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

通过技术驱动的诱捕器开发和人工智能引导的蚊子繁殖栖息地检测来控制下一代蚊子

• 批准号: 10490916
• 负责人: Sarah Murphy Gunter
• 金额: $ 74.97万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-17 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10490916
• 关键词: Abate; Aedes; Algorithms; Aptitude; Arbovirus Infections; Arboviruses; Area; Artificial Intelligence; Bite; Breeding; Budgets; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; Chikungunya virus; Cities; Climate; Clinical; Collection; Comparative Study; Competence; Complex; Compost; Culicidae; Data; Decision Making; Dengue; Dengue Virus; Detection; Development; Discipline; Disease; Disease Outbreaks; Ecology; Economics; Environment; Environmental Health; Environmental Impact; Epidemic; Evaluation; Event; Eye; Food; Gases; Geography; Gravid; Growth; Habitats; Health; Health Benefit; Household; Human; Human Bites; Image Analysis; Imagery; Impairment; Individual; Industry; Infrastructure; Insecticide Resistance; Insecticides; Intervention; Lasers; Life; Location; Machine Learning; Manuals; Maps; Methods; Microclimate; Mosquito Control; Mosquito-borne infectious disease; Natural Disasters; Neighborhoods; Neurologic; Oils; Outcome; Pattern; Persons; Pilot Projects; Population; Prevention; Preventive vaccine; Process; Protocols documentation; Public Health; Reaction; Recovery; Reproducibility; Resolution; Resources; Risk; Robotics; Security; Sentinel; Side; Site; Solid; Sorting - Cell Movement; Surveillance Methods; System; Techniques; Technology; Testing; Time; Toy; United States National Aeronautics and Space Administration; Visualization; Weather; ZIKA; Zika Virus; atmospheric sciences; base; chikungunya; climate change; combat; cost; cost efficient; data standards; high risk; improved; indexing; innovation; machine learning model; meteorological data; metropolitan; next generation; novel; operation; pathogen; predictive modeling; predictive signature; preference; preservation; programs; prospective; rapid detection; remote sensing; therapeutically effective; tool; transmission process; vector; vector control; wasting; weather patterns

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.

项目概要 每年，大约有 4 亿人因伊蚊叮咬而感染虫媒病毒疾病 伊蚊是主要的公共卫生威胁，因为它们具有很强的媒介能力。 多种病原体、它们对叮咬人类的偏好以及它们适应新的家庭环境的能力。 在美国，埃及伊蚊和白纹伊蚊种群的重新引入和建立已 不幸的是，在过去十年中，导致了寨卡病毒、登革热和基孔肯雅热的局部流行。 美国的项目通常预算有限，迫使大部分杀虫剂喷洒工作 是为了应对人群暴露而不是有针对性的预防，这也导致了 抗杀虫剂种群大幅增长，导致基础设施脆弱性差距不断扩大。 我们当前的提案旨在利用非健康学科的现有技术来促进蚊子的发展 我们建议验证技术驱动的捕蚊器的使用，以实现高捕蚊率。 对不同生命阶段的伊蚊进行吞吐量识别和计数，以便在何时做出决策 此外，我们建议制定严格的远程喷洒杀虫剂区域。 用于识别社区级伊蚊丰度风险并快速检测个体的传感工作流程 这项创新提案使用了多年的真实世界的蚊子栖息地。 来自两个不同大都市区的蚊子数据，以根据地理生态的差异进行仔细调整， 我们的研究将带来低成本的城市微气候、季节性气候模式和年度天气事件。 工具立即可供全国病媒控制机构广泛分发和整合。 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，告知预防性刺激方案，并缩短诱捕所需的时间 此外，我们建议的技术陷阱和知情地点的整合。 选择图将增加总体收集量，同时保留用于当地病媒控制的稀缺资源 该提案有可能使我们在全球范围内进行病媒控制的方式发生范式转变， 有针对性的干预可带来显着的经济、环境和临床效益。