A method for including additional socio-demographic factors in social contact matrices for compartment-based epidemic models
Abstract
Socio-demographic factors influence social contact patterns and play a fundamental role in shaping the transmission dynamics of infectious diseases. However, compartment-based models of infectious disease dynamics commonly consider the dependence of contact patterns on age, but ignore other factors that are likely to have compounding effects. Methods that stratify the population by multiple socio-demographic factors are few and require social contact surveys that contain information about all factors of interest. Here we present a method that can stratify an existing social contact matrix with an additional socio-demographic factor using information about the population structure of the socio-demographic factors and assumptions about the aggregate mixing rates within and between groups. We then analyse hypothetical populations and a projection of a social contact survey onto Aotearoa New Zealand's age-ethnic structure to show how these extended social contact matrices can change epidemic dynamics and outcomes. The inclusion of the additional factor has a big impact on the model reproduction number and final epidemic size. We find that minority group epidemic outcomes are most sensitive to variation in model parameter values.
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BibTeX
@misc{lomas2026method,
title = {{A method for including additional socio-demographic factors in social contact matrices for compartment-based epidemic models}},
author = {Vincent X. Lomas and Tim Chambers and Leighton Watson and Michael Plank},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2605.13870},
eprint = {2605.13870},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.13870},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A method for including additional socio-demographic factors in social contact matrices for compartment-based epidemic models
AU - Vincent X. Lomas
AU - Tim Chambers
AU - Leighton Watson
AU - Michael Plank
PY - 2026
DA - 2026/10/27
PB - arXiv
DO - 10.48550/arxiv.2605.13870
UR - https://arxiv.org/abs/2605.13870
AB - Socio-demographic factors influence social contact patterns and play a fundamental role in shaping the transmission dynamics of infectious diseases. However, compartment-based models of infectious disease dynamics commonly consider the dependence of contact patterns on age, but ignore other factors that are likely to have compounding effects. Methods that stratify the population by multiple socio-demographic factors are few and require social contact surveys that contain information about all factors of interest. Here we present a method that can stratify an existing social contact matrix with an additional socio-demographic factor using information about the population structure of the socio-demographic factors and assumptions about the aggregate mixing rates within and between groups. We then analyse hypothetical populations and a projection of a social contact survey onto Aotearoa New Zealand's age-ethnic structure to show how these extended social contact matrices can change epidemic dynamics and outcomes. The inclusion of the additional factor has a big impact on the model reproduction number and final epidemic size. We find that minority group epidemic outcomes are most sensitive to variation in model parameter values.
ER -