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  Use of soil moisture active passive satellite data and WorldClim 2.0 data to predict the potential distribution of visceral leishmaniasis and its vector Lutzomyia longipalpis in Sao Paulo and Bahia states, Brazil

  Moara de Santana Martins Rodgers, Elivelton Fonseca, Prixia del Mar Nieto, John B. Malone, Jeffery C. Luvall, Jennifer C. McCarroll, Ryan Harry Avery, Maria Emilia Bavia, Raul Guimaraes, Xue Wen, Marta Mariana Nascimento Silva, Deborah D.M.T. Carneiro, Luciana Lobato Cardim

  08-06-2022

  https://doi.org/10.4081/gh.2022.1095

  1810

  PDF: 1089

  HTML: 68
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  Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes

  Verónica Andreo, Juan Rosa, Karina Ramos, O. Daniel Salomón

  06-05-2022

  https://doi.org/10.4081/gh.2022.1033

  1964

  PDF: 1111

  Appendix: 215

  HTML: 42
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  Epidemiological aspects and spatial distribution of human and canine visceral leishmaniasis in an endemic area in northeastern Brazil

  Roseane Campos, Márcio Santos, Gabriel Tunon, Luana Cunha, Lucas Magalhães, Juliana Moraes, Danielle Ramalho, Sanmy Lima, José Antônio Pacheco, Michael Lipscomb, Amélia Ribeiro de Jesus, Roque Pacheco de Almeida

  11-05-2017

  https://doi.org/10.4081/gh.2017.503

  6021

  PDF: 2320

  HTML: 1163

• Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis

  Prixia Nieto, John B. Malone, Maria E. Bavia

  115-126

  01-11-2006

  https://doi.org/10.4081/gh.2006.286

  2428

  PDF: 1031
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  There is more to satellite imagery than meets the eye

  Robert Bergquist, John B. Malone

  31-05-2022

  https://doi.org/10.4081/gh.2022.1106

  2968

  PDF: 714

  HTML: 34