Statistical Models of Bio-surveillance for Monitoring Disease Outbreak

2001年的炭疽恐怖袭击、严重急性呼吸道综合征（SARS）爆发以及对流感大流行的恐惧促使美国许多公共卫生部门开发早期疾病爆发检测系统。疾病爆发的早期发现使公共卫生官员能够尽早实施疾病控制和预防措施。特别是考虑到生物恐怖主义的威胁，最近人们对开发能够检测疾病空间模式变化的生物监测系统产生了极大的兴趣。在这项研究中，我们开发了四个统计模型/方法，可以在监测系统中实施。我们首先提出了一个灵活的形状的空间扫描统计，可以检测每个区域的相对较小的邻域内的不规则形状的集群。提出的空间扫描统计量的性能进行了比较，Kulldorff的圆形空间扫描统计量与莫 关于我们 通过考虑几种圆形和非圆形热点团簇模型的nte Carlo模拟。所提出的空间扫描统计被证明有良好的通常的权力，再加上能够更准确地检测非圆形的热点集群比圆形的。其次，我们提出了一个扩展的功率的集群检测测试，其中包括通常的功率作为一种特殊情况。此外，我们定义了扩展功率的轮廓，预计它将在几个集群检测测试的评估和比较中发挥重要作用。Kulldorff的圆形空间扫描统计量（1995，1997）和Tango和Takahashi（2005）提出的灵活空间扫描统计量证明了所提出的扩展功率及其分布。第三，我们提出了一个灵活的形状的空时扫描统计的基础上灵活的空间扫描统计。特别是，我们开发了一个前瞻性的时空扫描统计疾病爆发的早期检测。建议的空时扫描统计的性能进行比较，与圆柱形扫描统计，使用Kulldorff等人提供的基准数据。为了比较空时扫描统计的性能，我们提出了一个空时功率分布，通过扩展纯粹的空间双变量功率分布。每日症状监测数据在马萨诸塞州，美国，被用来说明所提出的检验统计量，也比较性能的灵活的时空扫描统计与圆柱形的。最后，提出了一类基于病例对照点数据的二次型空间聚类检验方法。它包括Cuzick和Edwards的检验统计量（1990）。虽然他们使用了检验统计量的渐近正态性，但我们表明，对于中等规模的样本量，这种近似通常很差。相反，我们建议使用中心卡方分布作为检验统计量渐近分布的更好近似。此外，不仅要估计的最佳值的未知参数的规模集群，但也调整多次测试，由于重复的过程中，通过改变参数的值，我们提出了最小的轮廓p值的测试统计量的参数作为一个综合的测试统计量。少

The anthrax terrorist attacks in 2001, the severe acute respiratory syndrome (SARS) outbreak, and a fear of pandemic flu have motivated many public health departments to develop early disease outbreak detection systems in the United States. Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. Particularly in light of the perceived threat of bioterrorism, there has been a spate of recent interest in the development of biosurveillance systems that can detect changes in spatial patterns of disease. In this research, we developed four statistical models/methods that can be implemented in the surveillance system. We first proposed a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Mo … More nte Carlo simulation by considering several circular and noncircular hot-spot cluster models. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one. We second we proposed an extended power of the cluster detection tests, which includes the usual power as a special case. Further, we define the profile of the extended power, which can be expected to play an important role in the evaluation and comparison of several cluster detection tests. The proposed extended power and its profile are demonstrated by two tests -- Kulldorff's circular spatial scan statistic (1995,1997) and a flexible spatial scan statistic proposed by Tango and Takahashi(2005). Third, we propose a flexibly shaped space-time scan statistic based on the flexible spatial scan statistic. In particular, we develop a prospective space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic, using the benchmark data provided by Kulldorff et al. In order to compare the performance of space-time scan statistics we propose a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic and also to compare the performance of the flexible space-time scan statistic with that of the cylindrical one. Finally, a class of tests with quadratic forms for detecting spatial clustering of health events based on case-control point data was proposed. It includes Cuzick and Edwards' test statistic(1990). Although they used the property of asymptotic normality of the test statistic, we showed that such an approximation is generally poor for moderately large sample sizes. Instead, we suggested a central chi-square distribution as a better approximation to the asymptotic distribution of the test statistic. Furthermore, not only to estimate the optimal value of the unknown parameter on the scale of cluster but also to adjust for multiple testing due to repeating the procedure by changing the parameter value, we proposed the minimum of the profile p-value of the test statistic for the parameter as an integrated test statistic. Less