We propose a mathematical TB model that includes exogenous reinfection to gain a better understanding of the recent trend for TB incidence. We divide the simulation time window into two periods, 1970-2000 and 2001-2012, according to the implementation date of a new TB detection system.
Two sets of parameters, including the transmission rate, the latent period, the recovery rate, and the proportion of exogenous reinfection, are estimated using the least-squares method and calibrated to data on the incidence of active TB.
Among some key parameters in the model, the case finding effort turned out to be the most significant impacting component on the reduction in the active TB cases.