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Norovirus Dose–Response: Are Currently Available Data Informative Enough to Determine How Susceptible Humans Are to Infection from a Single Virus?

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  • Philip J. Schmidt

Abstract

Two forms of single‐hit infection dose‐response models have previously been developed to assess available data from human feeding trials and estimate the norovirus dose‐response relationship. The mechanistic interpretations of these models include strong assumptions that warrant reconsideration: the first study includes an implicit assumption that there is no immunity to Norwalk virus among the specific study population, while the recent second study includes assumptions that such immunity could exist and that the nonimmune have no defensive barriers to prevent infection from exposure to just one virus. Both models addressed unmeasured virus aggregation in administered doses. In this work, the available data are reanalyzed using a generalization of the first model to explore these previous assumptions. It was hypothesized that concurrent estimation of an unmeasured degree of virus aggregation and important dose‐response parameters could lead to structural nonidentifiability of the model (i.e., that a diverse range of alternative mechanistic interpretations yield the same optimal fit), and this is demonstrated using the profile likelihood approach and by algebraic proof. It is also demonstrated that omission of an immunity parameter can artificially inflate the estimated degree of aggregation and falsely suggest high susceptibility among the nonimmune. The currently available data support the assumption of immunity within the specific study population, but provide only weak information about the degree of aggregation and susceptibility among the nonimmune. The probability of infection at low and moderate doses may be much lower than previously asserted, but more data from strategically designed dose‐response experiments are needed to provide adequate information.

Suggested Citation

  • Philip J. Schmidt, 2015. "Norovirus Dose–Response: Are Currently Available Data Informative Enough to Determine How Susceptible Humans Are to Infection from a Single Virus?," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1364-1383, July.
  • Handle: RePEc:wly:riskan:v:35:y:2015:i:7:p:1364-1383
    DOI: 10.1111/risa.12323
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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. Philip J. Schmidt & Monica B. Emelko & Mary E. Thompson, 2020. "Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit," Risk Analysis, John Wiley & Sons, vol. 40(2), pages 352-369, February.
    3. Michael J. Messner & Philip Berger, 2016. "Cryptosporidium Infection Risk: Results of New Dose‐Response Modeling," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1969-1982, October.
    4. Nicole Van Abel & Mary E. Schoen & John C. Kissel & J. Scott Meschke, 2017. "Comparison of Risk Predicted by Multiple Norovirus Dose–Response Models and Implications for Quantitative Microbial Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(2), pages 245-264, February.
    5. Steven Duret & Régis Pouillot & Wendy Fanaselle & Efstathia Papafragkou & Girvin Liggans & Laurie Williams & Jane M. Van Doren, 2017. "Quantitative Risk Assessment of Norovirus Transmission in Food Establishments: Evaluating the Impact of Intervention Strategies and Food Employee Behavior on the Risk Associated with Norovirus in Food," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2080-2106, November.

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