Structural causal influence captures the forces of social inequality in models of infectious disease.

Authors

Sudam Surasinghe, Swathi Nachiar Manivannan, Samuel V Scarpino, Lorin Crawford, C Brandon Ogbunugafor

Published in

Biology letters. Volume 22. Issue 8. Aug 19, 2026.

Abstract

Mathematical models are central to understanding disease transmission for host-pathogen systems across the biosphere. However, most existing frameworks do not explicitly treat host population heterogeneity as a formal driver of variation in transmission dynamics. This gap is most visible in human disease, where social inequalities are well known to structure infectious disease risk, but applies broadly: ecological, behavioural and demographic structure shapes transmission in non-human host populations as well. Here, we introduce a new metric, structural causal influence, which uses causal analysis to quantify how subpopulations contribute to overall transmission through structural differences in exposure, susceptibility or recovery. Using a multi-population model, we show that even a population whose isolated reproduction number lies below one can be drawn into a sustained epidemic through minimal contact with a more affected group.

PMID:
42613058
Bibliographic data and abstract were imported from PubMed on 19 Aug 2026.

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