Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques
The findings emphasize the importance of integrating climate-driven forecasting tools to predict the abundance of mosquitoes where data are available. Furthermore, this study highlights the critical need for ongoing entomological surveillance to enhance mosquito spread forecasting and contribute to the development and assessment of effective vector control strategies in regions of mosquito expansion.
Authors
- Ana L. García‐Pérez (ORCID: https://orcid.org/0000-0001-7404-1380)
- Aitor Cevidanes (ORCID: https://orcid.org/0000-0003-1874-6399)
- Nico Stollenwerk (ORCID: https://orcid.org/0000-0001-9315-5586)
- Maíra Aguiar (ORCID: https://orcid.org/0000-0001-8354-9944)
- Vanessa Steindorf (ORCID: https://orcid.org/0000-0002-0707-9511)
- Patricia Vázquez (ORCID: https://orcid.org/0000-0002-5392-6451)
- Jesús F. Barandika
- H B (ORCID: https://orcid.org/0000-0002-7304-0922)
Institutions
- Ikerbasque (ES)
- Basque Center for Applied Mathematics (ES)
- Euskadiko Parke Teknologikoa (ES)
Publication Details
- Journal
- Parasites & Vectors
- Published
- 2025-03-15
- DOI
- https://doi.org/10.1186/s13071-025-06733-y
- Citations
- 4
- Primary Topic
- Mosquito-borne diseases and control
- Type
- article
- Field-Weighted Citation Impact
- 7.51
Funders
- Eusko Jaurlaritza