论文部分内容阅读
目的分析2008-2011年辽宁省大连市传染病自动预警信息的分布状况,为进一步优化传染病自动预警信息系统的预警效果提供依据。方法采用描述性流行病学研究方法对2008-2011年大连市传染病自动预警信息分布状况进行分析,并采用χ2检验和方差分析方法对不同地区、病种、时间的预警阳性率和响应时间进行比较。结果 2008-2011年大连市通过预警系统共收到预警信息9415条,经现场调查确定暴发/流行228起,预警阳性率为2.42%;各县(区)均有预警信息;涉及的病种18种,其中预警信息较多的病种有其它感染性腹泻病、流行性腮腺炎、风疹、细菌性痢疾、猩红热、手足口病,共计8648条,占总数的91.85%;预警阳性率较高的病种依次是甲型H1N1流感、流行性腮腺炎、风疹和手足口病;按照系统发出预警信号到填报异常信息卡的时间统计,响应时间中位数为0.53 h,四分位间距1.55 h,按照填报异常信息卡至开始现场调查时间统计,响应中位数为0.10 h,四分位间距为5.15 h。结论传染病自动预警信息系统在实际应用中存在一些局限性,有待于进一步优化。
Objective To analyze the distribution of automatic warning information on infectious diseases in Dalian, Liaoning Province from 2008 to 2011, and provide evidence for further optimizing the warning effect of automatic warning information system of infectious diseases. Methods Descriptive epidemiological methods were used to analyze the distribution of automatic warning information on infectious diseases in Dalian from 2008 to 2011. The positive rate and response time of early warning in different areas, diseases and time were analyzed by Chi-square test and analysis of variance Compare Results A total of 9,415 early-warning messages were received from Dalian City through the early warning system during 2008-2011. After field investigation, 228 outbreaks and epidemics were detected, with the positive rate of early warning being 2.42%. Early warning information was provided for all counties (districts) Among them, 8648 were infected with other infectious diarrhea, mumps, rubella, bacillary dysentery, scarlet fever and hand-foot-mouth disease, accounting for 91.85% of the total. The positive rate of early warning was higher Influenza A (H1N1), mumps (Mumps), rubella (Mumps) and hand-foot-and-mouth disease (MMR) were reported in this study. The median time to response was 0.53 h and the interquartile range was 1.55 h. According to the statistical information of filling in anomaly card to the time of on-site investigation, the median response was 0.10 h and the interquartile range was 5.15 h. Conclusion There are some limitations in the practical application of automatic warning information system for infectious diseases, which needs to be further optimized.