Ovipositional Reproduction of the Dengue Vector for Identifying High-Risk Urban Areas.

Autor: de Oliveira Lage M; Universidade de São Paulo - USP, PROCAM USP - Programa de Pós-Graduação em Ciências Ambientais, Av. Prof. Luciano Gualberto, 1289, Cidade Universitária, Butantã, São Paulo, SP, CEP: 05508-090, Brazil. mariana_lage@usp.br., Barbosa G; Superintendência de Controle de Endemias - SUCEN, R. Paula Sousa, Centro, São Paulo, SP, 166 - CEP: 01027-000 Centro, Brazil., Andrade V; Superintendência de Controle de Endemias - SUCEN, R. Paula Sousa, Centro, São Paulo, SP, 166 - CEP: 01027-000 Centro, Brazil., Gomes H; Superintendência de Controle de Endemias - SUCEN, R. Paula Sousa, Centro, São Paulo, SP, 166 - CEP: 01027-000 Centro, Brazil., Chiaravalloti F; Universidade de São Paulo - USP, FSP USP - Programa de Pós-Graduação em Saúde Pública, Av. Dr. Arnaldo, 715. CEP: 03178-200 Cerqueira César, São Paulo, SP, Brazil., Quintanilha JA; Institute of Energy and Environment - IEEUSP, Universidade de São Paulo - USP, Av. Prof. Luciano Gualberto, 1289, Cidade Universitária, Butantã, São Paulo, SP, CEP: 05508-090, Brazil.
Jazyk: angličtina
Zdroj: EcoHealth [Ecohealth] 2022 Mar; Vol. 19 (1), pp. 85-98. Date of Electronic Publication: 2022 Apr 19.
DOI: 10.1007/s10393-022-01581-z
Abstrakt: Identification and classification of high-risk areas for the presence of Aedes aegypti is not an easy task. To develop suitable methods to identify this areas is an essential task that will increase the efficiency and effectiveness of control measures and to optimize the use of resources. The objectives of this study were to identify high- risk areas for the presence of Ae. aegypti using mosquito traps and household visits to identify breeding sites; to identify and validate aspects of the remote sensing images that could characterize these areas; to evaluate the relationship between this spatial risk classification and the occurrence of Ae. aegypti; and provide a methodology to the health and control vector services and prioritize these areas for development of control measure. Information about the geographical coordinates of these traps will enable us to apply the kriging spatial analysis tool to generate maps with the predicted numbers of Ae. aegypti. Satellite images were used to identify the characteristic features the four areas, so that other areas could also be classified using only the sensing remote images. The developed methodology enables the identification of high-risk areas for Ae. aegypti and for the occurrence of Dengue, as well as Zika fever and Chikungunya fever using only sensing remote images. These results allow health and vector control services to prioritize these areas for developing surveillance and control measures. The use of the available resources can be optimized and potentially promote a decrease in the expected incidences of these diseases, particularly Dengue.
(© 2022. EcoHealth Alliance.)
Databáze: MEDLINE
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