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A Bayesian model identifying locations at risk from human-transported exotic pathogens
Natural Resource Modeling ( IF 1.6 ) Pub Date : 2021-05-04 , DOI: 10.1111/nrm.12307
Steven C. McKelvey 1 , Frank H. Koch 2 , William D. Smith 2 , Kelly R. Hawley 3, 4
Affiliation  

A two-phase Bayesian model is presented for updating risk assessments for locations susceptible to infection by exotic pathogens. Human transportation from previously infected regions to uninfected regions is the main dispersal mechanism. Information embedded in patterns within the transportation flow are exploited in the update process. We explore the sensitivity of the model's outputs to changes in inputs. A sample application of the model to sudden oak death, using fictitious infection data, is performed.

中文翻译:

贝叶斯模型识别人类传播的外来病原体的风险位置

提出了一个两阶段贝叶斯模型,用于更新易受外来病原体感染的位置的风险评估。人类从先前感染地区到未感染地区的运输是主要的传播机制。在更新过程中利用了嵌入在交通流模式中的信息。我们探索模型输出对输入变化的敏感性。使用虚构的感染数据,将模型应用于橡木猝死的示例。
更新日期:2021-05-04
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