House, Thomas; Riley, Heather; Pellis, Lorenzo; Pouwels, Koen B; Bacon, Sebastian; Eidukas, Arturas; Jahanshahi, Kaveh; Eggo, Rosalind M; Sarah Walker, A; (2022) Inferring risks of coronavirus transmission from community household data. Statistical methods in medical research, 31 (9). pp. 1738-1756. ISSN 0962-2802 DOI: https://doi.org/10.1177/09622802211055853
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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.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 36112916 |
Elements ID | 194804 |
Official URL | http://dx.doi.org/10.1177/09622802211055853 |
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