Capturing the implications of residential segregation for the dynamics of infectious disease transmission

Residential segregation is linked to racial and socioeconomic inequity in outcomes for numerous infections including SARS-CoV-2, influenza, STIs, and tuberculosis. Despite the importance of segregation as a driver of infection inequity, there are few mathematical models to inform our understanding of these dynamics.

We developed a transmission model including mechanistic relationships between residential segregation and infection inequity. We conceptualize segregation as a fundamental social cause of infection inequity that jointly impacts contact patterns and vulnerability to infection.

We show that the basic reproduction number, R₀, and equilibrium prevalence are sensitive to interactions between these factors. Our results show that separation alone is insufficient to explain segregation-associated differences in infection risks. Increasing separation only results in concentration of risk in segregated populations when accompanied by increasing vulnerability.

This work shows why it is important to consider causal linkages between high-level social determinants - like segregation - and more-proximal transmission mechanisms when crafting and evaluating public health policies. While the framework in this analysis is stylized, it lays the groundwork for data-driven explorations of the mechanistic impact of residential segregation on infection inequities.