title: CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection

text: Coronavirus (COVID-19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect on the global economy and health. A positive chest X-ray of infected patients is a crucial step in the battle against COVID-19. Early results suggest that abnormalities exist in chest X-rays of patients suggestive of COVID-19. This has led to the introduction of a variety of deep learning systems and studies have shown that the accuracy of COVID-19 patient detection through the use of chest X-rays is strongly optimistic. Deep learning networks like convolutional neural networks (CNNs) need a substantial amount of training data. Because the outbreak is recent, it is difficult to gather a significant number of radiographic images in such a short time. Therefore, in this research, we present a method to generate synthetic chest X-ray (CXR) images by developing an Auxiliary Classifier Generative Adversarial Network (ACGAN) based model called CovidGAN. In addition, we demonstrate that the synthetic images produced from CovidGAN can be utilized to enhance the performance of CNN for COVID-19 detection. Classification using CNN alone yielded 85% accuracy. By adding synthetic images produced by CovidGAN,the accuracy increased to 95%. We hope this method will speed up COVID-19 detection and lead to more robust systems of radiology.


title: Early-Morning vs Spot Posterior Oropharyngeal Saliva for Diagnosis of SARS-CoV-2 Infection: Implication of Timing of Specimen Collection for Community-Wide Screening

text: BACKGROUND: Posterior oropharyngeal saliva is increasingly recognized as a valid respiratory specimen for SARS-CoV-2 diagnosis. It is easy to collect and suitable for community-wide screening. The optimal timing of collection is currently unknown, and we speculate that an early-morning specimen before oral hygiene and breakfast would increase the diagnostic yield. METHODS: Posterior oropharyngeal saliva was collected at 5 different time points within the same day from 18 patients with previously confirmed SARS-CoV-2 infection by molecular testing. Cycle threshold (Ct) values were compared. RESULTS: There was an overall trend of lower Ct values from specimens collected in the early morning, with a gradual decrease of viral load towards nighttime, but reaching statistical significance only when compared with the specimens collected at bedtime. Eight out of 13 subjects had a higher viral load in the early morning than the rest of the 4 time points (before lunch, before teatime at 3 pm, before dinner, before bedtime). CONCLUSIONS: The result suggests a diurnal variation of viral shedding from the upper respiratory tract with a trend showing higher viral load in the early morning. For community screening purposes, posterior oropharyngeal saliva could be taken throughout the day, but preferably in the early morning to maximize the yield.


title: Common phobias among Egyptian primary schoolchildren: an emergency trigger for panic disorder due to corona pandemic. (Special Issue: Coronavirus disease (COVID-19).)

text: BACKGROUND: In the wake of the adverse situation we are currently facing globally due to the coronavirus pandemic outbreak, it is normal to feel stressed, confused, and scared but what is abnormal is to turn this to panic Phobias are more pronounced than fears They develop when a person has an exaggerated or unrealistic sense of danger that may be evolved to experience panic attacks AIM: Our objective was to identify the prevalence of most common phobias as well as panic disorder (PD) due to the coronavirus pandemic among Egyptian primary schoolchildren and their determinants METHODS: A cross-sectional study was conducted among 2015 schoolchildren from 3 to 6 grades in three governorates of Egypt Seven types of phobias were investigated: Agoraphobia, phobias from darkness, animal, untreatable illness (mainly coronavirus), insects, height, and social phobia The child's self-reported PD symptoms were assessed using DSM-IV with psychiatric diagnoses RESULTS: Almost two-thirds of the surveyed primary schoolchildren have phobias of the low score (9) versus one-third who had high phobias score (61 % vs 35%, respectively) with highly significant difference (p 0 001) The most prevalent phobias were from heights (66 5%) followed by darkness (60 0%) The important predictors of phobias were: Being a male child, living in an urban area, and studying at governmental school at fifth or sixth-grade residence The prevalence of PD due to the corona epidemic is very high, it is reported by almost half of the surveyed primary schoolchildren Fear of losing any of their family members, especially grandparents, was reported to be the highest PD symptom (97%) CONCLUSION AND RECOMMENDATION: Phobia from heights and darkness was the most common The prevalence of PD due to the coronavirus epidemic is reported to be very high Calming down children who might be experienced with a phobia that is triggering their PD is recommended


title: Mendelian randomization analysis to characterize causal association between coronary artery disease and COVID-19

text: Observational studies have suggested that having coronary artery disease increases the risk of Coronavirus disease 2019 (COVID-19) susceptibility and severity, but it remains unclear if this association is causal. Inferring causation is critical to facilitate the development of appropriate policies and/or individual decisions to reduce the incidence and burden of COVID-19. We applied Two-sample Mendelian randomization analysis and found that genetically predicted CAD was significantly associated with higher risk of COVID-19: the odds ratio was 1.29 (95% confidence interval 1.11 to 1.49; P = 0.001) per unit higher log odds of having CAD.


title: P0: Progress to zero: A simple metric to measure COVID-19 progress by country/region

text: The current COVID-19 pandemic is having a devastating impact on the world. As of May 8th, 2020, more than half of the world is in lockdown, 3.6 million people have been infected, and over 250,000 of them have died. This is the first pandemic in human history that has been tracked on a daily basis across the world. Currently, progress is being tracked by a series of metrics, including new cases, deaths, and the effective reproduction number over time (R(t)), which epidemiologists have emphasized. While it is an important measure, R(t) is not observable and is dependent on the absolute number of active cases; therefore, two geographies could have a similar R(t) but be having very different experiences. Here, we propose a metric to monitor progress on addressing the COVID pandemic that we name "progress to zero" or P0. P0 corresponds to the percentage decline from a previously recorded peak level. The metric ranges from 0% (representing a geography that has not yet peaked) to 100% (representing a geography wherein 0 cases have been recorded for at least seven days). Our metric helps leaders focus on progress to a desired goal, easily can be tracked over time, can quickly identify retreat from progress, and is comparable across geographies regardless of their size.


title: The impact of school reopening on the spread of COVID-19 in England

text: Background: In the UK, cases of COVID-19 have been declining since mid-April and there is good evidence to suggest that the effective reproduction number has dropped below 1, leading to a multi-phase relaxation plan for the country to emerge from lockdown. As part of this staggered process, primary schools are scheduled to partially reopen on 1st June. Evidence from a range of sources suggests that children are, in general, only mildly affected by the disease and have low mortality rates, though there is less certainty regarding children's role in transmission. Therefore, there is wide discussion on the impact of reopening schools. Methods: We compare eight strategies for reopening primary and secondary schools in England from 1st June, focusing on the return of particular year groups and the associated epidemic consequences. This is assessed through model simulation, modifying a previously developed dynamic transmission model for SARS-CoV-2. We quantify how the process of reopening schools affected contact patterns and anticipated secondary infections, the relative change in R according to the extent of school reopening, and determine the public health impact via estimated change in clinical cases and its sensitivity to decreases in adherence post strict lockdown. Findings: Whilst reopening schools, in any form, results in more mixing between children, an increase in R and hence transmission of the disease, the magnitude of that increase can be low dependent upon the age-groups that return to school and the behaviour of the remaining population. We predict that reopening schools in a way that allows half class sizes or that is focused on younger children is unlikely to push R above one, although there is noticeable variation between the regions of the country. Given that older children have a greater number of social contacts and hence a greater potential for transmission, our findings suggest reopening secondary schools results in larger increases in case burden than only reopening primary schools; reopening both generates the largest increase and could push R above one in some regions. The impact of less social-distancing in the rest of the population, generally has far larger effects than reopening schools and exacerbates the impacts of reopening. Discussion: Our work indicates that any reopening of schools will result in increased mixing and infection amongst children and the wider population, although the opening of schools alone is unlikely to push the value of R above one. However, impacts of other recent relaxations of lockdown measures are yet to be quantified, suggesting some regions may be closer to the critical threshold that would lead to a growth in cases. Given the uncertainties, in part due to limited data on COVID-19 in children, school reopening should be carefully monitored. Ultimately, the decision about reopening classrooms is a difficult trade-off between increased epidemiological consequences and the emotional, educational and developmental needs of children.


title: Plasma levels of soluble ACE2 are associated with sex, Metabolic Syndrome, and its biomarkers in a large cohort, pointing to a possible mechanism for increased severity in COVID-19

text: We examined the associations between plasma concentrations of soluble ACE2 and biomarkers of Metabolic Syndrome in a large (N=2,051) sample of individuals who participated in a commercial wellness program and who underwent deep molecular phenotyping. sACE2 levels were significantly higher in men, compared to women, and in individuals with Metabolic Syndrome, compared to controls. sACE2 levels showed reliable associations with all individuals components of Metabolic Syndrome, including obesity, hypertension, insulin resistance, hyperlipidemia, and as well as markers of liver damage. This profile of associations was statistically significantly stronger in men, compared to women, and suggests that preexisting cardiometabolic conditions might confer increased severity of symptoms in some COVID-19 patients through increased expression of ACE2 in the liver.


title: The Novel Coronavirus Disease (COVID-19): A PRISMA Systematic Review and Meta-analysis of Clinical and Paraclinical characteristics

text: An outbreak of pneumonia, caused by a novel coronavirus (COVID-19) was Identified in China in Dec 2019. This virus expanded worldwide, causing global concern. Clinical, laboratory and imaging features of this infection are characterized in some observational studies. We undertook a systematic review and meta-analysis to assess the frequency of clinical, laboratory, and CT features in COVID-19 patients. We did a systematic review and meta-analysis using three databases to identify clinical, laboratory, and CT features of rRT-PCR confirmed cases of COVID-19. Data for 3420 patients from 30 observational studies were included. Overall, the results showed that fever (84.2%, 95%CI 82.6-85.7), cough (62%, 95%CI 60-64), and fatigue (39.4%, 95%CI 37.2-41.6%) were the most prevalent symptoms in COVID-19 patients. Increased CRP level, decreased lymphocyte count, and increased D-dimer level were the most common laboratory findings. Among COVID-19 patients, 92% had a positive CT finding, most prevalently GGO (60%, 95%CI 58-62) and peripheral distribution (64%, 95%CI 60-69). These results demonstrate the clinical, paraclinical, and imaging features of COIVD-19.


title: Determination of daily reproduction numbers of SARS-CoV2 based on death cases suggests more rapid initial spread in Italy and the United States

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


title: Optimization Method for Forecasting Confirmed Cases of COVID-19 in China

text: In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting trapped at the local optima). The main idea of the proposed model, called FPASSA-ANFIS, is to improve the performance of ANFIS by determining the parameters of ANFIS using FPASSA. The FPASSA-ANFIS model is evaluated using the World Health Organization (WHO) official data of the outbreak of the COVID-19 to forecast the confirmed cases of the upcoming ten days. More so, the FPASSA-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination ([Formula: see text]), and computing time. Furthermore, we tested the proposed model using two different datasets of weekly influenza confirmed cases in two countries, namely the USA and China. The outcomes also showed good performances.


title: Pandemic democracy: elections and COVID-19

text: This article provides an initial assessment of the many risks posed by the COVID-19 pandemic on the conduct of genuine and transparent elections in the world. It begins with explaining why elections are a vital part of democracy, and then using the notion of the electoral cycle, constructs a risk matrix that assesses the relative impact and likelihood of risks to the cycle, as well as proposes a number of potential mitigations to these risks. The variety and number of elections, dimensions of the electoral cycle that can be disrupted, and the need for solutions raises significant questions about the future of democracy itself.


title: Search for SARS-CoV-2 inhibitors in currently approved drugs to tackle COVID-19 pandemia

text: Different treatments are currently used for clinical management of SARS-CoV-2 infection, but little is known about their efficacy yet. Here we present ongoing results to compare currently available drugs for a variety of diseases to find out if they counteract SARS-CoV-2-induced cytopathic effect in vitro. Our goal is to prioritize antiviral activity to provide a solid evidence-driven rationale for forthcoming clinical trials. Since the most effective antiviral approaches are usually based on combined therapies that tackle the viral life cycle at different stages, we are also testing combinations of drugs that may be critical to reduce the emergence of resistant viruses. We will provide results as soon as they become available, so data should be interpreted with caution, clearly understanding the limitations of the in vitro model, that may not always reflect what could happen in vivo. Thus, our goal is to test the most active antivirals identified in adequate animal models infected with SARS-CoV-2, to add more information about possible in vivo efficacy. In turn, successful antivirals could be tested in clinical trials as treatments for infected patients, but also as pre-exposure prophylaxis to avoid novel infections until an effective and safe vaccine is developed.


title: Instantaneous R calculation for COVID-19 epidemic in Brazil

text: COVID-19 pandemic represents a major challenge to health systems of all countries. Brazilian regions habe been showing marked di[ff]erences in onset and number of cases. Health authorities instituted widespread social distancing and lockdown measures but their implementation has also varied. The authors used data on con[fi]rmed cases of COVID-19 in Brazil and its states to calculate the value of instantaneous reproduction number at these regions. The results show a reduction of instantaneous reproduction number with time, probably due to social distancing measures put in place in the last weeks by brazillian authorities. It seems logical to maintain restrictions to social contact until the epidemic peak has occurred in Brazil.


title: Explaining the Bomb-Like Dynamics of COVID-19 with Modeling and the Implications for Policy

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


title: When will the Covid-19 epidemic fade out?

text: A discrete-time deterministic epidemic model is proposed with the aim of reproducing the behaviour observed in the incidence of real infectious diseases. For this purpose, we analyse a SIRS model under the framework of a small world network formulation. Using this model, we make predictions about the peak of the Covid-19 epidemic in Italy. A Gaussian fit is also performed, to make a similar prediction.


title: Are health indicators able to describe the ability to cope of Health Systems with COVID-19 epidemic?

text: The Coronavirus Disease 19 epidemic is an infectious disease which was declared as a pandemic and hit all the Countries, all over the world, from the beginning of the year 2020. Despite the emergency vigilance plans, in all the Countries, Health Systems experienced a different ratio of lethality, admissions to intensive care units and managing quarantine of positive patients. The aim of this study is to investigate if some health indicators might have been useful to understand the capacity of Italian National Health Service to manage the COVID 19 epidemic. We will compare data in two different Italian regions in the Northern part of Italy (Lombardy and Veneto) with the national data to understand if different health strategies might be significant to explain different patterns of COVID 19 epidemic in Italy. The two regions have two different health policies to face CoViD-2019 epidemic. To face epidemic like this one the answer should be outside hospitals but this means to have general practitioners well-trained and enough healthcare personnel working outside hospitals.


Sending a red signal: When a contact tracing app went wrong a journalist was forced to stay in their home in China


title: Telemedicine takes centre stage during COVID-19 pandemic

text: The COVID-19 pandemic continues to spread rapidly and overwhelm health systems around the world. To cope with this unprecedented usage of healthcare resources, increasingly novel solutions are being brought into the fray. Telemedicine has been thrust into the spotlight in the fight against COVID-19 and is being employed in many different ways to better tackle the challenges. Telemedicine will likely have a more permanent place in traditional healthcare delivery long after COVID-19 is over as users and providers recognise its utility.


title: Finding Tentative Causes for the reduced impact of Covid-19 on the Health Systems of poorer and developing nations: An ecological study of the effect of demographic, climatological and health-related factors on the global spread of Covid-19

text: Objective - The objective of this study is to evaluate the association with different factors empirically found to affect the spread and the severity of Covid-19. Evidently there is less likelihood of having one single and absolute solution to this pandemic. It is pragmatic to look for a multi-pronged and collaborative assembly of probable solutions, which is the higher objective of this study. Design - Ecological study. Setting - Global setting including 45 countries from all six inhabited continents Population Two (2) or three (3) countries from each geographical region of the continents selected on the basis of population Main outcome - measures correlation factors derived from comparisons between different sets of variables Results - Empirical trends suggested in the existing literature were quantified in a global setting establishing clear trends. Correlation between the proportion of the population affected and median age, prime climate zones, malaria and tuberculosis incidence, BCG coverage and mitigation measures were established. Conclusions The study findings suggest that demographic and climatological factors, high endemicity of TB and Malaria, and universal BCG programmes may have a cushioning effect in the impact of Covid-19 on health systems of poorer and developing nations. In the light of these findings more emphasis is necessary on the protective effects of BCG and antiviral properties of antimalarial drugs.


title: Summaries of contributions

text: Unknown


title: The COVID-19 pandemic is a paradoxical challenge to our nervous system: A polyvagal perspective

text: The spread of the SARSCov2 virus presents an unprecedented event that rapidly introduced widespread life threat, economic de-stabilization, and social isolation. The human nervous system is tuned to detect safety and danger, integrating body and brain responses via the autonomic nervous system. Polyvagal Theory provides a perspective to understand the impact of the pandemic on mental and physical health. This perspective highlights the important role of the state of the autonomic nervous system in exacerbating or dampening threat reactions to the pandemic. In addition, the theory alerts us to the impact of clinical history (e.g., trauma) on autonomic regulation as an important compounding risk factor lowering the threshold to behaviorally and physiologically destabilize in response to the pandemic. The theory provides a strategy to dampen the adverse reactions to threat (e.g., acute stress disorders) through portals of social engagement that evolved to downregulate defenses to promote calmness and connectedness.


title: Transmission dynamics of coronavirus disease 2019 outside of Daegu-Gyeongsangbuk provincial region in South Korea

text: We analyzed transmission of coronavirus disease 2019 in South Korea. We estimated that non-pharamaceutical measures reduced the immediate transmissibility by maximum of 34% for coronavirus disease 2019. Continuous efforts are needed for monitoring the transmissibility to optimize epidemic control.


title: C.A. Mims M.L. Cuzner

text: Unknown


title: The reproductive number R0 of COVID-19 based on estimate of a statistical time delay dynamical system

text: In this paper, we estimate the reproductive number R0 of COVID-19 based on Wallinga and Lipsitch framework {11} and a novel statistical time delay dynamic system. We use the observed data reported in CCDC's paper to estimate distribution of the generation interval of the infection and apply the simulation results from the time delay dynamic system as well as released data from CCDC to fit the growth rate. The conclusion is: Based our Fudan-CCDC model, the growth rate r of COVID-19 is almost in [0.30, 0.32] which is larger than the growth rate 0.1 estimated by CCDC {9}, and the reproductive number R0 of COVID-19 is estimated by 3.25≤ R0 ≤3.4 if we simply use R=1+r*Tc with Tc=7.5, which is bigger than that of SARS. Some evolutions and predictions are listed.


title: Estimation of the probability of reinfection with COVID-19 coronavirus by the SEIRUS model

text: With sensitivity of the Polymerase Chain Reaction (PCR) test used to detect the presence of the virus in the human host, the global health community has been able to record a great number of recovered population. Therefore, in a bid to answer a burning question of reinfection in the recovered class, the model equations which exhibits the disease-free equilibrium (E_0 ) state for COVID-19 coronavirus was developed in this study and was discovered to both exist as well as satisfy the criteria for a locally or globally asymptotic stability with a basic reproductive number R_0=0 for and endemic situation. Hence, there is a chance of no secondary reinfections from the recovered population as the rate of incidence of the recovered population vanishes, that is, B=0. Furthermore, numerical simulations were carried to complement the analytical results in investigating the effect of the implementation of quarantine and observatory procedures has on the projection of the further spread of the virus globally. Result shows that the proportion of infected population in the absence of curative vaccination will continue to grow globally meanwhile the recovery rate will continue slowly which therefore means that the ratio of infection to recovery rate will determine the death rate that is recorded globally and most significant for this study is the rate of reinfection by the recovered population which will decline to zero over time as the virus is cleared clinically from the system of the recovered class.


Repurposing factories with robotics in the face of COVID-19


title: Estimating the reproduction number of COVID-19 in Iran using epidemic modeling

text: Background: As reported by Iranian governments, the first cases of coronavirus (COVID-19) infections confirmed in Qom, Iran on February 19, 2020 (30 Bahman 1398). The number of identified cases afterward increased rapidly and the novel coronavirus spread to all provinces of the country. This study aimed to fit an epidemic model to the reported cases data to estimate the basic reproduction number (R_0) of COVID-19 in Iran. Methods: We used data from February 21, 2020, to April 21, 2020, on the number of cases reported by Iranian governments and we employed the SIR (Susceptible-Infectious-Removed) epidemic spreading model to fit the transmission model to the reported cases data by tuning the parameters in order to estimate the basic reproduction number of COVID-19 in Iran. Results: The value of reproduction number was estimated 4.86 in the first week and 4.5 in the second week. it decreased from 4.29 to 2.37 in the next four weeks. At the seventh week of the outbreak the reproduction number was reduced below 1. Conclusions: The results indicate that the basic reproduction number of COVID-19 was significantly larger than one in the early stages of the outbreak. However, implementing social distancing and preventing travelling on Nowruz (Persian New Year) effectively reduced the reproduction number. Although the results indicate that reproduction number is below one, it is necessary to continue social distancing and control travelling to prevent causing a second wave of outbreak.


title: Diagnostic accuracy of six commercial SARS-CoV-2 IgG/total antibody assays and identification of SARS-CoV-2 neutralizing antibodies in convalescent sera

text: The reliable detection of immunoglobulin G (IgG) or total antibodies directed against the novel severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is important for clinical diagnostics and epidemiological studies. Here, we compare the diagnostic accuracy of six commercially available SARS-CoV-2 IgG (Abbott SARS-CoV-2 IgG; Diasorin Liaison SARS-CoV-2 S1/2 IgG; Epitope EDI Novel Coronavirus COVID-19 IgG ELISA Kit; Euroimmun Anti-SARS-CoV-2 ELISA (IgG); Mikrogen recomWell SARS-CoV-2 IgG) or total SARS-CoV-2 antibody assays (Roche Elecsys Anti-SARS-CoV-2). The test sensitivities were analyzed with a set of 34 sera obtained from 26 patients after PCR-confirmed SARS-CoV-2 infection and varied from 76.9% (Euroimmun) to 96.2% (Abbott). The majority of assay results were confirmed in a laboratory-developed plaque reduction neutralization test and by a SARS-CoV-2 IgG-specific line assay including measurement of generally low IgG avidities (Mikrogen recomLine Coronavirus IgG [Aviditaet], prototype). Moreover, 100 stored sera collected during summer 2018 (N = 50) and winter season 2018/2019 (N = 50) were included to demonstrate test specificities. These varied from 96.0% (DiaSorin) to 100% (Epitope EDI). A subset of sera were retested with a lateral flow test (STANDARD Q COVID-19 IgM/IgG Duo) and a considerably lower sensitivity was noted. Overall, the diagnostic accuracy of the six SARS-CoV-2 IgG/total antibody assays was good and varied from 92.9% (Euroimmun) to 98.4% (Abbott). Due to the different specificities, results of commercially available SARS-CoV-2 antibody tests should be interpreted with caution. A high proportion of antibody-positive patient sera demonstrated neutralizing capacity against SARS-CoV-2.


title: The inevitability of Covid-19 related distress among healthcare workers: findings from a low caseload country under lockdown

text: Objectives: To characterize psychological distress and factors associated with distress in healthcare practitioners working during a stringent lockdown in a country (Jordan) with one of the lowest incidence rates of Covid-19 globally. Methods: A cross-sectional online survey sent to physicians, nurses and technicians, and pharmacists working in various hospitals and community pharmacies. Demographic, professional and psychological characteristics (distress using Kessler-6 questionnaire, anxiety, depression, burnout, sleep issues, exhaustion) were measured as were potential sources of fear. Descriptive and multivariable statistics were performed using level of distress as the key outcome. Results: We surveyed 1,006 practitioners (55.3% females). Approximately 63%, 13%, 17% and 7% were nurses/technicians, physicians, pharmacists, and other nonmedical personnel (respectively). 32% suffered from high distress while 20% suffered from severe distress. Exhaustion, anxiety, depression, and sleep disturbances were reported (in past seven days) by approximately 34%, 34%, 19%, and 29% of subjects (respectively). Being older or male, perception of effective protective institutional measures, and being satisfied at work, were significantly associated with lower distress. Conversely, suffering burnout; reporting sleep-related functional problems; exhaustion; being a pharmacist (relative to a physician) and working in a cancer center; harboring fear about virus spreading; fear that the virus threatened life; fear of alienation from family/friends; and fear of workload increases, were significantly associated with higher distress. Conclusion: Despite low caseloads, Jordanian practitioners still experienced high levels of distress. Identified demographic, professional and psychological factors influencing distress should inform interventions to improve medical professional resilience and distress likelihood, regardless of the variable Covid-19 situation.


title: Clean manufacturing of Ti-6Al-4V under CO2-snow and hybrid nanofluids

text: Abstract During the machining of α+β intermetallic stable titanium alloy, their poor thermal conductivity and resistance at elevated temperature accumulates most of the shearing and friction heat. The resulting heat damage the cutting tool, causes in high power consumption, shorter tool life and poor surface quality. Therefore, it is important to choose a latest cooling technique with excellent capacity to remove heat, chips and frictional effects from the cutting zone. Therefore, Carbon dioxide snow (CO2-snow) and hybrid copper oxide (CuO)-multi-walled carbon nanotubes (MWCNTs) nanofluids based minimum quantity lubrication (MQL) are compared to achieve clean cooling/lubrication technique to machine biomedical/aerospace material Ti-6Al-4V. Taguchi L9 orthogonal array was applied to design the experiments. Critical machining parameters are cutting speed (m/min), feed (mm/rev), and cooling mode. The output responses are surface quality Ra (μm), cutting power Pc (W), cutting temperature T (oC), and tool life TL (min) were evaluated under CO2-snow and MQL-hybrid nanofluids. Findings have revealed less surface roughness and longer tool life under hybrid nanofluids. While CO2-snow has justified less temperature and power consumption at high cutting conditions.


Maybe not an overreaction


title: CoV-AbDab: the Coronavirus Antibody Database

text: The emergence of a novel strain of betacoronavirus, SARS-CoV-2, has led to a pandemic that has been associated with hundreds of thousands of deaths. Research is ongoing around the world to create vaccines and therapies to minimise rates of disease spread and mortality. Crucial to these efforts are molecular characterisations of neutralising antibodies to SARS-CoV-2. Such antibodies would be valuable for measuring vaccine efficacy, diagnosing exposure, and developing effective biotherapeutics. Here, we describe our new database, CoV-AbDab, which already contains data on over 380 published/patented antibodies and nanobodies known to bind to at least one betacoronavirus. This database is the first consolidation of antibodies known to bind SARS-CoV-2 and other betacoronaviruses such as SARS-CoV-1 and MERS-CoV. We supply relevant metadata such as evidence of cross-neutralisation, antibody/nanobody origin, full variable domain sequence (where available) and germline assignments, epitope region, links to relevant PDB entries, homology models, and source literature. Our preliminary analysis exemplifies a spectrum of potential applications for the database, including identifying characteristic germline usage biases in receptor-binding domain antibodies and contextualising the diagnostic value of the SARS-CoV binding CDRH3s through comparison to over 500 million antibody sequences from SARS-CoV serologically naive individuals. Community submissions are invited to ensure CoV-AbDab is efficiently updated with the growing body of data analysing SARS-CoV-2. CoV-AbDab is freely available and downloadable on our website at http://opig.stats.ox.ac.uk/webapps/coronavirus.


title: Contact Tracing Evaluation for COVID-19 Transmission during the Reopening Phase in a Rural College Town

text: Contact tracing can play a vital role in controlling human-to-human transmission of a highly contagious disease such as COVID-19. To investigate the benefits and costs of contact tracing, we develop an individual-based contact-network model and a susceptible-exposed-infected-confirmed (SEIC) epidemic model for the stochastic simulations of COVID-19 transmission. We estimate the unknown parameters (reproductive ratio R0 and confirmed rate {delta}2) by using observed confirmed case data. After a two month-lockdown, states in the USA have started the reopening process. We provide simulations for four different reopening situations: under "stay-at-home" order or no reopening, 25% reopening, 50% reopening, and 75% reopening. We model contact tracing in a two-layer network by modifying the basic SEIC epidemic model. The two-layer network is composed by the contact network in the first layer and the tracing network in the second layer. Since the full contact list of an infected individual patient can be hard to obtain, then we consider different fractions of contacts from 60% to 5%. The goal of this paper is to assess the effectiveness of contact tracing to control the COVID-19 spreading in the reopening process. In terms of benefits, simulation results show that increasing the fraction of traced contacts decreases the size of the epidemic. For example, tracing 20% of the contacts is enough for all four reopening scenarios to reduce the epidemic size by half. Considering the act of quarantining susceptible households as the contact tracing cost, we have observed an interesting phenomenon. When we increase the fraction of traced contacts from 5% to 20%, the number of quarantined susceptible people increases because each individual confirmed case is mentioning more contacts. However, when we increase the fraction of traced contacts from 20% to 60%, the number of quarantined susceptible people decreases because the increment of the mentioned contacts is balanced by a reduced number of confirmed cases. The main contribution of this research lies in the investigation of the effectiveness of contact tracing for the containment of COVID-19 spreading during the initial phase of the reopening process of the USA.


title: Knowledge and Beliefs of General Public of India on COVID-19: A Web-based Cross-sectional Survey

text: Context: Despite many awareness programs conducted by the governments and other agencies, there are certain false beliefs among the general public of India towards the transmission, prevention, and treatment of COVID-19. Aims: To assess the knowledge and beliefs of the general public of India on COVID-19. Materials and Methods: A web-based cross-sectional survey was conducted between 20th March and 15th April 2020. A 17-item questionnaire was developed, validated, and used for the study. The questionnaire was randomly distributed among the public using Google forms through social media networks. Descriptive analysis was performed to represent the study characteristics, Chi-square test for assessing the associations among the study variables, and logistic regression analysis for identifying the factors influencing the beliefs. Results: A total of 462 participants with a mean (SD) age of 30.66 (11.31) years were responded to the questionnaire. Study participants are having fairly good knowledge of the basic aspects of COVID-19. However, a considerable fraction of participants were having false beliefs towards the transmission of new coronavirus, and prevention & treatment of COVID-19. It was observed that the participants who were aged 31-60 years and >60 years, education level of intermediate or diploma and high school certificate, and occupation as the unskilled workers had more of false beliefs towards COVID-19 compared to their counterparts. Conclusion: Though the overall knowledge on COVID-19 was good enough among the general public of India, still there is a need for education to avoid false beliefs especially among the people who are elderly, having a low level of education, and non-professional workers.


title: What Types of COVID-19 Conspiracies are Populated by Twitter Bots?

text: With people moving out of physical public spaces due to containment measures to tackle the novel coronavirus (COVID-19) pandemic, online platforms become even more prominent tools to understand social discussion. Studying social media can be informative to assess how we are collectively coping with this unprecedented global crisis. However, social media platforms are also populated by bots, automated accounts that can amplify certain topics of discussion at the expense of others. In this paper, we study 43.3M English tweets about COVID-19 and provide early evidence of the use of bots to promote political conspiracies in the United States, in stark contrast with humans who focus on public health concerns.


title: Social response to early-stage government control measures of COVID-19 in Colombia: population survey, April 8-20 2020.

text: On Monday, March 16, 2020, the government of Colombia announced actions to control COVID-19. These recommendations directly affected the entire population and included: reducing physical contact; reducing mobility and cancelling unnecessary travel; working from home; cancelling mass events; a 14 day at-home isolation period for people who arrived from international trips, or in cases in which someone in the household experienced a high temperature and sustained coughing; as well as increasing the frequency of hand washing and the use of face masks on public transport. In order to understand the public sentiment around these recommendations, Asociacion Profamilia developed an online survey through SurveyMonkey. The survey was completed by 3549 adult people in Colombia (+18 years) between April 8 and April 20, 2020. The survey in Colombia has four components: 1) socio-demographic characteristics, 2) responsibility for care and employment, 3) perceptions on risk and health, and 4) behaviour changes and ability to isolate. The considered socio-demographic characteristics were age, gender, residential area, vulnerable groups, education level, ethnicity, marital status, city of residence, home ownership and type of health insurance. For the socio-economic level, five indicators were considered: education level, employment status, income, household savings and home ownership.


title: Analysis and Prediction of COVID-19 Characteristics Using a Birth-and-Death Model

text: Its spreading speed together with the risk of fatality might be the main characteristic that separates COVID-19 from other infectious diseases in our recent history. In this scenario, mathematical modeling for predicting the spread of the disease could have great value in containing the disease. Several very recent papers have contributed to this purpose. In this study we propose a birth-and-death model for predicting the number of COVID-19 active cases. It relation to the Susceptible-Infected-Recovered (SIR) model has been discussed. An explicit expression for the expected number of active cases helps us to identify a stationary point on the infection curve, where the infection ceases increasing. Parameters of the model are estimated by fitting the expressions for active and total reported cases simultaneously. We analyzed the movement of the stationary point and the basic reproduction number during the infection period up to the 20th of April 2020. These provide information about the disease progression path and therefore could be really useful in designing containment strategies.


title: Russian trolls speaking Russian: Regional Twitter operations and MH17

text: The role of social media in promoting media pluralism was initially viewed as wholly positive. However, some governments are allegedly manipulating social media by hiring online commentators (also known as trolls) to spread propaganda and disinformation. In particular, an alleged system of professional trolls operating both domestically and internationally exists in Russia. In 2018, Twitter released data on accounts identified as Russian trolls, starting a wave of research. However, while foreign-targeted English language operations of these trolls have received significant attention, no research has analyzed their Russian language domestic and regional-targeted activities. We address this gap by characterizing the Russian-language operations of Russian trolls. We first perform a descriptive analysis, and then focus in on the trolls' operation related to the crash of Malaysia Airlines flight MH17. Among other things, we find that Russian-language trolls have run 163 hashtag campaigns (where hashtag use grows abruptly within a month). The main political sentiments of such campaigns were praising Russia and Putin (29%), criticizing Ukraine (26%), and criticizing the United States and Obama (9%). Further, trolls actively reshared information with 76% of tweets being retweets or containing a URL. Additionally, we observe periodic temporal patterns of tweeting suggesting that trolls use automation tools. Further, we find that trolls' information campaign on the MH17 crash was the largest in terms of tweet count. However, around 68% of tweets posted with MH17 hashtags were likely used simply for hashtag amplification. With these tweets excluded, about 49% of the tweets suggested to varying levels that Ukraine was responsible for the crash, and only 13% contained disinformation and propaganda presented as news. Interestingly, trolls promoted inconsistent alternative theories for the crash.


title: Measuring COVID-19 and Influenza in the Real World via Person-Generated Health Data

text: Background: Since the beginning of the COVID-19 pandemic data from smartphones and connected sensors has been used to learn about symptoms presentation and management outside the clinic walls. However, reports on the validity of such data are still sparse, especially when it comes to symptom progression and relevance of wearable sensors. Objective: To understand the relevance of Person-GeneratedHealth Data (PGHD) as a means for early detection, monitoring and management of COVID-19 in everyday life. This includes quantifying prevalence and progression of symptoms from self-reports as well as changes in activity and physiological parameters continuously measured from wearable sensors, and contextualizing findings for COVID-19 patients with those from cohorts of flu patients. Design, Setting, and Participants: Retrospective digital cohort study of individuals with a self-reported positive SARS-CoV-2 or influenza test followed over the period 2019-12-02 to2020-04-27. Three cohorts were derived: Patients who self-reported being diagnosed with flu prior to the SARS-CoV-2 pandemic (N=6270, of which 1226 also contributed sensorPGHD); Patients who reported being diagnosed with flu during the SARS-CoV-2 pandemic (N=426, of which 85 also shared sensor PGHD); and patients who reported being diagnosed withCOVID-19 (N=230, of which sensor PGHD was available for 41).The cohorts were derived from a large-scale digital participatory surveillance study designed to track Influenza-like Illness(ILI) incidence and burden over time. Exposures: Self-reported demographic data, comorbidities, and symptoms experienced during a diagnosed ILI episode, including SARS-CoV-2.Physiological and behavioral parameters measured daily from commercial wearable sensors, includingResting Heart Rate (RHR), total step count, and nightly sleep hours. Main Outcomes and Measures: We investigated the percent-age of individuals experiencing symptoms of a given type (e.g.shortness of breath) across demographic groups and over time. We examined illness duration, and care seeking behavior, and how RHR, step count, and nightly sleep hours deviated from expected behavior on healthy days over the course of the infection episode. Results: Self-reported symptoms of COVID-19 present differently from flu. COVID-19 cases tended to last longer than flu(median of 12 vs. 9 days), are uniquely characterized by chest pain/pressure, shortness of breath, and anosmia. The fraction of elevated RHR measurements collected daily from commercial wearable devices rise significantly in the 2 days surrounding ILI symptoms onset, but does not appear to do so in a way specific to COVID-19. Steps lost due to COVID-19 persists for longer. Conclusion and Relevance: PGHD can be a valid source of longitudinal real world data to detect and monitor COVID-19-related symptoms and behaviors at population scale. PGHD may provide continuous, near realtime feedback to intervention effectiveness that otherwise requires waiting for symptoms to develop into contacts with the healthcare system. It has also the potential to increase pre-test probability of other downstream diagnostics. To effectively leverage PGHD for participatory surveillance it is crucial to invest in the creation of trusted, long-term communication channels with individuals through whichdata can be efficiently collected, consented, and contextualized,while protecting the privacy of individuals and ultimately facilitating the transition in and out of care.


title: ASAM recommends virtual treatment of SUD for some patients

text: The American Society for Addiction Medicine (ASAM) says residential substance use disorder (SUD) programs should treat patients with COVID-19 virtually, not in person The organization also says to screen new patients by phone before admission and upon arrival, screen current patients and staff, and, if visitors are permitted, screen them as well Screening is done clinically, not by test


Covid-19: Government by Decree


title: Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact in Spanish regions

text: Background: The COVID-19 pandemic is causing substantial increases in mortality worldwide. To provide an interpretable summary of the impact on mortality of the COVID-19 pandemic we estimate weekly and annual life expectancies at birth in Spain and its regions. Methods: We used daily death count data from the Spanish Daily Mortality Surveillance System, MoMo, and death counts from 2018, and population on 1 July, 2019 by region (CCAA), age groups, and sex from the Spanish National Statistics Institute. We estimated weekly and annual (2019 and 2020*, the shifted annual calendar period up to 10 May 2020) life expectancies at birth as well as their differences over a short period of time. Results: Weekly life expectancies at birth in Spain were lower in weeks 11-20, 2020 compared to the same weeks in 2019. This drop in weekly life expectancy was especially strong in weeks 13 and 14 (March 23rd to April 5th), with national declines ranging between 6.1 and 7.6 years and maximum regional weekly declines of up to 15 years in Madrid. Annual life expectancy differences between 2019 and 2020* also reflected an overall drop in annual life expectancy of 0.8 years for both men and women. These drops ranged between 0 years in several regions (e.g. Canary and Balearic Islands) to 2.7 years among men in Madrid. Conclusions: Weekly and annual life expectancy are easy to interpret measures for understanding the heterogeneity of mortality patterns across Spanish regions. Weekly life expectancy is a valuable indicator of the immediate intensity of health impacts from the pandemic. This sensitive indicator is also useful for understanding disparities and communicating the gravity of the situation because differences are expressed in intuitive year units.


title: Improved detection of antibody against SARS-CoV-2 by microsphere-based antibody assay

text: Objective: Currently available COVID-19 antibody tests using enzyme immunoassay (EIA) or immunochromatographic assay have variable sensitivity and specificity. Here, we developed and evaluated a novel microsphere-based antibody assay (MBA) for the detection of immunoglobulin G (IgG) against SARS-CoV-2 nucleoprotein (NP) and spike protein receptor binding domain (RBD). Method: We developed a microsphere-based assay (MBA) to determine the levels of IgG against SARS-CoV-2 NP and spike RBD. The seropositive cut-off mean fluorescent intensity (MFI) was set using a cohort of 294 anonymous serum specimens collected in 2018. The specificity was assessed using serum specimens collected from organ donors or influenza patients before 2020. Seropositive rate was determined among patients with COVID-19. Time-to-seropositivity and signal-to-cutoff (S/CO) ratio were compared between MBA and EIA. Results: MBA had a specificity of 100% (93/93; 95% confidence interval [CI], 96-100%) for anti-NP IgG and 98.9% (92/93; 95% CI 94.2-100%) for anti-RBD IgG. The MBA seropositive rate for convalescent serum specimens of COVID-19 patients were 89.8% (35/39) for anti-NP IgG and 79.5% (31/39) for anti-RBD IgG. The time-to-seropositivity was shorter with MBA than that of EIA. When compared with EIA, MBA could better differentiate between COVID-19 patients and negative controls with significantly higher S/CO ratio for COVID-19 patients and lower S/CO ratio with negative controls. MBA also had fewer specimens in the equivocal range (S/CO 0.9-1.1) than EIA. Conclusion: MBA is robust and simple, and is suitable for clinical microbiology laboratory for the accurate determination of anti-SARS-CoV-2 antibody for retrospective diagnosis, serosurveillance, and vaccine trials.


title: Assisting Scalable Diagnosis Automatically via CT Images in the Combat against COVID-19

text: The pandemic of coronavirus Disease 2019 (COVID-19) caused enormous loss of life globally. 1-3 Case identification is critical. The reference method is using real-time reverse transcription PCR (rRT-PCR) assays, with limitations that may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that application of deep learning (DL) to the 3D CT images could help identify COVID-19 infections. Using the data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 patients. COVIDNet achieved an accuracy rate of 94.3% and an area under the curve (AUC) of 0.98. Application of DL to CT images may improve both the efficiency and capacity of case detection and long-term surveillance.


The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial cities


title: Protocol for the development and evaluation of a tool for predicting risk of short-term adverse outcomes due to COVID-19 in the general UK population

text: Introduction: Novel coronavirus 2019 (COVID-19) has propagated a global pandemic with significant health, economic and social costs. Emerging emergence has suggested that several factors may be associated with increased risk from severe outcomes or death from COVID-19. Clinical risk prediction tools have significant potential to generate individualised assessment of risk and may be useful for population stratification and other use cases. Methods and analysis: We will use a prospective open cohort study of routinely collected data from 1205 general practices in England in the QResearch database. The primary outcome is COVID-19 mortality (in or out-of-hospital) defined as confirmed or suspected COVID-19 mentioned on the death certificate, or death occurring in a person with SARS-CoV-2 infection between 24th January and 30th April 2020. Our primary outcome in adults is COVID-19 mortality (including out of hospital and in hospital deaths). We will also examine COVID-19 hospitalisation in children. Time-to-event models will be developed in the training data to derive separate risk equations in adults (19-100 years) for males and females for evaluation of risk of each outcome within the 3-month follow-up period (24th January to 30th April 2020), accounting for competing risks. Predictors considered will include age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, pre-existing medical co-morbidities, and concurrent medication. Measures of performance (prediction errors, calibration and discrimination) will be determined in the test data for men and women separately and by ten-year age group. For children, descriptive statistics will be undertaken if there are currently too few serious events to allow development of a risk model. The final model will be externally evaluated in (a) geographically separate practices and (b) other relevant datasets as they become available. Ethics and dissemination: The project has ethical approval and the results will be submitted for publication in a peer-reviewed journal.


title: The spatial and cell-type distribution of SARS-CoV-2 receptor ACE2 in human and mouse brain

text: By engaging angiotensin-converting enzyme 2 (ACE2 or Ace2), the novel pathogenic SARS-coronavirus 2 (SARS-CoV-2) may invade host cells in many organs, including the brain. However, the distribution of ACE2 in the brain is still obscure. Here we investigated the ACE2 expression in the brain by analyzing data from publicly available brain transcriptome databases. According to our spatial distribution analysis, ACE2 was relatively highly expressed in some brain locations, such as the choroid plexus and paraventricular nuclei of the thalamus. According to cell-type distribution analysis, nuclear expression of ACE2 was found in many neurons (both excitatory and inhibitory neurons) and some non-neuron cells (mainly astrocytes, oligodendrocytes, and endothelial cells) in human middle temporal gyrus and posterior cingulate cortex. A few ACE2-expressing nuclei were found in a hippocampal dataset, and none were detected in the prefrontal cortex. Except for the additional high expression of Ace2 in the olfactory bulb areas for spatial distribution as well as in the pericytes and endothelial cells for cell-type distribution, the distribution of Ace2 in mouse brain was similar to that in the human brain. Thus, our results reveal an outline of ACE2/Ace2 distribution in the human and mouse brain, which indicates the brain infection of SARS-CoV-2 may be capable of inducing central nervous system symptoms in coronavirus disease 2019 (COVID-19) patients. Potential species differences should be considered when using mouse models to study the neurological effects of SARS-CoV-2 infection.


title: Caring geographies: The COVID-19 interregnum and a return to mutual aid

text: Mutual aid is the fundamental basis of all human societies, an understanding that is exemplified with striking clarity during times of crises. The coronavirus pandemic has brought the caring geographies of mutual aid into sharp relief with the failings of both capitalism and the state. Beyond fear and uncertainty, this commentary examines the one single theme that has resonated with the COVID-19 pandemic more than all others: care.


title: Efficacy of remdesivir versus placebo for the treatment of COVID-19: A protocol for systematic review and meta-analysis of randomized controlled trials

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


title: Management of ophthalmic perioperative period during 2019 novel coronavirus disease outbreak/ 新型冠状病毒肺炎疫情下眼科患者围手术期管理实践

text: Objective: To explore the perioperative management and infection prevention methods for acute eye diseases during the outbreak of 2019 novel coronavirus disease (COVID-19). Methods: Since the COVID-19 was included in the Class B infectious diseases and was managed according to Class A infectious diseases in China, 127 patients who underwent ophthalmic surgery were enrolled in First Affiliated Hospital of Army Military Medical University from January 20 to February 19, 2020.The perioperative management according to the national epidemic prevention and control requirements was summarized, and the perioperative clinical management that should be taken during the epidemic prevention period were discussed. Results: One hundred and twenty-seven patients underwent ophthalmic surgeries, including emergency surgery, daytime surgery and other surgeries for sight-threatening diseases.The methods of anesthesia included general anesthesia, local anesthesia and ocular superficial anesthesia.According to the national epidemic prevention and control requirements, epidemic screening for these patients and infectious managing measures were performed during the perioperative period, including the sterilization of relevant environment and equipments, the personal medical prevention and protection for medical staffs and patients, which made sure all the operations went smoothly and safely.There were no 2019-nCoV infection, surgical-relative infection, crossing infection and operation-related complications occurred.Meanwhile, there were not COVID-19-related infection events of medical staffs.The air sampling compliance rate in the operating room, ward, examination room and other areas was 100%. Conclusions: During the prevention and control period of the epidemic of COVID-19, strict adherence to the prevention and control measures can effectively ensure the smooth implementation of the operation and the perioperative safety of medical staff and patients.


title: SARS-CoV-2 Community Transmission During Shelter-in-Place in San Francisco

text: ABSTRACT Background: We characterized SARS-CoV-2 infections in a densely-populated, majority Latinx San Francisco community six-weeks into the city's shelter-in-place order. Methods: We offered SARS-CoV-2 reverse transcription-PCR and antibody (Abbott ARCHITECT IgG) testing, regardless of symptoms, to all residents (>=4 years) and workers in a San Francisco census tract (population: 5,174) at outdoor, community-mobilized events over four days. We estimated SARS-CoV-2 point prevalence (PCR-positive) and cumulative incidence (antibody or PCR-positive) in the census tract and evaluated risk factors for recent (PCR-positive/antibody-negative) versus prior infection (antibody-positive/PCR-negative). SARS-CoV-2 genome recovery and phylogenetics were used to measure viral strain diversity, establish viral lineages present, and estimate number of introductions. Results: We tested 3,953 persons: 40% Latinx; 41% White; 9% Asian/Pacific Islander; and 2% Black. Overall, 2.1% (83/3,871) tested PCR-positive: 95% were Latinx and 52% asymptomatic when tested. 1.7% of residents and 6.0% of workers (non-census tract residents) were PCR-positive. Among 2,598 census tract residents, estimated point prevalence of PCR-positives was 2.3% (95%CI: 1.2-3.8%): 3.9% (95%CI: 2.0-6.4%) among Latinx vs. 0.2% (95%CI: 0.0-0.4%) among non-Latinx persons. Estimated cumulative incidence among residents was 6.1% (95%CI: 4.0-8.6%). Prior infections were 67% Latinx, 16% White, and 17% other ethnicities. Among recent infections, 96% were Latinx. Risk factors for recent infection were Latinx ethnicity, inability to shelter-in-place and maintain income, frontline service work, unemployment, and household income <$50,000/year. Five SARS-CoV-2 phylogenetic lineages were detected. Conclusion: SARS-CoV-2 infections from diverse lineages continued circulating among low-income, Latinx persons unable to work from home and maintain income during San Francisco's shelter-in-place ordinance.


title: Shut and re-open: the role of schools in the spread of COVID-19 in Europe

text: We investigate the effect of school closure and subsequent reopening on the transmission of COVID-19, by considering Denmark, Norway, Sweden, and German states as case studies. By comparing the growth rates in daily hospitalisations or confirmed cases under different interventions, we provide evidence that the effect of school closure is visible as a reduction in the growth rate approximately 9 days after implementation. Limited school attendance, such as older students sitting exams or the partial return of younger year groups, does not appear to significantly affect community transmission. A large-scale reopening of schools while controlling or suppressing the epidemic appears feasible in countries such as Denmark or Norway, where community transmission is generally low. However, school reopening can contribute to significant increases in the growth rate in countries like Germany, where community transmission is relatively high. Our findings underscore the need for a cautious evaluation of reopening strategies that ensure low classroom occupancy and a solid infrastructure to quickly identify and isolate new infections.


title: Seroprevalence of COVID-19 virus infection in Guilan province, Iran

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


title: Risk Assessment of Healthcare Workers at the Frontline against COVID-19

text: The novel coronavirus disease 2019 (COVID-19) is a global pandemic. Healthcare workers (HCWs) are on the frontline of treating patients infected with COVID-19. However, data related to its infection rate among HCWs are limited. The aim was to present evidence associated with the number of HCWs being infected with COVID-19 from most viral affected countries (Italy, China, United States, Spain, and France). Furthermore, we looked into the reasons for HCWs COVID 19 infections and strategies to overcome this problem. Early available evidence suggested that HCWs are being increasingly infected with the novel infection ranging from 15% to 18% and in some cases up to 20% of the infected population. Major factors for infection among HCWs include lack of understanding of the disease, inadequate use and availability of Personal Protective Equipment (PPE), uncertain diagnostic criteria, unavailability of diagnostic tests and psychological stress. Therefore the protection of HCWs by authorities should be prioritized through education and training, the readiness of staff, incentives, availability of PPEs, and psychological support.


title: ACE 2 Coding Variants: A Potential X-linked Risk Factor for COVID-19 Disease

text: Viral genetic variants are widely known to influence disease progression among infected humans. Given the recent and rapid emergence of pandemic SARS-CoV-2 infection, the cause of COVID-19 disease, viral protein variants have attracted research interest. However, little has yet been written about genetic risk factors among human hosts. Human genetic variation has proven to affect disease progression and outcome for important diseases such as HIV infection and malaria infestation. The fact that the human ACE2 protein is encoded on the X chromosome means that males who carry rare ACE2 coding variants will express those variants in all ACE2-expressing cells, whereas females will typically express those variants in a mosaic distribution determined by early X-inactivation events. This sex-based difference in ACE2 expression has unique implications for epidemiological studies designed to assess host genetic factors influencing progression from asymptomatic SARS-coV-2 infection to COVID-19. Here we present theoretical modelling of rare ACE2 coding variants documented to occur naturally in several human superpopulations and subpopulations, and show that rare variants predicted to affect the binding of ACE2 to the SARS-CoV-2 spike protein exist in people. Though the rs4646116 (p.Lys26Arg) allele is found in 1 in 70 Ashkenazi Jewish males, and in 1 in 172 non-Finnish European males, this allele is found at higher frequencies in females. Furthermore, the class of missense ACE2 alleles predicted to affect SARS-CoV-2 binding are found in aggregate among 1.43% and 2.16% of Ashkenazi males and females, respectively, as well as in 0.58% and 1.24% of European males and females outside of Finland. These alleles are rarer in other population groups, and almost absent from East Asians genotyped to date. Though we are aware that full genome-wide and exome-wide sequencing studies may ultimately be required to assess human genetic susceptibility to SARS-CoV-2 fully, we argue on the basis of strong prior probabilities that genotyping of this class of alleles is justified in cases of atypical SARS-CoV-2 diseases, such as asymptomatic super-spreaders (if any are identified), and in neonatal/paediatric-onset COVID-19 disease. Even relatively rare susceptibility factors (1% or fewer carriers) may become quantitatively important in the context of hundreds of thousands of infections. A small number of asymptomatic carriers, or a small number of super-spreaders, or a small segment of the population that is disproportionately likely to require intensive care, can magnify the medical, social and economic impacts of a pandemic of this size. The speed of the pandemic and the large number of affected cases worldwide justify efforts to identify all possible risk factors for adverse outcomes, including efforts to identify genetic susceptibility factors in human hosts.


title: A TRANSPARENT, OPEN-SOURCE SIRD MODEL FOR COVID19DEATH PROJECTIONS IN INDIA

text: As India emerges from the lockdown with ever higher COVID19 case counts and a mounting death toll, reliable projections of case numbers and deaths counts are critical in informing policy decisions. We examine various existing models and their shortcomings. Given the amount of uncertainty surrounding the disease we choose a simple SIRD model with minimal assumptions enabling us to make robust predictions. We employ publicly available mobility data from Google to estimate social distancing covariates which influence how fast the disease spreads. We further present a novel method for estimating the uncertainty in our predictions based on first principles. To demonstrate, we fit our model to three regions (Spain, Italy, NYC) where the peak has passed and obtain predictions for the Indian states of Delhi and Maharashtra where the peak is desperately awaited.


title: A simple model to show the relative risk of viral aerosol infection and the benefit of wearing masks in different settings with implications for Covid-19 .

text: Background . Widespread use of masks in the general population is being used in many countries for Covid-19 . There has been reluctance on the part of the WHO and some governments to recommend this . Methodology . A basic model has been constructed to show the relative risk of aerosol from normal breathing in various situations together with the benefit from use of masks which is multiplicative . Results . Social distancing at 2 metres is validated but in confined areas is time limited and the use of masks in the absence of extremely good ventilation is important. Where social distancing is not possible at all times or an infectious person is in a confined area for a prolonged period there is a higher risk of infection requiring protection . Conclusions . The use of masks should be factored into models and used at an early stage as widespread use of more efficient masks could have a large impact on control and spread of infection . Public health planning requires stockpiling masks and encouraging everyone to have suitable masks in their household when supplies are normalised . The use of a cloth mask will be better than no protection at all .


title: Tracking and Classifying Global COVID-19 Cases by using 1D Deep Convolution Neural Network

text: The novel coronavirus disease (COVID-19) and pandemic has taken the world by surprise and simultaneously challenged the health infrastructure of every country. Governments have resorted to draconian measures to contain the spread of the disease despite its devastating effect on their economies and education. Tracking the novel coronavirus 2019 disease remains vital as it influences the executive decisions needed to tighten or ease restrictions meant to curb the pandemic. One-Dimensional(1D) Convolution Neural Networks (CNN) have been used classify and predict several time-series and sequence data. Here 1D-CNN is applied to the time-series data of confirmed COVID-19 cases for all reporting countries and territories. The model performance was 90.5% accurate. The model was used to develop an automated AI tracker web app (AI Country Monitor) and is hosted on https://aicountrymonitor.org. This article also presents a novel concept of pandemic response curves based on cumulative confirmed cases that can be use to classify the stage of a country or reporting territory. It is our firm believe that this Artificial Intelligence COVID-19 tracker can be extended to other domains such as the monitoring/tracking of Sustainable Development Goals (SDGs) in addition to monitoring and tracking pandemics.


title: Virologic and clinical characteristics for prognosis of severe COVID-19: a retrospective observational study in Wuhan, China

text: Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has progressed to a pandemic associated with substantial morbidity and mortality. The WHO and the United States Center for Disease Control and Prevention (CDC) have issued interim clinical guidance for management of patients with confirmed coronavirus disease (COVID-19), but there is limited data on the virologic and clinical characteristics for prognosis of severe COVID-19. Methods: A total of 50 patients with severe COVID-19 were divided into good and poor recovery groups. The dynamic viral shedding and serological characteristics of SARS-CoV-2 were explored. The risk factors associated with poor recovery and lung lesion resolutions were identified. In addition, the potential relationships among the viral shedding, the pro-inflammatory response, and lung lesion evolutions were characterized. Results: A total of 58% of the patients had poor recovery and were more likely to have a prolonged interval of viral shedding. The longest viral shedding was 57 days after symptom onset. Older age, hyperlipemia, hypoproteinemia, corticosteroid therapy, consolidation on chest computed-tomography (CT), and prolonged SARS-CoV-2 IgM positive were all associated with poor recovery. Additionally, the odds of impaired lung lesion resolutions were higher in patients with hypoproteinemia, hyperlipemia, and elevated levels of IL-4 and ferritin. Finally, viral shedding and proinflammatory responses were closely correlated with lung lesion evolutions on chest CT. Conclusions Patients with severe COVID-19 have prolonged SARS-CoV-2 infection and delayed intermittent viral shedding. Older age, hyperlipemia, hypoproteinemia, corticosteroid usage, and prolonged SARS-CoV-2 IgM positive might be utilized as predicative factors for the patients with poor recovery.


title: COVID-19 containment policies through time may cost more lives at metapopulation level

text: The rapid and pandemic spread of COVID-19 has led to unprecedented containment policies in response to overloaded health care systems. Disease mitigation strategies require informed decision-making to ensure a balance between the protection of the vulnerable from disease and the maintenance of global economies. We show that temporally restricted containment efforts, that have the potential to flatten epidemic curves, can result in wider disease spread and larger epidemic sizes in metapopulations. Longer-term rewiring of metapopulation networks or the enforcement of feasible long-term measures that decrease disease transmissions appear to be more efficient than temporarily restricted intensive mitigation strategies (e.g. short-term mass quarantine). Our results may inform balanced containment strategies for short-term disease spread mitigation in response to overloaded health care systems and longer-term epidemiological sizes.


title: Easing social distancing index after COVID-19 pandemic

text: Abstract Context Easing social distancing (ESD) is a global public health issue in post-pandemic period of COVID-19 and requires a simple index for real time assessment. Objective We aimed to develop a simple index for ESD to quantify the impacts of social distancing for reducing confirmed infected cases, optimal triage and care of patients for recovery, and critical care capacity for reducing death from COVID-19. Design, Setting, and Participants Data on the retrospective cohort of 185 countries with reported numbers on confirmed cases, recovery, and death from COVID-19 were retrieved from publicity available repository. Up to May 31, a total of 5,844,136 confirmed cases, 2,639,961 recovered, and 327,487 deaths were reported globally. Main Outcome Measures The ESD index measured by cumulative number of COVID-19 cases and recovery and case-fatality rate. Results We developed a simple index for the guidance of easing social distancing (ESD). If the ESD index is less than 1, ESD would be considered. The global ESD index declined from 3.87 at peak in March to 1.35 by the end of May, consisting of 56.76% countries/regions (105/185) with the ESD lower than one. Conclusion and Relevance This simple ESD index provides a quantitative assessment on whether and when to ease social distancing from local to global community.


title: Safety of hydroxychloroquine, alone and in combination with azithromycin, in light of rapid wide-spread use for COVID-19: a multinational, network cohort and self-controlled case series study

text: Background: Hydroxychloroquine has recently received Emergency Use Authorization by the FDA and is currently prescribed in combination with azithromycin for COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin. Methods: New user cohort studies were conducted including 16 severe adverse events (SAEs). Rheumatoid arthritis patients aged 18+ and initiating hydroxychloroquine were compared to those initiating sulfasalazine and followed up over 30 days. Self-controlled case series (SCCS) were conducted to further establish safety in wider populations. Separately, SAEs associated with hydroxychloroquine-azithromycin (compared to hydroxychloroquine-amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, Netherlands, Spain, UK, and USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (CalHRs) according to drug use. Estimates were pooled where I2<40%. Results: Overall, 956,374 and 310,350 users of hydroxychloroquine and sulfasalazine, and 323,122 and 351,956 users of hydroxychloroquine-azithromycin and hydroxychloroquine-amoxicillin were included. No excess risk of SAEs was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. SCCS confirmed these findings. However, when azithromycin was added to hydroxychloroquine, we observed an increased risk of 30-day cardiovascular mortality (CalHR2.19 [1.22-3.94]), chest pain/angina (CalHR 1.15 [95% CI 1.05-1.26]), and heart failure (CalHR 1.22 [95% CI 1.02-1.45]) Conclusions: Short-term hydroxychloroquine treatment is safe, but addition of azithromycin may induce heart failure and cardiovascular mortality, potentially due to synergistic effects on QT length. We call for caution if such combination is to be used in the management of Covid-19.


title: Don’t stand so close to me: Public spaces, behavioral geography, and COVID-19

text: COVID-19 is influencing how people engage with one another in geographic space. Stay-at-home orders and social distancing have reduced people’s bodily presences and social interactions in public spaces. Revisiting classical behavioral geography, this commentary explores the perception and engagement of geographic space among residents in the downtown core of a large metropolitan region in Texas during the COVID-19 pandemic.


title: Evaluating the burden of COVID-19 on hospital resources in Bahia, Brazil: A modelling-based analysis of 14.8 million individuals

text: Here we present a general compartment model with a time-varying transmission rate to describe the dynamics of the COVID-19 epidemic, parameterized with the demographics of Bahia, a state in northeast Brazil. The dynamics of the model are influenced by the number of asymptomatic cases, hospitalization requirements and mortality due to the disease. A locally-informed model was determined using actual hospitalization records. Together with cases and casualty data, optimized estimates for model parameters were obtained within a metaheuristic framework based on Particle Swarm Optimization. Our strategy is supported by a statistical sensitivity analysis on the model parameters, adequate to properly account for the simulated scenarios. First, we evaluated the effect of previously enforced interventions on the transmission rate. Then, we studied its effects on the number of deaths as well as hospitalization requirements, considering the state as a whole. Special attention is given to the impact of asymptomatic individuals on the dynamic of COVID-19 transmission, as these were estimated to contribute to a 68% increase in the basic reproductive number. Finally, we delineated scenarios that can set guides to protect the health care system, particularly by keeping demand below total bed occupancy. Our results underscore the challenges related to maintaining a fully capable health infrastructure during the ongoing COVID-19 pandemic, specially in a low-resource setting such as the one focused in this work. The evidences produced by our modelling-based analysis show that decreasing the transmission rate is paramount to success in maintaining health resources availability, but that current local efforts, leading to a 38% decrease in the transmission rate, are still insufficient to prevent its collapse at peak demand. Carefully planned and timely applied interventions, that result in stark decreases in transmission rate, were found to be the most effective in preventing hospital bed shortages for the longest periods.


Update on coronavirus disease 2019 (COVID-19)


title: How Social Media and 3D Printing Tackles the PPE Shortage during Covid - 19 Pandemic

text: During the recent Covid-19 pandemic, additive Technology and Social Media were used to tackle the shortage of Personal Protective Equipment. A literature review and a social media listening software were employed to explore the number of the users referring to specific keywords related to 3D printing and PPE. Additionally, the QALY model was recruited to highlight the importance of the PPE usage. More than 7 billion users used the keyword covid or similar in the web while mainly Twitter and Facebook were used as a world platform for PPE designs distribution through individuals. More than 100 different 3D printable PPE designs were developed.


Spike in Poison Control Calls Related to Disinfectant Exposures


Australia and the Covid-19 crisis


title: Transmission of SARS-CoV-2 by inhalation of respiratory aerosol in the Skagit Valley Chorale superspreading event

text: During the 2020 COVID-19 pandemic, an outbreak occurred following attendance of a symptomatic index case at a regular weekly rehearsal on 10 March of the Skagit Valley Chorale (SVC). After that rehearsal, 53 members of the SVC among 61 in attendance were confirmed or strongly suspected to have contracted COVID-19 and two died. Transmission by the airborne route is likely. It is vital to identify features of cases such as this so as to better understand the factors that promote superspreading events. Based on a conditional assumption that transmission during this outbreak was by inhalation of respiratory aerosol, we use the available evidence to infer the emission rate of airborne infectious quanta from the primary source. We also explore how the risk of infection would vary with several influential factors: the rates of removal of respiratory aerosol by ventilation; deposition onto surfaces; and viral decay. The results indicate an emission rate of the order of a thousand quanta per hour (mean [interquartile range] for this event = 970 [680-1190] quanta per hour) and demonstrate that the risk of infection is modulated by ventilation conditions, occupant density, and duration of shared presence with an infectious individual.


title: COVID-19 Scenarios: an interactive tool to explore the spread and associated morbidity and mortality of SARS-CoV-2

text: The ongoing SARS-CoV-2 pandemic has caused large outbreaks around the world and every heavily affected community has experienced a substantial strain on the health care system and a high death toll. Communities therefore have to monitor the incidence of COVID-19 carefully and attempt to project the demand for health care. To enable such projections, we have developed an interactive web application that simulates an age-structured SEIR model with separate compartments for severely and critically ill patients. The tool allows the users to modify most parameters of the model, including age specific assumptions on severity. Infection control and mitigation measures that reduce transmission can be specified, as well as age-group specific isolation. The simulation of the model runs entirely on the client side in the browser; all parameter settings and results of the simulation can be exported for further downstream analysis. The tool is available at covid19-scenarios.org and the source code at github.com/neherlab/covid19_scenarios.


title: SIR-simulation of Corona pandemic dynamics in Europe

text: The SIR (susceptible-infected-removed) model, statistical approach to the parameter identification and the official WHO daily data about the confirmed cumulative number of cases were used to estimate the characteristics of COVID-19 pandemic in Italy, Spain, Germany, France, Austria and Moldova. The final sizes and durations of epidemic outbreaks in these countries are calculated.


title: Excess of Cardiovascular Deaths During the COVID-19 Pandemic in Brazilian Capital Cities

text: Introduction: During the COVID-19 pandemic, excess mortality has been reported, while hospitalizations for acute cardiovascular events reduced. Brazil is the second country with more deaths due to COVID-19. We aimed to evaluate excess cardiovascular mortality during COVID-19 pandemic in 6 Brazilian capital cities. Methods: Using the Civil Registry public database, we evaluated total and cardiovascular excess deaths, further stratified in ACS, stroke and unspecified cardiovascular deaths in the 6 Brazilian cities with greater number of COVID-19 deaths (Sao Paulo, Rio de Janeiro, Fortaleza, Recife, Belem, Manaus). We compared data from epidemiological weeks 12 to 22 of 2020, with the same period in 2019. We also compared the number of hospital and home deaths during the period. Results: There were 69,328 deaths and 17,877 COVID-19 deaths in the studied period and cities for 2020. Cardiovascular mortality increased in most cities, with greater magnitude in the Northern capitals. However, while there was a reduction in ACS and stroke in the most developed cities, the Northern capitals showed an increase of these events. For unspecified cardiovascular deaths, there was a marked increase in all cities, which strongly correlated to the rise in home deaths (r=0.86, p=0.01). Conclusion: The excess cardiovascular mortality was greater in the less developed cities, possibly associated with healthcare collapse. ACS and stroke deaths decreased in the most developed cities, in parallel with an increase in unspecified cardiovascular and home deaths, presumably as a result of misdiagnosis. Conversely, ACS and stroke deaths increased in cities with a healthcare collapse.


title: Forcing Seasonality of influenza-like epidemics with daily Solar resonance

text: Seasonality of acute viral respiratory diseases is a well-known and yet not fully understood phenomenon. Here we show that such seasonality, as well as the distribution of viral disease's epidemics with latitude on Earth, can be fully explained by the virucidal properties of UV-B and A Solar photons through a daily, minute-scale, resonant forcing mechanism. Such an induced periodicity can last, virtually unperturbed, from tens to hundreds of cycles, and even in presence of internal dynamics (host's loss of immunity) much slower than seasonal will, on a long period, generate seasonal oscillations.


title: Modeling and predicting the spread of COVID-19 in Lebanon: A Bayesian perspective

text: In this article, we investigate the problem of modelling the trend of the current Coronavirus disease 2019 pandemic in Lebanon along time. Two different models were developed using Bayesian Markov chain Monte Carlo simulation methods. The models fitted included Poisson autoregressive as a function of a short-term dependence only and Poisson autoregressive as a function of both a short-term dependence and a long-term dependence. The two models are compared in terms of their predictive ability using root mean squared error and deviance information criterion. The Poisson autoregressive model that allows to capture both short and long term memory effects performs best under all criterions. The use of such a model can greatly improve the estimation of number of new infections, and can indicate whether disease has an upward/downward trend, and where about every country is on that trend, so that containment measures can be applied and/or relaxed.


Preventing suicide in the context of the COVID‐19 pandemic


Can an anti-HIV combination or other existing drugs outwit the new coronavirus?


title: Severe acute respiratory syndrome coronavirus 2 and coronavirus disease 2019

text: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been confirmed as the etiological pathogen of the coronavirus disease 2019 (COVID-19) SARS-CoV-2 is the seventh member of coronavirus family that can infect humans after the emergence of the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) SARS-CoV-2 is a single-stranded, positive-sense RNA virus Due to its strong infectiousness and the lack of immunity in humans, the epidemic of the COVID-19 is still spreading On January 30, 2020 (local time), the World Health Organization (WHO) defined the epidemics of SARS-CoV-2-infected pneumonia as a Public Health Emergency of International Concern (PHEIC) This paper reviews the etiology and pathogenicity of SARS-CoV-2, and the detection and diagnosis, prevention and control, as well as the treatment of COVID-19


title: Potential Role of ACE2 in Coronavirus Disease 2019 (COVID-19) Prevention and Management

text: COVID-19 is the current public health threat all over the world. Unfortunately, there is no specific prevention and treatment strategy for this disease. We aim to explore the potential role of angiotensin-converting enzyme 2 (ACE2) in this regard through this literature review. As a crucial enzyme of renin-angiotensin-aldosterone system (RAAS), ACE2 not only mediates the virus entry but also affects the pathophysiological process of virus-induced acute lung injury (ALI), as well as other organs’ damage. As interaction of COVID-19 virus spike and ACE2 is essential for virus infection, COVID-19-specific vaccine based on spike protein, small molecule compound interrupting their interaction, human monoclonal antibody based on receptor-binding domain, and recombinant human ACE2 protein (rhuACE2) have aroused the interests of researchers. Meanwhile, ACE2 could catalyze angiotensin II (Ang II) to form angiotensin 1-7 (Ang 1-7), thus alleviates the harmful effect of Ang II and amplifies the protection effect of Ang1-7. ACE inhibitor and angiotensin II receptor blocker (ARB) have been shown to increase the level of expression of ACE2 and could be potential strategies in protecting lungs, heart, and kidneys. ACE2 plays a very important role in the pathogenesis and pathophysiology of COVID-19 infection. Strategies targeting ACE2 and its ligand, COVID-19 virus spike protein, may provide novel method in the prevention and management of novel coronavirus pneumonia.


title: Novel SARS-CoV-2 specific antibody and neutralization assays reveal wide range of humoral immune response during COVID-19

text: Development of antibody protection during SARS-CoV-2 (CoV-2) infection is a pressing question for public health and for vaccine development. We developed highly sensitive CoV-2-specific antibody and neutralization assays. CoV-2 Spike protein or Nucleocapsid protein specific IgG antibodies at titers more than 1:100,000 were detectable in all PCR+ subjects (n=87) and were absent in the negative controls. Other isotype antibodies (IgA, IgG1-4) were also detected. CoV-2 neutralization was determined in COVID-19 and convalescent plasma up to 10,000-fold dilution, using Spike protein pseudotyped lentiviruses, which was also blocked by neutralizing antibodies (NAbs). Hospitalized patients had up to 3000-fold higher antibody and neutralization titers compared to outpatients or convalescent plasma donors. Further, subjects who donated plasma further out from the diagnosis of COVID-19 appeared to have lower titers. Interestingly, some COVID-19 patients also contained NAbs against SARS Spike protein pseudovirus. Together these results demonstrate the high specificity and sensitivity of our assays, which may impact understanding the quality or duration of the antibody response during COVID-19 and in determining the effectiveness of potential vaccines.