WSARE3.0模型在成都市新都区手足口病聚集性疫情早期预警中的应用
|
摘要
目的探讨WSARE 3. 0模型在传染病暴发早期预警中的应用价值。方法运用WSARE 3. 0预警模型对2017年成都市新都区手足口病疫情进行预警。结果 WSARE 3. 0软件共探测到2017年新都区的13个镇(街道)出现了具有统计学意义的手足口病预警信号5次(P <0. 05),其中1月1次,4月2次,6月1次,10月1次,其中2次为双特征变量,3次为单特征变量。结论 WSARE模型对于多元分类资料的异常情况探测要优于单因素方法,但在应用该方法时,要结合数据本身的实际情况及特征,以便能更好的、准确的探测到疫情。
Objective To explore the application value of WSARE 3. 0 model in early warning of infectious disease outbreak. Methods WSARE 3. 0 early warning model was used to predict the epidemic situation of hand-foot-mouth disease in Xindu district of Chengdu in 2017. Results WSARE 3. 0 software detected 5 times of statistically significant early warning signals of hand-foot-mouth disease( P < 0. 05) showed in 13 towns(streets) in Xindu district in 2017,including 1 time in January,2 times in April,1 time in June,1 time in October,of which 2 times were double characteristic variables and 3 times were single characteristic variables.Conclusion WSARE model is superior to univariate method in detecting abnormal situation of multivariate classification data. However, the WSARE model should be combined with the actual situation and characteristics of the data for better and accurate detection of the epidemic situation.
Objective To explore the application value of WSARE 3. 0 model in early warning of infectious disease outbreak. Methods WSARE 3. 0 early warning model was used to predict the epidemic situation of hand-foot-mouth disease in Xindu district of Chengdu in 2017. Results WSARE 3. 0 software detected 5 times of statistically significant early warning signals of hand-foot-mouth disease( P < 0. 05) showed in 13 towns(streets) in Xindu district in 2017,including 1 time in January,2 times in April,1 time in June,1 time in October,of which 2 times were double characteristic variables and 3 times were single characteristic variables.Conclusion WSARE model is superior to univariate method in detecting abnormal situation of multivariate classification data. However, the WSARE model should be combined with the actual situation and characteristics of the data for better and accurate detection of the epidemic situation.
引文
[1]杨维中.传染病监测预警理论与实践[M].北京:人民卫生出版社,2012.
[2]中国疾病预防控制中心.全国传染病自动预警(时间模型)试运行工作方案[Z]. 2008.
[3]Wong WK,Moore AW,Cooper GF,et al. WSARE:What's Strange About Recent Events?[J]. J Urban Health,2003,80(2):i66-75.
[4]张子武,冯子健,李晓松. WSARE计算方法在传染病暴发早期预警中的应用[J].中华流行病学杂志,2010,31(11):1306-1310.
[5]林文成. 2011-2015年四川省眉山市彭山区手足口病疫情分析[J].职业卫生与病伤,2016,31(6):350-353.
[6]蔡颖,梁润梅,刘志鹏,等. 2009-2013年成都市青白江区手足口病疫情分析[J].职业卫生与病伤,2015,30(1):37-40.
[7]曹洋,洪志恒,金连梅,等. 2011-2012年全国手足口病疫情监测分析[J].疾病监测,2013,28(12):975-980.
[8]李兰娟,任红.传染病学[M]. 8版.北京:人民卫生出版社,2013.
[9]刘华,冯子健,张子武,等.基于历史数据基线的WSARE方法在传染病早期预警中的应用研究[J].现代预防医学,2010,37(8):1401-1404.
[10]张代涛,张奕,杨鹏,等. WSARE计算方法在猩红热暴发预警中的应用[J].中国预防医学杂志,2012,13(1):26-29.
[11]郑庆鸣,李媛,王铁强,等. WSARE 3. 0算法在深圳市流行性腮腺炎暴发早期预警中的应用[J].疾病监测,2014,29(5):399-402.
[12]龚华东.基于历史数据基线的WSARE方法在传染病早期预警中的应用研究[J].当代医学,2011,17(22):145-146.
[13]张子武,冯子健,李晓松. WSARE计算方法在传染病暴发早期预警中的应用[J].中华流行病学杂志,2010,31(11):1306-1310.
[2]中国疾病预防控制中心.全国传染病自动预警(时间模型)试运行工作方案[Z]. 2008.
[3]Wong WK,Moore AW,Cooper GF,et al. WSARE:What's Strange About Recent Events?[J]. J Urban Health,2003,80(2):i66-75.
[4]张子武,冯子健,李晓松. WSARE计算方法在传染病暴发早期预警中的应用[J].中华流行病学杂志,2010,31(11):1306-1310.
[5]林文成. 2011-2015年四川省眉山市彭山区手足口病疫情分析[J].职业卫生与病伤,2016,31(6):350-353.
[6]蔡颖,梁润梅,刘志鹏,等. 2009-2013年成都市青白江区手足口病疫情分析[J].职业卫生与病伤,2015,30(1):37-40.
[7]曹洋,洪志恒,金连梅,等. 2011-2012年全国手足口病疫情监测分析[J].疾病监测,2013,28(12):975-980.
[8]李兰娟,任红.传染病学[M]. 8版.北京:人民卫生出版社,2013.
[9]刘华,冯子健,张子武,等.基于历史数据基线的WSARE方法在传染病早期预警中的应用研究[J].现代预防医学,2010,37(8):1401-1404.
[10]张代涛,张奕,杨鹏,等. WSARE计算方法在猩红热暴发预警中的应用[J].中国预防医学杂志,2012,13(1):26-29.
[11]郑庆鸣,李媛,王铁强,等. WSARE 3. 0算法在深圳市流行性腮腺炎暴发早期预警中的应用[J].疾病监测,2014,29(5):399-402.
[12]龚华东.基于历史数据基线的WSARE方法在传染病早期预警中的应用研究[J].当代医学,2011,17(22):145-146.
[13]张子武,冯子健,李晓松. WSARE计算方法在传染病暴发早期预警中的应用[J].中华流行病学杂志,2010,31(11):1306-1310.