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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Predicting Aedes aegypti infestation using landscape and thermal features

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Autor(es):
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Lorenz, Camila [1] ; Castro, Marcia C. [2] ; Trindade, Patricia M. P. [3] ; Nogueira, Mauricio L. [4] ; Lage, Mariana de Oliveira [5] ; Quintanilha, Jose A. [5] ; Parra, Maisa C. [4] ; Dibo, Margareth R. [6] ; Favaro, Eliane A. [4] ; Guirado, Marluci M. [7] ; Chiaravalloti-Neto, Francisco [1]
Número total de Autores: 11
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Dept Epidemiol, Sch Publ Hlth, Av Dr Arnaldo, BR-715 Sao Paulo, SP - Brazil
[2] Harvard TH Chan Sch Publ Hlth, Dept Global Hlth & Populat, Boston, MA - USA
[3] Natl Inst Space Res INPE, Southern Reg Ctr, Santa Maria, RS - Brazil
[4] Fac Med Sao Jose do Rio Preto, Virol Res Lab, Sao Jose Do Rio Preto, SP - Brazil
[5] Univ Sao Paulo, Inst Energy & Environm IEE, Sci Div Management Environm Sci & Technol, Sao Paulo, SP - Brazil
[6] Endem Control Superintendence, Entomol Lab, Sao Paulo, SP - Brazil
[7] Endem Control Superintendence, Vectors Lab, Sao Jose Do Rio Preto, SP - Brazil
Número total de Afiliações: 7
Tipo de documento: Artigo Científico
Fonte: SCIENTIFIC REPORTS; v. 10, n. 1 DEC 10 2020.
Citações Web of Science: 0
Resumo

Identifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of SAo Jose do Rio Preto, SAo Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction. (AU)

Processo FAPESP: 17/10297-1 - Identificação de áreas de risco para arboviroses utilizando armadilhas para adultos de Aedes aegypti e Aedes albopictus e imagens de sensoriamento remoto
Beneficiário:Camila Lorenz
Linha de fomento: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 13/21719-3 - Estudo epidemiológico da dengue (sorotipos 1 a 4) em coorte prospectiva de São José do Rio Preto, São Paulo, Brasil, durante 2014 a 2018
Beneficiário:Maurício Lacerda Nogueira
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 19/08205-7 - Uso do sensoriamento remoto para mapear áreas de infestação por fêmeas adultas de Aedes aegypti
Beneficiário:Camila Lorenz
Linha de fomento: Bolsas no Exterior - Estágio de Pesquisa - Pós-Doutorado