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QMRA for Drinking Water: 1. Revisiting the Mathematical Structure of Single‐Hit Dose‐Response Models

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  • Vegard Nilsen
  • John Wyller

Abstract

Dose‐response models are essential to quantitative microbial risk assessment (QMRA), providing a link between levels of human exposure to pathogens and the probability of negative health outcomes. In drinking water studies, the class of semi‐mechanistic models known as single‐hit models, such as the exponential and the exact beta‐Poisson, has seen widespread use. In this work, an attempt is made to carefully develop the general mathematical single‐hit framework while explicitly accounting for variation in (1) host susceptibility and (2) pathogen infectivity. This allows a precise interpretation of the so‐called single‐hit probability and precise identification of a set of statistical independence assumptions that are sufficient to arrive at single‐hit models. Further analysis of the model framework is facilitated by formulating the single‐hit models compactly using probability generating and moment generating functions. Among the more practically relevant conclusions drawn are: (1) for any dose distribution, variation in host susceptibility always reduces the single‐hit risk compared to a constant host susceptibility (assuming equal mean susceptibilities), (2) the model‐consistent representation of complete host immunity is formally demonstrated to be a simple scaling of the response, (3) the model‐consistent expression for the total risk from repeated exposures deviates (gives lower risk) from the conventional expression used in applications, and (4) a model‐consistent expression for the mean per‐exposure dose that produces the correct total risk from repeated exposures is developed.

Suggested Citation

  • Vegard Nilsen & John Wyller, 2016. "QMRA for Drinking Water: 1. Revisiting the Mathematical Structure of Single‐Hit Dose‐Response Models," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 145-162, January.
  • Handle: RePEc:wly:riskan:v:36:y:2016:i:1:p:145-162
    DOI: 10.1111/risa.12389
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    References listed on IDEAS

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    1. Peter F. M. Teunis & Cynthia L. Chappell & Pablo C. Okhuysen, 2002. "Cryptosporidium Dose‐Response Studies: Variation Between Hosts," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 475-485, June.
    2. Harriet Namata & Marc Aerts & Christel Faes & Peter Teunis, 2008. "Model Averaging in Microbial Risk Assessment Using Fractional Polynomials," Risk Analysis, John Wiley & Sons, vol. 28(4), pages 891-905, August.
    3. Peter F. M. Teunis & Cynthia L. Chappell & Pablo C. Okhuysen, 2002. "Cryptosporidium Dose Response Studies: Variation Between Isolates," Risk Analysis, John Wiley & Sons, vol. 22(1), pages 175-185, February.
    4. Josep M Pujol & Joseph E Eisenberg & Charles N Haas & James S Koopman, 2009. "The Effect of Ongoing Exposure Dynamics in Dose Response Relationships," PLOS Computational Biology, Public Library of Science, vol. 5(6), pages 1-12, June.
    5. P. F. M. Teunis & A. H. Havelaar, 2000. "The Beta Poisson Dose‐Response Model Is Not a Single‐Hit Model," Risk Analysis, John Wiley & Sons, vol. 20(4), pages 513-520, August.
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    Cited by:

    1. Tucker Burch, 2019. "Validation of Quantitative Microbial Risk Assessment Using Epidemiological Data from Outbreaks of Waterborne Gastrointestinal Disease," Risk Analysis, John Wiley & Sons, vol. 39(3), pages 599-615, March.
    2. Vegard Nilsen & John Wyller, 2016. "QMRA for Drinking Water: 2. The Effect of Pathogen Clustering in Single‐Hit Dose‐Response Models," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 163-181, January.

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