移动流行区间法在青海省流感流行阈值制定中的应用

徐张懿; 赵金华; 丁小津; 徐莉立

doi:10.16462/j.cnki.zhjbkz.2021.12.016

移动流行区间法在青海省流感流行阈值制定中的应用

doi: 10.16462/j.cnki.zhjbkz.2021.12.016

徐张懿¹,
赵金华²,
丁小津²,
徐莉立^{1, 2, ,}

1.
810001 西宁，青海大学医学院公共卫生系
2.
810007 西宁，青海省疾病预防控制中心传染病预防控制所急传科

基金项目:

青海省应用基础研究和自然科学基金项目 2019-ZJ-7046

详细信息

通讯作者:
徐莉立，E-mail: qhcdcxull@126.com

中图分类号: R181.3
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- 文章访问数: 512
- HTML全文浏览量: 218
- PDF下载量: 59
- 被引次数: 0
出版历程
- 收稿日期: 2020-12-23
- 修回日期: 2021-02-24
- 网络出版日期: 2021-12-27
- 刊出日期: 2021-12-10

Application of moving epidemic method (MEM) in the formulation of influenza epidemic threshold in Qinghai Province

1.
Department of Public Health, Medical School, Qinghai University, Xining 810001, China
2.
Acute Infectious Disease Prevention Department, Institute for Infectious Disease Control and Prevention, Qinghai Provincial Center for Disease Control and Prevention, Xining 810007, China

Funds:

Qinghai Applied Basic Research and Natural Science Foundation Project 2019-ZJ-7046

More Information

Corresponding author: XU Li-li, E-mail: qhcdcxull@126.com

摘要

摘要: 目的利用移动流行区间法(moving epidemic method, MEM)建立流行性感冒(简称流感)预警系统，为青海省流感防控工作提供科学依据。方法利用《中国流感监测信息系统》获得青海省2013―2020年流感监测数据，取其中的流感病毒阳性率数据，按周进行整理，再利用MEM估计流感流行阈值和分级强度阈值，同时可用交叉验证法对MEM的预警效果进行验证。结果通过MEM获得相应的流感流行阈值和分级强度阈值，流行开始阈值、流行结束阈值、中强度阈值、高强度阈值和极高强度阈值分别为16%、7%、29%、48%、60%。本次研究的灵敏度为93%、特异度为96%，模型拟合效果较好。结论本次研究建立的MEM模型在青海省具有较高的灵敏度和特异度，可以利用此模型在青海省建立流感预警系统，指导流感预防工作。
- 流感 /
- 移动流行区间法 /
- 流行趋势 /
- 预警
Abstract: Objective Using moving epidemic method (MEM) to establish an influenza early warning system, so as to provide scientific basis for influenza prevention and control in Qinghai Province. Methods The influenza surveillance data of Qinghai Province from 2013-2020 were obtained in "China Influenza Surveillance Information System", and the positive rate data of influenza virus was collected and sorted weekly. Then the threshold of influenza epidemic and classification intensity were estimated by MEM, and the early warning effect of MEM was verified by cross-validation method. Results The corresponding influenza epidemic threshold and grading intensity threshold were obtained through MEM. The epidemic start threshold, epidemic end threshold, medium intensity threshold, high-intensity threshold, and extremely high-intensity threshold were 16%, 7%, 29%, 48%and 60%, respectively. The sensitivity and the specificity of this study were 93% and 96%, and the model fitting effect was good. Conclusion The MEM model established in this study has high sensitivity and specificity in Qinghai Province, which can be used to establish an influenza early warning system in Qinghai Province to guide influenza prevention.
- Influenza /
- Moving epidemic method /
- Epidemic trend /
- Warning

HTML全文

图 1 周PR值折线图

Figure 1. Weekly PR value line diagram

下载: 全尺寸图片幻灯片

图 2 周ILI%值折线图

Figure 2. Weekly ILI % value line diagram

下载: 全尺寸图片幻灯片

图 3 青海省2019-2020年流感季流行强度分析

Figure 3. Analysis of the epidemic intensity of the 2019-2020 influenza season in Qinghai Province

下载: 全尺寸图片幻灯片

表 1 PR数据不同δ取值下模型的效果评价

Table 1. The effect evaluation of the model under different δ values of PR data

δ值	灵敏度	特异度	阳性预测值	阴性预测值	阳性似然比	阴性似然比	马修斯相关系数	约登指数
2.00	0.94	0.95	0.83	0.98	18.42	0.07	0.85	0.89
2.10	0.94	0.95	0.83	0.98	18.42	0.07	0.85	0.89
2.20	0.94	0.95	0.83	0.98	18.42	0.07	0.85	0.89
2.30	0.94	0.95	0.83	0.98	18.42	0.07	0.85	0.89
2.40	0.93	0.95	0.84	0.98	19.44	0.07	0.85	0.88
2.50	0.93	0.95	0.84	0.98	19.44	0.07	0.85	0.88
2.60	0.93	0.95	0.84	0.98	19.44	0.07	0.85	0.88
2.70	0.93	0.96	0.86	0.98	23.38	0.07	0.87	0.89
2.80	0.90	0.97	0.88	0.97	27.43	0.11	0.86	0.86
2.90	0.90	0.97	0.88	0.97	27.43	0.11	0.86	0.86
3.00	0.87	0.97	0.88	0.97	28.00	0.13	0.84	0.84
3.10	0.87	0.97	0.88	0.97	28.00	0.13	0.84	0.84
3.20	0.86	0.97	0.89	0.96	31.60	0.15	0.84	0.83
3.30	0.83	0.98	0.91	0.96	38.27	0.17	0.84	0.81
3.40	0.81	0.98	0.91	0.95	38.75	0.20	0.82	0.78
3.50	0.81	0.98	0.91	0.95	38.75	0.20	0.82	0.78
3.60	0.60	0.98	0.91	0.90	38.78	0.41	0.69	0.58
3.70	0.58	0.98	0.91	0.90	37.79	0.42	0.68	0.57
3.80	0.58	0.98	0.91	0.90	37.79	0.42	0.68	0.57
3.90	0.58	0.98	0.91	0.90	37.79	0.42	0.68	0.57
4.00	0.58	0.98	0.91	0.90	37.79	0.42	0.68	0.57

下载: 导出CSV

表 2 PR数据各年份历史数据所建模型的效果评价

Table 2. The effect evaluation of the model built on the historical data of each year of PR data

年份(年)	灵敏度	特异度	阳性预测值	阴性预测值	阳性似然比	阴性似然比	马修斯相关系数	约登指数
2013-2014	0.91	0.98	0.94	0.98	55.62	0.09	0.91	0.90
2014-2015	0.68	1.00	1.00	0.94	-	0.32	0.80	0.68
2015-2016	0.95	1.00	1.00	0.90	-	0.05	0.97	0.95
2016-2017	0.98	0.91	0.69	1.00	10.76	0.02	0.78	0.89
2017-2018	1.00	0.96	0.88	1.00	23.80	0.00	0.92	0.96
2018-2019	0.94	1.00	1.00	0.97	-	0.06	0.96	0.94

下载: 导出CSV

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