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Ecological niche models for sand fly species and predicted distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in Bahia state, Brazil

de Santana Martins Rodgers, Moara, Bavia, Maria Emilia, Fonseca, Eduardo Oyama Lins, Cova, Bruno Oliveira, Silva, Marta Mariana Nascimento, Carneiro, Deborah Daniela Madureira Trabuco, Cardim, Luciana Lobato, Malone, John B.
Environmental monitoring and assessment 2019 v.191 no.Supplement 2 pp. 331
CDC light traps, Lutzomyia longipalpis, atmospheric precipitation, models, moderate resolution imaging spectroradiometer, monitoring, niches, normalized difference vegetation index, prediction, public health, remote sensing, resource allocation, risk factors, surface temperature, visceral leishmaniasis, Brazil
Visceral leishmaniasis is a public health problem in Brazil. This disease is endemic in most of Bahia state, with increasing reports of cases in new areas. Ecological niche models (ENM) can be used as a tool for predicting potential distribution for disease, vectors, and to identify risk factors associated with their distribution. In this study, ecological niche models (ENMs) were developed for visceral leishmaniasis (VL) cases and 12 sand fly species captured in Bahia state. Sand fly data was collected monthly by CDC light traps from July 2009 to December 2012. MODIS satellite imagery was used to calculate NDVI, NDMI, and NDWI vegetation indices, MODIS day and night land surface temperature (LST), enhanced vegetation index (EVI), and 19 Bioclim variables were used to develop the ENM using the maximum entropy approach (Maxent). Mean diurnal range was the variable that most contributed to all the models for sand flies, followed by precipitation in wettest month. For Lutzomyia longipalpis (L. longipalpis), annual precipitation, precipitation in wettest quarter, precipitation in wettest month, and NDVI were the most contributing variables. For the VL model, the variables that contributed most were precipitation in wettest month, annual precipitation, LST day, and temperature seasonality. L. longipalpis was the species with the widest potential distribution in the state. The identification of risk areas and factors associated with this distribution is fundamental to prioritize resource allocation and to improve the efficacy of the state’s program for surveillance and control of VL.