Socio-Economic and Clinical Drivers of COVID-19 Mortality: An Empirical Analysis of the Supply-side and Demand-side Moderators

Abstract

The COVID-19 pandemic has disrupted everyday life globally, with severe consequences in several countries and regions. A key concern related to the COVID-19 pandemic is the wide variation in mortality across nations and sub-national locations such as states and counties. Anecdotal evidence, as well as evidence from CDC, indicates that the risk of spread as well as the risk of mortality from the pandemic is higher for regions with a population characterized by disadvantaged economic (income) and racial (underserved communities) and demographic profiles (age). Multiple studies have indicated that the most crucial step toward reducing mortality is expanding critical care capacity through procuring personal protective equipment (PPE) and ventilators and training critical care frontline employees. It is projected that with exponential growth in the pandemic spread, many regions would fall short of critical care capacity, increasing mortality.Furthermore, the pandemic has imposed high levels of constraints on resource availability, even in developed nations. Under resource constraints in critical care delivery, mitigation strategies need to account for the variation in observed cases and the disparity in mortality across locations. In my dissertation, I make a concerted effort to contribute toward understanding the sources of variation in mortality and propose a framework that enables pandemic preparedness and mitigation strategies that encapsulate the spatial and temporal variation in risk of mortality from COVID-19. The mitigation strategies are divided into supply-side and demand-side moderators of mortality. Accordingly, I focus on two mitigation strategies: (i) ICU capacity as a supply-side moderator and (ii) Vaccination coverage as a demand-side moderator. The overarching objective of my dissertation is to understand the role of supply-side and demand-side moderators of mortality, independently and jointly, of the association between socio-economic, demographic (henceforth referred to as social), and clinical risk factors and COVID-19 mortality. Much of the epidemiological literature on COVID-19 has focused on reducing the spread. However, the ultimate goal is to reduce mortality. There is a necessity in both practice and academic literature to understand actionable policies that can reduce mortality in general and spatial variation of mortality in specific. This dissertation research primarily leverages empirical methodology combining matching procedures with fixed effect modeling of panel data to test the hypothesized relationships of interest.