Untangling the contribution of survey design and demographic change to observed differences in age-stratified contact patterns

Abstract

Social contact patterns are key drivers of infectious disease transmission. During the COVID-19 pandemic, differences between pre-COVID and COVID-era contact rates were widely attributed to non-pharmaceutical interventions such as lockdowns. However, the factors that drive changes in the distribution of contacts between different subpopulations remain poorly understood. Here, we present a clustering analysis of 45 contact matrices generated from surveys conducted before and during the COVID-19 pandemic, and analyse key structural features that distinguish contact matrices generated from POLYMOD and CoMix, two of the largest contact studies. Our analysis suggests that, while contextual featur..