Ethnic inequities in mathematical models for respiratory infectious disease: A systematic review.

Abstract

COVID-19 was the most recent pandemic to highlight profound ethnic inequities. However, most mathematical epidemiological models do not adequately represent these inequities, limiting the potential for such models to inform equitable public health responses and interventions. This systematic review identifies mathematical models of infectious respiratory disease transmission that report results by ethnic group and surveys the different mathematical modelling approaches used to attempt to capture ethnicity-related outcomes. Only 28 studies met the inclusion criteria, which is rare relative to the volume of infectious disease modelling literature. The most common model frameworks were compartmental models (11 studies), individual-based models (12 studies), and metapopulation models (5 studies). Across these studies, ethnic heterogeneities were represented directly by incorporating some combination of ethnic group population demographics, ethnicity-specific interaction patterns, and ethnicity-specific disease parameters, or indirectly through spatial differences in interaction patterns or disease transmission. Consideration of ethnicity in mathematical models of disease transmission is in its infancy, with only three of the studies published before 2020, but it has the potential to provide improved evidence for public health action that reduces the epidemic burden and inequities across ethnic groups.