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

PURPOSE: 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.

METHODS: 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.

RESULTS: We show that the basic reproduction number, R, 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.

CONCLUSIONS: 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.