{"id":8541,"date":"2020-07-29T10:49:45","date_gmt":"2020-07-29T17:49:45","guid":{"rendered":"https:\/\/depts.washington.edu\/pandemicalliance\/?p=8541"},"modified":"2021-04-05T11:06:29","modified_gmt":"2021-04-05T18:06:29","slug":"covid-19-literature-situation-report-july-29-2020","status":"publish","type":"post","link":"https:\/\/depts.washington.edu\/pandemicalliance\/2020\/07\/29\/covid-19-literature-situation-report-july-29-2020\/","title":{"rendered":"COVID-19 Literature Situation Report July 29, 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><span data-contrast=\"auto\">School closures were\u00a0<\/span><\/b><b><span data-contrast=\"auto\">associated\u00a0<\/span><\/b><b><span data-contrast=\"auto\">in time\u00a0<\/span><\/b><b><span data-contrast=\"auto\">with declines in COVID-19 incidence (<\/span><\/b><b><span data-contrast=\"auto\">-62%<\/span><\/b><b><span data-contrast=\"auto\">)<\/span><\/b><b><span data-contrast=\"auto\">\u00a0and mortality (-58%)<\/span><\/b><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><b><span data-contrast=\"auto\">across US states<\/span><\/b><b><span data-contrast=\"auto\">,\u00a0<\/span><\/b><b><span data-contrast=\"auto\">although<\/span><\/b><b><span data-contrast=\"auto\">\u00a0at least some of the\u00a0<\/span><\/b><b><span data-contrast=\"auto\">effect may have been due<\/span><\/b><b><span data-contrast=\"auto\">\u00a0to other\u00a0<\/span><\/b><b><span data-contrast=\"auto\">non<\/span><\/b><b><span data-contrast=\"auto\">&#8211;<\/span><\/b><b><span data-contrast=\"auto\">pharmaceutical\u00a0<\/span><\/b><b><span data-contrast=\"auto\">interventions implemented<\/span><\/b><b><span data-contrast=\"auto\">\u00a0concurrently.<\/span><\/b><span data-contrast=\"auto\">\u00a0<\/span><a href=\"https:\/\/doi.org\/10.1001\/jama.2020.14348\"><span data-contrast=\"none\">More<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0d8\" data-font=\"Wingdings\" data-listid=\"1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Among 15,920 individuals presenting to Michigan Medicine for COVID-19 testing, 1<\/span><\/b><b><span data-contrast=\"auto\">5<\/span><\/b><b><span data-contrast=\"auto\">% underwent multiple tests (average 2.6 tests per person). Among those who tested positive, hospitalization and ICU-level care\u00a0<\/span><\/b><b><span data-contrast=\"auto\">were\u00a0<\/span><\/b><b><span data-contrast=\"auto\">more common among those who tested multiple times<\/span><\/b><b><span data-contrast=\"auto\">.\u00a0<\/span><\/b><a href=\"https:\/\/doi.org\/10.1101\/2020.07.26.20162453\"><span data-contrast=\"none\">More<\/span><\/a><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0d8\" data-font=\"Wingdings\" data-listid=\"1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">An analysis of 85 patients with COVID-19 found that\u00a0<\/span><\/b><b><span data-contrast=\"auto\">a minority\u00a0<\/span><\/b><b><span data-contrast=\"auto\">had SARS-COV-2 RNA detected in serum<\/span><\/b><b><span data-contrast=\"auto\">, but that this finding<\/span><\/b><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><b><span data-contrast=\"auto\">was significantly associated with organ damage and in-hospital mortality.<\/span><\/b><span data-contrast=\"auto\">\u00a0<\/span><a href=\"https:\/\/doi.org\/10.1093\/cid\/ciaa1085\"><span data-contrast=\"none\">More<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0d8\" data-font=\"Wingdings\" data-listid=\"1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">The choice of which US reference population to use (CDC-weighted population<\/span><\/b><b><span data-contrast=\"auto\">\u00a0<\/span><\/b><b><span data-contrast=\"auto\">versus the unweighted US Census<\/span><\/b><b><span data-contrast=\"auto\">\u00a0population) results in considerable diff<\/span><\/b><b><span data-contrast=\"auto\">erences in the estimates of racial\/ethnic<\/span><\/b><b><span data-contrast=\"auto\">\u00a0disparities in COVID-19 deaths<\/span><\/b><b><span data-contrast=\"auto\">.<\/span><\/b><span data-contrast=\"auto\">\u00a0<\/span><a href=\"https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.16933\"><span data-contrast=\"none\">More<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/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 class=\"TextRun SCXW40369296 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW40369296 BCX0\" data-ccp-parastyle=\"heading 2\">Non-Pharmaceutical Interventions<\/span><\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-8547\" class=\"su-post\">\n<h5 class=\"su-post-title\">Prevalence of Mask Wearing in Northern Vermont in Response to SARS-CoV-2<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">During a 2-week period of\u00a0<\/span><span data-contrast=\"auto\">business re<\/span><span data-contrast=\"auto\">&#8211;<\/span><span data-contrast=\"auto\">open<\/span><span data-contrast=\"auto\">ing<\/span><span data-contrast=\"auto\">\u00a0in mid-May following an extended statewide lockdown<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">in Chittenden County, Vermont<\/span><span data-contrast=\"auto\">, observed face mask use at eight different business types was 76% overall, with higher mask use among females compared to males (<\/span><span data-contrast=\"auto\">8<\/span><span data-contrast=\"auto\">4% vs.\u00a0<\/span><span data-contrast=\"auto\">6<\/span><span data-contrast=\"auto\">8%). Older people (&gt;60 years old) were most likely to wear a mask (91%) and children (\u226414 years old) were the least likely (53%).<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">This survey reported by\u00a0<\/span><span data-contrast=\"auto\">Beckage et al.\u00a0<\/span><span data-contrast=\"auto\">monitored the entrances to eight different business types from a distance and visually assessed a cohort of 1<\/span><span data-contrast=\"auto\">,<\/span><span data-contrast=\"auto\">004 individuals<\/span><span data-contrast=\"auto\">\u00a0are recorded face mask use and estimated<\/span><span data-contrast=\"auto\">\u00a0age<\/span><span data-contrast=\"auto\">\u00a0and apparent<\/span><span data-contrast=\"auto\">\u00a0gender.<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Beckage et al. (July 25, 2020). Prevalence of Mask Wearing in Northern Vermont in Response to SARS-CoV-2. Pre-print downloaded July 27 from<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><a href=\"https:\/\/doi.org\/10.1101\/2020.07.23.20158980\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.23.20158980<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8545\" class=\"su-post\">\n<h5 class=\"su-post-title\">Comparison of Face-Touching Behaviors Before and During the Coronavirus Disease 2019 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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">Face mask-wearing and face-touching behaviors in the general population were analyzed using videos recorded in public areas in several countries before the COVID-19 pandemic (January 2018 to October 2019, n=4,699 individuals) and during the pandemic (February 2020 to March 2020, n=2,887 individuals). A significant increase in mask wearing was observed at locations in mainland China (from 1% to 99%), Japan (from 1% to 99%), South Korea (from 1% to 86%), and Western Europe (from 0.2% to 2%). Videos from the US showed a non-significant increase from 0.4% (1\/269) to 2% (4\/194) (p=0.17). Regression modeling showed that mask wearing was associated with a\u00a0<\/span><span data-contrast=\"auto\">reduction in face touching, which may prevent contact transmission of COVID-19 among the general population in public areas.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Chen et al. (July 29, 2020). Comparison of Face-Touching Behaviors Before and During the Coronavirus Disease 2019 Pandemic. JAMA Network Open.\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.16924\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.16924<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8543\" class=\"su-post\">\n<h5 class=\"su-post-title\">Association Between Statewide School Closure and COVID-19 Incidence and Mortality in the US<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">Auger, et al<\/span><span data-contrast=\"auto\">. conduc<\/span><span data-contrast=\"auto\">ted<\/span><span data-contrast=\"auto\">\u00a0a time<\/span><span data-contrast=\"auto\">\u00a0series analysis<\/span><span data-contrast=\"auto\">\u00a0for<\/span><span data-contrast=\"auto\">\u00a0all 50 US states and found that school closures were temporally associated with\u00a0<\/span><span data-contrast=\"auto\">declines in\u00a0<\/span><span data-contrast=\"auto\">COVID-19 incidence (adjusted relative change per week, -62%<\/span><span data-contrast=\"auto\">\u00a0[<\/span><span data-contrast=\"auto\">95% CI, -71% to -49%]<\/span><span data-contrast=\"auto\">)<\/span><span data-contrast=\"auto\">\u00a0and\u00a0<\/span><span data-contrast=\"auto\">mortality<\/span><span data-contrast=\"auto\">\u00a0(adjusted relative<\/span><span data-contrast=\"auto\">\u00a0change per week<\/span><span data-contrast=\"auto\">,<\/span><span data-contrast=\"auto\">\u00a0-58%<\/span><span data-contrast=\"auto\">\u00a0[<\/span><span data-contrast=\"auto\">95% CI, -68%<\/span><span data-contrast=\"auto\">\u00a0to -46%<\/span><span data-contrast=\"auto\">]<\/span><span data-contrast=\"auto\">)<\/span><span data-contrast=\"auto\">\u00a0during March 9<\/span><span data-contrast=\"auto\">-May 7, 2020.\u00a0<\/span><span data-contrast=\"auto\">S<\/span><span data-contrast=\"auto\">tates in the lowest quartile of COVID-19\u00a0<\/span><span data-contrast=\"auto\">cumulative\u00a0<\/span><span data-contrast=\"auto\">incidence at the time of\u00a0<\/span><span data-contrast=\"auto\">school closure had<\/span><span data-contrast=\"auto\">\u00a0the\u00a0<\/span><span data-contrast=\"auto\">largest<\/span><span data-contrast=\"auto\">\u00a0relative chan<\/span><span data-contrast=\"auto\">g<\/span><span data-contrast=\"auto\">e in incidence (<\/span><span data-contrast=\"auto\">-72<\/span><span data-contrast=\"auto\">%,\u00a0<\/span><span data-contrast=\"auto\">[<\/span><span data-contrast=\"auto\">95%<\/span><span data-contrast=\"auto\">\u00a0CI, &#8211;<\/span><span data-contrast=\"auto\">79% to -62%<\/span><span data-contrast=\"auto\">])<\/span><span data-contrast=\"auto\">\u00a0versus<\/span><span data-contrast=\"auto\">\u00a0states in the highest quartile<\/span><span data-contrast=\"auto\">\u00a0(-49%<\/span><span data-contrast=\"auto\">, [95% CI<\/span><span data-contrast=\"auto\">, -62%<\/span><span data-contrast=\"auto\">\u00a0to -33%<\/span><span data-contrast=\"auto\">]).\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">The authors acknowledge that some of the observed declines may have been due to other non-pharmaceutical interventions implemented concurrently with school closures.\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Auger et al. (July 29, 2020). Association Between Statewide School Closure and COVID-19 Incidence and Mortality in the US. JAMA.\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1001\/jama.2020.14348\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1001\/jama.2020.14348<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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 class=\"TextRun SCXW173333515 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW173333515 BCX0\" data-ccp-parastyle=\"heading 2\">Testing and Treatment<\/span><\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-8549\" class=\"su-post\">\n<h5 class=\"su-post-title\">Understanding the Patterns of Repeated Testing for COVID-19 Association with Patient Characteristics and Outcomes<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Among 15,920 individuals presenting to Michigan Medicine for COVID-19 testing between March 10 and June 4, 2020, most (85%) only tested once and never test<\/span><span data-contrast=\"auto\">ed<\/span><span data-contrast=\"auto\">\u00a0positive (9<\/span><span data-contrast=\"auto\">3<\/span><span data-contrast=\"auto\">%). A subse<\/span><span data-contrast=\"auto\">t of\u00a0<\/span><span data-contrast=\"auto\">1<\/span><span data-contrast=\"auto\">5<\/span><span data-contrast=\"auto\">% underwent multiple test<\/span><span data-contrast=\"auto\">s<\/span><span data-contrast=\"auto\">\u00a0(average 2.6 tests per person).\u00a0<\/span><span data-contrast=\"auto\">Non-Hispanic\u00a0<\/span><span data-contrast=\"auto\">B<\/span><span data-contrast=\"auto\">lack<\/span><span data-contrast=\"auto\">\u00a0people<\/span><span data-contrast=\"auto\">\u00a0were more likely to have additional testing than non-Hispanic white<\/span><span data-contrast=\"auto\">\u00a0people<\/span><span data-contrast=\"auto\">\u00a0(OR<\/span><span data-contrast=\"auto\">=<\/span><span data-contrast=\"auto\">1.21).\u00a0<\/span><span data-contrast=\"auto\">Women<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">were less likely\u00a0<\/span><span data-contrast=\"auto\">than men\u00a0<\/span><span data-contrast=\"auto\">to have additional testing (OR<\/span><span data-contrast=\"auto\">=<\/span><span data-contrast=\"auto\">0.86).<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Among 1<\/span><span data-contrast=\"auto\">,<\/span><span data-contrast=\"auto\">167 patients with at least one positive result, hospitalization (<\/span><span data-contrast=\"auto\">a<\/span><span data-contrast=\"auto\">OR<\/span><span data-contrast=\"auto\">=<\/span><span data-contrast=\"auto\">7.44) and ICU-level care (<\/span><span data-contrast=\"auto\">a<\/span><span data-contrast=\"auto\">OR<\/span><span data-contrast=\"auto\">=<\/span><span data-contrast=\"auto\">6.97) were significantly associated with repeated testing.\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Salerno et al. (July 29, 2020). Understanding the Patterns of Repeated Testing for COVID-19 Association with Patient Characteristics and Outcomes. Pre-print\u00a0downloaded July 29 from\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.07.26.20162453\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.26.20162453<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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 class=\"TextRun SCXW173333515 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW173333515 BCX0\" data-ccp-parastyle=\"heading 2\">Vaccines<\/span><\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-8551\" class=\"su-post\">\n<h5 class=\"su-post-title\">Evaluation of the MRNA-1273 Vaccine against SARS-CoV-2 in Nonhuman Primates<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">Corbett et al.<\/span><span data-contrast=\"auto\">\u00a0report that vaccination of\u00a0<\/span><span data-contrast=\"auto\">Indian-origin rhesus macaques with mRNA-1273,<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">a vaccine candidate encoding the prefusion-stabilized spike protein of SARS-CoV-2, induced robust antibody and T-cell responses before challenge with SARS-CoV-2<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">in upper- and lower-airway. Following exposure of the animals to infectious doses of SARS-CoV-2 there was indication of rapid protection from infection and no pathologic changes in the lungs of the animals.\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Corbett et al. (July 28, 2020). Evaluation of the MRNA-1273 Vaccine against SARS-CoV-2 in Nonhuman Primates. New England Journal of Medicine.\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1056\/NEJMoa2024671\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1056\/NEJMoa2024671<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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 class=\"TextRun SCXW22351167 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW22351167 BCX0\" data-ccp-parastyle=\"heading 2\">Clinical Characteristics<\/span><\/span><span class=\"TextRun SCXW22351167 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW22351167 BCX0\" data-ccp-parastyle=\"heading 2\"> and Health Care Setting<\/span><\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-8561\" class=\"su-post\">\n<h5 class=\"su-post-title\">Relationship Between Serum SARS-CoV-2 Nucleic Acid\u00a0(RNAemia) and Organ Damage in COVID-19 Patients: A 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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">Among a cohort of 85 COVID-19 patients hospitalized with laboratory-confirmed COVID-19<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">in Wuhan, China, 32 had SARS-CoV-2\u00a0<\/span><span data-contrast=\"auto\">RNA detected in serum<\/span><span data-contrast=\"auto\">\u00a0(RNAemia). Compared to patients without\u00a0RNAemia, patients with\u00a0RNAemia\u00a0had\u00a0<\/span><span data-contrast=\"auto\">a\u00a0<\/span><span data-contrast=\"auto\">higher rate of organ damage (18\/32 [56%] vs. 5\/53 [9%], p&lt;0.001), higher mortality (10\/32 [31%] vs. 3\/53 [<\/span><span data-contrast=\"auto\">6<\/span><span data-contrast=\"auto\">%], p=0.004), ,\u00a0and a variety of abnormal CT and laboratory biomarkers.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Xu et al. (July 28, 2020). Relationship Between Serum SARS-CoV-2 Nucleic Acid<\/span><\/i><i><span data-contrast=\"none\">\u00a0<\/span><\/i><i><span data-contrast=\"none\">(RNAemia) and Organ Damage in COVID-19 Patients: A Cohort Study. Clinical Infectious Diseases.\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1093\/cid\/ciaa1085\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1093\/cid\/ciaa1085<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8559\" class=\"su-post\">\n<h5 class=\"su-post-title\">ACE2 Expression Is Elevated in Airway Epithelial Cells from Aged and Male Donors but Reduced in Asthma<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Wark et al.\u00a0<\/span><span data-contrast=\"auto\">examined risk factors associated with ACE2 expression in 145 patients with asthma and chronic obstructive pulmonary disease (COPD) in Australia. They found\u00a0<\/span><span data-contrast=\"auto\">that\u00a0<\/span><span data-contrast=\"auto\">older age and male sex\u00a0<\/span><span data-contrast=\"auto\">were\u00a0<\/span><span data-contrast=\"auto\">associated with<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">increased ACE2 expression, and asthma was associated with reduced expression.\u00a0<\/span><span data-contrast=\"auto\">The authors\u00a0<\/span><span data-contrast=\"auto\">concluded that a<\/span><span data-contrast=\"auto\">ltered ACE2 expression in the lower airway may be an important factor in\u00a0<\/span><span data-contrast=\"auto\">SARS-CoV-2\u00a0<\/span><span data-contrast=\"auto\">virus tropism and may<\/span><span data-contrast=\"auto\">,<\/span><span data-contrast=\"auto\">\u00a0in part<\/span><span data-contrast=\"auto\">,<\/span><span data-contrast=\"auto\">\u00a0explain why\u00a0<\/span><span data-contrast=\"auto\">patients with\u00a0<\/span><span data-contrast=\"auto\">asthma\u00a0<\/span><span data-contrast=\"auto\">do not appear to be\u00a0<\/span><span data-contrast=\"auto\">overrepresented in those with COVID-19 complications.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Wark et al. (July 29, 2020). ACE2 Expression Is Elevated in Airway Epithelial Cells from Aged and Male Donors but Reduced in Asthma. Pre-print\u00a0downloaded July 29 from\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.07.26.20162248\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.26.20162248<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8557\" class=\"su-post\">\n<h5 class=\"su-post-title\">Baseline Cardiometabolic Profiles and SARS-CoV-2 Risk in the UK Biobank<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Scalsky\u00a0et al.\u00a0<\/span><span data-contrast=\"auto\">examined the effect of\u00a0<\/span><span data-contrast=\"auto\">c<\/span><span data-contrast=\"auto\">ardiometabolic\u00a0<\/span><span data-contrast=\"auto\">p<\/span><span data-contrast=\"auto\">rofiles\u00a0<\/span><span data-contrast=\"auto\">on the risk of testing positive for SARS-Co<\/span><span data-contrast=\"auto\">V<\/span><span data-contrast=\"auto\">-2 among 9,005 UK<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">B<\/span><span data-contrast=\"auto\">iobank<\/span><span data-contrast=\"auto\">\u00a0participants. They found that elevated\u00a0high density\u00a0lipoprotein (HDL) was associated with reduced risk of testing positive for SARS-CoV-2 (<\/span><span data-contrast=\"auto\">a<\/span><span data-contrast=\"auto\">OR=0.85). Type II diabetes and HbA1c were associated with increased risk (OR=1.21 and 1.06), but the effects\u00a0<\/span><span data-contrast=\"auto\">disappeared after<\/span><span data-contrast=\"auto\">\u00a0controlling for HDL.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Scalsky\u00a0et al. (July 29, 2020). Baseline Cardiometabolic Profiles and SARS-CoV-2 Risk in the UK Biobank. Pre-print\u00a0downloaded July 29 from\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.07.25.20161091\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.25.20161091<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8555\" class=\"su-post\">\n<h5 class=\"su-post-title\">30-Day Mortality and Morbidity in COVID-19 versus Influenza A Population-based 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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">In an analysis u<\/span><span data-contrast=\"auto\">sing<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">population-based\u00a0<\/span><span data-contrast=\"auto\">data from Denmark (November 1, 2017 to June 30, 2020),\u00a0<\/span><span data-contrast=\"auto\">among in<\/span><span data-contrast=\"auto\">patients<\/span><span data-contrast=\"auto\">, those\u00a0<\/span><span data-contrast=\"auto\">who\u00a0<\/span><span data-contrast=\"auto\">tested positive for SARS-CoV-2 (<\/span><span data-contrast=\"auto\">n=<\/span><span data-contrast=\"auto\">1<\/span><span data-contrast=\"auto\">,<\/span><span data-contrast=\"auto\">657<\/span><span data-contrast=\"auto\">)\u00a0<\/span><span data-contrast=\"auto\">had a 30-day mortality of 21% compared to 7% among those who tested positive for influenza (n=7,200). Among outpatients, the 30-day mortality was 2% among those positive for SARS-CoV-2\u00a0<\/span><span data-contrast=\"auto\">(n=6,263)\u00a0<\/span><span data-contrast=\"auto\">and 0.4% among those positive for<\/span><span data-contrast=\"auto\">\u00a0influenza<\/span><span data-contrast=\"auto\">\u00a0(n=7,204)<\/span><span data-contrast=\"auto\">.\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Nersesjan\u00a0et al. (July 28, 2020). 30-Day Mortality and Morbidity in COVID-19 versus Influenza A Population<\/span><\/i><i><span data-contrast=\"none\">&#8211;<\/span><\/i><i><span data-contrast=\"none\">based Study. Pre-print\u00a0downloaded July 29 from\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.07.25.20162156\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.25.20162156<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8553\" class=\"su-post\">\n<h5 class=\"su-post-title\">High Prevalence of SARS-CoV-2 and Influenza A Virus (H1N1) Co-Infection in Dead Patients in Northeastern Iran<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">Co-infection with influenza A virus was found in 22% of a sample of patients in Iran who died and had SARS-CoV-2 infection confirmed by RT-PCR (n=1,444). The contribution of these co-infections\u00a0<\/span><span data-contrast=\"auto\">to disease pathology is unclear from these results, but the authors note that such high rates of co-infection could make diagnostics more complicated<\/span><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Hashemi et al. (July 28, 2020). High Prevalence of SARS-CoV-2 and Influenza A Virus (H1N1) Co-Infection in Dead Patients in Northeastern Iran. Journal of Medical Virology.\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1002\/jmv.26364\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1002\/jmv.26364<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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 class=\"TextRun SCXW82890009 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW82890009 BCX0\" data-ccp-parastyle=\"heading 2\">Mode<\/span><\/span><span class=\"TextRun SCXW82890009 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW82890009 BCX0\" data-ccp-parastyle=\"heading 2\">ling and Prediction<\/span><\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-8563\" class=\"su-post\">\n<h5 class=\"su-post-title\">Threshold Analyses on Rates of Testing Transmission and Contact for COVID-19 Control in a University Setting<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Zhao et al.\u00a0<\/span><span data-contrast=\"auto\">simulated epidemic projections of a potential COVID-19 outbreak in a university population of 38,000 persons. They estimated that\u00a0<\/span><span data-contrast=\"auto\">the threshold number of contacts per person per day was 10 to prevent excess deaths<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">in a scenario with\u00a0<\/span><span data-contrast=\"auto\">a maximum capacity of trace and test\u00a0<\/span><span data-contrast=\"auto\">of\u00a0<\/span><span data-contrast=\"auto\">50%<\/span><span data-contrast=\"auto\">\u00a0and a 5.4%<\/span><span data-contrast=\"auto\">\u00a0chance of\u00a0<\/span><span data-contrast=\"auto\">transmission<\/span><span data-contrast=\"auto\">\u00a0rate<\/span><span data-contrast=\"auto\">\u00a0per contact per day.\u00a0<\/span><span data-contrast=\"auto\">Further reducing the number of daily<\/span><span data-contrast=\"auto\">\u00a0contacts to\u00a0<\/span><span data-contrast=\"auto\">4 or\u00a0<\/span><span data-contrast=\"auto\">fewer\u00a0<\/span><span data-contrast=\"auto\">allowed<\/span><span data-contrast=\"auto\">\u00a0for\u00a0<\/span><span data-contrast=\"auto\">up to<\/span><span data-contrast=\"auto\">\u00a0a\u00a0<\/span><span data-contrast=\"auto\">6-day\u00a0<\/span><span data-contrast=\"auto\">delay from the time of infection to diagnosis and isolation<\/span><span data-contrast=\"auto\">\u00a0without loss of epidemic control<\/span><span data-contrast=\"auto\">.\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">The authors\u00a0<\/span><span data-contrast=\"auto\">suggest\u00a0<\/span><span data-contrast=\"auto\">that these threshold estimates may help develop on-campus scheduling and indoor-spacing plans in conjunction with plans for asymptomatic testing for COVID-19.\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Zhao et al. (July 25, 2020). Threshold Analyses on Rates of Testing Transmission and Contact for COVID-19 Control in a University Setting. Pre-print downloaded July 27 from\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.07.21.20158303\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.21.20158303<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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 class=\"TextRun SCXW256833614 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW256833614 BCX0\" data-ccp-parastyle=\"heading 2\">Public Health Policy and Practice<\/span><\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-8567\" class=\"su-post\">\n<h5 class=\"su-post-title\">Magnitude Demographics and Dynamics of the Impact of the First Phase of the Covid-19 Pandemic on All-Cause Mortality in 17\u00a0Industrialised\u00a0Countries<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><i><span data-contrast=\"none\">[pre-print, not peer-reviewed]<\/span><\/i><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Kontis\u00a0et al.\u00a0<\/span><span data-contrast=\"auto\">modeled the impacts of the first phase of the COVID-19 pandemic on all-cause mortality for 17 industrialized countries. From mid-February through the end of May 2020, an estimated 202,900 (95%CI 179,400-224,900) more people died in these 17 countries than\u00a0<\/span><span data-contrast=\"auto\">were<\/span><span data-contrast=\"auto\">\u00a0expecte<\/span><span data-contrast=\"auto\">d had<\/span><span data-contrast=\"auto\">\u00a0the pandemic not\u00a0<\/span><span data-contrast=\"auto\">occurred<\/span><span data-contrast=\"auto\">. After accounting for population size, England and Wales and Spain experienced the largest relative increase in deaths<\/span><span data-contrast=\"auto\">,\u00a0<\/span><span data-contrast=\"auto\">with<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">37%\u00a0<\/span><span data-contrast=\"auto\">(<\/span><span data-contrast=\"auto\">95%CI 30-44<\/span><span data-contrast=\"auto\">)<\/span><span data-contrast=\"auto\">\u00a0in England and Wales<\/span><span data-contrast=\"auto\">\u00a0and<\/span><span data-contrast=\"auto\">\u00a038%\u00a0<\/span><span data-contrast=\"auto\">(<\/span><span data-contrast=\"auto\">95%CI 31-44<\/span><span data-contrast=\"auto\">)<\/span><span data-contrast=\"auto\">\u00a0in Spain).\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Kontis\u00a0et al. (July 28, 2020). Magnitude Demographics and Dynamics of the Impact of the First Phase of the Covid-19 Pandemic on All-Cause Mortality in 17\u00a0Industrialised\u00a0Countries. Pre-print\u00a0downloaded July 29 from\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1101\/2020.07.26.20161570\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1101\/2020.07.26.20161570<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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-8565\" class=\"su-post\">\n<h5 class=\"su-post-title\">Comparison of Weighted and Unweighted Population Data to Assess Inequities in Coronavirus Disease 2019 Deaths by Race\/Ethnicity Reported by the US Centers for Disease Control and Prevention<\/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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">Cowger et al.<\/span><span data-contrast=\"auto\">\u00a0compared\u00a0<\/span><span data-contrast=\"auto\">the percentage distribution\u00a0<\/span><span data-contrast=\"auto\">of COVID-19 deaths<\/span><span data-contrast=\"auto\">\u00a0in the US\u00a0<\/span><span data-contrast=\"auto\">by race\/ethnicity between\u00a0<\/span><span data-contrast=\"auto\">the\u00a0<\/span><span data-contrast=\"auto\">CDC<\/span><span data-contrast=\"auto\">\u2019s\u00a0<\/span><span data-contrast=\"auto\">N<\/span><span data-contrast=\"auto\">ational\u00a0<\/span><span data-contrast=\"auto\">C<\/span><span data-contrast=\"auto\">enter for\u00a0<\/span><span data-contrast=\"auto\">H<\/span><span data-contrast=\"auto\">ealth\u00a0<\/span><span data-contrast=\"auto\">S<\/span><span data-contrast=\"auto\">tatistics<\/span><span data-contrast=\"auto\">\u2013weighted population and\u00a0<\/span><span data-contrast=\"auto\">the<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">unweighted\u00a0<\/span><span data-contrast=\"auto\">US Census population\u00a0<\/span><span data-contrast=\"auto\">and found that\u00a0<\/span><span data-contrast=\"auto\">the\u00a0<\/span><span data-contrast=\"auto\">weighting approach<\/span><span data-contrast=\"auto\">\u00a0affects\u00a0<\/span><span data-contrast=\"auto\">the\u00a0<\/span><span data-contrast=\"auto\">relative\u00a0<\/span><span data-contrast=\"auto\">mortality burden by race\/ethnicity<\/span><span data-contrast=\"auto\">.<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">In an analysis using<\/span><span data-contrast=\"auto\">\u00a0the unweighted US Census data, Black individuals were the most overrepresented among COVID-19 deaths, accounting for an excess in absolute COVID-19 mortality of\u00a0<\/span><span data-contrast=\"auto\">10<\/span><span data-contrast=\"auto\">%, whereas\u00a0<\/span><span data-contrast=\"auto\">w<\/span><span data-contrast=\"auto\">hite\u00a0<\/span><span data-contrast=\"auto\">individuals were underrepresented (\u22128%). In contrast,\u00a0<\/span><span data-contrast=\"auto\">an analysis<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">with the CDC weighted data\u00a0<\/span><span data-contrast=\"auto\">show<\/span><span data-contrast=\"auto\">ed<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">that w<\/span><span data-contrast=\"auto\">hite individuals\u00a0<\/span><span data-contrast=\"auto\">were<\/span><span data-contrast=\"auto\">\u00a0most overrepresented (1<\/span><span data-contrast=\"auto\">1<\/span><span data-contrast=\"auto\">%)<\/span><span data-contrast=\"auto\">\u00a0and\u00a0<\/span><span data-contrast=\"auto\">Black individuals were less overrepresented (4%).\u00a0<\/span><span data-contrast=\"auto\">The different approaches also\u00a0<\/span><span data-contrast=\"auto\">yielded<\/span><span data-contrast=\"auto\">\u00a0d<\/span><span data-contrast=\"auto\">iscrepancies among Latinx (\u2212<\/span><span data-contrast=\"auto\">2<\/span><span data-contrast=\"auto\">% vs \u221210%) and Asian (0.1% vs \u2212<\/span><span data-contrast=\"auto\">6<\/span><span data-contrast=\"auto\">%) individuals.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"34\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><span data-contrast=\"auto\">The authors urged the CDC to publish data stratified by age, gender, education, and ZIP code characteristics instead of geographical distribution of racial groups to provide unbiased estimates of racial\/ethnic\u00a0<\/span><span data-contrast=\"auto\">disparities<\/span><span data-contrast=\"auto\">.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span data-contrast=\"none\">Cowger et al. (July 28, 2020). Comparison of Weighted and Unweighted Population Data to Assess Inequities in Coronavirus Disease 2019 Deaths by Race\/Ethnicity Reported by the US Centers for Disease Control and Prevention. JAMA Network Open.\u00a0<\/span><\/i><a href=\"https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.16933\"><span data-contrast=\"none\">https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.16933<\/span><\/a><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559685&quot;:720,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\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 data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"32\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><a href=\"https:\/\/doi.org\/10.1056\/NEJMms2024920\"><span data-contrast=\"none\">Reopening Primary Schools during the Pandemic<\/span><\/a><span data-contrast=\"auto\">\u00a0\u2013 New England Journal of Medicine (July 29)\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"32\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><a href=\"https:\/\/doi.org\/10.1016\/S2666-5247(20)30100-2\"><span data-contrast=\"none\">The Challenges of Informative Wastewater Sampling for SARS-CoV-2 Must Be Met: Lessons from Polio Eradication<\/span><\/a><span data-contrast=\"auto\">\u00a0\u2013 The Lancet Microbe (July 28)\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"32\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><a href=\"https:\/\/doi.org\/10.1177\/0194599820947667\"><span data-contrast=\"none\">Telemedicine in Minority and Socioeconomically Disadvantaged Communities Amidst COVID-19 Pandemic<\/span><\/a><span data-contrast=\"auto\">\u00a0\u2013 Otolaryngology (July 28)\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"32\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><a href=\"https:\/\/doi.org\/10.1001\/jama.2020.12646\"><span data-contrast=\"none\">NIH Launches Platform to Serve as Depository for COVID-19 Medical Data<\/span><\/a><span data-contrast=\"auto\">\u00a0\u2013 JAMA (July 28)\u00a0<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"32\" data-aria-posinset=\"2019\" data-aria-level=\"1\"><a href=\"https:\/\/doi.org\/10.1101\/2020.07.23.20160887\"><span data-contrast=\"none\">Divide in Vaccine Belief in COVID-19 Conversations Implications for Immunization Plans<\/span><\/a><span data-contrast=\"auto\">\u00a0\u2013\u00a0<\/span><span data-contrast=\"auto\">medRxiv<\/span><span data-contrast=\"auto\">\u00a0(July 29)<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>School closures were associated in time with declines in COVID-19 incidence (-62%) and mortality (-58%) across US states, although at least some of the effect may have been due to other non-pharmaceutical interventions implemented concurrently. <\/p>\n<div><a class=\"more\" href=\"https:\/\/depts.washington.edu\/pandemicalliance\/2020\/07\/29\/comparison-of-weighted-and-unweighted-population-data-to-assess-inequities-in-coronavirus-disease-2019-deaths-by-race-ethnicity-reported-by-the-us-centers-for-disease-control-and-prevention\/\">Read more<\/a><\/div>\n","protected":false},"author":8,"featured_media":6193,"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-8541","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\/8541","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=8541"}],"version-history":[{"count":1,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/8541\/revisions"}],"predecessor-version":[{"id":8569,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/8541\/revisions\/8569"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/media\/6193"}],"wp:attachment":[{"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/media?parent=8541"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/categories?post=8541"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/tags?post=8541"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/topic?post=8541"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}