Online

Langle-Chimal, Ollin Demian

Complex Systems and Data Science

2023

Ph. D.

This dissertation focuses on the exploration of societal responses to crises, with a particular interest in existing socio-economic disparities, using tools of data science and mathematical modeling. The scope of the research is comprised predominantly around the COVID-19 pandemic, incorporating an in-depth analysis across six middle-income countries; Brazil, Colombia, Indonesia, Mexico, Philippines, and South Africa. With GPS data of approximately three million users, we found significant differences in the adherence to stay-at-home guidelines, revealing a great contrast between individuals in high-wealth and low-wealth areas, showing the disparities of who were more able to stay at home without risking their livelihood. A closer look at Mexico reveals the economic disparities and economic resilience of groups during the pandemic. By using multiple data sources - GPS mobility data, bank expenditure data, and official employment data - we present a diverse landscape of the economic impact. We use a novel approach for estimating informality at subnational levels every quarter, helping us to understand societal factors that influence economic shocks in the society, and providing unique insights. In the final part of the dissertation, a game simulating the spread of an infectious disease is used to study decision-making processes in terms of biosecurity investment. The insights gained from this analysis offer a deeper understanding of human risk behavior and its implications for public health. Our findings not only shed light on the disparities amplified by crises, but also provide valuable evidence for the development of targeted interventions that can better manage future crises. These findings highlight the pivotal role of data science and mathematical modeling in enhancing our ability to respond equitably in times of crisis.