RAPID: SCH: Effectiveness of contact tracing for detection of Ebola risk during early introduction of the virus within the USA

RAPID：SCH：在病毒早期传入美国期间，接触者追踪对于检测埃博拉风险的有效性

• 批准号: 1513639
• 负责人: Caterina Scoglio
• 金额: $ 13.72万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2016-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1513639&HistoricalAwards=false
• 关键词: RAPID; SCH; Effectiveness; contact; tracing

The current outbreak of Ebola is the largest thus far, with more than 13,000 reported cases to date in West Africa. Secondary infections have also been reported in Spain and the United States, raising concerns about training of medical personnel and safety of the entire population. In an effort to stop the transmission of the virus within the USA during its very early stage, the Center for Disease Control and Prevention is adopting a "contact tracing" approach ? finding all individuals who have had close contact with an Ebola patient and monitoring the health status of those people for 21 days. This approach requires careful data collection, and is labor and cost intensive. A quantitative measure to evaluate the effectiveness of contact tracing is currently missing, due to the lack of previous experience of Ebola in the USA and insufficient supporting data from current cases. The goal of this project is to evaluate risk detection capabilities of contact tracing efforts for Ebola before the epidemic phase, and estimate the associated cost in potential scenarios. Not only will understanding the effectiveness of contact tracing be important for the current Ebola epidemic, but this project will also provide information for developing contact tracing guidelines and identifying critical circumstances hampering effective contact tracing in possible future epidemic threats. This project will develop a network-based stochastic modeling framework of Ebola transmission for the local contact network of infected individuals (household, workplace, hospital, airplane, etc.). This simulation framework will allow investigators to synthesize scenarios and activities compatible with daily news about Ebola. "Missed- detection probability" versus "contact tracing cost" will be estimated through extensive simulations. Missed-detection probability, in this case, denotes the probability that a secondary infected individual is not detected before transmitting the infection to others. The team will perform sensitivity analysis to account for inherent uncertainties in different scenarios. The in-silico analysis will allow the following: 1) test performance and associated cost of contact tracing efforts in multiple realistic scenarios and different parameter spaces, 2) propose contact tracing guidelines under limited resources, and 3) identify critical circumstances for which contact tracing is not fully effective. A successful implementation of this project will have immediate benefits to USA public health and security against infectious disease.

目前的埃博拉疫情是迄今为止规模最大的一次，西非迄今已报告13 000多例病例。西班牙和美国也报告了二次感染，引起了对医务人员培训和全体人口安全的担忧。为了阻止病毒在美国境内的早期传播，疾病控制和预防中心正在采取“接触者追踪”的方法？找到所有与埃博拉患者有过密切接触的人，并对这些人的健康状况进行为期21天的监测。这种方法需要仔细收集数据，而且劳动力和成本密集。目前缺乏评估接触者追踪有效性的定量措施，原因是美国缺乏埃博拉病毒的既往经验，以及现有病例的支持数据不足。该项目的目标是评估埃博拉病毒流行阶段之前接触者追踪工作的风险检测能力，并估计潜在情况下的相关成本。了解接触者追踪的有效性不仅对当前的埃博拉疫情很重要，而且该项目还将为制定接触者追踪指南和确定在未来可能的流行病威胁中阻碍有效追踪接触者的关键情况提供信息。该项目将为感染者的本地接触网络（家庭、工作场所、医院、飞机等）开发一个基于网络的埃博拉病毒传播随机建模框架。这一模拟框架将使调查人员能够综合与埃博拉每日新闻相符的情景和活动。将通过广泛的模拟来估计“漏诊概率”与“接触者追踪成本”。在这种情况下，漏诊概率表示在将感染传播给其他人之前未检测到继发感染个体的概率。该团队将进行敏感度分析，以说明不同情况下的固有不确定性。计算机模拟分析将允许：1）在多个现实场景和不同参数空间中测试接触者追踪工作的性能和相关成本，2）在有限资源下提出接触者追踪指南，以及3）确定接触者追踪不完全有效的关键情况。该项目的成功实施将对美国公共卫生和传染病安全产生直接效益。