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Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity

The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the...

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Autores principales: Subramanian, Rahul, He, Qixin, Pascual, Mercedes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936345/
https://www.ncbi.nlm.nih.gov/pubmed/33571106
http://dx.doi.org/10.1073/pnas.2019716118
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author Subramanian, Rahul
He, Qixin
Pascual, Mercedes
author_facet Subramanian, Rahul
He, Qixin
Pascual, Mercedes
author_sort Subramanian, Rahul
collection PubMed
description The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered.
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spelling pubmed-79363452021-03-11 Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity Subramanian, Rahul He, Qixin Pascual, Mercedes Proc Natl Acad Sci U S A Biological Sciences The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered. National Academy of Sciences 2021-03-02 2021-02-10 /pmc/articles/PMC7936345/ /pubmed/33571106 http://dx.doi.org/10.1073/pnas.2019716118 Text en Copyright © 2021 the Author(s). Published by PNAS. http://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Biological Sciences
Subramanian, Rahul
He, Qixin
Pascual, Mercedes
Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
title Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
title_full Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
title_fullStr Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
title_full_unstemmed Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
title_short Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
title_sort quantifying asymptomatic infection and transmission of covid-19 in new york city using observed cases, serology, and testing capacity
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936345/
https://www.ncbi.nlm.nih.gov/pubmed/33571106
http://dx.doi.org/10.1073/pnas.2019716118
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