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About:
COVID-19 Confirmed Cases and Fatalities in 883 U.S. Counties with a Population of 50,000 or More: Predictions Based on Social, Economic, Demographic Factors and Shutdown Days
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covidontheweb.inria.fr
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Academic Article
research paper
schema:ScholarlyArticle
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
COVID-19 Confirmed Cases and Fatalities in 883 U.S. Counties with a Population of 50,000 or More: Predictions Based on Social, Economic, Demographic Factors and Shutdown Days
Creator
Robertson, Leon
source
MedRxiv
abstract
The spread of the COVID-19 virus is highly variable among U.S. counties. Seventeen factors known or thought to be related to spread of the COVID-19 virus were studied by Poisson regression analysis of confirmed cases and deaths in 883 U.S. counties with a population of 50,000 or more as of May 31, 2020. With little exception, each factor was predictive of incidence and mortality. The regression equation can be used to identify priority locations for preventive efforts and preparation for medical care caseloads when prevention is unsuccessful. Based on the correlation of cases and deaths to days since stay-at-home orders were issued, the orders reduced the cases about 48 percent and deaths about 50 percent. Focusing preventive efforts on the more vulnerable counties may be more effective and less economically damaging than statewide shutdowns.
has issue date
2020-06-26
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bibo:doi
10.1101/2020.06.25.20139956
has license
medrxiv
sha1sum (hex)
4f9443deb4ce287b969dca3faccd038a40d80d9e
schema:url
https://doi.org/10.1101/2020.06.25.20139956
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COVID-19 Confirmed Cases and Fatalities in 883 U.S. Counties with a Population of 50,000 or More: Predictions Based on Social, Economic, Demographic Factors and Shutdown Days
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covid:4f9443deb4ce287b969dca3faccd038a40d80d9e#body_text
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named entity 'identify'
named entity 'POPULATION'
named entity 'KNOWN'
named entity 'PRIORITY'
named entity 'HOME'
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