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Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination

Some asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19. Here, we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate the relationship between asymptomatic proporti...

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Autores principales: Wang, Zengmiao, Wu, Peiyi, Wang, Jingyuan, Lourenço, José, Li, Bingying, Rader, Benjamin, Laine, Marko, Miao, Hui, Wang, Ligui, Song, Hongbin, Bharti, Nita, Brownstein, John S., Bjornstad, Ottar N., Dye, Christopher, Tian, Huaiyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554520/
http://dx.doi.org/10.1098/rsif.2022.0498
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author Wang, Zengmiao
Wu, Peiyi
Wang, Jingyuan
Lourenço, José
Li, Bingying
Rader, Benjamin
Laine, Marko
Miao, Hui
Wang, Ligui
Song, Hongbin
Bharti, Nita
Brownstein, John S.
Bjornstad, Ottar N.
Dye, Christopher
Tian, Huaiyu
author_facet Wang, Zengmiao
Wu, Peiyi
Wang, Jingyuan
Lourenço, José
Li, Bingying
Rader, Benjamin
Laine, Marko
Miao, Hui
Wang, Ligui
Song, Hongbin
Bharti, Nita
Brownstein, John S.
Bjornstad, Ottar N.
Dye, Christopher
Tian, Huaiyu
author_sort Wang, Zengmiao
collection PubMed
description Some asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19. Here, we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate the relationship between asymptomatic proportion and age. Epidemiological data obtained before mass vaccination provide valuable insights into the nature of pathogenicity of SARS-CoV-2. The data were collected by multiple rounds of city-wide PCR testing with contact tracing, where each patient was monitored for symptoms through the whole course of infection. The clinical endpoint (asymptomatic or symptomatic) for each patient was recorded (the pre-symptomatic patients were classified as symptomatic). We find that the proportion of infections that are asymptomatic declines with age (coefficient = −0.006, 95% CI: −0.008 to −0.003, p < 0.01), falling from 42% (95% CI: 6–78%) in age group 0–9 years to 11% (95% CI: 0–25%) in age group greater than 60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern, together with the distribution of cases by age, can explain most of the reported variation in asymptomatic proportions among cities. Our analysis suggests that SARS-CoV-2 surveillance strategies should take account of the variation in asymptomatic proportion with age.
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spelling pubmed-95545202022-10-25 Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination Wang, Zengmiao Wu, Peiyi Wang, Jingyuan Lourenço, José Li, Bingying Rader, Benjamin Laine, Marko Miao, Hui Wang, Ligui Song, Hongbin Bharti, Nita Brownstein, John S. Bjornstad, Ottar N. Dye, Christopher Tian, Huaiyu J R Soc Interface Life Sciences–Mathematics interface Some asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19. Here, we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate the relationship between asymptomatic proportion and age. Epidemiological data obtained before mass vaccination provide valuable insights into the nature of pathogenicity of SARS-CoV-2. The data were collected by multiple rounds of city-wide PCR testing with contact tracing, where each patient was monitored for symptoms through the whole course of infection. The clinical endpoint (asymptomatic or symptomatic) for each patient was recorded (the pre-symptomatic patients were classified as symptomatic). We find that the proportion of infections that are asymptomatic declines with age (coefficient = −0.006, 95% CI: −0.008 to −0.003, p < 0.01), falling from 42% (95% CI: 6–78%) in age group 0–9 years to 11% (95% CI: 0–25%) in age group greater than 60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern, together with the distribution of cases by age, can explain most of the reported variation in asymptomatic proportions among cities. Our analysis suggests that SARS-CoV-2 surveillance strategies should take account of the variation in asymptomatic proportion with age. The Royal Society 2022-10-12 /pmc/articles/PMC9554520/ http://dx.doi.org/10.1098/rsif.2022.0498 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
Wang, Zengmiao
Wu, Peiyi
Wang, Jingyuan
Lourenço, José
Li, Bingying
Rader, Benjamin
Laine, Marko
Miao, Hui
Wang, Ligui
Song, Hongbin
Bharti, Nita
Brownstein, John S.
Bjornstad, Ottar N.
Dye, Christopher
Tian, Huaiyu
Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination
title Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination
title_full Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination
title_fullStr Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination
title_full_unstemmed Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination
title_short Assessing the asymptomatic proportion of SARS-CoV-2 infection with age in China before mass vaccination
title_sort assessing the asymptomatic proportion of sars-cov-2 infection with age in china before mass vaccination
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554520/
http://dx.doi.org/10.1098/rsif.2022.0498
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