A Bayesian model identifying locations at risk from human‐transported exotic pathogens

Steven C. McKelvey; Frank H. H. Koch; William D. Smith; Kelly R. Hawley

doi:10.1111/nrm.12307

Treesearch

A Bayesian model identifying locations at risk from human‐transported exotic pathogens

Formally Refereed

Authors:

Steven C. McKelvey, Frank H. H. Koch, William D. Smith, Kelly R. Hawley

Year:

2021

Type:

Scientific Journal

Station:

Southern Research Station

DOI:

https://doi.org/10.1111/nrm.12307

Source:

Natural Resource Modeling

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Abstract

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.

Keywords

Bayesian analysis, human‐mediated pathways, infection detection and prevention, pathogen dispersal, Phytophthora ramorum, probabilistic network m

Citation

McKelvey, Steven C.; Koch, Frank H.; Smith, William D.; Hawley, Kelly R. 2021. A Bayesian model identifying locations at risk from human‐transported exotic pathogens. Natural Resource Modeling. 108(10): 1166-. https://doi.org/10.1111/nrm.12307.