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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.
Afiliação
  • de Santana Martins Rodgers M; School of Veterinary Medicine, Department of Pathobiological Sciences, Louisiana State University, Skip Bertman Dr, Baton Rouge, LA, 70803, USA.
  • Bavia ME; Department of Preventive Veterinary Medicine, Universidade Federal da Bahia, Salvador, Brazil.
  • Fonseca EOL; Department of Entomology Surveillance, Laboratorio Central de Saúde Pública da Bahia (LACEN/BA), Salvador, Brazil.
  • Cova BO; Department of Entomology Surveillance, Laboratorio Central de Saúde Pública da Bahia (LACEN/BA), Salvador, Brazil.
  • Silva MMN; Department of Preventive Veterinary Medicine, Universidade Federal da Bahia, Salvador, Brazil.
  • Carneiro DDMT; Department of Preventive Veterinary Medicine, Universidade Federal da Bahia, Salvador, Brazil.
  • Cardim LL; School of Health, Universidade Salvador (UNIFACS), Salvador, Brazil.
  • Malone JB; School of Health, Universidade Salvador (UNIFACS), Salvador, Brazil.
Environ Monit Assess ; 191(Suppl 2): 331, 2019 Jun 28.
Article em En | MEDLINE | ID: mdl-31254126
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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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Psychodidae / Ecossistema / Insetos Vetores / Leishmaniose Visceral Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals País/Região como assunto: America do sul / Brasil Idioma: En Revista: Environ Monit Assess Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Psychodidae / Ecossistema / Insetos Vetores / Leishmaniose Visceral Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals País/Região como assunto: America do sul / Brasil Idioma: En Revista: Environ Monit Assess Ano de publicação: 2019 Tipo de documento: Article