ABSTRACT
BackgroundContact 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. MethodsWe analysed data from 140,204 contacts of 39861 cases in Ireland from 1st May to 1st December 2020. Only close contacts were included in the analysis. A close contact was defined as any individual who had had > 15 minutes face-to-face (<2 m) contact with a case; any household contact; or any individual sharing a closed space for longer than 2 hours, in any setting. ResultsThe number of contacts per case was overdispersed, the mean varied considerably over time, and was temporally associated with government interventions. 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. DiscussionThese data were collected for a specific purpose and therefore any inferences must be made with caution. The data are representative of contact rates of cases, and not of the overall population. However, the data may be a more accurate indicator of the likely degree of onward transmission than might be the case if a random sample of the population were taken. Furthermore, since we analysed only the number of close contacts, the total number of contacts per case would have been higher. Nevertheless, this analysis provides useful information for monitoring the impact of government interventions on the number of contacts; for helping pre-empt increases or decreases in case numbers, and for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.
