Publication
Title
Population age and household structures shape transmission dynamics of emerging infectious diseases : a longitudinal microsimulation approach
Author
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.
Language
English
Source (journal)
Journal of the Royal Society interface: physical and life sciences. - London
Publication
London : 2023
ISSN
1742-5689
DOI
10.1098/RSIF.2023.0087
Volume/pages
20 :209 (2023) , p. 1-11
Article Reference
20230087
ISI
001113270300003
Pubmed ID
38053386
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Translational and Transdisciplinary research in Modeling Infectious Diseases (TransMID).
Using dynamic microsimulation as an integrated modelling framework to assess the impact of individual-level and contextual factors on past and future fertility trends.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 09.01.2024
Last edited 04.11.2024
To cite this reference