ArticleScientific reports2024
Assessing and correcting neighborhood socioeconomic spatial sampling biases in citizen science mosquito data collection.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Beyond the Mosquito: Social Determinants of Health and Global Strategies for Aedes-Borne Disease Control.Tropical medicine & international health : TM & IH · 2026Pooled it
- Accounting for spatial and environmental sampling bias in a species distribution model of Aedes vexans (Diptera: Culicidae).Scientific reports · 2026Article
- Tracking the Asian tiger mosquito (Aedes albopictus) in Austria: benefits of combining expert-based monitoring with citizen science data.Parasites & vectors · 2026Article
- New technologies for identification and surveillance of Chagas disease vectors.Revista da Sociedade Brasileira de Medicina Tropical · 2026Review
- The role of citizen science in mosquito-borne disease surveillance and control: A scoping review.PloS one · 2026Article
- Understanding the social determinants of Aedes-borne diseases in Iran: A qualitative exploration of challenges and policy solutions.PLoS neglected tropical diseases · 2025Article
- Strengthening resilience to emerging vector-borne diseases in Europe: lessons learnt from countries facing endemic transmission.The Lancet regional health. Europe · 2025Review
- Assessing and correcting neighborhood socioeconomic spatial sampling biases in citizen science mosquito data collection.Scientific reports · 2024Article
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Authors and funding
6 authors.
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Abstract
Climatic, ecological, and socioeconomic factors are facilitating the spread of mosquito-borne diseases, heightening the importance of vector surveillance and control. Citizen science is proving to be an effective tool to track mosquito populations, but methods are needed to detect and account for small scale sampling biases in citizen science surveillance. In this article we combine two types of traditional mosquito surveillance records with data from the Mosquito Alert citizen science system to explore the ways in which the socioeconomic characteristics of urban neighborhoods result in sampling biases in citizen scientists' mosquito reports, while also shaping the spatial distribution of mosquito populations themselves. We use Barcelona, Spain, as an example, and focus on Aedes albopictus, an invasive vector species of concern worldwide. Our results suggest citizen scientists' sampling effort is focused more in Barcelona's lower and middle income census tracts than in its higher income ones, whereas Ae. albopictus populations are concentrated in the city's upper-middle income tracts. High resolution estimates of the spatial distribution of Ae. albopictus risk can be improved by controlling for citizen scientists' sampling effort, making it possible to provide better insights for efficiently targeting control efforts. Our methodology can be replicated in other cities faced with vector mosquitoes to improve public health responses to mosquito-borne diseases, which impose massive burdens on communities worldwide.
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