论文部分内容阅读
目的用WSARE软件对猩红热监测数据进行分析,探测可能出现的暴发疫情。方法采用WSARE软件,应用基于历史数据基线的WSARE算法,对北京市2011年的猩红热监测数据进行分析,产生预警信号。结合原始监测数据,对预警信号进行描述和分级,评估出现暴发的可能性。结果共发出预警信号11次,双特征变量联合异常增高情况6次,单特征变量异常增高情况5次。出现高级别预警,暴发疫情存在可能性较大的有5月上、中旬西城区的学校和幼托机构;出现中级别预警,暴发疫情可能存在的有:5月中、下旬丰台区的幼托机构,5月下旬至6月初海淀区的幼托机构,6月中旬海淀区的幼托机构;出现低级别预警,暴发疫情存在可能性较小的有:6月上旬昌平区幼托机构,5月下旬朝阳区的学校。结论 WSARE计算方法是一种针对性强、灵活性强的时空预警方法。其可以实现对猩红热监测数据中的异常信号进行探测,早期提示可能出现的暴发疫情。
Objective To analyze the scarlet fever monitoring data by WSARE software to detect possible outbreaks. Methods Using WSARE software and WSARE algorithm based on the historical data baselines, the monitoring data of scarlet fever in Beijing in 2011 were analyzed and an early warning signal was generated. Combined with the original monitoring data, the warning signals are described and graded to assess the likelihood of an outbreak. Results A total of 11 early warning signals were sent out, the double eigenvariables combined with abnormal increase 6 times, and the single eigenvariable abnormalities 5 times. Emergence of high-level early warning, outbreaks are more likely in the upper and middle Xicheng District in May of the school and child care institutions; emergence of mid-level warning, the outbreak may exist: in mid-May, Institutions, early May to early June, Haidian District, child care institutions in mid-June Haidian District, child care institutions; there is a low-level early warning, outbreaks are less likely to have: early June Changping District, 5, Chaoyang District, late in the month the school. Conclusion WSARE calculation method is a kind of targeted and flexible time-space warning method. It enables the detection of anomalous signals in scarlet fever monitoring data and early warning of possible outbreaks.