Integrating citizen science and field sampling into next-generation early-warning systems for vector surveillance: twenty years of municipal detections of Aedes invasive mosquito species in Spain

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Eritja, Roger
• dc.contributor.author Sanpera Calbet, Isis
• dc.contributor.author Palmer, John R. B.
• dc.contributor.author Bartumeus, Frederic
• dc.date.accessioned 2025-10-20T07:16:20Z
• dc.date.available 2025-10-20T07:16:20Z
• dc.date.issued 2025
• dc.date.updated 2025-10-20T07:16:20Z
• dc.description.abstract The spread of the invasive mosquitoes Aedes albopictus, Aedes aegypti, and Aedes japonicus in Spain represents an increasing public health risk due to their capacity to transmit arboviruses such as dengue, Zika, and chikungunya, among others. Traditional field entomological surveillance remains essential for tracking their spread, but it faces limitations in terms of cost, scalability, and labor intensity. Since 2014, the Mosquito Alert citizen-science project has enabled public participation in surveillance through the submission of geolocated images via a mobile app, which are identified using AI in combination with expert validation. While field surveillance provides high accuracy, citizen science offers low-cost, large-scale, real-time data collection aligned with open data management principles. It is particularly useful for detecting long-distance dispersal events and has contributed up to one-third of the municipal detections of invasive mosquito species since 2014. This study assesses the value of integrating both surveillance systems to capitalize on their complementary strengths while compensating for their weaknesses in the areas of taxonomic accuracy, scalability, spatial detection patterns, data curation and validation systems, geographic precision, interoperability, and real-time output. We present the listing of municipal detections of these species from 2004 to 2024, integrating data from both sources. Spain's integrated approach demonstrates a pioneering model for cost-effective, scalable vector surveillance tailored to the dynamics of invasive species and emerging epidemiological threats.
• dc.format.mimetype application/pdf
• dc.identifier.citation Eritja R, Sanpera-Calbet I, Delacour-Estrella S, Ruiz-Arrondo I, Puig MA, Bengoa-Paulis M, et al. Integrating citizen science and field sampling into next-generation early-warning systems for vector surveillance: twenty years of municipal detections of Aedes invasive mosquito species in Spain. Insects. 2025 Sep;16(9):904. DOI: 10.3390/insects16090904
• dc.identifier.doi http://dx.doi.org/10.3390/insects16090904
• dc.identifier.issn 2075-4450
• dc.identifier.uri http://hdl.handle.net/10230/71564
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Insects. 2025 Sep;16(9):904
• dc.rights © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Aedes
• dc.subject.keyword Surveillance
• dc.subject.keyword Citizen science
• dc.subject.keyword Mosquito alert
• dc.subject.keyword Field sampling
• dc.subject.keyword Vector
• dc.subject.keyword Invasive
• dc.subject.keyword Disease
• dc.title Integrating citizen science and field sampling into next-generation early-warning systems for vector surveillance: twenty years of municipal detections of Aedes invasive mosquito species in Spain
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion