Visceral leishmaniasis and HIV coinfection in Brazil: epidemiological profile and spatial patterns

Background Geographical overlap of human visceral leishmaniasis (HVL) and HIV infection favors occurrences of HVL/HIV coinfection. The increasing numbers of cases of HVL/HIV coinfection are a worldwide concern and knowledge of the factors involved can help in developing preventive measures. Methods We aimed to identify spatial patterns and describe the epidemiological profile of HVL/HIV coinfection in Brazil from 2007 to 2015. This was an ecological study, in which thematic maps were created through geoprocessing tools, based on secondary data obtained from open-access platforms, to identify priority areas for interventions for controlling HLV/HIV coinfection, using the TerraView 4.2.2 software. Results We found spatial autocorrelations between the HVL/HIV rates of neighboring municipalities according to the global Moran index (0.10; p<0.01). The highest HVL/HIV rate was in the central-western region. Among the epidemiological characteristics according to the regions, an increasing trend in the annual variation rate was observed, with positive values over the years and statistical significance (p<0.05) in the North with 1.62 (95% CI 0.57 to 2.69; p=0.02) and Northeast with 6.41 (95% CI 2.60 to 10.37; p=0.006). Similarly, increasing trends were observed in the states of Maranhao with 21.34 (95% CI 13.99 to 9.16; p<0.001) and Sergipe with 5.44 (95% CI 0.61 to 10.50; p=0.04). Conclusions Our results showed spatial overlap between occurrences of HVL and HIV with spatial patterns of HVL/HIV coinfection, thus revealing that the numbers of cases reported are increasing. Identifying areas with higher coinfection indices contributes to applying interventions and control measures among targeted populations, to prevent new cases.

Automated summary

This study identified the spatial patterns of HVL/HIV coinfection in Brazil and found an increasing trend in the number of cases. The central-western region and the North and Northeast regions had higher rates of coinfection. This information can be used to target interventions and control measures to prevent new cases.