云南省边境地区症状监测预警系统的开发与实践

宋肖肖; 蔡乐; 刘伟; 崔文龙; 彭霞; 李琼芬; 董毅; 杨明东; 吴波清; 岳太科; 范建华; 李园园; 李燕

Abstract

宋肖肖,蔡乐,刘伟,崔文龙,彭霞,李琼芬,董毅,杨明东,吴波清,岳太科,范建华,李园园,李燕.云南省边境地区症状监测预警系统的开发与实践[J].Chinese journal of Epidemiology,2023,44(5):845-850

云南省边境地区症状监测预警系统的开发与实践

Development and application syndromic surveillance and early warning system in border area in Yunnan Province

Received:October 13, 2022

DOI：10.3760/cma.j.cn112338-20221013-00882

KeyWord: 传染病症状监测系统预警边境地区

English Key Word: Infectious disease Syndromic surveillance system Early warning Border area

FundProject:云南公共卫生与疾病防控协同创新中心项目(2014YN-PHXT23)

Author Name	Affiliation	E-mail
Song Xiaoxiao	School of Public Health, Kunming Medical University, Kunming 650500, China
Cai Le	School of Public Health, Kunming Medical University, Kunming 650500, China
Liu Wei	School of Public Health, Kunming Medical University, Kunming 650500, China
Cui Wenlong	School of Public Health, Kunming Medical University, Kunming 650500, China
Peng Xia	Yunnan Provincial Center for Disease Control and Prevention, Kunming 650022, China
Li Qiongfen	Yunnan Provincial Center for Disease Control and Prevention, Kunming 650022, China
Dong Yi	Yunnan Provincial Institute for Endemic Diseases Control and Prevention, Dali 671000, China
Yang Mingdong	Yunnan Provincial Institute of Parasitic Diseases, Pu'er 665000, China
Wu Boqing	Dehong Dai and Jingpo Autonomous Prefecture Center for Disease Control and Prevention, Yunnan Province, Mangshi 678400, China
Yue Taike	Dehong Dai and Jingpo Autonomous Prefecture Center for Disease Control and Prevention, Yunnan Province, Mangshi 678400, China
Fan Jianhua	Xishuangbanna Dai Autonomous Prefectural Center for Disease Control and Prevention, Yunnan Province, Jinghong 666100, China
Li Yuanyuan	Xishuangbanna Dai Autonomous Prefectural Center for Disease Control and Prevention, Yunnan Province, Jinghong 666100, China
Li Yan	School of Public Health, Kunming Medical University, Kunming 650500, China	yanli20021965@21cn.com

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Abstract:

目的利用信息化技术，在云南省边境地区建立持续动态症状监测预警系统，并探讨其有效性和及时性，以提升边境地区传染病防控能力。方法选择3个边境县，以全覆盖的方式，于2016年1月至2018年2月持续监测医疗机构14个症状及6个症候群，收集小学每天学生缺勤信息和边境口岸入境人员发热信息，构建基于手机和电脑平台的症状监测预警系统。结果采用EARS-3C和Kulldorff时空扫描的预警模型，发现皮疹、流感样症状和小学缺勤等多个监测信号源对手足口病、流感和水痘等常见传染病预警有较高的灵敏度和特异度（可提前1~5 d预警）。系统简便易用，安全性和可行性较强，以交互式图表及可视化地图的方式展示，相关人员能够随时掌握监测数据情况和预警信号的变化，及时采取处置措施。结论该系统科学有效、操作方便，能实时发现边境地区常见传染病的暴发或聚集事件，实现及时采取有效干预措施，减少本地及跨境传染病暴发的风险，具有实际应用价值。

English Abstract:

Objective To establish a dynamic syndromic surveillance system in the border areas of Yunnan Province based on information technology, evaluate its effectiveness and timeliness in the response to common communicable disease epidemics and improve the communicable disease prevention and control in border areas. Methods Three border counties were selected for full coverage as study areas, and dynamic surveillance for 14 symptoms and 6 syndromes were conducted in medical institutions, the daily collection of information about students' school absence in primary schools and febrile illness in inbound people at border ports were conducted in these counties from January 2016 to February 2018 to establish an early warning system based on mobile phone and computer platform for a field experimental study. Results With syndromes of rash, influenza-like illness and the numbers of primary school absence, the most common communicable disease events, such as hand foot and mouth disease, influenza and chickenpox, can be identified 1-5 days in advance by using EARS-3C and Kulldorff time-space scanning models with high sensitivity and specificity. The system is easy to use with strong security and feasibility. All the information and the warning alerts are released in the form of interactive charts and visual maps, which can facilitate the timely response. Conclusions This system is highly effective and easy to operate in the detection of possible outbreaks of common communicable diseases in border areas in real time, so the timely and effective intervention can be conducted to reduce the risk of local and cross-border communicable disease outbreaks. It has practical application value.

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