EMERGING AND RE-EMERING INFECTIOUS DISEASES AND THEIR SOCIAL CONTEXTS

Abstract

This dissertation explores contemporary challenges in re-/emerging infectious diseases and their social drivers and impacts, focusing on the COVID-19 pandemic and the infectious disease consequences of climate change. Chapter I presents the first multidecade climate-mortality study of a non-South African sub-Saharan African city, concentrating on enteric infectious diseases in Antananarivo, Madagascar. Utilizing vital registration data and non-parametric models, I reveal an increasing risk of mortality following heavy rainfall events over time. Given the anticipated increase in frequency and severity of such events due to climate change, these findings underscore the vulnerability of Antananarivo to mortality from re-emerging climate-sensitive diseases. In Chapter II, I analyze the impact of COVID-19-related travel restrictions on migration, focusing on migrants from North and West Africa. Employing digital trace data and dynamic linear panel models, I uncover a paradoxical increase in migrants in countries implementing these restrictions. This suggests that a commonly-used set of pandemic-response policies may be ineffective in achieving their intended goals, highlighting the need for effective policies that take the needs of migrants into account. Finally, Chapter III uses mechanistic epidemiological models to address the empirical challenge of disentangling the roles of interventions like social distancing and vaccination from pre-existing social conditions in the production of COVID-19 mortality gradients in Brazil, arising from a lack of counterfactual evidence from a scenario in which no interventions were implemented to control its spread. This is the first study to incorporate novel theoretical frameworks dissecting the pathways contributing to social gradients in emerging infectious disease mortality into mechanistic epidemiological models, and the first to model the socio-economic drivers of COVID mortality inequalities in Brazil on a national scale, with geospatial specificity, while utilizing real-world data-informed parameters. Parameterizing the model using census, survey, death registration, epidemiological surveillance, and digital trace data, I find that pre-existing social inequities were most responsible for producing COVID-19 mortality disparities, which were further exacerbated by unequally implemented interventions. However, the impacts of these pre-existing inequities could have been counteracted by intervention strategies prioritizing the most disadvantaged. These findings offer insights that could inform more equitable responses to future infectious disease epidemics.