CMSA Computer Science for Mathematicians: Population-Scale Study of Human Needs and Disparities During the COVID-19 Pandemic
Jina Suh - Microsoft Research and University of Washington
Most work to date on mitigating the COVID-19 pandemic is focused urgently on biomedicine and epidemiology. However, pandemic-related policy decisions cannot be made on health information alone but need to consider the broader impacts on people and their needs. In addition, understanding the disparate impacts of the pandemic and its policies on a full spectrum of human needs, especially for vulnerable populations, is critical for designing response and recovery efforts for major disruptions. Quantifying human needs across the population is challenging as it requires high geo-temporal granularity, high coverage across the population, and appropriate adjustment for seasonal and other external effects. Quantifying disparities across population groups require careful disentanglement of key factors that are engrained in our societal structure. In this talk, I will present computational approaches to leveraging web search interactions as a unique lens through which to examine changes in human needs as well as disparities in the expression of those needs during the COVID-19 pandemic. Grounding our analyses on well-established frameworks of human needs and social determinants of health, I will demonstrate how web search interactions can be used to enhance and complement our understanding of human behaviors during global crises.