UC Berkeley

The study of infectious disease is more than how pathogens transmit between hosts and cause illness and death. Infectious diseases are social, political, environmental, and infrastructural phenomena that humans have limited but equal power to eradicate or to exacerbate. Using modern disease modeling methods, researchers have the ability to test our assumptions about disease dynamics and to explore ways in which our behavior may help or hurt, and to imagine a better world with effective interventions. In this dissertation I focus on three applications of such models to two diseases: an evaluation of vaccine distribution and long-term seasonality of SARS-CoV-2, the pathogen causing the COVID-19 pandemic, and Chagas Disease, a parasitic infection in Brazil that despite its relative infrequency, has the potential to cause debilitating and fatal complications. In all studies, I focus on the heterogeneous risk of transmission and infection present in the population with an eye towards disease-averting interventions.In Chapter 1, I find that distributing vaccines for COVID-19 in decreasing priority by age is a more effective strategy to limit deaths than prioritizing by high-contact employment status, consistent with the CDC’s recommendations in early 2021. In the second chapter, I continue the analysis of SARS-CoV-2 using an Agent-Based Network Simulation, finding that recurrent outbreaks of the disease are likely to persist but, depending on the epidemiology of the pathogen, may be mitigated by annual booster doses distributed at certain times of year. Finally, I conclude in chapter 3 by finding that cases of Acute Chagas Disease may be expected to increase over the ensuing decade, driven by an increasing population in affected areas and changing climate.