{"id":6329,"date":"2020-04-28T14:23:53","date_gmt":"2020-04-28T21:23:53","guid":{"rendered":"https:\/\/depts.washington.edu\/pandemicalliance\/?p=6329"},"modified":"2021-03-10T14:44:48","modified_gmt":"2021-03-10T22:44:48","slug":"covid-19-literature-situation-report-april-28-2020","status":"publish","type":"post","link":"https:\/\/depts.washington.edu\/pandemicalliance\/2020\/04\/28\/covid-19-literature-situation-report-april-28-2020\/","title":{"rendered":"COVID-19 Literature Situation Report April 28, 2020"},"content":{"rendered":"<p>The scientific literature on COVID-19 is rapidly evolving and these articles were selected for review based on their relevance to Washington State decision making around COVID-19 response efforts. Included in these Lit Reps are some manuscripts that have been made available online as pre-prints but have not yet undergone peer review. Please be aware of this when reviewing articles included in the Lit Reps.<\/p>\n<h2>Key Takeaways<\/h2>\n<ul>\n<li><b>Barkan et al compares various exit strategy building blocks and measures to mitigate the current SARS-CoV-2 pandemic based on computerized simulations, finding significant differences in suppression among strategies with seemingly similar cost.\u00a0\u00a0<\/b><\/li>\n<li><b>African American race and Hispanic ethnicity are associated with higher likelihood of SARS-CoV-2 infection, even after adjusting for other important socio-demographic and comorbidity factors.<\/b><\/li>\n<li><b>A study found an increase of 1 <\/b><b>\ud835\udf07<\/b><b>g\/m3 in PM<\/b><b>2.5 <\/b><b>is associated with an 8% increase in the US COVID-19 death rate, highlighting the importance of enforcing existing air pollution regulations.\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li><b>Patients on ACEi\/ARB showed a 44% reduction in odds of developing severe disease and a 62% reduction in odds of death when compared to patients not on ACEi\/ARB.<\/b><\/li>\n<\/ul>\n<div id=\"uw-accordion-shortcode\">\n<h3>Article Summaries<\/h3>\n<div class=\"js-accordion\" data-accordion-prefix-classes=\"uw-accordion-shortcode\">\n<div class=\"js-accordion__panel\" >\n<h2 class=\"js-accordion__header\"><span style=\"font-weight: 400\">Non-Pharmaceutical Interventions<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-6330\" class=\"su-post\">\n<h5 class=\"su-post-title\">Comparison of SARS-CoV-2 Exit Strategies Building Blocks<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The authors compare various exit strategy building blocks and measures to mitigate the current SARS-CoV-2 pandemic based on computerized simulations, finding significant differences in suppression among strategies with seemingly similar cost.\u00a0\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The most effective strategies found integrate several base strategies, and allow for the release of large portions of the population. Stratified population release to achieve herd immunity did not perform well compared with other strategies. This information may help optimize exit strategies to be more effective and suitable for a particular area or country while maximizing human life and economic value.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Barkan et al. (April 28, 2020). Comparison of SARS-CoV-2 Exit Strategies Building Blocks. Pre-print downloaded Apr 28 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.23.20072850\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.23.20072850<\/span><\/a><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"js-accordion__panel\" >\n<h2 class=\"js-accordion__header\"><span style=\"font-weight: 400\">Transmission<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-6338\" class=\"su-post\">\n<h5 class=\"su-post-title\">Impact of temperature on the dynamics of COVID-19 outbreak in China<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This study examines the relationship between daily confirmed COVID-19 cases and temperature using data from 31 provincial regions in China.\u00a0 The authors\u2019 model showed a significant decrease in incidence with temperatures above 46-50\u2070F. This suggests that temperature played an important role in the outbreak of COVID-19 in China, and may be useful in predicting the potential spread of COVID-19 in other geographic areas.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Shi et al. (April 2020). Impact of temperature on the dynamics of COVID-19 outbreak in China. Sci Total Environ. <\/span><\/i><a href=\"https:\/\/doi.org\/10.1016\/j.scitotenv.2020.138890\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1016\/j.scitotenv.2020.138890<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6336\" class=\"su-post\">\n<h5 class=\"su-post-title\">Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">A cross-sectional ecological study used county-level data representing 98% of the US population to investigate the association between fine particulate matter (PM<\/span><span style=\"font-weight: 400\">2.5<\/span><span style=\"font-weight: 400\">) and COVID-19 death.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The authors found a statistically significant increase of only 1 <\/span><span style=\"font-weight: 400\">\ud835\udf07<\/span><span style=\"font-weight: 400\">g\/m3 in PM<\/span><span style=\"font-weight: 400\">2.5 <\/span><span style=\"font-weight: 400\">is associated with an 8% increase in the COVID-19 death rate (95% CI: 2-15%). Findings underscore the importance of continuing to enforce existing air pollution regulations to protect human health both during and after the COVID-19 crisis.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Wu et al. (April 7, 2020). Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study. Pre-print downloaded Apr 28<\/span><\/i> <span style=\"font-weight: 400\">from <\/span><a href=\"https:\/\/doi.org\/10.1101\/2020.04.05.20054502\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.05.20054502<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6334\" class=\"su-post\">\n<h5 class=\"su-post-title\">Regional differences in reported Covid-19 cases show genetic correlations with higher socio-economic status and better health, potentially confounding studies on the genetics of disease susceptibility<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This regional genome-wide association study included data from 396,042 individuals in England to investigate the association between genetic variants and regional differences in reported COVID-19 cases. The author found a temporary positive relationship between COVID-19 cases and regional socioeconomic status at the beginning of the outbreak, the opposite direction of expected disease increasing effects, and suggests that this may be due to higher rates of international travel, more social contacts, and\/or better testing capacities.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Abdellaoui (April 28, 2020). Regional differences in reported Covid-19 cases show genetic correlations with higher socio-economic status and better health, potentially confounding studies on the genetics of disease susceptibility. Pre-print downloaded Apr 28 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.24.20075333\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.24.20075333<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6332\" class=\"su-post\">\n<h5 class=\"su-post-title\">Racial and Ethnic Disparities in SARS-CoV-2 Pandemic: Analysis of a COVID-19 Observational Registry for a Diverse U.S. Metropolitan Population<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">A cross sectional analysis of 4,513 individuals, including 754 positive cases, explores race disparities and potential mediating pathways (low income, high population density, and high comorbidity burden).<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Findings show that African American race and Hispanic ethnicity are associated with higher likelihood of SARS-CoV-2 infection, even after adjusting for other important socio-demographic and comorbidity factors. The authors provide the potential explanation that residence in population-dense areas may limit ability to practice social distancing.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Vahidy et al. (April 28, 2020). Racial and Ethnic Disparities in SARS-CoV-2 Pandemic: Analysis of a COVID-19 Observational Registry for a Diverse U.S. Metropolitan Population. Pre-print downloaded Apr 28 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.24.20073148\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.24.20073148<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"js-accordion__panel\" >\n<h2 class=\"js-accordion__header\"><span style=\"font-weight: 400\">Testing and Treatment<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-6342\" class=\"su-post\">\n<h5 class=\"su-post-title\">Long period dynamics of viral load and antibodies for SARS-CoV-2 infection: an observational cohort study<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This retrospective observational case series of 33 patients with SARS-CoV-2 pneumonia reviewed analysis of throat swabs, sputum, stool, and blood samples to evaluate viral load, IgM, IgG, spike protein receptor binding domain (RBD), and nucleocapsid.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Results suggest that viral RNA persists in sputum and stool samples for a long time, and that anti-RBD may serve as a protective antibody against SARS-CoV-2 that is related to viral persistence and is valuable for development of vaccines.\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Huang et al. (April 27, 2020). Long period dynamics of viral load and antibodies for SARS-CoV-2 infection: an observational cohort study. Pre-print downloaded Apr 27 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.22.20071258\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.22.20071258<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6340\" class=\"su-post\">\n<h5 class=\"su-post-title\">The effect of angiotensin converting enzyme inhibitors and angiotensin receptor blockers on death and severity of disease in patients with coronavirus disease 2019 (COVID-19): A meta-analysis<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This meta-analysis includes five studies totaling 308 patients either taking or not taking angiotensin converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB).\u00a0 Patients on ACEi\/ARB showed a 44% reduction in odds of developing severe disease and a 62% reduction in odds of death when compared to patients not on ACEi\/ARB.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The authors conclude that it is safe to use ACEi\/ARB with COVID-19 patients, and that this data suggests these medications may reduce the risk of developing severe disease and death.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Ghosal et al. (April 28, 2020). The effect of angiotensin converting enzyme inhibitors and angiotensin receptor blockers on death and severity of disease in patients with coronavirus disease 2019 (COVID-19): A meta-analysis. Pre-print downloaded Apr 28 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.23.20076661\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.23.20076661<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"js-accordion__panel\" >\n<h2 class=\"js-accordion__header\"><span style=\"font-weight: 400\">Clinical Characteristics and Health Care Setting<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-6348\" class=\"su-post\">\n<h5 class=\"su-post-title\">Persistent viral RNA positivity during recovery period of a patient with SARS-CoV-2 infection<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This case report describes a SARS-CoV-2 infection with a clinical course of over 2 months, including reappearing viral RNA in saliva concurrent with viral specific antibodies. Findings indicate that SARS-CoV-2 can cause a long clinical course, and imply an immune evasion from the host immune system.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Yang et al. (April 24, 2020). Persistent viral RNA positivity during recovery period of a patient with SARS-CoV-2 infection. J Med Virol.<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1002\/jmv.25940\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1002\/jmv.25940<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6346\" class=\"su-post\">\n<h5 class=\"su-post-title\">Large-Vessel Stroke as a Presenting Feature of Covid-19 in the Young<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The authors discuss findings from five cases of large-vessel stroke in SARS-CoV-2 patients under 50 years of age in New York City.\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Oxley et al. (April 27, 2020). Large-Vessel Stroke as a Presenting Feature of Covid-19 in the Young. NEJM.<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1056\/NEJMc2009787\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1056\/NEJMc2009787<\/span><\/a><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6344\" class=\"su-post\">\n<h5 class=\"su-post-title\">Vitamin D insufficiency is prevalent in severe COVID-19<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This 20-patient retrospective observational study suggests a link between Vitamin D insufficiency (VDI) and severe COVID-19. Anecdotal and observational data indicate that VDI may play a significant role in the disease progression of COVID-19.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Lau et al. (April 28, 2020). Vitamin D insufficiency is prevalent in severe COVID-19. Pre-print downloaded Apr 28 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.24.20075838\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.24.20075838<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"js-accordion__panel\" >\n<h2 class=\"js-accordion__header\"><span style=\"font-weight: 400\">Modelling and Prediction<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-6352\" class=\"su-post\">\n<h5 class=\"su-post-title\">Estimating population immunity without serological testing<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The author proposes a methodology for estimating population immunity to COVID-19 using available mortality data and properties of the SIR model, illustrated using 10 US states\u2019 data.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Lesniewski (April 23, 2020).\u00a0 Estimating population immunity without serological testing. Pre-print downloaded Apr 27 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.23.20076786\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.23.20076786<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6350\" class=\"su-post\">\n<h5 class=\"su-post-title\">Forecasting the impact of the first wave of the COVID-19 pandemic on hospital demand and deaths for the USA and European Economic Areas<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This IHME study describes modeling techniques used to estimate the trajectory of COVID-19 deaths as a function of social distancing, hospital and ICU admissions, length of stay, and ventilator need.\u00a0 Excess medical demand in the US is predicted to peak at 9,079 total beds and 9,356 ICU beds, and ventilator use is predicted to peak at 16,545.\u00a0 Death peaks vary from March 30 through May 12 by state.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">These estimates can help inform the development and implementation of strategies to mitigate gaps, including reducing non-COVID-19 demand for services and temporarily increasing system capacity.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">IHME COVID-19 health service utilization forecasting team (April 26, 2020). Forecasting the impact of the first wave of the COVID-19 pandemic on hospital demand and deaths for the USA and European Economic Areas. Pre-print downloaded Apr 27 from <\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.04.21.20074732\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.21.20074732<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"js-accordion__panel\" >\n<h2 class=\"js-accordion__header\"><span style=\"font-weight: 400\">Public Health Policy and Practice<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-6358\" class=\"su-post\">\n<h5 class=\"su-post-title\">Prevalence of SARS-CoV-2 Infection in Residents of a Large Homeless Shelter in Boston<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Universal SARS-CoV-2 PCR testing of an adult homeless shelter in Boston shortly after a case cluster was identified yielded a prevalence of 36%, with a majority of newly identified infections being asymptomatic. Symptom screening in homeless shelters may not be adequate to capture the extent of disease transmission in this setting.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Baggett et al. (April 27, 2020). Prevalence of SARS-CoV-2 Infection in Residents of a Large Homeless Shelter in Boston. JAMA.<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1001\/jama.2020.6887\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1001\/jama.2020.6887<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6356\" class=\"su-post\">\n<h5 class=\"su-post-title\">Exposure to a Surrogate Measure of Contamination from Simulated Patients by Emergency Department Personnel Wearing Personal Protective Equipment<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The authors ran patient care simulations to assess updated PPE recommendations from WHO and CDC on use of N95 respirators, eye protection, isolation gowns, and gloves during aerosol-generating procedures.\u00a0\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Despite PPE, fluorescent markers were found on the uncovered skin, hair, and shoes of participants. These findings indicate that current recommendations for PPE may not fully prevent exposures in emergency department settings, and clothing that covers all skin may further diminish exposure risk.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Feldman et al. (April 27, 2020). Exposure to a Surrogate Measure of Contamination from Simulated Patients by Emergency Department Personnel Wearing Personal Protective Equipment. JAMA.<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1001\/jama.2020.6633\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1001\/jama.2020.6633<\/span><\/a><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<div id=\"su-post-6354\" class=\"su-post\">\n<h5 class=\"su-post-title\">Predictors of adherence to public health instructions during the COVID-19 pandemic<\/h5>\n<p>\t\t\t\t<!-- \n\n\n\n\n\n\n\n\n\n\n\n<div class=\"su-post-meta\">\n\t\t\t\t\t: \t\t\t\t<\/div>\n\n\n\n\n\n\n\n\n\n\n\n --><\/p>\n<div class=\"su-post-excerpt\">\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">This cross-sectional study of 654 Israeli participants found that male gender, not having children, smoking, ADHD symptoms, low pro-sociality, past risk-taking behavior, current psychological distress, low perceived risk of COVID-19 exposure, low exposure to instructions, and low perceived efficacy of instructions were associated with non-adherence to instructions. The findings suggest that in setting out and communicating public health instructions, policymakers should consider these characteristics.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Pollak et al. (April 28, 2020). Predictors of adherence to public health instructions during the COVID-19 pandemic. Pre-print downloaded Apr 28 from<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1101\/2020.04.24.20076620\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1101\/2020.04.24.20076620<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/p>\n<\/p>\n<\/div>\n<p>\t\t\t\t\t\t\t\t\t<!-- <a href=\"\" class=\"su-post-comments-link\"><\/a> --><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h3><strong>Other Resources and Commentaries<\/strong><\/h3>\n<ul>\n<li style=\"font-weight: 400\"><a href=\"https:\/\/doi.org\/10.1101\/2020.04.24.20070649\"><span style=\"font-weight: 400\">Performance of temporal artery temperature measurement in ruling out fever: implications for COVID-19 screening<\/span><\/a><span style=\"font-weight: 400\"> \u2013 Pre-print (Apr 28)<\/span><\/li>\n<li style=\"font-weight: 400\"><a href=\"https:\/\/doi.org\/10.1101\/2020.04.23.20074575\"><span style=\"font-weight: 400\">Wisconsin April 2020 election not associated with an increase in COVID-19 infection rates<\/span><\/a><span style=\"font-weight: 400\"> \u2013 Pre-print (Apr 28)\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><a href=\"https:\/\/doi.org\/10.1016\/S1473-3099(20)30357-1\"><span style=\"font-weight: 400\">Impact of contact tracing on SARS-CoV-2 transmission<\/span><\/a><span style=\"font-weight: 400\"> \u2013 Lancet Infect Dis (Apr 27)<\/span><\/li>\n<li style=\"font-weight: 400\"><a href=\"https:\/\/doi.org\/10.1101\/2020.04.24.20073957\"><span style=\"font-weight: 400\">The incubation period of COVID-19 \u2013 A rapid systematic review and meta-analysis of observational research<\/span><\/a><span style=\"font-weight: 400\"> \u2013 Pre-print (Apr 28)<\/span><\/li>\n<li style=\"font-weight: 400\"><a href=\"https:\/\/doi.org\/10.1007\/s11524-020-00438-6\"><span style=\"font-weight: 400\">Slum Health: Arresting COVID-19 and Improving Well-Being in Urban Informal Settlements<\/span><\/a><span style=\"font-weight: 400\">\u2013 J Urban Health (Apr 24)<\/span><\/li>\n<li style=\"font-weight: 400\"><a href=\"https:\/\/doi.org\/10.1016\/S0140-6736(20)30980-6\"><span style=\"font-weight: 400\">Atypical presentation of COVID-19 in young infants<\/span><\/a><span style=\"font-weight: 400\"> \u2013 Lancet (Apr 17)<\/span><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Barkan et al compares various exit strategy building blocks and measures to mitigate the current SARS-CoV-2 pandemic based on computerized simulations, finding significant differences in suppression among strategies with seemingly similar cost.  <\/p>\n<div><a class=\"more\" href=\"https:\/\/depts.washington.edu\/pandemicalliance\/2020\/04\/28\/predictors-of-adherence-to-public-health-instructions-during-the-covid-19-pandemic\/\">Read more<\/a><\/div>\n","protected":false},"author":8,"featured_media":1713,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[5],"tags":[],"topic":[],"class_list":["post-6329","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-covid-19-literature-situation-report"],"_links":{"self":[{"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/6329","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/comments?post=6329"}],"version-history":[{"count":1,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/6329\/revisions"}],"predecessor-version":[{"id":6361,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/6329\/revisions\/6361"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/media\/1713"}],"wp:attachment":[{"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/media?parent=6329"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/categories?post=6329"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/tags?post=6329"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/topic?post=6329"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}