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Article

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

1
Division of Environmental Health Sciences, College of Public Health, The Ohio State University, 1841 Neil Avenue, Columbus, OH 43210, USA
2
Community, Environment and Policy Department, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ 85721, USA
3
College of Medicine, Griffith University, Gold Coast, QLD 4222, Australia
4
College of Engineering, Michigan State University, East Lansing, MI 48824, USA
*
Author to whom correspondence should be addressed.
Water 2020, 12(1), 43; https://doi.org/10.3390/w12010043
Received: 30 September 2019 / Revised: 5 December 2019 / Accepted: 5 December 2019 / Published: 20 December 2019
(This article belongs to the Section Aquatic Systems—Quality and Contamination)
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 current QMRA method of modeling exposure volume heterogeneity is not an accurate method for pathogens such as Legionella pneumophila. Therefore, a new method 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. View Full-Text
Keywords: QMRA; Legionella; building water; premise plumbing; DALY QMRA; Legionella; building water; premise plumbing; DALY
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MDPI and ACS Style

Weir, M.H.; Mraz, A.L.; Mitchell, J. An Advanced Risk Modeling Method to Estimate Legionellosis Risks Within a Diverse Population. Water 2020, 12, 43. https://doi.org/10.3390/w12010043

AMA Style

Weir MH, Mraz AL, Mitchell J. An Advanced Risk Modeling Method to Estimate Legionellosis Risks Within a Diverse Population. Water. 2020; 12(1):43. https://doi.org/10.3390/w12010043

Chicago/Turabian Style

Weir, Mark H.; Mraz, Alexis L.; Mitchell, Jade. 2020. "An Advanced Risk Modeling Method to Estimate Legionellosis Risks Within a Diverse Population" Water 12, no. 1: 43. https://doi.org/10.3390/w12010043

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