Ecole Nationale Vétérinaire de Toulouse, Institut National de Recherche Pour L'Agriculture, L'Alimentation Et L'Environnement, Unité Mixte de Recherche Interactions Hôtes Agents Pathogènes, Université de Toulouse, 31076, Toulouse, France.
Reneco International Wildlife Consultants LLC, PO Box 61741, Abu Dhabi, United Arab Emirates.
Sci Rep. 2021 Feb 10;11(1):3491. doi: 10.1038/s41598-020-79184-3.
To understand the dynamics of a pathogen in an animal population, one must assess how the infection status of individuals changes over time. With wild animals, this can be very challenging because individuals can be difficult to trap and sample, even more so since they are tested with imperfect diagnostic techniques. Multi-event capture-recapture models allow analysing longitudinal capture data of individuals whose infection status is assessed using imperfect tests. In this study, we used a two-year dataset from a longitudinal field study of peridomestic wild bird populations in the United Arab Emirates during which thousands of birds from various species were captured, sampled and tested for Newcastle disease virus exposure using a serological test. We developed a multi-event capture-recapture model to estimate important demographic and epidemiological parameters of the disease. The modelling outputs provided important insights into the understanding of Newcastle disease dynamics in peridomestics birds, which varies according to ecological and epidemiological parameters, and useful information in terms of surveillance strategies. To our knowledge, this study is the first attempt to model the dynamics of Newcastle disease in wild bird populations by combining longitudinal capture data and serological test results. Overall, it showcased that multi-event capture-recapture models represent a suitable method to analyse imperfect capture data and make reliable inferences on infectious disease dynamics in wild populations.
要了解病原体在动物种群中的动态，必须评估个体的感染状况随时间如何变化。对于野生动物来说，这是非常具有挑战性的，因为即使使用不完善的诊断技术，个体也很难捕捉和采样，而且更难捕捉和采样。多事件捕获-再捕获模型允许分析使用不完善的测试来评估个体感染状况的个体的纵向捕获数据。在这项研究中，我们使用了来自阿拉伯联合酋长国两年的纵向野鸟种群现场研究的数据集，在此期间，数千只来自不同物种的鸟类被捕获、采样并使用血清学试验检测接触新城疫病毒。我们开发了一个多事件捕获-再捕获模型来估计疾病的重要人口统计学和流行病学参数。模型输出为了解家养鸟类中新城疫的动态提供了重要的见解，这些动态因生态和流行病学参数而异，并提供了有价值的监测策略信息。据我们所知，这是首次尝试通过结合纵向捕获数据和血清学试验结果来模拟野生鸟类中新城疫的动态。总体而言，它展示了多事件捕获-再捕获模型是一种分析不完善捕获数据并对野生动物传染病动态进行可靠推断的合适方法。
