Relationship between household attributes and contact patterns in urban and rural South Africa

Households play a crucial role in the propagation of infectious diseases due to the frequent and prolonged interactions that typically occur between their members. Recent studies have emphasized the need to include socioeconomic variables in epidemic models to account for the heterogeneity induced by human behavior. While sub-Saharan Africa suffers the highest burden of infectious disease diffusion, few studies have investigated the mixing patterns in the countries and their relation with social indicators. This work analyzes household contact matrices measured with wearable proximity sensors in a rural and an urban village in South Africa. Leveraging a rich data collection describing additional individual and household attributes, we investigate how the household contact matrix varies according to the household type (whether it is composed only of a familiar nucleus or by a larger group), the gender of its head (the primary decision-maker), the rural or urban context, and the season in which it was measured. We show the household type and the gender of its head induce differences in the interaction patterns between household members, particularly regarding child caregiving, suggesting they are relevant attributes to include in epidemic modeling.

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Publication Details

Journal
PLoS ONE
Published
2026-03-23
DOI
https://doi.org/10.1371/journal.pone.0344732
Primary Topic
COVID-19 epidemiological studies
Type
article
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article

Relationship between household attributes and contact patterns in urban and rural South Africa

PLoS ONE
COVID-19 epidemiological studies
article

Relationship between household attributes and contact patterns in urban and rural South Africa

article en

Abstract

Households play a crucial role in the propagation of infectious diseases due to the frequent and prolonged interactions that typically occur between their members. Recent studies have emphasized the need to include socioeconomic variables in epidemic models to account for the heterogeneity induced by human behavior. While sub-Saharan Africa suffers the highest burden of infectious disease diffusion, few studies have investigated the mixing patterns in the countries and their relation with social indicators. This work analyzes household contact matrices measured with wearable proximity sensors in a rural and an urban village in South Africa. Leveraging a rich data collection describing additional individual and household attributes, we investigate how the household contact matrix varies according to the household type (whether it is composed only of a familiar nucleus or by a larger group), the gender of its head (the primary decision-maker), the rural or urban context, and the season in which it was measured. We show the household type and the gender of its head induce differences in the interaction patterns between household members, particularly regarding child caregiving, suggesting they are relevant attributes to include in epidemic modeling.

PLoS ONEVol. 21(3)
National Health Laboratory Service (ZA), Institute for Scientific Interchange (IT), University of the Witwatersrand (ZA), The Task Force for Global Health (US), University of Turin (IT)
Good health and well-being
Openalex Percentile: Top 15%
COVID-19 epidemiological studies
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