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Source Attribution of Food‐Borne Zoonoses in New Zealand: A Modified Hald Model

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  • Petra Mullner
  • Geoff Jones
  • Alasdair Noble
  • Simon E. F. Spencer
  • Steve Hathaway
  • Nigel Peter French

Abstract

A Bayesian approach was developed by Hald et al.(1) to estimate the contribution of different food sources to the burden of human salmonellosis in Denmark. This article describes the development of several modifications that can be used to adapt the model to different countries and pathogens. Our modified Hald model has several advantages over the original approach, which include the introduction of uncertainty in the estimates of source prevalence and an improved strategy for identifiability. We have applied our modified model to the two major food‐borne zoonoses in New Zealand, namely, campylobacteriosis and salmonellosis. Major challenges were the data quality for salmonellosis and the inclusion of environmental sources of campylobacteriosis. We conclude that by modifying the Hald model we have improved its identifiability, made it more applicable to countries with less intensive surveillance, and feasible for other pathogens, in particular with respect to the inclusion of nonfood sources. The wider application and better understanding of this approach is of particular importance due to the value of the model for decision making and risk management.

Suggested Citation

  • Petra Mullner & Geoff Jones & Alasdair Noble & Simon E. F. Spencer & Steve Hathaway & Nigel Peter French, 2009. "Source Attribution of Food‐Borne Zoonoses in New Zealand: A Modified Hald Model," Risk Analysis, John Wiley & Sons, vol. 29(7), pages 970-984, July.
    • Handle: RePEc:wly:riskan:v:29:y:2009:i:7:p:970-984
    DOI: 10.1111/j.1539-6924.2009.01224.x
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    References listed on IDEAS

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    1. Purvi Vora & Andre Senecal & Donald W. Schaffner, 2003. "Survival of Staphylococcus aureus ATCC 13565 in Intermediate Moisture Foods is Highly Variable," Risk Analysis, John Wiley & Sons, vol. 23(1), pages 229-236, February.
    2. Tine Hald & David Vose & Henrik C. Wegener & Timour Koupeev, 2004. "A Bayesian Approach to Quantify the Contribution of Animal‐Food Sources to Human Salmonellosis," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 255-269, February.
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    1. Jukka Ranta & Dmitri Matjushin & Terhi Virtanen & Markku Kuusi & Hildegunn Viljugrein & Merete Hofshagen & Marjaana Hakkinen, 2011. "Bayesian Temporal Source Attribution of Foodborne Zoonoses: Campylobacter in Finland and Norway," Risk Analysis, John Wiley & Sons, vol. 31(7), pages 1156-1171, July.
    2. K. Glass & E. Fearnley & H. Hocking & J. Raupach & M. Veitch & L. Ford & M. D. Kirk, 2016. "Bayesian Source Attribution of Salmonellosis in South Australia," Risk Analysis, John Wiley & Sons, vol. 36(3), pages 561-570, March.
    3. Emma L. Snary & Arno N. Swart & Tine Hald, 2016. "Quantitative Microbiological Risk Assessment and Source Attribution for Salmonella: Taking it Further," Risk Analysis, John Wiley & Sons, vol. 36(3), pages 433-436, March.
    4. Nanna Munck & Patrick Murigu Kamau Njage & Pimlapas Leekitcharoenphon & Eva Litrup & Tine Hald, 2020. "Application of Whole‐Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1693-1705, September.

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