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

Occupational and residential segregation and other manifestations of social and economic inequity drive of racial and socioeconomic inequities in infection, severe disease, and death from a wide variety of infections including SARS-CoV-2, influenza, HIV, tuberculosis, and many others. Despite a deep and long-standing quantitative and qualitative literature on infectious disease inequity, mathematical models that give equally serious attention to the social and biological dynamics underlying infection inequity remain rare. In this paper, we develop a simple transmission model that accounts for the mechanistic relationship between residential segregation on inequity in infection outcomes. We conceptualize segregation as a high-level, fundamental social cause of infection inequity that impacts both who-contacts-whom (separation or preferential mixing) as well as the risk of infection upon exposure (vulnerability). We show that the basic reproduction number, ℛ 0 , and epidemic dynamics are sensitive to the interaction between these factors. Specifically, our analytical and simulation results and that separation alone is insufficient to explain segregation-associated differences in infection risks, and that increasing separation only results in the concentration of risk in segregated populations when it is accompanied by increasing vulnerability. Overall, this work shows why it is important to carefully consider the causal linkages and correlations between high-level social determinants - like segregation - and more-proximal transmission mechanisms when either crafting or evaluating public health policies. While the framework applied in this analysis is deliberately simple, it lays the groundwork for future, data-driven explorations of the mechanistic impact of residential segregation on infection inequities.