IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v24y2004i1p237-253.html
   My bibliography  Save this article

Scenario Tree Modeling to Analyze the Probability of Classical Swine Fever Virus Introduction into Member States of the European Union

Author

Listed:
  • Clazien J. De Vos
  • Helmut W. Saatkamp
  • Mirjam Nielen
  • Ruud B. M. Huirne

Abstract

The introduction of classical swine fever virus (CSFV) into a country free of disease without vaccination may have huge consequences in terms of both disease spread and economic losses. More quantitative insight into the main factors determining the probability of CSFV introduction (PCSFV) is needed to optimally use resources for the prevention of CSFV introduction. For this purpose a spreadsheet model was constructed that calculates the annual PCSFV into member states of the European Union (EU). The scenario pathway approach was used as most probabilities in the model are very small. Probability distributions were used to take into account inherent variability of input parameters. The model contained pathways of CSFV introduction including the import of pigs and pork products, returning livestock trucks, and contacts with wild boar. All EU member states were included as possible sources of CSFV. Default results for the Netherlands showed a mean overall annual PCSFV of approximately 0.06, indicating that the Netherlands can expect CSFV introduction on average once every 18 years from the pathways and countries included in the model. Almost 65% of this probability could be attributed to the pathway of returning livestock trucks. The most likely sources of CSFV introduction were Germany, Belgium, and the United Kingdom. Although the calculated probabilities were rather low when compared with expert estimates and recent history, the most likely causes of CSFV introduction indicated by the model were considered to be realistic. It was therefore concluded that the model is a useful tool to structure and analyze information for decision making concerning the prevention of CSFV introduction.

Suggested Citation

  • Clazien J. De Vos & Helmut W. Saatkamp & Mirjam Nielen & Ruud B. M. Huirne, 2004. "Scenario Tree Modeling to Analyze the Probability of Classical Swine Fever Virus Introduction into Member States of the European Union," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 237-253, February.
  • Handle: RePEc:wly:riskan:v:24:y:2004:i:1:p:237-253
    DOI: 10.1111/j.0272-4332.2004.00426.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.0272-4332.2004.00426.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.0272-4332.2004.00426.x?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
    ---><---

    References listed on IDEAS

    as
    1. Elizabeth L. Anderson & Dale Hattis, 1999. "A. Uncertainty and Variability," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 47-49, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fernando Sánchez‐Vizcaíno & Andrés Perez & Beatriz Martínez‐López & José Manuel Sánchez‐Vizcaíno, 2012. "Comparative Assessment of Analytical Approaches to Quantify the Risk for Introduction of Rare Animal Diseases: The Example of Avian Influenza in Spain," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1433-1440, August.
    2. João Delgado & Simon Pollard & Emma Snary & Edgar Black & George Prpich & Phil Longhurst, 2013. "A Systems Approach to the Policy‐Level Risk Assessment of Exotic Animal Diseases: Network Model and Application to Classical Swine Fever," Risk Analysis, John Wiley & Sons, vol. 33(8), pages 1454-1472, August.
    3. Clazien J. De Vos & Helmut W. Saatkamp & Mirjam Nielen & Ruud B. M. Huirne, 2006. "Sensitivity Analysis to Evaluate the Impact of Uncertain Factors in a Scenario Tree Model for Classical Swine Fever Introduction," Risk Analysis, John Wiley & Sons, vol. 26(5), pages 1311-1322, October.
    4. Hong Yao & Xin Qian & Hong Yin & Hailong Gao & Yulei Wang, 2015. "Regional Risk Assessment for Point Source Pollution Based on a Water Quality Model of the Taipu River, China," Risk Analysis, John Wiley & Sons, vol. 35(2), pages 265-277, February.
    5. João Delgado & Simon Pollard & Kerry Pearn & Emma L. Snary & Edgar Black & George Prpich & Phil Longhurst, 2017. "U.K. Foot and Mouth Disease: A Systemic Risk Assessment of Existing Controls," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1768-1782, September.

    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. Ramya Chari & Thomas A. Burke & Ronald H. White & Mary A. Fox, 2012. "Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead," IJERPH, MDPI, vol. 9(4), pages 1-20, March.
    2. Michael R. Greenberg & Karen Lowrie, 2016. "Elizabeth Anderson: Cancer Risk Assessment Pioneer," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 646-649, April.
    3. Adam M. Finkel & George Gray, 2018. "Taking the reins: how regulatory decision-makers can stop being hijacked by uncertainty," Environment Systems and Decisions, Springer, vol. 38(2), pages 230-238, June.
    4. Hamish Steptoe & Claire Souch & Julia Slingo, 2022. "Advances in numerical weather prediction, data science, and open‐source software herald a paradigm shift in catastrophe risk modeling and insurance underwriting," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(1), pages 69-81, April.
    5. Amirhossein Mokhtari & H. Christopher Frey, 2005. "Sensitivity Analysis of a Two‐Dimensional Probabilistic Risk Assessment Model Using Analysis of Variance," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1511-1529, December.
    6. Régis Pouillot & Pascal Beaudeau & Jean‐Baptiste Denis & Francis Derouin & AFSSA Cryptosporidium Study Group, 2004. "A Quantitative Risk Assessment of Waterborne Cryptosporidiosis in France Using Second‐Order Monte Carlo Simulation," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 1-17, February.

    More about this item

    Statistics

    Access and download statistics

    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:wly:riskan:v:24:y:2004:i:1:p:237-253. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.