title: Determinants of intent to uptake Coronavirus vaccination among respondents in Saudi Arabia: a web-based national survey

text: Background Vaccine hesitancy is a potential threat to global public health. Since, there is an unprecedented global effort to develop a vaccine against the COVID-19 disease much less is known about its acceptance in the community. Understanding key determinants that influence the preferences and demands of a future vaccine by the community may help to develop strategies for improving the global vaccination program. This study aimed to assess the prevalence of the acceptancy of COVID-19 vaccine and their determinants among people in Saudi Arabia. Methods A web-based cross-sectional study was designed using snowball sampling strategies under a highly restricted environment. A bilingual self-administered anonymous questionnaire was designed and send to 1000 study participants through social media platforms and email. Study participants were recruited across the country, including the four major cities (Riyadh, Dammam, Jeddah, and Abha) in Saudi Arabia. Associations between COVID-19 vaccine acceptance and sociodemographic profile of the respondents were explored using the chi-squared test. Key determinants in predicting vaccine acceptancy among respondents were modelled using logistic regression analysis. Results Of the 1000 survey invitees 992 responded to the survey. The majority of the study participants (29.53%) were in the age group (36 to 45 years) and 65.8% were female and 17.9% were Non-Saudi participants. Of the 992 respondents 642 said they are interested in taking the COVID-19 vaccine once it is available. Willingness to accept a future COVID-19 vaccine is relatively high among older age groups (79.2% among 45+ year old), married participants (69.3%), participants with education levels of a postgraduate degree or higher (68.8%), non-Saudi (69.1%), workings with government sector (68.9%). In multivariate model, respondents who were above 45 years (aOR: 2.15; 95% CI: 1.08-3.21), and married (aOR: 1.79; 95% CI: 1.28-2.50) were significantly associated with vaccine acceptance (p < .05). Besides, people having trust in the health system were most likely to accept vaccination (aOR: 3.05; 95% CI: 1.13-4.92).Participants having a higher perceived risk of acquiring infection were 2.13 times higher odds of reporting their intention to uptake the COVID-19 vaccine (aOR: 2.13; 95% CI: 1.35-3.85). Conclusion Addressing sociodemographic determinants relating to the COVID-19 vaccination may help to increase uptake of the global vaccination program to tackle future pandemics. Targeted health education measures are needed among the general population to increase the uptake of the COVID-19 vaccine.


title: Fatal Ischaemic Stroke During COVID-19 and Acute Lung Injury

text: Severe COVID-19 may predispose to both venous and arterial thrombosis. We describe a patient with acute ischaemic stroke while suffering from COVID-19 and respiratory failure, necessitating mechanical ventilation. Deep sedation may delay diagnosis. LEARNING POINTS: A thrombotic stroke can complicate severe COVID-19. Prolonged deep sedation during mechanical ventilation of COVID-19 patients may delay the diagnosis of stroke. The hypercoagulability and a thrombo-inflammatory response in COVID-19 is characterized by an increase in D-dimers and fibrinogen.


title: Exploring the Effect of 2019-nCoV Containment Policies on Crime: The Case of Los Angeles

text: The global spread of 2019-nCoV, a new virus belonging to the coronavirus family, forced national and local governments to apply different sets of measures aimed at containing its outbreak. Los Angeles has been one of the first cities in the United States to declare the state of emergency on March 4th, progressively issuing stronger policies involving--among the others--social distancing, the prohibition of crowded private and public gatherings and closure of leisure premises. These interventions highly disrupt and modify daily activities and habits, urban mobility and micro-level interactions between citizens. One of the many social phenomena that could be influenced by such measures is crime. Exploiting public data on crime in Los Angeles, and relying on routine activity and pattern theories of crime, this work investigates whether and how new coronavirus containment policies have an impact on crime trends in a metropolis using Bayesian structural time-series (BSTS) models. The article specifically focuses on nine urban crime categories, daily monitored from January 1st 2017 to March 28th 2020. The analyses have been updated bi-weekly (up to March 16\ts{th} and up to March 28\ts{th} 2020) to dynamically assess the short-term effects of mild and hard interventions to shed light on how crime adapts to such structural modification of the environment. The results show that overall crime in Las Angeles is significantly decreasing, as well as robbery, shoplifting, theft and battery. No significant effect has been found for stolen vehicle, burglary, assault with deadly weapon, intimate partner violence and homicide. In the last section of this article, policy implications are also discussed.


title: Low-Impact Social Distancing Interventions to Mitigate Local Epidemics of SARS-CoV-2

text: Background After many jurisdictions have implemented intensive social distancing to suppress SARS-CoV-2 transmission, the challenge now is to mitigate the ongoing COVID-19 epidemic without overburdening economic and social activities. This report explores low-impact interventions to mitigate SARS-CoV-2 with a minimum of social and economic disruption. Methods An agent-based model simulated the population of King County, Washington, with agents that interact in homes, schools, workplaces, and other community sites. SARS-CoV-2 transmission probabilities were estimated by fitting simulated to observed hospital admissions from February-May 2020. Interventions considered were (a) encouraging telecommuting; (b) reducing contacts to seniors and nursing home residents; (c) modest reductions to contacts outside of the home; (d) encouraging self-isolation of persons with COVID-19 symptoms; (e) rapid testing and household quarantining. Results Individual interventions are not expected to have a large impact on COVID-19 hospitalizations. No intervention reduced COVID-19 hospitalizations by more than 12.7% (95% confidence interval [CI], 12.0% to 13.3%). Removing all interventions would result in nearly 42,000 COVID-19 hospitalizations between June 2020 and January 2021, with peak hospital occupancy exceeding available beds 6-fold. Combining the interventions is predicted to reduce total hospitalizations by 48% (95% CI, 47-49%), with peak COVID-19 hospital occupancy of 70% of total beds. Targeted school closures can further reduce the peak occupancy. Conclusions Combining low-impact interventions may mitigate the course of the COVID-19 epidemic, keeping hospital burden within the capacity of the healthcare system. Under this approach SARS-CoV-2 can spread through the community, moving toward herd immunity, while minimizing social and economic disruption.


title: Critical Care for Severe COVID-19: A Population-based Study from a Province with Low Case-fatality Rate in China

text: Background Data regarding critical care for patients with severe COVID-19 are limited. We aimed to describe and analyse the clinical course, multi-strategy management, and respiratory support usage for the severe COVID-19 at the provincial level. Methods Using data from Sichuan Provincial Department of Health and the population-based multicentre cohort study, all microbiologically confirmed COVID-19 patients in Sichuan who met the national severe criteria were included from January 16 to March 15, 2020. All patients were followed-up from the day of inclusion, noted as Day one (D1), until discharge, death, or the end of the study. Findings Out of 539 COVID-19 patients, 81 severe cases (15.0%) were identified. The median (IQR) age was 50 (39-65) years, 37% were female, and 53.1% had chronic comorbidities. All severe cases were identified before requiring mechanical ventilation. Among the five predefined criteria for severe illness, low PaO2:FiO2 ratio (<300 mmHg) was the most commonly reported, accounting for 87.7% of the severe diagnosed. By establishing provisional ICUs, all 81 patients were admitted to hospitals capable of providing critical care, among whom 51 (63.0%) were treated in provisional ICUs. On D1, 77 patients (95.1%) were admitted, 76 (93.8%) were administered by respiratory support, including 51 (67.9%) by conventional oxygen therapy (COT). By D28, 53 (65.4%) were discharged, three (3.7%) were deceased, and 25 (30.9%) were still hospitalized. COT, administered to 95.1% of the patients, was the most commonly used respiratory support and met 62.7% of the respiratory support needed, followed by high-flow nasal cannula (19.5%) and non-invasive mechanical ventilation (10%). Interpretation The multi-strategy management for severe COVID-19 patients included early identification and timely critical care, including appropriate respiratory support in particular. Preparation of sufficient conventional oxygen equipment should be prioritized.


title: Immunity-and-Matrix-Regulatory Cells Derived from Human Embryonic Stem Cells Safely and Effectively Treat Mouse Lung Injury and Fibrosis

text: Lung injury and fibrosis represent the most significant outcomes of severe and acute lung disorders, including COVID-19. However, there are still no effective drugs to treat lung injury and fibrosis. In this study, we report the generation of clinical-grade human embryonic stem cells (hESCs)-derived immunity- and matrix-regulatory cells (IMRCs) produced under good manufacturing practice (GMP) requirements, that can treat lung injury and fibrosis in vivo. We generate IMRCs by sequentially differentiating hESCs with serum-free reagents. IMRCs possess a unique gene expression profile distinct from umbilical cord mesenchymal stem cells (UCMSCs), such as higher levels of proliferative, immunomodulatory and anti-fibrotic genes. Moreover, intravenous delivery of IMRCs inhibits both pulmonary inflammation and fibrosis in mouse models of lung injury, and significantly improves the survival rate of the recipient mice in a dose-dependent manner, likely through paracrine regulatory mechanisms. IMRCs are superior to both primary UCMSCs and FDA-approved pirfenidone, with an excellent efficacy and safety profile in mice and monkeys. In light of public health crises involving pneumonia, acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), our findings suggest that IMRCs are ready for clinical trials on lung disorders.


title: Forecasting COVID-19 cases using Machine Learning models

text: As of April 26, 2020, more than 2,994,958 cases of COVID-19 infection have been confirmed globally, raising a challenging public health issue. A predictive model of the disease would help allocate medical resources and determine social distancing measures more efficiently. In this paper, we gathered case data from Jan 22, 2020 to April 14 for 6 countries to compare different models' proficiency in COVID-19 cases prediction. We assessed the performance of 3 machine learning models including hidden Markov chain model (HMM), hierarchical Bayes model, and long-short-term-memory model (LSTM) using the root-mean-square error (RMSE). The LSTM model had the consistently smallest prediction error rates for tracking the dynamics of incidents cases in 4 countries. In contrast, hierarchical Bayes model provided the most realistic prediction with the capability of identifying a plateau point in the incidents growth curve.


title: COVID-19 pandemics modeling with SEIR(+CAQH), social distancing, and age stratification. The effect of vertical confinement and release in Brazil.

text: The ongoing COVID-19 epidemics poses a particular challenge to low and middle income countries, making some of them consider the strategy of vertical confinement. In this strategy, contact is reduced only to specific groups (like age groups) that are at increased risk of severe disease following SARS-CoV-2 infection. We aim to assess the feasibility of this scenario as an exit strategy for the current lockdown in terms of its ability to keep the number of cases under the health care system capacity. We developed a modified SEIR model, including confinement, asymptomatic transmission, quarantine and hospitalization. The population is subdivided into 9 age groups, resulting in a system of 72 coupled nonlinear differential equations. The rate of transmission is dynamic and derived from the observed delayed fatality rate; the parameters of the epidemics are derived with a Markov chain Monte Carlo algorithm. We used Brazil as an example of middle income country, but the results are easily generalizable to other countries considering a similar strategy. We find that starting from 60% horizontal confinement, an exit strategy on May 1st of confinement of individuals older than 60 years old and full release of the younger population results in 400 000 hospitalizations, 50 000 ICU cases, and 120 000 deaths in the 50-60 years old age group alone. The health care system avoids collapse if the 50-60 years old are also confined, but our model assumes an idealized lockdown where the confined are perfectly insulated from contamination, so our numbers are a conservative lower bound. Our results discourage confinement by age as an exit strategy.


title: We should pay close attention to some issues in the process of lung injury therapy of critical severe COVID-19/ 危重症新型冠状病毒肺炎肺损伤治疗过程中应关注的问题

text: Corona virus disease 2019 (COVID-19) progresses very rapidly and a part of patients' condition quickly deteriorate to a severe type or critical severe type, even died of multiple organ failure. Therapeutic principle of these patients is centered on improving oxygenation and lung protection and multiple organ function support. Respiration support includes high-flow nasal cannula oxygen therapy (HFNC), non-invasive positive pressure ventilation (NIPPV), tracheal cannula with mechanical ventilation and extracorporeal membrane oxygenation (ECMO) and assistance methods including lung recruitment and prone position ventilation. Considering COVID-19 progresses rapidly and is very difficult in respiratory therapy, we should pay close attention to above mentioned methods. In particular, identifying risk factors of treatment failure of HFNC and NIPPV in early phase, applying lung recruitment prudently and active application of turning around and beat back and prone position ventilation to help postural drainage and early tracheal cannula with mechanical ventilation and ECMO would be beneficial to the patients.


title: Screening and managing of suspected or confirmed novel coronavirus (COVID-19) patients: experiences from a tertiary hospital outside Hubei province

text: Objectives: To report our experiences screening and managing patients with suspected or confirmed novel coronavirus (COVID-19) disease using a hospital-specific protocol. Design: Longitudinal cohort study. Setting: A 1,200 bed tertiary care teaching hospital in Chengdu, Sichuan, China. Participants: 802 adults presenting to hospital with concerns of having COVID-19, 1,246 inpatients and 2,531 hospital visitors. Interventions: Screening and management of patients using a hospital-specific protocol, which included fever triage, monitoring visitors and patients, emergency response, personnel training for healthcare team members, health education for patients and family, medical materials management, disinfection and wastes disposal protocols. Results: Between 23 January and 28 February 2020, 73 people were identified as having fever plus respiratory signs with/without a history of exposure and were tested for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by our hospital lab using RT PCR. Forty-five of these 73 people were subsequently excluded based on one negative RT PCR result plus positive results to quick screening tests for flu or other respiratory viruses. The remaining 28 people received a second RT PCR test 24 h later. Three people were confirmed positive for COVID-19 based on two consecutive positive RT PCR tests whilst 25 people were excluded based on two consecutive negative tests. The three COVID-19 confirmed cases received non-critical care. There were no new infections of medical staff or new infections of other hospital inpatients. Conclusions: All three cases were detected as a result of vigilant monitoring of hospital visitors. Whilst screening out-patients presenting to a fever clinic remains important, monitoring visitors must not be overlooked.


title: COVID-19 versus non-COVID-19 pneumonia: A retrospective cohort study

text: Background and Objective: Since the outbreak of coronavirus disease 2019 (COVID-19) in December 2019 in Wuhan, Hubei Province, China, it has spread around the world and become a global public health emergency. It is important to distinguish COVID-19 from other viral pneumonias in order to properly screen and diagnose patients, reduce nosocomial infections, and complement the inadequacy of nucleic acid testing. In this study, we retrospectively analysed the clinical data of COVID-19 versus non-COVID-19 patients treated at our hospital between January 17 and February 27, 2020 in order to summarize our clinical experience in the differential diagnosis of COVID-19. Methods: In this retrospective cohort study, 23 confirmed COVID-19 patients were consecutively enrolled from January 17 to February 27, 2020, while 29 confirmed non-COVID-19 patients were enrolled in West China Hospital of Sichuan University. We collected baseline data, epidemiological data, clinical characteristics, imaging findings, viral nucleic acid test results, and survival data. SPSS v22.0 was used for statistical analysis. Outcomes were followed up until March 25. Results: A total of 52 patients were included in this study, including 23 COVID-19 patients and 29 non-COVID-19 patients. No significant between-group difference was observed in age, sex, primary signs or symptoms, cellular immunity, or platelet count. Significant between-group differences were observed in clinical characteristics such as dry cough, contact with individuals from Wuhan, some underlying diseases, nucleated cell count, chest imaging findings, viral nucleic acid test result,28-day mortality, and 28-day survival. Conclusion: Epidemiological data, clinical symptoms, nucleic acid test results for COVID-19 and chest CT manifestation may help distinguish COVID-19 from non-COVID-19 cases, prevent imported cases and nosocomial infections.


title: A systematic review protocol of the antiviral activity of chloroquine and hydroxychloroquine against COVID-19.

text: Introduction: The recent outbreak of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), or COVID-19 with no approved medicines has led to global health threat. Currently, repositioning of old medicines seems the most responsible strategy for potential cure and prevention COVID-19. Hydroxychloroquine and chloroquine have shown promising efficacy against COVID-19 related pneumonia in clinical studies. However, the mode of drug action of chloroquine and hydroxychloroquine against SARS-CoV-2 infection is not clear. This review aims to gather evidence on antiviral activity and possible mechanism of drug action of chloroquine and hydroxychloroquine on SARS-CoV-2, including in-vitro, animal studies, and studies in humans. Method: A structured search of five bibliographic databases namely; Medline, Web of Science, PubMed, Cochrane CENTRAL, and Google Scholar will be undertaken to retrieve studies that describe the antiviral activity and possible mechanism of drug action of chloroquine and hydroxychloroquine on SARS-CoV-2. No restrictions will be placed on publication date, but studies will be limited to only publications in English. Duplication of studies will be removed using EndNote reference manager. Three authors will screen the citations independently based on inclusion criteria. Data extraction and assessment of risk of bias will be done independently. Meta-analysis of selected studies will be done wherever suitable. Ethics and dissemination: Primary data collection will not be involved in this study, hence no need for formal ethical clearance. Findings from the study will be disseminated through a peer-reviewed publication and conference meeting. Trial registration number: https://doi.org/10.17605/OSF.IO/7DJMU


People with Diabetes Mellitus: Soft target for COVID-19 infection


title: Potent neutralizing antibodies from COVID-19 patients define multiple targets of vulnerability

text: The rapid spread of SARS-CoV-2 has a significant impact on global health, travel and economy. Therefore, preventative and therapeutic measures are urgently needed. Here, we isolated neutralizing antibodies from convalescent COVID-19 patients using a SARS-CoV-2 stabilized prefusion spike protein. Several of these antibodies were able to potently inhibit live SARS-CoV-2 infection at concentrations as low as 0.007 µg/mL, making them the most potent human SARS-CoV-2 antibodies described to date. Mapping studies revealed that the SARS-CoV-2 spike protein contained multiple distinct antigenic sites, including several receptor-binding domain (RBD) epitopes as well as previously undefined non-RBD epitopes. In addition to providing guidance for vaccine design, these mAbs are promising candidates for treatment and prevention of COVID-19.


title: Development and validation of a rapid single-step reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) system potentially to be used for reliable and high-throughput screening of COVID-19

text: The recent pandemic of COVID-19 has involved tens of thousands of patients in numerous countries and the causative virus, SARS COV-2 is highly transmissible. Molecular diagnostic tools are central to containment of the virus and initiating proper clinical care. Rapidity, user-friendliness, and high degree of sensitivity and specificity are desirable features of diagnostic assays for screening purposes. Herein, we present a single step reverse transcriptase LAMP assay (RT-LAMP), which can detect up to 500 viral copies in 30 minutes. We challenged our assay with a large number of clinical samples collected from 47 confirmed cases and 213 negative patients. Our LAMP assay showed a high degree of sensitivity and specificity compared to two commercialized qRT-PCR assay as gold standard. We present a rapid RT-LAMP assay that could extend the capacity of laboratories to process 2.5 more clinical samples relative to qRT-PCR and potentially could be used for high-throughput screening purposes.


title: Understanding Economic and Health Factors Impacting the Spread of COVID-19 Disease

text: The rapid spread of the Coronavirus 2019 disease (COVID-19) had drastically impacted life all over the world. While some economies are actively recovering from this pestilence, others are experiencing fast and consistent disease spread, compelling governments to impose social distancing measures that have put a halt on routines, especially in densely-populated areas. Aiming at bringing more light on key economic and public health factors affecting the disease spread, this initial study utilizes a quantitative statistical analysis based on the most recent publicly-available COVID-19 datasets. The study had shown and explained multiple significant relationships between the COVID-19 data and other country-level statistics. We have also identified and statistically profiled four major country-level clusters with relation to different aspects of COVID-19 development and country-level economic and health indicators. Specifically, this study has identified potential COVID-19 under-reporting traits as well as various economic factors that impact COVID-19 Diagnosis, Reporting, and Treatment. Based on the country clusters, we have also described the four disease development scenarios, which are tightly knit to country-level economic and public health factors. Finally, we have highlighted the potential limitation of reporting and measuring COVID-19 and provided recommendations on further in-depth quantitative research.


title: A single-cell RNA-seq Training and Analysis Suite using the Galaxy Framework

text: Background The vast ecosystem of single-cell RNA-seq tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically-driven methods needed to process and understand these ever-growing datasets. Results Here we outline several Galaxy workflows and learning resources for scRNA-seq, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows and trainings that not only enable users to perform one-click 10x preprocessing, but also empowers them to demultiplex raw sequencing data manually. The downstream analysis supports a wide range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal and clustering. The teaching resources cover an assortment of different concepts from computer science to cell biology. Access to all resources is provided at the singlecell.usegalaxy.eu portal. Conclusions The reproducible and training-oriented Galaxy framework provides a sustainable HPC environment for users to run flexible analyses on both 10x and alternatively derived datasets. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy Community provide a means for users to learn, publish and teach scRNA-seq analysis. Key Points Single-cell RNA-seq has stabilised towards 10x Genomics datasets. Galaxy provides rich and reproducible scRNA-seq workflows with a wide range of robust tools. The Galaxy Training Network provides tutorials for the processing of both 10x and non-10x datasets.


title: Modelling the thermal inactivation of viruses from the Coronaviridae family in suspensions or on surfaces with various relative humidities.

text: Temperature and relative humidity are major factors determining virus inactivation in the environment. This article reviews inactivation data of coronaviruses on surfaces and in liquids from published studies and develops secondary models to predict coronaviruses inactivation as a function of temperature and relative humidity. A total of 102 D-values (time to obtain a log10 reduction of virus infectivity), including values for SARS-CoV-2, were collected from 26 published studies. The values obtained from the different coronaviruses and studies were found to be generally consistent. Five different models were fitted to the global dataset of D-values. The most appropriate model considered temperature and relative humidity. A spreadsheet predicting the inactivation of coronaviruses and the associated uncertainty is presented and can be used to predict virus inactivation for untested temperatures, time points or new coronavirus strains.


Observations from the COVID-19 Pandemic


title: Serial interval, basic reproduction number and prediction of COVID-19 epidemic size in Jodhpur, India

text: Background: Understanding the epidemiology of COVID19 is important for design of effective control measures at local level. We aimed to estimate the serial interval and basic reproduction number for Jodhpur, India and to use it for prediction of epidemic size for next one month. Methods: Contact tracing of SARSCoV2 infected individuals was done to obtain the serial intervals. Aggregate and instantaneous R0 values were derived and epidemic projection was done using R software v4.0.0. Results: From among 79 infector infectee pairs, the estimated median and 95 percentile values of serial interval were 5.98 days (95% CI 5.39 to 6.65) and 13.17 days (95% CI 11.27 to 15.57), respectively. The overall R0 value in the first 30 days of outbreak was 1.64 (95% CI 1.12 to 2.25) which subsequently decreased to 1.07 (95% CI 1.06 to 1.09). The instantaneous R0 value over 14 days window ranged from a peak of 3.71 (95% CI 1.85 -2.08) to 0.88 (95% CI 0.81 to 0.96) as on 24 June 2020. The projected COVID-19 case-load over next one month was 1881 individuals. Reduction of R0 from 1.17 to 1.085 could result in 23% reduction in projected epidemic size over the next one month. Conclusion: Aggressive testing, contact-tracing and isolation of infected individuals in Jodhpur district resulted in reduction of R0. Further strengthening of control measures could lead to substantial reduction of COVID19 epidemic size. A data-driven strategy was found useful in surge capacity planning and guiding the public health strategy at local level.


title: Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients

text: Facing the rapidly spreading novel coronavirus disease (COVID-19), evidence to inform decision-making at both the clinical and policy-making level is highly needed. Based on the results of a study by Petrilli et al, we have developed a calculator using patient data at admission to predict the risk of critical illness (intensive care unit admission, use of mechanical ventilation, discharge to hospice, or death). We report a retrospective validation of the risk calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Of the 18 patients with critical illness, 17 were correctly identified by the model(sensitivity: 94.4%, 95% CI, 72.7% to 99.9%; specificity: 81.9%, 95% CI, 74.1% to 88.2%). Of the 127 patients with non-critical illness, 104 were correctly identified. This, despite considerable differences between the original and validation study populations. Our results show that data from published knowledge can be used to provide reliable, patient level, automated risk assessment, potentially reducing the cognitive burden on physicians and helping policy makers better prepare for future needs.


title: Preventing internal COVID-19 outbreaks within businesses and institutions: A methodology based on social networks analysis for supporting occupational health and safety services decision making

text: This study aims at developing and demonstrating in a real case study a methodology for supporting Occupational Health and Safety Services in the design and assessment of preventive measures to reduce the risks of COVID-19 outbreaks within their entities. The proposed methodology applies the concepts from Social Network Analysis (SNA) to the current challenge of preventing risks of contagion of viruses like SARS-COV-2 among employees. For this purpose, the authors consider a network of employees whose interaction is caused by triggers, which are defined as common circumstances between two workers that may result in contagion, like sharing an office or participating in the same management board. The network cohesion is then evaluated, and those core nodes, which are the most significant contributors to its integration, are identified to be addressed in the design of the preventive measures. The impact of the designed preventive measures on the networks' cohesion is assessed for its prioritization and further deployment. The methodology has been demonstrated in a real case, a Spanish Research Center, providing promising results in a quick and easy manner. The objective insights provided by its application were demonstrated as very valuable for the Occupational Health and Safety Services in the design and evaluation of the set of preventing measures to be implemented before the return of the employees to the facilities after the Spanish confinement period. The current COVID-19 outbreak brings the need to develop tools and methods to support businesses and institutions in the use of SNA for preventing outbreaks among their employees. Although some literature does exist in the field of SNA application in epidemiology, its adaptation for extensive use by the Occupational and Health Services is still a challenge.


title: Serological prevalence of antibodies to SARS CoV-2 amongst cancer centre staff

text: Objectives: the aim of this study was to test Rutherford Health (RH) staff for the presence of SARS CoV-2 antibodies to reduce the risk of infection to cancer patients. Setting: Between 14 and 24 April 2020 we tested 161 staff at four locations: our cancer centres in Reading - Berkshire, Newport - S Wales, Liverpool - Merseyside, and Bedlington in Northumberland. Participants: Testing was available to all staff who were on site at the four locations named above at the time the study was carried out. 161 staff (80 men, 81 women) gave voluntary consent to have the tests and all testing gave rise to valid results. Interventions: We used the South Korean test for antibodies to SARS CoV-2: Sugentech SGTi-flex COVID-19 IgM/IgG1. For each test, blood was collected and added to the sample well of the test cassette and buffer solution added. The test result was legible after 15 minutes. Outcome measures: The number of tests positive for the presence of antibodies was the primary outcome measure. The ratio of tests positive for the presence of IgM antibodies versus IgG antibodies was the secondary outcome measure. Results: Between 14 and 24 April 2020, 161 staff (age m = 43) were tested at four Rutherford Cancer Care centres that offer proton beam therapy, radiotherapy and chemotherapy. Out of 161, 12 samples (7.50%) tested positive of which 7 samples (4.35%) detected IgM only, 2 samples (1.24%) detected IgG only and 3 samples (1.86%) detected both IgM and IgG. Conclusions: The low seroconversion rate in the sample population limits the current utility of the test as a way of reducing risk to vulnerable patient populations but longitudinal retesting will provide further data.


title: Predicting the epidemic trend of COVID-19 in China and across the world using the machine learning approach

text: Background: Although COVID-19 has been well controlled in China, it is rapidly spreading outside the country and may have catastrophic results globally without implementation of necessary mitigation measures. Because the COVID-19 outbreak has made comprehensive and profound impacts on the world, an accurate prediction of its epidemic trend is significant. Although many studies have predicted the COVID-19 epidemic trend, most have used early-stage data and focused on Chinese cases. Methods: We first built models to predict daily numbers of cumulative confirmed cases (CCCs), new cases (NCs), and death cases (DCs) of COVID-19 in China based on data from January 20, 2020, to March 1, 2020. Based on these models, we built models to predict the epidemic trend across the world (outside China). We also built models to predict the epidemic trend in Italy, Spain, Germany, France, UK, and USA where COVID-19 is rapidly spreading. Findings: The COVID-19 outbreak will have peaked on February 22, 2020, in China and will peak on May 22, 2020, across the world. It will be basically under control in early April 2020 in China and end-August 2020 across the world. The total number of COVID-19 cases will reach around 89,000 in China and 6,126,000 across the world during the epidemic. Around 4,000 and 290,000 people will die of COVID-19 in China and across the world, respectively. The COVID-19 outbreak will have peaked recently in Italy and will peak in Spain, Germany, France, UK, and USA within two weeks. Interpretation: The COVID-19 outbreak is controllable in the foreseeable future if comprehensive and stringent control measures are taken.


Don’t just drone on: If drones are being used to spy on people breaking quarantine rules, what else could they be used for? We investigate


title: Can cell therapies halt cytokine storm in severe COVID-19 patients?

text: A pilot study of COVID-19 patients treated with mesenchymal stem cells demonstrates safety. Mesenchymal stromal cell (MSC) therapies, which have been explored for decades as a treatment for inflammatory diseases, are now being called into action to combat the cytokine storm induced by COVID-19. The severity of COVID-19 may be due in part to the patient's response to the infection. In some patients, the virus induces an outpouring of inflammatory mediators that leads to swelling, inflammatory infiltration, and reduced gas exchange in the alveoli of the lungs. To combat this cytokine storm, over 20 clinical trials aiming to treat COVID-19 with MSCs have been registered with ClinicalTrials.gov. Leng et al. recently conducted a pilot study of MSC transplantation in 10 patients in China. All patients tested positive for SARS-CoV-2 by polymerase chain reaction and had fever, shortness of breath, cough, and oxygen saturation at rest <95%. Seven of the patients received intravenous infusions of allogeneic MSCs while three received saline as a placebo control. All seven MSC treated patients experienced resolution of symptoms while one of the placebo-treated patients went on to develop ARDS and another died. The response of the most severely ill patient treated with MSCs was monitored throughout recovery. Of note, C-reactive protein levels dropped 10-fold after MSC treatment, suggesting a drop in systemic inflammation. Analysis of cytokine levels before and after treatment revealed that MSC treatment, but not placebo, was associated with a halt in the increase of serum tumor necrosis factor–α and an increase in anti-inflammatory interleukin-10 concentrations in the serum. Although this study is not designed to make definitive claims regarding the efficacy of MSC therapy for COVID-19 or the mechanisms by which MSCs may function to prevent or treat cytokine storm, it does provide important safety data and hints of efficacy that have motivated further exploration of MSCs as a treatment for COVID-19. Of particular note is a randomized, multicenter, placebo-controlled, Phase 2/3 trial enrolling 240 patients being conducted through a public-private partnership between the U.S. National Institutes of Health–funded Cardiothoracic Surgical Trials Network and Mesoblast. As multiple clinical trials are launched around the world, we should not have to wait long to determine if MSCs are a viable and effective treatment option for severe COVID-19.


Updates on COVID-19 Infection During Pregnancy


title: Variation among states in rate of coronavirus spread

text: The corona virus, COVID-19, has been spreading rapidly across the USA since early March, but at a decreasing rate, where the rate r is defined as the exponential increase. I modeled the way the rate of increase y = ln(e^r - 1) has declined through time in each of the 51 states with the goal of determining how quickly the rate has declined, whether the decline has changed, and whether states differ. A piecewise linear regression was used, with a single break point. This model can identify whether there was a change in the rate of decline, when the change happened, and which states have shown the greatest improvement in reducing the spread of COVID-19. The piecewise model identified a significant breakpoint on 24 Mar for all states combined, and all states had nearly the same breakpoint. Prior to 24 Mar, the average change in y was -0.013 per day, meaning a reduction in the rate of spread from 23.5% per day to 19.5% per day; after 24 Mar, the average change in y was -0.070 per day, a reduction from 19.5% per day to 7.5% per day. Prior to 24 Mar there was no significant variation among states in the decline in y, but after 24 Mar there was substantial variation. Montana, Idaho, and Vermont showed the greatest improvement, while Nebraska, South Dakota, and Iowa the least. The improvement as measured by the reduction after 24 Mar did not correlate with case density in a state, nor state population. The next question is whether it correlates with differences among states in the health measures taken to combat the spread.


title: Global versus focused isolation during the SARS-CoV-2 pandemic-A cost-effectiveness analysis

text: Background: The novel coronavirus (SARS-CoV-2) pandemic is driving many countries to adopt global isolation measures in an attempt to slow-down its spread. These extreme measures are associated with extraordinary economic costs. Objective: To compare the cost-effectiveness of global isolation of the whole population to focused isolation of individuals at high risk of being exposed, augmented by thorough PCR testing. Design: We applied a modified Susceptible, Exposed, Infectious, Removed (SEIR) model to compare two different strategies in controlling the SARS-CoV-2 spread. Data sources and target population: We modeled the dynamics in Israel, a small country with ~ 9 million people. Time horizon: 200 days. Interventions: 1. Global isolation of the whole population (strategy 1) 2. Focused isolation of people at high risk of exposure with extensive PCR testing (strategy 2). Outcome measures: Number of deaths and the cost per one avoided death in strategy 1 vs 2. Results of Base-Case analysis: The number of expected deaths is 389 in strategy 1 versus 432 in strategy 2. The incremental cost-effectiveness ratio (ICER) in case of adhering to global isolation will be $ 102,383,282 to prevent one case of death. Results of sensitivity analysis: The ICER value is between $ 22.5 million to over $280 million per one avoided death. Conclusions: According to our model, global isolation will save ~43 more lives compared to a strategy of focused isolation and extensive screening. This benefit is implicated in tremendous costs that might result in overwhelming economic effects. Limitations: Compartment models do not necessarily fit to countries with heterogeneous populations. In addition, we rely on current published parameters that might not reliably reflect infection dynamics.


title: SARS-CoV-2 receptor ACE2 and TMPRSS2 are predominantly expressed in a transient secretory cell type in subsegmental bronchial branches

text: The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.


title: Development of a SARS-CoV-2 total antibody assay and the dynamics of antibody response over time in hospitalized and non-hospitalized patients with COVID-19

text: SARS-CoV-2 infections often cause only mild disease that may evoke relatively low antibody titers compared to patients admitted to hospitals. Generally, total antibody bridging assays combine good sensitivity with high selectivity. Therefore, we developed sensitive total antibody bridging assays for detection of SARS-CoV-2 antibodies to the receptor-binding domain (RBD) and nucleocapsid protein (NP), in addition to conventional isotype-specific assays. Antibody kinetics was assessed in PCR-confirmed hospitalized COVID-19 patients (n=41) and three populations of patients with COVID-19 symptoms not requiring hospital admission: PCR-confirmed convalescent plasmapheresis donors (n=182), PCR-confirmed hospital care workers (n=47), and a group of longitudinally sampled symptomatic individuals highly suspect of COVID-19 (n=14). In non-hospitalized patients, the antibody response to RBD is weaker but follows similar kinetics as has been observed in hospitalized patients. Across populations, the RBD bridging assay identified most patients correctly as seropositive. In 11/14 of the COVID-19-suspect cases, seroconversion in the RBD bridging assay could be demonstrated before day 12; NP antibodies emerged less consistently. Furthermore, we demonstrated the feasibility of finger prick sampling for antibody detection against SARS-CoV-2 using these assays. In conclusion, the developed bridging assays reliably detect SARS-CoV-2 antibodies in hospitalized and non-hospitalized patients, and are therefore well-suited to conduct seroprevalence studies.


title: Commercial Airline Protocol during Covid-19 Pandemic: An Experience of Thai Airways International

text: Introduction: Coronavirus disease 2019 (COVID-19) pandemic has affected the aviation industry. Existing protocols have relied on scientifically questionable evidence and might not lead to the optimal balance between public health safety and airlines' financial viability. Objective: To explore the implementation feasibility of Thai Airways International protocol from the perspectives of passengers and aircrews. Design: An online questionnaire survey of passengers and an in-depth interview with aircrews. Setting: Two randomly selected repatriation flights operated by Thai Airways International using Boeing 777 aircraft (TG476 from Sydney and TG492 from Auckland to Bangkok) Participants: 377 Thai passengers and 35 aircrews. Results: The mean age of passengers was 28.14 (95%CI 26.72 to 29.55) years old; 57.03% were female. TG492 passengers were mostly students and significantly younger than that of TG476 (p<0.0001) with comparable flying experience (p=0.1192). The average body temperature was 36.52 (95%CI 36.48 to 36.55) degrees Celsius. Passengers estimated average physical distances of 1.59 (95%CI 1.48 to 1.70), 1.41 (95%CI 1.29 to 1.53), and 1.26 (95%CI 1.12 to 1.41) meters at check-in, boarding, and in-flight, respectively. Passengers were checked for body temperature during the flight 1.97 (95%CI 1.77 to 2.18) times on average which is significantly more frequent in longer than shorter flight (p<0.0001). Passengers moved around or went to the toilet during the flight 2.00 (95%CI 1.63 to 2.37) and 2.08 (95%CI 1.73 to 2.43) times which are significantly more frequent in longer than shorter flight (p=0.0186 and 0.0049, respectively). The aircrews were satisfied with the protocol and provided several practical suggestions. Conclusion: The protocol was well received by the passengers and aircrews of the repatriation flights with some suggestions for improvement.


title: Unveiling ‘Warp Speed,’ the White House’s America-first push for a coronavirus vaccine

text: Conventional wisdom is that a vaccine for COVID-19 is at least 1 year away, but the organizers of a U S government push called Operation Warp Speed have little use for conventional wisdom The project, vaguely described to date but likely to be formally announced by the White House in the coming days, will pick a diverse set of vaccine candidates and pour essentially limitless resources into unprecedented comparative studies in animals, fast-tracked human trials, and manufacturing Eschewing international cooperation—and any vaccine candidates from China—it hopes to have 300 million doses by January 2021 of a proven product, reserved for Americans


title: Testing lags and emerging COVID-19 outbreaks in federal penitentiaries in Canada

text: Objectives: To provide the first known comprehensive analysis of COVID-19 outcomes in a federal penitentiary system. We examined the following COVID-19 outcomes within federal penitentiaries and contrasted them with the overall population in the penitentiaries' respective provincial jurisdictions: testing, prevalence, the proportion recovered, and fatality. Methods: Data for prisons were obtained from the Correctional Service of Canada and, for the general population, from COVID-19 Esri Canadian Outbreak Tracking Hub. Data were retrieved between March 30 and April 21, 2020, and are accurate to this date. Penitentiary-, province- and sex-specific frequency statistics for each outcome were calculated. Results: Data on 50 of 51 penitentiaries (98%) were available. Of these, 72% of penitentiaries reported fewer tests per 1000 population than the Canadian general population average (16 tests/1000 population), and 24% of penitentiaries reported zero tests. Penitentiaries with high levels of testing were those that already had elevated COVID-19 prevalence. Five penitentiaries reported an outbreak (at least one case). Hardest hit penitentiaries were those in Quebec and British Columbia, with some prisons reporting COVID-19 prevalence of 30% to 40%. Of these, two were women's prisons. Female prisoners were over-represented among cases (31% of cases overall, despite representing 5% of the total prison population). Conclusion: Increased sentinel or universal testing may be appropriate given the confined nature of prison populations. This, along with rigorous infection prevention control practices and the potential release of prisoners, will be needed to curb current outbreaks and those likely to come.


Stroke During COVID-19 Pandemic.


title: Enacting national social distancing policies corresponds with dramatic reduction in COVID19 infection rates

text: The outbreak the SARS-CoV-2 (CoV-2) virus has resulted in over 2.5 million cases of COVID19, greatly stressing global healthcare infrastructure. Lacking medical prophylactic measures to combat disease spread, many nations have adopted social distancing policies in order to mitigate transmission of CoV-2. While mathematical models have suggested the efficacy of social distancing to curb the spread of CoV-2, there is a lack of systematic studies to quantify the real-world efficacy of these approaches. Here, we quantify the spread rate of COVID19 before and after national social distancing measures were implemented in 26 nations and compare this to the changes in COVID19 spread rate over equivalent time periods in 27 nations that did not enact social distancing policies. We find that social distancing policies significantly reduced the COVID19 spread rate. Using mixed linear regression models we estimate that social distancing policies reduced the spread of COVID19 by 66%. These data suggest that social distancing policies may be a powerful tool to prevent spread of COVID19 in real-world scenarios.


title: Rational and practical use of imaging in COVID-19 pneumonia

text: The severe form of the COVID-19 pandemic caused by the SARS-CoV-2 virus, has largely manifested as a predominant respiratory illness causing severe pneumonia characterized by bilateral, subpleural ground glass haze, progressing to consolidation, and fibrosis on imaging. There is some discrepancy between the governmental guidelines, professional Societies and Radiology and Respiratory Medicine specialists with divided opinions between the use of the chest X-rays and CT scan, and whether the use be screening or diagnostic. So far, the most balanced recommendations have been proposed by the Fleischner Society, which are endorsed by the Radiological Society of Pakistan as well. This writeup describes the approach for a rational use of imaging to the best advantage in the current situation according to local resources, and restricting the spread of infection. The most practical compromise for Pakistan appears to be the use of portable digital radiography equipment, and point-of- care ultrasound; with CT scan reserved for clinical situations not explained by the above two modalities, or demanding disease stratification.


title: How Understanding Society: The UK Household longitudinal study adapted to the COVID-19 pandemic

text: Understanding Society is a household panel survey with continuous fieldwork (monthly sam-ples) using a mixed mode design. Prior to March 2020, around half of all interviews were carried out face-to-face, amounting to around 1,150 interviews per month. This article outlines how the survey rapidly transitioned to a protocol without face-to-face interviews and presents some initial indicators of the impact of the change on field outcomes.


title: Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing

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


title: Experiences of A University Hospital During The COVID-19 Pandemic in Turkey

text: New Corona Virus Disease (COVID-19) was identified on January 13, 2020, as a result of first researches conducted in patients who developed similar respiratory symptoms in Wuhan Province, China at the end of December 2019 After the diagnosis of the first case on March 10, 2020 in Turkey, 'COVID-19 Action Plan' was prepared to inform all employees to act in coordination and to define their duties and responsibilities Although the hospitals function mainly on treatment in the epidemic, screening and preventive measures have to gain momentum during the epidemic process, especially for the staff For this reason, sharing the occupational health and safety policies carried out in hospitals, will contribute the upcoming period The aim of this paper is to report the efforts to protect the health of both hospital staff and patients during the Covid-19 pandemic in a tertiary hospital We think that this will set an example for different pandemic processes that may be experienced in future


title: The system dynamic model of the labor migrant policy in economic growth affected by COVID-19. (Special Issue: Covid-19.)

text: At the end of 2019, the new virus called Coronavirus Disease (Covid-19) spread widely from China all over the world In March 2020 the World Health Organization declared a new virus outbreak as "a global pandemic", and recommended social distancing and quarantine Most countries in Europe have been quarantined The social aspect of this issue is complicated by the fact that Europe nowadays hosts 82 million international migrants If migrant workers leave the host country, it reduces the Covid-19 spread Nevertheless, if migrant workers do not return, it will worsen the situation with the economic crisis The subject of the study is the instrumental and mathematical aspects of impact simulation of labor migrants' policy on the economic growth of the host country affected by COVID-19 pandemic The aim of the work is to develop the system dynamics model for assessing labor migrants' policy impact on the economic growth of the host country during COVID-19 pandemic It examined through hypotheses of different scenarios of labor migrants policy impact on the host country economic growth in Covid-19 pandemic The proposed model combines epidemiological and the economic growth models and relies upon real statistical data The analysis was carried out in four European countries The results of the study enabled to state that without migrant workers the gross domestic product may fall to 43% in Italy, 45% in Netherlands, 37% in Spain and 200% in Switzerland in 2020


title: A protocol for adding knowledge to Wikidata, a case report

text: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a “commons”. Wikidata, a public knowledge graph aligned with Wikipedia, is such a commons and uses unique identifiers to link knowledge in other knowledge bases However, Wikidata may not always have the right schema for the urgent questions. In this paper, we address this problem by showing how a data schema required for the integration can be modelled with entity schemas represented by Shape Expressions. As a telling example, we describe the process of aligning resources on the genomes and proteomes of the SARS-CoV-2 virus and related viruses as well as how Shape Expressions can be defined for Wikidata to model the knowledge, helping others studying the SARS-CoV-2 pandemic. How this model can be used to make data between various resources interoperable, is demonstrated by integrating data from NCBI Taxonomy, NCBI Genes, UniProt, and WikiPathways. Based on that model, a set of automated applications or bots were written for regular updates of these sources in Wikidata and added to a platform for automatically running these updates. Although this workflow is developed and applied in the context of the COVID-19 pandemic, to demonstrate its broader applicability it was also applied to other human coronaviruses (MERS, SARS, Human Coronavirus NL63, Human coronavirus 229E, Human coronavirus HKU1, Human coronavirus OC4).


title: Can China return to normalcy while keeping the coronavirus in check?

text: Life is almost back to normal in much of China Shops, restaurants, bars, and offices are open for business Manufacturing activity is picking up Traffic once again jams the highways of major cities Three quarters of China's workforce was back on the job as of 24 March, according to one company’s estimate Wuhan, where the COVID-19 pandemic originated, is lagging, as is the rest of Hubei province—but even there, the lockdown is due to lift 8 April China has done what few believed was possible: bring a blazing epidemic of a respiratory virus to a virtual standstill On 18 March, the country reported zero locally transmitted cases of COVID-19 for the first time Since then, only 6 of such infections have been reported, only one of them in Wuhan Now, the key question is: Can China keep it that way?


title: Psoriatic disease and body composition: a systematic review of the literature

text: Background. Obesity is a leading comorbidity in psoriatic disease, including both psoriasis (Pso) and psoriatic arthritis (PsA), and is associated with adverse metabolic and cardiovascular (CV) outcomes. Anthropometric parameters, such as weight, body mass index (BMI) and waist-to-hip ratio, have been extensively reported in psoriatic disease. However, the associations of body composition and fat distribution with psoriasis have not been fully defined. Objectives. To identify whether patients with psoriatic disease, including psoriatic arthritis, have altered body composition compared with the general population, and to review existing modalities for the assessment of body composition. Methods. Electronic searches of the literature were conducted in PubMed, Medline (Ovid), Embase (Ovid), Cochrane Central Register and Google Scholar. Titles and abstracts were reviewed by two authors independently against a set of prespecified inclusion/exclusion criteria. Results. Twenty-five full text articles met the inclusion criteria and were included in the final narrative analysis. The studies were of heterogeneous design and used a range of objective measures to assess body composition, including simple anthropometric measures, bioimpedance analysis (BIA), dual energy X-ray absorptiometry (DXA) and computed tomography (CT). Few studies met all the quality assessment criteria. Conclusions. Patients with psoriatic disease reveal defined body composition changes that are independent of obesity and the customary metabolic syndrome, including higher overall body fat, visceral fat and sarcopenia. These findings emphasize that patients with psoriatic disease should be screened for abnormal adipose effects beyond their weight and body mass index (BMI). Our findings show that the last decade has seen an exciting expansion of research interest in the development and validation of new modalities for the assessment of body composition. There is no consensus on the optimal assessment method of body composition for this diverse group, hence there is a need for validation of existing modalities and standardization of assessment tools.


title: Deep learning models for COVID-19 infected area segmentation in CT images

text: Recent studies indicated that detecting radiographic patterns on CT chest scans could in some cases yield higher sensitivity and specificity for COVID-19 detection compared to other methods such as RTPCR. In this work, we scrutinize the effectiveness of deep learning models for semantic segmentation of pneumonia infected area segmentation in CT images for the detection of COVID-19. We explore the efficacy of U-Nets and Fully Convolutional Neural Networks in this task using real-world CT data from COVID-19 patients. The results indicate that Fully Convolutional Neural Networks are capable of accurate segmentation despite the class imbalance on the dataset and the man-made annotation errors on the boundaries of symptom manifestation areas, and can be a promising method for further analysis of COVID-19 induced pneumonia symptoms in CT images.


Safety of Ultrasonic Enhancing Agents in Patients with COVID-19


Offline: COVID-19—bewilderment and candour


title: Chinese Law on SARS. Chenglin Liu. Buffalo, NY: William Hein, Inc., 2004. xiv, 186 pp. (Chinese Law Series, v. 7). $82.00. (cloth) ISBN 0-8377-3406-1.

text: Unknown


title: Cremation based estimates suggest significant under- and delayed reporting of COVID-19 epidemic data in Wuhan and China

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


Ferritin levels and COVID-19


title: A collaborative transformation beyond coal and cars? Co-creation and corporatism in the german energy and mobility transitions

text: In this article, we critically discuss the role of collaboration in Germany's path towards a post-carbon economy. We consider civic movements and novel forms of collaboration as a potentially transformative challenger to the predominant approach of corporatist collaboration in the mobility and energy sectors. However, while trade unions and employer organizations provide a permanent and active arena for policy-oriented collaboration, civil society groups cannot rely on an equivalently institutionalized corridor to secure policy impact and public resonance. In that sense, conventional forms of collaboration tend to hinder the transformation towards a post-carbon economy. Collaboration in the German corporatist setting is thus, from a sustainability perspective, simultaneously a problem and a solution. We argue for more institutionalized corridors between civil society and state institutions. Co-creation, as we would like to call this methodical approach to collaborating, can be anchored within the environmental and industrial policy arenas.


title: Epidemiological Determinants of COVID-19-Related Patient Outcomes in Different Countries and Plan of Action: A Retrospective Analysis

text: Current development around the pandemic of novel coronavirus disease 2019 (COVID-19) presents a significant healthcare resource burden threatening to overwhelm the available nationwide healthcare infrastructure. It is essential to consider, especially for resource-limited nations, strategizing the coordinated response to handle this crisis effectively and preparing for the upcoming emergence of calamity caused by this yet-to-know disease entity. Relevant epidemiological data were retrieved from currently available online reports related to COVID-19 patients. The correlation coefficient was calculated by plotting dependant variables - the number of COVID-19 cases and the number of deaths due to COVID 19 on the Y-axis and independent variables - critical-care beds per capita, the median age of the population of the country, the number of COVID-19 tests per million population, population density (persons per square km), urban population percentage, and gross domestic product (GDP) expense on health care - on the X-axis. After analyzing the data, both the fatality rate and the total number of COVID-19 cases were found to have an inverse association with the population density with the variable - the number of cases of COVID-19 - achieving a statistical significance (p-value 0.01). The negative correlation between critical care beds and the fatality rate is well-justified, as intensive care unit (ICU) beds and ventilators are the critical elements in the management of complicated cases. There was also a significant positive correlation between GDP expenses on healthcare by a country and the number of COVID-19 cases being registered (p-value 0.008), although that did not affect mortality (p-value 0.851). This analysis discusses the overview of various epidemiological determinants possibly contributing to the variation in patient outcomes across regions and helps improve our understanding to develop a plan of action and effective control measures in the future.


title: Management of rheumatic diseases in the times of COVID-19 pandemic- perspectives of rheumatology practitioners from India

text: Background. The Coronavirus disease 19 (COVID-19) pandemic has led to widespread concerns about the risk of infection in patients with rheumatic diseases (RD) receiving disease modifying ant-rheumatic drugs (DMARDs) and other immunosuppressants (IS). Methods. A SurveyMonkey based electronic survey was conducted amongst members of the Indian Rheumatology Association to understand the need for changes in prevailing practices. Results. Of the 861 invitees, 221 responded. In the wake of the pandemic, 47.5% would reduce biological DMARDs (bDMARDs) while only 12.2% would reduce the use of conventional synthetic DMARDs. 64.2% were likely to defer change in IS, the reluctance being most with rituximab (58.3%) followed by cyclophosphamide (53.3%), anti-tumor necrosis factor alpha agents (52.4%) and Janus kinase inhibitors (34.39%). Hydroxychloroquine was the preferred choice (81.9%) for the treatment of COVID-19 followed by protease inhibitors (22.1%) and intravenous immunoglobulin (8.1%). Chloroquine was less preferred (19%). More than two-thirds (70.5%) believed that COVID-19 might trigger macrophage activation syndrome. Social distancing (98.1%) and hand hygiene (74.6%) were recommended by majority. 62.8% would avoid touch for clinical examination whenever feasible. Conclusion. Most rheumatologists perceived the need to change treatment of RDs during the COVID-19 pandemic; reduce immunosuppression and defer the usage of rituximab and bDMARDs.


title: Relationship between the ABO Blood Group and the COVID-19 Susceptibility

text: The novel coronavirus disease-2019 (COVID-19) has been spreading around the world rapidly and declared as a pandemic by WHO. Here, we compared the ABO blood group distribution in 2,173 patients with COVID-19 confirmed by SARS-CoV-2 test from three hospitals in Wuhan and Shenzhen, China with that in normal people from the corresponding regions. The results showed that blood group A was associated with a higher risk for acquiring COVID-19 compared with non-A blood groups, whereas blood group O was associated with a lower risk for the infection compared with non-O blood groups. This is the first observation of an association between the ABO blood type and COVID-19. It should be emphasized, however, that this is an early study with limitations. It would be premature to use this study to guide clinical practice at this time, but it should encourage further investigation of the relationship between the ABO blood group and the COVID-19 susceptibility.


title: Recombination and purifying selection preserves covariant movements of mosaic SARS-CoV-2 protein S

text: In depth evolutionary and structural analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolated from bats, pangolins, and humans are necessary to assess the role of natural selection and recombination in the emergence of the current pandemic strain. The SARS-CoV-2 S glycoprotein unique features have been associated with efficient viral spread in the human population. Phylogeny-based and genetic algorithm methods clearly show that recombination events between viral progenitors infecting animal hosts led to a mosaic structure in the S gene. We identified recombination coldspots in the S glycoprotein and strong purifying selection. Moreover, although there is little evidence of diversifying positive selection during host-switching, structural analysis suggests that some of the residues emerged along the ancestral lineage of current pandemic strains may contribute to enhanced ability to infect human cells. Interestingly, recombination did not affect the long-range covariant movements of SARS-CoV-2 S glycoprotein monomer in pre-fusion conformation but, on the contrary, could contribute to the observed overall viral efficiency. Our dynamic simulations revealed that the movements between the host cell receptor binding domain (RBD) and the novel furin-like cleavage site are correlated. We identified threonine 333 (under purifying selection), at the beginning of the RBD, as the hinge of the opening/closing mechanism of the SARS-CoV-2 S glycoprotein monomer functional to hACE2 binding. Our findings support a scenario where ancestral recombination and fixation of amino acid residues in the RBD of the S glycoprotein generated a virus with unique features, capable of extremely efficient infection of the human host.


title: CoVID-19 prediction for India from the existing data and SIR(D) model study

text: CoVID-19 is spreading throughout the world at an alarming rate. So far it has spread over 200 countries in the whole world. Mathematical modelling of an epidemic like CoVID-19 is always useful for strategic decision making, especially it is very useful to gain some understanding of the future of the epidemic in densely populous countries like India. We use a simple yet effective mathematical model SIR(D) to predict the future of the epidemic in India by using the existing data. We also estimate the effect of lock-down/social isolation via a time-dependent coefficient of the model. The model study with realistic parameters set shows that the epidemic will be at its peak around the end of June or the first week of July with almost 108 Indians most likely being infected if the lock-down relaxed after May 3, 2020. However, the total number of infected population will become one-third of what predicted here if we consider that people only in the red zones (approximately one-third of India's population) are susceptible to the infection. Even in a very optimistic scenario we expect that at least the infected numbers of people will be of the order of 107.


title: Artificial Intelligence for COVID-19 Risk Classification in Kidney Disease: Can Technology Unmask an Unseen Disease?

text: Background: We developed two unique machine learning (ML) models that predict risk of: 1) a major COVID-19 outbreak in the service county of a local HD population within following week, and 2) a hemodialysis (HD) patient having an undetected SARS-CoV-2 infection that is identified after following 3 or more days. Methods: We used county-level data from United States population (March 2020) and HD patient data from a network of clinics (February-May 2020) to develop two ML models. First was a county-level model that used data from general and HD populations (21 variables); outcome of a COVID-19 outbreak in a dialysis service area was defined as a clinic being located in one of the national counties with the highest growth in COVID-19 positive cases (number and people per million (ppm)) in general population during 22-28 Mar 2020. Second was a patient-level model that used HD patient data (82 variables) to predict an individual having an undetected SARS-CoV-2 infection that is identified in subsequent [≥]3 days. Results: Among 1682 counties with dialysis clinics, 82 (4.9%) had a COVID-19 outbreak during 22-28 Mar 2020. Area under the receiver operating characteristic curve (AUROC) for the county-level model was 0.86 in testing dataset. Top predictor of a county experiencing an outbreak was the COVID-19 positive ppm in the general population in the prior week. In a select group (n=11,664) used to build the patient-level model, 28% of patients had COVID-19; prevalence was by design 10% in the testing dataset. AUROC for the patient-level model was 0.71 in the testing dataset. Top predictor of an HD patient having a SARS-CoV-2 infection was mean pre-HD body temperature in the prior week. Conclusions: Developed ML models appear suitable for predicting counties at risk of a COVID-19 outbreak and HD patients at risk of having an undetected SARS-CoV-2 infection.


title: The Immediate Effect of COVID-19 Policies on Social Distancing Behavior in the United States

text: In the absence of a vaccine and effective antiviral medications, most of the non-pharmaceutical interventions focus on reducing social contact rates through different social distancing policies. However, the effectiveness of different policies and their relative impact vis-a-vis that of mechanisms driven by public awareness and voluntary actions have not been studied. This is crucial since in most places we observe significant reductions in social interaction before any policy was implemented. Variations in types and effective dates of different social distancing policies across different states in the US create a natural experiment to study the causal impact of each policy during the early stage of the outbreak. Using these policy variations and the aggregate human mobility and location trends published by Google for the month of March 2020, we employ a quasi-experimental approach to measure the impact of six common policies on people's presence at home and their mobility in different types of public places. Our results rank six common social distancing policies based on the magnitude and significance of their impact, beyond what has already been achieved through voluntary actions. They show that while strong policies such as statewide stay home mandate and non-essential business closure have strong causal impacts on reducing social interactions, most of the expected impact of more lenient policies (such as large gathering ban and school closure mandates) are already reaped from non-policy mechanisms such as voluntary actions and public awareness.


title: How was the Mental Health of Colombian people on March during Pandemics Covid19?

text: Actual pandemic started with first cases in China and fast spread in Europe, Asia and the next continents became a global concern from March, so the most of countries ordered a lockdown to decrease infection rate forced people to stay at home. Meanwhile, the infection was growing around all the world, daily news usually show the number of cases per country and people increased the use of Internet to work trough videoconference tools and use of Social Networks to communicate what they think, feel about covid19 issue. In Colombia the first case was detected on March 6, the lockdwon was announced on March 20 and the first death on March 21. During all this time, people were evolving his concern about covid19 and staying at home slowly therefore this behaviour was changing over the time. The proposal of the paper is analyzed the behaviour of the population using Social Media and Text Mining algorithms. The results shows how the topic covid19 was increasing during the time, sleep patterns changed, and people were worried about fear to death, family travelling outside of Colombia and public health actions.


title: Several countries in one: a mathematical modeling analysis for COVID-19 in inner Brazil

text: Early 2020 and the world experiences its very first pandemic of globalized era. A novel coronavirus, SARS-Cov-2, is the causative agent of severe pneumonia and rapidly spread through many nations, crashing health systems. In Brazil, the emergence of local epidemics in major metropolitan areas is a concern. In a huge and heterogeneous country, with regional disparities and climate diversity, several factors can modulate the dynamics of COVID-19. What should be the scenario for an inner Brazil and what can we do to control infection transmission in each one of these locations? In this paper, a mathematical model was developed to simulate disease transmission among individuals in several scenarios, differing by the intensity and type of control measures. Mitigation strategies rely on social distancing of all individuals, and detection and isolation of infected ones. The model shows that control effort varies among cities. The social distancing is the most efficient method to control disease transmission but improving detection and isolation of infected individuals can help loosening this mitigation strategy.


COVID-19 mask: A modified anatomical face mask


title: Is there hope for the Hajj? Using the SIR Model to Forecast COVID-19 Progression in the City of Makkah

text: Abstract: Background: The Hajj is the largest annual gathering in the world, and it is a very important event for every Muslim. Makkah annually receives three million pilgrims who perform Hajj. Although precautionary measures have been taken in Saudi Arabia to slow down the spread of COVID-19, such as locking down the most affected cities, practicing social distancing, and applying the infection-control precautions, the number of cases has increased. The total confirmed number of cases in Makkah was 10,709 with 127 deaths as of May 16, 2020. Aims of the study: Forecasting the COVID-19 progression in the city of Makkah will help the policymakers decide if the Hajj will be able to operate this year. Thus, to see a clear picture of the fight against COVID-19 for the economy and healthcare industry in Saudi Arabia, specifically in Makkah, the SIR model will predict COVID-19 progression in the city of Makkah. Method: The Susceptible, Infected, and Recovered (SIR) model has been used to track the transmission dynamics and growth among the city of Makkah. The growth index was calculated, according to the data from March 16 until May 9. The estimated vital epidemiological parameters, such as forecasting works and transmission rates, were done. Result: The data showed an interesting result about the peak of the disease progression. It is projected to occur around the 12th day after running the model. According to the model, the peak time will be around the 22nd of May. Then, the number of cases will start to decrease. Conclusion: Using the SIR model, the result predicts the disease progression peak and an estimated end of COVID-19 in the city of Makkah to help the policymakers decide if the Hajj will be able to operate this year.


title: BRAIN MR SPECTROSCOPIC FINDINGS IN THREE CONSECUTIVE COVID-19 PATIENTS: PRELIMINARY OBSERVATIONS

text: Brain magnetic resonance spectroscopic imaging (MRSI) was performed in three consecutive COVID-19 patients, as part of a pilot investigation of the pathophysiological processes underlying the brain involvement by the SARS-CoV-2 infection. These included one with necrotizing leukoencephalopathy, one after recent PEA cardiac arrest without leukoencephalopathy, and one without frank encephalopathy or recent severe hypoxic episode. The MRSI findings were compared to those of two patients with white matter pathology not SARS-CoV2 infection related, and a control patient without clinical encephalopathy. The N-acetyl-aspartate reduction, choline elevation, and glutamate/glutamine elevation found in the COVID necrotizing leukoencephalopathy patient and, to a lesser degree, the COVID post-cardiac arrest patient, follow a similar pattern as seen with the delayed post-hypoxic leukoencephalopathy patient. Lactate elevation was most pronounced in the patient with COVID necrotizing leukoencephalopathy.


title: Time-variant strategies for optimizing the performance of non-pharmaceutical interventions (NPIs) in protecting lives and livelihoods during the COVID-19 pandemic

text: A stochastic Individual Contact Model (ICM) using SIR compartments allowing for time-variant parameters was used to simulate 100 non-pharmaceutical intervention (NPI) strategies and exit trajectories for a hypothetical population, and to collect epidemiological and non-epidemiological outcomes to measure the performance of these strategies over the course of a period of intervention (up to six months) for a total duration of one-year to allow the full implications of the strategy and endgame to manifest. We find that variations in the time dimension and intensity of various strategies can have vastly different performance outcomes: (i) the timing of NPIs can 'shrink the area under the curve' (cumulative infections) not just 'flatten the curve'; (ii) prolonged lockdowns have diminishing margins of returns; (iii) smooth, submaximal lockdowns perform better than pulsatile lockdowns; and (iv) the efficiency of various strategies incorporating both epidemiological and non-epidemiological outcomes vary substantially. Most sobering, none of the simulated strategies allow for an 'acceptable' path to exit within six months due to very large gaps in health system capacity.


title: The novel coronavirus outbreak in Wuhan, China

text: The novel coronavirus (2019-nCoV, or COVID-19) epidemic first broke out in Wuhan and has been spreading in whole China and the world. The numbers of new infections and deaths in Wuhan are still increasing, which have posed major public health and governance concerns. A series of mandatory actions have been taken by the municipal and provincial governments supported by the central government, such as measures to restrict travels across cities, case detection and contact tracing, quarantine, guidance and information to the public, detection kit development, etc. Challenges such as lacking effective drugs, insufficient hospital services and medical supplies, logistics, etc. have much alleviated with the solidarity of the whole society. The pandemic will definitely be ended with the continuous efforts of both national and international multi-sectoral bodies.


title: Metabolic indicators associated with non-communicable diseases deteriorated in COVID-19 outbreak: evidence from a two-center, retrospective study

text: Objective: Our study aimed to investigate whether the metabolic indicators associated with non-communicable diseases (NCDs) in the general population have changed during the COVID-19 outbreak. METHODS: This retrospective self-controlled study enrolled adult participants with metabolic indicators relate to NCDs followed at Fujian Provincial Hospital and Fujian Provincial Hospital South Branch. The metabolic indicators followed during January 1, 2020 and April 30, 2020, the peak period of the COVID-19 epidemic in China, were compared with the baseline value in the same period last year. Pared-samples T-test and Wilcoxon signed-rank test were performed to analyze the differences between paired data. Results: The follow-up total cholesterol was significantly increased than that of the baseline (4.73 (4.05, 5.46) mmol/L vs 4.71 (4.05, 5.43) mmol/L, p=0.019; n=3379). Similar results were observed in triglyceride (1.29 (0.91, 1.88) vs 1.25 (0.87, 1.81) mmol/L, p<0.001; n=3381), uric acid (330.0 (272.0, 397.0) vs 327.0 (271.0, 389.0) umol/L, p<0.001; n=3364), and glycosylated hemoglobin (6.50 (6.10, 7.30) vs 6.50 (6.10, 7.20) %, p=0.013; n=532). No significant difference was observed in low density lipoprotein, body mass index and blood pressure. Conclusions: Metabolic indicators associated with NCDs deteriorated in the COVID-19 outbreak. We should take action to prevent and control NCDs without delay.


title: Combining PCR and CT testing for COVID

text: We analyze the effect of using a screening CT-scan for evaluation of potential COVID-19 infections in order to isolate and perform contact tracing based upon a viral pneumonia diagnosis. RT-PCR is then used for continued isolation based upon a COVID diagnosis. Both the low false negative rates and rapid results of CT-scans lead to dramatically reduced transmission. The reduction in cases after 60 days with widespread use of CT-scan screening compared to PCR by itself is as high as 50x, and the reduction of effective reproduction rate R(t) is 0.20. Our results imply that much more rapid extinction of COVID is possible by combining social distancing with CT-scans and contact tracing.


title: Outcomes from COVID-19 across the range of frailty: excess mortality in fitter older people

text: Purpose Our aim was to quantify the mortality from COVID-19 and identify any interactions with frailty and other demographic factors. Methods Hospitalised patients aged [≥]70 were included, comparing COVID-19 cases with non-COVID-19 controls admitted over the same period. Frailty was prospectively measured and mortality ascertained through linkage with national and local statutory reports. Results In 217 COVID-19 cases and 160 controls, older age and South Asian ethnicity, though not socioeconomic position, were associated with higher mortality. For frailty, differences in effect size were evident between cases (HR 1.02, 95%CI 0.93-1.12) and controls (HR 1.99, 95%CI 1.46-2.72), with an interaction term (HR 0.51, 95%CI 0.37-0.71) in multivariable models. Conclusions Our findings suggest that (i) frailty is not a good discriminator of prognosis in COVID-19 and (ii) pathways to mortality may differ in fitter compared with frailer older patients.


title: Research on CNN-based Models Optimized by Genetic Algorithm and Application in the Diagnosis of Pneumonia and COVID-19

text: In this research, an optimized deep learning method was proposed to explore the possibility and practicality of neural net-work applications in medical imaging. The method was used to achieve the goal of judging common pneumonia and even COVID-19 more effectively. Where, the genetic algorithm was taken advantage to optimize the Dropout module, which is essential in neural networks so as to improve the performance of typical neural network models. The experiment results demonstrate that the proposed method shows excellent performance and strong practicability in judging pneumonia, and the application of advanced artificial intelligence technology in the field of medical imaging has broad prospects.


title: Structural Motifs, Disorder, and the Efficacy of Viral Vaccines

text: We demonstrate that it is possible to draw direct numerical correlations between virus particles and effective virus-like particle (VLP) derived vaccines through extraction of a Bragg-Williams order parameter from electron microscopy. The method has its roots in studies of disorder in metal alloys, and is adapted to describe the type and occurrence of structural motifs within the arrangement of viral coat proteins, captured by the value of the order parameter as a measure of disorder. A conventional approach to viral vaccine design consists of replicating select proteins to create a VLP designed to trigger an immune response while remaining non-infectious. Understanding variations between viruses and vaccine strains therefore tends to focus on differences between proteins, which can be characterized through genetic analysis. While such an approach provides vital information about the functioning and interactions of the proteins, it does not yet yield an early-stage pathway towards predicting the efficacy of a vaccine, and so large-scale clinical trials are required to obtain critical information. With the urgency associated with pandemics, including Coronavirus Disease-2019 (COVID-19) originating from the SARS-CoV-2 virus, there is a need for earlier indications of whether a vaccine has the necessary characteristics. Application of the methodology to Dengue and influenza virus particles indicates that temperature and pH during incubation could potentially be exploited to fine-tune the order parameter of VLP-based vaccines to match the corresponding virus. Additionally, utilization of an Ising model plot reveals a clear relationship between case fatality rate and order parameter for distinct virus families.


title: Cancer inpatient with COVID-19: a report from the Brazilian National Cancer Institute

text: Brazil has been recording a frightening exponential curve of confirmed cases of SARS-CoV-2 infection. Cancer patients with COVID-19 are likely to have a greater risk of complications and death. A retrospective search in the electronic medical records of cancer inpatients admitted to the Brazilian National Cancer Institute from April 30, 2020 to May 26, 2020 granted identification of 181 patients with COVID-19 confirmed by RT-PCR method. The mean age was 55.3 years (SD 21.1). The most prevalent solid tumors were breast (40 [22.1%]), gastrointestinal (24 [13.3%]), and gynecological (22 [12.2%]). Among hematological malignancies, lymphoma (20 [11%]) and leukemia (10 [5.5%]) predominated. The most common complications were respiratory failure (70 [38.7%]), septic shock (40 [22.1%]) and acute kidney injury (33 [18.2%]). A total of 60 (33.1%) patients died due to COVID-19 complications. By multivariate analysis, cases with admission due to symptoms of COVID-19 (p = 0.027) and with two or more metastatic sites (p <0.001) showed a higher risk of COVID-19-specific death. This is the first study in a cohort of Brazilian cancer patients with COVID-19. The rates of complications and COVID-19-specific death were significantly high. Our data prompts urgent and effective public policies for this group of especially vulnerable patients.


title: Guidelines for preventing respiratory illness in older adults aged 60 years and above living in long-term care: A rapid review of clinical practice guidelines

text: Background: The overall objective of this rapid review was to identify infection protection and control recommendations from published clinical practice guidelines (CPGs) for adults aged 60 years and older in long-term care settings Methods: Comprehensive searches in MEDLINE, EMBASE, the Cochrane Library, and relevant CPG publishers/repositories were carried out in early March 2020. Title/abstract and full-text screening, data abstraction, and quality appraisal (AGREE-II) were carried out by single reviewers. Results: A total of 17 relevant CPGs were identified, published in the USA (n=8), Canada (n=6), Australia (n=2), and the United Kingdom (n=1). All of the CPGs dealt with infection control in long-term care facilities (LTCF) and addressed various types of viral respiratory infections (e.g., influenza, COVID-19, severe acute respiratory syndrome). Ten or more CPGs recommended the following infection control measures in LTCF: hand hygiene (n=13), wearing personal protective equipment (n=13), social distancing or isolation (n=13), disinfecting surfaces (n=12), droplet precautions (n=12), surveillance and evaluation (n=11), and using diagnostic testing to confirm illness (n=10). While only two or more CPGs recommended these infection control measures: policies and procedures for visitors, staff and/or residents (n=9), respiratory hygiene/cough etiquette (n=9), providing supplies (n=9), staff and/or residents education (n=8), increasing communication (n=6), consulting or notifying health professionals (n=6), appropriate ventilation practices (n=2), and cohorting equipment (n=2). Ten CPGs also addressed management of viral respiratory infections in LTCF and recommended antiviral chemoprophylaxis (n=10) and one CPG recommended early mobilization of residents. Conclusion: The recommendations from current guidelines overall seem to support environmental measures for infection prevention and antiviral chemoprophylaxis for infection management as the most appropriate first-line response to viral respiratory illness in long-term care.


title: To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic

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