Addressing current limitations of household transmission studies by collecting contact data.

ABSTRACT

Modeling studies of household transmission data have helped characterize the role of children in influenza and COVID-19 epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of SARS-CoV-2-like and influenza-like infections in a synthetic population of 1,000 households assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father-mother pair, followed by the child-mother, child-child, and finally child-father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.