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Stat Methods Med Res . Inferring risks of coronavirus transmission from community household data

tetano

Editor, Senior Moderator
Stat Methods Med Res


. 2022 Sep;31(9):1738-1756.
doi: 10.1177/09622802211055853.
Inferring risks of coronavirus transmission from community household data


Thomas House[SUP] 1 2 3 [/SUP], Heather Riley[SUP] 1 [/SUP], Lorenzo Pellis[SUP] 1 3 [/SUP], Koen B Pouwels[SUP] 4 5 6 [/SUP], Sebastian Bacon[SUP] 7 [/SUP], Arturas Eidukas[SUP] 8 [/SUP], Kaveh Jahanshahi[SUP] 8 [/SUP], Rosalind M Eggo[SUP] 9 [/SUP], A Sarah Walker[SUP] 4 5 10 11 [/SUP]



Affiliations

Abstract

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.

Keywords: COVID-19; Epidemic; infection; model; risk factors.
 
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