23rd Annual Student Research Conference
An Epidemiological Agent-Based Model of Tuberculosis
Ngoc Thai
Dr. Phil Ryan, Faculty Mentor
Tuberculosis (TB) is an often deadly disease, estimated to infect one-third of the world's population. Latently infected people may become clinically ill with active TB as a consequence of exogenous reinfection. Besides, doubly HIV/latent TB infected individuals are at a much greater risk of developing active TB. This project examines the dynamics of TB using agent-based modeling. We use NetLogo to design and implement complex epidemiological models of TB. The basic reproductive number, R0, a metric to help determine whether an infectious disease will spread through a population, is directly calculated in all of our models. Our sensitivity analysis of R0 suggests that the probability that an immune-competent individual contacts an infectious individual and receives infection is the most significant factor for the disease to remain endemic.
Keywords: Agent-Based Modeling, Tuberculosis, Disease Models
Topic(s):Mathematical Biology
Interdisciplinary
Presentation Type: Poster
Session: 7-4
Location: SUB-GEO
Time: 4:15