Methods for evaluating bioterrorism surveillance tools

说明： 我们怎么知道什么时候生物恐怖分子袭击了我们？ 自2001年10月炭疽热的恐怖主义传播以来，人们一直担心该国易受生物恐怖主义的影响，也就是说，由于生物制剂的传播而易受恐怖主义的影响。因此，越来越多的资源用于监测旨在侦测这类攻击的系统。一种有希望的检测方法是监测初级保健医生的就诊情况。这种方法依赖于这样一个事实，即许多潜在的生物恐怖主义制剂会导致非特异性的早期症状。如果通过这些早期症状可以检测到发作，那么治疗、预防和遏制就可以比需要明确诊断的情况更早地开始。然而，通过监测早期症状进行检测是困难的，因为生物恐怖主义的“信号”必须与自然发生的疾病的“噪音”相对照地进行检测。 已经提出了几种用于这种信号检测的统计算法；然而，人们对这些方法的相对性能知之甚少。这是一个重要的问题，因为在给定相同数据的情况下，相对于其他统计技术，可以通过一些统计技术实现显著改进的检测。 有两个主要障碍阻碍了技术的比较：首先，必须模拟生物恐怖袭击，因为它们具有排除简单化和概括化的特点。我们已经解决了这个问题，创建了一个复杂的微观模拟来描述炭疽攻击的影响，以及它将如何出现在我们操作的监视系统中。其次，必须创建可行的比较指标。在这种情况下，相对简单的方法，如ARL或ROC曲线，是不够的，因为它们忽略了关键特征，例如检测的及时性、针对不同的假阳性率的方法的不同排名、和/或受影响的人数。 在这一应用中，我们建议开发工具来比较生物恐怖袭击检测的统计方法。我们将探索：1)加权ROC曲线；2)广义多维ROC曲面；3)基于成本的评估，包括调查和假阳性成本，以及每种方法引起和避免的死亡率和发病率的价值。

DESCRIPTION: How will we know when a bioterrorist attacks us? Since the terrorist dissemination of anthrax in October of 2001, there has been concern about the nation's vulnerability to bioterrorism, that is, to terrorism by the spread of biological agents. Increasing resources have thus been devoted to surveillance systems intended to detect such attacks. One promising detection method is to monitor visits to primary care physicians. This approach relies on the fact that many potential bioterrorism agents cause early symptoms that are non-specific. If an attack can be detected through these early symptoms, then treatment, prophylaxis, and containment can be started earlier than if definitive diagnoses are required. However, detection through surveillance of early symptoms is difficult since the 'signal' of the bioterrorism must be detected against the 'noise' of naturally occurring disease. Several statistical algorithms have been proposed for this signal detection; however, relatively little is known about the relative performance of the methods. This is an important question, as substantially improved detection may be achieved by some statistical techniques relative to others, given the same data. There are two major obstacles impeding the comparison of techniques: First, bioterrorist attacks must be simulated, since they have traits that rule out simplification and generalization. We have addressed this problem by creating a complex microsimulation to describe the effects of an anthrax attack and how it would appear in a surveillance system we operate. Second, viable metrics for comparison must be created. In this case, relatively simple methods such as ARLs or ROC curves, are insufficient, since they ignore crucial features, such as timeliness of detection, variable rankings of methods for different false positive rates, and/or the number of people affected. In this application, we propose developing tools to compare statistical methods for detection of bioterrorist attack. We will explore: 1) weighted ROC curves; 2) generalized multidimensional ROC surfaces; and 3) cost-based evaluation incorporating investigation and false positive costs as well as the value of mortality and morbidity incurred and averted by each method.