Crise du COVID – 19: l’économiste et l’infectiologue - Le regard de Jean Tirole


title: Risk estimation and prediction by modeling the transmission of the novel coronavirus (COVID-19) in mainland China excluding Hubei province

text: Background: In December 2019, an outbreak of coronavirus disease (COVID-19)was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in mainland China excluding Hubei province based on the published data and a novel mathematical model. Methods: A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number Rc, as well as the effective daily reproduction ratio Re(t), of the disease transmission in mainland China excluding Hubei province. Results: The estimation outcomes indicate that the control reproduction number is 3.36 (95% CI 3.20-3.64) and Re(t) has dropped below 1 since January 31st, 2020, which implies that the containment strategies implemented by the Chinese government in mainland China excluding Hubei province are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to the spread of disease for a longer time and more people would be infected, and may even cause epidemic or outbreak again. By calculating the effective reproduction ratio, we proved that the contact rate should be kept at least less than 30% of the normal level by April, 2020. Conclusions: To ensure the epidemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in mainland China apart from Hubei province.


title: A simple model for learning in volatile environments

text: Sound principles of statistical inference dictate that uncertainty shapes learning. In this work, we revisit the question of learning in volatile environments, in which both the first and second-order statistics of observations dynamically evolve over time. We propose a new model, the volatile Kalman filter (VKF), which is based on a tractable state-space model of uncertainty and extends the Kalman filter algorithm to volatile environments. The proposed model is algorithmically simple and encompasses the Kalman filter as a special case. Specifically, in addition to the error-correcting rule of Kalman filter for learning observations, the VKF learns volatility according to a second error-correcting rule. These dual updates echo and contextualize classical psychological models of learning, in particular hybrid accounts of Pearce-Hall and Rescorla-Wagner. At the computational level, compared with existing models, the VKF gives up some flexibility in the generative model to enable a more faithful approximation to exact inference. When fit to empirical data, the VKF is better behaved than alternatives and better captures human choice data in two independent datasets of probabilistic learning tasks. The proposed model provides a coherent account of learning in stable or volatile environments and has implications for decision neuroscience research.


title: Why lockdown? Simplified arithmetic tools for decision-makers, health professionals, journalists and the general public to explore containment options for the novel coronavirus

text: Half the world's population is already under lock-down and the remainder will have to follow if the ongoing novel coronavirus 2019 (COVID-19) virus pandemic is to be contained. Faced with such brutally difficult decisions, it is essential that as many people as possible understand (1) why lock-down interventions represent the only realistic way for individual countries to contain their national-level epidemics before they turn into public health catastrophes, (2) why these need to be implemented so early, so aggressively and for such extended periods, and (3) why international co-operation to conditionally re-open trade and travel between countries that have successfully eliminated local transmission represents the only way to contain the pandemic at global level. Here we present simplified arithmetic models of COVID-19 transmission, control and elimination in user-friendly Shiny and Excel formats that allow non-specialists to explore, query, critique and understand the containment decisions facing their country and the world at large. Based on parameter values representative of the United Republic of Tanzania, which is still early enough in its epidemic cycle and response to avert a national catastrophe, national containment and elimination with less than 10 deaths is predicted for highly rigorous lock down within 5 weeks of the first confirmed cases and maintained for 15 weeks. However, elimination may only be sustained if case importation from outside the country is comprehensively contained by isolating for three weeks all incoming travellers, except those from countries certified as COVID-free in the future. Any substantive relaxation of these assumptions, specifically shortening the lock-down period, less rigorous lock-down or imperfect importation containment, may facilitate epidemic re-initiation, resulting in over half a million deaths unless rigorously contained a second time. Removing contact tracing and isolation has minimal impact on successful containment trajectories because high incidence of similar mild symptoms caused by other common pathogens attenuates detection success of COVID-19 testing. Nevertheless, contact tracing is recommended as an invaluable epidemiological surveillance platform for monitoring and characterizing the epidemic, and for understanding the influence of interventions on transmission dynamics.


title: Prevention tools in endoscopy suites during the covid-19 pandemic/ Herramientas de prevención en las unidades de endoscopia digestiva en época de pandemia

text: Last December, SARS-CoV-2 emerged in Wuhan, China, like a new coronavirus, producing the coronavirus disease (COVID-19), that as of April 15, 2020, it has infected more than 2,000,000 people worldwide and caused 128,833 deaths. Due to the way SARS-CoV-2 is transmitted, endoscopy rooms and endoscopic procedures are an easy source of dissemination, as they fulfill the different characteristics of a contaminated environment for patients and healthcare personnel involved in endoscopic procedures. It is of great importance to establish measures within endoscopy units to prevent and reduce the risk of spreading this infection, creating a safe environment that protects patients and health personnel. A Pubmed search was performed with the following terms: (“COVID-19” OR “coronavirus” OR “SARS-Cov-2”) and (“gastrointestinal” OR “transmission” OR “intestinal” OR “digestive” OR “endoscopy “OR” esophagogastroduodenoscopy “OR” colonoscopy “). The gastroenterology team of our institution, considers that all patients brought to endoscopic procedures should be classified as high risk and presents the recommendations that all healthcare staff in endoscopy units, should take into account to reduce the risk of infection.


title: Worldwide Effectiveness of Various Non-Pharmaceutical Intervention Control Strategies on the Global COVID-19 Pandemic: A Linearised Control Model

text: Background COVID-19 is a virus which has lead to a global pandemic. Worldwide, more than 100 countries have imposed severe restrictions regarding freedom of movement amongst their citizens in a bid to slow the spread of the virus. These restrictions, which are part of a set of non-pharmaceutical interventions, have recently been classified by the Oxford COVID-19 Government Response Tracker (OxCGRT) team and a nominal index measure has been defined for use by the wider international community. We address the use of this index measure to establish the degree and characteristics of control of the transmission rate of the virus within a representative sample of countries in the World and states in the United States of America. Methods Country specific, Susceptible-Infected-Recovered-Deaths (SIRD) models with latent dynamics were constructed using publicly available data for 23 countries and 25 states of the United States of America. Each of the models were linearised and classical frequentist error propagation was applied to them individually. The time varying, observable model parameters were extracted for each day that data was made available. The OxCGRT stringency index, p, was used to regress against these model parameters. The regression of the transmission rate as a function of p in each locale was through a linear parameter _s. In addition, macroscopic indices from the World Bank were used to explore inter-country variation in the measured parameters. Results The world average was _s=0.01 (95% CI 0.0102 - 0.0112) with an ensemble standard deviation of 0.0017 (95% C.I. 0.0014 - 0.0021), strongly indicating a universal behavior. While lockdown measures have been successful in curbing the spread, our study indicates that removing them too swiftly will result in the resurgence of the spread within one to two months. Reducing the stringency index by 10 will delay reaching the apex by about 6 months, where reducing it by 20 will delay by only four months. During the post-lockdown period it is essential to increase _s. For the system to remain sub-critical, the rate with which _s increases should outpace that of the decrease of the stringency index. The spread of the virus is found to be insensitive to the Gini index and other socio-economic indexes. The typical adjustment time to see the effects of control varied between 1.49 days for Peru and 38.09 days for Sweden. In the United States, the typical adjustment time to see the effects of control varied between 1.41 days for Colorado to 15.91 days for Ohio. Interpretation Given the measured characterisations of each locale, the effects of any change in non-pharmaceutical intervention may be anticipated and predictions can be made regarding the possible case load which is specific to that environment. This is accomplished by specifying an acceptable level of transmission, {beta}_f, given the prevailing economic and social constraints which uniquely determines an overall stringency of intervention level p. As a policy maker, there are possible intervention combinations to choose from and a combination must be selected that achieves p or greater.


title: A novel RNA virus, Macrobrachium rosenbergii Golda virus (MrGV), linked to mass mortalities of the larval giant freshwater prawn in Bangladesh

text: Mass mortalities of the larval stage of the giant freshwater prawn, Macrobrachium rosenbergii, have been occurring in Bangladesh since 2011. Mortalities can reach 100% and have resulted in an 80% decline in the number of hatcheries actively producing M. rosenbergii. To investigate a causative agent for the mortalities, a disease challenge was carried out using infected material from a hatchery experiencing mortalities. Moribund larvae from the challenge were prepared for metatranscriptomic sequencing. De novo virus assembly revealed a 29 kb single-stranded positive-sense RNA virus with similarities in key protein motif sequences to yellow head virus (YHV), an RNA virus that causes mass mortalities in marine shrimp aquaculture, and other viruses in the Nidovirales order. Primers were designed against the novel virus and used to screen cDNA from larvae sampled from hatcheries in the South of Bangladesh from two consecutive years. Larvae from all hatcheries screened from both years were positive by PCR for the novel virus, including larvae from a hatchery that at the point of sampling appeared healthy, but later experienced mortalities. These screens suggest that the virus is widespread in M. rosenbergii hatchery culture in southern Bangladesh, and that early detection of the virus can be achieved by PCR. The hypothesised protein motifs of MrGV suggest that it is likely to be a new species within the Nidovirales order. Biosecurity measures should be taken in order to mitigate global spread through the movement of post-larvae within and between countries, which has previously been linked to other virus outbreaks in crustacean aquaculture.


title: A pattern categorization of CT findings to predict outcome of COVID-19 pneumonia

text: Purpose As global healthcare system is overwhelmed by novel coronavirus disease (COVID-19), early identification of risks of adverse outcomes becomes the key to optimize management and improve survival. This study aimed to provide a CT-based pattern categorization to predict outcome of COVID-19 pneumonia. Methods 165 patients with COVID-19 (91 men, 4-89 years) underwent chest CT were retrospectively enrolled. CT findings were categorized as Pattern0 (negative), Pattern1 (bronchopneumonia), Pattern2 (organizing pneumonia), Pattern3 (progressive organizing pneumonia) and Pattern4 (diffuse alveolar damage). Clinical findings were compared across different categories. Time-dependent progression of CT patterns and correlations with clinical outcomes, i.e. discharge or adverse outcome (admission to ICU, requiring mechanical ventilation, or death), with pulmonary sequelae (complete absorption or residuals) on CT after discharge were analyzed. Results Of 94 patients with outcome, 81(86.2%) were discharged, 3(3.2%) were admitted to ICU, 4(4.3%) required mechanical ventilation, 6(6.4%) died. 31(38.3%) had complete absorption at median day 37 after symptom-onset. Significant differences between pattern-categories were found in age, disease-severity, comorbidity and laboratory results (all P<0.05). Remarkable evolution was observed in Pattern0-2 and Pattern3-4 within 3 and 2 weeks after symptom-onset, respectively; most of patterns remained thereafter. After controlling for age, CT pattern significantly correlated with adverse outcomes (Pattern4 vs. Pattern0-3 [reference]; hazard-ratio[95%CI], 18.90[1.91-186.60], P=0.012). CT pattern (Pattern3-4 vs. Pattern0-2 [reference]; 0.26[0.08-0.88], P=0.030) and C-reactive protein (>10 vs. [≤]10mg/L [reference]; 0.31[0.13-0.72], P=0.006) were risk-factors associated with pulmonary residuals. Conclusion CT pattern categorization allied with clinical characteristics within 2 weeks after symptom-onset would facilitate early prognostic stratification in COVID-19 pneumonia.


title: A Multi-Task Pipeline with Specialized Streams forClassification and Segmentation of InfectionManifestations in COVID-19 Scans

text: We are concerned with the challenge of coronavirus disease (COVID-19) detection in chest X-ray and Computed Tomography (CT) scans, and the classification and segmentation of related infection manifestations. Even though it is arguably not an established diagnostic tool, using machine learning-based analysis of COVID-19 medical scans has shown the potential to provide a preliminary digital second opinion. This can help in managing the current pandemic, and thus has been attracting significant research attention. In this research, we propose a multi-task pipeline that takes advantage of the growing advances in deep neural network models. In the first stage, we fine-tuned an Inception-v3 deep model for COVID-19 recognition using multi-modal learning, i.e., using X-ray and CT scans. In addition to outperforming other deep models on the same task in the recent literature, with an attained accuracy of 99.4%, we also present comparative analysis for multi-modal learning against learning from X-ray scans alone. The second and the third stages of the proposed pipeline complement one another in dealing with different types of infection manifestations. The former features a convolutional neural network architecture for recognizing three types of manifestations, while the latter transfers learning from another knowledge domain, namely, pulmonary nodule segmentation in CT scans, to produce binary masks for segmenting the regions corresponding to these manifestations. Our proposed pipeline also features specialized streams in which multiple deep models are trained separately to segment specific types of infection manifestations, and we show the significant impact that this framework has on various performance metrics. We evaluate the proposed models on widely adopted datasets, and we demonstrate an increase of approximately 4% and 7% for dice coefficient and mean intersection-over-union (mIoU), respectively, while achieving 60% reduction in computational time, compared to the recent literature.


title: The rush for land and agricultural investment in Ethiopia: What we know and what we are missing

text: More than a decade has passed since the triple crises of food, energy and finance in the period 2007-2008. Those events turned global investor interest to agriculture and its commodities and thereafter the leasing of tens of millions of hectares of land. This article reviews and synthesizes the available evidence regarding the agricultural investments that have taken place in Ethiopia since that time. We use a systematic review approach to identify literature from theWeb of Science and complement that with additional literature found via Google Scholar. Qualitative and quantitative methods are used to analyze the available literature. In so doing, we raise questions of data quality, by analyzing the evidence base used by many studies (the Land Matrix database) and compare it with data we obtained from the Government of Ethiopia. We find that while the Land Matrix is the largest available database, it appears to present only a fraction of the reality. In critically assessing the literature, we identify areas that have been under-researched or are missing from the literature, namely assessments of gendered impacts, the role of diaspora and domestic investors, interdisciplinary approaches (e.g., integrating climate change, biodiversity, and water), and studies that move beyond technical assessment, such as looking at the impacts on traditional knowledge and socio-cultural systems.


title: Repurposing Didanosine as a Potential Treatment for COVID-19 Using Single-Cell RNA Sequencing Data

text: As of today (7 April 2020), more than 81,000 people around the world have died from the coronavirus disease 19 (COVID-19) pandemic. There is no approved drug or vaccine for COVID-19, although more than 10 clinical trials have been launched to test potential drugs. In an urgent response to this pandemic, I developed a bioinformatics pipeline to identify compounds and drug candidates to potentially treat COVID-19. This pipeline is based on publicly available single-cell RNA sequencing (scRNA-seq) data and the drug perturbation database “Library of Integrated Network-Based Cellular Signatures” (LINCS). I developed a ranking score system that prioritizes these drugs or small molecules. The four drugs with the highest total score are didanosine, benzyl-quinazolin-4-yl-amine, camptothecin, and RO-90-7501. In conclusion, I have demonstrated the utility of bioinformatics for identifying drugs than can be repurposed for potentially treating COVID-19 patients.


title: A deeper look at COVID-19 CFR: health care impact and roots of discrepancy

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


title: Delayed-Phase Thrombocytopenia in Patients of Coronavirus Disease 2019 (COVID-19)

text: The pandemic COVID19 pneumonia has engulfed the entire world. Hematopoietic system can also be affected by COVID19. Thrombocytopenia at admission was prevalent, while late phase or delayed phase thrombocytopenia is obscure. This retrospective case series analyzed patients with COVID19 at the Union Hospital, Wuhan, China, from January 25th to March 9th, 2020. Analysis began on March 11th, 2020. COVID19 associated delayed phase thrombocytopenia was occurred in 11.8% percent of enrolled patients. The delayed phase thrombocytopenia in COVID19 is prone to develop in elderly patients or patients with low lymphocyte count on admission. The delayed-phase thrombocytopenia is significantly associated with increased length of hospital stay and higher ICU admission rate. Delayed phase nadir platelet counts demonstrated a high and significantly negative linear correlation with B cell percentages and serum IL 6 levels. We also presented bone marrow aspiration pathology of three patients with delayed phase thrombocytopenia, showing impaired maturation of megakaryocytes. We speculated that the delayed phase platelet destruction might be mediated by antibodies, and suggest immunoregulatory treatment in severe patients to improve outcomes. Besides, clinicians need to pay attention to the delayed phase thrombocytopenia especially at 3 to 4 weeks after symptom onset.


title: COVID 19: Effect on leading pharmaceutical stocks listed with NSE

text: The purpose of this study is to examine how Covid 19 outbreak has affected leading pharmaceutical stocks listed with the National Stock Exchange of India. We have selected ten leading pharmaceutical companies listed with NSE, and the selection was purely based on the market capitalization of the companies. The general hypothecation of this study was the pharmaceutical stocks will move against the general market trend (contrarian effect). The study period was classified in to pre-crisis period and Covid 19 crisis period. The data consists of 123 daily price observations of the selected 10 pharmaceutical companies. The period of study is ranging from 3rdSeptember 2019 to 28thFebruary 2020. The results reported that momentum effect is persisting with pharmaceutical stocks as the pharmaceutical stocks are moving in accordance with the general benchmarking index. Only two com-panies, namely Aurobindo Pharma Ltd and Lupin Ltd reported with varied return trend during the study period. This study also signifies that companies like Sun Pharma, Cipla, Glenmark with strong brand reputation were seems to be sustaining in the crisis period in spite of the general falling market trend. This paper is strongly urge the need for backward integration and enhanced research and development activities to Indian Pharmaceutical sector for ensuring their sustainable long-run operations.


title: Enzyme immunoassay for SARS-CoV-2 antibodies in dried blood spot samples: A minimally-invasive approach to facilitate community- and population-based screening

text: Background Serological testing for SARS-CoV-2 IgG antibodies is needed to document the community prevalence and distribution of the virus, particularly since many individuals have mild symptoms and cannot access molecular diagnostic testing of naso-pharyngeal swabs. However, the requirement for serum/plasma limits serological testing to clinical settings where it is feasible to collect and process venous blood. To address this problem we developed a serological test for SARS-CoV-2 IgG antibodies that requires only a single drop of capillary whole blood, collected from a simple finger prick and dried on filter paper (dried blood spot, DBS). Methods Enzyme linked immunosorbent assay (ELISA) was optimized to detect SARS-CoV-2 IgG antibodies against the receptor-binding domain (RBD) of the spike protein. DBS samples were eluted overnight and transferred to a 96-well plate coated with antigen, and anti-human IgG-HRP was used to generate signal in proportion to bound antibody. DBS samples spiked with anti-SARS IgG antibody, and samples from known positive and negative cases, were compared to evaluate assay performance. Results Analysis of samples with known concentrations of anti-SARS IgG produced the expected pattern of dose-response. Optical density (OD) values were significantly elevated for known positive cases in comparison with samples from unexposed individuals. Discussion DBS ELISA provides a minimally-invasive alternative to venous blood collection that combines the convenience of sample collection in the home or non-clinical setting with the accuracy of ELISA in the lab. Serological testing for SARS-CoV-2 IgG antibodies in DBS samples should facilitate research across a wide range of community- and population-based settings on seroprevalence, predictors and duration of antibody responses, as well as correlates of protection from reinfection, each of which is critically important for pandemic control.


title: Global between-countries variance in SARS-CoV-2 mortality is driven by reported prevalence, age distribution, and case detection rate

text: Objective: To explain the global between-countries variance in number of deaths per million citizens (nDpm) and case fatality rate (CFR) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design: Systematic analysis. Data sources: Worldometer, European Centre for Disease Prevention and Control, United Nations Main outcome measures: The explanators of nDpm and CFR were mathematically hypothesised and tested on publicly-available data from 88 countries with linear regression models on May 1st 2020. The derived explanators - age-adjusted infection fatality rate (IFRadj) and case detection rate (CDR) - were estimated for each country based on a SARS-CoV-2 model of China. The accuracy and agreement of the models with observed data was assessed with R2 and Bland-Altman plots, respectively. Sensitivity analyses involved removal of outliers and testing the models at five retrospective and two prospective time points. Results: Globally, IFRadj estimates varied between countries, ranging from below 0.2% in the youngest nations, to above 1.3% in Portugal, Greece, Italy, and Japan. The median estimated global CDR of SARS-CoV-2 infections on April 16th 2020 was 12.9%, suggesting that most of the countries have a much higher number of cases than reported. At least 93% and up to 99% of the variance in nDpm was explained by reported prevalence expressed as cases per million citizens (nCpm), IFRadj, and CDR. IFRadj and CDR accounted for up to 97% of the variance in CFR, but this model was less reliable than the nDpm model, being sensitive to outliers (R2 as low as 67.5%). Conclusions: The current differences in SARS-CoV-2 mortality between countries are driven mainly by reported prevalence of infections, age distribution, and CDR. The nDpm might be a more stable estimate than CFR in comparing mortality burden between countries.


Ten gentle reminders to social workers in the pandemic


title: Stachyose increases intestinal barrier through Akkermansia muciniphila and reduces gut inflammation in germ-free mice after human fecal transplantation

text: Early life is a crucial period for the development of the intestinal microbiota and is related to the body's immunity. Yet research is lacking regarding the effect of stachyose on infants gut microbiomes at this stage and the mechanism is not clear. Therefore, in this experiment, feces samples collected from infants were transplanted into germ-free mice, to explore the effect of stachyose on the intestinal microbiota and host gut barrier. We found that stachyose promoted the relative abundance of A. muciniphila in human feces; enhanced the symbiotic relationships of A. muciniphila; increased the short-chain fatty acid level, and secretory immunoglobulin A level; reduced the levels of lipopolysaccharide, IL-1, IL-17 and TNF-α through downregulated the expression of NF-κB; increased expression of tight junction proteins (occludin and ZO-1) and goblet cell through A. muciniphila. The intake of stachyose is conducive to promoting the proliferation of beneficial bacteria and enhancing the intestinal barrier in germ-free mice. This research provides a theoretical basis for the use of prebiotics to improve intestinal microbiota and barrier in humans.


title: New York senator convenes virtual meeting on opioids

text: Last week, New York State Sen Pete Harckham, a Democrat from the Hudson Valley who chairs the Joint Senate Task Force on Opioids, held a virtual conference to discuss the challenges faced by substance use disorder (SUD) treatment programs during the pandemic


title: Magnitude and kinetics of anti-SARS-CoV-2 antibody responses and their relationship to disease severity

text: Background: SARS-CoV-2 infection can be detected indirectly by measuring the host immune response. Anti-viral antibody concentrations generally correlate with host protection and viral neutralization, but in rare cases, antibodies can promote disease progression. Elucidation of the kinetics and magnitude of the SARS-CoV-2 antibody response is essential to understand the pathogenesis of COVID-19 and identify potential therapeutic targets. Methods: Sera (n=533) from patients with RT-PCR confirmed COVID-19 (n=153) were tested using a high-throughput quantitative IgM and IgG assay that detects antibodies to the spike protein receptor binding domain and nucleocapsid protein. Individual and serial samples covered the time of initial diagnosis, during the disease course, and following recovery. We evaluated antibody kinetics and correlation between magnitude of the response and disease severity. Results: Patterns of SARS-CoV-2 antibody production varied considerably. Among 52 patients with 3 or more serial specimens, 44 (84.6%) and 42 (80.8%) had observed IgM and IgG seroconversion at a median of 8 and 10 days, respectively. Compared to those with milder disease, peak measurements were significantly higher for patients admitted to the intensive care unit for all time intervals between 6 and 20 days for IgM, and all intervals after 5 days for IgG. Conclusions: High sensitivity assays with a robust dynamic range provide a comprehensive picture of host antibody response to SARS-CoV-2. IgM and IgG responses were significantly higher in patients with severe than mild disease. These differences may affect strategies for seroprevalence studies, therapeutics and vaccine development.


title: Modeling COVID-19 Growing Trends to Reveal the Differences in the Effectiveness of Non-Pharmaceutical Interventions among Countries in the World

text: Objective: We hypothesize that COVID-19 case growth data reveals the efficacy of NPIs. In this study, we conduct a secondary analysis of COVID-19 case growth data to compare the differences in the effectiveness of NPIs among 16 representative countries in the world. Methods: This study leverages publicly available data to learn patterns of dynamic changes in the reproduction rate for sixteen countries covering Asia, Europe, North America, South America, Australia, and Africa. Furthermore, we model the relationships between the cumulative number of cases and the dynamic reproduction rate to characterize the effectiveness of the NPIs. We learn four levels of NPIs according to their effects in the control of COVID-19 growth and categorize the 16 countries into the corresponding groups. Results: The dynamic changes of the reproduction rate are learned via linear regression models for all of the studied countries, with the average adjusted R-squared at 0.96 and the 95% confidence interval as [0.94 0.98]. China, South Korea, Argentina, and Australia are at the first level of NPIs, which are the most effective. Japan and Egypt are at the second level of NPIs, and Italy, Germany, France, Netherlands, and Spain, are at the third level. The US and UK have the most inefficient NPIs, and they are at the fourth level of NPIs. Conclusions: COVID-19 case growth data provides evidence to demonstrate the effectiveness of the NPIs. Understanding the differences in the efficacy of the NPIs among countries in the world can give guidance for emergent public health events.


title: Risk factors related to hepatic injury in patients with corona virus disease 2019

text: Aims: Corona virus disease 2019 (COVID-19) has rapidly become the most severe public health issue all over the world. Despite respiratory symptoms, hepatic injury has also been observed in clinical settings. This study aimed to investigate the risk factors involved with hepatic injury in the patients with COVID-19. Methods: A total of 85 hospitalized patients who were diagnosed with COVID-19 in Beijing Youan Hospital were retrospectively analyzed. According to liver function, they were divided into ALT normal group (n=52) and ALT elevation group (n=33). Clinical features and laboratory data were compared between the two groups. The independent risk factors for liver injury were analyzed. Results: There were 33 patients with hepatic injury in our study, accounting for 38.8% (33/85). The patients in ALT elevation group were older than those in ALT normal group. The levels of lactic acid, CRP, myoglobin, and neutrophils were significantly higher in ALT elevation group. The lymphocytes and albumin were significantly lower in ALT elevation group. The proportion of severe and critical patients in ALT elevation group was significantly higher. Multivariate logistic regression analysis showed CRP ≥20 mg/L and lymphocyte count< 1.1*10^9/L were independently related to hepatic injury. Conclusions: Lymphopenia and CRP may serve as the risk factors related to hepatic injury in patients with COVID-19, which might be related to inflammatory cytokine storm in liver injury. Early detection and timely treatment of hepatic injury in patients with COVID-19 are necessary.


title: Optimize Clinical Laboratory Diagnosis of COVID-19 from Suspect Cases by Likelihood Ratio of SARS-CoV-2 IgM and IgG antibody

text: Objective: To optimize clinical laboratory diagnosis of COVID-19 from suspect cases by Likelihood Ratio of SARS-CoV-2 IgM and IgG antibody. Methods: By reinterpreting the data in the article "Diagnostic Value of Combined Detection of Serum 2019 novel coronavirus IgM and IgG Antibodies in novel coronavirusin Infection", the positive likelihood ratio of IgM and IgG antibody in diagnosis of COVID-19 (nucleic acid positive patients) was calculated, and the posterior probability of IgM and IgG antibodies and their tandem detection to diagnose was finally calculated. Results: The positive likelihood ratios of single IgM and IgG antibody were 18.50 and 12.65 respectively, and the posterior probabilities were 90.18% and 86.26% respectively. However, the posterior probability of the two antibodies tandem detection is 99.15%, which can give clinicians quantitative confidence in the diagnosis of COVID-19 from suspected cases. According to the results of this study, combining the advantages and disadvantages of nucleic acid detection and antibody detection, the clinical pathway for clinicians to diagnose COVID-19 is found. Conclusion: For suspected cases, IgM and IgG antibody tests should be firstly done at the same time. If the antibody tests are all positive, COVID-19 can be confirmed. If not, nucleic acid detection (one or more times) is performed, and in extreme cases, high-throughput viral genome sequencing is performed.


title: SARS-CoV-2-specific antibody detection for sero-epidemiology: a multiplex analysis approach accounting for accurate seroprevalence

text: Background The COVID-19 pandemic demands detailed understanding of the kinetics of antibody production induced by infection with SARS-CoV-2. We aimed to develop a high throughput multiplex assay to detect antibodies to SARS-CoV-2 to assess immunity to the virus in the general population. Methods Spike protein subunits S1 and RBD, and Nucleoprotein were coupled to distinct microspheres. Sera collected before the emergence of SARS-CoV-2 (N=224), and of non-SARS-CoV-2 influenza-like illness (N=184), and laboratory-confirmed cases of SARS-CoV-2 infection (N=115) with various severity of COVID-19 were tested for SARS-CoV-2-specific concentrations of IgG. Results Our assay discriminated SARS-CoV-2-induced antibodies and those induced by other viruses. The assay obtained a specificity between 95.1 and 99.0% with a sensitivity ranging from 83.6-95.7%. By merging the test results for all 3 antigens a specificity of 100% was achieved with a sensitivity of at least 90%. Hospitalized COVID-19 patients developed higher IgG concentrations and the rate of IgG production increased faster compared to non-hospitalized cases. Conclusions The bead-based serological assay for quantitation of SARS-CoV-2-specific antibodies proved to be robust and can be conducted in many laboratories. Finally, we demonstrated that testing of antibodies against different antigens increases sensitivity and specificity compared to single antigen-specific IgG determination.


title: Deep Transfer Learning-based COVID-19 prediction using Chest X-rays

text: The novel coronavirus disease (COVID-19) is spreading very rapidly across the globe because of its highly contagious nature, and is declared as a pandemic by world health organization (WHO). Scientists are endeavoring to ascertain the drugs for its efficacious treatment. Because, till now, no full-proof drug is available to cure this deadly disease. Therefore, identifying COVID-19 positive people and to quarantine them, can be an effective solution to control its spread. Many machine learning and deep learning techniques are being used quite effectively to classify positive and negative cases. In this work, a deep transfer learning-based model is proposed to classify the COVID-19 cases using chest X-rays or CT scan images of infected persons. The proposed model is based on the ensembling of DenseNet121 and SqueezeNet1.0, which is named as DeQueezeNet. The model can extract the importance of various influential features from the X-ray images, which are effectively used to classify the COVID-19 cases. The performance study of the proposed model depicts its effectiveness in terms of accuracy and precision. A comparative study has also been done with the recently published works and it is observed the performance of the proposed model is significantly better.


title: Safety-Critical Control of Active Interventions for COVID-19 Mitigation

text: The world has recently undergone the most ambitious mitigation effort in a century, consisting of wide-spread quarantines aimed at preventing the spread of COVID-19. The use of influential epidemiological models of COVID-19 helped to encourage decision makers to take drastic non-pharmaceutical interventions. Yet, inherent in these models are often assumptions that the active interventions are static, e.g., that social distancing is enforced until infections are minimized, which can lead to inaccurate predictions that are ever evolving as new data is assimilated. We present a methodology to dynamically guide the active intervention by shifting the focus from viewing epidemiological models as systems that evolve in autonomous fashion to control systems with an "input" that can be varied in time in order to change the evolution of the system. We show that a safety-critical control approach to COVID-19 mitigation gives active intervention policies that formally guarantee the safe evolution of compartmental epidemiological models. This perspective is applied to current US data on cases while taking into account reduction of mobility, and we find that it accurately describes the current trends when time delays associated with incubation and testing are incorporated. Optimal active intervention policies are synthesized to determine future mitigations necessary to bound infections, hospitalizations, and death, both at national and state levels. We therefore provide means in which to model and modulate active interventions with a view toward the phased reopenings that are currently beginning across the US and the world in a decentralized fashion. This framework can be converted into public policies, accounting for the fractured landscape of COVID-19 mitigation in a safety-critical fashion.


Possible overlap of laboratory findings between patients with COVID-19 and substance use disorders


title: Covid-19 Pandemic Data Analysis and Forecasting using Machine Learning Algorithms

text: India reported its first case of covid-19 on 30th Jan 2020. Though we did not notice a significant rise in the number of cases in the month of February and like many other countries, this number escalated like anything from March 2020. This research paper will include analysis of covid-19 data initially at a global level and then drilled down to the scenario of India. Data is gathered from multiple data sources from several authentic government websites. The paper will also include analysis of various features like gender, geographical location, age using Python and Data Visualization techniques. Getting insights on Trend pattern and time series analysis will bring more clarity to the current scenario as analysis is totally on real-time data(till 19th June). Finally we will use some machine learning algorithms and perform predictive analytics of the near future scenario. We are using a sigmoid model to give an estimate of the day on which we can expect the number of active cases to reach its peak and also when the curve will start to flatten sigmoid model gives us a count of date which is a unique feature of analysis in this paper. We are also using certain feature engineering techniques to transfer data into logarithmic scale for better comparison removing any data extremities or outliers. Based on the predictions of the short-term interval, our model can be tuned to forecast long time intervals. Needless to mention there are a lot of factors responsible for the cases to come in the upcoming days. It depends on the people of the country and how strictly they obey the rules and restriction imposed by the Government.


title: ACE2 polymorphisms and individual susceptibility to SARS-CoV-2 infection: insights from an in silico study

text: The current SARS covid-19 epidemic spread appears to be influenced by ethnical, geographical and sex-related factors that may involve genetic susceptibility to diseases. Similar to SARS-CoV, SARS-CoV-2 exploits angiotensin-converting enzyme 2 (ACE2) as a receptor to invade cells, notably type II alveolar epithelial cells. Importantly, ACE2 gene is highly polymorphic. Here we have used in silico tools to analyze the possible impact of ACE2 single-nucleotide polymorphisms (SNPs) on the interaction with SARS-CoV-2 spike glycoprotein. We found that S19P (common in African people) and K26R (common in European people) were, among the most diffused SNPs worldwide, the only two SNPs that were able to potentially affect the interaction of ACE2 with SARS-CoV-2 spike. FireDock simulations demonstrated that while S19P may decrease, K26R might increase the ACE2 affinity for SARS-CoV-2 Spike. This finding suggests that the S19P may genetically protect, and K26R may predispose to more severe SARS-CoV-2 disease.


title: Engaging with global urban governance in the midst of a crisis

text: The COVID-19 pandemic crisis offers a chance for urban scholars to play an even more explicit role in shaping ‘global urban governance’. Recognizing this international political realm, and the fundamental role that information exchange plays within it, urban studies can help drive a more progressive and inclusive global urban imagination.


title: Systematic review and meta-analysis of predictive symptoms and comorbidities for severe COVID-19 infection

text: Background/introduction COVID−19, a novel coronavirus outbreak starting in China, is now a rapidly developing public health emergency of international concern. The clinical spectrum of COVID−19 disease is varied, and identifying factors associated with severe disease has been described as an urgent research priority. It has been noted that elderly patients with pre-existing comorbidities are more vulnerable to more severe disease. However, the specific symptoms and comorbidities that most strongly predict disease severity are unclear. We performed a systematic review and meta-analysis to identify the symptoms and comorbidities predictive of COVID−19 severity. Method This study was prospectively registered on PROSPERO. A literature search was performed in three databases (MEDLINE, EMBASE and Global Health) for studies indexed up to 5th March 2020. Two reviewers independently screened the literature and both also completed data extraction. Quality appraisal of studies was performed using the STROBE checklist. Random effects meta-analysis was performed for selected symptoms and comorbidities to identify those most associated with severe COVID−19 infection or ICU admission. Results Of the 2259 studies identified, 42 were selected after title and abstract analysis, and 7 studies (including 1813 COVID−19 patients) were chosen for inclusion. The ICU group were older (62.4 years) compared to the non-ICU group (46 years), with a significantly higher proportion of males (67.2% vs. 57.1%, p=0.04). Dyspnoea was the only significant symptom predictive for both severe disease (pOR 3.70, 95% CI 1.83 − 7.46) and ICU admission (pOR 6.55, 95% CI 4.28 − 10.0). Notwithstanding the low prevalence of COPD in severe disease and ICU-admitted groups (4.5% and 9.7%, respectively), COPD was the most strongly predictive comorbidity for both severe disease (pOR 6.42, 95% CI 2.44 − 16.9) and ICU admission (pOR 17.8, 95% CI 6.56 − 48.2). Cardiovascular disease and hypertension were also strongly predictive for both severe disease and ICU admission. Those with CVD and hypertension were 4.4 (95% CI 2.64 − 7.47) and 3.7 (95% CI 2.22 − 5.99) times more likely to have an ICU admission respectively, compared to patients without the comorbidity. Conclusions Dyspnoea was the only symptom strongly predictive for both severe disease and ICU admission, and could be useful in guiding clinical management decisions early in the course of illness. When looking at ICU-admitted patients, who represent the more severe end of the spectrum of clinical severity, COPD patients are particularly vulnerable, and those with cardiovascular disease and hypertension are also at a high-risk of severe illness. To aid clinical assessment, risk stratification, efficient resource allocation, and targeted public health interventions, future research must aim to further define those at high-risk of severe illness with COVID−19.


COVID 19. A Flash in Mid-March


title: CoViD19 Meta heuristic optimization based forecast method on time dependent bootstrapped data

text: A compounded method, exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques, is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the CoViD19 virus in Italy. Futures lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.


title: CliqueSNV: An Efficient Noise Reduction Technique for Accurate Assembly of Viral Variants from NGS Data

text: Rapidly evolving RNA viruses continuously produce viral minority variants following infection that can quickly spread and become dominant variants if they are drug-resistant or can better evade the immune system. Early detection of minority viral variants may help to promptly change a patient’s treatment plan preventing potential disease complications. Next-generation sequencing (NGS) technologies used for viral testing have recently gained popularity in commercial pipelines and can efficiently identify minority variants. Unfortunately, NGS data require nontrivial computational analyses to eliminate sequencing noise and current computational haplotyping methods do not adequately address this challenging task. To overcome this limitation, we developed CliqueSNV, which finds statistically linked mutations from the same haplotypes to detect minor mutations with an abundance below the sequencing error rates. We compared the performance of CliqueSNV with five state-of-the-art methods with six benchmarks, including three Illumina and one PacBio in vitro sequencing datasets.We show that CliqueSNV can assemble viral haplotypes with frequencies as low as 0.1%. CliqueSNV haplotype predictions were the closest to the experimental viral populations and showed up to a 2.94-fold improvement on Illumina data and a 19.3-fold improvement on PacBio data.


title: A preliminary study on the reproductive toxicity of GS-5734 on male mice

text: The authors have withdrawn their manuscript given that some conclusions need more research and data support. In addition, they intend to improve the experimental design to make the research more rigorous. If you have any questions, please contact the corresponding author.


title: Current treatment protocol for COVID-19 in India

text: The whole world is now facing the battle against the severe and dangerous pandemic COVID-19, which is not only physically harming, but also mentally disturbing all the people because of the unceasingly escalating number of affected patients and deaths globally In India, the containment strategies constitute in identifying, tracing-contacts, quarantine, social distancing, and following other health advisories The current treatment protocols include real-time PCR test and Point-of-Care molecular diagnostic assays for its diagnosis;some states in India have begun the pool testing Hydroxychloroquine (HCQ) is being recommended as chemoprophylaxis drug for asymptomatic healthcare personnel handling of COVID-19 cases, while the frontline workers, asymptomatic contacts of the confirmed cases, and hydroxychloroquine-azithromycin combination for patients with serious sickness India has also launched ‘ArogyaSetu’ mobile-application for tracking the movements of the citizens and has also commenced convalescent plasma therapy to combat the deadly COVID-19 This timely article is a report on the current situation of COVID-19 in India The discussion can throw light on the potential of a developing country such as India to deal with the pandemic and some of these can be helpful in adverse circumstances in the future


title: Conditions for a second wave of COVID-19 due to interactions between disease dynamics and social processes

text: In May 2020, many jurisdictions around the world began lifting physical distancing restrictions against the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), giving rise to concerns about a possible second wave of coronavirus disease 2019 (COVID-19). These restrictions were imposed as a collective population response to the presence of COVID-19 in communities. However, lifting restrictions is also a population response to their socio-economic impacts, and is expected to increase COVID-19 cases, in turn. This suggests that the COVID-19 pandemic exemplifies a coupled behaviour-disease system. Here we develop a minimal mathematical model of the interaction between social support for school and workplace closure and the transmission dynamics of SARS-CoV-2. We find that a second wave of COVID-19 occurs across a broad range of plausible model input parameters, on account of instabilities generated by behaviour-disease interactions. We conclude that second waves of COVID-19--should they materialize--can be interpreted as the outcomes of nonlinear interactions between disease dynamics and population behaviour.


title: Presence and vitality of SARS-CoV-2 virus in wastewaters and rivers

text: Wastewater-based epidemiology has been proposed to monitor the diffusion and trend of SARS-CoV-2 pandemic. In the present study, raw and treated samples from three wastewater treatment plants, and two river samples characterized the Milano Metropolitan Area, Italy, were surveyed for SARS-CoV-2 RNA positivity to real time PCR and infectiveness. Moreover, whole genome sequencing and phylogenetic analysis of isolated strains was performed. Raw wastewater samples resulted positive to PCR amplification, while treated water samples were always negative (four and two samples, respectively, sampled in two dates). Moreover, the rate of positivity in raw wastewater samples decreased after eight days, in congruence with the epidemiological trend estimated for the interested provinces. Virus infectiveness was always not significant, indicating the effectiveness of wastewater treatments, or the natural decay of viral vitality, which implied the absence of significant risk of infection from wastewaters. Samples from receiving rivers (two sites, sampled in the same dates as wastewaters) showed in some cases a positivity to PCR amplification, probably due to non-treated discharges, or the combined sewage overflows. Nevertheless, also for rivers vitality was negligible, indicating the absence of sanitary risks. Phylogenetic analysis of genome indicated that the isolated virus belongs to the most spread strain present in Europe and similar to another strain found in Lombardy.


title: The benefits of peer transparency in safe workplace operation post pandemic lockdown

text: The benefits, both in terms of productivity and public health, are investigated for different levels of engagement with the test, trace and isolate procedures in the context of a pandemic in which there is little or no herd immunity. Simple mathematical modelling is used in the context of a single, relatively closed workplace such as a factory or back-office where, in normal operation, each worker has lengthy interactions with a fixed set of colleagues. A discrete-time SEIR model on a fixed interaction graph is simulated with parameters that are motivated by the recent COVID-19 pandemic in the UK during a post-peak phase, including a small risk of viral infection from outside the working environment. Two kinds of worker are assumed, transparents who regularly test, share their results with colleagues and isolate as soon as a contact tests positive for the disease, and opaques who do none of these. Moreover, the simulations are constructed as a "playable model" in which the transparency level, disease parameters and mean interaction degree can be varied by the user. The model is analysed in the continuum limit. All simulations point to the double benefit of transparency in maximising productivity and minimising overall infection rates. Based on these findings, public policy implications are discussed on how to incentivise this mutually beneficial behaviour in different kinds of workplace, and simple recommendations are made.


title: Psychophysical Olfactory Findings of Mild-to-moderate COVID-19 Patients: Preliminary Report.

text: Since the onset of the COVID-19 infection, many patients reported sudden loss of smell (SLS). However, due to the lack of psychophysical testings, it remains difficult to know if these patients really have hyposmia or anosmia. Our group investigated the prevalence of anosmia and hyposmia in 28 COVID-19 patients and the potential association with nasal complaints.


title: COVID-19 pneumonia in an Iraqi pregnant woman with preterm delivery

text: Coronavirus disease 2019 (COVID-19) is a highly infectious disease due to the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV2). Vertical transmission and clinical presentation of COVID-19 in pregnancy is still obscure. Additionally, the potential hazard of COVID-19 in pregnancy on the fetus and post-delivery risk for the neonate remain under investigations. Patient concern: A young-aged Asian pregnant woman with 28 weeks of gestation presented with fever, dyspnoea, headache, and joint pain with decreased fetal movement for about one week. Diagnosis: The patient was diagnosed with COVID-19 pneumonia. Interventions: The patient was referred to the quarantine sector and was treated with chloroquine orally, intravenous fluid and other supportive treatment. Outcomes: After one week of treatment, the patient improved. Seventeen days after admission to hospital and at 30 weeks of gestation, she started vaginal preterm delivery of a viable healthy neonate with negative COVID-19 test for two occasions. Lessons: COVID-19 pneumonia during pregnancy presents with similar clinical presentation of non-pregnant women. COVID-19 pneumonia during pregnancy increases the risk of preterm labour without evidence of vertical transmission.


title: A review novel coronavirus

text: Coronaviruses (CoVs), incorporated positive-sense RNA diseases, are depicted by the club-like spikes that adventure from their surface, an abnormally huge RNA genome, and a specific replication technique. CoVs cause a selection of diseases in mammals and birds ranging from enteritis in cows and pigs and upper respiratory sickness in chickens too possibly deadly human respiratory diseases. Here, we provide a quick presentation to CoVs talking about their replication and pathogenicity, and current avoidance and treatment techniques. We likewise mention the episodes of the profoundly pathogenic severe acute respiratory syndrome CoV (SARS-CoV) and thus the recently identify Middle Eastern respiratory syndrome CoV (MERS-CoV).


title: Intention to participate in a COVID-19 vaccine clinical trial and to get vaccinated against COVID-19 in France during the pandemic

text: Background: The world is facing the COVID-19 pandemic. Development of vaccine is challenging. Aim: To determine the proportion of people who intend to get vaccinated against COVID-19 in France or to participate in a vaccine clinical trial. Methods: We conducted an anonymous on-line survey from the 26th of March to the 20th of April 2020. Primary endpoints were the intention to get vaccinated against COVID-19 if a vaccine was available or participate in a vaccine clinical trial. Results: Three thousand two hundred and fifty nine individuals answered the survey; women accounted for 67.4 % of the responders, 670 (20.6 %) were under 30 years of age, 1,502 (46.1 %) between 30-49 years, 803 (24.6 %) between 50-64 years, 271 (8.3%) between 65-80 years, 13 (0.4%) over 80 years of age. According to their statements, 2.512 participants (77.6%, 95 % CI 76.2-79 %) will certainly or probably agree to get vaccinated against COVID-19. Older age, male gender, fear about COVID-19, being healthcare workers and individual perceived risk were associated with COVID-19 vaccine acceptance Vaccine hesitancy was associated with a decrease in COVID-19 vaccine acceptance. One thousand and five hundred and fifty responders (47.6 % 95 % CI 45.9-49.3 %) will certainly or probably agree to participate in a COVID-19 vaccine clinical trial. Conclusions and Relevance: Nearly 75 % and 48 % of the survey responders were likely to accept vaccination or participation in a clinical trial against COVID-19. Vaccine hesitancy will be the major barrier to COVID-19 vaccine uptake.


title: Higher pharyngeal epithelial gene expression of Angiotensin-Converting Enzyme-2 in upper respiratory infection patients

text: We analyzed the expression of ACE2 in pharyngeal epithelium and examined its relationship with clinical features and serological parameters in the upper respiratory infection (URI) patients. The expression of ACE2 were significantly higher in URI patients than in healthy controls individuals, and positively correlated with age and body temperature.


COVID-19: Komorbiditäten prädisponieren für schweren Verlauf


title: A retrospective study of the clinical characteristics of COVID-19 infection in 26 children

text: Background: The outbreak of novel coronavirus pneumonia in China began in December 2019. Studies on novel coronavirus disease (COVID-19) were less based on pediatric patients. This study aimed to reveal the clinical characteristics of COVID-19 in children. Method: This study retrospectively analyzed the clinical symptoms, laboratory results, chest CT, and treatment of children with laboratory-confirmed COVID-19(ie, with samples that were positive for 2019 novel coronavirus[2019-nCoV]) who were admitted to Shenzhen Center of National Infectious Disease Clinical Medical Research from January 16 to February 8, 2020. Result: Nine patients had no obvious clinical symptom. 11 patients developed fever. Other symptoms, including cough(in eleven of seventeen patients), rhinorrhea(in two), diarrhea(in two), vomiting(in two), were also observed. A small minority of patients had lymphocytopenia. Alanine transaminase or transaminase increased in three cases. According to chest CT scan, 11 patients showed unilateral pneumonia, 8 patients had no pulmonary infiltration. No serious complications such as acute respiratory syndrome and acute lung injury occurred in all patients. Conclusion: The clinical characteristics of 2019-nCoV infection in children were different from adult. The overall condition of children were mild and have a good prognosis.


title: Reduced expression of TCF7L2 in adipocyte impairs glucose tolerance associated with decreased insulin secretion, incretins levels and lipid metabolism dysregulation in male mice

text: Transcription factor 7-like 2 (TCF7L2) is a downstream effector of the Wnt/beta-catenin signalling pathway and its expression is critical for adipocyte development. The precise role of TCF7L2 in glucose and lipid metabolism in adult adipocytes remains to be defined. Here, we aim to investigate how changes in TCF7L2 expression in mature adipocytes affect glucose homeostasis. Tcf7l2 was selectively ablated from mature adipocytes in C57BL/6J mice using an adiponectin promoter-driven Cre recombinase to recombine alleles floxed at exon 1 of the Tcf7l2 gene. Mice lacking Tcf7l2 in mature adipocytes displayed normal body weight. Male mice exhibited normal glucose homeostasis at eight weeks of age. Male heterozygote knockout mice (aTCF7L2het) exhibited impaired glucose tolerance (AUC increased 1.14 ± 0.04 -fold, p=0.03), as assessed by intraperitoneal glucose tolerance test, and changes in fat mass at 16 weeks (increased by 1.4 ± 0.09-fold, p=0.007). Homozygote knockout mice exhibited impaired oral glucose tolerance at 16 weeks of age (AUC increased 2.15 ± 0.15-fold, p=0.0001). Islets of Langerhans exhibited impaired glucose-stimulated insulin secretion in vitro (decreased 0.54 ± 0.13-fold aTCF7L2KO vs control, p=0.02), but no changes in in vivo glucose-stimulated insulin secretion. Female mice in which one or two alleles of the Tcf7l2 gene was knocked out in adipocytes displayed no changes in glucose tolerance, insulin sensitivity or insulin secretion. Plasma levels of glucagon-like peptide-1 and gastric inhibitory polypeptide were lowered in knockout mice (decreased 0.57 ± 0.03-fold and 0.41 ± 0.12-fold, p=0.04 and p=0.002, respectively), whilst plasma free fatty acids and Fatty Acid Binding Protein 4 circulating levels were increased by 1.27 ± 0.07 and 1.78 ± 0.32-fold, respectively (p=0.05 and p=0.03). Mice with biallelic Tcf7l2 deletion exposed to high fat diet for 9 weeks exhibited impaired glucose tolerance (p=0.003 at 15 min after glucose injection) which was associated with reduced in vivo glucose-stimulated insulin secretion (decreased 0.51 ± 0.03-fold, p=0.02). Thus, our data indicate that loss of Tcf7l2 gene expression in adipocytes leads to impairments on metabolic responses which are dependent on gender, age and nutritional status. Our findings further illuminate the role of TCF7L2 in the maintenance of glucose homeostasis.


title: Ascertainment rate of novel coronavirus disease (COVID-19) in Japan

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


title: Half of children entitled to free school meals do not have access to the scheme during the COVID-19 lockdown in the UK.

text: Objectives To investigate access to free school meals (FSM) among eligible children, to describe factors associated with uptake and investigate whether receiving FSM was associated with measures of food insecurity in the UK using the COVID-19 wave of the UK Household Longitudinal Study (UKHKS). Study design Cross sectional analyses of UKHLS COVID-19 wave data collected in April 2020. Methods UKHLS participants completed a COVID-19 questionnaire in April 2020. 635 children who were FSM eligible with complete data were included in the analytic sample. Accessing a FSM was defined as having receiving a FSM voucher or a cooked meal at school. Multivariable logistic regression was used to investigate (i) associations between characteristics and access to FSM and (ii) associations between access to FSM and household food insecurity measures. All analyses accounted for survey design and sample weights. Results 51% of eligible children accessed a FSM. Children in junior schools or above (aged 8+ years) (OR 11.81; 95% CI 5.54,25.19), who were low income (AOR 4.81; 95% CI 2.10,11.03) or still attending schools (AOR 5.87; 95% CI 1.70,20.25) were more likely to receive FSM. Children in Wales were less likely to access FSM than those in England (AOR 0.11; 95% CI 0.03,0.43). Receiving a FSM was associated with an increased odds of recently using a food bank, but not reporting feeling hungry. Conclusions In the month following the COVID-19 lockdown, 49% of eligible children did not receive any form of FSM. The present analyses highlight that the voucher scheme did not adequately serve children who could not attend school during the lockdown. Moreover, more needs to be done to support families relying on income-related benefits, who still report needed to access a foodbank. As scheme may be continued in summer or in second wave, large improvements will be needed to improve its reach.


title: How the pandemic made this virologist an unlikely cult figure

text: ” On 20 April, the German Research Foundation announced it was awarding Drosten a one-off prize for “outstanding science communication during the COVID-19 pandemic (Leong survived his bout with SARS and is now treating COVID-19 patients himself His research interests were ideal preparation for COVID-19


title: Dose-response effect of dietary nitrate on muscle contractility and blood pressure in older subjects

text: Purpose: We have recently demonstrated that dietary nitrate, a source of nitric oxide via the enterosalivary pathway, can improve muscle contractile function in healthy older men and women. Nitrate ingestion has also been shown to reduce blood pressure in some, but not all, studies of older individuals. However, the optimal dose for eliciting these beneficial effects is unknown. Methods: A randomized, double-blind, placebo-controlled crossover study was performed to determine the effects of ingesting 3.3 mL/kg of concentrated beetroot juice (BRJ) containing 0, 200, or 400 umol/kg of nitrate in nine healthy older subjects (one man, eight women; mean age 70+/-1 y). Maximal knee extensor power (Pmax) and speed (Vmax) were measured 2 h after BRJ ingestion using isokinetic dynamometry. Blood pressure was monitored periodically throughout each study. Results: Pmax (in W/kg) was higher (P<0.05) after the low dose (3.9+/-0.4) compared to the placebo (3.7+/-0.4) or high dose (3.7+/-0.4). Vmax (in rad/s) also tended higher (P=0.08) in the low (11.9+/-0.7) compared to the placebo (10.8+/-0.8) or high dose (11.20+/-.8) trials. Eight out of nine subjects achieved a higher Pmax and Vmax after the lower vs. the higher dose. These dose-related changes in muscle contractility paralleled changes in nitric oxide (NO) bioavailability, as reflected by changes in breath NO and plasma 3 nitrotyrosine levels. No significant changes were found in systolic, diastolic, or mean arterial pressure. Conclusions: Varying doses of dietary nitrate have differential effects on muscle function and blood pressure in older individuals. A moderate dose of nitrate increases muscle speed and power, but these improvements are lost at a higher dose. Blood pressure, on the other hand, is not reduced even with a higher dose.


title: Will an imperfect vaccine curtail the COVID-19 pandemic in the U.S.?

text: The novel coronavirus (COVID-19) that emerged from Wuhan city of China in late December 2019 continue to pose devastating public health and economic challenges across the world. Although the community-wide implementation of basic non-pharmaceutical intervention measures, such as social-distancing, quarantine of suspected COVID-19 cases, isolation of confirmed cases, use of face masks in public, and contact-tracing, have been quite effective in curtailing and mitigating the burden of the pandemic, it is universally believed that the use of an anti-COVID-19 vaccine is necessary to build the community herd immunity needed to effectively control and eliminate the pandemic. This study is based on the design and use of a mathematical model for assessing the population-level impact of a hypothetical imperfect anti-COVID-19 vaccine on the control of COVID-19. An analytical expression for the minimum number of unvaccinated susceptible individuals needed to be vaccinated to achieve vaccine-induced community herd immunity is derived. The epidemiological consequence of the herd immunity threshold is that the disease can be effectively controlled or eliminated if the minimum herd immunity threshold is achieved in the community. Simulations of the model, using baseline parameter values obtained from fitting the model with mortality data relevant to COVID-19 dynamics in the US states of New York and Florida, as well as for the entire US, show that, for an anti-COVID-19 vaccine with an assumed protective efficacy of 80%, the minimum herd immunity threshold for the entire US, state of New York and state of Florida are, respectively, 90%, 84% and 85%. Furthermore, it was shown that, while a significantly large increase in vaccination rate (from baseline) is necessarily needed to eliminate COVID-19 from the entire US, the pandemic can be eliminated from the states of New York and Florida if the vaccination rate is marginally increased (by as low as 10%) from its baseline value. The prospect of COVID-19 elimination in the US or in the two states of New York and Florida is greatly enhanced if the vaccination program is combined with a public mask use program or an effective social-distancing measure. Such combination of strategies significantly reduces the vaccine-induced herd immunity threshold. Finally, it is shown that the vaccination program is more likely to lead to COVID-19 elimination in the state of Florida, followed by the state of New York and then the entire US.


title: Perspective from Ecuador, the Second Country with More Confirmed Cases of Coronavirus Disease 2019 in South America: A Review

text: To face the pandemic outbreak of a novel coronavirus many countries developed a series of containment methods; however, developing countries in South America had reacted apathetically to this worldwide concern. Ecuador's response to the novel virus Coronavirus Disease 2019 (COVID-19) started on February 26, 2020, one month after the outbreak began in China. As of today, the countries with more confirmed cases in South America are Brazil and Ecuador. Although Brazil has two times the number of cases than Ecuador (Brazil: 700 cases per 100000 people vs. Ecuador: 400 cases per 100000), the huge population difference between the two countries raises concerns about the public health policies implemented by the Ecuadorian government. Even though there is no cure for COVID-19, chloroquine and hydroxychloroquine are promising alternatives. The COVID-19 pandemic outbreak has shown that there is room for improvement in the healthcare systems worldwide and the disastrous results on the fragile often unprepared are those systems in developing countries.


title: Oncology Clinical Pharmacy Services in Chinese Hospitals

text: In recent years, with an increasing number of oncology patients and continuous introduction of new antitumor drugs in China, the demand for oncology clinical pharmacy services is growing rapidly, which is both an opportunity and a challenge for clinical pharmacists. However, there have not been many reports about different types of oncology clinical pharmacy services in China. In this report, we have summarized different oncology clinical pharmacy services commonly practiced in Chinese hospitals based on our review of the literature and current practice in our hospital. We are reporting the training programs and the certification process for oncology clinical pharmacists, basic and advanced patient services, pharmacist-driven and pharmacist-participated guidelines/expert consensuses/books on oncology pharmacotherapy, as well as professional and public health education performed by pharmacists. Based on what we have observed, oncology clinical pharmacy services in China are relatively comprehensive, however, there are needs for expanding certain advanced pharmacy services. Increasing the time spent on clinical services, improving pharmacists’ competency, and optimizing clinical pharmacy workflow and evaluation mechanisms are important for enhancing the value of oncology clinical pharmacists in China. This article is protected by copyright. All rights reserved.


title: Current Clinical Trials and Vaccine Development Strategies for Corona Virus Disease (COVID-19)

text: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached global epidemic status claiming more than 319K lives and affecting more than 4 81M people and counting worldwide Considering the severity of the situation and low recovery rate many research institutions and pharmaceutical industries are rushing to learn more about this new virus and the morbid physiology of this disease with effective diagnostic methods, therapeutic agents and vaccines Various approaches are highlighted for comparing the possible treatment methods available for COVID-19 some of which are BCG vaccination on COVID-19 and Non-pharmaceutical interventions, drug based clinical trials of Hydroxychloroquine-Azithromycin, chloroquine, lopinavir/ritonavir, ChAdOx1 nCoV-19, Remdesivir, Stem Cell therapy and mesenchymal stromal cell therapy, etc


title: Viewpoint: Connecting with New Partners in COVID‐19 Response

text: The COVID‐19 crisis has called for the mobilization of diverse resources and coordination through administrative networks. This mobilization has brought to light the challenges involved in the recruiting and retention of diverse administrative networks. This article reviews the importance of and difficulties in maintaining diverse administrative networks. The review is followed by concrete strategies for building and maintaining diverse networks in Norman, OK. The lessons emphasize the role of active and imaginative recruitment and a realistic assessment of the challenges facing members of the network that can interfere with their participation. This article is protected by copyright. All rights reserved.


title: A sub-national analysis of the rate of transmission of COVID-19 in Italy

text: Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28,238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. New interventions, such as enhanced testing and contact tracing are going to be introduced and will likely contribute to reductions in transmission; therefore our estimates should be viewed as pessimistic projections. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a second wave will not be immediately apparent from just monitoring of the daily number of deaths. Our results suggest that SARS-CoV-2 transmission as well as mobility should be closely monitored in the next weeks and months. To compensate for the increase in mobility that will occur due to the relaxation of the currently implemented NPIs, adherence to the recommended social distancing measures alongside enhanced community surveillance including swab testing, contact tracing and the early isolation of infections are of paramount importance to reduce the risk of resurgence in transmission.


title: Misinformation During the Coronavirus Disease 2019 Outbreak: How Knowledge Emerges From Noise

text: Although the amount of information generated during this most recent coronavirus disease 2019 pandemic is enormous, much is of uncertain trustworthiness. This review summaries the many potential sources of information that clinicians turn to during pandemic illness, the challenges associated with performing methodologically sound research in this setting and potential approaching to conducting well done research during a health crisis. DATA SOURCES: Not applicable. STUDY SELECTION: Not applicable. DATA EXTRACTION: Not applicable. DATA SYNTHESIS: Not applicable. CONCLUSIONS: Pandemics and healthcare crises provide extraordinary opportunities for the rapid generation of reliable scientific information but also for misinformation, especially in the early phases, which may contribute to public hysteria. The best way to combat misinformation is with trustworthy data produced by healthcare researchers. Although challenging, research can occur during pandemics and crises and is facilitated by advance planning, governmental support, targeted funding opportunities, and collaboration with industry partners. The coronavirus disease 2019 research response has highlighted both the dangers of misinformation as well as the benefits and possibilities of performing rigorous research during challenging times.


title: Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs

text: Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and, thus, repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a new virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (Mpro). The accurate FEP-ABFE predictions were based on the use of a new restraint energy distribution (RED) function designed to accelerate the FEP-ABFE calculations and make the practical FEP-ABFE-based virtual screening of the existing drug library possible for the first time. As a result, out of twenty-five drugs predicted, fifteen were confirmed as potent inhibitors of SARS-CoV-2 Mpro. The most potent one is dipyridamole (Ki=0.04 μM) which has showed promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (Ki=0.36 μM) and chloroquine (Ki=0.56 μM) were also found to potently inhibit SARS-CoV-2 Mpro for the first time. We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts. Significance Statement Drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. It has been demonstrated that a new virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions can reach an unprecedently high hit rate, leading to successful identification of 16 potent inhibitors of SARS-CoV-2 main protease (Mpro) from computationally selected 25 drugs under a threshold of Ki = 4 μM. The outcomes of this study are valuable for not only drug repurposing to treat COVID-19, but also demonstrating the promising potential of the FEP-ABFE prediction-based virtual screening approach.


title: COVID-19 PCR Test Performance for Samples Stored at Ambient Temperature

text: Background The new type of Coronavirus infection had become a pandemic in a very short period since it was first seen in Wuhan. The outbreak had a negative impact on all health care systems throughout the world and overwhelmed the diagnostic laboratories as well. During the pandemic, handling patient specimens in accordance with the universal guidelines was troublesome as WHO, CDC and ECDC required cold chain compliance during transporting and storing the swap samples. Materials and methods In this study, we tested diagnostic performance of RT-PCR on 30 swab samples stored at ambient temperature and compared them with the samples stored at +4°C. Results Our results revealed that all the samples stored at ambient temperature remain PCR positive for at least five days. We did not see any false negativity. Conclusion In conclusion, we report that transferring and storing of nasopharyngeal/oropharyngeal samples at ambient temperature could be possible in the resource-limited conditions like pandemic.


title: The Association of Lymphocyte count and levels of CRP, D-Dimer, and LDH with severe coronavirus disease 2019 (COVID-19): A Meta-Analysis

text: The rapid progression of Coronavirus disease 2019 (COVID-19) and its increasing burden on health systems necessitate the identification of parameters of severe infection to help in monitoring, prognoses and development of treatment algorithms. This review aims to investigate the association of lymphocyte count, CRP, LDH, and D-Dimer with the severe form of COVID-19. This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The databases of MEDLINE/PubMed, WHO-Virtual Health Library (VHL), and ScienceDirect were used for the systematic search. Random effects model was used to estimate the pooled standardized mean differences (SMD) with the corresponding 95% confidence interval (CI), using OpenMeta Analyst software. A total of 11 studies, with 2437 COVID-19 patients, which fulfilled the eligibility criteria were included in the meta-analysis. The analysis revealed that lymphocyte count was significantly lower in patients with the severe form of COVID-19 (SMD = - 1.025, P value <.001). Also, the analysis of SMD showed that patients with severe COVID-19 have a significantly higher serum levels of CRP (SMD = 3.363, P value <.001), D-Dimer (SMD = 1.073, P value <.001), and LDH (SMD = 3.345, P value <.001). Low lymphocyte count and high levels of CRP, LDH, and D-Dimer are associated with severe COVID-19. These laboratory markers could be used as clinical indicators of worsening illness and poor prognosis of COVID-19.


title: Crystal structures of SARS-CoV-2 ADP-ribose phosphatase (ADRP): from the apo form to ligand complexes

text: Among 15 nonstructural proteins (Nsps), the newly emerging SARS-CoV-2 encodes a large, multidomain Nsp3. One of its units is ADP-ribose phosphatase domain (ADRP, also known as macrodomain) which is believed to interfere with the host immune response. Such a function appears to be linked to the protein’s ability to remove ADP-ribose from ADP-ribosylated proteins and RNA, yet the precise role and molecular targets of the enzyme remains unknown. Here, we have determined five, high resolution (1.07 - 2.01 Å) crystal structures corresponding to the apo form of the protein and complexes with 2-(N-morpholino)ethanesulfonic acid (MES), AMP and ADPr. We show that the protein undergoes conformational changes to adapt to the ligand in a manner previously observed before for in close homologs from other viruses. We also identify a conserved water molecule that may participate in hydrolysis. This work builds foundations for future structure-based research of the ADRP, including search for potential antiviral therapeutics.


title: Neutralising antibodies to SARS coronavirus 2 in Scottish blood donors - a pilot study of the value of serology to determine population exposure

text: Background. The extent of spread of SARS coronavirus 2 (SARS-CoV-2) in the UK and elsewhere is unknown because typically only symptomatic individuals are diagnosed. We performed a serological study of recent blood donors in Scotland to detect antibodies to SARS-CoV-2 as a marker of past infection. Methods. A pseudotyped SARS-CoV-2 virus microneutralisation assay was used to detect neutralising antibodies to SARS-CoV-2. The study group comprised samples from 1000 blood donors collected in Scotland during March, 2020. Controls were collected from 100 donors in Scotland during 2019. Findings. All samples collected on the 17th March, 2020 (n=500) were negative in the pseudotyped SARS-CoV-2 virus microneutralisation assay. Neutralising antibodies were detected in 5 of the 500 samples collected 21st to 23rd March; one further sample was reactive in an anti-spike ELISA. Interpretation. Although we cannot use the rise in numbers seropositive to infer the contemporary seroprevalence or the growth rate of the epidemic, we note that they are consistent with frequency of reported diagnosed infections and SARS-CoV-2-associated deaths reported in that time period in Scotland, given that seroconversion takes up to 2-3 weeks. It should also be noted that blood donors are not representative of the general population; in particular, those with a history of recent respiratory infections are deferred. Finally, it is unknown what proportion of infected individuals seroconvert and become reactive in the assays used. Serial follow up studies are needed to track infection and seroconversion in this and other similar populations However, these data indicate that sero-surveys of blood banks can serve as a useful tool for tracking the emergence and progression of an epidemic like the current SARS-CoV-2 outbreak.


title: Battle with COVID-19 Under Partial to Zero Lockdowns in India

text: The cumulative records of COVID-19 are rapidly increasing day by day in India. The key question prevailing in minds of all is when will it get over? There have been several attempts in literature to address this question using time series, Machine learning, epidemiological and statistical models. However due to high level of uncertainty in the domain and lack of big historical data, the performance of these models suffer. In this work, we present an intuitive model that uses a combination of epidemiological model (SEIR) and mathematical curve fitting method to forecast spread of COVID-19 in India in future. By using the combination model, we get characteristics benefits of these models under limited knowledge and historical data about the novel Coronavirus. Instead of fixing parameters of the standard SEIR model before simulation, we propose to learn them from the real data set consisting of progression of Corona spread in India. The learning of model is carefully designed by understanding that available data set consist of records of cases under full, partial to zero lockdown phases in India. Hence, we make two separate predictions by our propose model. One under the situation of full lockdown in India and, other with partial to zero restrictions in India. With continued strict lockdown after May 03, 2020, our model predicted May 14, 2020 as the date of peak of Coronavirus in India. However, in current scenario of partial to zero lockdown phase in India, the peak of Coronavirus cases is predicted to be July 31, 2020. These two predictions presented in this work provide awareness among citizens of India on importance of control measures such as full, partial and zero lockdown and the spread of Corona disease infection rate. In addition to this, it is a beneficial study for the government of India to plan the things ahead.


title: Efficient sample pooling strategies for COVID-19 data gathering

text: Sample pooling of CoViD-19 PCR tests has been recently proposed as a low cost alternative to individual tests. We show that sample pooling is efficient as long as the fraction of the population infected is relatively small. Fisher information theory suggests a rule of thumb that for low infection rates p, pooling 2/p samples is close to optimal. We present a simple strategy for survey design when not even a ballpark estimate of the infection rate is available.


title: Local response in health emergencies: key considerations for addressing the COVID-19 pandemic in informal urban settlements

text: This paper highlights the major challenges and considerations for addressing COVID-19 in informal settlements. It discusses what is known about vulnerabilities and how to support local protective action. There is heightened concern about informal urban settlements because of the combination of population density and inadequate access to water and sanitation, which makes standard advice about social distancing and washing hands implausible. There are further challenges to do with the lack of reliable data and the social, political and economic contexts in each setting that will influence vulnerability and possibilities for action. The potential health impacts of COVID-19 are immense in informal settlements, but if control measures are poorly executed these could also have severe negative impacts. Public health interventions must be balanced with social and economic interventions, especially in relation to the informal economy upon which many poor urban residents depend. Local residents, leaders and community-based groups must be engaged and resourced to develop locally appropriate control strategies, in partnership with local governments and authorities. Historically, informal settlements and their residents have been stigmatized, blamed, and subjected to rules and regulations that are unaffordable or unfeasible to adhere to. Responses to COVID-19 should not repeat these mistakes. Priorities for enabling effective control measures include: collaborating with local residents who have unsurpassed knowledge of relevant spatial and social infrastructures, strengthening coordination with local governments, and investing in improved data for monitoring the response in informal settlements.


title: Classification of COVID-19 in intensive care patients: towards rational and effective clinical triage

text: The number of pertinent researches of COVID-19 has increased rapidly but they mainly focused on the description of general information of patients with confirmed infection. We aimed to bridge the gap between disease classification and clinical outcome in intensive care patients, data of which are scarce and such classification could help in individual evaluation and provide effective triage for treatment and management. Specifically, we collected and filtered out 151 intensive care patients with complete medical records from Tongji hospital in Wuhan, China. We constructed a fully Bayesian latent variable model for integrative clustering of six data categories, including demographic information, symptoms, original comorbidities, vital signs, blood routine tests and inflammatory marker measurements. We identified four prognostic types of COVID-19 in intensive care patients, presenting a stepwise distribution in age, respiratory condition and inflammatory markers, suggesting the prognostic efficacy of these indicators. This report, to our knowledge, is the first attempt of dealing with classification of COVID-19 in intensive care patients. We acknowledge the limitation of ignoring the effect of treatment, but we believe such classification is enlightening for better triage, allowing for a more rational allocation of scarce medical resources in a resource constrained environment.


title: Positivity of SARS-CoV-2, by RT-PCR among workers of a Public Hospital in the city of Santos, SP, Brazil 2020.

text: Background: Infection with SARS-CoV-2, associated with severe respiratory symptoms, currently called COVID-19, represents one of the greatest health challenges of this century. Health professionals, as well as hospital workers, are the most vulnerable population for acquiring SARS-CoV-2 due to their greater proximity to sick patients, especially in specialized hospitals for the treatment of these patients. Study Design: We ran a questionnaire by all the employees of a Public Service Hospital specialised in COVID-19 treatment (1307 employees), in the municipality of Santos, Sao Paulo, Brazil, who presented some symptoms compatible with COVID-19 and positive results by RT-PCR, in Oropharynx Swab collection. The questionnaire collected socio-demographic information, as well as data related to the work areas where they were divided into two groups: Employees at higher risk or those who directly deal with patients (914 employees or 69.9%) and lower risk for employees in the administrative area (393 employees or 30.1%). Results: 211 (16.1%) of the Hospital's employees had to stop their work-related activities due to presenting positive RT-PCR. There were 39 (9.9%) positives in low risk areas and 172 (18.8%) positives in employees in high risk areas. Within the latter group, Nurses, Nursing Assistants and Doctors were the most frequently infected professionals. Regarding the symptoms of professionals positively diagnosed based on RT-PCR, the most frequent symptoms were body pain (83.4%); headache (80.6%); fever (57.8%) and dry cough (53.1%). Conclusion: A high proportion of workers in COVID-19 specialized hospitals was infected by the virus, despite all the protective measures adopted, showing the high transmission capacity of this virus. Stricter individual protection measures among employees must be adopted.


title: Prevalence, Severity and Mortality associated with COPD and Smoking in patients with COVID-19: A Rapid Systematic Review and Meta-Analysis

text: Background: Coronavirus disease 2019 (COVID-19) is an evolving infectious disease that dramatically spread all over the world in the early part of 2020. No studies have yet summarised the potential severity and mortality risks caused by COVID-19 in patients with chronic obstructive pulmonary disease (COPD), and we update information in smokers. Methods: We systematically searched electronic databases from inception to March 24, 2020. Data were extracted by two independent authors in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Study quality was assessed using a modified version of the Newcastle Ottawa Scale. We synthesised a narrative from eligible studies and conducted a meta-analysis using a random-effects model to calculate pooled prevalence rates and 95% confidence intervals (95%CI). Results: In total, 123 abstracts were screened and 61 full-text manuscripts were reviewed. A total of 15 studies met the inclusion criteria, which included a total of 2473 confirmed COVID-19 patients. All studies were included in the meta-analysis. The crude case fatality rate of COVID-19 was 6.4%. The pooled prevalence rates of COPD patients and smokers in COVID-19 cases were 2% (95% CI, 1%-3%) and 9% (95% CI, 4%-14%) respectively. COPD patients were at a higher risk of more severe disease (risk of severity = 63%, (22/35) compared to patients without COPD 33.4% (409/1224) [calculated RR, 1.88 (95% CI, 1.4-2.4)]. This was associated with higher mortality (60%). Our results showed that 22% (31/139) of current smokers and 46% (13/28) of ex-smokers had severe complications. The calculated RR showed that current smokers were 1.45 times more likely [95% CI: 1.03-2.04] to have severe complications compared to former and never smokers. Current smokers also had a higher mortality rate of 38.5%. Conclusion: Although COPD prevalence in COVID-19 cases was low in current reports, COVID-19 infection was associated with substantial severity and mortality rates in COPD. Compared to former and never smokers, current smokers were at greater risk of severe complications and higher mortality rate. Effective preventive measures are required to reduce COVID-19 risk in COPD patients and current smokers.