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

This dataset accompanies an article titled, 'Untangling the contribution of survey design and demographic change to observed differences in age-stratified contact patterns', by T. Harris et al. A preprint can be found at https://arxiv.org/abs/2406.01639.

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 33 contact matrices generated from surveys conducted before and during the COVID-19 pandemic, and analyse key features distinguishing their structures such as the extent of age assortativity. Our analysis demonstrates that, while aspects of pandemic scenarios (such as the implementation of lockdowns) could account for some of these distinguishing features, they can also be explained by differences in study design and, to a lesser extent, long-term demographic trends. Our results caution against using survey data from different studies in counterfactual analysis of epidemic mitigation strategies. Doing so risks attributing differences stemming from survey design choices or long-term changes to the short-term effects of interventions.

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