IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v36y2016i2p191-202.html
   My bibliography  Save this article

Research Synthesis Methods in an Age of Globalized Risks: Lessons from the Global Burden of Foodborne Disease Expert Elicitation

Author

Listed:
  • World Health Organization, Foodborne Epidemiology Reference Group, Source Attribution Task Force

Abstract

We live in an age that increasingly calls for national or regional management of global risks. This article discusses the contributions that expert elicitation can bring to efforts to manage global risks and identifies challenges faced in conducting expert elicitation at this scale. In doing so it draws on lessons learned from conducting an expert elicitation as part of the World Health Organizations (WHO) initiative to estimate the global burden of foodborne disease; a study commissioned by the Foodborne Disease Epidemiology Reference Group (FERG). Expert elicitation is designed to fill gaps in data and research using structured, transparent methods. Such gaps are a significant challenge for global risk modeling. Experience with the WHO FERG expert elicitation shows that it is feasible to conduct an expert elicitation at a global scale, but that challenges do arise, including: defining an informative, yet feasible geographical structure for the elicitation; defining what constitutes expertise in a global setting; structuring international, multidisciplinary expert panels; and managing demands on experts’ time in the elicitation. This article was written as part of a workshop, “Methods for Research Synthesis: A Cross‐Disciplinary Approach” held at the Harvard Center for Risk Analysis on October 13, 2013.

Suggested Citation

  • World Health Organization, Foodborne Epidemiology Reference Group, Source Attribution Task Force, 2016. "Research Synthesis Methods in an Age of Globalized Risks: Lessons from the Global Burden of Foodborne Disease Expert Elicitation," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 191-202, February.
    • Handle: RePEc:wly:riskan:v:36:y:2016:i:2:p:191-202
    DOI: 10.1111/risa.12385
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/risa.12385
    Download Restriction: no
    File URL: https://libkey.io/10.1111/risa.12385?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. Flandoli, F. & Giorgi, E. & Aspinall, W.P. & Neri, A., 2011. "Comparison of a new expert elicitation model with the Classical Model, equal weights and single experts, using a cross-validation technique," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1292-1310.
    2. Baker, Erin & Bosetti, Valentina & Jenni, Karen E. & Ricci, Elena Claire, 2014. "Facing the Experts: Survey Mode and Expert Elicitation," Climate Change and Sustainable Development 163585, Fondazione Eni Enrico Mattei (FEEM).
    3. Willy Aspinall, 2010. "A route to more tractable expert advice," Nature, Nature, vol. 463(7279), pages 294-295, January.
    4. J. L. Bamber & W. P. Aspinall, 2013. "An expert judgement assessment of future sea level rise from the ice sheets," Nature Climate Change, Nature, vol. 3(4), pages 424-427, April.
    5. Brecht Devleesschauwer & Arie Havelaar & Charline Maertens de Noordhout & Juanita Haagsma & Nicolas Praet & Pierre Dorny & Luc Duchateau & Paul Torgerson & Herman Oyen & Niko Speybroeck, 2014. "Calculating disability-adjusted life years to quantify burden of disease," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 59(3), pages 565-569, June.
    6. Christopher W. Karvetski & Kenneth C. Olson & David R. Mandel & Charles R. Twardy, 2013. "Probabilistic Coherence Weighting for Optimizing Expert Forecasts," Decision Analysis, INFORMS, vol. 10(4), pages 305-326, December.
    7. Lisa A. Robinson & James K. Hammitt, 2015. "Introduction to the Special Series on Research Synthesis: A Cross‐Disciplinary Approach," Risk Analysis, John Wiley & Sons, vol. 35(6), pages 963-970, June.
    8. Hoffmann, Sandra & Harder, William, 2010. "Food Safety and Risk Governance in Globalized Markets," RFF Working Paper Series dp-09-44, Resources for the Future.
    9. H. J. Van der Fels‐Klerx & Roger M. Cooke & Maarten N. Nauta & Louis H. Goossens & Arie H. Havelaar, 2005. "A Structured Expert Judgment Study for a Model of Campylobacter Transmission During Broiler‐Chicken Processing," Risk Analysis, John Wiley & Sons, vol. 25(1), pages 109-124, February.
    10. Lin, Shi-Woei & Bier, Vicki M., 2008. "A study of expert overconfidence," Reliability Engineering and System Safety, Elsevier, vol. 93(5), pages 711-721.
    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. Cooke, Roger M., 2014. "Deep and Shallow Uncertainty in Messaging Climate Change," RFF Working Paper Series dp-14-11, Resources for the Future.
    2. David R. Mandel & Daniel Irwin, 2021. "Tracking accuracy of strategic intelligence forecasts: Findings from a long‐term Canadian study," Futures & Foresight Science, John Wiley & Sons, vol. 3(3-4), September.
    3. Colson, Abigail R. & Cooke, Roger M., 2017. "Cross validation for the classical model of structured expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 109-120.
    4. Jeremy Rohmer & Eric Chojnacki, 2021. "Forecast of environment systems using expert judgements: performance comparison between the possibilistic and the classical model," Environment Systems and Decisions, Springer, vol. 41(1), pages 131-146, March.
    5. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
    6. Alvarado-Valencia, Jorge & Barrero, Lope H. & Önkal, Dilek & Dennerlein, Jack T., 2017. "Expertise, credibility of system forecasts and integration methods in judgmental demand forecasting," International Journal of Forecasting, Elsevier, vol. 33(1), pages 298-313.
    7. Eggstaff, Justin W. & Mazzuchi, Thomas A. & Sarkani, Shahram, 2014. "The effect of the number of seed variables on the performance of Cooke′s classical model," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 72-82.
    8. James K. Hammitt & Yifan Zhang, 2013. "Combining Experts’ Judgments: Comparison of Algorithmic Methods Using Synthetic Data," Risk Analysis, John Wiley & Sons, vol. 33(1), pages 109-120, January.
    9. Christopher W. Karvetski & David R. Mandel & Daniel Irwin, 2020. "Improving Probability Judgment in Intelligence Analysis: From Structured Analysis to Statistical Aggregation," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 1040-1057, May.
    10. Alexander M. R. Bakker & Domitille Louchard & Klaus Keller, 2017. "Sources and implications of deep uncertainties surrounding sea-level projections," Climatic Change, Springer, vol. 140(3), pages 339-347, February.
    11. Sulian Wang & Chen Wang, 2021. "Quantile Judgments of Lognormal Losses: An Experimental Investigation," Decision Analysis, INFORMS, vol. 18(1), pages 78-99, March.
    12. Abigail R Colson & Roger M Cooke, 2018. "Expert Elicitation: Using the Classical Model to Validate Experts’ Judgments," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 113-132.
    13. Abigail R Colson & Itamar Megiddo & Gerardo Alvarez-Uria & Sumanth Gandra & Tim Bedford & Alec Morton & Roger M Cooke & Ramanan Laxminarayan, 2019. "Quantifying uncertainty about future antimicrobial resistance: Comparing structured expert judgment and statistical forecasting methods," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-18, July.
    14. Lee Stapleton, 2015. "Do academics doubt their own research?," SPRU Working Paper Series 2015-24, SPRU - Science Policy Research Unit, University of Sussex Business School.
    15. Meissner, Philip & Brands, Christian & Wulf, Torsten, 2017. "Quantifiying blind spots and weak signals in executive judgment: A structured integration of expert judgment into the scenario development process," International Journal of Forecasting, Elsevier, vol. 33(1), pages 244-253.
    16. Morais, Caroline & Estrada-Lugo, Hector Diego & Tolo, Silvia & Jacques, Tiago & Moura, Raphael & Beer, Michael & Patelli, Edoardo, 2022. "Robust data-driven human reliability analysis using credal networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    17. Le Bars, Dewi, 2018. "Uncertainty in sea level rise projections due to the dependence between contributors," Earth Arxiv uvw3s, Center for Open Science.
    18. Tony E. Wong & Alexander M. R. Bakker & Klaus Keller, 2017. "Impacts of Antarctic fast dynamics on sea-level projections and coastal flood defense," Climatic Change, Springer, vol. 144(2), pages 347-364, September.
    19. repec:cup:judgdm:v:8:y:2013:i:5:p:552-560 is not listed on IDEAS
    20. Stapleton, L.M. & Hanna, P. & Ravenscroft, N. & Church, A., 2014. "A flexible ecosystem services proto-typology based on public opinion," Ecological Economics, Elsevier, vol. 106(C), pages 83-90.
    21. repec:cup:judgdm:v:13:y:2018:i:6:p:607-621 is not listed on IDEAS
    22. Klaus Desmet & Robert E. Kopp & Scott A. Kulp & Dávid Krisztián Nagy & Michael Oppenheimer & Esteban Rossi-Hansberg & Benjamin H. Strauss, 2021. "Evaluating the Economic Cost of Coastal Flooding," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(2), pages 444-486, April.

    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:36:y:2016:i:2:p:191-202. 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.