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

Risk Analysis : an Official Publication of the Society for Risk Analysis
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 for...Continue Reading

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Jan 27, 2016·Risk Analysis : an Official Publication of the Society for Risk Analysis·Vegard Nilsen, John Wyller

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Citations

Jan 27, 2016·Risk Analysis : an Official Publication of the Society for Risk Analysis·Vegard Nilsen, John Wyller
Jan 14, 2017·Risk Analysis : an Official Publication of the Society for Risk Analysis·Philip J Schmidt, Cynthia L Chappell
Apr 8, 2017·PLoS Computational Biology·Andrew F BrouwerJoseph N S Eisenberg
Oct 5, 2018·Risk Analysis : an Official Publication of the Society for Risk Analysis·Tucker Burch
Aug 24, 2019·Risk Analysis : an Official Publication of the Society for Risk Analysis·Philip J SchmidtMary E Thompson

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