Exploratory COVID-19 Modeling: Because There Weren’t Already Enough Predictive COVID-19 Projects
Project Overview
This project explores the dynamics of the COVID-19 pandemic through three lenses: healthcare system strain, pandemic fatigue, and policy effectiveness. We developed predictive models for ICU utilization using LSTM and ensemble methods, achieving strong generalizability across countries and time periods. Pandemic fatigue was operationalized and detected using social media sentiment, policy data, and case trends, reaching over 89% balanced accuracy. We also applied causal and time-series methods, including wavelet coherence, to study the delayed effects of policy interventions.