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Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data

We describe a method to estimate individual risks of hospitalization and death attributable to non-household and household transmission of SARS-CoV-2 using available public data on confirmed-case incidence data along with estimates of the clinical fraction, timing of transmission, isolation adherenc...

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Autores principales: Bhatia, Rajiv, Klausner, Jeffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721133/
https://www.ncbi.nlm.nih.gov/pubmed/33284861
http://dx.doi.org/10.1371/journal.pone.0243026
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author Bhatia, Rajiv
Klausner, Jeffrey
author_facet Bhatia, Rajiv
Klausner, Jeffrey
author_sort Bhatia, Rajiv
collection PubMed
description We describe a method to estimate individual risks of hospitalization and death attributable to non-household and household transmission of SARS-CoV-2 using available public data on confirmed-case incidence data along with estimates of the clinical fraction, timing of transmission, isolation adherence, secondary infection risks, contact rates, and case-hospitalization and case-fatality ratios. Using the method, we estimate that risks for a 90-day period at the median daily summertime U.S. county confirmed COVID-19 case incidence of 10.8 per 100,000 and pre-pandemic contact rates range from 0.4 to 8.9 per 100,000 for the four deciles of age between 20 and 60 years. The corresponding 90-day period risk of hospitalization ranges from 13.7 to 69.2 per 100,000. Assuming a non-household secondary infection risk of 4% and pre-pandemic contact rates, the share of transmissions attributable to household settings ranges from 73% to 78%. These estimates are sensitive to the parameter assumptions; nevertheless, they are comparable to the COVID-19 hospitalization and fatality rates observed over the time period. We conclude that individual risk of hospitalization and death from SARS-CoV-2 infection is calculable from publicly available data sources. Access to publicly reported infection incidence data by setting and other exposure characteristics along with setting specific estimates of secondary infection risk would allow for more precise individual risk estimation.
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spelling pubmed-77211332020-12-15 Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data Bhatia, Rajiv Klausner, Jeffrey PLoS One Research Article We describe a method to estimate individual risks of hospitalization and death attributable to non-household and household transmission of SARS-CoV-2 using available public data on confirmed-case incidence data along with estimates of the clinical fraction, timing of transmission, isolation adherence, secondary infection risks, contact rates, and case-hospitalization and case-fatality ratios. Using the method, we estimate that risks for a 90-day period at the median daily summertime U.S. county confirmed COVID-19 case incidence of 10.8 per 100,000 and pre-pandemic contact rates range from 0.4 to 8.9 per 100,000 for the four deciles of age between 20 and 60 years. The corresponding 90-day period risk of hospitalization ranges from 13.7 to 69.2 per 100,000. Assuming a non-household secondary infection risk of 4% and pre-pandemic contact rates, the share of transmissions attributable to household settings ranges from 73% to 78%. These estimates are sensitive to the parameter assumptions; nevertheless, they are comparable to the COVID-19 hospitalization and fatality rates observed over the time period. We conclude that individual risk of hospitalization and death from SARS-CoV-2 infection is calculable from publicly available data sources. Access to publicly reported infection incidence data by setting and other exposure characteristics along with setting specific estimates of secondary infection risk would allow for more precise individual risk estimation. Public Library of Science 2020-12-07 /pmc/articles/PMC7721133/ /pubmed/33284861 http://dx.doi.org/10.1371/journal.pone.0243026 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Bhatia, Rajiv
Klausner, Jeffrey
Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data
title Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data
title_full Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data
title_fullStr Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data
title_full_unstemmed Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data
title_short Estimating individual risks of COVID-19-associated hospitalization and death using publicly available data
title_sort estimating individual risks of covid-19-associated hospitalization and death using publicly available data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721133/
https://www.ncbi.nlm.nih.gov/pubmed/33284861
http://dx.doi.org/10.1371/journal.pone.0243026
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