docid: tkajjrri

title: SHELTER IN PLACE ORDER CONTAINED COVID-19 GROWTH RATE IN GREECE

text: Background: The Greek authorities implemented the strong social distancing measures within the first few weeks after the first confirmed case of the virus to curtail the COVID-19 growth rate. Objectives: To estimate the effect of the two-stage strong social distancing measures, the closure of all non-essential shopping centers and businesses on March 16 and the shelter in place orders (SIPOs) on March 23 on the COVID-19 growth rate in Greece Methods: We obtained data on COVID-19 cases in Greece from February 26th through May 4th from publicly available sources. An interrupted time-series regression analysis was used to estimate the effect of the measures on the exponential growth of confirmed COVID-19 cases, controlling for the number of daily testing, and weekly fixed-effects. Results: The growth rate of the COVID-19 cases in the pre-policies implementation period was positive as expected (p=0.003). Based on the estimates of the interrupted time-series, our results indicate that the SIPO on March 23 significantly slowed the growth rate of COVID-19 in Greece (p=0.04). However, we did not find evidence on the effectiveness of standalone and partial measures such as the non-essential business closures implemented on March 16 on the COVID-19 spread reduction. Discussion: The combined social distancing measures implemented by the Greek authorities within the first few weeks after the first confirmed case of the virus reduced the COVID-19 growth rate. These findings provide evidence and highlight the effectiveness of these measures to flatten the curve and to slow the spread of the virus.


title: CT-derived measurements of pulmonary blood volume in small vessels and need for oxygen in COVID-19 patients

text: In contrast to early reports of conventional acute respiratory distress syndrome (ARDS) as the underlying pathophysiology of hypoxemic respiratory failure observed in patients with severe COVID-19, more recent findings implicate direct involvement of the pulmonary vasculature in giving rise to these symptoms. In earlier research, we demonstrated that patients with COVID-19 showed markedly reduced pulmonary blood volumes in pulmonary vessels <5 mm2 in cross-sectional area visible on imaging (termed "BV5"), with attendant dilation of larger, more proximal vessels. Here, we present preliminary results in which reduced BV5 is shown to correlate significantly with increased need for supplemental oxygen and abnormal arterial blood gas measurements in hospitalized COVID-19 patients. We suggest a potential mechanistic link between observed clinical, pathological, and imaging findings, and outline how these may be helpful in clinical assessment as well as the development of novel therapies.


docid: oblipjpe

title: Ophthalmologists’ strategy for the prevention and control of coronavirus pneumonia with conjunctivitis or with conjunctivitis as the first symptom/ 伴发或首发病毒性结膜炎的新型冠状病毒感染下眼科医师的防控策略

text: China is currently in a critical stage of controlling the outbreak of novel coronavirus pneumonia (COVID-19). As ophthalmologists working in the center of Wuhan city, the virus’s front line, we recently found conjunctivitis in five COVID-19 patients of a total of 92 COVID-19 patients.One of these five patients had conjunctivitis as the first symptom and was then diagnosed with COVID-19.These observations suggest: the mechanism and pathway of transmission of the novel coronavirus need to be further clarified; the symptoms of conjunctivitis accompanying novel coronavirus infection and conjunctiva as an important entrance point of the virus need to be further verified; early diagnosis, implementation of medical isolation, and giving appropriate treatment to patients with asymptomatic and mild-symptom conjunctivitis are essential to prevent the spread of the epidemic; those with conjunctivitis symptoms should be distinguished from other types of viral conjunctivitis; strict personal protection measures should be taken; and more sensitive techniques should be developed as soon as possible for virus detection in tear and conjunctiva swabs.


title: A living systematic review protocol for COVID-19 clinical trial registrations

text: Since the coronavirus disease 2019 (COVID-19) outbreak was identified in December 2019 in Wuhan, China, a strong response from the research community has been observed with the proliferation of independent clinical trials assessing diagnostic methods, therapeutic and prophylactic strategies. While there is no intervention for the prevention or treatment of COVID-19 with proven clinical efficacy to date, tools to distil the current research landscape by intervention, level of evidence and those studies likely powered to address future research questions is essential. This living systematic review aims to provide an open, accessible and frequently updated resource summarising the characteristics of COVID-19 clinical trial registrations. Weekly search updates of the WHO International Clinical Trials Registry Platform (ICTRP) and source registries will be conducted. Data extraction by two independent reviewers of trial characteristic variables including categorisation of trial design, geographic location, intervention type and targets, level of evidence and intervention adaptability to low resource settings will be completed. Descriptive and thematic synthesis will be conducted. A searchable and interactive visualisation of the results database will be created, and made openly available online. Weekly results from the continued search updates will be published and made available on the Infectious Diseases Data Observatory (IDDO) website ( COVID-19 website). This living systematic review will provide a useful resource of COVID-19 clinical trial registrations for researchers in a rapidly evolving context. In the future, this sustained review will allow prioritisation of research targets for individual patient data meta-analysis.


title: Disruption of the renal service during COVID-19 pandemic, physicians survey responses from 5 countries

text: The outbreak of COVID-19 has significant impact on health care systems. The workflow in renal care facilities and dialysis facilities is complex. The aim of his study was to explore multinational renal physician perspective about the disruption of outflow of renal service amid COVID-19 pandemic. Methods: we distributed a questionnaire electronically to renal physicians of various grades from 5 countries. The questionnaire was formulated of 9 questions with domains centered on the acute and chronic renal services Results 97 physicians took part in the survey from 5 countries. 58% of the participating renal physicians agreed that there has been disruption to the acute service offered to renal patients. 38% of the physicians who took the survey report disruption to the hemodialysis facilities. Conclusion At this challenging time of the pandemic, it is important to perform audits and quality control to explore the deficiencies of acute and chronic renal care pathways.


docid: vxjfgdbi

title: Visualization of Countermeasures against COVID-19 Infections in Japan by Systems Thinking : The reason why the Japanese government and its Council of Experts couldn't increase PCR tests

text: Many people in Japan and around the world have questioned whether Japan's "number of tests" for COVID-19 infection control is sufficient Because the scope of influence caused by infection is broad and complex, it is difficult to see the whole picture by only cutting one aspect of the situation, and there are differences among the sectors involved This misunderstanding can be seen as a communication failure in Japan's countermeasures against COVID-19 infection, and it is important for science and technology to clarify the reasons for the failure Why has the number of tests been narrowed down? The problem is not limited to the government's ability to execute, but there are also systemic impediments and overlooked issues in the effective implementation of countermeasures against new coronavirus infection In this paper, we first used a systems thinking technique (causal loop diagram) to visualize the situation related to COVID-19 infection, and confirmed its characteristics as a system Our causal loop diagram consists of an "infection model" and an "incidence response model" The government and the Council of Experts) have separated the "infection model" from the "incidence model" with the goal of reducing the number of deaths and, by extension, serious illnesses as much as possible In the process, attention has been paid to avoiding the depletion of medical resources, which is probably one of the reasons why the number of tests has not been able to increase so far However, while this approach is reasonable when each model is taken separately, it turns out that there are serious systemic weaknesses that occur at the interface between the two models For example, raising the testing hurdle will increase the number of mild cases that are active in the city without being tested, increasing the chance of infection and increasing the number of new cases This will create a new spread of infection Considering this, the following two measures need to be implemented It is necessary to implement blockades or other measures to reduce the number of opportunities for infection as soon as possible, or equivalent measures to reduce the number of opportunities for infection (e g , school closures, refraining from going outside, cancellation of events, city blockades, etc ) In order to expand inspections, it is necessary to introduce an inspection system that minimizes the connection with medical resources, such as the combination of drive-through inspections and walk-through inspections, which are famous in Korea, with Internet interviews However, in the current situation where infection is spreading to a certain extent and medical resources are tight, a two-sided strategy, such as increasing the number of tests, is necessary to control the spread of infection by lightly infected people (and subclinical infected people) who spread infection in the city in order to deal with the serious systemic problems at the interface between the two models The causal loop diagram shows that citizens are also required to take measures to prevent infection, such as masks and hand washing, and to change their behavior in order to reduce the chance of infection This case is an example of the importance of system-wide understanding of the situation for both citizens and experts, and of sharing that understanding Translated with www DeepL com/Translator (free version)


title: Persistent SARS-CoV-2 presence is companied with defects in adaptive immune system in non-severe COVID-19 patients

text: Background: COVID-19 has been widely spreading. We aim to examine adaptive immune cells in non-severe patients with persistent SARS-CoV-2 shedding. Methods 37 non-severe patients with persistent SARS-CoV-2 presence transferred to Zhongnan hospital of Wuhan University were retrospectively recruited to PP (persistently positive) group, which was further allocated to PPP group (n=19) and PPN group (n=18), according to their testing results after 7 days (N=negative). Epidemiological, demographic, clinical and laboratory data were collected and analyzed. Data from age- and sex-matched non-severe patients at disease onset (PA [positive on admission] patients, n=37), and lymphocyte subpopulation measurements from matched 54 healthy subjects were extracted for comparison. Results Compared with PA patients, PP patients had much improved laboratory findings, including WBCs, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, albumin, AST, CRP, SAA, and IL-6. The absolute numbers of CD3+ T cells, CD4+ T cells, and NK cells were significantly higher in PP group than that in PA group, and were comparable to that in healthy controls. PPP subgroup had markedly reduced B cells and T cells compared to PPN group and healthy subjects. Finally, paired results of these lymphocyte subpopulations from 10 PPN patients demonstrated that the number of T cells and B cells significantly increased when the SARS-CoV-2 tests turned negative. Conclusion Persistent SARS-CoV-2 presence in non-severe COVID-19 patients is associated with reduced numbers of adaptive immune cells. Monitoring lymphocyte subpopulations could be clinically meaningful in identifying fully recovered COVID-19 patients. Abbreviations COVID-19: Coronavirus disease 2019; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2; HC: Healthy controls.


title: Transmission Dynamics of the COVID-19 Epidemics in England

text: The ongoing COVID-19 pandemic has caused a tremendous health burden and impact on the world economy. As one of the European countries experiencing one of the worst COVID-19 epidemics, the UK government at the end of March 2020 implemented the biggest lockdown of society during peacetime in British history, aiming to contain the rapid spread of the virus. While the lockdown has been maintained for seven weeks in UK, the effectiveness of the control measures in suppressing the transmission of the disease remains incompletely understood. Here we applied a Bayesian SEIR (susceptible-exposed-infected-removed) epidemiological model to rebuild the local transmission dynamics of the spread of COVID-19 in nine regions of England. We found that the basic reproduction number (R0) in England is relatively high compared with China. Our estimation of the net reproduction number (Rt) suggests that the control measures, especially the forceful lockdown, were effective to reduce the transmissibility and curb the COVID-19 epidemic. Although the overall incidence rate in the UK has declined, our forecasting highlights the possibility of a second wave of the disease in several regions, which may be currently underway in one of the cities there (e.g. Leicester, East Midlands). This study enhances our understanding of the current outbreak and effectiveness of control measures in the UK.


docid: cueqxibh

title: Estimating effective reproduction number using generation time versus serial interval, with application to COVID-19 in the Greater Toronto Area, Canada

text: BACKGROUND. The effective reproductive number Re(t) is a critical measure of epidemic potential. Re(t) can be calculated in near real time using an incidence time series and the generation time distribution---the time between infection events in an infector-infectee pair. In calculating Re(t), the generation time distribution is often approximated by the serial interval distribution---the time between symptom onset in an infector-infectee pair. However, while generation time must be positive by definition, serial interval can be negative if transmission can occur before symptoms, such as in COVID-19, rendering such an approximation improper in some contexts. METHODS. We developed a method to infer the generation time distribution from parametric definitions of the serial interval and incubation period distributions. We then compared estimates of Re(t) for COVID-19 in the Greater Toronto Area of Canada using: negative-permitting versus non-negative serial interval distributions, versus the inferred generation time distribution. RESULTS. We estimated the generation time of COVID-19 to be Gamma-distributed with mean 3.99 and standard deviation 2.96 days. Relative to the generation time distribution, non-negative serial interval distribution caused overestimation of Re(t) due to larger mean, while negative-permitting serial interval distribution caused underestimation of Re(t) due to larger variance. IMPLICATIONS. Approximation of the generation time distribution of COVID-19 with non-negative or negative-permitting serial interval distributions when calculating Re(t) may result in over or underestimation of transmission potential, respectively.


title: The geography of COVID-19 spread in Italy and implications for the relaxation of confinement measures

text: We examine the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Italy, to address the appropriate methodological choices for the design of selective relaxations of the current containment measures. Pressing relevance stems from the need to restart the economy dramatically affected by the lockdown. We employ a spatially explicit, data-intensive model of the patterns of disease spread in Italy, with the goal of providing tools to: estimate the baseline trajectory, i.e. the expected unfolding of the outbreak if the current containment measures were kept in place indefinitely; assess possible deviations from the baseline, should relaxations of the current lockdown result in increased disease transmission; and estimate the isolation effort required to prevent a resurgence of the outbreak. For instance, a 50% increase in effective transmission as a result of the loosening of confinement measures, to be instated on May 4, yields an epidemic curve that shows a major rebound larger than the previous peaks in most regions. A control effort, capable of isolating a daily percentage of approximately 7% of the individuals in the exposed and pre-symptomatic stages, proves necessary to counterbalance such an increase, and maintain the epidemic curve onto the decreasing baseline trajectory. We explore several scenarios, provide the basic data to design the related control strategies and discuss their feasibility. Should suitable control via tracing and testing prove unfeasible, stop-and-go enforcement or delay of the lockdown relaxations would be necessary to reduce the isolation effort required to maintain the epidemic trajectory under control.


title: Omics BioAnalytics: Reproducible Research using R Shiny and Alexa

text: Summary High-throughput technologies produce complex high-dimensional datasets which are analyzed using a variety of ever-evolving bioinformatics tools. Well-designed web frameworks enable more intuitive and efficient analysis such that less time is spent on coding and more time is spent on interpretation of results and addressing insightful biological questions aided by interactive visualizations. Here, we present Omics BioAnalytics, a full-service Web framework that enables comprehensive, multi-level characterization, analysis, and integration of omics datasets. Blending web-based (R Shiny) and voice-based (Amazon’s Alexa) analytics, Omics BioAnalytics can be used both by expert computational biologists and non-coding biological domain experts, alike. Our web framework can be utilized to explore complex datasets and identify biosignatures and discriminative biomarkers of health and disease processes, and generate testable hypotheses relating to underlying molecular mechanisms. Availability Omics BioAnalytics is freely available at https://github.com/singha53/omicsBioAnalytics and the web app is deployed at https://amritsingh.shinyapps.io/omicsBioAnalytics/. The source code for the companion Alexa Skill can be found at https://github.com/singha53/omics-bioanalytics-alexa-skill.


title: Novel indicators for evaluating topological threats to populations from pandemics applied to COVID-19

text: BACKGROUND To deal with pandemics, evaluating the temporal status of an outbreak is important. However, prevailing standards in this respect are mostly empirical and arbitrary. As an alternative, we focus on a novel approach which configures indicators that evaluate topological threats to populations due to the COVID-19 pandemic. METHODS We extended the current PzDom model to calculate a threshold of the model for accelerated growth, an indicator of growth extent Re(v), covariance Re(s), a topological number E(l), and expected sums of possibly increasing numbers of infected people. We term this the exPzDom model. RESULTS The indicators in the exPzDom model adhere well to the empirical dynamics of SARS-CoV-2 infected people and align appropriately with actual policies instituted by the Japanese government. CONCLUSIONS The described indicators could be leveraged pursuant of objective evaluation based on mathematics. Further testing of the reliability and robustness of exPzDom model in other pandemic contexts is warranted.


title: Time-sync Video Tag Extraction Using Semantic Association Graph

text: Time-sync comments reveal a new way of extracting the online video tags. However, such time-sync comments have lots of noises due to users' diverse comments, introducing great challenges for accurate and fast video tag extractions. In this paper, we propose an unsupervised video tag extraction algorithm named Semantic Weight-Inverse Document Frequency (SW-IDF). Specifically, we first generate corresponding semantic association graph (SAG) using semantic similarities and timestamps of the time-sync comments. Second, we propose two graph cluster algorithms, i.e., dialogue-based algorithm and topic center-based algorithm, to deal with the videos with different density of comments. Third, we design a graph iteration algorithm to assign the weight to each comment based on the degrees of the clustered subgraphs, which can differentiate the meaningful comments from the noises. Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF). In this way, the video tags are extracted automatically in an unsupervised way. Extensive experiments have shown that SW-IDF (dialogue-based algorithm) achieves 0.4210 F1-score and 0.4932 MAP (Mean Average Precision) in high-density comments, 0.4267 F1-score and 0.3623 MAP in low-density comments; while SW-IDF (topic center-based algorithm) achieves 0.4444 F1-score and 0.5122 MAP in high-density comments, 0.4207 F1-score and 0.3522 MAP in low-density comments. It has a better performance than the state-of-the-art unsupervised algorithms in both F1-score and MAP.


INTRODUCTION-Special issue on foreign trade and investment in China’s continuing economic opening and the Belt and Road Initiative


title: Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China

text: BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSIONS 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: Neutrophil-to-Lymphocyte Ratio Predicts Severe Illness Patients with 2019 Novel Coronavirus in the Early Stage

text: Background: Severe ill patients with 2019 novel coronavirus (2019-nCoV) infection progressed rapidly to acute respiratory failure. We aimed to select the most useful prognostic factor for severe illness incidence. Methods: The study prospectively included 61 patients with 2019-nCoV infection treated at Beijing Ditan Hospital from January 13, 2020 to January 31, 2020. Prognostic factor of severe illness was selected by the LASSO COX regression analyses, to predict the severe illness probability of 2019-CoV pneumonia. The predictive accuracy was evaluated by concordance index, calibration curve, decision curve and clinical impact curve. Results: The neutrophil-to-lymphocyte ratio (NLR) was identified as the independent risk factor for severe illness in patients with 2019-nCoV infection. The NLR had a c-index of 0.807 (95% confidence interval, 0.676-0.38), the calibration curves fitted well, and the decision curve and clinical impact curve showed that the NLR had superior standardized net benefit. In addition, the incidence of severe illness was 9.1% in age ≥ 50 and NLR < 3.13 patients, and half of patients with age ≥ 50 and NLR ≥ 3.13 would develop severe illness. Based on the risk stratification of NLR with age, the study developed a 2019-nCoV pneumonia management process. Conclusions: The NLR was the early identification of risk factors for 2019-nCoV severe illness. Patients with age ≥ 50 and NLR ≥ 3.13 facilitated severe illness, and they should rapidly access to intensive care unit if necessary.


title: Estimating the efficacy of symptom-based screening for COVID-19

text: There is substantial interest in using presenting symptoms to prioritize testing for COVID-19 and establish symptom-based surveillance However, little is currently known about the specificity of COVID-19 symptoms To assess the feasibility of symptom-based screening for COVID-19, we used data from tests for common respiratory viruses and SARS-CoV-2 in our health system to measure the ability to correctly classify virus test results based on presenting symptoms Based on these results, symptom-based screening may not be an effective strategy to identify individuals who should be tested for SARS-CoV-2 infection or to obtain a leading indicator of new COVID-19 cases


title: Sequential informed pooling approach to detect SARS-CoV2 infection

text: The alarming spread of the pandemic coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is requiring several measures to reduce the risk of contagion. Every successful strategy in controlling SARS-CoV2 infection depends on the timely viral diagnosis which should include asymptomatic carriers. Consequently, strategies to increase the throughput for clinical laboratories to conduct large-scale diagnostic testing are urgently needed. Here we support the hypothesis that standard diagnostic protocol for SARS-CoV-2 virus could be conveniently applied to pooled samples obtained from different subjects. We suggest that a two-step sequential pooling procedure could identify positive subjects, ensuring at the same time significant benefits of costs and time. Simulation data are used to assess the efficiency, in terms of number of required tests, both for random assignment of the subjects to the pools and for situations when epidemiological and clinical data are used to create an "informed" version of the pooling. Different scenarios are examined in the simulations to measure the effect of different pool sizes and different values for the virus frequency. Our results allow to customize the pooling strategy according to the specific characteristics of the cohort to be tested.


title: Understanding the CoVID-19 pandemic Curve through statistical approach

text: Current research is an attempt to understand the CoVID-19 pandemic curve through statistical approach of probability density function with associated skewness and kurtosis measures, change point detection and polynomial fitting to estimate infected population along with 30 days projection. The pandemic curve has been explored for above average affected countries, six regions and global scale during 64 days of 22nd January to 24th March, 2020. The global cases infection as well as recovery rate curves remained in the ranged of 0 - 9.89 and 0 - 8.89%, respectively. The confirmed cases probability density curve is high positive skewed and leptokurtic with mean global infected daily population of 6620. The recovered cases showed bimodal positive skewed curve of leptokurtic type with daily recovery of 1708. The change point detection helped to understand the CoVID-19 curve in term of sudden change in term of mean or mean with variance. This pointed out disease curve is consist of three phases and last segment that varies in term of day lengths. The mean with variance based change detection is better in differentiating phases and associated segment length as compared to mean. Global infected population might rise in the range of 0.750 to 4.680 million by 24th April 2020, depending upon the pandemic curve progress beyond 24th March, 2020. Expected most affected countries will be USA, Italy, China, Spain, Germany, France, Switzerland, Iran and UK with at least infected population of over 0.100 million. Infected population polynomial projection errors remained in the range of -78.8 to 49.0%.


title: Management strategies and prediction of COVID-19 by a fractional order generalized SEIR model

text: In this project, we study a class of fractional order generalized SEIR epidemic models. Based on the public data from Jan. 22th to May 15th, 2020, we reliably estimate key epidemic parameters and make predictions on the peak point and possible ending time for the target region. We analyze the current management strategy and predict the future implementation of different management strategies. Numerical simulations which support our analysis are also given.


title: Electrohydrodynamic inkjet printing of Polydimethylsiloxane (PDMS)

text: Abstract The current fabrication methods for micro and nano scale Polydimethylsiloxane (PDMS) devices either require high environmental conditions or sophisticated procedures at high cost. Electrohydrodynamic inkjet (EHD) printing is a potential method to effectively fabricate micro scale PDMS devices because EHD printing is environment-friendly, low-cost, compatible to various inks, and most importantly, high resolution. However, little research has been conducted to study EHD printing of PDMS-based ink. In this paper, EHD printing of PDMS has been investigated. The effects of several critical parameters on the printing process were studied. The dimension of the printed patterns and the printing frequency were preciously controlled by the voltage parameters. The patterns with a network structure was demonstrated. The results indicated that the voltage amplitude and the pulse frequency could both control the dimensions of droplets and the printing frequency. As future work, we plan to develop a simulation tool to predict printing quality of PDMS and optimize printing process to fabricated 3D PDMS structures in micro scale.


title: Closed-loop fMRI neurofeedback to reduce negative attentional bias in depression

text: Depressed individuals show an attentional bias toward negatively valenced stimuli and thoughts. Here we present a novel closed-loop neurofeedback procedure that seeks to remediate this bias. Internal attentional states were detected by applying machine learning techniques to fMRI data in real-time, and externalized using a visually presented stimulus that the participant could learn to control. We trained 15 depressed and 12 healthy control participants over three fMRI sessions, preceded and followed by behavioral and clinical assessments. Initially, depressed participants were more likely than non-depressed participants to get “stuck” in negative attentional states, but this diminished with neurofeedback training relative to controls. Depression severity also decreased from pre- to post-training. These results demonstrate that our method is sensitive to the negative attentional bias in depressed individuals, and its reduction after training showcases the potential of this method as a treatment in the future.


title: Recapitulation of SARS-CoV-2 Infection and Cholangiocyte Damage with Human Liver Organoids

text: The newly emerged pandemic coronavirus, SARS-CoV-2, has posed a significant public health threat worldwide. However, the mode of virus transmission and tissue tropism is not well established yet. Recent findings of substantial liver damage in patients and ACE2+ cholangiocytes in healthy liver tissues prompted us to hypothesize that human liver ductal organoids could serve as a model to determine the susceptibility and mechanisms underlining the liver damage upon SARS-CoV-2 infection. By single-cell RNA sequencing, we found that long-term liver ductal organoid culture preserved the human specific ACE2+ population of cholangiocytes. Moreover, human liver ductal organoids were permissive to SARS-CoV-2 infection and support robust replication. Notably, virus infection impaired the barrier and bile acid transporting functions of cholangiocytes through dysregulation of genes involved in tight junction formation and bile acid transportation, which could explain the bile acid accumulation and consequent liver damage in patients. These results indicate that control of liver damage caused directly by viral infection should be valued in treating COVID-19 patients. Our findings also provide an application of human organoids in investigating the tropism and pathogenesis of SARS-CoV-2, which would facilitate novel drug discovery.


title: A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing

text: Background: An outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England. Methods: We adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China. Results: We predict that a CoVID-19 outbreak will peak 126 to 147 days (~4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate. Discussion: We provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for healthcare capacity planning.


title: SARS-CoV-2 in human sewage in Santa Catalina, Brazil, November 2019

text: We analysed human sewage located in Florianopolis (Santa Catalina, Brazil) from late October until the Brazil lockdown on early March. We detected SARS-CoV-2 in two samples collected independently on 27th November 2019 (5.49 {+/-} 0.02 log genome copies/L). Subsequent samplings were positive until 4th March 2020 (coinciding with the first COVID-19 case reported in Santa Catalina), with a SARS-CoV-2 RNA increase of one log (6.68 {+/-} 0.02 log genome copies/L). Our results show that SARS-CoV-2 has been circulating in Brazil since late November 2019, much earlier than the first reported case in the Americas (21st January 2020, USA).


title: Estimate of the Maximum Limit of Total Cases of Infected Patients COVID-19

text: In this work, we present a method to estimate the maximum limit of total cases of COVID-19 considering that the time in which the maximum number of new daily cases occurs corresponds to the inflection point of the curve described by the total number of cases that assumed to have a growth according to a logistical function in which the number of total cases at the inflection point will correspond to half of the maximum limit of total cases COVID-19. We estimate this maximum limit for China and South Korea, obtaining results compatible with the observations. And we also estimate for Italy, Germany, United Kingdom, United States and Spain.


title: eCovSens-Ultrasensitive Novel In-House Built Printed Circuit Board Based Electrochemical Device for Rapid Detection of nCovid-19 antigen, a spike protein domain 1 of SARS-CoV-2

text: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or nCovid-19) outbreak has become a huge public health issue due to its rapid transmission and global pandemic. Currently, there are no vaccines or drugs available for nCovid-19, hence early detection is crucial to help and manage the outbreak. Here, we report an in-house built biosensor device (eCovSens) and compare it with a commercial potentiostat for the detection of nCovid-19 spike antigen (nCovid-19Ag) in spiked saliva samples. A potentiostat based sensor was fabricated using fluorine doped tin oxide electrode (FTO) with gold nanoparticle (AuNPs) and immobilized with nCovid-19 monoclonal antibody (nCovid-19Ab) to measure change in the electrical conductivity. Similarly, eCovSens was used to measure change in electrical conductivity by immobilizing nCovid-19 Ab on screen printed carbon electrode (SPCE). The performances of both sensors were recorded upon interaction of nCovid-19Ab with its specific nCovid-19Ag. Under optimum conditions, the FTO based immunosensor and eCovSens displayed high sensitivity for detection of nCovid-19Ag, ranging from 1 fM to 1 μM. Our in-house developed device can successfully detect nCovid-19Ag at 10 fM concentration in standard buffer that is in close agreement with FTO/AuNPs sensor. The limit of detection (LOD) was found to be 90 fM with eCovSens and 120 fM with potentiostst in case of spiked saliva samples. The proposed portable eCovSens device can be used as a diagnostic tool for the rapid (within 10-30 s) detection of nCovid-19Ag traces directly in patient saliva in a non-invasive manner.


docid: apkbzwcc

title: ACE2 diversity in placental mammals reveals the evolutionary strategy of SARS-CoV-2

text: The recent emergence of SARS-CoV-2 is responsible for the current pandemic of COVID-19, which uses the human membrane protein ACE2 as a gateway to host-cell infection. We performed a comparative genomic analysis of 70 ACE2 placental mammal orthologues to identify variations and contribute to the understanding of evolutionary dynamics behind this successful adaptation to infect humans. Our results reveal that 4% of the ACE2 sites are under positive selection, all located in the catalytic domain, suggesting possibly taxon-specific adaptations related to the ACE2 function, such as cardiovascular physiology. Considering all variable sites, we selected 30 of them located at the critical ACE2 binding sites to the SARS-CoV-like viruses for analysis in more detail. Our results reveal a relatively high diversity of ACE2 between placental mammal species, while showing no polymorphism within human populations, at least considering the 30 inter-species variable sites. A perfect scenario for natural selection favored this opportunistic new coronavirus in its trajectory of infecting humans. We suggest that SARS-CoV-2 became a specialist coronavirus for human hosts. Differences in the rate of infection and mortality could be related to the innate immune responses, other unknown genetic factors, as well as non-biological factors.


title: Analytical Validation of a COVID-19 qRT-PCR Detection Assay Using a 384-well Format and Three Extraction Methods

text: 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: Impacts of genomic networks governed by human-specific regulatory sequences and genetic loci harboring fixed human-specific neuro-regulatory single nucleotide mutations on phenotypic traits of Modern Humans

text: Recent advances in identification and characterization of human-specific regulatory DNA sequences set the stage for the assessment of their global impact on physiology and pathology of Modern Humans. Gene set enrichment analyses (GSEA) of 8,405 genes linked with 35,074 human-specific neuro-regulatory single-nucleotide changes (hsSNCs) revealed a staggering breadth of significant associations with morphological structures, physiological processes, and pathological conditions of Modern Humans. Significantly enriched traits include more than 1,000 anatomically-distinct regions of the adult human brain, many different types of cells and tissues, more than 200 common human disorders and more than 1,000 records of rare diseases. Thousands of genes connected with neuro-regulatory hsSNCs have been identified, which represent essential genetic elements of the autosomal inheritance and offspring survival phenotypes. A total of 1,494 hsSNC- linked genes are associated with either autosomal dominant or recessive inheritance and 2,273 hsSNC-linked genes have been associated with premature death, embryonic lethality, as well as pre-, peri-, neo-, and post-natal lethality phenotypes of both complete and incomplete penetrance. Differential GSEA implemented on hsSNC-linked loci and associated genes identify 7,990 genes linked to evolutionary distinct classes of human-specific regulatory sequences (HSRS), expression of a majority of which (5,389 genes; 67%) is regulated by stem cell-associated retroviral sequences (SCARS). Interrogations of the MGI database revealed readily available mouse models tailored for precise experimental definitions of functional effects of hsSNCs and SCARS on genes causally affecting thousands of mammalian phenotypes and implicated in hundreds of common and rare human disorders. These observations suggest that a preponderance of human-specific traits evolved under a combinatorial regulatory control of HSRS and neuro-regulatory loci harboring hsSNCs that are fixed in humans, distinct from other primates, and located in differentially-accessible chromatin regions during brain development.


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title: Seroprevalence of SARS-CoV-2 IgG Specific Antibodies among Healthcare Workers in the Northern Metropolitan Area of Barcelona, Spain, after the first pandemic wave

text: Background: The rapid spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) around the world has caused a global pandemic, infecting millions of individuals worldwide, with an unprecedented impact in health care systems worldwide. Healthcare workers are one of the risk groups that need to be well characterized due to their strategic role in the management of patients, presently and in prevention of healthcare needs for future outbreaks. This study presents the results of the first SARS-CoV-2 seroprevalence study in the Northern Metropolitan Area of Barcelona, Spain. Methods: IgG SARS-CoV2 antibodies were analyzed in serum samples from 7563 healthcare workers of the Northern Metropolitan Area of Barcelona taken during the pandemia (from May 4th to May 22nd, 2020) by chemiluminescence assays. Results: A total of 779 of 7563 (10.3%) healthcare workers had detectable anti-SARS-CoV-2 IgG (specific for either S1/S2 or N antigens). No significant differences were observed between those working at primary care or at the reference hospital. Interestingly, in 29 (8.53%) of the previously confirmed positive reverse-transcriptase polymerase chain reaction (rRT-PCR) patients SARS-CoV-2 IgG (S1/S2 or recombinant N antigen) were negative. Conclusion: Seroprevalence of anti-SARS-CoV-2 IgG in the healthcare workers of the Nord Metropolitan Area of Barcelona was significantly increased in comparison with the general population in the same geographical area. These results give us an important insight for a better understanding of SARS-CoV-2 epidemiology, in a collective that is essential for the response against this pandemic.


title: Genomic trans-biopolitics: Why more-than-human geography is critical amid the COVID-19 pandemic

text: The rapidity of technological change underpins the centrality of genomes in framing COVID-19 problems and proposals for remedies. We counter such framings through a critical perspective that seeks to infuse more-than-human geographies into public health.


title: COVID-19 epidemic in Sri Lanka: A mathematical and computational modelling approach to control

text: The ongoing COVID19 outbreak originated in the city of Wuhan, China has caused a significant damage to the world population and the global economy. It has claimed more than 50,000 lives worldwide and more than one million of people have been infected as of 04th April 2020. In Sri Lanka, the first case of COVI19 was reported late January 2020 was a Chinese national and the first local case was identified in the second week of March. Since then, the government of Sri Lanka introduced various sequential measures to improve social distancing such as closure of schools and education institutes, introducing work from home model to reduce the public gathering, introducing travel bans to international arrivals and more drastically, imposed island wide curfew expecting to minimize the burden of the disease to the Sri Lankan health system and the entire community. Currently, there are 159 cases with five fatalities and also reported that 24 patients are recovered and discharged from hospitals. In this study, we use the SEIR conceptual model and its modified version by decomposing infected patients into two classes; patients who show mild symptoms and patients who tend to face severe respiratory problems and are required to treat in intensive care units. We numerically simulate the models for about five months period considering three critical parameters of COVID transmission mainly in the Sri Lankan context; efficacy of control measures, rate of overseas imported cases and time to introduce social distancing measures by the respective authorities.


title: Strategies to control and prevent novel coronavirus 2019: A quick overview

text: The emergence of Novel Coronavirus (2019-nCoV) in the Wuhan City of China and its rapid shedding among countries, which reminded the history of Severe Acute Respiratory Syndrome (SARS) happened almost two decades ago. However, the genome sequence of 2019-nCoV shared within few days of outbreak shows the better response of China and the world against the virus, perhaps due to the availability of advanced technology and lesson learned from previous epidemics. The researchers trying to determine the virulence, pathogenicity and transmission of 2019-nCoV. It is believed that disease reporting and data sharing about the emerged Coronavirus with international researchers are important steps to reduce the spread of the virus to the rest of the world. This report is aimed to understand the current status of the 2019-nCoV, problems related to it and possible measures for prevention. The infection may spread through wildlife and asymptomatic patients. People in underdeveloped countries having no basic facilities are at higher risk. Ban on wildlife trade and avoiding unnecessary traveling for a certain period is required to minimize the spread of the disease. The use of face masks, keeping away from the public gathering are other possible means of precautions, capacity building of health workers and provided relevant facilities (equipment, kits, etc.) to underdeveloped countries will further help to contain the pandemic. In the current scenario, it is concluded that 2019-nCoV is spreading irrespective of the borders and become pandemic. Extensive research is a cry of the day to contain the virus and curtail human losses.


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title: COVID-19 Mortality Risk Assessment: An International Multi-Center Study

text: Background: Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients. Methods: De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts. Findings: The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation ([≤] 93%), elevated levels of C-reactive protein ([≥] 130 mg/L), blood urea nitrogen ([≥] 18 mg/dL), and blood creatinine ([≥] 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87-0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88-0.95) on Seville patients, 0.87 (95% CI, 0.84-0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76-0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use. Interpretation: The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.


title: TRENDS IN PERCEPTION OF COVID-19 IN POLISH INTERNET

text: INTRODUCTION: Due to the spread of SARS-CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-19 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time. METHODS: We study the perception of COVID-19 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques. RESULTS: We identified seven temporal major clusters of interest on the topic COVID-19: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government declared war against disease around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term antiviral mask in Google, encyclopaedic definition in Wikipedia SARS-CoV-2 as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection. CONCLUSIONS: Traditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.


title: Long-term Positivity to SARS-CoV-2: A Clinical Case of COVID-19 with Persistent Evidence of Infection

text: In December 2019, an outbreak of a new coronavirus (SARS-CoV-2) was reported in Hubei province in China. The disease has since spread worldwide and the World Health Organization declared it a pandemic on 11 March 2020. We describe the case of a 65-year-old woman who clinically recovered from COVID-19 but showed persistent infection with SARS-CoV-2 for 51 days. LEARNING POINTS: A case of persistent infection with SARS-CoV-2 is described. Some tests may pick up viral RNA fragments, giving a false positive result. The quarantining of infected patients to limit possible SARS-CoV-2 spread is important.


title: Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study

text: Background: Preliminary studies suggest that people from Black, Asian and Minority Ethnic (BAME) backgrounds experience higher mortality from COVID-19 but the underlying reasons remain unclear. Methods: Prospective analysis of registry data describing patients admitted to five acute NHS Hospitals in east London, UK for COVID-19. Emergency hospital admissions with confirmed SARS-CoV-2 aged 16 years or over were included. Data, including ethnicity, social deprivation, frailty, patient care and detailed risk factors for mortality, were extracted from hospital electronic records. Multivariable survival analysis was used to assess associations between ethnic group and mortality accounting for the effects of age, sex and various other risk factors. Results are presented as hazard ratios (HR) or odds ratios (OR) with 95% confidence intervals. Findings: 1996 adult patients were admitted between 1st March and 13th May 2020. After excluding 259 patients with missing ethnicity data, 1737 were included in our analysis of whom 511 had died by day 30 (29%). 538 (31%) were from Asian, 340 (20%) Black and 707 (40%) white backgrounds. Compared to white patients, those from BAME backgrounds were younger, with differing co-morbidity profiles and less frailty. Asian and black patients were more likely to be admitted to intensive care and to receive invasive ventilation (OR 1.54, [1.06-2.23]; p=0.023 and 1.80 [1.20-2.71]; p=0.005, respectively). After adjustment for age and sex, patients from Asian (HR 1.49 [1.19-1.86]; p<0.001) and black (HR 1.30 [1.02-1.65]; p=0.036) backgrounds were more likely to die. These findings persisted across a range of risk-factor adjusted analyses. Interpretation: Patients from Asian and Black backgrounds are more likely to die from COVID-19 infection despite controlling for all previously identified confounders. Higher rates of invasive ventilation in intensive care indicate greater acute disease severity. Our analyses suggest that patients of Asian and Black backgrounds suffered disproportionate rates of premature death from COVID-19.


3d Virtual Patho-Histology of Lung Tissue from Covid-19 Patients based on Phase Contrast X-ray Tomography


title: Phylogenetic Analysis of the Novel Coronavirus Reveals Important Variants in Indian Strains

text: Recently classified as a pandemic by WHO, novel Corononavirus 2019 has affected almost every corner of the globe causing human deaths in a range of hundred thousands. The virus having its roots in Wuhan (China) has been spread over the world by its own property to change itself accordingly. These changes correspond to its transmission and pathogenicity due to which the concept of social distancing appeared into the picture. In this paper, a few findings from the whole genome sequence analysis of viral genome sequences submitted from India are presented. The data used for analysis comprises 440 collective genome sequences of virus submitted in GenBank, GISAID, and SRA projects, from around the world as well as 28 viral sequences from India. Multiple sequence alignment of all genome sequences was performed and analysed. A novel non-synonymous mutation 4809C>T (S1515F) in NSP3 gene of SARS-CoV2 Indian strains is reported along with other frequent and important changes from around the world: 3037C>T, 14408C>T, and 23403A>G. The novel change was observed in samples collected in the month of March, whereas was found to be absent in samples collected in January with the respective persons’ travel history to China. Phylogenetic analysis clustered the sequences with this change as one separate clade. Mutation was predicted as stabilising change by insilco tool DynaMut. A second patient in the world to our knowledge with multiple (Wuhan and USA) strain contraction was observed in this study. The infected person is among the two early infected patients with travel history to China. Strains sequenced in Iran stood out to have different variants, as most of the reported frequent variants were not observed. The objective of this paper is to highlight the similarities and changes observed in the submitted Indian viral strains. This helps to keep track on the activity, that how virus is changing into a new subtype. Major strains observed were European with the novel change in India and other being emergent clade of Iran. Its important to observe the changes in NSP3 gene, as this gene has been reported with extensive positive selection as well as potential drug target. Extensive Positive Selection Drives the Evolution of Nonstructural Proteins. With the limited number of sequences this was the only frequent novel non-synonymous change observed from Indian strains, thereby making this change vulnerable for investigation in future. This paper has a special focus on tracking of Indian viral sequences submitted in public domain.


title: Characteristics, outcome and predictors of in-hospital mortality in an elderly population from a SARS-CoV-2 outbreak in a long-term care facility.

text: Since December 2019, coronavirus disease 2019 (COVID-19) pandemic has spread from China all over the world, many COVID-19 outbreaks have been reported in long-term care facilities (LCTF). However, data on clinical characteristics and prognostic factors in such settings are scarce. We conducted a retrospective, observational cohort study to assess clinical characteristics and baseline predictors of mortality of COVID-19 patients hospitalized after an outbreak of SARS-CoV-2 infection in a LTCF. A total of 50 patients were included. Mean age was 80 years (SD, 12 years), and 24/50 (57.1%) patients were males. A total of 42/50 (84%) patients experienced symptoms of SARS-CoV-2 infection. The overall in-hospital mortality rate was 32%. In Cox regression, significant predictors of in-hospital mortality were: hypernatremia (HR 9.12), lymphocyte count <1000 cells/L (HR 7.45), cardiovascular diseases other than hypertension (HR 6.41), and higher levels of serum interleukin-6 (IL-6, pg/mL) (HR 1.005). Our study shows a high in-hospital mortality rate in a cohort of elderly patients with COVID-19 and hypernatremia, lymphopenia, CVD other than hypertension, and higher IL-6 serum levels were identified as independent predictors of in-hospital mortality. Further studies are necessary to better understand and confirm our findings in the setting of a LTCF outbreak of COVID-19.


title: Structures, conformations and distributions of SARS-CoV-2 spike protein trimers on intact virions

text: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virions are surrounded by a lipid bilayer from which spike (S) protein trimers protrude. Heavily glycosylated S trimers bind the ACE2 receptor and mediate entry of virions into target cells. S exhibits extensive conformational flexibility: it modulates the exposure of its receptor binding site and later undergoes complete structural rearrangement to drive fusion of viral and cellular membranes. The structures and conformations of soluble, overexpressed, purified S proteins have been studied in detail using cryo-electron microscopy. The structure and distribution of S on the virion surface, however, has not been characterised. Here we applied cryo-electron microscopy and tomography to image intact SARS-CoV-2 virions, determining the high-resolution structure, conformational flexibility and distributions of S trimers in situ on the virion surface. These results provide a basis for understanding the conformations of S present on the virion, and for studying their interactions with neutralizing antibodies.


title: Knowledge, attitude, practice and fear of COVID-19: A cross-cultural study

text: Abstract Background: Knowledge, Attitude and Practice (KAP), and Fear toward COVID-19 are an important issue when designing public health approaches to control the spread of this highly contagious disease like COVID-19 during the global pandemic period. Studies with KAP and fear measures are limited only regional or country level, not yet with global or cross-cultural populations. The study is aimed to measure KAP and fear level towards COVID-19 and explore its cross-cultural variances in knowledge by socio-demographic factors among the general population of 8 different countries over 5 continents. Method: A cross-sectional online survey was conducted in April 2020 among 1296 participants using the Google form platform. Considering the social distancing formula and pandemic situation, we collect data using popular social media networks. Univariate and bivariate analyses were used to explore the collected data on KAP, fear, and sociodemographic factors. Result: Overall knowledge score was 9.7 (out of 12) and gender differences (female vs male: 9.8 vs 9.5) were significant (p=0.008) in the bivariate analysis. Knowledge score variances found significant in some regions by gender, marital status and education qualification. The highest and lowest mean knowledge scores were recorded in the Middle East (10.0) and Europe (9.3). Despite having a high fear score (22.5 out of 35), 78.35% of respondents were in a positive attitude and 81.7% in good practice level. Fear score rankings: Middle East (1st; 23.8), Europe (2nd; 23.2); Africa (3rd; 22.7); South Asia (4th; 22.1); Oceania (5th; 21.9); and North America (6th; 21.7). We did not find a correlation between fear and knowledge. Limitation: Due to the nature of the online survey, aged and rural populations are under-representing (e.g. more than half of the responders are 16-29 age group). Conclusion: KAP and fear variation exist among geographical regions. Gender, marital status and education qualification are factors in knowledge variances for some regions. KAP and fear measures can assist health education programs considering some sociodemographic factors and regions during an outbreak of highly contagious disease and, which can uplift a positive attitude and good practice. Keywords: COVID-19, knowledge; attitude; practice; fear; cross-cultural study; online survey


title: Association between Cardiovascular Burden and Requirement of Intensive Care among Patients with Mild COVID-19

text: Background: Information regarding the impact of cardiovascular disease (CVD) on disease progression among patients with mild coronavirus disease 2019 (COVID-19) is limited. Methods: This study evaluated the association of underlying CVD with disease progression in patients with mild COVID-19. The primary outcome was the need to be transferred to intensive care due to disease progression. The patients were divided with and without CVD as well as stable and intensive care groups. Results: Of 332 patients with mild COVID-19, median age was 51 years (IQR, 40-59 years), and 200 (61.2%) were female. Of 48 (14.5%) patients with CVD, 23 (47.9%) progressed to severe disease status and required intensive care. Compared with patients without CVD, patients with CVD were older, and more likely to have fatigue, chest tightness, and myalgia. The rate of requiring intensive care was significantly higher among patients with CVD than in patients without CVD (47.92% vs. 12.4%; P<0.001). In subgroup analysis, rate of requiring intensive care was also higher among patients with either hypertension or coronary heart disease than in patients without hypertension or coronary heart disease. The multivariable regression model showed CVD served as an independent risk factor for intensive care (Odd ratio [OR], 2.652 [95% CI, 1.019-6.899]) after adjustment for various cofounders. Conclusions: Patients with mild COVID-19 complicating CVD in are susceptible to develop severe disease status and requirement for intensive care.


A CHOGM under COVID cloud


title: SARS-CoV-2 and SARS-CoV differ in their cell tropism and drug sensitivity profiles

text: SARS-CoV-2 is a novel coronavirus currently causing a pandemic. We show that the majority of amino acid positions, which differ between SARS-CoV-2 and the closely related SARS-CoV, are differentially conserved suggesting differences in biological behaviour. In agreement, novel cell culture models revealed differences between the tropism of SARS-CoV-2 and SARS-CoV. Moreover, cellular ACE2 (SARS-CoV-2 receptor) and TMPRSS2 (enables virus entry via S protein cleavage) levels did not reliably indicate cell susceptibility to SARS-CoV-2. SARS-CoV-2 and SARS-CoV further differed in their drug sensitivity profiles. Thus, only drug testing using SARS-CoV-2 reliably identifies therapy candidates. Therapeutic concentrations of the approved protease inhibitor aprotinin displayed anti-SARS-CoV-2 activity. The efficacy of aprotinin and of remdesivir (currently under clinical investigation against SARS-CoV-2) were further enhanced by therapeutic concentrations of the proton pump inhibitor omeprazole (aprotinin 2.7-fold, remdesivir 10-fold). Hence, our study has also identified anti-SARS-CoV-2 therapy candidates that can be readily tested in patients.


title: Global Economic Cost of Deaths Attributable to Ambient Air Pollution: Disproportionate Burden on the Ageing Population

text: Summary Background The health impacts of ambient air pollution impose large costs on society. While all people are exposed to air pollution, older individuals tend to be disproportionally affected. As a result, there is growing concern about the public health impacts of air pollution as many countries undergo rapid population ageing. We investigated the spatial and temporal variation in the health economic cost of deaths attributable to ambient air pollution, and its interaction with population ageing from 2000 to 2016 at global and regional levels. Methods We developed an age-adjusted measure of the value of a statistical life year (VSLY) to estimate the health economic cost attributable to ambient PM2.5 pollution using the Global Burden of Disease 2017 data and country-level socioeconomic information. First, we estimated the global age- and cause-specific mortality and years of life lost (YLL) attributable to PM2.5 pollution using the global exposure mortality model (GEMM) and global estimates of exposure derived from ground monitoring, satellite retrievals and chemical transport model simulations at 0.1 by 0.1 degree (~11 km at the equator) resolution. Second, for each year between 2000 and 2016, we translated the YLL within each age-group into a health-related economic cost using a country-specific, age-adjusted measure of VSLY. Third, we decomposed the major driving factors that contributed to the temporal change in health costs related to PM2.5. Finally, we conducted a sensitivity test to analyze the variability of the estimated health costs to four alternative valuation measures. We identified the uncertainty intervals (UIs) from 1000 draws of the parameters and exposure-response functions by age, cause, country and year. All economic values are reported in 2011 purchasing-power-parity-adjusted US dollars. Findings Globally, 8.42 million (95% UI: 6.50, 10.52) deaths and 163.68 million (116.03, 219.44) YLL were attributable to ambient PM2.5 in 2016. The average attributable mortality for the older population was 12 times higher than for those younger than 60 years old. In 2016, the global health economic cost of ambient PM2.5 pollution for the older population was US$2.40 trillion (1.89, 2.93) accounting for 59% of the cost for the total population. The health cost for the older population alone was equivalent to 2.1% (1.7%, 2.6%) of global gross domestic product (GDP) in 2016. While the economic cost per capita for the older population was US$2739 (2160, 3345) in 2016, the cost per capita for the younger population was only US$268 (205, 335). From 2000 to 2016, the annual global health economic cost for the total population increased from US$2.37 trillion (1.88, 2.87) to US$4.09 trillion (3.19, 5.05). Decomposing the factors that contributed to the rise in health economic costs, we found that increases in GDP per capita, population ageing, population growth, age-specific mortality reduction, and PM2.5 exposure changed the total health economic cost by 77%, 21.2%, 15.6%, -41.1% and -0.2%, respectively. Compared to using an age-invariant VSLY or an age-invariant value of a statistical life (VSL), the estimates of the older population share of the total health economic cost using an age-adjusted VSLY was 2 and 18 percentage points lower, respectively. Interpretation The health economic cost borne by the older population almost doubled between 2000 and 2016, driven primarily by GDP growth, population ageing and population growth. Compared to younger individuals, air pollution leads to disproportionately higher health costs amongst the older population, even after accounting for their relatively shorter remaining life expectancy and increased disability. The age-specific estimates of health economic cost inform the optimal design of air pollution reduction strategies and allocation of healthcare resources. The positive relationship between age and economic costs suggests that countries with severe air pollution and rapid aging rates would particularly benefit from improving their air quality. In addition, strategies aimed at enhancing healthcare services, especially for the older population, may be beneficial for reducing the costs of ambient air pollution.


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

text: 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: The impact of occupational risk from COVID on GP supply in England: A cross-sectional study

text: Objectives: To identify the risk of general practitioner mortality from COVID and the impact of measures to mitigate this risk on the level and socioeconomic distribution of primary care provision in the English NHS Design: Cross sectional study Setting: All GP practices providing primary care under the NHS in England Participants: 45,858 GPs and 6,771 GP practices in the English NHS Main outcome measures: Numbers of high-risk GPs, high-risk single-handed GP practices, patients associated with these high-risk single-handed practices and the regional and socioeconomic distribution of each. Mortality rates from COVID by age, sex and ethnicity were used to attribute risk to GPs and the Index of Multiple Deprivation was used to determine socioeconomic distributions of the outcomes. Results: Of 45,858 GPs in our sample 3,632 (7.9%) were classified as high risk or very high risk. Of 6,771 GP practices in our sample 639 (9.4%) were identified as single-handed practices and of these 209 (32.7%) were run by a GP at high or very high risk. These 209 single-handed practices care for 710,043 patients. GPs at the highest levels of risk from COVID, and single-handed practices run by high-risk GPs were concentrated in the most deprived neighbourhoods in the country. London had the highest proportion of both GPs and single-handed GP practices at very high risk of COVID mortality with 1,160 patients per 100,000 population registered to these practices. Conclusions: A significant proportion of GPs working in England, particularly those serving patients in the most deprived neighbourhoods, are at high risk of dying from COVID. Many of these GPs run single-handed practices. These GPs are particularly concentrated in London. There is an opportunity to provide additional support to mitigate COVID risk for GPs, GP practices and their patients. Failure to do so will likely exacerbate existing health inequalities.


title: A new design of an adaptive model of infectious diseases based on artificial intelligence approach: monitoring and forecasting of COVID-19 epidemic cases

text: Background: Mathematical infectious disease models available in literature, mostly take in their design that the parameters of basic reproduction number R_0 and interval serial S_I as constant values during tracking the outbreak cases. In this report a new intelligent model called HH-COVID-19 is proposed, with simple design and adaptive parameters. Methods: The parameters R_0 and S_I are adapted by adding three new weighting factors α, β and γ and two free parameters σ_1 and σ_2 in function of time t, thus the HH-COVID-19 become time-variant model. The parameters R_0, S_I, α, β, γ, σ_1 and σ_2 are estimated optimally based on a recent algorithm of artificial intelligence (AI), inspired from nature called Harris Hawks Optimizer (HHO), using the data of the confirmed infected cases in Algeria country in the first t=55 days. Results: Parameters estimated optimally: R_0= 1.341, S_I= 5.991, α= 2.987, β= 1.566, γ= 4.998 σ_1= -0.133 and σ_2= 0.0324. R_0 starts on 1.341 and ends to 2.677, and S_I starts on 5.991 and ends to 6.692. The estimated results are identically to the actual infected incidence in Algeria, HH-COVID-19 proved its superiority in comparison study. HH-COVID-19 predicts that in 1 May, the infected cases exceed 50 000, during May, to reach quickly the herd immunity stage at beginning of July. Conclusion: HH-COVID-19 can be used for tracking any COVID-19 outbreak cases around the world, just should updating its new parameters to fitting the area to be studied, especially when the population is directly vulnerable to COVID-19 infection.


title: COVID-19 in Italy: An overview from the first case to date

text: This paper is aimed to point out the current state of the COVID-19 pandemics in Italy. Currently, COVID-19 is an international crisis and all the continents have recorded a certain number of cases to date. After the first report of such infectious threat in China, the disease has progressively widespread thorough the world, and all the countries have attempted to point out specific protocols and therapies to face this new, unknown condition. The authors report an overview of how the Italian health service is facing this crisis after two months from the first internal reported cases. At last, special considerations highlight the non-sanitary issues of COVID-19 outbreak in Italy.


title: Hydroxychloroquine has no effect on SARS-CoV-2 load in nasopharynx of patients with mild form of COVID-19

text: Due to the urgent need to stop the spread of the COVID-19 attempts to find the drug with anti SARS-CoV-2 effects among ones already available on a market are actively being made. A number of in vitro as well as in vivo model animal studies have shown that widely used compound hydroxychloroquine (HCQ) is able to cause anti-viral effect on SARS-CoV-2. While there is no enough clinical data to support the use of HCQ, several countries including Russia have already approved HCQ as treatment and prophylactic option. In the current study we analyzed the dynamics of the SARS-CoV-2 RNA quantity change in nasopharynx swabs of infected patients in mild condition and compared that of patients receiving HCQ and receiving no antiviral pharmacological therapy. We found that most of the patients demonstrated gradual decrease in the number of SARS-CoV-2 RNA copies in the swab regardless of the HCQ receiving. Noteworthy that patients with RNA load higher than 106 copies were hospitalized due to condition deteriorating significantly more frequently compared to those with RNA load below 106 copies even with HCQ administration. In addition, the results of the current study indicate that recovering patients may produce viruses at least during 18 days from the onset of symptoms and HCQ therapy does not block or reduce it.


Armarium facilitating angina management post myocardial infarction concomitant with coronavirus disease 2019


title: The estimated impact of the COVID-19 epidemic in the general population of France

text: Background Model-based predictions for the COVID-19 outbreak revealed the potential for extraordinary mortality and saturation of health care systems if no action was taken. The pandemic hit France in late January 2020. Lockdown was implemented on March 17, 2020. The goal was to drastically reduce the number of infections, but at the cost of fear of a second epidemic wave when easing the lockdown. Our aim was to characterize the dynamics of the COVID-19 spread in France and estimate the proportion of coronavirus-infected individuals using ground truth from syndromic surveillance data. Methods National health authorities provide data from syndromic surveillance of the diagnosis of suspected COVID-19 reported by a sample of primary care physicians and from epidemic surveillance of confirmed cases, originating from hospitals. By extrapolation, COVID-19 incidence in the general population can be estimated. In turn, a back-calculation model can infer the number of contagious individuals, providing an idea of the spread of the epidemic before the implementation of lockdown measures. Results This study estimated that 12.3 million individuals were diagnosed 'suspected COVID-19' on May 6, 2020. At lockdown start, 2.5 million people were already contagious. The infection attack rate peaked on March 27, ten days after lockdown. The predicted sharp drop was not observed. The dynamics of the epidemic followed a continuous curve with a decline phase 2.35 times slower than the growth phase. 80% of infections occurred after lockdown. Conclusions These results call into question the effectiveness of lockdown. The epidemic would have followed its 'natural trajectory', beginning long before the health system detected the first cases. This hypothesis does not dispute the caution required with regard to the extraordinary spread of the epidemic, with less affected geographic areas becoming a source of susceptible individuals.


title: Contact Tracing: a game of big numbers in the time of COVID-19

text: One of the more widely advocated solutions to slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for contact tracing as this provides a major gain over a manual implementation. In this work, we study the characteristics of automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work for the current pandemic. We display the vulnerabilities of the strategy to inadequately sample the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that a strong reliance on contact tracing to contain the spread of the SARS-CoV-2 pandemic can lead to the potential danger of allowing the pandemic to spread unchecked. A carefully thought out strategy for controlling the spread of the pandemic along with automated contact tracing can lead to an optimal solution.


title: Using Machine Learning of Clinical Data to Diagnose COVID-19

text: The recent pandemic of Coronavirus Disease 2019 (COVID-19) has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests. In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aimed to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID -19 patients and influenza patients based on clinical variables alone. We discovered several novel associations between clinical variables, including correlations between being male and having higher levels of serum lymphocytes and neutrophils. We found that COVID-19 patients could be clustered into subtypes based on serum levels of immune cells, gender, and reported symptoms. Finally, we trained an XGBoost model to achieve a sensitivity of 92.5% and a specificity of 97.9% in discriminating COVID-19 patients from influenza patients. We demonstrated that computational methods trained on large clinical datasets could yield ever more accurate COVID-19 diagnostic models to mitigate the impact of lack of testing. We also presented previously unknown COVID-19 clinical variable correlations and clinical subgroups.


Does the coronavirus a global threat?


title: Ultraviolet A Radiation and COVID-19 Deaths: A Multi Country Study

text: Objectives To determine whether UVA exposure might be associated with COVID-19 deaths Design Ecological model and meta-analysis Setting 2,474 counties of the contiguous USA, 6,755 municipalities in Italy, 6,274 areas in England. Data were collected during their Vitamin D winter (monthly mean UVvitd of under 165 KJ/m2) from Jan to April 2020. Participants The at-risk population is the total county population, with measures to incorporate spatial infection into the model. The model is adjusted for: age, ethnicity, socioeconomic deprivation, long term PM2.5, and UV weighted by the vitamin D action spectrum. Main outcome measures We derive UVA measures for each area and estimate their relationship with COVID-19 mortality with a random effect for States, in a multilevel zero-inflated negative binomial model. In the USA and England death certificates had to record COVID-19. In Italy excess deaths in 2020 over expected from 2015-19. Data sources Satellite derived mean daily UVA dataset from Japan Aerospace Exploration Agency. Data on deaths compiled by Center for Disease Control (USA), Office for National Statistics (England) and Italian Institute of Statistics. Results Daily mean UVA (January-April 2020) varied between 450 to 1,000 KJ/m2 across the three countries. Our fully adjusted model showed an inverse correlation between UVA and COVID-19 mortality with a Mortality Risk Ratio (MRR) of 0.73 (0.62 to 0.87)per 100KJ/m2 increase UVA in the USA, 0.81 (0.71 to 0.93) in Italy and 0.51 (0.39 to 0.66) in England. Pooled MRR was 0.68 (0.53 to 0.66). Conclusions Our analysis, replicated in 3 independent national datasets, suggests ambient UVA exposure is associated with lower COVID-19 specific mortality. This effect is independent of vitamin D, as it occurred at irradiances below that likely to induce significant cutaneous vitamin D3 synthesis. Causal interpretations must be made cautiously in observational studies. Nonetheless this study suggests strategies for reduction of COVID-19 mortality


title: Perversely expressed long noncoding RNAs can alter host response and viral proliferation in SARS-CoV-2 infection

text: Background Since December 2019, the world is experiencing an unprecedented crisis due to a novel coronavirus, SARS-CoV-2. Owing to poor understanding of pathogenicity, the virus is eluding treatment and complicating recovery. Regulatory roles of long non-coding RNAs (lncRNAs) during viral infection and associated antagonism of host antiviral immune responses has become more evident in last decade. To elucidate possible functions of lncRNAs in the COVID-19 pathobiology, we have utilized RNA-seq dataset of SARS-CoV-2 infected lung epithelial cells. Results Our analyses uncover 21 differentially expressed lncRNAs whose functions are broadly involved in cell survival and regulation of gene expression. By network enrichment analysis we find that these lncRNAs can directly interact with differentially expressed protein-coding genes ADAR, EDN1, KYNU, MALL, TLR2 and YWHAG; and also AKAP8L, EXOSC5, GDF15, HECTD1, LARP4B, LARP7, MIPOL1, UPF1, MOV10 and PRKAR2A, host genes that interact with SARS-CoV-2 proteins. These genes are involved in cellular signaling, metabolism, immune response and RNA homeostasis. Since lncRNAs have been known to sponge microRNAs and protect expression of upregulated genes, we also identified 9 microRNAs that are induced in viral infections; however, some lncRNAs are able to block their usual suppressive effect on overexpressed genes and consequently contribute to host defense and cell survival. Conclusions Our investigation determines that deregulated lncRNAs in SARS-CoV-2 infection are involved in viral proliferation, cellular survival, and immune response, ultimately determining disease outcome and this information could drive the search for novel RNA therapeutics as a treatment option.


title: A targeted e-learning approach to reduce student mixing during a pandemic

text: The COVID-19 pandemic has resulted in widespread closure of schools and universities. These institutions have turned to distance learning to provide educational continuity. Schools now face the challenge of how to reopen safely and resume in-class learning. However, there is little empirical evidence to guide decision-makers on how this can be achieved. Here, we show that selectively deploying e-learning for larger classes is highly effective at decreasing campus-wide opportunities for student-to-student contact, while allowing most in-class learning to continue uninterrupted. We conducted a natural experiment at a large university that implemented a series of e-learning interventions during the COVID-19 outbreak. Analyses of >24 million student connections to the university Wi-Fi network revealed that population size can be manipulated by e-learning in a targeted manner according to class size characteristics. Student mixing showed accelerated growth with population size according to a power law distribution. Therefore, a small e-learning dependent decrease in population size resulted in a large reduction in student clustering behaviour. Our results show that e-learning interventions can decrease potential for disease transmission while minimizing disruption to university operations. Universities should consider targeted e-learning a viable strategy for providing educational continuity during early or late stages of a disease outbreak.


title: Analysis of meteorological conditions and prediction of epidemic trend of 2019-nCoV infection in 2020

text: Objective: To investigate the meteorological condition for incidence and spread of 2019-nCoV infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease. Methods: The meteorological factors during the outbreak period of the novel coronavirus pneumonia in Wuhan in 2019 were collected and analyzed, and were confirmed with those of Severe Acute Respiratory Syndrome (SARS) in China in 2003. Data of patients infected with 2019-nCoV and SARS coronavirus were collected from WHO website and other public sources. Results: This study found that the suitable temperature range for 2019-nCoV coronavirus survival is (13-24 degree Celsius), among which 19 degree Celsius lasting about 60 days is conducive to the spread between the vector and humans; the humidity range is 50%-80%, of which about 75% humidity is conducive to the survival of the coronavirus; the suitable precipitation range is below 30 mm/ month. Cold air and continuous low temperature over one week are helpful for the elimination of the virus. The prediction results show that with the approach of spring, the temperature in north China gradually rises, and the coronavirus spreads to middle and high latitudes along the temperature line of 13-18 degree Celsius. The population of new coronavirus infections is concentrated in Beijing, Tianjin, Hebei, Jiangsu, Zhejiang, Shanghai and other urban agglomerations. Starting from May 2020, the Beijing-Tianjin-Hebei urban agglomeration, the Central China Zhengzhou-Wuhan urban agglomeration, the eastern Jiangsu-Zhejiang-Shanghai urban agglomeration, and the southern Pearl River Delta urban agglomeration are all under a high temperature above 24 degree Celsius, which is not conducive to the survival and reproduction of coronaviruses, so the epidemic is expected to end. Conclusions: A wide range of continuous warm and dry weather is conducive to the survival of 2019-nCoV. The coming of spring, in addition to the original Wuhan-Zhengzhou urban agglomeration in central China, means that the prevention and control measures in big cities located in mid-latitude should be strengthened, especially the monitoring of transportation hubs. The Pearl River Delta urban agglomeration is a concentrated area of population in south China, with a faster temperature rise than those in mid-high latitudes, and thus the prevention in this area should be prioritized. From a global perspective, cities with a mean temperature below 24 degree Celsius are all high-risk cities for 2019-nCoV transmission before June.


title: Chloroquine, hydroxychloroquine, and COVID-19: systematic review and narrative synthesis of efficacy and safety

text: Background: The COVID-19 pandemic has required clinicians to urgently identify new treatment options or the repurposing of existing drugs. Several drugs are now being repurposed with the aim of identifying if these drugs provide some level of disease resolution. Of particular interest are chloroquine (CQ) and hydroxychloroquine (HCQ), first developed as an antimalarial therapy. There is increasing concern with regards to the efficacy and safety of these agents. The aims of this review are to systematically identify and collate studies describing the use of CQ and HCQ in human clinical trials and provide a detailed synthesis of evidence of its efficacy and safety. Methods and Findings: Searches for (COVID AND chloroquine [title/abstract] AND outcomes[full text]) and two (COVID AND hydroxychloroquine[title/abstract] AND outcomes[full text]) yielded 272 unique articles. Unique articles were manually checked for inclusion and exclusion criteria and also subjected to a quality appraisal assessment. A total of 19 articles were included in the systematic review. Seventy-five percent of observational studies employing an endpoint specific to efficacy recorded no significant difference in the attainment of outcomes, between COVID-19 patients given a range of CQ and/or HCQ doses, and the control groups. All clinical trials and 82% of observational studies examining an indicator unique to drug safety discovered a higher probability of adverse events in those treated patients suspected of, and diagnosed with, COVID-19. Seventy-five percent of the total papers focusing on cardiac side-effects found a greater incidence among patients administered a wide range of CQ and/or HCQ doses, with QTc prolongation the most common finding, in addition to its consequences of VT and cardiac arrest. Of the total studies using mortality rate as an end-point, 60% reported no significant change in the risk of death, while 30% showed an elevation, and 10% a depression, in treated relative to control patients. Conclusion: The strongest available evidence suggests that, relative to standard in-hospital management of symptoms, the use of CQ and HCQ to treat hospitalised COVID-19 patients has likely been unsafe. At the very least, the poor quality of data failing to find any significant changes in the risk of VT should preclude definitive judgment on drug safety until the completion of high-quality randomised clinical trials.


title: Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data

text: A better understanding of how the COVID-19 epidemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number (R0) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the epidemic.


title: Real Time Investigation of a large Nosocomial Influenza A Outbreak Informed by Genomic Epidemiology

text: Background: Nosocomial respiratory virus outbreaks represent serious public health challenges. Rapid and precise identification of cases and tracing of transmission chains is critical to end outbreaks and to inform prevention measures. Methods: We combined conventional surveillance with Influenza A virus (IAV) genome sequencing to identify and contain a large IAV outbreak in a metropolitan healthcare system. A total of 381 individuals, including 91 inpatients and 290 health care workers (HCWs), were included in the investigation. Results: During a 12-day period in early 2019, infection preventionists identified 89 HCWs and 18 inpatients as cases of influenza-like illness (ILI), using an amended definition, without the requirement for fever. Sequencing of IAV genomes from available nasopharyngeal (NP) specimens identified 66 individuals infected with a nearly identical strain of influenza A H1N1 (43 HCWs, 17 inpatients, and 6 with unspecified affiliation). All HCWs infected with the outbreak strain had received the seasonal influenza virus vaccination. Characterization of five representative outbreak viral isolates did not show antigenic drift. In conjunction with IAV genome sequencing, mining of electronic records pinpointed the origin of the outbreak as a single patient and a few interactions in the emergency department that occurred one day prior to the index ILI cluster. Conclusions: We used precision surveillance to identify and control a large nosocomial IAV outbreak, mapping the source of the outbreak to a single patient rather than HCWs as initially assumed based on conventional epidemiology. These findings have important ramifications for more effective prevention strategies to curb nosocomial respiratory virus outbreaks.


title: Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV

text: 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.


docid: rklajich

title: A new pandemic out of China: the Wuhan 2019-nCoV coronavirus syndrome