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Hierarchical Bayesian Modeling of Disease Dynamics: A Case Example Using Chronic Wasting Disease

Hierarchical Bayesian Modeling of Disease Dynamics: A Case Example Using Chronic Wasting Disease
疾病动态的分层贝叶斯模型:使用慢性消耗性疾病的案例
批准号:
0914489
负责人:
N. Thompson Hobbs
金额:
$249.99万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-08-01 至 2015-09-30

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中文摘要
翻译
慢性消耗性疾病(CWD)困扰着鹿科成员。与绵羊和牛的疾病(牛海绵状脑病或“疯牛病”)相似,CWD是由错误折叠的蛋白质引起的,这些蛋白质抵抗细胞内的酶的分解。这些蛋白质不可避免地会造成致命的神经损伤。CWD对北美的鹿种群构成了严重威胁,随着时间的推移,还会对全世界的鹿种群构成严重威胁。理解和管理慢性萎缩性脑病依赖于开发代表疾病传播方式的预测模型。研究人员将对野生骡鹿种群进行实地研究,以开发出解决三个问题的模型:1)传播机制是什么?2)有多少易感个体被单一感染的个体感染?3)个体的基因构成如何与其接触CWD的情况相互作用,以确定其感染风险?动物将被捕获,并用无线电发射器进行标记,以便调查人员在以后重新捕获它们。将确定被标记的个人的疾病状况,并从他们身上提取样本进行基因分析。使用基于捕获历史和每次捕获时的动物疾病状态的方法,将根据个体的遗传学、运动模式和与其他个体的关联来估计个体的感染风险。该项目将支持对这种疾病的管理决策,如果不加以控制,这种疾病可能会对生态系统和农村经济造成严重损害。该项目的广泛影响包括1)研究生的创新培训,2)K-12教师的课程开发和研究经验,3)面向参观落基山国家公园的公民,4)支持北美西部野生动物机构关于疾病管理的决策,以及5)对研究社区进行项目所使用的建模方法的培训。
英文摘要
Chronic wasting disease (CWD) afflicts members of the deer family. Similar to diseases in sheep (scrapie) and cattle (bovine spongiform encephalopathy or "mad cow disease"), CWD is caused by misfolded proteins that resist breakdown by enzymes within cells. These proteins cause inevitably fatal, neurological damage. CWD poses grave threats to deer populations in North America and, in the fullness of time, throughout the world. Understanding and managing CWD depends on developing predictive models that represent how the disease spreads. The investigators will conduct field studies on wild populations of mule deer to develop models addressing three questions: 1) What is the mechanism of transmission? 2) How many susceptible individuals are infected by a single infected one? 3) How does an individual's genetic make-up interact with its exposure to CWD to determine its risk of infection? Animals will be captured and marked with radio transmitters to allow the investigators to recapture them at a later date. The disease status of marked individuals will be determined and samples will be taken from them for genetic analysis. Using methods based on histories of captures and the animals disease status at each capture, an individual's risk of infection will be estimated based on its genetics, movement patterns, and associations with other individuals. This project will support decisions on management of a disease that, left unchecked, is likely to cause grave harm to ecosystems and to rural economies. Broader impacts of the project include 1) innovative training of graduate students, 2) curriculum development and research experience for K-12 teachers, 3) outreach to citizens visiting Rocky Mountain National Park, 4) support for decisions on disease management by wildlife agencies in western North America, and 5) training for the research community in the modeling methods used by the project.
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