Hay Simon I, Simba Milka, Busolo Millie, Noor Abdisalan M, Guyatt Helen L, Ochola Sam A, Snow Robert W
Department of Zoology, University of Oxford, Oxford, United Kingdom.
Emerg Infect Dis. 2002 Jun;8(6):555-62. doi: 10.3201/eid0806.010310.
Epidemic detection algorithms are being increasingly recommended for malaria surveillance in sub-Saharan Africa. We present the results of applying three simple epidemic detection techniques to routinely collected longitudinal pediatric malaria admissions data from three health facilities in the highlands of western Kenya in the late 1980s and 1990s. The algorithms tested were chosen because they could be feasibly implemented at the health facility level in sub-Saharan Africa. Assumptions of these techniques about the normal distribution of admissions data and the confidence intervals used to define normal years were also investigated. All techniques identified two "epidemic" years in one of the sites. The untransformed Cullen method with standard confidence intervals detected the two "epidemic" years in the remaining two sites but also triggered many false alarms. The performance of these methods is discussed and comments made about their appropriateness for the highlands of western Kenya.
在撒哈拉以南非洲地区，流行病检测算法越来越多地被推荐用于疟疾监测。我们展示了将三种简单的流行病检测技术应用于20世纪80年代末和90年代从肯尼亚西部高地三个医疗机构常规收集的纵向儿科疟疾入院数据的结果。之所以选择测试这些算法，是因为它们可以在撒哈拉以南非洲地区的医疗机构层面切实可行地实施。还研究了这些技术关于入院数据正态分布的假设以及用于定义正常年份的置信区间。所有技术在其中一个地点都识别出了两个“流行”年份。采用标准置信区间的未转换卡伦方法在其余两个地点检测到了这两个“流行”年份，但也引发了许多误报。讨论了这些方法的性能，并对它们在肯尼亚西部高地的适用性发表了评论。
