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10.1377/hlthaff.2020.00455 http://scihub22266oqcxt.onion/10.1377/hlthaff.2020.00455 32379502!ä!32379502 Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32379502&cmd=llinks): Failed to open stream: HTTP request failed! 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Estimating The Infection Fatality Rate Among Symptomatic COVID-19 Cases In The United States |pdf=|usr=}}{{32379502}} gab.com Text Estimating The Infection Fatality Rate Among Symptomatic COVID-19 Cases In The United States JO: Health Aff (Millwood) http://www.kidney.de/pget.php?&tw=1&pmid=32379502 #FOAvip Knowing the infection fatality rate (IFR) of novel coronavirus (SARS-CoV-2) infections is essential for the fight against the coronavirus disease (COVID-19) pandemic. Using data through April 20, 2020, I fit a statistical model to COVID-19 case fatality rates over time at the US county level to estimate the COVID-19 IFR among symptomatic cases (IFR-S) as time goes to infinity. The IFR-S in the US was estimated to be 1.3 percent. County-specific rates varied from 0.5 percent to 3.6 percent. The overall IFR for COVID-19 should be lower when I account for cases where patients are asymptomatic and recover without symptoms. When used with other estimating approaches, my model and estimates can help disease and policy modelers obtain more accurate predictions for the epidemiology of the disease and the impact of various policy levers to contain the pandemic. The model could also be used with future pandemics to get an early sense of the magnitude of symptomatic infection at the population level before other direct estimates are available. Substantial variation across patient demographics likely exists and should be the focus of future studies. Twit Text FOAVip Estimating The Infection Fatality Rate Among Symptomatic COVID-19 Cases In The United States ????Health Aff (Millwood) http://www.kidney.de/pget.php?&tw=1&pmid=32379502 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32379502 #FOAvip English Wikipedia <ref>{{Cite pmid|32379502}}</ref> Estimating The Infection Fatality Rate Among Symptomatic COVID-19 Cases In The United States #MMPMID32379502 Basu A Health Aff (Millwood) 2020[Jul]; 39 (7): 1229-1236 PMID32379502show ga Knowing the infection fatality rate (IFR) of novel coronavirus (SARS-CoV-2) infections is essential for the fight against the coronavirus disease (COVID-19) pandemic. Using data through April 20, 2020, I fit a statistical model to COVID-19 case fatality rates over time at the US county level to estimate the COVID-19 IFR among symptomatic cases (IFR-S) as time goes to infinity. The IFR-S in the US was estimated to be 1.3 percent. County-specific rates varied from 0.5 percent to 3.6 percent. The overall IFR for COVID-19 should be lower when I account for cases where patients are asymptomatic and recover without symptoms. When used with other estimating approaches, my model and estimates can help disease and policy modelers obtain more accurate predictions for the epidemiology of the disease and the impact of various policy levers to contain the pandemic. The model could also be used with future pandemics to get an early sense of the magnitude of symptomatic infection at the population level before other direct estimates are available. Substantial variation across patient demographics likely exists and should be the focus of future studies. |*Cause of Death[MESH] |*Mortality[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology[MESH] |Databases, Factual[MESH] |Female[MESH] |Humans[MESH] |Incidence[MESH] |Male[MESH] |Models, Statistical[MESH] |Pandemics/*statistics & numerical data[MESH] |Pneumonia, Viral/*epidemiology[MESH] |Predictive Value of Tests[MESH] |Severity of Illness Index[MESH]Estimating The Infection Fatality Rate Among Symptomatic COVID-19 Case(epmc).pdf DeepDyve Pubget Overpricing