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中文摘要
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描述(由申请人提供): 本研究的长期目标是促进决策分析在生物监测中的应用。在不确定性和时间压力下,卫生部门的疾病监测人员面临着越来越多的高风险决策。造成这种情况的部分原因是生物恐怖主义和新出现的疾病的威胁,部分原因是它们建立了新的监测系统。这些系统收集的诊断准确性较低但较早的监测数据,以尽可能早地发现疾病爆发。 研究的具体目标是(1)使用标准决策分析技术构建具有代表性的生物监测决策问题的决策分析,以及(2)在分析师和流行病学家的决策支持系统中部署底层决策模型。 这项研究有可能提高公共卫生应对疫情的速度和效力,从而有可能降低发病率和死亡率。这项研究还可能通过为合理设定警报阈值提供依据来提高生物监测系统的效率。
英文摘要
DESCRIPTION (provided by applicant): The long-term objective of this research is to advance the use of decision analysis in biosurveillance. The disease surveillance staff in a health department face an increasing number of high-stakes decisions under uncertainty and time pressure. This situation is in part due to the threat of bioterrorism and emerging diseases and in part a result of new surveillance systems they have constructed. These systems collect less diagnostically precise--but earlier--surveillance data in an effort to detect disease outbreaks as early as possible. The specific aims of the research are to (1) construct decision analyses of representative bio-surveillance decision problems using standard decision analytic techniques, and (2) deploy the underlying decision models in a decision-support system for analysts and epidemiologists. The research has the potential to improve the speed and efficacy of public health response to outbreaks and thereby potentially reduce morbidity and mortality. The research also has the potential to increase the efficiency of bio-surveillance systems by providing a basis for rational setting of alarm thresholds.
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Probabilistic Disease Surveillance
UNIVERSITY OF PITTSBURGH CENTER FOR ADVANCED STUDY OF INFORMATICS IN PUBLIC HEALT
HK09-001, Centers of Excellence in Public Health Informatics
UNIVERSITY OF PITTSBURGH CENTER FOR ADVANCED STUDY OF INFORMATICS IN PUBLIC HEALT
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