AN AGENT-BASED SIMULATION OF A TUBERCULOSIS EPIDEMIC: UNDERSTANDING THE TIMING OF TRANSMISSION

Tuberculosis (TB) transmission is a key factor for disease-control policy, but the timing and distribution of transmission and the role of social contacts remain obscure. We develop an agent-based simulation of a TB epidemic in a single population, and consider a hierarchically structured contact network in three levels, typical of airborne diseases. The parameters are adopted from the literature, and the model is calibrated to a setting of high TB incidence. We model the dynamics of transmission at the individual level, and study the timing of secondary infections from a single source throughout the duration of the disease. We compare the patterns of transmission among different networks and discuss implications. Sensitivity analysis of outputs indicates the robustness of the results to variations in the parameter values.