Addressing current limitations of household transmission studies by collecting contact data
Year: 2024
Type: article
Abstract: Modeling studies of household transmission data have helped characterize the role of children in influenza and coronavirus disease 2019 (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 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like and influenza virus-like infections in a synthetic population of 1000 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.
Source: American Journal of Epidemiology
DOI: 10.1093/aje/kwae106
Institutions: Centre National de la Recherche Scientifique, Institut Pasteur, Université Paris Cité, Sorbonne Université, Génomique évolutive, modélisation et santé, University of Antwerp, Hasselt University, University Medical Center Utrecht, Laboratory of Data Discovery for Health, University of Hong Kong
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $5,099
Awards: G1979782309, Versatile Emerging infectious disease Observatory, G282427092, G3062667675, G434337789, Rapid European SARS-CoV-2 Emergency research Response, Institut Convergences pour l’étude de l’Emergence des Pathologies au Travers des Individus et des populatiONs, G7240651115, Integrative Biology of Emerging Infectious Diseases, G8670608220
OpenAlex ID: W4399454715
