Date/Time
Date(s) - 19/09/2024
4:30 pm - 5:30 pm

Location: ETB 124

Speaker: Emma Coates

Title: Combined effects of heterogeneous transmission and disparate vaccination rates

Abstract: How can mathematical modeling be used as a powerful tool in public health? In this study, we present how deterministic models can be used to inform public health policies with a specific example of disparities observed in SARS-CoV-2 seroprevalence data and vaccination efforts to address the observed disparities.

Ma et al. in 2021 modeled the impact of racial and ethnic disparities on COVID-19 epidemic disparities by fitting structured compartmental models to early outbreak seroprevalence data stratified by race and ethnicity from New York City. Ma et al. used these mathematical models to investigate whether disparate seroprevalence could be explained by differences in per-contact susceptibility or by differences in contact rates and patterns.

Using the Ma et al. paper as a guide, we investigate how vaccine uptake combines with existing transmission disparities in modeled outcomes by developing a mathematical modeling framework for quantify potential effects of interventions aiming to reduce disparities through vaccination efforts.