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 | Zendy

Moara de Santana Martins Rodgers | Zendy; Elivelton da Silva Fonseca | Zendy; Prixia Nieto | Zendy; John B. Malone | Zendy; Jeffery C. Luvall | Zendy; Jennifer C. McCarroll | Zendy; Ryan Avery | Zendy; Maria Emília Bavia | Zendy; Raúl Borges Guimarães | Zendy; Xue Wen | Zendy; Marta Mariascimento Silva | Zendy; Deborah Daniela Madureira Trabuco Carneiro | Zendy; Luciana Lobato Cardim | Zendy

Open Access

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

Author(s) -

Moara de Santana Martins Rodgers,

Elivelton da Silva Fonseca,

Prixia Nieto,

John B. Malone,

Jeffery C. Luvall,

Jennifer C. McCarroll,

Ryan Avery,

Maria Emília Bavia,

Raúl Borges Guimarães,

Xue Wen,

Marta Mariascimento Silva,

Deborah Daniela Madureira Trabuco Carneiro,

Luciana Lobato Cardim

Publication year - 2022

Publication title -

geospatial health

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.545

H-Index - 36

eISSN - 1970-7096

pISSN - 1827-1987

DOI - 10.4081/gh.2022.1095

Subject(s) - environmental science , visceral leishmaniasis , spatial distribution , precipitation , water content , environmental niche modelling , moisture , ecological niche , remote sensing , leishmaniasis , ecology , geography , meteorology , biology , habitat , geology , immunology , geotechnical engineering

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