Joshua Hewitt, Grete Wilson-Henjum, Derek T. Collins, Jourdan M. Ringenberg, Christopher A. Quintanal, Robert Pleszewski, Jeffrey C. Chandler, Thomas J. DeLiberto, Kim M. Pepin
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引用次数: 0
摘要
野生动物疾病监测计划和研究跟踪感染情况,并确定野生种群、人类和农业的风险因素。通常情况下,会从个体身上采集多种类型的样本,以提供有关动物感染历史的更完整信息。通过流行病学过程模型联合分析多种数据流以研究疾病出现和感染驱动因素的方法仍未得到充分发展。联合分析方法可以更全面地分析所有可用数据,更精确地量化流行过程、疫情爆发状况和风险。我们提出了一种配对数据建模方法,可对来自个体的多个样本进行分析。我们使用 "表征图",通过分层统计观测模型将配对数据与流行病学过程联系起来。我们的方法可以提供贝叶斯和频数估计的流行病学参数和状态。我们的方法还可以结合检验灵敏度和特异性,并提出了模型拟合诊断方法。我们通过使用成对病原体和抗体检测试验来估算广泛应用的易感、感染、恢复(SIR)模型的参数和感染轨迹的需要来激发我们的方法。我们提供了将特征描述图与任意过程模型和数据集联系起来的通用公式,以及能更好地适应配对数据的扩展 SIR 模型。我们通过模拟发现,与非配对数据相比,配对数据能更有效地估算 SIR 参数,所需的个体样本也要少 5 到 10 倍。我们使用我们的方法研究了美国三个县的野生白尾鹿(Odocoileus virginianus)的 SARS-CoV-2 感染情况。平均感染时间的估计值与圈养动物的研究结果相吻合。据估计,三个县受感染鹿的平均累计比例为 73%,基本繁殖数 (R0) 为 1.88。野生动物疾病监测计划和调查研究可以使用我们的方法来联合分析配对数据,以估计流行病学过程参数并追踪疫情。在取样有限的情况下,配对数据分析可以提高精确度和准确性。我们的方法使用了一般统计理论,使应用范围超越了我们考虑的 SIR 模型,并扩展到更复杂的配对数据实例。这些方法还可以嵌入到更大的分层模型中,以提供景观尺度的风险评估并确定感染的驱动因素。
期刊介绍:
A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas.
MEE publishes methodological papers in any area of ecology and evolution, including:
-Phylogenetic analysis
-Statistical methods
-Conservation & management
-Theoretical methods
-Practical methods, including lab and field
-This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual.
A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.