Spatial and temporal modeling of the global burden of Cutaneous Leishmaniasis in Brazil: A 21-year ecological study.

Abstract

BackgroundCutaneous Leishmaniasis (CL) is a neglected tropical disease endemic in Brazil. Morbidity and disabilities caused by CL lesions require an analysis of a Global Burden of Disease (GBD), which would help discern the impact on the Brazilian population. Herein, we assess the burden of CL and its spatial and temporal patterns in Brazil between 2001 and 2021.Methodology/principal findingsWe estimated rates per 100,000 population for years lived with disabilities (YLD), years of life lost prematurely (YLL) and disability-adjusted life years (DALY) for each year of the study, sex assigned at birth, age group, and for each municipality in Brazil. In addition, the relative changes in these metrics over time for each region and sex were determined, as well as temporal trends using segmented joinpoint regression models. Using spatiotemporal analysis tools, we created choropleth maps representing DALY, YLD and YLL for three distinct periods (P1 = 2001 to 2007; P2 = 2008 to 2014; P3 = 2015 to 2021). These maps were constructed to visualize the inferences from Bayesian spatial statistics and Moran's autocorrelation using the Poisson model. The data were obtained from the DATASUS database. Although the global burden of CL has reduced over two decades, with the continual high impact among adults aged 20 to 39 years. In turn, YLL increased over time in 40-year-old populations, while among the elderly (>60 years old) this rate almost doubled from 2010 to 2021. Regarding the region of residence, we observed an average increase of 28% in YLL in Southeast, South and Central-West. Furthermore, the global burden of CL does not have a random spatial distribution, since there was a high-risk clustering of YLD in the north of the country. Interestingly, the YLL showed a vast geographic expansion through Brazilian territory.ConclusionsThis study provides a comprehensive analysis of the burden of CL in Brazil, pointing out areas of highest disease burden, where control and surveillance efforts should be undertaken.