RAPID: Characterization of Pathogens in Water, Soil and Animal Facilities for Resilience Assessment of Civil Infrastructure After Extreme Weather Events

飓风佛罗伦萨在北卡罗来纳州造成大面积洪水。饲养了数千头猪和数百万只鸡的设施被淹没，导致猪粪便、粪便、动物残留物扩散，并可能将危险的病原体释放到水中。在依赖农业的沿海地区，飓风后的淹没可能导致一种或多种疾病的爆发，极端自然事件对人类和动物基础设施的联合影响尚未得到研究。健全的民用基础设施（动物收容所、水分配和处理系统、交通运输和动物粪便泻湖）对于尽量减少这些相互作用和限制自然灾害后疾病的爆发至关重要。直到报告了少数人感染病例后，通常才开始对广泛的病原体进行监测和检测。这个快速反应研究（Rapid）项目将收集关于病原体存在和丰度的关键数据，这些数据通常被假设为相反的，从而导致预防和遏制疾病爆发的反应性资源分配战略可能不准确。该RAPID项目的目标是利用基因组流行病学结合生物信息学和计算系统发育分析来跟踪病原体来源和在水体中的扩散，以创建空间致病谱。将系统地在被淹农场附近收集水和土壤样本，上游地点作为对照。现场数据收集和相关分析的结果将提供有关水中病原体丰度、存在和来源的数据，以评估所研究地区水基础设施的功能。病原体概况将与人口、社会人口统计、基础设施损害信息和快速洪水模型的数据相结合，以制定一个初步指数，该指数将表征受影响区域疾病暴发的空间风险。该分析将有助于指导将对策（基础设施恢复、药品、紧急人员、救济和清洁水供应）的重点放在何处，以控制感染风险。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Hurricane Florence caused extensive flooding in North Carolina. Facilities housing thousands of pigs and millions of chickens were flooded, causing the spread of the hog waste, manure, animal residue and potentially releasing dangerous pathogens into the water. The inundation after hurricanes may lead to the outbreak of one or more In agricultural-dependent coastal regions and the joint impact of extreme natural events on human and animal infrastructure has not been studied. A robust civil infrastructure (animal shelters, water distribution and treatment systems, transportation, and animal waste lagoons) is critical to minimize these interactions and to limit the outbreak of diseases after a natural disaster. Surveillance and detection of a broad range of pathogens are not usually initiated until a few human cases of infection are reported. This Rapid Response Research (RAPID) project will collect key data on the presence and abundance of pathogens, which are often assumed otherwise, leading to potentially inaccurate reactive resource allocation strategies for disease outbreak prevention and containment.The objective of this RAPID project is to use genomic epidemiology combined with bioinformatics and computational phylogenetic analyses to track pathogen sources and dispersal in water bodies to create spatial pathogenic profiles. Water and soil samples will be systematically collected near flooded farms with upstream locations serving as controls. Results from field data collection and associated analysis will provide data on the abundance, presence, and source of pathogens in water to assess the functionality of water infrastructure in the studied regions. The pathogen profiles will be combined with the human population, socio-demographics, infrastructure damage information, and data from a rapid flood model to develop a preliminary index which will characterize the spatial risk of disease outbreaks in the affected region. The analysis will help provide guidance on where to focus countermeasures (infrastructure rehabilitation, medicines, emergency personal, relief, and clean water supplies) to contain the risk of infection.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.