281 - Global Mosquito Observations Dashboard (GMOD): integrating citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes

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 mosquito control personnel, researchers, and policymakers. This GIS mapping platform, the Global Mosquito Observations Dashboard (GMOD), is freely accessible at www.mosquitodashboard.org for visualizing and downloading data in various tabular and geospatial formats. 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 such as Aedes scapularis and Aedes vittatus. For mosquito control organizations, such citizen science efforts can contribute valuable surveillance data to complement traditional trapping methods and to validate habitat models. Additionally, we leveraged pooled image data along with imagery generated in collaboration with the CDC, to develop a toolset of artificial intelligence (AI) algorithms for deployment in taxonomic and anatomical identification. The beta version of our AI tools for analyzing photos of larval and adult mosquitoes are freely available at www.mosquitoID.org, primarily targeting the urban malaria vector Anopheles stephensi that has recently invaded Africa. 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. [publication: bit.ly/3RyztIo]