Abstract
Host population demographics and patterns of host-to-host interactions are important drivers of heterogeneity in infectious disease transmission. To improve our understanding of how population structures and changes therein influence disease transmission dynamics at the individual and population level, we model a dynamic age- and household-structured population using longitudinal microdata drawn from Belgian census and population registers. At different points in time, we simulate the spread of a close-contact infectious disease and vary the age profiles of infectiousness and susceptibility to reflect specific infections (e.g. influenza and SARS-CoV-2) using a two-level mixing model, which distinguishes between exposure to infection in the household and exposure in the community. We find that the strong relationship between age and household structures, in combination with social mixing patterns and epidemiological parameters, shape the spread of an emerging infection. Disease transmission in the adult population in particular is to a large degree explained by differential household compositions and not just household size. Moreover, we highlight how demographic processes alter population structures in an ageing population and how these in turn affect disease transmission dynamics across population groups.