Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model.
Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID-19 disease burden. We e...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1010465&type=printable |
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| author | Melanie H Chitwood Marcus Russi Kenneth Gunasekera Joshua Havumaki Fayette Klaassen Virginia E Pitzer Joshua A Salomon Nicole A Swartwood Joshua L Warren Daniel M Weinberger Ted Cohen Nicolas A Menzies |
| author_facet | Melanie H Chitwood Marcus Russi Kenneth Gunasekera Joshua Havumaki Fayette Klaassen Virginia E Pitzer Joshua A Salomon Nicole A Swartwood Joshua L Warren Daniel M Weinberger Ted Cohen Nicolas A Menzies |
| author_sort | Melanie H Chitwood |
| collection | DOAJ |
| description | Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID-19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 404,214 COVID-19 deaths by the end of 2020, and that 28% of the US population had been infected. There was county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers. |
| format | Article |
| id | doaj-art-66e6ed9b6f2b4fafb21783168d04d1c1 |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2022-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-66e6ed9b6f2b4fafb21783168d04d1c12025-08-20T03:44:45ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582022-08-01188e101046510.1371/journal.pcbi.1010465Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model.Melanie H ChitwoodMarcus RussiKenneth GunasekeraJoshua HavumakiFayette KlaassenVirginia E PitzerJoshua A SalomonNicole A SwartwoodJoshua L WarrenDaniel M WeinbergerTed CohenNicolas A MenziesReported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID-19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 404,214 COVID-19 deaths by the end of 2020, and that 28% of the US population had been infected. There was county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1010465&type=printable |
| spellingShingle | Melanie H Chitwood Marcus Russi Kenneth Gunasekera Joshua Havumaki Fayette Klaassen Virginia E Pitzer Joshua A Salomon Nicole A Swartwood Joshua L Warren Daniel M Weinberger Ted Cohen Nicolas A Menzies Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. PLoS Computational Biology |
| title | Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. |
| title_full | Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. |
| title_fullStr | Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. |
| title_full_unstemmed | Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. |
| title_short | Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. |
| title_sort | reconstructing the course of the covid 19 epidemic over 2020 for us states and counties results of a bayesian evidence synthesis model |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1010465&type=printable |
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