多源数据的学校和托幼机构传染病聚集性疫情预警监测系统综合评价

梁洁雅; 覃绰亨; 周梦茜

doi:10.16835/j.cnki.1000-9817.2023.11.026

多源数据的学校和托幼机构传染病聚集性疫情预警监测系统综合评价

doi: 10.16835/j.cnki.1000-9817.2023.11.026

1.
广东省佛山市南海区疾病预防控制中心应急管理科，528200
2.
广东省佛山市南海区疾病预防控制中心疾病控制科

详细信息

作者简介:
梁洁雅(1981-)，女，广东佛山人，大学本科，副主任医师，主要从事传染病防控及应急管理方面工作

利益冲突声明 所有作者声明无利益冲突。
中图分类号: R181.3⁺² G478 R51
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- 被引次数: 0
出版历程
- 收稿日期: 2023-08-04
- 修回日期: 2023-08-29
- 网络出版日期: 2023-11-27
- 刊出日期: 2023-11-25

Comprehensive evaluation of the epidemic warning and monitoring system for infectious disease aggregation in schools or daycare institutions with multi-source data

1.
Emergency Management Department, Nanhai District Centre for Disease Control and Prevention, Foshan (528200), Guangdong Province, China

摘要

摘要: 目的通过对多源数据的学校和托幼机构传染病聚集性疫情预警监测系统(WMS)的综合评价, 为优化其预警功能和探索进一步整合其他数据来源提供依据。方法收集2021年1月年至2023年7月期间国家传染病自动预警系统(ARS)、广东省佛山市学生健康监护系统(SHMS)和WMS产生的传染病预警数据, 采用灵敏度、特异度、约登指数、阳性预测值、预警及时性中位数等指标对预警监测系统进行综合评价。结果 ARS对于学校或托幼机构的常见传染病预警不敏感, SHMS和WMS的预警及时性中位数均为1 d。SHMS和WMS对手足口病、感染性腹泻、流感样病例、水痘等传染病的预警灵敏度均在70%以上, 但对新型冠状病毒感染的灵敏度分别只有10.42%和64.58%。WMS的约登指数和阳性预测值均最高。结论 WMS能及时、有效地对学校和托幼机构聚集性疫情进行预警, 提高了阳性预测值。未来需不断增加数据来源以提高预警能力。
- 日托幼儿园 /
- 疾病暴发流行 /
- 传染病 /
- 人群监测
Abstract: Objective To comprehensively evaluate the early warning monitoring system (WMS) for infectious disease aggregation in schools or daycare institutions with multi-source data, to identify the advantages and disadvantages of the system, and to provide a basis for optimizing its warning function and exploring further integration of other data sources. Methods The infectious disease warning data from the Chinese infectious disease Automated-alert and Response System (ARS), the Student Health Monitoring System (SHMS) in Foshan City, Guangdong Province, and WMS were collected from January 2021 to July 2023.The indicators such as sensitivity, specificity, Youden index, positive predictive value, early warning and median timeliness were used to comprehensively evaluate the early warning monitoring system. Results The ARS was not sensitive to common infectious disease warnings in schools or daycare institutions.The median timeliness of the SHMS and the WMS was 1 day.The sensitivity of SHMS and the WMS for early warning of hand-foot-mouth disease, infectious diarrhea, influenza-like cases, chickenpox and other infectious diseases were more than 70%, while the sensitivity for novel coronavirus infection were only 10.42% and 64.58%.The Youden index and positive predictors of the WMS were both the highest. Conclusion The WMS can timely and effectively warn schools or daycare institutions of clustered epidemics, improve the positive predictive value, but the data sources are still insufficient, and it is necessary to continuously increase the data sources in future exploration to improve the warning ability.
- Child day care centers /
- Disease outbreaks /
- Communicable diseases /
- Population surveillance
注释:

1) 利益冲突声明 所有作者声明无利益冲突。

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表 1 2021—2023年不同学校类型WMS预警情况分析/条

Table 1. Analysis of the WMS early warning among different types of schools in 2021-2023/section

学校类型	流感样病例	手足口病	水痘	其它感染性腹泻病	新型冠状病毒感染	急性出血性结膜炎	猩红热	流行性腮腺炎	合计
托幼机构	112	456	26	19	0	2	3	0	618
小学	313	62	78	101	11	4	0	1	570
中学	129	0	66	33	20	0	0	0	248
合计	554	518	170	153	31	6	3	1	1 443

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表 2 3个系统对不同病种传染病的预警效果比较

Table 2. Comparison of early warning effect of three systems on different kinds of infectious deseases

系统	手足口病					感染性腹泻					流感样病例					水痘					新型冠状病毒感染
系统	预警数	灵敏度/%	特异度/%	约登指数/%	阳性预测值/%	预警数	灵敏度/%	特异度/%	约登指数/%	阳性预测值/%	预警数	灵敏度/%	特异度/%	约登指数/%	阳性预测值/%	预警数	灵敏度/%	特异度/%	约登指数/%	阳性预测值/%	预警数	灵敏度/%	特异度/%	约登指数/%	阳性预测值/%
ARS	240	0	76.89	-	0	49	0	91.17	-	0	18	0	88.89	-	0	0	0	100.00	-	0	246	2.08	97.95	0.04	0.41
SHMS	675	72.95	88.84	61.80	43.56	261	78.89	59.49	38.38	27.20	3 179	92.37	44.44	36.82	10.29	228	75.81	64.47	40.28	41.23	5	10.42	100.00	10.42	100.00
WMS	525	86.85	93.36	80.21	66.67	153	78.89	65.66	44.55	46.41	554	85.31	96.71	82.02	54.51	170	87.10	71.76	58.86	63.53	31	64.58	100.00	64.58	100.00

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参考文献(10)

[1]	肖林, 赵冰. 学校传染病聚集性疫情风险防控定量评估指标构建及应用[J]. 中国公共卫生管理, 2021, 37(2): 237-240. https://www.cnki.com.cn/Article/CJFDTOTAL-GGWS202102029.htm XIAO L, ZHAO B. Establishment and application of quantitative evaluation index for risk prevention and control of cluster infectious diseases in the school[J]. Chin J Public Health Manage, 2021, 37(2): 237-240. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GGWS202102029.htm
[2]	孙秀梅, 孙鑫贵, 刘晓峰, 等. 北京市2010—2020年学校突发传染病事件流行病学特征[J]. 中国学校卫生, 2022, 43(4): 622-626, 631. doi: 10.16835/j.cnki.1000-9817.2022.04.034 SUN X M, SUN X G, LIU X F, et al. Epidemiological characteristics of school outbreaks of infectious diseases in Beijing from 2010 to 2020[J]. Chin J Sch Health, 2022, 43(4): 622-626, 631. (in Chinese) doi: 10.16835/j.cnki.1000-9817.2022.04.034
[3]	李曦亮, 任美璇, 董爱虎, 等. 广西2010—2019年学校传染病突发事件流行特征分析[J]. 现代预防医学, 2022, 49(1): 17-20. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF202201005.htm LI X L, REN M X, DONG A H, et al. Epidemiological analysis on infectious diseases emergenciesat schools in Guangxi, 2010-2019[J]. Mod Prev Med, 2022, 49(1): 17-20. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF202201005.htm
[4]	高慧, 仲委, 李莉, 等. 新形势下我国传染病监测系统发展的思考与建议[J]. 中国医院管理, 2020, 40(7): 54-55. https://www.cnki.com.cn/Article/CJFDTOTAL-YYGL202007025.htm GAO H, ZHONG W, LI L, et al. Thoughts and suggestions on the development of China's infectious disease surveillance system under the new situation[J]. Chin Hospit Manage, 2020, 40(7) : 54-55. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YYGL202007025.htm
[5]	邓源, 任翔, 黄硕, 等. 大数据在传染病监测预警中的主要研究与应用进展[J]. 疾病监测, 2022, 37(8): 1003-1009. https://www.cnki.com.cn/Article/CJFDTOTAL-JBJC202208006.htm DENG Y, REN X, HUANG S, et al. Progress in research and application of big data in surveillance and early warming of infectious diseases[J]. Dis Surveill, 2022, 37(8): 1003-1009. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JBJC202208006.htm
[6]	杜明梅, 刘运喜. 我国传染病监测预警系统的发展与应用[J]. 中华医院感染学杂志, 2022, 32(6): 801-804. https://www.cnki.com.cn/Article/CJFDTOTAL-ZHYY202206001.htm DU M M, LIU Y X. Development and application of infectious diseases monitoring and early warning system in China[J]. Chin J Nosocomiol, 2022, 32(6): 801-804. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZHYY202206001.htm
[7]	赖圣杰, 冯录召, 冷志伟, 等. 传染病暴发早期预警模型和预警系统概述与展望[J]. 中华流行病学杂志, 2021, 42(8): 1330-1335. LAI S J, FENG L Z, LENG Z W, et al. Summary and prospect of early warning models and systems for infectious disease outbreaks[J]. Chin J Epidemiol, 2021, 42(8): 1330-1335. (in Chinese)
[8]	代吉亚, 宋铁, 郭汝宁, 等. 2014—2019年广东省传染病自动预警系统运行效果评价[J]. 预防医学论坛, 2020, 26(10): 729-731, 735. https://www.cnki.com.cn/Article/CJFDTOTAL-YXWX202010005.htm DAI J Y, SONG T, GUO R N, et al. Evaluation on operational effect of automatic early warning system for infectious diseases, Guangdong province, 2014-2019[J]. Prev Med Trib, 2020, 26(10): 729-731, 735. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YXWX202010005.htm
[9]	杨维中, 兰亚佳, 吕炜, 等. 建立我国传染病智慧化预警多点触发机制和多渠道监测预警机制[J]. 中华流行病学杂志, 2020, 41(11): 1753-1757. YANG W Z, LAN Y J, LYU W, et al. Establishment of multi-point trigger and multi-channel surveillance mechanism for intelligent early warning of infectious disease in China[J]. Chin J Epidemiol, 2020, 41(11) : 1753-1757. (in Chinese)
[10]	蒋琦, 陶沁, 吴军, 等. 贵州省传染病疫情预警与应用实践[J]. 疾病监测, 2020, 35(7): 633-636. https://www.cnki.com.cn/Article/CJFDTOTAL-JBJC202007022.htm JIANG Q, TAO Q, WU J, et al. Establishment and application of early warning of infectious disease in Guizhou[J]. Dis Surveill, 2020, 35(7): 633-636. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JBJC202007022.htm