Next generation mosquito control through technology-driven trap development and artificial intelligence guided detection of mosquito breeding habitats

项目摘要 每年约有4亿人因被伊蚊叮咬而感染一种虫媒病毒病 SPP蚊子。伊蚊。蚊子是主要的公共卫生威胁，因为它们对媒介的能力很强 多种病原体，它们咬人的偏好，以及它们适应新的国内环境的能力。在……里面 美国埃及伊蚊和白纹伊蚊种群的重新引入和建立 导致过去十年寨卡病毒、登革热和基孔肯雅热的局部流行。不幸的是，蚊子控制 美国的项目通常预算有限，迫使大多数杀虫剂喷洒 为应对人口暴露而不是有针对性的预防而进行，这也有助于 对杀虫剂有抵抗力的人口大幅增长，导致基础设施脆弱性差距扩大。 我们目前的提案旨在利用非健康学科的现有技术来推动蚊子 检测和消除。我们建议验证技术驱动的蚊子诱捕器的使用，这种诱蚊器允许高度- 对不同生命阶段的伊蚊进行吞吐量识别和计数，以便为决策提供依据 选择喷洒杀虫剂和减少杀虫剂的区域。此外，我们建议开发严格的远程 用于识别邻居级伊蚊丰度风险和快速检测个体的传感工作流 伊蚊在家庭层面上繁殖的栖息地。这一创新方案使用多年和现实世界 来自两个不同大都市地区的蚊子数据，以统计调整地理生态的差异， 城市小气候、季节气候模式和年度天气事件。我们的研究将导致低成本 立即准备好由全国病媒控制机构广泛分发和整合的工具。这个 我们的研究结果有望直接影响病媒控制机构的决策过程 选择诱蚊地点，告知预防性教唆方案，并缩短所需时间 蚊子采集和鉴定。此外，我们建议的技术陷阱和知情站点的集成 选择地图将增加总体采集量，同时为局部病媒生物控制保留稀缺资源 经纪公司。这一提议有可能在全球范围内改变我们处理媒介控制的方式， 通过有针对性的干预，产生显著的经济、环境和临床效益。

Project Summary Each year, approximately 400 million people are infected with an arboviral disease from the bite of an Aedes spp mosquito. Aedes spp. mosquitoes are a leading public health threat due to their high competency to vector multiple pathogens, their preference to bite humans, and their ability to adapt to new domestic environments. In the US, reintroduction and establishment of Aedes aegypti and Aedes albopictus mosquito populations has resulted in local epidemics of Zika, dengue and chikungunya in the past decade. Unfortunately, mosquito control programs in the US generally operate with limited budgets, forcing the majority of insecticide spraying to be conducted in reaction to population exposure instead of targeted prevention, which has also contributed to considerable growth of insecticide resistant populations, yielding a widening gap of infrastructure vulnerability. Our current proposal aims to leverage existing technologies from non-health disciplines to advance mosquito detection and abatement. We propose to validate the use of technology-driven mosquito traps that allow for high- throughput identification and counting of Aedes mosquitos at various life stages to inform decision making when selecting areas for insecticide spraying and abatement. Additionally, we propose to develop rigorous remote sensing workflows for identification of neighborhood-level Aedes abundance risk and rapid detection of individual Aedes mosquito breeding habitats on a household-level. This innovative proposal uses multi-year and real-world mosquito data from two different metropolitan areas to statistically adjust for variances in geographic ecologies, urban microclimates, seasonal climate patterns, and annual weather events. Our study will result in low-cost tools immediately ready for broad distribution and integration by vector control agencies nationally. The outcomes of our study have promise to directly impact vector control agency’s decision-making processes for mosquito trapping site selection, inform preventative abetment protocols, and shorten the time required for mosquito collection and identification. Further, integration of our proposed technology traps and informed site selection maps will increase overall collection volumes while preserving scarce resources for local vector control agencies. This proposal has the potential to create a paradigm shift in how we approach vector control globally, with a targeted intervention resulting in significant economic, environmental, and clinical benefits.