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

目前的埃博拉疫情是迄今为止最大的一次，到目前为止，西非报告的病例超过1.3万例。西班牙和美国也报告了二次感染，这引发了人们对医务人员培训和整个人口安全的担忧。为了在病毒非常早期的阶段阻止病毒在美国境内的传播，疾病控制和预防中心正在采用一种“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，并在21天内监测这些人的健康状况。这种方法需要仔细收集数据，而且是劳动力密集型和成本密集型的。由于缺乏美国以前的埃博拉经验，以及来自当前病例的支持数据不足，目前缺乏评估接触者追踪有效性的量化衡量标准。该项目的目标是在埃博拉流行阶段之前评估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，而且该项目还将提供信息，以制定接触者追踪指南，并确定在未来可能出现的流行病威胁中阻碍有效接触者追踪的关键情况。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传播随机建模框架。这个模拟框架将允许调查人员合成与埃博拉日常新闻兼容的情景和活动。“漏检概率”与“接触追踪成本”将通过广泛的模拟进行估算。在这种情况下，漏检概率表示在将感染传播给他人之前没有检测到二次感染个体的概率。该团队将进行敏感性分析，以考虑到不同情况下的固有不确定性。计算机内分析将允许：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)识别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影响。

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.