Leprosy remains an important health problem in Brazil - the country register the second largest number of new leprosy cases each year, accounting for 14% of the world's new cases in 2019. Although there was increasing advances in leprosy surveillance worldwide, the true number of leprosy cases is expected to be much larger than the reported. Leprosy underreporting impair planning effective interventions and thoughful decisions about the distribution of financial and health resources. In this study, we estimated leprosy underreporting for each Brazilian microregion in order to guide effective interventions and resouce allocation to improve leprosy detection in the country. We extracted the number of new cases of leprosy from 2007 to 2015 and population and socioeconomic information from the 2010 Census for each Brazilian municipality and grouped data in microregions. We applied a Bayesian hierarchical model to obtain the best explicative model for leprosy underreporing using Grade 2 of leprosy-related disabilities as a proxy to explain the incidence rates. Then, we estimated the number of missing leprosy cases (underreported cases) and the corrected leprosy incidence rates for each Brazilian microrregion.
Estimating Under Reporting of Leprosy in Brazil using a Bayesian Approach
