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  • An Advanced Risk Modeling Method to Estimate Legionellosis Risks Within a Diverse Population

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    Weir421519-Published.pdf (2.769Mb)
    File version
    Version of Record (VoR)
    Author(s)
    Weir, Mark H
    Mraz, Alexis L
    Mitchell, Jade
    Griffith University Author(s)
    Weir, Mark H.
    Year published
    2020
    Metadata
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    Abstract
    Quantitative microbial risk assessment (QMRA) is a computational science leveraged to optimize infectious disease controls at both population and individual levels. Often, diverse populations will have different health risks based on a population's susceptibility or outcome severity due to heterogeneity within the host. Unfortunately, due to a host homogeneity assumption in the microbial dose-response models' derivation, the currentQMRAmethod of modeling exposure volume heterogeneity is not an accurate method for pathogens such as Legionella pneumophila. Therefore, a newmethod to model within-group heterogeneity is needed. ...
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    Quantitative microbial risk assessment (QMRA) is a computational science leveraged to optimize infectious disease controls at both population and individual levels. Often, diverse populations will have different health risks based on a population's susceptibility or outcome severity due to heterogeneity within the host. Unfortunately, due to a host homogeneity assumption in the microbial dose-response models' derivation, the currentQMRAmethod of modeling exposure volume heterogeneity is not an accurate method for pathogens such as Legionella pneumophila. Therefore, a newmethod to model within-group heterogeneity is needed. The method developed in this research uses USA national incidence rates from the Centers for Disease Control and Prevention (CDC) to calculate proxies for the morbidity ratio that are descriptive of the within-group variability. From these proxies, an example QMRA model is developed to demonstrate their use. This method makes the QMRA results more representative of clinical outcomes and increases population-specific precision. Further, the risks estimated demonstrate a significant difference between demographic groups known to have heterogeneous health outcomes after infection. The method both improves fidelity to the real health impacts resulting from L. pneumophila infection and allows for the estimation of severe disability-adjusted life years (DALYs) for Legionnaires' disease, moderate DALYs for Pontiac fever, and post-acute DALYs for sequela after recovering from Legionnaires' disease.
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    Journal Title
    Water
    Volume
    12
    Issue
    1
    DOI
    https://doi.org/10.3390/w12010043
    Copyright Statement
    © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Veterinary epidemiology
    Science & Technology
    Life Sciences & Biomedicine
    Physical Sciences
    Environmental Sciences
    Water Resources
    Publication URI
    http://hdl.handle.net/10072/413317
    Collection
    • Journal articles

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