社群媒体可用于预测流行病


  【24drs.com】新研究认为,海地2010年爆发的霍乱分析方面,透过非正式管道(例如HealthMap新闻媒体和Twitter)及早报告案例的趋势, 与正式通报的案例资料相当一致。
  
  哈佛医学院、波士顿儿童医院小儿科研究员Rumi Chunara博士,在2010年1月的美国热带医学与卫生期刊中发表他们的研究结果。
  
  作者们指出,疾病爆发的最初几天内,医师、公卫官方、决策者都需要迅速可得的资料,以对即将发生的流行病拟定计划,而透过官方公卫机构搜集资料与报告往往需时数周。
  
  Chunara博士等人报告指出,这是首度研究指出非正式的社群与新闻媒体可以更快地一窥演变中的流行病,他们指出,这提供了采取更即时且有效的介入机会。
  
  这篇研究中,作者们评估了3种讯息来源的案例数量:HealthMap(监测全球疾病爆发新闻的一个网站)与Twitter,这两者被视为非正式管道,另一则是海地公卫部[MSPP]的官方资料,这被视为正式管道。
  
  他们共检视了3期资料:爆发初期(2010年10月20日至2010年11月3日)、飓风Tomas侵袭期间(2010年11月3日至2010年12月1日)以及爆发开始后的100天。
  
  第一期, HealthMap有995件关于疫情爆发的讯息,65,728篇霍乱相关的推文,在飓风Tomas侵袭期间,有2,248件 HealthMap警讯与84,992篇推文。整体而言,在爆发后的100天内,研究者掌握了188,819篇推文与4,697件 HealthMap初步警讯,这些资料和官方的MSPP案例量明显相关,但是提早了2周。
  
  作者们也指出,这3个资料来源可以作为估计流行病的关键参数 -有效再生数,从累积的非正式资料与MSPP报告的爆发案例建立流行病曲线。
  
  初期,估计有效再生数分别是1.54-6.89 (非官方来源)与1.27- 3.72 (官方来源),在飓风Tomas期间,有效再生数将近重迭,分别是1.04-1.51 (非官方来源)和1.06-1.73 (官方来源)。
  
  作者们指出,近乎即时的估计流行病活性可对疾病爆发的轨迹提供有价值的见解,帮助预期流行病的扩散程度、对控制措施之所需提供指引,此处所报告的方法与资料类型可以应用到其它疾病与疾病活性的其它指标,不过,他们也指出,非正式管道可能包括的偏见必须被纳入考量。
  
  资料来源:http://www.24drs.com/professional/list/content.asp?x_idno=6707&x_classno=0&x_chkdelpoint=Y
  

Social Media May Be Useful in Predicting Epidemics

By Emma Hitt, PhD
Medscape Medical News

January 13, 2012 — Trends in the volume of cases reported early through informal sources — such as the HealthMap news media and Twitter — correlated well with officially reported case data in an analysis of the 2010 cholera outbreak in Haiti, new research suggests.

Rumi Chunara, PhD, research fellow in pediatrics from the Children's Hospital Boston at Harvard Medical School in Massachusetts, and colleagues published their findings in the January 2012 issue of the American Journal of Tropical Medicine and Hygiene.

The authors note that "[i]n the early days of a disease outbreak, clinicians, public health officials, and policy makers need rapidly available data to plan a response to an impending epidemic" and that "[d]ata collected and reported through official public health institutions is often not available for weeks..."

Dr. Chunara and colleagues report that theirs is the first study to demonstrate the use of informal social and news media "to gain early insight into an evolving epidemic." They state that this provides an opportunity "for the implementation of more timely and effective interventions."

In this study, the authors evaluated trends in volume of cases reported through 3 sources: HealthMap (a Web site that monitors news of outbreaks around the world) and Twitter, both of which are considered "informal," and data from a government body, the Haitian Ministry of Public Health (Ministere de la Sante Publique et de la Population [MSPP]), which were considered "official."

They examined the data from 3 periods: during the initial phase of the outbreak (October 20, 2010 -November 3, 2010), around the timing of Hurricane Tomas (November 3, 2010 - December 1, 2010), and 100 days from the start of the outbreak.

In the first period, there were 995 HealthMap alerts about the outbreak and 65,728 cholera-related tweets, and in the period of influence by Hurricane Tomas, there were 2248 HealthMap alerts and 84,992 tweets. In total, the researchers captured 188,819 tweets and 4697 HealthMap primary alerts from the period lasting 100 days after the initial upsurge of the outbreak. These data significantly correlated with the "official" MSPP case volume, but were available up to 2 weeks earlier.

The authors also demonstrated the potential use of each of these 3 sources in estimating a key epidemic parameter, the effective reproductive number, by creating epidemic curves from the cumulative volume of informal data and MSPP-reported case burden.

The estimates of effective reproductive number for the initial period ranged from 1.54 to 6.89 (informal sources) and from 1.27 to 3.72 (official sources). During the period of Hurricane Tomas, the effective reproductive numbers were nearly overlapping, ranging from 1.04 to 1.51 (informal sources) and 1.06 to 1.73 (official sources).

"Near real-time estimates of epidemic activity may provide valuable insights into the trajectory of an infectious disease outbreak, help project the spread of an epidemic, and provide guidance on the magnitude of control measures needed," the authors note. They add that "the methods and data types presented here can be extended to other diseases and to other metrics of disease activity." However, they also add that "[i]nformal data sources may contain biases that should be considered."

The study was supported by a grant from Google.org, the National Library of Medicine, the National Institutes of Health, and the National Institute of Allergy and Infectious Diseases. The authors have disclosed no relevant financial relationships.

Am J Trop Med Hyg . 2012;86:39-45.

    
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