Dataset Information

Predicting Aedes aegypti infestation using landscape and thermal features.

ABSTRACT: 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 São José do Rio Preto, São 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.

SUBMITTER: Lorenz C

PROVIDER: S-EPMC7729962 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Predicting Aedes aegypti infestation using landscape and thermal features.

Lorenz Camila C Castro Marcia C MC Trindade Patricia M P PMP Nogueira Maurício L ML de Oliveira Lage Mariana M Quintanilha José A JA Parra Maisa C MC Dibo Margareth R MR Fávaro Eliane A EA Guirado Marluci M MM Chiaravalloti-Neto Francisco F

Scientific reports 20201210 1

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 São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegy ...[more]

PMID: 33303912

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Project description:BACKGROUND:Arbovirus transmission by the mosquito Aedes aegypti can be reduced by the introduction and establishment of the endosymbiotic bacteria Wolbachia in wild populations of the vector. Wolbachia spreads by increasing the fitness of its hosts relative to uninfected mosquitoes. However, mosquito fitness is also strongly affected by population size through density-dependent competition for limited food resources. We do not understand how this natural variation in fitness affects symbiont spread, which limits our ability to design successful control strategies. RESULTS:We develop a mathematical model to predict A. aegypti-Wolbachia dynamics that incorporates larval density-dependent variation in important fitness components of infected and uninfected mosquitoes. Our model explains detailed features of the mosquito-Wolbachia dynamics observed in two independent experimental A. aegypti populations, allowing the combined effects on dynamics of multiple density-dependent fitness components to be characterized. We apply our model to investigate Wolbachia field release dynamics, and show how invasion outcomes can depend strongly on the severity of density-dependent competition at the release site. Specifically, the ratio of released relative to wild mosquitoes required to attain a target infection frequency (at the end of a release program) can vary by nearly an order of magnitude. The time taken for Wolbachia to become established following releases can differ by over 2 years. These effects depend on the relative fitness of field and insectary-reared mosquitoes. CONCLUSIONS:Models of Wolbachia invasion incorporating density-dependent demographic variation in the host population explain observed dynamics in experimental A. aegypti populations. These models predict strong effects of density-dependence on Wolbachia dynamics in field populations, and can assist in the effective use of Wolbachia to control the transmission of arboviruses such as dengue, chikungunya and zika.

Dataset Information

Predicting Aedes aegypti infestation using landscape and thermal features.

Publications

Predicting Aedes aegypti infestation using landscape and thermal features.

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