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互联网监测在突发公共卫生事件防控中的重要性:来自甲型H7N9禽流感疫情期间一项数字流行病学研究的证据

Importance of Internet surveillance in public health emergency control and prevention: evidence from a digital epidemiologic study during avian influenza A H7N9 outbreaks.

作者信息

Gu Hua, Chen Bin, Zhu Honghong, Jiang Tao, Wang Xinyi, Chen Lei, Jiang Zhenggang, Zheng Dawei, Jiang Jianmin

机构信息

Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.

出版信息

J Med Internet Res. 2014 Jan 17;16(1):e20. doi: 10.2196/jmir.2911.

Abstract

BACKGROUND

Outbreaks of human infection with a new avian influenza A H7N9 virus occurred in China in the spring of 2013. Control and prevention of a new human infectious disease outbreak can be strongly affected by public reaction and social impact through the Internet and social media.

OBJECTIVE

This study aimed to investigate the potential roles of Internet surveillance in control and prevention of the human H7N9 outbreaks.

METHODS

Official data for the human H7N9 outbreaks were collected via the China National Health and Family Planning Committee website from March 31 to April 24, 2013. We obtained daily posted and forwarded number of blogs for the keyword "H7N9" from Sina microblog website and a daily Baidu Attention Index (BAI) from Baidu website, which reflected public attention to the outbreak. Rumors identified and confirmed by the authorities were collected from Baidu search engine.

RESULTS

Both daily posted and forwarded number and BAI for keyword H7N9 increased quickly during the first 3 days of the outbreaks and remained at a high level for 5 days. The total daily posted and forwarded number for H7N9 on Sina microblog peaked at 850,000 on April 3, from zero blogs before March 31, increasing to 97,726 on April 1 and to 370,607 on April 2, and remaining above 500,000 from April 5-8 before declining to 208,524 on April 12. The total daily BAI showed a similar pattern of change to the total daily posted and forwarded number over time from March 31 to April 12. When the outbreak locations spread, especially into other areas of the same province/city and the capital, Beijing, daily posted and forwarded number and BAI increased again to a peak at 368,500 and 116,911, respectively. The median daily BAI during the studied 25 days was significantly higher among the 7 provinces/cities with reported human H7N9 cases than the 2 provinces without any cases (P<.001). So were the median daily posted and forwarded number and daily BAI in each province/city except Anhui province. We retrieved a total of 32 confirmed rumors spread across 19 provinces/cities in China. In all, 84% (27/32) of rumors were disseminated and transmitted by social media.

CONCLUSIONS

The first 3 days of an epidemic is a critical period for the authorities to take appropriate action through Internet surveillance to prevent and control the epidemic, including preparation of personnel, technology, and other resources; information release; collection of public opinion and reaction; and clarification, prevention, and control of rumors. Internet surveillance can be used as an efficient and economical tool to prevent and control public health emergencies, such as H7N9 outbreaks.

摘要

背景

2013年春季中国出现了人感染新型甲型H7N9禽流感病毒疫情。新型人类传染病疫情的防控会受到公众通过互联网和社交媒体做出的反应及产生的社会影响的强烈影响。

目的

本研究旨在探讨互联网监测在人感染H7N9禽流感疫情防控中的潜在作用。

方法

通过中国国家卫生和计划生育委员会网站收集2013年3月31日至4月24日人感染H7N9禽流感疫情的官方数据。我们从新浪微博网站获取了关键词“H7N9”每日发布和转发的博客数量,以及从百度网站获取了每日百度关注度指数(BAI),该指数反映了公众对疫情的关注。从百度搜索引擎收集经官方确认的谣言。

结果

疫情爆发的前3天,关键词H7N9的每日发布和转发数量以及BAI均迅速增加,并在5天内保持在较高水平。新浪微博上H7N9每日发布和转发的总数在4月3日达到峰值85万条,3月31日前为零博客,4月1日增至97726条,4月2日增至370607条,4月5日至8日保持在50万条以上,4月12日降至208524条。从3月31日至4月12日,每日百度关注度指数的总体变化趋势与每日发布和转发总数相似。当疫情爆发地点扩散,特别是扩散到同一省/市的其他地区以及首都北京时,每日发布和转发数量以及BAI再次上升至峰值,分别为368500条和116911。在报告有人感染H7N9病例的7个省/市中,研究的25天内每日百度关注度指数中位数显著高于无病例的2个省(P<0.001)。除安徽省外,每个省/市的每日发布和转发中位数以及每日百度关注度指数中位数也是如此。我们共检索到在中国19个省/市传播的32条经确认的谣言。其中,84%(27/32)的谣言是通过社交媒体传播的。

结论

疫情爆发的前3天是当局通过互联网监测采取适当行动防控疫情的关键时期,包括人员、技术和其他资源的准备;信息发布;收集公众意见和反应;以及澄清、预防和控制谣言。互联网监测可作为防控公共卫生突发事件(如H7N9疫情)的一种高效且经济的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b2a/3906895/1f90bd4a9600/jmir_v16i1e20_fig1.jpg

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