HCoV-EMC/2012 prototypes a novel species in the genus Betacoronavirus. HCoV-EMC/2012 may be most closely related to a coronavirus detected in Pipistrellus pipistrellus in The Netherlands, but because only a short sequence from the most conserved part of the RNA-dependent RNA polymerase-encoding region of the genome was reported for this bat virus, its genetic distance from HCoV-EMC remains uncertain. HCoV-EMC/2012 is the sixth coronavirus known to infect humans and the first human virus within betacoronavirus lineage C.

title: On Accelerated Testing for COVID-19 Using Group Testing
abstract: COVID-19 has resulted in a global health crisis that may become even more acute over the upcoming months. One of the main reasons behind the current rapid growth of COVID-19 in the U.S. population is the limited availability of testing kits and the relatively-high cost of screening tests. In this draft, we demonstrate the effectiveness of group testing (pooling) ideas to accelerate testing for COVID-19. This draft is semi-tutorial in nature and is written for a broad audience with interest in mathematical formulations relevant to COVID-19 testing. Therefore, ideas are presented through illustrative examples rather than through purely theoretical formulations. The focus is also on pools of size less than 64 such as what is practical with current RT-PCR technology.

title: Variation of positiveness to enhance testing of specimens during an epidemic
abstract: Rapid testing of appropriate specimens from patients suspected for a disease during an epidemic, such as the current Coronavirus outbreak, is of a great importance for the disease management and control. We propose a method to enhance processing large amounts of collected samples. The method is based on mixing samples in testing tubes in a specific configuration, as opposed to testing single samples in each tube, and accounting for natural virus amounts in infected patients from variation of positiveness in test tubes. To illustrate the efficiency of the suggested method we carry out numerical tests for actual scenarios under various tests. Applying the proposed method enhances the number of tests by order of magnitudes, where all positives are identified with no false negatives, and the effective testing time can be reduced drastically even when the uncertainty in the test is relatively high.

title: An epidemiological forecast model and software assessing interventions on COVID-19 epidemic in China
abstract: We develop a health informatics toolbox that enables public health workers to timely analyze and evaluate the time-course dynamics of the novel coronavirus (COVID-19) infection using the public available data from the China CDC. This toolbox is built upon a hierarchical epidemiological model in which two observed time series of daily proportions of infected and removed cases are emitted from the underlying infection dynamics governed by a Markov SIR infectious disease process. We extend the SIR model to incorporate various types of time-varying quarantine protocols, including government-level macro isolation policies and community-level micro inspection measures. We develop a calibration procedure for under-reported infected cases. This toolbox provides forecast, in both online and offline forms, of turning points of interest, including the time when daily infected proportion becomes smaller than the previous ones and the time when daily infected proportions becomes smaller than that of daily removed proportion, as well as the ending time of the epidemic. An R software is made available for the public, and examples on the use of this software are illustrated. Some possible extensions of our novel epidemiological models are discussed.

title: Dynamic profile for the detection of anti-SARS-CoV-2 antibodies using four immunochromatographic assays
abstract: In order to fight the SARS-CoV-2 pandemic infection, there is a growing need and demand for diagnostic tools that are complementary and different from the RT-PCR currently in use. Multiple serological tests are or will be very soon available but need to be evaluated and validated. We have thus tested 4 immunochromatographic tests for the detection of antibodies to SARS-CoV-2. In addition, we assessed the kinetics of antibody appearance using these assays in 22 patients after they were tested positive by RT-PCR. We observed great heterogeneity in antiboy detection post-symptom onset. The median antibody detection time was between 8 and 10 days according to the manufacturers. All the tests showed a sensitivity of 60 to 80% on day 10 and 100% on day 15. In addition, a single cross-reaction was observed with other human coronavirus infections. Thus, immunochromatographic tests for the detection of anti-SARS-CoV-2 antibodies may have their place for the diagnostic panel of COVID-19.

title: Risk for Transportation of 2019 Novel Coronavirus (COVID-19) from Wuhan to Cities in China
abstract: On January 23, 2020, China quarantined Wuhan to contain an emerging coronavirus (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 cities in China before the quarantine. The expected risk is >50% in 130 (95% CI 89–190) cities and >99% in the 4 largest metropolitan areas of China.

title: Importance of diagnostics in epidemic and pandemic preparedness
abstract: Diagnostics are fundamental for successful outbreak containment. In this supplement, ‘Diagnostic preparedness for WHO Blueprint pathogens’, we describe specific diagnostic challenges presented by selected priority pathogens most likely to cause future epidemics. Some challenges to diagnostic preparedness are common to all outbreak situations, as highlighted by recent outbreaks of Ebola, Zika and yellow fever. In this article, we review these overarching challenges and explore potential solutions. Challenges include fragmented and unreliable funding pathways, limited access to specimens and reagents, inadequate diagnostic testing capacity at both national and community levels of healthcare and lack of incentives for companies to develop and manufacture diagnostics for priority pathogens during non-outbreak periods. Addressing these challenges in an efficient and effective way will require multiple stakeholders—public and private—coordinated in implementing a holistic approach to diagnostics preparedness. All require strengthening of healthcare system diagnostic capacity (including surveillance and education of healthcare workers), establishment of sustainable financing and market strategies and integration of diagnostics with existing mechanisms. Identifying overlaps in diagnostic development needs across different priority pathogens would allow more timely and cost-effective use of resources than a pathogen by pathogen approach; target product profiles for diagnostics should be refined accordingly. We recommend the establishment of a global forum to bring together representatives from all key stakeholders required for the response to develop a coordinated implementation plan. In addition, we should explore if and how existing mechanisms to address challenges to the vaccines sector, such as Coalition for Epidemic Preparedness Innovations and Gavi, could be expanded to cover diagnostics.

title: Climate effect on COVID-19 spread rate: an online surveillance tool
abstract: COVID-19 outbreak poses an unprecedented challenge for societies, healthcare organizations and economies. In the present analysis we coupled climate data with COVID-19 spread rates worldwide, and in a single country (USA).  Data of confirmed COVID-19 cases was derived from the COVID-19 Global Cases by the CSSE at Johns Hopkins University up to March 19, 2020. We assessed disease spread by two measures: replication rate (RR), the slope of the logarithmic curve of confirmed cases, and the rate of spread (RoS), the slope of the linear regression of the logarithmic curve.  Based on predefined criteria, the mean COVID-19 RR was significantly lower in warm climate countries (0.12± 0.02) compared with cold countries (0.24± 0.01), (P<0.0001). Similarly, RoS was significantly lower in warm climate countries 0.12± 0.02 vs. 0.25± 0.01 than in cold climate countries (P<0.001). In all countries (independent of climate classification) both RR and RoS displayed a moderate negative correlation with temperature R= -0.69, 95% confidence interval [CI], -0.87 to -0.36; P<0.001 and R= -0.72, 95% confidence interval [CI], -0.87 to -0.36; P<0.001, respectively. We identified a similar moderate negative correlation with the dew point temperature. Additional climate variables did not display a significant correlation with neither RR nor RoS. Finally, in an ancillary analysis, COVID-19 intra-country model using an inter-state analysis of the USA did not identify yet correlation between climate parameters and RR or RoS as of March, 19, 2020.  Our analysis suggests a plausible negative correlation between warmer climate and COVID-19 spread rate as defined by RR and RoS worldwide. This initial correlation should be interpreted cautiously and be further validated over time, the pandemic is at different stages in various countries as well as in regions within these countries. As such, some associations may be more affected by local transmission patterns rather than by climate. Importantly, we provide an online surveillance dashboard (https://covid19.net.technion.ac.il/) to further assess the association between climate parameters and outbreak dynamics worldwide as time goes by

title: COVID-19, Australia: Epidemiology Report 16 (Reporting week to 23:59 AEST 17 May 2020)
abstract: Confirmed cases in Australia notified up to 17 May 2020: notifications = 7,075; deaths = 100. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. Social distancing measures, public health action and the reduction in international travel have likely been effective in slowing the spread of the disease, in the Australian community. Testing rates over the past week have increased markedly, with a continued very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. New cases of COVID-19 are currently being reported by by only some jurisdictions, albeit at relatively low rates. Although case numbers are low, new cases tend to still be a mix of overseas-acquired and locally-acquired infections. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of new cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years. One third of all cases in this age group have been associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, while the number of new cases each day remains relatively stable at the global level, some areas such as Brazil and India are showing a dramatic rise in reported cases. Although some low-income countries have so far reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of true disease incidence.

title: Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China
abstract: Studies have reminded that cardiovascular metabolic comorbidities made patients more susceptible to suffer 2019 novel corona virus (2019-nCoV) disease (COVID-19), and exacerbated the infection. The aim of this analysis is to determine the association of cardiovascular metabolic diseases with the development of COVID-19.  A meta-analysis of eligible studies that summarized the prevalence of cardiovascular metabolic diseases in COVID-19 and compared the incidences of the comorbidities in ICU/severe and non-ICU/severe patients was performed. Embase and PubMed were searched for relevant studies.  A total of six studies with 1527 patients were included in this analysis. The proportions of hypertension, cardia-cerebrovascular disease and diabetes in patients with COVID-19 were 17.1%, 16.4% and 9.7%, respectively. The incidences of hypertension, cardia-cerebrovascular diseases and diabetes were about twofolds, threefolds and twofolds, respectively, higher in ICU/severe cases than in their non-ICU/severe counterparts. At least 8.0% patients with COVID-19 suffered the acute cardiac injury. The incidence of acute cardiac injury was about 13 folds higher in ICU/severe patients compared with the non-ICU/severe patients.  Patients with previous cardiovascular metabolic diseases may face a greater risk of developing into the severe condition and the comorbidities can also greatly affect the prognosis of the COVID-19. On the other hand, COVID-19 can, in turn, aggravate the damage to the heart.

title: Vaccine against Middle East respiratory syndrome coronavirus

title: Treatment and vaccines for severe acute respiratory syndrome
abstract: The causative agent of severe acute respiratory syndrome (SARS), which affected over 8000 individuals worldwide and was responsible for over 700 deaths in the 2002–2003 outbreak, is a coronavirus that was unknown before the outbreak. Although many different treatments were used during the outbreak, none were implemented in a controlled fashion. Thus, the optimal treatment for SARS is unknown. Since the outbreak, much work has been done testing new agents against SARS using in-vitro methods and animal models. In addition, global research efforts have focused on the development of vaccines against SARS. Efforts should be made to evaluate the most promising treatments and vaccines in controlled clinical trials, should another SARS outbreak occur.

title: Epidemic Landscape and Forecasting of SARS-CoV-2 in India
abstract: India was one of the countries to institute strict measures for SARS-CoV-2 control in early phase. Since, then, the epidemic growth trajectory was slow before registering an explosion of cases due to local cluster transmissions.  We estimated growth rate and doubling time of SARS-CoV-2 for India and high burden states using crowd sourced time series data. Further, we also estimated Basic Reproductive Number (R0) and time dependent reproductive number (Rt) using serial intervals from the data. We compared the R0 estimated from five different methods and R0 from SB was further used in analysis. We modified standard SIR models to SIRD model to accommodate deaths using R0 with the Sequential Bayesian method (SBM) for simulation in SIRD models.  On an average, 2.8 individuals were infected by an index case. The mean serial interval was 3.9 days. The R0 estimated from different methods ranged from 1.43 to 1.85. The mean time to recovery was 14, SD 5.3 days. Daily epidemic growth rate of India was 0.16 [95%CI; 0.14, 0.17] with a doubling time of 4.30 days [95%CI; 3.96, 4.70]. From the SIRD model, it can be deduced that the peak of SARS-CoV-2 in India will be around mid-July to early August 2020 with around 12.5% likely to be infected at peak time of incidence.  The pattern of spread of SARS-CoV-2 in India is suggestive of community transmission. There is a need to increase fund for infectious disease research and epidemiologic studies. All the current gains may be reversed rapidly if air travel and social mixing resumes rapidly. For the time being, these must be resumed only in a phased manner, and should be back to normal levels only after we are prepared to deal with the disease with efficient tools like vaccine or a medicine.

title: Lianhuaqingwen exerts anti-viral and anti-inflammatory activity against novel coronavirus (SARS-CoV-2)
abstract: Lianhuaqingwen (LH) as traditional Chinese medicine (TCM) formula has been used to treat influenza and exerted broad-spectrum antiviral effects on a series of influenza viruses and immune regulatory effects Ding et al. (2017). The goal of this study is to demonstrate the antiviral activity of LH against the novel SARS-CoV-2 virus and its potential effect in regulating host immune response.  The antiviral activity of LH against SARS-CoV-2 was assessed in Vero E6 cells using CPE and plaque reduction assay. The effect of LH on virion morphology was visualized under transmission electron microscope. Pro-inflammatory cytokine expression levels upon SARS-CoV-2 infection in Huh-7 cells were measured by real-time quantitative PCR assays.  LH significantly inhibited SARS-CoV-2 replication in Vero E6 cells and markedly reduced pro-inflammatory cytokines (TNF-α, IL-6, CCL-2/MCP-1 and CXCL-10/IP-10) production at the mRNA levels. Furthermore, LH treatment resulted in abnormal particle morphology of virion in cells.  LH significantly inhibits the SARS-COV-2 replication, affects virus morphology and exerts anti-inflammatory activity in vitro. These findings indicate that LH protects against the virus attack, making its use a novel strategy for controlling the COVID-19 disease.

title: Testing Asymptomatic Emergency Department Patients for Coronavirus Disease 2019 (COVID-19) in a Low-prevalence Region

title: Characterization of a novel coronavirus responsible for severe acute respiratory syndrome
abstract: In February, a new avian H5N1/03 virus took two persons' lives in Hong Kong. After this incidence, a newly emerged disease has been identified, associated with pneumonia in infected patients. Here we report that a newly discovered coronoavirus (Cov) is responsible for this disease. In addition, the basic features, diagnosis and possible animal sources of Severe Acute Respiratory Syndrome (SARS) Cov are also discussed.

title: Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status
abstract: It has been 2 months since the first case of coronavirus disease 2019 (COVID-19) was reported in Wuhan, China. So far, COVID-19 has affected 85 403 patients in 57 countries/territories and has caused 2924 deaths in 9 countries. However, epidemiological data differ between countries. Although China had higher morbidity and mortality than other sites, the number of new daily cases in China has been lower than outside of China since 26 February 2020. The incidence ranged from 61.44 per 1 000 000 people in the Republic of Korea to 0.0002 per 1 000 000 people in India. The daily cumulative index (DCI) of COVID-19 (cumulative cases/no. of days between the first reported case and 29 February 2020) was greatest in China (1320.85), followed by the Republic of Korea (78.78), Iran (43.11) and Italy (30.62). However, the DCIs in other countries/territories were <10 per day. Several effective measures including restricting travel from China, controlling the distribution of masks, extensive investigation of COVID-19 spread, and once-daily press conferences by the government to inform and educate people were aggressively conducted in Taiwan. This is probably the reason why there was only 39 cases (as of 29 February 2020) with a DCI of 1 case per day in Taiwan, which is much lower than that of nearby countries such as the Republic of Korea and Japan. In addition, the incidence and mortality were correlated with the DCI. However, further study and continued monitoring are needed to better understand the underlying mechanism of COVID-19.

title: A human monoclonal antibody blocking SARS-CoV-2 infection
abstract: The emergence of the novel human coronavirus SARS-CoV-2 in Wuhan, China has caused a worldwide epidemic of respiratory disease (COVID-19). Vaccines and targeted therapeutics for treatment of this disease are currently lacking. Here we report a human monoclonal antibody that neutralizes SARS-CoV-2 (and SARS-CoV). This cross-neutralizing antibody targets a communal epitope on these viruses and offers potential for prevention and treatment of COVID-19.

title: Transmission and epidemiological characteristics of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected Pneumonia (COVID-19): preliminary evidence obtained in comparison with 2003-SARS
abstract: Latest epidemic data of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected Pneumonia (COVID-19) was collected and a detailed statistical analysis was carried out to make comparison with 2003-SARS in order to provide scientific reference for the prevention and control of COVID-19.  The information of COVID-19 and 2003-SARS from websites of NHCPRC and the World Health Organization was collected, and then the transmission dynamics of the two kinds of infectious diseases were analyzed. The information of 853 confirmed COVID-19 patients obtained from the website of health committees of 18 provinces. A descriptive epidemiological analysis method was employed to carefully analyze the epidemic characteristics. Subsequently, the COVID-19 epidemic data in Wuhan and other inland regions of China was analyzed separately and compared. A multivariate function model was constructed based on the confirmed COVID-19 case data.  The growth rate of new cases and deaths of COVID-19 were significantly faster than those of 2003-SARS. The number of confirmed cases in Wuhan and other inland areas both showed increasing trends. 853 confirmed COVID-19 cases aged 1 months to 94 years and the average age was (45.05 ± 17.22) years. The gender ratio (M: F) was 1.12: 1.  The fatality rate of COVID-19 is lower than that of 2003-SARS and the cure rate is higher. The age of COVID-19 patients is mainly concentrated in the 30-50 years old (60.61%). The harm of the first-generation COVID-19 patients is higher than that of secondary cases.

title: Rapid implementation of mobile technology for real-time epidemiology of COVID-19
abstract: The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.25 million users to date. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge.

title: A multicentre collaboration to investigate the cause of severe acute respiratory syndrome
abstract: Acute respiratory syndrome is a new disease in human beings, first recognised in late February, 2003, in Hanoi, Vietnam. The severity of the disease, combined with its rapid spread along international air-travel routes, prompted WHO to set up a network of scientists from 11 laboratories around the world to try to identify the causal agent and develop a diagnostic test. The network unites laboratories with different methods and capacities to rapidly fulfil all postulates for establishing a virus as the cause of a disease. Results are shared in real time via a secure website, on which microscopy pictures, protocols for testing, and PCR primer sequences are also posted. Findings are discussed in daily teleconferences. Progress is further facilitated through sharing between laboratories of samples and test materials. The network has identified a new coronavirus, consistently detected in samples of SARS patients from several countries, and conclusively named it as the causative agent of SARS; the strain is unlike any other known member of the genus Coronavirus. Three diagnostic tests are now available, but all have limitations.

title: Group Testing for COVID-19: How to Stop Worrying and Test More
abstract: The corona virus disease 2019 (COVID-19) caused by the novel corona virus has an exponential rate of infection. COVID-19 is particularly notorious as the onset of symptoms in infected patients are usually delayed and there exists a large number of asymptomatic carriers. In order to prevent overwhelming of medical facilities and large fatality rate, early stage testing and diagnosis are key requirements. In this article, we discuss the methodologies from the group testing literature and its relevance to COVID-19 diagnosis. Specifically, we investigate the efficiency of group testing using polymerase chain reaction (PCR) for COVID-19. Group testing is a method in which multiple samples are pooled together in groups and fewer tests are performed on these groups to discern all the infected samples. We study the effect of dilution due to pooling in group testing and show that group tests can perform well even in the presence of dilution effects. We present multiple group testing algorithms that could reduce the number of tests performed for COVID-19 diagnosis. We analyze the efficiency of these tests and provide insights on their practical relevance. With the use of algorithms described here, test plans can be developed that can enable testing centers to increase the number of diagnosis performed without increasing the number of PCR tests. The codes for generating test plans are available online at .

title: Estimating Preventable COVID19 Infections Related to Elective Outpatient Surgery in Washington State: A Quantitative Model
abstract: As the number of suspected and confirmed COVID19 cases in the US continues to rise, the US surgeon general, Centers for Disease Control and Prevention, and several specialty societies have issued recommendations to consider canceling elective surgeries. However, these recommendations have also faced controversy and opposition.  The goal of this study is to provide a quantitative analysis and model for preventable COVID19 infections from elective outpatient or ambulatory surgery cases, which can also be adapted to analyze COVID19 transmission in other healthcare settings. Furthermore, given the controversy over the appropriate handling of elective surgical cases during this pandemic, we hope that our results may have a positive impact on health policy and public health.  Using previously published information on elective ambulatory or outpatient surgical procedures and publicly available data on COVID19 infections in the US and on the Diamond Princess cruise ship, we calculated a transmission rate and generated a mathematical model to predict a lower bound for the number of healthcare-acquired COVID19 infections that could be prevented by canceling or postponing elective outpatient surgeries in Washington state.  Our model predicts that over the course of 30 days, at least 2445 preventable patient infections and at least 1557 preventable healthcare worker (HCW) infections would occur in WA state alone if elective outpatient procedures were to continue as usual. The majority of these infections are caused by transmission from HCW who became infected at work.  Given the large numbers of COVID19 infections that could be prevented by canceling elective outpatient surgeries, our findings support the recommendations of the US Surgeon General, CDC, American College of Surgeons (ACS), American Society of Anesthesiologists (ASA), and Anesthesia Patient Safety Foundation (APSF) to consider rescheduling or postponing elective surgeries until the COVID19 pandemic is under better control in the US.

title: Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modelling study in Hubei, China and northern Italy
abstract: The epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that originated in Wuhan, China in late 2019 is now pandemic. Reliable estimates of death from coronavirus disease 2019 (COVID-19) are essential to guide control efforts and to plan health care system requirements. The objectives of this study are to: 1) simulate the transmission dynamics of SARS-CoV-2 using publicly available surveillance data; 2) give estimates of SARS-CoV-2 mortality adjusted for bias in the two regions with the world's highest numbers of confirmed Covid-19 deaths: Hubei province, China and northern Italy.  We developed an age-stratified susceptible-exposed-infected-removed (SEIR) compartmental model describing the dynamics of transmission and mortality during the SARS-CoV-2 epidemic. Our model accounts for two biases; preferential ascertainment of severe cases and delayed mortality (right-censoring). We fitted our transmission model to surveillance data from Hubei province (1 January to 11 February 2020) and northern Italy (8 February to 3 March 2020). Overall mortality among all symptomatic and asymptomatic infections was estimated to be 3.0% (95% credible interval: 2.6-3.4%) in Hubei province and 3.3% (2.0-4.7%) in northern Italy. Mortality increased with age; we estimate that among 80+ year olds, 39.0% (95%CrI: 31.1-48.9%) in Hubei province and 89.0% (95%CrI: 56.2-99.6%) in northern Italy dies or will die. Limitations are that the model requires data recorded by date of onset and that sex-disaggregated mortality was not available.  We developed a mechanistic approach to correct the crude CFR for bias due to right-censoring and preferential ascertainment and provide adjusted estimates of mortality due to SARS-CoV-2 infection by age group. While specific to the situation in Hubei, China and northern Italy during these periods, these findings will help the mitigation efforts and planning of resources as other regions prepare for SARS-CoV-2 epidemics.

title: SARS-CoV-2 detection using digital PCR for COVID-19 diagnosis, treatment monitoring and criteria for discharge
abstract: SARS-CoV-2 nucleic acid detection by RT-PCR is one of the criteria approved by China FDA for diagnosis of COVID-19. However, inaccurate test results (for example, high false negative rate and some false positive rate) were reported in both China and US CDC using the RT-PCR method. Inaccurate results are caused by inadequate detection sensitivity of RT-PCR, low viral load in some patients, difficulty to collect samples from COVID-19 patients, insufficient sample loading during RT-PCR tests, and RNA degradation during sample handling process. False negative detection could subject patients to multiple tests before diagnosis can be made, which burdens health care system. Delayed diagnosis could cause infected patients to miss the best treatment time window. False negative detection could also lead to prematurely releasing infected patients who still carry residual SARS-CoV-2 virus. In this case, these patients could infect many others. A high sensitivity RNA detection method to resolve the existing issues of RT-PCR is in need for more accurate COVID-19 diagnosis.  Digital PCR (dPCR) instrument DropX-2000 and assay kits were used to detect SARS-CoV-2 from 108 clinical specimens from 36 patients including pharyngeal swab, stool and blood from different days during hospitalization. Double-blinded experiment data of 108 clinical specimens by dPCR methods were compared with results from officially approved RT-PCR assay. A total of 109 samples including 108 clinical specimens and 1 negative control sample were tested in this study. All of 109 samples, 26 were from 21patients reported as positive by officially approved clinical RT-PCR detection in local CDC and then hospitalized in Nantong Third Hospital. Among the 109 samples, dPCR detected 30 positive samples on ORFA1ab gene, 47 samples with N gene positive, and 30 samples with double positive on ORFA1ab and N genes.  The lower limit of detection of the optimize dPCR is at least 10-fold lower than that of RT-PCR. The overall accuracy of dPCR for clinical detection is 96.3%. 4 out 4 of (100 %) negative pharyngeal swab samples checked by RT-PCR were positive judged by dPCR based on the follow-up investigation. 2 of 2 samples in the RT-PCR grey area (Ct value > 37) were confirmed by dPCR with positive results. 1 patient being tested positive by RT-PCR was confirmed to be negative by dPCR. The dPCR results show clear viral loading decrease in 12 patients as treatment proceed, which can be a useful tool for monitoring COVID-19 treatment.  Digital PCR shows improved lower limit of detection, sensitivity and accuracy, enabling COVID-19 detection with less false negative and false positive results comparing with RT-PCR, especially for the tests with low viral load specimens. We showed evidences that dPCR is powerful in detecting asymptomatic patients and suspected patients. Digital PCR is capable of checking the negative results caused by insufficient sample loading by quantifying internal reference gene from human RNA in the PCR reactions. Multi-channel fluorescence dPCR system (FAM/HEX/CY5/ROX) is able to detect more target genes in a single multiplex assay, providing quantitative count of viral load in specimens, which is a powerful tool for monitoring COVID-19 treatment.

title: The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak – an update on the status
abstract: An acute respiratory disease, caused by a novel coronavirus (SARS-CoV-2, previously known as 2019-nCoV), the coronavirus disease 2019 (COVID-19) has spread throughout China and received worldwide attention. On 30 January 2020, World Health Organization (WHO) officially declared the COVID-19 epidemic as a public health emergency of international concern. The emergence of SARS-CoV-2, since the severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002 and Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012, marked the third introduction of a highly pathogenic and large-scale epidemic coronavirus into the human population in the twenty-first century. As of 1 March 2020, a total of 87,137 confirmed cases globally, 79,968 confirmed in China and 7169 outside of China, with 2977 deaths (3.4%) had been reported by WHO. Meanwhile, several independent research groups have identified that SARS-CoV-2 belongs to β-coronavirus, with highly identical genome to bat coronavirus, pointing to bat as the natural host. The novel coronavirus uses the same receptor, angiotensin-converting enzyme 2 (ACE2) as that for SARS-CoV, and mainly spreads through the respiratory tract. Importantly, increasingly evidence showed sustained human-to-human transmission, along with many exported cases across the globe. The clinical symptoms of COVID-19 patients include fever, cough, fatigue and a small population of patients appeared gastrointestinal infection symptoms. The elderly and people with underlying diseases are susceptible to infection and prone to serious outcomes, which may be associated with acute respiratory distress syndrome (ARDS) and cytokine storm. Currently, there are few specific antiviral strategies, but several potent candidates of antivirals and repurposed drugs are under urgent investigation. In this review, we summarized the latest research progress of the epidemiology, pathogenesis, and clinical characteristics of COVID-19, and discussed the current treatment and scientific advancements to combat the epidemic novel coronavirus.

title: Estimation of the probability of reinfection with COVID-19 coronavirus by the SEIRUS model
abstract: With sensitivity of the Polymerase Chain Reaction (PCR) test used to detect the presence of the virus in the human host, the global health community has been able to record a great number of recovered population. Therefore, in a bid to answer a burning question of reinfection in the recovered class, the model equations which exhibits the disease-free equilibrium (E_0 ) state for COVID-19 coronavirus was developed in this study and was discovered to both exist as well as satisfy the criteria for a locally or globally asymptotic stability with a basic reproductive number R_0=0 for and endemic situation. Hence, there is a chance of no secondary reinfections from the recovered population as the rate of incidence of the recovered population vanishes, that is, B=0. Furthermore, numerical simulations were carried to complement the analytical results in investigating the effect of the implementation of quarantine and observatory procedures has on the projection of the further spread of the virus globally. Result shows that the proportion of infected population in the absence of curative vaccination will continue to grow globally meanwhile the recovery rate will continue slowly which therefore means that the ratio of infection to recovery rate will determine the death rate that is recorded globally and most significant for this study is the rate of reinfection by the recovered population which will decline to zero over time as the virus is cleared clinically from the system of the recovered class.

title: Confronting Another Pandemic: Lessons from HIV can Inform Our COVID-19 Response
abstract: The novel coronavirus 2019 illness (COVID-19) has completely transformed and uprooted lives across the globe. While different diseases, there are critical observations and lessons to be learned from the ongoing HIV epidemic to inform our response to COVID-19. We reflect on how this relates to (1) testing, including contact tracing; (2) health system redesign; (3) telehealth; (4) health disparities; (5) political denial, with inadequate and uncoordinated governmental response; (6) occupational exposure; and (7) complex reactions among healthcare providers. Decades of experiences with HIV provide an important framework for moving forward as we combat COVID-19.

title: A study of non-prescription usage of antibiotics in the upper respiratory tract infections in the urban population

title: MERS coronavirus: diagnostics, epidemiology and transmission
abstract: The first known cases of Middle East respiratory syndrome (MERS), associated with infection by a novel coronavirus (CoV), occurred in 2012 in Jordan but were reported retrospectively. The case first to be publicly reported was from Jeddah, in the Kingdom of Saudi Arabia (KSA). Since then, MERS-CoV sequences have been found in a bat and in many dromedary camels (DC). MERS-CoV is enzootic in DC across the Arabian Peninsula and in parts of Africa, causing mild upper respiratory tract illness in its camel reservoir and sporadic, but relatively rare human infections. Precisely how virus transmits to humans remains unknown but close and lengthy exposure appears to be a requirement. The KSA is the focal point of MERS, with the majority of human cases. In humans, MERS is mostly known as a lower respiratory tract (LRT) disease involving fever, cough, breathing difficulties and pneumonia that may progress to acute respiratory distress syndrome, multiorgan failure and death in 20 % to 40 % of those infected. However, MERS-CoV has also been detected in mild and influenza-like illnesses and in those with no signs or symptoms. Older males most obviously suffer severe disease and MERS patients often have comorbidities. Compared to severe acute respiratory syndrome (SARS), another sometimes- fatal zoonotic coronavirus disease that has since disappeared, MERS progresses more rapidly to respiratory failure and acute kidney injury (it also has an affinity for growth in kidney cells under laboratory conditions), is more frequently reported in patients with underlying disease and is more often fatal. Most human cases of MERS have been linked to lapses in infection prevention and control (IPC) in healthcare settings, with approximately 20 % of all virus detections reported among healthcare workers (HCWs) and higher exposures in those with occupations that bring them into close contact with camels. Sero-surveys have found widespread evidence of past infection in adult camels and limited past exposure among humans. Sensitive, validated reverse transcriptase real-time polymerase chain reaction (RT-rtPCR)-based diagnostics have been available almost from the start of the emergence of MERS. While the basic virology of MERS-CoV has advanced over the past three years, understanding of the interplay between camel, environment, and human remains limited.  contains supplementary material, which is available to authorized users.

title: Reconstructing and forecasting the COVID-19 epidemic in the United States using a 5-parameter logistic growth model
abstract: Many studies have modeled and predicted the spread of COVID-19 (coronavirus disease 2019) in the U.S. using data that begins with the first reported cases. However, the shortage of testing services to detect infected persons makes this approach subject to error due to its underdetection of early cases in the U.S. Our new approach overcomes this limitation and provides data supporting the public policy decisions intended to combat the spread of COVID-19 epidemic.  We used Centers for Disease Control and Prevention data documenting the daily new and cumulative cases of confirmed COVID-19 in the U.S. from January 22 to April 6, 2020, and reconstructed the epidemic using a 5-parameter logistic growth model. We fitted our model to data from a 2-week window (i.e., from March 21 to April 4, approximately one incubation period) during which large-scale testing was being conducted. With parameters obtained from this modeling, we reconstructed and predicted the growth of the epidemic and evaluated the extent and potential effects of underdetection.  The data fit the model satisfactorily. The estimated daily growth rate was 16.8% overall with 95% CI: [15.95, 17.76%], suggesting a doubling period of 4 days. Based on the modeling result, the tipping point at which new cases will begin to decline will be on April 7th, 2020, with a peak of 32,860 new cases on that day. By the end of the epidemic, at least 792,548 (95% CI: [789,162, 795,934]) will be infected in the U.S. Based on our model, a total of 12,029 cases were not detected between January 22 (when the first case was detected in the U.S.) and April 4.  Our findings demonstrate the utility of a 5-parameter logistic growth model with reliable data that comes from a specified period during which governmental interventions were appropriately implemented. Beyond informing public health decision-making, our model adds a tool for more faithfully capturing the spread of the COVID-19 epidemic.

title: Epidemic size of novel coronavirus-infected pneumonia in the Epicenter Wuhan: using data of five-countries' evacuation action
abstract: Since late December 2019, novel coronavirus-infected pneumonia (NCP) emerged in Wuhan, Hubei province, China. Meanwhile, NCP rapidly spread from China to other countries, and several countries' government rush to evacuate their citizens from Wuhan. We analyzed the infection rate of the evacuees and extrapolated the results in Wuhan's NCP incidence estimation.  We collected the total number and confirmed cases of 2019-nCov infection in the evacuation of Korea, Japan, Germany, Singapore, and France and estimated the infection rate of the 2019 novel coronavirus (2019-nCov) among people who were evacuated from Wuhan with a meta-analysis. NCP incidence of Wuhan was indirectly estimated based on data of evacuation.  From Jan 29 to Feb 2, 2020, 1916 people have been evacuated from Wuhan, among them 17 have been confirmed 2019-nCov infected. The infection rate is estimated to be 1.1% (95% CI 0.4%-3.1%) using one group meta-analysis method with random effect model. We then estimated that almost 110,000 (95% CI: 40,000-310,000) people were infected with 2019-nCov in Wuhan around Feb 2, 2020, assuming the infection risk of evacuees is close to Chinese citizens in Wuhan.  At the beginning of the outbreak, incidence of NCP may be vastly underestimated. Our result emphasizes that 2019-nCov has proposed a huge public health threats in Wuhan. We need to respond more rapidly, take large-scale public health interventions and draconian measures to limiting population mobility and control the epidemic.

title: The Novel Coronavirus, 2019-nCoV, is Highly Contagious and More Infectious Than Initially Estimated
abstract: The novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R0, was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus.

title: Prolonged presence of SARS-CoV-2 in feces of pediatric patients during the convalescent phase
abstract: Severe acute respiratory coronavirus 2 (SARS-CoV-2) is a newly identified virus which mainly spreads from person-to-person. Fecal shedding of SARS-CoV-2 has been constantly reported in patients with coronavirus disease 2019 (COVID-19). Most published studies focus on adult populations, whereas data concerning pediatric patients is relatively scarce.  From January 17, 2020 to March 6, 2020, three pediatric cases of COVID-19 were reported in Qingdao, Shandong Province, China. Epidemiological, clinical, laboratory, and radiological characteristics and treatment data of these children were collected. Real-time fluorescence reverse-transcriptase-polymerase-chain reaction (RT-PCR) was performed to detect SARS-CoV-2 RNA in throat swabs and fecal specimens.  All the three pediatric cases were household contacts of adults whose symptoms developed earlier. There has been no evidence showing the virus was transmitted from the children to others. Severity of disease of these children was mild to moderate and fever was the most consistent and predominant symptom at onset of illness (two cases had body temperature higher than 38.5 Celsius). All children showed increased lymphocytes (>4.4*109/L) with normal white blood cell counts on admission. One child had elevated serum levels of procalcitonin and C-reaction protein. Radiological changes were not typical for COVID-19. All children showed good response to supportive treatment. Clearance of SARS-CoV-2 in respiratory tract occurred within two weeks after abatement of fever, whereas persistent presence of viral RNA was found in stools of all children. One case had fecal SARS-CoV-2 turned negative 8 days after throat swabs showing negative, while that of another child lagged behind for 20 days. At the time of writing, one child still had positive results for RT-PCR analysis in stools after negative conversion of viral RNA in respiratory samples (over 19 days behind).  Pediatric patients with COVID-19 are very different from adult patients in regards to epidemiological, clinical, laboratory, and radiological characteristics. Prolonged shedding of SARS-CoV-2 in stools of infected children indicates the potential for the virus to be transmitted through fecal excretion. Massive efforts should be made at all levels to prevent spreading of the infection among children after reopening of kindergartens and schools.

title: SARS-CoV-2 Serology: Much Hype, Little Data

title: Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility — King County, Washington, March 2020
abstract: Older adults are susceptible to severe coronavirus disease 2019 (COVID-19) outcomes as a consequence of their age and, in some cases, underlying health conditions (1). A COVID-19 outbreak in a long-term care skilled nursing facility (SNF) in King County, Washington that was first identified on February 28, 2020, highlighted the potential for rapid spread among residents of these types of facilities (2). On March 1, a health care provider at a second long-term care skilled nursing facility (facility A) in King County, Washington, had a positive test result for SARS-CoV-2, the novel coronavirus that causes COVID-19, after working while symptomatic on February 26 and 28. By March 6, seven residents of this second facility were symptomatic and had positive test results for SARS-CoV-2. On March 13, CDC performed symptom assessments and SARS-CoV-2 testing for 76 (93%) of the 82 facility A residents to evaluate the utility of symptom screening for identification of COVID-19 in SNF residents. Residents were categorized as asymptomatic or symptomatic at the time of testing, based on the absence or presence of fever, cough, shortness of breath, or other symptoms on the day of testing or during the preceding 14 days. Among 23 (30%) residents with positive test results, 10 (43%) had symptoms on the date of testing, and 13 (57%) were asymptomatic. Seven days after testing, 10 of these 13 previously asymptomatic residents had developed symptoms and were recategorized as presymptomatic at the time of testing. The reverse transcription-polymerase chain reaction (RT-PCR) testing cycle threshold (Ct) values indicated large quantities of viral RNA in asymptomatic, presymptomatic, and symptomatic residents, suggesting the potential for transmission regardless of symptoms. Symptom-based screening in SNFs could fail to identify approximately half of residents with COVID-19. Long-term care facilities should take proactive steps to prevent introduction of SARS-CoV-2 (3). Once a confirmed case is identified in an SNF, all residents should be placed on isolation precautions if possible (3), with considerations for extended use or reuse of personal protective equipment (PPE) as needed (4).

title: Coronavirus disease 2019: The harms of exaggerated information and non‐evidence‐based measures
abstract: The evolving coronavirus disease 2019 (COVID-19) epidemic1 is certainly cause for concern. Proper communication and optimal decision-making is an ongoing challenge, as data evolve. The challenge is compounded, however, by exaggerated information. This can lead to inappropriate actions. It is important to differentiate promptly the true epidemic from an epidemic of false claims and potentially harmful actions.

title: Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic
abstract: The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern. Here, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number (R0), probability of death in the vulnerable fraction of the population, infectious period and time from infection to death, with the intention of exploring the sensitivity of the system to the actual fraction of the population vulnerable to severe disease and death. Our simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease. This relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood banks and paired samples of acute and convalescent sera from confirmed cases of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.

title: The reproductive number of COVID-19 is higher compared to SARS coronavirus
abstract: Our review found the average R0 for 2019-nCoV to be 3.28, which exceeds WHO estimates of 1.4 to 2.5.

title: CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image
abstract: Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method, however, its accuracy in detection is only ~70-75%. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80-98%, but similar accuracy of 70%. To enhance the accuracy of CT imaging detection, we developed an open-source set of algorithms called CovidCTNet that successfully differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 90% compared to radiologists (70%). The model is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. In order to facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and parametric details in an open-source format. Open-source sharing of our CovidCTNet enables developers to rapidly improve and optimize services, while preserving user privacy and data ownership.

title: Psychological Impact and Coping Strategies of Frontline Medical Staff in Hunan Between January and March 2020 During the Outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei, China
abstract: Throughout China, during the recent epidemic in Hubei province, frontline medical staff have been responsible for tracing contacts of patients infected with coronavirus disease 2019 (COVID-19). This study aimed to investigate the psychological impact and coping strategies of frontline medical staff in Hunan province, adjacent to Hubei province, during the COVID-19 outbreak between January and March 2020.  A cross-sectional observational study included doctors, nurses, and other hospital staff throughout Hunan province between January and March 2020. The study questionnaire included five sections and 67 questions (scores, 0–3). The chi-squared χ(2) test was used to compare the responses between professional groups, age-groups, and gender.  Study questionnaires were completed by 534 frontline medical staff. The responses showed that they believed they had a social and professional obligation to continue working long hours. Medical staff were anxious regarding their safety and the safety of their families and reported psychological effects from reports of mortality from COVID-19 infection. The availability of strict infection control guidelines, specialized equipment, recognition of their efforts by hospital management and the government, and reduction in reported cases of COVID-19 provided psychological benefit.  The COVID-19 outbreak in Hubei resulted in increased stress for medical staff in adjacent Hunan province. Continued acknowledgment of the medical staff by hospital management and the government, provision of infection control guidelines, specialized equipment and facilities for the management of COVID-19 infection should be recognized as factors that may encourage medical staff to work during future epidemics.

title: Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk
abstract: The new Middle East respiratory syndrome coronavirus (MERS-CoV) infection shares many clinical, epidemiological, and virological similarities with that of severe acute respiratory syndrome (SARS)-CoV. We aimed to estimate virus transmissibility and the epidemic potential of MERS-CoV, and to compare the results with similar findings obtained for prepandemic SARS.  We retrieved data for MERS-CoV clusters from the WHO summary and subsequent reports, and published descriptions of cases, and took into account 55 of the 64 laboratory-confirmed cases of MERS-CoV reported as of June 21, 2013, excluding cases notified in the previous 2 weeks. To assess the interhuman transmissibility of MERS-CoV, we used Bayesian analysis to estimate the basic reproduction number (R(0)) and compared it to that of prepandemic SARS. We considered two scenarios, depending on the interpretation of the MERS-CoV cluster-size data.  With our most pessimistic scenario (scenario 2), we estimated MERS-CoV R(0) to be 0·69 (95% CI 0·50–0·92); by contrast, the R(0) for prepandemic SARS-CoV was 0·80 (0·54–1·13). Our optimistic scenario (scenario 1) yielded a MERS-CoV R(0) of 0·60 (0·42–0·80). Because of recent implementation of effective contact tracing and isolation procedures, further MERS-CoV transmission data might no longer describe an entire cluster, but only secondary infections directly caused by the index patient. Hence, we calculated that, under scenario 2, eight or more secondary infections caused by the next index patient would translate into a 5% or higher chance that the revised MERS-CoV R(0) would exceed 1—ie, that MERS-CoV might have pandemic potential.  Our analysis suggests that MERS-CoV does not yet have pandemic potential. We recommend enhanced surveillance, active contact tracing, and vigorous searches for the MERS-CoV animal hosts and transmission routes to human beings.

title: Prevalence of SARS-CoV-2 Antibodies Among Healthcare Workers at a Tertiary Academic Hospital in New York City
abstract: SARS-CoV-2 antibody testing is important for understanding immunity prevalence, and may have implications for healthcare workers (HCW) during the SARS-CoV-2 pandemic.  We conducted immunologic testing of healthcare workers to determine the prevalence of SARS-CoV-2 IgG in this population. HCW were advised to wait at least two weeks from time of symptom onset or suspected exposure before undergoing testing. All participants were self-reported asymptomatic for at least three days at the time of testing.  Two hundred eighty-five samples were collected from March 24, 2020 to April 4, 2020. The average age of participants was 38 years (range 18-84), and 54% were male. Thirty-three percept tested IgG positive, 3% tested weakly positive, and 64% tested negative. Neither age nor sex was associated with antibody development.  Thirty-six percent of HCW had IgG antibodies to SARS-CoV-2, reflecting the high exposure of inpatient and ambulatory frontline staff to this viral illness, most of whom had minimal symptoms and were working in the weeks preceding testing. While we continue to recommend standard protective precautions per CDC guidelines for all HCW, HCW with SARS-CoV-2 IgG may become our safest frontline providers as we learn if our IgG antibodies confer immunity. Knowing IgG antibody status may ease concerns regarding personal risk as this pandemic continues.

title: Timeliness of infectious disease reporting, the Netherlands, 2003 to 2017: law change reduced reporting delay, disease identification delay is next
abstract: Timely notification of infectious diseases is essential for effective disease control and needs regular evaluation.  Our objective was to evaluate the effects that statutory adjustments in the Netherlands in 2008 and raising awareness during outbreaks had on notification timeliness.  In a retrospective analyses of routine surveillance data obtained between July 2003 and November 2017, delays between disease onset and laboratory confirmation (disease identification delay), between laboratory confirmation and notification to Municipal Health Services (notification delay) and between notification and reporting to the National Institute for Public Health and the Environment (reporting delay) were analysed for 28 notifiable diseases. Delays before (period 1) and after the law change (periods 2 and 3) were compared with legal timeframes. We studied the effect of outbreak awareness in 10 outbreaks and the effect of specific guidance messages on disease identification delay for two diseases.  We included 144,066 notifications. Average notification delay decreased from 1.4 to 0.4 days across the three periods (six diseases; p < 0.05), reporting delay decreased mainly in period 2 (from 0.5 to 0.1 days, six diseases; p < 0.05). In 2016–2017, legal timeframes were met overall. Awareness resulted in decreased disease identification delay for three diseases: measles and rubella (outbreaks) and psittacosis (specific guidance messages).  Legal adjustments decreased notification and reporting delays, increased awareness reduced identification delays. As disease identification delay dominates the notification chain, insight in patient, doctor and laboratory delay is necessary to further improve timeliness and monitor the impact of control measures during outbreaks.

title: 2019 novel coronavirus (2019-nCoV) outbreak: A new challenge
abstract: Following the public-health emergency of international concern (PHEIC) declared by the World Health Organization (WHO) on 30 January 2020 and the recent outbreak caused by 2019 novel coronavirus (2019-nCoV) [officially renamed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] in China and 29 other countries, we aimed to summarise the clinical aspects of the novelBetacoronavirus disease (COVID-19) and its possible clinical presentations together with suggested therapeutic algorithms for patients who may require antimicrobial treatment.  The currently available literature was reviewed for microbiologically confirmed infections by 2019-nCoV or COVID-19 at the time of writing (13 February 2020). A literature search was performed using the PubMed database and Cochrane Library. Search terms included 'novel coronavirus' or '2019-nCoV' or 'COVID-19'.  Published cases occurred mostly in males (age range, 8-92 years). Cardiovascular, digestive and endocrine system diseases were commonly reported, except previous chronic pulmonary diseases [e.g. chronic obstructive pulmonary disease (COPD), asthma, bronchiectasis] that were surprisingly underreported. Fever was present in all of the case series available, flanked by cough, dyspnoea, myalgia and fatigue. Multiple bilateral lobular and subsegmental areas of consolidation or bilateral ground-glass opacities were the main reported radiological features of 2019-nCoV infection, at least in the early phases of the disease.  The new 2019-nCoV epidemic is mainly associated with respiratory disease and few extrapulmonary signs. However, there is a low rate of associated pre-existing respiratory co-morbidities.

title: Features, Evaluation and Treatment Coronavirus (COVID-19)
abstract: According to the World Health Organization (WHO), viral diseases continue to emerge and represent a serious issue to public health In the last twenty years, several viral epidemics such as the severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002 to 2003, and H1N1 influenza in 2009, have been recorded Most recently, the Middle East respiratory syndrome coronavirus (MERS-CoV) was first identified in Saudi Arabia in 2012 In a timeline that reaches the present day, an epidemic of cases with unexplained low respiratory infections detected in Wuhan, the largest metropolitan area in China's Hubei province, was first reported to the WHO Country Office in China, on December 31, 2019 Published literature can trace the beginning of symptomatic individuals back to the beginning of December 2019 As they were unable to identify the causative agent, these first cases were classified as "pneumonia of unknown etiology " The Chinese Center for Disease Control and Prevention (CDC) and local CDCs organized an intensive outbreak investigation program The etiology of this illness is now attributed to a novel virus belonging to the coronavirus (CoV) family, COVID-19 On February 11, 2020, the WHO Director-General, Dr Tedros Adhanom Ghebreyesus, announced that the disease caused by this new CoV was a "COVID-19," which is the acronym of "coronavirus disease 2019" In the past twenty years, two additional coronavirus epidemics have occurred SARS-CoV provoked a large-scale epidemic beginning in China and involving two dozen countries with approximately 8000 cases and 800 deaths, and the MERS-CoV that began in Saudi Arabia and has approximately 2,500 cases and 800 deaths and still causes as sporadic cases This new virus seems to be very contagious and has quickly spread globally In a meeting on January 30, 2020, per the International Health Regulations (IHR, 2005), the outbreak was declared by the WHO a Public Health Emergency of International Concern (PHEIC) as it had spread to 18 countries with four countries reporting human-to-human transmission An additional landmark occurred on February 26, 2020, as the first case of the disease, not imported from China, was recorded in the United States Initially, the new virus was called 2019-nCoV Subsequently, the task of experts of the International Committee on Taxonomy of Viruses (ICTV) termed it the SARS-CoV-2 virus as it is very similar to the one that caused the SARS outbreak (SARS-CoVs) The CoVs have become the major pathogens of emerging respiratory disease outbreaks They are a large family of single-stranded RNA viruses (+ssRNA) that can be isolated in different animal species For reasons yet to be explained, these viruses can cross species barriers and can cause, in humans, illness ranging from the common cold to more severe diseases such as MERS and SARS Interestingly, these latter viruses have probably originated from bats and then moving into other mammalian hosts — the Himalayan palm civet for SARS-CoV, and the dromedary camel for MERS-CoV — before jumping to humans The dynamics of SARS-Cov-2 are currently unknown, but there is speculation that it also has an animal origin The potential for these viruses to grow to become a pandemic worldwide seems to be a serious public health risk Concerning COVID-19, the WHO raised the threat to the CoV epidemic to the "very high" level, on February 28, 2020 Probably, the effects of the epidemic caused by the new CoV has yet to emerge as the situation is quickly evolving World governments are at work to establish countermeasures to stem possible devastating effects Health organizations coordinate information flows and issues directives and guidelines to best mitigate the impact of the threat At the same time, scientists around the world work tirelessly, and information about the transmission mechanisms, the clinical spectrum of disease, new diagnostics, and prevention and therapeutic strategies are rapidly developing Many uncertainties remain with regard to both the virus-host interac ion and the evolution of the epidemic, with specific reference to the times when the epidemic will reach its peak At the moment, the therapeutic strategies to deal with the infection are only supportive, and prevention aimed at reducing transmission in the community is our best weapon Aggressive isolation measures in China have led to a progressive reduction of cases in the last few days In Italy, in geographic regions of the north of the peninsula, political and health authorities are making incredible efforts to contain a shock wave that is severely testing the health system In the midst of the crisis, the authors have chosen to use the "Statpearls" platform because, within the PubMed scenario, it represents a unique tool that may allow them to make updates in real-time The aim, therefore, is to collect information and scientific evidence and to provide an overview of the topic that will be continuously updated

title: Managing ACS during COVID-19 infection: do not follow the traditional route
abstract: COVID-19 pandemic is creating havoc in the world. It is also spreading in India creating a massive healthcare problem. Few major hospitals were closed down because of the spread among healthcare personnel. Management of several commonly occurring diseases needed modifications to a lesser or greater extent because of this pandemic. Management of acute coronary syndrome (ACS) also requires certain modifications. In this opinion paper an attempt has been made to give an outline of ACS management in this changed scenario.

title: Access to Care for Dementia patients suffering from COVID-19

title: Infectious Disease Epidemiology
abstract: Most textbooks dealing with the epidemiology of infectious diseases address the epidemiological features (also named biology) of specific infectious diseases. In this chapter, the focus is placed on the concepts and methods more specific to the general epidemiological study of infectious diseases. At a later stage, implementation of these methods must be adapted to the specific infectious disease under consideration. Then, detailed knowledge of the disease biology is of capital importance.

title: 2019 CIS Annual Meeting: Immune Deficiency & Dysregulation North American Conference

title: Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020
abstract: Adjusting for delay from confirmation to death, we estimated case and infection fatality ratios (CFR, IFR) for coronavirus disease (COVID-19) on the Diamond Princess ship as 2.6% (95% confidence interval (CI): 0.89–6.7) and 1.3% (95% CI: 0.38–3.6), respectively. Comparing deaths on board with expected deaths based on naive CFR estimates from China, we estimated CFR and IFR in China to be 1.2% (95% CI: 0.3–2.7) and 0.6% (95% CI: 0.2–1.3), respectively.

title: Bioengineering and semisynthesis of an optimized cyclophilin inhibitor for treatment of chronic viral infection
abstract: Inhibition of host-encoded targets, such as the cyclophilins, provides an opportunity to generate potent, high barrier to resistance antivirals for the treatment of a broad range of viral diseases. However, many host-targeted agents are natural products which can be difficult to optimize using synthetic chemistry alone. We describe the orthogonal combination of bioengineering and semisynthetic chemistry to optimize the drug-like properties of sanglifehrin A, a known cyclophilin inhibitor of mixed non-ribosomal peptide/polyketide origin in order to generate the drug candidate NVP018 (formerly BC556). NVP018 is a potent inhibitor of HBV, HCV and HIV-1 replication, shows minimal inhibition of major drug transporters and has a high barrier to generation of both HCV and HIV-1 resistance.

title: Serological detection of 2019-nCoV respond to the epidemic: A useful complement to nucleic acid testing
abstract: Corona Virus Disease 2019 (COVID-19) has spread rapidly to more than 70 countries and regions overseas and over 80000 cases have been infected, resulting in more than three thousand deaths. Rapid diagnosis of patients remains a bottleneck in containing the progress of the epidemic. We used automated chemiluminescent immunoassay to detect serum IgM and IgG antibodies to 2019-nCoV of 736 subjects. COVID-19 patients were becoming reactive(positive) for specific antibodies from 7-12 days after the onset of morbidity. Specific IgM and IgG increased with the progression of the disease. The areas under the ROC curves of IgM and IgG were 0.988 and 1.000, respectively. Specific antibody detection has good sensitivity and specificity. Detection of specific antibodies in patients with fever can be a good distinction between COVID-19 and other diseases, so as to be a complement to nucleic acid diagnosis to early diagnosis of suspected cases.

title: Interleukin-6 in COVID-19: A Systematic Review and Meta-Analysis
abstract: Coronaviruses may activate dysregulated host immune responses. As exploratory studies have suggested that interleukin-6 (IL-6) levels are elevated in cases of complicated COVID-19 and that the anti-IL-6 biologic tocilizumab may be beneficial, we undertook a systematic review and meta-analysis to assess the evidence in this field.  We systematically searched MEDLINE and EMBASE for studies investigating the immunological response in COVID-19 or its treatment with tocilizumab; additional grey literature searches were undertaken. Meta-analysis was undertaken using random effects models.  Eight published studies, three pre-prints, and five registered trials were eligible. Meta-analysis of mean IL-6 concentrations demonstrated 2.9-fold higher levels in patients with complicated COVID-19 compared with patients with non-complicated disease (six studies; n=1302; 95%CI, 1.17-7.19; I2=100%). A single non-randomized, single-arm study assessed tocilizumab in patients with severe COVID-19, demonstrating decreased oxygen requirements, resolution of radiographic abnormalities, and clinical improvement. No adverse events or deaths were observed.  In patients with COVID-19, IL-6 levels are significantly elevated and associated with adverse clinical outcomes. While inhibition of IL-6 with tocilizumab appears to be efficacious and safe in preliminary investigation, the results of several ongoing clinical trials should be awaited to better define the role of tocilizumab in COVID-19 prior to routine clinical application.

title: There are asymptomatic and pre-symptomatic patients infected with COVID-19. So what? Pandemic response implications
abstract: Asymptomatic but infectious people have been reported in many infectious diseases. Asymptomatic and pre-symptomatic carriers would be a hidden reservoir of COVID-19.  This review identifies primary empirical evidence about the ability of asymptomatic carriers to infect others with COVID-19 pandemic and reflects on the implications for control measures.  A systematic review is followed by a narrative report and commentary inclusion criteria were: studies reporting primary data on asymptomatic or pre-symptomatic patients, who were considered to have passed on COVID-19 infection; and published in indexed journals or in peer review between January 1 and March 31, 2020.  Nine articles reported on 83 asymptomatic or pre-symptomatic persons.  The evidence confirms COVID-19 transmission from people who were asymptomatic at the time. A series of implications for health service response are laid out.  Covid-19, Asymptomatic, Pre-symptomatic, Public Health

title: Protease inhibitors broadly effective against feline, ferret and mink coronaviruses
abstract: Ferret and mink coronaviruses typically cause catarrhal diarrhea in ferrets and minks, respectively. In recent years, however, systemic fatal coronavirus infection has emerged in ferrets, which resembles feline infectious peritonitis (FIP) in cats. FIP is a highly fatal systemic disease caused by a virulent feline coronavirus infection in cats. Despite the importance of coronavirus infections in these animals, there are no effective commercial vaccines or antiviral drugs available for these infections. We have previously reported the efficacy of a protease inhibitor in cats with FIP, demonstrating that a virally encoded 3C-like protease (3CLpro) is a valid target for antiviral drug development for coronavirus infections. In this study, we extended our previous work on coronavirus inhibitors and investigated the structure-activity relationships of a focused library of protease inhibitors for ferret and mink 3CLpro. Using the fluorescence resonance energy transfer assay, we identified potent inhibitors broadly effective against feline, ferret and mink coronavirus 3CLpro. Multiple amino acid sequence analysis and modelling of 3CLpro of ferret and mink coronaviruses were conducted to probe the structural basis for these findings. The results of this study provide support for further research to develop broad-spectrum antiviral agents for multiple coronavirus infections. To the best of our knowledge, this is the first report on small molecule inhibitors of ferret and mink coronaviruses.

title: Predictors of COVID-19 incidence, mortality, and epidemic growth rate at the country level
abstract: The burden of the coronavirus disease 2019 (COVID-19) pandemic has been geographically disproportionate. Certain weather factors and population characteristics are thought to drive transmission, but studies examining these factors are limited. We aimed to identify weather, sociodemographic, and geographic drivers of COVID-19 at the global scale using a comprehensive collection of country/territory-level data, and to use discovered associations to estimate the timing of community transmission.  We examined COVID-19 cases and deaths reported up to May 2, 2020 across 205 countries and territories in relation to weather data collected from capital cities for the eight weeks prior to and four weeks after the date of the first reported case, as well as country/territory-level population, geographic, and planetary data. We performed univariable and multivariable regression modeling and odds ratio analyses to investigate associations with COVID-19 cases, deaths, and epidemic growth rate. We also conducted maximum likelihood analysis to estimate the timing of initial community spread.  Lower temperature (p<0.0001), lower humidity (p=0.006), higher altitude (p=0.0080), higher percentage of urban population (p<0.0001), increased air travelers (p=0.00019), and higher prevalence of obesity (p<0.0001) were strong independent predictors of national COVID-19 incidence, mortality, and epidemic growth rate. Temperature at 5-7 weeks before the first reported case best predicted epidemic growth, suggesting that significant community transmission was occurring on average 1-2 months prior to detection.  The results of this ecologic analysis demonstrate that global COVID-19 burden and timing of country-level epidemic growth can be predicted by weather and population factors. In particular, we find that cool, dry, and higher altitude environments, as well as more urban and obese populations, may be conducive to more rapid epidemic spread.

title: Infections and Identified Cases of COVID-19 from Random Testing Data
abstract: There are many hard-to-reconcile numbers circulating concerning Covid-19. Using reports from random testing, the fatality ratio per infection is evaluated and used to extract further information on the actual fraction of infections and the success of their identification for different countries.

title: Using Google Trends to Examine the Spatio-Temporal Incidence and Behavioral Patterns of Dengue Disease: A Case Study in Metropolitan Manila, Philippines
abstract: Dengue is a major public health concern and an economic burden in the Philippines. Despite the country’s improved dengue surveillance, it still suffers from various setbacks and needs to be complemented with alternative approaches. Previous studies have demonstrated the potential of Internet-based surveillance such as Google Dengue Trends (GDT) in supplementing current epidemiological methods for predicting future dengue outbreaks and patterns. With this, our study has two objectives: (1) assess the temporal relationship of weekly GDT and dengue incidence in Metropolitan Manila from 2009–2014; and (2) examine the health-seeking behavior based on dengue-related search queries of the population. The study collated the population statistics and reported dengue cases in Metropolitan Manila from respective government agencies to calculate the dengue incidence (DI) on a weekly basis for the entire region and annually per city. Data processing of GDT and dengue incidence was performed by conducting an ‘adjustment’ and scaling procedures, respectively, and further analyzed for correlation and cross-correlation analyses using Pearson’s correlation. The relative search volume of the term ‘dengue’ and top dengue-related search queries in Metropolitan Manila were obtained and organized from the Google Trends platform. Afterwards, a thematic analysis was employed, and word clouds were generated to examine the health behavior of the population. Results showed that weekly temporal GDT pattern are closely similar to the weekly DI pattern in Metropolitan Manila. Further analysis showed that GDT has a moderate and positive association with DI when adjusted or scaled, respectively. Cross-correlation analysis revealed a delayed effect where GDT leads DI by 1–2 weeks. Thematic analysis of dengue-related search queries indicated 5 categories namely; (a) dengue, (b) sign and symptoms of dengue, (c) treatment and prevention, (d) mosquito, and (e) other diseases. The majority of the search queries were classified in ‘signs and symptoms’ which indicate the health-seeking behavior of the population towards the disease. Therefore, GDT can be utilized to complement traditional disease surveillance methods combined with other factors that could potentially identify dengue hotspots and help in public health decisions.

title: COVID-19: The unreasonable effectiveness of simple models
abstract: When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the comprehensiveness of many widely established models, the official figures that recount the course of the outbreak still sketch a largely elusive and intimidating picture. Here we show unambiguously that the dynamics of the COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. Our analysis naturally leads us to establish that there exists a fundamental limitation to any theoretical approach, namely the unpredictable non-stationarity of the testing frames behind the reported figures. However, we show how such bias can be quantified self-consistently and employed to mine useful and accurate information from the data. In particular, we describe how the time evolution of the reporting rates controls the occurrence of the apparent epidemic peak, which typically follows the true one in countries that were not vigorous enough in their testing at the onset of the outbreak. The importance of testing early and resolutely appears as a natural corollary of our analysis, as countries that tested massively at the start clearly had their true peak earlier and less deaths overall.

title: 68 Consecutive patients assessed for COVID-19 infection; experience from a UK regional infectious disease unit
abstract: Clinical assessment of possible infection with SARS-CoV-2, the novel coronavirus responsible for the outbreak of COVID-19 respiratory illness, has been a major activity of infectious diseases services in the UK and elsewhere since the first report of cases in December 2019. We report our case series of 68 patients, reviewed by Infectious Diseases Consultants at a Regional Infectious Diseases Unit in the UK. We prospectively evaluated our service between the 29th Jan 2020 and 24th Feb 2020. Demographic, clinical, epidemiological and laboratory data were collected. We have compared clinical features and subsequent diagnosis between well patients not requiring admission for clinical reasons or antimicrobials with those assessed as needing either admission or antimicrobial treatment. Final microbiological diagnoses included SARS-CoV-2 (COVID-19), Mycoplasma pneumonia, influenza A, RSV, non SARS/MERS coronaviruses, rhinovirus/enterovirus. 9/68 were treated with antimicrobials, 15/68 were admitted to a negative pressure room of whom 5/68 were admitted solely due to an inability to isolate at home. Patients requiring either admission on clinical grounds or antimicrobials (14/68) were similar to those not requiring admission or antimicrobials, with modestly more fever and shortness of breath in the clinically admitted / antimicrobial group. The most commonly prescribed antimicrobials were doxycycline, moxifloxacin and oseltamivir. The majority of patients had mild illness which did not require a clinical intervention to manage. This finding supports a community testing approach supported by clinicians to review the proportion of more unwell patients.

title: Serology characteristics of SARS-CoV-2 infection since the exposure and post symptoms onset
abstract: Timely diagnosis of SARS-CoV-2 infection is the prerequisite for treatment and preventive quarantine. The serology characteristics and complement diagnosis value of antibody test to RNA test needs to be demonstrated.  A patient cohort study was conducted at the first affiliated hospital of Zhejiang University, China. Serial sera of COVID-19 patients were collected and total antibody (Ab), IgM and IgG antibody against SARS-CoV-2 were detected. The antibody dynamics during the infection were described.  The seroconversion rate for Ab, IgM and IgG in COVID-19 patients was 98.8% (79/80), 93.8% (75/80) and 93.8% (75/80), respectively. The first detectible serology marker is total antibody and followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 day post exposure (d.p.e) or 9, 10 and 12 days post onset, separately. The antibody levels increased rapidly since 6 d.p.o and accompanied with the decline of viral load. For patients in the early stage of illness (0-7d.p.o),Ab showed the highest sensitivity (64.1%) compared to the IgM and IgG (33.3% for both, p<0.001). The sensitivities of Ab, IgM and IgG detection increased to 100%, 96.7% and 93.3% two weeks later, respectively.  Typical acute antibody response is induced during the SARS-CoV-2 infection. The serology testing provides important complementation to RNA test for pathogenic specific diagnosis and helpful information to evaluate the adapted immunity status of patient. It should be strongly recommended to apply well-validated antibody tests in the clinical management and public health practice to improve the control of COVID-19 infection.

title: Smell and taste symptom‐based predictive model for COVID‐19 diagnosis
abstract: The presentation of COVID‐19 overlaps with common influenza symptoms. There is limited data on whether a specific symptom or collection of symptoms may be useful to predict test positivity.  An anonymous electronic survey was publicized through social media to query participants with COVID‐19 testing. Respondents were questioned regarding 10 presenting symptoms, demographic information, comorbidities and COVID‐19 test results. Stepwise logistic regression was used to identify predictors for COVID positivity. Selected classifiers were assessed for prediction performance using receiver operating characteristic analysis (ROC).  One‐hundred and forty‐five participants with positive COVID‐19 testing and 157 with negative results were included. Participants had a mean age of 39 years, and 214 (72%) were female. Smell or taste change, fever, and body ache were associated with COVID‐19 positivity, and shortness of breath and sore throat were associated with a negative test result (p<0.05). A model using all 5 diagnostic symptoms had the highest accuracy with a predictive ability of 82% in discriminating between COVID‐19 results. To maximize sensitivity and maintain fair diagnostic accuracy, a combination of 2 symptoms, change in sense of smell or taste and fever was found to have a sensitivity of 70% and overall discrimination accuracy of 75%.  Smell or taste change is a strong predictor for a COVID‐19 positive test result. Using the presence of smell or taste change with fever, this parsimonious classifier correctly predicts 75% of COVID‐19 test results. A larger cohort of respondents will be necessary to refine classifier performance. This article is protected by copyright. All rights reserved

title: Pandemic influenza preparedness (PIP) framework: Progress challenges in improving influenza preparedness response capacities in the Eastern Mediterranean Region, 2014–2017
abstract: Influenza viruses with pandemic potential have been detected in humans in the Eastern Mediterranean Region. The Pandemic Influenza Preparedness (PIP) Framework aims to improve the sharing of influenza viruses with pandemic potential and increase access of developing countries to vaccines and other life-saving products during a pandemic. Under the Framework, countries have been supported to enhance their capacities to detect, prepare for and respond to pandemic influenza. In the Eastern Mediterranean Region, seven countries are priority countries for Laboratory and Surveillance (L&S) support: Afghanistan, Djibouti, Egypt, Jordan, Lebanon, Morocco and Yemen. During 2014–2017, US$ 2.7 million was invested in regional capacity-building and US$ 4.6 million directly in the priority countries. Countries were supported to strengthen influenza diagnostic capacities to improve detection, enhance influenza surveillance systems including sentinel surveillance for severe acute respiratory infection and influenza-like illness, and increase global sharing of surveillance data and influenza viruses. This paper highlights the progress made in improving influenza preparedness and response capacities in the Region from 2014 to 2017, and the challenges faced. By 2017, 18 of the 22 countries of the Region had laboratory-testing capacity, 19 had functioning sentinel influenza surveillance systems and 22 had trained national rapid response teams. The number of countries correctly identifying all influenza viruses in the WHO external quality assurance panel increased from 9 countries scoring 100% in 2014 to 15 countries in 2017, and the number sharing influenza viruses with WHO collaborating centres increased by 75% (from eight to 14 countries); more than half now share influenza data with regional or global surveillance platforms. Seven countries have estimated influenza disease burden and seven have introduced influenza vaccination for high-risk groups. Challenges included: protracted complex emergencies faced by nine countries which hindered implementation of influenza surveillance in areas with the most needs, high staff turnover, achieving timely virus sharing and limited utilization of influenza data where they are available to inform vaccine policies or establish threshold values to measure the start and severity of influenza seasons.

title: The Severe Acute Respiratory Syndrome Coronavirus Nucleocapsid Inhibits Type I Interferon Production by Interfering with TRIM25-Mediated RIG-I Ubiquitination.
abstract: Severe acute respiratory syndrome (SARS) is a respiratory disease, caused by a coronavirus (SARS-CoV), that is characterized by atypical pneumonia. The nucleocapsid protein (N protein) of SARS-CoV plays an important role in inhibition of type I interferon (IFN) production via an unknown mechanism. In this study, the SARS-CoV N protein was found to bind to the SPRY domain of the tripartite motif protein 25 (TRIM25) E3 ubiquitin ligase, thereby interfering with the association between TRIM25 and retinoic acid-inducible gene I (RIG-I) and inhibiting TRIM25-mediated RIG-I ubiquitination and activation. Type I IFN production induced by poly I·C or Sendai virus (SeV) was suppressed by the SARS-CoV N protein. SARS-CoV replication was increased by overexpression of the full-length N protein but not N amino acids 1 to 361, which could not interact with TRIM25. These findings provide an insightful interpretation of the SARS-CoV-mediated host innate immune suppression caused by the N protein. The SARS-CoV N protein is essential for the viral life cycle and plays a key role in the virus-host interaction. We demonstrated that the interaction between the C terminus of the N protein and the SPRY domain of TRIM25 inhibited TRIM25-mediated RIG-I ubiquitination, which resulted in the inhibition of IFN production. We also found that the Middle East respiratory syndrome CoV (MERS-CoV) N protein interacted with TRIM25 and inhibited RIG-I signaling. The outcomes of these findings indicate the function of the coronavirus N protein in modulating the host's initial innate immune response.

title: Multilingual chief complaint classification for syndromic surveillance: An experiment with Chinese chief complaints
abstract: Syndromic surveillance is aimed at early detection of disease outbreaks. An important data source for syndromic surveillance is free-text chief complaints (CCs), which may be recorded in different languages. For automated syndromic surveillance, CCs must be classified into predefined syndromic categories to facilitate subsequent data aggregation and analysis. Despite the fact that syndromic surveillance is largely an international effort, existing CC classification systems do not provide adequate support for processing CCs recorded in non-English languages. This paper reports a multilingual CC classification effort, focusing on CCs recorded in Chinese.  We propose a novel Chinese CC classification system leveraging a Chinese-English translation module and an existing English CC classification approach. A set of 470 Chinese key phrases was extracted from about one million Chinese CC records using statistical methods. Based on the extracted key phrases, the system translates Chinese text into English and classifies the translated CCs to syndromic categories using an existing English CC classification system.  Compared to alternative approaches using a bilingual dictionary and a general-purpose machine translation system, our approach performs significantly better in terms of positive predictive value (PPV or precision), sensitivity (recall), specificity, and F measure (the harmonic mean of PPV and sensitivity), based on a computational experiment using real-world CC records.  Our design provides satisfactory performance in classifying Chinese CCs into syndromic categories for public health surveillance. The overall design of our system also points out a potentially fruitful direction for multilingual CC systems that need to handle languages beyond English and Chinese.

title: Dynamic Modeling to Identify Mitigation Strategies for Covid-19 Pandemic
abstract: Relevant pandemic-spread scenario simulations provide guiding principles for containment and mitigation policy developments. Here we devise a simple model to predict the effectiveness of different mitigation strategies. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries and the number of Covid-19-inflicted deaths. For simplification, we assume that Covid-19 survivors are immune (e.g. mutations are not considered) and that the virus can only be passed on by persons with undetected infections. While the latter assumption is a simplification (it is neglected that e.g. hospital staff may be infected by detected patients with symptoms), it was introduced here to keep the model as simple as possible. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. Some of the model parameters have been fitted to the reported cases outside of China1 from January 22 to March 12 of the 2020 Covid-19 pandemic. The other parameters were chosen in a plausible range to the best of our knowledge. We compared infection rates, the total number of people getting infected and the number of deaths in six different scenarios. Social distancing or increased testing can contain or drastically reduce the infections and the predicted number of deaths when compared to a situation without mitigation. We find that mass-testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economical costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the Covid-19 pandemic. The website corona-lab.ch provides an interactive simulation tool based on the presented model.

title: Defining the true impact of coronavirus disease 2019 in the at-risk population of patients with cancer
abstract: In light of the coronavirus disease 2019 (COVID-19) pandemic, cancer centres in the United Kingdom and Europe re-organised their services at an unprecedented pace, and many patients with cancer have had their treatments severely disrupted. Patients with cancer were considered at high risk on sparse evidence, and despite a small number of emerging observational studies, the true incidence and impact of COVID-19 in the ‘at-risk’ population of patients with cancer is yet to be defined.  Epidemiological and clinical data were collected prospectively for patients attending the Royal Marsden Hospital and three network hospitals between March 1st and April 30th 2020 that were confirmed to have SARS-CoV2 infection. Significance of clinical and pathological characteristics was assessed using the Fisher's exact test and Wilcoxon rank sum test, whilst univariate and multivariate logistic regression models were used to further assess risk. The number of patients attending in March/April 2020 for face-to-face attendances was also extracted.  During the 2-month study period, 867 of 13,489 (6.4%) patients met the criteria leading to swab testing. Of the total at-risk population, only 113 of 13,489 (0.84%) were swab positive, 101 of 13,489 (0.75%) required hospital admission and 29 of 13,489 (0.21%) died of COVID-19. Of the patients that attended the hospital to receive cytotoxic chemotherapy alone or in combination with other therapy, 59 of 2001 (2.9%) were admitted to the hospital for COVID-19–related issues and 20 of 2001 (1%) died. Of the patients that collected targeted treatments, 16 of 1126 (1.4%) were admitted and 1 of 1126 (0.1%) died. Of the 11 patients that had received radiotherapy, 6 of 1042 (0.6%) required inpatient admission and 2 of 1042 (0.2%) died.  Administration of systemic anticancer therapy appears to be associated with a modest risk of severe COVID-19 infection. Based on this snapshot taken as the first wave of COVID-19 hit our practice, we conclude that continuation of active cancer treatment, even in the palliative setting, is appropriate.

title: Coronavirus disease (COVID-19): a scoping review
abstract: BackgroundIn December 2019, a pneumonia caused by a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and has rapidly spread around the world since then.AimThis study aims to understand the research gaps related to COVID-19 and propose recommendations for future research.MethodsWe undertook a scoping review of COVID-19, comprehensively searching databases and other sources to identify literature on COVID-19 between 1 December 2019 and 6 February 2020. We analysed the sources, publication date, type and topic of the retrieved articles/studies.ResultsWe included 249 articles in this scoping review. More than half (59.0%) were conducted in China. Guidance/guidelines and consensuses statements (nâ¯=â¯56; 22.5%) were the most common. Most (nâ¯=â¯192; 77.1%) articles were published in peer-reviewed journals, 35 (14.1%) on preprint servers and 22 (8.8%) posted online. Ten genetic studies (4.0%) focused on the origin of SARS-CoV-2 while the topics of molecular studies varied. Nine of 22 epidemiological studies focused on estimating the basic reproduction number of COVID-19 infection (R0). Of all identified guidance/guidelines (nâ¯=â¯35), only ten fulfilled the strict principles of evidence-based practice. The number of articles published per day increased rapidly until the end of January.ConclusionThe number of articles on COVID-19 steadily increased before 6 February 2020. However, they lack diversity and are almost non-existent in some study fields, such as clinical research. The findings suggest that evidence for the development of clinical practice guidelines and public health policies will be improved when more results from clinical research becomes available.

title: Estimating the presymptomatic transmission of COVID19 using incubation period and serial interval data
abstract: We estimated the fraction and timing of presymptomatic transmissions of COVID19 with mathematical models combining the available data of the incubation period and serial interval. We found that up to 79.7% transmissions could be presymptomatic among the imported cases in China outside Wuhan. The average timing of presymptomatic transmissions is 3.8 days (SD = 6.1) before the symptom onset, which is much earlier than previously assumed.

title: Transmission in Latent Period Causes A Large Number of Infected People in the United States
abstract: By April 29, 2020, the cumulative number of confirmed cases in the United States has exceeded one million, becoming the country with the most serious pandemic in the world. It is urgent to analyze the real situation and follow-up trend of the epidemic in the United States. The proposed model divides the time period into two different phases, before and after March 21, 2020. The results show that the basic reproduction number in the early period of propagation in the United States is estimated to be 4.06 (95% CI: 1.86-6.73) based on the confirmed cases data ranging from January 21, 2020 to March 21, 2020. The normalized contributions to R_0 for three different categories of communicators were estimated, including the numbers of the latent population (in incubation period) L, the documented infectious population Id, and the undocumented infectious population Iu. The results show that L contributes 16.17% (95% CI: 12.86% - 21.60%) to R_0, Id contributes 55.13% (95% CI: 43.15% - 63.97%), and Iu contributes 28.70% (95% CI: 19.29% - 40.07%) to R0. The metapopulation network was used to simulate the true spread of COVID-19 in the United States, and the Bayesian inference was applied to estimate the key parameters including the rate of the number of the susceptibles and the infected beta, the infection ratio between undocumented and documented transmission 1, the infection ratio between latent and documented transmission 2, the proportion of confirmed cases in the infectious population x, and the duration of latent period (incubation period) TL . From the analysis of phase one, 1 was estimated to be 0.40 (95% CI: 0.17 - 0.54), 2 was estimated to be 0.06 (95% CI: 0.02 - 0.11), x was estimated to be 0.70 (95% CI: 0.55 - 0.78), T_L was estimated to be 8.41 (95% CI: 6.64 - 9.42). As of April 13, 2020, it was estimated that only 45% (95% CI: 35% - 73%) of symptom onset cases in the United States have been documnented. The infectivity of undocumented infectious population was 0.59 (95% CI: 0.21 - 0.70) of that of the documented infectious population, while that of the latent population was 0.19 (95% CI: 0.11 - 0.27) of that of the documented infectious population. The incubation period of COVID-19 was estimated to be 10.69 days (95% CI: 10.02 - 11.74). We estimated that if the current control interventions are continued, the pandemic situation in the United States is likely to keep climbing up, and the cumulative number of confirmed cases is expected to reach more than 1.7 million in July and continue to grow. We also performed component analysis and sensitivity analysis, researching the compositions of the people with COVID-19, and considering that there is only a random time delay between the number of patients in the incubation period and the actual number of patients.

title: COVID-19: more evidence emerges

title: The Estimated Time-Varying Reproduction Numbers during the Ongoing Epidemic of the Coronavirus Disease 2019 (COVID-19) in China
abstract: How could we anticipate the progression of the ongoing epidemic of the coronavirus disease 2019 (COVID-19) in China? As a measure of transmissibility, the value of basic reproduction number varies over time during an epidemic of infectious disease. Hence, this study aimed to estimate concurrently the time-varying reproduction number over time during the COVID-19 epidemic in China.  We extracted the epidemic data from the "Tracking the Epidemic" website of the Chinese Center for Disease Control and Prevention for the duration of January 19, 2020 and March 14, 2020. Then, we applied the novel method implemented in the incidence and EpiEstim packages to the data of daily new confirmed cases for robustly estimating the time-varying reproduction number in the R software.  The epidemic curve of daily new confirmed cases in China peaked around February 4-6, 2020, and then declined gradually, except the very high peak on February 12, 2020 owing to the added clinically diagnosed cases (Hubei Province only). Under two specified plausible scenarios for the distribution of serial interval, both curves of the estimated time-varying reproduction numbers fell below 1.0 around February 17-18, 2020. Finally, the COVID-19 epidemic in China abated around March 7-8, 2020, indicating that the prompt and aggressive control measures of China were effective.  Seeing the estimated time-varying reproduction number going downhill was more informative than looking for the drops in the daily number of new confirmed cases during an ongoing epidemic of infectious disease. We urged public health authorities and scientists to estimate time-varying reproduction numbers routinely during epidemics of infectious diseases and to report them daily to the public until the end of the COVID-19 epidemic.

title: A quantitative framework to define the end of an outbreak: application to Ebola Virus Disease
abstract: Declaring the end of an outbreak is an important step in controlling infectious disease outbreaks. An objective estimation of the probability of cases arising in the future is important to reduce the risk of post-declaration flare-ups. We developed a simulation-based model to quantify that probability. We tested it on simulated Ebola Virus Disease (EVD) data and found this probability was most sensitive to the instantaneous reproduction number, the reporting rate, and the delay between symptom onset and recovery or death of the last detected case. For EVD, our results suggest that the current WHO criterion of 42 days since the outcome of the last detected case is too short and very sensitive to underreporting. The 90 days of enhanced surveillance period after the end-of-outbreak declaration is therefore crucial to capture potential flare-ups of cases. Hence, we suggest a shift to a preliminary end-of-outbreak declaration after 63 days from the symptom onset day of the last detected case. This should be followed by a 90-day enhanced surveillance, after which the official end-of-outbreak can be declared. This corresponds to less than 5% probability of flare ups in most of the scenarios examined. Our quantitative framework could be adapted to define end-of-outbreak criteria for other infectious diseases.

title: Daily Situation Report on Coronavirus disease (COVID-19) in Iran; March 14, 2020
abstract: After detection of the first confirmed cases of COVID-19 in Iran, the National Committee on COVID-19 Epidemiology in Ministry of Health and Medical Education was established. This Committee is official source of gathering, analyzing, and reporting the COVID-19 data in Iran. The data of all sources in the country including, medical care monitoring center (MCMC), Hospitals’ Information Systems (HIS), Laboratory portal, the data of the center for communicable disease control (MOH), as well as the data from community health centers are integrated and used in this regards. This factsheet contain daily situation report on coronavirus disease (covid-19) in Iran; March 14, 2020.

title: Reconstructing the global dynamics of under-ascertained COVID-19 cases and infections
abstract: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures.  Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever >= to 37.5C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the case fatality ratio (CFR) as an assumed baseline. We then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment.  We estimate that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.38% (Bangladesh) to 99.6% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6th July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 17.8 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. Despite low case detection in some countries, our results that adjust for this still suggest that all countries have had only a small fraction of their populations infected as of July 2020.  We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country's population infected with SARS-CoV-2 worldwide is generally low.

title: Smart technologies for fighting pandemics: The techno- and human- driven approaches in controlling the virus transmission
abstract: How do governments in China and Western democracies differ in their technological response to control the transmission of the pandemic? Based on an analysis of academic papers, World Health Organization reports and newspapers, this research compares two opposing approaches, whereas the Chinese cities and government have adopted a techno-driven approach, Western governments have adopted a human-driven approach to control the transmission of Covid-19. The findings highlight that although the techno driven approach may be more productive to identify, isolate and quarantine infected individuals, it also results in the suppression and censoring the citizen views. It is further emphasized that human interaction with the technology is mediated by the political and institutional context in which the technologies are implemented. This paper contributes to literature by understanding the human-technology relationship, and offers five practical observations for controlling virus transmissions during pandemics.

title: Critical evaluation of FDA-approved respiratory multiplex assays for public health surveillance
abstract: Clinical management and identification of respiratory diseases has become more rapid and increasingly specific due to widespread use of PCR(polymerase chain reaction) multiplex technologies. Although significantly improving clinical diagnosis, multiplexed PCR assays could have a greater impact on local and global disease surveillance. The authors wish to propose methods of evaluating respiratory multiplex assays to maximize diagnostic yields specifically for surveillance efforts.  The authors review multiplexed assays and critically assess what barriers have limited these assays for disease surveillance and how these barriers might be addressed. The manuscript focuses specifically on the case study of using multiplexed assays for surveillance of respiratory pathogens. The authors also provide a method of validation of specific surveillance measures.  PCR assays are widely used for clinical diagnosis; however, specific barriers have limited their use for surveillance. Key barriers include differences in testing phase requirements and diagnostic performance evaluation. In this work the authors clarify phase testing requirements and introduce unique diagnostic performance measures that simplify the use of these assays on a per target basis for disease surveillance.

title: $\alpha$-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19
abstract: The novel coronavirus and its deadly outbreak have posed grand challenges to human society: as of March 26, 2020, there have been 85,377 confirmed cases and 1,293 reported deaths in the United States; and the World Health Organization (WHO) characterized coronavirus disease (COVID-19) - which has infected more than 531,000 people with more than 24,000 deaths in at least 171 countries - a global pandemic. A growing number of areas reporting local sub-national community transmission would represent a significant turn for the worse in the battle against the novel coronavirus, which points to an urgent need for expanded surveillance so we can better understand the spread of COVID-19 and thus better respond with actionable strategies for community mitigation. By advancing capabilities of artificial intelligence (AI) and leveraging the large-scale and real-time data generated from heterogeneous sources (e.g., disease related data from official public health organizations, demographic data, mobility data, and user geneated data from social media), in this work, we propose and develop an AI-driven system (named $\alpha$-Satellite}, as an initial offering, to provide hierarchical community-level risk assessment to assist with the development of strategies for combating the fast evolving COVID-19 pandemic. More specifically, given a specific location (either user input or automatic positioning), the developed system will automatically provide risk indexes associated with it in a hierarchical manner (e.g., state, county, city, specific location) to enable individuals to select appropriate actions for protection while minimizing disruptions to daily life to the extent possible. The developed system and the generated benchmark datasets have been made publicly accessible through our website. The system description and disclaimer are also available in our website.

title: Do COVID-19 and crude oil prices drive the US economic policy uncertainty?
abstract: This paper investigates the effect of the novel coronavirus and crude oil prices on the United States (US) economic policy uncertainty (EPU). Using daily data for the period January 21-March 13, 2020, our Autoregressive Distributed Lag (ARDL) model shows that the new infection cases reported at global level, and the death ratio, have no significant effect on the US EPU, whereas the oil price negative dynamics leads to increased uncertainty. However, analyzing the situation outside China, we discover that both new case announcements and the COVID-19 associated death ratio have a positive influence on the US EPU.

title: Covid-19: Pandemonium in our time
abstract: While pandemonium has come to mean wild and noisy disorder, the reference here is to John Milton's epic poem Paradise Lost and the upheaval following Lucifer's banishment from Heaven and his construction of Pandæmonium as his hub. Today's avalanche of conflicting news on how to deal with the coronavirus disease 2019 (Covid-19) brings to mind the Trinity nuclear bomb test with Enrico Fermi estimating its strength by releasing small pieces of paper into the air and measuring their displacement by the shock wave. Fermi's result, in fact not far from the true value, emphasised his ability to make good approximations with few or no actual data. The current wave of Covid-19 presents just this kind of situation as it engulfs the world from ground zero in Wuhan, China. Much information is indeed missing, but datasets that might lead to useful ideas on how to handle this pandemic are steadily accumulating.

title: Scalable and Resilient SARS-CoV2 testing in an Academic Centre
abstract: The emergence of the novel coronavirus SARS-CoV-2 has led to a pandemic infecting more than two million people worldwide in less than four months, posing a major threat to healthcare systems. This is compounded by the shortage of available tests causing numerous healthcare workers to unnecessarily self-isolate. We provide a roadmap instructing how a research institute can be repurposed in the midst of this crisis, in collaboration with partner hospitals and an established diagnostic laboratory, harnessing existing expertise in virus handling, robotics, PCR, and data science to derive a rapid, high throughput diagnostic testing pipeline for detecting SARS-CoV-2 in patients with suspected COVID-19. The pipeline is used to detect SARS-CoV-2 from combined nose-throat swabs and endotracheal secretions/ bronchoalveolar lavage fluid. Notably, it relies on a series of in-house buffers for virus inactivation and the extraction of viral RNA, thereby reducing the dependency on commercial suppliers at times of global shortage. We use a commercial RT-PCR assay, from BGI, and results are reported with a bespoke online web application that integrates with the healthcare digital system. This strategy facilitates the remote reporting of thousands of samples a day with a turnaround time of under 24 hours, universally applicable to laboratories worldwide.

title: Estimating population immunity without serological testing
abstract: We propose an approximate methodology for estimating the overall level of immunity against COVID-19 in a population that has been affected by the recent epidemic. The methodology relies on the currently available mortality data and utilizes the properties of the SIR model. We illustrate the application of the method by estimating the recent levels of immunity in 10 US states with highest case numbers of COVID-19.

title: Lessons from SARS and H1N1/A: Employing a WHO–WTO forum to promote optimal economic-public health pandemic response
abstract: No formal system exists to review trade restrictions imposed during international public health emergencies rapidly. Failure to put one in place creates disincentives for surveillance and reporting, thereby undermining protection efforts. The 2003 SARS outbreak exposed weaknesses in global governance that caused uncoordinated public health and economic responses. New International Health Regulations (IHR), applied first during the 2009 H1N1 influenza outbreak, demonstrated improvement. Yet they failed to allow for management of public health emergencies in a way that balanced threats to health and those to economies and trade. Establishment of a joint WHO–WTO committee to adjudicate these conflicts might better achieve that balance.

title: Underestimation of COVID-19 cases in Japan: an analysis of RT-PCR testing for COVID-19 among 47 prefectures in Japan
abstract: Under the unique Japanese policy to restrict reverse transcriptase-polymerase chain reaction (RT-PCR) testing against severe acute respiratory syndrome coronavirus 2, a nationwide number of its confirmed cases and mortality remains to be low. Yet the information is lacking on geographical differences of these measures and their associated factors.  Evaluation of prefecture-based geographical differences and associated predictors for the incidence and number of RT-PCR tests for COVID-19.   We retrieved domestic laboratory-confirmed cases, deaths, and the number of RT-PCR testing for COVID-19 from January 15 to April 6, 2020 in 47 prefectures in Japan, using publicly-available data by the Ministry of Health, Labour and Welfare. We did descriptive analyses of these three measures and identified significant predictors for the incidence and RT-PCR testing through multiple regression analyses and correlates with the number of deaths through correlation analysis.  The median prefectural-level incidence and number of RT-PCR testing per 100,000 population were 1.14 and 38.6, respectively. Multiple regression analyses revealed that significant predictors for the incidence were prefectural-level population (p < 0.001) and the number of RT-PCR testing (p = 0.03); and those for RT-PCR testing were the incidence (p = 0.025), available beds (p = 0.045) and cluster infections (p = 0.034).  Considering bidirectional association between the incidence and RT-PCR testing, there may have been an underdiagnosed population for the infection. The restraint policy for RT-PCR testing should be revisited to meet the increasing demand under the COVID-19 epidemic.

title: Coronavirus Disease 2019 (COVID-19) Pneumonia in a Hemodialysis Patient
abstract: Coronavirus disease 2019 (COVID-19) is a highly infective disease caused by the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). Previous studies of the COVID-19 pneumonia outbreak were based on information from the general population. Limited data are available for hemodialysis patients with COVID-19 pneumonia. This report describes the clinical characteristics of COVID-19 in an in-center hemodialysis patient, as well as our experience in implementing steps to prevent the spread of COVID-19 pneumonia among in-center hemodialysis patients. The diagnosis, infection control, and treatment of COVID-19 in hemodialysis patients are discussed in this report, and we conclude with recommendations for how a dialysis facility can respond to COVID-19 based on our experiences.

title: Screening and managing of suspected or confirmed novel coronavirus (COVID-19) patients: experiences from a tertiary hospital outside Hubei province
abstract: To report our experiences screening and managing patients with suspected or confirmed novel coronavirus (COVID-19) disease using a hospital-specific protocol.  Longitudinal cohort study.  A 1,200 bed tertiary care teaching hospital in Chengdu, Sichuan, China.  802 adults presenting to hospital with concerns of having COVID-19, 1,246 inpatients and 2,531 hospital visitors.  Screening and management of patients using a hospital-specific protocol, which included fever triage, monitoring visitors and patients, emergency response, personnel training for healthcare team members, health education for patients and family, medical materials management, disinfection and wastes disposal protocols.  Between 23 January and 28 February 2020, 73 people were identified as having fever plus respiratory signs with/without a history of exposure and were tested for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by our hospital lab using RT PCR. Forty-five of these 73 people were subsequently excluded based on one negative RT PCR result plus positive results to quick screening tests for flu or other respiratory viruses. The remaining 28 people received a second RT PCR test 24 h later. Three people were confirmed positive for COVID-19 based on two consecutive positive RT PCR tests whilst 25 people were excluded based on two consecutive negative tests. The three COVID-19 confirmed cases received non-critical care. There were no new infections of medical staff or new infections of other hospital inpatients.  All three cases were detected as a result of vigilant monitoring of hospital visitors. Whilst screening out-patients presenting to a fever clinic remains important, monitoring visitors must not be overlooked.

title: Social distancing strategies for curbing the COVID-19 epidemic
abstract: The SARS-CoV-2 pandemic is straining healthcare resources worldwide, prompting social distancing measures to reduce transmission intensity. The amount of social distancing needed to curb the SARS-CoV-2 epidemic in the context of seasonally varying transmission remains unclear. Using a mathematical model, we assessed that one-time interventions will be insufficient to maintain COVID-19 prevalence within the critical care capacity of the United States. Seasonal variation in transmission will facilitate epidemic control during the summer months but could lead to an intense resurgence in the autumn. Intermittent distancing measures can maintain control of the epidemic, but without other interventions, these measures may be necessary into 2022. Increasing critical care capacity could reduce the duration of the SARS-CoV-2 epidemic while ensuring that critically ill patients receive appropriate care.

title: Coronavirus disease (COVID-19): a scoping review
abstract: In December 2019, a pneumonia caused by a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and has rapidly spread around the world since then.  This study aims to understand the research gaps related to COVID-19 and propose recommendations for future research.  We undertook a scoping review of COVID-19, comprehensively searching databases and other sources to identify literature on COVID-19 between 1 December 2019 and 6 February 2020. We analysed the sources, publication date, type and topic of the retrieved articles/studies.  We included 249 articles in this scoping review. More than half (59.0%) were conducted in China. Guidance/guidelines and consensuses statements (n = 56; 22.5%) were the most common. Most (n = 192; 77.1%) articles were published in peer-reviewed journals, 35 (14.1%) on preprint servers and 22 (8.8%) posted online. Ten genetic studies (4.0%) focused on the origin of SARS-CoV-2 while the topics of molecular studies varied. Nine of 22 epidemiological studies focused on estimating the basic reproduction number of COVID-19 infection (R(0)). Of all identified guidance/guidelines (n = 35), only ten fulfilled the strict principles of evidence-based practice. The number of articles published per day increased rapidly until the end of January.  The number of articles on COVID-19 steadily increased before 6 February 2020. However, they lack diversity and are almost non-existent in some study fields, such as clinical research. The findings suggest that evidence for the development of clinical practice guidelines and public health policies will be improved when more results from clinical research becomes available.

title: Impact of relaxing Covid-19 social distancing measures on rural North Wales: a simulation analysis
abstract: Social distancing policies aimed to limit Covid-19 are gradually being relaxed as nationally reported peaks in incident cases are passed. Population density is an important driver of national incidence rates; however peak incidences in rural regions may lag national figures by several weeks. We aimed to forecast the impact of relaxed social distancing rules on rural North Wales.  Daily data on the deaths of people with a positive test for Covid-19 were obtained from Public Health Wales and the UK Government. Sigmoidal growth functions were fitted by non-linear least squares and model averaging used to extrapolate mortality over time. The dates of peak mortality incidences for North Wales, Wales and the UK; and the percentage predicted maximum mortality (as of 7th May 2020) were estimated.  The peak daily death rates in Wales and the UK were estimated to have occurred on the 14/04/2020 and 15/04/2020, respectively. For North Wales, this occurred on the 07/05/2020, corresponding to the date of analysis. The number of deaths reported in North Wales represents 31% of the predicted total cumulative number, compared with 71% and 60% for Wales and the UK, respectively.  Policies governing the movement of people in the gradual release from lockdown are likely to impact significantly on areas -principally rural in nature- where cases of Covid-19, deaths and immunity are likely to be much lower than in populated areas. This is particularly difficult to manage across jurisdictions, such as between England and Wales, and in popular holiday destinations.

title: Estimating the seroprevalence of SARS-CoV-2 infections: systematic review
abstract: Accurate seroprevalence estimates of SARS-CoV-2 in different populations could help gauge the true magnitude and spread of the infection seroprevalence. Reported estimates have varied greatly, but many have derived from biased samples, and inadequate testing methods.  To estimate the range of valid seroprevalence rates of SARS-CoV-2 in different populations, and compare these seroprevalence estimates with the cumulative cases seen in the same population.  We searched PubMed, Embase, the Cochrane COVID-19 trials, and Europe-PMC for published studies and pre-prints from January 2020 to 25 May 2020 that reported anti-SARS-CoV-2 IgG, IgM and/or IgA antibodies for serosurveys of either the general community or of defined sub-populations, such healthcare workers and other organizations.  Of the 837 studies identified, 49 were assessed and 14 were includable. Included studies represented 10 countries and 100,557 subjects: 9 from randomly selected populations, 2 from healthcare workers, 2 from industry populations, and 1of parturient women. The seroprevalence proportions in 10 studies ranged between 1%-10%, and 2 study estimates under 1%, and 2 over 10% - from the notably hard-hit regions of Gangelt in Germany and from Northwest Iran. The two studies in healthcare workers, in Italy and Spain, had seroprevalence rates at higher range of estimates, with the Barcelona hospitals having a higher rate than the Spanish national survey. For only one study was the seroprevalence estimate higher than the cumulative incidence, though these were proximate for several studies. In five studies, the seroprevalence was similar to the cumulative case numbers in the same population. For seropositive cases not previously detected as COVID-19 cases, the majority had prior COVID-like symptoms.  The seroprevalence of SARS-CoV-2 mostly less than 10% with the level of infection lower in the general community, suggesting levels well below herd immunity. The similarity of seroprevalence and reported cases is several studies, and high symptom rates in seropositive cases suggest that gaps between seroprevalence rates and reported cases are likely due to undertesting of symptomatic people.

title: Failure in initial stage containment of global COVID‐19 epicenters
abstract: With multiple virus epicenters, COVID‐19 has been declared a pandemic by the World Health Organization. Consequently, many countries have implemented different policies to manage this crisis including curfew and lockdown. However, the efficacy of individual policies remains unclear with respect to COVID‐19 case development. We analyzed available data on COVID‐19 cases of eight majorly affected countries, including China, Italy, Iran, Germany, France, Spain, South Korea, and Japan. Growth rates and doubling time of cases were calculated for the first 6 weeks after the initial cases were declared for each respective country and put into context with implemented policies. Although the growth rate of total confirmed COVID‐19 cases in China has decreased, those for Japan have remained constant. For European countries, the growth rate of COVID‐19 cases considerably increased during the second time interval. Interestingly, the rates for Germany, Spain, and France are the highest measured in the second interval and even surpass the numbers in Italy. Although the initial data in Asian countries are encouraging with respect to case development at the initial stage, the opposite is true for European countries. Based on our data, disease management in the 2 weeks following the first reported cases is of utmost importance.

title: COVID-19 and cardiovascular disease: What we know, what we think we know, and what we need to know

title: Snapshot PCR Surveillance for SARS-CoV-2 in Hospital Staff in England
abstract: Significant nosocomial transmission of SARS-CoV-2 has been demonstrated. Understanding the prevalence of SARS-CoV-2 carriage amongst HCWs at work is necessary to inform the development of HCW screening programmes to control nosocomial spread.  Cross-sectional snapshot survey from April-May 2020; HCWs recruited from six UK hospitals. Participants self-completed a health questionnaire and underwent a combined viral nose and throat swab, tested by Polymerase Chain Reaction (PCR) for SARS-CoV-2 with viral culture on majority of positive samples.  Point prevalence of SARS-CoV-2 carriage across the sites was 2.0% (23/1152 participants), median cycle threshold value 35.70 (IQR:32.42-37.57). 17 were previously symptomatic, two currently symptomatic (isolated anosmia and sore throat); the remainder declared no prior or current symptoms. Symptoms in the past month were associated with threefold increased odds of testing positive (aOR 3.46, 95%CI 1.38-8.67; p=0.008). SARS-CoV-2 virus was isolated from only one (5%) of nineteen cultured samples. A large proportion (39%) of participants reported symptoms in the past month.  The point-prevalence is similar to previous estimates for HCWs in April 2020, though a magnitude higher than in the general population. Based upon interpretation of symptom history and testing results including viral culture, the majority of those testing positive were unlikely to be infectious at time of sampling. Development of screening programmes must balance the potential to identify additional cases based upon likely prevalence, expanding the symptoms list to encourage HCW testing, with resource implications and risks of excluding those unlikely to be infectious with positive tests.

title: COVID-19 and diabetes mellitus: what we know, how our patients should be treated now, and what should happen next

title: Rapid sputum testing and not thermal screening alone should be the first-line screening test at airports: A Bayesian analysis

title: COVID-19 infection during pregnancy: fetus as a patient deserves more attention.
abstract: The novel coronavirus disease 2019 (COVID-19) pandemic is causing concern also for the management and outcome of COVID-19-positive pregnant women and their offspring, as reported cases are rare. Current evidence suggests the association of COVID-19 infection in pregnancy with both severe maternal morbidity requiring intensive care and perinatal complications (preterm birth with consequent neonatal morbidity and even perinatal death). Most of the reported cases focused specifically on the maternal outcomes and possible vertical transmission, but less attention has been paid to fetus as a patient in such pregnancies. The use of antenatal steroids and fetal neuroprotection with magnesium sulfate is clearly underreported. Several recently issued guidelines suggest lowering the upper gestational age for antenatal steroid administration and also advocate extreme caution or even restraining from the use of magnesium sulfate. Also, the rate of cesarean deliveries among COVID-19 women is unacceptably high. Here we provide arguments for NOT changing the existing guidelines and caution against cesarean delivery that was the prevalent delivery mode in the reported cases and case series.

title: Asymmetry of lower extremity force and muscle activation during knee extension and functional tasks.
abstract: Strength and power asymmetries of >10% may negatively impact physical function.  Twenty-four healthy participants, 30-60 years of age, were assessed for muscle power asymmetry during isokinetic knee extension and ground reaction force asymmetry during chair-rise and vertical jump tasks. Neuromuscular activation asymmetry and coactivation of vastus lateralis (VL) and biceps femoris (BF) were assessed in each condition. Symmetric (SG) and asymmetric (AG) groups were identified using a 10% knee extension power asymmetry criterion.  The AG had greater chair-rise rate of force development asymmetry (P = 0.003, d = 1.29), but a similar chair-rise and vertical jump peak force asymmetry as the SG. Large group effects were found for VL activation asymmetry during knee extension (P = 0.047, d = 0.87), BF activation asymmetry during vertical jump (P = 0.015, d = 1.12), and strong leg coactivation during vertical jump (P = 0.028, d = 0.96).  Compensation for muscle power asymmetry may occur during functional tasks, potentially through differential activation of strong and weak leg muscles. Muscle Nerve 56: 495-504, 2017.

title: A Real-Time Statistical Model for Tracking and Forecasting COVID-19 Deaths, Prevalence and Incidence
abstract: Pandemics do not occur frequently and when they do there is a paucity of predictive tools that could help drive government responses to mitigate worst outcomes. Here we provide a forecasting model that is based on measurable variables and that strives for simplicity over complexity to obtain stable convergent forecasts of death, prevalence, incidence, and safe days for social easing.  We assume, based on prior pandemic data, that death rate rise and fall approximately follows a Gaussian distribution, which can be asymmetric, which we describe. By taking daily death data for foreign countries and U.S. states and fitting it to an appropriate Gaussian function provides an estimate of where in the cycle a particular population lies. From that time point one can integrate remaining time to obtain a final total death. By also using measured values for the time from infection to recovery or death and a mortality factor, the prevalence (active cases) and incidence (new cases) totals and rate curves can be constructed. It is also possible by setting a downward threshold on prevalence that an estimate of a minimum date to begin relaxing social restrictions may be considered.  To demonstrate the model we chose the most severe hot-bed countries and U.S. states as a test-bed to evolve and improve our model and to compare with other models. The model can readily be applied to other countries by inputting data from public data bases. We also compare our forecasts to the University of Washington (UW) IHME model and are reassuringly similar yet show less variability on a weekly basis. The sum of squares for error (SSE) for international and U.S. states, respectively, that we track are: 34% and 33% for our model vs. 49% and 59% for the IHME model.  Our model appears closest to the UW IHME model; however, there are important differences and while both models forecast many of the same results of interest, each one offers unique benefits that the other does not. We believe that the model reported here excels for its simplicity, which makes the model easy to use.

title: On the true numbers of COVID-19 infections: behind the available data
abstract: In December-2019 China reported several cases of a novel coronavirus later called COVID-19. In this work, we will use a probabilistic method for approximating the true daily numbers of infected. Based on two distribution functions to describe the spontaneous recovered cases on the one hand and the detected cases on the other hand. The impact of the underlying variables of these functions is discussed. The detected rate is predicted to be between 5.3% and 10,8%, which means that there would be about 38 million infected until now (10-May 2020), rather than the officially declared number of 3.99 million worldwide cases.

title: Impact of SARS-CoV-2 infection on neurodegenerative and neuropsychiatric diseases: A delayed pandemic?
abstract: SARS-CoV-2 was first detected in December 2019 in the Chinese city of Wuhan and has since spread across the world. At present, the virus has infected over 1.7 million people and caused over 100000 deaths worldwide. Research is currently focused on understanding the acute infection and developing effective treatment strategies. In view of the magnitude of the epidemic, we conducted a speculative review of possible medium- and long-term neurological consequences of SARS-CoV-2 infection, with particular emphasis on neurodegenerative and neuropsychiatric diseases of neuroinflammatory origin, based on the available evidence on neurological symptoms of acute SARS-CoV-2 infection. Development We systematically reviewed the available evidence about the pathogenic mechanisms of SARS-CoV-2 infection, the immediate and lasting effects of the cytokine storm on the central nervous system, and the consequences of neuroinflammation for the central nervous system.  SARS-CoV-2 is a neuroinvasive virus capable of triggering a cytokine storm, with persistent effects in specific populations. Although our hypothesis is highly speculative, the impact of SARS-CoV-2 infection on the onset and progression of neurodegenerative and neuropsychiatric diseases of neuroinflammatory origin should be regarded as the potential cause of a delayed pandemic that may have a major public health impact in the medium to long term. Cognitive and neuropsychological function should be closely monitored in COVID-19 survivors.

title: The dynamics of Covid-19: weather, demographics and infection timeline
abstract: We study the effects of three types of variables on the early pace of spread of Covid-19: weather variables, temperature and absolute humidity; population density; the timeline of Covid-19 infection, as outbreak of disease occurs in different dates for different regions. The regions considered were all 50 U.S. states and 110 countries (those which had enough data available by April 10th. We looked for associations between the above variables and an estimate of the growth rate of cases, the exponential coefficient, computed using data for 10 days starting when state/country reached 100 confirmed cases. The results for U.S. states indicate that one cannot expect that higher temperatures and higher levels of absolute humidity would translate into slower pace of Covid-19 infection rate, at least in the ranges of those variables during the months of February and March of 2020 (-2.4 to 24C and 2.3 to 15g/m3). In fact, the opposite is true: the higher the temperature and the absolute humidity, the faster the Covid-19 has expanded in the U.S. states, in the early stages of the outbreak. Secondly, using the highest county population density for each state, there is strong positive association between population density and (early) faster spread of Covid-19. Finally, there is strong negative association between the date when a state reached 100 accumulated cases and the speed of Covid-10 outbreak (the later, the lower the estimate of growth rate). When these variables are considered together, only population density and the timeline variable show statistical significance. We also develop the basic models for the collection of countries, without the demographic variable. Despite the evidence, in that case, that warmer and more humid countries have shown lower rates of Covid-19 expansion, the weather variables lose statistical significance when the timeline variable is added.

title: [Covid-19 - deaths and analysis].
abstract: Mortality from Covid-19 is monitored in detail and compared between countries with different strategies against the virus. There is, however, often a lack of understanding of what is required in terms of measures and interpretation to enable correct comparisons. The number of deaths from Covid-19 is affected by the testing strategy and many other things that differ between countries. Therefore, today, the most reliable source for monitoring and comparing mortality from Covid-19 is total mortality. In Sweden, there is good correspondence of Covid-19 deaths and total mortality, with a tendency to a higher total mortality indicating some under-reporting of Covid-19 mortality.

title: The proportion testing positive for SARS-COV-2 among the tested population in the U.S.: Benefits of the positive test ratio under scaled testing scenarios
abstract: The ratios offer simple ways to account for variations in testing and reporting. Tracking the ratios in addition to cases offer a more precise view of the pandemic. Our observations underscore the need to scale mass testing with accurate and reliable tests, to implement testing systematically and report results consistently.

title: An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City
abstract: New York City was the first major urban center of the COVID-19 pandemic in the USA. Cases are clustered in the city, with certain neighborhoods experiencing more cases than others. We investigate whether potential socioeconomic factors can explain between-neighborhood variation in the number of detected COVID-19 cases.  Data were collected from 177 Zip Code Tabulation Areas (ZCTA) in New York City (99.9% of the population). We fit multiple Bayesian Besag-York-Mollié (BYM) mixed models using positive COVID-19 tests as the outcome and a set of 10 representative economic, demographic, and health-care associated ZCTA-level parameters as potential predictors. The BYM model includes both spatial and nonspatial random effects to account for clustering and overdispersion.  Multiple different regression approaches indicated a consistent, statistically significant association between detected COVID-19 cases and dependent (under 18 or 65+ years old) population, male to female ratio, and median household income. In the final model, we found that an increase of only 1% in dependent population is associated with a 2.5% increase in detected COVID-19 cases (95% confidence interval (CI): 1.6% to 3.4%, p < 0.0005). An increase of 1 male per 100 females is associated with a 1.0% (95% CI: 0.6% to 1.5%, p < 0.0005) increases in detected cases. A decrease of $10,000 median household income is associated with a 2.5% (95% CI: 1.0% to 4.1% p = 0.002) increase in detected COVID-19 cases.  Our findings indicate associations between neighborhoods with a large dependent population, those with a high proportion of males, and low-income neighborhoods and detected COVID-19 cases. Given the elevated mortality in aging populations, the study highlights the importance of public health management during and after the current COVID-19 pandemic. Further work is warranted to fully understand the mechanisms by which these factors may have affected the number of detected cases, either in terms of the true number of cases or access to testing.

title: Age-stratified Infection Probabilities Combined with Quarantine-Modified SEIR Model in the Needs Assessments for COVID-19
abstract: We use the age-stratified COVID-19 infection and death distributions from China (more than 44,672 infectious as of February 11, 2020) as an estimate for a study area infection and morbidity probabilities at each age group. We then apply these probabilities into the actual age-stratified population to predict infectious individuals and deaths at peak. Testing with different countries shows the predicted infectious skewing with the country median age and age stratification, as expected. We added a Q parameter to the classic SEIR compartmental model to include the effect of quarantine (Q-SEIR). The projections from the age-stratified probabilities give much lower predicted incidences of infection than the Q-SEIR model. As expected, quarantine tends to delay the peaks for both Exposed and Infectious, and to flatten the curve or lower the predicted values for each compartment. These two estimates were used as a range to inform planning and response to the COVID-19 threat.

title: Increasing Incidence of Zygomycosis (Mucormycosis), France, 1997–2006
abstract: We analyzed hospital records to provide a population-based estimate of zygomycosis incidence and trends over a 10-year period at a national level in France. Data showed an increasing incidence from 0.7/million in 1997 to 1.2/million in 2006 (p<0.001). We compared our data with those from the French Mycosis Study Group, a recently established voluntary network of French mycologists coordinated by the National Reference Center for Mycoses and Antifungals. We documented that incidence of zygomycosis increased, particularly in patients with hematologic malignancies or bone marrow transplants. The role of previous exposure to antifungal drugs lacking activity against zygomycetes could explain this increase but does not appear exclusive. Incidence also increased in the population of patients with diabetes mellitus. We conclude that observed trends reflect a genuine increase of zygomycosis cases in at-risk populations.

title: Early impact of COVID‐19 on transplant center practices and policies in the United States
abstract: COVID‐19 is a novel, rapidly changing pandemic: consequently, evidence‐based recommendations in solid organ transplantation (SOT) remain challenging and unclear. To understand the impact on transplant activity across the United States, and center‐level variation in testing, clinical practice, and policies, we conducted a national survey between March 24, 2020 and March 31, 2020 and linked responses to the COVID‐19 incidence map. Response rate was a very high 79.3%, reflecting a strong national priority to better understand COVID‐19. Complete suspension of live donor kidney transplantation was reported by 71.8% and live donor liver by 67.7%. While complete suspension of deceased donor transplantation was less frequent, some restrictions to deceased donor kidney transplantation were reported by 84.0% and deceased donor liver by 73.3%; more stringent restrictions were associated with higher regional incidence of COVID‐19. Shortage of COVID‐19 tests was reported by 42.5%. Respondents reported a total of 148 COVID‐19 recipients from <1 to >10 years posttransplant: 69.6% were kidney recipients, and 25.0% were critically ill. Hydroxychloroquine (HCQ) was used by 78.1% of respondents; azithromycin by 46.9%; tocilizumab by 31.3%, and remdesivir by 25.0%. There is wide heterogeneity in center‐level response across the United States; ongoing national data collection, expert discussion, and clinical studies are critical to informing evidence‐based practices.

title: Private Equity-Backed Hospital Investments and the Impact of the Coronavirus Disease 2019 (COVID-19) Epidemic

title: 2019 Novel Coronavirus Disease (COVID-19): Paving the Road for Rapid Detection and Point-of-Care Diagnostics
abstract: We believe a point-of-care (PoC) device for the rapid detection of the 2019 novel Coronavirus (SARS-CoV-2) is crucial and urgently needed. With this perspective, we give suggestions regarding a potential candidate for the rapid detection of the coronavirus disease 2019 (COVID-19), as well as factors for the preparedness and response to the outbreak of the COVID-19.

title: Clinical features of the first cases and a cluster of Coronavirus Disease 2019 (COVID-19) in Bolivia imported from Italy and Spain
abstract: In March 2020, Coronavirus Disease 2019 (COVID-19) arrived in Bolivia. Here, we report the main clinical findings, and epidemiological features of the first series of cases, and a cluster, confirmed in Bolivia.  For this observational, retrospective and cross-sectional study, information was obtained from the Hospitals and the Ministry of Health for the cases that were laboratory-diagnosed and related, during March 2020. rRT-PCR was used for the detection of the RNA of SARS-CoV-2 following the protocol Charité, Berlin, Germany, from nasopharyngeal swabs.  Among 152 suspected cases investigated, 12 (7.9%) were confirmed with SARS-CoV-2 infected by rRT-PCR. The median age was 39 years (IQR 25–43), six of them male. Two cases proceed from Italy and three from Spain. Nine patients presented fever, and cough, five sore throat, and myalgia, among other symptoms. Only a 60 y-old woman with hypertension was hospitalized. None of the patients required ICU nor fatalities occurred in this group.  This is the first report of surveillance of COVID-19 in Bolivia, with patients managed mainly with home isolation. Preparedness for a significant epidemic, as is going on in other countries, and the deployment of response plans for it, in the country is now taking place to mitigate the impact of the COVID-19 pandemic in the population.

title: Modelling the transmission dynamics of COVID-19 in six high burden countries
abstract: The new coronavirus disease, officially known as COVID-19, originated in China in 2019 and has since spread around the globe. We presented a modified Susceptible-Latent-Infected-Removed (SLIR) compartmental model of COVID-19 disease transmission with nonlinear incidence during the epidemic period. We provided the model calibration to estimate parameters with day wise corona virus (COVID-19) data i.e. reported cases by worldometer from the period of 15th February to 30th March, 2020 in six high burden countries including Australia, Italy, Spain, USA, UK and Canada. We estimate transmission rates for each countries and found that the highest transmission rate country in Spain, which may be increase the new cases and deaths in Spain than the other countries. Sensitivity analysis was used to identify the most important parameters through the partial rank correlation coefficient method. We found that the transmission rate of COVID-19 had the largest influence on the prevalence. We also provides the prediction of new cases in COVID-19 until May 18, 2020 using the developed model and recommends, control strategies of COVID-19. The information that we generated from this study would be useful to the decision makers of various organizations across the world including the Ministry of Health in Australia, Italy, Spain, USA, UK and Canada to control COVID-19.

title: True epidemic growth construction through harmonic analysis
abstract: In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second phase, we used this partial data to generate plausible complete data through wavelets. We have provided two numerical examples. This procedure is novel and implementable and adaptable to machine learning modeling framework.

title: Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19
abstract: Traveller screening is being used to limit further spread of COVID-19 following its recent emergence, and symptom screening has become a ubiquitous tool in the global response. Previously, we developed a mathematical model to understand factors governing the effectiveness of traveller screening to prevent spread of emerging pathogens (Gostic et al., 2015). Here, we estimate the impact of different screening programs given current knowledge of key COVID-19 life history and epidemiological parameters. Even under best-case assumptions, we estimate that screening will miss more than half of infected people. Breaking down the factors leading to screening successes and failures, we find that most cases missed by screening are fundamentally undetectable, because they have not yet developed symptoms and are unaware they were exposed. Our work underscores the need for measures to limit transmission by individuals who become ill after being missed by a screening program. These findings can support evidence-based policy to combat the spread of COVID-19, and prospective planning to mitigate future emerging pathogens.

title: Estimation of COVID-2019 burden and potential for international dissemination of infection from Iran
abstract: The Coronavirus Disease 2019 (COVID-19) epidemic began in Wuhan, China in late 2019 and continues to spread globally, with exported cases confirmed in 28 countries at the time of writing. During the interval between February 19 and 23, 2020, Iran reported its first 43 cases with eight deaths. Three exported cases originating in Iran were identified, suggesting a underlying burden of disease in that country than is indicated by reported cases. A large epidemic in Iran could further fuel global dissemination of COVID-19. We sought to estimate COVID-19 outbreak size in Iran based on known exported case counts and air travel links between Iran and other countries, and to anticipate where infections originating in Iran may spread to next. We assessed interconnectivity between Iran and other countries using using International Air Transport Association (IATA) data. We used the methods of Fraser et al. to estimate the size of the underlying epidemic that would result in cases being observed in the United Arab Emirates (UAE), Lebanon, and Canada. Time at risk estimates were based on a presumed 6 week epidemic age, and length of stay data for visitors to Iran derived from the United Nations World Tourism Organization (UNWTO). We evaluated the relationship between the strength of travel links with Iran, and destination country rankings on the Infectious Disease Vulnerability Index (IDVI), a validated metric that estimates the capacity of a country to respond to an infectious disease outbreak . Scores range between 0-1, with higher scores reflecting greater capacity to manage infectious outbreaks. UAE, Lebanon, and Canada ranked 3rd, 21st, and 31st, respectively, for outbound air travel volume from Iran in February 2019. We estimated that 18,300 (95% confidence interval: 3770 to 53,470) COVID-19 cases would have had to occur in Iran, assuming an outbreak duration of 1.5 months in the country, in order to observe these three internationally exported cases reported at the time of writing. Results were robust under varying assumptions about undiagnosed case numbers in Syria, Azerbaijan and Iraq. Even if it were assumed that all cases were identified in all countries with certainty, the "best case" outbreak size was substantial (1820, 95% CI: 380-5320 cases), and far higher than reported case counts. Given the low volumes of air travel to countries with identified cases of COVID-19 with origin in Iran (such as Canada), it is likely that Iran is currently experiencing a COVID-19 epidemic of significant size for such exportations to be occurring. This is concerning, both for public health in Iran itself, and because of the high likelihood for outward dissemination of the epidemic to neighbouring countries with lower capacity to respond to infectious diseases epidemics.

title: A Social Network Model of the COVID-19 Pandemic
abstract: In the COVID-19 coronavirus pandemic, currently vaccines and specific anti-viral treatment are not yet available. Thus, preventing viral transmission by case isolation, quarantine, and social distancing is essential to slowing its spread. Here we model social networks using weighted graphs, where vertices represent individuals and edges represent contact. As public health measures are implemented, connectivity in the graph decreases, resulting in lower effective reproductive numbers, and reduced viral transmission. For COVID-19, model parameters were derived from the coronavirus epidemic in China, validated by epidemic data in Italy, then applied to the United States. We calculate that, in the U.S., the public is able to contain viral transmission by limiting the average number of contacts per person to less than 7 unique individuals over each 5 day period. This increases the average social distance between individuals to 10 degrees of separation.

title: Multi-Stage Group Testing Improves Efficiency of Large-Scale COVID-19 Screening
abstract: SARS-CoV-2 test kits are in critical shortage in many countries. This limits large-scale population testing and hinders the effort to identify and isolate infected individuals.  Herein, we developed and evaluated multi-stage group testing schemes that test samples in groups of various pool sizes in multiple stages. Through this approach, groups of negative samples can be eliminated with a single test, avoiding the need for individual testing and achieving considerable savings of resources.  We designed and parameterized various multi-stage testing schemes and compared their efficiency at different prevalence rates using computer simulations.  We found that three-stage testing schemes with pool sizes of maximum 16 samples can test up to three and seven times as many individuals with the same number of test kits for prevalence rates of around 5% and 1%, respectively. We propose an adaptive approach, where the optimal testing scheme is selected based on the expected prevalence rate.  These group testing schemes could lead to a major reduction in the number of testing kits required and help improve large-scale population testing in general and in the context of the current COVID-19 pandemic.

title: Robust estimation of diagnostic rate and real incidence of COVID-19 for European policymakers
abstract: Policymakers need a clear and fast assessment of the real spread of the epidemic of COVID-19 in each of their respective countries. Standard measures of the situation provided by the governments include reported positive cases and total deaths. While total deaths immediately indicate that countries like Italy and Spain have the worst situation as of mid April 2020, on its own, reported cases do not provide a correct picture of the situation. The reason is that different countries diagnose diversely and present very distinctive reported case fatality rate (CFR). The same levels of reported incidence and mortality might hide a very different underlying picture. Here we present a straightforward and robust estimation of the diagnostic rate in each European country. From that estimation we obtain an uniform unbiased incidence of the epidemic. The method to obtain the diagnostic rate is transparent and empiric. The key assumption of the method is that the real CFR in Europe of COVID-19 is not strongly country-dependent. We show that this number is not expected to be biased due to demography nor the way total deaths are reported. The estimation protocol has a dynamic nature, and it has been giving converging numbers for diagnostic rates in all European countries as of mid April 2020. From this diagnostic rate, policy makers can obtain an Effective Potential Growth (EPG) updated everyday providing an unbiased assessment of the countries with more potential to have an uncontrolled situation. The method developed will be used to track possible improvements on the diagnostic rate in European countries as the epidemic evolves.

title: How to Best Predict the Daily Number of New Infections of Covid-19
abstract: Knowledge about the daily number of new infections of Covid-19 is important because it is the basis for political decisions resulting in lockdowns and urgent health care measures. We use Germany as an example to illustrate shortcomings of official numbers, which are, at least in Germany, disclosed only with several days of delay and severely underreported on weekends (more than 40%). These shortcomings outline an urgent need for alternative data sources. The other widely cited source provided by the Center for Systems Science and Engineering at Johns Hopkins University (JHU) also deviates for Germany on average by 79% from the official numbers. We argue that Google Search and Twitter data should complement official numbers. They predict even better than the original values from Johns Hopkins University and do so several days ahead. These two data sources could also be used in parts of the world where official numbers do not exist or are perceived to be unreliable.

title: Poster Sessions

title: Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak
abstract: The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.

title: Application of the ARIMA model on the COVID-2019 epidemic dataset
abstract: Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors and analyses are subject to potential bias. Here, we propose a simple econometric model that could be useful to predict the spread of COVID-2019. We performed Auto Regressive Integrated Moving Average (ARIMA) model prediction on the Johns Hopkins epidemiological data to predict the epidemiological trend of the prevalence and incidence of COVID-2019. For further comparison or for future perspective, case definition and data collection have to be maintained in real time.

title: Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
abstract: As of March 31, 2020, the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued.  Here we estimate the effective reproduction number, Rt, of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts.  The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI 0.3, 1.0) during the first transmission wave by February 14, 2020, while the overall R based on the cluster size distribution as of March 17, 2020, was estimated at 0.6 (95% CI 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p < 0.001).  The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.

title: The usefulness of SARS-CoV-2 test positive proportion as a surveillance tool
abstract: Comparison of COVID-19 case numbers over time and between locations is complicated by limits to virologic testing confirm SARS-CoV-2 infection, leading to under-reporting of incidence, and by variations in testing capacity between locations and over time. The proportion of tested individuals who have tested positive (test positive proportion, TPP) can potentially be used to qualitatively assess the testing capacity of a location; a high TPP could provide evidence that too few people are tested, leading to more under-reporting. In this study we propose a simple model for testing in a population experiencing an epidemic of COVID-19, and derive an expression for TPP in terms of well-defined parameters in the model, related to testing and presence of other pathogens causing COVID-19 like symptoms. We use simulations to show situations in which the TPP is higher or lower than we expect based on these parameters, and the effect of testing strategies on the TPP. In our simulations, we find in the absence of dramatic shifts of testing practices in time or between spatial locations, the TPP is positively correlated with the incidence of infection. As a corollary, the TPP can be used to distinguish between a decline in confirmed cases due to decline in incidence (in which case TPP should decline) and a decline in confirmed cases due to testing constraints (in which case TPP should remain constant). We show that the proportion of tested individuals who present COVID-19 like symptoms (test symptomatic proportion, TSP) encodes similar information to the TPP but has different relationships with the testing parameters, and can thus provide additional information regarding dynamic changes in TPP and incidence. Finally, we compare data on confirmed cases and TPP from US states. We conjecture why states may have higher or lower TPP than average. We suggest that collection of symptom status and age/risk category of tested individuals can aid interpretation of changes in TPP and increase the utility of TPP in assessing the state of the pandemic in different locations and times.

title: Considerations for pharmacoepidemiological analyses in the SARS-CoV-2 pandemic.
abstract: The coronavirus disease 2019 (COVID-19) pandemic has triggered several hypotheses regarding use of specific medicines and risk of infection as well as prognosis. Under these unique circumstances, rapid answers require quick engagement in data collection and analyses, however, appropriate design and conduct of pharmacoepidemiologic studies is needed to generate valid and reliable evidence. In this paper, endorsed by the International Society for Pharmacoepidemiology, we provide methodological considerations for the conduct of pharmacoepidemiological studies in relation to the pandemic across eight domains: (1) timeliness of evidence, including the need to prioritize some questions over others in the acute phase of the pandemic; (2) the need to align observational and interventional research on efficacy; (3) the specific challenges related to 'real-time epidemiology' during an ongoing pandemic; (4) what design to use to answer a specific question; (5) considerations on the definition of exposures; (6) what covariates to collect; (7) considerations on the definition of outcomes; and (8) the need for transparent reporting. This article is protected by copyright. All rights reserved.

title: COVID-19 in Africa -- outbreak despite interventions?
abstract: In Africa, while most countries report some COVID-19 cases, the fraction of reported patients is low, with about 20,000 cases compared to the more than 2.3 million cases reported globally as of April 18, 2020. Few African countries have reported case numbers above one thousand, with South Africa reporting 3,034 cases being hit hardest in Sub-Saharan Africa. Several African countries, especially South Africa, have already taken strong non-pharmaceutical interventions that include physical distancing, restricted economic, educational and leisure activities and reduced human mobility options. The required strengths and overall effectiveness of such interventions, however, are debated because of simultaneous but opposing interests in most African countries: strongly limited health care capacities and testing capabilities largely conflict with pressured national economies and socio-economic hardships on the individual level, limiting compliance to intervention targets. Here we investigate implications of interventions on the COVID-19 outbreak dynamics, focusing on South Africa before and after the national lockdown enacted on March 27, 2020. Our analysis shows that initial exponential growth of existing case numbers is consistent with doubling times of about 2.5 days. After lockdown, the growth remains exponential, now with doubling times of 18 days, but still in contrast to subexponential growth reported for Hubei/China after lockdown. Moreover, a scenario analysis of a computational data-driven agent based mobility model for the Nelson Mandela Bay Municipality (with 1.14 million inhabitants) hints that keeping current levels of intervention measures and compliance until the end of April is of insufficient length and still too weak, too unspecific or too inconsistently complied with to not overload local intensive care capacity. Yet, enduring, slightly stronger, more specific interventions combined with sufficient compliance may constitute a viable option for interventions for regions in South Africa and potentially for large parts of the African continent and the Global South.

title: Covid-19: Selected NHS patients will be treated with remdesivir

title: Use of Available Data To Inform The COVID-19 Outbreak in South Africa: A Case Study
abstract: The coronavirus disease (COVID-19), caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organization (WHO) in February 2020. Currently, there are no vaccines or treatments that have been approved after clinical trials. Social distancing measures, including travel bans, school closure, and quarantine applied to countries or regions are being used to limit the spread of the disease and the demand on the healthcare infrastructure. The seclusion of groups and individuals has led to limited access to accurate information. To update the public, especially in South Africa, announcements are made by the minister of health daily. These announcements narrate the confirmed COVID-19 cases and include the age, gender, and travel history of people who have tested positive for the disease. Additionally, the South African National Institute for Communicable Diseases updates a daily infographic summarising the number of tests performed, confirmed cases, mortality rate, and the regions affected. However, the age of the patient and other nuanced data regarding the transmission is only shared in the daily announcements and not on the updated infographic. To disseminate this information, the Data Science for Social Impact research group at the University of Pretoria, South Africa, has worked on curating and applying publicly available data in a way that is computer-readable so that information can be shared to the public - using both a data repository and a dashboard. Through collaborative practices, a variety of challenges related to publicly available data in South Africa came to the fore. These include shortcomings in the accessibility, integrity, and data management practices between governmental departments and the South African public. In this paper, solutions to these problems will be shared by using a publicly available data repository and dashboard as a case study.

title: Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases
abstract: The novel of COVID-19 disease started in late 2019 making the worldwide governments came across a high number of critical and death cases, beyond constant fear of the collapse in their health systems. Since the beginning of the pandemic, researchers and authorities are mainly concerned with carrying out quantitative studies (modeling and predictions) overcoming the scarcity of tests that lead us to under- reporting cases. To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil. The proposed model was enforced to obtain estimates of important quantities such as the reproductive rate and the average infection period, along with the more likely date when the pandemic peak may occur. Several under-reporting scenarios were considered in the simulation study, showing how impacting is the lack of information in the modeling.

title: The novel Coronavirus (SARS-CoV-2) is a one health issue

title: Health literacy of inland population in the mitigation phase 3.2. of COVID-19's pandemic in Portugal - a descriptive cohort study
abstract: COVID-19 is a respiratory disease transmitted through respiratory droplets with a high transmission rate. There's still no effective and approved antiretroviral treatment or vaccine, thus, preventive measures are the main key to contain this pandemic. Portugal is now in phase 3.2 of the mitigation of COVID-19, being imperative to understand the health literacy of our country and how to prevent the lack of information, through community empowerment.  A cross-sectional study with a cohort from a primary care facility was conducted. We collected demographic and epidemiological data and carried out a questionnaire by phone call. Descriptive statistics and nonparametric tests were used to assess associations between the independent variables and the level of health literacy. The level of significance was set at p<0.05.  Our cohort includes 222 subjects (median age: 62 years old), mostly females (131), undergraduate (193) and with at least one risk factor for COVID-19 (144). Globally, younger individuals, females, graduates and the Non-Risk Group appear to have higher levels of health literacy, with some exceptions to this pattern.  We observe a well-informed population. However, being a pandemic situation, we intend to identify and correct outliers/misconceptions. This work allows a perspective of the current state/pattern of health literacy as well as its possible predictors. Furthermore, this study makes aware of how relevant the specific communication approaches are. Further studies to understand the predictors of health literacy are necessary.  COVID-19, pandemic, SARS-CoV2, Portugal, Health literacy.

title: American Indian Reservations and COVID-19: Correlates of Early Infection Rates in the Pandemic
abstract: To determine the household and community characteristics most closely associated with variation in COVID-19 incidence on American Indian reservations in the lower 48 states.  Multivariate analysis with population weights.  Two hundred eighty-seven American Indian Reservations and tribal homelands (in Oklahoma) and, as of April 10, 2020, 861 COVID-19 cases on these reservation lands.  The relationship between rate per 1000 individuals of publicly reported COVID-19 cases at the tribal reservation and/or community level and average household characteristics from the 2018 5-Year American Community Survey records.  By April 10, 2020, in regression analysis, COVID-19 cases were more likely by the proportion of homes lacking indoor plumbing (10.83, P = .001) and were less likely according to the percentage of reservation households that were English-only (-2.43, P = .03). Household overcrowding measures were not statistically significant in this analysis (-6.40, P = .326).  Failure to account for the lack of complete indoor plumbing and access to potable water in a pandemic may be an important determinant of the increased incidence of COVID-19 cases. Access to relevant information that is communicated in the language spoken by many reservation residents may play a key role in the spread of COVID-19 in some tribal communities. Household overcrowding does not appear to be associated with COVID-19 infections in our data at the current time. Previous studies have identified household plumbing and overcrowding, and language, as potential pandemic and disease infection risk factors. These risk factors persist. Funding investments in tribal public health and household infrastructure, as delineated in treaties and other agreements, are necessary to protect American Indian communities.

title: Is ethnicity linked to incidence or outcomes of covid-19?

title: Estimating epidemic exponential growth rate and basic reproduction number
abstract: The initial exponential growth rate of an epidemic is an important measure of the severeness of the epidemic, and is also closely related to the basic reproduction number. Estimating the growth rate from the epidemic curve can be a challenge, because of its decays with time. For fast epidemics, the estimation is subject to over-fitting due to the limited number of data points available, which also limits our choice of models for the epidemic curve. We discuss the estimation of the growth rate using maximum likelihood method and simple models.

title: Prevalence of acute liver injury and hypertransaminemia in patients with COVID-19: a protocol for a systematic review
abstract: COVID-19 has spread rapidly in China and around the world. Published studies have revealed that some patients with COVID-19 had abnormal liver function in laboratory tests. However, the results were inconsistent and the analysis of epidemiological data stratified by the severity of COVID-19 was not available in previous meta-analyses. Furthermore, these meta-analyses were suspected of overestimating the incidence of liver injury in patients with COVID-19 because some studies considered transaminase elevation as liver injury, which might partially result from cardiac and muscle injury. This systematic review aims to enrol published literatures related to COVID-19 without language restriction, analyse the data based on the severity of the COVID-19 and explore the impact of varied definitions of liver injury on the incidence of liver injury.  We have conducted a preliminary search on PubMed and Excerpta Medica Database on 13 April 2020, for the studies published after December 2019 on the prevalence of acute liver injury and hypertransaminemia in patients with COVID-19. Two reviewers will independently screen studies, extract data and assess the risk of bias. We will estimate the pooled incidence of hypertransaminemia and acute liver injury in patients with COVID-19 by using the random-effects model. The I² test will be used to identify the extent of heterogeneity. Publication bias will be assessed by funnel plot and performing the Begg's and Egger's test if adequate studies are available. We will perform a risk of bias assessment using the Joanna Briggs Institute's critical appraisal checklist.  Since this study will be based on the published data, it does not require ethical approval. The final results of this study will be published in a peer-reviewed journal.

title: Retrospective analysis of cases of intraoperative awareness in a large multi-hospital health system reported in the early postoperative period.
abstract: Awareness with recall under general anesthesia remains a rare but important issue that warrants further study.  We present a series of seven cases of awareness that were identified from provider-reported adverse event data from the electronic anesthesia records of 647,000 general anesthetics.  The low number of identified cases suggests an under-reporting bias. Themes that emerge from this small series can serve as important reminders to anesthesia providers to ensure delivery of an adequate anesthetic for each patient. Commonalities between a majority of our identified anesthetic awareness cases include: obesity, use of total intravenous anesthesia, use of neuromuscular blockade, and either a lack of processed electroencephalogram (EEG) monitoring or documented high depth of consciousness index values. An interesting phenomenon was observed in one case, where adequately-dosed anesthesia was delivered without technical issue, processed EEG monitoring was employed, and the index value suggested an adequate depth of consciousness throughout the case.  Provider-reported adverse event data in the immediate post-operative period are likely insensitive for detecting cases of intraoperative awareness. Though causation cannot firmly be established from our data, themes identified in this series of cases of awareness with recall under general anesthesia provide important reminders for anesthesia providers to maintain vigilance in monitoring depth and dose of anesthesia, particularly with total intravenous anesthesia.

title: Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer
abstract: There is currently a lack of pathologic data on the novel coronavirus (severe acute respiratory syndrome coronavirus 2) pneumonia, or coronavirus disease 2019 (COVID-19), from autopsy or biopsy. Two patients who recently underwent lung lobectomies for adenocarcinoma were retrospectively found to have had COVID-19 at the time of the operation. These two cases thus provide important first opportunities to study the pathology of COVID-19. Pathologic examinations revealed that apart from the tumors, the lungs of both patients exhibited edema, proteinaceous exudate, focal reactive hyperplasia of pneumocytes with patchy inflammatory cellular infiltration, and multinucleated giant cells. Hyaline membranes were not prominent. Because both patients did not exhibit symptoms of pneumonia at the time of operation, these changes likely represent an early phase of the lung pathology of COVID-19 pneumonia.

title: Coronavirus Outbreak: Is Radiology Ready? Mass Casualty Incident Planning
abstract: On March 11, 2020, the World Health Organization declared a coronavirus disease 2019 (COVID-19) pandemic. Health care systems worldwide should be prepared for an unusually high volume of patients in the next few weeks to months. Even the most efficient radiology department will undergo tremendous stress when victims of a mass casualty flood the emergency department and in turn the radiology department. A significant increase is expected in the number of imaging studies ordered for the initial diagnosis and treatment follow-up of cases of COVID-19. Here, we highlight recommendations for developing and implementing a mass casualty incident (MCI) plan for a viral outbreak, such as the current COVID-19 infection. The MCI plan consists of several steps, including preparation, mobilization of resources, imaging chain, adjusting imaging protocols, and education, such as MCI plan simulation and in-service training. Having an MCI plan in place for a viral outbreak will protect patients and staff and ultimately decrease virus transmission. The use of simulations will help identify throughput and logistical issues.

title: [Covid-19 - radiologic and histologic features].
abstract: We here describe the current knowledge about the radiologic and histologic pulmonary features of covid-19, caused by SARS-CoV-2, and present lung histology from a case with fatal disease. Initial findings on computed tomography (CT) typically include peripheral multifocal bilateral ground-glass opacities, and correspondingly microscopic alveolar edema. This is followed by peripheral consolidations with air bronchogram and perilobular pattern on CT, signs of organizing pneumonia, corresponding to loose (potentially reversible) fibrosis. The posterior parts of the lungs and the lower lobes are typically more markedly affected. In severe disease with acute respiratory distress syndrome, thickened interlobular septa and crazy paving pattern appear on CT, which corresponds to histologic diffuse alveolar damage with, depending on the stage of the disease, features such as edema, hyaline membranes, reactive epithelium, inflammation, and fibrosis.

title: Testing for COVID-19: willful ignorance or selfless behavior?
abstract: Widespread testing is key to controlling the spread of COVID-19. But should we worry about self-selection bias in the testing? The recent literature on willful ignorance says we should – people often avoid health information. In the context of COVID-19, such willful ignorance can bias testing data. Furthermore, willful ignorance often arises when selfish wants conflict with social benefits, which might be particularly likely for potential ‘super-spreaders’ – people with many social interactions – given people who test positive are urged to self-isolate for two weeks. We design a survey in which participants (n = 897) choose whether to take a costless COVID-19 test. We find that 70% would take a test. Surprisingly, the people most likely to widely spread COVID-19 – the extraverts, others who meet more people in their daily lives and younger people – are the most willing to take a test. People's ability to financially or emotionally sustain self-isolation does not matter to their decision. We conclude that people are selfless in their decision to test for COVID-19. Our results are encouraging – they imply that COVOD-19 testing may succeed in targeting those who generate the largest social benefits from self-isolation if infected, which strengthens the case for widespread testing.

title: The effect of human mobility and control measures on the COVID-19 epidemic in China
abstract: The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.

title: Understanding the Anemic Global Response to COVID-19
abstract: The COVID-19 outbreak is the most serious test of the international system since the 2008 global financial crisis. Rather than cooperate to contain and respond to a common threat, the world's leading powers, the United States and China, increasingly blamed each other through wildly speculative theories about the origins of the virus. The World Health Organization (WHO) sought to coordinate a global response but it has been hamstrung and come under attack. Given past cooperation between major powers to mobilize and eradicate smallpox and previous U.S. leadership to fight HIV/AIDS and the 2014 West African Ebola crisis, the limited cooperation and lack of leadership are puzzling. What explains the anemic global response to date? This paper draws from structural international relations theory to suggest a partial but somewhat dissatisfying answer. International organizations are inherently weak faced with opposition by major powers. The international system simultaneously incentivizes states to cooperate and address common threats but at the same time encourages countries to take care of themselves, potentially at the expense of others. Which of these motives dominates cannot be explained by structural theory, requiring us to look to other factors such as the attributes of states or of leaders themselves.

title: The Appropriate Use of Testing for COVID-19
abstract: Many public officials are calling for increased testing for the 2019 novel coronavirus disease (COVID-19), and some governments have taken extraordinary measures to increase the availability of testing. However, little has been published about the sensitivity and specificity of the reverse transcriptase-polymerase chain reaction (RT-PCR) nasopharyngeal swabs that are commonly used for testing. This narrative review evaluates the literature regarding the accuracy of these tests, and makes recommendations based on this literature. In brief, a negative RT-PCR nasopharyngeal swab test is insufficient to rule out COVID-19. Thus, over-reliance on the results of the test may be dangerous, and the push for widespread testing may be overstated.

title: Phylogenetic perspectives on the epidemiology and origins of SARS and SARS-like coronaviruses
abstract: Syndrome (SARS) is a respiratory disease caused by a zoonotic coronavirus (CoV) named SARS-CoV (SCoV), which rapidly swept the globe after its emergence in rural China during late 2002. The origins of SCoV have been mysterious and controversial, until the recent discovery of SARS-like CoV (SLCoV) in bats and the proposal of bats as the natural reservior of the Coronaviridae family. In this article, we focused on discussing how phylogenetics contributed to our understanding towards the emergence and transmission of SCoV. We first reviewed the epidemiology of SCoV from a phylogenetic perspective and discussed the controversies over its phylogenetic origins. Then, we summarized the phylogenetic findings in relation to its zoonotic origins and the proposed inter-species viral transmission events. Finally, we also discussed how the discoveries of SCoV and SLCoV expanded our knowledge on the evolution of the Coronaviridae family as well as its implications on the possible future re-emergence of SCoV.

title: Severe underestimation of COVID-19 case numbers: effect of epidemic growth rate and test restrictions
abstract: To understand the scope and development of the COVID-19 pandemic, knowledge of the number of infected persons is essential. Often, the number of "confirmed cases", which is based on positive RT-PCR test results, is regarded as a reasonable indicator. However, limited COVID-19 test capacities in many countries are restricting the amount of testing that can be done. This can lead to the implementation of testing policies that restrict access to COVID-19 tests, and to testing backlogs and delays. As a result, confirmed case numbers can be significantly lower than the actual number of infections, especially during rapid growth phases of the epidemic. This study examines the quantitative relation between infections and reported confirmed case numbers for two different testing strategies, "limited" and "inclusive" testing, in relation to the growth rate of the epidemic. The results indicate that confirmed case numbers understate the actual number of infections substantially; during rapid growth phases where the daily growth rate can reach or exceed 30%, as has been seen in many countries, the confirmed case numbers under-report actual infections by up to 50 to 100-fold.

title: RSNA Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19: Interobserver Agreement Between Chest Radiologists
abstract: To assess the interobserver variability between chest radiologists in the interpretation of the Radiological Society of North America (RSNA) expert consensus statement reporting guidelines in patients with suspected coronavirus disease 2019 (COVID-19) pneumonia in a setting with limited reverse transcription polymerase chain reaction testing availability.  Chest computed tomography (CT) studies in 303 consecutive patients with suspected COVID-19 were reviewed by 3 fellowship-trained chest radiologists. Cases were assigned an impression of typical, indeterminate, atypical, or negative for COVID-19 pneumonia according to the RSNA expert consensus statement reporting guidelines, and interobserver analysis was performed.  CT features associated with COVID-19 pneumonia and distribution of findings were recorded.  The Fleiss kappa for all observers was almost perfect for typical (0.815), atypical (0.806), and negative (0.962) COVID-19 appearances (P < .0001) and substantial (0.636) for indeterminate COVID-19 appearance (P < .0001). Using Cramer V analysis, there were very strong correlations between all radiologists’ interpretations, statistically significant for all (typical, indeterminate, atypical, and negative) COVID-19 appearances (P < .001).  CT imaging findings were recorded in similar percentages of typical cases by all observers.  The RSNA expert consensus statement on reporting chest CT findings related to COVID-19 demonstrates substantial to almost perfect interobserver agreement among chest radiologists in a relatively large cohort of patients with clinically suspected COVID-19. It therefore serves as a reliable reference framework for radiologists to accurately communicate their level of suspicion based on the presence of evidence-based objective findings.

title: Ascertainment rate of novel coronavirus disease (COVID-19) in Japan
abstract: To estimate the ascertainment rate of novel coronavirus (COVID-19).  We analyzed the epidemiological dataset of confirmed cases with COVID-19 in Japan as of 28 February 2020. A statistical model was constructed to describe the heterogeneity of reporting rate by age and severity. We estimated the number of severe and non-severe cases, accounting for under-ascertainment.  The ascertainment rate of non-severe cases was estimated at 0.44 (95% confidence interval: 0.37, 0.50), indicating that unbiased number of non-cases would be more than twice the reported count.  Severe cases are twice more likely diagnosed and reported than other cases. Considering that reported cases are usually dominated by non-severe cases, the adjusted total number of cases is also about a double of observed count. Our finding is critical in interpreting the reported data, and it is advised to interpret mild case data of COVID-19 as always under-ascertained.

title: Characterizing COVID-19 case detection utilizing influenza surveillance data in the United States, January-March, 2020
abstract: COVID-19 reached the US in January, 2020, but state and local case detection efforts varied in timing and scale. We conducted a state-level ecological analysis of COVID-19 epidemiology alongside CDC influenza surveillance data and policy timelines. Our findings show wide variation in COVID-19 case detection and influenza-like-illness activity between states.

title: Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study
abstract: The coronavirus disease (COVID-19) pandemic is a global health emergency with over 6 million cases worldwide as of the beginning of June 2020. The pandemic is historic in scope and precedent given its emergence in an increasingly digital era. Importantly, there have been concerns about the accuracy of COVID-19 case counts due to issues such as lack of access to testing and difficulty in measuring recoveries.  The aims of this study were to detect and characterize user-generated conversations that could be associated with COVID-19-related symptoms, experiences with access to testing, and mentions of disease recovery using an unsupervised machine learning approach.  Tweets were collected from the Twitter public streaming application programming interface from March 3-20, 2020, filtered for general COVID-19-related keywords and then further filtered for terms that could be related to COVID-19 symptoms as self-reported by users. Tweets were analyzed using an unsupervised machine learning approach called the biterm topic model (BTM), where groups of tweets containing the same word-related themes were separated into topic clusters that included conversations about symptoms, testing, and recovery. Tweets in these clusters were then extracted and manually annotated for content analysis and assessed for their statistical and geographic characteristics.  A total of 4,492,954 tweets were collected that contained terms that could be related to COVID-19 symptoms. After using BTM to identify relevant topic clusters and removing duplicate tweets, we identified a total of 3465 (<1%) tweets that included user-generated conversations about experiences that users associated with possible COVID-19 symptoms and other disease experiences. These tweets were grouped into five main categories including first- and secondhand reports of symptoms, symptom reporting concurrent with lack of testing, discussion of recovery, confirmation of negative COVID-19 diagnosis after receiving testing, and users recalling symptoms and questioning whether they might have been previously infected with COVID-19. The co-occurrence of tweets for these themes was statistically significant for users reporting symptoms with a lack of testing and with a discussion of recovery. A total of 63% (n=1112) of the geotagged tweets were located in the United States.  This study used unsupervised machine learning for the purposes of characterizing self-reporting of symptoms, experiences with testing, and mentions of recovery related to COVID-19. Many users reported symptoms they thought were related to COVID-19, but they were not able to get tested to confirm their concerns. In the absence of testing availability and confirmation, accurate case estimations for this period of the outbreak may never be known. Future studies should continue to explore the utility of infoveillance approaches to estimate COVID-19 disease severity.

title: Spatial Analysis of Global Variability in Covid-19 Burden
abstract: Since the first occurrence of coronavirus disease 2019 (Covid-19), a number of online tools have become available to assist with tracking Covid-19 prevalence. Yet we are unaware of resources that provide country-specific Covid-19 incidence data.  We undertook a descriptive analysis of the global impact of Covid-19 using data reported on March 17, 2020. The prevalence of Covid-19 cases, fatalities attributed to Covid-19, and the case fatality rate for each of the 238 countries were accessed from the World Health Organization global Covid-19 tracking site, and we additionally calculated Covid-19 incidence based on country-specific population data. We determined the country-specific point prevalence and incidence of Covid-19 and associated deaths while using geocoded data to display their spatial distribution with geographic heat maps.  The analysis included 193,197 Covid-19 cases and 7859 associated deaths. The point prevalence was highest in China (80,881), Italy (31,506), Iran (16,169), and Spain (11,312); no other country reported more than 10,000 cases. The incidence (per million population) was highest in San Marino (3389) followed by Iceland (645) and Italy (521); no other country had an incidence above 400 per million population.  Countries with a high Covid-19 prevalence may not have a high incidence, and vice versa. Public health agencies that provide real-time infection tracking tools should report country-specific Covid-19 incidence metrics, in addition to prevalence data.

title: Reconciling early-outbreak estimates of the basic reproductive number and its uncertainty: framework and applications to the novel coronavirus (SARS-CoV-2) outbreak
abstract: A novel coronavirus (SARS-CoV-2) has recently emerged as a global threat. As the epidemic progresses, many disease modelers have focused on estimating the basic reproductive number Ro -- the average number of secondary cases caused by a primary case in an otherwise susceptible population. The modeling approaches and resulting estimates of Ro vary widely, despite relying on similar data sources. Here, we present a novel statistical framework for comparing and combining different estimates of Ro across a wide range of models by decomposing the basic reproductive number into three key quantities: the exponential growth rate $r$, the mean generation interval $\bar G$, and the generation-interval dispersion $\kappa$. We then apply our framework to early estimates of Ro for the SARS-CoV-2 outbreak. We show that many early Ro estimates are overly confident. Our results emphasize the importance of propagating uncertainties in all components of Ro, including the shape of the generation-interval distribution, in efforts to estimate Ro at the outset of an epidemic.

title: Analysis on the Clinical Characteristics of 36 Cases of Novel Coronavirus Pneumonia in Kunming
abstract: To analyze the clinical characteristics of patients with novel coronavirus pneumonia in Kunming City, and to study the correlation between nutritional status and immune function.  Clinical data of 36 patients with novel coronavirus pneumonia in isolation area of Kunming Third People's Hospital from January 31 to February 15, 2020 were collected, and the basic situation, clinical characteristics, laboratory examination and CT imaging characteristics were analyzed. Serum albumin (ALB), prealbumin (PAB), hypersensitive c-reactive protein (hs-crp), CD3T cells, CD4T cells, CD8T cells and normal control group were analyzed. A simple linear regression analysis of the relationship between proalbumin and T cell subpopulation counts in the blood of patients.  (1) The patients with new coronavirus pneumonia in Kunming were mainly of common type. (2) 50% of the patients' first symptoms were fever and cough; (3) The total number of white blood cells in peripheral blood was normal or decreased in 23 cases (79%), and the lymphocyte count decreased in 5 cases (13.89%), without anemia. Hypersensitive c-reactive protein increased in 19 (52.78%) cases, and procalcitonin increased in 1 case. Albumin decreased in 5 cases (13.89%), proalbumin decreased in 15 cases (41.67%), alanine transaminase increased slightly in 4 cases (11.11%), alanine transaminase increased slightly in 4 cases (11.11%), total bilirubin increased slightly in 11 cases (30.56%), and renal function and blood coagulation were normal. Absolute value of CD3+T cells is with a decrease in 21 cases (58.3%), CD4+T in 28 cases (77.8%), CD8+T in 17 cases (47.2%), and CD4+/ CD8+ inverse in 6 cases (16.7%). (4) The prealbumin, CD3 T cells, CD4 T cells and CD8 T cells in the new coronavirus pneumonia group were significantly lower than those in the normal control group, and the hypersensitive c-reactive protein was higher than that in the normal control group. (5) The levels of PAB in the serum of the patients were linearly correlated with hs-crp, CD3 T cells, CD4 T cells and CD8 T cells, and the correlation coefficients were -0.474, 0.558, 0.467 and 0.613, respectively, showing statistical differences.  The clinical characteristics of the novel coronavirus pneumonia in Kunming are different from those in Wuhan. The changes of serum proalbumin and T cell subsets are relatively obvious. Changes in serum proalbumin may contribute to the early warning of novel coronavirus pneumonia. The nutritional status of patients with common and mild pneumonia should be considered.

title: Assessing Differential Impacts of COVID-19 on Black Communities
abstract: Given incomplete data reporting by race, we used data on COVID-19 cases and deaths in US counties to describe racial disparities in COVID-19 disease and death and associated determinants.  Using publicly available data (accessed April 13, 2020), predictors of COVID-19 cases and deaths were compared between disproportionately (>13%) black and all other (<13% black) counties. Rate ratios were calculated and population attributable fractions (PAF) were estimated using COVID-19 cases and deaths via zero-inflated negative binomial regression model. National maps with county-level data and an interactive scatterplot of COVID-19 cases were generated.  Nearly ninety-seven percent of disproportionately black counties (656/677) reported a case and 49% (330/677) reported a death versus 81% (1987/2,465) and 28% (684/ 2465), respectively, for all other counties. Counties with higher proportions of black people have higher prevalence of comorbidities and greater air pollution. Counties with higher proportions of black residents had more COVID-19 diagnoses (RR 1.24, 95% CI 1.17-1.33) and deaths (RR 1.18, 95% CI 1.00-1.40), after adjusting for county-level characteristics such as age, poverty, comorbidities, and epidemic duration. COVID-19 deaths were higher in disproportionally black rural and small metro counties. The PAF of COVID-19 diagnosis due to lack of health insurance was 3.3% for counties with <13% black residents and 4.2% for counties with >13% black residents.  Nearly twenty-two percent of US counties are disproportionately black and they accounted for 52% of COVID-19 diagnoses and 58% of COVID-19 deaths nationally. County-level comparisons can both inform COVID-19 responses and identify epidemic hot spots. Social conditions, structural racism, and other factors elevate risk for COVID-19 diagnoses and deaths in black communities.

title: Estimating the risk of COVID-19 death during the course of the outbreak in Korea, February-March, 2020
abstract: In Korea, a total of 8,799 confirmed cases of COVID-19 including 102 deaths have been recorded as of Mar 21, 2020. The time-delay adjusted case fatality risk of COVID-19 in Korea is yet to be estimated.  We obtained the daily series of confirmed cases and deaths in Korea reported prior to March 21,2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in the city of Daegu, Gyeongsangbuk-do, other regions in Korea, as well as for the entire country.  Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do, partially due to the reporting delay. Our estimates of the risk for death in Gyeongsangbuk-do reached 2.4% (95% CrI: 1.6-3.4%), 1.3% (95% CrI: 1.0-1.6%) in Daegu and 0.7% (95% CrI: 0.3-1.4%) in other regions, whereas the national estimate of the risk for death was estimated at 1.4% (95% CrI: 1.2-1.7%) in Korea.  The relatively low CFRs are associated with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings in Korea. Geographic differences in CFR are likely influenced by clusters of nosocomial transmission.

title: Respiratory rehabilitation in elderly patients with COVID-19: A randomized controlled study
abstract: Different degrees of disorders are reported in respiratory function, physical function and psychological function in patients with corona virus disease 2019 (COVID-19), especially in elderly patients. With the experience of improved and discharged COVID-19 patients, timely respiratory rehabilitation intervention may improve prognosis, maximize functional preservation and improve quality of life (QoL), but there lacks of studies worldwide exploring the outcome of this intervention.  To investigate the effects of 6-week respiratory rehabilitation training on respiratory function, QoL, mobility and psychological function in elderly patients with COVID-19.  This paper reported the findings of an observational, prospective, quasi-experimental study, which totally recruited 72 participants, of which 36 patients underwent respiratory rehabilitation and the rest without any rehabilitation intervention. The following outcomes were measured: pulmonary function tests including plethysmography and diffusing lung capacity for carbon monoxide (DLCO), functional tests (6-min walk distance test), Quality of life (QoL) assessments (SF-36 scores), activities of daily living (Functional Independence Measure, FIM scores), and mental status tests (SAS anxiety and SDS depression scores).  After 6 weeks of respiratory rehabilitation in the intervention group, there disclosed significant differences in FEV1(L), FVC(L), FEV1/FVC%, DLCO% and 6-min walk test. The SF-36 scores, in 8 dimensions, were statistically significant within the intervention group and between the two groups. SAS and SDS scores in the intervention group decreased after the intervention, but only anxiety had significant statistical significance within and between the two groups.  Six-week respiratory rehabilitation can improve respiratory function, QoL and anxiety of elderly patients with COVID-19, but it has little significant improvement on depression in the elderly.

title: A novel IDEA: The impact of serial interval on a modified-Incidence Decay and Exponential Adjustment (m-IDEA) model for projections of daily COVID-19 cases
abstract: The SARS-CoV-2 virus causes the disease COVID-19, and has caused high morbidity and mortality worldwide. Empirical models are useful tools to predict future trends of disease progression such as COVID-19 over the near-term. A modified Incidence Decay and Exponential Adjustment (m-IDEA) model was developed to predict the progression of infectious disease outbreaks. The modification allows for the production of precise daily estimates, which are critical during a pandemic of this scale for planning purposes. The m-IDEA model was employed using a range of serial intervals given the lack of knowledge on the true serial interval of COVID-19. Both deterministic and stochastic approaches were applied. Model fitting was accomplished through minimizing the sum-of-square differences between predicted and observed daily incidence case counts, and performance was retrospectively assessed. The performance of the m-IDEA for projection cases in the near-term was improved using shorter serial intervals (1–4 days) at early stages of the pandemic, and longer serial intervals at mid-to late-stages (5–9 days) thus far. This, coupled with epidemiological reports, suggests that the serial interval of COVID-19 might increase as the pandemic progresses, which is rather intuitive: Increasing serial intervals can be attributed to gradual increases in public health interventions such as facility closures, public caution and social distancing, thus increasing the time between transmission events. In most cases, the stochastic approach captured the majority of future reported incidence data, because it accounts for the uncertainty around the serial interval of COVID-19. As such, it is the preferred approach for using the m-IDEA during dynamic situation such as in the midst of a major pandemic.

title: Liver injury in COVID-19: management and challenges

title: Treatment for emerging viruses: Convalescent plasma and COVID-19
abstract: Use of convalescent plasma transfusions could be of great value in the current pandemic of coronavirus disease (COVID-19), given the lack of specific preventative and therapeutic options. This convalescent plasma therapy is of particular interest when a vaccine or specific therapy is not yet available for emerging viruses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This report summarizes existing literature around convalescent plasma as a therapeutic option for COVID-19. It also includes recommendations for establishing a convalescent plasma program, enhancement considerations for convalescent plasma, and considerations around pathogen reduction treatment of convalescent plasma. Time is of the essence to set up protocols for collection, preparation, and administration of apheresis-collected convalescent plasma in response to the current pandemic. The immediate use of convalescent plasma provides prompt availability of a promising treatment while specific vaccines and treatments are evaluated and brought to scale. Further development of improved convalescent plasma, vaccines and other therapeutics depends on quick generation of additional data on pathogenesis and immune response. Additionally, given the lack of information around the natural history of this disease, PRT should be considered to add a layer of safety to protect recipients of convalescent plasma.

title: On-farm biosecurity practices and causes of preweaning mortality in Canadian commercial mink kits
abstract: Mink are an important animal commodity group in Canada and excessive kit mortality represents a significant loss to production. National biosecurity standards have been developed for Canadian mink farms, but it is unclear how well these standards have been implemented as there are no studies correlating management practices of mink producers with causes of death in mink kits. To that end, we surveyed Ontario mink producers on their biosecurity and management practices and conducted almost 5660 post mortem examinations on found-dead, preweaned kits to characterize mink farm biosecurity practices and causes of death in preweaned kits.  We found that very few biosecurity and management practices were uniformly used by producers, despite good awareness of appropriate practices. Use of personal protective equipment was implemented by fewer than 50% of respondents, while control of mink shed access, disinfection of feed containers after use, and use of a rodent control program were the only practices implemented by greater than 70% of respondents. Only 18% of producers reported regular use of antimicrobials in feed or water, although 91% stated they used antimicrobials for treatment of bacterial diseases on a regular basis. On post mortem examination, no gross abnormalities were noted in 71% of the kits, 45% were thought to be stillborn or aborted, 27% had some form of abnormal fluid distribution in the body, and 2% had a congenital malformation. A subset of 69 gastrointestinal tract samples was submitted for bacterial culture, of which 45 samples yielded sufficient growth. Most interesting was the identification of Salmonella enterica serovar Heidelberg in 11% of samples.  The results of this study will provide a benchmark for Canadian mink producers and their veterinarians, defining the areas to which greater attention should be given to ensure more rigorous biosecurity practices are in place. Ultimately, these improvements in practices may contribute to increased mink production and animal well-being.  contains supplementary material, which is available to authorized users.

title: Isolation and Characterization of a Novel Bat Coronavirus Closely Related to the Direct Progenitor of Severe Acute Respiratory Syndrome Coronavirus.
abstract: We report the isolation and characterization of a novel bat coronavirus which is much closer to the severe acute respiratory syndrome coronavirus (SARS-CoV) in genomic sequence than others previously reported, particularly in its S gene. Cell entry and susceptibility studies indicated that this virus can use ACE2 as a receptor and infect animal and human cell lines. Our results provide further evidence of the bat origin of the SARS-CoV and highlight the likelihood of future bat coronavirus emergence in humans.

title: Working Together to Meet the Needs of Patients with Inflammatory Bowel Diseases

title: Complementing conventional infectious disease surveillance with national health insurance claims data in the Republic of Korea
abstract: Surveillance remains an important tool for timely outbreak detection and response. Many countries, including Korea, have established national infectious disease surveillance systems with clinical notification. We aimed to evaluate the National Health Insurance Claims-based Surveillance (NHICS) compared to conventional passive report-based National Infectious Diseases Surveillance (NIDS). Reported to claimed cases ratios (R/C ratio) were evaluated from monthly notifiable disease cases captured by NIDS and NHICS. The relationships between 26 infectious diseases and each surveillance system were analysed using Pearson’s correlation analysis and linear regression. There was an overall increase in R/C ratio from 2010–2017 (0.37 to 0.78). In 22 infectious diseases, there was a correlation between NIDS and NHICS. Moreover, claim-based surveillance showed less fluctuating disease incidence rates than report-based surveillance for specific infectious diseases, such as varicella, mumps, and scarlet fever. However, for infectious diseases with episodic outbreaks or low incidence, it was difficult to assess NHICS usefulness. Claim-based surveillance is less affected by limitations of conventional report-based surveillance systems, such as reporting rate. Given delays in claim systems, a claim-based surveillance is expected to be complementary to conventional systems for the detection of various infectious diseases with the advancement of bio-information technology.

title: Prognostication and Proactive Planning in COVID-19
abstract: Accurate prognostication is challenging in the setting of SARS-CoV-2, the virus responsible for COVID-19, due to rapidly changing data, studies that are not generalizable and lack of morbidity and functional outcomes in survivors. To provide meaningful guidance to patients, existing mortality data must be considered and appropriately applied. While most people infected with SARS-CoV-2 will recover, mortality increases with age and co-morbidity in those who develop severe illness.

title: Prevalence, Severity and Mortality associated with COPD and Smoking in patients with COVID-19: A Rapid Systematic Review and Meta-Analysis
abstract: Coronavirus disease 2019 (COVID-19) is an evolving infectious disease that dramatically spread all over the world in the early part of 2020. No studies have yet summarised the potential severity and mortality risks caused by COVID-19 in patients with chronic obstructive pulmonary disease (COPD), and we update information in smokers.  We systematically searched electronic databases from inception to March 24, 2020. Data were extracted by two independent authors in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Study quality was assessed using a modified version of the Newcastle Ottawa Scale. We synthesised a narrative from eligible studies and conducted a meta-analysis using a random-effects model to calculate pooled prevalence rates and 95% confidence intervals (95%CI).  In total, 123 abstracts were screened and 61 full-text manuscripts were reviewed. A total of 15 studies met the inclusion criteria, which included a total of 2473 confirmed COVID-19 patients. All studies were included in the meta-analysis. The crude case fatality rate of COVID-19 was 6.4%. The pooled prevalence rates of COPD patients and smokers in COVID-19 cases were 2% (95% CI, 1%-3%) and 9% (95% CI, 4%-14%) respectively. COPD patients were at a higher risk of more severe disease (risk of severity = 63%, (22/35) compared to patients without COPD 33.4% (409/1224) [calculated RR, 1.88 (95% CI, 1.4-2.4)]. This was associated with higher mortality (60%). Our results showed that 22% (31/139) of current smokers and 46% (13/28) of ex-smokers had severe complications. The calculated RR showed that current smokers were 1.45 times more likely [95% CI: 1.03-2.04] to have severe complications compared to former and never smokers. Current smokers also had a higher mortality rate of 38.5%.  Although COPD prevalence in COVID-19 cases was low in current reports, COVID-19 infection was associated with substantial severity and mortality rates in COPD. Compared to former and never smokers, current smokers were at greater risk of severe complications and higher mortality rate. Effective preventive measures are required to reduce COVID-19 risk in COPD patients and current smokers.

title: The impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak - evidence from China
abstract: To investigate the impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak.  provincial-level regions in mainland China.  Data on COVID-19 incidence and climate between Jan 20 and Feb 29, 2020.  The number of new confirm COVID-19 cases in mainland China peaked on Feb 1, 2020. COVID-19 daily incidence were lowest at -10 and highest at 10 ,while the maximum incidence was observed at the absolute humidity of approximately 7 g/m3. COVID-19 incidence changed with temperature as daily incidence decreased when the temperature rose. No significant association between COVID-19 incidence and absolute humidity was observed in distributed lag nonlinear models. Additionally, A modified susceptible-exposed-infectious-recovered (M-SEIR) model confirmed that transmission rate decreased with the increase of temperature, leading to further decrease of infection rate and outbreak scale.  Temperature is an environmental driver of the COVID-19 outbreak in China. Lower and higher temperatures might be positive to decrease the COVID-19 incidence. M-SEIR models help to better evaluate environmental and social impacts on COVID-19.

title: Deaths from Covid-19: Who are the forgotten victims?
abstract: With the spreading global pandemic of coronavirus disease 2019 (Covid-19) there has been disruption to normal clinical activity in response to the increased demand on health services. There are reports of a reduction in non-Covid-19 emergency presentations. Consequentially, there are concerns that deaths from non-Covid-19 causes could increase. We examined recent reported population-based mortality rates, compared with expected rates, and compared any excess in deaths with the number of deaths attributed to Covid-19.  National agency and death registration reports were searched for numbers of deaths attributed to Covid-19 and overall mortality that had been publicly reported by 16 April 2020. Data on the number of deaths attributed to Covid-19, the total number of deaths registered in the population and the historical average over at least 3 years were collected. Data were available for 3 Northern European countries (England & Wales, Scotland and the Netherlands) and New York State, United States of America.  There was an increase in observed, compared with expected, mortality in Scotland (+27%), England and Wales (+35%), the Netherlands (+60%) and New York state (+26%). Of these deaths, only 43% in Scotland and England and Wales, 49% in the Netherlands and 30% in New York state were attributed to Covid-19 leaving a number of excess deaths not attributed to Covid-19.  A substantial proportion of excess deaths observed during the current COVID-19 pandemic are not attributed to COVID-19 and may represent an excess of deaths due to other causes.

title: Abstracts of FIS/HIS 2016 – Poster Presentations

title: Early impact of COVID-19 on transplant center practices and policies in the United States
abstract: COVID-19 is a novel, rapidly changing pandemic: consequently, evidence-based recommendations in solid organ transplantation (SOT) remain challenging and unclear. To understand the impact on transplant activity across the United States, and center-level variation in testing, clinical practice, and policies, we conducted a national survey between March 24, 2020 and March 31, 2020 and linked responses to the COVID-19 incidence map. Response rate was a very high 79.3%, reflecting a strong national priority to better understand COVID-19. Complete suspension of live donor kidney transplantation was reported by 71.8% and live donor liver by 67.7%. While complete suspension of deceased donor transplantation was less frequent, some restrictions to deceased donor kidney transplantation were reported by 84.0% and deceased donor liver by 73.3%; more stringent restrictions were associated with higher regional incidence of COVID-19. Shortage of COVID-19 tests was reported by 42.5%. Respondents reported a total of 148 COVID-19 recipients from <1 to >10 years posttransplant: 69.6% were kidney recipients, and 25.0% were critically ill. Hydroxychloroquine (HCQ) was used by 78.1% of respondents; azithromycin by 46.9%; tocilizumab by 31.3%, and remdesivir by 25.0%. There is wide heterogeneity in center-level response across the United States; ongoing national data collection, expert discussion, and clinical studies are critical to informing evidence-based practices.

title: Intensive COVID-19 testing associated with reduced mortality - an ecological analysis of 108 countries
abstract: Intensive screening and testing for COVID-19 could facilitate early detection and isolation of infected persons and thereby control the size of the epidemic. It could also facilitate earlier and more targeted therapy. These factors could plausibly reduce attributable mortality which was the hypothesis tested in this study.  Linear regression was used to assess the country-level association between COVID-19 attributable mortality per 100 000 inhabitants (mortality/capita) and COVID-19 tests/capita (number of tests/100 000 inhabitants) controlling for the cumulative number of COVID-19 infections/100 000 inhabitants (cases/capita), the age of the epidemic (number of days between first case reported and 8 April), national health expenditure per capita and WHO world region.  The COVID-19 mortality rate varied between 0.3 and 3110 deaths/100 000 inhabitants (median 30, IQR 8-105). The intensity of testing per 100 000 also varied considerably (median 21,970, IQR 2,735-89,095) as did the number of COVID-19 cases per 100 000 (median 1,600, IQR 340-4,760 cases/100 000). In the multivariate model, the COVID-19 mortality rate was negatively associated with tests/capita (Coef. -0.036, 95% CI -0.047- -0.025) and positively associated with cases/capita (Coef. 0.093, 95% CI 0.819- 1.034).  The results are compatible with the hypothesis that intensive testing and isolation could play a role in reducing COVID-10 mortality rates.

title: Prediction of number of cases expected and estimation of the final size of coronavirus epidemic in India using the logistic model and genetic algorithm
abstract: In this paper, we have applied the logistic growth regression model and genetic algorithm to predict the number of coronavirus infected cases that can be expected in upcoming days in India and also estimated the final size and its peak time of the coronavirus epidemic in India.

title: ELM—the database of eukaryotic linear motifs
abstract: Linear motifs are short, evolutionarily plastic components of regulatory proteins and provide low-affinity interaction interfaces. These compact modules play central roles in mediating every aspect of the regulatory functionality of the cell. They are particularly prominent in mediating cell signaling, controlling protein turnover and directing protein localization. Given their importance, our understanding of motifs is surprisingly limited, largely as a result of the difficulty of discovery, both experimentally and computationally. The Eukaryotic Linear Motif (ELM) resource at http://elm.eu.org provides the biological community with a comprehensive database of known experimentally validated motifs, and an exploratory tool to discover putative linear motifs in user-submitted protein sequences. The current update of the ELM database comprises 1800 annotated motif instances representing 170 distinct functional classes, including approximately 500 novel instances and 24 novel classes. Several older motif class entries have been also revisited, improving annotation and adding novel instances. Furthermore, addition of full-text search capabilities, an enhanced interface and simplified batch download has improved the overall accessibility of the ELM data. The motif discovery portion of the ELM resource has added conservation, and structural attributes have been incorporated to aid users to discriminate biologically relevant motifs from stochastically occurring non-functional instances.

title: The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
abstract: Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.

title: Clinical and Transmission Dynamics Characteristics of 406 Children with Coronavirus Disease 2019 in China: A Review
abstract: Chinese pediatricians are working on the front line to fight COVID-19. They have published a great amount of first-hand clinical data. Collecting their data and forming a large sample for analysis is more conducive to the recognition, prevention and treatment of coronavirus disease 2019 in children. The epidemic prevention and control experience of Chinese pediatricians should be shared with the world.  By searching Chinese and English literature, the data of 406 children with COVID-19 in China were analyzed.  It was found that the clustered incidence of children's families is a dynamic transmission feature; the incidence is low; asymptomatic infections and mild cases account for 44.8%, with only 7 cases of critical illness; laboratory examination of lymphocyte counts is not reduced, as it is for adults; chest CT findings are less severe than those for adults. These presentations are the clinical features of COVID-19 in children. Only 55 of the 406 cases were tested by anal swab for virus nucleic acid, 45 of which were positive, accounting for 81.8% of stool samples.  There are more children than adults with asymptomatic infections, milder conditions, faster recovery, and a better prognosis. Some concealed morbidity characteristics also bring difficulties to the early identification, prevention and control of COVID-19. COVID-19 screening is needed in the pediatric fever clinic, and respiratory and digestive tract nucleic acid tests should be performed. Efforts should be made to prevent children from becoming a hidden source of transmission in kindergartens, schools or families. Furthermore, China's experience in treating COVID-19 in children has led to faster recovery of sick children.

title: A proposal for the return to routine endoscopy during the COVID-19 pandemic
abstract: In response to the COVID-19 pandemic, many jurisdictions and gastroenterological societies around the world have suspended nonurgent endoscopy. Subject to country-specific variability, it is projected that with current mitigation measures in place, the peak incidence of active COVID-19 infections may be delayed by over 6 months. Although this aims to prevent the overburdening of healthcare systems, prolonged deferral of elective endoscopy will become unsustainable. Herein, we propose that by incorporating readily available point-of-care tests and conducting accurate clinical risk assessments, a safe and timely return to elective endoscopy is feasible. Our algorithm not only focuses on the safety of patients and healthcare workers, but also assists in rationalizing the use of invaluable resources such as personal protective equipment.

title: A Spatio‐Temporal Analysis of the Environmental Correlates of COVID‐19 Incidence in Spain
abstract: The novel SARS‐CoV2 has disrupted health systems and the economy, and public health interventions to slow its spread have been costly. How and when to ease restrictions to movement hinges in part on whether SARS‐CoV2 will display seasonality due to variations in temperature, humidity, and hours of sunshine. Here, we address this question by means of a spatio‐temporal analysis in Spain of the incidence of COVID‐19, the disease caused by the virus. Use of spatial Seemingly Unrelated Regressions (SUR) allows us to model the incidence of reported cases of the disease per 100,000 population as an interregional contagion process, in addition to a function of temperature, humidity, and sunshine. In the analysis we also control for GDP per capita, percentage of older adults in the population, population density, and presence of mass transit systems. The results support the hypothesis that incidence of the disease is lower at higher temperatures and higher levels of humidity. Sunshine, in contrast, displays a positive association with incidence of the disease. Our control variables also yield interesting insights. Higher incidence is associated with higher GDP per capita and presence of mass transit systems in the province; in contrast, population density and percentage of older adults display negative associations with incidence of COVID‐19.

title: Asymptomatic carrier state, acute respiratory disease, and pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): Facts and myths
abstract: Since the emergence of coronavirus disease 2019 (COVID-19) (formerly known as the 2019 novel coronavirus [2019-nCoV]) in Wuhan, China in December 2019, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), more than 75,000 cases have been reported in 32 countries/regions, resulting in more than 2000 deaths worldwide. Despite the fact that most COVID-19 cases and mortalities were reported in China, the WHO has declared this outbreak as the sixth public health emergency of international concern. The COVID-19 can present as an asymptomatic carrier state, acute respiratory disease, and pneumonia. Adults represent the population with the highest infection rate; however, neonates, children, and elderly patients can also be infected by SARS-CoV-2. In addition, nosocomial infection of hospitalized patients and healthcare workers, and viral transmission from asymptomatic carriers are possible. The most common finding on chest imaging among patients with pneumonia was ground-glass opacity with bilateral involvement. Severe cases are more likely to be older patients with underlying comorbidities compared to mild cases. Indeed, age and disease severity may be correlated with the outcomes of COVID-19. To date, effective treatment is lacking; however, clinical trials investigating the efficacy of several agents, including remdesivir and chloroquine, are underway in China. Currently, effective infection control intervention is the only way to prevent the spread of SARS-CoV-2.

title: Effectiveness and safety of antiviral or antibody treatments for coronavirus: A rapid review
abstract: To identify safe and effective medical countermeasures (e.g., antivirals/antibodies) to address the current outbreak of a novel coronavirus (COVID-19)  Comprehensive literature searches were developed by an experienced librarian for MEDLINE, EMBASE, the Cochrane Library, and biorxiv.org/medrxiv.org; additional searches for ongoing trials and unpublished studies were conducted in clinicaltrials.gov and the Global Infectious Diseases and Epidemiology Network (GIDEON). Title/abstract and full-text screening, data abstraction, and risk of bias appraisal were carried out by single reviewers.  54 studies were included in the review: three controlled trials, 10 cohort studies, seven retrospective medical record/database studies, and 34 case reports or series. These studies included patients with severe acute respiratory syndrome (SARs, n=33), middle east respiratory syndrome (MERS, n=16), COVID-19 (n=3), and unspecified coronavirus (n=2). The most common treatment was ribavirin (n=41), followed by oseltamivir (n=10) and the combination of lopinavir/ritonavir (n=7). Additional therapies included broad spectrum antibiotics (n=30), steroids (n=39) or various interferons (n=12). No eligible studies examining monoclonal antibodies for COVID-19 were identified. One trial found that ribavirin prophylactic treatment statistically significantly reduced risk of MERS infection in people who had been exposed to the virus. Of the 21 studies reporting rates of ICU admission in hospitalized SARS or MERS patients, none reported statistically significant results in favour of or against antiviral therapies. Of the 40 studies reporting mortality rates in hospitalized SARS or MERS patients, one cohort study (MERS) and one retrospective study (SARS) found a statistically significant increase in the mortality rate for patients treated with ribavirin. Eighteen studies reported potential drug-related adverse effects including gastrointestinal symptoms, anemia, and altered liver function in patients receiving ribavirin.  The current evidence for the effectiveness and safety of antiviral therapies for coronavirus is inconclusive and suffers from a lack of well-designed prospective trials or observational studies, preventing any treatment recommendations from being made. However, it is clear that the existing body of evidence is weighted heavily towards ribavirin (41/54 studies), which has not shown conclusive evidence of effectiveness and may cause harmful adverse events so future investigations may consider focusing on other candidates for antiviral therapy.

title: Meta-analysis of outcomes of patients with COVID-19 infection with versus without gastrointestinal symptoms
abstract: This systematic review analyzed whether the presence or absence of gastrointestinal symptoms in patients with SARS-COV-2 infection is associated with adverse outcomes. Searching the Cochrane Center Register of Controlled Trials, we included any studies looking at patients with COVID-19 with gastrointestinal symptoms (nausea, vomiting, diarrhea, abdominal pain) compared to those with COVID-19 but without gastrointestinal manifestations as a control group. The final search yielded 186 articles, all of which were individually screened. Seven studies were identified but three were excluded: one due to lack of a control group without gastrointestinal symptoms, one reported as viral RNA in the stool, and one with only non-critically ill patients. Results of the meta-analysis showed a pooled odds ratio for mortality among those with COVID-19 and gastrointestinal symptoms of 0.91 (confidence interval 0.49–1.68) with heterogeneity of 0% and a pooled odds ratio for acute respiratory distress syndrome of 2.94 (confidence interval 1.17–7.40) with heterogeneity of 0%. In conclusion, gastrointestinal symptoms with COVID-19 are associated with a higher risk of acute respiratory distress syndrome, but do not increase the risk for mortality.

title: Estimating the Fraction of Unreported Infections in Epidemics with a Known Epicenter: an Application to COVID-19
abstract: We develop a simple analytical method to estimate the fraction of unreported infections in epidemics with a known epicenter and estimate the number of unreported COVID-19 infections in the US during the first half of March 2020. Our method utilizes the covariation in initial reported infections across US regions and the number of travelers to these regions from the epicenter, along with the results of a randomized testing study in Iceland. We estimate that 4%-14% (1.5%-10%) of actual infections had been reported in US up to March 16, accounting for an assumed reporting lag of 8 (5) days.

title: Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
abstract: We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.

title: Incidence of venous thromboembolism in hospitalized patients with COVID-19.
abstract: Coronavirus disease 2019 (COVID-19) can lead to systemic coagulation activation and thrombotic complications. We investigated the incidence of objectively confirmed venous thromboembolism (VTE) in 198 hospitalized patients with COVID-19 in a single-center cohort study. Seventy-five patients (38%) were admitted to the intensive care unit (ICU). At time of data collection, 16 (8%) were still hospitalized and 19% had died. During a median follow-up of 7 days (IQR, 3-13), 39 patients (20%) were diagnosed with VTE of whom 25 (13%) had symptomatic VTE, despite routine thrombosis prophylaxis. The cumulative incidences of VTE at 7, 14 and 21 days were 16% (95% CI, 10-22), 33% (95% CI, 23-43) and 42% (95% CI 30-54) respectively. For symptomatic VTE, these were 10% (95% CI, 5.8-16), 21% (95% CI, 14-30) and 25% (95% CI 16-36). VTE appeared to be associated with death (adjusted HR, 2.4; 95% CI, 1.02-5.5). The cumulative incidence of VTE was higher in the ICU (26% (95% CI, 17-37), 47% (95% CI, 34-58), and 59% (95% CI, 42-72) at 7, 14 and 21 days) than on the wards (any VTE and symptomatic VTE 5.8% (95% CI, 1.4-15), 9.2% (95% CI, 2.6-21), and 9.2% (2.6-21) at 7, 14, and 21 days). The observed risk for VTE in COVID-19 is high, particularly in ICU patients, which should lead to a high level of clinical suspicion and low threshold for diagnostic imaging for DVT or PE. Future research should focus on optimal diagnostic and prophylactic strategies to prevent VTE and potentially improve survival.

title: Global profiling of SARS-CoV-2 specific IgG/ IgM responses of convalescents using a proteome microarray
abstract: COVID-19 is caused by SARS-CoV-2, and has become a global pandemic. There is no highly effective medicine or vaccine, most of the patients were recovered by their own immune response, especially the virus specific IgG and IgM responses. However, the IgG/ IgM responses is barely known. To enable the global understanding of SARS-CoV-2 specific IgG/ IgM responses, a SARS-CoV-2 proteome microarray with 18 out of the 28 predicted proteins was constructed. The microarray was applied to profile the IgG/ IgM responses with 29 convalescent sera. The results suggest that at the convalescent phase 100% of patients had IgG/ IgM responses to SARS-CoV-2, especially to protein N, S1 but not S2. S1 purified from mammalian cell demonstrated the highest performance to differentiate COVID-19 patients from controls. Besides protein N and S1, significant antibody responses to ORF9b and NSP5 were also identified. In-depth analysis showed that the level of S1 IgG positively correlate to age and the level of LDH (lactate dehydrogenase), especially for women, while the level of S1 IgG negatively correlate to Ly% (Lymphocyte percentage). This study presents the first whole picture of the SARS-CoV-2 specific IgG/ IgM responses, and provides insights to develop precise immuno-diagnostics, effective treatment and vaccine.

title: Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak
abstract: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city of China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.  Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.  The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.  The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.

title: Limiting spread of COVID-19 from cruise ships - lessons to be learnt from Japan ;QJM: An International Journal of Medicine ;Oxford Academic
abstract: Spread of COVID-19 infection on a Cruise Ship in Yokohama, Japan Japan's response to the novel coronavirus (COVID-19) infection has been problematic since the outbreak was first reported in China A typical example was the case of a cruise ship “Diamond Princess,” anchored in Yokohama, Japan As of March, 6, the WHO officially reported that there were 17,481 laboratory-confirmed cases of Covid-19 infection globally outside China In Japan, there were 1,045 such cases, but there were 696 laboratory-confirmed cases on the Diamond Princess 1 The Japanese government have quarantined the ship’s 3,711 passengers and crew members since February 5, 2020 until February 19, under the Japan’s Quarantine Act enacted in 1951, effectively prohibiting the disembarkation of anyone onto Japanese soil We have three primary concerns about this quarantine action First, the quarantine in the cruise ship may not be effective enough to prevent the contagion of the virus in Japan Although the disease has a relatively low case fatality rate (currently 0 3% in China), each COVID-19 infected individual is reported to infect 2 2 people, similarly to the influenza virus, a basic reproductive number of which is 1 4-4 0 2 Given the fact that Japan has received hundreds of thousands of Chinese tourists since the start of the outbreak in earlyDecember, several of whom may have been from the Wuhan region, it is obvious that COVID-19 is already in Japan, as evidenced by the 13 locally-transmitted individuals, including a taxi driver and bus driver who had transported Chinese tourists at the time when the quarantine was initiated Second, quarantine in the cruise ship could accelerate a contagion of the virus in the ship since it has been reported that cruise ships can become incubators of the viruses because a large number of people are packed in the semi-enclosed space, with limited sanitation as we as restricted water and food supply 3 Indeed, the infection on the cruise ship appears not to have been well-controlled, and the number of infected people has been steadily rising, with 137 new confirmed cases on February 16, according to WHO’s daily update Third, care for the passengers and crew members has been poor The majority of the passenger of the ship are the elderly, with more than 200 people over the age of 80 As Japan has learned from past emergencies, the elderly, especially those with existing with comorbidities, are at grave risk not just from the emerging Covid-19 infection, but from the physical and psychological stress that may make their existing ailments worse, actually jeopardizing their health and well being With increased international criticism of the poor management of the those on board, the Japanese government allowed some elderly passengers to leave the ship on February 14, rather than wait until the quarantine ends on February 19 As of February 23, 36 severe cases of the COVID-19 have been reported among the passengers, requiring treatment in land-based intensive care units After this quarantine on the cruise ship, hundreds of others on board had been repatriated to their home countries, where they will start another 14 days of quarantine There is growing global concern about how illegal immigrants and individuals such as the potentially infected on the “Diamond Princess,” are being treated We believe that the response of the authorities to the cruise ship dilemma has not been patient-oriented with respect to those on board While it is important to respect the concept of quarantining people who could pose a significant danger to the nation’s entire population, which is the government’s overriding responsibility, alternative solutions may be possible The reported development of a 15-minute https://mc manuscriptcentral com/qjm Downloaded from https://academic oup com/qjmed/advance-article-abstract/doi/10 1093/qjmed/hcaa092/5805396 by Kobbe University Library user on 16 March 2020 blood-based Covid-1- test kit by Chinese scientists may help in future, if it is accurate and does not produce repeated false-negatives as the existing test does Similarly, creation of a purposebuilt mass quarantine facility somewhere in Japan would be useful We hope learned from this experience in Japan would be help improve the situation on a cruise ship “Grand Princess” off the coast of California, where 21 Covid-19 cases were confirmed on March 5

title: The impact of the undetected COVID-19 cases on its transmission dynamics
abstract: The COVID-19 pandemic is currently ongoing. Presently, due to the unavailability of a definitive vaccine to decrease its acquiring, it is essential to understand its transmissibility in the community by undetected cases to control its transmission. This study aims to study this context using mathematical modelling.  A COVID-19 transmission model was framed that estimated the basic reproduction number (R_0, a measurement of disease risk) using the next-generation method. It explored the contribution of exposed and infected (detected and undetected) individuals, and environmental pathogen to the overall risk of infection spreading, utilizing the publicly reported data of this infection in Maharashtra between March 22, 2020, and May 4, 2020. A sensitivity analysis was performed to study the effect of a rising number of undetected cases to R_0.  The estimated basic reproduction number is R_0=4.63, which increases rapidly with the rise in the undetected COVID-19 cases. Although the exposed individuals made the largest contribution to infection transmission (R_1=2.42), the contaminated environment also played a significant role.  It is crucial to identify the individuals exposed and infected to COVID-19 disease and isolate them to control its transmission. The awareness of the role of fomites in infection transmission is also important in this regard.

title: The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China.
abstract: Australia implemented a travel ban on China on February 1st 2020. Partial lifting of the ban is being considered, given the decline in incidence of COVID-19 in China. We modelled three scenarios to test the impact of travel bans on epidemic control in Australia. Scenario one was no ban, scenario two was the current ban, scenario three was a partial lifting of the current ban to allow over 100,000 university students to enter Australia, but not tourists. We used disease incidence data from China and air travel passenger movements between China and Australia, derived from incoming passenger arrival cards. We estimated the true incidence of disease in China using data on expected proportion of under-ascertainment of cases. We used an age specific deterministic model divided in 18 age stratified groups to model the epidemic in each scenario. The modelled epidemic with the full ban fitted the observed incidence of cases well. The modelled epidemic of the current ban predicts 57 cases on March 6th in Australia, compared to 66 observed on this date. The modelled impact without a travel ban implemented on February the 1st shows the epidemic would continue for more than a year resulting in more than 2000 cases and about 400 deaths. The impact of a partial lifting of a ban is minimal, and may be safe to consider. Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia and averted a much larger epidemic. The epidemic is still containable if other measures are used in tandem as cases surge in other countries. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.

title: Significance of norovirus in occupational health: a review of published norovirus outbreaks in Central and Northern Europe
abstract: Globally, norovirus (NoV) is the leading cause of gastroenteritis infection among all ages. The development of prevention strategies in the field of occupational health requires a detailed knowledge about the impact of the disease on employees. This review article aims not only at evaluating the burden of NoV outbreaks on staff but also at discussing implications for future prevention strategies.  Published NoV outbreaks in Central and Northern Europe were identified via a systematic literature search. Additionally, published NoV outbreaks in Germany were detected via a manual literature search. Key epidemiological data, as the number of symptomatic staff, was then extracted. The proportion of affected employees was calculated for each dataset (single NoV outbreaks or aggregated data of multiple outbreaks).  Overall, 116 datasets were extracted from 72 relevant articles. 144,852 persons were affected by NoV gastroenteritis, 25,408 out of them (17.5%) were employees. 23,874 (94.0%) of them fell sick during outbreaks in hospitals and related settings. NoV cases among personnel in food establishments were reported only sporadically (mean ratio: 0.01).  Employees in hospitals and community facilities seem quantitatively to be most vulnerable towards NoV epidemics. Therefore, high quality of prevention measures in these settings, respective compliance with prevention strategies should have the highest priority. The disease can be considered as an occupational disease, even regularly without long-term consequences. Following work safety rules, a vaccination for vulnerable groups should be recommended if the vaccine development turns out to be successful.  The online version of this article (10.1007/s00420-020-01543-4) contains supplementary material, which is available to authorized users.

title: COVID-19, Australia: Epidemiology Report 19 (Fortnightly reporting period ending 21 June 2020).
abstract: Notified cases of COVID-19 and associated deaths reported to the National Notifiable Diseases Surveillance System (NNDSS) to 21 June 2020. Confirmed cases in Australia notified up to 7 June 2020: notifications = 7,491; deaths = 102. The incidence of COVID-19 has markedly reduced since a peak in mid-March. A combination of early case identification, physical distancing, public health measures and a reduction in international travel have been effective in slowing the spread of disease in Australia. Of the 215 cases notified between 8 and 21 June, 75% (163 cases) were notified from Victoria. Most of these cases were acquired locally. In contrast, cases notified from other states (NSW, Qld and WA) over this period were mostly overseas-acquired. Of locally-acquired cases in Victoria in this period, 51% were associated with contacts of a confirmed case or in a known outbreak, while 49% were unable to be linked to another case or were under investigation at the time of reporting. There are several clusters across a range of settings, including extended families, hotel quarantine facilities and a retail store, with most cases limited in geographic spread to a number of Local Government Areas around Melbourne. In response, the Victorian Government has re-introduced restrictions for household and outdoor gatherings, has delayed plans to ease other restrictions and has implemented enhanced public health response activities, particularly with regard to testing and contact tracing. A small proportion of overall cases have experienced severe disease, requiring hospitalisation or intensive care, with some fatalities. The crude case fatality rate amongst Australian cases is 1.4%. People who are older and have one or more comorbidities are more likely to experience severe disease. The highest rate of COVID-19 continues to be among people aged 65-79 years. Three-quarters of all cases in this age group have been associated with overseas travel, including several outbreaks linked to cruise ships. The lowest rate of disease is in children under 18 years, a pattern reflected in international reports. Internationally, as of 21 June 2020, the largest numbers of both cases and deaths have been reported in the United States. Of the confirmed cases reported globally, the case fatality rate is approximately 5.3%. Other countries in the Americas region, such as Brazil and Chile, are seeing rapid growth in case numbers. Case numbers in Europe remain relatively steady, while there is significant growth in the South East Asia region, including in India and Bangladesh. Reported cases are increasing in Africa, although the numbers are much smaller. In the Pacific region there are few new cases reported daily.

title: Teicoplanin potently blocks the cell entry of 2019-nCoV
abstract: Since December 2019, the outbreak of a new coronavirus, named 2019-nCoV, has greatly threatened the public health in China and raised great concerns worldwide. No specific treatment for this infection is currently available. We previously reported that teicoplanin, a glycopeptide antibiotic which has routinely been used in the clinic to treat bacterial infection with low toxicity, significantly inhibits the invasion of cells by Ebola virus, SARS-CoV and MERS-CoV, via specifically inhibiting the activity of cathepsin L. Here, we tested the efficacy of teicoplanin against 2019-nCoV virus infection and found that teicoplanin potently prevents the entrance of 2019-nCoV-Spike-pseudoviruses into the cytoplasm, with an IC50 of 1.66 μM. Although the inhibitory effect upon the replication of wildtype viruses ex vivo and in vivo remains to be determined, our preliminary result indicates that the potential antiviral activity of teicoplanin could be applied for the treatment of 2019-nCoV virus infection.

title: Novel astroviruses in insectivorous bats.
abstract: Bats are increasingly recognized to harbor a wide range of viruses, and in most instances these viruses appear to establish long-term persistence in these animals. They are the reservoir of a number of human zoonotic diseases including Nipah, Ebola, and severe acute respiratory syndrome. We report the identification of novel groups of astroviruses in apparently healthy insectivorous bats found in Hong Kong, in particular, bats belonging to the genera Miniopterus and Myotis. Astroviruses are important causes of diarrhea in many animal species, including humans. Many of the bat astroviruses form distinct phylogenetic clusters in the genus Mamastrovirus within the family Astroviridae. Virus detection rates of 36% to 100% and 50% to 70% were found in Miniopterus magnater and Miniopterus pusillus bats, respectively, captured within a single bat habitat during four consecutive visits spanning 1 year. There was high genetic diversity of viruses in bats found within this single habitat. Some bat astroviruses may be phylogenetically related to human astroviruses, and further studies with a wider range of bat species in different geographic locations are warranted. These findings are likely to provide new insights into the ecology and evolution of astroviruses and reinforce the role of bats as a reservoir of viruses with potential to pose a zoonotic threat to human health.

title: Time Course of COVID-19 epidemic in Algeria: Retrospective estimate of the actual burden
abstract: Since December 2019, the five continents have been incrementally invaded by SARS-CoV-2. Africa is the last and least affected to date. However, Algeria is among the first countries affected since February 25, 2020. In order to benefit from its experience in the least affected countries, this study aims to describe the current situation of the epidemic and then retrospectively estimate its real burden. As a first part of the study, we described the indicators of the epidemic as; the cumulative and daily reported cases and deaths, and we computed the R0 evolution. Secondly, we used the New York City cases-fatality rate standardized by Algerian age structure, to retrospectively estimate the actual burden. We found that reported cases are in a clear diminution, but, the epidemic epicentre is moving from Blida to other cities. We noted a clear peak in daily cases-fatality from March 30, to April 17, 2020, Fig. 3, due to underestimating the actual infections of the first 25 days. Since May 8, 2020, the daily R0 is around one, Fig. 4. Moreover, we noticed 31% reduction of its mean value from 1,41 to 0,97 between the last two months. The Algerian Age-Standardized Infection Fatality Rate we found is 0,88%. Based on that, we demonstrated that only 1,5% of actual infections were detected and reported before March 30, and 20% after March 31, Fig. 5. Therefore, the actual infections burden is currently five times higher than reported. At the end, we found that at least 0,2 % of the population have been infected until May 27. Consequently, the acquired herd immunity to date is therefore not sufficient to avoid a second wave. We believe that, the under estimation of the actual burden of the epidemic is probably due to the lack of testing capacities, however, all the indicators show that the situation is currently controlled. This requires more vigilance for the next weeks during the gradual easing of the preventive measures.

title: Potential association between COVID-19 mortality and health-care resource availability

title: Collaborative Multi-Disciplinary Incident Command at Seattle Children’s Hospital for Rapid Preparatory Pediatric Surgery Countermeasures to the COVID-19 Pandemic
abstract: Washington State was the first U.S. state to have a patient test positive for COVID-19. Prior to this, our children’s hospital proactively implemented an incident command structure which allowed for collaborative creation of safety measures, policies and procedures for both patients, families, staff and providers. Although the treatment and protective standards are continuously evolving, this commentary shares our thoughts on how an institution, specifically surgical services may develop collaborative process improvement to accommodate for rapid and ongoing change. Specific changes outlined include  early establishment of incident command  personal protective equipment conservation,  workforce safety,  surgical and ambulatory patient triage, and [5] optimization of trainee education. Please note that the contents of this manuscript are shared in the interest of providing collaborative information and are under continuous development as our regional situation changes. We recognize the limitations of this commentary and do not suggest that our approaches represent validated best practices.

title: An Italian Neurology Outpatient Clinic Facing SARS-CoV-2 Pandemic: Data From 2,167 Patients
abstract: Neurological sequelae of SARS-CoV-2 infection have already been reported, but there is insufficient data about the impact of the pandemic on the management of the patients with chronic neurological diseases. We aim to analyze the effect of COVID-19 pandemic and social restriction rules on these fragile patients.  Patients with chronic neurologic diseases routinely followed at the outpatient clinic of Gemelli University Hospital, Rome, were assessed for symptoms suggestive of SARS-CoV-2 infection in the pandemic period, consequences of social restrictions, and neurological disease features, concomitant medical conditions, current medical and disease-specific treatments.  a dedicated telephone survey designed to encompass questions on COVID-19 symptoms and on pandemic effects in chronic neurologic conditions.  Overall, 2,167 individuals were analyzed: 63 patients reported contact with COVID-19 positive cases, 41 performed the swab, and 2 symptomatic patients tested positive for COVID-19 (0.09%). One hundred fifty-eight individuals (7%) needed urgent neurological care, deferred due to the pandemic; 641 patients (30%) suspended hospital treatments, physiotherapy or other support interventions; 405 individuals (19%) reported a subjective worsening of neurological symptoms.  In our population, the presence of neurological chronic diseases did not increase the prevalence of COVID-19 infection. Nevertheless, the burden of neurological disorders has been worsened by the lockdown.

title: Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV
abstract: Estimating the key epidemiological features of the novel coronavirus (2019-nCoV) epidemic proves to be challenging, given incompleteness and delays in early data reporting, in particular, the severe under-reporting bias in the epicenter, Wuhan, Hubei Province, China. As a result, the current literature reports widely varying estimates. We developed an alternative geo-stratified debiasing estimation framework by incorporating human mobility with case reporting data in three stratified zones, i.e., Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. We estimated the latent infection ratio to be around 0.12% (18,556 people) and the basic reproduction number to be 3.24 in Wuhan before the city's lockdown on January 23, 2020. The findings based on this debiasing framework have important implications to prioritization of control and prevention efforts.

title: COVID-19 Impact on People with Diabetes in the South and Central America
abstract: The present observational study aims to describe the political actions in place to fight COVID-19 in the South and Central America region (SACA) while protecting individuals with diabetes.  A survey with 12 questions was shared with all IDF-SACA member organizations, in 18 countries. A descriptive analysis was performed and a multivariate cluster analysis technique pam (partitioning around medoids) was applied.  Two groups of countries were identified. The first group reported more difficulties (limitations in accessing basic or health needs) and fears (concerns regarding the impact of the pandemic), mostly countries with stricter measures to contain the spread of the virus, whereas most of the second group consisted of countries with less restrictive measures, and reported fewer difficulties. Only 37% responded that a policy was put into place to protect individuals with diabetes delivering their medicines and supplies at home (16%) or receiving at once medicine and supplies enough for 2-3 months (21%). All respondents reported as one of the main fears “be infected and do not receive adequate treatment” and/or “getting infected if going to the hospital or medical appointments”.  Most of the SACA countries lack timely implemented measures to protect individuals with diabetes, which may lead to present and future severe impact on the individuals, health system and economy.

title: Incidence of thrombotic complications in critically ill ICU patients with COVID-19
abstract: COVID-19 may predispose to both venous and arterial thromboembolism due to excessive inflammation, hypoxia, immobilisation and diffuse intravascular coagulation. Reports on the incidence of thrombotic complications are however not available.  We evaluated the incidence of the composite outcome of symptomatic acute pulmonary embolism (PE), deep-vein thrombosis, ischemic stroke, myocardial infarction or systemic arterial embolism in all COVID-19 patients admitted to the ICU of 2 Dutch university hospitals and 1 Dutch teaching hospital.  We studied 184 ICU patients with proven COVID-19 pneumonia of whom 23 died (13%), 22 were discharged alive (12%) and 139 (76%) were still on the ICU on April 5th 2020. All patients received at least standard doses thromboprophylaxis. The cumulative incidence of the composite outcome was 31% (95%CI 20-41), of which CTPA and/or ultrasonography confirmed VTE in 27% (95%CI 17-37%) and arterial thrombotic events in 3.7% (95%CI 0-8.2%). PE was the most frequent thrombotic complication (n = 25, 81%). Age (adjusted hazard ratio (aHR) 1.05/per year, 95%CI 1.004-1.01) and coagulopathy, defined as spontaneous prolongation of the prothrombin time > 3 s or activated partial thromboplastin time > 5 s (aHR 4.1, 95%CI 1.9-9.1), were independent predictors of thrombotic complications.  The 31% incidence of thrombotic complications in ICU patients with COVID-19 infections is remarkably high. Our findings reinforce the recommendation to strictly apply pharmacological thrombosis prophylaxis in all COVID-19 patients admitted to the ICU, and are strongly suggestive of increasing the prophylaxis towards high-prophylactic doses, even in the absence of randomized evidence.

title: Oscillations in USA COVID-19 Incidence and Mortality Data reflect societal factors
abstract: The COVID-19 pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produces each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response and diagnosis and reporting. Both daily new cases and daily mortality data in the US exhibit periodic oscillatory patterns. By analyzing NYC and LA testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses such as increased infections on certain days of the week as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the US data is mostly an artifact of reporting, which disappears in datasets that record death by episode date, such as the NYC and LA datasets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting social or biological mechanisms.

title: Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries
abstract: The coronavirus disease 2019 (COVID-19) pandemic is the defining global health crisis of our time and the greatest challenge facing the world. Meteorological parameters are reportedly crucial factors affecting respiratory infectious disease epidemics; however, the effect of meteorological parameters on COVID-19 remains controversial. This study investigated the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, which has useful implications for policymakers and the public. Daily data on meteorological conditions, new cases and new deaths of COVID-19 were collected for 166 countries (excluding China) as of March 27, 2020. Log-linear generalized additive model was used to analyze the effects of temperature and relative humidity on daily new cases and daily new deaths of COVID-19, with potential confounders controlled for, including wind speed, median age of the national population, Global Health Security Index, Human Development Index and population density. Our findings revealed that temperature and relative humidity were both negatively related to daily new cases and deaths. A 1 °C increase in temperature was associated with a 3.08% (95% CI: 1.53%, 4.63%) reduction in daily new cases and a 1.19% (95% CI: 0.44%, 1.95%) reduction in daily new deaths, whereas a 1% increase in relative humidity was associated with a 0.85% (95% CI: 0.51%, 1.19%) reduction in daily new cases and a 0.51% (95% CI: 0.34%, 0.67%) reduction in daily new deaths. The results remained robust when different lag structures and the sensitivity analysis were used. These findings provide preliminary evidence that the COVID-19 pandemic may be partially suppressed with temperature and humidity increases. However, active measures must be taken to control the source of infection, block transmission and prevent further spread of COVID-19.

title: A Novel Coronavirus from Patients with Pneumonia in China, 2019
abstract: In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.

title: Estimating the number of undetected COVID-19 cases exported internationally from all of China
abstract: During the early phase of the COVID-19 pandemic, when SARS-CoV-2 was chiefly reported in the city of Wuhan, cases exported to other locations were largely predicted using flight travel data from Wuhan. However, given Wuhan’s connectivity to other cities in mainland China prior to the lockdown, there has likely been a substantial risk of exportation of cases from other Chinese cities. It is likely that many of these exportations remained undetected because early international case definitions for COVID-19 required a recent travel history from Wuhan. Here, we combine estimates of prevalence in 18 Chinese cities with estimates of flight volume, accounting for the effects of travel bans and the timing of Lunar New Year, to approximate the number of cases exported from cities outside of Wuhan from early December 2019 to late February 2020. We predict that for every one case from Wuhan exported internationally, there were approximately 2.9 cases from large Chinese cities exported internationally that likely remained undetected. Additionally, we predict the number of exported cases in six destinations for which predictions on exported cases have yet to be made, surveillance has likely been low, and where health care systems will likely face issues in managing current or potential outbreaks. We observe heterogeneities in exported case counts across these destinations. The predicted number of cases exported to Egypt and South Africa exceeds the predicted number of cases exported to Mauritania. These trends may anticipate differences in the timing and emergence of local transmission in these countries. Our findings highlight the importance of setting accurate travel history requirements for case definition guidelines in the initial phase of an epidemic, and actively updating these guidelines as the epidemic advances.

title: Estimation of Basic Reproduction Number of the COVID-19 Epidemic in Denmark using a Two-Step Model
abstract: To conduct an early estimation of the Basic Reproduction Number (BRN) induced by government interference, and to project resulting day to day number of in-patients, ICU-patients and cumulative number of deaths in a Danish setting.  We used the Kermack and McKendrick model with varying basic reproduction number to estimate number infected and age stratified percentages to estimate number of in-patients, ICU-patients and cumulative number of deaths. Changes in basic reproduction number was estimated based on current in-patient numbers.  The basic reproductive number in the time period of February 27th to March 18th was found to be 2.65, however, this number was reduced to 1.99 after March 18th.  COVID-19, basic reproduction number, Danish population

title: Estimating the burden of SARS-CoV-2 in France
abstract: France has been heavily affected by the SARS-CoV-2 epidemic and went into lockdown on the 17th March 2020. Using models applied to hospital and death data, we estimate the impact of the lockdown and current population immunity. We find 2.6% of infected individuals are hospitalized and 0.53% die, ranging from 0.001% in those <20y to 8.3% in those >80y. Across all ages, men are more likely to be hospitalized, enter intensive care, and die than women. The lockdown reduced the reproductive number from 3.3 to 0.5 (84% reduction). By 11 May, when interventions are scheduled to be eased, we project 3.7 million (range: 2.3-6.7) people, 5.7% of the population, will have been infected. Population immunity appears insufficient to avoid a second wave if all control measures are released at the end of the lockdown.

title: Direitos humanos das mulheres no parto frente à pandemia de Covid-19: o que fazer da enfermagem obstétrica
abstract: esta comunicação tem por objetivo provocar a reflexão de enfermeiras(os) obstétricas(os) a seguir na luta pela garantia de direitos das mulheres e de seus bebês, em meio à pandemia de COVID-19 DESENVOLVIMENTO: chama a atenção a violação dos Direitos Humanos das mulheres, seus filhos e de enfermeiras obstétricas e obstetrizes, principalmente pelo impacto da pandemia Endossa a Declaração da International Confederation of the Midwives intitulada &quot;Os direitos das mulheres no parto devem ser mantidos durante a pandemia&quot;, e evoca a Enfermagem Obstétrica a um quefazer, solidário e pautado pela justiça social, construído e anunciado pelos corpos e vozes daquelas(es) que cuidam e são cuidadas(os) CONSIDERAÇÕES FINAIS: sinalizamos o compromisso político-social com a democracia enquanto processo que legitima a cidadania num campo especial de interesse: a vida e a saúde das mulheres, a partir do direito constitucional e dos desafios éticos que nos convoca a pandemia  To reflect on the impacts of COVID-19 in northern Italy, the European epicenter of the pandemic DEVELOPMENT: The approach developed since the advent of the disease, its arrival in Italy and its repercussions, not only in the health field, but also in the human relationships and the social environment The epidemic has been impacting the lives of health professionals and has mobilized advances in research around the world FINAL CONSIDERATIONS: It is considered that coping with the disease in the country evidenced the role of Nursing as a care profession and that it will allow for a new thinking about Nursing teaching, care, and research

title: Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic
abstract: The ongoing novel coronavirus disease (COVID-19) pandemic has rapidly spread in early 2020, causing tens of thousands of deaths, over a million cases and widespread socioeconomic disruption. With no vaccine available and numerous national healthcare systems reaching or exceeding capacity, interventions to limit transmission are urgently needed. While there is broad agreement that travel restrictions and closure of non-essential businesses and schools are beneficial in limiting local and regional spread, recommendations around the use of face masks for the general population are less consistent internationally. In this study, we examined the role of face masks in mitigating the spread of COVID-19 in the general population, using epidemic models to estimate the total reduction of infections and deaths under various scenarios. In particular, we examined the optimal deployment of face masks when resources are limited, and explored a range of supply and demand dynamics. We found that face masks, even with a limited protective effect, can reduce infections and deaths, and can delay the peak time of the epidemic. We consistently found that a random distribution of masks in the population was a suboptimal strategy when resources were limited. Prioritizing coverage among the elderly was more beneficial, while allocating a proportion of available resources for diagnosed infected cases provided further mitigation under a range of scenarios. In summary, face mask use, particularly for a pathogen with relatively common asymptomatic carriage, can effectively provide some mitigation of transmission, while balancing provision between vulnerable healthy persons and symptomatic persons can optimize mitigation efforts when resources are limited.

title: A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19
abstract: The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19.

title: Introductions and early spread of SARS-CoV-2 in the New York City area
abstract: New York City (NYC) has emerged as one of the epicenters of the current SARS-CoV2 pandemic. To identify the early events underlying the rapid spread of the virus in the NYC metropolitan area, we sequenced the virus causing COVID19 in patients seeking care at the Mount Sinai Health System. Phylogenetic analysis of 84 distinct SARS-CoV2 genomes indicates multiple, independent but isolated introductions mainly from Europe and other parts of the United States. Moreover, we find evidence for community transmission of SARS-CoV2 as suggested by clusters of related viruses found in patients living in different neighborhoods of the city.

title: Safety and immunogenicity of an anti-Middle East respiratory syndrome coronavirus DNA vaccine: a phase 1, open-label, single-arm, dose-escalation trial
abstract: Middle East respiratory syndrome (MERS) coronavirus causes a highly fatal lower-respiratory tract infection. There are as yet no licensed MERS vaccines or therapeutics. This study (WRAIR-2274) assessed the safety, tolerability, and immunogenicity of the GLS-5300 MERS coronavirus DNA vaccine in healthy adults.  This study was a phase 1, open-label, single-arm, dose-escalation study of GLS-5300 done at the Walter Reed Army Institute for Research Clinical Trials Center (Silver Spring, MD, USA). We enrolled healthy adults aged 18–50 years; exclusion criteria included previous infection or treatment of MERS. Eligible participants were enrolled sequentially using a dose-escalation protocol to receive 0·67 mg, 2 mg, or 6 mg GLS-5300 administered by trained clinical site staff via a single intramuscular 1 mL injection at each vaccination at baseline, week 4, and week 12 followed immediately by co-localised intramuscular electroporation. Enrolment into the higher dose groups occurred after a safety monitoring committee reviewed the data following vaccination of the first five participants at the previous lower dose in each group. The primary outcome of the study was safety, assessed in all participants who received at least one study treatment and for whom post-dose study data were available, during the vaccination period with follow-up through to 48 weeks after dose 3. Safety was measured by the incidence of adverse events; administration site reactions and pain; and changes in safety laboratory parameters. The secondary outcome was immunogenicity.  and is completed.  Between Feb 17 and July 22, 2016, we enrolled 75 individuals and allocated 25 each to 0·67 mg, 2 mg, or 6 mg GLS-5300. No vaccine-associated serious adverse events were reported. The most common adverse events were injection-site reactions, reported in 70 participants (93%) of 75. Overall, 73 participants (97%) of 75 reported at least one solicited adverse event; the most common systemic symptoms were headache (five [20%] with 0·67 mg, 11 [44%] with 2 mg, and seven [28%] with 6 mg), and malaise or fatigue (five [20%] with 0·67 mg, seven [28%] with 2 mg, and two [8%] with 6 mg). The most common local solicited symptoms were administration site pain (23 [92%] with all three doses) and tenderness (21 [84%] with all three doses). Most solicited symptoms were reported as mild (19 [76%] with 0·67 mg, 20 [80%] with 2 mg, and 17 [68%] with 6 mg) and were self-limiting. Unsolicited symptoms were reported for 56 participants (75%) of 75 and were deemed treatment-related for 26 (35%). The most common unsolicited adverse events were infections, occurring in 27 participants (36%); six (8%) were deemed possibly related to study treatment. There were no laboratory abnormalities of grade 3 or higher that were related to study treatment; laboratory abnormalities were uncommon, except for 15 increases in creatine phosphokinase in 14 participants (three participants in the 0·67 mg group, three in the 2 mg group, and seven in the 6 mg group). Of these 15 increases, five (33%) were deemed possibly related to study treatment (one in the 2 mg group and four in the 6 mg group). Seroconversion measured by S1-ELISA occurred in 59 (86%) of 69 participants and 61 (94%) of 65 participants after two and three vaccinations, respectively. Neutralising antibodies were detected in 34 (50%) of 68 participants. T-cell responses were detected in 47 (71%) of 66 participants after two vaccinations and in 44 (76%) of 58 participants after three vaccinations. There were no differences in immune responses between dose groups after 6 weeks. At week 60, vaccine-induced humoral and cellular responses were detected in 51 (77%) of 66 participants and 42 (64%) of 66, respectively.  The GLS-5300 MERS coronavirus vaccine was well tolerated with no vaccine-associated serious adverse events. Immune responses were dose-independent, detected in more than 85% of participants after two vaccinations, and durable through 1 year of follow-up. The data support further development of the GLS-5300 vaccine, including additional studies to test the efficacy of GLS-5300 in a region endemic for MERS coronavirus.  US Department of the Army and GeneOne Life Science.

title: Quantifying spatiotemporal heterogeneity of MERS-CoV transmission in the Middle East region: A combined modelling approach
abstract: coronavirus cases notified in the Middle East region since the identification of the virus in 2012 have displayed variations in time and across geography. Through a combined modelling approach, we estimate the rates of generation of cases along the zoonotic and human-to-human transmission routes and assess their spatiotemporal heterogeneity. We consider all cases notified to WHO from March 2012 to mid-September 2014. We use a stochastic modelling of the time series of case incidence in the Middle East region to estimate time- and space-dependent zoonotic and human-to-human transmission parameters. The model also accounts for possible lack of identification of secondary transmissions among notified cases. This approach is combined with the analysis of imported cases out of the region to assess the rate of underreporting of cases. Out of a total of 32 possible models, based on different parameterisation and scenario considered, the best-fit model is characterised by a large heterogeneity in time and across space for both zoonotic and human-to-human transmission. The variation in time that occurred during Spring 2014 led to a 17-fold and 3-fold increase in the two transmissions, respectively, bringing the reproductive rate to values above 1 during that period for all regions under study. The model suggests that 75% of MERS-CoV cases are secondary cases (human-to-human transmission), which is substantially higher than the 34% of reported cases with an epidemiological link to another case. Overall, estimated reporting rate is 0.26. Our findings show a higher level of spatial heterogeneity in zoonotic transmission compared to human-to-human, highlighting the strong environmental component of the epidemic. Since sporadic introductions are predicted to be a small proportion of notified cases and are responsible for triggering secondary transmissions, a more comprehensive understanding of zoonotic source and path of transmission could be critical to limit the epidemic spread.

title: COVID-19: The unreasonable effectiveness of simple models
abstract: When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the comprehensiveness of many widely established models, the official figures that recount the course of the outbreak still sketch a largely elusive and intimidating picture. Here we show unambiguously that the dynamics of the COVID-19 outbreak belongs to the simple universality class of the SIR model and extensions thereof. Our analysis naturally leads us to establish that there exists a fundamental limitation to any theoretical approach, namely the unpredictable non-stationarity of the testing frames behind the reported figures. However, we show how such bias can be quantified self-consistently and employed to mine useful and accurate information from the data. In particular, we describe how the time evolution of the reporting rates controls the occurrence of the apparent epidemic peak, which typically follows the true one in countries that were not vigorous enough in their testing at the onset of the outbreak. The importance of testing early and resolutely appears as a natural corollary of our analysis, as countries that tested massively at the start clearly had their true peak earlier and less deaths overall.

title: Excess mortality during the Covid-19 pandemic: Early evidence from England and Wales
abstract: The Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as Covid-19-related has increased compared to what would have been expected in the absence of the pandemic. Reasons behind this might include Covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown. I used weekly ONS data on the number of deaths in England and Wales that did not officially involve Covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a difference-in-differences econometric approach to study whether there was a relative increase in deaths not registered as Covid-19-related during the pandemic, compared to a control. Results suggest that there were an additional 968 weekly deaths that officially did not involve Covid-19, compared to what would have otherwise been expected. It is possible that some people are dying from Covid-19 without being diagnosed, and/or that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.

title: Interaction between malarial transmission and BCG vaccination with COVID-19 incidence in the world map: A changing landscape human immune system?
abstract: COVID-19 (Corona virus Disease-2019) is a new public health emergency and is a pandemic currently. Incidence and mortality of COVID-19 vary in different geographical areas. In this study we aimed to analyse the relationship between malaria transmission and BCG vaccination with COVID-19 incidence in the world map.  We collected malaria cases data (World Health Organisation (WHO), 2018), worldwide COVID-19 cases and mortality data (European Centre for Disease Prevention and Control) and data on BCG vaccination. COVID-19 incidence and mortality was compared.  Data on 5316978938 persons from 166 countries were analysed. Malaria incidence rate was negatively correlated with COVID-19 incidence rate (correlation coefficient = -0.513, p<0.001). Malaria free countries had significantly higher number of COVID-19 cases compared to malaria endemic countries. In Europe and Americas, countries, which have higher BCG vaccination coverage, had significantly less mortality per thousand population compared to those with low BCG coverage (median 0.0002 (0-0.0005) vs 0.0029 (0.0002-0.0177), p=0.017). The case fatality ratio of COVID-19 was related nonlinearly to the malaria incidence.  The results suggest the changing human immune system as we progress to eliminate parasitic diseases with time. Chloroquine exposure in malaria endemic zones might have a protective effect.

title: Active surveillance for suspected COVID-19 cases in inpatients with information technology

title: Clinical Performance of SARS-CoV-2 Molecular Testing
abstract: Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the test clinical performance is poorly understood. From 3/10/2020-5/1/2020 NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed in 3,432 patients, of which 2,413 had negative and 1,019 had positive first day results. Repeat-tested patients were more likely to be older, male, African-American or Hispanic, and to have severe disease. Among the patients with initially negative results, 18.6% became positive upon repeat-testing. Only 58.1% of any-time positive patients had a result of "detected" on the first test. The clinical sensitivity of COVID-19 molecular assays is estimated between 66.2% and 95.6%, depending on the unknown number of false negative results in single-tested patients. Conversion to a negative result is unlikely to occur before 15 to 20 days after initial testing or 20-30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Forty-nine initially-positive patients converted to negative and then back to positive in subsequent days. Conversion from first day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely 15 to 20 days after a positive test and the same or next 2 days after a negative test in a patient with high suspicion for COVID-19.

title: COVID-19 infection during pregnancy: fetus as a patient deserves more attention
abstract: The novel coronavirus disease 2019 (COVID-19) pandemic is causing concern also for the management and outcome of COVID-19-positive pregnant women and their offspring, as reported cases are rare. Current evidence suggests the association of COVID-19 infection in pregnancy with both severe maternal morbidity requiring intensive care and perinatal complications (preterm birth with consequent neonatal morbidity and even perinatal death). Most of the reported cases focused specifically on the maternal outcomes and possible vertical transmission, but less attention has been paid to fetus as a patient in such pregnancies. The use of antenatal steroids and fetal neuroprotection with magnesium sulfate is clearly underreported. Several recently issued guidelines suggest lowering the upper gestational age for antenatal steroid administration and also advocate extreme caution or even restraining from the use of magnesium sulfate. Also, the rate of cesarean deliveries among COVID-19 women is unacceptably high. Here we provide arguments for NOT changing the existing guidelines and caution against cesarean delivery that was the prevalent delivery mode in the reported cases and case series.

title: COVID-19 Spread in India: Dynamics, Modeling, and Future Projections
abstract: COVID-19 is an extremely infectious disease with a relatively large virus incubation period in the affected people who may be asymptomatic. Therefore, to reduce the transmission of this pathogen, several countries have taken many intervention measures. In this paper, we show that the impact of these measures in India is different from several other countries. It is shown that an early lockdown in late March 2020 changed the initial exponential growth curve of COVID-19 to a linear one, but a surge in the number of cases from late April 2020 brought India back to a quadratic trajectory. A regional analysis shows the disparate impact of the intervention in different states. It is further shown that the number of reported infections correlates with the number of tests, and therefore regions with limited diagnostics resources may not have a realistic estimate of the virus spread. This insufficiency of diagnostic test data is also reflected in an increasing positivity rate for India nearly 2.5 months after the lockdown, inconsistent with the trends observed for other geographical regions. Nonetheless, future projections are made using different epidemiological models based on the available data, and a comparative study is presented. In the absence of a reliable estimate of the true number of infections, these projections will have a limited accuracy: with that limitation, the most optimistic prediction suggests a continuing virus transmission through September 2020.

title: Investigating the likely association between genetic ancestry and COVID-19 manifestation
abstract: The novel coronavirus 2019-nCoV/SARS-CoV-2 infection has shown discernible variability across the globe. While in some countries people are recovering relatively quicker, in others, recovery times have been comparatively longer and numbers of those succumbing to it high. In this study, we aimed to evaluate the likely association between an individual's ancestry and the extent of COVID-19 manifestation employing Europeans as the case study. We employed 10,215 ancient and modern genomes across the globe assessing 597,573 single nucleotide polymorphisms (SNPs). Pearson's correlation coefficient (r) between various ancestry proportions of European genomes and COVID-19 death/recovery ratio was calculated and its significance was statistically evaluated. We found significant positive correlation (p=0.03) between European Mesolithic hunter gatherers (WHG) ancestral fractions and COVID-19 death/recovery ratio and a marginally significant negative correlation (p=0.06) between Neolithic Iranian ancestry fractions and COVID-19 death/recovery ratio. We further identified 404 immune response related single nucleotide polymorphisms (SNPs) by comparing publicly available 753 genomes from various European countries against 838 genomes from various Eastern Asian countries in a genome wide association study (GWAS). Prominently we identified that SNPs associated with Interferon stimulated antiviral response, Interferon-stimulated gene 15 mediated antiviral mechanism and 2'-5' oligoadenylate synthase mediated antiviral response show large differences in allele frequencies between Europeans and East Asians. Overall, to the best of our knowledge, this is the first study evaluating the likely association between genetic ancestry and COVID-19 manifestation. While our current findings improve our overall understanding of the COVID-19, we note that the development of effective therapeutics will benefit immensely from a more detailed analyses of individual genomic sequence data from COVID-19 patients of varied ancestries.

title: COVID-19 peak estimation and effect of nationwide lockdown in India
abstract: There was a fury of the pandemic because of novel coronavirus (2019-nCoV/SARS-CoV-2) that happened in Wuhan, Hubei province, in China in December 2019. Since then, many model predictions on the COVID-19 pandemic in Wuhan and other parts of China have been reported. The first incident of coronavirus disease 2019 (COVID-19) in India was reported on 30 January 2020, which was a student from Wuhan. The number of reported cases has started to increase day by day after 30 February 2020. The purpose of this investigation is to provide a prediction of the epidemic peak for COVID-19 in India by utilizing real-time data from 30 February to 14 April 2020. We apply the well-known epidemic compartmental model "SEIR" to predict the epidemic peak of COVID-19, India. Since we do not have the complete detail of the infective population, using the available infected population data, we identify the R0 by using polynomial regression. By using the third-order polynomial equation, we estimate that the basic reproduction number for the epidemic in India is R0 = 3.3 (95%CI, 3.1 to 3.5), and the epidemic peak could be reached by September 2020.

title: Cotton tipped plastic swabs for SARS-CoV-2 RT-qPCR diagnosis to prevent supplies shortage.
abstract: Nasopharyngeal sampling protocols for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis guidelines only recommend synthetic fiber swabs. We show that simple and cheap cotton tipped plastic swabs do not inhibit PCR and have equivalent performance to rayon swabs. Cotton tipped plastic swabs are massively produced worldwide and would prevent swabs supplies shortage during current high SARS-CoV-2 testing demands, particularly on developing countries.

title: Comments on "Preliminary estimation of the basic reproduction number of novel Coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven Analysis in the early phase of the outbreak"

title: Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak
abstract: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city in China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and other countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak.  Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (Î³), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI.  The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.  The mean estimate of R0 for the 2019-nCoV ranges from 2.24 to 3.58, and is significantly larger than 1. Our findings indicate the potential of 2019-nCoV to cause outbreaks.

title: Estimating false-negative detection rate of SARS-CoV-2 by RT-PCR
abstract: Reverse transcription-polymerase chain reaction (RT-PCR) assays are used to test patients and key workers for infection with the causative SARS-CoV-2 virus. RT-PCR tests are highly specific and the probability of false positives is low, but false negatives can occur if the sample contains insufficient quantities of the virus to be successfully amplified and detected. The amount of virus in a swab is likely to vary between patients, sample location (nasal, throat or sputum) and through time as infection progresses. Here, we analyse publicly available data from patients who received multiple RT-PCR tests and were identified as SARS-CoV-2 positive at least once. We identify that the probability of a positive test decreases with time after symptom onset, with throat samples less likely to yield a positive result relative to nasal samples. Empirically derived distributions of the time between symptom onset and hospitalisation allowed us to comment on the likely false negative rates in cohorts of patients who present for testing at different clinical stages. We further estimate the expected numbers of false negative tests in a group of tested individuals and show how this is affected by the timing of the tests. Finally, we assessed the robustness of these estimates of false negative rates to the probability of false positive tests. This work has implications both for the identification of infected patients and for the discharge of convalescing patients who are potentially still infectious.

title: Mutated COVID-19 may foretell a great risk for mankind in the future
abstract: Coronavirus disease 2019 SARS-CoV-2 (COVID-19) is a zoonotic virus causing a variety of severe respiratory diseases. SARS-CoV-2 is closest to SARS-CoV and MERS-CoV in structure. The high prevalence of COVID-19 is a result of a lack of symptoms at onset. Our study aimed to present an overview of the virus in terms of structure, epidemiology, symptoms, treatment and prevention. Whole genome sequences and some viral proteins were investigated to determine gaps and changes in alternation of nucleotides and amino acid sequences. We evaluate 11 complete genome sequences of different coronaviruses using BAST and MAFFT software. We also selected seven types of structural proteins. We conclude that COVID-19 might produce new mutations, specifically in glycoproteins, so caution and complete preparation by health authorities is required.

title: Update: Severe Respiratory Illness Associated With a Novel Coronavirus—Worldwide, 2012–2013
abstract: A novel coronavirus associated with severe respiratory tract illness and person‐to‐person spread has been described in patients with travel to the Arabian peninsula and neighboring countries as well as their close contacts. Although not yet described in transplant recipients or donors, providers should be aware of this association.

title: Predicting the epidemic trend of COVID-19 in China and across the world using the machine learning approach
abstract: Although COVID-19 has been well controlled in China, it is rapidly spreading outside the country and may have catastrophic results globally without implementation of necessary mitigation measures. Because the COVID-19 outbreak has made comprehensive and profound impacts on the world, an accurate prediction of its epidemic trend is significant. Although many studies have predicted the COVID-19 epidemic trend, most have used early-stage data and focused on Chinese cases.  We first built models to predict daily numbers of cumulative confirmed cases (CCCs), new cases (NCs), and death cases (DCs) of COVID-19 in China based on data from January 20, 2020, to March 1, 2020. Based on these models, we built models to predict the epidemic trend across the world (outside China). We also built models to predict the epidemic trend in Italy, Spain, Germany, France, UK, and USA where COVID-19 is rapidly spreading.  The COVID-19 outbreak will have peaked on February 22, 2020, in China and will peak on May 22, 2020, across the world. It will be basically under control in early April 2020 in China and end-August 2020 across the world. The total number of COVID-19 cases will reach around 89,000 in China and 6,126,000 across the world during the epidemic. Around 4,000 and 290,000 people will die of COVID-19 in China and across the world, respectively. The COVID-19 outbreak will have peaked recently in Italy and will peak in Spain, Germany, France, UK, and USA within two weeks.  The COVID-19 outbreak is controllable in the foreseeable future if comprehensive and stringent control measures are taken.

title: What are the risks of COVID-19 infection in pregnant women?

title: Commentary

title: [Epidemic trend of corona virus disease 2019 (COVID-19) in mainland China]
abstract: In order to master the epidemic trend of corona virus disease 2019 (COVID-19) and evaluate the effect of prevention and control, we evaluate the epidemic dynamics of COVID-19 in mainland China, Hubei province, Wuhan city and other provinces outside Hubei from January 16 to February 14, 2020.  We collected the daily number of new confirmed COVID-19 cases by nucleic acid detection reported by the National Health Commission from January 16, 2020 to February 14, 2020. The analysis includes the epidemic curve of the new confirmed cases, multiple of the new confirmed cases for period-over-period, multiple of the new confirmed cases for fixed-base, and the period-over-period growth rate of the new confirmed cases.  From January 16 to February 14, 2020, the cumulative number of new confirmed cases of COVID-19 in mainland China was 50 031, including 37 930 in Hubei province, 22 883 in Wuhan city and 12 101 in other provinces outside Hubei. The peak of the number of new confirmed cases in other provinces outside Hubei was from January 31 to February 4, 2020, and the peak of new confirmed cases in Wuhan city and Hubei province was from February 5 to February 9, 2020. The number of new confirmed cases in other provinces outside Hubei showed a significant decline (23% compared with the peak) from February 5 to February 9, 2020, while the number of new confirmed cases in Wuhan city (30% compared with the peak) and Hubei Province (37% compared with the peak) decreased significantly from February 10 to February 14, 2020.  The epidemic prevention and control measures taken by the state and governments at all levels have shown very significant effects, effectively curbing the spread of the COVID-19 epidemic in China.

title: Severe Acute Respiratory Syndrome Historical, Epidemiologic, and Clinical Features
abstract: Severe acute respiratory syndrome coronavirus (SARS-CoV), emerged from China and rapidly spread worldwide. Over 8098 people fell ill and 774 died before the epidemic ended in July 2003. Bats are likely an important reservoir for SARS-CoV. SARS-like CoVs have been detected in horseshoe bats and civet cats. The main mode of transmission of SARS-CoV is through inhalation of respiratory droplets. Faeco-oral transmission has been recorded. Strict infection control procedures with respiratory and contact precautions are essential. Fever and respiratory symptoms predominate, and diarrhea is common. Treatment involves supportive care. There are no specific antiviral treatments or vaccines available.

title: The novel coronavirus outbreak: what can be learned from China in public reporting?
abstract: The new coronavirus outbreak gets everyone’s attention. China’s national actions against the outbreak have contributed great contributions to the world. China has been learning from practice for better reporting and is fast to adapt itself. In this article we discuss China’s practice in public reporting and its implications to global health. Confirmed cases, dynamic suspected cases, recovered cases, and deaths have been reported both in accumulative numbers and their daily updates. Some ratio indictors reporting (fatality rate, recovery rate, etc.), trend reporting, and global surveillance have been applied as well. Some improvements can still be made. It is necessary to further explore the influential factors behind the indicators for interventions. Recommendations are made to the World Health Organization and other countries for better public reporting and surveillance.

title: Testing lags and emerging COVID-19 outbreaks in federal penitentiaries in Canada
abstract: To provide the first known comprehensive analysis of COVID-19 outcomes in a federal penitentiary system. We examined the following COVID-19 outcomes within federal penitentiaries and contrasted them with the overall population in the penitentiaries' respective provincial jurisdictions: testing, prevalence, the proportion recovered, and fatality.  Data for prisons were obtained from the Correctional Service of Canada and, for the general population, from COVID-19 Esri Canadian Outbreak Tracking Hub. Data were retrieved between March 30 and April 21, 2020, and are accurate to this date. Penitentiary-, province- and sex-specific frequency statistics for each outcome were calculated.  Data on 50 of 51 penitentiaries (98%) were available. Of these, 72% of penitentiaries reported fewer tests per 1000 population than the Canadian general population average (16 tests/1000 population), and 24% of penitentiaries reported zero tests. Penitentiaries with high levels of testing were those that already had elevated COVID-19 prevalence. Five penitentiaries reported an outbreak (at least one case). Hardest hit penitentiaries were those in Quebec and British Columbia, with some prisons reporting COVID-19 prevalence of 30% to 40%. Of these, two were women's prisons. Female prisoners were over-represented among cases (31% of cases overall, despite representing 5% of the total prison population).  Increased sentinel or universal testing may be appropriate given the confined nature of prison populations. This, along with rigorous infection prevention control practices and the potential release of prisoners, will be needed to curb current outbreaks and those likely to come.

title: The spatiotemporal estimation of the dynamic risk and the international transmission of 2019 Novel Coronavirus (COVID-19) outbreak: A global perspective
abstract: An ongoing novel coronavirus SARS-CoV-2 pneumonia infection outbreak called COVID-19 started in Wuhan, Hubei Province, China, in December 2019. It both spread rapidly to all provinces in China and started spreading around the world quickly through international human movement from January 2020. Currently, the spatiotemporal epidemic transmission patterns, prediction models, and possible risk analysis for the future are insufficient for COVID-19 but we urgently need relevant information, particularly from the global perspective. We have developed a novel two-stage simulation model to simulate the spatiotemporal changes in the number of COVID-19 cases and estimate the future worldwide risk. Based on the connectivity of countries to China and the country's medical and epidemic prevention capabilities, different scenarios are generated to analyze the possible transmission throughout the world and use this information to evaluate each country's vulnerability to and the dynamic risk of COVID-19. Countries' vulnerability to the COVID-19 outbreak from China is calculated for 63 countries around the world. Taiwan, South Korea, Hong Kong, and Japan are the most vulnerable areas. The relationship between each country's vulnerability and days before the first imported case occurred shows a very high exponential decrease. The cumulative number of cases in each country also has a linear relationship with vulnerability, which can compare and quantify the initial epidemic prevention capabilities to various countries' management strategies. In total, 1,000 simulation results of future cases around the world are generated for the spatiotemporal risk assessment. According to the simulation results of this study, if there is no specific medicine for it, it will likely form a global pandemic. This method can be used as a preliminary risk assessment of the spatiotemporal spread for a new global epidemic.

title: Temperature, humidity, and wind speed are associated with lower Covid-19 incidence
abstract: In absence of empirical research data, there has been considerable speculative hypothesis on the relationship between climatic factors (such as temperature and humidity) and the incidence of Covid-19. This study analyzed the data from 310 regions across 116 countries that reported confirmed cases of Covid-19 by March 12, 2020, and found that temperature, humidity, and wind speed were inversely associated with the incidence rate of Covid-19 after adjusting for the regional and temporal trend in the incidence of Covid-19, columnar density of ozone, precipitation probability, sea-level air-pressure, and length of daytime.

title: Estimating excess 1-year mortality associated with the COVID-19 pandemic according to underlying conditions and age: a population-based cohort study
abstract: The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease.  In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation.  We included 3â862â012 individuals (1â957â935 [50·7%] women and 1â904â077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41-4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18â374 excess deaths with an RR of 1·5, 36â749 with an RR of 2·0, and 73â498 with an RR of 3·0. In a do nothing scenario, we estimated 146â996 excess deaths with an RR of 1·5, 293â991 with an RR of 2·0, and 587â982 with an RR of 3·0.  We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality.

title: Inferring the COVID-19 infection curve in Italy
abstract: Aim of this manuscript is to show a simple method to infer the time-course of new COVID-19 infections (the most important information in order to establish the effect of containment strategies) from available aggregated data, such as number of deaths and hospitalizations. The method, that was used for HIV-AIDS and was named `back-calculation', relies on good estimates of the distribution of the delays between infection and the observed events; assuming that the epidemic follows a simple SIR model with a known generation interval, we can then estimate the parameters that define the time-varying contact rate through maximum likelihood. We show the application of the method to data from Italy and several of its region; it is found that $R_0$ had decreased consistently below 1 around March 20, and in the beginning of April it was between 0.5 and 0.8 in the whole Italy and in most regions.

title: SARS-CoV-2: diagnostic and design conundrums, and the male factor infertility
abstract: The question on whether SARS-CoV-2 (Severe acute respiratory syndrome-related coronavirus (SARS-CoV or SARS-CoV-2, Covid-19) can be harboured in testes and/or the semen is currently unanswered. It is essential to understand the limitations of both antibody and real time polymerase chain reaction (RT-PCR) tests in interpreting SARS-CoV-2 data in relation to semen and testicular tissues analyses without appropriate controls. Here we critically analyse the evidence so far and the possible implications. The diagnostic test limitations posed in both sampling and testing methodologies, their validation, and relevancy in interpreting data are also highlighted.

title: Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA
abstract: The aim of our work was to better understand misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves. We examined publically available time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, about the sensitivity and specificity of the PCR-based diagnostic test. Data originated from Alberta, Canada (available on 3/28/2020) and city of Philadelphia, USA (available on 3/31/2020). Our analysis revealed that the data were compatible with near-perfect specificity but it was challenging to gain information about sensitivity (prior and posterior largely overlapped). We applied these insights to uncertainty/bias analysis of epidemic curves into jurisdictions under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the observed and adjusted epidemic curves likely fall within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60–70% range. In the extreme scenario, hundreds of undiagnosed cases, even among tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves, a task for which the Bayesian method we presented is well-suited.

title: Predicting the number of reported and unreported cases for the COVID-19 epidemics in China, South Korea, Italy, France, Germany and United Kingdom
abstract: The novel coronavirus (SARS-CoV-2) is currently causing concern in the medical, epidemiological and mathematical communities as the virus is rapidly spreading around the world. Internationally, there are more than 1,200,000 cases detected and confirmed in the world on April 6. The asymptomatic and mild symptomatic cases are just going to be really crucial for us to understand what is driving this epidemic to transmit rapidly. Combining a mathematical model of severe (SARS-CoV-2) transmission with data from China, South Korea, Italy, France, Germany and United Kingdom, we provide the epidemic predictions of the number of reported and unreported cases for the SARS-CoV-2 epidemics and evaluate the effectiveness of control measures for each country.

title: Respiratory viruses in young South African children with acute lower respiratory infections and interactions with HIV
abstract: Human rhinovirus (RV) is the most common respiratory virus and has been associated with frequent and severe acute lower respiratory infections (ALRI). The prevalence of RV species among HIV-infected children in South Africa is unknown.  To describe the prevalence of respiratory viruses, including RV species, associated with HIV status and other clinical symptoms in children less than two years of age with and without ALRI in Pretoria, South Africa.  Nasopharyngeal aspirates were collected from 105 hospitalized ALRI cases and 53 non-ALRI controls less than two years of age. HIV status was determined. Common respiratory viruses were identified by PCR, and RV species and genotypes were identified by semi-nested PCR, sequencing and phylogenetic tree analyses.  Respiratory viruses were more common among ALRI cases than controls (83.8% vs. 69.2%; p=0.041). RV was the most commonly identified virus in cases with pneumonia (45.6%) or bronchiolitis (52.1%), regardless of HIV status, as well as in controls (39.6%). RV-A was identified in 26.7% of cases and 15.1% of controls while RV-C was identified in 21.0% of cases and 18.9% of controls. HIV-infected children were more likely to be diagnosed with pneumonia than bronchiolitis (p<0.01). RSV was not identified in any HIV-infected cases (n=15) compared with 30.6% of HIV-uninfected cases (n=85, p=0.013), and was identified more frequently in bronchiolitis than in pneumonia cases (43.8% vs. 12.3%; p<0.01). A and RV-C are endemic in South African children and HIV infection may be protective against RSV and bronchiolitis.

title: Neurological complications of coronavirus and COVID-19.
abstract: Clinical and experimental studies have shown that the coronavirus family has a certain tropism for the central nervous system. Seven types of coronavirus can infect humans.  Coronaviruses are not always confined to the respiratory tract, and under certain conditions they can invade the central nervous system and cause neurological pathologies. The potential for neuroinvasion is well documented in most human coronaviruses (OC-43, 229E, MERS and SARS) and in some animal coronaviruses (porcine haemagglutinating encephalomyelitis coronavirus). Neurological symptoms have been reported in patients affected by COVID-19, such as headache, dizziness, myalgia and anosmia, as well as cases of encephalopathy, encephalitis, necrotising haemorrhagic encephalopathy, stroke, epileptic seizures, rhabdomyolysis and Guillain-Barre syndrome, associated with SARS-CoV-2 infection.  Future epidemiological studies and case records should elucidate the real incidence of these neurological complications, their pathogenic mechanisms and their therapeutic options.

title: Statistical methods for batch screening of input populations by stage and group in COVID-19 nucleic acid testing
abstract: To screen for COVID-19 patients in immigration using minimal nucleic acid testing (NAT).  In the first phase, nasopharyngeal swab samples from the inbound population were numbered and grouped. The samples in the group were mixed together, and a NAT test was performed. When the test result is negative, it means that everyone in the group is not infected and the screening of the group is complete. When the test results were positive, the group moved on to the second stage. In the second stage, all samples in the positive group will be tested individually for NAT.  The advantages and considerations of the method are discussed. Prevalence in the incoming population was a determinant of the sample size within the group. The lower the incidence, the larger the sample size within the group, the higher the savings in NAT and testing costs.  This method has significant efficiency and cost advantages in COVID-19 screening. It can also be used to screen other populations, such as community populations and people at high risk of infection, etc.  NAT; nucleic acid testing; screening; nasopharyngeal swab

title: Belgian Covid-19 Mortality, Excess Deaths, Number of Deaths per Million, and Infection Fatality Rates (8 March - 9 May 2020)
abstract: Scrutiny of COVID-19 mortality in Belgium over the period 8 March-9 May 2020 (Weeks 11-19), using number of deaths per million, infection fatality rates, and the relation between COVID-19 mortality and excess death rates.  Publicly available COVID-19 mortality (2020); overall mortality (2009-2020) data in Belgium and demographic data on the Belgian population; data on the nursing home population; results of repeated sero-prevalence surveys in March-April 2020.  Reweighing, missing-data handling, rate estimation, visualization.  Belgium has virtually no discrepancy between COVID-19 reported mortality (confirmed and possible cases) and excess mortality. There is a sharp excess death peak over the study period; the total number of excess deaths makes April 2020 the deadliest month of April since WWII, with excess deaths far larger than in early 2017 or 2018, even though influenza-induced January 1951 and February 1960 number of excess deaths were similar in magnitude. Using various sero-prevalence estimates, infection fatality rates (IFRs; fraction of deaths among infected cases) are estimated at 0.38-0.73% for males and 0.20-0.39% for females in the non-nursing home population (non-NHP), and at 0.79-1.52% for males and 0.88-1.31% for females in the entire population. Estimates for the NHP range from 38 to 73% for males and over 22 to 37% for females. The IFRs rise from nearly 0% under 45 years, to 4.3% and 13.2% for males in the non-NHP and the general population, respectively, and to 1.5% and 11.1% for females in the non-NHP and general population, respectively. The IFR and number of deaths per million is strongly influenced by extensive reporting and the fact that 66.0% of the deaths concerned NH residents. At 764 (our re-estimation of the figure 735, presented by "Our World in Data"), the number of COVID-19 deaths per million led the international ranking on May 9, 2020, but drops to 262 in the non-NHP. The NHP is very specific: age-related increased risk; highly prevalent comorbidities that, while non-fatal in themselves, exacerbate COVID-19; larger collective households that share inadvertent vectors such as caregivers and favor clustered outbreaks; initial lack of protective equipment, etc. High-quality health care countries have a relatively older but also more frail population , which is likely to contribute to this result.

title: The Challenges Of Urgent Radical Sigmoid Colorectal Cancer Resection In A COVID-19 Patient; A Case Report
abstract: The COVID-19 pandemic presents a unique global health challenge further complicating surgical management of COVID-19 positive patients due to a lack of published literature.  Within we discuss a 48-year-old Chinese man, presenting with acute gastrointestinal obstruction due to sigmoid colonic mass. The patient was screened and tested positive for COVID 19 due to his employment in Wuhan, China at the COVID-19 pandemic epicenter. The patient was subsequently taken for open sigmoid colonic resection, however the case presented multiple challenges due to the patient's COVID-19 positive status.  The challenges of surgical management of COVID-19 positive patients exist are four-fold. First the unknown efficacy of pre-surgical risk stratification in COVID-19 positive patients, second the risk of aerosolized COVID-19 transmission during intubation for surgery, third the risk of fecal COVID-19 transmission to surgical staff during large bowel resection, and fourth the post-operative challenges of caring for COVID-19 positive patients.  Further research is needed into these topics, as well as the medical management of COVID-19 surgical patients.

title: Eco-epidemiological assessment of the COVID-19 epidemic in China, January-February 2020
abstract: The outbreak of COVID-19 in China in early 2020 provides a rich data source for exploring the ecological determinants of this new infection, which may be of relevance elsewhere.  Assessing the spread of the COVID-19 across China, in relation to associations between cases and ecological factors including population density, temperature, solar radiation and precipitation.  Open-access COVID-19 case data include 18,069 geo-located cases in China during January and February 2020, which were mapped onto a 0.25° latitude/longitude grid together with population and weather data (temperature, solar radiation and precipitation). Of 15,539 grid cells, 559 (3.6%) contained at least one case, and these were used to construct a Poisson regression model of cell-weeks. Weather parameters were taken for the preceding week given the established 5-7 day incubation period for COVID-19. The dependent variable in the Poisson model was incident cases per cell-week and exposure was cell population, allowing for clustering of cells over weeks, to give incidence rate ratios.  The overall COVID-19 incidence rate in cells with confirmed cases was 0.12 per 1,000. There was a single case in 113/559 (20.2%) of cells, while two grid cells recorded over 1,000 cases. Weekly means of maximum daily temperature varied from -28.0 to 30.1 °C, minimum daily temperature from -42.4 to 23.0 °C, maximum solar radiation from 0.04 to 2.74 MJm-2 and total precipitation from 0 to 72.6 mm. Adjusted incidence rate ratios suggested brighter, warmer and drier conditions were associated with lower incidence.  Though not demonstrating cause and effect, there were appreciable associations between weather and COVID-19 incidence during the epidemic in China. This does not mean the pandemic will go away with summer weather but demonstrates the importance of using weather conditions in understanding and forecasting the spread of COVID-19.

title: Recent update on COVID-19 in India: Is locking down the country enough?
abstract: India is the second-largest population in the world, and it is not well equipped, hitherto, in the scenario of the global pandemic, SARS-CoV-2 could impart a devastating impact on the Indian population. Only way to respond against this critical condition is by practicing large-scale social distancing. India lock down for 21 days, however, till 7 April 2020, SARS-CoV-2 positive cases were growing exponentially, which raises the concerns if the number of reported and actual cases are similar.  We use Lasso Regression with α=0.12 and Polynomial features of degree 2 to predict the growth factor. Also, we predicted Logistic curve using the Prophet Python. Further, using the growth rate to logistic, and carrying capacity is 20000 allowed us to calculate the maximum cases and new cases per day.  We found the predicted growth factor with a standard deviation of 0.3443 for the upcoming days. When the growth factor becomes 1.0, which is known as Inflection point, it will be safe to state that the rate is no longer exponential. The estimated time to reach the inflection point is between 15-20 April. At that time, the estimated number of total positive cases will be over 12500, if lockdown remains continue.  Our analysis suggests that there is an urgent need to take action to extend the period of lockdown and allocate enough resources, including personnel, beds, and intensive care facilities, to manage the situation in the next few days and weeks. Otherwise, the outbreak in India can reach the level of the USA or Italy or could be worse than these countries within a few days or weeks, given the size of the population and lack of resources.

title: An Invited Commentary on Impact of the Coronavirus (COVID-19) pandemic on surgical practice- -Part 1

title: Clinical Manifestations of Children with COVID-19: a Systematic Review
abstract: The coronavirus disease 2019 (COVID-19) outbreak is an unprecedented global public health challenge, leading to thousands of deaths every day worldwide. Despite the epidemiological importance, clinical patterns of children with COVID-19 remain unclear.  To describe the clinical, laboratorial and radiological characteristics of children with COVID-19.  The Medline database was searched between December 1st 2019 and March 30th 2020.  Inclusion criteria were: (1) studied patients younger than 18 years old; (2) presented original data from cases of COVID-19 confirmed by reverse-transcription polymerase chain reaction; and (3) contained descriptions of clinical manifestations, laboratory tests or radiological examinations.  Number of cases, gender, age, clinical manifestations, laboratory tests, radiological examinations and outcomes.  A total of 34 studies (1,118 cases) were included. From all the cases, 1,111 had their severity classified: 14.3% were asymptomatic, 36.4% were mild, 46.0% were moderate, 2.2% were severe and 1.2% were critical. The most prevalent symptom was fever (16.3%), followed by cough (14.4%), nasal symptoms (3.6%), diarrhea (2.7%) and nausea/vomiting (2.5%). One hundred forty-five (12.9%) children were diagnosed with pneumonia and 43 (3.8%) upper airway infections were reported. Reduced lymphocyte count were reported in 13.1% of cases. Abnormalities on computed tomography was reported in 62.7% of cases. The most prevalent abnormalities reported were ground glass opacities, patchy shadows and consolidations. Only one death was reported.  Clinical manifestations of children with COVID-19 differ widely from adults cases. Fever and respiratory symptoms should not be considered a hallmark of COVID-19 in children.

title: Forecasting the incidence of tuberculosis in China using the seasonal auto-regressive integrated moving average (SARIMA) model
abstract: The aims of this study were to develop a forecasting model for the incidence of tuberculosis (TB) and analyze the seasonality of infections in China; and to provide a useful tool for formulating intervention programs and allocating medical resources.  Data for the monthly incidence of TB from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health (China). The Box–Jenkins method was applied to fit a seasonal auto-regressive integrated moving average (SARIMA) model to forecast the incidence of TB over the subsequent six months.  During the study period of 144 months, 12,321,559 TB cases were reported in China, with an average monthly incidence of 6.4426 per 100,000 of the population. The monthly incidence of TB showed a clear 12-month cycle, and a seasonality with two peaks occurring in January and March and a trough in December. The best-fit model was SARIMA (1,0,0)(0,1,1)12, which demonstrated adequate information extraction (white noise test, p> 0.05). Based on the analysis, the incidence of TB from January to June 2016 were 6.6335, 4.7208, 5.8193, 5.5474, 5.2202 and 4.9156 per 100,000 of the population, respectively.  According to the seasonal pattern of TB incidence in China, the SARIMA model was proposed as a useful tool for monitoring epidemics.

title: Prevalence of COVID-19 among patients with rheumatic diseases: the need to await results from large collaborative studies. Response to: 'COVID-19 pneumonia in a large cohort of patients treated with biological and targeted synthetic antirheumatic drugs' by Conticini et al

title: Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis
abstract: Since being first reported in Wuhan, China, in December 8, 2019, the outbreak of the novel coronavirus, now known as COVID-19, has spread globally. Some case studies regarding the characteristics and outcome of patients with COVID-19 have been published recently. We conducted a meta-analysis to evaluate the risk factors of COVID-19.  Medline, SinoMed, EMBASE, and Cochrane Library were searched for clinical and epidemiological studies on confirmed cases of COVID-19.  The incidence of fever, cough, fatigue, and dyspnea symptoms were 85.6 % (95CI 81.3–89.9 %), 65.7 % (95CI 60.1–71.4 %), 42.4 % (95CI 32.2–52.6 %) and 21.4 % (95CI 15.3–27.5 %). The prevalence of diabetes was 7.7 % (95CI 6.1–9.3 %), hypertension was 15.6 % (95CI 12.6–18.6 %), cardiovascular disease was 4.7 % (95CI 3.1–6.2 %), and malignancy was 1.2 % (95CI 0.5–1.8 %). The complications, including ARDS risk, ranged from 5.6–13.2 %, with the pooled estimate of ARDS risk at 9.4 %, ACI at 5.8 % (95CI 0.7–10.8 %), AKI at 2.1 % (95CI 0.6–3.7 %), and shock at 4.7 % (95CI 0.9–8.6 %). The risks of severity and mortality ranged from 12.6 to 23.5% and from 2.0 to 4.4 %, with pooled estimates at 18.0 and 3.2 %, respectively. The percentage of critical cases in diabetes and hypertension was 44.5 % (95CI 27.0–61.9 %) and 41.7 % (95CI 26.4–56.9 %), respectively.  Fever is the most common symptom in patients with COVID-19. The most prevalent comorbidities are hypertension and diabetes which are associated with the severity of COVID-19. ARDS and ACI may be the main obstacles for patients to treatment recovery. The case severe rate and mortality is lower than that of SARS and MERS.

title: [Analysis of the pregnancy outcomes in pregnant women with COVID-19 in Hubei Province].
abstract: To study the effect of COVID-19 on pregnancy outcomes and neonatal prognosis in Hubei Province.  A retrospective comparison of the pregnancy outcomes was done between 16 women with COVID-19 and 45 women without COVID-19. Also, the results of laboratory tests, imaging examinations, and the 2019-nCoV nucleic acid test were performed in 10 cases of neonatal deliverd from women with COVID-19.  (1) Of the 16 pregnant women with COVID-19, 15 cases were ordinary type and 1 case was severe type. No one has progressed to critical pneumonia. The delivery method of the two groups was cesarean section, and the gestational age were (38.7±1.4) and (37.9±1.6) weeks, there was no significant difference between the two groups (P> 0.05). Also, there wee no significant differences in the intraoperative blood loss and birth weight of the newborn between the two groups (all P>0.05). (2) Ten cases of neonates delivered from pregnant women with COVID-19 were collected. The 2019-nCoV nucleic acid test were all negative. There were no significant differences in fetal distress, meconium-stained amniotic fluid, preterm birth, and neonatal asphyxia between the two groups (all P>0.05). (3) In the treatment of uterine contraction fatigue, carbetocin or carboprost tromethamine was used more in cesarean section for pregnant women with COVID-19 (1.3±0.6), compared with Non-COVID-19 group (0.5±0.7), the difference was statistically significant (P=0.001).  If there is an indication for obstetric surgery or critical illness of COVID-19 in pregnant women, timely termination of pregnancy will not increase the risk of premature birth and asphyxia of the newborn, but it is beneficial to the treatment and rehabilitation of maternal pneumonia. Preventive use of long-acting uterotonic agents could reduce the incidence of postpartum hemorrhage during surgery. 2019-nCoV infection has not been found in neonates deliverd from pregnant women with COVID-19.

title: Electron microscopic reporting of gastrointestianal viruses in the United Kingdom, 1985–1987
abstract: We examined some epidemiological features of the viruses associated with gastrointestinal illness, using national data reported by electron microscopists in the United Kingdom. During the 3 years analyzed (1985–1987), a total of 1,993 positive detections of astroviruses, caliciviruses, coronaviruses, and small round structured viruses (SRSVs) were reported. In 1 year of this period, 8,210 rotaviruses were reported. More than 90% of the astroviruses and caliciviruses were detected in children under 5 years of age, while coronaviruses and SRSVs were detected in adults as well as children. Detections of astroviruses increased in the winter and were infrequent during the summer, a seasonal pattern similar to that observed for rotaviruses. There was some variability between reporting regions in rates of detection of fecal viruses. We have attempted to identify the reasons for this. We make suggestions for improving the detection of human fecal viruses, and we recognize the need for continued surveillance of these agents.

title: Comparison between dairy cow disease incidence in data registered by farmers and in data from a disease-recording system based on veterinary reporting
abstract: Sweden has a national disease-recording system based on veterinary reporting. From this system, all cattle-disease records are transferred to the dairy industry cattle database (DDD) where they are used for several purposes including research and dairy-health statistics. Our objective was to evaluate the completeness of this data source by comparing it with disease data registered by dairy farmers. The proportion of veterinary-treated disease events was estimated, by diagnosis. Disease incidence in the DDD was compared, by diagnosis and age, with disease data registered by the farmers. Comparison was made, by diagnosis, for (i) all disease events and (ii) those reported as veterinary-treated. Disease events, defined as “observed deviations in health, from the normal” were recorded by the farmers during January, April, July and October 2004. For the diagnoses calving problems, peripartum disorders, puerperal paresis and retained placenta, incidence proportions (IP) with 95% confidence intervals (CIs) were estimated. For all other disease problems, incidence rates (IR) were used. In total, 177 farmers reported at least 1 month and 148 reported all 4 months. Fifty-four percent of all disease events in the farmers’ data were reported as veterinary-treated. For several of the most common diagnoses, the IRs and IPs for all events were significantly higher in farmers’ data than in the DDD. Examples are, in cows: clinical mastitis, cough, gastro-intestinal disorders and lameness in hoof and limb; and in young stock: cough and gastro-intestinal disorders. For veterinary-treated events only, significant differences with higher IR in the farmers’ data were found in young stock for sporadic cough and sporadic gastro-intestinal disorders. The diagnosis “other disorders” had significantly more events in the DDD than in farmers’ data, i.e. veterinarians tended to choose more unspecific diagnoses than the farmers. This result indicates that the true completeness is likely to be higher than our estimate. We conclude that for the time period studied there was differential under-reporting associated with the diagnosis, the age of the animal and whether the herd was served by a state-employed or private veterinarian.

title: Rapidly increasing cumulative incidence of coronavirus disease (COVID-19) in the European Union/European Economic Area and the United Kingdom, 1 January to 15 March 2020
abstract: The cumulative incidence of coronavirus disease (COVID-19) cases is showing similar trends in European Union/European Economic Area countries and the United Kingdom confirming that, while at a different stage depending on the country, the COVID-19 pandemic is progressing rapidly in all countries. Based on the experience from Italy, countries, hospitals and intensive care units should increase their preparedness for a surge of patients with COVID-19 who will require healthcare, and in particular intensive care.

title: Positive SARS-Cov-2 test in a woman with COVID-19 at 22 days after hospital discharge: A case report
abstract: In a few discharged patients with coronavirus disease 2019 (COVID-19), the nucleic acid test shows positive results again. Whether this is due to relapse of the disease, reinfection by the virus, or a false-positive result at hospital discharge is worth exploring.  A woman with COVID-19 was discharged from the hospital after integrative treatment with traditional Chinese and Western medicine because she met the discharge standards. However, she obtained positive results on a nucleic acid test 22 days later.  Based on this positive test result in a discharged patient with COVID-19, anal tests and coronavirus antibody tests should be combined with throat swab tests to further develop the diagnosis and discharge standards for patients with COVID-19.

title: HIV Epidemiology in Africa: Weak Variables and Tendentiousness Generate Wobbly Conclusions

title: Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases
abstract: On January 23, 2020, a quarantine was imposed on travel in and out of Wuhan, where the 2019 novel coronavirus (2019-nCoV) outbreak originated from. Previous analyses estimated the basic epidemiological parameters using symptom onset dates of the confirmed cases in Wuhan and outside China.  We obtained information on the 46 coronavirus cases who traveled from Wuhan before January 23 and have been subsequently confirmed in Hong Kong, Japan, Korea, Macau, Singapore, and Taiwan as of February 5, 2020. Most cases have detailed travel history and disease progress. Compared to previous analyses, an important distinction is that we used this data to informatively simulate the infection time of each case using the symptom onset time, previously reported incubation interval, and travel history. We then fitted a simple exponential growth model with adjustment for the January 23 travel ban to the distribution of the simulated infection time. We used a Bayesian analysis with diffuse priors to quantify the uncertainty of the estimated epidemiological parameters. We performed sensitivity analysis to different choices of incubation interval and the hyperparameters in the prior specification.  We found that our model provides good fit to the distribution of the infection time. Assuming the travel rate to the selected countries and regions is constant over the study period, we found that the epidemic was doubling in size every 2.9 days (95% credible interval [CrI], 2 days--4.1 days). Using previously reported serial interval for 2019-nCoV, the estimated basic reproduction number is 5.7 (95% CrI, 3.4--9.2). The estimates did not change substantially if we assumed the travel rate doubled in the last 3 days before January 23, when we used previously reported incubation interval for severe acute respiratory syndrome (SARS), or when we changed the hyperparameters in our prior specification.  Our estimated epidemiological parameters are higher than an earlier report using confirmed cases in Wuhan. This indicates the 2019-nCoV could have been spreading faster than previous estimates.

title: Multinational modeling of SARS-CoV-2 spreading dynamics: Insights on the heterogeneity of COVID-19 transmission and its potential healthcare burden
abstract: Modelling and projections of COVID-19 using a single set of transmission parameters can be an elaborated because the application of different levels of containment measures at different stages of the worldwide COVID-19 outbreak.  We developed a piecewise fitting SEIR methodology to fit the progress of the COVID-19 that can be applied on any of the 185 countries listed in John Hopkins Coronavirus Resource Center. The contagious contact rate, the rate of removal and the initially exposed population were obtained at three different stages of the pandemic for a set of 18 countries, and globally for the total number of cases worldwide. The active number of infections and the removed populations were fitted simultaneously to validate the SEIR model against the available time series reports on the number of confirmed infections, recoveries and deaths. We evaluate the effect of a reduction of contagious contact rate on the level of burden put on local healthcare infrastructure considering different levels of intervention. As a guideline for future public health interventions, we also estimated the maximum number of future cases and its potential peak date.  We project that the peak in the number of infections worldwide will take place after the third quarter of 2020 with a decline rate that might extend beyond 2020. For 12 out of the 18 countries analyzed, we observe that, following the trend at the date of this study, the number of severe infections will surpass their healthcare capacity. For a 90% reduction scenario of the contagious contact rate, four out of the 18 countries analyzed will undergo a significant delay in the peak of infection, extending the course of the epidemic further than our simulation window (365 days).  We identify three stages for the COVID-19 transmission dynamics, which suggest that it is highly heterogeneous between countries and its contagious contact rate, is currently affected by both local responses of the public health interventions and to the population's adherence to the measures.

title: Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study
abstract: The COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.  We collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.  The median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January.  Our findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

title: Updated Information on the Epidemiology of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Infection and Guidance for the Public, Clinicians, and Public Health Authorities, 2012–2013
abstract: The Middle East respiratory syndrome coronavirus (MERS-CoV) was first reported to cause human infection in September 2012. In July 2013, the World Health Organization (WHO) International Health Regulations Emergency Committee determined that MERS-CoV did not meet criteria for a "public health emergency of international concern," but was nevertheless of "serious and great concern". This report summarizes epidemiologic information and provides updates to CDC guidance about patient evaluation, case definitions, travel, and infection control as of September 20, 2013.

title: Acute Type A Aortic Dissection during COVID-19 Outbreak
abstract: As of April 7, 2020, approximately 1,300,000 cases and 80,000 deaths related to coronavirus disease 2019 (COVID-19) have been reported in > 180 countries/territories. Healthcare infrastructures and resources, particularly as it relates to the care of the most critically ill patients, are currently being strained globally. In this context, however, there has been little clinical guidance or information regarding life-threatening conditions requiring emergency surgery that cannot be delayed. We herein present a case of acute type A aortic dissection with COVID-19 in order to highlight the clinical implications of a true emergent procedure during the COVID-19 outbreak.

title: Pseudo acute myocardial infarction in a young COVID-19 patient
abstract: A 29 year old man tested positive for COVID-19 and developed acute respiratory distress syndrome (ARDS). While mechanically ventilated, his electrocardiogram (EKG) showed inferior ST segment elevations, with normal serial cardiac troponin I and transthoracic echocardiograms. He was treated conservatively, with complete clinical recovery and resolution of his EKG abnormalities.

title: BCG vaccination policy and preventive chloroquine usage: do they have an impact on COVID-19 pandemic?
abstract: Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. Interestingly, the global spreading of the disease is not uniform, but has so far left some countries relatively less affected. The reason(s) for this anomalous behavior are not fully understood, but distinct hypotheses have been proposed. Here we discuss the plausibility of two of them: the universal vaccination with Bacillus Calmette–Guerin (BCG) and the widespread use of the antimalarial drug chloroquine (CQ). Both have been amply discussed in the recent literature with positive and negative conclusions: we felt that a comprehensive presentation of the data available on them would be useful. The analysis of data for countries with over 1000 reported COVID-19 cases has shown that the incidence and mortality were higher in countries in which BCG vaccination is either absent or has been discontinued, as compared with the countries with universal vaccination. We have performed a similar analysis of the data available for CQ, a widely used drug in the African continent and in other countries in which malaria is endemic; we discuss it here because CQ has been used as the drug to treat COVID-19 patients. Several African countries no longer recommend it officially for the fight against malaria, due to the development of resistance to Plasmodium, but its use across the continent is still diffuse. Taken together, the data in the literature have led to the suggestion of a possible inverse correlation between BCG immunization and COVID-19 disease incidence and severity.

title: Charting the challenges behind the testing of COVID-19 in developing countries: Nepal as a case study
abstract: The infrastructure needed to detect SARS-CoV-2 infection (COVID-19) that complies completely with WHO guidelines is lacking across many parts of the globe, especially in developing countries, including Nepal. We outline the problems faced by such countries and suggest that the national and international community should collaborate in the development and adoption of novel protocols for the rapid detection of COVID-19 according to locally available infrastructure, in order to fight against the outbreak.

title: Understanding and Interpretation of Case Fatality Rate of Coronavirus Disease 2019

title: A comparison of group testing architectures for COVID-19 testing
abstract: An important component of every country's COVID-19 response is fast and efficient testing -- to identify and isolate cases, as well as for early detection of local hotspots. For many countries, producing a sufficient number of tests has been a serious limiting factor in their efforts to control COVID-19 infections. Group testing is a well-established mathematical tool, which can provide a serious and rapid improvement to this situation. In this note, we compare several well-established group testing schemes in the context of qPCR testing for COVID-19. We include example calculations, where we indicate which testing architectures yield the greatest efficiency gains in various settings. We find that for identification of individuals with COVID-19, array testing is usually the best choice, while for estimation of COVID-19 prevalence rates in the total population, Gibbs-Gower testing usually provides the most accurate estimates given a fixed and relatively small number of tests. This note is intended as a helpful handbook for labs implementing group testing methods.

title: Using observational data to quantify bias of traveller-derived COVID-19 prevalence estimates in Wuhan, China
abstract: The incidence of coronavirus disease 2019 (COVID-19) in Wuhan, China, has been estimated using imported case counts of international travellers, generally under the assumptions that all cases of the disease in travellers have been ascertained and that infection prevalence in travellers and residents is the same. However, findings indicate variation among locations in the capacity for detection of imported cases. Singapore has had very strong epidemiological surveillance and contact tracing capacity during previous infectious disease outbreaks and has consistently shown high sensitivity of case-detection during the COVID-19 outbreak.  We used a Bayesian modelling approach to estimate the relative capacity for detection of imported cases of COVID-19 for 194 locations (excluding China) compared with that for Singapore. We also built a simple mathematical model of the point prevalence of infection in visitors to an epicentre relative to that in residents.  The weighted global ability to detect Wuhan-to-location imported cases of COVID-19 was estimated to be 38% (95% highest posterior density interval [HPDI] 22-64) of Singapore's capacity. This value is equivalent to 2·8 (95% HPDI 1·5-4·4) times the current number of imported and reported cases that could have been detected if all locations had had the same detection capacity as Singapore. Using the second component of the Global Health Security index to stratify likely case-detection capacities, the ability to detect imported cases relative to Singapore was 40% (95% HPDI 22-67) among locations with high surveillance capacity, 37% (18-68) among locations with medium surveillance capacity, and 11% (0-42) among locations with low surveillance capacity. Treating all travellers as if they were residents (rather than accounting for the brief stay of some of these travellers in Wuhan) contributed modestly to underestimation of prevalence.  Estimates of case counts in Wuhan based on assumptions of 100% detection in travellers could have been underestimated by several fold. Furthermore, severity estimates will be inflated several fold since they also rely on case count estimates. Finally, our model supports evidence that underdetected cases of COVID-19 have probably spread in most locations around the world, with greatest risk in locations of low detection capacity and high connectivity to the epicentre of the outbreak.

title: Voices from the frontline: findings from a thematic analysis of a rapid online global survey of maternal and newborn health professionals facing the COVID-19 pandemic
abstract: To prospectively document experiences of frontline maternal and newborn healthcare providers during the COVID-19 pandemic.  We analysed responses using descriptive statistics and qualitative thematic analysis disaggregating by low- and middle-income countries (LMICs) and high-income countries (HICs). Setting 81 countries, between March 24 and April 10, 2020. Participants 714 maternal and newborn healthcare providers.  Preparedness for and response to COVID-19, experiences of health workers providing care to women and newborns, and adaptations to 17 outpatient and inpatient care processes during the pandemic.  Only one third of respondents received training on COVID-19 from their health facility and nearly all searched for information themselves. Half of respondents in LMICs received updated guidelines for care provision compared with 82% in HICs. Overall, only 47% of participants in LMICs, and 69% in HICs felt mostly or completely knowledgeable in how to care for COVID-19 maternity patients. Facility-level responses to COVID-19 (signage, screening, testing, and isolation rooms) were more common in HICs than LMICs. Globally, 90% of respondents reported somewhat or substantially higher levels of stress. There was a widespread perception of reduced use of routine maternity care services, and of modification in care processes, some of which were not evidence-based.  Substantial knowledge gaps exist in guidance on management of maternity cases with or without COVID-19. Formal information sharing channels for providers must be established and mental health support provided. Surveys of maternity care providers can help track the situation, capture innovations, and support rapid development of effective responses.

title: Testing for tracing or testing just for treating? A comparative analysis between strategies to face COVID-19 pandemic.
abstract: There is some consensus in Europe and Asia about testing rates being crucial to controlling COVID-19 pandemics. There are though misconceptions on what means an effective high testing rate. This paper demonstrates that the rate of tests per detected case (Tests/Case) is the important variable, correlating negatively with the number of deaths. The higher the Tests/Case rate, the lower the death rate, as this predictor is causally related to contact tracing and isolation of the vectors of the disease. Doubling Tests/Case typically divides by three the number of deaths. On the other hand, per capita testing rate is a poor predictor for the performance of policies to fight the pandemics. The number of tests per 1,000 inhabitants (Tests/1,000) tends to correlate positively with the number of deaths. In some cases, high levels of Tests/1,000 just mean an epidemic that ran out of control, with an explosion of cases that demands high testing rates just to confirm the diagnosis of the very sick.

title: Modeling reductions in SARS-CoV-2 transmission and hospital burden achieved by prioritizing testing using a clinical prediction rule
abstract: Prompt identification of cases is critical for slowing the spread of COVID-19. However, many areas have faced diagnostic testing shortages, requiring difficult decisions to be made regarding who receives a test, without knowing the implications of those decisions on population-level transmission dynamics. Clinical prediction rules (CPRs) are commonly used tools to guide clinical decisions. We used data from electronic health records to develop a parsimonious 5-variable CPR to identify those who are most likely to test positive, and found that its application to prioritize testing increases the proportion of those testing positive in settings of limited testing capacity. To consider the implications of these gains in daily case detection on the population level, we incorporated testing using the CPR into a compartmentalized disease transmission model. We found that prioritized testing led to a delayed and lowered infection peak (i.e. 'flattens the curve'), with the greatest impact at lower values of the effective reproductive number (such as with concurrent social distancing measures), and when higher proportions of infectious persons seek testing. Additionally, prioritized testing resulted in reductions in overall infections as well as hospital and intensive care unit (ICU) burden. In conclusion, we present a novel approach to evidence-based allocation of limited diagnostic capacity, to achieve public health goals for COVID-19.

title: A new pandemic out of China: the Wuhan 2019-nCoV coronavirus syndrome

title: A Method to Identify the Missing COVID-19 Cases in the U.S. and Results for mid-April 2020
abstract: I use the COVID-19 death rate in South Korea and a method relating the ratio of death rates in a U.S. state to its share of cumulative positive tests to estimate the total cases of COVID-19 in the U.S. and to estimate the extent of infection and the unidentified share of the infected population in each of the lower-48 states and in New York City in mid-April, 2020. I identify a logarithmic relationship between the cumulative death rate in a state and its cumulative positive share of tests. Using this relationship, I find that 4.3-5.4 million people, 1.4-1.7% of the U.S. population, were infected, with rates of infection that ranged from 0.1% in more rural states to 8-10% in New York state and 11-13% in New York City. Only 16-20% of these infected individuals were identified later through testing.

title: Update: Severe Respiratory Illness Associated with a Novel Coronavirus — Worldwide, 2012–2013
abstract: CDC continues to work closely with the World Health Organization (WHO) and other partners to better understand the public health risk posed by a novel coronavirus that was first reported to cause human infection in September 2012. Genetic sequence analyses have shown that this new virus is different from any other known human coronaviruses, including the one that caused severe acute respiratory syndrome (SARS). As of March 7, 2013, a total of 14 confirmed cases of novel coronavirus infection have been reported to WHO, with eight deaths. Illness onsets have occurred from April 2012 through February 2013. To date, no cases have been reported in the United States.

title: A systematic review of MERS-CoV (Middle East Respiratory Syndrome Coronavirus) seroprevalence and viral RNA prevalence in dromedary camels: implications for animal vaccination
abstract: Human infection with Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is driven by recurring dromedary-to-human spill-over events, leading decision-makers to consider dromedary vaccination. Dromedary vaccine candidates in the development pipeline are showing hopeful results, but gaps in our understanding of the epidemiology of MERS-CoV in dromedaries must be addressed to design and evaluate potential vaccination strategies. We systematically reviewed the published literature reporting seroprevalence and/or prevalence of active MERS-CoV infection in dromedary populations from both cross-sectional and longitudinal studies, including 60 studies in our qualitative syntheses. MERS-CoV seroprevalence increased with age up to 80-100% in adult dromedaries supporting geographically wide spread endemicity of MERS-CoV in dromedaries in both the Arabian Peninsula and countries exporting dromedaries from Africa. The high prevalence of active infection measured in juveniles and at sites where dromedary populations mix should guide further investigation – particularly of dromedary movement – and inform vaccination strategy design.

title: Laboratory surveillance for SARS-CoV-2 in India: Performance of testing & descriptive epidemiology of detected COVID-19, January 22 - April 30, 2020.
abstract: India has been reporting the cases of coronavirus disease 2019 (COVID-19) since January 30, 2020. The Indian Council of Medical Research (ICMR) formulated and established laboratory surveillance for COVID-19. In this study, an analysis of the surveillance data was done to describe the testing performance and descriptive epidemiology of COVID-19 cases by time, place and person.  The data were extracted from January 22 to April 30, 2020. The frequencies of testing performance were described over time and by place. We described cases by time (epidemic curve by date of specimen collection; seven-day moving average), place (area map) and person (attack rate by age, sex and contact status), and trends were represented along with public health measures and events.  Between January 22 and April 30, 2020, a total of 1,021,518 individuals were tested for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Testing increased from about 250 individuals per day in the beginning of March to 50,000 specimens per day by the end of April 2020. Overall, 40,184 (3.9%) tests were reported positive. The proportion of positive cases was highest among symptomatic and asymptomatic contacts, 2-3-fold higher than among those with severe acute respiratory infection, or those with an international travel history or healthcare workers. The attack rate (per million) by age was highest among those aged 50-69 yr (63.3) and was lowest among those under 10 yr (6.1). The attack rate was higher among males (41.6) than females (24.3). The secondary attack rate was 6.0 per cent. Overall, 99.0 per cent of 736 districts reported testing and 71.1 per cent reported COVID-19 cases.  The coverage and frequency of ICMR's laboratory surveillance for SARS-CoV-2 improved over time. COVID-19 was reported from most parts of India, and the attack rate was more among men and the elderly and common among close contacts. Analysis of the data indicates that for further insight, additional surveillance tools and strategies at the national and sub-national levels are needed.

title: A County-level Dataset for Informing the United States' Response to COVID-19
abstract: As the coronavirus disease 2019 (COVID-19) becomes a global pandemic, policy makers must enact interventions to stop its spread. Data driven approaches might supply information to support the implementation of mitigation and suppression strategies. To facilitate research in this direction, we present a machine-readable dataset that aggregates relevant data from governmental, journalistic, and academic sources on the county level. In addition to county-level time-series data from the JHU CSSE COVID-19 Dashboard, our dataset contains more than 300 variables that summarize population estimates, demographics, ethnicity, housing, education, employment and in come, climate, transit scores, and healthcare system-related metrics. Furthermore, we present aggregated out-of-home activity information for various points of interest for each county, including grocery stores and hospitals, summarizing data from SafeGraph. By collecting these data, as well as providing tools to read them, we hope to aid researchers investigating how the disease spreads and which communities are best able to accommodate stay-at-home mitigation efforts. Our dataset and associated code are available at https://github.com/JieYingWu/COVID-19_US_County-level_Summaries.

title: Kidney disease is associated with in-hospital death of patients with COVID-19
abstract: In December 2019, a coronavirus 2019 (COVID-19) disease outbreak occurred in Wuhan, Hubei Province, China, and rapidly spread to other areas worldwide. Although diffuse alveolar damage and acute respiratory failure were the main features, the involvement of other organs needs to be explored. Since information on kidney disease in patients with COVID-19 is limited, we determined the prevalence of acute kidney injury (AKI) in patients with COVID-19. Further, we evaluated the association between markers of abnormal kidney function and death in patients with COVID-19. This was a prospective cohort study of 701 patients with COVID-19 admitted in a tertiary teaching hospital that also encompassed three affiliates following this major outbreak in Wuhan in 2020 of whom 113 (16.1%) died in hospital. Median age of the patients was 63 years (interquartile range, 50-71), including 367 men and 334 women. On admission, 43.9% of patients had proteinuria and 26.7% had hematuria. The prevalence of elevated serum creatinine, elevated blood urea nitrogen and estimated glomerular filtration under 60 ml/min/1.73m2 were 14.4, 13.1 and 13.1%, respectively. During the study period, AKI occurred in 5.1% patients. Kaplan-Meier analysis demonstrated that patients with kidney disease had a significantly higher risk for in-hospital death. Cox proportional hazard regression confirmed that elevated baseline serum creatinine (hazard ratio: 2.10, 95% confidence interval: 1.36-3.26), elevated baseline blood urea nitrogen (3.97, 2.57-6.14), AKI stage 1 (1.90, 0.76-4.76), stage 2 (3.51, 1.49-8.26), stage 3 (4.38, 2.31-8.31), proteinuria 1+ (1.80, 0.81-4.00), 2+∼3+ (4.84, 2.00-11.70), and hematuria 1+ (2.99, 1.39-6.42), 2+∼3+ (5.56,2.58- 12.01) were independent risk factors for in-hospital death after adjusting for age, sex, disease severity, comorbidity and leukocyte count. Thus, our findings show the prevalence of kidney disease on admission and the development of AKI during hospitalization in patients with COVID-19 is high and is associated with in-hospital mortality. Hence, clinicians should increase their awareness of kidney disease in patients with severe COVID-19.

title: Etiology of Coinfections in Children with Influenza during 2015/16 Winter Season in Nepal
abstract: Acute respiratory infections (ARIs) are one of the major public health problems in developing countries like Nepal. Besides the influenza, several other pathogens are responsible for acute respiratory infection in children. Etiology of infections is poorly characterized at the course of clinical management, and hence empirical antimicrobial agents are used. The objective of this study was to characterize the influenza and other respiratory pathogens by real-time PCR assay. A total of 175 throat swab specimens of influenza-positive cases collected at National Influenza Center, Nepal, during the 2015/16 winter season were selected for detecting other respiratory copathogens. Total nucleic acid was extracted using Pure Link viral RNA/DNA mini kit (Invitrogen), and multiplex RT-PCR assays were performed. Influenza A and B viruses were found in 120 (68.6%) and 55 (31.4%) specimens, respectively, among which coinfections were found in 106 (60.6%) specimens. Among the influenza A-positive cases, 25 (20.8%) were A/H1N1 pdm09 and 95 (79.2%) were A/H3 subtypes. Viruses coinfected frequently with influenza virus in children were rhinovirus (26; 14.8%), respiratory syncytial virus A/B (19; 10.8%), adenovirus (14; 8.0%), coronavirus (CoV)-HKU1 (14; 8.0%), CoV-OC43 (5; 2.9%), CoV-229E (2; 1.1%), metapneumovirus A/B (5; 2.9%), bocavirus (6; 3.4%), enterovirus (5; 2.9%), parainfluenza virus-1 (3; 1.7%), and parainfluenza virus-3 (2; 1.1%). Coinfection of Mycoplasma pneumoniae with influenza virus was found in children (5; 2.8%). Most of the viral infection occurred in young children below 5 years of age. In addition to influenza virus, nine different respiratory pathogens were detected, of which coinfections of rhinovirus and respiratory syncytial virus A/B were predominantly found in children. This study gives us better information on the respiratory pathogen profile and coinfection combinations which are important for diagnosis and treatment of ARIs.

title: First genome sequences of buffalo coronavirus from water buffaloes in Bangladesh
abstract: We report the complete genome sequences of a buffalo coronavirus (BufCoV HKU26) detected from the faecal samples of two domestic water buffaloes (Bubalus bubalis) in Bangladesh. They possessed 98–99% nucleotide identities to bovine coronavirus (BCoV) genomes, supporting BufCoV HKU26 as a member of Betacoronavirus 1. Nevertheless, BufCoV HKU26 possessed distinct accessory proteins between spike and envelope compared to BCoV. Sugar-binding residues in the N-terminal domain of S protein in BCoV are conserved in BufCoV HKU26.

title: A Novel Protein Drug, Novaferon, as the Potential Antiviral Drug for COVID-19
abstract: Novaferon, a novel protein drug approved for the treatment of chronic hepatitis B in China, exhibits potent antiviral activities. We aimed to determine the anti-SARS-CoV-2 effects of Novaferon in vitro, and conducted a randomized, open-label, parallel group study to explore the antiviral effects of Novaferon for COVID-19.  In laboratory, the inhibition of Novaferon on viral replication in cells infected with SARS-CoV-2, and on SARS-CoV-2 entry into healthy cells was determined. Antiviral effects of Novaferon were evaluated in COVID-19 patients with treatment of Novaferon, Novaferon plus Lopinavir/Ritonavir, or Lopinavir/Ritonavir. The primary endpoint was the SARS-CoV-2 clearance rates on day 6 of treatment, and the secondary endpoint was the time to the SARS-CoV-2 clearance in COVID-19 patients Results Novaferon inhibited the viral replication in infected cells (EC50=1.02 ng/ml), and protected healthy cells from SARS-CoV-2 infection (EC50=0.1 ng/ml). Results from the 89 enrolled COVID-19 patients showed that both Novaferon and Novaferon plus Lopinavir/Ritonavir groups had significantly higher SARS-CoV-2 clearance rates on day 6 than the Lopinavir/Ritonavir group (50.0% vs.24.1%, p = 0.0400, and 60.0% vs.24.1%, p = 0.0053). Median time to SARS-CoV-2 clearance were 6 days, 6 days, and 9 days for three groups respectively, suggesting a 3-dayreduction of time to SARS-CoV-2 clearance in both Novaferon and Novaferon plus Lopinavir/Ritonavir groups compared with Lopinavir/Ritonavir group.  Novaferon exhibited anti-SARS-CoV-2 effects in vitro and in COVID-19 patients. These data justified the further evaluation of Novaferon.  COVID-19, SARS-CoV-2, Novaferon, Antiviral drug,

title: De-isolating Coronavirus Disease 2019 Suspected Cases: A Continuing Challenge

title: Real time estimation of the risk of death from novel coronavirus (2019-nCoV) infection: Inference using exported cases
abstract: The exported cases of 2019 novel coronavirus (2019-nCoV) infection who were confirmed in other countries provide a chance to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in China. Knowledge of the cCFR is critical to characterize the severity and understand pandemic potential of 2019-nCoV in the early stage of epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number, i.e., the average number of secondary cases generated by a single primary case in a naive population. As of 24 January 2020, with 23 exported cases, and estimating the growth rate from 8 December 2019 (scenario 1) and using the data since growth of exported cases (scenario 2), the cumulative incidence in China was estimated at 5433 cases (95% confidence interval (CI): 3883, 7160) and 17780 cases (95% CI: 9646, 28724), respectively. The latest estimates of the cCFR were 4.6% (95% CI: 3.1-6.6) for scenario 1 and 7.7% (95% CI: 4.9-11.3%) for scenario 2, respectively. The basic reproduction number was estimated to be 2.2 (95% CI: 2.1, 2.3) and 3.7 (95% CI: 3.1, 4.3) for scenarios 1 and 2, respectively. Based on the results, we note that current 2019-nCoV epidemic has a substation potential to cause a pandemic. The proposed approach can provide insights into early risk assessment using only publicly available data.

title: Characterizing the transmission and identifying the control strategy for COVID-19 through epidemiological modeling
abstract: The outbreak of the novel coronavirus disease, COVID-19, originating from Wuhan, China in early December, has infected more than 70,000 people in China and other countries and has caused more than 2,000 deaths. As the disease continues to spread, the biomedical society urgently began identifying effective approaches to prevent further outbreaks. Through rigorous epidemiological analysis, we characterized the fast transmission of COVID-19 with a basic reproductive number 5.6 and proved a sole zoonotic source to originate in Wuhan. No changes in transmission have been noted across generations. By evaluating different control strategies through predictive modeling and Monte carlo simulations, a comprehensive quarantine in hospitals and quarantine stations has been found to be the most effective approach. Government action to immediately enforce this quarantine is highly recommended.

title: Population modeling of early COVID-19 epidemic dynamics in French regions and estimation of the lockdown impact on infection rate
abstract: We propose a population approach to model the beginning of the French COVID-19 epidemic at the regional level. We rely on an extended Susceptible-Exposed-Infectious-Recovered (SEIR) mechanistic model, a simplified representation of the average epidemic process. Combining several French public datasets on the early dynamics of the epidemic, we estimate region-specific key parameters conditionally on this mechanistic model through Stochastic Approximation Expectation Maximization (SAEM) optimization using Monolix software. We thus estimate basic reproductive numbers by region before isolation (between 2.4 and 3.1), the percentage of infected people over time (between 2.0 and 5.9% as of May 11th, 2020) and the impact of nationwide household confinement on the infection rate (decreasing the transmission rate by 72% toward a Re ranging from 0.7 to 0.9). We conclude that a lifting of the lockdown should be accompanied by further interventions to avoid an epidemic rebound.

title: Coronavirus infections reported by ProMED, February 2000-January 2020
abstract: Sources describing the global burden of emerging diseases accurately are still limited. We reviewed coronavirus infections reported by ProMED and assessed the reliability of the data retrieved compared to published reports. We evaluated the effectiveness of ProMED as a source of epidemiological data on coronavirus.  Using the keyword "coronavirus" in the ProMED search engine, we reviewed all the information from the reports and collected data using a structured form, including year, country, gender, occupation, the number of infected individuals, and the number of fatal cases.  We identified 109 entries reported between February 29, 2000 and January 22, 2020. A total of 966 cases were reported, with death reported in 188 cases, suggesting an overall case fatality rate (CFR) of 19.5%. Of 70 cases for which the gender was reported, 47 (67.1%) were male. Most of the cases were reported from China, the United Arab Emirates, and Saudi Arabia, with reports from other countries, including imported cases in Europe and North America.  Internet-based reporting systems such as ProMED are useful to gather information and synthesize knowledge on emerging infections. Although certain areas need to be improved, ProMED provided useful information about coronaviruses especially during outbreaks.

title: A national prospective cohort study of SARS/COV2 pandemic outcomes in the U.S.: The CHASING COVID Cohort
abstract: The Chasing COVID Cohort (C3) study is a US-based, geographically and socio-demographically diverse sample of adults (18 and older) enrolled into a prospective cohort study during the upswing of the U.S. COVID-19 pandemic.  We used internet-based strategies to enroll C3 participants beginning March 28th, 2020. Following baseline questionnaire completion, study participants will be contacted monthly (for 6 months) to complete assessments of engagement in non-pharmaceutical interventions (e.g., use of cloth masks, avoiding large gatherings); COVID-19 symptoms; SARS/COV2 testing and diagnosis; hospitalizations; healthcare access; and uptake of health messaging. Dried blood spot (DBS) specimens will be collected at the first follow-up assessment (last week of April 2020) and at month 3 (last week of June 2020) and stored until a validated serologic test is available.  As of April 20, 2020, the number of people that completed the baseline survey and provided contact information for follow-up was 7,070. Participants resided in all 50 US states, the District of Columbia, Puerto Rico, and Guam. At least 24% of participants were frontline workers (healthcare and other essential workers). Twenty-three percent (23%) were 60+ years, 24% were Black or Hispanic, 52% were men, and 52% were currently employed. Nearly 20% reported recent COVID-like symptoms (cough, fever or shortness of breath) and a high proportion reported engaging in non-pharmaceutical interventions that reduce SARS/COV2 spread (93% avoided groups >20, 58% wore masks; 73% quarantined). More than half (54%) had higher risk for severe COVID-19 illness should they become infected with SARS/COV2 based on age, underlying health conditions (e.g., chronic lung disease), or daily smoking.  A geographically and socio-demographically diverse group of participants was rapidly enrolled in the C3 during the upswing of the SARS/COV2 pandemic. Strengths of the C3 include the potential for direct observation of, and risk factors for, seroconversion and incident COVID disease (among those with or without antibodies to SARS/COV2) in areas of active transmission.

title: Impact of COVID-19 epidemic curtailment strategies in selected Indian states: an analysis by reproduction number and doubling time with incidence modelling
abstract: The Government of India in networks with its state government has implemented the epidemic curtailment strategies inclusive of case-isolation, quarantine and lockdown in response to ongoing novel coronavirus (COVID-19) outbreak . In this manuscript we attempt to estimate the effect of these steps across ten Indian states using crowd-sourced data. The chosen transmission parameters are -reproduction number (R0), doubling time and growth rate during the early epidemic phase (15 days into lockdown) and 30 days into lockdown (23rd April 2020) through maximum likelihood approach. The overall analysis shows the decreasing trends in reproductive numbers and growth rate (with few exceptions) and incremental doubling time. The curtailment strategies employed by the Indian government seemed to be effective in reducing the transmission parameters of the COVID-19 epidemic. The effective reproductive numbers are still higher above the threshold of 1 and the resultant absolute numbers tend to be exponentiating fundamentally. The curtailment strategy thus may take into account these findings while formulating further course of actions.

title: Coronavirus (COVID-19) Outbreak: What the Department of Radiology Should Know
abstract: In December 2019, a novel coronavirus (COVID-19) pneumonia emerged in Wuhan, China. Since then, this highly contagious COVID-19 has been spreading worldwide, with a rapid rise in the number of deaths. Novel COVID-19–infected pneumonia (NCIP) is characterized by fever, fatigue, dry cough, and dyspnea. A variety of chest imaging features have been reported, similar to those found in other types of coronavirus syndromes. The purpose of the present review is to briefly discuss the known epidemiology and the imaging findings of coronavirus syndromes, with a focus on the reported imaging findings of NCIP. Moreover, the authors review precautions and safety measures for radiology department personnel to manage patients with known or suspected NCIP. Implementation of a robust plan in the radiology department is required to prevent further transmission of the virus to patients and department staff members.

title: The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study
abstract: In December, 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus, emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures in response to the outbreak, including extended school and workplace closures. We aimed to estimate the effects of physical distancing measures on the progression of the COVID-19 epidemic, hoping to provide some insights for the rest of the world.  To examine how changes in population mixing have affected outbreak progression in Wuhan, we used synthetic location-specific contact patterns in Wuhan and adapted these in the presence of school closures, extended workplace closures, and a reduction in mixing in the general community. Using these matrices and the latest estimates of the epidemiological parameters of the Wuhan outbreak, we simulated the ongoing trajectory of an outbreak in Wuhan using an age-structured susceptible-exposed-infected-removed (SEIR) model for several physical distancing measures. We fitted the latest estimates of epidemic parameters from a transmission model to data on local and internationally exported cases from Wuhan in an age-structured epidemic framework and investigated the age distribution of cases. We also simulated lifting of the control measures by allowing people to return to work in a phased-in way and looked at the effects of returning to work at different stages of the underlying outbreak (at the beginning of March or April).  Our projections show that physical distancing measures were most effective if the staggered return to work was at the beginning of April; this reduced the median number of infections by more than 92% (IQR 66–97) and 24% (13–90) in mid-2020 and end-2020, respectively. There are benefits to sustaining these measures until April in terms of delaying and reducing the height of the peak, median epidemic size at end-2020, and affording health-care systems more time to expand and respond. However, the modelled effects of physical distancing measures vary by the duration of infectiousness and the role school children have in the epidemic.  Restrictions on activities in Wuhan, if maintained until April, would probably help to delay the epidemic peak. Our projections suggest that premature and sudden lifting of interventions could lead to an earlier secondary peak, which could be flattened by relaxing the interventions gradually. However, there are limitations to our analysis, including large uncertainties around estimates of R 0 and the duration of infectiousness. Funding Bill & Melinda Gates Foundation, National Institute for Health Research, Wellcome Trust, and Health Data Research UK.

title: ESTIMATION OF COVID-19 CASES IN FRANCE AND IN DIFFERENT COUNTRIES: HOMOGENEISATION BASED ON MORTALITY
abstract: Every day the authorities of different countries provide an estimate of the number of persons affected by Covid-19 and a count of fatality. We propose to use the fatality reported in each country to provide a better estimate (Ct0-estimated) of the number of cases at a given time t0. Ct0-estimated = (Ft0 / Fr-est) * (1+ [C(est-d) / C(est-3d)])6 With Ft0: number of actual fatalities reported in a country at time t0; Fr-est: estimated fatality rate; C(est-d): estimated fatalities 18 days before t0; C(est-3d): estimated fatalities 21 days before t0. Based on Ct0-estimated calculated using a fatality rate of 2%, we assessed the number of cases April 10th, 2020 in Belgium, China, France, Germany, Iran, Italy, South Korea, Netherlands, Spain, United Kingdom and USA. This number reached 2,872,097 in France and 924,892 persons in Germany. The proposed formulas also make it possible to evaluate the impact of policies to prevent the spread of epidemic on the appearance of new cases.

title: Global transmission network of SARS-CoV-2: from outbreak to pandemic
abstract: The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is straining health systems around the world. Although the Chinese government implemented a number of severe restrictions on people’s movement in an attempt to contain its local and international spread, the virus had already reached many areas of the world in part due to its potent transmissibility and the fact that a substantial fraction of infected individuals develop little or no symptoms at all. Following its emergence, the virus started to generate sustained transmission in neighboring countries in Asia, Western Europe, Australia, Canada and the United States, and finally in South America and Africa. As the virus continues its global spread, a clear and evidence-based understanding of properties and dynamics of the global transmission network of SARS-CoV-2 is essential to design and put in place efficient and globally coordinated interventions.  We employ molecular surveillance data of SARS-CoV-2 epidemics for inference and comprehensive analysis of its global transmission network before the pandemic declaration. Our goal was to characterize the spatial-temporal transmission pathways that led to the establishment of the pandemic. We exploited a network-based approach specifically tailored to emerging outbreak settings. Specifically, it traces the accumulation of mutations in viral genomic variants via mutation trees, which are then used to infer transmission networks, revealing an up-to-date picture of the spread of SARS-CoV-2 between and within countries and geographic regions.  The analysis suggest multiple introductions of SARS-CoV-2 into the majority of world regions by means of heterogeneous transmission pathways. The transmission network is scale-free, with a few genomic variants responsible for the majority of possible transmissions. The network structure is in line with the available temporal information represented by sample collection times and suggest the expected sampling time difference of few days between potential transmission pairs. The inferred network structural properties, transmission clusters and pathways and virus introduction routes emphasize the extent of the global epidemiological linkage and demonstrate the importance of internationally coordinated public health measures.

title: Incidental finding of COVID-19 pulmonary infiltrates on SPECT/CT attenuation correction CT

title: COVID-19 Testing, Epidemic Features, Hospital Outcomes, and Household Prevalence, New York State—March 2020
abstract: The United States’ COVID-19 epidemic has grown extensively since February 2020, with substantial associated hospitalizations and mortality; New York State (NYS) has emerged as the national epicenter. We report on the extent of testing and test results during the month of March in NYS, along with risk factors, outcomes, and household prevalence among initial cases subject to in-depth investigations.  Specimen collection for COVID-19 testing was conducted in healthcare settings, community-based collection sites, and by home testing teams. Information on demographics, risk factors, and hospital outcomes of cases was obtained through epidemiological investigations and an electronic medical records match, and summarized descriptively. Active testing of initial case’s households enabled estimation of household prevalence.  During March In NYS, outside of New York City, a total of 47,326 persons tested positive for SARS-CoV-2, out of 141,495 tests (33% test-positive), with the highest number of cases located in the metropolitan region counties. Among 229 initial cases diagnosed through March 12, by March 30 13% were hospitalized and 2% died. Testing conducted among 498 members of these case’s households found prevalent infection among 57%; excluding first-reported cases 38%. In these homes, we found a significant age gradient in prevalence, from 23% among those <5 years to 68% among those ≥65 years (p<.0001).  New York State faced a substantial and increasing COVID-19 outbreak during March 2020. The earliest cases had high levels of infection in their households and by the end of the month, the risks of hospitalization and death were high.

title: Analysis of the impact of lockdown on the evolution Covid-19 epidemics in Spain
abstract: The late 2019 Covid-19 disease outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, with local specificities. The objective of this work is to evaluate the impact of the measures undertaken in Spain to deal with the pandemic.  We estimated the number of cases and the impact of lockdown on the reproducibility number based on the hospitalization reports.  The estimated number of cases shows a sharp increase until the lockdown, followed by a slowing down and then a decrease after full quarantine was implemented. Differences in the basic reproduction ratio are also very significant, dropping from de 5.89 (95% CI: 5.46-7.09) before the lockdown to 0.48 (95% CI: 0.15-1.17) afterwards.  Handling a pandemic like Covid-19 is very complex and requires quick decision making. The large differences found in the speed of propagation of the disease show us that being able to implement interventions at the earliest stage is crucial to minimise the impact of a potential infectious threat. Our work also stresses the importance of reliable up to date epidemiological data in order to accurately assess the impact of Public Health policies on viral outbreak.

title: Laboratory practices to mitigate biohazard risks during the COVID-19 outbreak: an IFCC global survey.
abstract: A global survey was conducted by the IFCC Task Force on COVID-19 to better understand how general biochemistry laboratories manage the pre-analytical, analytical and post-analytical processes to mitigate biohazard risks during the coronavirus disease 2019 (COVID-19) pandemic.  An electronic survey was developed to record the general characteristics of the laboratory, as well as the pre-analytical, analytical, post-analytical and operational practices of biochemistry laboratories that are managing clinical samples of patients with COVID-19.  A total of 1210 submissions were included in the analysis. The majority of responses came from hospital central/core laboratories that serve hospital patient groups and handle moderate daily sample volumes. There has been a decrease in the use of pneumatic tube transport, increase in hand delivery and increase in number of layers of plastic bags for samples of patients with clinically suspected or confirmed COVID-19. Surgical face masks and gloves are the most commonly used personal protective equipment (PPE). Just >50% of the laboratories did not perform an additional decontamination step on the instrument after analysis of samples from patients with clinically suspected or confirmed COVID-19. A fifth of laboratories disallowed add-on testing on these samples. Less than a quarter of laboratories autoclaved their samples prior to disposal.  The survey responses showed wide variation in pre-analytical, analytical and post-analytical practices in terms of PPE adoption and biosafety processes. It is likely that many of the suboptimal biosafety practices are related to practical local factors, such as limited PPE availability and lack of automated instrumentation.

title: Cryo-EM structure of infectious bronchitis coronavirus spike protein reveals structural and functional evolution of coronavirus spike proteins
abstract: As cell-invading molecular machinery, coronavirus spike proteins pose an evolutionary conundrum due to their high divergence. In this study, we determined the cryo-EM structure of avian infectious bronchitis coronavirus (IBV) spike protein from the γ-genus. The trimeric IBV spike ectodomain contains three receptor-binding S1 heads and a trimeric membrane-fusion S2 stalk. While IBV S2 is structurally similar to those from the other genera, IBV S1 possesses structural features that are unique to different other genera, thereby bridging these diverse spikes into an evolutionary spectrum. Specifically, among different genera, the two domains of S1, the N-terminal domain (S1-NTD) and C-terminal domain (S1-CTD), diverge from simpler tertiary structures and quaternary packing to more complex ones, leading to different functions of the spikes in receptor usage and membrane fusion. Based on the above structural and functional comparisons, we propose that the evolutionary spectrum of coronavirus spikes follows the order of α-, δ-, γ-, and β-genus. This study has provided insight into the evolutionary relationships among coronavirus spikes and deepened our understanding of their structural and functional diversity.

title: Occurrence of SARS‐CoV‐2 during mycophenolate mofetil treatment for pemphigus
abstract: we read with great interest the article entitled “Should SARS‐CoV‐2 influence immunosuppressive therapy for autoimmune blistering diseases?” published by Di Altobrando A. et al. in the JEADV. This is the first report of COronaVIrus DIsease 2019 (COVID‐19) in a patient affected by autoimmune blistering disease (ABD) during immunosuppressive treatment (i.e. azathioprine). The authors conclude that it is crucial to learn of more cases of ABD patients under immunosuppressive treatment who have developed COVID‐19, in order to better quantify the risk of infection under immunosuppressive therapy.

title: Modeling the COVID-19 outbreak in the United States
abstract: The COVID-19 contagion has developed at an alarming rate in the US and as of April 24, 2020, tens of thousands of people have already died from the disease. In the event of an outbreak like such, forecasting the extent of the mortality that will occur is crucial to aid the implementation of effective interventions. Mortality depends on two factors: the case fatality rate and the case incidence. We combine a cohort-based model that determines case fatality rates along with a modified logistic model that evaluates the case incidence to determine the number of deaths in all the US states over time; the model is also able to include the impact of interventions. Both models yield exceptional goodness-of-fit. The model predicted a range of death outcomes (79k to 246k) all of which are considerably greater than the figures presented in mainstream media. This model can be used more effectively than current models to estimate the number of deaths during an outbreak, allowing for better planning.

title: Estimating Absolute and Relative Case Fatality Ratios from Infectious Disease Surveillance Data
abstract: Knowing which populations are most at risk for severe outcomes from an emerging infectious disease is crucial in deciding the optimal allocation of resources during an outbreak response. The case fatality ratio (CFR) is the fraction of cases that die after contracting a disease. The relative CFR is the factor by which the case fatality in one group is greater or less than that in a second group. Incomplete reporting of the number of infected individuals, both recovered and dead, can lead to biased estimates of the CFR. We define conditions under which the CFR and the relative CFR are identifiable. Furthermore, we propose an estimator for the relative CFR that controls for time-varying reporting rates. We generalize our methods to account for elapsed time between infection and death. To demonstrate the new methodology, we use data from the 1918 influenza pandemic to estimate relative CFRs between counties in Maryland. A simulation study evaluates the performance of the methods in outbreak scenarios. An R software package makes the methods and data presented here freely available. Our work highlights the limitations and challenges associated with estimating absolute and relative CFRs in practice. However, in certain situations, the methods presented here can help identify vulnerable subpopulations early in an outbreak of an emerging pathogen such as pandemic influenza.

title: Nanopore target sequencing for accurate and comprehensive detection of SARS-CoV-2 and other respiratory viruses
abstract: The ongoing novel coronavirus pneumonia COVID-19 outbreak in Wuhan, China, has engendered numerous cases of infection and death. COVID-19 diagnosis relies upon nucleic acid detection; however, current recommended methods exhibit high false-negative rates, low sensitivity, and cannot identify other respiratory virus infections, thereby resulting patient misdiagnosis and impeding epidemic containment. Combining the advantages of target amplification and long-read, real-time nanopore sequencing, we developed nanopore target sequencing (NTS) to detect SARS-CoV-2 and other respiratory viruses simultaneously within 6-10 h. Parallel testing with approved qPCR kits of SARS-CoV-2 and NTS using 61 nucleic acid samples from suspected COVID-19 cases confirmed that NTS identified more infected patients as positive, and could also monitor for mutated nucleic acid sequence or other respiratory virus infection in the test sample. NTS is thus suitable for contemporary COVID-19 diagnosis; moreover, this platform can be further extended for diagnosing other viruses or pathogens.

title: Transmissibility of 2019 Novel Coronavirus: zoonotic vs. human to human transmission, China, 2019-2020
abstract: The novel coronavirus (2019-nCoV) originating from Wuhan has rapidly spread throughout China. While the origin of the outbreak remains uncertain, accumulating evidence links a wet market in Wuhan for the early spread of 2019-nCoV. Similarly, the influence of the marketplace on the early transmission dynamics is yet to be investigated.  Using the daily series of COVID-19 incidenceincluding contact history with the market, we have conducted quantitative modeling analyses to estimate the reproduction numbers (R) for the market-to-human and human-to-human transmission together with the reporting probability and the early effects of public health interventions.  Our mean R estimates for China in 2019-2020 are estimated at 0.37 (95%CrI: 0.02-1.78) for market-to-human transmission, and 3.87 (95%CrI: 3.18-4.78) for human-to-human transmission, respectively. Moreover we estimated that the reporting rate cases stemming from market-to-human transmission was 3-31 fold higher than that for cases stemming from human-to-human transmission, suggesting that contact history with the wet market played a key role in identifying COVID-19 cases.  Our findings suggest that the proportions of asymptomatic and subclinical patients constitute a substantial component of the epidemic's magnitude. Findings suggest that the development of rapid diagnostic tests could help bring the epidemic more rapidly under control.

title: ElaD, a Deubiquitinating Protease Expressed by E. coli
abstract: Ubiquitin and ubiquitin-like proteins (Ubl) are designed to modify polypeptides in eukaryotes. Covalent binding of ubiquitin or Ubls to substrate proteins can be reversed by specific hydrolases. One particular set of cysteine proteases, the CE clan, which targets ubiquitin and Ubls, has homologs in eukaryotes, prokaryotes, and viruses.  We have cloned and analyzed the E. coli protein elaD, which is distantly related to eukaryotic CE clan members of the ULP/SENP protease family that are specific for SUMO and Nedd8. Previously misannotated as a putative sulfatase/phosphatase, elaD is an efficient and specific deubiquitinating enzyme in vitro. Interestingly, elaD is present in all intestinal pathogenic E. coli strains, but conspicuously absent from extraintestinal pathogenic strains (ExPECs). Further homologs of this protease can be found in Acanthamoeba Polyphaga Mimivirus, and in Alpha-, Beta-and Gammaproteobacteria.  The expression of ULP/SENP-related hydrolases in bacteria therefore extends to plant pathogens and medically relevant strains of Escherichia coli, Legionella pneumophila, Rickettsiae, Chlamydiae, and Salmonellae, in which the elaD ortholog sseL has recently been identified as a virulence factor with deubiquitinating activity. As a counterpoint, our phylogenetic and functional examination reveals that ancient eukaryotic ULP/SENP proteases also have the potential of ubiquitin-specific hydrolysis, suggesting an early common origin of this peptidase clan.

title: Bringing together emerging and endemic zoonoses surveillance: shared challenges and a common solution
abstract: Early detection of disease outbreaks in human and animal populations is crucial to the effective surveillance of emerging infectious diseases. However, there are marked geographical disparities in capacity for early detection of outbreaks, which limit the effectiveness of global surveillance strategies. Linking surveillance approaches for emerging and neglected endemic zoonoses, with a renewed focus on existing disease problems in developing countries, has the potential to overcome several limitations and to achieve additional health benefits. Poor reporting is a major constraint to the surveillance of both emerging and endemic zoonoses, and several important barriers to reporting can be identified: (i) a lack of tangible benefits when reports are made; (ii) a lack of capacity to enforce regulations; (iii) poor communication among communities, institutions and sectors; and (iv) complexities of the international regulatory environment. Redirecting surveillance efforts to focus on endemic zoonoses in developing countries offers a pragmatic approach that overcomes some of these barriers and provides support in regions where surveillance capacity is currently weakest. In addition, this approach addresses immediate health and development problems, and provides an equitable and sustainable mechanism for building the culture of surveillance and the core capacities that are needed for all zoonotic pathogens, including emerging disease threats.

title: Linking Statistics With Testing Policy to Manage COVID-19 in the Community
abstract: To determine the public health surveillance severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing volume needed, both for acute infection and seroprevalence.  Required testing volumes were developed using standard statistical methods based on test analytical performance, disease prevalence, desired precision, and population size.  Widespread testing for individual health management cannot address surveillance needs. The number of people who must be sampled for public health surveillance and decision making, although not trivial, is potentially in the thousands for any given population or subpopulation, not millions.  While the contributions of diagnostic testing for SARS-CoV-2 have received considerable attention, concerns abound regarding the availability of sufficient testing capacity to meet demand. Different testing goals require different numbers of tests and different testing strategies; testing strategies for national or local disease surveillance, including monitoring of prevalence, receive less attention. Our clinical laboratory and diagnostic infrastructure are capable of incorporating required volumes for many local, regional, and national public health surveillance studies into their current and projected testing capacity. However, testing for surveillance requires careful design and randomization to provide meaningful insights.

title: National Smoking Rates Correlate Inversely with COVID-19 Mortality
abstract: Recent studies show cigarette smokers are markedly under-represented among patients hospitalized for COVID-19 in over a dozen countries. It is unclear if this may be related to confounding factors such as age distribution, access to care, and inaccurate records. We hypothesized that these concerns could be avoided by studying smoking prevalence in relation to COVID-19 mortality. Since climate has been identified as a factor in COVID-19, we studied groups of countries with relatively comparable temperatures.  The 20 hottest and 20 coldest countries in the Johns Hopkins Mortality Analysis database with a minimum mortality rate of .3 deaths/100,000 were selected on the basis of the average temperatures of their largest city. Mortality rates were determined as of May 1, 2020 and correlated with national smoking rate adjusting for sex ratio, obesity, temperature, and elderly population.  A highly significant inverse correlation between current daily smoking prevalence and COVID-19 mortality rate was noted for the group of hot countries (R=-.718, p = .0002), cold countries (R=-.567, p=.0046), and the combined group (R=-.324, p=.0207). However, after adjustments only the regression for hot countries and the combined group remained significant. In hot countries, for each percentage point increase in smoking rate mortality decreased by .147 per 100,000 population (95% CI .102- 192, p=.0066). This resulted in mortality rates several-fold elevated in the countries with the lowest smoking rates relative to the highest smoking rates. In the combined group, mortality decreased by .257 per 100,000 population (95% CI .175-.339, p=.0034).  These findings add support to the finding of an inverse relationship between current smoking and seriously symptomatic COVID-19. However, we conclude that the difference in mortality between the highest and lowest smoking countries appears too large to be due primarily to the effects of smoking per se. A potentially beneficial effect of smoking is surprising, but compatible with a number of hypothetical mechanisms which deserve exploration: 1) Studies show smoking alters ACE2 expression which may affect COVID-19 infection or its progression to serious lung pathology. 2) Nicotine has anti-inflammatory activity and also appears to alter ACE2 expression. 3) Nitric oxide in cigarette smoke is known to be effective in treating pulmonary hypertension and has shown in vitro antiviral effects including against SARS-CoV-2. 4) Smoking has complicated effects on the immune system involving both up and down regulation, any of which might alone or in concert antagonize progression of COVID-19. 5) Smokers are exposed to hot vapors which may stimulate immunity in the respiratory tract by various heat-related mechanisms (e.g. heat shock proteins). Studies of steam and sauna treatments have shown efficacy in other viral respiratory conditions. At this time there is no clear evidence that smoking is protective against COVID-19, so the established recommendations to avoid smoking should be emphasized. The interaction of smoking and COVID-19 will only be reliably determined by carefully designed prospective study, and there is reason to believe that there are unknown confounds that may be spuriously suggesting a protective effect of smoking. However, the magnitude of the apparent inverse association of COVID-19 and smoking and its myriad clinical implications suggest the importance of further investigation.

title: Spatiotemporal evolution of coronavirus disease 2019 mortality in Brazil in 2020

title: Novel coronavirus: From discovery to clinical diagnostics
abstract: A novel coronavirus designated as 2019-nCoV first appeared in Wuhan, China in late December 2019. Dozens of people died in China, and thousands of people infected as 2019-nCoV continues to spread around the world. We have described the discovery, emergence, genomic characteristics, and clinical diagnostics of 2019-nCoV.

title: [Diagnosis and clinical management of 2019 novel coronavirus infection: an operational recommendation of Peking Union Medical College Hospital (V2.0)].
abstract: Since December 2019, China has been experiencing an outbreak of new infectious disease caused by 2019 novel coronavirus (2019-nCoV). The clinical features include fever, coughing, shortness of breath, and inflammatory pulmonary infiltration revealed by X ray. China rapidly identified 2019-nCoV-related pneumonia a statutory infectious disease. To standardize the diagnosis and treatment of this new infectious disease, operational guidelines for the diagnosis and management of 2019-nCoV infection is accomplished by Peking Union Medical College Hospital.

title: Stop playing with data: there is no sound evidence that Bacille Calmette-Guérin may avoid SARS-CoV-2 infection (for now).
abstract: Since the beginning of the COVID-19 epidemic, a possible explanation for the high heterogeneity of infection/mortality rates across involved countries was hinted in the prevalence of tuberculosis vaccination with Bacille Calmette-Guérin (BCG). A systematic review was therefore performed on May 2, 2020. A total of 13 articles were ultimately retrieved, 12 of them as preprint papers. All articles were ecological studies of low quality. Most of them did not include main confounding factors (i.e. demographic of the assessed countries, share of peo- ple residing in urban settings, etc.), and simply assessed the differences among incidence/mortality of COVID-19 with vaccination rates or by having vs. having not any vaccination policy for BCG. Even though all studies shared the very same information sources (i.e. international registries for BCG vaccination rates and open source data for COVID-19 epidemics), results were conflicting, with later studies apparently denying any true correlation between COVID-19 occurrence and BCG vaccination rates and/or policies. As a consequence, there is no sound evidence to recommend BCG vaccination for the prevention of COVID-19.

title: The Estimated Time-Varying Reproduction Numbers during the Ongoing Pandemic of the Coronavirus Disease 2019 (COVID-19) in 12 Selected Countries outside China
abstract: How can we anticipate the progression of the ongoing pandemic of the coronavirus disease 2019 (COVID-19)? As a measure of transmissibility, we aimed to estimate concurrently the time-varying reproduction number, R0(t), over time during the COVID-19 pandemic for each of the following 12 heavily-attacked countries: Singapore, South Korea, Japan, Iran, Italy, Spain, Germany, France, Belgium, United Kingdom, the United States of America, and South Africa.  We downloaded the publicly available COVID-19 pandemic data from the WHO COVID-19 Dashboard website (https://covid19.who.int/) for the duration of January 11, 2020 and May 1, 2020. Then, we specified two plausible distributions of serial interval to apply the novel estimation method implemented in the incidence and EpiEstim packages to the data of daily new confirmed cases for robustly estimating R0(t) in the R software.  We plotted the epidemic curves of daily new confirmed cases for the 12 selected countries. A clear peak of the epidemic curve appeared in 10 of the 12 selected countries at various time points, and then the epidemic curve declined gradually. However, the United States of America and South Africa happened to have two or more peaks and their epidemic curves either reached a plateau or still climbed up. Almost all curves of the estimated R0(t) monotonically went down to be less than or close to 1.0 up to April 30, 2020 except Singapore, South Korea, Japan, Iran, and South Africa, of which the curves surprisingly went up and down at various time periods during the COVID-19 pandemic. Finally, the United States of America and South Africa were the two countries with the approximate R0(t) [≥] 1.0 at the end of April, and thus they were now facing the harshest battles against the coronavirus among the 12 selected countries. By contrast, Spain, Germany, and France with smaller values of the estimated R0(t) were relatively better than the other 9 countries.  Seeing the estimated R0(t) going downhill speedily is more informative than looking for the drops in the daily number of new confirmed cases during an ongoing epidemic of infectious disease. We urge public health authorities and scientists to estimate R0(t) routinely during an epidemic of infectious disease and to report R0(t) daily to the public until the end of the epidemic.

title: Optimising SARS-CoV-2 pooled testing for low-resource settings

title: Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study
abstract: Coronavirus disease 2019 (COVID-19) causes severe community and nosocomial outbreaks. Comprehensive data for serial respiratory viral load and serum antibody responses from patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are not yet available. Nasopharyngeal and throat swabs are usually obtained for serial viral load monitoring of respiratory infections but gathering these specimens can cause discomfort for patients and put health-care workers at risk. We aimed to ascertain the serial respiratory viral load of SARS-CoV-2 in posterior oropharyngeal (deep throat) saliva samples from patients with COVID-19, and serum antibody responses.  We did a cohort study at two hospitals in Hong Kong. We included patients with laboratory-confirmed COVID-19. We obtained samples of blood, urine, posterior oropharyngeal saliva, and rectal swabs. Serial viral load was ascertained by reverse transcriptase quantitative PCR (RT-qPCR). Antibody levels against the SARS-CoV-2 internal nucleoprotein (NP) and surface spike protein receptor binding domain (RBD) were measured using EIA. Whole-genome sequencing was done to identify possible mutations arising during infection.  Between Jan 22, 2020, and Feb 12, 2020, 30 patients were screened for inclusion, of whom 23 were included (median age 62 years [range 37–75]). The median viral load in posterior oropharyngeal saliva or other respiratory specimens at presentation was 5·2 log10 copies per mL (IQR 4·1–7·0). Salivary viral load was highest during the first week after symptom onset and subsequently declined with time (slope −0·15, 95% CI −0·19 to −0·11; R 2=0·71). In one patient, viral RNA was detected 25 days after symptom onset. Older age was correlated with higher viral load (Spearman's ρ=0·48, 95% CI 0·074–0·75; p=0·020). For 16 patients with serum samples available 14 days or longer after symptom onset, rates of seropositivity were 94% for anti-NP IgG (n=15), 88% for anti-NP IgM (n=14), 100% for anti-RBD IgG (n=16), and 94% for anti-RBD IgM (n=15). Anti-SARS-CoV-2-NP or anti-SARS-CoV-2-RBD IgG levels correlated with virus neutralisation titre (R 2>0·9). No genome mutations were detected on serial samples.  Posterior oropharyngeal saliva samples are a non-invasive specimen more acceptable to patients and health-care workers. Unlike severe acute respiratory syndrome, patients with COVID-19 had the highest viral load near presentation, which could account for the fast-spreading nature of this epidemic. This finding emphasises the importance of stringent infection control and early use of potent antiviral agents, alone or in combination, for high-risk individuals. Serological assay can complement RT-qPCR for diagnosis.

title: Identification of potential vaccine candidates against SARS-CoV-2, A step forward to fight novel coronavirus 2019-nCoV: A Reverse Vaccinology Approach
abstract: The recent Coronavirus Disease 2019 (COVID-19) causes an immense health crisis to global public health. The World Health Organization (WHO) declared the COVID-19 as a pandemic. The COVID-19 is the etiologic agent of a recently arose disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Presently, there is no vaccine available against this emerged viral disease. Therefore, it is indeed a need of the hour to develop an effectual and safe vaccine against this decidedly pandemic disease. In the current study, we collected SARS-CoV-2 genome from Indian geographical origin against human host, further more using reverse vaccinology and immunoinformatics tools here we claim effective vaccine candidates that can be mile stone in battle against COVID19. This novel study divulged two promising antigenic peptide GVYFASTEK and NFRVQPTESIV from surface glycoproteins (protein accession no. – QIA98583.1 and QHS34546.1) of SARS-CoV-2, which were predicated to be interacted with class I and class II MHC alleles and showed up to 90% conservancy and high value of antigenicity. Subsequently, the molecular docking studies were verified molecular interaction of these prime antigenic peptides with the residues of HLA-A*11-01 allele for MHC Class I and HLA DRB1*04-01 allele for MHC class II. After vigorous analysis, these peptides were predicted to be suitable epitopes which are capable to elicit the strong cell-mediated immune response against the SARS-CoV-2. Consequences from the present study could facilitate selecting SARS-CoV-2 epitopes for vaccine production pipelines in the immediate future. This novel research will certainly pave the way for a fast, reliable and virtuous platform to provide timely countermeasure of this dangerous pandemic disease, COVID-19.

title: Simulation-based Estimation of the Spread of COVID-19 in Iran
abstract: The 2019 Coronavirus (COVID-19) has turned into a global pandemic with unprecedented challenges for the global community. Understanding the state of the disease and planning for future trajectories relies heavily on data on the spread and mortality. Yet official data coming from various countries are highly unreliable: symptoms similar to common cold in majority of cases and limited screening resources and delayed testing procedures may contribute to under-estimation of the burden of disease. Anecdotal and more limited data are available, but few have systematically combined those with official statistics into a coherent view of the epidemic. This study is a modeling-in-real-time of the emerging outbreak for understanding the state of the disease. Our focus is on the case of the spread of disease in Iran, as one of the epicenters of the disease in the first months of 2020.  We develop a simple dynamic model of the epidemic to provide a more reliable picture of the state of the disease based on existing data. Building on the generic SEIR (Susceptible, Exposed, Infected, and Recovered) framework we incorporate two behavioral and logistical considerations. First we capture the endogenous changes in contact rate (average contact per person) as more death are reported. As a result the reproduction number changes endogenously in the model. Second we differentiate reported and true cases by including simple formulations for how only a fraction of cases might be diagnosed, and how that fraction changes in response to epidemic's progression. In estimating the model we use both the official data as well as the discovered infected travelers and unofficial medical community estimates and triangulate these sources to build a more complete picture. Calibration is completed by forming a likelihood function for observing the actual time series data conditional on model parameters, and conducting a Markov Chain Monte Carlo simulations. The model is used to estimate current "true" cases of infection and death. We analyze the future trajectory of the disease under six conditions related to the seasonal effects and policy measures targeting social distancing.  The model closely replicates the past data but also shows the true number of cases is likely far larger. We estimate about 493,000 current infected cases (90% CI: 271K-810K) as of March 20th, 2020. Our estimate for cumulative cases of infection until that date is 916,000 (90% CI: 508K, 1.5M), and for total death is 15,485 (90% CI: 8.4K, 25.8K). These numbers are significantly (more than one order of magnitude) higher than official statistics. The trajectory of the epidemic until the end of June could take various paths depending on the impact of seasonality and policies targeting social distancing. In the most optimistic scenario for seasonal effects, depending on policy measures, 1.6 million Iranians (90% CI: 0.9M-2.6M) are likely to get infected, and death toll will reach about 58,000 cases (90% CI: 32K-97K), while in the more pessimistic scenarios, death toll may exceed 103,000 cases (90% CI: 56K-172K).  Our results suggest that the number of cases and deaths may be over an order of magnitude larger than official statistics in Iran. Absent extended testing capacity other countries may face a significant under-count of existing cases and thus be caught off guard about the actual toll of the epidemic.

title: Infection Density and Epidemic Size of COVID-19 in China outside the Hubei province
abstract: The novel coronavirus (COVID-19) has spread to almost all countries in the world, claiming more than 160,000 lives and sickening more than 2,400,000 people by April 21, 2020. There has been research showing that on average, each infected person spreads the infection to more than two persons. Therefore the majority of the population is at risk of infection if no intervention measures were undertaken. The true size of the COVID-19 epidemic remains unknown, as a significant proportion of infected individuals only exhibit mild symptoms or are even asymptomatic. A timely assessment of the evolving epidemic size is crucial for resource allocation and triage decisions. In this article, we modify the back-calculation algorithm to obtain a lower bound estimate of the number of COVID-19 infected persons in China outside the Hubei province. We estimate the infection density among infected and show that the drastic control measures enforced throughout China following the lockdown of Wuhan City effectively slowed down the spread of the disease in two weeks. Our findings from China are expected to provide guidelines and enlightenment for surveillance and control activities of COVID-19 in other countries around the world.

title: Global research trends of World Health Organization’s top eight emerging pathogens
abstract: On December 8(th), 2015, World Health Organization published a priority list of eight pathogens expected to cause severe outbreaks in the near future. To better understand global research trends and characteristics of publications on these emerging pathogens, we carried out this bibliometric study hoping to contribute to global awareness and preparedness toward this topic.  Scopus database was searched for the following pathogens/infectious diseases: Ebola, Marburg, Lassa, Rift valley, Crimean-Congo, Nipah, Middle Eastern Respiratory Syndrome (MERS), and Severe Respiratory Acute Syndrome (SARS). Retrieved articles were analyzed to obtain standard bibliometric indicators.  A total of 8619 journal articles were retrieved. Authors from 154 different countries contributed to publishing these articles. Two peaks of publications, an early one for SARS and a late one for Ebola, were observed. Retrieved articles received a total of 221,606 citations with a mean ± standard deviation of 25.7 ± 65.4 citations per article and an h-index of 173. International collaboration was as high as 86.9%. The Centers for Disease Control and Prevention had the highest share (344; 5.0%) followed by the University of Hong Kong with 305 (4.5%). The top leading journal was Journal of Virology with 572 (6.6%) articles while Feldmann, Heinz R. was the most productive researcher with 197 (2.3%) articles. China ranked first on SARS, Turkey ranked first on Crimean-Congo fever, while the United States of America ranked first on the remaining six diseases. Of retrieved articles, 472 (5.5%) were on vaccine – related research with Ebola vaccine being most studied.  Number of publications on studied pathogens showed sudden dramatic rise in the past two decades representing severe global outbreaks. Contribution of a large number of different countries and the relatively high h-index are indicative of how international collaboration can create common health agenda among distant different countries.

title: Increasing testing throughput and case detection with a pooled-sample Bayesian approach in the context of COVID-19
abstract: Rapid and widespread implementation of infectious disease surveillance is a critical component in the response to novel health threats. Molecular assays are the preferred method to detect a broad range of pathogens with high sensitivity and specificity. The implementation of molecular assay testing in a rapidly evolving public health emergency can be hindered by resource availability or technical constraints. In the context of the COVID-19 pandemic, the applicability of a pooled-sample testing protocol to screen large populations more rapidly and with limited resources is discussed. A Bayesian inference analysis in which hierarchical testing stages can have different sensitivities is implemented and benchmarked against early COVID-19 testing data. Optimal pool size and increases in throughput and case detection are calculated as a function of disease prevalence. Even for moderate losses in test sensitivity upon pooling, substantial increases in testing throughput and detection efficiency are predicted, suggesting that sample pooling is a viable avenue to circumvent current testing bottlenecks for COVID-19.

title: Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics
abstract: In December 2019, a new virus (initially called ‘Novel Coronavirus 2019-nCoV’ and later renamed to SARS-CoV-2) causing severe acute respiratory syndrome (coronavirus disease COVID-19) emerged in Wuhan, Hubei Province, China, and rapidly spread to other parts of China and other countries around the world, despite China’s massive efforts to contain the disease within Hubei. As with the original SARS-CoV epidemic of 2002/2003 and with seasonal influenza, geographic information systems and methods, including, among other application possibilities, online real-or near-real-time mapping of disease cases and of social media reactions to disease spread, predictive risk mapping using population travel data, and tracing and mapping super-spreader trajectories and contacts across space and time, are proving indispensable for timely and effective epidemic monitoring and response. This paper offers pointers to, and describes, a range of practical online/mobile GIS and mapping dashboards and applications for tracking the 2019/2020 coronavirus epidemic and associated events as they unfold around the world. Some of these dashboards and applications are receiving data updates in near-real-time (at the time of writing), and one of them is meant for individual users (in China) to check if the app user has had any close contact with a person confirmed or suspected to have been infected with SARS-CoV-2 in the recent past. We also discuss additional ways GIS can support the fight against infectious disease outbreaks and epidemics.

title: COVID-19: A promising cure for the global panic
abstract: The novel Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, which is the causative agent of a potentially fatal disease that is of great global public health concern. The outbreak of COVID-19 is wreaking havoc worldwide due to inadequate risk assessment regarding the urgency of the situation. The COVID-19 pandemic has entered a dangerous new phase. When compared with SARS and MERS, COVID-19 has spread more rapidly, due to increased globalization and adaptation of the virus in every environment. Slowing the spread of the COVID-19 cases will significantly reduce the strain on the healthcare system of the country by limiting the number of people who are severely sick by COVID-19 and need hospital care. Hence, the recent outburst of COVID-19 highlights an urgent need for therapeutics targeting SARS-CoV-2. Here, we have discussed the structure of virus; varying symptoms among COVID-19, SARS, MERS and common flu; the probable mechanism behind the infection and its immune response. Further, the current treatment options, drugs available, ongoing trials and recent diagnostics for COVID-19 have been discussed. We suggest traditional Indian medicinal plants as possible novel therapeutic approaches, exclusively targeting SARS-CoV-2 and its pathways.

title: Comorbid Diabetes Mellitus was Associated with Poorer Prognosis in Patients with COVID-19: A Retrospective Cohort Study
abstract: The 2019 novel coronavirus disease (COVID-19) emerged in Wuhan, Hubei province, China, and was characterized as pandemic by the World Health Organization. Diabetes mellitus is an established risk factor for poor clinical outcomes, but the association of diabetes with the prognosis of COVID-19 have not been reported yet.  In this cohort study, we retrospectively reviewed 258 consecutive hospitalized COVID-19 patients with or without diabetes at the West Court of Union Hospital of Huazhong University of Science and Technology in Wuhan, China, recruited from January 29 to February 12, 2020. The cases were confirmed by real-time PCR and the demographic, clinical, laboratory, radiological, and treatment data were collected and analyzed. Prognosis was defined as hospitalization, discharged survivor and death, which was followed up until March 12, 2020.  Of the 258 hospitalized patients (63 with diabetes) with COVID-19, the median age was 64 years (range 23-91), and 138 (53.5%) were male. No significant differences in age and sex were identified between patients with and without diabetes. Common symptoms included fever (82.2%), dry cough (67.1%), polypnea (48.1%), and fatigue (38%). Patients with diabetes had significantly higher leucocyte and neutrophil counts, and higher levels of fasting blood glucose, serum creatinine, urea nitrogen and creatine kinase isoenzyme MB at admission compared with those without diabetes. COVID-19 patients with diabetes were more likely to develop severe or critical disease condition with more complications at presentation, and had higher incidence rates of antibiotic therapy, non-invasive and invasive mechanical ventilation, and death (11.1% vs. 4.1%). Cox proportional hazard model showed that diabetes (adjusted hazard ratio [aHR]=3.64; 95% confidence interval [CI]: 1.09, 12.21) and fasting blood glucose (aHR=1.19; 95% CI: 1.08, 1.31) were associated with the fatality of COVID-19, adjusting for potential confounders.  Diabetes mellitus is associated with greater disease severity and a higher risk of mortality in patients with COVID-19. Primary and secondary prevention strategies are needed for COVID-19 patients with diabetes.

title: Crude incidence in two-phase designs in the presence of competing risks
abstract: In many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies. Common examples include the nested case-control and the case-cohort designs. For two-phase studies, appropriate weighted survival estimates have been derived; however, no estimator of cumulative incidence accounting for competing events has been proposed. This is relevant in the presence of multiple types of events, where estimation of event type specific quantities are needed for evaluating outcome.  We develop a non parametric estimator of the cumulative incidence function of events accounting for possible competing events. It handles a general sampling design by weights derived from the sampling probabilities. The variance is derived from the influence function of the subdistribution hazard.  The proposed method shows good performance in simulations. It is applied to estimate the crude incidence of relapse in childhood acute lymphoblastic leukemia in groups defined by a genotype not available for everyone in a cohort of nearly 2000 patients, where death due to toxicity acted as a competing event. In a second example the aim was to estimate engagement in care of a cohort of HIV patients in resource limited setting, where for some patients the outcome itself was missing due to lost to follow-up. A sampling based approach was used to identify outcome in a subsample of lost patients and to obtain a valid estimate of connection to care.  A valid estimator for cumulative incidence of events accounting for competing risks under a general sampling design from an infinite target population is derived.

title: Novel Screening and Triage Strategy in Iran During Deadly Coronavirus Disease 2019 (COVID-19) Epidemic: Value of Humanitarian Teleconsultation Service

title: The close relationship between sudden loss of smell and COVID-19
abstract: The real number of COVID-19 cases may be underestimated since several countries have difficulty offering laboratory tests for all the population. Therefore, finding a symptom with a high predictive value would help in diagnostic and isolation strategies.  To correlate the sudden loss of the sense of smell in the context of the COVID-19 pandemic with results of diagnostic tests for COVID-19.  This is a cross-sectional observational study. An online questionnaire was digitally addressed to 725 outpatients in Brazil who reported partial or total sudden loss of the sense of smell from March to April 2020.  Total or partial sudden loss of the sense of smell showed high Positive Predictive Value (PPV) for COVID-19 diagnosis, during the COVID-19 pandemic in Brazil (88.8%). There were no differences between groups tested positive and negative in regard to demographic and clinical characteristics such as presence of allergy, rhinitis, neither to olfactory recovery time.  The identification of sudden loss of the sense of smell during COVID-19 pandemic may serve as a sentinel symptom and may be a warning to establish measures to prevent the transmission of the disease.

title: Chapter 8 The Middle East Respiratory Syndrome Coronavirus: An Emerging Virus of Global Threat
abstract: Middle East respiratory syndrome (MERS) is a viral respiratory illness caused by a coronavirus (CoV), first identified in Saudi Arabia in 2012. Since then, almost 2000 cases have been reported from 27 countries, with Saudi Arabia being the epicenter. This newly emerging virus is highly pathogenic and has a case mortality rate of 35%. It is similar to the CoV causing severe acute respiratory syndrome CoV (SARS-CoV) in that both belong to the genus beta CoVs that are of zoonotic origin and cause lower respiratory infection. The natural reservoir for MERS-CoV remains unknown. Serological studies indicate that most dromedary camels in the Middle East have been infected with this virus, and they maybe the potential intermediate host. However, the mode of transmission from camels to humans is poorly understood. The majority of confirmed human cases have resulted from human-to-human transmission, most probably via respiratory route. Patients most at risk of developing severe MERS-CoV infection appear to be those with underlying conditions such as diabetes, hypertension, obesity, cardiac diseases, chronic respiratory diseases, and cancer. Unlike SARS-CoV, MERS-CoV is considered an ongoing public health problem, particularly for the Middle East region. In this chapter, we outline the prevailing information regarding the emergence and epidemiology of this virus, its mode of transmission and pathogenicity, its clinical features, and the potential strategies for prevention.

title: Concerns and Fears of Indian Dentists on Professional Practice During the Coronavirus Disease‐2019 (COVID‐19) Pandemic
abstract: The Coronavirus disease‐2019 (COVID‐19) pandemic, due to the Severe Acute Respiratory Syndrome Virus 2 (SARS‐CoV‐2) was declared a public health emergency of international concern by the World Health Organization on 30(th) of January 2020 (World Health Organization, 2020). The first case of COVID‐19 was reported in India on the same day, and at the time of writing, on 20(th) May 2020, India has reported over 106,000 patients, with over 3,300 related deaths. The country is under a state of lockdown since 25(th) March, 2020, and over 600 health care providers have been infected.

title: Microbiology
abstract: The management and containment of many treatable and preventable infectious diseases in resource-poor countries is limited by the failure to make an accurate diagnosis. Most of the world's population lacks access to accurate, affordable, easy-to-use, quality-assured, reliable, and accessible diagnostic tests and misdiagnosis of infectious diseases is common and compromises patient care. Laboratory diagnostics are also needed for the detection and surveillance of the increasing levels of antimicrobial resistance. Accurate clinical diagnosis in resource-poor settings relies strongly on the laboratory service, and the need to support the development of a quality-assured laboratory service in such settings is increasingly recognized. International organizations are actively working with local and national providers to improve laboratory services. The development of laboratory services will contribute to improved health for the local population, protection against emerging pathogens, and ensure better use of scarce health care resources.

title: A case report of neonatal COVID-19 infection in China
abstract: In December 2019, the 2019 novel coronavirus disease (COVID-19) caused by SARS-CoV-2 emerged in China and now has spread in many countries. Pregnant women are susceptible population of COVID-19 which are more likely to have complications and even progresse to severe illness. We report a case of neonatal COVID-19 infection in China with pharyngeal swabs tested positive by rRT-PCR assay 36 hours after birth. However, whether the case is a vertical transmission from mother to child remains to be confirmed.

title: The first confirmed case of COVID-19 in Tanzania: recommendations based on lesson learned from China
abstract: As the coronavirus disease (COVID-19) takes its course outside China, the number of imported cases to other countries is on the rise. Currently, Tanzania has received the first imported case on 16 March 2020. This letter serves to describe this specific event and put forth a number of recommendations including establishing more testing points, discouraging all forms of public and religious gatherings, and tailoring a unique model for lockdown and social distancing to prevent further spread of the disease. The letter has also suggested ways to further improve the efforts already in place so as to strengthen the prevention and control system.

title: Abstracts of the XX World Allergy Congress™ 2007 December 2-6, 2007, Bangkok, Thailand

title: Data-Based Analysis, Modelling and Forecasting of the COVID-19 outbreak
abstract: Since the first suspected case of coronavirus disease-2019 (COVID-19) on December 1st, 2019, in Wuhan, Hubei Province, China, a total of 40,235 confirmed cases and 909 deaths have been reported in China up to February 10, 2020, evoking fear locally and internationally. Here, based on the publicly available epidemiological data for Hubei, China from January 11 to February 10, 2020, we provide estimates of the main epidemiological parameters. In particular, we provide an estimation of the case fatality and case recovery ratios, along with their 90% confidence intervals as the outbreak evolves. On the basis of a Susceptible-Infected-Recovered-Dead (SIDR) model, we provide estimations of the basic reproduction number (R0), and the per day infection mortality and recovery rates. By calibrating the parameters of the SIRD model to the reported data, we also attempt to forecast the evolution of the of the outbreak at the epicenter three weeks ahead, i.e. until February 29. As the number of infected individuals, especially of those with asymptomatic or mild courses, is suspected to be much higher than the official numbers, which can be considered only as a subset of the actual numbers of infected and recovered cases in the total population, we have repeated the calculations under a second scenario that considers twenty times the number of confirmed infected cases and forty times the number of recovered, leaving the number of deaths unchanged. Based on the reported data, the expected value of R0 as computed considering the period from the 11th of January until the 18th of January, using the official counts of confirmed cases was found to be ~4.6, while the one computed under the second scenario was found to be ~3.2. Thus, based on the SIRD simulations, the estimated average value of R0 was found to be ~2.6 based on confirmed cases and ~2 based on the second scenario. Our forecasting flashes a note of caution for the presently unfolding outbreak in China. Based on the official counts for confirmed cases, the simulations suggest that the cumulative number of infected could reach 180,000 (with lower bound of 45,000) by February 29. Regarding the number of deaths, simulations forecast that on the basis of the up to the 10th of February reported data, the death toll might exceed 2,700 (as a lower bound) by February 29. Our analysis further reveals a significant decline of the case fatality ratio from January 26 to which various factors may have contributed, such as the severe control measures taken in Hubei, China (e.g. quarantine and hospitalization of infected individuals), but mainly because of the fact that the actual cumulative numbers of infected and recovered cases in the population most likely are much higher than the reported ones. Thus, in a scenario where we have taken twenty times the confirmed number of infected and forty times the confirmed number of recovered cases, the case fatality ratio is around 0.15% in the total population. Importantly, based on this scenario, simulations suggest a slow down of the outbreak in Hubei at the end of February.

title: Identification of New Respiratory Viruses in the New Millennium
abstract: The rapid advancement of molecular tools in the past 15 years has allowed for the retrospective discovery of several new respiratory viruses as well as the characterization of novel emergent strains. The inability to characterize the etiological origins of respiratory conditions, particularly in children, led several researchers to pursue the discovery of the underlying etiology of disease. In 2001, this led to the discovery of human metapneumovirus (hMPV) and soon following that the outbreak of Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) promoted an increased interest in coronavirology and the latter discovery of human coronavirus (HCoV) NL63 and HCoV-HKU1. Human bocavirus, with its four separate lineages, discovered in 2005, has been linked to acute respiratory tract infections and gastrointestinal complications. Middle East Respiratory Syndrome coronavirus (MERS-CoV) represents the most recent outbreak of a completely novel respiratory virus, which occurred in Saudi Arabia in 2012 and presents a significant threat to human health. This review will detail the most current clinical and epidemiological findings to all respiratory viruses discovered since 2001.

title: Early forecasts of the evolution of the COVID-19 outbreaks and quantitative assessment of the effectiveness of countering measures.
abstract: We discovered that the time evolution of the inverse fractional daily growth of new infections, N/dN, in the current outbreak of COVID-19 is accurately described by a universal function, namely the two-parameter Gumbel cumulative function, in all countries that we have investigated. While the two Gumbel parameters, as determined bit fits to the data, vary from country to country (and even within different regions of the same country), reflecting the diversity and efficacy of the adopted containment measures, the functional form of the evolution of N/dN appears to be universal. The result of the fit in a given region or country appears to be stable against variations of the selected time interval. This makes it possible to robustly estimate the two parameters from the data data even over relatively small time periods. In turn, this allows one to predict with large advance and well-controlled confidence levels, the time of the peak in the daily new infections, its magnitude and duration (hence the total infections), as well as the time when the daily new infections decrease to a pre-set value (e.g. less than about 2 new infections per day per million people), which can be very useful for planning the reopening of economic and social activities. We use this formalism to predict and compare these key features of the evolution of the COVID-19 disease in a number of countries and provide a quantitative assessment of the degree of success in in their efforts to countain the outbreak.

title: The serial interval of COVID-19 from publicly reported confirmed cases
abstract: We estimate the distribution of serial intervals for 468 confirmed cases of COVID-19 reported in 93 Chinese cities by February 8, 2020. The mean and standard deviation are 3.96 (95% CI 3.53–4.39) and 4.75 (95% CI 4.46–5.07) days, respectively, with 12.6% of reports indicating pre-symptomatic transmission.

title: Current status of treatment for 2019 novel coronavirus pneumonia/ 中华微生物学和免疫学杂志
abstract: 2019 novel coronavirus (2019-nCoV) is a new member of coronavirus family that can cause serious respiratory diseases after the emergence of severe acute respiratory syndrome-coronavirus (SARS-CoV) and middle east respiratory syndrome-coronavirus (MERS-CoV). At present, there is no specific antiviral drug targeting 2019-nCoV. In facing of the increasingly serious epidemic of 2019 novel coronavirus pneumonia and the urgent needs in drug treatment strategies, this paper reviewed the current research situation and progress in antiviral treatment for the newly identified disease.

title: Evaluation of COVID-19 RT-qPCR test in multi-sample pools
abstract: The recent emergence of SARS-CoV-2 lead to a current pandemic of unprecedented levels. Though diagnostic tests are fundamental to the ability to detect and respond, many health systems are already experiencing shortages of reagents associated with this test. Here, testing a pooling approach for the standard RT-qPCR test, we find that a single positive sample can be detected even in pools of up to 32 samples, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, though may require additional amplification cycles. As it uses the standard protocols, reagents and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for COVID-19 would allow expanding current screening capacities thereby enabling the expansion of detection in the community, as well as in close integral groups, such as hospital departments, army units, or factory shifts.

title: Incidence, Etiology, and Outcomes of Community-Acquired Pneumonia: A Population-Based Study
abstract: The microbial etiology of community-acquired pneumonia (CAP) is often unclear in clinical practice, and previous studies have produced variable results. Population-based studies examining etiology and incidence are lacking. This study examined the incidence and etiology of CAP requiring hospitalization in a population-based cohort as well as risk factors and outcomes for specific etiologies.  Consecutive admissions due to CAP in Reykjavik, Iceland were studied. Etiologic testing was performed with cultures, urine-antigen detection, and polymerase chain reaction analysis of airway samples. Outcomes were length of stay, intensive care unit admission, assisted ventilation, and mortality.  The inclusion rate was 95%. The incidence of CAP requiring hospitalization was 20.6 cases per 10000 adults/year. A potential pathogen was detected in 52% (164 of 310) of admissions and in 74% (43 of 58) with complete sample sets. Streptococcuspneumoniae was the most common pathogen (61 of 310, 20%; incidence: 4.1/10000). Viruses were identified in 15% (47 of 310; incidence: 3.1/10000), Mycoplasmapneumoniae were identified in 12% (36 of 310; incidence: 2.4/10000), and multiple pathogens were identified in 10% (30 of 310; incidence: 2.0/10000). Recent antimicrobial therapy was associated with increased detection of M pneumoniae (P < .001), whereas a lack of recent antimicrobial therapy was associated with increased detection of S pneumoniae (P = .02). Symptoms and outcomes were similar irrespective of microbial etiology.  Pneumococci, M pneumoniae, and viruses are the most common pathogens associated with CAP requiring hospital admission, and they all have a similar incidence that increases with age. Symptoms do not correlate with specific agents, and outcomes are similar irrespective of pathogens identified.

title: Coronavirus infections: Epidemiological, clinical and immunological features and hypotheses
abstract: Coronaviruses (CoVs) are a large family of enveloped, positive-strand RNA viruses. Four human CoVs (HCoVs), the non-severe acute respiratory syndrome (SARS)-like HCoVs (namely HCoV 229E, NL63, OC43, and HKU1), are globally endemic and account for a substantial fraction of upper respiratory tract infections. Non-SARS-like CoV can occasionally produce severe diseases in frail subjects but do not cause any major (fatal) epidemics. In contrast, SARS like CoVs (namely SARS-CoV and Middle-East respiratory syndrome coronavirus, MERS-CoV) can cause intense short-lived fatal outbreaks. The current epidemic caused by the highly contagious SARS-CoV-2 and its rapid spread globally is of major concern. There is scanty knowledge on the actual pandemic potential of this new SARS-like virus. It might be speculated that SARS-CoV-2 epidemic is grossly underdiagnosed and that the infection is silently spreading across the globe with two consequences: (i) clusters of severe infections among frail subjects could haphazardly occur linked to unrecognized index cases; (ii) the current epidemic could naturally fall into a low-level endemic phase when a significant number of subjects will have developed immunity. Understanding the role of paucisymptomatic subjects and stratifying patients according to the risk of developing severe clinical presentations is pivotal for implementing reasonable measures to contain the infection and to reduce its mortality. Whilst the future evolution of this epidemic remains unpredictable, classic public health strategies must follow rational patterns. The emergence of yet another global epidemic underscores the permanent challenges that infectious diseases pose and underscores the need for global cooperation and preparedness, even during inter-epidemic periods.

title: The deadly coronaviruses: The 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China
abstract: The 2019-nCoV is officially called SARS-CoV-2 and the disease is named COVID-19. This viral epidemic in China has led to the deaths of over 1800 people, mostly elderly or those with an underlying chronic disease or immunosuppressed state. This is the third serious Coronavirus outbreak in less than 20 years, following SARS in 2002–2003 and MERS in 2012. While human strains of Coronavirus are associated with about 15% of cases of the common cold, the SARS-CoV-2 may present with varying degrees of severity, from flu-like symptoms to death. It is currently believed that this deadly Coronavirus strain originated from wild animals at the Huanan market in Wuhan, a city in Hubei province. Bats, snakes and pangolins have been cited as potential carriers based on the sequence homology of CoV isolated from these animals and the viral nucleic acids of the virus isolated from SARS-CoV-2 infected patients. Extreme quarantine measures, including sealing off large cities, closing borders and confining people to their homes, were instituted in January 2020 to prevent spread of the virus, but by that time much of the damage had been done, as human-human transmission became evident. While these quarantine measures are necessary and have prevented a historical disaster along the lines of the Spanish flu, earlier recognition and earlier implementation of quarantine measures may have been even more effective. Lessons learned from SARS resulted in faster determination of the nucleic acid sequence and a more robust quarantine strategy. However, it is clear that finding an effective antiviral and developing a vaccine are still significant challenges. The costs of the epidemic are not limited to medical aspects, as the virus has led to significant sociological, psychological and economic effects globally. Unfortunately, emergence of SARS-CoV-2 has led to numerous reports of Asians being subjected to racist behavior and hate crimes across the world.

title: Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States
abstract: Detection of SARS-CoV-2 infections to date has relied heavily on RT-PCR testing. However, limited test availability, high false-negative rates, and the existence of asymptomatic or sub-clinical infections have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how influenza-like illness (ILI) outpatient surveillance data can be used to estimate the prevalence of SARS-CoV-2. We found a surge of non-influenza ILI above the seasonal average in March 2020 and showed that this surge correlated with COVID-19 case counts across states. If 1/3 of patients infected with SARS-CoV-2 in the US sought care, this ILI surge would have corresponded to more than 8.7 million new SARS-CoV-2 infections across the US during the three-week period from March 8 to March 28, 2020. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to have been doubling slower than every 4 days. Together these results suggest a conceptual model for the COVID-19 epidemic in the US characterized by rapid spread across the US with over 80% infected patients remaining undetected. We emphasize the importance of testing these findings with seroprevalence data and discuss the broader potential to use syndromic surveillance for early detection and understanding of emerging infectious diseases.

title: 2019 Novel Coronavirus can be detected in urine, blood, anal swabs and oropharyngeal swabs samples
abstract: We tested samples collected from nine patients diagnosed with coronavirus disease 2019 (COVID-19). The virus was found in urine, blood, anal swabs and oropharyngeal swabs. It is the first time for SARS-CoV-2 found in urine, though no urinary irritation was found.

title: Respiratory Illness and Allergy Related to Work and Home Environment among Commercial Pilots
abstract: The aim was to study associations between work and home environment and prevalence and incidence of respiratory health and a history of atopy in a 3-y cohort of commercial pilots. A questionnaire was mailed in 1997 to all pilots in a Scandinavian airline company (N = 622); 577 (93%) participated. The same questionnaire was sent to the participants 3 years later, 436 participated (76%). There were questions on asthma, respiratory symptoms and infections, allergies, the cabin environment, psychosocial environment and the home environment. Associations were analyzed by multiple logistic regression, calculating odds ratios (OR) with 95% confidence intervals (95%CI). The incidence of doctors’ diagnosed asthma and atopy were 2.4 and 16.6 per 1000 person years, respectively. Pilots changing type of flight during follow-up got more airway infections (OR = 11.27; 95% CI 2.39–53.14). Those reporting decreased work control (OR = 1.85; 95% CI 1.03–3.31 for 1 unit change) and those with environmental tobacco smoke (ETS) at home (OR = 3.73; 95% CI 1.09–12.83) had a higher incidence of atopy during follow up. Dampness or mould at home was associated with a higher prevalence of asthma symptoms (OR = 3.55; 95% CI 1.43–8.82) and airway infections (OR = 3.12 95% CI 1.27–7.68). Window pane condensation in winter at home, reported at baseline, was associated with increased incidence of asthma symptoms (OR = 4.14; 95% CI 1.32–12.97) and pilots living in newer buildings at baseline had a higher incidence of airway infections (OR = 5.23; 95% CI 1.43–19.10). In conclusion, lack of work control and ETS at home can be a risk factors for development of allergic symptoms in pilots. Window pane condensation at home can be a risk factor for incidence of asthma symptoms. Dampness and mould at home can be a risk factor for prevalence of asthma symptoms and airway infections and living in newer buildings can be a risk factor for incidence of airway infections.

title: Abstract Presentations from the AABB Annual Meeting San Diego, CA ctober 7‐10, 2017

title: Tabagisme et maladie à coronavirus 2019 (COVID-19)

title: Use of all cause mortality to quantify the consequences of covid-19 in Nembro, Lombardy: descriptive study
abstract: To quantify the impact of coronavirus disease 2019 (covid-19) on all cause mortality in Nembro, an Italian city severely affected by the covid-19 pandemic.  Descriptive study.  Nembro, in the Bergamo province of Lombardy, northern Italy.  Residents of Nembro.  Monthly all cause mortality between January 2012 and April 2020 (data to 11 April), number of confirmed deaths from covid-19 to 11 April 2020, and weekly absolute number of deaths between 1 January and 4 April across recent years by age group and sex.  Nembro had 11 505 residents as of 1 January 2020. Monthly all cause mortality between January 2012 and February 2020 fluctuated around 10 per 1000 person years, with a maximum of 21.5 per 1000 person years. In March 2020, monthly all cause mortality reached a peak of 154.4 per 1000 person years. For the first 11 days in April, this rate decreased to 23.0 per 1000 person years. The observed increase in mortality was driven by the number of deaths among older people (≥65 years), especially men. From the outbreak onset until 11 April 2020, only 85 confirmed deaths from covid-19 in Nembro were recorded, corresponding to about half of the 166 deaths from all causes observed in that period.  The study findings show how covid-19 can have a considerable impact on the health of a small community. Furthermore, the results suggest that the full implications of the covid-19 pandemic can only be completely understood if, in addition to confirmed deaths related to covid-19, consideration is also given to all cause mortality in a given region and time frame.

title: Estimation of Undetected Covid-19 Infections in India
abstract: While the number of detected COVID-19 infections are widely available, an understanding of the extent of undetected COVID- 19 cases is urgently needed for an effective tackling of the pandemic and as a guide to lifting the lockdown. The aim of this work is to estimate and predict the true number of COVID-19 (detected and undetected) infections in India for short to medium forecast horizons. In particular, using publicly available COVID-19 infection data upto 16th April 2020, we predict the true number of infections in India during and upto the end of the formal lockdown period (21st April 2020).  The high death rate observed in most COVID-19 hit countries is suspected to be a function of the undetected infections existing in the population. An estimate of the age weighted infection fatality rate (IFR) of the disease of 0.41%, specifically calculated by taking into account the age structure of Indian population, is already available in the literature. In addition, the recorded case fatality rate (CFR= 0.70%) of Kerala, the only state in India to report single digit new infections over the second week of April, is used as a second estimate of the IFR. These estimates are used to formulate a relationship between deaths recorded and the true number of infections. The estimated undetected and detected cases time series based on these two IFR estimates are then used to fit a discrete time multivariate infection model to predict the total infections at the end of the formal lockdown period.  In two consecutive fortnights during the lockdown, it was noted that the rise in detected infections has decreased by 2.7 times. For an IFR of 0.41%, the rise in undetected infections decreased by 3.2 times and the predicted number of total infections in India is 3.14 lakhs. While for an IFR of 0.70%, the rise in undetected cases decreased by 3.3 times and the total number of infections predicted on 21st April is 1.75 lakhs.  The behaviour of the undetected cases over time effectively illustrates the effects of lockdown and increased testing. From our estimates, it is found that the lockdown has brought down the undetected to detected cases ratio, and has consequently dampened the increase in the number of total cases. However, even though the rate of rise in total infections has fallen, the lifting of the lockdown should be done keeping in mind that 1.75 to 3 lakhs undetected cases will already exist in the population on 21st April.

title: Data From the COVID-19 Epidemic in Florida Suggest That Younger Cohorts Have Been Transmitting Their Infections to Less Socially Mobile Older Adults
abstract: We analyzed the daily incidence of newly reported COVID-19 cases among adults aged 20-39 years, 40-59 years, and 60 or more years in the sixteen most populous counties of the state of Florida from March 1 through June 27, 2020. In all 16 counties, an increase in reported COVID-19 case incidence was observed in all three age groups soon after the governor-ordered Full Phase 1 reopening went into effect. Trends in testing, hospitalization and mortality do not support the hypothesis that the observed increase in case incidence was merely the result of liberalization of testing criteria. Parameter estimates from a parsimonious two-group heterogeneous SIR model strongly support the hypothesis that younger persons, having first acquired their infections through increasing social contact with their peers, then transmitted their infections to older, less socially mobile individuals.

title: Maximizing the Calm Before the Storm: Tiered Surgical Response Plan for Novel Coronavirus (COVID-19)
abstract: The novel coronavirus (COVID-19) was first diagnosed in Wuhan, China in December 2019 and has now spread throughout the world, being verified by the World Health Organization as a Pandemic on March 11th. This had led to the calling of a national emergency on March 13th in the United States. Many hospitals, healthcare networks, and specifically Departments of Surgery are asking the same questions of how to cope and plan for surge capacity, personnel attrition, novel infrastructure utilization, and resource exhaustion. Herein, we present a tiered plan for surgical department planning based on incident command levels. This includes Acute Care Surgeon deployment (given their critical care training and vertically integrated position in the hospital), recommended infrastructure and transfer utilization, triage principles, and faculty, resident and advanced care practitioner deployment.

title: Inside China and COVID-19: Questions and answers

title: A systematic review of Anakinra, Tocilizumab, Sarilumab and Siltuximab for coronavirus-related infections
abstract: There is accumulating evidence for an overly activated immune response characterised by the release of pro-inflammatory cytokines in severe Covid-19. Suppression of the inflammatory response with immunomodulatory therapies may be a potential therapeutic strategy. We systematically review and assess the effectiveness of specific interleukin-1 and -6 inhibitors for the treatment of coronavirus-related infections.  Electronic databases, pre-print servers and clinical trial registries were searched to identify current and ongoing studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19 and other coronavirus related super infections. The co-primary outcome was time to hospital discharge (days) and severity on an ordinal scale measured at day 15.  Five retrospective studies (tocilizumab, two case series and two case reports; siltuximab, one case series) were shortlisted for inclusion, totalling 59 patients. All studies had a moderate or high risk of bias, with multiple limitations. Insufficient data and inter-study heterogeneity prevented meta-analysis. Primary outcomes were inconsistently reported but suggest many patients experienced an improvement in status seven days following therapy. The case fatality ratio (CFR) of patients with severe Covid-19 included in our review was 6.8%, a figure substantially lower than that estimated in non-interventional case series. Of the studies measuring IL-6, all reported elevated baseline levels. Twenty-five ongoing registered clinical trials exploring immunomodulatory agents in Covid-19 were identified, although inconsistency in participants and endpoints are noted.  Inhibition of IL-6 with tocilizumab and siltuximab requires further evaluation in managing the assumed hyperinflammatory response associated with severe Covid-19. These early data are considered hypothesis generating and justify the need for well-designed randomised clinical studies.

title: COVID-19: what has been learned and to be learned about the novel coronavirus disease
abstract: The outbreak of Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), has thus far killed over 3,000 people and infected over 80,000 in China and elsewhere in the world, resulting in catastrophe for humans. Similar to its homologous virus, SARS-CoV, which caused SARS in thousands of people in 2003, SARS-CoV-2 might also be transmitted from the bats and causes similar symptoms through a similar mechanism. However, COVID-19 has lower severity and mortality than SARS but is much more transmissive and affects more elderly individuals than youth and more men than women. In response to the rapidly increasing number of publications on the emerging disease, this article attempts to provide a timely and comprehensive review of the swiftly developing research subject. We will cover the basics about the epidemiology, etiology, virology, diagnosis, treatment, prognosis, and prevention of the disease. Although many questions still require answers, we hope that this review helps in the understanding and eradication of the threatening disease.

title: Coronavirus (COVID-19): ARIMA based time-series analysis to forecast near future
abstract: COVID-19, a novel coronavirus, is currently a major worldwide threat. It has infected more than a million people globally leading to hundred-thousands of deaths. In such grave circumstances, it is very important to predict the future infected cases to support prevention of the disease and aid in the healthcare service preparation. Following that notion, we have developed a model and then employed it for forecasting future COVID-19 cases in India. The study indicates an ascending trend for the cases in the coming days. A time series analysis also presents an exponential increase in the number of cases. It is supposed that the present prediction models will assist the government and medical personnel to be prepared for the upcoming conditions and have more readiness in healthcare systems.

title: Developing and financing neglected disease vaccines in our new era of “blue marble health” and the anthropocene epoch
abstract: New findings of widespread neglected diseases among the poor living in wealthy group of 20 (G20) economies and the concept of “blue marble health” offer innovative mechanisms for financing urgently new vaccines, especially for vector-borne neglected tropical diseases (NTDs). This approach could complement or parallel a recently suggested global vaccine development fund for pandemic threats.

title: COVID-19, Australia: Epidemiology Report 16 (Reporting week to 23:59 AEST 17 May 2020)
abstract: Confirmed cases in Australia notified up to 17 May 2020: notifications = 7,075; deaths = 100. The incidence of new cases of COVID-19 has reduced dramatically since a peak in mid-March. Social distancing measures, public health action and the reduction in international travel have likely been effective in slowing the spread of the disease, in the Australian community. Testing rates over the past week have increased markedly, with a continued very low proportion of people testing positive. These low rates of detection are indicative of low levels of COVID-19 transmission. It is important that testing rates and community adherence to public health measures remain high to support the continued suppression of the virus, particularly in vulnerable high-risk groups and settings. New cases of COVID-19 are currently being reported by by only some jurisdictions, albeit at relatively low rates. Although case numbers are low, new cases tend to still be a mix of overseas-acquired and locally-acquired infections. Most locally-acquired cases can be linked back to a known case or cluster. Although the proportion of locally-acquired cases has increased, the overall rate of new cases, regardless of place of acquisition, continues to decrease. The crude case fatality rate in Australia remains low (1.4%), compared with the WHO reported global rate (6.9%). The low case fatality rate is likely reflective of high case detection and high quality of health care services in Australia. Deaths from COVID-19 in Australia have occurred predominantly among the elderly and those with comorbidities, with no deaths occurring in those under 40 years. The highest rate of COVID-19 continues to be among people aged 60-79 years. One third of all cases in this age group have been associated with several outbreaks linked to cruise ships. The lowest rate of disease is in young children, a pattern reflected in international reports. Internationally, while the number of new cases each day remains relatively stable at the global level, some areas such as Brazil and India are showing a dramatic rise in reported cases. Although some low-income countries have so far reported few cases, it is possible that this is due to limited diagnostic and public health capacity, and may not be reflective of true disease incidence.

title: Social and administrative issues related to the COVID-19 pandemic in Pakistan: better late than never
abstract: The study critically reviewed Pakistan’s provincial updates of coronavirus disease 2019 (COVID-19) and discussed the current challenges faced by the government in a given context. The coronavirus-associated death tolls have been increasing rapidly in a country. The provincial status of confirmed cases of coronavirus is higher in Punjab, followed by the Sindh, Khyber Pakhtunkhwa (KPK), and Balochistan. The case fatality ratio shows that KPK has a higher ratio, i.e., 5.11%, followed by the Punjab, i.e., 1.82%; Sindh, i.e., 1.80%; Balochistan, i.e., 1.28%; Gilgit-Baltistan, i.e., 0.71%; and Federal territory, i.e., 0.66%. The country has a less testing capacity to identify more suspected coronavirus patients. The study calculated that if we increase five times our testing capacity from the current date, the total registered cases will be reached to 137,370 and death tolls will increase up to 3090. It is highly needed to increase testing capacity across Pakistan in order to minimize the outbreak of coronavirus. The provincial government should follow the Federal Government instructions to contain coronavirus by increasing testing capacities, tracing suspected patients, smart lockdowns, emergency relief to the poor, and vigilant monitoring system.

title: Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases
abstract: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored.  This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks.  Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets.

title: Olfactory Dysfunction in Coronavirus Disease 2019 Patients: Observational Cohort Study and Systematic Review
abstract: Olfactory dysfunction (OD) has been reported in coronavirus disease 2019 (COVID-19). However, there are knowledge gaps about the severity, prevalence, etiology, and duration of OD in COVID-19 patients.  Olfactory function was assessed in all participants using questionnaires and the butanol threshold test (BTT). Patients with COVID-19 and abnormal olfaction were further evaluated using the smell identification test (SIT), sinus imaging, and nasoendoscopy. Selected patients received nasal biopsies. Systematic review was performed according to PRISMA guidelines. PubMed items from January 1, 2020 to April 23, 2020 were searched. Studies that reported clinical data on olfactory disturbances in COVID-19 patients were analyzed.  We included 18 COVID-19 patients and 18 controls. Among COVID-19 patients, 12 of 18 (67%) reported olfactory symptoms and OD was confirmed in 6 patients by BTT and SIT. Olfactory dysfunction was the only symptom in 2 patients. Mean BTT score of patients was worse than controls (P = .004, difference in means = 1.8; 95% confidence interval, 0.6–2.9). Sinusitis and olfactory cleft obstruction were absent in most patients. Immunohistochemical analysis of nasal biopsy revealed the presence of infiltrative CD68(+) macrophages harboring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen in the stroma. Olfactory dysfunction persisted in 2 patients despite clinical recovery. Systematic review showed that the prevalence of olfactory disturbances in COVID-19 ranged from 5% to 98%. Most studies did not assess olfaction quantitatively.  Olfactory dysfunction is common in COVID-19 and may be the only symptom. Coronavirus disease 2019-related OD can be severe and prolonged. Mucosal infiltration by CD68(+) macrophages expressing SARS-CoV-2 viral antigen may contribute to COVID-19-related OD.

title: Coalition: Advocacy for prospective clinical trials to test the post-exposure potential of hydroxychloroquine against COVID-19
abstract: Our coalition of public health experts, doctors, and scientists worldwide want to draw attention to the need for high-quality evaluation protocols of the potential beneficial effect of hydroxychloroquine (HCQ) as a post-exposure drug for exposed people, meaning people with close contact with positive tested patients, including home and medical caregivers. We have reviewed the mechanisms of antiviral effect of HCQ, the risk-benefit ratio taking into consideration the PK/PD of HCQ and the thresholds of efficacy. We have studied its use as an antimalarial, an antiviral, and an immunomodulating drug and concluded that the use of HCQ at does matching that of the standard treatment of Systemic Lupus erythematous, which has proven safety and efficacy in terms of HCQ blood and tissue concentration adapted to bodyweight (2,3), at 6 mg/kg/day 1 (loading dose) followed by 5 mg/kg/day, with a maximum limit of 600 mg/day in all cases should swiftly be clinically evaluated as a post-exposure drug for exposed people.

title: [Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China].
abstract: To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments.  Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number R(0)(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time.  For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the R(0)(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, R(0)(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the R(0)(t)s less than 1. The results could be used for the decision making to free population floating conditionally.  Dynamic R(0)(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.

title: Why are pregnant women susceptible to COVID-19? An immunological viewpoint
abstract: The 2019 novel coronavirus disease (COVID-19) was first detected in December 2019 and became epidemic in Wuhan, Hubei Province, China. COVID-19 has been rapidly spreading out in China and all over the world. The virus causing COVID-19, SARS-CoV-2 has been known to be genetically similar to severe acute respiratory syndrome coronavirus (SARS-CoV) but distinct from it. Clinical manifestation of COVID-19 can be characterized by mild upper respiratory tract infection, lower respiratory tract infection involving non-life threatening pneumonia, and life-threatening pneumonia with acute respiratory distress syndrome. It affects all age groups, including newborns, to the elders. Particularly, pregnant women may be more susceptible to COVID-19 since pregnant women, in general, are vulnerable to respiratory infection. In pregnant women with COVID-19, there is no evidence for vertical transmission of the virus, but an increased prevalence of preterm deliveries has been noticed. The COVID-19 may alter immune responses at the maternal-fetal interface, and affect the well-being of mothers and infants. In this review, we focused on the reason why pregnant women are more susceptible to COVID-19 and the potential maternal and fetal complications from an immunological viewpoint.

title: Investigating the Impact of Asymptomatic Carriers on COVID-19 Transmission
abstract: Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this sub-population, as well as persons with mild, represent a major contributor in the propagation of COVID-19. The asymptomatic sub-population frequently escapes detection by public health surveillance systems. Because of this, the currently accepted estimates of the basic reproduction number (Ro) of the virus are inaccurate. It is unlikely that a pathogen can blanket the planet in three months with an Ro in the vicinity of 3, as reported in the literature. In this manuscript, we present a mathematical model taking into account asymptomatic carriers. Our results indicate that an initial value of the effective reproduction number could range from 5.5 to 25.4, with a point estimate of 15.4, assuming mean parameters. The first three weeks of the model exhibit exponential growth, which is in agreement with average case data collected from thirteen countries with universal health care and robust communicable disease surveillance systems; the average rate of growth in the number of reported cases is 23.3% per day during this period.

title: An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)
abstract: The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known that the estimation of this number may vary due to several methodological issues, including different assumptions and choice of parameters, utilized models, used datasets and estimation period. With the spreading of the novel coronavirus (2019-nCoV) infection, the reproduction number has been found to vary, reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies that have been rapidly improved, enabling to shorten the time from infection/symptoms onset to diagnosis, leading to faster confirmation of the new coronavirus cases, our previous estimations on the transmission risk of the 2019-nCoV need to be revised. By using time-dependent contact and diagnose rates, we refit our previously proposed dynamics transmission model to the data available until January 29th(,) 2020 and re-estimated the effective daily reproduction ratio that better quantifies the evolution of the interventions. We estimated when the effective daily reproduction ratio has fallen below 1 and when the epidemics will peak. Our updated findings suggest that the best measure is persistent and strict self-isolation. The epidemics will continue to grow, and can peak soon with the peak time depending highly on the public health interventions practically implemented.

title: COVID-19: a meta-analysis of diagnostic test accuracy of commercial assays registered in Brazil
abstract: The accuracy of commercially available tests for COVID-19 in Brazil remains unclear. We aimed to perform a meta-analysis to describe the accuracy of available tests to detect COVID-19 in Brazil. We searched at the Brazilian Health Regulatory Agency (ANVISA) online platform to describe the pooled sensitivity (Se), specificity (Sp), diagnostic odds ratio (DOR) and summary receiver operating characteristic curves (SROC) for detection of IgM/IgG antibodies and for tests using naso/oropharyngeal swabs in the random-effects models. We identified 16 tests registered, mostly rapid-tests. Pooled diagnostic accuracy measures [95%CI] were: (i) for IgM antibodies Se=82% [76-87]; Sp=97% [96-98]; DOR=168 [92-305] and SROC=0.98 [0.96-0.99]; (ii) for IgG antibodies Se=97% [90-99]; Sp=98% [97-99]; DOR=1994 [385-10334] and SROC=0.99 [0.98-1.00]; and (iii) for detection of SARS-CoV-2 by antigen or molecular assays in naso/oropharyngeal swabs Se=97% [85-99]; Sp=99% [77-100]; DOR=2649 [30-233056] and SROC=0.99 [0.98-1.00]. These tests can be helpful for emergency testing during the COVID-19 pandemic in Brazil. However, it is important to highlight the high rate of false negative results from tests which detect SARS-CoV-2 IgM antibodies in the initial course of the disease and the scarce evidence-based validation results published in Brazil. Future studies addressing the diagnostic performance of tests for COVID-19 in the Brazilian population are urgently needed.

title: Perspectives from the Cancer and Aging Research Group: Caring for the vulnerable older patient with cancer and their caregivers during the COVID-19 crisis in the United States

title: Monitoring the COVID-19 epidemic in the context of widespread local transmission

title: ABSTRACT BOOK

title: A population-based study of the prevalence of COVID-19 infection in Espirito Santo, Brazil: methodology and results of the first stage
abstract: COVID-19 is affecting almost the entire world, causing more than four hundred thousand deaths and undermining the health care systems, as much as the economy, of the afflicted countries. The strategies for prevention depend on largely lacking information, as infection prevalence and virus pathogenicity. This study aimed to determine the prevalence, the pathogenicity, and the speed of infection spreading in a large population in Brazil.  This is a serial cross-sectional study designed on a population basis and structured over houses as the sampling units. The sampling consisted of four visits at 15 days intervals in randomly selected census-designated sectors of the State major municipalities (reference municipalities) and two visits at 30 days intervals in smaller municipalities of the same regions of those of reference. At each visit, the investigators sampled houses and sampled one individual in each house for data collection. After the informed consent, the investigators performed a rapid antibody detection test (Celer Technology, Inc) and applied a questionnaire containing clinical and demographic questions.  From May 13th to 15th, the investigators performed 6,393 rapid tests in 4,612 individuals of the reference municipalities, 1,163 individuals of the smaller municipalities, and 166 contacts of the positive individuals. Ninety-seven dwellers were positive in the reference municipalities, giving a prevalence of 2.1% (CI 95%: 1.67-2.52%). In the smaller municipalities, the figure was 0.26% (CI 95%: 0.05%-0.75%) (three positives). There was an association of the positive result with female sex (p = 0.013) and houses with five dwellers or more (p = 0.003). Seventy-eight positive individuals reported symptoms in the previous 15 days (80.4%), being anosmia (45.4%), cough (40.2%), and myalgia (38.1%) the more frequent. About one-third of them reported fever (28.9%).  The results reveal a still small prevalence of infection in the study area, despite the significant number of sick people overloading the health system. The figures indicate an important underreporting in the area and a frequency that still can grow, making necessary public health actions for the containment of the transmission.

title: Novel Coronavirus and Related Public Health Interventions Are Negatively Impacting Mental Health Services

title: The effectiveness of interventions to reduce COVID-19 transmission in a large urban jail
abstract: To estimate the impact of various mitigation strategies on COVID-19 transmission in a U.S. jail beyond those offered in national guidelines.  We developed a stochastic dynamic transmission model of COVID-19 in one large urban U.S. jail among staff and incarcerated individuals. We divided the outbreak into four intervention phases: the start of the outbreak, depopulation of the jail, increased proportion of people in single cells, and asymptomatic testing. We used the next generation method to estimate the basic reproduction ratio, R0, in each phase. We estimated the fraction of new cases, hospitalizations, and deaths averted by these interventions along with the standard measures of sanitization, masking, and social distancing interventions.  For the first outbreak phase, the estimated R0 was 8.23 (95% CrI: 5.01-12.90), and for the subsequent phases, R0, phase 2 = 3.58 (95% CrI: 2.46-5.08), R0, phase 3 = 1.72 (95% CrI: 1.41-2.12), and R0, phase 4 = 0.45 (95% CrI: 0.32-0.59). In total, the jail's interventions prevented approximately 83% of projected cases and hospitalizations and 89% of deaths over 83 days.  Depopulation, single celling, and asymptomatic testing within jails can be effective strategies to mitigate COVID-19 transmission in addition to standard public health measures.  Decision-makers should prioritize reductions in the jail population, single celling, and testing asymptomatic populations, as additional measures to manage COVID-19 within correctional settings.

title: Evolving status of the 2019 novel coronavirus infection: Proposal of conventional serologic assays for disease diagnosis and infection monitoring

title: Bayesian adjustment for preferential testing in estimating the COVID-19 infection fatality rate: Theory and methods
abstract: A key challenge in estimating the infection fatality rate (IFR) of COVID-19 is determining the total number of cases. The total number of cases is not known because not everyone is tested but also, more importantly, because tested individuals are not representative of the population at large. We refer to the phenomenon whereby infected individuals are more likely to be tested than non-infected individuals, as"preferential testing."An open question is whether or not it is possible to reliably estimate the IFR without any specific knowledge about the degree to which the data are biased by preferential testing. In this paper we take a partial identifiability approach, formulating clearly where deliberate prior assumptions can be made and presenting a Bayesian model, which pools information from different samples. Results suggest that when limited knowledge is available about the magnitude of preferential testing, reliable estimation of the IFR is still possible so long as there is sufficient"heterogeneity of bias"across samples.

title: Recent progress in understanding 2019 novel coronavirus (SARS-CoV-2) associated with human respiratory disease: detection, mechanisms and treatment
abstract: Viral respiratory diseases such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) always pose a severe threat to people. First identified in late December 2019, a novel coronavirus (2019-nCoV; SARS-CoV-2) has affected many provinces in China and multiple countries worldwide. The viral outbreak has aroused panic and a public-health emergency around the world, and the number of infections continues to rise. However, the causes and consequences of the pneumonia remain unknown. To effectively implement epidemic prevention, early identification and diagnosis are critical to disease control. Here we scrutinise a series of available studies by global scientists on the clinical manifestations, detection methods and treatment options for the disease caused by SARS-CoV-2, named coronavirus disease 2019 (COVID-19), and also propose potential strategies for preventing the infection.

title: Reversal of the Progression of Fatal Coronavirus Infection in Cats by a Broad-Spectrum Coronavirus Protease Inhibitor
abstract: Coronaviruses infect animals and humans causing a wide range of diseases. The diversity of coronaviruses in many mammalian species is contributed by relatively high mutation and recombination rates during replication. This dynamic nature of coronaviruses may facilitate cross-species transmission and shifts in tissue or cell tropism in a host, resulting in substantial change in virulence. Feline enteric coronavirus (FECV) causes inapparent or mild enteritis in cats, but a highly fatal disease, called feline infectious peritonitis (FIP), can arise through mutation of FECV to FIP virus (FIPV). The pathogenesis of FIP is intimately associated with immune responses and involves depletion of T cells, features shared by some other coronaviruses like Severe Acute Respiratory Syndrome Coronavirus. The increasing risks of highly virulent coronavirus infections in humans or animals call for effective antiviral drugs, but no such measures are yet available. Previously, we have reported the inhibitors that target 3C-like protease (3CLpro) with broad-spectrum activity against important human and animal coronaviruses. Here, we evaluated the therapeutic efficacy of our 3CLpro inhibitor in laboratory cats with FIP. Experimental FIP is 100% fatal once certain clinical and laboratory signs become apparent. We found that antiviral treatment led to full recovery of cats when treatment was started at a stage of disease that would be otherwise fatal if left untreated. Antiviral treatment was associated with a rapid improvement in fever, ascites, lymphopenia and gross signs of illness and cats returned to normal health within 20 days or less of treatment. Significant reduction in viral titers was also observed in cats. These results indicate that continuous virus replication is required for progression of immune-mediated inflammatory disease of FIP. These findings may provide important insights into devising therapeutic strategies and selection of antiviral compounds for further development for important coronaviruses in animals and humans.

title: Convalescent plasma or hyperimmune immunoglobulin for people with COVID-19: a rapid review.
abstract: Convalescent plasma and hyperimmune immunoglobulin may reduce mortality in patients with respiratory virus diseases, and are currently being investigated in trials as a potential therapy for coronavirus disease 2019 (COVID-19). A thorough understanding of the current body of evidence regarding the benefits and risks is required.  To assess whether convalescent plasma or hyperimmune immunoglobulin transfusion is effective and safe in the treatment of people with COVID-19.  The protocol was pre-published with the Center for Open Science and can be accessed here: osf.io/dwf53 We searched the World Health Organization (WHO) COVID-19 Global Research Database, MEDLINE, Embase, Cochrane COVID-19 Study Register, Centers for Disease Control and Prevention COVID-19 Research Article Database and trials registries to identify ongoing studies and results of completed studies on 23 April 2020 for case-series, cohort, prospectively planned, and randomised controlled trials (RCTs).  We followed standard Cochrane methodology and performed all steps regarding study selection in duplicate by two independent review authors (in contrast to the recommendations of the Cochrane Rapid Reviews Methods Group). We included studies evaluating convalescent plasma or hyperimmune immunoglobulin for people with COVID-19, irrespective of disease severity, age, gender or ethnicity. We excluded studies including populations with other coronavirus diseases (severe acute respiratory syndrome (SARS) or Middle East respiratory syndrome (MERS)) and studies evaluating standard immunoglobulins.  We followed recommendations of the Cochrane Rapid Reviews Methods Group regarding data extraction and assessment. To assess bias in included studies, we used the assessment criteria tool for observational studies, provided by Cochrane Childhood Cancer. We rated the certainty of evidence using the GRADE approach for the following outcomes: all-cause mortality at hospital discharge, improvement of clinical symptoms (7, 15, and 30 days after transfusion), grade 3 and 4 adverse events, and serious adverse events.  We included eight studies (seven case-series, one prospectively planned, single-arm intervention study) with 32 participants, and identified a further 48 ongoing studies evaluating convalescent plasma (47 studies) or hyperimmune immunoglobulin (one study), of which 22 are randomised. Overall risk of bias of the eight included studies was high, due to: study design; small number of participants; poor reporting within studies; and varied type of participants with different severities of disease, comorbidities, and types of previous or concurrent treatments, including antivirals, antifungals or antibiotics, corticosteroids, hydroxychloroquine and respiratory support. We rated all outcomes as very low certainty, and we were unable to summarise numerical data in any meaningful way. As we identified case-series studies only, we reported results narratively. Effectiveness of convalescent plasma for people with COVID-19 The following reported outcomes could all be related to the underlying natural history of the disease or other concomitant treatment, rather than convalescent plasma. All-cause mortality at hospital discharge All studies reported mortality. All participants were alive at the end of the reporting period, but not all participants had been discharged from hospital by the end of the study (15 participants discharged, 6 still hospitalised, 11 unclear). Follow-up ranged from 3 days to 37 days post-transfusion. We do not know whether convalescent plasma therapy affects mortality (very low-certainty evidence). Improvement of clinical symptoms (assessed by respiratory support) Six studies, including 28 participants, reported the level of respiratory support required; most participants required respiratory support at baseline. All studies reported improvement in clinical symptoms in at least some participants. We do not know whether convalescent plasma improves clinical symptoms (very low-certainty evidence). Time to discharge from hospital Six studies reported time to discharge from hospital for at least some participants, which ranged from four to 35 days after convalescent plasma therapy. Admission on the intensive care unit (ICU) Six studies included patients who were critically ill. At final follow-up the majority of these patients were no longer on the ICU or no longer required mechanical ventilation. Length of stay on the ICU Only one study (1 participant) reported length of stay on the ICU. The individual was discharged from the ICU 11 days after plasma transfusion. Safety of convalescent plasma for people with COVID-19 Grade 3 or 4 adverse events The studies did not report the grade of adverse events after convalescent plasma transfusion. Two studies reported data relating to participants who had experienced adverse events, that were presumably grade 3 or 4. One case study reported a participant who had moderate fever (38.9 °C). Another study (3 participants) reported a case of severe anaphylactic shock. Four studies reported the absence of moderate or severe adverse events (19 participants). We are very uncertain whether or not convalescent plasma therapy affects the risk of moderate to severe adverse events (very low-certainty evidence). Serious adverse events One study (3 participants) reported one serious adverse event. As described above, this individual had severe anaphylactic shock after receiving convalescent plasma. Six studies reported that no serious adverse events occurred. We are very uncertain whether or not convalescent plasma therapy affects the risk of serious adverse events (very low-certainty evidence).  We identified eight studies (seven case-series and one prospectively planned single-arm intervention study) with a total of 32 participants (range 1 to 10). Most studies assessed the risks of the intervention; reporting two adverse events (potentially grade 3 or 4), one of which was a serious adverse event. We are very uncertain whether convalescent plasma is effective for people admitted to hospital with COVID-19 as studies reported results inconsistently, making it difficult to compare results and to draw conclusions. We identified very low-certainty evidence on the effectiveness and safety of convalescent plasma therapy for people with COVID-19; all studies were at high risk of bias and reporting quality was low. No RCTs or controlled non-randomised studies evaluating benefits and harms of convalescent plasma have been completed. There are 47 ongoing studies evaluating convalescent plasma, of which 22 are RCTs, and one trial evaluating hyperimmune immunoglobulin. We will update this review as a living systematic review, based on monthly searches in the above mentioned databases and registries. These updates are likely to show different results to those reported here.

title: New threat: 2019 novel Coronavirus infection and infection control perspective in Turkey

title: Survival-Convolution Models for Predicting COVID-19 Cases and Assessing Effects of Mitigation Strategies
abstract: Countries around the globe have implemented unprecedented measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic. We aim to predict COVID-19 disease course and compare effectiveness of mitigation measures across countries to inform policy decision making. We propose a robust and parsimonious survival-convolution model for predicting key statistics of COVID-19 epidemics (daily new cases). We account for transmission during a pre-symptomatic incubation period and use a time-varying effective reproduction number (R(t)) to reflect the temporal trend of transmission and change in response to a public health intervention. We estimate the intervention effect on reducing the infection rate and quantify uncertainty by permutation. In China and South Korea, we predicted the entire disease epidemic using only data in the early phase (two to three weeks after the outbreak). A fast rate of decline in R(t) was observed and adopting mitigation strategies early in the epidemic was effective in reducing the infection rate in these two countries. The lockdown in Italy did not further accelerate the speed at which the infection rate decreases. The effective reproduction number has staggered around R(t) = 1.0 for more than 2 weeks before decreasing to below 1.0, and the epidemic in Italy is currently under control. In the US, R(t) significantly decreased during a 2-week period after the declaration of national emergency, but afterwards the rate of decrease is substantially slower. If the trend continues after May 1, the first wave of COVID-19 may be controlled by July 26 (CI: July 9 to August 27). However, a loss of temporal effect on infection rate (e.g., due to relaxing mitigation measures after May 1) could lead to a long delay in controlling the epidemic (November 19 with less than 100 daily cases) and a total of more than 2 million cases.

title: Acute kidney injury in patients hospitalized with COVID-19 in Wuhan, China: A single-center retrospective observational study
abstract: The kidney may be affected in coronavirus-2019 disease (COVID-19). This study assessed the predictors and outcomes of acute kidney injury (AKI) among individuals with COVID-19.  This observational study, included data on all patients with clinically confirmed COVID-19 admitted to Hankou Hospital, Wuhan, China from January 5 to March 8, 2020. Data were extracted from clinical and laboratory records. Follow-up was censored on March 8, 2020. This is a single-center, retrospective, observational study. Patients clinically confirmed COVID-19 and admitted to Hankou Hospital, Wuhan, China from January 5 to March 8, 2020 were enrolled. We evaluated the association between changes in the incidence of AKI and COVID-19 disease and clinical outcomes by using logistic regression models.  A total of 287 patients, 55 with AKI and 232 without AKI, were included in the analysis. Compared to patients without AKI, AKI patients were older, predominantly male, and were more likely to present with hypoxia and have pre-existing hypertension and cerebrovascular disease. Moreover, AKI patients had higher levels of white blood cells, D-dimer, aspartate aminotransferase, total bilirubin, creatine kinase, lactate dehydrogenase, procalcitonin, C-reactive protein, a higher prevalence of hyperkalemia, lower lymphocyte counts, and higher chest computed tomographic scores. The incidence of stage 1 AKI was 14.3%, and the incidence of stage 2 or 3 AKI was 4.9%. Patients with AKI had substantially higher mortality.  AKI is an important complication of COVID-19. Older age, male, multiple pre-existing comorbidities, lymphopenia, increased infection indicators, elevated D-dimer, and impaired heart and liver functions were the risk factors of AKI. AKI patients who progressed to stages 2 or 3 AKI had a higher mortality rate. Prevention of AKI and monitoring of kidney function is very important for COVID 19 patients.

title: Does coronavirus affect the audio-vestibular system? A rapid systematic review
abstract: This rapid systematic review investigated audio-vestibular symptoms associated with coronavirus. The protocol for the rapid review was registered in the International Prospective Register of Systematic Reviews and the review methods were developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed using the National Institute of Heath quality assessment tools. After rejecting more than 2300 records, there were five case reports and two cross-sectional studies that met the inclusion criteria. No records of audio-vestibular symptoms were reported with the earlier types of coronavirus (i.e. severe acute respiratory syndrome [SARS] and Middle East respiratory syndrome [). Reports of hearing loss, tinnitus, and vertigo have rarely been reported in individuals who tested positive for the SARS-CoV-2.Conclusion: Reports of audio-vestibular symptoms in confirmed COVID-19 cases are few, with mostly minor symptoms, and the studies are of poor quality. Emphasis over time is likely to shift from life-threatening concerns to longer-term health-related consequences such as audio-vestibular dysfunction. High-quality studies are needed to investigate the acute effects of COVID-19, as well as for understanding long-term risks, on the audio-vestibular system.

title: Understanding of guidance for acupuncture and moxibustion interventions on COVID-19 (Second edition) issued by CAAM
abstract: At present, the situation of global fight against COVID-19 is serious. WHO (World Health Organization)-China Joint Mission fully confirms the success of “China's model” against COVID-19 in the report. In fact, one particular power in “China's model” is acupuncture and moxibustion of traditional Chinese medicine. To better apply “non-pharmaceutic measures”—the external technique of traditional Chinese medicine, in the article, the main content of Guidance for acupuncture and moxibustion interventions on COVID-19 (Second edition) issued by China Association of Acupuncture–Moxibution is introduced and the discussion is stressed on the selection of moxibustion device and the duration of its exertion.

title: Considerations in performing endoscopy during the COVID-19 pandemic

title: Inferring the number of COVID-19 cases from recently reported deaths
abstract: We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.

title: A British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic

title: No Participant Left Behind: Conducting Science During COVID-19
abstract: Cognitive scientists have ramped up online testing in response to the coronavirus pandemic. Although research conducted online solves the problem of data collection, a lack of internet access among low-income and minority communities may reduce the diversity of study samples and, thus, impact the generalizability of scientific findings.

title: Human Coronavirus-NL63 infections in Korean children, 2004–2006
abstract: Human coronavirus-NL63 (HCoV-NL63) has been isolated from children with respiratory tract infections and its prevalence in Korea has not been reported.  This study was designed to investigate the presence and the clinical features of HCoV-NL63 during two winter seasons.  During April 2004–April 2006, nasopharyngeal specimens from children hospitalized with acute respiratory disease were tested for common respiratory viruses, including RSV, influenza A, influenza B, parainfluenza viruses, and adenovirus by IFA. hMPV infection was excluded by nested RT-PCR using primers for F-gene. To detect HCoV-NL63, previously described nested PCR assays for 1a and 1b were used. PCR products of the 1a gene for HCoV-NL63 were sequenced.  Out of 872 nasopharyngeal aspirate from children aged under 16 years, 14 (1.7%) were positive for HCoV-NL63. Most of the patients had croup (64.2%) or bronchiolitis (21.4%). The peak prevalence was found in November (28.5%). Most were collected between November 2004 and February 2005.  HCoV-NL63 may be one of the causative agents of acute respiratory tract infection, especially croup.

title: Self-reported anosmia and dysgeusia as key symptoms of coronavirus disease 2019
abstract: To slow down the transmission of coronavirus disease 2019 (COVID-19), it is important to identify specific symptoms for effective screening. While anosmia/hyposmia and dysgeusia/ageusia have been identified as highly prevalent symptoms, there are wide geographic variations, necessitating the regional evaluation of the prevalence of the symptoms.  A cross-sectional study was performed to evaluate the self-reported symptoms among adults (over 18 years old) who underwent COVID-19 tests at an ambulatory assessment centre. We identified 1,345 patients (102 positive and 1,243 negative) who visited the assessment centre between March 16 and April 15, 2020. We randomly sampled negative patients in a 1:3 ratio. The primary outcome was the prevalence of self-reported anosmia/hyposmia and dysgeusia/ageusia. Logistic regression was performed to evaluate the association between COVID-19 positivity and loss of smell and taste.  Fifty-six of 102 (50%) positive patients and 72 of 306 (23.5%) negative patients completed the survey. Anosmia/hyposmia and dysgeusia/ageusia were more prevalent among COVID-19 positive patients (41.1% v. 4.2%, p < 0.001 for smell and 46.4% v. 5.6%, p < 0.001 for taste). Anosmia/hyposmia and dysgeusia/ageusia were independently highly associated with COVID-19 positivity (adjusted odds ratios 14.4 and 11.4 for smell and taste, respectively).  In this Canadian study, smell and taste loss may be key symptoms of COVID-19. This evidence can be helpful in the clinical diagnosis of COVID-19, particularly settings of limited testing capacity.

title: Prediction on Covid-19 epidemic for different countries: Focusing on South Asia under various precautionary measures
abstract: The coronavirus disease 2019 (COVID-19), which emerged from Wuhan, China, is now a pandemic, affecting across the globe. Government of different countries have developed and adopted various policies to contain this epidemic and the most common were the social distancing and lockdown. We proposed a SEIR epidemic model that accommodates the effects of lockdown and individual based precautionary measures and used it to estimate model parameters from the epidemic data up to 2nd April, 2020, freely available in GitHub repository for COVID-19, for nine developed and developing countries. We used the estimated parameters to predict the disease burden in these countries with special emphasis on India, Bangladesh and Pakistan. Our analysis revealed that the lockdown and recommended individual hygiene can slow down the outbreak but unable to eradicate the disease from the society. With the current human-to-human transmission rate and existing level of personal precautionary, the number of infected individuals in India will be increasing at least for the next 3 months and the peak will come in 5 months. We can, however, reduce the epidemic size and prolong the time to arrive epidemic peak by seriously following the measures suggested by the authorities. We need to wait for another one month to obtain more data and epidemiological parameters for giving a better prediction about the pandemic. It is to be mentioned that research community is working for drugs and/ or vaccines against COVID19 and the presence of such pharmaceutical interventions will significantly alter the results.

title: A Novel Triage Tool of Artificial Intelligence Assisted Diagnosis Aid System for Suspected COVID-19 pneumonia In Fever Clinics
abstract: Currently, the prevention and control of COVID-19 outside Hubei province in China, and other countries has become more and more critically serious. We developed and validated a diagnosis aid model without CT images for early identification of suspected COVID-19 pneumonia (S-COVID-19-P) on admission in adult fever patients and made the validated model available via an online triage calculator. Patients admitted from Jan 14 to Feb 26, 2020 with the epidemiological history of exposure to COVID-19 were included [Model development (n = 132) and validation (n = 32)]. Candidate features included clinical symptoms, routine laboratory tests and other clinical information on admission. Features selection and model development were based on Lasso regression. The primary outcome is the development and validation of a diagnosis aid model for S-COVID-19-P early identification on admission. The development cohort contains 26 S-COVID-19-P and 7 confirmed COVID-19 pneumonia cases. The model performance in held-out testing set and validation cohort resulted in AUCs of 0.841 and 0.938, F-1 score of 0.571 and 0.667, recall of 1.000 and 1.000, specificity of 0.727 and 0.778, and the precision of 0.400 and 0.500. Based on this model, an optimized strategy for S-COVID-19-P early identification in fever clinics has also been designed. S-COVID-19-P could be identified early by a machine-learning model only used collected clinical information without CT images on admission in fever clinics with 100% recall score. The well performed and validated model has been deployed as an online triage tool, which is available at: https://intensivecare.shinyapps.io/COVID19/.

title: Accounting for incomplete testing in the estimation of epidemic parameters
abstract: As the COVID-19 pandemic spreads across the world, it is important to understand its features and responses to public health interventions in real-time. The field of infectious diseases epidemiology has highly advanced modeling strategies that yield relevant estimates. These include the doubling time of the epidemic and various other representations of the numbers of cases identified over time. Crude estimates of these quantities suffer from dependence on the underlying testing strategies within communities. We clarify the functional relationship between testing and the epidemic parameters, and thereby derive sensitivity analyses that explore the range of possible truths under various testing dynamics. We derive the required adjustment to the estimates of interest for New York City. We demonstrate that crude estimates that assume stable testing or complete testing can be biased.

title: Association between ambient temperature and COVID-19 infection in 122 cities from China
abstract: Coronavirus disease 2019 (COVID-19) has become a severe public health problem globally. Both epidemiological and laboratory studies have shown that ambient temperature could affect the transmission and survival of coronaviruses. This study aimed to determine whether the temperature is an essential factor in the infection caused by this novel coronavirus.  Daily confirmed cases and meteorological factors in 122 cities were collected between January 23, 2020, to February 29, 2020. A generalized additive model (GAM) was applied to explore the nonlinear relationship between mean temperature and COVID-19 confirmed cases. We also used a piecewise linear regression to determine the relationship in detail.  The exposure-response curves suggested that the relationship between mean temperature and COVID-19 confirmed cases was approximately linear in the range of <3 °C and became flat above 3 °C. When mean temperature (lag0–14) was below 3 °C, each 1 °C rise was associated with a 4.861% (95% CI: 3.209–6.513) increase in the daily number of COVID-19 confirmed cases. These findings were robust in our sensitivity analyses.  Our results indicate that mean temperature has a positive linear relationship with the number of COVID-19 cases with a threshold of 3 °C. There is no evidence supporting that case counts of COVID-19 could decline when the weather becomes warmer, which provides useful implications for policymakers and the public.

title: Understanding Epidemic Data and Statistics: A case study of COVID-19
abstract: The 2019-Novel-Coronavirus (COVID-19) has affected 181 countries and out of about 1197405 confirmed cases (By April 5). Understanding the transmission dynamics of the infection in each country which affected on a daily basis and evaluating the effectiveness of control policies is critical for our further actions. To date, the statistics of COVID-19 reported cases show more than 80 percent of infected had a mild case of disease, while around 14 percent of infected experienced a severe one and about 5 percent are categorized as critical disease victims. Today's report (2020-04-05; daily updates in the prepared website) shows the confirmed cases of COVID-19 in the US, Spain, Italy, and Germany are 308850, 126168, 124632, and 96092; respectively. Calculating the total Case Fatality Rate (CFR) of Italy (2020-04-04), about 13.3% of confirmed cases passed away. Compared to South Korea's rate of 1.8% (7 times lower than Italy) and China's 4% (69% lower than Italy), the CFR of Italy is too high. There are some effective policies that yield significant changes in the trend of cases. The lockdown policy in China, Italy, and Spain (the effect observed after some days), Shutdown of all non-essential companies in Hubei (the effect observed after 5 days), combined policy in South Korea, and reducing working hours in Iran.

title: Influence of countries adopted policies for COVID-19 reduction under the view of the airborne transmission framework
abstract: Daily new cases dataset since January 2020 were used to search for evidences of SARS-CoV-2 community transmission as the main nowadays cause of constant infection rates among countries. Despite traditional forms of transmission of this virus (droplets and aerosols in medical facilities), new evidence suggests aerosols forming patterns in the atmosphere as a main factor of community transmission outside medical spaces. Following these findings, this research focused on comparing some countries and the adopted policy used as preventive framework for virus community transmission. Countries social distancing policy aspect, of one to two meters of physical distance, was statistically analyzed from January to early May 2020, and countries were divided into those implementing only social physical distance and those implementing distancing with additional transmission isolation (with masks and city disinfection). Correlating countries social distancing policy adoption with other preventive measures such as social isolation and COVID-19 testing, a new indicator results, derived from SIR models and Weibull parameterization, show that only social physical distance measure could act as a factor for SARS-CoV-2 transmission with respect to atmosphere carrier potential. In this sense, the type of social distancing framework adopted by some countries without additional measures might represent a main model for the constant reproductive spread patterns of SARS-CoV-2 within the community transmission. Finally, the findings have important implications for the policy making to be adopted globally as well as individual-scale preventive methods.

title: Implications of social distancing in Brazil in the COVID-19 pandemic

title: Modeling serological testing to inform relaxation of social distancing for COVID-19 control
abstract: The value of serological testing to inform the public health response to the SARS-CoV-2 pandemic is debated. Using a transmission model, we examined how serology can be implemented to allow seropositive individuals to resume more normal levels of social interaction while offsetting the risks. We simulated the use of widespread serological testing with realistic assay characteristics, in which seropositive individuals partially restore their social contacts and act as immunological ‘shields’. If social distancing is relaxed by 50% at the same time that quarterly serological screening is initiated, approximately 120,000 deaths could be averted and a quarter of the US population could be released from social distancing in the first year of the epidemic, compared to a scenario without serological testing. This strategy has the potential to substantially flatten the COVID-19 epidemic curve while also allowing a substantial number of individuals to safely return to social and economic interactions.

title: The impact of believing you have had COVID-19 on behaviour: Cross-sectional survey
abstract: To investigate whether people who think they have had COVID-19 are less likely to engage in social distancing measures compared with those who think they have not had COVID-19.  On-line cross-sectional survey.  Data were collected between 20th and 22nd April.  6149 participants living in the UK aged 18 years or over.  Perceived immunity to COVID-19, self-reported adherence to social distancing measures (going out for essential shopping, nonessential shopping, and meeting up with friends/family; total out-of-home activity), worry about COVID-19 and perceived risk of COVID-19 to oneself and people in the UK. Knowledge that cough and high temperature / fever are the main symptoms of COVID-19.  In this sample, 1493 people (24.3%) thought they had had COVID-19. Only 245 (4.0%) reported receiving a test result saying they had COVID-19. Reported test results were often incongruent with participants' belief that they had had COVID-19. People who believed that they had had COVID-19 were: more likely to agree that they had some immunity to COVID-19; less likely to report adhering to social distancing measures; less worried about COVID-19; and less likely to know that cough and high temperature / fever are two of the most common symptoms of COVID-19.  The number of people in the UK who think they have already had COVID-19 is about twice the rate of current prevalence estimates. People who think that they have had COVID-19 may contribute to transmission of the virus through non-adherence to social distancing measures. Clear communications to this growing group are needed to explain why protective measures continue to be important and to encourage sustained adherence.

title: Early real-time estimation of the basic reproduction number of emerging or reemerging infectious diseases in a community with heterogeneous contact pattern: Using data from Hong Kong 2009 H1N1 Pandemic Influenza as an illustrative example
abstract: Emerging and re-emerging infections such as SARS (2003) and pandemic H1N1 (2009) have caused concern for public health researchers and policy makers due to the increased burden of these diseases on health care systems. This concern has prompted the use of mathematical models to evaluate strategies to control disease spread, making these models invaluable tools to identify optimal intervention strategies. A particularly important quantity in infectious disease epidemiology is the basic reproduction number, R(0.) Estimation of this quantity is crucial for effective control responses in the early phase of an epidemic. In our previous study, an approach for estimating the basic reproduction number in real time was developed. This approach uses case notification data and the structure of potential transmission contacts to accurately estimate R(0) from the limited amount of information available at the early stage of an outbreak. Based on this approach, we extend the existing methodology; the most recent method features intra- and inter-age groups contact heterogeneity. Given the number of newly reported cases at the early stage of the outbreak, with parsimony assumptions on removal distribution and infectivity profile of the diseases, experiments to estimate real time R(0) under different levels of intra- and inter-group contact heterogeneity using two age groups are presented. We show that the new method converges more quickly to the actual value of R(0) than the previous one, in particular when there is high-level intra-group and inter-group contact heterogeneity. With the age specific contact patterns, number of newly reported cases, removal distribution, and information about the natural history of the 2009 pandemic influenza in Hong Kong, we also use the extended model to estimate R(0) and age-specific R(0).

title: Use of National Pneumonia Surveillance to Describe Influenza A(H7N9) Virus Epidemiology, China, 2004–2013
abstract: In mainland China, most avian influenza A(H7N9) cases in the spring of 2013 were reported through the pneumonia of unknown etiology (PUE) surveillance system. To understand the role of possible underreporting and surveillance bias in assessing the epidemiology of subtype H7N9 cases and the effect of live-poultry market closures, we examined all PUE cases reported from 2004 through May 3, 2013. Historically, the PUE system was underused, reporting was inconsistent, and PUE reporting was biased toward A(H7N9)-affected provinces, with sparse data from unaffected provinces; however, we found no evidence that the older ages of persons with A(H7N9) resulted from surveillance bias. The absolute number and the proportion of PUE cases confirmed to be A(H7N9) declined after live-poultry market closures (p<0.001), indicating that market closures might have positively affected outbreak control. In China, PUE surveillance needs to be improved.

title: The Hypothesis of Testing: Paradoxes arising out of reported coronavirus case-counts
abstract: Many statisticians, epidemiologists, economists and data scientists have registered serious reservations regarding the reported coronavirus case-counts. Limited testing capacity across the country has been widely identified as a key driver of suppressed coronavirus case-counts. The calls to increase testing capacity are well-justified as they become a more frequent point of discussion in the public sphere. While expanded testing is a laudable goal, selection bias will impact estimates of disease prevalence and the effective reproduction number until the entire population is sampled. Moreover, tests are imperfect as false positive/negative rates interact in complex ways with selection bias. In this paper, we attempt to clarify this interaction. Through simple calculations, we demonstrate pitfalls and paradoxes that can arise when considering case-count data in the presence of selection bias and measurement error. The discussion guides several suggestions on how to improve current case-count reporting.

title: Would India Really Touch the Peak of SARS COVID 19 Cases or Deaths in Near Future?
abstract: The Government, Health System and even an individual citizen of India is alarmed expecting the height of pandemic of SARS-COVID-19 in near future. Many experts worldwide predict it to happen in India between end of May and end of July.  The aim of this research was to find an answer that whether India would come across the looming conditions of SARS-COVID-19 in coming days given the prevailing circumstances so far.  The proposed approach used fundamental concept of Statistics by fixing the standard reference to the number of daily new tests conducted by a country. We thus computed the percentage of daily new cases and daily new deaths, in using such references. The trends were studied using simple line chart. The theory of three sigma was also used to build the upper bound for daily new cases and deaths, specifically for India to see the extreme conditions.  The analysis was done using data from January to till May 18, 2020 for India, Italy, USA and UK. The trend of India was almost fix between ~2% to ~6% till May 18, 2020. On contrary, Italy, USA and UK were touched the Peak on March 29, 2020 (24.38%), April 26, 2020 (23.51%) and April 24, 2020 (24.91%), respectively and declining since then. Similar trends were also noted in daily new deaths, except Italy.  The proposed new concept for fixing universal reference provides a consistent and coherent results. It is thus clear from observed data so far that India is not going to encounter the frightened conditions or peak, like, Italy, USA, and UK for pandemic SARS-COVID-19, given the existing conditions, excluding the current migration.

title: Determinants of COVID-19 incidence and mortality: A cross-country analysis
abstract: We undertook this study to explore the role of important determinants affecting global COVID-19 incidence and mortality taking multifactorial disease dynamics into consideration.  Secondary data as on March 28, 2020 were obtained for 97 countries. Association of COVID-19 cumulative incidence and mortality measures were assessed with ten indictors representing health system characteristics, climate, demography, promptness of international travel restriction and population movement using Generalized Linear Modelling.  Country-specific COVID-19 cumulative incidence, cumulative cause-specific mortality and case fatality rate.  Significant inter-country variation in incidence and mortality rates were observed. Five variables were found to be associated with cumulative incidence: testing rate per 1000 population ({beta} = 0.119, p < 0.01), UHC index ({beta} = 0.043, p = 0.04), percentage elderly population ({beta} = 0.122, p < 0.01), percentage below-poverty line population ({beta} = -0.048, p < 0.01) and disability adjusted life years due to NCDs ({beta} = -0.013, p < 0.01). Case fatality rate was observed to be associated with testing rate per 1000 population ({beta} = -0.058, p = 0.03) and population density ({beta} = 0.002, p = 0.02), while the cumulative cause-specific mortality was associated with only percentage elderly population ({beta} = 0.096, p = 0.04) in the country.  Health system response, population susceptibility and demography were the most important factors determining the progression. Policy response should focus towards increasing testing, primarily targeting high population density areas. Health system strengthening and reduction in population risk factors should be long term goals for a better response to such epidemics.

title: A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks
abstract: A better characterization of the early growth dynamics of an epidemic is needed to dissect the important drivers of disease transmission, refine existing transmission models, and improve disease forecasts.  We introduce a 2-parameter generalized-growth model to characterize the ascending phase of an outbreak and capture epidemic profiles ranging from sub-exponential to exponential growth. We test the model against empirical outbreak data representing a variety of viral pathogens in historic and contemporary populations, and provide simulations highlighting the importance of sub-exponential growth for forecasting purposes.  We applied the generalized-growth model to 20 infectious disease outbreaks representing a range of transmission routes. We uncovered epidemic profiles ranging from very slow growth (p =0.14 for the Ebola outbreak in Bomi, Liberia (2014)) to near exponential (p >0.9 for the smallpox outbreak in Khulna (1972), and the 1918 pandemic influenza in San Francisco). The foot-and-mouth disease outbreak in Uruguay displayed a profile of slower growth while the growth pattern of the HIV/AIDS epidemic in Japan was approximately linear. The West African Ebola epidemic provided a unique opportunity to explore how growth profiles vary by geography; analysis of the largest district-level outbreaks revealed substantial growth variations (mean p =0.59, range: 0.14–0.97). The districts of Margibi in Liberia and Bombali and Bo in Sierra Leone had near-exponential growth, while the districts of Bomi in Liberia and Kenema in Sierra Leone displayed near constant incidences.  Our findings reveal significant variation in epidemic growth patterns across different infectious disease outbreaks and highlights that sub-exponential growth is a common phenomenon, especially for pathogens that are not airborne. Sub-exponential growth profiles may result from heterogeneity in contact structures or risk groups, reactive behavior changes, or the early onset of interventions strategies, and consideration of “deceleration parameters” may be useful to refine existing mathematical transmission models and improve disease forecasts.

title: The rationale of fever surveillance to identify patients with severe acute respiratory syndrome in Taiwan.
abstract: To establish a predictive scoring system and to determine its effectiveness for severe acute respiratory syndrome (SARS) cases confirmed by RT-PCR in patients with fever.  A study was conducted of 484 consecutive patients seen in the emergency department (ED) of our tertiary care center during the SARS outbreak in Taiwan. The scoring system was divided into triage and screening station stages. Data were analysed with multivariable and logistic regression analysis.  Of 737 patients who presented to our ED for possible SARS from March to June 2003, we enrolled 484 patients with a temperature >38.0 degrees C (>100.3 degrees F) (age >18 years). Dyspnoea, diarrhoea, travel, close contact, hospital exposure, and household history were identified as predictive indicators in the triage stage. The triage score was the total of six items. With a one-point cutoff value, the sensitivity and specificity were 81.8% (18/22) and 73.6% (340/462). Leukocytosis, thrombocytopenia, lymphopenia, and CXR were identified as predictive indicators in the fever screening stage. Screening station scores (the sum of 10 items) consisted of triage scores, white blood cell count, and CXR. With a three-point cutoff value, the sensitivity and specificity were 95.5% (21/22) and 87.2% (403/462).  Syndromic and traditional surveillance play a role in early identification of SARS in an endemic area. The SARS scoring system described is easily applicable and highly effective in screening patients during outbreaks.

title: Unprecedented disruption of lives and work: Health, distress and life satisfaction of working adults in China one month into the COVID-19 outbreak
abstract: We assess the health and wellbeing of normal adults living and working after one month of confinement to contain the COVID-19 outbreak in China. On Feb 20–21, 2020, we surveyed 369 adults in 64 cities in China that varied in their rates of confirmed coronavirus cases on their health conditions, distress and life satisfaction. 27% of the participants worked at the office, 38% resorted to working from home, and 25% stopped working due to the outbreak. Those who stopped working reported worse mental and physical health conditions as well as distress. The severity of COVID-19 in an individual's home city predicts their life satisfaction, and this relationship is contingent upon individuals’ existing chronic health issues and their hours of exercise. Our evidence supports the need to pay attention to the health of people who were not infected by the virus, especially for people who stopped working during the outbreak. Our results highlight that physically active people might be more susceptible to wellbeing issues during the lockdown. Policymakers who are considering introducing restrictive measures to contain COVID-19 may benefit from understanding such health and wellbeing implications.

title: Within the lack of chest COVID-19 X-ray dataset: A novel detection model based on GAN and deep transfer learning
abstract: The coronavirus (COVID-19) pandemic is putting healthcare systems across the world under unprecedented and increasing pressure according to theWorld Health Organization (WHO). With the advances in computer algorithms and especially Artificial Intelligence, the detection of this type of virus in the early stages will help in fast recovery and help in releasing the pressure off healthcare systems. In this paper, a GAN with deep transfer learning for coronavirus detection in chest X-ray images is presented. The lack of datasets for COVID-19 especially in chest X-rays images is the main motivation of this scientific study. The main idea is to collect all the possible images for COVID-19 that exists until the writing of this research and use the GAN network to generate more images to help in the detection of this virus from the available X-rays images with the highest accuracy possible. The dataset used in this research was collected from different sources and it is available for researchers to download and use it. The number of images in the collected dataset is 307 images for four different types of classes. The classes are the COVID-19, normal, pneumonia bacterial, and pneumonia virus. Three deep transfer models are selected in this research for investigation. The models are the Alexnet, Googlenet, and Restnet18. Those models are selected for investigation through this research as it contains a small number of layers on their architectures, this will result in reducing the complexity, the consumed memory and the execution time for the proposed model. Three case scenarios are tested through the paper, the first scenario includes four classes from the dataset, while the second scenario includes 3 classes and the third scenario includes two classes. All the scenarios include the COVID-19 class as it is the main target of this research to be detected. In the first scenario, the Googlenet is selected to be the main deep transfer model as it achieves 80.6% in testing accuracy. In the second scenario, the Alexnet is selected to be the main deep transfer model as it achieves 85.2% in testing accuracy, while in the third scenario which includes two classes (COVID-19, and normal), Googlenet is selected to be the main deep transfer model as it achieves 100% in testing accuracy and 99.9% in the validation accuracy. All the performance measurement strengthens the obtained results through the research.

title: Taste and Smell Impairment in COVID-19: An AAO-HNS Anosmia Reporting Tool-Based Comparative Study
abstract: To identify the taste and smell impairment in coronavirus disease 2019 (COVID-19)–positive subjects and compare the findings with COVID-19–negative subjects using the American Academy of Otolaryngology–Head and Neck Surgery (AAO-HNS) Anosmia Reporting Tool.  Tertiary referral center/COVID-19 pandemic hospital.  Comparative study.  After power analysis, 128 subjects were divided into 2 groups according to real-time polymerase chain reaction (RT-PCR) COVID-19 testing results. Subjects were called via telephone, and the AAO-HNS Anosmia Reporting Tool was used to collect responses.  The mean age of the study group was 38.63 ± 10.08 years. At the time of sampling, rhinorrhea was significantly high in the COVID-19–negative group, whereas those complaints described as “other” were significantly high in the COVID-19–positive group. There was a significant difference in the smell/taste impairment rates of the groups (n = 46% [71.9%] for the COVID-19–positive group vs n = 17 [26.6%] for the COVID-19–negative group, P = .001). For subjects with a smell impairment, anosmia rates did not differ between the groups. The rates of hyposmia and parosmia were significantly high in the COVID-19–positive group. For the subjects with taste impairment, ageusia rates did not differ between groups. The rate of hypogeusia and dysgeusia was significantly high in the COVID-19–positive group. Logistic regression analysis indicates that smell/taste impairment in COVID-19–positive subjects increases the odds ratio by 6.956 (95% CI, 3.16-15.29) times.  COVID-19–positive subjects are strongly associated with smell/taste impairment.

title: The incubation period of 2019-nCoV infections among travellers from Wuhan, China
abstract: Currently, a novel coronavirus 2019-nCoV causes an outbreak of viral pneumonia in Wuhan, China. Little is known about its epidemiological characteristics. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan, we estimate the mean incubation period to be 6.4 (5.6 - 7.7, 95% CI) days, ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values help to inform case definitions for 2019-nCoV and appropriate durations for quarantine.

title: Management of patients with suspected or confirmed COVID-19, in the radiology department
abstract: From December 2019, a novel coronavirus disease named COVID-19 was reported in China. Within 3 months, the World Health Organization defined COVID-19 as a pandemic, with more than 370,000 cases and 16,000 deaths worldwide. In consideration of the crucial role of diagnostic testing during COVID-19, the aim of this technical note was to provide a complete synthesis of approaches implemented for the management of suspected or confirmed COVID-19 patients.  The planning of a robust plan to prevent the transmission of the virus to patients and department staff members should be fundamental in each radiology service. Moreover, the speed of spread and the incidence of the pandemic make it necessary to optimize the use of personal protective devices and dedicated COVID-19 equipment, given the limited availability of supplies.  In the management of radiographic and CT imaging, staff should take special precautions to limit contamination between patients and other patients or professionals.  An isolated imaging room should be dedicated to suspected or confirmed COVID-19 cases, including radiography and CT scanners. This paper will provide guidance concerning disposable protective gear to be utilized, as well as on the cleaning and sanitation of radiology room and equipment.

title: A scientometric overview of CORD-19
abstract: As the COVID-19 pandemic unfolds, researchers from all disciplines are coming together and contributing their expertise. CORD-19, a dataset of COVID-19 and coronavirus publications, has recently been published alongside calls to help mine the information it contains, and to create tools to search it more effectively. Here, we focus on the delineation of the publications included in CORD-19, and analyse this delineation from a scientometric perspective. We find that CORD-19 contains research not only on COVID-19 and coronaviruses, but on viruses in general. Publications from CORD-19 mostly focus on a few, well-defined areas, including: coronaviruses (primarily SARS, MERS, COVID-19); public health and viral epidemics; the molecular biology of viruses; influenza and other families of viruses; immunology and antivirals; methodology (testing, diagnosing, clinical trials). CORD-19 publications published in 2020, especially focused on topics of pressing relevance (spread, infection, efficacy of counter-measures), are disproportionately popular on social media. While we fully endorse the initiative that led to CORD-19, we also advise to consider its relatively broad content critically.

title: Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-nCoV) in China
abstract: We quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities' new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated "actual" cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epicenter cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere.

title: Universal SARS-CoV-2 testing on admission to Labor and Delivery: Low prevalence among asymptomatic obstetric patients

title: From a single host to global spread. The global mobility based modelling of the COVID-19 pandemic implies higher infection and lower detection rates than current estimates.
abstract: Since the outbreak of the COVID-19 pandemic, multiple efforts of modelling of the geo-temporal transmissibility of the virus have been undertaken, but none succeeded in describing the pandemic at the global level. We propose a set of parameters for the first COVID-19 Global Epidemic and Mobility Model (GLEaM). The simulation starting with just a single pre-symptomatic, yet infectious, case in Wuhan, China, results in an accurate prediction of the number of diagnosed cases after 125 days in multiple countries across three continents.  We have built a modified SIR model and parameterized it analytically, according to the literature and by fitting the missing parameters to the observed dynamics of the virus spread. We compared our results with the number of diagnosed cases in sixeight selected countries which provide reliable statistics but differ substantially in terms of strength and speed of undertaken precautions. The obtained 95% confidence intervals for the predictions fit well to the empirical data.  The parameters that successfully model the pandemic are: the basic reproduction number R0, ~4.4; a latent non-infectious period of 1.1. days followed by 4.6 days of the presymptomatic infectious period; the probability of developing severe symptoms, 0.01; the probability of being diagnosed when presenting severe symptoms of 0.6; the probability of diagnosis for cases with mild symptoms or asymptomatic, 0.001. Also, the higher the testing rate per country, the lower the discrepancy between data (diagnosed cases) and model.  Parameters that successfully reproduce the observed number of cases indicate that both R0 and the prevalence of the virus might be underestimated. This is in concordance with the newest research on undocumented COVID-19 cases. Consequently, the actual mortality rate is putatively lower than estimated. Confirmation of the pandemic characteristic by further refinement of the model and screening tests is crucial for developing an effective strategy for the global epidemiological crisis.

title: Outcome reporting from protocols of clinical trials of Coronavirus Disease 2019 (COVID-19): a review
abstract: To examine heterogeneity of outcomes in protocols of clinical trials of Coronavirus Disease 2019 (COVID-19) and to identify outcomes for prioritization in developing a core outcome set (COS) in this field.  This study is a review.  Databases of ICMJE-accepted clinical trial registry platform were searched on February 14, 2020.  Randomized controlled trials (RCTs) and non-RCTs of COVID-19 were considered.Conditions of patients include common type, severe type or critical type. Interventions include traditional Chinese medicine (TCM) and Western medicine. We excluded trials that for discharged patients, psychological intervention and complications of COVID-19.  The general information and outcomes, outcome measurement instruments and measurement times were extracted. The results were analysed by descriptive analysis.  19 registry platforms were searched. A total of 97 protocols were included from 160 protocols. For protocols of TCM clinical trials, 76 outcomes from 16 outcome domains were reported, and almost half (34/76, 44.74%) of outcomes were reported only once; the most frequently reported outcome was time of SARS-CoV-2 RNA turns to negative. 27 (27/76, 35.53%) outcomes were provided one or more outcome measurement instruments. 10 outcomes were provided one or more measurement time frame. For protocols of western medicine clinical trials, 126 outcomes from 17 outcome domains were reported; almost half (62/126, 49.21%) of outcomes were reported only once; the most frequently reported outcome was proportion of patients with negative SARS-CoV-2. 27 outcomes were provided one or more outcome measurement instruments. 40 (40/126, 31.75%) outcomes were provided one or more measurement time frame.  Outcome reporting in protocols of clinical trials of COVID-19 is inconsistent. Thus, developing a core outcome set is necessary.  Outcomes; clinical trials, COVID-19; review.

title: The Appropriate Use of Testing for COVID-19
abstract: Many public officials are calling for increased testing for the 2019 novel coronavirus disease (COVID-19), and some governments have taken extraordinary measures to increase the availability of testing. However, little has been published about the sensitivity and specificity of the reverse transcriptase-polymerase chain reaction (RT-PCR) nasopharyngeal swabs that are commonly used for testing. This narrative review evaluates the literature regarding the accuracy of these tests, and makes recommendations based on this literature. In brief, a negative RT-PCR nasopharyngeal swab test is insufficient to rule out COVID-19. Thus, over-reliance on the results of the test may be dangerous, and the push for widespread testing may be overstated.

title: Abstract of 29th Regional Congress of the ISBT

title: Epidemiology and Virology of Acute Respiratory Infections During the First Year of Life: A Birth Cohort Study in Vietnam
abstract: Understanding viral etiology and age-specific incidence of acute respiratory infections in infants can help identify risk groups and inform vaccine delivery, but community-based data is lacking from tropical settings.  One thousand four hundred and seventy-eight infants in urban Ho Chi Minh City and 981 infants in a semi-rural district in southern Vietnam were enrolled at birth and followed to 1 year of age. Acute respiratory infection (ARI) episodes were identified through clinic-based illness surveillance, hospital admissions and self-reports. Nasopharyngeal swabs were collected from infants with respiratory symptoms and tested for 14 respiratory pathogens using multiplex reverse transcription-polymerase chain reaction.  Estimated incidence of ARI was 542 and 2691 per 1000 infant-years, and hospitalization rates for ARI were 81 and 138 per 1000 infant-years, in urban and semi-rural cohorts, respectively, from clinic- and hospital-based surveillance. However self-reported ARI episodes were just 1.5-fold higher in the semi-rural versus urban cohort, indicating that part of the urban–rural difference was explained by under-ascertainment in the urban cohort. Incidence was higher in infants ≥6 months of age than <6 months, but this was pathogen-specific. One or more viruses were detected in 53% (urban) and 64% (semi-rural) of samples from outpatients with ARI and in 78% and 66% of samples from hospitalized ARI patients, respectively. The most frequently detected viruses were rhinovirus, respiratory syncytial virus, influenza virus A and bocavirus. ARI-associated hospitalizations were associated with longer stays and more frequent ICU admission than other infections.  ARI is a significant cause of morbidity in Vietnamese infants and influenza virus A is an under-appreciated cause of vaccine-preventable disease and hospitalizations in this tropical setting. Public health strategies to reduce infant ARI incidence and hospitalization rates are needed.

title: Data-based analysis, modelling and forecasting of the COVID-19 outbreak
abstract: Since the first suspected case of coronavirus disease-2019 (COVID-19) on December 1st, 2019, in Wuhan, Hubei Province, China, a total of 40,235 confirmed cases and 909 deaths have been reported in China up to February 10, 2020, evoking fear locally and internationally. Here, based on the publicly available epidemiological data for Hubei, China from January 11 to February 10, 2020, we provide estimates of the main epidemiological parameters. In particular, we provide an estimation of the case fatality and case recovery ratios, along with their 90% confidence intervals as the outbreak evolves. On the basis of a Susceptible-Infectious-Recovered-Dead (SIDR) model, we provide estimations of the basic reproduction number (R(0)), and the per day infection mortality and recovery rates. By calibrating the parameters of the SIRD model to the reported data, we also attempt to forecast the evolution of the outbreak at the epicenter three weeks ahead, i.e. until February 29. As the number of infected individuals, especially of those with asymptomatic or mild courses, is suspected to be much higher than the official numbers, which can be considered only as a subset of the actual numbers of infected and recovered cases in the total population, we have repeated the calculations under a second scenario that considers twenty times the number of confirmed infected cases and forty times the number of recovered, leaving the number of deaths unchanged. Based on the reported data, the expected value of R(0) as computed considering the period from the 11th of January until the 18th of January, using the official counts of confirmed cases was found to be ∼4.6, while the one computed under the second scenario was found to be ∼3.2. Thus, based on the SIRD simulations, the estimated average value of R(0) was found to be ∼2.6 based on confirmed cases and ∼2 based on the second scenario. Our forecasting flashes a note of caution for the presently unfolding outbreak in China. Based on the official counts for confirmed cases, the simulations suggest that the cumulative number of infected could reach 180,000 (with a lower bound of 45,000) by February 29. Regarding the number of deaths, simulations forecast that on the basis of the up to the 10th of February reported data, the death toll might exceed 2,700 (as a lower bound) by February 29. Our analysis further reveals a significant decline of the case fatality ratio from January 26 to which various factors may have contributed, such as the severe control measures taken in Hubei, China (e.g. quarantine and hospitalization of infected individuals), but mainly because of the fact that the actual cumulative numbers of infected and recovered cases in the population most likely are much higher than the reported ones. Thus, in a scenario where we have taken twenty times the confirmed number of infected and forty times the confirmed number of recovered cases, the case fatality ratio is around ∼0.15% in the total population. Importantly, based on this scenario, simulations suggest a slow down of the outbreak in Hubei at the end of February.

title: Prior and novel coronaviruses, Coronavirus Disease 2019 (COVID-19), and human reproduction: what is known?
abstract: To summarize current understanding of the effects of novel and prior coronaviruses on human reproduction, specifically male and female gametes, and in pregnancy.  Review of English publications in PubMed and Embase to April 6, 2020.  Articles were screened for reports including coronavirus, reproduction, pathophysiology, and pregnancy.  Reproductive outcomes, effects on gametes, pregnancy outcomes, and neonatal complications. RESULT(S): Seventy-nine reports formed the basis of the review. Coronavirus binding to cells involves the S1 domain of the spike protein to receptors present in reproductive tissues, including angiotensin-converting enzyme-2 (ACE2), CD26, Ezrin, and cyclophilins. Severe Acute Respiratory Syndrome Coronavirus 1 (SARS-CoV-1) may cause severe orchitis leading to germ cell destruction in males. Reports indicate decreased sperm concentration and motility for 72-90 days following Coronavirus Disease 2019 (COVID-19) infection. Gonadotropin-dependent expression of ACE2 was found in human ovaries, but it is unclear whether SARS-Coronavirus 2 (CoV-2) adversely affects female gametogenesis. Evidence suggests that COVID-19 infection has a lower maternal case fatality rate than SARS or Middle East respiratory syndrome (MERS), but anecdotal reports suggest that infected, asymptomatic women may develop respiratory symptoms postpartum. Coronavirus Disease 2019 infections in pregnancy are associated with preterm delivery. Postpartum neonatal transmission from mother to child has been reported. CONCLUSION(S): Coronavirus Disease 2019 infection may affect adversely some pregnant women and their offspring. Additional studies are needed to assess effects of SARS-CoV-2 infection on male and female fertility.

title: Prediction of Number of Cases of 2019 Novel Coronavirus (COVID-19) Using Social Media Search Index
abstract: Predicting the number of new suspected or confirmed cases of novel coronavirus disease 2019 (COVID-19) is crucial in the prevention and control of the COVID-19 outbreak. Social media search indexes (SMSI) for dry cough, fever, chest distress, coronavirus, and pneumonia were collected from 31 December 2019 to 9 February 2020. The new suspected cases of COVID-19 data were collected from 20 January 2020 to 9 February 2020. We used the lagged series of SMSI to predict new suspected COVID-19 case numbers during this period. To avoid overfitting, five methods, namely subset selection, forward selection, lasso regression, ridge regression, and elastic net, were used to estimate coefficients. We selected the optimal method to predict new suspected COVID-19 case numbers from 20 January 2020 to 9 February 2020. We further validated the optimal method for new confirmed cases of COVID-19 from 31 December 2019 to 17 February 2020. The new suspected COVID-19 case numbers correlated significantly with the lagged series of SMSI. SMSI could be detected 6–9 days earlier than new suspected cases of COVID-19. The optimal method was the subset selection method, which had the lowest estimation error and a moderate number of predictors. The subset selection method also significantly correlated with the new confirmed COVID-19 cases after validation. SMSI findings on lag day 10 were significantly correlated with new confirmed COVID-19 cases. SMSI could be a significant predictor of the number of COVID-19 infections. SMSI could be an effective early predictor, which would enable governments’ health departments to locate potential and high-risk outbreak areas.

title: A Transmissible Gastroenteritis Coronavirus Nucleoprotein Epitope Elicits T Helper Cells That Collaborate in the in Vitro Antibody Synthesis to the Three Major Structural Viral Proteins
abstract: Four strong T cell epitopes have been identified studying the blastogenic response of lymphocytes from haplotype-defined transmissible gastroenteritis virus (TGEV) immune miniswine to sixty-one 15-mer synthetic peptides. Three of these epitopes are located on the nucleoprotein (N48 amino acids 46 to 60; N272, amino acids 272 to 286; and N321 amino acid 321 to 335), and one on the membrane protein (M196, amino acids 196 to 210). N321, peptide induced the highest T cell response and was recognized by immune miniswine lymphocytes with haplotypes dd, aa , and cc. T lymphocytes from peptide N321-immune miniswine reconstituted the in vitro synthesis of TGEV-specific antibodies by complementing CD4- TGEV-immune cells. This response was directed at least against the three major structural proteins. The synthesized antibodies specific for S protein preferentially recognized discontinous epitopes and neutralized TGEV infectivity. These results show that peptide N321 defines a functional T helper epitope eliciting T cells capable of collaborating with B cells specific for different proteins of TGEV.

title: The severity of COVID-19 in children on immunosuppressive medication

title: Does coronavirus affect the audio-vestibular system? A rapid systematic review.
abstract: This rapid systematic review investigated audio-vestibular symptoms associated with coronavirus. The protocol for the rapid review was registered in the International Prospective Register of Systematic Reviews and the review methods were developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias was assessed using the National Institute of Heath quality assessment tools. After rejecting more than 2300 records, there were five case reports and two cross-sectional studies that met the inclusion criteria. No records of audio-vestibular symptoms were reported with the earlier types of coronavirus (i.e. severe acute respiratory syndrome [SARS] and Middle East respiratory syndrome [). Reports of hearing loss, tinnitus, and vertigo have rarely been reported in individuals who tested positive for the SARS-CoV-2.Conclusion: Reports of audio-vestibular symptoms in confirmed COVID-19 cases are few, with mostly minor symptoms, and the studies are of poor quality. Emphasis over time is likely to shift from life-threatening concerns to longer-term health-related consequences such as audio-vestibular dysfunction. High-quality studies are needed to investigate the acute effects of COVID-19, as well as for understanding long-term risks, on the audio-vestibular system.

title: Cross-reactive antibody response between SARS-CoV-2 and SARS-CoV infections
abstract: The World Health Organization has recently declared the ongoing outbreak of COVID-19, which is caused by a novel coronavirus SARS-CoV-2, as pandemic. There is currently a lack of knowledge in the antibody response elicited from SARS-CoV-2 infection. One major immunological question is concerning the antigenic differences between SARS-CoV-2 and SARS-CoV. We address this question by using plasma from patients infected by SARS-CoV-2 or SARS-CoV, and plasma obtained from infected or immunized mice. Our results show that while cross-reactivity in antibody binding to the spike protein is common, cross-neutralization of the live viruses is rare, indicating the presence of non-neutralizing antibody response to conserved epitopes in the spike. Whether these non-neutralizing antibody responses will lead to antibody-dependent disease enhancement needs to be addressed in the future. Overall, this study not only addresses a fundamental question regarding the antigenicity differences between SARS-CoV-2 and SARS-CoV, but also has important implications in vaccine

title: Occurrence of canine parvovirus in dogs from Henan province of China in 2009–2014
abstract: There is no information concerning the genotype of Canine parvovirus (CPV) currently circulating in Henan province, China. Therefore, the aim of the present study was to provide insights into the epidemiology and molecular characterization of CPV circulating in Henan province from 2009 to 2014.  Nineteen thousand nine hundred seven dogs from pet hospitals in the cities of Luoyang, Anyang, Jiaozuo, Sanmenxia, Xinxiang, Zhengzhou in Henan province between 2009 and 2014 were investigated. Over the 6-year period, 1169 CPV-positive cases were identified and the morbidity of CPV infection ranged from 4.16 to 8.06 %, although morbidity was not significant (P > 0.05) between 2009 and 2014. Factors associated with morbidity included sampling season, dog age, breed, vaccination status, and sex. CPV co-infection with coccidium (10.00 %), canine distemper virus (4.79 %), hookworm (2.40 %), canine coronavirus (1.11 %), roundworm (1.03 %), tapeworm (0.17 %) and Babesia spp. (0.09 %) were observed. The new CPV-2a variant was more prevalent than the new CPV-2b variant in Henan province. CPV 2c was not observed in this study.  The epidemiology of CPV infection and identification of the circulating genotypes in Henan province, China from 2009 to 2014 determined that the new CPV-2a variant was more prevalent.

title: Broad-spectrum coronavirus antiviral drug discovery
abstract: The highly pathogenic coronaviruses severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) are lethal zoonotic viruses that have emerged into human populations these past 15 years. These coronaviruses are associated with novel respiratory syndromes that spread from person-to-person via close contact, resulting in high morbidity and mortality caused by the progression to Acute Respiratory Distress Syndrome (ARDS).  The risks of re-emergence of SARS-CoV from bat reservoir hosts, the persistence of MERS-CoV circulation, and the potential for future emergence of novel coronaviruses indicate antiviral drug discovery will require activity against multiple coronaviruses. In this review, approaches that antagonize viral nonstructural proteins, neutralize structural proteins, or modulate essential host elements of viral infection with varying levels of efficacy in models of highly pathogenic coronavirus disease are discussed.  Treatment of SARS and MERS in outbreak settings has focused on therapeutics with general antiviral activity and good safety profiles rather than efficacy data provided by cellular, rodent, or nonhuman primate models of highly pathogenic coronavirus infection. Based on lessons learned from SARS and MERS outbreaks, lack of drugs capable of pan-coronavirus antiviral activity increases the vulnerability of public health systems to a highly pathogenic coronavirus pandemic.

title: Phase adjusted estimation of the number of 2019 novel coronavirus cases in Wuhan, China
abstract: An outbreak of clusters of viral pneumonia due to a novel coronavirus (2019-nCoV / SARS-CoV-2) happened in Wuhan, Hubei Province in China in December 2019. Since the outbreak, several groups reported estimated R0 of Coronavirus Disease 2019 (COVID-19) and generated valuable prediction for the early phase of this outbreak. After implementation of strict prevention and control measures in China, new estimation is needed. An infectious disease dynamics SEIR (Susceptible, Exposed, Infectious and Removed) model was applied to estimate the epidemic trend in Wuhan, China under two assumptions of Rt. In the first assumption, Rt was assumed to maintain over 1. The estimated number of infections would continue to increase throughout February without any indication of dropping with Rt = 1.9, 2.6 or 3.1. The number of infections would reach 11,044, 70,258 and 227,989, respectively, by 29 February 2020. In the second assumption, Rt was assumed to gradually decrease at different phases from high level of transmission (Rt = 3.1, 2.6 and 1.9) to below 1 (Rt = 0.9 or 0.5) owing to increasingly implemented public heath intervention. Several phases were divided by the dates when various levels of prevention and control measures were taken in effect in Wuhan. The estimated number of infections would reach the peak in late February, which is 58,077-84,520 or 55,869-81,393. Whether or not the peak of the number of infections would occur in February 2020 may be an important index for evaluating the sufficiency of the current measures taken in China. Regardless of the occurrence of the peak, the currently strict measures in Wuhan should be continuously implemented and necessary strict public health measures should be applied in other locations in China with high number of COVID-19 cases, in order to reduce Rt to an ideal level and control the infection.

title: Epidemiological shift and geographical heterogeneity in the burden of leptospirosis in China
abstract: Leptospirosis morbidity and mortality rates in China have decreased since the 2000s. Further analyses of the spatiotemporal and demographic changes occurring in the last decade and its implication on estimates of disease burden are required to inform intervention strategies. In this study, we quantified the epidemiological shift and geographical heterogeneity in the burden of leptospirosis during 2005–2015 in China.  We used reported leptospirosis case data from 1st January 2005 to 31st of December 2015 that routinely collected by the China Information System for Disease Control and Prevention (CISDCP) to analyze the epidemiological trend and estimate the burden in terms of disability-adjusted life-years (DALYs) over space, time, and demographical groups.  A total of 7763 cases were reported during 2005–2015. Of which, 2403 (31%) cases were the laboratory-confirmed case. Since 2005, the notified incidence rate was gradually decreased (P < 0.05) and it was relatively stable during 2011–2015 (P > 0.05). During 2005–2015, we estimated a total of 10 313 DALYs were lost due to leptospirosis comprising a total of 1804 years-lived with disability (YLDs) and 8509 years-life lost (YLLs). Males had the highest burden of disease (7149 DALYs) compared to females (3164 DALYs). The highest burden estimate was attributed to younger individuals aged 10–19 years who lived in southern provinces of China. During 2005–2015, this age group contributed to approximately 3078 DALYs corresponding to 30% of the total DALYs lost in China. Yet, our analysis indicated a declining trend in burden estimates (P < 0.001) since 2005 and remained relatively low during 2011–2015. Low burden estimates have been identified in the endemic regions where infections principally distributed. Most of the changes in DALY estimates were driven by changes in YLLs.  In the last 11-years, the burden estimates of leptospirosis have shown a declining trend across the country; however, leptospirosis should not be neglected as it remains an important zoonotic disease and potentially affecting the young and productive population in economically less-developed provinces in southern of China. In addition, while in the last five years the incidence has been reported at very low-level, this might not reflect the true incidence of leptospirosis. Strengthened surveillance in the endemic regions is, hence, substantially required to capture the actual prevalence to better control leptospirosis in China.

title: Identifying a Kidney Transplant Recipient COVID Phenotype to Aid Test Utilization in the Setting of Limited Testing Availability - Does One Exist?
abstract: The high morbidity and mortality of COVID-19 in immunocompetent patients raises significant concern for immunosuppressed kidney transplant recipients (KTRs). This level of concern, both on the part of the KTRs and transplant professionals, is heightened by a lack of prior knowledge on how SARS-CoV-2 may manifest differently in immunosuppressed patients. Characterizing how KTRs may present differently than the general population would allow for more targeted and timely evaluation and treatment of KTRs with COVID-19 infection.  Without prior knowledge of how this virus would affect our transplant center’s delivery of care to KTRs who are SARS-CoV-2 positive or Patients Under Investigation (PUIs), and in the setting of limited testing availability, we initiated a Quality Assurance and Improvement Project (QAPI) to track KTRs followed at our transplant center through the SARS-CoV-2 testing process.  Of the 53 symptomatic patients, 20 (38%) tested positive for SARS-CoV-2 either on presentation to the emergency department, or referral to a designated outpatient testing center. In addition, 16 (80%) of the 20 patients who tested positive required inpatient treatment. Intriguingly, patients with a history of polyoma BK viremia (BKV) had a higher incidence of testing positive for SARS-CoV-2 compared to patients without history of BKV (80% and 28%, respectively; p= 0.002). The Positive Predictive Value and Likelihood ratio was 80% and 6.6 for this association, respectively. Among our KTRs tested, those receiving belatacept had a lower likelihood of testing positive for SARS-CoV-2. This finding approached, but did not achieve, statistical significance (p=0.06).

title: Transmission potential of COVID-19 in Iran
abstract: We estimated the reproduction number of 2020 Iranian COVID-19 epidemic using two different methods: R0 was estimated at 4.4 (95% CI, 3.9, 4.9) (generalized growth model) and 3.50 (1.28, 8.14) (epidemic doubling time) (February 19 - March 1) while the effective R was estimated at 1.55 (1.06, 2.57) (March 6-19).

title: First detection of neboviruses in yak (Bos grunniens) and identification of a novel neboviruses based on complete genome
abstract: Neboviruses (NeVs) is an important causative agent of calf diarrhea. Here, 354 diarrhoeic samples were collected from yak on 55 farms in the Qinghai-Tibet Plateau, China. 22.0% of the diarrhoeic samples were detected as NeVs-positive by RT–PCR assay. Phylogenetic analysis of 78 NeVs RdRp fragments showed that 69 strains were closely related to NB-like strains, and the remaining 9 strains were clustered into an independent branch, which may represent a novel RdRp genotype. Two complete NeVs genomes (YAK/NRG-17/17/CH and YAK/HY1-2/18/CH) were successfully sequenced with 7459 nt and 7460 nt in length, respectively. The genomes of the two strains only shared 68.1%–69.3% nt identity with all six known NeVs genomes, and phylogenetic trees based on its genome, VP1, RdRp, VP2, P34, NTPase, P30, VPg and 3CLpro proteins suggested that the two strains may represent a novel NeVs strain with novel VP1 genotype and novel RdRp genotype. Notably, 11.5% NeVs strains were screened as the novel NeVs strains based VP1 and RdRp sequences. These novel NeVs strains were detected from 6 farms in two counties, indicating that the novel NeVs has spread in local region. To best of our knowledge, this is the first detection of NeVs in yak. Moreover, a novel NeVs strain was identified based on complete genome. These results contribute to further understand the prevalence and genetic evolution of NeVs.

title: Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study
abstract: The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.  We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (R(t)) at the provincial level.  We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30.  Our estimates of the incubation period and serial interval were similar, suggesting an early peak of infectiousness, with possible transmission before the onset of symptoms. Our results also indicate that, as the epidemic progressed, infectious individuals were isolated more quickly, thus shortening the window of transmission in the community. Overall, our findings indicate that strict containment measures, movement restrictions, and increased awareness of the population might have contributed to interrupt local transmission of SARS-CoV-2 outside Hubei province.

title: Evaluating Incidence and Impact Estimates of the COVID-19 Outbreak from Wuhan before Lockdown
abstract: Wuhan, China was the epicenter of COVID-19 pandemic. The goal of current study is to understand the infection transmission dynamics before intervention measures were taken.  Data and key events were searched through pubmed and internet. Epidemiological data were calculated using data extracted from a variety of data sources.  We established a timeline showing by January 1, 2020, Chinese authorities had been presented convincing evidence of human-to-human transmission; however, it was not until January 20, 2020 that this information was shared with the public. Our study estimated that there would have been 10989 total infected cases if interventions were taken on January 2, 2020, versus 239875 cases when lockdown was put in place on January 23, 2020.  China's withholding of key information about the 2020 COVID-19 outbreak and its delayed response ultimately led to the largest public health crisis of this century and could have been avoided with earlier countermeasures.

title: Infections in Hematology Patients
abstract: Infections are major causes of morbidity and mortality in hematology patients especially those having undergone allogeneic hematopoietic stem cell transplantation. The management relies on early diagnosis and rapid introduction of appropriate antimicrobial drugs frequently before the infectious agent has been identified. The use of broad-spectrum antibacterial drugs has reduced the mortality in febrile neutropenia. However, the increase of multiresistant strains has in several countries become a major threat, and the development of new antibacterial drugs is urgently needed. Infection control strategies are also very important to limit the spread of multiresistant bacteria. Early diagnosis with imaging and tests for antigen or DNA is important for the management of fungal infections. High-risk patients should also receive prophylaxis. Viral infections are important causes of severe disease in patients having undergone allogeneic stem cell transplantation but do occur also in non-transplanted patients. Early diagnosis usually with tests for viral nucleic acids is the key for appropriate management. Prevention and treatment with antiviral drugs are available for some viruses especially herpesviruses.

title: RAN translation and frameshifting as translational challenges at simple repeats of human neurodegenerative disorders
abstract: Repeat-associated disorders caused by expansions of short sequences have been classified as coding and noncoding and are thought to be caused by protein gain-of-function and RNA gain-of-function mechanisms, respectively. The boundary between such classifications has recently been blurred by the discovery of repeat-associated non-AUG (RAN) translation reported in spinocerebellar ataxia type 8, myotonic dystrophy type 1, fragile X tremor/ataxia syndrome and C9ORF72 amyotrophic lateral sclerosis and frontotemporal dementia. This noncanonical translation requires no AUG start codon and can initiate in multiple frames of CAG, CGG and GGGGCC repeats of the sense and antisense strands of disease-relevant transcripts. RNA structures formed by the repeats have been suggested as possible triggers; however, the precise mechanism of the translation initiation remains elusive. Templates containing expansions of microsatellites have also been shown to challenge translation elongation, as frameshifting has been recognized across CAG repeats in spinocerebellar ataxia type 3 and Huntington's disease. Determining the critical requirements for RAN translation and frameshifting is essential to decipher the mechanisms that govern these processes. The contribution of unusual translation products to pathogenesis needs to be better understood. In this review, we present current knowledge regarding RAN translation and frameshifting and discuss the proposed mechanisms of translational challenges imposed by simple repeat expansions.

title: Implications of SARSr-CoV 2 infection in thalassemias: Do patients fall into the "high clinical risk" category?
abstract: We're all flying blind regarding coronavirus, but it's fair to think if thalassemic patients are particularly vulnerable to SARS-COV-2 infection or are at potential higher risk of complications from COVID-19 than normal population, specially when they become older. The frustrating thing is that, right now, this virus is still new. It only came to the attention of the World Health Organization at the end of December. Very few cases in thalassemia have so far been reported; is this due to lack of testing or a true lack of infection/susceptibility? However, we believe that more data should be collected to better characterise the impact of SARS-CoV-2 infection in patients with thalassemias. Therefore, a multicenter registry and the collection of comprehensive data from both positive COVID-19 thalassemia major and non-transfusion dependent thalassemia are necessary to clarify debated issues. In the meantime an early and vigilant monitoring along with high quality supportive care are needed in thalassemic patients at high risk for SARS-CoV-2 infection.

title: Early dynamics of transmission and control of COVID-19: a mathematical modelling study
abstract: An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 95 333 confirmed cases as of March 5, 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. Combining a mathematical model of severe SARS-CoV-2 transmission with four datasets from within and outside Wuhan, we estimated how transmission in Wuhan varied between December, 2019, and February, 2020. We used these estimates to assess the potential for sustained human-to-human transmission to occur in locations outside Wuhan if cases were introduced.  We combined a stochastic transmission model with data on cases of coronavirus disease 2019 (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January, 2020, and February, 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas. To estimate the early dynamics of transmission in Wuhan, we fitted a stochastic transmission dynamic model to multiple publicly available datasets on cases in Wuhan and internationally exported cases from Wuhan. The four datasets we fitted to were: daily number of new internationally exported cases (or lack thereof), by date of onset, as of Jan 26, 2020; daily number of new cases in Wuhan with no market exposure, by date of onset, between Dec 1, 2019, and Jan 1, 2020; daily number of new cases in China, by date of onset, between Dec 29, 2019, and Jan 23, 2020; and proportion of infected passengers on evacuation flights between Jan 29, 2020, and Feb 4, 2020. We used an additional two datasets for comparison with model outputs: daily number of new exported cases from Wuhan (or lack thereof) in countries with high connectivity to Wuhan (ie, top 20 most at-risk countries), by date of confirmation, as of Feb 10, 2020; and data on new confirmed cases reported in Wuhan between Jan 16, 2020, and Feb 11, 2020.  We estimated that the median daily reproduction number (R(t)) in Wuhan declined from 2·35 (95% CI 1·15–4·77) 1 week before travel restrictions were introduced on Jan 23, 2020, to 1·05 (0·41–2·39) 1 week after. Based on our estimates of R(t), assuming SARS-like variation, we calculated that in locations with similar transmission potential to Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.  Our results show that COVID-19 transmission probably declined in Wuhan during late January, 2020, coinciding with the introduction of travel control measures. As more cases arrive in international locations with similar transmission potential to Wuhan before these control measures, it is likely many chains of transmission will fail to establish initially, but might lead to new outbreaks eventually.

title: Noninvasive ventilation in acute respiratory failure due to H1N1 influenza: A word of caution

title: Preliminary evaluation of COVID-19 disease outcomes, test capacities and management approaches among African countries.
abstract: Following the declaration of COVID-19 as a global pandemic and the report of index case in Africa, the number of countries in Africa with confirmed cases of the infection has grown tremendously with disease now being reported in almost all countries on the continent, with the exemption of Lesotho after 75 days. It is therefore necessary to evaluate the disease outcomes among the African countries as the situation unfolds for early identification of best practices for adoption.  In this study, COVID-19 disease outcomes (confirmed cases, deaths and recoveries), testing capacities and disease management approaches among African countries were evaluated. The relationship between COVID-19 infections in African countries and their performance on global resilient indices including the Human Development Index (HDI), performance on Sustainable Development Goals (SDGs) and the Global Risk Index (GRI) were also examined. Data acquired from various standard databases were evaluated over a period of 75 days from the date of reporting the index case.  This study has revealed compelling spatial differences in the incidence, deaths and recoveries from COVID-19 among African countries. Egypt, South Africa, Morocco and Algeria were clustered as countries with highest values of COVID-19 disease outcomes on the continent during the 75-day period of observation. The cluster analysis and comparison of countries in terms of percentage recovered cases of confirmed infections revealed that Mauritius, Mauritania, Gambia, Burkina Faso, Madagascar, Togo and Uganda had the highest scores. Comparative analysis of COVID-19 across the world revealed that the parameters were relatively inconsequential in Oceania and Africa continents, while Europe, North America and Asia had significantly higher cases of disease outcomes. For COVID-19 testing capacities, South Africa, Ghana and Egypt are leading in total number of tests carried out. However when the number of tests carried out were related to population number of the countries, Djibouti, Mauritius, Ghana and South Africa are found to be the leading countries. With respect to management of the disease in Africa, all the countries adopted the WHO protocols, personal hygiene, economic palliatives and social distancing measures. Only three countries in Africa (Madagascar, Togo and Burkina Faso) had a state supported initiative to utilise traditional medicines or herbs as alternatives to control COVID-19. Additionally, most of the countries are providing prompt treatment of the patients with a range of drugs especially Hydroxychloroquine, Chloroquine and Chloroquine-Azithromycin combination. The study found that no strong relationship currently exists between the global resilient indicators (HDI, SDG and GRI) and COVID-19 cases across Africa.  This study has revealed compelling spatial differences in disease outcomes among African countries and also found testing capacities for COVID-19 to be abysmally low in relation to the population. During the 75 days of observation, African countries have recorded significantly low number of deaths associated with COVID-19 and relatively high recovery rates. Countries in Africa with higher rate of recovery from the disease were found to have adopted strict adherence to some of WHO protocol to contain the disease, isolate all those who test positive to the disease and provide prompt treatment of the patients with a range of drugs especially Hydroxychloroquine, Chloroquine and Chloroquine-Azithromycin combination. The study recommends that the approaches adopted by the African countries which achieved high recovery rates from COVID-19 should be integrated into healthcare management plans for the disease across the continent even as the situation unfolds.

title: Clinical and Radiographic Presentations of COVID-19 among Patients Receiving Radiation Therapy for Thoracic Malignancies
abstract: The 2019 novel coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a pandemic affecting healthcare centers across the globe. Patients with cancer have been reported to be particularly vulnerable to infection, morbidity, and severe events. Given the high proportion of asymptomatic carriers and concerns regarding speed and availability of laboratory testing, novel detection strategies are necessary to supplement traditional screening methods and facilitate mitigation of viral transmission. Recent data support the diagnostic consistency and potential value of computed tomography (CT) scans to aid early diagnosis of COVID-19. Volumetric CT image-guidance is commonly employed in patients undergoing radiotherapy and presents a unique opportunity to screen for COVID-specific lung changes. This case series describes the presentation of SARS-CoV-2 infections among three patients undergoing thoracic radiotherapy across multiple institutions. We highlight their clinical symptoms, imaging findings, potential confounders, and clinical workflow to triage these patients to the next level of care.

title: Differences by country-level income in COVID-19 cases, deaths, case-fatality rates, and rates per million population in the first five months of the pandemic
abstract: To describe differences by country-level income in COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates per million population.  Publicly available data on COVID-19 cases and deaths from December 31, 2019 to June 3, 2020 were analyzed. Kruskal-Wallis tests were used to examine associations of country-level income with COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates.  A total of 380,803 deaths out of 6,348,204 COVID-19 cases were reported from 210 countries and territories globally in the period under study, and the global case-fatality rate was 6.0%. Of the total globally reported cases and deaths, the percentages of cases and deaths were 59.9% and 75.0% for high-income countries, and 30.9% and 20.7% for upper-middle-income countries. Countries in higher-income categories had higher incidence rates and death rates. Between April and May, the incidence rates in higher-income groups of countries decreased, but in other groups, it increased.  In the first five months of the COVID-19 pandemic, most cases and deaths were reported from high-income and upper-middle-income countries, and those countries had higher incidence rates and death rates per million population than did lower-middle and low-income countries.  COVID-19, incidence rate, death rate, case fatality rate, income, and country

title: RT-qPCR Testing of SARS-CoV-2: A Primer
abstract: Testing for the presence of coronavirus is an essential diagnostic tool for monitoring and managing the current COVID-19 pandemic. The only reliable test in current use for testing acute infection targets the genome of SARS-CoV-2, and the most widely used method is quantitative fluorescence-based reverse transcription polymerase chain reaction (RT-qPCR). Despite its ubiquity, there is a significant amount of uncertainty about how this test works, potential throughput and reliability. This has resulted in widespread misrepresentation of the problems faced using this test during the current COVID-19 epidemic. This primer provides simple, straightforward and impartial information about RT-qPCR.

title: Prevalence of diabetes mellitus in 2019 novel coronavirus: a Meta-analysis
abstract: Since December 2019, a new strain ofcoronavirus named 2019 novel coronavirus (2019-nCoV) has been discovered in Wuhan. The prevalence of diabetes mellitus, which is a great public health issue leading to immunity inhibition and anincreased incidenceofinfections, has been increasing over the past ten years. The aim of this research was to systematically assess the prevalence of diabetes mellitus among 2019-nCoV.  We searched PubMed, Embase, Web of Science and Medline for observational studies up to February 25, 2020. A random effects model or fixed-effects model was applied to evaluate the pooled prevalence of diabetes mellitus and odds ratio (OR) with 95% confidence interval (CI).  In total, nine papers met the eligibility criteria. The pooled prevalence of DM was 9% (95% CI 6%–12%). There was obvious heterogeneity (I2 65%, p=0.004) in the prevalence of DM in these studies. The prevalence of DM in moderate patients with 2019-nCoV was 7% (95% CI 4%–10%). The prevalence of DM in severe patients with 2019-nCoV was 17% (95% CI 13%–21%). The prevalence of DM in severe patients with 2019-nCoV was significantly higher than that in moderate patients with 2019-nCoV (OR 2.49, 95% CI 1.70 to 3.64).  To our knowledge, this work is the first report showing the prevalence of diabetes mellitus in patients with 2019-nCoV, which is beneficial to prevent the spread of 2019-nCoV in the future.

title: Time-adjusted Analysis Shows Weak Associations Between BCG Vaccination Policy and COVID-19 Disease Progression
abstract: In this study, we ascertain the associations between BCG vaccination policies and progression of COVID-19 through analysis of various time-adjusted indicators either directly extracted from the incidence and death reports, or estimated as parameters of disease progression models. We observe weak correlation between BCG vaccination status and indicators related to disease reproduction characteristics. We did not find any associations with case fatality rates (CFR), but the differences in CFR estimates are at present likely dominated by differences in testing and case reporting between countries.

title: A Statistical Analysis Of CoV-19 Positive Test Frequency Data Indicates A Need For Greater Attention To CoV-19 Test Quality And Pre-Wuhan Cov-19 Prevalence
abstract: Increased attention to analysis of SARS-CoV-2 (CoV-19) positive test frequency data is essential for achievement of better knowledge of the natural history of the virus in human populations, improved accuracy of CoV-19 epidemiological data, and development of public response policies that are better crafted to address the current CoV-19-induced global crisis. A statistical analysis of currently available positive test frequency data reveals a surprisingly uniform relationship between the number of CoV-19 test performed and the number of positive tests obtained. The uniformity is particularly striking for United States CoV-19 test data. Such observations warrant closer evaluation of other factors, besides virus spread, that may also contribute to the nature of the coronavirus pandemic. These include indigenous CoV-19 and the quality of CoV-19 testing.

title: The need for COVID-19 research in low- and middle-income countries
abstract: In the early months of the pandemic, most reported cases and deaths due to COVID-19 occurred in high-income countries. However, insufficient testing could have led to an underestimation of true infections in many low- and middle-income countries. As confirmed cases increase, the ultimate impact of the pandemic on individuals and communities in low- and middle-income countries is uncertain. We therefore propose research in three broad areas as urgently needed to inform responses in low- and middle-income countries: transmission patterns of SARS-CoV-2, the clinical characteristics of the disease, and the impact of pandemic prevention and response measures. Answering these questions will require a multidisciplinary approach led by local investigators and in some cases additional resources. Targeted research activities should be done to help mitigate the potential burden of COVID-19 in low- and middle-income countries without diverting the limited human resources, funding, or medical supplies from response activities.

title: Assessment of Specimen Pooling to Conserve SARS CoV-2 Testing Resources
abstract: To establish the optimal parameters for group testing of pooled specimens for the detection of SARS-CoV-2.  The most efficient pool size was determined to be five specimens using a web-based application. From this analysis, 25 experimental pools were created using 50 µL from one SARS-CoV-2 positive nasopharyngeal specimen mixed with 4 negative patient specimens (50 µL each) for a total volume of 250 µL. Viral RNA was subsequently extracted from each pool and tested using the CDC SARS-CoV-2 RT-PCR assay. Positive pools were consequently split into individual specimens and tested by extraction and PCR. This method was also tested on an unselected group of 60 nasopharyngeal specimens grouped into 12 pools.  All 25 pools were positive with cycle threshold (Ct) values within 0 and 5.03 Ct of the original individual specimens. The analysis of 60 specimens determined that 2 pools were positive followed by identification of 2 individual specimens among the 60 tested. This testing was accomplished while using 22 extractions/PCR tests, a savings of 38 reactions.  When the incidence rate of SARS-CoV-2 infection is 10% or less, group testing will result in the saving of reagents and personnel time with an overall increase in testing capability of at least 69%.

title: Prevalence Threshold and Temporal Interpretation of Screening Tests: The Example of the SARS-CoV-2 (COVID-19) Pandemic
abstract: The curvilinear relationship between a screening test's positive predictive value (PPV) and its target disease prevalence is proportional. In consequence, there is an inflection point of maximum curvature in the screening curve defined as a function of the sensitivity and specificity beyond which the rate of change of a test's PPV declines sharply relative to disease prevalence. Herein, we demonstrate a mathematical model exploring this phenomenon and define the prevalence threshold point where this change occurs. Understanding where this prevalence point lies in the curve has important implications for the interpretation of test results, the administration of healthcare systems, the implementation of public health measures, and in cases of pandemics like SARS-CoV-2, the functioning of society at large. To illustrate the methods herein described, we provide the example of the screening strategies used in the SARS-CoV-2 (COVID-19) pandemic, and calculate the prevalence threshold statistic of different tests available today. This concept can help contextualize the validity of a screening test in real time, thereby enhancing our understanding of the dynamics of the current pandemic.

title: The Coronavirus 2019 pandemic in Canada: the impact of public health interventions on the course of the outbreak in Alberta and other provinces
abstract: The SARS-CoV-2 disease 2019 (COVID-19) pandemic has spread across the world with varying impact on health systems and outcomes. We assessed how the type and timing of public- health interventions impacted the course of the outbreak in Alberta and other Canadian provinces.  We used publicly-available data to summarize rates of laboratory data and mortality in relation to measures implemented to contain the outbreak and testing strategy. We estimated the transmission potential of SARS-CoV-2 before the state of emergency declaration for each province (R0) and at the study end date (Rt).  The first cases were confirmed in Ontario (January 25) and British Columbia (January 28). All provinces implemented the same health-policy measures between March 12 and March 30. Alberta had a higher percentage of the population tested (3.8%) and a lower mortality rate (3/100,000) than Ontario (2.6%; 11/100,000) or Quebec (3.1%; 31/100,000). British Columbia tested fewer people (1.7%) and had similar mortality as Alberta. Data on provincial testing strategies were insufficient to inform further analyses. Mortality rates increased with increasing rates of lab- confirmed cases in Ontario and Quebec, but not in Alberta. R0 was similar across all provinces, but varied widely from 2.6 (95% confidence intervals 1.9-3.4) to 6.4 (4.3-8.5), depending on the assumed time interval between onset of symptoms in a primary and a secondary case (serial interval). The outbreak is currently under control in Alberta, British Columbia and Nova Scotia (Rt <1).  COVID-19-related health outcomes varied by province despite rapid implementation of similar health-policy interventions across Canada. Insufficient information about provincial testing strategies and a lack of primary data on serial interval are major limitations of existing data on the Canadian COVID-19 outbreak.

title: Signals of T(h)2 immune response from COVID-19 patients requiring intensive care

title: Causes of severe pneumonia requiring hospital admission in children without HIV infection from Africa and Asia: the PERCH multi-country case-control study
abstract: Pneumonia is the leading cause of death among children younger than 5 years. In this study, we estimated causes of pneumonia in young African and Asian children, using novel analytical methods applied to clinical and microbiological findings.  We did a multi-site, international case-control study in nine study sites in seven countries: Bangladesh, The Gambia, Kenya, Mali, South Africa, Thailand, and Zambia. All sites enrolled in the study for 24 months. Cases were children aged 1–59 months admitted to hospital with severe pneumonia. Controls were age-group-matched children randomly selected from communities surrounding study sites. Nasopharyngeal and oropharyngeal (NP-OP), urine, blood, induced sputum, lung aspirate, pleural fluid, and gastric aspirates were tested with cultures, multiplex PCR, or both. Primary analyses were restricted to cases without HIV infection and with abnormal chest x-rays and to controls without HIV infection. We applied a Bayesian, partial latent class analysis to estimate probabilities of aetiological agents at the individual and population level, incorporating case and control data.  Between Aug 15, 2011, and Jan 30, 2014, we enrolled 4232 cases and 5119 community controls. The primary analysis group was comprised of 1769 (41·8% of 4232) cases without HIV infection and with positive chest x-rays and 5102 (99·7% of 5119) community controls without HIV infection. Wheezing was present in 555 (31·7%) of 1752 cases (range by site 10·6–97·3%). 30-day case-fatality ratio was 6·4% (114 of 1769 cases). Blood cultures were positive in 56 (3·2%) of 1749 cases, and Streptococcus pneumoniae was the most common bacteria isolated (19 [33·9%] of 56). Almost all cases (98·9%) and controls (98·0%) had at least one pathogen detected by PCR in the NP-OP specimen. The detection of respiratory syncytial virus (RSV), parainfluenza virus, human metapneumovirus, influenza virus, S pneumoniae, Haemophilus influenzae type b (Hib), H influenzae non-type b, and Pneumocystis jirovecii in NP-OP specimens was associated with case status. The aetiology analysis estimated that viruses accounted for 61·4% (95% credible interval [CrI] 57·3–65·6) of causes, whereas bacteria accounted for 27·3% (23·3–31·6) and Mycobacterium tuberculosis for 5·9% (3·9–8·3). Viruses were less common (54·5%, 95% CrI 47·4–61·5 vs 68·0%, 62·7–72·7) and bacteria more common (33·7%, 27·2–40·8 vs 22·8%, 18·3–27·6) in very severe pneumonia cases than in severe cases. RSV had the greatest aetiological fraction (31·1%, 95% CrI 28·4–34·2) of all pathogens. Human rhinovirus, human metapneumovirus A or B, human parainfluenza virus, S pneumoniae, M tuberculosis, and H influenzae each accounted for 5% or more of the aetiological distribution. We observed differences in aetiological fraction by age for Bordetella pertussis, parainfluenza types 1 and 3, parechovirus–enterovirus, P jirovecii, RSV, rhinovirus, Staphylococcus aureus, and S pneumoniae, and differences by severity for RSV, S aureus, S pneumoniae, and parainfluenza type 3. The leading ten pathogens of each site accounted for 79% or more of the site's aetiological fraction.  In our study, a small set of pathogens accounted for most cases of pneumonia requiring hospital admission. Preventing and treating a subset of pathogens could substantially affect childhood pneumonia outcomes.

title: Special attention to nurses’ protection during the COVID-19 epidemic
abstract: As of March 8, 2020, the novel coronavirus disease 2019 (COVID-19) had caused 80,815 human infections and 3073 deaths in China, including more than 3000 infections among medical staff. Guangdong Second Provincial General Hospital (Guangzhou, Guangdong Province, China), a provincial emergency hospital, has treated more than 35 confirmed cases of COVID-19 and more than 260 suspected cases. Most of nurses’ work involves direct contact with patients. As nurses have high vulnerability to COVID-19, it is necessary to establish hospital-specific protocols to reduce the risk of nurses’ infection in interactions with COVID-19 patients. Our hospital has maintained a “zero nurse infection” rate while battling SARS in 2003 and during the present COVID-19 epidemic. The following are the key measures implemented in our hospital.

title: News coverage of the COVID-19 pandemic: Missed opportunities to promote health sustaining behaviors
abstract: Given that individuals may make health decisions based on mass media coverage, and given that such decisions have broad consequences in the case of highly contagious infectious disease, it is imperative that public health practitioners are aware of mass media coverage on emerging health threats such as COVID-19. The purpose of this study was to examine the content of news segments covering COVID-19 posted on-line.  Using the Google Videos function on a cleared browser, all videos identified from January and February, 2020 were archived by URL for analysis. After applying exclusion criteria, a total of 401 remained, comprising the sample. Content categories derived from trusted sources were applied to assess the content of broadcast news segments pertaining to COVID-19 on Google Videos.  The most common topic mentioned across all videos was death and the death rate (43.6%) and many connoted anxieties surrounding the COVID-19 outbreak (37.4%). Critically important information about the prevention of COVID-19 spread received little attention. For example, only 3.0% of videos discussed coughing into or blowing one's nose into a tissue and throwing the tissue away, 6.2% talked about wearing a facemask when caring for the ill, and 8.8% covered disinfecting highly touched objects and surfaces. International videos more often presented captions and English subtitles (with and without narration) (7.8% vs. 0.9%, p = 0.018) and even more frequently discussed death and the death rate associated with COVID-19 (56.9% vs. 41.7%, p = 0.04).  Coupled with the resultant increase in negative emotion, the majority of video messages missed an opportunity to reframe messages to encourage/promote coping strategies and health sustaining behaviors.

title: Epidemiological Trends of Coronavirus Disease 2019 in China
abstract: The Coronavirus Disease 2019 (COVID-19) epidemic broke out in Wuhan, China, and it spread rapidly. Since January 23, 2020, China has launched a series of unusual and strict measures, including the lockdown of Wuhan city to contain this highly contagious disease. We collected the epidemiological data to analyze the trend of this epidemic in China.  We closely tracked the Chinese and global official websites to collect the epidemiological information about COVID-19. The number of total and daily new confirmed cases of COVID-19 in China was presented to illustrate the trend of this epidemic.  On January 23, 2020, 835 confirmed COVID-19 cases were reported in China. On February 6, 2020, there were 31211 cases. By February 20, 2020, the number reached as high as 75,993. Most cases were distributed in and around Wuhan, Hubei province. Since January 23, 2020, the number of daily new cases in China except Hubei province reached a peak of 890 on the eleventh day and then it declined to a low level of 34 within two full-length incubation periods (28 days), and the number of daily new cases in Hubei also started to decrease on the twelfth day, from 3156 on February 4, 2020 to 955 on February 15, 2020.  The COVID-19 epidemic has been primarily contained in China. The battle against this epidemic in China has provided valuable experiences for the rest of the world. Strict measures need to be taken as earlier as possible to prevent its spread.

title: Animal models for SARS and MERS coronaviruses
abstract: The emergence of Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) and Middle East Respiratory Syndrome coronavirus (MERS-CoV), two strains of animal coronaviruses that crossed the species barrier to infect and cause severe respiratory infections in humans within the last 12 years, have taught us that coronaviruses represent a global threat that does not recognize international borders. We can expect to see other novel coronaviruses emerge in the future. An ideal animal model should reflect the clinical signs, viral replication and pathology seen in humans. In this review, we present factors to consider in establishing an animal model for the study of novel coronaviruses and compare the different animal models that have been employed to study SARS-CoV and MERS-CoV.

title: Regional difference in the rate of spread of SARS-CoV-2

title: Concerns for activated breathing control (ABC) with breast cancer in the era of COVID-19: Maximizing infection control while minimizing heart dose

title: Mesenchymal Stem Cell Infusion Shows Promise for Combating Coronavirus (COVID-19)- Induced Pneumonia
abstract: A new study published by the journal Aging & Disease reported that intravenous administration of clinical-grade human mesenchymal stem cells (MSCs) into patients with coronavirus disease 2019 (COVID-19) resulted in improved functional outcomes (Leng et al., Aging Dis, 11:216-228, 2020). This study demonstrated that intravenous infusion of MSCs is a safe and effective approach for treating patients with COVID-19 pneumonia, including elderly patients displaying severe pneumonia. COVID-19 is a severe acute respiratory illness caused by a new coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, treating COVID-19 patients, particularly those afflicted with severe pneumonia, is challenging as no specific drugs or vaccines against SARS-CoV-2 are available. Therefore, MSC therapy inhibiting the overactivation of the immune system and promoting endogenous repair by improving the lung microenvironment after the SARS-CoV-2 infection found in this study is striking. Additional studies in a larger cohort of patients are needed to validate this therapeutic intervention further, however.

title: Flocked swab might be one main reason causing the high false-negative rate in COVID-19 screening----the advantages of a novel silicone swab
abstract: RNA testing using RT-PCR can provide direct evidence for diagnoses of COVID-19 which has brought unexpected disasters and changes to our human society. However, the absorption of cotton swab for RNA lysates may lead to a low concentration of detectable RNA, which might be one of the main reasons for the unstable positive detecting rate. We designed and manufactured a kind of silicone swab with concave-convex structure, and further compared the effects of silicone and cotton swab on RNA extraction. Principal component analysis and Paired Wilcoxcon test suggested that a higher RNA concentration and A260/A280 would be obtained using silicone swab. The results indicated that our silicone swab had a more excellent ability to sample than the cotton swab, characterized by the higher quantity and quality of extracted RNA. Thus, we advised that the current cotton swabs need to be improved urgently in COVID-19 diagnoses and the process of “sample collection” and “sample pre-processing” must be standardized and emphasized. Highlights The current cotton swabs need to be improved urgently in COVID-19 screening.

title: Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach
abstract: Coronavirus disease 2019 (COVID-19) has raised urgent questions about containment and mitigation, particularly in countries where the virus has not yet established human-to-human transmission. The objectives of this study were to find out if it was possible to prevent, or delay, the local outbreaks of COVID-19 through restrictions on travel from abroad and if the virus has already established in-country transmission, to what extent would its impact be mitigated through quarantine of symptomatic patients?  These questions were addressed in the context of India, using simple mathematical models of infectious disease transmission. While there remained important uncertainties in the natural history of COVID-19, using hypothetical epidemic curves, some key findings were illustrated that appeared insensitive to model assumptions, as well as highlighting critical data gaps.  It was assumed that symptomatic quarantine would identify and quarantine 50 per cent of symptomatic individuals within three days of developing symptoms. In an optimistic scenario of the basic reproduction number (R(0)) being 1.5, and asymptomatic infections lacking any infectiousness, such measures would reduce the cumulative incidence by 62 per cent. In the pessimistic scenario of R(0)=4, and asymptomatic infections being half as infectious as symptomatic, this projected impact falls to two per cent.  Port-of-entry-based entry screening of travellers with suggestive clinical features and from COVID-19-affected countries, would achieve modest delays in the introduction of the virus into the community. Acting alone, however, such measures would be insufficient to delay the outbreak by weeks or longer. Once the virus establishes transmission within the community, quarantine of symptomatics may have a meaningful impact on disease burden. Model projections are subject to substantial uncertainty and can be further refined as more is understood about the natural history of infection of this novel virus. As a public health measure, health system and community preparedness would be critical to control any impending spread of COVID-19 in the country.

title: A kinetic model for qualitative understanding and analysis of the effect of complete lockdown imposed by India for controlling the COVID-19 disease spread by the SARS-CoV-2 virus
abstract: The present ongoing global pandemic caused by SARS-CoV-2 virus is creating havoc across the world. The absence of any vaccine as well as any definitive drug to cure, has made the situation very grave. Therefore only few effective tools are available to contain the rapid pace of spread of this disease, named as COVID-19. On 24th March, 2020, the the Union Government of India made an announcement of unprecedented complete lockdown of the entire country effective from the next day. No exercise of similar scale and magnitude has been ever undertaken anywhere on the globe in the history of entire mankind. This study aims to scientifically analyze the implications of this decision using a kinetic model covering more than 96% of Indian territory. This model was further constrained by large sets of realistic parameters pertinent to India in order to capture the ground realities prevailing in India, such as: (i) true state wise population density distribution, (ii) accurate state wise infection distribution for the zeroth day of simulation (20th March, 2020), (iii) realistic movements of average clusters, (iv) rich diversity in movements patterns across different states, (v) migration patterns across different geographies, (vi) different migration patterns for pre- and post-COVID-19 outbreak, (vii) Indian demographic data based on the 2011 census, (viii) World Health Organization (WHO) report on demography wise infection rate and (ix) incubation period as per WHO report. This model does not attempt to make a long-term prediction about the disease spread on a standalone basis; but to compare between two different scenarios (complete lockdown vs. no lockdown). In the framework of model assumptions, our model conclusively shows significant success of the lockdown in containing the disease within a tiny fraction of the population and in the absence of it, it would have led to a very grave situation.

title: Estimation of COVID-19 transmission rates in California and the U.S. with reporting delays
abstract: We estimated time-varying reproduction numbers of COVID-19 transmission in counties and regions of California and in states of the United States, using the Wallinga-Teunis method of estimations applied to publicly available data. The serial interval distribution assumed incorporates wide uncertainty in delays from symptom onset to case reporting. This assumption contributes smoothing and a small but meaningful increase in numerical estimates of reproduction numbers due to the likely existence of secondary cases not yet reported. Transmission in many areas of the U.S. may not yet be controlled, including areas in which case counts appear to be stable or slowly declining.

title: Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.
abstract: The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues to take its toll, with >2.6 million confirmed infections and >183,000 deaths. Dire projections are surfacing almost every day, and policymakers worldwide are using projections for critical decisions. Given this background, we modeled unobserved infections to examine the extent to which we might be grossly underestimating COVID-19 infections in North America.  We developed a machine-learning model to uncover hidden patterns based on reported cases and to predict potential infections. First, our model relied on dimensionality reduction to identify parameters that were key to uncovering hidden patterns. Next, our predictive analysis used an unbiased hierarchical Bayesian estimator approach to infer past infections from current fatalities.  Our analysis indicates that, when we assumed a 13-day lag time from infection to death, the United States, as of April 22, 2020, likely had at least 1.3 million undetected infections. With a longer lag time-for example, 23 days-there could have been at least 1.7 million undetected infections. Given these assumptions, the number of undetected infections in Canada could have ranged from 60,000 to 80,000. Duarte's elegant unbiased estimator approach suggested that, as of April 22, 2020, the United States had up to >1.6 million undetected infections and Canada had at least 60,000 to 86,000 undetected infections. However, the Johns Hopkins University Center for Systems Science and Engineering data feed on April 22, 2020, reported only 840,476 and 41,650 confirmed cases for the United States and Canada, respectively.  We have identified 2 key findings: (1) as of April 22, 2020, the United States may have had 1.5 to 2.029 times the number of reported infections and Canada may have had 1.44 to 2.06 times the number of reported infections and (2) even if we assume that the fatality and growth rates in the unobservable population (undetected infections) are similar to those in the observable population (confirmed infections), the number of undetected infections may be within ranges similar to those described above. In summary, 2 different approaches indicated similar ranges of undetected infections in North America.

title: Foodborne Diseases: Overview of Biological Hazards and Foodborne Diseases
abstract: Foodborne diseases can occur as single cases or outbreaks and sometimes as in the case of cholera spread around the world to cause pandemics. The burden of foodborne diseases is hard to estimate but is in the billions of dollars for loss of life or reduced quality of life, particularly for diseases that are endemic. The bacterial, viral, and parasitic agents cause gastrointestinal symptoms lasting from a few hours to many months, but some agents trigger sequelae that can cause other adverse effects on the body. Everyone is exposed to these types of agents from time to time, but more frequently where there is poor sanitation and lack of temperature control of food, as it occurs in many parts of the developing world.

title: Rapidly Bootstrapping a Question Answering Dataset for COVID-19
abstract: We present CovidQA, the beginnings of a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle's COVID-19 Open Research Dataset Challenge. To our knowledge, this is the first publicly available resource of its type, and intended as a stopgap measure for guiding research until more substantial evaluation resources become available. While this dataset, comprising 124 question-article pairs as of the present version 0.1 release, does not have sufficient examples for supervised machine learning, we believe that it can be helpful for evaluating the zero-shot or transfer capabilities of existing models on topics specifically related to COVID-19. This paper describes our methodology for constructing the dataset and presents the effectiveness of a number of baselines, including term-based techniques and various transformer-based models. The dataset is available at

title: The international imperative to rapidly and inexpensively monitor community-wide Covid-19 infection status and trends

title: New Insights into Flavivirus Evolution, Taxonomy and Biogeographic History, Extended by Analysis of Canonical and Alternative Coding Sequences
abstract: To generate the most diverse phylogenetic dataset for the flaviviruses to date, we determined the genomic sequences and phylogenetic relationships of 14 flaviviruses, of which 10 are primarily associated with Culex spp. mosquitoes. We analyze these data, in conjunction with a comprehensive collection of flavivirus genomes, to characterize flavivirus evolutionary and biogeographic history in unprecedented detail and breadth. Based on the presumed introduction of yellow fever virus into the Americas via the transatlantic slave trade, we extrapolated a timescale for a relevant subset of flaviviruses whose evolutionary history, shows that different Culex-spp. associated flaviviruses have been introduced from the Old World to the New World on at least five separate occasions, with 2 different sets of factors likely to have contributed to the dispersal of the different viruses. We also discuss the significance of programmed ribosomal frameshifting in a central region of the polyprotein open reading frame in some mosquito-associated flaviviruses.

title: Sudden hyposmia as a prevalent symptom of COVID-19 infection.
abstract: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has recently caused a pandemic that has involved Italy as the second worldwide nation in terms of infected patients and deaths. The clinical manifestation of Covid-19 ranges from asymptomatic carrier status to severe pneumonia. Asymptomatic individuals in Covid-19 are those who are carriers of the virus but do not show clinical symptoms and are able to transmit the disease in the same degree as symptomatic carriers. In order to contain contagions is of supreme importance to identify asymptomatic patients because this subpopulation is one of the main factors contributing to the spread of this disease. We report on six Italian patients with COVID-19 who presented sudden hyposmia as the only or most prominent disease manifestation, without upper or lower respiratory tract involvement or other major features of the disease. A supra-threshold olfaction test confirmed the hyposmia in all patients. The onset of hyposmia during a Covid-19 outbreak should be considered as a warning sign of an infection that requires a diagnostic test for Covid-19

title: Clinical Performance of Two SARS-CoV-2 Serologic Assays
abstract: The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a rapid proliferation of serologic assays. However, little is known about their clinical performance. Here, we compared two commercial SARS-CoV-2 IgG assays.  103 specimens from 48 patients with PCR confirmed SARS-CoV-2 infections and 153 control specimens were analyzed using SARS-CoV-2 serologic assays by Abbott and EUROIMMUN (EI). Duration from symptom onset was determined by medical record review. Diagnostic sensitivity, specificity, and concordance were calculated.  The Abbott SARS-CoV-2 assay had a diagnostic specificity of 99.4% (95% CI; 96.41-99.98%), and sensitivity of 0.0% (95% CI; 0.00-26.47%) at <3 days post symptom onset, 30.0% (95% CI; 11.89-54.28) at 3-7d, 47.8% (95% CI; 26.82-69.41) at 8-13d and 93.8% (95% CI; 82.80-98.69) at ≥14d. Diagnostic specificity on the EI assay was 94.8% (95% CI; 89.96-97.72) if borderline results were considered positive and 96.7% (95% CI; 92.54-98.93) if borderline results were considered negative. The diagnostic sensitivity was 0.0% (95% CI; 0.00-26.47%) at <3d, 25.0% (95% CI; 8.66-49.10) at 3-7d, 56.5% (95% CI; 34.49-76.81) at 3-7d and 85.4% (95% CI; 72.24-93.93) at ≥14d if borderline results were considered positive. The qualitative concordance between the assays was 0.83 (95% CI; 0.75-0.91).  The Abbott SARS-CoV-2 assay had fewer false positive and false negative results than the EI assay. However, diagnostic sensitivity was poor in both assays during the first 14 days of symptoms.

title: Evaluation of Pool-based Testing Approaches to Enable Population-wide Screening for COVID-19
abstract: Rapid testing for an infection is paramount during a pandemic to prevent continued viral spread and excess morbidity and mortality. This study aimed to determine whether alternative testing strategies based on sample pooling can increase the speed and throughput of screening for SARS-CoV-2.  A mathematical modelling approach was chosen to simulate six different testing strategies based on key input parameters (infection rate, test characteristics, population size, testing capacity etc.). The situations in five countries (US, DE, UK, IT and SG) currently experiencing COVID-19 outbreaks were simulated to reflect a broad variety of population sizes and testing capacities. The primary study outcome measurements that were finalised prior to any data collection were time and number of tests required; number of cases identified; and number of false positives.  The performance of all tested methods depends on the input parameters, i.e. the specific circumstances of a screening campaign. To screen one tenth of each country's population at an infection rate of 1% - e.g. when prioritising frontline medical staff and public workers -, realistic optimised testing strategies enable such a campaign to be completed in ca. 29 days in the US, 71 in the UK, 25 in Singapore, 17 in Italy and 10 in Germany (ca. eight times faster compared to individual testing). When infection rates are considerably lower, or when employing an optimal, yet logistically more complex pooling method, the gains are more pronounced. Pool-based approaches also reduces the number of false positive diagnoses by 50%.  The results of this study provide a clear rationale for adoption of pool-based testing strategies to increase speed and throughput of testing for SARS-CoV-2. The current individual testing approach unnecessarily wastes valuable time and resources.

title: Effects of coronavirus disease 2019 (COVID‐19) on maternal, perinatal and neonatal outcomes: a systematic review
abstract: To evaluate the effects of coronavirus disease 2019 (COVID‐19) on maternal, perinatal and neonatal outcomes by performing a systematic review of available published literature on pregnancies affected by COVID‐19.  We performed a systematic review to evaluate the effects of COVID‐19 on pregnancy, perinatal and neonatal outcomes. We conducted a comprehensive literature search using PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure Database and Wan Fang Data until 20 April 2020 (studies were identified through PubMed alert after that date). For the research strategy, combinations of the following keywords and MeSH terms were used: SARS‐CoV‐2, COVID‐19, coronavirus disease 2019, pregnancy, gestation, maternal, mothers, vertical transmission, maternal‐fetal transmission, intrauterine transmission, neonates, infant, delivery.  Exclusion criteria were non‐peer‐reviewed or unpublished reports, unspecified date and location of the study, suspicion of duplicate reporting, and unreported maternal or perinatal outcomes. No language restrictions were applied.  We identified a high number of relevant case reports and case series, but only 24 studies, including a total of 324 pregnant women with COVID‐19, met the eligibility criteria and were included in the systematic review. These comprised nine case series (eight consecutive) and 15 case reports. A total of 20 pregnant patients with laboratory‐confirmed COVID‐19 were included in the case reports. In the combined data from the eight consecutive case series, including 211 (71.5%) cases of laboratory‐confirmed and 84 (28.5%) of clinically diagnosed COVID‐19, the maternal age ranged from 20 to 44 years and the gestational age on admission ranged from 5 to 41 weeks. The most common symptoms at presentation were fever, cough, dyspnea/shortness of breath, fatigue and myalgia. The rate of severe pneumonia reported amongst the case series ranged from 0 to 14%, with the majority of the cases requiring admission to the intensive care unit. Almost all cases from the case series had positive computer tomography chest findings. All six and 22 cases that had nucleic‐acid testing in vaginal mucus and breast milk samples, respectively, were negative for SARS‐CoV‐2. Only four cases of spontaneous miscarriage or abortion were reported. In the consecutive case series, 219/295 women had delivered at the time of reporting, and the majority of these had Cesarean section. The gestational age at delivery ranged from 28 to 41 weeks. Apgar scores at 1 and 5 min ranged from 7 to 10 and 7 to 10, respectively. Only eight neonates had birth weight <2500 g and nearly one‐third of cases were transferred to the neonatal intensive care unit. There was one case each of neonatal asphyxia and neonatal death. In 155 neonates that had nucleic‐acid testing in throat swab, all, except three cases, were negative for SARS‐CoV‐2. There were seven maternal deaths, four intrauterine fetal deaths (one with twin pregnancy) and two neonatal deaths (twin pregnancy) reported in a non‐consecutive case series of nine cases with severe COVID‐19. From the case reports, two maternal deaths, one neonatal death and two cases of neonatal SARS‐CoV‐2 infection were reported.  Despite the increasing number of published studies on COVID‐19 in pregnancy, there are insufficient good‐quality data to draw unbiased conclusions with regard to the severity of the disease or specific complications of COVID‐19 in pregnant women, as well as vertical transmission, perinatal and neonatal complications. In order to answer specific questions in relation to the impact of COVID‐19 on pregnant women and their fetuses through meaningful good‐quality research, we urge researchers and investigators to present complete outcome data and reference previously published cases in their publications, and to record such reporting when the data of a case are entered into a registry or several registries. This article is protected by copyright. All rights reserved.

title: Total COVID-19 Mortality in Italy: Excess Mortality and Age Dependence through Time-Series Analysis
abstract: We perform a counterfactual time series analysis using two different Data Science methods applied to 2020 mortality data reported from towns in Italy, with data from the previous five years as control. We find an excess mortality that is correlated in time with the COVID-19 reported death rate time series. Our analysis shows good agreement with reported COVID-19 mortality for age<70 years, but an excess in total mortality increasing with age above 70 years, suggesting there is a large population of predominantly old people missing from the official fatality statistics. We estimate that the number of COVID-19 deaths in Italy is 52,000 ± 2000 as of April 18 2020, more than a factor of 2 higher than the official number. The Population Fatality Rate (PFR) has reached 0.22% in the most affected region of Lombardia and 0.57% in the most affected province of Bergamo,which constitutes a lower bound to the Infection Fatality Rate (IFR). We estimate PFR as a function of age, finding a steep age dependence: in Lombardia (Bergamo province) 0.6% (1.7%) of the total population in age group 70-79 died, 1.6% (4.6%) in age group 80-89, and 3.41% (10.2%) in the age group above 90. We combine this with the Test Positivity Rate to estimate the lower bound of 0.84% on the IFR for Lombardia. We observe IFR to trace the Yearly Mortality Rate (YMR) above 60 years, which can be used to estimate the IFR for other regions in the world. We predict an IFR lower bound of 0.5% for NYC and 26% of total COVID-19 mortality arising from the population below 65 years, in agreement with the existing data and several times higher than Lombardia. Combining PFR with the Princess Diamond cruise ship IFR for ages above 70 we estimate the infection rates(IR) of regions in Italy, which peak in Lombardia at 23% (12%-41%, 95% c.l.), and for provinces in Bergamo at 67% (33%-100%, 95% c.l.). This suggests that Bergamo may have reached herd immunity, and that the number of infected people greatly exceeds the number of positive tests, by a factor of 35 in Lombardia.

title: COVID-19 in the Shadows of MERS-CoV in the Kingdom of Saudi Arabia.
abstract: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) has plagued the Middle East since it was first reported in 2012. Recently, at the end of December 2019, a cluster of pneumonia cases were reported from Wuhan city, Hubei Province, China, linked to a wet seafood market with a new coronavirus identified as the etiologic agent currently named SARS-CoV-2. Most cases are in Mainland China with international spread to 25 countries. The novelty of the virus, the rapid national and international spread, and the lack of therapeutic and preventative strategies have led the WHO International Health Regulation emergency committee to declare the disease as Public Health Emergency of International Concern (PHEIC) on January 30, 2020. As it relates to countries with the ongoing MERS-CoV community cases and hospital acquired infections, there will be a huge challenge for HCWs to deal with both coronaviruses, especially with the lack of standardized and approved point of care testing. This challenge will now be faced by the whole global health community dealing with COVID-19 since both coronaviruses have similar presentation. Those patients should now be tested for both MERS-CoV and SARS-CoV-2 simultaneously, and with the continuing wide international spread of SARS-CoV-2, the travel history to China in the last 14 days will be of less significance.

title: Target Virus or Target Ourselves for COVID-19 Drugs Discovery?-Lessons learned from anti-influenzas virus therapies
abstract: The COVID-19 pandemic, after it was reported in December 2019, is a highly contagious and now spreading to over 190 countries, causing a severe public health burden. Currently, there is no vaccine or specific drug to treat COVID-19, which is caused by a novel coronavirus, SARS-2-CoV. For this emergency, the FDA has approved Remdesivir and Hydroxychloroquine for treatment of COVID-19 as Emergency Use Authorization. However, even after this pandemic, COVID-19 may still have a chance to come back. Therefore, we need to come out with new strategies for drug discovery for combating COVID-19 in the future.

title: A demographic scaling model for estimating the total number of COVID-19 infections
abstract: Understanding how widely COVID-19 has spread is critical for examining the pandemic's progression. Despite efforts to carefully monitor the pandemic, the number of confirmed cases may underestimate the total number of infections. We introduce a demographic scaling model to estimate COVID-19 infections using an broadly applicable approach that is based on minimal data requirements: COVID-19 related deaths, infection fatality rates (IFRs), and life tables. As many countries lack reliable estimates of age-specific IFRs, we scale IFRs between countries using remaining life expectancy as a marker to account for differences in age structures, health conditions, and medical services. Across 10 countries with most COVID-19 deaths as of May 13, 2020, the number of infections is estimated to be four [95% prediction interval: 2-11] times higher than the number of confirmed cases. Cross-country variation is high. The estimated number of infections is 1.4 million (six times the number of confirmed cases) for Italy; 3.1 million (2.2 times the number of confirmed cases) for the U.S.; and 1.8 times the number of confirmed cases for Germany, where testing has been comparatively extensive. Our prevalence estimates, however, are markedly lower than most others based on local seroprevalence studies. We introduce formulas for quantifying the bias that is required in our data on deaths in order to reproduce estimates published elsewhere. This bias analysis shows that either COVID-19 deaths are severely underestimated, by a factor of two or more; or alternatively, the seroprevalence based results are overestimates and not representative for the total population.

title: Monitoring and forecasting the number of reported and unreported cases of the COVID-19 epidemic in Brazil using Particle Filter
abstract: In this paper, we combine algorithm of Liu & West for the Particle Filter (PF) with SIRU-type epidemic model to monitor and forecast cases of Covid-19 in Brazil from February up to September. We filter the number of cumulative reported cases and estimate model parameters and more importantly unreported infectious cases (asymptomatic and symptomatic infectious individuals). The parameters under study are related to the attenuation factor of the transmission rate and the fraction of asymptomatic infectious becoming reported as symptomatic infectious. Initially, the problem is analysed through Particle Swarm Optimization (PSO) based simulations to provide initial guesses, which are then refined by means of PF simulations. Subsequently, two additional steps are performed to verify the capability of the adjusted model to predict and forecast new cases. According to the results, the pandemic peak is expected to take place in mid-June 2020 with about 25,000 news cases per day. As medical and hospital resources are limited, this result shows that public health interventions are essential and should not be relaxed prematurely, so that the coronavirus pandemic is controlled and conditions are available for the treatment of the most severe cases.

title: CT Manifestations of Novel Coronavirus Pneumonia: A Case Report
abstract: Since December 2019, the outbreak of the novel coronavirus has impacted nearly >90,000 people in more than 75 countries. In this case report, we aim to define the chest computed tomography findings of 2019-novel coronavirus associated with pneumonia and its successful resolution after treatment.  A fifty-year-old female patient, who is a businesswoman, presented with chief complaints of “fever for one week, diarrhea, anorexia, and asthenia.” Initially, she was given Tamiflu. The influenza A virus serology was negative. Three days later, levofloxacin was started because the patient’s symptoms did not improve. The novel coronavirus nucleic acid test was negative. It was noted that before the onset of the disease, the patient went to Wuhan on a business trip. Despite the given treatment, her body temperature rose to 39.2°C and she was referred to our clinic for further evaluation. Then, chest computed tomography was performed and showed bilateral multifocal ground glass opacities with consolidation which suggested viral pneumonia as a differential diagnosis, and the subsequent 2019-novel coronavirus pneumonia nucleic acid test was positive.  Chest computed tomography offers fast and convenient evaluation of patients with suspected 2019-novel coronavirus pneumonia.

title: Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China/ 中华流行病学杂志
abstract: evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments.@*Methods@#Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number R0(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time.@*Results@#For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the R0(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, R0(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the R0(t)s less than 1. The results could be used for the decision making to free population floating conditionally.@* Conclusions@#Dynamic R0(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.

title: Efficacy and safety of Chou-Ling-Dan granules in the treatment of seasonal influenza via combining Western and traditional Chinese medicine: protocol for a multicentre, randomised controlled clinical trial
abstract: Chou-Ling-Dan (CLD) (Laggerapterodonta) granules are an ethnic herbal medicine from Yunnan province of China. CLD granules have been used for the treatment of inflammatory conditions and feverish diseases in China, including seasonal influenza, but few evidence-based medicine (EBM) clinical studies have been conducted to assess its efficacy and safety in the treatment of influenza. Here, we performed an EBM clinical trial combining Western Chinese medicine and traditional Chinese medicine (TCM) evaluation systems to evaluate the efficacy and safety of CLD granules in the treatment of seasonal influenza.  The study is designed as a multicentre, randomised, double-blinded, double-simulation, oseltamivir-controlled and placebo-controlled, parallel-design clinical trial. Eligible subjects (n=318) will be allocated after satisfying the criteria (Western medicine). Subjects will be randomised to receive CLD granules, oseltamivir, or a placebo for 5 days of treatment and with follow-up after treatment to record symptoms and signs and to collect pharyngeal/throat swabs and serum samples for detecting the virus and antibodies. At the same time, the syndrome differentiation criteria of TCM, such as tongue body, furred tongue and type of pulse, will be recorded as determined by doctors of both Western and Chinese medicine. Participants will be instructed to comply with the protocol and to keep a daily record of symptoms. The primary and secondary outcomes and safety indicators will be used to evaluate the efficacy and safety of CLD granules in the treatment of seasonal influenza based on both Western Chinese medicine and TCM evaluation systems.  The CLD granules clinical trial will be conducted in accordance with the Declaration of Helsinki and Good Clinical Practice and has been approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University. All participants must provide written informed consent. The results obtained will be disseminated at international medical conferences and in peer-reviewed publications.

title: Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis
abstract: Coronavirus disease 2019 (COVID-19) is a novel infectious disease with lack of established laboratory markers available to evaluate illness severity. In this study, we investigate whether platelet count could differentiate between COVID-19 patients with or without severe disease. Additionally, we evaluate if thrombocytopenia is associated with severe COVID-19.  An electronic search in Medline, Scopus and Web of Science was performed to identify studies reporting data on platelet count in COVID-19 patients. A meta-analysis was performed, with calculation of weighted mean difference (WMD) of platelet number in COVID-19 patients with or without severe disease and odds ratio (OR) of thrombocytopenia for severe form of COVID-19.  Nine studies with 1779 COVID-19 patients, 399 (22.4%) with severe disease, were included in the meta-analysis. The pooled analysis revealed that platelet count was significantly lower in patients with more severe COVID-19 (WMD -31×10(9)/L; 95% CI, from -35 to -29×10(9)/L). A subgroup analysis comparing patients by survival, found an even lower platelet count was observed with mortality (WMD, -48×10(9)/L; 95% CI, -57 to -39×10(9)/L. In the four studies (n=1427) which reported data on rate of thrombocytopenia, a low platelet count was associated with over fivefold enhanced risk of severe COVID-19 (OR, 5.1; 95% CI, 1.8-14.6).  Low platelet count is associated with increased risk of severe disease and mortality in patients with COVID-19, and thus should serve as clinical indicator of worsening illness during hospitalization.

title: Need for integrative thinking to fight against emerging infectious diseases. Proceedings of the 5th seminar on emerging infectious diseases, March 22, 2016 – current trends and proposals
abstract: We present here the proceedings of the 5th seminar on emerging infectious diseases, held in Paris on March 22nd, 2016, with seven priority proposals that can be outlined as follows: encourage research on the prediction, screening and early detection of new risks of infection; develop research and surveillance concerning transmission of pathogens between animals and humans, with their reinforcement in particular in intertropical areas (“hot-spots”) via public support; pursue aid development and support in these areas of prevention and training for local health personnel, and foster risk awareness in the population; ensure adapted patient care in order to promote adherence to treatment and to epidemic propagation reduction measures; develop greater awareness and better education among politicians and healthcare providers, in order to ensure more adapted response to new types of crises; modify the logic of governance, drawing from all available modes of communication and incorporating new information-sharing tools; develop economic research on the fight against emerging infectious diseases, taking into account specific driving factors in order to create a balance between preventive and curative approaches.

title: Forecasting the novel coronavirus COVID-19
abstract: What will be the global impact of the novel coronavirus (COVID-19)? Answering this question requires accurate forecasting the spread of confirmed cases as well as analysis of the number of deaths and recoveries. Forecasting, however, requires ample historical data. At the same time, no prediction is certain as the future rarely repeats itself in the same way as the past. Moreover, forecasts are influenced by the reliability of the data, vested interests, and what variables are being predicted. Also, psychological factors play a significant role in how people perceive and react to the danger from the disease and the fear that it may affect them personally. This paper introduces an objective approach to predicting the continuation of the COVID-19 using a simple, but powerful method to do so. Assuming that the data used is reliable and that the future will continue to follow the past pattern of the disease, our forecasts suggest a continuing increase in the confirmed COVID-19 cases with sizable associated uncertainty. The risks are far from symmetric as underestimating its spread like a pandemic and not doing enough to contain it is much more severe than overspending and being over careful when it will not be needed. This paper describes the timeline of a live forecasting exercise with massive potential implications for planning and decision making and provides objective forecasts for the confirmed cases of COVID-19.

title: Doubling Time of the COVID-19 Epidemic by Chinese Province
abstract: COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. The harmonic mean of the arithmetic mean doubling time estimates ranged from 1.4 (Hunan, 95% CI, 1.2–2.0) to 3.1 (Xinjiang, 95% CI, 2.1–4.8), with an estimate of 2.5 days (95% CI, 2.4–2.6) for Hubei.

title: Analysis of temporal trends in potential COVID-19 cases reported through NHS Pathways England
abstract: The NHS Pathways triage system collates data on enquiries to 111 and 999 services in England. Since the 18th of March 2020, these data have been made publically available for potential COVID-19 symptoms self-reported by members of the public. Trends in such reports over time are likely to reflect behaviour of the ongoing epidemic within the wider community, potentially capturing valuable information across a broader severity profile of cases than hospital admission data. We present a fully reproducible analysis of temporal trends in NHS Pathways reports until 14th May 2020, nationally and regionally, and demonstrate that rates of growth/decline and effective reproduction number estimated from these data may be useful in monitoring transmission. This is a particularly pressing issue as lockdown restrictions begin to be lifted and evidence of disease resurgence must be constantly reassessed. We further assess the correlation between NHS Pathways reports and a publicly available NHS dataset of COVID-19-associated deaths in England, finding that enquiries to 111/999 were strongly associated with daily deaths reported 16 days later. Our results highlight the potential of NHS Pathways as the basis of an early warning system. However, this dataset relies on self-reported symptoms, which are at risk of being severely biased. Further detailed work is therefore necessary to investigate potential behavioural issues which might otherwise explain our conclusions.

title: Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods
abstract: Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach, coupled with Monte Carlo methods, to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 countries where reliable data are available. We find a positive relationship between the testing rate per 1,000 people and the implied true detection rate of COVID-19, and a negative relationship between the proportion who test positive and the implied true detection rate. Our estimates suggest that the true number of people infected across our sample of 15 developed countries is 18.2 (5-95% CI: 11.9-39.0) times greater than the reported number of cases. In individual countries, the true number of cases exceeds the reported figure by factors that range from 1.7 (5-95% CI: 1.1-3.6) for Australia to 35.6 (5-95% CI: 23.2-76.3) for Belgium.

title: Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations
abstract: As coronavirus disease 2019 (COVID-19) spreads across the world, the intensive care unit (ICU) community must prepare for the challenges associated with this pandemic. Streamlining of workflows for rapid diagnosis and isolation, clinical management, and infection prevention will matter not only to patients with COVID-19, but also to health-care workers and other patients who are at risk from nosocomial transmission. Management of acute respiratory failure and haemodynamics is key. ICU practitioners, hospital administrators, governments, and policy makers must prepare for a substantial increase in critical care bed capacity, with a focus not just on infrastructure and supplies, but also on staff management. Critical care triage to allow the rationing of scarce ICU resources might be needed. Researchers must address unanswered questions, including the role of repurposed and experimental therapies. Collaboration at the local, regional, national, and international level offers the best chance of survival for the critically ill.

title: Serial interval of novel coronavirus (2019-nCoV) infections
abstract: To estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs.  We collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset (n=28) and a subset of pairs with highest certainty in reporting (n=18). In addition, we adjusting for right truncation of the data as the epidemic is still in its growth phase.  Accounting for right truncation and analyzing all pairs, we estimated the median serial interval at 4.0 days (95% credible interval [CrI]: 3.1, 4.9). Limiting our data to only the most certain pairs, the median serial interval was estimated at 4.6 days (95% CrI: 3.5, 5.9).  The serial interval of COVID-19 is shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 serial interval is also shorter than the serial interval of severe acute respiratory syndrome (SARS), indicating that calculations made using the SARS serial interval may introduce bias.

title: Chapter 7 Scientific Advances in the Diagnosis of Emerging and Reemerging Viral Human Pathogens
abstract: Despite scientific advances, the diagnosis of infectious diseases is primarily possible through vaccination and later by antibiotics. Emerging and reemerging pathologies are still considered to be dangerous to humanity because of the unique nature of these diseases: it is the encounter between two living organisms that have coexisted for millions of years within the people on the same planet without being previously recognized. These infectious agents, such as bacteria, viruses, fungi, or parasites, pose no threat to humans. In fact, only a few hundred are able to inflict damage to the human host. In addition, the spectrum of human disease caused by a particular pathogen varies considerably depending on the factors related to the ecological agent, the host, and the infectious agents. Several emerging or reemerging infectious agents are organisms that could be used in biological control. The differentiation of a natural epidemic from a bioterrorian event is based on several epidemiological indices as well as on the molecular characterization of the pathogen(s) involved. The role of pathologists is indeed very important. It is in this context that this chapter aims to discuss the various scientific advances, particularly molecular, in terms of diagnosis of these diseases; the new discoveries in the role of nanotechnologies and nanobiosensors; and also the implication of biomarkers, especially microRNAs (miRNAs), since it was reported that a single miRNA has the ultimate capacity to target multiple genes simultaneously. In a viral infection context, miRNAs have been connected with the interplay between host and pathogen and occupy a major role in the host–parasite interaction and pathogenesis. It is in this context that various molecular and nanomethods for the detection of emerging viruses and experimental validation of miRNAs during quelling viruses target transcripts will be discussed in this chapter.

title: Seeding COVID-19 across sub-Saharan Africa: an analysis of reported importation events across 40 countries
abstract: The first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. While case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, SSA countries remain vulnerable to significant COVID morbidity and mortality due to systemic healthcare weaknesses, less financial resources and infrastructure to address the new crisis, and untreated comorbidities. Variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events.  Confirmed cases reported by SSA countries were line-listed to capture epidemiological details related to early transmission events into and within countries. Data were retrieved from publicly available sources, including institutional websites, situation reports, press releases, and social media accounts, with supplementary details obtained from news articles. A data availability score was calculated for each imported case in terms of how many indicators (sex, age, travel history, date of arrival in country, reporting date of confirmation, and how detected) could be identified. We assessed the relationship between time to first importation and overall Global Health Security Index (GHSI) using Cox regression. K-means clustering grouped countries according to healthcare capacity and health and demographic risk factors.  A total of 2417 confirmed cases of COVID-19 were reported by 40 countries in sub-Saharan Africa during the 30 days after the first known introduction to the region. Out of the 876 cases for which information was publicly available, 677 (77.3%) were considered importation events. At the regional level, imported cases tended to be male (67.3%), were a median 43.0 years old (Range: 6 weeks - 88 years), and most frequently had recent travel history from Europe (43.3%). The median time to reporting an introduction was 19 days; a country's time to report its first importation was not related to GHSI. Mean data availability scores were lowest for countries that had, on average, the highest case fatality rates, lowest healthcare capacity, and highest probability of premature death due to non-communicable diseases.  Countries with systemic, demographic, and pre-existing health vulnerabilities to severe COVID-related morbidity and mortality are less likely to report any cases or are reporting with limited public availability of information. Reporting of information on COVID detection and response efforts, as well as on trends in non-COVID illness and care-seeking behavior, is critical to assessing direct and indirect consequences and capacity needs in resource-constrained settings. Such assessments aid in the ability to make data-driven decisions about interventions, country priorities, and risk assessment.

title: A Global Scale Estimate of Novel Coronavirus (COVID-19) Cases Using Extreme Value Distributions
abstract: The COVID 19 pandemic has created a global crisis and the governments are fighting rigorously to control the spread by imposing intervention measures and increasing the medical facilities. In order to tackle the crisis effectively we need to know the trajectories of number of the people infected (i.e. confirmed cases). Such information is crucial to government agencies for developing effective preparedness plans and strategies. We used a statistical modeling approach (extreme value distributions, EVDs) for projecting the future confirmed cases on a global scale. Using the 69 days data (from January 22, 2020 to March 30, 2020), the EVDs model predicted the number of confirmed cases from March 31, 2020 to April 9, 2020 (validation period) with an absolute percentage error < 15 % and then projected the number of confirmed cases until the end of June 2020. Also, we have quantified the uncertainty in the future projections due to the delay in reporting of the confirmed cases on a global scale. Based on the projections, we found that total confirmed cases would reach around 11.4 million globally by the end of June 2020.The USA may have 2.9 million number of confirmed cases followed by Spain(1.52 million) and Italy (1.28 million).

title: Projections for COVID-19 pandemic in India and effect of temperature and humidity
abstract: As, the COVID-19 has been deemed a pandemic by World Health Organization (WHO), and since it spreads everywhere throughout the world, investigation in relation to this disease is very much essential. Investigation of pattern in the occurrence of COVID-19, to check the influence of different meteorological factors on the incidence of COVID-19 and prediction of incidence of COVID-19 are the objectives of this paper.  For trend analysis, Sen's Slope and Man-Kendall test have been used, Generalized Additive Model (GAM) of regression has been used to check the influence of different meteorological factors on the incidence and to predict the frequency of COVID-19, and Verhulst (Logistic) Population Model has been used.  Statistically significant linear trend found for the daily-confirmed cases of COVID-19. The regression analysis indicates that there is some influence of the interaction of average temperature (AT) and average relative humidity (ARH) on the incidence of COVID-19. However, this result is not consistent throughout the study area. The projections have been made up to 21st May, 2020.  Trend and regression analysis give an idea of the incidence of COVID-19 in India while projection made by Verhulst (Logistic) Population Model for the confirmed cases of the study area are encouraging as the sample prediction is as same as the actual number of confirmed COVID-19 cases.

title: Malaria and Parasitic Neglected Tropical Diseases: Potential Syndemics with COVID-19?
abstract: The COVID-19 pandemic, caused by SARS-CoV-2, have surpassed 5 million cases globally. Current models suggest that low- and middle-income countries (LMICs) will have a similar incidence but substantially lower mortality rate than high-income countries. However, malaria and neglected tropical diseases (NTDs) are prevalent in LMICs, and coinfections are likely. Both malaria and parasitic NTDs can alter immunologic responses to other infectious agents. Malaria can induce a cytokine storm and pro-coagulant state similar to that seen in severe COVID-19. Consequently, coinfections with malaria parasites and SARS-CoV-2 could result in substantially worse outcomes than mono-infections with either pathogen, and could shift the age pattern of severe COVID-19 to younger age-groups. Enhancing surveillance platforms could provide signals that indicate whether malaria, NTDs, and COVID-19 are syndemics (synergistic epidemics). Based on the prevalence of malaria and NTDs in specific localities, efforts to characterize COVID-19 in LMICs could be expanded by adding testing for malaria and NTDs. Such additional testing would allow the determination of the rates of coinfection and comparison of severity of outcomes by infection status, greatly improving the understanding of the epidemiology of COVID-19 in LMICs and potentially helping to mitigate its impact.

title: Internet and Free Press Are Associated with Reduced Lags in Global Outbreak Reporting
abstract: Global outbreak detection and reporting have generally improved for a variety of infectious diseases and geographic regions in recent decades. Nevertheless, lags in outbreak reporting remain a threat to the global human health and economy. In the time between first occurrence of a novel disease incident and public notification of an outbreak, infected individuals have a greater possibility of traveling and spreading the pathogen to other nations. Shortening outbreak reporting lags has the potential to improve global health by preventing local outbreaks from escalating into global epidemics.  Reporting lags between the first record and the first public report of an event were calculated for 318 outbreaks occurring 1996-2009. The influence of freedom of the press, Internet usage, per capita health expenditure, and cell phone subscriptions, on the timeliness of outbreak reporting was evaluated.  Freer presses and increasing Internet usage correlate with reduced time between the first record of an outbreak and the public report. Increasing Internet usage reduced the expected reporting lag from more than one month in nations without Internet users to one day in those where 75 of 100 people use the Internet.  Advances in technology and the emergence of more open and free governments are associated with to improved global infectious disease surveillance.

title: Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA
abstract: Despite widespread use, the accuracy of the diagnostic test for SARS-CoV-2 infection is poorly understood. The aim of our work was to better quantify misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves using publicly available surveillance data from Alberta, Canada and Philadelphia, USA.  We examined time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, the sensitivity and specificity of the diagnostic test.  Our analysis revealed that the data were compatible with near-perfect specificity, but it was challenging to gain information about sensitivity. We applied these insights to uncertainty/bias analysis of epidemic curves under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the adjusted epidemic curves likely falls within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60–70% range. In the extreme scenario, hundreds of undiagnosed cases, even among the tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate.  The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves.

title: Comparison of SARS‐CoV‐2 detection from nasopharyngeal swab samples by the Roche cobas 6800 SARS‐CoV‐2 test and a laboratory‐developed real‐time RT‐PCR test
abstract: The urgent need to implement and rapidly expand testing for severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection has led to the development of multiple assays. How these tests perform relative to one another is poorly understood. We evaluated the concordance between the Roche Diagnostics cobas 6800 SARS‐CoV‐2 test and a laboratory‐developed test (LDT) real‐time reverse transcription‐polymerase chain reaction based on a modified Centers for Disease Control and Prevention protocol, for the detection of SARS‐CoV‐2 in samples submitted to the Clinical Laboratories of the Mount Sinai Health System. A total of 1006 nasopharyngeal swabs in universal transport medium from persons under investigation were tested for SARS‐CoV‐2 as part of routine clinical care using the cobas SARS‐CoV‐2 test with subsequent evaluation by the LDT. Cycle threshold values were analyzed and interpreted as either positive (“detected” or “presumptive positive”), negative (not detected), inconclusive, or invalid. Statistical analysis was performed using GraphPad Prism 8. The cobas SARS‐CoV‐2 test reported 706 positive and 300 negative results. The LDT reported 640 positive, 323 negative, 34 inconclusive, and 9 invalid results. When excluding inconclusive and invalid results, the overall percent agreement between the two platforms was 95.8%. Cohen's κ coefficient was 0.904 (95% confidence interval, 0.875‐0.933), suggesting almost perfect agreement between both platforms. An overall discordance rate of 4.2% between the two systems may reflect differences in primer sequences, assay limit of detection, or other factors, highlighting the importance of comparing the performance of different testing platforms.

title: Real-time monitoring the transmission potential of COVID-19 in Singapore, March 2020
abstract: As of March 31, 2020 the ongoing COVID-19 epidemic that started in China in December 2019 is now generating local transmission around the world. The geographic heterogeneity and associated intervention strategies highlight the need to monitor in real time the transmission potential of COVID-19. Singapore provides a unique case example for monitoring transmission, as there have been multiple disease clusters, yet transmission remains relatively continued.  Here we estimate the effective reproduction number, R(t), of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays as of March 17, 2020. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis that accounts for truncation of case counts.  The local incidence curve displays sub-exponential growth dynamics, with the reproduction number following a declining trend and reaching an estimate at 0.7 (95% CI: 0.3, 1.0) during the first transmission wave by February 14, 2020 while the overall R based on the cluster size distribution as of March 17, 2020 was estimated at 0.6 (95% CI: 0.4, 1.02). The overall mean reporting delay was estimated at 6.4 days (95% CI: 5.8, 6.9), but it was shorter among imported cases compared to local cases (mean 4.3 vs. 7.6 days, Wilcoxon test, p<0.001).  The trajectory of the reproduction number in Singapore underscores the significant effects of successful containment efforts in Singapore, but it also suggests the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.

title: COVID-19 Pandemic and Surgical Oncology: Preserving the Academic Mission
abstract: The global pandemic of respiratory disease cause by the novel human coronavirus (SARS-CoV-2) has caused untold suffering, loss of life and upheaval in society. The pandemic has lead to massive redirection of health care resources to treat the surge of COVID-19 patients, and enforcement of social distancing to reduce the rate of transmission.  Editorial Board members provided observations of the implications of the pandemic on academic surgical oncology.  Delivery of health care to other populations including cancer patients has been significantly disrupted. The implications both short term and long term threaten preservation of the academic mission in medicine at large, and certainly in the field of surgical oncology.  The effects on surgical oncology training, research and clinical trials are major.

title: UV Sterilization of Personal Protective Equipment with Idle Laboratory Biosafety Cabinets During the Covid-19 Pandemic
abstract: Personal protective equipment (PPE), including surgical masks and N95 respirators, is crucially important to the safety of both patients and medical personnel, particularly in the event of infectious pandemics. As the incidence of Coronavirus Disease (COVID-19) is increasing exponentially in the United States and worldwide, healthcare provider demand for these necessities is currently outpacing supply. As such, strategies to safely expand the lifespan of the supply of medical equipment are critically important. In the recent days, weeks, and months, in the midst of the current pandemic, there has been a concerted effort to identify viable ways to conserve Personal Protective Equipment, including sterilization after use. Some hospitals have already begun using UV-C light to sterilize N95 respirators, but many lack the space or equipment to implement existing protocols. In this study, we outline a procedure by which N95 respirators may be sterilized using ultraviolet (UV) radiation in biosafety cabinets (BSCs), a common element of many academic, public health, and hospital laboratories. The primary obstacle to this approach is the possibility the UV radiation levels vary within BSCs. To account for this potential variation in dosing across the base of the BSC, we tested the UV-C radiation in two randomly chosen idle BSCs in our research institute and observed a maximum ratio between the minimum and maximum recorded intensities within a given BSC to be 1.98. Based on these values, we calculated that an N95 mask placed within a BSC with a manufacturer reported fluence of 100 W/cm^2 should be effectively sanitized for reuse after approximately 15-20 minutes per side. Our results provide support to healthcare organizations looking for alternative methods to extend their reserves of PPE. It is our hope that with an easily implemented strategy, as we have presented here, idle BSCs can be utilized to alleviate the PPE shortage by providing a way to sterilize PPE to allow safe daily re-use. This should be tested on a larger scale, and confirmed in a virology laboratory before adoption, though we contend that in extremis, this method would be preferred compared to re-use without sterilization.

title: How will this continue? Modelling interactions between the COVID-19 pandemic and policy responses
abstract: Much of the uncertainty about the progression of the COVID-19 pandemic stems from questions about when and how non-pharmaceutical interventions (NPI) by governments, in particular social distancing measures, are implemented, to what extent the population complies with these measures, and how compliance changes through time. Further uncertainty comes from a lack of knowledge of the potential effects of removing interventions once the epidemic is declining. By combining an epidemiological model of COVID-19 for the United Kingdom with simple sub-models for these societal processes, this study aims to shed light on the conceivable trajectories that the pandemic might follow over the next 1.5 years. We show strong improvements in outcomes if governments review NPI more frequently whereas, in comparison, the stability of compliance has surprisingly small effects on cumulative mortality. Assuming that mortality does considerably increase once a country's hospital capacity is breached, we show that the inherent randomness of societal processes can lead to a wide range of possible outcomes, both in terms of disease dynamics and mortality, even when the principles according to which policy and population operate are identical.. Our model is easily modified to take other aspects of the socio-pandemic interaction into account.

title: Outbreak of Middle East respiratory syndrome coronavirus in Saudi Arabia: a retrospective study
abstract: The Middle East respiratory syndrome (MERS) is proposed to be a zoonotic disease. Dromedary camels have been implicated due to reports that some confirmed cases were exposed to camels. Risk factors for MERS coronavirus (MERS-CoV) infections in humans are incompletely understood. This study aimed to describe the demographic characteristics, mortality rate, clinical manifestations and comorbidities with confirmed cases of MERS-CoV.  Retrospective chart review were performed to identify all laboratory-confirmed cases of MERS-CoV in Saudi Arabia who reported to the Ministry of Health (MOH) of Saudi Arabia and WHO between April 23, 2014 and August 31, 2015. Patients’ charts were also reviewed for demographic information, mortality, comorbidities, clinical presentations, health care facility and presented with descriptive and comparative statistics using non parametric binomial test and Chi-square test.  Confirmed cases of male patients (61.1%) exceeded those of female patients (38.9%). Infections among Saudi patients (62.6%) exceeded those among non-Saudi patients (37.4%; P = 0.001). The majority of the patients were aged 21–40 years (37.4%) or 41–60 years (35.8%); 43 (22.6%) were aged >61 years, and (8) 4.2% were aged 0–20 years. There was a difference in mortality between confirmed MERS-CoV cases (63.7% alive versus 36.3% dead cases, respectively). Furthermore, fever with cough and shortness of breath (SOB) (n = 39; 20.5%), fever with cough (n = 29; 15.3%), fever (n = 18; 9.5%), and fever with SOB (n = 13; 6.8%), were the most common clinical manifestations associated with confirmed MERS-CoV cases.  MERS-CoV is considered an epidemic in Saudi Arabia. The results of the present study showed that the frequency of cases is higher among men than women, in Saudi patients than non-Saudi, and those between 21 to 60 years are most affected. Further studies are required to improve the surveillance associated with MERS-CoV to get definite and clear answers and better understanding of the MERS-CoV outbreak as well the source, and route of infection transmission in Saudi Arabia.

title: Control Strategies to Curtail Transmission of COVID-19
abstract: Recently, the World Health Organization has declared the outbreak of a severe acute respiratory syndrome coronavirius as a pandemic, and declared it as Public Health Emergency of International Concern. More than 6,83,536 positive cases and 32,139 deaths caused by coronavirus 2019 affecting 199 countries and territories. This pandemic can transform into an extremely destructive form if we still do not take it seriously. In this present study, we propose a generalized SEIR model of COVID-2019 to study the behavior of its transmission under different control strategies.

title: Disaster incubation, cumulative impacts and the urban/ex-urban/rural dynamic
abstract: This article explores environmental impacts and risks that can accumulate in rural and ex-urban areas and regions and their relation to urban and global development forces. Two Southern Ontario cases are examined: an area level water disaster and cumulative change at the regional level. The role of disaster incubation analysis and advanced environmental assessment tools are discussed in terms of their potential to contribute to more enlightened and effective assessment and planning processes. It is concluded that conventional approaches to EA and planning are characteristically deficient in addressing the full range of impacts and risks, and particularly those originating from pathogens, dispersed and insidious sources. Rigorous application of disaster incubation analysis and more advanced forms of EA has considerable potential to influence a different pattern of planning and decision making.

title: New Methanol Poisoning Outbreaks in Iran Following COVID-19 Pandemic

title: Chinese effective control and other countries uncharted challenge against COVID-19: an epidemiological and modelling study
abstract: On the present trajectory, COVID is inevitably becoming a global epidemic, leading to concerns regarding the pandemic potential in China and other countries.  In this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries.  We used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide.  Based on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18 (IQR 1.92 - 6.65) days. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb (Rt were 0.99 {+/-} 0.02, 0.99 {+/-} 0.02 and 0.96 {+/-} 0.02), respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore (Rt was 0.92 {+/-} 0.17).  The epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.

title: COVID-19 in Italy: impact of containment measures and prevalence estimates of infection in the general population.
abstract: Since the beginning of the COVID-19 epidemic in Italy, the Italian Government implemented several restrictive measures to contain the spread of the infection. Data shows that, among these measures, the lockdown implemented as of 9 March had a positive impact, in particular the central and southern regions of Italy, while other actions appeared to be less effective. When the true prevalence of a disease is unknown, it is possible estimate it, based on mortality data and the assumptive case-fatality rate of the disease. Given these assumptions, the estimated period-prevalence of COVID-19 in Italy varies from 0.35% in Sicity to 13.3% in Lombardy.

title: The risk factors associated with MERS-CoV patient fatality: A global survey
abstract: Risk factors associated with Middle East respiratory syndrome coronavirus (MERS-CoV) infection outcome were established by analyses of WHO data from September 23, 2012 to 18 June 2018. Of the 2220 reported cases, 1408 cases, including 451 MERS-CoV deaths, were analyzed. The case fatality rate was 32% (95% CI: 29.4–34.5). Compared to MERS patients ≤30 years old, those with >30 years had the adjusted odds ratio estimate for death of 2.38 [95% CI: 1.75–3.22]. This index was 1.43 [95% CI: 1.06–1.92] for Saudi patients in comparison to non-Saudi; 1.76 [95% CI: 1.39–2.22] for patient with comorbidity in comparison to those without comorbidity; 0.58 [95% CI: 0.44–0.75] for those who had close contact to a camel in the past 14 days and 0.42 [95% CI: 0.31–0.57] for patients with >14 days with onset of signs and hospital admission compared to patients with ≤14 days.

title: Cardiovascular Considerations for Patients, Health Care Workers, and Health Systems During the Coronavirus Disease 2019 (COVID-19) Pandemic
abstract: The coronavirus disease-2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 that has significant implications for the cardiovascular care of patients. First, those with COVID-19 and preexisting cardiovascular disease (CVD) have an increased risk of severe disease and death. Second, infection has been associated with multiple direct and indirect cardiovascular complications including acute myocardial injury, myocarditis, arrhythmias and venous thromboembolism. Third, therapies under investigation for COVID-19 may have cardiovascular side effects. Fourth, the response to COVID-19 can compromise the rapid triage of non-COVID-19 patients with cardiovascular conditions. Finally, the provision of cardiovascular care may place health care workers in a position of vulnerability as they become host or vectors of virus transmission. We hereby review the peer-reviewed and  literature pertaining to cardiovascular considerations related to COVID-19 and highlight gaps in knowledge that require further study pertinent to patients, health care workers, and health systems.

title: Data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing
abstract: We show that the COVID-19 pandemic under social distancing exhibits universal dynamics. The cumulative numbers of both infections and deaths quickly cross over from exponential growth at early times to a longer period of power law growth, before eventually slowing. In agreement with a recent statistical forecasting model by the IHME, we show that this dynamics is well described by the erf function. Using this functional form, we perform a data collapse across countries and US states with very different population characteristics and social distancing policies, confirming the universal behavior of the COVID-19 outbreak. We show that the predictive power of statistical models is limited until a few days before curves flatten, forecast deaths and infections assuming current policies continue and compare our predictions to the IHME models. We present simulations showing this universal dynamics is consistent with disease transmission on scale-free networks and random networks with non-Markovian transmission dynamics.

title: Effects of temperature and humidity on the spread of COVID-19: A systematic review.
abstract: Faced with the global pandemic of COVID-19, declared by World Health Organization (WHO) on March 11th 2020, and the need to better understand the seasonal behavior of the virus, our team conducted this systematic review to describe current knowledge about the emergence and replicability of the virus and its correlation with different weather factors such as temperature and relative humidity.  The review was registered with the PROSPERO database. The electronic databases PubMed, Scopus, Web of Science, Cochrane Library, LILACS, OpenGrey and Google Scholar were examined with the searches restricted to the years 2019 and 2020. Risk of bias assessment was performed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist tool. The GRADE tool was used to assess the quality of the evidence.  The initial screening identified 517 articles. After examination of the full texts, seventeen studies met the review's eligibility criteria. Great homogeneity was observed in the findings regarding the effect of temperature and humidity on the seasonal viability and transmissibility of COVID-19. Cold and dry conditions were potentiating factors on the spread of the virus. After quality assessment, four studies had a high risk of bias and thirteen studies were scored as moderate risk of bias. The certainty of evidence was graded as low for both outcomes evaluated.  Considering the existing scientific evidence, warm and wet climates seem to reduce the spread of COVID-19. The certainty of the evidence generated was graded as low. However, these variables alone could not explain most of the variability in disease transmission.

title: COVID-19 pandemic perception in adults with celiac disease: an impulse to implement the use of telemedicine: COVID-19 and CeD
abstract: Coronavirus Disease 2019 (COVID-19) causes severe complications and deaths all over the world. COVID-19 also has indirect effects from the lockdown and the possible lack of food. We aimed to evaluate the perception of this in Celiac Disease (CeD) patients who require a lifelong gluten-free diet as a therapy.  We invited by e-mail CeD adult patients from the University of Salerno (Campania, South Italy) and the University of Padua (Veneto, North Italy) to answer an ad hoc COVID-19 survey.  We sent the web survey to 651 email addresses and we received 276 answers (42,4%). CeD patients did not feel more vulnerable because they had CeD (not at all 56.6%)and they did not worry much about the possible shortness of gluten-free food during the epidemic(not at all 48.5%)The most worried were the elderly patients, patients with other comorbidities and females. Finally, CeD patients were happy with remote consultations and explicitly asked to have them.  The COVID-19 pandemic has impacted a proportion of patients with CeD; in particular, women, elderly patients, patients with other comorbidities. COVID-19, although a challenging experience from the medical and the psychological point of view, has offered an opportunity to practice, on a large-scale, a remote consultation approach for CeD healthcare.

title: Challenges of global surveillance during an influenza pandemic
abstract: Surveillance is an essential foundation for monitoring and evaluating any disease process, and is especially critical when new disease agents appear. The H1N1 influenza pandemic of 2009 tested the capacities of countries to detect, assess, notify and report events as required by the 2005 International Health Regulations (IHR). As detailed in the IHR, the World Health Organization drew on official reports from Member States as well as unofficial sources (e.g. media alerts) to quickly report and disseminate information about the appearance of the novel influenza virus. The pre-existing Global Influenza Surveillance Network for virological surveillance also provided crucial information for rapid development of a vaccine and for detection of changes in the virus. However, the pandemic also highlighted a number of shortcomings in global epidemiological surveillance for respiratory disease. These included the lack of standards for reporting illness, risk factor and mortality data, and a mechanism for systematic reporting of epidemiological data. Such measures would have facilitated direct comparison of data between countries and improved timely understanding of the characteristics and impact of the pandemic. This paper describes the surveillance strategies in place before the pandemic and the methods that were used at global level to monitor the pandemic. Enhancements of global surveillance are proposed to improve preparedness and response for similar events in the future.

title: The United States and Canada as a coupled epidemiological system: An example from hepatitis A
abstract: Hepatitis A (HA) is a low-incidence, non-endemic disease in Canada and the United States (US). However, a large difference in HA incidence between Canada and HA-endemic countries has made travel an important contributor to hepatitis A prevalence in Canada. There is also a (smaller) incidence differential between Canada and the US. Although the US has only moderately higher HA incidence, the volume of travel by Canadians to the US is many times higher than travel volume to endemic countries. Hence, travel to the US may constitute a source of low to moderate risk for Canadian travelers. To our knowledge, travel to the US has never been included as a potential risk factor for HA infection in Canadian epidemiologic analyses. The objective of this study was to use dynamic models to investigate the possible effects on hepatitis A incidence in Canada due to (1) implementing vaccination in the US, and (2) varying the volume of travel by Canadians to the US.  We developed and analyzed age-structured compartmental models for the transmission and vaccination of hepatitis A, for both Canada and the US. Models were parameterized using data on seroprevalence, case reporting, and travel patterns. The potential effect of hepatitis A prevalence in the US on hepatitis A prevalence in Canada was captured through a term representing infection of Canadians due to travel in the US.  The model suggests that approximately 22% of HA cases in Canada in the mid 1990s may have been attributable to travel to the US. A universal vaccination programme that attained 70% coverage in young children in the US in the mid 1990s could have reduced Canadian incidence by 21% within 5 years.  Since not all necessary data were available to parameterize the model, the results should be considered exploratory. However, the analysis shows that, under plausible assumptions, the US may be more important for determining HA prevalence in Canada than is currently supposed. As international travel continues to grow, making vaccination policies ever more relevant to populations beyond a country's borders, such multi-country models will most likely come into wider use as predictive aids for policy development.

title: Diagnosing COVID-19: Did We Miss Anything?
abstract: In late 2019, a mass of patients showing symptoms of a pneumonia-like disease of unknown origin emerged in Wuhan, China. Little did the world know it was the prelude of what would be a devastating pandemic. Samples were collected from these patients and the use of unbiased sequencing, and subsequent isolation of the pathogen using human airway epithelial cells led to the discovery of a novel coronavirus, named 2019-nCoV by the World Health Organization (WHO) and Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses. The disease caused by this virus is officially called the coronavirus disease 2019 (COVID-19).

title: Asymptomatic novel coronavirus pneumonia patient outside Wuhan: The value of CT images in the course of the disease
abstract: The purpose of this case report is to describe the imaging and associated clinical features of an asymptomatic novel coronavirus pneumonia (COVID-19) patient outside Wuhan, China. The principle findings are that in this patient with laboratory-confirmed COVID-19, CT findings preceded symptoms and included bilateral pleural effusions, previously not reported in association with COVID-19. The role of this case report is promotion of potential recognition amongst radiologists of this new disease, which has been declared a global health emergency by the World Health Organization (WHO).

title: Machine Learning Analysis of Chest CT Scan Images as a Complementary Digital Test of Coronavirus (COVID-19) Patients
abstract: This paper reports on the development and performance of machine learning schemes for the analysis of Chest CT Scan images of Coronavirus COVID-19 patients and demonstrates significant success in efficiently and automatically testing for COVID-19 infection. In particular, an innovative frequency domain algorithm, to be called FFT-Gabor scheme, will be shown to predict in almost real-time the state of the patient with an average accuracy of 95.37%, sensitivity 95.99% and specificity 94.76%. The FFT-Gabor scheme is adequately informative in that clinicians can visually examine the FFT-Gabor feature to support their final diagnostic.

title: COVID-19 in the Shadows of MERS-CoV in the Kingdom of Saudi Arabia
abstract: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) has plagued the Middle East since it was first reported in 2012. Recently, at the end of December 2019, a cluster of pneumonia cases were reported from Wuhan city, Hubei Province, China, linked to a wet seafood market with a new coronavirus identified as the etiologic agent currently named SARS-CoV-2. Most cases are in Mainland China with international spread to 25 countries. The novelty of the virus, the rapid national and international spread, and the lack of therapeutic and preventative strategies have led the WHO International Health Regulation emergency committee to declare the disease as Public Health Emergency of International Concern (PHEIC) on January 30, 2020. As it relates to countries with the ongoing MERS-CoV community cases and hospital acquired infections, there will be a huge challenge for HCWs to deal with both coronaviruses, especially with the lack of standardized and approved point of care testing. This challenge will now be faced by the whole global health community dealing with COVID-19 since both coronaviruses have similar presentation. Those patients should now be tested for both MERS-CoV and SARS-CoV-2 simultaneously, and with the continuing wide international spread of SARS-CoV-2, the travel history to China in the last 14 days will be of less significance.

title: Increasing the Signal-to-Noise Ratio: COVID-19 Clinical Synopsis for Outpatient Providers
abstract: The novel coronavirus (SARS-CoV-2), which is the cause of coronavirus disease (COVID-19 formally 2019-nCoV), has received widespread attention from the medical community. Despite the rapid publication of research on the virus and the disease it causes, there is a lack of concise and relevant material to help busy medical providers navigate recognition and management of the disease in the ambulatory setting. This review article aims to bridge this gap by briefly reviewing the key points of the evaluation and treatment of patients with COVID-19 in the ambulatory clinic environment.

title: TB infection and BCG vaccination: are we protected from COVID-19?
abstract: The incidence of emerging coronavirus disease 2019 (COVID-19) disease is variable across the different parts of the world. Apart from travel patterns, other factors determining this difference may include host immune response. The aim of this study was to assess the effect of tuberculosis (TB) endemicity and Bacille Calmette-Guerin (BCG) coverage on COVID-19.  This was a cross-sectional study.  We reviewed available data regarding TB incidence, BCG coverage (as per the World Health Organization), and COVID-19 incidence of 174 countries. We divided the countries into four cohorts depending on annual TB incidence and BCG coverage.  Countries with high TB incidence had lower COVID-19 than countries with low TB incidence. Similarly, countries with high BCG coverage had lower incidence of COVID-19, suggesting some protective mechanisms in TB-endemic areas. However, the ecological differences and different testing strategies between countries could not be accounted for in this analysis.  Higher TB incidence and BCG coverage were found to be associated with lesser incidence of COVID-19. This outcome paves the way for further research into pathogenesis and immune response in COVID-19.

title: Middle East respiratory syndrome coronavirus: a comprehensive review
abstract: The Middle East respiratory syndrome coronavirus was first identified in 2012 and has since then remained uncontrolled. Cases have been mostly reported in the Middle East, however travel-associated cases and outbreaks have also occurred. Nosocomial and zoonotic transmission of the virus appear to be the most important routes. The infection is severe and highly fatal thus necessitating rapid and efficacious interventions. Here, we performed a comprehensive review of published literature and summarized the epidemiology of the virus. In addition, we summarized the virological aspects of the infection and reviewed the animal models used as well as vaccination and antiviral tested against it.

title: Understanding the Anemic Global Response to COVID-19
abstract: The COVID-19 outbreak is the most serious test of the international system since the 2008 global financial crisis. Rather than cooperate to contain and respond to a common threat, the world's leading powers, the United States and China, increasingly blamed each other through wildly speculative theories about the origins of the virus. The World Health Organization (WHO) sought to coordinate a global response but it has been hamstrung and come under attack. Given past cooperation between major powers to mobilize and eradicate smallpox and previous U.S. leadership to fight HIV/AIDS and the 2014 West African Ebola crisis, the limited cooperation and lack of leadership are puzzling. What explains the anemic global response to date? This paper draws from structural international relations theory to suggest a partial but somewhat dissatisfying answer. International organizations are inherently weak faced with opposition by major powers. The international system simultaneously incentivizes states to cooperate and address common threats but at the same time encourages countries to take care of themselves, potentially at the expense of others. Which of these motives dominates cannot be explained by structural theory, requiring us to look to other factors such as the attributes of states or of leaders themselves.

title: Cumulative Contents for 2008

title: Sentinel Event Surveillance to Estimate Total SARS-CoV-2 Infections, United States
abstract: Human infections with a novel coronavirus (SARS-CoV-2) were first identified via syndromic surveillance in December of 2019 in Wuhan China. Since identification, infections (coronavirus disease-2019; COVID-19) caused by this novel pathogen have spread globally, with more than 180,000 confirmed cases as of March 16, 2020. Effective public health interventions, including social distancing, contact tracing, and isolation/quarantine rely on the rapid and accurate identification of confirmed cases. However, testing capacity (having sufficient tests and laboratory throughput) to support these non-pharmaceutical interventions remains a challenge for containment and mitigation of COVID-19 infections. We undertook a sentinel event strategy (where single health events signal emerging trends) to estimate the incidence of COVID-19 in the US. Data from a recent national conference, the Conservative Political Action Conference, (CPAC) near Washington, DC and from the outbreak in Wuhan, China were used to fit a simple exponential growth model to estimate the total number of incident SARS- CoV-2 infections in the United States on March 1, 2020, and to forecast subsequent infections potentially undetected by current testing strategies. Our analysis and forecasting estimates a total of 54,100 SARS-CoV-2 infections (80 % CI 5,600 to 125,300) have occurred in the United States to March 12, 2020. Our forecast predicts that a very substantial number of infections are undetected, and without extensive and far-reaching non-pharmaceutical interventions, the number of infections should be expected to grow at an exponential rate.

title: Rapid implementation of mobile technology for real-time epidemiology of COVID-19
abstract: The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.8 million users as of May 2, 2020. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge.

title: Protocol of a population-based prospective COVID-19 cohort study Munich, Germany (KoCo19)
abstract: Due to the SARS-CoV-2 pandemic, public health interventions have been introduced globally in order to prevent the spread of the virus and avoid the overload of health care systems, especially for the most severely affected patients. Scientific studies to date have focused primarily on describing the clinical course of patients, identifying treatment options and developing vaccines. In Germany, as in many other regions, current tests for SARS-CoV2 are not conducted on a representative basis and in a longitudinal design. Furthermore, knowledge about the immune status of the population is lacking. Nonetheless, these data are needed to understand the dynamics of the pandemic and hence to appropriately design and evaluate interventions. For this purpose, we recently started a prospective population-based cohort in Munich, Germany, with the aim to develop a better understanding of the state and dynamics of the pandemic.  In 100 out of 755 randomly selected constituencies, 3000 Munich households are identified via random route and offered enrollment into the study. All household members are asked to complete a baseline questionnaire and subjects ≥14 years of age are asked to provide a venous blood sample of ≤3 ml for the determination of SARS-CoV-2 IgG/IgA status. The residual plasma and the blood pellet are preserved for later genetic and molecular biological investigations. For twelve months, each household member is asked to keep a diary of daily symptoms, whereabouts and contacts via WebApp. If symptoms suggestive for COVID-19 are reported, family members, including children < 14 years, are offered a pharyngeal swab taken at the Division of Infectious Diseases and Tropical Medicine, LMU University Hospital Munich, for molecular testing for SARS-CoV-2. In case of severe symptoms, participants will be transferred to a Munich hospital. For one year, the study teams re-visits the households for blood sampling every six weeks.  With the planned study we will establish a reliable epidemiological tool to improve the understanding of the spread of SARS-CoV-2 and to better assess the effectiveness of public health measures as well as their socio-economic effects. This will support policy makers in managing the epidemic based on scientific evidence.

title: A simulation of a COVID-19 epidemic based on a deterministic SEIR model
abstract: An epidemic disease caused by a new coronavirus has spread in Northern Italy with a strong contagion rate. We implement an SEIR model to compute the infected population and number of casualties of this epidemic. The example may ideally regard the situation in the Italian Region of Lombardy, where the epidemic started on February 25, but by no means attempts to perform a rigorous case study in view of the lack of suitable data and uncertainty of the different parameters, namely, the variation of the degree of home isolation and social distancing as a function of time, the number of initially exposed individuals and infected people, the incubation and infection periods and the fatality rate. First, we perform an analysis of the results of the model, by varying the parameters and initial conditions (in order the epidemic to start, there should be at least one exposed or one infected human). Then, we consider the Lombardy case and calibrate the model with the number of dead individuals to date (April 19, 2020) and constraint the parameters on the basis of values reported in the literature. The peak occurs at day 37 (April 1) approximately, when there is a rapid decrease, with a reproduction ratio R0 = 3 initially, 1.38 at day 22 and 0.64 after day 35, indicating different degrees of lockdown. The predicted death toll is almost 14000 casualties, with 2.4 million infected individuals at the end of the epidemic. The incubation period providing a better fit of the dead individuals is 4.25 days and the infection period is 4 days, with a fatality rate of 0.00144/day [values based on the reported (official) number of casualties]. The infection fatality rate (IFR) is 0.57 %, and 2.36 % if twice the reported number of casualties is assumed. However, these rates depend on the initially exposed individuals. If approximately nine times more individuals are exposed, there are three times more infected people at the end of the epidemic and IFR = 0.47 %. If we relax these constraints and use a wider range of lower and upper bounds for the incubation and infection periods, we observe that a higher incubation period (13 versus 4.25 days) gives the same IFR (0.6 versus 0.57 %), but nine times more exposed individuals in the first case. Therefore, a precise determination of the fatality rate is subject to the knowledge of the characteristics of the epidemic. We plan to perform again these calculations and publish a short note when the epidemic is over and the complete and precise data is available. Besides the specific example, the analysis proposed in this work shows how isolation measures, social distancing and knowledge of the diffusion conditions help us to understand the dynamics of the epidemic. Hence, the importance to quantify the process to verify the effectiveness of the isolation.

title: Global epidemiology of coronavirus disease 2019 (COVID-19): disease incidence, daily cumulative index, mortality, and their association with country healthcare resources and economic status
abstract: It has been 2 months since the first case of coronavirus disease 2019 (COVID-19) was reported in Wuhan, China. So far, COVID-19 has affected 85 403 patients in 57 countries/territories and has caused 2924 deaths in 9 countries. However, epidemiological data differ between countries. Although China had higher morbidity and mortality than other sites, the number of new daily cases in China has been lower than outside of China since 26 February 2020. The incidence ranged from 61.44 per 1 000 000 people in the Republic of Korea to 0.0002 per 1 000 000 people in India. The daily cumulative index (DCI) of COVID-19 (cumulative cases/no. of days between the first reported case and 29 February 2020) was greatest in China (1320.85), followed by the Republic of Korea (78.78), Iran (43.11) and Italy (30.62). However, the DCIs in other countries/territories were <10 per day. Several effective measures including restricting travel from China, controlling the distribution of masks, extensive investigation of COVID-19 spread, and once-daily press conferences by the government to inform and educate people were aggressively conducted in Taiwan. This is probably the reason why there was only 39 cases (as of 29 February 2020) with a DCI of 1 case per day in Taiwan, which is much lower than that of nearby countries such as the Republic of Korea and Japan. In addition, the incidence and mortality were correlated with the DCI. However, further study and continued monitoring are needed to better understand the underlying mechanism of COVID-19.

title: COVID-19 in Children with Brain-Based Developmental Disabilities: A Rapid Review
abstract: The prevalence of symptomatic COVID-19 in children remains low to date. In just a few months, COVID-19 has affected millions of people worldwide, and as of the date of this publication, the pandemic continues. Based on the current available evidence, children do not appear to be at higher risk of contracting COVID-19 than adults. However, children with neurological and neuromuscular conditions are vulnerable to the respiratory complications of other viral infections.  To assess whether children with brain-based developmental disabilities were more likely to develop COVID-19 and have complications or poorer outcomes following infection.  We conducted a two-week rapid review on studies with primary data regarding children aged between zero and 18 years old with brain-based developmental disabilities, or who were at risk of developing such disabilities, with confirmed or suspected COVID-19. We performed our literature searches on April 18, 2020.  Our search strategy identified 538 individual records, of which four were included in our review. Of the 50 COVID-19 pediatric patients reported in the included studies, a total of seven children were at risk of developing brain-based disabilities. Symptoms ranged in severity. However, generally, patients were discharged or saw improvements in their symptoms by the end of the study period. No deaths were reported.  Our study highlights a knowledge gap regarding the impact of COVID-19 in children with brain-based developmental disabilities.

title: A Randomized Trial of Hydroxychloroquine as Postexposure Prophylaxis for Covid-19
abstract: Coronavirus disease 2019 (Covid-19) occurs after exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For persons who are exposed, the standard of care is observation and quarantine. Whether hydroxychloroquine can prevent symptomatic infection after SARS-CoV-2 exposure is unknown.  We conducted a randomized, double-blind, placebo-controlled trial across the United States and parts of Canada testing hydroxychloroquine as postexposure prophylaxis. We enrolled adults who had household or occupational exposure to someone with confirmed Covid-19 at a distance of less than 6 ft for more than 10 minutes while wearing neither a face mask nor an eye shield (high-risk exposure) or while wearing a face mask but no eye shield (moderate-risk exposure). Within 4 days after exposure, we randomly assigned participants to receive either placebo or hydroxychloroquine (800 mg once, followed by 600 mg in 6 to 8 hours, then 600 mg daily for 4 additional days). The primary outcome was the incidence of either laboratory-confirmed Covid-19 or illness compatible with Covid-19 within 14 days.  We enrolled 821 asymptomatic participants. Overall, 87.6% of the participants (719 of 821) reported a high-risk exposure to a confirmed Covid-19 contact. The incidence of new illness compatible with Covid-19 did not differ significantly between participants receiving hydroxychloroquine (49 of 414 [11.8%]) and those receiving placebo (58 of 407 [14.3%]); the absolute difference was −2.4 percentage points (95% confidence interval, −7.0 to 2.2; P=0.35). Side effects were more common with hydroxychloroquine than with placebo (40.1% vs. 16.8%), but no serious adverse reactions were reported.  After high-risk or moderate-risk exposure to Covid-19, hydroxychloroquine did not prevent illness compatible with Covid-19 or confirmed infection when used as postexposure prophylaxis within 4 days after exposure.

title: Global prediction of unreported SARS-CoV2 infection from observed COVID-19 cases
abstract: Estimation of infectiousness and fatality of the SARS-CoV-2 virus in the COVID-19 global pandemic is complicated by ascertainment bias resulting from incomplete and non-representative samples of infected individuals. We developed a strategy for overcoming this bias to obtain more plausible estimates of the true values of key epidemiological variables. We fit mechanistic Bayesian latent-variable SIR models to confirmed COVID-19 cases, deaths, and recoveries, for all regions (countries and US states) independently. Bayesian averaging over models, we find that the raw infection incidence rate underestimates the true rate by a factor, the case ascertainment ratio CARt that depends upon region, and show how CARt changes over time. At the regional onset of COVID-19, the predicted global median for each case confirmed was 13 infections unreported (CARt = 0.07 C.I. (0.02, 0.4)). As the infection spread, the median CARt rose to 9 unreported cases for every one diagnosed as of April 15, 2020 (CARt = 0.1 C.I. (0.02, 0.5)). We also estimate that the median global initial reproduction number R0 is 3.3 (C.I (1.5, 8.3)) and the total infection fatality rate near the onset is 0.17% (C.I. (0.05%, 0.9%)). However the time-dependent reproduction number Rt and infection fatality rate as of April 15 were 1.2 (C.I. (0.6, 2.5)) and 0.8% (C.I. (0.2%,4%)), respectively. We find that there is great variability between country- and state-level values. Our estimates are consistent with recent serological estimates of cumulative infections for the state of New York, but inconsistent with claims that very large fractions of the population have already been infected in most other regions. For most regions, our estimates imply a great deal of uncertainty about the current state and trajectory of the epidemic.

title: Molecular immune pathogenesis and diagnosis of COVID-19
abstract: Coronavirus disease 2019 (COVID-19) is a kind of viral pneumonia which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The emergence of SARS-CoV-2 has been marked as the third introduction of a highly pathogenic coronavirus into the human population after the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) in the twenty-first century. In this minireview, we provide a brief introduction of the general features of SARS-CoV-2 and discuss current knowledge of molecular immune pathogenesis, diagnosis and treatment of COVID-19 on the base of the present understanding of SARS-CoV and MERS-CoV infections, which may be helpful in offering novel insights and potential therapeutic targets for combating the SARS-CoV-2 infection.

title: Electrophysiologic evidence of polyneuropathy in a cat with signs of bilateral brachial plexus neuropathy.
abstract: A 2-year-old spayed female domestic shorthair cat was examined because of bilateral thoracic limb weakness of acute onset.  Clinical signs included muscle atrophy, paresis, depressed spinal reflexes, hyperesthesia of the thoracic limbs, and reduced jaw muscle tone. Pelvic limb reflexes were normal. Results of a neurologic examination were suggestive of multifocal lesions involving both brachial plexuses and the trigeminal nerves. Abnormal nerve conduction across the brachial plexus and delayed late potentials were found on electrodiagnostic testing, and diffuse subclinical involvement of other regions of the peripheral nervous system was confirmed on the basis of abnormal electromyographic findings for the masticatory muscles and conduction block of the peroneal nerve. TREATMENT AND OUTCOME No specific treatments were given, and neurologic signs resolved within a month. A relapse occurred 2 months after the first episode, with clinical signs affecting both the pelvic and the thoracic limbs on this occasion. Again, the condition resolved without specific treatment, and 13 months after the initial episode, the cat reportedly was normal.  Findings suggested that brachial plexus neuropathy can be a multifocal disease in cats, even if clinically apparent neurologic deficits are initially subtle or absent, and that electrodiagnostic techniques can be used to identify subclinical involvement of the peripheral nerves.

title: Gender differences in the frequency of gastrointestinal symptoms and olfactory or taste disorders among 1,942 non-hospitalized patients with COVID-19.
abstract: The Coronavirus Disease 2019 (COVID 19) is a communicable disease caused by novel coronavirus.  This study aimed to assess self-reported frequency of gastrointestinal symptoms and olfactory or taste disorders in non-hospitalized patients with COVID-19 in Poland.  This cross-sectional survey was conducted between April 17 and 18, 2020, among 4,516 non-hospitalized patients with COVID-19 in Poland. The questionnaire included eight questions related to the health status, symptoms of COVID-19, comorbidities, and smoking status.  Completed questionnaires were obtained from 1,942 patients with COVID-19, a response rate of 43%. The median age of the respondents was 50 years; 60.2% were women. Among non-hospitalized patients with COVID-19, 21.3% had hypertension, 4.5% had diabetes, and 3.1% of COVID-19 cases had chronic respiratory disease. Regular tobacco use was declared by 11.2% of patients with COVID-19. At least one gastrointestinal symptom was reported by 53.6% of patients. Almost half of patients (47%) with COVID-19 reported lack of appetite and 24.2% reported diarrhea. Among 1,942 interviewed patients, 54.2% reported at least one olfactory or taste disorder and 42.5% reported both alterations. Self-reported olfactory and taste disorders were 49.2% and 47.5%, respectively. Self-reported frequency of gastrointestinal symptoms and olfactory or taste disorders during COVID-19 course was significantly higher (p<0.001) among women than men.  In conclusion, this study demonstrated that olfactory and taste disorders are frequent symptoms in mild-to-moderate COVID-19 patients. Moreover, our study indicates gender differences in the frequency of gastrointestinal symptoms and olfactory or taste disorders among non-hospitalized patients with COVID-19.

title: Transmission Dynamics and Control Methodology of COVID-19: a Modeling Study
abstract: The coronavirus disease 2019 (COVID-19) has grown up to be a pandemic within a short span of time. To investigate transmission dynamics and then determine control methodology, we took epidemic in Wuhan as a study case. Unfortunately, to our best knowledge, the existing models are based on the common assumption that the total population follows a homogeneous spatial distribution, which is not the case for the prevalence occurred both in the community and in hospital due to the difference in the contact rate. To solve this problem, we propose a novel epidemic model called SEIR-HC, which is a novel epidemic model with two different social circles. Using the model alongside the exclusive optimization algorithm, the spread process of COVID-19 epidemic in Wuhan city is reproduced and then the propagation characteristics and unknown data are estimated. Furthermore, the control measures implemented in Wuhan are assessed and the control methodology of COVID-19 is discussed to provide guidance for limiting the epidemic spread.

title: A relevance and quality-based ranking algorithm applied to evidence-based medicine
abstract: The amount of information available about millions of different subjects is growing every day. This has led to the birth of new search tools specialized in different domains, because classical information retrieval models have trouble dealing with the special characteristics of some of these domains. Evidence-based Medicine is a case of a complex domain where classical information retrieval models can help search engines retrieve documents by considering the presence or absence of terms, but these must be complemented with other specific strategies which allow retrieving and ranking documents including the best current evidence and methodological quality.  The goal is to present a ranking algorithm able to select the best documents for clinicians considering aspects related to the relevance and the quality of said documents.  In order to assess the effectiveness of this proposal, an experimental methodology has been followed by using Medline as a data set and the Cochrane Library as a gold standard.  Applying the evaluation methodology proposed, and after submitting 40 queries on the platform developed, the MAP (Mean Average Precision) obtained was 20.26%.  Successful results have been achieved with the experiments, improving on other studies, but under different and even more complex circumstances.

title: Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States
abstract: Despite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data.

title: Estimation of COVID-19 outbreak size in Italy based on international case exportations
abstract: Italy is currently experiencing an epidemic of COVID-19 which emerged in the Lombardy region . During the interval between February 25-29, 2020, we identified 46 cases of COVID-19 reported in 21 countries in Europe, Africa, North America, and South America which were either in individuals with recent travel from Italy, or who had presumed infection by a traveler from Italy 2. In six cases, in four of the affected countries (Switzerland, France, Austria, Croatia), land travel was a likely route of introduction, or was documented to have been the route of introduction. We used air travel volume between Italian cities and cities in other countries as an index of connectedness, using data available from the International Air Transport Association (IATA) for February 2015 (2.61 million total departing international air passengers from Italy). We used the methods of Fraser et al. to estimate the size of the underlying epidemic in Italy necessary in order for these cases to be observed with a reasonable probability. To estimate the time at risk of COVID-19 exposure for travelers departing Italy, we obtained data from the United Nations World Tourism Organization (UNWTO) for the proportion of international travelers that are non-residents of Italy (63%) and the average length of stay of tourists to Italy (3.4 days), and assumed the Italian epidemic began one month prior to February 29, 2020. We also performed sensitivity analyses in which we included outbound travel to all countries regardless of reported case importations, inflated travel volumes by 35%, to account for the relative increase in flight numbers from 2015-2019, and excluded cases in bordering countries and which were documented to have been introduced by overland travel. When all cases were considered we estimated a true outbreak size of 3971 cases (95% CI 2907-5297), as compared to a reported case count of 1128 on February 29, 2020, suggesting non-identification of 72% (61-79%) of cases. In sensitivity analyses, outbreak sizes varied from 1552 to 4533 cases (implying non-identification of 27-75% of cases). We recently used similar methods to estimate a much larger epidemic size in Iran, with a far greater degree of under-reporting, based on many fewer exported cases. The reason for this difference relates to the relatively high volume of travel from Italy, relative to Iran. In summary, we suggest that the numerous COVID-19 case exportations from Italy in recent days suggest an epidemic that is larger than official case counts suggest, and which is approximately on a par with that currently occurring in South Korea, which reports 3526 cases (and fewer deaths) as of February 29, 2020.

title: Relative disease burdens of COVID-19 and seasonal influenza in New York City, February 1 - April 18, 2020.
abstract: Comparisons between the mortality burdens of COVID-19 and seasonal influenza often fail to account for the fact that the United States Centers for Disease Control and Prevention (CDC) reports annual influenza mortality estimates which are calculated based upon a series of assumptions about the underreporting of flu deaths. COVID-19 deaths, in contrast, are being reported as raw counts. In this report, we compare COVID-19 death counts to seasonal influenza death counts in New York City during the interval from February 1 - April 18, 2020. Using this approach, COVID-19 appears to have caused 21.4 times the number of deaths as seasonal influenza during the same period. We also assessed excess mortality in order to verify this finding. New York City has had approximately 13,032 excess all-cause mortality deaths during this time period. We assume that most of these deaths are COVID-19 related. We therefore calculated the ratio of excess deaths (i.e. assumed COVID-19 deaths) to seasonal influenza deaths during the same time interval and found a similar ratio of 21.1 COVID-19 to seasonal influenza deaths. Our findings are consistent with conditions on the ground today. Comparing COVID-19 deaths with CDC estimates of yearly influenza-related deaths would suggest that, this year, seasonal influenza has killed approximately the same number of Americans as COVID-19 has. This does not comport with the realities of the pandemic we see today.

title: SARS: responding to an unknown virus
abstract: The severe acute respiratory syndrome (SARS) is an emerging infection caused by a novel coronavirus which first appeared in southern China at the end of 2002. In early 2003, through a single incident, it spread to Hong Kong, Singapore, Canada and Vietnam. For busy clinicians in large public hospitals, the response to the virus was initially based on ensuring a high level of protection for staff. However, as the epidemic progressed and more information became available about the virus, procedures were rationalized and the virus is currently under control worldwide. There are, however, numerous unanswered questions concerning super-spreading events, the modes of transmission of the virus and, perhaps most importantly, the rapid detection of the virus early in the course of disease. These issues need to be addressed in case the virus becomes more widespread in the near future.

title: Genetic inactivation of COPI coatomer separately inhibits vesicular stomatitis virus entry and gene expression.
abstract: Viruses coopt cellular membrane transport to invade cells, establish intracellular sites of replication, and release progeny virions. Recent genome-wide RNA interference (RNAi) screens revealed that genetically divergent viruses require biosynthetic membrane transport by the COPI coatomer complex for efficient replication. Here we found that disrupting COPI function by RNAi inhibited an early stage of vesicular stomatitis virus (VSV) replication. To dissect which replication stage(s) was affected by coatomer inactivation, we used visual and biochemical assays to independently measure the efficiency of viral entry and gene expression in hamster (ldlF) cells depleted of the temperature-sensitive ε-COP subunit. We show that ε-COP depletion for 12 h caused a primary block to virus internalization and a secondary defect in viral gene expression. Using brefeldin A (BFA), a chemical inhibitor of COPI function, we demonstrate that short-term (1-h) BFA treatments inhibit VSV gene expression, while only long-term (12-h) treatments block virus entry. We conclude that prolonged coatomer inactivation perturbs cellular endocytic transport and thereby indirectly impairs VSV entry. Our results offer an explanation of why COPI coatomer is frequently identified in screens for cellular factors that support cell invasion by microbial pathogens.

title: Rapid Detection of 2019 Novel Coronavirus SARS-CoV-2 Using a CRISPR-based DETECTR Lateral Flow Assay
abstract: An outbreak of novel betacoronavirus, SARS-CoV-2 (formerly named 2019-nCoV), began in Wuhan, China in December 2019 and the COVID-19 disease associated with infection has since spread rapidly to multiple countries. Here we report the development of SARS-CoV-2 DETECTR, a rapid (~30 min), low-cost, and accurate CRISPR-Cas12 based lateral flow assay for detection of SARS-CoV-2 from respiratory swab RNA extracts. We validated this method using contrived reference samples and clinical samples from infected US patients and demonstrated comparable performance to the US CDC SARS-CoV-2 real-time RT-PCR assay.

title: Estimating COVID-19 Prevalence in the United States: A Sample Selection Model Approach
abstract: Public health efforts to determine population infection rates from coronavirus disease 2019 (COVID-19) have been hampered by limitations in testing capabilities and the large shares of mild and asymptomatic cases. We developed a methodology that corrects observed positive test rates for non-random sampling to estimate population infection rates across U.S. states from March 31 to April 7.  We adapted a sample selection model that corrects for non-random testing to estimate population infection rates. The methodology compares how the observed positive case rate vary with changes in the size of the tested population, and applies this gradient to infer total population infection rates. Model identification requires that variation in testing rates be uncorrelated with changes in underlying disease prevalence. To this end, we relied on data on day-to-day changes in completed tests across U.S. states for the period March 31 to April 7, which were primarily influenced by immediate supply-side constraints. We used this methodology to construct predicted infection rates across each state over the sample period. We also assessed the sensitivity of the results to controls for state-specific daily trends in infection rates.  The median population infection rate over the period March 31 to April 7 was 0.9% (IQR 0.64 1.77). The three states with the highest prevalence over the sample period were New York (8.5%), New Jersey (7.6%), and Louisiana (6.7%). Estimates from models that control for state-specific daily trends in infection rates were virtually identical to the baseline findings. The estimates imply a nationwide average of 12 population infections per diagnosed case. We found a negative bivariate relationship (corr. = -0.51) between total per capita state testing and the ratio of population infections per diagnosed case.  The effectiveness of the public health response to the coronavirus pandemic will depend on timely information on infection rates across different regions. With increasingly available high frequency data on COVID-19 testing, our methodology could be used to estimate population infection rates for a range of countries and subnational districts. In the United States, we found widespread undiagnosed COVID-19 infection. Expansion of rapid diagnostic and serological testing will be critical in preventing recurrent unobserved community transmission and identifying the large numbers individuals who may have some level of viral immunity.

title: China’s Internationalized Higher Education During Covid-19: Collective Student Autoethnography
abstract: This article presents 15 autoethnographical texts detailing student experiences at Beijing Normal University in the midst of the Covid-19 pandemic. Contributions have been collected over 6 weeks between 15 February and 1 April 2020, edited by Hejia Wang (assisted by Moses Oladele Ogunniran and Yingying Huang), and supervised by Michael Peters. Through shared in-depth empirical feelings and representations from a wide variety of cultural, historical, and social contexts, the article outlines an answer to the question: How do students, connected virtually but separated physically in an internationalized university, deal with disruption brought about by the Covid-19 pandemic? Student testimonies offer reflections on Covid-19 and Chinese international education, experiences of online teaching and learning, reflections on university coping mechanisms, an account of realities and feelings related to changes in academic life, and discussions on coping strategies in Chinese international higher education. Contributors expose their individual feelings, effects, benefits, challenges, and risk management strategies. Collected at the peak of the Covid-19 pandemic, these testimonies are unable to offer systemic answers to challenges facing the whole world. However, these experiences and feelings will provide important inputs to global discussions about the future of the world, after Covid-19.

title: Testing Asymptomatic Emergency Department Patients for Coronavirus of 2019 (COVID‐19) in a Low Prevalence Region
abstract: The first cases of Coronavirus of 2019 (COVID‐19) were reported in Wuhan, China in December 2019(1). The literature demonstrates geographical variation with regards to estimates of infection incidence, suggesting that COVID‐19 has been underdiagnosed in certain regions(2,3). The rate of asymptomatic infection has been estimated to be as high as 30.8%, which may help explain variation in incidence, particularly in regions with differing screening practices (3). Transmission of COVID‐19 by asymptomatic carriers has been reported in multiple family units, indicating that this mode of infection is important in understanding disease epidemiology and population risk(4,5).

title: Coronavirus infections reported by ProMED, February 2000–January 2020
abstract: Sources describing the global burden of emerging diseases accurately are still limited. We reviewed coronavirus infections reported by ProMED and assessed the reliability of the data retrieved compared to published reports. We evaluated the effectiveness of ProMED as a source of epidemiological data on coronavirus.  Using the keyword “coronavirus” in the ProMED search engine, we reviewed all the information from the reports and collected data using a structured form, including year, country, gender, occupation, the number of infected individuals, and the number of fatal cases.  We identified 109 entries reported between February 29, 2000 and January 22, 2020. A total of 966 cases were reported, with death reported in 188 cases, suggesting an overall case fatality rate (CFR) of 19.5%. Of 70 cases for which the gender was reported, 47 (67.1%) were male. Most of the cases were reported from China, the United Arab Emirates, and Saudi Arabia, with reports from other countries, including imported cases in Europe and North America.  Internet-based reporting systems such as ProMED are useful to gather information and synthesize knowledge on emerging infections. Although certain areas need to be improved, ProMED provided useful information about coronaviruses especially during outbreaks.

title: Cardiovascular disease and COVID-19
abstract: Many patients with coronavirus disease 2019 (COVID-19) have underlying cardiovascular (CV) disease or develop acute cardiac injury during the course of the illness. Adequate understanding of the interplay between COVID-19 and CV disease is required for optimum management of these patients.  A literature search was done using PubMed and Google search engines to prepare a narrative review on this topic.  Respiratory illness is the dominant clinical manifestation of COVID-19; CV involvement occurs much less commonly. Acute cardiac injury, defined as significant elevation of cardiac troponins, is the most commonly reported cardiac abnormality in COVID-19. It occurs in approximately 8–12% of all patients. Direct myocardial injury due to viral involvement of cardiomyocytes and the effect of systemic inflammation appear to be the most common mechanisms responsible for cardiac injury. The information about other CV manifestations in COVID-19 is very limited at present. Nonetheless, it has been consistently shown that the presence of pre-existing CV disease and/or development of acute cardiac injury are associated with significantly worse outcome in these patients.  Most of the current reports on COVID-19 have only briefly described CV manifestations in these patients. Given the enormous burden posed by this illness and the significant adverse prognostic impact of cardiac involvement, further research is required to understand the incidence, mechanisms, clinical presentation and outcomes of various CV manifestations in COVID-19 patients.

title: Discovery of a novel canine respiratory coronavirus support genetic recombination among betacoronavirus1
abstract: Although canine respiratory coronavirus (CRCoV) is an important respiratory pathogen that is prevalent in many countries, only one complete genome sequence of CRCoV (South Korea strain K37) has been obtained to date. Genome-wide analyses and recombination have rarely been conducted, as small numbers of samples and limited genomic characterization have previously prevented further analyses. Herein, we report a unique CRCoV strain, denoted strain BJ232, derived from a CRCoV-positive dog with a mild respiratory infection. Phylogenetic analysis based on complete genome of all available coronaviruses consistently show that CRCoV BJ232 is most closely related to human coronavirus OC43 (HCoV-OC43) and BCoV, forming a separate clade that split off early from other Betacoronavirus 1. Based on the phylogenetic and SimPlot analysis we propose that CRCoV-K37 was derived from genetic recombination between CRCoV-BJ232 and BCoV. In detail, spike (S) gene of CRCoV-K37 clustered with CRCoV-BJ232. However orf1ab, membrane (M) and nucleocapsid (N) genes were more related to Bovine coronavirus (BCoV) than CRCoV-B232. Molecular epidemic analysis confirmed the prevalence of CRCoV-BJ232 lineage around the world for a long time. Recombinant events among Betacoronavirus 1 may have implications for CRCoV transmissibility. All these findings provide further information regarding the origin of CRCoV.

title: The Novel Coronavirus, 2019-nCoV, is Highly Contagious and More Infectious Than Initially Estimated
abstract: The novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R0, was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus.

title: Population-scale testing can suppress the spread of COVID-19
abstract: We propose an additional intervention that would contribute to the control of the COVID-19 pandemic, offer more protection for people working in essential jobs, and help guide an eventual reopening of society. The intervention is based on: (1) testing every individual (2) repeatedly, and (3) self-quarantine of infected individuals. Using a standard epidemiological model (SIR), we show here that by identification and isolation of the majority of infectious individuals, including those who may be asymptomatic, the reproduction number R0 of SARS-CoV-2 would be reduced well below 1.0, and the epidemic would collapse. We replicate these observations in a more complex stochastic dynamic model on a social network graph. We also find that the testing regime would be additive to other interventions, and be effective at any level of prevalence. If adopted as a policy, any industrial society could sustain the regime for as long as it takes to find a safe and effective cure or vaccine. Our model also indicates that unlike sampling-based tests, population-scale testing does not need to be very accurate: false negative rates up to 15% could be tolerated if 80% comply with testing every ten days, and false positives can be almost arbitrarily high when a high fraction of the population is already effectively quarantined. Testing at the required scale would be feasible if existing qPCR-based methods are scaled up and multiplexed. A mass produced, low throughput field test kit could also be carried out at home. Economic analysis also supports the feasibility of the approach: current reagent costs for tests are in the range of a dollar or less, and the estimated benefits for population-scale testing are so large that the policy would be cost-effective even if the costs were larger by more than two orders of magnitude. To identify both active and previous infections, both viral RNA and antibodies could be tested. All technologies to build such test kits, and to produce them in the scale required to test the entire world's population exist already. Integrating them, scaling up production, and implementing the testing regime will require resources and planning, but at a scale that is very small compared to the effort that every nation would devote to defending itself against a more traditional foe.

title: Estimating the case fatality ratio of the COVID-19 epidemic in China
abstract: Corona Virus Disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan city and rapidly spread throughout China since late December 2019. Crude case fatality ratio (CFR) with dividing the number of known deaths by the number of confirmed cases does not represent the true CFR and might be off by orders of magnitude. We aim to provide a precise estimate of the CFR of COVID-19 using statistical models at the early stage of the epidemic.  We extracted data from the daily released epidemic report published by the National Health Commission P. R. China from 20 Jan 2020, to 1 March 2020. Competing risk model was used to obtain the cumulative hazards for death, cure, and cure-death hazard ratio. Then the CFR was estimated based on the slope of the last piece in joinpoint regression model, which reflected the most recent trend of the epidemic.  As of 1 March 2020, totally 80,369 cases were diagnosed as COVID-19 in China. The CFR of COVID-19 were estimated to be 70.9% (95% CI: 66.8%-75.6%) during Jan 20-Feb 2, 20.2% (18.6%-22.1%) during Feb 3-14, 6.9% (6.4%-7.4%) during Feb 15-23, 1.5% (1.4%-1.6%) during Feb 24-March 1 in Hubei province, and 20.3% (17.0%-25.3%) during Jan 20-28, 1.9% (1.8%-2.1%) during Jan 29-Feb 12, 0.9% (0.8%-1.1%) during Feb 13-18, 0.4% (0.4%-0.5%) during Feb 19-March 1 in other areas of China, respectively.  Based on analyses of public data, we found that the CFR in Hubei was much higher than that of other regions in China, over 3 times in all estimation. The CFR would follow a downwards trend based on our estimation from recently released data. Nevertheless, at early stage of outbreak, CFR estimates should be viewed cautiously because of limited data source on true onset and recovery time.

title: Reproducibility and reporting practices in COVID-19 preprint manuscripts
abstract: The novel coronavirus, COVID-19, has sparked an outflow of scientific research seeking to understand the virus, its spread, and best practices in prevention and treatment. If this international research effort is going to be as swift and effective as possible, it will need to rely on a principle of open science. When researchers share data, code, and software and generally make their work as transparent as possible, it allows other researchers to verify and expand upon their work. Furthermore, it allows public officials to make informed decisions. In this study, we analyzed 535  articles related to COVID-19 for eight transparency criteria and recorded study location and funding information. We found that individual researchers have lined up to help during this crisis, quickly tackling important public health questions, often without funding or support from outside organizations. However, most authors could improve their data sharing and scientific reporting practices. The contrast between the commitment of researchers to doing important research and their reporting practices reveals underlying weaknesses in reporting habits, but not necessarily their science.

title: Symptoms, Stress, and HIV-Related Care Among Older People Living with HIV During the COVID-19 Pandemic, Miami, Florida

title: Letter: The Risk of COVID-19 Infection During Neurosurgical Procedures: A Review of Severe Acute Respiratory Distress Syndrome Coronavirus 2 (SARS-CoV-2) Modes of Transmission and Proposed Neurosurgery-Specific Measures for Mitigation

title: New statistical model for misreported data with application to current public health challenges
abstract: The main goal of this work is to present a new model able to deal with potentially misreported continuous time series. The proposed model is able to handle the autocorrelation structure in continuous time series data, which might be partially or totally underreported or overreported. Its performance is illustrated through a comprehensive simulation study considering several autocorrelation structures and two real data applications on human papillomavirus incidence in Girona (Catalunya, Spain) and COVID-19 incidence in the Chinese region of Heilongjiang.

title: A Cautionary Tale of False-Negative Nasopharyngeal COVID-19 Testing
abstract: There remains diagnostic uncertainty regarding the sensitivity of reverse transcription polymerase chain reaction in detection of SARS-CoV-2 from nasopharyngeal specimens. We present a case where two nasopharyngeal specimens were negative, followed by a positive sputum sample. Serial testing for COVID-19 is indicated in patients with high pretest probability of disease.

title: TADs in the Dromedary
abstract: The transboundary diseases in camel are mainly linked to the regional camel meat market from Sahelian countries (from Mauritania to Somalia) to the Arabian peninsula and North Africa. Indeed, the camel flow in relationship with this market is based on live animals’ export. Because the camel trade can be formal and informal with interconnections between both sectors and despite veterinary controls in the main exporting ports, some diseases such as Rift Valley fever (RVF), PPR-like disease, and MERS-coronavirus can spread from exporting countries to importing ones. However, the epidemiological status of these different diseases is quite variable and the transmission to humans in case of zoonosis (RVF and MERS-Cov) is not necessarily due to transboundary camel trade despite the impact of outbreak on the regional camel market. Globally, dromedary camel is less affected than other ruminants by infectious diseases under transboundary surveillance. But, because camel breeding is concentrated in countries where the disease surveillance systems often lack means, where the frontiers in desert areas are often “porous,” and where the herd mobility is difficult to assess, the risk of transboundary diseases’ transmission through borders is not negligible. Nowadays, the challenge of TADs control is limited to Rift Valley fever, but special attention must be paid to emerging diseases, including the recent discovery of prion disease in Algeria.

title: Elective, Non-urgent Procedures and Aesthetic Surgery in the Wake of SARS–COVID-19: Considerations Regarding Safety, Feasibility and Impact on Clinical Management
abstract: The worldwide spread of a novel coronavirus disease (COVID-19) has led to a near total stop of non-urgent, elective surgeries across all specialties in most affected countries. In the field of aesthetic surgery, the self-imposed moratorium for all aesthetic surgery procedures recommended by most international scientific societies has been adopted by many surgeons worldwide and resulted in a huge socioeconomic impact for most private practices and clinics. An important question still unanswered in most countries is when and how should elective/aesthetic procedures be scheduled again and what kind of organizational changes are necessary to protect patients and healthcare workers when clinics and practices reopen. Defining manageable, evidence-based protocols for testing, surgical/procedural risk mitigation and clinical flow management/contamination management will be paramount for the safety of non-urgent surgical procedures.  We conducted a MEDLINE/PubMed research for all available publications on COVID-19 and surgery and COVID-19 and anesthesia. Articles and referenced literature describing possible procedural impact factors leading to exacerbation of the clinical evolution of COVID-19-positive patients were identified to perform risk stratification for elective surgery. Based on these impact factors, considerations for patient selection, choice of procedural complexity, duration of procedure, type of anesthesia, etc., are discussed in this article and translated into algorithms for surgical/anesthesia risk management and clinical management. Current recommendations and published protocols on contamination control, avoidance of cross-contamination and procedural patient flow are reviewed. A COVID-19 testing guideline protocol for patients planning to undergo elective aesthetic surgery is presented and recommendations are made regarding adaptation of current patient information/informed consent forms and patient health questionnaires.  The COVID-19 crisis has led to unprecedented challenges in the acute management of the crisis, and the wave only recently seems to flatten out in some countries. The adaptation of surgical and procedural steps for a risk-minimizing management of potential COVID-19-positive patients seeking to undergo elective aesthetic procedures in the wake of that wave will present the next big challenge for the aesthetic surgery community. We propose a clinical algorithm to enhance patient safety in elective surgery in the context of COVID-19 and to minimize cross-contamination between healthcare workers and patients. New evidence-based guidelines regarding surgical risk stratification, testing, and clinical flow management/contamination management are proposed. We believe that only the continuous development and broad implementation of guidelines like the ones proposed in this paper will allow an early reintegration of all aesthetic procedures into the scope of surgical care currently performed and to prepare the elective surgical specialties better for a possible second wave of the pandemic.  This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.

title: Cyberbiosecurity Challenges of Pathogen Genome Databases
abstract: Pathogen detection, identification, and tracking is shifting from non-molecular methods, DNA fingerprinting methods, and single gene methods to methods relying on whole genomes. Viral Ebola and influenza genome data are being used for real-time tracking, while food-borne bacterial pathogen outbreaks and hospital outbreaks are investigated using whole genomes in the UK, Canada, the USA and the other countries. Also, plant pathogen genomes are starting to be used to investigate plant disease epidemics such as the wheat blast outbreak in Bangladesh. While these genome-based approaches provide never-seen advantages over all previous approaches with regard to public health and biosecurity, they also come with new vulnerabilities and risks with regard to cybersecurity. The more we rely on genome databases, the more likely these databases will become targets for cyber-attacks to interfere with public health and biosecurity systems by compromising their integrity, taking them hostage, or manipulating the data they contain. Also, while there is the potential to collect pathogen genomic data from infected individuals or agricultural and food products during disease outbreaks to improve disease modeling and forecast, how to protect the privacy of individuals, growers, and retailers is another major cyberbiosecurity challenge. As data become linkable to other data sources, individuals and groups become identifiable and potential malicious activities targeting those identified become feasible. Here, we define a number of potential cybersecurity weaknesses in today's pathogen genome databases to raise awareness, and we provide potential solutions to strengthen cyberbiosecurity during the development of the next generation of pathogen genome databases.

title: Reliability and usefulness of a rapid IgM‐IgG antibody test for the diagnosis of SARS-CoV-2 infection: a preliminary report.

title: BCG VACCINES MAY NOT REDUCE COVID-19 MORTALITY RATES
abstract: The reason for the observed country-wise variability in incidence and severity of the COVID-19 outcome remains unknown. Few recent studies have suggested a positive protective correlation of the BCG vaccination policy of the countries with the observed COVID-19 severity. The current study was undertaken to reassess the existing data as of 4th April 2020. The incidence rates (cases per million population), Case Fatality Rates (CFR) and inherently more robust Infection Fatality Rates (IFR) were calculated across countries accounting for about 99% COVID-19 deaths. The initial scrutiny suggested a weaker association with BCG vaccination policy or BCG coverage, so positivity to the Tuberculin Sensitivity Test (TST)/ Interferon Gamma Release Assay (IGRA) as a measure of the potential protective effect of the resident populations exposure to Mycobacterium spp. whether from BCG vaccination or as a result of exposure to environmental mycobacteria was analyzed. The incidence rates (the number of cases per million population) decreased with an increase in % LTBI (TST/IGRA positivity) for the analyzed countries with R2 =0.6343, suggesting an exponentially negative covariation. However, the covariation of CFR estimates that ranged from 0.29% to 12.25 % (average 5.39%) among countries, was tenuous. Interim estimates of IFR (i-IFR), a more dependable measure for such studies, for the best and worst-case scenarios, i.e., i-IFR-l and i-IFR-h, predict on an average 20.57% to 30.15 % COVID-19 fatality rates globally, but individual country estimates display huge variation. Among countries accounting for 92.14% deaths (11 countries; top 20% countries included in current study) the estimate for lowest IFRs (i-IFR-l=4.16 (China) & i-IFR-h=4.61 (China)) and highest IFRs (i-IFR-l=96.39% (UK); & i-IFR-h=96.54% (UK)) displayed huge difference (average for the group: CFR=6.8 ± 3.6%; i-IFR-l=34.97 ± 30.55%; & i-IFR-h=44.20 ± 29.08%). Currently, the worst affected countries Italy (CFR=12.25%; i-IFR-l=42.63%; i-IFR-h=48.69%) and Spain (CFR=9.39%; i-IFR-l=26.85%; i-IFR-h=36.60%) would seemingly cope with COVID-19 better than UK, Netherlands and USA while the countries Germany (CFR=1.40%; i-IFR-l=4.93%; i-IFR-h=17.49%) and Switzerland (CFR=3.01%; i-IFR-l=10.87%; i-IFR-h=16.23%) along with China could fare the best. The rest of the 80% countries (accounting for 6.74% deaths), seemed to have reduced mortality (CFR=2.45 ± 2.01; i-IFR-l= 30.62 ± 28.24%; i-IFR-h=40.99 ± 30.47%) with associated high % LTBI (17.28 ± 8.87) than top 20% countries. The inherent issues in the data set (e.g., heterogeneity, non-random sampling, different criteria of sampling and reporting, access to health care, genetic composition, underlying co-morbidities, etc) need to be taken into account for making informed decisions.

title: Reply to “Studies on Influenza Virus Transmission between Ferrets: the Public Health Risks Revisited”

title: COVID-19 cases are less prevalent in countries where malaria is endemic, suggesting a role for anti-malarial drugs as prophylaxis
abstract: Almost every country across the world has felt the repercussions of the pandemic of disease termed coronavirus disease 2019 (COVID-19) caused by the novel coronavirus identified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A recently published article points to a method of prevention and prophylaxis of COVID-19 through the use of anti-malarial drugs such as the 4-aminoquinolones: chloroquine and hydroxychloroquine, based on their mechanisms of action against SARS-CoV-2. This report aims to explore the correlation between COVID-19 cases and countries where malaria is prevalent using statistical means. It is hypothesized that countries where malaria is endemic will have few cases of COVID-19 since these countries use the 4-aminoquinolone antimalarial drugs for prophylaxis. Statistical analysis demonstrates that the numbers and incidence of COVID-19 cases and COVID-19 related deaths are substantially lower (multiple-fold lower) in countries with the highest prevalence of malaria. The difference between both the COVID-19 incidence rate and the COVID-19 mortality rate in malaria prevalent countries compared to COVID-19 prevalent countries is statistically significant (p = 0.02 and p = 0.04 respectively). This study provides further evidence that anti-malaria drugs may prove essential to breaking the spread of SARS-CoV-2 and preventing COVID-19 and COVID-19 related mortality. As the pandemic continues to evolve and doctors and researchers across the globe try to attenuate or stop the spread of SARS-CoV-2, the medical community should not overlook the potential role of the 4-aminoquinolones anti-malarial drugs, chloroquine and hydroxychloroquine, and 8-aminoquinolone anti-malaria drugs, tafenoquine and primaquine, as a prophylaxis.

title: Level of underreporting including underdiagnosis before the first peak of COVID-19 in various countries: Preliminary retrospective results based on wavelets and deterministic modeling

title: Predict the next moves of COVID-19: reveal the temperate and tropical countries scenario
abstract: The spread of COVID-19 engulfs almost all the countries and territories of the planet, and infections and fatality are increasing rapidly. The first epi-center of its' massive spread was in Wuhan, Hubei province, China having a temperate weather, but the spread has got an unprecedented momentum in European temperate countries mainly in Italy and Spain (as of March 30, 2020). However, Malaysia and Singapore and the neighboring tropical countries of China got relatively low spread and fatality that created a research interest on whether there are potential impacts of weather condition on COVID-19 spread. Adopting the SIR (Susceptible Infected Removed) deviated model to predict potential cases and death in the coming days from COVID-19 was done using the secondary and official sources of data. This study shows that COVID-19 spread and fatality tend to be high across the world but compared to tropical countries, it is going to be incredibly high in the temperate countries having lower temperature (7-16°C) and humidity (80-90%) in last March. However, some literature predicted that this might not to be true, rather irrespective of weather conditions there might be a continuous spread and death. Moreover, a large number of asymptotic COVID-19 carrier in both temperate and tropical countries may re-outbreak in the coming winter. Therefore, a comprehensive global program with the leadership of WHO for testing of entire population of the world is required, which will be very useful for the individual states to take proper political action, social movement and medical services.

title: Which preventive measures might protect health care workers from SARS?
abstract: Despite the use of a series of preventive measures, a high incidence of severe acute respiratory syndrome (SARS) was observed among health care workers (HCWs) during the SARS epidemic. This study aimed to determine which preventive measures may have been effective in protecting HCWs from infection, and which were not effective.  A retrospective study was performed among 758 'frontline' health care workers who cared for SARS patients at the Second Affiliated Hospital and the Third Affiliated Hospital of Sun Yat-sen University. The HCWs with IgG against SARS and those without IgG against SARS were respectively defined as the "case group" and the "control group", and logistic regression was conducted to explore the risk factors for SARS infection in HCWs.  After adjusting for age, gender, marital status, educational level, professional title, and the department in which an individual worked, the results of a multivariate logistic regression analysis indicated that incidence of SARS among HCWs was significantly and positively associated with: performing tracheal intubations for SARS patients, methods used for air ventilation in wards, avoiding face-to-face interaction with SARS patients, the number of pairs of gloves worn by HCWs, and caring for serious SARS cases.  Some measures, particularly good air ventilation in SARS wards, may be effective in minimizing or preventing SARS transmission among HCWs in hospitals.

title: Longitudinal analyses of the relationship between development density and the COVID-19 morbidity and mortality rates: Early evidence from 1,165 metropolitan counties in the United States
abstract: This longitudinal study aimed to investigative the impacts of development density on the spread and mortality rates of COVID-19 in metropolitan counties in the United States. Multilevel Linear Modeling (MLM) were employed to model the infection rate and the mortality rate of COVID-19, accounting for the hierarchical (two-level) and longitudinal structure of the data. This study found that large metropolitan size (measured in terms of population) lead to significantly higher COVID-19 infection rates and higher mortality rates. After controlling for metropolitan size and other confounding variables, county density leads to significantly lower infection rates and lower death rates. These findings recommend that urban planners and health professionals continue to advocate for compact development and continue to oppose urban sprawl for this and many other reasons documented in the literature, including the positive relationship between compact development and fitness and general health.

title: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2)
abstract: Estimation of the prevalence and contagiousness of undocumented novel coronavirus (SARS-CoV2) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV2, including the fraction of undocumented infections and their contagiousness. We estimate 86% of all infections were undocumented (95% CI: [82%–90%]) prior to 23 January 2020 travel restrictions. Per person, the transmission rate of undocumented infections was 55% of documented infections ([46%–62%]), yet, due to their greater numbers, undocumented infections were the infection source for 79% of documented cases. These findings explain the rapid geographic spread of SARS-CoV2 and indicate containment of this virus will be particularly challenging.

title: Syndromic surveillance in Vanuatu since Cyclone Pam: a descriptive study
abstract: In 2012, Vanuatu designed and implemented a syndromic surveillance system based on the guidelines developed by the Pacific Community and the World Health Organization to provide early warning of outbreaks and other important public health events. Four core syndromes were endorsed for surveillance: acute fever and rash, prolonged fever, influenza-like illness and acute watery diarrhoea. In March 2015, Vanuatu was struck by Cyclone Pam, after which several important changes and improvements to the country’s syndromic surveillance were made. To date, there has been no formal evaluation of whether regular reports are occurring or that core syndromes are being documented. We therefore carried out a descriptive study in the 11 sentinel sites in Vanuatu conducting syndromic surveillance between July and December 2015. There was a total of 53 822 consultations which were higher in the first 13 weeks (n = 29 622) compared with the last 13 weeks (n = 24 200). During the six months, there were no cases of acute fever and rash or prolonged fever. There were cases with influenza-like illness from week 27 to 35, but no case was reported after week 35. Acute watery diarrhoea occurred in one or two cases per week during the whole study period. For these two core syndromes, there were generally more females than males, and about one third were children aged under 5 years. In conclusion, Vanuatu implemented changes to its new syndromic surveillance system from July to December 2015, although laboratory components had not yet been incorporated. The laboratory components are working in 2016 and will be the subject of a further report.

title: Expected impact of lockdown in Île-de-France and possible exit strategies
abstract: More than half of the global population is currently under strict forms of social distancing, with more than 90 countries in lockdown, including France. Estimating the expected impact of the lockdown, and the potential effectiveness of different exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis. We use a stochastic age-structured transmission model integrating data on age profile and social contacts in the Île-de-France region to (i) assess the current epidemic situation, (ii) evaluate the expected impact of the lockdown implemented in France on March 17, 2020, and (iii) estimate the effectiveness of possible exit strategies. The model is calibrated on hospital admission data of the region before lockdown and validated on syndromic and virological surveillance data. Different types and durations of social distancing interventions are simulated, including a progressive lifting of the lockdown targeted on specific classes of individuals (e.g. allowing a larger proportion of the population to go to work, while protecting the elderly), and large-scale testing. We estimate the basic reproductive number at 3.0 [2.8, 3.2] (95% confidence interval) prior to lockdown and the population infected by COVID-19 as of April 5 to be in the range 1% to 6%. The average number of contacts is predicted to be reduced by 80% during lockdown, leading to a substantial reduction of the reproductive number (RLD = 0.68 [0.62-0.73]). Under these conditions, the epidemic curve reaches ICU system capacity and slowly decreases during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave largely overwhelming the healthcare system. Extensive case-finding, testing and isolation are required to envision social distancing strategies that gradually relax current constraints (larger fraction of individuals going back to work, progressive reopening of activities), while keeping schools closed and seniors isolated. As France faces the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case-finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.

title: Retrospective testing and case series study of porcine delta coronavirus in U.S. swine herds
abstract: Porcine deltacoronavirus (PDCoV) was first reported in the United States (US) in February 2014. This was the second novel swine enteric coronavirus detected in the US since May 2013. In this study, we conducted retrospective testing of samples submitted to three veterinary diagnostic laboratories where qualifying biological samples were derived from previously submitted diagnostic case submissions from US commercial swine farms with a clinical history of enteric disease or from cases that had been previously tested for transmissible gastroenteritis virus, PEDV, or rotavirus. Overall, 2286 banked samples were tested from 27 States. Samples were collected in 3 separate years and in 17 different months. Test results revealed 4 positive samples, 3 collected in August 2013 and 1 collected in October 2013. In addition, a case series including 42 operations in 10 States was conducted through administration of a survey. Survey data collected included information on characteristics of swine operations that had experienced PDCoV clinical signs. Special emphasis was placed on obtaining descriptive estimates of biosecurity practices and disease status over time of each operation. Clinical signs of PDCoV were reported to be similar to those of PEDV. The average number of animals on each operation exhibiting clinical signs (morbidity) and the average number of case fatalities was greatest for suckling and weaned pigs. Average operation-level weaned pig morbidity was greatest in the first week of the outbreak while average operation-level suckling pig case fatality was greatest in the second week of the outbreak. The survey included questions regarding biosecurity practices for visitors and operation employees; trucks, equipment and drivers; and feed sources. These questions attempted to identify a likely pathway of introduction of PDCoV onto the operations surveyed.

title: Reporting of D-dimer data in COVID-19: some confusion and potential for misinformation
abstract: Coronavirus disease 2019 (COVID-19) represents a new pandemic caused by severe acute respiratory syndrome virus coronavirus 2 (SARS-CoV-2). A previous pooled analysis clearly identified elevated D-dimer levels as being associated with severity of COVID-19. Since then, several other studies have provided clearer support for this initial evidence. However, potentially under-recognized by those reporting on D-dimer is the considerable variation in reporting units for D-dimer, and thus also the potential for misreporting of D-dimer data based on poor or incomplete reporting. A PubMed search was used to identify recent papers reporting on D-dimers in COVID-19-based studies. We report that: (1) most publications did not identify either the manufacturer or D-dimer product used; (2) most did not identify whether D-dimer values were reported as D-dimer units (DDU) or fibrinogen equivalent units (FEU) (~2 × differences); (3) nearly half did not identify normal cut-off values; (4) some did not report numerical findings or units for D-dimer; (5) where reported, most identified units as either mg/L or µg/mL; (6) we identified at least four errors in reporting from 21 papers. It may not be possible to truly standardize D-dimer assays, but it should be feasible to harmonize D-dimer assays to a single unit of measurement.

title: Do the current cases reported to the WHO provide a realistic incidence rate of countries infected with COVID-19?

title: Assembly and operation of an open-source, computer numerical controlled (CNC) robot for performing cranial microsurgical procedures.
abstract: Cranial microsurgery is an essential procedure for accessing the brain through the skull that can be used to introduce neural probes that measure and manipulate neural activity. Neuroscientists have typically used tools such as high-speed drills adapted from dentistry to perform these procedures. As the number of technologies available for neuroscientists has increased, the corresponding cranial microsurgery procedures to deploy them have become more complex. Using a robotic tool that automatically performs these procedures could standardize cranial microsurgeries across neuroscience laboratories and democratize the more challenging procedures. We have recently engineered a robotic surgery platform that utilizes principles of computer numerical control (CNC) machining to perform a wide variety of automated cranial procedures. Here, we describe how to adapt, configure and use an inexpensive desktop CNC mill equipped with a custom-built surface profiler for performing CNC-guided microsurgery on mice. Detailed instructions are provided to utilize this 'Craniobot' for performing circular craniotomies for coverslip implantation, large craniotomies for implanting transparent polymer skulls for cortex-wide imaging access and skull thinning for intact skull imaging. The Craniobot can be set up in <2 weeks using parts that cost <$1,500, and we anticipate that the Craniobot could be easily adapted for use in other small animals.

title: COVID-19 diagnostic approaches: different roads to the same destination
abstract: “SARS-CoV2”, a previously unknown strain of coronaviruses caused a severe respiratory disease called Coronavirus disease (COVID-19) which emerged from Wuhan city of China on 30 December 2019, and declared as Global health problem by World Health Organisation within a month. In less than two and half months (11 March, 2020) it was declared as a pandemic disease due to its rapid spreading ability, it covered more than 211 countries infecting around 1.7 million persons and claiming around 1.1 lakhs lives within merely 100 days of its emergence. Containment of the infection of this virus is the only available measure to control the disease as no vaccine or specific antiviral treatment is available. Confirmed detection of the virus followed by isolation of the infected person at the earliest possible is the only measure to prevent this disease. Although there are number of methods available for detection of virus and to combat this disease in the present pandemic situation, but these available diagnostic methods have their own limitations. The speedy and exponential global spread of this disease strongly urges the fast and economic diagnostics tools. Additional to the available diagnostic methods, there is a sudden surge for development of various of methods and platforms to diagnose the COVID-19. The review summarized the advantage and disadvantage of various diagnostic approaches being used presently for COVID-19, newer detection methods in developmental stage and the feasibility of advanced platforms like newer nano-sensor based on-the-spot detection technologies.

title: The explosive epidemic outbreak of novel coronavirus disease 2019 (COVID-19) and the persistent threat of respiratory tract infectious diseases to global health security

title: Challenges in the diagnosis of paediatric pneumonia in intervention field trials: recommendations from a pneumonia field trial working group
abstract: Pneumonia is a leading killer of children younger than 5 years despite high vaccination coverage, improved nutrition, and widespread implementation of the Integrated Management of Childhood Illnesses algorithm. Assessing the effect of interventions on childhood pneumonia is challenging because the choice of case definition and surveillance approach can affect the identification of pneumonia substantially. In anticipation of an intervention trial aimed to reduce childhood pneumonia by lowering household air pollution, we created a working group to provide recommendations regarding study design and implementation. We suggest to, first, select a standard case definition that combines acute (≤14 days) respiratory symptoms and signs and general danger signs with ancillary tests (such as chest imaging and pulse oximetry) to improve pneumonia identification; second, to prioritise active hospital-based pneumonia surveillance over passive case finding or home-based surveillance to reduce the risk of non-differential misclassification of pneumonia and, as a result, a reduced effect size in a randomised trial; and, lastly, to consider longitudinal follow-up of children younger than 1 year, as this age group has the highest incidence of severe pneumonia.

title: Prognostic value of NT-proBNP in patients with severe COVID-19
abstract: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China has been declared a public health emergency of international concern. The cardiac injury was dominate in the process. However, whether N terminal pro B type natriuretic peptide (NT-proBNP) predicted outcome of COVID-19 patients was unknown. The study initially enrolled 102 patients with severe COVID-19 pneumonia from a continuous sample. After screening out the ineligible cases, 54 patients were analyzed in this study. Results found that patients with higher NT-proBNP (above 88.64 pg/mL) level had more risks of in-hospital death. After adjusting for potential cofounders in separate modes, NT-proBNP presented as an independent risk factor of in-hospital death in patients with severe COVID-19.

title: A call for action for COVID-19 surveillance and research during pregnancy

title: La chirurgie digestive urgente, victime collatérale de la crise du Covid-19?

title: Management of patients with suspected or confirmed COVID-19, in the radiology department
abstract: From December 2019, a novel coronavirus named COVID-19 was reported in China. Within 3 months, the World Health Organization defined COVID-19 as a pandemic, with more than 370,000 cases and 16,000 deaths worldwide. In consideration of the crucial role of diagnostic testing during COVID-19, the aim of this technical note was to provide a complete synthesis of approaches implemented for the management of suspected or confirmed COVID-19 patients.  The planning of a robust plan to prevent the transmission of the virus to patients and department staff members should be fundamental in each radiology service. Moreover, the speed of spread and the incidence of the pandemic make it necessary to optimize the use of personal protective devices and dedicated COVID-19 equipment, given the limited availability of supplies.  In the management of radiographic and CT imaging, staff should take special precautions to limit contamination between patients and other patients or professionals. Implications for practice An isolated imaging room should be dedicated to suspected or confirmed COVID-19 cases, including radiography and CT scanners. This paper will provide guidance concerning disposable protective gear to be utilized, as well as on the cleaning and sanitation of radiology room and equipment.

title: The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak
abstract: Coronavirus disease (COVID-19) is caused by SARS-COV2 and represents the causative agent of a potentially fatal disease that is of great global public health concern. Based on the large number of infected people that were exposed to the wet animal market in Wuhan City, China, it is suggested that this is likely the zoonotic origin of COVID-19. Person-to-person transmission of COVID-19 infection led to the isolation of patients that were subsequently administered a variety of treatments. Extensive measures to reduce person-to-person transmission of COVID-19 have been implemented to control the current outbreak. Special attention and efforts to protect or reduce transmission should be applied in susceptible populations including children, health care providers, and elderly people. In this review, we highlights the symptoms, epidemiology, transmission, pathogenesis, phylogenetic analysis and future directions to control the spread of this fatal disease.

title: Group Testing for Sars-Cov-2 to Enable Rapid Scale-Up of Testing and Real-Time Surveillance of Incidence
abstract: High-throughput molecular testing for SARS-CoV-2 may be enabled by group testing in which pools of specimens are screened, and individual specimens tested only after a pool tests positive. Several labs have recently published examples of pooling strategies applied to SARS-CoV-2 specimens, but overall guidance on efficient pooling strategies is lacking. Therefore we developed a model of the efficiency and accuracy of specimen pooling algorithms based on available data on SAR-CoV-2 viral dynamics. For a fixed number of tests, we estimate that programs using group testing could screen 2 to 20 times as many specimens compared to individual testing; increase the total number of true positive infections identified; and improve the positive predictive value of results. We compare outcomes that may be expected in different testing situations and provide general recommendations for group testing implementation. A free, publicly-available web calculator is provided to help inform laboratory decisions on SARS-CoV-2 pooling algorithms.

title: Recurrence of positive SARS-CoV-2 RNA in COVID-19: A case report
abstract: The ongoing outbreak of COVID-19 that began in Wuhan, China, has constituted a Public Health Emergency of International Concern, with cases confirmed in multiple countries. Currently, patients are the primary source of infection. We report a confirmed case of COVID-19 whose oropharyngeal swab test of SARS-CoV-2 RNA turned positive in convalescence. This case highlights the importance of active surveillance of SARS-CoV-2 RNA for infectivity assessment.

title: Ascertainment rate of novel coronavirus disease (COVID-19) in Japan
abstract: To estimate the ascertainment rate of novel coronavirus (COVID-19).  We analyzed the epidemiological dataset of confirmed cases with COVID-19 in Japan as of 28 February 2020. A statistical model was constructed to describe the heterogeneity of reporting rate by age and severity. We estimated the number of severe and non-severe cases, accounting for under-ascertainment.  The ascertainment rate of non-severe cases was estimated at 0.44 (95% confidence interval: 0.37, 0.50), indicating that unbiased number of non-cases would be more than twice the reported count.  Severe cases are twice more likely diagnosed and reported than other cases. Considering that reported cases are usually dominated by non-severe cases, the adjusted total number of cases is also about a double of observed count. Our finding is critical in interpreting the reported data, and it is advised to interpret mild case data of COVID-19 as always under-ascertained.

title: Radiologist Reporting and Operational Management for Patients With Suspected COVID-19
abstract: The aim of this study was to evaluate the adoption and outcomes of locally designed reporting guidelines for patients with possible coronavirus disease 2019 (COVID-19).  A departmental guideline was developed for radiologists that specified reporting terminology and required communication for patients with imaging findings suggestive of COVID-19, on the basis of patient test status and imaging indication. In this retrospective study, radiology reports completed from March 1, 2020, to May 3, 2020, that mentioned COVID-19 were reviewed. Reports were divided into patients with known COVID-19, patients with "suspected" COVID-19 (having an order indication of respiratory or infectious signs or symptoms), and "unsuspected patients" (other order indications, eg, trauma or non-chest pain). The primary outcome was the percentage of COVID-19 reports using recommended terminology; the secondary outcome was percentages of suspected and unsuspected patients diagnosed with COVID-19. Relationships between categorical variables were assessed using the Fisher exact test.  Among 77,400 total reports, 1,083 suggested COVID-19 on the basis of imaging findings; 774 of COVID-19 reports (71%) used recommended terminology. Of 574 patients without known COVID-19 at the time of interpretation, 345 (60%) were eventually diagnosed with COVID-19, including 61% (315 of 516) of suspected and 52% (30 of 58) of unsuspected patients. Nearly all unsuspected patients (46 of 58) were identified on CT.  Radiologists rapidly adopted recommended reporting terminology for patients with suspected COVID-19. The majority of patients for whom radiologists raised concern for COVID-19 were subsequently diagnosed with the disease, including the majority of clinically unsuspected patients. Using unambiguous terminology and timely notification about previously unsuspected patients will become increasingly critical to facilitate COVID-19 testing and contact tracing as states begin to lift restrictions.

title: Eosinophil count in severe coronavirus disease 2019 (COVID-19)

title: Short-Term Covid-19 Forecast for Latecomers
abstract: The number of Covid-19 cases is increasing dramatically worldwide. Therefore, the availability of reliable forecasts for the number of cases in the coming days is of fundamental importance. We propose a simple statistical method for short-term real-time forecasting of the number of Covid-19 cases and fatalities in countries that are latecomers -- i.e., countries where cases of the disease started to appear some time after others. In particular, we propose a penalized (LASSO) regression with an error correction mechanism to construct a model of a latecomer in terms of the other countries that were at a similar stage of the pandemic some days before. By tracking the number of cases and deaths in those countries, we forecast through an adaptive rolling-window scheme the number of cases and deaths in the latecomer. We apply this methodology to Brazil, and show that (so far) it has been performing very well. These forecasts aim to foster a better short-run management of the health system capacity.

title: Early identification of pneumonia patients at increased risk of Middle East respiratory syndrome coronavirus infection in Saudi Arabia
abstract: The rapid and accurate identification of individuals who are at high risk of Middle East respiratory syndrome coronavirus (MERS-CoV) infection remains a major challenge for the medical and scientific communities. The aim of this study was to develop and validate a risk prediction model for the screening of suspected cases of MERS-CoV infection in patients who have developed pneumonia.  A two-center, retrospective case–control study was performed. A total of 360 patients with confirmed pneumonia who were evaluated for MERS-CoV infection by real-time reverse transcription polymerase chain reaction (rRT-PCR) between September 1, 2012 and June 1, 2016 at King Abdulaziz Medical City in Riyadh and King Fahad General Hospital in Jeddah, were included. According to the rRT-PCR results, 135 patients were positive for MERS-CoV and 225 were negative. Demographic characteristics, clinical presentations, and radiological and laboratory findings were collected for each subject.  A risk prediction model to identify pneumonia patients at increased risk of MERS-CoV was developed. The model included male sex, contact with a sick patient or camel, diabetes, severe illness, low white blood cell (WBC) count, low alanine aminotransferase (ALT), and high aspartate aminotransferase (AST). The model performed well in predicting MERS-CoV infection (area under the receiver operating characteristics curves (AUC) 0.8162), on internal validation (AUC 0.8037), and on a goodness-of-fit test (p =0.592). The risk prediction model, which produced an optimal probability cut-off of 0.33, had a sensitivity of 0.716 and specificity of 0.783.  This study provides a simple, practical, and valid algorithm to identify pneumonia patients at increased risk of MERS-CoV infection. This risk prediction model could be useful for the early identification of patients at the highest risk of MERS-CoV infection. Further validation of the prediction model on a large prospective cohort of representative patients with pneumonia is necessary.

title: Impact of immune enhancement on Covid-19 polyclonal hyperimmune globulin therapy and vaccine development
abstract: The pandemic spread of a novel coronavirus – SARS coronavirus-2 (SARS-CoV-2) as a cause of acute respiratory illness, named Covid-19, is placing the healthcare systems of many countries under unprecedented stress. Global economies are also spiraling towards a recession in fear of this new life-threatening disease. Vaccines that prevent SARS-CoV-2 infection and therapeutics that reduces the risk of severe Covid-19 are thus urgently needed. A rapid method to derive antiviral treatment for Covid-19 is the use of convalescent plasma derived hyperimmune globulin. However, both hyperimmune globulin and vaccine development face a common hurdle – the risk of antibody-mediated disease enhancement. The goal of this review is to examine the body of evidence supporting the hypothesis of immune enhancement that could be pertinent to Covid-19. We also discuss how this risk could be mitigated so that both hyperimmune globulin and vaccines could be rapidly translated to overcome the current global health crisis.

title: Feeling Positive About Reopening?New Normal Scenarios from COVID-19 ReopenSentiment Analytics
abstract: The Coronavirus pandemic has created complex challenges and adverse circumstances. This research identifies public sentiment amidst problematic socioeconomic consequences of the lockdown, and explores ensuing four potential sentiment associated scenarios. The severity and brutality of COVID-19 have led to the development of extreme feelings, and emotional and mental healthcare challenges. This research focuses on emotional consequences - the presence of extreme fear, confusion and volatile sentiments, mixed along with trust and anticipation. It is necessary to gauge dominant public sentiment trends for effective decisions and policies. This study analyzes public sentiment using Twitter Data, time-aligned to the COVID-19 reopening debate, to identify dominant sentiment trends associated with the push to 'reopen' the economy. Present research uses textual analytics methodologies to analyze public sentiment support for two potential divergent scenarios - an early opening and a delayed opening, and consequences of each. Present research concludes on the basis of exploratory textual analytics and textual data visualization, that Tweets data from American Twitter users shows more positive sentiment support, than negative, for reopening the US economy. This research develops a novel sentiment polarity based four scenarios framework, which will remain useful for future crisis analysis, well beyond COVID-19. With additional validation, this research stream could present valuable time sensitive opportunities for state governments, the federal government, corporations and societal leaders to guide local and regional communities, and the nation into a successful new normal future.

title: ENT manifestation in COVID-19 patients
abstract: to detect, analyze and discuss the different ear nose throat (ENT) manifestations those were reported in COVID19 positive patients in the reviewed and published literatures.  We performed a search in the PubMed databases, Web of Science, LILACS, MEDLINE, SciELO, and Cochrane Library using the keywords; COVID-19, Novel coronavirus, corona, 2019-nCoV, SARS-CoV-2, ENT, ear, nose, throat, otorhinolaryngology, ORL, pharynx, ORL, smell, larynx, different ENT related symptoms. We reviewed published and peer reviewed studies that reported the ENT manifestations in COVID-19 laboratory-confirmed positive patients.  within the included 1773 COVID-19 laboratory-confirmed positive patients, the most common ENT manifestations of COVID-19 were sore throat (11.3%) and headache (10.7%). While the other reported ENT manifestations were pharyngeal erythema (5.3%), nasal congestion (4.1%), runny nose or rhinorrhea (2.1%), upper respiratory tract infection (URTI) (1.9%), and tonsil enlargement (1.3%).  ENT manifestations for COVID-19 are not common as fever and cough. But, a universal questionnaire using well-defined COVID-19 manifestations is needed to make the COVID-19 data precisely defined, complete and homogenous.

title: Update: Severe Respiratory Illness Associated With a Novel Coronavirus—Worldwide, 2012-2013

title: Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters
abstract: Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China in December 2019, and is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is a pandemic with an estimated death rate between 1% and 5%; and an estimated R 0 between 2.2 and 6.7 according to various sources. As of March 28th, 2020, there were over 649,000 confirmed cases and 30,249 total deaths, globally. In the United States, there were over 115,500 cases and 1891 deaths and this number is likely to increase rapidly. It is critical to detect clusters of COVID-19 to better allocate resources and improve decision-making as the outbreaks continue to grow. Using daily case data at the county level provided by Johns Hopkins University, we conducted a prospective spatial-temporal analysis with SaTScan. We detect statistically significant space-time clusters of COVID-19 at the county level in the U.S. between January 22nd-March 9th, 2020, and January 22nd-March 27th, 2020. The space-time prospective scan statistic detected “active” and emerging clusters that are present at the end of our study periods – notably, 18 more clusters were detected when adding the updated case data. These timely results can inform public health officials and decision makers about where to improve the allocation of resources, testing sites; also, where to implement stricter quarantines and travel bans. As more data becomes available, the statistic can be rerun to support timely surveillance of COVID-19, demonstrated here. Our research is the first geographic study that utilizes space-time statistics to monitor COVID-19 in the U.S.

title: Report from the American Society for Microbiology COVID-19 International Summit, 23 March 2020: Value of Diagnostic Testing for SARS–CoV-2/COVID-19

title: Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China
abstract: Strict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.

title: Opinion de comité de la SOGC – COVID-19 pendant la grossesse

title: Bacterial and fungal co-infection in individuals with coronavirus: A rapid review to support COVID-19 antimicrobial prescribing
abstract: To explore and describe the current literature surrounding bacterial/fungal co-infection in patients with coronavirus infection.  MEDLINE, EMBASE, and Web of Science were searched using broad based search criteria relating to coronavirus and bacterial co-infection. Articles presenting clinical data for patients with coronavirus infection (defined as SARS-1, MERS, SARS-COV-2, and other coronavirus) and bacterial/fungal co-infection reported in English, Mandarin, or Italian were included. Data describing bacterial/fungal co-infections, treatments, and outcomes were extracted. Secondary analysis of studies reporting antimicrobial prescribing in SARS-COV-2 even in the absence of co-infection was performed.  1007 abstracts were identified. Eighteen full texts reported bacterial/fungal co-infection were included. Most studies did not identify or report bacterial/fungal coinfection (85/140;61%). 9/18 (50%) studies reported on COVID-19, 5/18 (28%) SARS-1, 1/18 (6%) MERS, and 3/18 (17%) other coronavirus.For COVID-19, 62/806 (8%) patients were reported as experiencing bacterial/fungal co-infection during hospital admission. Secondary analysis demonstrated wide use of broad-spectrum antibacterials, despite a paucity of evidence for bacterial coinfection. On secondary analysis, 1450/2010 (72%) of patients reported received antimicrobial therapy. No antimicrobial stewardship interventions were described.For non-COVID-19 cases bacterial/fungal co-infection was reported in 89/815 (11%) of patients. Broad-spectrum antibiotic use was reported.  Despite frequent prescription of broad-spectrum empirical antimicrobials in patients with coronavirus associated respiratory infections, there is a paucity of data to support the association with respiratory bacterial/fungal co-infection. Generation of prospective evidence to support development of antimicrobial policy and appropriate stewardship interventions specific for the COVID-19 pandemic are urgently required.

title: Evaluating efficiency of pooling specimens for PCR-based detection of COVID-19
abstract: In the age of a pandemic, such as the ongoing one caused by SARS-CoV-2, the world faces limited supply of tests, PPE and reagents, and factories are struggling to meet the growing demands. This study aimed to evaluate the efficacy of pooling specimen for testing of SARS-CoV-2 virus, to determine whether costs and resource savings could be achieved without impacting the sensitivity of the testing. Ten specimens were pooled for testing, containing either one or two known positive specimen of varying viral concentrations. Pooling specimens did not affect the sensitivity of detecting SARS-CoV-2, and the PCR cycle threshold (Ct) between testing of pooling specimen and subsequent individual testing was not significantly different using paired t-test. This study also identified cost savings garnered from pooling of specimen for testing at 4 differing prevalence rates, ranging from 0.1-10%. Pooling specimens to test for COVID-19 infection in low prevalence areas or in low risk population can dramatically decrease the resources burden on lab operations by up to 80%. This paves the possibility for large-scale population screening, allowing for assured policy decisions by governmental bodies to ease lockdown restrictions in areas with low incidence of infection, or with lower risk populations.

title: COVID-Net: A deep learning based and interpretable predication model for the county-wise trajectories of COVID-19 in the United States
abstract: The confirmed cases of novel coronavirus disease (COVID-19) have been reported in the United States since late January 2020. There were over 4.8 million confirmed cases and about 320,000 deaths as of May 19, 2020 in the world. We examined the characteristics of the confirmed cases and deaths of COVID-19 in all affected counties of the United States. We proposed a COVID-Net combining the architecture of both Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) by using the trajectories of COVID-19 during different periods until May 19, 2020, as the training data. The validation of the COVID-Net was performed by predicting the numbers of confirmed cases and deaths in subsequent 3-day, 5-day, and 7-day periods. The COVID-Net produced relatively smaller Mean Relative Errors (MREs) for the 10 counties with the most severe epidemic as of May 19, 2020. On average, MREs were 0.01 for the number of confirmed cases in all validation periods, and 0.01, 0.01, and 0.03 for the number of deaths in the 3-day, 5-day, and 7-day periods, respectively. The COVID-Net incorporated five risk factors of COVID-19 and was used to predict the trajectories of COVID-19 in Hudson County, New Jersey and New York County, New York until June 28, 2020. The risk factors include the percentage of the population with access to exercise opportunities, average daily PM2.5, population size, preventable hospitalization rate, and violent crime rate. The expected number of cumulative confirmed cases and deaths depends on the dynamics of these five risk factors.

title: What Have We Learned About Middle East Respiratory Syndrome Coronavirus Emergence in Humans? A Systematic Literature Review
abstract: Middle East respiratory syndrome coronavirus (MERS-CoV) was first identified in humans in 2012. A systematic literature review was conducted to synthesize current knowledge and identify critical knowledge gaps.  We conducted a systematic review on MERS-CoV using PRISMA guidelines. We identified 407 relevant, peer-reviewed publications and selected 208 of these based on their contributions to four key areas: virology; clinical characteristics, outcomes, therapeutic and preventive options; epidemiology and transmission; and animal interface and the search for natural hosts of MERS-CoV.  Dipeptidyl peptidase 4 (DPP4/CD26) was identified as the human receptor for MERS-CoV, and a variety of molecular and serological assays developed. Dromedary camels remain the only documented zoonotic source of human infection, but MERS-like CoVs have been detected in bat species globally, as well as in dromedary camels throughout the Middle East and Africa. However, despite evidence of camel-to-human MERS-CoV transmission and cases apparently related to camel contact, the source of many primary cases remains unknown. There have been sustained health care-associated human outbreaks in Saudi Arabia and South Korea, the latter originating from one traveler returning from the Middle East. Transmission mechanisms are poorly understood; for health care, this may include environmental contamination. Various potential therapeutics have been identified, but not yet evaluated in human clinical trials. At least one candidate vaccine has progressed to Phase I trials.  There has been substantial MERS-CoV research since 2012, but significant knowledge gaps persist, especially in epidemiology and natural history of the infection. There have been few rigorous studies of baseline prevalence, transmission, and spectrum of disease. Terms such as “camel exposure” and the epidemiological relationships of cases should be clearly defined and standardized. We strongly recommend a shared and accessible registry or database. Coronaviruses will likely continue to emerge, arguing for a unified “One Health” approach.

title: Diagnostic Challenge

title: Teicoplanin: an alternative drug for the treatment of coronavirus COVID-19?
abstract: In December 2019, a new coronavirus, named SARS-CoV-2, has emerged from China causing pneumonia outbreaks first in the Wuhan region and have now spread worldwide because of its probable high transmission efficiency. Due to the lack of efficient and specific treatments and the need to contain the epidemic, drug repurposing appears to be the best tool to find therapeutic solution. Chloroquine, remdesivir, lopinavir, ribavirin or ritonavir have shown efficacy to inhibit coronavirus in vitro. Teicoplanin, an antibiotic used to treat staphylococci infection, previously showed efficacy to inhibit the first stage of MERS-coronarivus viral cycle in human cells. This activity is conserved on the SARS-Cov-2, thus placing teicoplanin as a potential treatment for patients with this virus.

title: Coagulation disorders in coronavirus infected patients: COVID-19, SARS-CoV-1, MERS-CoV and lessons from the past
abstract: Coronavirus disease 2019 (COVID-19) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus strain disease, has recently emerged in China and rapidly spread worldwide. This novel strain is highly transmittable and severe disease has been reported in up to 16% of hospitalized cases. More than 600,000 cases have been confirmed and the number of deaths is constantly increasing. COVID-19 hospitalized patients, especially those suffering from severe respiratory or systemic manifestations, fall under the spectrum of the acutely ill medical population, which is at increased venous thromboembolism risk. Thrombotic complications seem to emerge as an important issue in patients infected with COVID-19. Preliminary reports on COVID-19 patients’ clinical and laboratory findings include thrombocytopenia, elevated D-dimer, prolonged prothrombin time, and disseminated intravascular coagulation. As the pandemic is spreading and the whole picture is yet unknown, we highlight the importance of coagulation disorders in COVID-19 infected patients and review relevant data of previous coronavirus epidemics caused by the severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and the Middle East Respiratory Syndrome coronavirus (MERS-CoV).

title: Projection of COVID-19 Cases and Deaths in the US as Individual States Re-open May 4,2020
abstract: In March and April 2020, control measures enforcing social distancing and restricting individual movement and contact were adopted across the United States in an effort to slow the spread and growth of COVID-19. However, a number of states have now begun to ease these restrictions. Here, we evaluate the effects of loosening stay-at-home orders on COVID-19 incidence and related outcomes. We use a metapopulation model applied at county resolution to simulate the spread and growth of COVID-19 incidence in the United States. We calibrate the model against county-level daily case and death data collected from February 21, 2020 to May 2, 2020, and project the outbreak in 3,142 US counties for 6 weeks into the future. Projections for daily reported cases, daily new infections (both reported and unreported), new and cumulative hospital bed demand, ICU bed and ventilator demand, as well as daily mortality, are generated. We observe a rebound in COVID-19 incidence and deaths beginning in late May, approximately 2 to 4 weeks after states begin to reopen. Importantly, the lag between infection acquisition and case confirmation, coupled with insufficient broader testing and contact tracing, will mask any rebound and exponential growth of the COVID-19 until it is well underway.

title: Proceedings of Réanimation 2019, the French Intensive Care Society International Congress

title: Parameter Estimation from ICC curves
abstract: Incidence - Cumulative Cases (ICC) curves are introduced and shown to provide a simple framework for parameter identification in the case of the most elementary epidemiological model, consisting of susceptible, infected, and removed compartments. This novel methodology is used to estimate the basic reproductive number of recent outbreaks, including the ongoing COVID-19 epidemic.

title: Severe acute respiratory syndrome (SARS) in a paediatric cluster in Singapore
abstract: Severe acute respiratory syndrome (SARS) is a major infectious disease pandemic that occurred in early 2003, and one of the diagnostic criteria is the presence of chest radiographic findings.  To describe the radiographic features of SARS in a cluster of affected children.  The chest radiographs of four related children ranging in age from 18 months to 9 years diagnosed as having SARS were reviewed for the presence of air-space shadowing, air bronchograms, peribronchial thickening, interstitial disease, pleural effusion, pneumothorax, hilar lymphadenopathy and mediastinal widening.  Ill-defined air-space shadowing was the common finding in all the children. The distribution was unifocal or multifocal. No other findings were seen on the radiographs. None of the children developed radiographic findings consistent with acute respiratory distress syndrome. All four children showed significant resolution of the radiographic findings 4–6 days after the initial radiograph.  Early recognition of these features is important in implementing isolation and containment measures to prevent the spread of infection. SARS in children appears to manifest as a milder form of the disease as compared to adults.

title: Re-analysis of SARS-CoV-2 infected host cell proteomics time-course data by impact pathway analysis and network analysis. A potential link with inflammatory response
abstract: The disease known as coronavirus disease 19 (COVID-19), potentially caused by an outbreak of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) in Wuhan, China, has hit the world hard, and has led to an unprecedent health and economic crisis. In order to develop treatment options able to stop or ameliorate SARS-CoV-2 effects, we need to understand the biology of the virus inside cells, but this kind of studies are still scarce. A recent study investigated translatome and proteome host cell changes induced in vitro by SARS-CoV-2. In the present study, we use the publicly available proteomics data from this study to re-analyze the mechanisms altered by the virus infection by impact pathways analysis and network analysis. Proteins linked to inflammatory response, but also proteins related to chromosome segregation during mitosis, were found to be regulated. The up-regulation of the inflammatory-related proteins observed could be linked to the propagation of inflammatory reaction and lung injury that is observed in advanced stages of COVID-19 patients.

title: Rapid prototyping and clinical testing of a reusable face shield for health care workers responding to the COVID-19 pandemic
abstract: Due to supply chain disruption, the COVID-19 pandemic has caused severe shortages in personal protective equipment (PPE) for health care professionals. Local fabrication based on 3D printing is one way to address this challenge, particularly in the case of simple products such as protective face shields. As a consequence, many public domain designs for face shields have become available. No clear path exists, however, for introducing a locally fabricated and unapproved product into a clinical setting. In a US health care setting, face shields are regulated by the Food and Drug Administration (FDA); similar policies exist in other countries. We describe a research protocol under which rapid iteration on an existing design, coupled with clinical feedback and real-world testing in an emergency department, allowed a face shield to be implemented by the members of the incident command team at a major academic medical center. We describe our design and testing process and provide an overview of regulatory considerations associated with fabrication and testing of face shields and related products. All designs, materials used, testing protocols, and survey results are reported in full to facilitate the execution of similar face shield efforts in other clinical settings. Our work serves as a case study for development of a robust local response to pandemics and other health care emergencies, with implications for healthcare professionals, hospital administrators, regulatory agencies and concerned citizens.

title: Covid-19 pandemic by the “real-time” monitoring: the Tunisian case and lessons for global epidemics in the context of 3PM strategies
abstract: Covid-19 is neither the first nor the last viral epidemic which societies around the world are, were and will be affected by. Which lessons should be taken from the current pandemic situation? The Covid-19 disease is still not well characterised, and many research teams all over the world are working on prediction of the epidemic scenario, protective measures to populations and sub-populations, therapeutic and vaccination issues, amongst others. Contextually, countries with currently low numbers of Covid-19-infected individuals such as Tunisia are intended to take lessons from those countries which already reached the exponential phase of the infection distribution as well as from those which have the exponential phase behind them and record a minor number of new cases such as China. To this end, in Tunisia, the pandemic wave has started with a significant delay compared with Europe, the main economic partner of the country. In this paper, we do analyse the current pandemic situation in this country by studying the infection evolution and considering potential protective strategies to prevent a pandemic scenario. The model is predictive based on a large number of undetected Covid-19 cases that is particularly true for some country regions such as Sfax. Infection distribution and mortality rate analysis demonstrate a highly heterogeneous picture over the country. Qualitative and quantitative comparative analysis leads to a conclusion that the reliable “real-time” monitoring based on the randomised laboratory tests is the optimal predictive strategy to create the most effective evidence-based preventive measures. In contrast, lack of tests may lead to incorrect political decisions causing either unnecessary over-protection of the population that is risky for a long-term economic recession, or under-protection of the population leading to a post-containment pandemic rebound. Recommendations are provided in the context of advanced predictive, preventive and personalised (3P) medical approach.

title: Epidemiology of the 2020 pandemic of COVID‐19 in the state of Georgia: Inadequate critical care resources and impact after 7 weeks of community spread
abstract: Novel coronavirus (COVID‐19) is a global pandemic currently spreading rapidly across the United States. We provide a comprehensive look at COVID‐19 epidemiology across the state of Georgia, which includes vast rural communities that may be disproportionately impacted by the spread of this infectious disease.  All 159 Georgia counties were included in this study. We examined the geographic variation of COVID‐19 in Georgia from March 3 through April 24, 2020 by extracting data on incidence and mortality from various national and state datasets. We contrasted county‐level mortality rates per 100,000 population (MRs) by county‐level factors.  Metropolitan Atlanta had the overall highest number of confirmed cases; however, the southwestern rural parts of Georgia, surrounding the city of Albany, had the highest bi‐weekly increases in incidence rate. Among counties with >10 cases, MRs were highest in the rural counties of Randolph (233.2), Terrell (182.5), Early (136.3), and Dougherty (114.2). Counties with the highest MRs (22.5–2332 per 100,000) had a higher proportion of: non‐Hispanic Blacks residents, adults aged 60+, adults earning <$20,000 annually, and residents living in rural communities when compared with counties with lower MRs. These counties also had a lower proportion of the population with a college education, lower number of ICU beds per 100,000 population, and lower number of primary care physicians per 10,000 population.  While urban centers in Georgia account for the bulk of COVID‐19 cases, high mortality rates and low critical care capacity in rural Georgia are also of critical concern.

title: Increased prevalence of VTE reported by Klok and colleagues, the numbers don't add up

title: A Commentary on Rural‐Urban Disparities in COVID‐19 Testing Rates per 100,000 and Risk Factors

title: Human Coronaviruses: A Review of Virus–Host Interactions
abstract: Human coronaviruses (HCoVs) are known respiratory pathogens associated with a range of respiratory outcomes. In the past 14 years, the onset of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) have thrust HCoVs into spotlight of the research community due to their high pathogenicity in humans. The study of HCoV-host interactions has contributed extensively to our understanding of HCoV pathogenesis. In this review, we discuss some of the recent findings of host cell factors that might be exploited by HCoVs to facilitate their own replication cycle. We also discuss various cellular processes, such as apoptosis, innate immunity, ER stress response, mitogen-activated protein kinase (MAPK) pathway and nuclear factor kappa B (NF-κB) pathway that may be modulated by HCoVs.

title: AGA Institute Rapid Recommendations for Gastrointestinal Procedures During the COVID-19 Pandemic

title: Duration of rhinovirus shedding in the upper respiratory tract in the first year of life.
abstract: Current molecular diagnostic methods have detected rhinovirus RNA in a high proportion of asymptomatic infants and children, raising the question of the clinical significance of these findings. This study investigates the prevalence of prolonged rhinovirus RNA presence in the upper respiratory tract of infants during the first year of life.  In a longitudinal study, infants were followed from birth up to 12 months. Nasopharyngeal specimens were collected monthly (months 1-6 and month 9) and during an upper respiratory infection. Rhinoviruses were detected by quantitative reverse-transcription polymerase chain reaction. Presence of repeated rhinovirus RNA was evaluated by nucleotide sequence analysis.  A total of 2153 specimens from 362 infants were studied; 341 distinct rhinovirus infections in 216 infants were identified. Follow-up specimens were available within 30 days for 179 infections, creating the sample set to assess prolonged rhinovirus presence. Of the 179 infections, 46 involved the detection of the same rhinovirus strain in repeated specimens, including 8 events of prolonged presence of the same strain (detected in specimens collected >30 days apart), representing 4.5% of the evaluable rhinovirus infections. There were 26 events in which a rhinovirus strain was replaced by a different strain within a 30-day interval, representing 14.5% of the 179 infections.  Although rhinovirus infections are common in healthy infants, prolonged presence of rhinovirus RNA in the respiratory tract after an upper respiratory infection was uncommon (<5%). Detection of rhinovirus RNA in an infant most likely represents an infection within a 30-day period.

title: Mechanism of thrombocytopenia in COVID-19 patients
abstract: Since December 2019, a novel coronavirus has spread throughout China and across the world, causing a continuous increase in confirmed cases within a short period of time. Some studies reported cases of thrombocytopenia, but hardly any studies mentioned how the virus causes thrombocytopenia. We propose several mechanisms by which coronavirus disease 2019 causes thrombocytopenia to better understand this disease and provide more clinical treatment options.

title: Impact assessment of non-pharmaceutical interventions against COVID-19 and influenza in Hong Kong: an observational study
abstract: A range of public health measures have been implemented to delay and reduce local transmission of COVID-19 in Hong Kong, and there have been major changes in behaviours of the general public. We examined the effect of these interventions and behavioral changes on the incidence of COVID-19 as well as on influenza virus infections which may share some aspects of transmission dynamics with COVID-19.  We reviewed policy interventions and measured changes in population behaviours through two telephone surveys, on January 20-23 and February 11-14. We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (R_t), for COVID-19 and influenza A(H1N1).  COVID-19 transmissibility has remained at or below 1, indicating successful containment to date. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% confidence interval, CI: 34% to 53%) reduction in transmissibility in the community, and a 33% (95% CI: 24% to 43%) reduction in transmissibility based on paediatric hospitalization rates. In the two surveys we estimated that 74.5% and 97.5% of the general adult population wore masks when going out, and 61.3% and 90.2% avoided going to crowded places, respectively.  Containment measures, social distancing measures and changes in population behaviour have successfully prevented spread of COVID-19. The social distancing measures and behavioural changes led to a substantial reduction in influenza transmission in early February 2020. However, it may be challenging to avoid fatigue and sustain these measures and population behaviours as COVID-19 continues to spread globally.

title: The effect of human mobility and control measures on the COVID-19 epidemic in China
abstract: The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19.

title: Impact of Comorbidity on Fatality Rate of Patients with Middle East Respiratory Syndrome
abstract: To date, 1841 cases of Middle East respiratory syndrome coronavirus (MERS-CoV) infection have been reported worldwide, with 652 deaths. We used a publically available case line list to explore the effect of relevant factors, notably underlying comorbidities, on fatal outcome of Middle East respiratory syndrome (MERS) cases up to the end of October 2016. A Bayesian Weibull proportional hazards regression model was used to assess the effect of comorbidity, age, epidemic period and sex on the fatality rate of MERS cases and its variation across countries. The crude fatality rate of MERS cases was 32.1% (95% credibility interval (CI): 29.9%, 34.3%). Notably, the incremental change of daily death rate was most prominent during the first week since disease onset with an average increase of 13%, but then stabilized in the remaining two weeks when it only increased 3% on average. Neither sex, nor country of infection were found to have a significant impact on fatality rates after taking into account the age and comorbidity status of patients. After adjusting for age, epidemic period, MERS patients with comorbidity had around 4 times the risk for fatal infection than those without (adjusted hazard ratio of 3.74 (95% CI: 2.57, 5.67)).

title: A rapid scoping review of Middle East respiratory syndrome coronavirus in animal hosts
abstract: Middle East respiratory syndrome coronavirus (MERS‐CoV) is an emerging zoonotic pathogen discovered in 2012. The purpose of this scoping review was to summarize the empirical evidence for MERS‐CoV in animals in order to map knowledge gaps and to extract data for modelling disease transmission in dromedary camels. A review protocol was developed a priori, and a systematic search, data extraction and summary were conducted using the Arksey and O'Malley framework. Ninety‐nine publications were identified for full review out of 1,368 unique records. Of these publications, 71 were articles in scientific journals. Ninety of the studies were observational and the remaining nine were experimental. We summarize characteristics of animal studies including study design, study population and outcomes of interest for future transmission modelling in the reservoir population. The majority of field studies reported measures of prevalence, while experimental studies provided estimates of transmission parameters that pertain to the natural course of disease.

title: Estimation of the reproductive number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond Princess cruise ship: A data-driven analysis
abstract: Up to February 16, 2020, 355 cases have been confirmed as having COVID-19 infection on the Diamond Princess cruise ship. It is of crucial importance to estimate the reproductive number (R0) of the novel virus in the early stage of outbreak and make a prediction of daily new cases on the ship.  We fitted the reported serial interval (mean and standard deviation) with a gamma distribution and applied “earlyR” package in R to estimate the R0 in the early stage of COVID-19 outbreak. We applied “projections” package in R to simulate the plausible cumulative epidemic trajectories and future daily incidence by fitting the data of existing daily incidence, a serial interval distribution, and the estimated R0 into a model based on the assumption that daily incidence obeys approximately Poisson distribution determined by daily infectiousness.  The Maximum-Likelihood (ML) value of R0 was 2.28 for COVID-19 outbreak at the early stage on the ship. The median with 95% confidence interval (CI) of R0 values was 2.28 (2.06–2.52) estimated by the bootstrap resampling method. The probable number of new cases for the next ten days would gradually increase, and the estimated cumulative cases would reach 1514 (1384–1656) at the tenth day in the future. However, if R0 value was reduced by 25% and 50%, the estimated total number of cumulative cases would be reduced to 1081 (981–1177) and 758 (697–817), respectively.  The median with 95% CI of R0 of COVID-19 was about 2.28 (2.06–2.52) during the early stage experienced on the Diamond Princess cruise ship. The future daily incidence and probable outbreak size is largely dependent on the change of R0. Unless strict infection management and control are taken, our findings indicate the potential of COVID-19 to cause greater outbreak on the ship.

title: "Off-label" use of hydroxychloroquine, azithromycin, lopinavir-ritonavir and chloroquine in COVID-19: A survey of cardiac adverse drug reactions by the French Network of Pharmacovigilance Centers
abstract: COVID-19 is an unprecedented challenge for physicians and scientists. Several publicized drugs are being used with not much evidence of their efficacy such as hydroxychloroquine, azithromycin or lopinavir-ritonavir. Yet, the cardiac safety of these drugs in COVID-19 deserves scrutiny as they are known to foster cardiac adverse ADRs, notably QTc interval prolongation on the electrocardiogram and its arrhythmogenic consequences.  Since March 27th, 2020, the French Pharmacovigilance Network directed all cardiac adverse drug reactions associated with "off-label" use of hydroxychloroquine, azithromycin and lopinavir-ritonavir in COVID-19 to the Nice Regional Center of Pharmacovigilance. Each Regional Center of Pharmacovigilance first assessed causality of drugs. We performed a specific analysis of these cardiac adverse drug reactions amidst an array of risk factors, reassessed the electrocardiograms and estimated their incidence in coronavirus disease 2019.  In one month, 120 reports of cardiac adverse drug reactions have been notified, 103 of which associated with hydroxychloroquine alone (86%), or associated with azithromycin (60%). Their estimated incidence is 0.77% to 1.54% of all patients, notwithstanding strong underreporting. Lopinavir-ritonavir came third with 17 reports (14%) and chloroquine fourth with 3 reports (2.5%). There were 8 sudden, unexplained or aborted deaths (7%), 8 ventricular arrhythmias (7%), 90 reports of prolonged QTc (75%) most of them "serious" (64%), 48 of which proved &#8805; 500ms, 20 reports of severe conduction disorders (17%) and 5 reports of other cardiac causes (4%). Six reports derived from automedication.  "Off-label" use of treatments in COVID-19 increases the risk of cardiac ADRs, some of them avoidable. Even if these drugs are perceived as familiar, they are used in patients with added risk factors caused by infection. Precautions should be taken to mitigate the risk, even if they will be proven efficacious.

title: An Evolving Approach to the Laboratory Assessment of COVID‐19
abstract: As the COVID‐19 outbreak has evolved in each country, the approach to the laboratory assessment of SARS‐CoV‐2 infection has had to evolve as well. This review addresses the evolving approach to the laboratory assessment of COVID‐19 and discusses how algorithms for testing have been driven, in part, by the demand for testing overwhelming the capacity to accomplish such testing. This review focused on testing in the United States as this testing is evolving whereas in China and other countries such as South Korea testing is widely available and includes both molecular testing for SARS‐CoV‐2 as well as serological testing using both ELISA methodology and lateral flow immunoassay methodology. Although commercial testing systems are becoming available, there will likely be insufficient numbers of such tests due to high demand. Serological testing will be the next testing issue as the COVID‐19 begins to subside. This will allow immunity testing as well as will allow the parameters of the COVID‐19 outbreak to be defined. This article is protected by copyright. All rights reserved.

title: Bounding the Predictive Values of COVID-19 Antibody Tests
abstract: COVID-19 antibody tests have imperfect accuracy. There has been lack of clarity on the meaning of reported rates of false positives and false negatives. For risk assessment and clinical decision making, the rates of interest are the positive and negative predictive values of a test. Positive predictive value (PPV) is the chance that a person who tests positive has been infected. Negative predictive value (NPV) is the chance that someone who tests negative has not been infected. The medical literature regularly reports different statistics, sensitivity and specificity. Sensitivity is the chance that an infected person receives a positive test result. Specificity is the chance that a non-infected person receives a negative result. Knowledge of sensitivity and specificity permits one to predict the test result given a person's true infection status. These predictions are not directly relevant to risk assessment or clinical decisions, where one knows a test result and wants to predict whether a person has been infected. Given estimates of sensitivity and specificity, PPV and NPV can be derived if one knows the prevalence of the disease, the rate of illness in the population. There is considerable uncertainty about the prevalence of COVID-19. This paper addresses the problem of inference on the PPV and NPV of COVID-19 antibody tests given estimates of sensitivity and specificity and credible bounds on prevalence. I explain the methodological problem, show how to estimate bounds on PPV and NPV, and apply the findings to some tests authorized by the FDA.

title: Genetic diversification of penaeid shrimp infectious myonecrosis virus between Indonesia and Brazil
abstract: Infectious myonecrosis virus (IMNV) is a pathogen of penaeid shrimp, most notably the whiteleg shrimp Litopenaeus vannamei. First discovered in L. vannamei from Brazilian aquaculture farms in 2003, IMNV was additionally confirmed in L. vannamei from Indonesian farms in 2006 and has since been found in numerous provinces there. Only two complete sequences of IMNV strains have been reported to date, one strain from the Brazilian state of Piauí collected in 2003 and another from the Indonesian province of East Java collected in 2006. In this study, we determined the complete sequences of two additional Indonesian strains, one from Lampung province collected in 2011 and another from East Java province collected in 2012. We also determined partial sequences for six other strains to enhance phylogenetic comparisons, which have heretofore been limited by the small number of reported sequences, including only one for an Indonesian strain. The new results demonstrate clear genetic diversification of IMNV between Indonesia and Brazil, as well as within Indonesia. Analyses of conserved sequence motifs suggest a revised RNA pseudoknot prediction for ribosomal frameshifting.

title: False positives in reverse transcription PCR testing for SARS-CoV-2
abstract: Large-scale testing for SARS-CoV-2 by RT-PCR is a key element of the response to COVID-19, but little attention has been paid to the potential frequency and impacts of false positives.  From a meta-analysis of external quality assessments of RT-PCR assays of RNA viruses, we derived a conservative estimate of the range of false positive rates that can reasonably be expected in SARS-CoV-2 testing, and analyzed the effect of such rates on analyses of regional test data and estimates of population prevalence and asymptomatic ratio.  Review of external quality assessments revealed false positive rates of 0-16.7%, with an interquartile range of 0.8-4.0%. Such rates would have large impacts on test data when prevalence is low. Inclusion of such rates significantly alters four published analyses of population prevalence and asymptomatic ratio.  The high false discovery rate that results, when prevalence is low, from false positive rates typical of RT-PCR assays of RNA viruses raises questions about the usefulness of mass testing; and indicates that across a broad range of likely prevalences, positive test results are more likely to be wrong than are negative results, contrary to public health advice about SARS-CoV-2 testing. There are myriad clinical and case management implications. Failure to appreciate the potential frequency of false positives and the consequent unreliability of positive test results across a range of scenarios could unnecessarily remove critical workers from service, expose uninfected individuals to greater risk of infection, delay or impede appropriate medical treatment, lead to inappropriate treatment, degrade patient care, waste personal protective equipment, waste human resources in unnecessary contact tracing, hinder the development of clinical improvements, and weaken clinical trials. Measures to raise awareness of false positives, reduce their frequency, and mitigate their effects should be considered.

title: Anesthesiologists’ and Intensive Care Providers’ Exposure to Coronavirus Disease 2019 Infection in a New York City Academic Center: A Prospective Cohort Study Assessing Symptoms and Coronavirus Disease 2019 Antibody Testing
abstract: Protecting first-line health care providers against work-related Coronavirus Disease 2019 (COVID-19) infection at the onset of the pandemic has been a crucial challenge in the United States. Anesthesiologists in particular are considered at risk, since aerosol-generating procedures, such as intubation and extubation, have been shown to significantly increase the odds for respiratory infections during severe acute respiratory syndrome (SARS) outbreaks. This study assessed the incidence of COVID-19–like symptoms and thepresence of COVID-19 antibodies after work-related COVID-19 exposures, among physicians working in a large academic hospital in New York City (NYC).  An e-mail survey was addressed to anesthesiologists and affiliated intensive care providers at Columbia University Irving Medical Center on April 15, 2020. The survey assessed 4 domains: (1) demographics and medical history, (2) community exposure to COVID-19 (eg, use of NYC subway), (3) work-related exposure to COVID-19, and (4) development of COVID-19–like symptoms after work exposure. The first 100 survey responders were invited to undergo a blood test to assess antibody status (presence of immunoglobulin M [IgM]/immunoglobulin G [IgG] specific to COVID-19). Work-related exposure was defined as any episode where the provider was not wearing adequate personal protective equipment (airborne or droplet/contact protection depending on the exposure type). Based on the clinical scenario, work exposure was categorized as highrisk (eg, exposure during intubation) or lowrisk (eg, exposure during doffing).  Two hundred and five health care providers were contacted and 105 completed the survey (51%); 91 completed the serological test. Sixty-one of the respondents (58%) reported at least 1 work-related exposure and 54% of the exposures were highrisk. Among respondents reporting a work-related exposure, 16 (26.2%) reported postexposure COVID-19–like symptoms. The most frequent symptoms were myalgia (9 cases), diarrhea (8 cases), fever (7 cases), and sore throat (7 cases). COVID-19 antibodies were detected in 11 of the 91 tested respondents (12.1%), with no difference between respondents with (11.8%) or without (12.5%) a work-related exposure, including high-risk exposure. Compared with antibody-negative respondents, antibody-positive respondents were more likely to use NYC subway to commute to work and report COVID-19–like symptoms in the past90 days.  In the epicenter of the United States’ pandemic and within 6–8 weeks of the COVID-19 outbreak, a small proportion of anesthesiologists and affiliated intensive care providers reported COVID-19–like symptoms after a work-related exposure and even fewer had detectable COVID-19 antibodies. Thepresenceof COVID-19 antibodies appeared to be associated with community/environmental transmission rather than secondary to work-related exposures involving high-risk procedures.

title: Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis
abstract: Recently, Coronavirus Disease 2019 (COVID-19) outbreak started in Wuhan, China. Although the clinical features of COVID-19 have been reported previously, data regarding the risk factors associated with the clinical outcomes are lacking.  To summary and analyze the clinical characteristics and identify the predictors of disease severity and mortality.  The PubMed, Web of Science Core Collection, Embase, Cochrane and MedRxiv databases were searched through February 25, 2020. Meta-analysis of Observational Studies in Epidemiology (MOOSE) recommendations were followed. We extracted and pooled data using random-effects meta-analysis to summary the clinical feature of the confirmed COVID-19 patients, and further identify risk factors for disease severity and death. Heterogeneity was evaluated using the I2 method and explained with subgroup analysis and meta-regression.  A total of 30 studies including 53000 patients with COVID-19 were included in this study, the mean age was 49.8 years (95% CI, 47.5-52.2 yrs) and 55.5% were male. The pooled incidence of severity and mortality were 20.2% (95% CI, 15.1-25.2%) and 3.1% (95% CI, 1.9-4.2%), respectively. The predictor for disease severity included old age (≥ 50 yrs, odds ratio [OR] = 2.61; 95% CI, 2.29-2.98), male (OR =1.348, 95% CI, 1.195-1.521), smoking (OR =1.734, 95% CI, 1.146-2.626) and any comorbidity (OR = 2.635, 95% CI, 2.098-3.309), especially chronic kidney disease (CKD, OR = 6.017; 95% CI, 2.192-16.514), chronic obstructive pulmonary disease (COPD, OR = 5.323; 95% CI, 2.613-10.847) and cerebrovascular disease (OR = 3.219; 95% CI, 1.486-6.972). In terms of laboratory results, increased lactate dehydrogenase (LDH), C-reactive protein (CRP) and D-dimer and decreased blood platelet and lymphocytes count were highly associated with severe COVID-19 (all for P < 0.001). Meanwhile, old age (≥ 60 yrs, RR = 9.45; 95% CI, 8.09-11.04), followed by cardiovascular disease (RR = 6.75; 95% CI, 5.40-8.43) hypertension (RR = 4.48; 95% CI, 3.69-5.45) and diabetes (RR = 4.43; 95% CI, 3.49-5.61) were found to be independent prognostic factors for the COVID-19 related death.  To our knowledge, this is the first evidence-based medicine research to explore the risk factors of prognosis in patients with COVID-19, which is helpful to identify early-stage patients with poor prognosis and adapt effective treatment.

title: Lack of dyspnea in patients with Covid‐19: another neurological conundrum?
abstract: One relevant feature of the Covid-19 disease is the absence of dyspnea, described as 'shortness of breath' or 'an unpleasant urge to breathe'. The lack of dyspnea is observed even in the most severe cases, in which subjects present tachypnea and tachycardia. In the Wuhan cohort, 62.4% of severe cases and 46.3% of those who ended up intubated, ventilated or dead did not present dyspnea[1,2].

title: Emerging Influenza and Psychosis: An Important Story in Psychological Medicine

title: Building an International Consortium for Tracking Coronavirus Health Status
abstract: Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease. In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.

title: Early and massive testing saves lives: COVID-19 related infections and deaths in the United States during March of 2020
abstract: To optimize epidemiologic interventions, predictors of mortality should be identified. The US COVID-19 epidemic data, reported up to 31 March 2020, were analyzed using kernel regularized least squares regression. Six potential predictors of mortality were investigated: (i) the number of diagnostic tests performed in testing week I; (ii) the proportion of all tests conducted during week I of testing; (iii) the cumulative number of (test-positive) cases through 3-31-2020, (iv) the number of tests performed/million citizens; (v) the cumulative number of citizens tested; and (vi) the apparent prevalence rate, defined as the number of cases/million citizens. Two metrics estimated mortality: the number of deaths and the number of deaths/million citizens. While both expressions of mortality were predicted by the case count and the apparent prevalence rate, the number of deaths/million citizens was {approx}3.5 times better predicted by the apparent prevalence rate than the number of cases. In eighteen states, early testing/million citizens/population density was inversely associated with the cumulative mortality reported by 31 March, 2020. Findings support the hypothesis that early and massive testing saves lives. Other factors --e.g., population density-- may also influence outcomes. To optimize national and local policies, the creation and dissemination of high resolution geo-referenced, epidemic data is recommended.

title: Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020
abstract: There’s an outbreak of a novel coronavirus (SARS-CoV-2) infection since December 2019, first in China, and currently with more than 80 thousand confirmed infection globally in 29 countries till March 2, 2020. Identification, isolation and caring for patients early are essential to limit human-to-human transmission including reducing secondary infections among close contacts and health care workers, preventing transmission amplification events. The RT-PCR detection of viral nucleic acid test (NAT) was one of the most quickly established laboratory diagnosis method in a novel viral pandemic, just as in this COVID-19 outbreak.  4880 cases that had respiratory infection symptoms or close contact with COVID-19 patients in hospital in Wuhan, China, were tested for SARS-CoV-2 infection by use of quantitative RT-PCR (qRT-PCR) on samples from the respiratory tract. Positive rates were calculated in groups divided by genders or ages.  The positive rate was about 38% for the total 4880 specimens. Male and older population had a significant higher positive rates. However, 57% was positive among the specimens from the Fever Clinics. Binary logistic regression analysis showed that age, not gender, was the risk factor for SARS-CoV-2 infection in fever clinics.  Therefore, we concluded that viral NAT played an important role in identifying SARS-CoV-2 infection.

title: Interim Analysis of Pandemic Coronavirus Disease 2019 (COVID-19) and the SARS-CoV-2 virus in Latin America and the Caribbean: Morbidity, Mortality and Molecular Testing Trends in the Region
abstract: The relentless advance of the SARS-CoV-2 virus pandemic has resulted in a significant burden on countries, regardless of their socio-economic conditions. The virus has infected more than 2.5 million people worldwide, causing to date more than 150,000 deaths in over 210 countries.  The aim of this study was to describe the trends in cases, tests and deaths related to novel coronavirus disease (COVID-19) in Latin American and Caribbean (LAC) countries.  Data were retrieved from the WHO-Coronavirus Disease (COVID-2019) situation reports and the Center for Systems Science and Engineering (CSSE) databases from Johns Hopkins University. Descriptive statistics including death rates, cumulative mortality and incidence rates, as well as testing rates per population at risk were performed. A comparison analysis among countries with [≥]50 confirmed cases was performed from February 26th, 2020 to April 8th, 2020.  Brazil had the greatest number of cases and deaths in the region. Panama experienced a rapid increase in the number of confirmed cases with Trinidad and Tobago, Bolivia and Honduras having the highest case fatality rates. Panama and Chile conducted more tests per million inhabitants and more tests per day per million inhabitants, followed by Uruguay and El Salvador. Dominican Republic, Bolivia, Ecuador and Brazil had the highest positive test rates.  The COVID-19 disease pandemic caused by the SARS-CoV-2 virus has progressed rapidly in LAC countries. Some countries have been affected more severely than others, with some adopting similar disease control methods to help slow down the spread of the virus. With limited testing and other resources, social distancing is needed to help alleviate the strain on already stretched health systems.

title: Targeted Proteomics for the Detection of SARS-CoV-2 Proteins
abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). The rapid, sensitive and specific diagnosis of SARS-CoV-2 by fast and unambiguous testing is widely recognized to be critical in responding the current outbreak. Since the current testing capacity by conventional PCR based methods is insufficient because of shortages of supplies such as RNA extraction kits and PCR reagents, alternative and/or complementary testing assays should be developed. Here, we exploit the potential of targeted mass spectrometry based proteomic technologies to solve the current issue of insufficient SARS-CoV-2 diagnostic testing capacity. We have assessed the limit of detection by parallel reaction monitoring (PRM) on an Orbitrap Eclipse mass spectrometer for target tryptic peptides of several SARS-CoV-2 proteins from a sample of virus infected Vero cells. For Nucleocapsid protein the limit of detection was found to be in the mid-attomole range (0.9 × 10−12 g), which would theoretically correspond to approximately 10,000 SARS-CoV-2 particles, under the assumption that all viral proteins are assembled in macromolecular virus particles. Whether or not this sensitivity is sufficient to play a role in SARS-CoV-2 detection in patient material such as swabs or body fluids largely depends on the amount of viral proteins present in such samples and is subject of further research. If yes, mass spectrometry based methods could serve as a complementary protein based diagnostic tool and further steps should be focused on sample preparation protocols and on improvements in sample throughput.

title: Estimating the last day for COVID-19 outbreak in mainland China
abstract: Our main aim is to estimate the last day for COVID-19 outbreak in mainland China. We developed mathematical models to predict reasonable bounds on the date of end of the COVID-19 epidemics in mainland China with strong quarantine and testing measures for a sufficiently long time. We used reported data in China from January 20, 2020 to April 9, 2020. We firstly used a deterministic approach to obtain a formula to compute the probability distribution of the extinction date by combining the models and continuous-time Markov processes. Then we present the individual based model (IMB) simulations to compare the result by deterministic approach and show the absolute difference between the estimated cumulative probability distribution computed by simulations and formula. We provide the predictions of the last day of epidemic for different fractions f of asymptomatic infectious that become reported symptomatic infectious.

title: Are we equal in adversity? Does Covid-19 affect women and men differently?
abstract: This article examines whether women are less prone than men to Covid-19 infections and their complications.  We reviewed available databases and searched systematically for publications. To be taken into account, data had to be broken down by gender. There was no study evaluation nor quantification synthesis, due to the large heterogeneity of the studies. Nineteen databases were selected. 73 publications were considered and 33 were selected, to which 12 more were added.  Globally, the proportion of men and women who tested positive is comparable. However, men are about 60% more likely to be severely ill or to die from the complications of Covid-19 than are women.  The study was hampered by a large heterogeneity in testing and reporting of the data.  Although in the pandemic men die more frequently than women from Covid-19, it is not clear whether this is due to biological differences between men and women, differences in behavioral habits, or differences in the rates of co-morbidities.  Countries and studies should report their data by age, gender and co-morbidities. This may have implications in terms of vaccination strategies, the choice of treatments and future consequences for long-term health issues concerning gender equality.

title: Quantitative assessment of the role of undocumented infection in the 2019 novel coronavirus (COVID-19) pandemic
abstract: An urgent problem in controlling COVID-19 spreading is to understand the role of undocumented infection. We develop a five-state model for COVID-19, taking into account the unique features of the novel coronavirus, with key parameters determined by the government reports and mathematical optimization. Tests using data from China, South Korea, Italy, and Iran indicate that the model is capable of generating accurate prediction of the daily accumulated number of confirmed cases and is entirely suitable for real-time prediction. The drastically disparate testing and diagnostic standards/policies among different countries lead to large variations in the estimated parameter values such as the duration of the outbreak, but such uncertainties have little effect on the occurrence time of the inflection point as predicted by the model, indicating its reliability and robustness. Model prediction for Italy suggests that insufficient government action leading to a large fraction of undocumented infection plays an important role in the abnormally high mortality in that country. With the data currently available from United Kingdom, our model predicts catastrophic epidemic scenarios in the country if the government did not impose strict travel and social distancing restrictions. A key finding is that, if the percentage of undocumented infection exceeds a threshold, a non-negligible hidden population can exist even after the the epidemic has been deemed over, implying the likelihood of future outbreaks should the currently imposed strict government actions be relaxed. This could make COVID-19 evolving into a long-term epidemic or a community disease a real possibility, suggesting the necessity to conduct universal testing and monitoring to identify the hidden individuals.

title: Spatial variability in the risk of death from COVID-19 in Italy, 2020
abstract: Italy is bearing the brunt of the COVID-19 pandemic, as the death toll there has already surpassed that in Wuhan, the city in China where the coronavirus emerged in December 2019. Here we employ statistical methods to assess the severity of COVID-19 pandemic across different regions of Italy.  We manually retrieved the daily cumulative numbers of laboratory-confirmed cases and deaths attributed to COVID-19 stratified by region in Italy. We estimated both the crude and time-delay adjusted case fatality ratio across five geographic regions of Italy.  The Northwest that includes Lombardy exhibited the highest time-delay-adjusted CFR at 23.0% followed by the Northeast (14.2%), the Center region (11.6%) and the South region (12.1%). The Island region has exhibited the lowest CFR (9.6%).  Our estimates in the Northwest and the Northeast are higher than those reported from most affected areas in China. The CFR in Northwest Italy is 1.9-fold higher than that in Wuhan. Our finding reflects the need of urgent medical support in the Northwest region and the appropriate planning and supplies procurement in other regions of Italy focusing on medical care delivery to those who are at the highest risk of poorer outcomes due to COVID-19.

title: Spatial transmission of COVID-19 via public and private transportation in China

title: Transmission potential of COVID-19 in South Korea
abstract: Since the first identified individual of 2019 novel coronavirus (COVID-19) infection on Jan 20, 2020 in South Korea, the number of confirmed cases rapidly increased. As of Feb 26, 2020, 1,261 cases of COVID-19 including 12 deaths were confirmed in South Korea. Using the incidence data of COVID-19, we estimate the reproduction number at 1.5 (95% CI: 1.4-1.6), which indicates sustained transmission and support the implementation of social distancing measures to rapidly control the outbreak.

title: Excess mortality during COVID-19 in five European countries and a critique of mortality analysis data
abstract: The COVID-19 pandemic is an ongoing event disrupting lives, health systems, and economies worldwide. Clear data about the pandemic's impact is lacking, namely regarding mortality. This work aims to study the impact of COVID-19 through the analysis of all-cause mortality data made available by different European countries, and to critique their mortality surveillance data.  European countries that had publicly available data about the number of deaths per day/week were selected (England and Wales, France, Italy, Netherlands and Portugal). Two different methods were selected to estimate the excess mortality due to COVID19: (DEV) deviation from the expected value from homologue periods, and (RSTS) remainder after seasonal time series decomposition. We estimate total, age- and gender-specific excess mortality. Furthermore, we compare different policy responses to COVID-19.  Excess mortality was found in all 5 countries, ranging from 10.6% in Portugal (DEV) to 98.5% in Italy (DEV). Furthermore, excess mortality is higher than COVID-attributed deaths in all 5 countries.  The impact of COVID-19 on mortality appears to be larger than officially attributed deaths, in varying degrees in different countries. Comparisons between countries would be useful, but large disparities in mortality surveillance data could not be overcome. Unreliable data, and even a lack of cause-specific mortality data undermine the understanding of the impact of policy choices on both direct and indirect deaths during COVID-19. European countries should invest more on mortality surveillance systems to improve the publicly available data.

title: COVID-19 pandemic, healthcare providers’ contamination and death: an international view

title: Effect of social distancing on COVID-19 incidence and mortality in the US
abstract: Social distancing policies were implemented in most US states as a containment strategy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The effectiveness of these policy interventions on morbidity and mortality remains unknown. Our analysis examined the associations between statewide policies and objective measures of social distancing, and objective social distancing and COVID-19 incidence and mortality. We used nationwide, de-identified smartphone GPS data to estimate county-level social distancing. COVID-19 incidence and mortality data were from the Johns Hopkins Coronavirus Resource Center. Generalized linear mixed models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between objective social distancing and COVID-19 incidence and mortality. Stay-at-home orders were associated with a 35% increase in social distancing. Higher social distancing was associated with a 29% reduction in COVID-19 incidence (adjusted IRR 0.71; 95% CI 0.57–0.87) and a 35% reduction in COVID-19 mortality (adjusted IRR 0.65; 95% CI 0.55–0.76). These findings provide evidence to inform ongoing national discussions on the effectiveness of these public health measures and the potential implications of returning to normal social activity.

title: Comparing the impact of various interventions to control the spread of COVID-19 in 12 countries

title: Unmasking the Actual COVID-19 Case Count
abstract: This report presents a novel approach to estimate the number of COVID-19 cases, including undocumented infections, in the US, by combining CDC’s influenza-like illness surveillance data with aggregated prescription data. We estimated that the cumulative number of COVID-19 cases in the US by April 4 was above 2.5 million.

title: Evolutionary Medicine IV. Evolution and Emergence of Novel Pathogens
abstract: This article discusses how evolutionary and ecological factors interact to affect the epidemiology of emerging infectious diseases. It further explains how the nascent field of phylodynamics constructs mathematical models, which link evolution and epidemiology, to study pathogen transmission. To illustrate the importance of considering both evolution and ecology – along with the utility of the phylodynamic approach – when studying novel pathogens, the author considers examples from HIV, influenza, and Ebola.

title: A pandemic at the Tunisian scale. Mathematical modelling of reported and unreported COVID-19 infected cases
abstract: Starting from the city of Wuhan in China in late December 2019, the pandemic quickly spread to the rest of the world along the main intercontinental air routes. At the time of writing this article, there are officially about five million infections and more than 300 000 deaths. Statistics vary widely from country to country, revealing significant differences in anticipation and management of the crisis. We propose to examine the COVID-19 epidemic in Tunisia through mathematical models, which aim to determine the actual number of infected cases and to predict the course of the epidemic. As of May 11, 2020, there are officially 1032 COVID-19 infected cases in Tunisia. 45 people have died. Using a mathematical model based on the number of reported infected cases, the number of deaths, and the effect of the 18-day delay between infection and death, this study estimates the actual number of COVID-19 cases in Tunisia as 2555 cases. This paper analyses the evolution of the epidemic in Tunisia using population dynamics with an SEIR model combining susceptible cases S(t), asymptomatic infected cases A(t), reported infected cases V (t), and unreported infected cases U(t). This work measures the basic reproduction number R0, which is the average number of people infected by a COVID-19 infected person. The model predicts an R0 = 2.73. Strict containment measures have led to a significant reduction in the reproduction rate. Contact tracing and respect for isolation have an impact: at the current time, we compute that Tunisia has an Rt = 0.42 (95% CI 0.14-0.70). These values depend on physical separation and can vary over time depending on the management of suspicious cases. Their objective estimation and the study of their evolution are however necessary to understand the pandemic and to reduce their unintended damage (due to an absence of symptoms, or the confusion of certain symptoms with less contagious diseases, or unavailable or unreliable tests).

title: Associations between immune-suppressive and stimulating drugs and novel COVID-19—a systematic review of current evidence
abstract: Cancer and transplant patients with COVID-19 have a higher risk of developing severe and even fatal respiratory diseases, especially as they may be treated with immune-suppressive or immune-stimulating drugs. This review focuses on the effects of these drugs on host immunity against COVID-19.  Using Ovid MEDLINE, we reviewed current evidence for immune-suppressing or -stimulating drugs: cytotoxic chemotherapy, low-dose steroids, tumour necrosis factorα (TNFα) blockers, interlukin-6 (IL-6) blockade, Janus kinase (JAK) inhibitors, IL-1 blockade, mycophenolate, tacrolimus, anti-CD20 and CTLA4-Ig.  89 studies were included. Cytotoxic chemotherapy has been shown to be a specific inhibitor for severe acute respiratory syndrome coronavirus in in vitro studies, but no specific studies exist as of yet for COVID-19. No conclusive evidence for or against the use of non-steroidal anti-inflammatory drugs (NSAIDs) in the treatment of COVID-19 patients is available, nor is there evidence indicating that TNFα blockade is harmful to patients in the context of COVID-19. COVID-19 has been observed to induce a pro-inflammatory cytokine generation and secretion of cytokines, such as IL-6, but there is no evidence of the beneficial impact of IL-6 inhibitors on the modulation of COVID-19. Although there are potential targets in the JAK-STAT pathway that can be manipulated in treatment for coronaviruses and it is evident that IL-1 is elevated in patients with a coronavirus, there is currently no evidence for a role of these drugs in treatment of COVID-19.  The COVID-19 pandemic has led to challenging decision-making about treatment of critically unwell patients. Low-dose prednisolone and tacrolimus may have beneficial impacts on COVID-19. The mycophenolate mofetil picture is less clear, with conflicting data from pre-clinical studies. There is no definitive evidence that specific cytotoxic drugs, low-dose methotrexate for auto-immune disease, NSAIDs, JAK kinase inhibitors or anti-TNFα agents are contraindicated. There is clear evidence that IL-6 peak levels are associated with severity of pulmonary complications.

title: Impact of COVID-19 infection on maternal and neonatal outcomes: a review of 287 pregnancies
abstract: Pregnant women are vulnerable group in viral outbreaks especially in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The aim of this review was to identify maternal and neonatal outcomes in available articles on pregnancies affected by COVID-19. The articles that had assessed outcomes of pregnancy and perinatal of women with COVID-19 between Oct 2019 and Apr 30, 2020 without language limitation were considered. All kinds of studies such as case report, case series, retrospective cohort, case control were included. We searched databases, selected relevant studies and extracted data regarding maternal and neonatal outcomes from each article. Data of 287 pregnant women with COVID-19 of 6 countries were assessed from 28 articles between December 8, 2019 and April 6, 2020. Most pregnant women reported in their third trimester, 102 (35.5%) cases were symptomatic at the time of admission. Common onset symptoms, abnormal laboratory findings, and chest computed tomography pattern were fever (51.5%), lymphocytopenia (67.9%), and multiple ground-glass opacities (78.5%) respectively. 93% of all deliveries were done through cesarean section. No maternal mortality and 3 % ICU admission were reported. Vertical transmission was not reported but its possibility was suggested in three neonates. One neonatal death, one stillbirth, and one abortion were reported. All newborns were not breastfed. This review showed fewer adverse maternal and neonatal outcomes in pregnant women with COVID-19 in comparison with previous coronavirus outbreak infection in pregnancy. Limited data are available regarding possibility of virus transmission in utero, during vaginal childbirth and breastfeeding. Effect of COVID-19 on first and second trimester and ongoing pregnancy outcomes in infected mothers is still questionable.

title: Interferon-β 1a and SARS Coronavirus Replication
abstract: A global outbreak of severe acute respiratory syndrome (SARS) caused by a novel coronavirus began in March 2003. The rapid emergence of SARS and the substantial illness and death it caused have made it a critical public health issue. Because no effective treatments are available, an intensive effort is under way to identify and test promising antiviral drugs. Here, we report that recombinant human interferon (IFN)-β 1a potently inhibits SARS coronavirus replication in vitro.

title: The timing of one-shot interventions for epidemic control
abstract: The apparent early success in China's large-scale intervention to control the COVID-19 epidemic has led to interest in whether other countries can replicate it as well as concerns about a resurgence of the epidemic if or when China relaxes the interventions. In this paper we look at the impact of a single short-term intervention on an epidemic. We see that if an intervention cannot be sustained long-term, it has the greatest impact if it is imposed once infection levels have become large enough that there is an appreciable number of infections present. For minimising the total number infected it should start close to the peak so that there is no rebound once the intervention is stopped, while to minimise the peak prevalence, it should start earlier, allowing two peaks of comparable size rather than one very large peak. In populations with distinct subgroups, synchronized interventions are less effective than targeting the interventions in each sub-population separately. We do not attempt to clearly determine what makes an intervention sustainable or not. We believe that is a policy question. If an intervention is sustainable, it should be kept in place. Our intent is to offer insight into how best to time an intervention whose impact on society is too great to maintain.

title: Comparative tropism, replication kinetics, and cell damage profiling of SARS-CoV-2 and SARS-CoV with implications for clinical manifestations, transmissibility, and laboratory studies of COVID-19: an observational study
abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was reported from China in January, 2020. SARS-CoV-2 is efficiently transmitted from person to person and, in 2 months, has caused more than 82 000 laboratory-confirmed cases of coronavirus disease 2019 (COVID-19) and 2800 deaths in 46 countries. The total number of cases and deaths has surpassed that of the 2003 severe acute respiratory syndrome coronavirus (SARS-CoV). Although both COVID-19 and severe acute respiratory syndrome (SARS) manifest as pneumonia, COVID-19 is associated with apparently more efficient transmission, fewer cases of diarrhoea, increased mental confusion, and a lower crude fatality rate. However, the underlying virus–host interactive characteristics conferring these observations on transmissibility and clinical manifestations of COVID-19 remain unknown.  We systematically investigated the cellular susceptibility, species tropism, replication kinetics, and cell damage of SARS-CoV-2 and compared findings with those for SARS-CoV. We compared SARS-CoV-2 and SARS-CoV replication in different cell lines with one-way ANOVA. For the area under the curve comparison between SARS-CoV-2 and SARS-CoV replication in Calu3 (pulmonary) and Caco2 (intestinal) cells, we used Student's t test. We analysed cell damage induced by SARS-CoV-2 and SARS-CoV with one-way ANOVA.  SARS-CoV-2 infected and replicated to comparable levels in human Caco2 cells and Calu3 cells over a period of 120 h (p=0·52). By contrast, SARS-CoV infected and replicated more efficiently in Caco2 cells than in Calu3 cells under the same multiplicity of infection (p=0·0098). SARS-CoV-2, but not SARS-CoV, replicated modestly in U251 (neuronal) cells (p=0·036). For animal species cell tropism, both SARS-CoV and SARS-CoV-2 replicated in non-human primate, cat, rabbit, and pig cells. SARS-CoV, but not SARS-CoV-2, infected and replicated in Rhinolophus sinicus bat kidney cells. SARS-CoV-2 consistently induced significantly delayed and milder levels of cell damage than did SARS-CoV in non-human primate cells (VeroE6, p=0·016; FRhK4, p=0·0004).  As far as we know, our study presents the first quantitative data for tropism, replication kinetics, and cell damage of SARS-CoV-2. These data provide novel insights into the lower incidence of diarrhoea, decreased disease severity, and reduced mortality in patients with COVID-19, with respect to the pathogenesis and high transmissibility of SARS-CoV-2 compared with SARS-CoV. Funding May Tam Mak Mei Yin, The Shaw Foundation Hong Kong, Richard Yu and Carol Yu, Michael Seak-Kan Tong, Respiratory Viral Research Foundation, Hui Ming, Hui Hoy and Chow Sin Lan Charity Fund, Chan Yin Chuen Memorial Charitable Foundation, Marina Man-Wai Lee, The Hong Kong Hainan Commercial Association South China Microbiology Research Fund, The Jessie & George Ho Charitable Foundation, Perfect Shape Medical, The Consultancy Service for Enhancing Laboratory Surveillance of Emerging Infectious Diseases and Research Capability on Antimicrobial Resistance for the Department of Health of the Hong Kong Special Administrative Region Government, The Theme-Based Research Scheme of the Research Grants Council, Sanming Project of Medicine in Shenzhen, and The High Level-Hospital Program, Health Commission of Guangdong Province, China.

title: Covid-19 prevalence estimation by random sampling in the wider population - Optimal sample pooling under varying assumptions about true prevalence
abstract: The number of confirmed Covid-19 cases in a population is used as a coarse measurement for the burden of disease. However, this number depends heavily on the sampling intensity and the various test criteria used in different jurisdictions. A wide range of sources indicate that a large fraction of cases go undetected. Estimates of the true prevalence of Covid-19 can be made by random sampling in the wider population. Here we use simulations to explore confidence intervals of prevalence estimates under different sampling intensities and degrees of sample pooling.

title: Common Pitfalls in the Interpretation of COVID-19 Data and Statistics
abstract: Policymakers, experts and the general public heavily rely on the data that are being reported in the context of the coronavirus pandemic. Daily data releases on confirmed COVID-19 cases and deaths provide information on the course of the pandemic.

title: CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China
abstract: Aimed to characterize the CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia.  Asymptomatic cases with COVID-19 pneumonia confirmed by SARS-COV-2 nucleic acid testing in Renmin Hospital of Wuhan University were retrospectively enrolled. The characteristics of CT imaging and clinical feature were collected and analyzed.  58 asymptomatic cases with COVID-19 pneumonia admitted to our hospital between Jan 1, 2020 and Feb 23, 2020 were enrolled. All patients had history of exposure to SARS-CoV-2. On admission, patients had no symptoms and laboratory findings were normal. The predominant feature of CT findings in this cohort was ground glass opacity (GGO) (55, 94.8%) with peripheral (44, 75.9%) distribution, unilateral location (34, 58.6%) and mostly involving one or two lobes (38, 65.5%), often accompanied by characteristic signs. After short-term follow-up, 16 patients (27.6%) presented symptoms with lower lymphocyte count and higher CRP, mainly including fever, cough and fatigue. The evolution of lesions on CT imaging were observed in 10 patients (17.2%). The average days of hospitalization was19.80±10.82 days, and was significantly longer in progression patients (28.60±7.55 day).  CT imaging of asymptomatic cases with COVID-19 pneumonia has definite characteristics. Since asymptomatic infections as “covert transmitter”, and some patients can progress rapidly in the short term. It is essential to pay attention to the surveillance of asymptomatic patients with COVID-19. CT scan has great value in screening and detecting patients with COVID-19 pneumonia, especially in the highly suspicious, asymptomatic cases with negative nucleic acid testing.

title: Breaking the back of COVID-19: Is Bangladesh doing enough testing?
abstract: Following detection of the first 100 confirmed cases of COVID-19 in early April, Bangladesh stepped up its efforts to strengthen testing capacity in order to curb the spread of the disease across the country. This paper sheds light on the position of Bangladesh in relation to its South Asian neighbors India and Pakistan with respect to testing capacity and ability to detect cases with increased testing. It also analyzes recent data on case counts and testing numbers in Bangladesh, to provide an idea regarding the number of extra tests needed to detect a substantial number of cases within a short period of time. Findings indicate that compared to India and Pakistan, Bangladesh was able to detect more cases by increasing testing levels and expand its testing capacity by performing more per capita tests. In spite of these achievements, the rate of reported cases per 100 tests was consistently higher for Bangladesh compared to India, which suggests that in addition to increased testing, other factors, such as, effective enforcement of social distancing and efficient contact tracing are just as important in curbing the spread of the disease. The analysis reveals that current testing levels in Bangladesh are not adequate. Based on the findings, we recommend a 30-50% growth of the current test rate in the next few days so that by detecting and isolating more cases, Bangladesh could, in effect, contain the spread of new infections. The challenge, however, is to mobilize resources necessary to expand geographical coverage and improve testing quality while enforcing social distancing and performing efficient contact tracing.

title: Methods to infer transmission risk factors in complex outbreak data
abstract: Data collected during outbreaks are essential to better understand infectious disease transmission and design effective control strategies. But analysis of such data is challenging owing to the dependency between observations that is typically observed in an outbreak and to missing data. In this paper, we discuss strategies to tackle some of the ongoing challenges in the analysis of outbreak data. We present a relatively generic statistical model for the estimation of transmission risk factors, and discuss algorithms to estimate its parameters for different levels of missing data. We look at the problem of computational times for relatively large datasets and show how they can be reduced by appropriate use of discretization, sufficient statistics and some simple assumptions on the natural history of the disease. We also discuss approaches to integrate parametric model fitting and tree reconstruction methods in coherent statistical analyses. The methods are tested on both real and simulated datasets of large outbreaks in structured populations.

title: COVID-19: An Update on the Epidemiological, Genomic Origin, Phylogenetic study, India centric to Worldwide current status
abstract: The pandemic spread of novel coronavirus, (SARS-CoV-2) causing CoronaVirus Infectious Diseases (COVID-19) emerged into a global threat for human life causing serious death rates and economic crunch all over the globe. As on April 17, 2020 at 2:00am CEST, there include a total of 2,034,802 confirmed cases for Corona and 1,35,163 deaths worldwide have been reported which includes 212 countries, areas or territories reported by World Health Organization (WHO), in which USA tops 6,32,781 confirmed cases (28,221 deaths) followed by Italy 1,65,155 (21,647 deaths), Spain 1,77,633 (18,579 deaths) and China 84,149 (4,642 deaths). This study aims to compare the genomic nature of SARS-CoV-2 genome reported from Wuhan, China with two Indian isolate genome reported by ICMR-NIV, India. Further Phylogenetic studies performed with coronavirus infecting non-human species like Bats, Duck, and sparrow were compared with Indian and other country whole genome sequences of SARS-CoV2 using MegaX and traced out the association between the human coronavirus with the other species viral genome. In addition, epidemiological reports on COVID-19 among Worldwide and India centric data were compared between April 7, 2020 to April 17, 2020 global data and the number of active cases were increased dramatically in this 10 days period studied, highlighted in the current study.

title: COVID-19 outbreak in Greece has passed its rising inflection point and stepping into its peak
abstract: Since the beginning of 2020, COVID-19 is the most urgent and challenging task for the international scientific community, in order to identify its behaviour, track its progress and plan effective mitigation policies. In this study, Greece is the main focus for assessing the national outbreak and estimating the general trends and outlook of it. Multiple data analytics procedures, spectral decomposition and curve-fitting formulations are developed based on the data available at hand. Standard SIEQRDP epidemic modelling is applied for Greece and for the general region around it, providing hints for the outbreak progression in the mid- and long-term, for various infections under-reporting rates. The overall short-term outlook for Greece seems to be towards positive, with a downward trend in infections rate daily increase (i.e., now beyond the exponential growth rate), a possible peak within a few days beyond April 14th, as well as the high availability level of ICU w.r.t. expected demand at peak. On the negative side, the fade-out period seems to be in the order of several months, with high probability of recurrent surges of the outbreak. The mitigation policies for the `next day' should be focused on close tracking of the epidemic via large-scale tests, strict border checking in international travelling and an adaptive plan for selective activation of mitigation measures when deemed necessary.

title: Thrombosis risk associated with COVID-19 infection. A scoping review
abstract: Infection by the 2019 novel coronavirus (COVID-19) has been reportedly associated with a high risk of thrombotic complications. So far information is scarce and rapidly emerging.  We conducted a scoping review using a single engine search for studies assessing thrombosis and coagulopathy in COVID-19 patients. Additional studies were identified by secondary review and alert services.  Studies reported the occurrence of venous thromboembolism and stroke in approximately 20% and 3% of patients, respectively. A higher frequency seems to be present in severely ill patients, in particular those admitted to intensive care units. The thrombotic risk is elevated despite the use of anticoagulant prophylaxis but optimal doses of anticoagulation are not yet defined. Although and increase of biomarkers such as D-dimer has been consistently reported in severely ill COVID-19, the optimal cut-off level and prognostic value are not known.  A number of pressing issues were identified by this review, including defining the true incidence of VTE in COVID patients, developing algorithms to identify those susceptible to develop thrombotic complications and severe disease, determining the role of biomarkers and/or scoring systems to stratify patients' risk, designing adequate and feasible diagnostic protocols for PE, establishing the optimal thromboprophylaxis strategy, and developing uniform diagnostic and reporting criteria.

title: Does communicable diseases (including COVID-19) may increase global poverty risk? A cloud on the horizon
abstract: Coronavirus epidemic can push millions of people in poverty. The shortage of healthcare resources, lack of sanitation, and population compactness leads to an increase in communicable diseases, which may increase millions of people add in a vicious cycle of poverty. The study used the number of factors that affect poverty incidence in a panel of 76 countries for a period of 2010–2019. The dynamic panel GMM estimates show that the causes of death by communicable diseases, chemical-induced carbon and fossil fuel combustion, and lack of access to basic hand washing facilities menace to increase poverty headcounts, whereas, an increase in healthcare expenditures substantially decreases poverty headcounts across countries. Further, the results show the U-shaped relationship between economic growth and poverty headcounts, as economic growth first decreases and later increase poverty headcount due to rising healthcare disparities among nations. The causality estimates show that lack of access to basic amenities lead to increase of communicable diseases including COVID-19 whereas chemical-induced carbon and fossil fuel emissions continue to increase healthcare expenditures and economic growth in a panel of selected countries. The rising healthcare disparities, regional conflicts, and public debt burden further ‘hold in the hand’ of communicable diseases that push millions of people in the poverty trap.

title: Time to realise the true potential of Ayurveda against COVID-19

title: Forecasting Transmission Dynamics of COVID-19 Epidemic in India under Various Containment Measures- A Time-Dependent State-Space SIR Approach
abstract: Our primary objective is to predict the dynamics of COVID-19 epidemic in India while adjusting for the effects of various progressively implemented containment measures. Apart from forecasting the major turning points and parameters associated with the epidemic, we intend to provide an epidemiological assessment of the impact of these containment measures in India.  We propose a method based on time-series SIR model to estimate time-dependent modifiers for transmission rate of the infection. These modifiers are used in state-space SIR model to estimate reproduction number R0, expected total incidence, and to forecast the daily prevalence till the end of the epidemic. We consider four different scenarios, two based on current developments and two based on hypothetical situations for the purpose of comparison.  Assuming gradual relaxation in lockdown post 17 May 2020, we expect the prevalence of infecteds to cross 9 million, with at least 1 million severe cases, around the end of October 2020. For the same case, estimates of R0 for the phases no-intervention, partial-lockdown and lockdown are 4.46 (7.1), 1.47 (2.33), and 0.817 (1.29) respectively, assuming 14-day (24-day) infectious period.  Estimated modifiers give consistent estimates of unadjusted R0 across different scenarios, demonstrating precision. Results corroborate the effectiveness of lockdown measures in substantially reducing R0. Also, predictions are highly sensitive towards estimate of infectious period.

title: Flattening the curves: on-off lock-down strategies for COVID-19 with an application to Brazi
abstract: The current COVID-19 pandemic is affecting different countries in different ways. The assortment of reporting techniques alongside other issues, such as underreporting and budgetary constraints, makes predicting the spread and lethality of the virus a challenging task. This work attempts to gain a better understanding of how COVID-19 will affect one of the least studied countries, namely Brazil. Currently, several Brazilian states are in a state of lock-down. However, there is political pressure for this type of measures to be lifted. This work considers the impact that such a termination would have on how the virus evolves locally. This was done by extending the SEIR model with an on / off strategy. Given the simplicity of SEIR we also attempted to gain more insight by developing a neural regressor. We chose to employ features that current clinical studies have pinpointed has having a connection to the lethality of COVID-19. We discuss how this data can be processed in order to obtain a robust assessment.

title: L’épidémie de COVID-19 bouscule tout.Organisation des soins, télémédecine, éducation thérapeutique, édition médicale, et rôles du diabète et du terrain cardiovasculaire

title: Optimization of group size in pool testing strategy for SARS‐CoV‐2: A simple mathematical model
abstract: Coronavirus disease (Covid‐19) has reached unprecedented pandemic levels and is affecting almost every country in the world. Ramping up the testing capacity of a country supposes an essential public health response to this new outbreak. A pool testing strategy where multiple samples are tested in a single reverse transcriptase‐polymerase chain reaction (RT‐PCR) kit could potentially increase a country's testing capacity. The aim of this study is to propose a simple mathematical model to estimate the optimum number of pooled samples according to the relative prevalence of positive tests in a particular healthcare context, assuming that if a group tests negative, no further testing is done whereas if a group tests positive, all the subjects of the group are retested individually. The model predicts group sizes that range from 11 to 3 subjects. For a prevalence of 10% of positive tests, 40.6% of tests can be saved using testing groups of four subjects. For a 20% prevalence, 17.9% of tests can be saved using groups of three subjects. For higher prevalences, the strategy flattens and loses effectiveness. Pool testing individuals for severe acute respiratory syndrome coronavirus 2 is a valuable strategy that could considerably boost a country's testing capacity. However, further studies are needed to address how large these groups can be, without losing sensitivity on the RT‐PCR. The strategy best works in settings with a low prevalence of positive tests. It is best implemented in subgroups with low clinical suspicion. The model can be adapted to specific prevalences, generating a tailored to the context implementation of the pool testing strategy.

title: Investigating the cases of novel coronavirus disease (COVID-19) in China using dynamic statistical techniques
abstract: The initial investigation by local hospital attributed the outbreak of the novel coronavirus disease (COVID-19) to pneumonia with unknown cause that appeared like the 2003 severe acute respiratory syndrome (SARS). The World Health Organization declared COVID-19 as public health emergency after it spread outside China to several countries. Thus, an assessment of the novel coronavirus disease (COVID-19) with novel estimation approaches is essential to the global debate. This study is the first to develop both time series and panel data models to construct conceptual tools that examine the nexus between death from COVID-19 and confirmed cases. We collected daily data on four health indicators namely deaths, confirmed cases, suspected cases, and recovered cases across 31 Provinces/States in China. Due to the complexities of the COVID-19, we investigated the unobserved factors including environmental exposures accounting for the spread of the disease through human-to-human transmission. We used estimation methods capable of controlling for cross-sectional dependence, endogeneity, and unobserved heterogeneity. We predicted the impulse-response between confirmed cases of COVID-19 and COVID-19-attributable deaths. Our study revealed that the effect of confirmed cases on the novel coronavirus attributable deaths is heterogeneous across Provinces/States in China. We found a linear relationship between COVID-19 attributable deaths and confirmed cases whereas a nonlinear relationship was confirmed for the nexus between recovery cases and confirmed cases. The empirical evidence revealed that an increase in confirmed cases by 1% increases coronavirus attributable deaths by ~0.10%–~1.71% (95% CI). Our empirical results confirmed the presence of unobserved heterogeneity and common factors that facilitates the novel coronavirus attributable deaths caused by increased levels of confirmed cases. Yet, the role of such a medium that facilitates the transmission of COVID-19 remains unclear. We highlight safety precaution and preventive measures to circumvent the human-to-human transmission.

title: CORONAVIRUS IN PREGNANCY AND DELIVERY: RAPID REVIEW AND EXPERT CONSENSUS
abstract: Person to person spread of COIVD-19 in the UK has now been confirmed. There are limited case series reporting the impact on women affected by coronaviruses (CoV) during pregnancy. In women affected by SARS and MERS, the case fatality rate appeared higher in women affected in pregnancy compared with non-pregnant women. We conducted a rapid, review to guide management of women affected by COVID -19 during pregnancy and developed interim practice guidance with the RCOG and RCPCH to inform maternity and neonatal service planning METHODS Searches were conducted in PubMed and MedRxiv to identify primary case reports, case series, observational studies or randomised-controlled trial describing women affected by coronavirus in pregnancy and on neonates. Data was extracted from relevant papers and the review was drafted with representatives of the RCPCH and RCOG who also provided expert consensus on areas where data were lacking  From 9964 results on PubMed and 600 on MedRxiv, 18 relevant studies (case reports and case series) were identified. There was inconsistent reporting of maternal, perinatal and neonatal outcomes across case reports and series concerning COVID-19, SARS, MERS and other coronaviruses. From reports of 19 women to date affected by COVID-19 in pregnancy, delivering 20 babies, 3 (16%) were asymptomatic, 1 (5%) was admitted to ICU and no maternal deaths have been reported. Deliveries were 17 by caesarean section, 2 by vaginal delivery, 8 (42%) delivered pre-term. There was one neonatal death, in 15 babies who were tested there was no evidence of vertical transmission.  Morbidity and mortality from COVID-19 appears less marked than for SARS and MERS, acknowledging the limited number of cases reported to date. Pre-term delivery affected 42% of women hospitalised with COVID-19, which may put considerable pressure on neonatal services if the UK reasonable worse-case scenario of 80% of the population affected is realised. There has been no evidence of vertical transmission to date. The RCOG and RCPCH have provided interim guidance to help maternity and neonatal services plan their response to COVID-19.

title: Bayesian Network Analysis of Covid-19 data reveals higher Infection Prevalence Rates and lower Fatality Rates than widely reported
abstract: Widely reported statistics on Covid-19 across the globe fail to take account of both the uncertainty of the data and possible explanations for this uncertainty. In this paper we use a Bayesian Network (BN) model to estimate the Covid-19 infection prevalence rate (IPR) and infection fatality rate (IFR) for different countries and regions, where relevant data are available. This combines multiple sources of data in a single model. The results show that Chelsea Mass. USA and Gangelt Germany have relatively higher infection prevalence rates (IPR) than Santa Clara USA, Kobe, Japan and England and Wales. In all cases the infection prevalence is significantly higher than what has been widely reported, with much higher community infection rates in all locations. For Santa Clara and Chelsea, both in the USA, the most likely IFR values are 0.3-0.4%. Kobe, Japan is very unusual in comparison with the others with values an order of magnitude less than the others at, 0.001%. The IFR for Spain is centred around 1%. England and Wales lie between Spain and the USA/German values with an IFR around 0.8%. There remains some uncertainty around these estimates but an IFR greater than 1% looks remote for all regions/countries. We use a Bayesian technique called "virtual evidence" to test the sensitivity of the IFR to two significant sources of uncertainty: survey quality and uncertainty about Covid-19 death counts. In response the adjusted estimates for IFR are most likely to be in the range 0.3%-0.5%.

title: Nowcasting Covid-19 statistics reported withdelay: a case-study of Sweden
abstract: The new corona virus disease -- COVID-2019 -- is rapidly spreading through the world. The availability of unbiased timely statistics of trends in disease events are a key to effective responses. But due to reporting delays, the most recently reported numbers are frequently underestimating of the total number of infections, hospitalizations and deaths creating an illusion of a downward trend. Here we describe a statistical methodology for predicting true daily quantities and their uncertainty, estimated using historical reporting delays. The methodology takes into account the observed distribution pattern of the lag. It is derived from the removal method, a well-established estimation framework in the field of ecology.

title: Modeling COVID-19 dynamics in Illinois under non-pharmaceutical interventions
abstract: We present modeling of the COVID-19 epidemic in Illinois, USA, capturing the implementation of a Stay-at-Home order and scenarios for its eventual release. We use a non-Markovian age-of-infection model that is capable of handling long and variable time delays without changing its model topology. Bayesian estimation of model parameters is carried out using Markov Chain Monte Carlo (MCMC) methods. This framework allows us to treat all available input information, including both the previously published parameters of the epidemic and available local data, in a uniform manner. To accurately model deaths as well as demand on the healthcare system, we calibrate our predictions to total and in-hospital deaths as well as hospital and ICU bed occupancy by COVID-19 patients. We apply this model not only to the state as a whole but also its sub-regions in order to account for the wide disparities in population size and density. Without prior information on non-pharmaceutical interventions (NPIs), the model independently reproduces a mitigation trend closely matching mobility data reported by Google and Unacast. Forward predictions of the model provide robust estimates of the peak position and severity and also enable forecasting the regional-dependent results of releasing Stay-at-Home orders. The resulting highly constrained narrative of the epidemic is able to provide estimates of its unseen progression and inform scenarios for sustainable monitoring and control of the epidemic.

title: COVID-19 Antibody Seroprevalence in Santa Clara County, California
abstract: Addressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County.  On 4/3-4/4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics. We report the prevalence of antibodies to SARS-CoV-2 in a sample of 3,330 people, adjusting for zip code, sex, and race/ethnicity. We also adjust for test performance characteristics using 3 different estimates: (i) the test manufacturer's data, (ii) a sample of 37 positive and 30 negative controls tested at Stanford, and (iii) a combination of both.  The unadjusted prevalence of antibodies to SARS-CoV-2 in Santa Clara County was 1.5% (exact binomial 95CI 1.11-1.97%), and the population-weighted prevalence was 2.81% (95CI 2.24-3.37%). Under the three scenarios for test performance characteristics, the population prevalence of COVID-19 in Santa Clara ranged from 2.49% (95CI 1.80-3.17%) to 4.16% (2.58-5.70%). These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50-85-fold more than the number of confirmed cases.  The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases. Population prevalence estimates can now be used to calibrate epidemic and mortality projections.

title: Comparison of two commercial molecular tests and a laboratory-developed modification of the CDC 2019-nCOV RT-PCR assay for the qualitative detection of SARS-CoV-2 from upper respiratory tract specimens
abstract: We compared the ability of 2 commercial molecular amplification assays [RealTime SARS-CoV-2 on the m2000 (Abbott) and ID NOW COVID-19 (Abbott)] and a laboratory developed test [modified CDC 2019-nCoV RT-PCR assay with RNA extraction by eMag(R) (bioMeriux) and amplification on QuantStudio 6 or ABI 7500 Real-Time PCR System (Life Technologies)] to detect SARS-CoV-2 RNA in upper respiratory tract specimens. Discrepant results were adjudicated by medical record review. 200 nasopharyngeal swab specimens in viral transport medium were collected from symptomatic patients between March 27 and April 9, 2020. Results were concordant for 167 specimens (84.3% overall agreement), including 94 positive and 73 negative specimens. The RealTime SARS-CoV-2 assay on the m2000 yielded 33 additional positive results, 25 of which were also positive by the modified CDC assay but not by the ID NOW COVID-19 assay. In a follow-up evaluation, 97 patients for whom a dry nasal swab specimen yielded negative results by the ID NOW COVID-19 assay had a paired nasopharyngeal swab specimen collected in viral transport medium and tested by the RealTime SARS-CoV-2 assay; SARS-CoV-2 RNA was detected in 13 (13.4%) of these specimens. Medical record review deemed all discrepant results to be true positives. The ID NOW COVID-19 test was fastest (as soon as 5 minute for positive and 13 minute for negative result.) The RealTime SARS-CoV-2 assay on the m2000 detected more cases of COVID-19 infection than the modified CDC assay or the ID NOW COVID-19 test.

title: Appropriate measures of influenza immunization program effectiveness
abstract: Groll and Thomson's evaluation of the effectiveness of Ontario's Universal Influenza Immunization Campaign used per capita cases of laboratory-confirmed influenza. We argue that these data are susceptible to various biases and should not be used as an outcome measure. Laboratory data are traditionally used to identify the presence of influenza activity rather than to identify levels of influenza activity. A better measure of viral activity is the proportion of influenza tests positive; whereas the weekly proportion of tests positive was relatively consistent, a marked increase over time in the numbers of laboratory-confirmed cases paralleled an increase in the number of tests performed. Regardless, for evaluating universal influenza immunization program effectiveness, other established and available measures employed in previous studies describing the epidemiology of influenza should be used instead of laboratory data.

title: Covid-19 health care demand and mortality in Sweden in response to non-pharmaceutical (NPIs) mitigation and suppression scenarios
abstract: While the outbreak in China is now contained, since mid March 2020, the epicentre of the COVID-19 pandemic is in Europe, with Italy reporting more deaths than China. Various European countries have seen an exponential growth in daily new cases, and unless strong reductions in transmission, the wave is expected to hit all of Europe by the end of March 2020. There is an urgent need to reduce transmission and thus reduce the growth rate of this epidemic, reduce the height of the epidemic peak and the peak demand on healthcare services, as well as reduce the total number of infected persons. Here we estimate the impact of COVID-19 on the Swedish population at the municipality level, considering demography and human mobility under scenarios of mitigation and suppression. We estimate the timelines of incidence, hospitalization rates, the intensive care (ICU) need, and the mortality in relation to the current Swedish ICU capacity, and costs of care. We further investigate the sensitivity to various degrees of potential underreporting on the estimates.

title: Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes
abstract: The 2014 Ebola epidemic in West Africa has attracted public interest worldwide, leading to millions of Ebola-related Internet searches being performed during the period of the epidemic. This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred. The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola.  Google Trends (GT) was used to explore Internet activity related to Ebola. The study period was from 29 December 2013 to 14 June 2015. Pearson’s correlation was performed to correlate Ebola-related relative search volumes (RSVs) with the number of weekly and overall Ebola cases. Multivariate regression was performed using Ebola-related RSV as a dependent variable, and the overall number of Ebola cases and the Human Development Index were used as predictor variables.  The greatest RSV was registered in the three West African countries mainly affected by the Ebola epidemic. The queries varied in the different countries. Both quantitative and qualitative differences between the affected African countries and other Western countries with primary cases were noted, in relation to the different flux volumes and different time courses. In the affected African countries, web query search volumes were mostly concentrated in the capital areas. However, in Western countries, web queries were uniformly distributed over the national territory. In terms of the three countries mainly affected by the Ebola epidemic, the correlation between the number of new weekly cases of Ebola and the weekly GT index varied from weak to moderate. The correlation between the number of Ebola cases registered in all countries during the study period and the GT index was very high.  Google Trends showed a coarse-grained nature, strongly correlating with global epidemiological data, but was weaker at country level, as it was prone to distortions induced by unbalanced media coverage and the digital divide. Global and local health agencies could usefully exploit GT data to identify disease-related information needs and plan proper communication strategies, particularly in the case of health-threatening events.  contains supplementary material, which is available to authorized users.

title: Human Subtilase SKI-1/S1P Is a Master Regulator of the HCV Lifecycle and a Potential Host Cell Target for Developing Indirect-Acting Antiviral Agents
abstract: HCV infection is a major risk factor for liver cancer and liver transplantation worldwide. Overstimulation of host lipid metabolism in the liver by HCV-encoded proteins during viral infection creates a favorable environment for virus propagation and pathogenesis. In this study, we hypothesize that targeting cellular enzymes acting as master regulators of lipid homeostasis could represent a powerful approach to developing a novel class of broad-spectrum antivirals against infection associated with human Flaviviridae viruses such as hepatitis C virus (HCV), whose assembly and pathogenesis depend on interaction with lipid droplets (LDs). One such master regulator of cholesterol metabolic pathways is the host subtilisin/kexin-isozyme-1 (SKI-1) – or site-1 protease (S1P). SKI-1/S1P plays a critical role in the proteolytic activation of sterol regulatory element binding proteins (SREBPs), which control expression of the key enzymes of cholesterol and fatty-acid biosynthesis. Here we report the development of a SKI-1/S1P-specific protein-based inhibitor and its application to blocking the SREBP signaling cascade. We demonstrate that SKI-1/S1P inhibition effectively blocks HCV from establishing infection in hepatoma cells. The inhibitory mechanism is associated with a dramatic reduction in the abundance of neutral lipids, LDs, and the LD marker: adipose differentiation-related protein (ADRP)/perilipin 2. Reduction of LD formation inhibits virus assembly from infected cells. Importantly, we confirm that SKI-1/S1P is a key host factor for HCV infection by using a specific active, site-directed, small-molecule inhibitor of SKI-1/S1P: PF-429242. Our studies identify SKI-1/S1P as both a novel regulator of the HCV lifecycle and as a potential host-directed therapeutic target against HCV infection and liver steatosis. With identification of an increasing number of human viruses that use host LDs for infection, our results suggest that SKI-1/S1P inhibitors may allow development of novel broad-spectrum biopharmaceuticals that could lead to novel indirect-acting antiviral options with the current standard of care.

title: Measures of frequency: calculating prevalence and incidence in the era of COVID-19

title: Computed Tomography Features of Coronavirus Disease 2019 (COVID-19): A Review for Radiologists
abstract: Coronavirus Disease 2019 (COVID-19) pneumonia has become a global pandemic. Although the rate of new infections in China has decreased, currently, 169 countries report confirmed cases, with many nations showing increasing numbers daily. Testing for COVID-19 infection is performed via reverse transcriptase polymerase chain reaction, but availability is limited in many parts of the world. The role of chest computed tomography is yet to be determined and may vary depending on the local prevalence of disease and availability of laboratory testing. A common but nonspecific pattern of disease with a somewhat predictable progression is seen in patients with COVID-19. Specifically, patchy ground-glass opacities in the periphery of the lower lungs may be present initially, eventually undergoing coalescence, consolidation, and organization, and ultimately showing features of fibrosis. In this article, we review the computed tomography features of COVID-19 infection. Familiarity with these findings and their evolution will help radiologists recognize potential COVID-19 and recognize the significant overlap with other causes of acute lung injury.

title: Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey
abstract: Unprecedented measures have been adopted to control the rapid spread of the ongoing COVID-19 epidemic in China. People's adherence to control measures is affected by their knowledge, attitudes, and practices (KAP) towards COVID-19. In this study, we investigated Chinese residents' KAP towards COVID-19 during the rapid rise period of the outbreak. An online sample of Chinese residents was successfully recruited via the authors' networks with residents and popular media in Hubei, China. A self-developed online KAP questionnaire was completed by the participants. The knowledge questionnaire consisted of 12 questions regarding the clinical characteristics and prevention of COVID-19. Assessments on residents' attitudes and practices towards COVID-19 included questions on confidence in winning the battle against COVID-19 and wearing masks when going out in recent days. Among the survey completers (n=6910), 65.7% were women, 63.5% held a bachelor degree or above, and 56.2% engaged in mental labor. The overall correct rate of the knowledge questionnaire was 90%. The majority of the respondents (97.1%) had confidence that China can win the battle against COVID-19. Nearly all of the participants (98.0%) wore masks when going out in recent days. In multiple logistic regression analyses, the COVID-19 knowledge score (OR: 0.75-0.90, P<0.001) was significantly associated with a lower likelihood of negative attitudes and preventive practices towards COVID-2019. Most Chinese residents of a relatively high socioeconomic status, in particular women, are knowledgeable about COVID-19, hold optimistic attitudes, and have appropriate practices towards COVID-19. Health education programs aimed at improving COVID-19 knowledge are helpful for Chinese residents to hold optimistic attitudes and maintain appropriate practices. Due to the limited sample representativeness, we must be cautious when generalizing these findings to populations of a low socioeconomic status.

title: Spatiotemporal Analysis of the 2014 Ebola Epidemic in West Africa
abstract: In 2014–2016, Guinea, Sierra Leone and Liberia in West Africa experienced the largest and longest Ebola epidemic since the discovery of the virus in 1976. During the epidemic, incidence data were collected and published at increasing resolution. To monitor the epidemic as it spread within and between districts, we develop an analysis method that exploits the full spatiotemporal resolution of the data by combining a local model for time-varying effective reproduction numbers with a gravity-type model for spatial dispersion of the infection. We test this method in simulations and apply it to the weekly incidences of confirmed and probable cases per district up to June 2015, as reported by the World Health Organization. Our results indicate that, of the newly infected cases, only a small percentage, between 4% and 10%, migrates to another district, and a minority of these migrants, between 0% and 23%, leave their country. The epidemics in the three countries are found to be similar in estimated effective reproduction numbers, and in the probability of importing infection into a district. The countries might have played different roles in cross-border transmissions, although a sensitivity analysis suggests that this could also be related to underreporting. The spatiotemporal analysis method can exploit available longitudinal incidence data at different geographical locations to monitor local epidemics, determine the extent of spatial spread, reveal the contribution of local and imported cases, and identify sources of introductions in uninfected areas. With good quality data on incidence, this data-driven method can help to effectively control emerging infections.

title: Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020
abstract: Since December 2019, China has been experiencing a large outbreak of a novel coronavirus (2019-nCoV) which can cause respiratory disease and severe pneumonia. We estimated the basic reproduction number R(0) of 2019-nCoV to be around 2.2 (90% high density interval: 1.4–3.8), indicating the potential for sustained human-to-human transmission. Transmission characteristics appear to be of similar magnitude to severe acute respiratory syndrome-related coronavirus (SARS-CoV) and pandemic influenza, indicating a risk of global spread.

title: Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study
abstract: The coronavirus disease (COVID-19) pandemic is a global health emergency with over 6 million cases worldwide as of the beginning of June 2020. The pandemic is historic in scope and precedent given its emergence in an increasingly digital era. Importantly, there have been concerns about the accuracy of COVID-19 case counts due to issues such as lack of access to testing and difficulty in measuring recoveries.  The aims of this study were to detect and characterize user-generated conversations that could be associated with COVID-19-related symptoms, experiences with access to testing, and mentions of disease recovery using an unsupervised machine learning approach.  Tweets were collected from the Twitter public streaming application programming interface from March 3-20, 2020, filtered for general COVID-19-related keywords and then further filtered for terms that could be related to COVID-19 symptoms as self-reported by users. Tweets were analyzed using an unsupervised machine learning approach called the biterm topic model (BTM), where groups of tweets containing the same word-related themes were separated into topic clusters that included conversations about symptoms, testing, and recovery. Tweets in these clusters were then extracted and manually annotated for content analysis and assessed for their statistical and geographic characteristics.  A total of 4,492,954 tweets were collected that contained terms that could be related to COVID-19 symptoms. After using BTM to identify relevant topic clusters and removing duplicate tweets, we identified a total of 3465 (<1%) tweets that included user-generated conversations about experiences that users associated with possible COVID-19 symptoms and other disease experiences. These tweets were grouped into five main categories including first- and secondhand reports of symptoms, symptom reporting concurrent with lack of testing, discussion of recovery, confirmation of negative COVID-19 diagnosis after receiving testing, and users recalling symptoms and questioning whether they might have been previously infected with COVID-19. The co-occurrence of tweets for these themes was statistically significant for users reporting symptoms with a lack of testing and with a discussion of recovery. A total of 63% (n=1112) of the geotagged tweets were located in the United States.  This study used unsupervised machine learning for the purposes of characterizing self-reporting of symptoms, experiences with testing, and mentions of recovery related to COVID-19. Many users reported symptoms they thought were related to COVID-19, but they were not able to get tested to confirm their concerns. In the absence of testing availability and confirmation, accurate case estimations for this period of the outbreak may never be known. Future studies should continue to explore the utility of infoveillance approaches to estimate COVID-19 disease severity.

title: Ideas for how informaticians can get involved with COVID-19 research
abstract: The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on population health and wellbeing. Biomedical informatics is central to COVID-19 research efforts and for the delivery of healthcare for COVID-19 patients. Critical to this effort is the participation of informaticians who typically work on other basic science or clinical problems. The goal of this editorial is to highlight some examples of COVID-19 research areas that could benefit from informatics expertise. Each research idea summarizes the COVID-19 application area, followed by an informatics methodology, approach, or technology that could make a contribution. It is our hope that this piece will motivate and make it easy for some informaticians to adopt COVID-19 research projects.

title: Trends and prediction in daily incidence and deaths of COVID-19 in the United States: a search-interest based model
abstract: The coronavirus disease 2019 (COVID-19) infected more than 586,000 patients in the U.S. However, its daily incidence and deaths in the U.S. are poorly understood. Internet search interest was found correlated with COVID-19 daily incidence in China, but not yet applied to the U.S. Therefore, we examined the association of internet search-interest with COVID-19 daily incidence and deaths in the U.S.  We extracted the COVDI-19 daily incidence and death data in the U.S. from two population-based datasets. The search interest of COVID-19 related terms was obtained using Google Trends. Pearson correlation test and general linear model were used to examine correlations and predict future trends, respectively.  There were 555,245 new cases and 22,019 deaths of COVID-19 reported in the U.S. from March 1 to April 12, 2020. The search interest of COVID, “COVID pneumonia,” and “COVID heart” were correlated with COVDI-19 daily incidence with ~12-day of delay (Pearson’s r=0.978, 0.978 and 0.979, respectively) and deaths with 19-day of delay (Pearson’s r=0.963, 0.958 and 0.970, respectively). The COVID-19 daily incidence and deaths appeared to both peak on April 10. The 4-day follow-up with prospectively collected data showed moderate to good accuracies for predicting new cases (Pearson’s r=−0.641 to −0.833) and poor to good accuracies for daily new deaths (Pearson’s r=0.365 to 0.935).  Search terms related to COVID-19 are highly correlated with the trends in COVID-19 daily incidence and deaths in the U.S. The prediction-models based on the search interest trend reached moderate to good accuracies.

title: Protocol for a multicentre study of nosocomial SARS-CoV2 transmission The NOSO-COR Project
abstract: The newly identified SARS-CoV2 can cause serious acute respiratory infections such as pneumonia with a mortality rate of approximately 2% to 4%. In the current context of high incidence rates of SARS-CoV2 in the community, a significant increase in the rate of nosocomial transmission is expected. The risk of nosocomial transmission could even be higher in low-income countries that have fragile healthcare systems. This protocol is intended to study and document suspected or confirmed cases of nosocomial SARS-CoV2 infection, the clinical spectrum and the determinants (risk factors/protective) at participating hospitals.  This will be an international multicentre prospective, observational, hospital-based study in adults and children. It will include volunteer patients, care givers and healthcare professionals in France and hospitals affiliated with the GABRIEL network. Demographic and clinical data will be collected using case-report forms designed especially for the purpose of the project. A nasopharyngeal swab will be collected and tested for SARS-CoV2 by RT-PCR. Characteristics of the study participants, the proportion of confirmed nosocomial SARS-CoV2 infections relative to all patients with syndromes suggestive of 2019-nCoV infection will be analysed. Appropriate multivariate modelling will be used to identify the determinants associated with nosocomial onset. Ethics and dissemination: This study was approved by the clinical research and committee of Ile de France V on March 8, 2020.

title: Covid-19, the pandemic war: Implication for neurologists