ArticleEnvironmental monitoring and assessment2019
Ecological niche models for sand fly species and predicted distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in Bahia state, Brazil.
Article in Environmental monitoring and assessment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Regression Analysis of the Main Environmental Risk Factors for Mountainous Subtype of Zoonotic VL in China.Journal of tropical medicine · 2026Article
- Ecological niche and rickettsial risk mapping ofFrontiers in cellular and infection microbiology · 2026Article
- Canine leishmaniasis in the Atlantic Rainforest Biome region of Bahia, Brazil, affected by deforestation: a one health perspective.Revista brasileira de parasitologia veterinaria = Brazilian journal of veterinary parasitology : Orgao Oficial do Colegio Brasileiro de Parasitologia Veterinaria · 2026Article
- Climate change and its impact on spatial and temporal distribution of visceral leishmaniasis transmission risk in Nepal.BMC infectious diseases · 2025Article
- Circulation aspects of phlebotomines (Diptera:Journal of parasitic diseases : official organ of the Indian Society for Parasitology · 2025Article
- The Human Footprint and Climate Change Shape Current and Future Scenarios of Visceral Leishmaniasis Distribution in Doce River Basin in Brazil.The American journal of tropical medicine and hygiene · 2025Article
- Detection ofAnimals : an open access journal from MDPI · 2025Article
- Article
- Spatial and Temporal Variability of Visceral Leishmaniasis in Colombia, 2007 to 2018.The American journal of tropical medicine and hygiene · 2021Article
- The Effect of Geographical and Climatic Factors on the Distribution ofJournal of arthropod-borne diseases · 2021Article
- Lutzomyia longipalpis, Gone with the Wind and Other Variables.Neotropical entomology · 2021Review
- Predicted distribution of sand fly (Diptera: Psychodidae) species involved in the transmission of Leishmaniasis in São Paulo state, Brazil, utilizing maximum entropy ecological niche modeling.Pathogens and global health · 2021Article
- Space-time risk cluster of visceral leishmaniasis in Brazilian endemic region with high social vulnerability: An ecological time series study.PLoS neglected tropical diseases · 2021Article
- Feline Leishmaniasis Caused byFrontiers in veterinary science · 2021Article
- Niches of nine mangrove species in aEcology and evolution · 2020Article
- Geospatial technology in environmental health applications.Environmental monitoring and assessment · 2019Article
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Authors and funding
8 authors.
Funding
Abstract
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.
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