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Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections

BACKGROUND: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic ind...

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Autores principales: Russell, Timothy W., Golding, Nick, Hellewell, Joel, Abbott, Sam, Wright, Lawrence, Pearson, Carl A. B., van Zandvoort, Kevin, Jarvis, Christopher I., Gibbs, Hamish, Liu, Yang, Eggo, Rosalind M., Edmunds, W. John, Kucharski, Adam J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577796/
https://www.ncbi.nlm.nih.gov/pubmed/33087179
http://dx.doi.org/10.1186/s12916-020-01790-9
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author Russell, Timothy W.
Golding, Nick
Hellewell, Joel
Abbott, Sam
Wright, Lawrence
Pearson, Carl A. B.
van Zandvoort, Kevin
Jarvis, Christopher I.
Gibbs, Hamish
Liu, Yang
Eggo, Rosalind M.
Edmunds, W. John
Kucharski, Adam J.
author_facet Russell, Timothy W.
Golding, Nick
Hellewell, Joel
Abbott, Sam
Wright, Lawrence
Pearson, Carl A. B.
van Zandvoort, Kevin
Jarvis, Christopher I.
Gibbs, Hamish
Liu, Yang
Eggo, Rosalind M.
Edmunds, W. John
Kucharski, Adam J.
author_sort Russell, Timothy W.
collection PubMed
description BACKGROUND: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. METHODS: Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever ≥ 37.5 °C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the baseline case fatality ratio (CFR), which was adjusted for delays and under-ascertainment, then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. RESULTS: Based on reported cases and deaths, we estimated that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.4% (Bangladesh) to 100% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6 July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 18 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. As of 7 June, our seroprevalence estimates range from 0% (many countries) to 13% (95% CrI 5.6–24%) (Belgium). CONCLUSIONS: We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country’s population infected with SARS-CoV-2 worldwide is generally low.
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spelling pubmed-75777962020-10-22 Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections Russell, Timothy W. Golding, Nick Hellewell, Joel Abbott, Sam Wright, Lawrence Pearson, Carl A. B. van Zandvoort, Kevin Jarvis, Christopher I. Gibbs, Hamish Liu, Yang Eggo, Rosalind M. Edmunds, W. John Kucharski, Adam J. BMC Med Research Article BACKGROUND: Asymptomatic or subclinical SARS-CoV-2 infections are often unreported, which means that confirmed case counts may not accurately reflect underlying epidemic dynamics. Understanding the level of ascertainment (the ratio of confirmed symptomatic cases to the true number of symptomatic individuals) and undetected epidemic progression is crucial to informing COVID-19 response planning, including the introduction and relaxation of control measures. Estimating case ascertainment over time allows for accurate estimates of specific outcomes such as seroprevalence, which is essential for planning control measures. METHODS: Using reported data on COVID-19 cases and fatalities globally, we estimated the proportion of symptomatic cases (i.e. any person with any of fever ≥ 37.5 °C, cough, shortness of breath, sudden onset of anosmia, ageusia or dysgeusia illness) that were reported in 210 countries and territories, given those countries had experienced more than ten deaths. We used published estimates of the baseline case fatality ratio (CFR), which was adjusted for delays and under-ascertainment, then calculated the ratio of this baseline CFR to an estimated local delay-adjusted CFR to estimate the level of under-ascertainment in a particular location. We then fit a Bayesian Gaussian process model to estimate the temporal pattern of under-ascertainment. RESULTS: Based on reported cases and deaths, we estimated that, during March 2020, the median percentage of symptomatic cases detected across the 84 countries which experienced more than ten deaths ranged from 2.4% (Bangladesh) to 100% (Chile). Across the ten countries with the highest number of total confirmed cases as of 6 July 2020, we estimated that the peak number of symptomatic cases ranged from 1.4 times (Chile) to 18 times (France) larger than reported. Comparing our model with national and regional seroprevalence data where available, we find that our estimates are consistent with observed values. Finally, we estimated seroprevalence for each country. As of 7 June, our seroprevalence estimates range from 0% (many countries) to 13% (95% CrI 5.6–24%) (Belgium). CONCLUSIONS: We found substantial under-ascertainment of symptomatic cases, particularly at the peak of the first wave of the SARS-CoV-2 pandemic, in many countries. Reported case counts will therefore likely underestimate the rate of outbreak growth initially and underestimate the decline in the later stages of an epidemic. Although there was considerable under-reporting in many locations, our estimates were consistent with emerging serological data, suggesting that the proportion of each country’s population infected with SARS-CoV-2 worldwide is generally low. BioMed Central 2020-10-22 /pmc/articles/PMC7577796/ /pubmed/33087179 http://dx.doi.org/10.1186/s12916-020-01790-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Russell, Timothy W.
Golding, Nick
Hellewell, Joel
Abbott, Sam
Wright, Lawrence
Pearson, Carl A. B.
van Zandvoort, Kevin
Jarvis, Christopher I.
Gibbs, Hamish
Liu, Yang
Eggo, Rosalind M.
Edmunds, W. John
Kucharski, Adam J.
Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
title Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
title_full Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
title_fullStr Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
title_full_unstemmed Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
title_short Reconstructing the early global dynamics of under-ascertained COVID-19 cases and infections
title_sort reconstructing the early global dynamics of under-ascertained covid-19 cases and infections
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577796/
https://www.ncbi.nlm.nih.gov/pubmed/33087179
http://dx.doi.org/10.1186/s12916-020-01790-9
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