Spatially Scalable Integrated Tick Vector/Rodent Reservoir Management to Reduce Human Risk of Exposure to Ixodes scapularis Ticks Infected with Lyme Disease Spirochetes
Spatially Scalable Integrated Tick Vector/Rodent Reservoir Management to Reduce Human Risk of Exposure to Ixodes scapularis Ticks Infected with Lyme Disease Spirochetes
批准号:
9336684
负责人:
Neeta Pardanani Connally
金额:
$49.77万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2020-08-31
中文摘要
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英文摘要
PROJECT SUMMARY
Effective tick control is an important public health measure for combating Lyme
disease. It is generally believed that the majority of Lyme disease cases are
acquired from ticks living in the peridomestic landscape, thereby placing
responsibility for disease prevention mostly at the local level, and especially on
individual householders. Despite several studies documenting effective
peridomestic tick control measures, human exposures to ticks are increasingly
common and cases of Lyme disease have not been reduced. This project aims to
bridge the gap between tick control research and human behavior by 1) assessing
the effectiveness of an integrated tick management (ITM) strategy applied to either
individual or contiguous residential properties, and 2) identifying patterns of human
activity within and outside of the peridomestic landscape that lead to encounters
with infected ticks. Our ITM approach will integrate the application of well-timed
sprays of tick-killing chemicals (to reduce host-seeking ticks) with installation of
rodent-targeted bait boxes (to reduce the prevalence of ticks carrying Lyme-
causing germs). This approach will be evaluated simultaneously at properties in
Lyme-endemic towns located in western Connecticut and southern Rhode Island.
Tick abundance will be compared between treated and untreated properties using
standard tick collecting methods. Human tick encounters will be recorded and
compared using a novel crowd-sourced reporting system (TickSpotters). Study
participants will be asked to document the location of their outdoor activity
throughout the day in easy-to-use digital journals. Expected outcomes of this
project are a reduction in the number of infected blacklegged ticks and
human tick encounters at residences receiving an integrated tick management
intervention, and an improved understanding of where people encounter ticks
both around human habitations and in public outdoor settings.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: