ArticleScientific reports2026
Unravelling the activity rhythms of urban vector mosquitoes with smart-trap technology.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- The CRISPR-Cas toolkit for mosquito-borne virus surveillance: detection, tracing, and discovery.Frontiers in cellular and infection microbiology · 2026Review
- High-resolution characterisation of diel activity rhythms inCurrent research in parasitology & vector-borne diseases · 2026Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding mosquito activity in dense urban areas is essential to assess human exposure to nuisance and health risks. We analyzed real-time mosquito data from four smart traps operating between 2021 and 2024 in Barcelona (NE Spain), focusing on the fine-scale temporal dynamics of two major urban vector species, Aedes albopictus and Culex pipiens. Both species exhibited consistent bimodal diel activity patterns aligned with sunrise and sunset, with species-specific differences in peak intensity and timing as well as seasonal fluctuations. Using a random forest framework, we identified light-related cues as primary activators of mosquito host-seeking activity; and light cues, temperature and rainfall also acting as modulators of activity, roles varying by species and temporal scale. This activator-modulator perspective illustrates how intrinsic circadian rhythms interact with extrinsic environmental drivers to determine mosquito activity across temporal scales. Our findings highlight the ecological value of high-resolution monitoring and the potential of next-generation surveillance tools to support early warning systems and evidence-based vector control in the context of smart cities.
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