Carney Ryan M, Mapes Connor, Low Russanne D, Long Alex, Bowser Anne, Durieux David, Rivera Karlene, Dekramanjian Berj, Bartumeus Frederic, Guerrero Daniel, Seltzer Carrie E, Azam Farhat, Chellappan Sriram, Palmer John R B
Department of Integrative Biology, University of South Florida (USF), Tampa, FL 33620, USA.
Woodrow Wilson International Center for Scholars, Washington, DC 20007, USA.
Insects. 2022 Jul 27;13(8):675. doi: 10.3390/insects13080675.
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.
蚊媒疾病每年仍在肆虐人类,造成超过7亿人感染,近100万人死亡。然而,在3500多种蚊子中,只有一小部分会传播疾病,因此需要进行广泛监测和精确识别。不幸的是,这些工作成本高昂、耗时且需要昆虫学专业知识。正如全球蚊子警报联盟所设想的那样,公民科学可以提供一个可扩展的解决方案。然而,迄今为止,现有平台之间不同的数据标准阻碍了真正的全球整合。在这里,我们利用开放地理空间联盟的标准,协调了来自三款成熟移动应用程序——蚊子警报、iNaturalist以及全球观察者组织的蚊子栖息地地图绘制与土地覆盖应用程序的四条数据流,以促进研究人员、蚊虫控制人员和政策制定者之间的互操作性和实用性。我们还开展了协调一致的媒体宣传活动,产生了前所未有的观察数量和类型,包括成功拍摄到目标入侵物种和病媒物种的首批图像。此外,我们利用汇总的图像数据开发了一套人工智能算法工具集,以备将来用于分类和解剖识别。最终,通过利用公民科学和人工智能的联合力量,我们建立了一个下一代监测框架,作为全球抗击蚊媒疾病持续威胁的统一战线。