Analysis of Lifetime Mortality Trajectories in Wildlife Disease Research: BaSTA and Beyond
Analysis of Lifetime Mortality Trajectories in Wildlife Disease Research: BaSTA and Beyond
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野生动物疾病研究中终生死亡率轨迹分析：BaSTA 及其他
DOI：
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
D. Hodgson
中科院分区：
文献类型：
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作者：
Dave W. Hudson;R. Delahay;R. Mcdonald;T. McKinley;D. Hodgson
野生动物宿主是世界范围内各种人类和牲畜感染的重要宿主，在某些情况下，野生动物种群受到疾病的威胁。然而，野生动物疾病很难监测，我们往往缺乏对基本流行病学参数的了解，而这些参数可能会为疾病管理和有针对性的干预措施的设计提供信息。疾病对宿主生存的影响通常与年龄有关，但传统的流行病学模型往往使用简单的宿主年龄分类。死亡轨迹分析提供了了解疾病对特定年龄的影响和揭示整个生命史流行病学模式的机会。在这里，我们使用贝叶斯生存轨迹分析（BaSTA）软件来分析捕获标记再捕获数据从人口的野生獾Meles Meles自然感染牛分枝杆菌，结核病的病原体在獾和牛。我们揭示了非恒定的死亡率轨迹，并表明感染夸大了老年死亡率的年龄依赖性增加。这项研究为獾的精算衰老提供了证据，獾是一种以前被认为在一生中都会显示恒定死亡率的物种。我们的案例研究展示了死亡轨迹分析在野生动物疾病研究中的应用，但也突出了重要的局限性。我们建议在流行病学研究中使用BaSTA进行死亡率轨迹分析，但也建议结合可以包括诊断不确定性和随着年龄增长宿主在疾病状态之间移动的方法。我们建议未来将多状态和多事件建模框架的组合用于包含年龄变化疾病状态的复杂系统。
Wildlife hosts are important reservoirs of a wide range of human and livestock infections worldwide, and in some instances, wildlife populations are threatened by disease. Yet wildlife diseases are difficult to monitor, and we often lack an understanding of basic epidemiological parameters that might inform disease management and the design of targeted interventions. The impacts of disease on host survival are generally associated with age, yet traditional epidemiological models tend to use simplistic categories of host age. Mortality trajectory analysis provides the opportunity to understand age-specific impacts of disease and uncover epidemiological patterns across complete life histories. Here, we use Bayesian survival trajectory analysis (BaSTA) software to analyse capture-mark-recapture data from a population of wild badgers Meles meles naturally infected with Mycobacterium bovis, the causative agent of tuberculosis in badgers and cattle. We reveal non-constant mortality trajectories, and show that infection exaggerates an age-dependent increase in late-life mortality. This study provides evidence for actuarial senescence in badgers, a species previously believed to display constant mortality throughout life. Our case study demonstrates the application of mortality trajectory analysis in wildlife disease research, but also highlights important limitations. We recommend BaSTA for mortality trajectory analysis in epidemiological research, but also suggest combining approaches that can include diagnostic uncertainty and the movement of hosts between disease states as they age. We recommend future combinations of multi-state and multi-event modelling frameworks for complex systems incorporating age-varying disease states.
DOI：
10.1093/gerona/57.2.b69
发表时间：
2002-02-01
影响因子：
5.1
作者：
Ricklefs, RE;Scheuerlein, A
通讯作者：
Scheuerlein, A