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

在刚果盆地森林周边人畜共患病蔓延时推进单一健康数据采集

• 批准号: 10741526
• 负责人: Tierra Smiley Evans
• 金额: $ 20.94万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-17 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10741526
• 关键词: Acute; Address; Africa; Africa South of the Sahara; Antibodies; Biodiversity; Border Community; Cellular Phone; Chikungunya virus; Chiroptera; Collaborations; Communicable Diseases; Communication; Communities; Congo; Data; Data Analytics; Data Collection; Democratic Republic of the Congo; Dengue Fever; Detection; Disease; Disease Outbreaks; Disease Surveillance; Early Diagnosis; Early identification; Ebola Hemorrhagic Fever; Ebola virus; Ecosystem; Emerging Communicable Diseases; Epidemiology; Event; Fever; Filovirus; Funding; Goals; Health; Health Personnel; Health Professional; Health care facility; Hospitals; Household; Human; Human Resources; Immunoglobulin G; Incidence; Infrastructure; Machine Learning; Marburg Virus Disease; Methods; Modeling; Monitor; Morbidity - disease rate; National Institute of Allergy and Infectious Disease; Outcome; Patients; Pattern; Phase; Population; Primates; Proliferating; Reaction Time; Reporting; Research; Risk; Risk Factors; Sampling; Specimen; Surveillance Program; System; Systems Analysis; Technology; Telephone; Testing; Time; Uganda; Virus; Yellow Fever; Zika Virus; Zoonoses; dashboard; data dissemination; data streams; deep neural network; design; electronic data; falls; forest; future outbreak; health data; health empowerment; human data; improved; mHealth; machine learning algorithm; member; mortality; new outbreak; next generation; pandemic potential; pathogen; preempt; prevent; prevent outbreaks; programs; prospective; remote communities; smartphone application; spillover event; surveillance network; technology platform; tool; trend; zoonotic spillover; Acute; Address; Africa; Africa South of the Sahara; Antibodies; Biodiversity; Border Community; Cellular Phone; Chikungunya virus; Chiroptera; Collaborations; Communicable Diseases; Communication; Communities; Congo; Data; Data Analytics; Data Collection; Democratic Republic of the Congo; Dengue Fever; Detection; Disease; Disease Outbreaks; Disease Surveillance; Early Diagnosis; Early identification; Ebola Hemorrhagic Fever; Ebola virus; Ecosystem; Emerging Communicable Diseases; Epidemiology; Event; Fever; Filovirus; Funding; Goals; Health; Health Personnel; Health Professional; Health care facility; Hospitals; Household; Human; Human Resources; Immunoglobulin G; Incidence; Infrastructure; Machine Learning; Marburg Virus Disease; Methods; Modeling; Monitor; Morbidity - disease rate; National Institute of Allergy and Infectious Disease; Outcome; Patients; Pattern; Phase; Population; Primates; Proliferating; Reaction Time; Reporting; Research; Risk; Risk Factors; Sampling; Specimen; Surveillance Program; System; Systems Analysis; Technology; Telephone; Testing; Time; Uganda; Virus; Yellow Fever; Zika Virus; Zoonoses; dashboard; data dissemination; data streams; deep neural network; design; electronic data; falls; forest; future outbreak; health data; health empowerment; human data; improved; mHealth; machine learning algorithm; member; mortality; new outbreak; next generation; pandemic potential; pathogen; preempt; prevent; prevent outbreaks; programs; prospective; remote communities; smartphone application; spillover event; surveillance network; technology platform; tool; trend; zoonotic spillover

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.

项目摘要 由于人类对刚果盆地森林脆弱生态系统的侵占，人畜共患病的溢出 进入边境社区的病原体激增并产生了全世界的影响。该地区 Bwindi坚不可摧的森林，位于乌干达的西南角，与民主共和国接壤 刚果（DRC）是一个生物多样性的热点 非洲的森林。它也位于非洲人口最密集的地区之一。卫生保健 该地区的设施仍然警惕爆发埃博拉病毒疾病（EVD）或马堡出血热。 （MHF）。鉴于最近确认的EVD在邻近地区爆发，这尤其及时。利用一个 一种健康方法，该项目将建立一个基本的监视基础设施，以调查埃博拉病毒 以及通过开发允许医疗保健的集成MHealth系统来开发的其他人畜共患病溢出事件 提供者同时监测人类和野生动植物的疾病暴发。目标的目标 监视系统是改善对Bwindi地区人畜共患溢出的检测，并有助于回答数十年 关于支持埃博拉病毒出现的生态场景的长期问题 有助于防止未来的爆发。具体来说，在该项目的R21阶段，我们将：（1）开发一个村庄 卫生团队（VHT）数据收集系统，以捕获AFI和野生动植物的发病率 /死亡率信息 使用基于健康智能手机的应用程序和基于社区的SMS系统的森林设置； （2）开发 使用手机塔三角剖分，具有机器学习优化的被动地理位置系统，可以是 跨智能手机和非智能手机的技术实施，以提高本地化的准确性 爆发; （3）在Bwindi地区创建一个集成的健康AFI AFI爆发警报系统， 优化以快速，准确地检测暴发。在该项目的R33阶段，我们将：（1）完善， 扩展和评估分层的MHealth监视平台，以改善纵向AFI病例识别； （2）利用Bwindi MHealth监视系统研究埃博拉病毒暴露的流行病学 与该地区的野生动植物接触有关。该项目与现有的NIAID资助的AFI完善 监视计划并与乌干达卫生部紧密合作。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的最佳方案 疾病监测，使所有发达平台的可持续性受益。