Modeling the Pandemic: Challenges and Responses

This lecture delves into the complexities of modeling the COVID-19 pandemic, exploring the challenges and hopes associated with building accurate models. The instructors discuss the difficulties in data collection, such as ascertainment bias, and the importance of utilizing various data sources, from public to private. They analyze the impact of different lockdown measures and the community response to rising case numbers. Through stochastic and multinomial models, they aim to predict the spread of the virus and manage hospital logistics effectively. The lecture also covers the use of Google and Apple mobility data to understand changes in human activity during the pandemic.