Advancing One Health Data Capture at the Point of Zoonotic Spillover in the Congo Basin Forest Perimeter

项目摘要 由于人类对刚果盆地森林周边脆弱生态系统的侵蚀，人畜共患病的溢出 进入边境社区的病原体激增，并造成世界范围的影响。该地区的 布温迪密林，位于乌干达西南角，与刚果民主共和国接壤 刚果(金)是生物多样性的热点地区，是灵长类和蝙蝠物种最多的 非洲的森林。它还位于非洲人口最稠密的地区之一。医疗保健 该地区的设施仍在警惕埃博拉病毒病(EVD)或马尔堡出血热的爆发 (MHF)。考虑到最近在邻近地区确认的埃博拉疫情暴发，这一点尤其及时。利用一种 一个健康的方法，这个项目将建立一个基本的监测基础设施，以调查埃博拉病毒 和其他人畜共患病溢出事件，通过开发一个集成的mHealth系统，允许医疗保健 供应商同时监测人类和野生动物的疾病暴发。这样做的目的是 监测系统将改进对布温迪地区人畜共患病溢出的检测，并帮助回答数十年 关于支持埃博拉病毒出现的生态情景的长期问题，使预测成为可能 帮助预防未来的疫情。具体地说，在这个项目的R21阶段，我们将：(1)开发一个村庄 医疗团队(VHT)数据收集系统，用于远程捕获AFI和野生动物发病率/死亡率信息 使用基于One Health智能手机的应用程序和基于社区的短信系统设置森林环境；(2)开发 利用手机发射塔三角测量和机器学习优化的被动地理定位系统，可以 在智能手机和非智能手机技术中实施，以提高本地化的准确性 (3)创建在布温迪地区运行的一个综合的健康AFI疫情警报系统， 针对快速准确地检测疫情进行了优化。在这个项目的R33阶段，我们将：(1)完善， 扩展和评估分级mHealth监测平台，以改进纵向AFI病例识别； (2)利用Bwindi mHealth监测系统调查埃博拉病毒暴露的流行病学 与该地区的野生动物接触有关。该项目与现有的NIAID资助的AFI很好地结合在一起 监测方案，并与乌干达卫生部密切合作。该项目将提供一个 严格评估将mHealth组件添加到长期人畜共患病的益处的最佳方案 疾病监测，有利于所有发达平台的可持续性。

Project Summary Due to human encroachment on the fragile ecosystems of the Congo basin forest perimeter, spillover of zoonotic pathogens into border communities have proliferated and resulted in worldwide implications. The region of the Bwindi Impenetrable Forest, located in the southwestern corner of Uganda bordering the Democratic Republic of Congo (DRC) is a biodiversity hotspot harboring among the largest number of primate and bat species of any forest in Africa. It is also situated in one of the most densely human populated regions of Africa. Healthcare facilities in this region remain vigilant for an outbreak of Ebola virus disease (EVD) or Marburg hemorrhagic fever (MHF). This is especially timely given the recent confirmed outbreaks of EVD in neighboring districts. Utilizing a One Health approach, this project will build an essential surveillance infrastructure for investigating ebolavirus and other zoonotic disease spillover events by developing an integrated mHealth system that allows healthcare providers to monitor outbreaks of disease in both humans and wildlife simultaneously. The goal of this surveillance system is to improve detection of zoonotic spillover in the Bwindi region and help to answer decades long questions about the ecological scenarios supporting ebolavirus emergence, enabling forecasting that could help prevent future outbreaks. Specifically, during the R21 phase of this project we will: (1) develop a Village Health Team (VHT) data collection system to capture AFI and wildlife morbidity / mortality information in remote forest settings using a One Health smartphone based APP and community-based SMS system; (2) develop a passive geo-location system using cell-phone tower triangulation with machine learning optimization that can be implemented across smartphone and non-smartphone-based technologies to improve accuracy in localization of outbreaks; and (3) create an integrated One Health AFI outbreak alert system operational in the Bwindi region, optimized for rapid and accurate detection of outbreaks. During the R33 phase of this project we will: (1) refine, expand and evaluate the tiered mHealth surveillance platform for improved longitudinal AFI case identification; and (2) utilize the Bwindi mHealth surveillance system to investigate the epidemiology of ebolavirus exposure associated with wildlife contact in the region. This project is well integrated with existing NIAID funded AFI surveillance programs and collaborates closely with the Ugandan Ministry of Health. This project will provide an optimal scenario for rigorously evaluating the benefits of adding an mHealth component to long term zoonotic disease monitoring, benefiting the sustainability of all developed platforms.