A method for including socio-demographic factors in social contact matrices for compartment-based epidemic models

TL;DR

This paper introduces a method to incorporate additional socio-demographic factors into social contact matrices, enhancing epidemic models by accounting for more complex population structures.

Contribution

It presents a novel approach to stratify existing contact matrices with extra socio-demographic factors using population data and mixing assumptions.

Findings

Including socio-demographic factors significantly affects epidemic outcomes.

Minority groups' epidemic results are highly sensitive to model parameters.

Extended contact matrices alter the basic reproduction number and epidemic size.

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.