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ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Environmentally Integrated Dairy Management Research » Research » Publications at this Location » Publication #344737

Research Project: Improving Nutrient Use Efficiency and Mitigating Nutrient and Pathogen Losses from Dairy Production Systems

Location: Environmentally Integrated Dairy Management Research

Title: Validation of quantitative microbial risk assessment using epidemiological data from outbreaks of waterborne gastrointestinal disease

Author
item Burch, Tucker

Submitted to: Risk Analysis
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/20/2018
Publication Date: 10/4/2018
Citation: Burch, T.R. 2018. Validation of quantitative microbial risk assessment using epidemiological data from outbreaks of waterborne gastrointestinal disease. Risk Analysis. 39(3), 599–615. https://doi.org/10.1111/risa.13189.
DOI: https://doi.org/10.1111/risa.13189

Interpretive Summary: Exposure to low levels of gastrointestinal pathogens through environmental routes – particularly through drinking water – causes an important public health burden. Quantitative microbial risk assessment (QMRA) is an approach that can be used to predict this burden, but QMRA predictions have never been validated for many pathogens. The objective of this research was to validate QMRA predictions using epidemiological measurements from reported outbreaks of waterborne gastrointestinal disease. Comparison of QMRA predictions to epidemiological measurements was generally good. Predicted disease rates matched measured disease rates for 10 of 14 outbreaks. These results demonstrate the validity of QMRA for estimating disease rates due to waterborne gastrointestinal pathogens. This means that QMRA can be used by policy-makers and agricultural engineers to accurately predict the health burden of exposure to these pathogens through environmental routes, including exposure to pathogens that originate on livestock farms and pollute ground and surface water during manure disposal. Such predicted health burdens are crucial to evaluating public health and environmental policies related to agriculture.

Technical Abstract: The assumptions underlying quantitative microbial risk assessment (QMRA) are simple, plausible, and conservative towards protecting public health, but QMRA predictions have never been validated for many pathogens. The objective of this work was to validate QMRA predictions against epidemiological measurements from reported outbreaks of waterborne gastrointestinal disease. More than 2000 papers were screened and used to identify 14 outbreaks with the necessary data: disease rates measured using epidemiological methods and pathogen concentrations measured in the source water. All 14 outbreaks involved treated public drinking water supplies; ten 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 per person-day, and reported pathogen concentrations varied from 1.2×10-4 to 8.6×102 per liter. These concentrations were used with published dose-response models for all three pathogens to conduct QMRA, producing both point and interval predictions of disease rates for each outbreak. Initial comparison of QMRA predictions to epidemiological measurements showed only moderate agreement; interval predictions contained measured disease rates for 6 of 14 outbreaks. However, this initial comparison failed to account for under-reporting of laboratory-confirmed cases and over-reporting of clinical cases. After accounting for these biases, agreement between QMRA predictions and epidemiological measurements was substantially improved. Interval predictions contained measured disease rates for 10 of 14 outbreaks, with point predictions off by a median factor of 6.4 (range = 1.3 – 20,000). These results demonstrate the validity of QMRA for predicting disease rates due to waterborne Cryptosporidium, Giardia, and norovirus. Furthermore, validation at low doses supports the credibility of the assumptions underlying QMRA.