Wilson James M, Polyak Marat G, Blake Jane W, Collmann Jeff
Argus Research Operations Center, Division of Integrated Biodefense, Imaging Science and Information System Center, Georgetown University, 2115 Wisconsin Ave, Suite 603, Washington, DC 20007, USA.
J Am Med Inform Assoc. 2008 Mar-Apr;15(2):158-71. doi: 10.1197/jamia.M2558. Epub 2007 Dec 20.
This paper presents a model designed to enable rapid detection and assessment of biological threats that may require swift intervention by the international public health community.
We utilized Strauss' grounded theory to develop an expanded model of social disruption due to biological events based on retrospective and prospective case studies. We then applied this model to the temporal domain and propose a heuristic staging model, the Wilson-Collmann Scale for assessing biological event evolution.
We retrospectively and manually examined hard copy archival local media reports in the native vernacular for three biological events associated with substantial social disruption. The model was then tested prospectively through media harvesting based on keywords corresponding to the model parameters.
Our heuristic staging model provides valuable information about the features of a biological event that can be used to determine the level of concern warranted, such as whether the pathogen in question is responding to established public health disease control measures, including the use of antimicrobials or vaccines; whether the public health and medical infrastructure of the country involved is adequate to mount the necessary response; whether the country's officials are providing an appropriate level of information to international public health authorities; and whether the event poses a international threat. The approach is applicable for monitoring open-source (public-domain) media for indications and warnings of such events, and specifically for markers of the social disruption that commonly occur as these events unfold. These indications and warnings can then be used as the basis for staging the biological threat in the same manner that the United States National Weather Service currently uses storm warning models (such as the Saffir-Simpson Hurricane Scale) to detect and assess threatening weather conditions.
Used as a complement to current epidemiological surveillance methods, our approach could aid global public health officials and national political leaders in responding to biological threats of international public health significance.
本文介绍了一个旨在实现对可能需要国际公共卫生界迅速干预的生物威胁进行快速检测和评估的模型。
我们利用施特劳斯的扎根理论,基于回顾性和前瞻性案例研究,开发了一个因生物事件导致社会混乱的扩展模型。然后,我们将该模型应用于时间领域,并提出了一个启发式分期模型——威尔逊 - 科尔曼生物事件演变评估量表。
我们回顾性地并人工检查了以当地母语撰写的硬拷贝存档本地媒体报道,这些报道涉及三起造成重大社会混乱的生物事件。然后,通过基于与模型参数对应的关键词进行媒体信息收集,对该模型进行前瞻性测试。
我们的启发式分期模型提供了有关生物事件特征的有价值信息,这些信息可用于确定应予以关注的程度,例如所涉病原体是否对既定的公共卫生疾病控制措施有反应,包括使用抗菌药物或疫苗;所涉国家的公共卫生和医疗基础设施是否足以做出必要反应;该国官员是否向国际公共卫生当局提供了适当水平的信息;以及该事件是否构成国际威胁。该方法适用于监测开源(公共领域)媒体,以获取此类事件的迹象和警告,特别是这些事件发生时通常会出现的社会混乱的标志。然后,这些迹象和警告可作为对生物威胁进行分期的基础,其方式与美国国家气象局目前使用风暴预警模型(如萨菲尔 - 辛普森飓风等级量表)来检测和评估威胁性天气状况相同。
作为当前流行病学监测方法的补充,我们的方法可帮助全球公共卫生官员和国家政治领导人应对具有国际公共卫生意义的生物威胁。