Ethnic inequities in mathematical models for respiratory infectious diseases: a systematic review

The COVID-19 pandemic highlighted profound infectious disease inequities between different ethnic groups, but most mathematical epidemiological modelling does not capture these inequities. There is limited knowledge on how some groups, particularly marginalised ethnic groups, can be appropriately represented in models. This systematic review identifies mathematical models of infectious respiratory disease transmission that report results by ethnic group. Only twenty-eight studies met the inclusion criteria. Most studies were published during or after the COVID-19 pandemic. The most common model frameworks were compartmental models (12 studies) and individual based models (12), followed by spatial metapopulation models (5). Across these studies, ethnic heterogeneities were represented by incorporating a combination of ethnic group population size distributions, ethnic-specific interaction patterns, and ethnic-specific model parameters. Relative to the volume of infectious disease modelling literature, ethnicity representation is incredibly uncommon. Incorporation of ethnicity in models has the potential to provide enhanced evidence for public health action that reduces the epidemic burden for the total population and the inequities across ethnic groups.