Statistical Models for Anthrax
Statistical Models for Anthrax
批准号:
6561227
负责人:
RONALD S BROOKMEYER
金额:
$24.53万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-09-30 至 2004-08-31
关键词:
中文摘要
描述(申请人提供):本申请的目标是开发炭疽病暴发和吸入性炭疽病发病机制的统计模型。由于吸入性炭疽相对于其他疾病的实验室和实地研究数据有限,必须通过开发和应用最先进的统计方法以及数学和统计模型,从现有数据中收集尽可能多的信息。具体目标有三个:
1.建立炭疽暴发的统计模型。这些模型将使人们能够估计炭疽疫情的规模、抗菌素预防的影响、疫情结束的可能性以及病例接触孢子的可能日期。这些方法将应用于2001年美国炭疽疫情。这些方法的性能和操作特点将通过计算机模拟进行评估。这些方法将被扩展到开发统计算法,这些算法可以用来预测和表征未来的炭疽疫情。
2.建立吸入性炭疽病潜伏期分布的统计和数学模型,考虑年龄和吸入孢子数量的依赖关系。这些模型将基于对1979年斯维尔德洛夫斯克疫情的重新分析以及其他已发表的实验和实地研究。
3.对所提出的模型和方法的基本假设进行敏感性分析,并量化结果中的统计误差。这项工作将讨论结果对潜育期分布参数形式的敏感性,参数的可信区间程序,以及孢子在大气中重新悬浮或延长孢子循环等现象的影响。这项工作将取决于具体目标1和2的结果。
英文摘要
DESCRIPTION (provided by applicant): The objective of this application is to develop statistical models for anthrax outbreaks and the pathogenesis of inhalation anthrax. Because of limited laboratory and field study data on inhalation anthrax relative to other diseases, it is imperative to glean as much information as possible from the available data through development and application of state-of-the-art statistical methods and mathematical and statistical models. There are three specific aims:
1. Develop statistical models for anthrax outbreaks. These models would allow one to estimate the size of an anthrax outbreak, the impact of antimicrobial prophylaxis, the probability that an outbreak has ended, and the likely date cases were exposed to the spores. The methods will be applied to the 2001 U.S anthrax outbreak. The performance and operating characteristics of the methods will be evaluated by computer simulation. The methods will be extended to develop statistical algorithms that could be used to forecast and characterize future anthrax outbreaks.
2. Develop statistical and mathematical models for the incubation period distribution of inhalation anthrax that account for dependence on age and numbers of inhaled spores. These models will be based on reanalysis of the Sverdlovsk outbreak in 1979 as well as other published experimental and field studies.
3. Perform sensitivity analyses to underlying assumptions of the proposed models and methods, and, quantify the statistical error in the results. This work will address sensitivity of the results to the parametric form of the incubation period distribution, confidence interval procedures for parameters, and impact of phenomenon such as resuspension of spores or prolonged spore circulation in the atmosphere. This work will depend on results from specific aims 1 and 2.
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