title: The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States

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


title: FAR AWAY FROM HERD IMMUNITY TO SARS-CoV-2: results from a survey in healthy blood donors in South Eastern Italy

text: Here we present results from a survey on anti-SARS-CoV-2 seroprevalence in healthy blood donors from a low incidence COVID-19 area (Apulia region, South Eastern Italy). Among 904 subjects tested, only in 9 cases (0.99%) antibodies against SARS-CoV-2 were demonstrated. All the 9 seropositive patients were negative for the research of viral RNA by RT-PCR in nasopharyngeal swab. These data, along with those recently reported from other countries, clearly show that we are very far from herd immunity and that the containment measures are at the moment the only realistic instrument we have to slow the spread of the pandemic.


title: Profiling ACE2 expression in colon tissue of healthy adults and colorectal cancer patients by single-cell transcriptome analysis

text: A newly identified novel coronavirus (2019-nCoV) has caused numerous acute respiratory syndrome cases in Wuhan China from December 2019 to Feb 2020. Its fast spreading to other provinces in China and overseas is very likely causing a pandemic. Since the novel coronavirus has been reported to be capable of endangering thousands of lives, it is extremely important to find out how the coronavirus is transmitted in human organs. Apart from fever and respiratory complications, gastrointestinal symptoms are observed in some patients with 2019-nCoV but the significance remains undetermined. The cell receptor angiotensin covering enzyme II (ACE2), which is the major receptor of SARS-nCoV, has been reported to be a cellular entry receptor of 2019-nCoV as well. Here, to more precisely explore the potential pathogen transmission route of the 2019-nCoV infections in the gastrointestinal tract, we analyzed the ACE2 RNA expression profile in the colon tissue of healthy adults and colorectal cancer patients of our cohort and other databases. The data indicates that ACE2 is mainly expressed in epithelial cells of the colon. The expression of ACE2 is gradually increased from healthy control, adenoma to colorectal cancer patients in our cohort as well as in the external Asian datasets. According to the expression profile of ACE2 in colon epithelial cells, we speculate adenoma and colorectal cancer patients are more likely to be infected with 2019-nCoV than healthy people. Our data may provide a theoretical basis for the classification and management of future 2019-nCoV susceptibility people in clinical application.


title: Going to “War”: Military Approach as the Antidote to Defeating COVID-19

text: War metaphors are consistently utilized during times of adversity in popular culture, with the current global pandemic being no exception. This paper discusses use of war analogies to conjure images of bravery and sacrifice, while noting that these images tend to focus exclusively on the negative aspects of war. Taking analogies of war further, this paper expands on how the use of other military strategies and experiences, such as a mission-focused approach, clear leadership, and building resilience may indeed positively impact our global effort to slow the spread of SARS-COV-2.


title: Making Do During a Pandemic: Morally Distressing and Injurious Events.

text: The coronavirus disease (COVID-19) pandemic has placed nurses and other health care professionals in morally distressing situations related to personal safety, resource allocation, and family versus public care needs Making do, referring to managing with insufficient means, has been the norm of pandemic testing and care Health care professionals and essential employees at the sharp point of care and service have been required to pay the price associated with this new normal Some have described these crushingly difficult circumstances as contributing to moral injury and moral distress Nurses, physicians, and other essential professionals are affirmatively responding to demands for their services while acknowledging that necessary clinical equipment and protective gear are unavailable in the quantities required for safe care delivery Moral injury is unique from moral distress Moral injury has its roots in war and was diagnosed in veterans harmed after perpetrating, failing to thwart, or witnessing acts that violated their deeply held moral convictions and expectations


title: Evaluation of nine commercial SARS-CoV-2 immunoassays

text: Due to urgency and demand, numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoassays are rapidly being developed and placed on the market with limited validation on clinical samples. Thorough validation of serological tests are required to facilitate their use in the accurate diagnosis of SARS-CoV-2 infection, confirmation of molecular results, contact tracing, and epidemiological studies. This study evaluated the sensitivity and specificity of nine commercially available serological tests. These included three enzyme-linked immunosorbent assays (ELISAs) and six point-of-care (POC) lateral flow tests. The assays were validated using serum samples from: i) SARS-CoV-2 PCR-positive patients with a documented first day of disease; ii) archived sera obtained from healthy individuals before the emergence of SARS-CoV-2 in China; iii) sera from patients with acute viral respiratory tract infections caused by other coronaviruses or non-coronaviruses; and iv) sera from patients positive for dengue virus, cytomegalovirus and Epstein Barr virus. The results showed 100% specificity for the Wantai SARS-CoV-2 Total Antibody ELISA, 93% for the Euroimmun IgA ELISA, and 96% for the Euroimmun IgG ELISA with sensitivities of 90%, 90%, and 65%, respectively. The overall performance of the POC tests according to manufacturer were in the rank order of AutoBio Diagnostics > Dynamiker Biotechnology = CTK Biotech > Artron Laboratories > Acro Biotech ≥ Hangzhou Alltest Biotech. Overall, these findings will facilitate selection of serological assays for the detection SARS-CoV-2-specific antibodies towards diagnosis as well as sero-epidemiological and vaccine development studies.


title: COVID-19 impact on consecutive neurological patients admitted to the emergency department

text: Abstract Objective: Aim of this study was to analyse the impact of COVID-19 on clinical and laboratory findings and outcome of neurological patients consecutively admitted to the emergency department (ED) of a tertiary hub center. Methods: All adult patients consecutively admitted to the ED for neurological manifestations from February 20 th through April 30 th 2020 at Spedali Civili of Brescia entered the study. Demographic, clinical, and laboratory data were extracted from medical records and compared between patients with and without COVID-19. Results: Out of 505 consecutively patients evaluated at ED with neurological symptoms, 147 (29.1%) tested positive for SARS-CoV-2. These patients displayed at triage higher values of CRP, AST, ALT, and fibrinogen but not lymphopenia (p<0.05). They were older (73.1 + 12.4 vs 65.1 + 18.9 years, p=0.001) had higher frequency of stroke (34.7% vs 29.3%), encephalitis/meningitis (9.5% vs 1.9%) and delirium (16.3% vs 5.0%). Compared to patients without COVID, they were more frequently hospitalized (91.2% vs 69.3%, p<0.0001) and showed higher mortality rates (29.7% vs 1.8%, p<0.0.001) and discharge disability, independently from age. Conclusions: COVID-19 impacts on clinical presentation of neurological disorders, with higher frequency of stroke, encephalitis and delirium, and was strongly associated with increased hospitalisation, mortality and disability.


title: Temporal signal and the phylodynamic threshold of SARS-CoV-2

text: The ongoing SARS-CoV-2 outbreak marks the first time that large amounts of genome sequence data have been generated and made publicly available in near real-time. Early analyses of these data revealed low sequence variation, a finding that is consistent with a recently emerging outbreak, but which raises the question of whether such data are sufficiently informative for phylogenetic inferences of evolutionary rates and time scales. The phylodynamic threshold is a key concept that refers to the point in time at which sufficient molecular evolutionary change has accumulated in available genome samples to obtain robust phylodynamic estimates. For example, before the phylodynamic threshold is reached, genomic variation is so low that even large amounts of genome sequences may be insufficient to estimate the virus’s evolutionary rate and the time scale of an outbreak. We collected genome sequences of SARS-CoV-2 from public databases at 8 different points in time and conducted a range of tests of temporal signal to determine if and when the phylodynamic threshold was reached, and the range of inferences that could be reliably drawn from these data. Our results indicate that by February 2nd 2020, estimates of evolutionary rates and time scales had become possible. Analyses of subsequent data sets, that included between 47 to 122 genomes, converged at an evolutionary rate of about 1.1×10−3 subs/site/year and a time of origin of around late November 2019. Our study provides guidelines to assess the phylodynamic threshold and demonstrates that establishing this threshold constitutes a fundamental step for understanding the power and limitations of early data in outbreak genome surveillance.


title: Work Related and Personal Predictors of Covid 19 transmission

text: The paper provides new evidence from a survey of 2000 individuals in the US and UK related to predictors of Covid-19 transmission. Specifically, it investigates work and personal predictors of transmission experience reported by respondents using regression models to better understand possible transmission pathways and mechanisms in the community. Three themes emerge from the analysis. Firstly, transport roles and travelling practices are significant predictors of infection. Secondly, evidence from the US especially shows union membership, consultation over safety measures and the need to use public transport to get to work are also significant predictors. This is interpreted as evidence of the role of deprivation and of reactive workplace consultations. Thirdly and finally, there is some, often weaker, evidence that income, car-owership, use of a shared kitchen, university degree type, risk-aversion, extraversion and height are predictors of transmission. The comparative nature of the evidence indicates that the less uniformly stringent nature of the US lockdown provides more information about both structural and individual factors that predict transmission. The evidence about height is discussed in the context of the aerosol transmission debate. The paper concludes that both structural and individual factors must be taken into account when predicting transmission or designing effective public health measures and messages to prevent or contain transmission.


title: Epidemiological and clinical characteristics of COVID-19 in Shenzhen, the largest migrant city of China

text: We conducted a retrospective study among 417 confirmed COVID-19 cases from Jan 1 to Feb 28, 2020 in Shenzhen, the largest migrant city of China, to identify the epidemiological and clinical features in settings of high population mobility. We estimated the median incubation time to be 5.0 days. 342 (82.0%) cases were imported, 161 (38.6%) cases were identified by surveillance, and 247 (59.2%) cases were reported from cluster events. The main symptoms on admission were fever and dry cough. Most patients (91.4%) had mild or moderate illnesses. Age of 50 years or older, breathing problems, diarrhea, and longer time between the first medical visit and admission were associated with higher level of clinical severity. Surveillance-identified cases were much less likely to progress to severe illness. Although the COVID-19 epidemic has been contained in Shenzhen, close monitoring and risk assessments are imperative for prevention and control of COVID-19 in future.


title: Discovery of Drug-like Ligands for the Mac1 Domain of SARS-CoV-2 Nsp3

text: The Mac1 domain of the multifunctional SARS-CoV-2 non-structural protein 3 (nsp3) is a potential COVID-19 drug target because it is suspected to enhance the ability of the virus to evade the human immune system. The SARS-CoV-2 Mac1 domain binds ADP-ribose and proteins harboring this important post-translational modification. Small molecules that bind the Mac1 domain in place of ADP-ribose might therefore be useful as molecular probes or scaffolds for antiviral drug discovery. Two high throughput screens were used here to identify such ligands in small libraries of drugs and drug-like compounds. The first screen used differential scanning fluorimetry (DSF, aka the thermal shift or ThermoFluor assay) to examine the melting temperature of SARS-CoV-2 Mac1 domain in the presence of various compounds. In the second screen, various high-resolution SARS-CoV-2 Mac1 structures were used with Autodock VINA to identify potential ligands. Numerous hit compounds were either steroids (estradiol valerate & flunisolide), beta-lactams (cefaclor & cefatrizine), or benzimidazoles (telmisartan, rabeprazole, omeprazole, & esomeprazole). Isothermal titration calorimetry was used to confirm that rabeprazole, omeprazole, and compounds in other chemical classes, such as irinotecan, nifedipine, trifluoperazine, bind SARS-CoV-2 Mac1 with an affinity similar to ADP-ribose.


title: Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections

text: Background: The outbreak of novel coronavirus pneumonia (NCP) caused by 2019-nCoV spread rapidly, and elucidation the diagnostic accuracy of different respiratory specimens is crucial for the control and treatment of this diseases. Methods: Respiratory samples including nasal swabs, throat swabs, sputum and bronchoalveolar lavage fluid (BALF) were collected from Guangdong CDC confirmed NCP patients, and viral RNAs were detected using a CFDA approved detection kit. Results were analyzed in combination with sample collection date and clinical information. Finding: Except for BALF, the sputum possessed the highest positive rate (74.4%~88.9%), followed by nasal swabs (53.6%~73.3%) for both severe and mild cases during the first 14 days after illness onset (d.a.o). For samples collected ≥ 15 d.a.o, sputum and nasal swabs still possessed a high positive rate ranging from 42.9%~61.1%. The positive rate of throat swabs collected ≥ 8 d.a.o was low, especially in samples from mild cases. Viral RNAs could be detected in all the lower respiratory tract of severe cases, but not the mild cases. CT scan of cases 02, 07 and 13 showed typical viral pneumonia with ground glass opacity, while no viral RNAs were detected in first three or all the upper respiratory samples. Interpretation: Sputum is most accurate for laboratory diagnosis of NCP, followed by nasal swabs. Detection of viral RNAs in BLAF is necessary for diagnosis and monitoring of viruses in severe cases. CT scan could serve as an important make up for the diagnosis of NCP. Funding National Science and Technology Major Project, Sanming Project of Medicine and China Postdoctoral Science Foundation.


title: An Epidemiological Study on COVID-19: A Rapidly Spreading Disease

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


title: A Proposed Randomized, Double Blind, Placebo Controlled Study Evaluating Doxycycline for the Prevention of COVID-19 Infection and Disease In Healthcare Workers with Ongoing High Risk Exposure to COVID-19

text: This paper proposes both a rationale and potential study design for evaluation of low dose doxycycline (20mg BID) for the prevention of COVID-19 infection in exposed health care workers. More generally, it provides a potential study design blueprint to other investigators for any interventional COVID-19 study looking to evaluate interventions for prevention or treatment of COVID-19 infection. This specific study described is a randomized, double blind, placebo controlled study to evaluate the efficacy and safety of doxycycline for the prevention of COVID-19 infection and disease in healthcare workers with ongoing high risk exposure to COVID-19. This study would consist of a 50-day Treatment Period (Day 0-Day 50), followed by an End of Study Visit, approximately 30 days after completion of study drug dosing. Initially, for approximately the first 4 to 6 weeks, an initial open-label arm would be enrolled with up to 1938 subjects who will be assigned to take 20mg doxycycline BID. In the double blind, placebo controlled arms approximately 3,692 participants would be randomized to either doxycycline or placebo for 50 days. Doxycycline is a rational candidate drug to be evaluated for repurposing against SARS-CoV-2. Doxycycline is a generally safe tetracycline derivative that has been available for decades, most commonly dosed at 100mg BID to treat bacterial infections. However, in addition to its anti-microbial properties, doxycycline (and more generally tetracycline derivatives) may have a role as an effective anti-viral agent and as an anti-inflammatory drug. Early studies indicate potential efficacy of minocycline against respiratory syncytial virus (RSV) [12], and doxycycline against Dengue and Chikungunya infection[9, 10]. In addition, doxycycline is known or proposed to target several pathways that regulate viral replication. [13, 14, 15]. Doxycycline is a particularly attractive candidate as a COVID-19 prophylactic given it has been used in clinical practice for decades and maintains an excellent safety profile as demonstrated in multiple clinical studies. Any effective prophylaxis for COVID-19 should be able to demonstrate high efficacy at preventing infection and/or lowering severity of disease. Equally important, it should demonstrate this efficacy at dosing levels that are highly unlikely to precipitate any untoward severe side effects. Doxycycline has been selected based on its ability to: 1) inhibit metalloproteinases (MMPs), implicated in initial viral entry into the cell as well as in acute respiratory distress syndrome (ARDS) associated with severe COVID-19 infection [13, 16]; 2) potential to inhibit Papain-like proteinase (PLpro) responsible for proteolytic cleavage of the replicase polyprotein to release non-structural proteins 1, 2 & 3 (Nsp1, Nsp2 and Nsp3) all essential for viral replication. [19]; 3) potential to inhibit 3C-like main protease (3CLpro) or Nsp5 which is cleaved from the polyproteins causes further cleavage of Nsp4-16 and mediates maturation of Nsps which is essential in the virus lifecycle. [19]; 4) act as an ionophore help transport Zinc intracellularly, increasing cellular concentrations of Zinc to inhibit viral replication. [6, 15]; 5) inhibit Nf-kB which may lower inflammatory response to COVID-19 infection, and lower risk of viral entry due to decreasing DPP4 cell surface receptor. [20, 21]; 6) inhibits (specifically low-dose doxycycline) expression of CD147/EMMPRIN that may be necessary for SARS-CoV-2 entry into T lymphocytes [22, 23].


title: Sensitivity of Nasopharyngeal, Nasal and Throat Swab for the Detection of SARS-CoV-2

text: Nasopharyngeal (NP), nasal and throat swabs are the most practical specimen sources to test for upper respiratory pathogens. We compared the sensitivity of NP, nasal and throat swabs to detect SARS-CoV-2 in community patients. Using detection at any site as the standard, the sensitivities were 90%, 80% and 87% for NP, nasal and throat respectively (n=30 positive at any site). Throat swabs are likely a suitable alternative to NP swabs for the detection of COVID-19 infections.


title: Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States

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


title: An agent-based epidemic model REINA for COVID-19 to identify destructive policies

text: Background. Countries have adopted disparate policies in tackling the COVID-19 coronavirus pandemic. For example, South Korea started a vigorous campaign to suppress the virus by testing patients with respiratory symptoms and tracing and isolating all their contacts, and many European countries are trying to slow down the spread of the virus with varying degrees of shutdowns. There is clearly a need for a model that can realistically simulate different policy actions and their impacts on the disease and health care capacity in a country or a region. Specifically, there is a need to identify destructive policies, i.e. policies that are, based on scientific knowledge, worse than an alternative and should not be implemented. Methods. We developed an agent-based model (REINA) using Python and accelerated it by the Cython optimising static compiler. It follows a population over time at individual level at different stages of the disease and estimates the number of patients in hospitals and in intensive care. It estimates death rates and counts based on the treatment available. Any number of interventions can be added on the timeline from a selection including e.g. physical isolation, testing and tracing, and controlling the amount of cases entering the area. The model has open source code and runs online. Results. The model uses the demographics of the Helsinki University Hospital region (1.6 million inhabitants). A mitigation strategy aims to slow down the spread of the epidemic to maintain the hospital capacity by implementing mobility restrictions. A suppression strategy initially consists of the same restrictions but also aggressive testing, tracing, and isolating all coronavirus positive patients and their contacts. The modelling starting point is 2020-02-18. The strategies follow the actual situation until 2020-04-06 and then diverge. The default mitigation scenario with variable 30−40% mobility reduction appears to delay the peak of the epidemic (as intended) but not suppress the disease. In the suppression strategy, active testing and tracing of patients with symptoms and their contacts is implemented in addition to 20−25% mobility reduction. This results in a reduction of the cumulative number of infected individuals from 820 000 to 80 000 and the number of deaths from 6000 to only 640, when compared with the mitigation strategy (during the first year of the epidemic). Discussion. The agent-based model (REINA) can be used to simulate epidemic outcomes for various types of policy actions on a timeline. Our results lend support to the strategy of combining comprehensive testing, contact tracing and targeted isolation measures with social isolation measures. While social isolation is important in the early stages to prevent explosive growth, relying on social isolation alone (the mitigation strategy) appears to be a destructive policy. The open-source nature of the model facilitates rapid further development. The flexibility of the modelling logic supports the future implementation of several already identified refinements in terms of more realistic population models and new types of more specific policy interventions. Improving estimates of epidemic parameters will make it possible to improve modelling accuracy further.


title: Emergence of multiple variants of SARS-CoV-2 with signature structural changes

text: This study explores the divergence pattern of SARS-CoV-2 using whole genome sequences of the isolates from various COVID-19 affected countries. The phylogenomic analysis indicates the presence of at least four distinct groups of the SARS-CoV-2 genomes. The emergent groups have been found to be associated with signature structural changes in specific proteins. Also, this study reveals the differential levels of divergence patterns for the protein coding regions. Moreover, we have predicted the impact of structural changes on a couple of important viral proteins via structural modelling techniques. This study further advocates for more viral genetic studies with associated clinical outcomes and hosts’ response for better understanding of SARS-CoV-2 pathogenesis enabling better mitigation of this pandemic situation.


title: Molecular modelling predicts SARS-CoV-2 ORF8 protein and human complement Factor 1 catalytic domain sharing common binding site on complement C3b

text: Function of Open Reading Frame 8 (ORF8) protein of SARS-CoV-2 is still unclear. Here, we predict the functional role of ORF8 of SARS-CoV-2 in the context of host-pathogen relationship and the impact of mutations acquired during transmission. Mutational entropy analysis of 1042 ORF8 sequences of SARS-CoV-2 reveals a remarkable conservation among all isolates with high propensity of mutations only at amino-acid positions S24, V62, and L84. Search for structural homolog of ORF8 protein identified human complement factor 1 (F1; PDB ID: 2XRC) with 48% similarity to the C-terminus serine-protease domain. Comparative protein-protein interaction modelling predicts ORF8 binding with human complement C3b, an endogenous substrate of F1. ORF8 appears to bind via overlapping F1-interacting region on C3b (Chain B) with higher binding energy than F1-C3b complex. However, introduction of natural mutations on ORF8 reduced the binding energy. Thus, ORF8 can potentially disrupt complement activation by competing with F1 for C3b binding.


title: When Second Best Might be the Best: Using Hospitalization Data to Monitor the Novel Coronavirus Pandemic

text: The novel coronavirus' high rate of asymptomatic transmission combined with a lack of testing kits call for a different approach to monitor its spread and severity. We proposed the use of hospitalizations and hospital utilization data to monitor the spread and severity. A proposed threshold of a declining 7-day moving average over a 14-day period, "7&14" was set to communicate when a wave of the novel coronavirus may have passed. The state of Ohio was chosen to illustrate this threshold. While not the ideal solution for monitoring the spread of the epidemic, the proposed approach is an easy to implement framework accounting for limitations of the data inherent in the current epidemic. Hospital administrators and policy makers may benefit from incorporating this approach into their decision making.


title: Estimating the cure rate and case fatality rate of the ongoing epidemic COVID-19

text: The epidemic caused by the novel coronavirus COVID-19 in Wuhan at the end of 2019 has become an urgent public event of worldwide concern. However, due to the changing data of the epidemic, there is no scientific estimate of the cure rate and case fatality rate of the epidemic. This study proposes a method to estimate the cure rate and case fatality rate of COVID-19. The ratio of cumulative discharges on a given day to the sum of cumulative discharges on a given day and cumulative deaths before j days is used to estimate the cure rate. Moreover, the case fatality ratio can also be estimated. After simulation calculations, j is statistically appropriate when it is 8-10, and it is also clinically appropriate. When j is 9, based on the available data, it is inferred that the cure rate of this epidemic is about 93% and the case fatality rate is about 7%. This method of estimating the cure rate can be used to evaluate the effectiveness of treatment in different medical schemes and different regions, and has great value and significance for decision-making in the epidemic.


title: The development of competency frameworks in healthcare professions: a scoping review.

text: Background Competency frameworks serve many roles including outlining characteristics of a competent workforce, to provide clarity to complex constructs, to facilitate professional mobility, and to help structure analysis, evaluation or assessment of professional expertise. Given these roles and their relevance in the health professions, we sought to understand the methods and strategies used in the development of existing competency frameworks. Methods The Arksey and O'Malley framework was applied to undertake this scoping review. Six electronic databases (MEDLINE, CINAHL, PsycINFO, EMBASE, Scopus, and ERIC) and three grey literature sources (greylit.org, Trove and Google Scholar) were searched using keywords related to competency frameworks. Studies of all types were included that described the development of a competency framework in a healthcare profession. Studies were screened for inclusion, and data were extracted independently by two reviewers. Data synthesis was both quantitative and qualitative. Results Among 5,710 citations, 190 were selected for analysis. The majority of studies were conducted in medicine and nursing professions. Group techniques were utilised in 140 studies (74%), literature reviews were conducted in 112 (59%), and 81 (43%) outlined some form of stakeholder deliberation. We found a significant degree of diversity in methodological strategies, inconsistent adherence to existing guidance on the selection of methods, who was involved, and based on the variation we observed in timeframes, form, choice, sequence, combination, function, application and reporting of methods and strategies, there is no apparent gold standard or standardised approach to competency framework development. Conclusions This review observed significant variation within the conduct and reporting of the competency framework development process. Such variation is a cause for concern, potentially resulting in the development of frameworks that may not have captured the complexities of clinical practice, which are therefore of limited value to the profession, and may unwillingly create and legitimise artificial outcomes. The results of this review suggest there is a need for improved guidance in the process for developing and reporting competency frameworks.


title: Endocrine disrupting chemicals and COVID-19 relationships: a computational systems biology approach

text: Background: Patients at high risk of severe forms of COVID-19 frequently suffer from chronic diseases, but other risk factors may also play a role. Environmental stressors, such as endocrine disrupting chemicals (EDCs), can contribute to certain chronic diseases and might aggravate the course of COVID-19. Objectives: To explore putative links between EDCs and COVID-19 severity, an integrative systems biology approach was constructed and applied. Methods: As a first step, relevant data sets were compiled from major data sources. Biological associations of major EDCs to proteins were extracted from the CompTox database. Associations between proteins and diseases known as important COVID-19 comorbidities were obtained from the GeneCards and DisGeNET databases. Based on these data, we developed a tripartite network (EDCs-proteins-diseases) and used it to identify proteins overlapping between the EDCs and the diseases. Signaling pathways for common proteins were then investigated by over-representation analysis. Results: We found several statistically significant pathways that may be dysregulated by EDCs and that may also be involved in COVID-19 severity. The Th17 and the AGE/RAGE signaling pathways were particularly promising. Conclusions: Pathways were identified as possible targets of EDCs and as contributors to COVID-19 severity, thereby highlighting possible links between exposure to environmental chemicals and disease development. This study also documents the application of computational systems biology methods as a relevant approach to increase the understanding of molecular mechanisms linking EDCs and human diseases, thereby contributing to toxicology prediction.


title: Us and Uk Labour Markets before and during the Covid-19 Crash

text: We examine labour market performance in the US and the UK prior to the onset of the Covid-19 crash We then track the changes that have occurred in the months and days from the beginning of March 2020 using what we call the Economics of Walking About (EWA) that shows a collapse twenty times faster and much deeper than the Great Recession We examine unemployment insurance claims by state by day in the US as well as weekly national data We track the distributional impact of the shock and show that already it is hitting the most vulnerable groups who are least able to work from home the hardest – the young, the least educated and minorities We have no official labour market data for the UK past January but see evidence that job placements have fallen sharply We report findings from an online poll fielded from 11–16 April 2020 showing that a third of workers in Canada and the US report that they have lost at least half of their income due to the Covid-19 crisis, compared with a quarter in the UK and 45 per cent in China We estimate that the unemployment rate in the US is around 20 per cent in April It is hard to know what it is in the UK given the paucity of data, but it has gone up a lot


The covid-19 crisis–and the future of the economy and economics


title: List of Abbreviations

text: Unknown


title: Prediction of COVID-19 Spreading Profiles in South Korea, Italy and Iran by Data-Driven Coding

text: This work applies a data-driven coding method for prediction of the COVID-19 spreading profile in any given population that shows an initial phase of epidemic progression. Based on the historical data collected for COVID-19 spreading in 367 cities in China and the set of parameters of the augmented Susceptible-Exposed-Infected-Removed (SEIR) model obtained for each city, a set of profile codes representing a variety of transmission mechanisms and contact topologies is formed. By comparing the data of an early outbreak of a given population with the complete set of historical profiles, the best fit profiles are selected and the corresponding sets of profile codes are used for prediction of the future progression of the epidemic in that population. Application of the method to the data collected for South Korea, Italy and Iran shows that peaks of infection cases are expected to occur before the end of March 2020, and that the percentage of population infected in each city will be less than 0.01%, 0.05% and 0.02%, for South Korea, Italy and Iran, respectively.


title: Improved survival outcome in SARs-CoV-2 (COVID-19) Acute Respiratory Distress Syndrome patients with Tocilizumab administration

text: ABSTRACT Background: The novel human coronavirus, severe acute respiratory syndrome coronavirus-2 (SARs-CoV-2), was declared a global pandemic by the World Health Organization on March 11, 2020. Hence, there is an urgency to find effective treatment. Of those patients afflicted in the United States, many have required treatment with ventilator secondary to acute respiratory distress syndrome (ARDS). Data are needed regarding the benefit of treatment and prevention of the cytokine storms in COVID-19 patients with Tocilizumab. Methods: Clinical outcomes data for patients admitted to Orange Regional Medical Center with confirmed COVID-19 from Mar 15, 2020 to Apr 20, 2020 were identified through electronic health record chart review. We conducted a retrospective case-control study in confirmed COVID 19 positive patients with ARDS requiring mechanical ventilation and compared outcome in terms of mortality and length of stay amongst those who received Tocilizumab as treatment modality opposed to those that did not. Results: A total of 94 patients with COVID-19 ARDS were analyzed. 44 were in the study group and 50 in the control group. We tried to match both group as close as possible in terms of age, sex, BMI and HS score- calculated using inflammatory markers- ferritin, triglycerides, AST and fibrinogen. The median age was 55.5 years in the study group and 66 in the control group, difference was not statistically significant. Average HS score was 114 in the Tocilizumab group and 92 in the control group, difference was statistically significant with P<0.0001. Also, the patients in the study group had elevated levels of IL-6, triglycerides, AST, ferritin which were statistically significant with p < 0.0001 when compared to the control group. Length of stay was longer, average 17.9 days in the Tocilizumab. Survival rate was much lower at 48 % in the control group and 61.36 % in patients who received Tocilizumab with significant P value of < 0.00001. The number needed to treat (NNT) was 7.48, if we treat 8 patients with Tocilizumab, 1 will not die. Conclusions: Cytokine Release Syndrome (CRS) occurs in a large number of patients with severe COVID-19, which is also an important cause of death. IL- 6 is the key molecule of CRS, so IL-6R antagonist Tocilizumab may be of value in improving outcomes. In our study Tocilizumab group seemed to have improved survival outcome. Results have to be interpreted with caution since this is a retrospective study and mortality is affected by multiple, confounding factors. We await the results of ongoing randomized controlled trials to definitely answer the question of whether Tocilizumab improves survival in COVID-19 ARDS patients.


title: Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases

text: In the past several decades, epidemic modelling for communicable diseases has experienced transitions from treating the entire study area as a whole to addressing spatial variation within the area, and from targeting the entire population to incorporating characteristics of categorized subpopulations and finally going down to the individual level. These transitions have been first driven by the recognition that generalizations of space and population in conventional epidemic modelling may have hampered the effectiveness of the modelling; they then have been supported by increasingly available data that allow depiction of detailed spatiotemporal characteristics of an epidemic, as well as those characteristics of the environment in both human and natural aspects; and finally they have been facilitated by developments in geographic information science, data science, computer science, and computing technologies. Based on a review of a variety of recently developed communicable disease models, we explicitly put forward the notions of spatialization and individualization in this area, and point out that the integration of the two is the future of communicable disease modelling. We also point out that in this area models based on the object conceptualization are good at modelling spatiotemporal process, whereas models based on the field conceptualization are good at representing spatialized information. We propose a procedural framework of epidemic modelling that implements the integration of individualization and spatialization, integration of object-based process and field-based representation, and integration of modelling that retrospectively traces infection relationships based on historical patient data and modelling that prospectively predicts such relationships of future epidemics.


title: A simple SIR model with a large set of asymptomatic infectives

text: There is increasing evidence that one of the most difficult problems in trying to control the ongoing COVID-19 epidemic is the presence of a large cohort of asymptomatic infectives. We develop a SIR-type model taking into account the presence of asymptomatic, or however undetected, infective, and the substantially long time these spend being infective and not isolated. We discuss how a SIR-based prediction of the epidemic course based on early data but not taking into account the presence of a large set of asymptomatic infectives would give wrong estimate of very relevant quantities such as the need of hospital beds, the time to the epidemic peak, and the number of people which are left untouched by the first wave and thus in danger in case of a second epidemic wave. In the second part of the note, we apply our model to the COVID-19 epidemics in Italy. We obtain a good agreement with epidemiological data; according to the best fit of epidemiological data in terms of this model, only 10\% of infectives in Italy is symptomatic.


title: COVID-19: Modeling, prediction, and control

text: The newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, has been recognized as a pandemic by the World Health Organization (WHO) on 11th March 2020. There are many unknowns about this virus to date and no vaccine or conclusive treatment due to the lack of understanding of its pathogenesis and proliferation pathways which are unknown and cannot be traced. The prime objective is to stop its spread worldwide. This article aims to provide predictions of its spread using a stochastic Lotka-Volterra model coupled with an extended Kalman Filter (EKF) algorithm to model the COVID-19 dynamics. Our results show the feasibility of utilizing this model for predicting the spread of the virus and the ability of different control measures (e.g., social distancing) on reducing the number of affected people.


Breast Cancer Diagnosis, Treatment and Follow-Up During COVID-19 Pandemic.


Characteristics and impact of covid-19 pandemic: A word of caution for dental practices


title: Pandemic pupils: COVID-19 and the impact on student paramedics

text: The COVID-19 pandemic is having a profound effect on the learning of student paramedics. This commentary aims to explores how student paramedics have been affected by COVID-19 and seeks to identify the perceived impact of this experience.


Aerosol containment device for use on suspected COVID-19 patients


title: Influence of countries adopted policies for COVID-19 reduction under the view of the airborne transmission framework

text: Daily new cases dataset since January 2020 were used to search for evidences of SARS-CoV-2 community transmission as the main nowadays cause of constant infection rates among countries. Despite traditional forms of transmission of this virus (droplets and aerosols in medical facilities), new evidence suggests aerosols forming patterns in the atmosphere as a main factor of community transmission outside medical spaces. Following these findings, this research focused on comparing some countries and the adopted policy used as preventive framework for virus community transmission. Countries social distancing policy aspect, of one to two meters of physical distance, was statistically analyzed from January to early May 2020, and countries were divided into those implementing only social physical distance and those implementing distancing with additional transmission isolation (with masks and city disinfection). Correlating countries social distancing policy adoption with other preventive measures such as social isolation and COVID-19 testing, a new indicator results, derived from SIR models and Weibull parameterization, show that only social physical distance measure could act as a factor for SARS-CoV-2 transmission with respect to atmosphere carrier potential. In this sense, the type of social distancing framework adopted by some countries without additional measures might represent a main model for the constant reproductive spread patterns of SARS-CoV-2 within the community transmission. Finally, the findings have important implications for the policy making to be adopted globally as well as individual-scale preventive methods.


title: SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search

text: The COVID-19 pandemic has sparked unprecedented mobilization of scientists, already generating thousands of new papers that join a litany of previous biomedical work in related areas. This deluge of information makes it hard for researchers to keep track of their own field, let alone explore new directions. Standard search engines are designed primarily for targeted search and are not geared for discovery or making connections that are not obvious from reading individual papers. In this paper, we present our ongoing work on SciSight, a novel framework for exploratory search of COVID-19 research. Based on formative interviews with scientists and a review of existing tools, we build and integrate two key capabilities: first, exploring interactions between biomedical facets (e.g., proteins, genes, drugs, diseases, patient characteristics); and second, discovering groups of researchers and how they are connected. We extract entities using a language model pre-trained on several biomedical information extraction tasks, and enrich them with data from the Microsoft Academic Graph (MAG). To find research groups automatically, we use hierarchical clustering with overlap to allow authors, as they do, to belong to multiple groups. Finally, we introduce a novel presentation of these groups based on both topical and social affinities, allowing users to drill down from groups to papers to associations between entities, and update query suggestions on the fly with the goal of facilitating exploratory navigation. SciSight1 has thus far served over 10K users with over 30K page views and 13% returning users. Preliminary user interviews with biomedical researchers suggest that SciSight complements current approaches and helps find new and relevant knowledge.


title: On the sensitivity of non-pharmaceutical intervention models for SARS-CoV-2 spread estimation

text: Introduction: A series of modelling reports that quantify the effect of non pharmaceutical interventions (NPIs) on the spread of the SARS-CoV-2 virus have been made available prior to external scientific peer-review. The aim of this study was to investigate the method used by the Imperial College COVID-19 Research Team (ICCRT) for estimation of NPI effects from the system theoretical viewpoint of model identifiability. Methods: An input-sensitivity analysis was performed by running the original software code of the systems model that was devised to estimate the impact of NPIs on the reproduction number of the SARS-CoV-2 infection and presented online by ICCRT in Report 13 on March 30 2020. An empirical investigation was complemented by an analysis of practical parameter identifiability, using an estimation theoretical framework. Results: Despite being simplistic with few free parameters, the system model was found to suffer from severe input sensitivities. Our analysis indicated that the model lacks practical parameter identifiability from data. The analysis also showed that this limitation is fundamental, and not something readily resolved should the model be driven with data of higher reliability. Discussion: Reports based on system models have been instrumental to policymaking during the SARS-CoV-2 pandemic. With much at stake during all phases of a pandemic, we conclude that it is crucial to thoroughly scrutinise any SARS-CoV-2 effect analysis or prediction model prior to considering its use as decision support in policymaking. The enclosed example illustrates what such a review might reveal.


title: SARS-CoV-2 selectively mimics a cleavable peptide of human ENaC in a strategic hijack of host proteolytic machinery

text: Molecular mimicry of host proteins is an evolutionary strategy adopted by viruses to evade immune surveillance and exploit host cell systems. We report that SARS-CoV-2 has evolved a unique S1/S2 cleavage site (RRARSVAS), absent in any previous coronavirus sequenced, that results in mimicry of an identical FURIN-cleavable peptide on the human epithelial sodium channel α-subunit (ENaC-α). Genetic truncation at this ENaC-α cleavage site causes aldosterone dysregulation in patients, highlighting the functional importance of the mimicked SARS-CoV-2 peptide. Single cell RNA-seq from 65 studies shows significant overlap between the expression of ENaC-α and ACE2, the putative receptor for the virus, in cell types linked to the cardiovascular-renal-pulmonary pathophysiology of COVID-19. Triangulating this cellular fingerprint with amino acid cleavage signatures of 178 human proteases shows the potential for tissue-specific proteolytic degeneracy wired into the SARS-CoV-2 lifecycle. We extrapolate that the evolution of SARS-CoV-2 into a global coronavirus pandemic may be in part due to its targeted mimicry of human ENaC and hijack of the associated host proteolytic network.


title: Clinical characteristics and early outcomes in patients with COVID-19 treated with tocilizumab at a United States academic center

text: Limited evidence is available to guide treatment of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A hyperinflammatory state mediated by interleukin-6 (IL-6) has been proposed as a driver of severe disease. Use of the IL-6 receptor inhibitor tocilizumab for severe COVID-19 was first reported in China, where a case series described marked improvements in inflammatory markers, fever, oxygen requirement, and outcomes following its administration. Here, we provide the first description of a tocilizumab-treated cohort of patients with COVID-19 in the United States. We describe 11 patients from a single academic medical center, nine (82%) of whom were critically ill requiring mechanical ventilation in an intensive care unit at the time of tocilizumab administration. C-reactive protein levels decreased in all patients following treatment (median 211.6 pre- vs. 19.7 mg/L 5 days post-tocilizumab [p=0.001]). When IL-6 levels were obtained before and after therapy, wide variation was seen in baseline levels; post-dose IL-6 concentrations were consistently increased. In contrast to prior reports, we did not observe significant clinical improvement in temperature or oxygen requirements in most patients. Two patients were discharged (18%), five remained in critical condition in the intensive care unit (46%), one was weaned off the ventilator to room air (9%), and three died (27%). Our findings suggest that tocilizumab should be used with caution in severe and critically ill patients and highlight the need for data from randomized controlled trials to determine its efficacy in the treatment of COVID-19.


title: Expansion of SARS-CoV-2-specific Antibody-secreting Cells and Generation of Neutralizing Antibodies in Hospitalized COVID-19 Patients

text: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in late 2019 and has since become a global pandemic. Pathogen-specific antibodies are typically a major predictor of protective immunity, yet B cell and antibody responses during COVID-19 are not fully understood. Here, we analyzed antibody-secreting cell (ASC) and antibody responses in twenty hospitalized COVID-19 patients. The patients exhibited typical symptoms of COVID-19, and presented with reduced lymphocyte numbers and increased T cell and B cell activation. Importantly, we detected an expansion of SARS-CoV-2 nucleocapsid protein-specific ASCs in all twenty COVID-19 patients using a multicolor FluoroSpot assay. Out of the 20 patients, 16 had developed SARS-CoV-2-neutralizing antibodies by the time of inclusion in the study. SARS-CoV-2-specific IgA, IgG and IgM antibody levels positively correlated with SARS-CoV-2-neutralizing antibody titers, suggesting that SARS-CoV-2-specific antibody levels may reflect the titers of neutralizing antibodies in COVID-19 patients during the acute phase of infection. Lastly, we showed that interleukin 6 (IL-6) and C-reactive protein (CRP) concentrations were higher in serum of patients who were hospitalized for longer, supporting the recent observations that IL-6 and CRP could be used to predict COVID-19 severity. Altogether, this study constitutes a detailed description of clinical and immunological parameters in twenty COVID-19 patients, with a focus on B cell and antibody responses, and provides tools to study immune responses to SARS-CoV-2 infection and vaccination.


title: Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis

text: Introduction Since December 2019, a novel coronavirus (SARS-CoV-2) has triggered a world-wide pandemic with an enormous medical, societal, and economic toll. Thus, our aim was to gather all available information regarding comorbidities, clinical signs and symptoms, outcomes, laboratory findings, imaging features, and treatments in patients with coronavirus disease 2019 (COVID-19). Methods EMBASE, PubMed/ Medline, Scopus, and Web of Science were searched for studies published in any language between December 1st, 2019 and March 28th. Original studies were included if the exposure of interest was an infection with SARS-CoV-2 or confirmed COVID-19. The primary outcome was the risk ratio of comorbidities, clinical signs and symptoms, imaging features, treatments, outcomes, and complications associated with COVID-19 morbidity and mortality. We performed random-effects pairwise meta-analyses for proportions and relative risks, I2, Tau2, and Cochrane Q, sensitivity analyses, and assessed publication bias. Results: 148 met the inclusion criteria for the systematic review and meta-analysis with 12149 patients (5739 female) and a median age was 47.0 [35.0-64.6]. 617 patients died from COVID-19 and its complication, while 297 patients were reported as asymptomatic. Older age (SMD: 1.25 [0.78- 1.72]; p < 0.001), being male (RR = 1.32 [1.13-1.54], p = 0.005) and pre-existing comorbidity (RR = 1.69 [1.48-1.94]; p < 0.001) were identified as risk factors of in-hospital mortality. The heterogeneity between studies varied substantially (I2; range: 1.5-98.2%). Publication bias was only found in eight studies (Eggers test: p < 0.05). Conclusions: Our meta-analyses revealed important risk factors that are associated with severity and mortality of COVID-19.


Information about the open-access article 'Statistics-Based Predictions of Coronavirus Epidemic Spreading in Mainland China' in DOAJ DOAJ is an online directory that indexes and provides access to quality open access, peer-reviewed journals


title: Innate immunity in coronavirus infection/ ВРОЖДЕННЫЙ ИММУНИТЕТ ПРИ КОРОНАВИРУСНОЙ ИНФЕКЦИИ

text: Coronaviruses (CoVs) comprise a polymorphic group of respiratory viruses causing acute inflammatory diseases in domestic and agricultural animals (chicken, pig, buffalo, cat, dog). Until recently, this infection in humans was mainly observed during the autumn-winter period and characterized by a mild, often asymptomatic, course. The situation changed dramatically in 2003, when SARS outbreak caused by pathogenic CoV (SARS-CoV) was recorded in China. A decade later, a new CoV outbreak occurred in the form of the Middle East respiratory syndrome (MERS-CoV), whereas in December 2019, SARS-CoV-2 (COVID-19) cases were recorded, which transformed within the first months of 2020 into the pandemic. In all three cases, CoV disease led to severe bronchopulmonary lesions, varying from dry, debilitating cough to acute respiratory distress syndrome (ARDS). At the same time, multiple changes in innate immunity were noted most often manifested as a pronounced inflammatory reaction in the lower respiratory tract, featured by damaged type II pneumocytes, apoptosis, hyalinization of alveolar membranes, focal or generalized pulmonary edema. Destructive processes in the respiratory tract were accompanied by migration of monocytes/macrophages and granulocyte neutrophils to the inflammatory focus. Such events were accompanied by production of pro-inflammatory cytokines, which magnitude could ascend up to a cytokine storm. SARS-CoV is characterized by symptoms of secondary immunosuppression, manifested by the late onset of interferon production and activation of NLRP3 inflammasomes – the key inflammatory factor. The reason for such reaction may be accounted for by CoV arsenal containing extensive set of structural and non-structural proteins exerting pro-inflammatory and immunosuppressive properties. Delayed IFN production allowed CoV to replicate actively and freely, and when type I IFN synthesis was eventually triggered, its activity was detrimental and accompanied by an aggravated infection course. Thus, SARS can surely be referred to immune-dependent infections with a marked immunopathological component. The purpose of this review was to describe some mechanisms underlying formation of innate immune response to infection caused by pathogenic coronaviruses SARS-CoV, MERS-CoV and SARS-CoV-2 (COVID-19).


title: Characteristics and risk factors for COVID-19 diagnosis and adverse outcomes in Mexico: an analysis of 89,756 laboratory-confirmed COVID-19 cases

text: Background: There is insufficient information about risk factors for COVID-19 diagnosis and adverse outcomes from low and middle-income countries (LMICs). Objectives: We estimated the association between patients characteristics and COVID-19 diagnosis, hospitalization and adverse outcome in Mexico. Methods: This retrospective case series used a publicly available nation-level dataset released on May 31, 2020 by the Mexican Ministry of Health, with patients classified as suspected cases of viral respiratory disease. Patients with COVID-19 were laboratory-confirmed. Their profile was stratified by COVID-19 diagnosis or not. Differences among COVID-19 patients based on two separate clinical endpoints, hospitalization and adverse outcome, were examined. Multivariate logistic regressions examined the associations between patient characteristics and hospitalization and adverse outcome. Results: Overall, 236,439 patients were included, with 89,756 (38.0%) being diagnosed with COVID-19. COVID-19 patients were disproportionately older, males and with increased prevalence of one or more comorbidities, particularly diabetes, obesity, and hypertension. Age, male gender, diabetes, obesity and having one or more comorbidities were independently associated with laboratory-confirmed COVID-19. Current smokers were 23% less likely to be diagnosed with COVID-19 compared to non-smokers. Of all COVID-19 patients, 34.8% were hospitalized and 13.0% experienced an adverse outcome. Male gender, older age, having one or more comorbidities, and chronic renal disease, diabetes, obesity, COPD, immunosuppression and hypertension were associated with hospitalization and adverse outcome. Current smoking was not associated with adverse outcome. Conclusion: This largest ever case series of COVID-19 patients identified risk factors for COVID-19 diagnosis, hospitalization and adverse outcome. The findings could provide insight for the priorities the need to be set, especially by LMICs, to tackle the pandemic.


title: Even in a global pandemic, there’s no such thing as a crisis

text: In my 2019 publication, Constructing Crisis: Leaders, Crisis, and Claims of Urgency, I argued that “crisis” is a label, a claim of urgency employed, typically by leaders, to characterize a set of contingencies that are, together, taken to pose a serious and immediate threat. I then proposed a typology for sorting through any such claim in order to reach a judgment concerning the legitimacy of the claim. Classification systems such as typologies are foundational to knowledge creation in that they enable pattern recognition. How we classify phenomenon has a real impact on how we consider and behave in response to that phenomenon. In the context of a global pandemic, the importance of critical judgment is especially salient. Labeling the global pandemic as a crisis may be non-controversial (to most). But there are enumerable claims being made under the general rubric of that pandemic that are not nearly so widely and easily accepted. Furthermore, claims of urgency will continue long after this particular contingency passes. It is never advisable to relax a critical perspective, especially when assertions of power and interests are involved and the stakes are so high.


title: Evaluation of ELISA tests for the qualitative determination of IgG, IgM and IgA to SARS-CoV-2

text: Serological assays for anti-SARS-CoV-2 antibodies are now of critical importance to support diagnosis, guide epidemiological intervention, and understand immune response to natural infection and vaccine administration. We developed and validated new anti-SARS-CoV-2 IgG, IgM and IgA ELISA tests (ENZY-WELL SARS-CoV-2 ELISA, DIESSE Diagnostica Senese S.p.a.) based on whole-virus antigens. We used a total of 553 serum samples including samples from COVID-19 suspected and confirmed cases, healthy donors, and patients positive for other infections or autoimmune conditions. Overall, the assays showed good concordance with the indirect immunofluorescence reference test in terms of sensitivity and specificity. Especially for IgG and IgA, we observed high sensitivity (92.5 and 93.6%, respectively); specificity was high (>96%) for all antibody types ELISAs. In addition, sensitivity was linked to the days from symptoms onset (DSO) due to the seroconversion window, and for ENZY-WELL SARS-CoV-2 IgG and IgA ELISAs resulted 100% in those samples collected after 10 and 12 DSO, respectively. The results showed that ENZY-WELL SARS-CoV-2 ELISAs may represent a valid option for both diagnostic and epidemiological purposes, covering all different antibody types developed in SARS-CoV-2 immune response.


title: Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

text: The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks.


title: The impact of early social distancing at COVID-19 Outbreak in the largest Metropolitan Area of Brazil.

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


title: Significantly Improved COVID-19 Outcomes in Countries with Higher BCG Vaccination Coverage: A Multivariable Analysis

text: COVID-19 started in Hubei province in China and has spread to 210 countries within 3 months. The statistic of COVID-19 across the world is reported daily, providing a dynamic perspective for each country. We tested the hypothesis that the vaccination against tuberculosis with BCG correlates with better outcomes for COVID-19 patients. To this end, we combined the information on demography, economy, major chronic diseases, and immunization policies with the COVID-19 outcomes. We filtered out at a fixed date all countries that were below a predetermined value for population size and number of COVID-19 deaths per million (DPM). Altogether, 55 countries, covering 62.9% of the world population, met our criteria and were analyzed. To allow a reliable comparison between countries, each was aligned to a critical alignment threshold date (0.5 DPM). We found that the years of BCG admission are negatively correlated with DPM at varying times post alignment. Results from multivariable regression tests with 22 quantitative properties of each country and its population substantiate the dominant contribution of BCG admission years to the COVID-19 outcomes. Analyzing countries according to an age group partition across several time-points, reveals that the strongest correlation is attributed to the coverage in BCG vaccination of the young population (<25 years), to a lesser degree the middle age group (25-64 years), while BCG coverage status of the elderly (>65 years) was insignificant. More specifically, the signal is attributed to recent immunizations (last 15 years) rather than past policies. We propose that BCG immunization coverage, especially among the most recently vaccinated, may contribute to attenuation of the COVID-19 spread and severity.


title: Digital Inclusion Across the Americas and the Caribbean

text: This research brings together scholarship across the Americas and Caribbean to examine digital inclusion initiatives in the following countries: Uruguay, Chile, Peru, Brazil, Mexico, Cuba, Jamaica, the United States, and Canada Across the cases, several themes emerge that offer important indicators for future digital inclusion initiatives First, public policy can effectively reduce access gaps when it addresses the trifecta of network, device, and skill provision Second, this triple-crown of public policy is highly effective for longitudinal effect when implemented early via educational institutions Third, rural-urban digital inequality is resistant to change such that rural populations benefit less from policy initiatives than their urban counterparts Fourth, digital inclusion in rural areas and among marginalized populations is most effective when co-created with communities to ensure community investment, participation, and control Fifth, stay-at-home orders during the COVID-19 pandemic are rapidly increasing our dependence on digital technologies, making digital inclusion more important than ever for education and rural communities We therefore close the article with discussion of how the COVID-19 pandemic is amplifying digital disadvantage and exclusion across the Americas, the Caribbean, and the globe


title: An Epidemic Model SIPHERD and its application for prediction of the spread of COVID-19 infection in India

text: After originating from Wuhan, China, in late 2019, with a gradual spread in the last few months, COVID-19 has become a pandemic crossing 9 million confirmed positive cases and 450 thousand deaths. India is not only an overpopulated country but has a high population density as well, and at present, a high-risk nation where COVID-19 infection can go out of control. In this paper, we employ a compartmental epidemic model SIPHERD for COVID-19 and predict the total number of confirmed, active and death cases, and daily new cases. We analyze the impact of lockdown and the number of tests conducted per day on the prediction and bring out the scenarios in which the infection can be controlled faster. Our findings indicate that increasing the tests per day at a rapid pace (10k per day increase), stringent measures on social-distancing for the coming months and strict lockdown in the month of July all have a significant impact on the disease spread.


title: “We can’t return to normal”: committing to tourism equity in the post-pandemic age

text: Tourism transformation must bring an actionable focus on equity. A new normal openly recognizes the crises and tensions inhabiting tourism well before the COVID-19 pandemic along with the holistic and integrated nature of a pro-equity agenda. A resilient post-pandemic tourism must be more equitable and just, in terms of how it operates, its effects on people and place, and how we as scholars teach, study and publicly engage the travel industry—particularly in preparing its current and future leaders. A commitment to equity is about making specific changes in practices and decisions at multiple levels, along with growing a wider ethical framework. This pivot of a mindset requires us, as tourists, corporations, and educators to step away from a selfish perspective and critically change our perception and understanding of tourism to a truly equitable focus. Consequently, these actions force us to question the consumerism and capitalistic lens that has contributed to mass growth across the touristic landscape and instead, choose a system that fosters sustainable and equitable growth - which in turn, ‘slows down’ our ways of consuming the world around us - transforming our values and experiences of what tourism is and should be.


Cost-effective innovative personal protective equipment for the management of COVID-19 patients


title: Recurrent Neural Network-based Acute Concussion Classifier using Raw Resting State EEG Data

text: Concussion is a global health concern. Despite its high prevalence, a sound understanding of the mechanisms underlying this type of diffuse brain injury remains elusive. It is, however, well established that concussions cause significant functional deficits; that children and youths are disproportionately affected and have longer recovery time than adults; and recovering individuals are more prone to suffer additional concussions, with each successive injury increasing the risk of long term neurological and mental health complications. Currently, concussion management faces two significant challenges: there are no objective, clinically accepted, brain-based approaches for determining (i) whether an athlete has suffered a concussion, and (ii) when the athlete has recovered. Diagnosis is based on clinical testing and self-reporting of symptoms and their severity. Self-reporting is highly subjective and symptoms only indirectly reflect the underlying brain injury. Here, we introduce a deep learning Long Short Term Memory (LSTM)-based recurrent neural network that is able to distinguish between healthy and acute post-concussed adolescent athletes using only a short (i.e. 90 seconds long) sample of resting state EEG data as input. The athletes were neither required to perform a specific task nor subjected to a stimulus during data collection, and the acquired EEG data was neither filtered, cleaned of artefacts, nor subjected to explicit feature extraction. The LSTM network was trained and tested on data from 27 male, adolescent athletes with sports related concussion, bench marked against 35 healthy, adolescent athletes. During rigorous testing, the classifier consistently identified concussions with an accuracy of >90% and its ensemble-median Area Under the Curve (AUC) corresponds to 0.971. This is the first instance of a high-performing classifier that relies only on easy-to-acquire resting state EEG data. It represents a key step towards the development of an easy-to-use, brain-based, automatic classification of concussion at an individual level.


title: The target landscape of N4-hydroxycytidine based on its chemical neighborhood

text: N4-hydroxycytidine (NHC) has been recently reported to have promising antiviral activity against SARS-CoV-2. To join worldwide efforts in identifying potential drug targets against this pandemic, the target landscape of NHC was defined by extracting all known targets of its chemical neighborhood, including drugs, analogues, and metabolites, and by performing target predictions from two independent platforms, following the recent Public Health Assessment via Structural Evaluation (PHASE) protocol. The analysis provides a list of over 30 protein targets that could be useful in future design activities of new COVID-19 antivirals. The relevance for existing drugs within the same chemical space, such as remdesivir, is also discussed.


title: Spurious Correlation? A review of the relationship between Vitamin D and Covid-19 infection and mortality

text: The study reviews the evidence presented in a recent study linking vitamin D levels and Covid-19 infection and mortality. It was argued that correlation alone may not be useful in establishing a relationship between vitamin D levels and Covid-19 infections and mortality. Appropriate controls need to be included for improved understanding of the relationship. We proposed life expectancy as a potential control. Including this control in a regression model, we find that vitamin D levels are not a statistically significant predictor of Covid-19 infections or mortality. Life expectancy, on the other hand, was found to be statistically significant predictor of infections and mortality at country level.


title: The global and local distribution of RNA structure throughout the SARS-CoV-2 genome

text: SARS-CoV-2 is the causative viral agent of COVID-19, the disease at the center of the current global pandemic. While knowledge of highly structured regions is integral for mechanistic insights into the viral infection cycle, very little is known about the location and folding stability of functional elements within the massive, ~30kb SARS-CoV-2 RNA genome. In this study, we analyze the folding stability of this RNA genome relative to the structural landscape of other well-known viral RNAs. We present an in-silico pipeline to locate regions of high base pair content across this long genome and also identify well-defined RNA structures, a method that allows for direct comparisons of RNA structural complexity within the several domains in SARS-CoV-2 genome. We report that the SARS-CoV-2 genomic propensity to stable RNA folding is exceptional among RNA viruses, superseding even that of HCV, one of the most highly structured viral RNAs in nature. Furthermore, our analysis reveals varying levels of RNA structure across genomic functional regions, with accessory and structural ORFs containing the highest structural density in the viral genome. Finally, we take a step further to examine how individual RNA structures formed by these ORFs are affected by the differences in genomic and subgenomic contexts. The conclusions reported in this study provide a foundation for structure-function hypotheses in SARS-CoV-2 biology, and in turn, may guide the 3D structural characterization of potential RNA drug targets for COVID-19 therapeutics.


title: Campaign-Based Citizen Science for Environmental Mycology: the “Science Solstice” and “Summer Soil-stice” Projects to Assess Drug Resistance in Air and Soilborne Aspergillus fumigatus

text: Citizen science projects are often undertaken for ecological and environmental research purposes but also have great potential for use in microbiology research to track the emergence and spread of pathogens in the environment. ‘Science Solstice’ and ‘Summer Soil-stice’ are mycology citizen science projects aimed at assessing drug resistance in Aspergillus fumigatus fungal spores found in air and soil, respectively, in the United Kingdom (UK). A. fumigatus plays an important role in the environment as a decomposer of plant material, but is also an opportunistic human lung pathogen. Infection with drug-resistant spores can lead to a worse clinical outcome for the patient. On the first four solstice and equinox days between June 2018 and June 2019, volunteers were asked to collect air samples from their homes and workplaces and return them to our lab in Freepost envelopes. An additional round of samples was requested from volunteer’s gardens and/or compost on the June 2019 solstice. In total, 787 volunteers returned 2,132 air samples and 509 soil samples, which grew a total of 7,991 A. fumigatus colonies. The estimated total cost of the study was £2,650; the equivalent of 33 pence per A. fumigatus colony grown. Incorporating citizen science into the environmental surveillance of drug-resistant A. fumigatus allowed for the simultaneous collection of hundreds of environmental samples across the entire UK on the same day. The insights generated from this study would not be practical in the absence of public participation and offers opportunities to ask scientific questions that were previously unaskable.


title: Quantifying treatment effects of hydroxychloroquine and azithromycin for COVID-19: a secondary analysis of an open label non-randomized clinical trial (Gautret et al, 2020)

text: Human infections with a novel coronavirus (SARS-CoV-2) were first identified via syndromic surveillance in December of 2019 in Wuhan China. Since identification, infections (coronavirus disease-2019; COVID-19) caused by this novel pathogen have spread globally, with more than 250,000 confirmed cases as of March 21, 2020. An open-label clinical trial has just concluded, suggesting improved resolution of viremia with use of two existing therapies: hydroxychloroquine (HCQ) as monotherapy, and in combination with azithromycin (HCQ-AZ). The results of this important trial have major implications for global policy in the rapid scale-up and response to this pandemic. The authors present results with p-values for differences in proportions between the study arms, but their analysis is not able to provide effect size estimates. To address this gap, more modern analytical methods including survival models, have been applied to these data, and show modest to no impact of HCQ treatment, with more significant effects from the HCQ-AZ combination, potentially suggesting a role for co-infections in COVID-19 pathogenesis. The trial of Gautret and colleagues, with consideration of the effect sizes, and p-values from multiple models, does not provide sufficient evidence to support wide-scale rollout of HCQ monotherapy for the treatment of COVID-19; larger randomized studies should be considered. The trial of Gautret and colleagues, with consideration of the effect sizes, and p-values from multiple models, does not provide sufficient evidence to support wide-scale rollout of HCQ monotherapy for the treatment of COVID-19; larger randomized studies should be considered. These data also suggest further randomized-controlled studies of HCQ-AZ combination therapy should be undertaken.


title: Nano short peptide nutrition intervention on the prognosis of patients with COVID-19

text: Summary BackgroundThe continuous outbreak of COVID-19 poses a devastating threat to the global public health, and there's no special therapeutic drugs.This paper is to explore the effect of high fiber whey short peptide enteral nutrition on the prognosis of patients with COVID-19, to find ways to prevent patients from progressing to severe illness, and to reduce the harm of epidemic situation to human beings. Methods: The course of fighting against COVID-19 in our hospital for 49 days was reviewed. Three nutritional interventions including five-step nutrition treatment, early intervention of whole protein, and high fiber whey short peptide intervention were conducted consecutively.The effect of high fiber whey short peptide on nutrition, immune function and prognosis of patients with COVID-19 was compared with that of whole protein intervention. Results: High fiber whey short peptide group when compared with whey protein group, can significantly improve prealbumin in patients with covid-19, improve the negative nitrogen balance of patients, and reduce the average period of turning negative by 39.06%. Conclusion: High fiber whey short peptide can significantly improve the recovery speed of patients with covid-19.


title: Smart Pooling: AI-powered COVID-19 testing

text: Massive molecular testing for COVID-19 has been pointed as fundamental to moderate the spread of the disease. Pooling methods can enhance testing efficiency, but they are viable only at very low prevalences of the disease. We propose Smart Pooling, a machine learning method that uses sociodemographic data from patients to increase the efficiency of pooled molecular testing for COVID-19 by arranging samples into all-negative pools. We show efficiency gains of 42% with respect to individual testing at disease prevalence of up to 25%, a regime in which two-step pooling offers marginal efficiency gains. Additionally, we calculate the possible efficiency gains of one- and two-dimensional two-step pooling strategies and present the optimal strategies for disease prevalences up to 25%. We discuss practical limitations to conduct pooling in the laboratory.


title: A population-based study of the prevalence of COVID-19 infection in Espirito Santo, Brazil: methodology and results of the first stage

text: BACKGROUND: COVID-19 is affecting almost the entire world, causing more than four hundred thousand deaths and undermining the health care systems, as much as the economy, of the afflicted countries. The strategies for prevention depend on largely lacking information, as infection prevalence and virus pathogenicity. This study aimed to determine the prevalence, the pathogenicity, and the speed of infection spreading in a large population in Brazil. MATERIALS AND METHODS: This is a serial cross-sectional study designed on a population basis and structured over houses as the sampling units. The sampling consisted of four visits at 15 days intervals in randomly selected census-designated sectors of the State major municipalities (reference municipalities) and two visits at 30 days intervals in smaller municipalities of the same regions of those of reference. At each visit, the investigators sampled houses and sampled one individual in each house for data collection. After the informed consent, the investigators performed a rapid antibody detection test (Celer Technology, Inc) and applied a questionnaire containing clinical and demographic questions. RESULTS: From May 13th to 15th, the investigators performed 6,393 rapid tests in 4,612 individuals of the reference municipalities, 1,163 individuals of the smaller municipalities, and 166 contacts of the positive individuals. Ninety-seven dwellers were positive in the reference municipalities, giving a prevalence of 2.1% (CI 95%: 1.67-2.52%). In the smaller municipalities, the figure was 0.26% (CI 95%: 0.05%-0.75%) (three positives). There was an association of the positive result with female sex (p = 0.013) and houses with five dwellers or more (p = 0.003). Seventy-eight positive individuals reported symptoms in the previous 15 days (80.4%), being anosmia (45.4%), cough (40.2%), and myalgia (38.1%) the more frequent. About one-third of them reported fever (28.9%). CONCLUSIONS: The results reveal a still small prevalence of infection in the study area, despite the significant number of sick people overloading the health system. The figures indicate an important underreporting in the area and a frequency that still can grow, making necessary public health actions for the containment of the transmission.


title: How ophthalmologists should understand and respond to the current epidemic of novel coronavirus pneumonia/ 眼科医生和研究人员如何理解和应对新型冠状病毒肺炎的流行

text: The new coronavirus pneumonia (COVID-19)that caused by 2019 new coronavirus (2019-nCoV) and first appeared in Wuhan, China, in December 2019 has attracted great attention from both the Chinese government and the international community.The International Committee on Viral Classification named the virus "Severe Acute Respiratory Syndrome Coronavirus 2" (SARS-CoV-2), and the WHO named the pneumonia it causesCOVID-19". At present, the disease is centered in Wuhan City and is spreading rapidly to all parts of China, as well as twenty other countries.About 20% of the people infected during the SARS epidemic in 2003 were employees in hospital environments.COVID-19 has infected an even greater number of heath care workers.Therefore, ophthalmologists need to understand the disease and recognize the importance of taking preventive measures.Although ophthalmologists do not work on the front lines of the outbreak, due to their area of expertise, a variety of situations, such as infection consultations or ophthalmic emergency treatments, can lead to the exposure of ophthalmologists to high-risk environments.This risk will only increase as the number of infected patients continues to increase.When dealing with seemingly normal ophthalmic patients, the vigilance of ophthalmologists and associated staff tends to be significantly reduced.To better protect patients, families, and health care workers, it is strongly recommended that in addition to the standard precautions for the care of all patients, strict contact precautions and droplet precautions need to be taken by ophthalmologists.These measures include (1) wearing an efficient mask (an N95 mask); (2) always performing hand hygiene before and after examining a patient; (3) wearing sterile gloves when entering a patient’s room and touching a patient; (4) wearing a gown when contact is expected with items and environmental surfaces surrounding a patient or when the patient is incontinent or has diarrhea or a surgical or other invasive wound with oozing fluid; (5) cleaning and disinfecting ophthalmic equipment and correctly handling medical waste after examination to prevent transmission to patients who are subsequently examined; (6) wearing goggles and a disposable mask to cover the front and sides of the face before touching a patient, as the virus could spread through the ocular surface; (7) performing the relevant screening for COVID-19 for regular patients who have conjunctivitis and respiratory symptoms at the same time; (8) prohibiting the use of infected patients as potential donors for corneal transplants and temporarily adding donor 2019-CoV screening to the medical standard of the eye bank during the outbreak; (9) for the purposes of scientific research, diagnosis, and other special needs, packing, shipping, and transporting collected specimens according to the relevant dangerous biological goods regulations.


title: The Impact of the COVID-19 Outbreak on the Medical Treatment of Chinese Children with Chronic Kidney Disease (CKD)：A Multicenter Cross-section Study in the Context of a Public Health Emergency of International Concern

text: Objective: To investigate the impact of the COVID-19 outbreak on the medical advice seeking of Chinese children with chronic kidney disease (CKD). Materials and Methods: An anonymous online questionnaire survey was conducted in 17 pediatric nephropathy diagnosis and treatment centers in China. The questions collected basic information on the patients and their parents and data on changes in the approach to medical treatment and their needs in the context of the outbreak etc. This is a Multicenter Cross-section Study. Results: A total of 735 valid questionnaires were collected. 555 patients (75.5%) and their parents said that the outbreak had a significant influence on their medical treatment: 264 patients (47.6%) said that it would be delayed by 2 to 4 weeks and 199 patients (35.9%) by 4 to 8 weeks. 510 patients (84.16%) hoped to get in touch with specialists through online consultation, and 528 patients (84.5%) hoped that online consultation could be implemented and that medication could be delivered to them.. A total of 458 patients (62.3%) said that their greatest concern was that the CKD would be aggravated or that they would experience a relapse; only 203 patients were infected by 2019-nCoV. A total of 313 patients (42.5%) experienced anxiety and thus required the intervention of psychologists. Conclusion: The COVID-19 outbreak has affected the medical treatment of children with CKD. Online consultation, medication delivery and psychological counselling are the greatest needs reported by patients and their families and could especially provide solutions for the management of low income children with CKD in remote rural areas in the context of the COVID-19 epidemic.


title: Modelling exit strategies for the UK Covid-19 lockdown with revised mortality data

text: The number of daily deaths, reported by Public Health England (PHE) during the UK Covid-19 epidemic, initially omitted out-of-hospital deaths in England. The epidemic has been mitigated by social distancing and the lockdown introduced on 17 and 23 March 2020 respectively. We recently reported a stochastic model of a mitigated epidemic which incorporated changes in social interactions and daily movements and whose simulations were consistent with the initial PHE daily mortality data. However, on 29 April, PHE revised their historic data to include out-of-hospital deaths in England. Out-of-hospital deaths occur sooner than in-hospital deaths. Here we show that if 20% of deaths, representing out-of-hospital deaths, are assigned a shorter illness period, then simulated daily mortality matches the revised PHE mortality at least until 4 May. We now predict that if the lockdown is gently relaxed in late May, whilst maintaining social distancing, there would be a modest second-wave which may be acceptable when weighed against the risks of maintaining the lockdown. Our model complements other more sophisticated work currently guiding national policy but which is not presently in the public domain.


title: Retrospective Pooled Screening for SARS-CoV-2 RNA in late 2019

text: Reports have emerged documenting earlier SARS-CoV-2 cases than previously recognized. To investigate this possibility in the Bay Area, we retrospectively tested 1,700 samples from symptomatic individuals for the last 2 months of 2019. No SARS-CoV-2 positive pools were identified, consistent with limited transmission in this population at this time.


title: Pre-test probability for SARS-Cov-2-related Infection Score: the PARIS score

text: Background: Diagnostic tests for SARS-CoV-2 infection (mostly RT-PCR and Computed Tomography) are not widely available in numerous countries, expensive and with imperfect performance Methods: This multicenter retrospective study aimed to determine a pre-test probability score for SARS-CoV-2 infection based on clinical and biological variables. Patients were recruited from emergency and infectious disease departments and were divided into a training and a validation cohort. Demographic characteristics, clinical symptoms, and results of blood tests (complete white blood cell count, serum electrolytes and CRP) were collected. The pre-test probability score was derived from univariate analyses between patients and controls, followed by multivariate binary logistic analysis to determine the independent variables associated with SARS-CoV-2 infection. Points were assigned to each variable to create the PARIS score. ROC curve analysis determined the area under the curve (AUC) Findings: One hundred subjects with clinical suspicion of SARS-CoV-2 infection were included in the training cohort, and 300 other consecutive individuals were included in the validation cohort. Low lymphocyte (<1.3 G/L), eosinophil (<0.06G/L), basophil (<0.04G/L) and neutrophil counts (<5G/L) were associated with a high probability of SARS-CoV-2 infection. No clinical variable was statistically significant. The score had a good performance in the validation cohort (AUC=0.889 (CI: [0.846-0.932]; STD=0.022) with a sensitivity and Positive Predictive Value of high-probability score of 80.3% and 92.3% respectively. Furthermore, a low-probability score excluded SARS-CoV-2 infection with a Negative Predictive Value of 99.5% Interpretation: The PARIS score based on complete white blood cell count has a good performance to categorize the pre-test probability of SARS-CoV-2 infection. It could help clinicians avoid diagnostic tests in patients with a low-probability score and conversely keep on testing individuals with high-probability score but negative RT-PCR or CT. It could prove helpful in countries with a low-availability of PCR and/or CT during the current period of pandemic