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Validation of Quantitative Microbial Risk Assessment Using Epidemiological Data from Outbreaks of Waterborne Gastrointestinal Disease

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  • Tucker Burch

Abstract

The assumptions underlying quantitative microbial risk assessment (QMRA) are simple and biologically plausible, but QMRA predictions have never been validated for many pathogens. The objective of this study was to validate QMRA predictions against epidemiological measurements from outbreaks of waterborne gastrointestinal disease. I screened 2,000 papers and identified 12 outbreaks with the necessary data: disease rates measured using epidemiological methods and pathogen concentrations measured in the source water. Eight of the 12 outbreaks were caused by Cryptosporidium, three by Giardia, and one by norovirus. Disease rates varied from 5.5 × 10−6 to 1.1 × 10−2 cases/person‐day, and reported pathogen concentrations varied from 1.2 × 10−4 to 8.6 × 102 per liter. I used these concentrations with single‐hit dose–response models for all three pathogens to conduct QMRA, producing both point and interval predictions of disease rates for each outbreak. Comparison of QMRA predictions to epidemiological measurements showed good agreement; interval predictions contained measured disease rates for 9 of 12 outbreaks, with point predictions off by factors of 1.0–120 (median = 4.8). Furthermore, 11 outbreaks occurred at mean doses of less than 1 pathogen per exposure. Measured disease rates for these outbreaks were clearly consistent with a single‐hit model, and not with a “two‐hit” threshold model. These results demonstrate the validity of QMRA for predicting disease rates due to Cryptosporidium and Giardia.

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  • 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.
  • Handle: RePEc:wly:riskan:v:39:y:2019:i:3:p:599-615
    DOI: 10.1111/risa.13189
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Charles N. Haas & Joan B. Rose & Charles Gerba & Stig Regli, 1993. "Risk Assessment of Virus in Drinking Water," Risk Analysis, John Wiley & Sons, vol. 13(5), pages 545-552, October.
    4. Kent, G.P. & Greenspan, J.R. & Herndon, J.L. & Mofenson, L.M. & Harris, J.-A.S. & Eng, T.R. & Waskin, H.A., 1988. "Epidemic giardiasis caused by a contaminated public water supply," American Journal of Public Health, American Public Health Association, vol. 78(2), pages 139-143.
    5. Rose, J.B. & Haas, C.N. & Regli, S., 1991. "Risk assessment and control of waterborne giardiasis," American Journal of Public Health, American Public Health Association, vol. 81(6), pages 709-713.
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    Cited by:

    1. Ropo E. Ogunsakin & Oluwakemi Ebenezer & Themba G. Ginindza, 2022. "A Bibliometric Analysis of the Literature on Norovirus Disease from 1991–2021," IJERPH, MDPI, vol. 19(5), pages 1-27, February.
    2. Tucker R. Burch, 2020. "Outbreak‐Based Giardia Dose–Response Model Using Bayesian Hierarchical Markov Chain Monte Carlo Analysis," Risk Analysis, John Wiley & Sons, vol. 40(4), pages 705-722, April.

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