Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies

Author:

McAloon Conor G.,Wall Patrick,Butler Francis,Codd Mary,Gormley Eamonn,Walsh Cathal,Duggan Jim,Murphy T. Brendan,Nolan Philip,Smyth Breda,O’Brien Katie,Teljeur Conor,Green Martin J.,O’Grady Luke,Culhane Kieran,Buckley Claire,Carroll Ciara,Doyle Sarah,Martin Jennifer,More Simon J.

Abstract

Abstract Background Contact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling. We analysed data from 140,204 close contacts of 39,861 cases in Ireland from 1st May to 1st December 2020. Results Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days. Conclusions We found that the number of contacts per infected case was overdispersed, the mean varied considerable over time and was temporally associated with government interventions. Analysis of the reported number of contacts per individual in contact tracing data may be a useful early indicator of changes in behaviour in response to, or indeed despite, government restrictions. This study provides useful information for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health

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