Household bubbles and COVID-19 transmission: insights from percolation theory.


Journal

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
ISSN: 1471-2970
Titre abrégé: Philos Trans R Soc Lond B Biol Sci
Pays: England
ID NLM: 7503623

Informations de publication

Date de publication:
19 07 2021
Historique:
entrez: 31 5 2021
pubmed: 1 6 2021
medline: 11 6 2021
Statut: ppublish

Résumé

In the era of social distancing to curb the spread of COVID-19, bubbling is the combining of two or more households to create an exclusive larger group. The impact of bubbling on COVID-19 transmission is challenging to quantify because of the complex social structures involved. We developed a network description of households in the UK, using the configuration model to link households. We explored the impact of bubbling scenarios by joining together households of various sizes. For each bubbling scenario, we calculated the percolation threshold, that is, the number of connections per individual required for a giant component to form, numerically and theoretically. We related the percolation threshold to the household reproduction number. We find that bubbling scenarios in which single-person households join with another household have a minimal impact on network connectivity and transmission potential. Ubiquitous scenarios where all households form a bubble are likely to lead to an extensive transmission that is hard to control. The impact of plausible scenarios, with variable uptake and heterogeneous bubble sizes, can be mitigated with reduced numbers of contacts outside the household. Bubbling of households comes at an increased risk of transmission; however, under certain circumstances risks can be modest and could be balanced by other changes in behaviours. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Identifiants

pubmed: 34053262
doi: 10.1098/rstb.2020.0284
pmc: PMC8165589
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

20200284

Subventions

Organisme : Medical Research Council
ID : MC_PC_19067
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_19067/2
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/V038613/1
Pays : United Kingdom

Références

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pubmed: 33623826

Auteurs

Leon Danon (L)

Department of Engineering Mathematics, University of Bristol, University Walk, Bristol BS8 1TW, UK.

Lucas Lacasa (L)

School of Mathematical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK.

Ellen Brooks-Pollock (E)

University of Bristol School of Veterinary Sciences, Langford BS40 5DU, UK.
NIHR HPRU in Behaviour Change and Evaluation, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK.

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