{"id":4031,"date":"2020-02-05T14:47:13","date_gmt":"2020-02-05T22:47:13","guid":{"rendered":"https:\/\/depts.washington.edu\/pandemicalliance\/?p=4031"},"modified":"2021-02-22T11:55:13","modified_gmt":"2021-02-22T19:55:13","slug":"covid-19-literature-situation-report-february-5-2020","status":"publish","type":"post","link":"https:\/\/depts.washington.edu\/pandemicalliance\/2020\/02\/05\/covid-19-literature-situation-report-february-5-2020\/","title":{"rendered":"COVID-19 Literature Situation Report February 5, 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>Researchers continue to conclude that bats are the most likely evolutionary predecessor to 2019-nCoV, though there remains no agreement on precisely how the jump may have occurred.<\/b><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400\"><b>Ongoing reports support that older age and co-morbid conditions (e.g., cardiovascular disease, diabetes) are risks for 2019-nCoV mortality.<\/b><\/li>\n<li style=\"font-weight: 400\"><b>The term \u201cpandemic\u201d is not being used by CDC, and is being specifically not-used by WHO.<\/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\">Modeling and Prediction<\/span><\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-4034\" class=\"su-post\">\n<h5 class=\"su-post-title\">Using predicted imports of 2019-nCoV cases to determine locations that may not be identifying all imported cases<\/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\">DeSalazar, <\/span><i><span style=\"font-weight: 400\">et al.<\/span><\/i><span style=\"font-weight: 400\"> use air travel volume estimates out of Wuhan to identify countries that may have undetected cases. Their primary findings indicate the Indonesia likely has undetected cases; and that Cambodia and Thailand may have an undercount of cases. Improved public health surveillance is recommended for these countries.\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">DeSalazar, et al. (Feb 5, 2020). Using predicted imports of 2019-nCoV cases to determine locations that may not be identifying all imported cases. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.medrxiv.org\/content\/10.1101\/2020.02.04.20020495v1\"><span style=\"font-weight: 400\">https:\/\/www.medrxiv.org\/content\/10.1101\/2020.02.04.20020495v1<\/span><\/a><i><span style=\"font-weight: 400\">\u00a0\u00a0<\/span><\/i><\/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-4032\" class=\"su-post\">\n<h5 class=\"su-post-title\">Risk assessment of novel coronavirus 2019-nCoV outbreaks outside 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\">Boldog, et al. model the risk for 2019-nCoV outbreaks outside China by developing local reproduction numbers (R<\/span><span style=\"font-weight: 400\">loc<\/span><span style=\"font-weight: 400\">) that incorporate factors affecting epidemiology in China and new locations, and their connectivity.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Countries should balance controlling spread after introduction with preventing introduction. Countries with a low ability to control spread should focus on travel restrictions and traveler screening; whereas those better able, should focus on internal control activities. (Those in between should balance both.)<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Boldog P, et al. (Feb 5, 2020). Risk assessment of novel coronavirus 2019-nCoV outbreaks outside China. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.medrxiv.org\/content\/10.1101\/2020.02.04.20020503v1\"><span style=\"font-weight: 400\">https:\/\/www.medrxiv.org\/content\/10.1101\/2020.02.04.20020503v1<\/span><\/a><i><span style=\"font-weight: 400\">\u00a0<\/span><\/i><\/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\">Virology<\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-4042\" class=\"su-post\">\n<h5 class=\"su-post-title\">Machine learning-based analysis of genomes suggests associations between Wuhan 2019-nCoV and bat Betacoronaviruses<\/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\">Randhawa, <\/span><i><span style=\"font-weight: 400\">et al.<\/span><\/i><span style=\"font-weight: 400\"> use a machine-learning approach to confirm classification of 2019-nCoV as a <\/span><i><span style=\"font-weight: 400\">Betacoronavirus<\/span><\/i><span style=\"font-weight: 400\">, subgenus <\/span><i><span style=\"font-weight: 400\">Sarbecovirus<\/span><\/i><span style=\"font-weight: 400\">, of bat origin<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Randhawa, et al. (Feb 4, 2020). Machine learning-based analysis of genomes suggests <\/span><\/i><i><span style=\"font-weight: 400\">associations between Wuhan 2019-nCoV and bat Betacoronaviruses. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.03.932350v1\"><span style=\"font-weight: 400\">https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.03.932350v1<\/span><\/a><i><span style=\"font-weight: 400\">\u00a0 <\/span><\/i><\/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-4040\" class=\"su-post\">\n<h5 class=\"su-post-title\">Genomic variance of the 2019-nCoV coronavirus<\/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 phylogenetic analysis including 2019-nCoV, SARS-CoV and bat CoVs found evidence of the evolutionary link between bat and bat\/SARS-CoV-like viruses and 2019-nCoV, with bat\/Yunnan\/RaTG13\/2013 as a potential most-recent ancestor. Additional epitope identification is also presented.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Ramaiah A and Arumugaswami V (Jan 30, 2020). Genomic variance of the 2019-nCoV coronavirus. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2020.01.29.925867v2\"><span style=\"font-weight: 400\">https:\/\/www.biorxiv.org\/content\/10.1101\/2020.01.29.925867v2<\/span><\/a><i><span style=\"font-weight: 400\">\u00a0<\/span><\/i><\/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-4038\" class=\"su-post\">\n<h5 class=\"su-post-title\">Genomic variance of the 2019-nCoV coronavirus<\/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\">Ceraolo and Giorgi construct an expansive phylogenetic tree of representative <\/span><i><span style=\"font-weight: 400\">coronaviridae<\/span><\/i><span style=\"font-weight: 400\">. They confirm a &gt;99% match among sequenced 2019-nCov isolates; and a 96.2% match between 2019-nCoV and the most closely-related bat coronavirus. While 2019-nCoV sequences were fairly homogenous, at least two hyper-variable genomic areas were identified (ORF 1ab, silent; ORF8, serine\/leucine variation).<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">They also assessed protein homology, finding again considerable similarity between 2019-nCoV and one of the bat CoVs. Envelope, membrane, and nucleocapsid proteins were generally highly conserved.\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Ceraolo C and Giorgi FM (Feb 4, 2020). Genomic variance of the 2019-nCoV coronavirus. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.02.931162v2\"><span style=\"font-weight: 400\">https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.02.931162v2<\/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-4036\" class=\"su-post\">\n<h5 class=\"su-post-title\">Preliminary identification of potential vaccine targets for 2019-nCoV based on SARS-CoV immunological studies<\/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\">Using previously described similarities between 2019-nCoV and SARS-CoV, Ahmed, et al. used SARS-CoV-derived experimentally-determined B- and T-cell epitope data to find epitopes in the S and N structural proteins of 2019-nCoV that were identical between the two viruses.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Epitopes are parts of the virus \u201cseen\u201d by the immune system. By finding comparable sites across the two viruses, the researchers were hoping to leverage what is known about SARS-CoV immunogenicity to identify potential vaccine antigen candidates\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">They found several sites where SARS-CoV epitopes mapped to 2019-nCoV proteins. The areas of the genes for the 2019-nCoV epitopes appeared stable (i.e., no reported mutations to date), making them good vaccine antigen candidates.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Also, based on population coverage criteria for the T-cell epitopes (i.e., considering MHC allele distribution in populations to assess the percentage of individuals within a population likely to elicit an immune response to at least one T cell epitope from the set), use of these epitopes as a vaccine target could provide population coverage of 84% (China) or 94% (global) coverage.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Ahmed SF, et al. (Feb 4, 2020). Preliminary identification of potential vaccine targets for <\/span><\/i><i><span style=\"font-weight: 400\">2019-nCoV based on SARS-CoV immunological studies. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.03.933226v1\"><span style=\"font-weight: 400\">https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.03.933226v1<\/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\">Clinical Characteristics and Care Seeking<\/h2>\n<div class=\"su-posts su-posts-default-loop\">\n<div id=\"su-post-4044\" class=\"su-post\">\n<h5 class=\"su-post-title\">Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV 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;\">Liver function abnormalities have been observed in some 2019-nCoV patients. Chai, et al. assess potential pathways for this damage given the presumed role ACE2 expression in 2019-nCoV infection.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">They found liver abnormalities of 2019-nCoV patients could involve cholangiocyte dysfunction more than hepatocyte damage. Drug induced and systemic inflammatory response may also have a role.\u00a0<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400;\">Chai X, et al. (Feb 4, 2020). Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage <\/span><\/i><i><span style=\"font-weight: 400;\">After 2019-nCoV Infection. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><span style=\"font-weight: 400;\">https:\/\/www.biorxiv.org\/content\/10.1101\/2020.02.03.931766v1<\/span><i><span style=\"font-weight: 400;\">\u00a0<\/span><\/i><\/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-4048\" class=\"su-post\">\n<h5 class=\"su-post-title\">Baricitinib as potential treatment for 2019-nCoV acute respiratory disease<\/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\">Using BenevolentAI, knowledge of coronavirus receptors, and assumptions about vulnerable cell types, Richardson, <\/span><i><span style=\"font-weight: 400\">et al.<\/span><\/i><span style=\"font-weight: 400\"> assess AP2-associated protein kinase 1 (AAK1) inhibitors for potential 2019-nCoV therapeutic use. They identify baricitinib as a candidate for trials based on its plasma concentration at therapeutic doses.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Richardson, et al. (Feb 3, 2020). Baricitinib as potential treatment for 2019-nCoV acute <\/span><\/i><i><span style=\"font-weight: 400\">respiratory disease. The Lancet.<\/span><\/i> <a href=\"https:\/\/doi.org\/10.1016\/S0140-6736(20)30304-4\"><span style=\"font-weight: 400\">https:\/\/doi.org\/10.1016\/S0140-6736(20)30304-4<\/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-4046\" class=\"su-post\">\n<h5 class=\"su-post-title\">Machine intelligence design of 2019-nCoV drugs<\/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\">Gao, <\/span><i><span style=\"font-weight: 400\">et al.<\/span><\/i><span style=\"font-weight: 400\"> apply a generative network complex (GNC) machine intelligence approach to identify candidate protease inhibitors for treating 2019-nCoV, including an assessment of two HIV protease inhibitors.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">The GNC identifies 3-dimensional (3-D) drug candidates based on elements that include structure generation and property prediction algorithms. Molecule generation includes assessment of properties like binding affinity for known antigenic sites, solubility, similarity to know protease inhibitors, etc. Information on sequence identity and structural similarity between 2019-nCoV and SARS-CoV proteases was the basis of identifying candidates for an initial protease inhibitor dataset for the training set.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">15 anti-2019-nCov molecules were generated through the GNC process. A related assessment of the HIV protease inhibitors lopinavir (Aluvia) and ritonavir (Norvir) found them to have some potential (e.g., fit with target protease), but generally scored lower than other protease inhibitors identified.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Gao, et al. (Feb 4, 2020). Machine intelligence design of 2019-nCoV drugs. Pre-Print downloaded on 5 Feb, 2020 from, <\/span><\/i><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2020.01.30.927889v1\"><span style=\"font-weight: 400\">https:\/\/www.biorxiv.org\/content\/10.1101\/2020.01.30.927889v1<\/span><\/a><i><span style=\"font-weight: 400\">\u00a0<\/span><\/i><\/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<\/strong><\/h3>\n<p><strong><i>Need to get caught up? Today\u2019s MMWR and the Infectious Disease Society of America can help:<\/i><\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">In today\u2019s MMWR Early Release, Patel, <\/span><i><span style=\"font-weight: 400\">et al.<\/span><\/i><span style=\"font-weight: 400\"> summarize the epidemiology, response, clinical features, and clinical guidance for the US 2019-nCoV outbreak, from Dec 31 through Feb 4, 2020.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">After a brief review of current countermeasures, they describe the overall US public health response goals as slowing spread to provide time to better:<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Prepare health care systems and the general public [in the case of] widespread transmission\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Characterize 2019-nCoV infection to guide public health recommendations and medical countermeasures<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><i><span style=\"font-weight: 400\">General epidemiology of 2019-nCoV:<\/span><\/i><span style=\"font-weight: 400\"> No commitment regarding \u201cexact origin.\u201d Person-to-person transmission \u201cevident,\u201d but lack understanding of ease. Primary mode of transmission, respiratory droplet. Primary signs and symptoms, fever, cough, and shortness of breath. Incubation period of 2-14 days. Older adults and persons with underlying health conditions identified as high-risk for severe illness, though overall implications \u201cremain unclear.\u201d<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">A brief summary of the 11 US cases to date is provided (noting the nine travelers from Wuhan and the 2 household contacts)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">CDC and US Public Health Service activation is described, including coordination with WHO and a review of the US Quarantine Station locations and authorities. Entry screening in coordination with US Customs and Boarder Protection is on-going. Enhanced screening was added.<\/span>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">As of February 1, 2020, a total of 3,099 persons on 437 flights were screened; five symptomatic travelers were referred by CDC to local health care providers for further medical evaluation, and one of these persons tested positive for 2019-nCoV.<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Sharing of genomic information and the high-level overview of RT-PCR use is described, including permissions to use at CDC-qualified labs<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Current CDC guidance based on management and prevention of other respiratory illnesses including influenza, MERS, and SARS (pending further 2019-nCoV) is provided, with reference to the third Health Advisory with interim guidance for clinicians and public health practitioners. The travel history period cited is 14 days. Social distancing recommendation are also provided.<\/span><\/li>\n<\/ul>\n<p><i><span style=\"font-weight: 400\">Patel A, et al. Initial Public Health Response and Interim Clinical Guidance for the 2019 Novel Coronavirus Outbreak \u2014 United States, December 31, 2019\u2013February 4, 2020. MMWR 2020;69(Early release). Available from: <\/span><\/i><a href=\"https:\/\/www.cdc.gov\/mmwr\/volumes\/69\/wr\/mm6905e1.htm\"><span style=\"font-weight: 400\">https:\/\/www.cdc.gov\/mmwr\/volumes\/69\/wr\/mm6905e1.htm<\/span><\/a><i><span style=\"font-weight: 400\">\u00a0<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400\">From official sources summarized in ProMED Mail (IDSA), 1.) China reports that, among their fatal cases, 80% are over 60 years old and &gt;75% of have a co-morbid condition; 2.) WHO is not considering the 2019-nCoV epidemic a pandemic at this time, citing intensive global control activities. <\/span><i><span style=\"font-weight: 400\">\u00a0<\/span><\/i><\/p>\n<p><strong><i>Dashboards with updated maps and information on global case counts are available at,<\/i><\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">WHO:<\/span><a href=\"http:\/\/who.maps.arcgis.com\/apps\/opsdashboard\/index.html#\/c88e37cfc43b4ed3baf977d77e4a0667\"><span style=\"font-weight: 400\">http:\/\/who.maps.arcgis.com\/apps\/opsdashboard\/index.html#\/c88e37cfc43b4ed3baf977d77e4a0667<\/span><\/a><span style=\"font-weight: 400\">\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">JHU:<\/span><a href=\"https:\/\/gisanddata.maps.arcgis.com\/apps\/opsdashboard\/index.html#\/bda7594740fd40299423467b48e9ecf6\"><span style=\"font-weight: 400\">https:\/\/gisanddata.maps.arcgis.com\/apps\/opsdashboard\/index.html#\/bda7594740fd40299423467b48e9ecf6<\/span><\/a><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Harvard and Boston Children\u2019s Hospital: <\/span><a href=\"https:\/\/www.healthmap.org\/ncov2019\/\"><span style=\"font-weight: 400\">https:\/\/www.healthmap.org\/ncov2019\/<\/span><\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Researchers continue to conclude that bats are the most likely evolutionary predecessor to 2019-nCoV, though there remains no agreement on precisely how the jump may have occurred.<\/p>\n<div><a class=\"more\" href=\"https:\/\/depts.washington.edu\/pandemicalliance\/2020\/02\/05\/machine-intelligence-design-of-2019-ncov-drugs\/\">Read more<\/a><\/div>\n","protected":false},"author":8,"featured_media":1174,"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-4031","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\/4031","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=4031"}],"version-history":[{"count":4,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/4031\/revisions"}],"predecessor-version":[{"id":4492,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/posts\/4031\/revisions\/4492"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/media\/1174"}],"wp:attachment":[{"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/media?parent=4031"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/categories?post=4031"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/tags?post=4031"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/depts.washington.edu\/pandemicalliance\/wp-json\/wp\/v2\/topic?post=4031"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}