Cargando…

Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study

BACKGROUND: Regional monitoring of the proportion of the population who have been infected by SARS-CoV-2 is important to guide local management of the epidemic, but is difficult in the absence of regular nationwide serosurveys. We aimed to estimate in near real time the proportion of adults who have...

Descripción completa

Detalles Bibliográficos
Autores principales: Hozé, Nathanaël, Paireau, Juliette, Lapidus, Nathanaël, Tran Kiem, Cécile, Salje, Henrik, Severi, Gianluca, Touvier, Mathilde, Zins, Marie, de Lamballerie, Xavier, Lévy-Bruhl, Daniel, Carrat, Fabrice, Cauchemez, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032222/
https://www.ncbi.nlm.nih.gov/pubmed/33838700
http://dx.doi.org/10.1016/S2468-2667(21)00064-5
_version_ 1783676190584733696
author Hozé, Nathanaël
Paireau, Juliette
Lapidus, Nathanaël
Tran Kiem, Cécile
Salje, Henrik
Severi, Gianluca
Touvier, Mathilde
Zins, Marie
de Lamballerie, Xavier
Lévy-Bruhl, Daniel
Carrat, Fabrice
Cauchemez, Simon
author_facet Hozé, Nathanaël
Paireau, Juliette
Lapidus, Nathanaël
Tran Kiem, Cécile
Salje, Henrik
Severi, Gianluca
Touvier, Mathilde
Zins, Marie
de Lamballerie, Xavier
Lévy-Bruhl, Daniel
Carrat, Fabrice
Cauchemez, Simon
author_sort Hozé, Nathanaël
collection PubMed
description BACKGROUND: Regional monitoring of the proportion of the population who have been infected by SARS-CoV-2 is important to guide local management of the epidemic, but is difficult in the absence of regular nationwide serosurveys. We aimed to estimate in near real time the proportion of adults who have been infected by SARS-CoV-2. METHODS: In this modelling study, we developed a method to reconstruct the proportion of adults who have been infected by SARS-CoV-2 and the proportion of infections being detected, using the joint analysis of age-stratified seroprevalence, hospitalisation, and case data, with deconvolution methods. We developed our method on a dataset consisting of seroprevalence estimates from 9782 participants (aged ≥20 years) in the two worst affected regions of France in May, 2020, and applied our approach to the 13 French metropolitan regions over the period March, 2020, to January, 2021. We validated our method externally using data from a national seroprevalence study done between May and June, 2020. FINDINGS: We estimate that 5·7% (95% CI 5·1–6·4) of adults in metropolitan France had been infected with SARS-CoV-2 by May 11, 2020. This proportion remained stable until August, 2020, and increased to 14·9% (13·2–16·9) by Jan 15, 2021. With 26·5% (23·4–29·8) of adult residents having been infected in Île-de-France (Paris region) compared with 5·1% (4·5–5·8) in Brittany by January, 2021, regional variations remained large (coefficient of variation [CV] 0·50) although less so than in May, 2020 (CV 0·74). The proportion infected was twice as high (20·4%, 15·6–26·3) in 20–49-year-olds than in individuals aged 50 years or older (9·7%, 6·9–14·1). 40·2% (34·3–46·3) of infections in adults were detected in June to August, 2020, compared with 49·3% (42·9–55·9) in November, 2020, to January, 2021. Our regional estimates of seroprevalence were strongly correlated with the external validation dataset (coefficient of correlation 0·89). INTERPRETATION: Our simple approach to estimate the proportion of adults that have been infected with SARS-CoV-2 can help to characterise the burden of SARS-CoV-2 infection, epidemic dynamics, and the performance of surveillance in different regions. FUNDING: EU RECOVER, Agence Nationale de la Recherche, Fondation pour la Recherche Médicale, Institut National de la Santé et de la Recherche Médicale (Inserm).
format Online
Article
Text
id pubmed-8032222
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher The Author(s). Published by Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-80322222021-04-09 Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study Hozé, Nathanaël Paireau, Juliette Lapidus, Nathanaël Tran Kiem, Cécile Salje, Henrik Severi, Gianluca Touvier, Mathilde Zins, Marie de Lamballerie, Xavier Lévy-Bruhl, Daniel Carrat, Fabrice Cauchemez, Simon Lancet Public Health Articles BACKGROUND: Regional monitoring of the proportion of the population who have been infected by SARS-CoV-2 is important to guide local management of the epidemic, but is difficult in the absence of regular nationwide serosurveys. We aimed to estimate in near real time the proportion of adults who have been infected by SARS-CoV-2. METHODS: In this modelling study, we developed a method to reconstruct the proportion of adults who have been infected by SARS-CoV-2 and the proportion of infections being detected, using the joint analysis of age-stratified seroprevalence, hospitalisation, and case data, with deconvolution methods. We developed our method on a dataset consisting of seroprevalence estimates from 9782 participants (aged ≥20 years) in the two worst affected regions of France in May, 2020, and applied our approach to the 13 French metropolitan regions over the period March, 2020, to January, 2021. We validated our method externally using data from a national seroprevalence study done between May and June, 2020. FINDINGS: We estimate that 5·7% (95% CI 5·1–6·4) of adults in metropolitan France had been infected with SARS-CoV-2 by May 11, 2020. This proportion remained stable until August, 2020, and increased to 14·9% (13·2–16·9) by Jan 15, 2021. With 26·5% (23·4–29·8) of adult residents having been infected in Île-de-France (Paris region) compared with 5·1% (4·5–5·8) in Brittany by January, 2021, regional variations remained large (coefficient of variation [CV] 0·50) although less so than in May, 2020 (CV 0·74). The proportion infected was twice as high (20·4%, 15·6–26·3) in 20–49-year-olds than in individuals aged 50 years or older (9·7%, 6·9–14·1). 40·2% (34·3–46·3) of infections in adults were detected in June to August, 2020, compared with 49·3% (42·9–55·9) in November, 2020, to January, 2021. Our regional estimates of seroprevalence were strongly correlated with the external validation dataset (coefficient of correlation 0·89). INTERPRETATION: Our simple approach to estimate the proportion of adults that have been infected with SARS-CoV-2 can help to characterise the burden of SARS-CoV-2 infection, epidemic dynamics, and the performance of surveillance in different regions. FUNDING: EU RECOVER, Agence Nationale de la Recherche, Fondation pour la Recherche Médicale, Institut National de la Santé et de la Recherche Médicale (Inserm). The Author(s). Published by Elsevier Ltd. 2021-06 2021-04-08 /pmc/articles/PMC8032222/ /pubmed/33838700 http://dx.doi.org/10.1016/S2468-2667(21)00064-5 Text en © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Articles
Hozé, Nathanaël
Paireau, Juliette
Lapidus, Nathanaël
Tran Kiem, Cécile
Salje, Henrik
Severi, Gianluca
Touvier, Mathilde
Zins, Marie
de Lamballerie, Xavier
Lévy-Bruhl, Daniel
Carrat, Fabrice
Cauchemez, Simon
Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study
title Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study
title_full Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study
title_fullStr Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study
title_full_unstemmed Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study
title_short Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study
title_sort monitoring the proportion of the population infected by sars-cov-2 using age-stratified hospitalisation and serological data: a modelling study
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032222/
https://www.ncbi.nlm.nih.gov/pubmed/33838700
http://dx.doi.org/10.1016/S2468-2667(21)00064-5
work_keys_str_mv AT hozenathanael monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT paireaujuliette monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT lapidusnathanael monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT trankiemcecile monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT saljehenrik monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT severigianluca monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT touviermathilde monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT zinsmarie monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT delamballeriexavier monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT levybruhldaniel monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT carratfabrice monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy
AT cauchemezsimon monitoringtheproportionofthepopulationinfectedbysarscov2usingagestratifiedhospitalisationandserologicaldataamodellingstudy