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Inferring risks of coronavirus transmission from community household data

The response of many governments to the COVID-19 pandemic has involved measures to control within- and between-household transmission, providing motivation to improve understanding of the absolute and relative risks in these contexts. Here, we perform exploratory, residual-based, and transmission-dy...

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Autores principales: House, Thomas, Riley, Heather, Pellis, Lorenzo, Pouwels, Koen B, Bacon, Sebastian, Eidukas, Arturas, Jahanshahi, Kaveh, Eggo, Rosalind M, Sarah Walker, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465559/
https://www.ncbi.nlm.nih.gov/pubmed/36112916
http://dx.doi.org/10.1177/09622802211055853
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author House, Thomas
Riley, Heather
Pellis, Lorenzo
Pouwels, Koen B
Bacon, Sebastian
Eidukas, Arturas
Jahanshahi, Kaveh
Eggo, Rosalind M
Sarah Walker, A.
author_facet House, Thomas
Riley, Heather
Pellis, Lorenzo
Pouwels, Koen B
Bacon, Sebastian
Eidukas, Arturas
Jahanshahi, Kaveh
Eggo, Rosalind M
Sarah Walker, A.
author_sort House, Thomas
collection PubMed
description The response of many governments to the COVID-19 pandemic has involved measures to control within- and between-household transmission, providing motivation to improve understanding of the absolute and relative risks in these contexts. Here, we perform exploratory, residual-based, and transmission-dynamic household analysis of the Office for National Statistics COVID-19 Infection Survey data from 26 April 2020 to 15 July 2021 in England. This provides evidence for: (i) temporally varying rates of introduction of infection into households broadly following the trajectory of the overall epidemic and vaccination programme; (ii) susceptible-Infectious transmission probabilities of within-household transmission in the 15–35% range; (iii) the emergence of the Alpha and Delta variants, with the former being around 50% more infectious than wildtype and 35% less infectious than Delta within households; (iv) significantly (in the range of 25–300%) more risk of bringing infection into the household for workers in patient-facing roles pre-vaccine; (v) increased risk for secondary school-age children of bringing the infection into the household when schools are open; (vi) increased risk for primary school-age children of bringing the infection into the household when schools were open since the emergence of new variants.
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spelling pubmed-94655592022-09-13 Inferring risks of coronavirus transmission from community household data House, Thomas Riley, Heather Pellis, Lorenzo Pouwels, Koen B Bacon, Sebastian Eidukas, Arturas Jahanshahi, Kaveh Eggo, Rosalind M Sarah Walker, A. Stat Methods Med Res Special Issue Articles The response of many governments to the COVID-19 pandemic has involved measures to control within- and between-household transmission, providing motivation to improve understanding of the absolute and relative risks in these contexts. Here, we perform exploratory, residual-based, and transmission-dynamic household analysis of the Office for National Statistics COVID-19 Infection Survey data from 26 April 2020 to 15 July 2021 in England. This provides evidence for: (i) temporally varying rates of introduction of infection into households broadly following the trajectory of the overall epidemic and vaccination programme; (ii) susceptible-Infectious transmission probabilities of within-household transmission in the 15–35% range; (iii) the emergence of the Alpha and Delta variants, with the former being around 50% more infectious than wildtype and 35% less infectious than Delta within households; (iv) significantly (in the range of 25–300%) more risk of bringing infection into the household for workers in patient-facing roles pre-vaccine; (v) increased risk for secondary school-age children of bringing the infection into the household when schools are open; (vi) increased risk for primary school-age children of bringing the infection into the household when schools were open since the emergence of new variants. SAGE Publications 2022-09-10 2022-09 /pmc/articles/PMC9465559/ /pubmed/36112916 http://dx.doi.org/10.1177/09622802211055853 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Special Issue Articles
House, Thomas
Riley, Heather
Pellis, Lorenzo
Pouwels, Koen B
Bacon, Sebastian
Eidukas, Arturas
Jahanshahi, Kaveh
Eggo, Rosalind M
Sarah Walker, A.
Inferring risks of coronavirus transmission from community household data
title Inferring risks of coronavirus transmission from community household data
title_full Inferring risks of coronavirus transmission from community household data
title_fullStr Inferring risks of coronavirus transmission from community household data
title_full_unstemmed Inferring risks of coronavirus transmission from community household data
title_short Inferring risks of coronavirus transmission from community household data
title_sort inferring risks of coronavirus transmission from community household data
topic Special Issue Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9465559/
https://www.ncbi.nlm.nih.gov/pubmed/36112916
http://dx.doi.org/10.1177/09622802211055853
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