IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v149y2023icp1-11.html
   My bibliography  Save this article

Analytical Bayesian approach for the design of surveillance and control programs to assess pest-eradication success

Author

Listed:
  • Barnes, B.
  • Parsa, M.
  • Giannini, F.
  • Ramsey, D.

Abstract

Large invasive species eradication programs are undertaken to protect native biodiversity and agriculture. Programs are typically followed by a series of surveys to assess the likelihood of eradication success and, when residual pests are detected, small-scale control or ‘mop-ups’ are implemented to eliminate these infestations. Further surveys follow to confirm absence with ‘freedom’ declared when a target probability of absence is reached. Such biosecurity programs comprise many interacting processes — stochastic biological processes including growth, and response and control interventions — and are an important component of post-border biosecurity. Statistical frameworks formulated to contribute to the design and efficiency of these surveillance and control programs are few and, those available, rely on the simulation of the component processes. In this paper we formulate an analytical Bayesian framework for a general biosecurity program with multiple components to assess pest-eradication success. Our model incorporates stochastic growth and detection processes, and several pest control mechanisms. Survey results and economic considerations are also taken into account to support a range of biosecurity management decisions. Using a case study we demonstrate that solutions match published simulation results and extend the available analysis. Principally, we show how analytical solutions can offer a powerful tool to support the design of effective and cost-efficient biosecurity systems, and we establish some general principles that guide and contribute to robust design.

Suggested Citation

  • Barnes, B. & Parsa, M. & Giannini, F. & Ramsey, D., 2023. "Analytical Bayesian approach for the design of surveillance and control programs to assess pest-eradication success," Theoretical Population Biology, Elsevier, vol. 149(C), pages 1-11.
  • Handle: RePEc:eee:thpobi:v:149:y:2023:i:c:p:1-11
    DOI: 10.1016/j.tpb.2022.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580922000715
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2022.11.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rout, Tracy M. & Moore, Joslin L. & Possingham, Hugh P. & McCarthy, Michael A., 2011. "Allocating biosecurity resources between preventing, detecting, and eradicating island invasions," Ecological Economics, Elsevier, vol. 71(C), pages 54-62.
    2. Peter Caley & Simon C Barry, 2014. "Quantifying Extinction Probabilities from Sighting Records: Inference and Uncertainties," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-11, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sara Pasquali & Gianni Gilioli & Dirk Janssen & Stephan Winter, 2015. "Optimal Strategies for Interception, Detection, and Eradication in Plant Biosecurity," Risk Analysis, John Wiley & Sons, vol. 35(9), pages 1663-1673, September.
    2. İ. Esra Büyüktahtakın & Robert G. Haight, 2018. "A review of operations research models in invasive species management: state of the art, challenges, and future directions," Annals of Operations Research, Springer, vol. 271(2), pages 357-403, December.
    3. Barnes, B. & Parsa, M. & Giannini, F. & Ramsey, D., 2022. "Analytical Bayesian models to quantify pest eradication success or species absence using zero-sighting records," Theoretical Population Biology, Elsevier, vol. 144(C), pages 70-80.
    4. Kompas, Tom & Chu, Long & McKirdy, Simon & Thomas, Melissa & Van Der Merwe, Johann, 2023. "Optimal post-border surveillance against invasive pests to protect a valuable nature reserve and island asset," Ecological Economics, Elsevier, vol. 208(C).
    5. Carrasco, L. Roman & Cook, David & Baker, Richard & MacLeod, Alan & Knight, Jon D. & Mumford, John D., 2012. "Towards the integration of spread and economic impacts of biological invasions in a landscape of learning and imitating agents," Ecological Economics, Elsevier, vol. 76(C), pages 95-103.
    6. Dalmazzone, Silvana & Giaccaria, Sergio, 2014. "Economic drivers of biological invasions: A worldwide, bio-geographic analysis," Ecological Economics, Elsevier, vol. 105(C), pages 154-165.
    7. Kenneth R. Szulczyk, 2023. "Estimating the economic costs and mitigation of rice blast infecting the Malaysian paddy fields," SN Business & Economics, Springer, vol. 3(1), pages 1-21, January.
    8. Olaniyi, Oladokun Nafiu & Szulczyk, Kenneth R., 2020. "Estimating the economic damage and treatment cost of basal stem rot striking the Malaysian oil palms," Forest Policy and Economics, Elsevier, vol. 116(C).
    9. Peter Caley & David S L Ramsey & Simon C Barry, 2015. "Inferring the Distribution and Demography of an Invasive Species from Sighting Data: The Red Fox Incursion into Tasmania," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-18, January.
    10. Robert C. Cope & Joshua V. Ross & Talia A. Wittmann & Michael J. Watts & Phillip Cassey, 2019. "Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 35-53, January.
    11. Epanchin-Niell, Rebecca S. & Liebhold, Andrew M., 2015. "Benefits of invasion prevention: Effect of time lags, spread rates, and damage persistence," Ecological Economics, Elsevier, vol. 116(C), pages 146-153.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:thpobi:v:149:y:2023:i:c:p:1-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.