Proposing a Compartmental Model for Leprosy and Parameterizing Using Regional Incidence in Brazil

Hansen’s disease (HD), or leprosy, is still considered a public health risk in much of Brazil. Understanding the dynamics of the infection at a regional level can aid in identification of targets to improve control. A compartmental continuous-time model for leprosy dynamics was designed based on understanding of the biology of the infection. The transmission coefficients for the model and the rate of detection were fit for each region using Approximate Bayesian Computation applied to paucibacillary and multibacillary incidence data over the period of 2000 to 2010, and model fit was validated on incidence data from 2011 to 2012. Regional variation was noted in detection rate, with cases in the Midwest estimated to be infectious for 10 years prior to detection compared to 5 years for most other regions. Posterior predictions for the model estimated that elimination of leprosy as a public health risk would require, on average, 44–45 years in the three regions with the highest prevalence. The model is easily adaptable to other settings, and can be studied to determine the efficacy of improved case finding on leprosy control.Author Summary: Control of Hansen’s disease, or leprosy, requires understanding how quickly the infection moves through the population and how long it takes to detect the disease. These rates vary regionally, resulting in differences in the number of people detected with disease each year. We have estimated the risk of infection and the rate of detection for this disease in each of the 5 regions of Brazil. This allowed us to predict the long-term impact of Brazil’s current leprosy control program, which found that some regions of Brazil will require 44–45 years to eliminate leprosy as a public health risk, primarily due to the long delay in detection of cases.