ArticleScientific reports2020
Predicting Aedes aegypti infestation using landscape and thermal features.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05893134 (Identification of Risk Determinants of Dengue Transmission Through Landscape Analysis in the Neighborhood "El Vergel", Tapachula, Chiapas), which is not on this map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Identification of Risk Determinants of Dengue Transmission Through Landscape Analysis in the Neighborhood "El Vergel", Tapachula, Chiapas
Who cites it
17 citing papers in PubMed, 54 citations in OpenAlex.
- How technologies are driving digital innovation in mosquito surveillance systems: a global scoping review over the past decade.BMJ public health · 2026Article
- Influence of climatic and land use factors on post-monsoon distribution of Aedes mosquito vectors in Udupi taluk.Scientific reports · 2025Observational
- Chikungunya clusters in the state of Bahia: influence of environmental and social factors.Revista da Sociedade Brasileira de Medicina Tropical · 2025Article
- Spatial and temporal characterization of Aedes albopictus oviposition activity in candidate urban settings for sterile insect technique testing in La Reunion Island.Infectious diseases of poverty · 2024Article
- The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city.BMC public health · 2024Article
- Exploring fine-scale urban landscapes using satellite data to predict the distribution of Aedes mosquito breeding sites.International journal of health geographics · 2024Article
- Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis.PLoS neglected tropical diseases · 2024Article
- Spatial analysis of dengue transmission in an endemic city in Brazil reveals high spatial structuring on local dengue transmission dynamics.Scientific reports · 2024Article
- An optical system to detect, surveil, and kill flying insect vectors of human and crop pathogens.Scientific reports · 2024Article
- Aedes aegypti abundance in urban neighborhoods of Maricopa County, Arizona, is linked to increasing socioeconomic status and tree cover.Parasites & vectors · 2023Article
- An Integrative Explainable Artificial Intelligence Approach to Analyze Fine-Scale Land-Cover and Land-Use Factors Associated with Spatial Distributions of Place of Residence of Reported Dengue Cases.Tropical medicine and infectious disease · 2023Article
- Entomo-VirologicalPathogens (Basel, Switzerland) · 2022Article
- Multidisciplinary approach for surveillance and risk identification of yellow fever and other arboviruses in Colombia.One health (Amsterdam, Netherlands) · 2022Article
- Association between densities of adult and immature stages of Aedes aegypti mosquitoes in space and time: implications for vector surveillance.Parasites & vectors · 2022Article
- Mapping the spatial distribution of the dengue vectorOne health (Amsterdam, Netherlands) · 2021Article
- Spatial Distribution ofInsects · 2021Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.