Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes

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• dc.contributor.author Carney, Ryan M.
• dc.contributor.author Mapes, Connor
• dc.contributor.author Low, Russanne D.
• dc.contributor.author Long, Alex
• dc.contributor.author Bowser, Anne
• dc.contributor.author Durieux, David
• dc.contributor.author Rivera, Karlene
• dc.contributor.author Dekramanjian, Berj
• dc.contributor.author Bartumeus, Frederic
• dc.contributor.author Guerrero, Daniel
• dc.contributor.author Seltzer, Carrie E.
• dc.contributor.author Azam, Farhat
• dc.contributor.author Chellappan, Sriram
• dc.contributor.author Palmer, John R. B.
• dc.date.accessioned 2023-05-05T06:17:16Z
• dc.date.available 2023-05-05T06:17:16Z
• dc.date.issued 2022
• dc.description.abstract Mosquito-borne diseases continue to ravage humankind with >700 million infections and nearly one million deaths every year. Yet only a small percentage of the >3500 mosquito species transmit diseases, necessitating both extensive surveillance and precise identification. Unfortunately, such efforts are costly, time-consuming, and require entomological expertise. As envisioned by the Global Mosquito Alert Consortium, citizen science can provide a scalable solution. However, disparate data standards across existing platforms have thus far precluded truly global integration. Here, utilizing Open Geospatial Consortium standards, we harmonized four data streams from three established mobile apps—Mosquito Alert, iNaturalist, and GLOBE Observer’s Mosquito Habitat Mapper and Land Cover—to facilitate interoperability and utility for researchers, mosquito control personnel, and policymakers. We also launched coordinated media campaigns that generated unprecedented numbers and types of observations, including successfully capturing the first images of targeted invasive and vector species. Additionally, we leveraged pooled image data to develop a toolset of artificial intelligence algorithms for future deployment in taxonomic and anatomical identification. Ultimately, by harnessing the combined powers of citizen science and artificial intelligence, we establish a next-generation surveillance framework to serve as a united front to combat the ongoing threat of mosquito-borne diseases worldwide.
• dc.description.sponsorship This research was funded by the National Science Foundation under Grant No. IIS-2014547 to R.M.C., S.C., R.D.L. and A.B. The GLOBE Observer app and citizen science programming are supported through National Aeronautics and Space Administration (NASA) cooperative agreement NNX16AE28A to the Institute for Global Environmental Strategies (IGES) for the NASA Earth Science Education Collaborative (NESEC, PI: Theresa Schwerin). F.B. and J.R.B.P. acknowledge funding from: (a) the European Commission, under Grants CA17108 (AIM-COST Action), 874735 (VEO), 853271 (H-MIP), and 2020/2094 (NextGenerationEU, through CSIC’s Global Health Platform, PTI Salud Global); (b) the Dutch National Research Agenda (NWA), under Grant NWA/00686468; and (c) “la Caixa” Foundation, under Grant HR19-00336.
• dc.format.mimetype application/pdf
• dc.identifier.citation Carney RM, Mapes C, Low RD, Long A, Bowser A, Durieux D, Rivera K, Dekramanjian B, Bartumeus F, Guerrero D, Seltzer CE, Azam F, Chellappan S, Palmer JRB. Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes. Insects. 2022;13(8):675. DOI: 10.3390/insects13080675
• dc.identifier.doi http://dx.doi.org/10.3390/insects13080675
• dc.identifier.issn 2075-4450
• dc.identifier.uri http://hdl.handle.net/10230/56689
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Insects. 2022;13(8):675.
• dc.relation.isreferencedby http://mosquitodashboard.org/
• dc.relation.isreferencedby http://mosquitoalert.com/en/access-to-mosquito-alert-data-portal
• dc.relation.isreferencedby http://mosquito-alert.github.io/metadata_public_portal/meta_ipynb/tigapics.html
• dc.relation.isreferencedby http://globe.gov/globe-data
• dc.relation.isreferencedby https://github.com/IGES-Geospatial
• dc.relation.isreferencedby http://geospatial.strategies.org/
• dc.relation.isreferencedby http://inaturalist.org/
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/874735
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/853271
• dc.rights © 2022 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 (https:// 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 artificial intelligence
• dc.subject.keyword citizen science
• dc.subject.keyword computer vision
• dc.subject.keyword geographic information systems
• dc.subject.keyword invasive species
• dc.subject.keyword machine learning
• dc.subject.keyword mosquito monitoring
• dc.subject.keyword smartphone
• dc.subject.keyword vector-borne disease
• dc.subject.keyword vector surveillance
• dc.title Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion