An Agent-Based Model of COVID-19: Evaluating the Effects of Demographic Factors and Intervention Policies
Jonathan Huang, Berke Nuri
The purpose of the project is to discover how the prevalence and mortality of a pandemic change depending on a population's demographic factors as well as various intervention policies through a NetLogo agent-based model. This model will simulate how demographic factors affect the course of COVID-19 (infection rate, recovery rate, and death rate). Demographic factors of interest will include population density, GDP per capita, age distribution, and number of hospital beds per capita. Intervention policies include vaccination, social distancing, mask wearing, mass testing, and quarantining. Conclusions about the effect of demographic factors on the infection, recovery, and death rate will be based on comparative analysis among different case studies including U.S. states, cities, and communities.