Systems modeling to address the social and biological drivers of disparities in infection and mortality from emerging infectious diseases

Modified Project Summary/Abstract Section ABSTRACT The distribution of disease and death from the COVID-19 pandemic was characterized by wide geographic and sociodemographic variation. Lower-risk, wealthier, and Whiter individuals have received earlier access to vaccination than their counterparts. To those viewing the pandemic through the theoretical lens of social epidemiology and medical sociology, the extremity and nature of these disparities was easily anticipated. However, the predictive and dynamic systems models that have guided the domestic and global COVID-19 response have routinely ignored the social determinants of infection and its outcomes. The objective of this application is to outline a multi-level approach to infectious disease transmission modeling and data analysis that places the social determinants of exposure, severe disease and mortality on an equal footing with the biological features of transmission and disease progression. Our overarching goal is to develop a set of tools that will extend lessons from the COVID-19 pandemic to prevent similar disparities in future outbreaks, epidemics, and pandemics. The first aim of this project will develop and analyze transmission models that integrate the joint social and biological drivers of infection disparities. This proposed work will identify etiologic factors driving disparities in infection risk and propose alternative approaches to measuring infection disparities. Our second aim will evaluate the sensitivity of population-based prospective and observational study designs to socioeconomic disparities in infection risk and outcomes. We will use simulation studies with input parameters derived from the analysis of detailed SARS-CoV-2 case data to understand the circumstances under which these study designs obscure key dimensions of disparity. The third aim will assess long-term effects of vaccination policies, behavior, and interventions on population-level infection disparities. As the COVID-19 vaccination campaign has progressed it has become clear that vaccine access and behavior are interacting risks for sustaining population immunity. We will integrate survey data on vaccine behavior with data on healthcare access and SARS-CoV-2 incidence to parameterize a spatial transmission model highlighting heterogeneity in risks and avenues for closing these gaps for COVID-19 and other vaccine preventable diseases. Taken together, the proposed projects will lay the foundation systems modeling tools that can be used to improve future epidemic and pandemic responses.