Estimators of annual probability of infection for quantitative microbial risk assessment

Karavarsamis, Natalie; Hamilton, Andrew J.

doi:10.2166/wh.2010.045

Cited by 32 publications

(18 citation statements)

References 20 publications

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“…All computations were performed in R () and using the mc2d package [64]. Random sampling of daily risks with replacement was conducted as per the preferred method for annualizing probability of infection using 100,000 iterations [65]. …”

Section: Methodsmentioning

confidence: 99%

Drivers of Microbial Risk for Direct Potable Reuse and de Facto Reuse Treatment Schemes: The Impacts of Source Water Quality and Blending

Chaudhry

Hamilton

Haas

et al. 2017

IJERPH

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Although reclaimed water for potable applications has many potential benefits, it poses concerns for chemical and microbial risks to consumers. We present a quantitative microbial risk assessment (QMRA) Monte Carlo framework to compare a de facto water reuse scenario (treated wastewater-impacted surface water) with four hypothetical Direct Potable Reuse (DPR) scenarios for Norovirus, Cryptosporidium, and Salmonella. Consumer microbial risks of surface source water quality (impacted by 0–100% treated wastewater effluent) were assessed. Additionally, we assessed risks for different blending ratios (0–100% surface water blended into advanced-treated DPR water) when source surface water consisted of 50% wastewater effluent. De facto reuse risks exceeded the yearly 10−4 infections risk benchmark while all modeled DPR risks were significantly lower. Contamination with 1% or more wastewater effluent in the source water, and blending 1% or more wastewater-impacted surface water into the advanced-treated DPR water drove the risk closer to the 10−4 benchmark. We demonstrate that de facto reuse by itself, or as an input into DPR, drives microbial risks more so than the advanced-treated DPR water. When applied using location-specific inputs, this framework can contribute to project design and public awareness campaigns to build legitimacy for DPR.

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Section: Methodsmentioning

confidence: 99%

Drivers of Microbial Risk for Direct Potable Reuse and de Facto Reuse Treatment Schemes: The Impacts of Source Water Quality and Blending

Chaudhry

Hamilton

Haas

et al. 2017

IJERPH

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“…By series expansion, Furumoto and Mickey (16) showed that, given a fixed value of α, for sufficiently large values of β, Equation (1) is a valid approximation for Equation (4); they also asked readers to pay at- 6 Note that the beta-Poisson model is applied to cases where the dose is assumed to have Poisson error. If the dose is exact, then the proper model (with exponential dose-response parameter beta-distributed across subjects) would be beta-binomial, which has a simple closed-form expression of the dose-response model: tention to the cases when α < 1 and β > 1, and a particular example with α = 0.0001 and β = 4.0 was given to show a good approximation of Equation (1) for Equation (4). Many years later, Teunis and Havelaar (15) noted that Equation (1) can be derived from a different perspective.…”

Section: Model Specificationmentioning

confidence: 99%

“…Quantitative microbial risk assessment (QMRA) is a valuable framework for analyzing the adverse health outcomes associated with exposures to pathogenic organisms . The QMRA approach is a four‐step process comprising (i) hazard identification; (ii) exposure assessment; (iii) dose–response analysis; and (iv) risk characterization .…”

Section: Introductionmentioning

confidence: 99%

“…Quantitative microbial risk assessment (QMRA) (1,2) is a valuable framework for analyzing the adverse health outcomes associated with exposures to pathogenic organisms. (3,4) The QMRA approach is a four-step process comprising (i) hazard identification; (ii) exposure assessment; (iii) doseresponse analysis; and (iv) risk characterization. (1,2) QMRA has become increasingly accepted by health authorities and is referenced in many major health guideline documents pertaining to water-borne pathogens (e.g., drinking water, (5,6) wastewater irrigation, (7)(8)(9) recreational waters, (10) ) and to food-safety.…”

Section: Introductionmentioning

confidence: 99%

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Guidelines for Use of the Approximate Beta‐Poisson Dose–Response Model

et al. 2016

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For dose-response analysis in quantitative microbial risk assessment (QMRA), the exact beta-Poisson model is a two-parameter mechanistic dose-response model with parameters α>0 and β>0, which involves the Kummer confluent hypergeometric function. Evaluation of a hypergeometric function is a computational challenge. Denoting PI(d) as the probability of infection at a given mean dose d, the widely used dose-response model PI(d)=1-(1+dβ)-α is an approximate formula for the exact beta-Poisson model. Notwithstanding the required conditions α<<β and β>>1, issues related to the validity and approximation accuracy of this approximate formula have remained largely ignored in practice, partly because these conditions are too general to provide clear guidance. Consequently, this study proposes a probability measure Pr(0 < r < 1 | α̂, β̂) as a validity measure (r is a random variable that follows a gamma distribution; α̂ and β̂ are the maximum likelihood estimates of α and β in the approximate model); and the constraint conditions β̂>(22α̂)0.50 for 0.02<α̂<2 as a rule of thumb to ensure an accurate approximation (e.g., Pr(0 < r < 1 | α̂, β̂) >0.99) . This validity measure and rule of thumb were validated by application to all the completed beta-Poisson models (related to 85 data sets) from the QMRA community portal (QMRA Wiki). The results showed that the higher the probability Pr(0 < r < 1 | α̂, β̂), the better the approximation. The results further showed that, among the total 85 models examined, 68 models were identified as valid approximate model applications, which all had a near perfect match to the corresponding exact beta-Poisson model dose-response curve.

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“…The model uses the Karavarsamis-Hamilton method [111], together with the norovirus dose-response model by…”

Section: Quantitative Microbial Risk Assessment (Qmra)mentioning

confidence: 99%

Wastewater use in urban agriculture: an exposure and risk assessment in Accra, Ghana

Agyei

Ensink

2016

Jnl Sci Tech

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In order to minimize the health risks to agricultural workers, and consumers of wastewater irrigated produce, the World Health Organisation has developed guidelines for the safe use of wastewater in agriculture. This study sought to test the appropriateness of the current Quantitative Microbial Risk Assessment model and the multiple-barrier approach advocated by the WHO guidelines.Over a one year period, over 500 produce and ready-to-eat salad samples were collected from fields, markets, and kitchens in Accra, Ghana, and over 300 soil and irrigation water samples were collected. All samples were analysed for E. coli, human adenovirus and norovirus using standard microbiological procedures. In addition, almost 700 participants including farmers, food vendors, and consumers were interviewed and observed to assess critical exposures associated with the transmission of faecal pathogens.The results showed that irrigation water was significantly more contaminated than farm soil, though exposure to soil was found to pose the key risk to farmers due to hand-to-mouth events. Over 80% of produce samples were found contaminated with E. coli, with street food salad being the most contaminated (4.23 Log E. coli/g), and that consumption of salads did not meet health standards. Risk factors identified for produce contamination included farm soil contamination, wastewater use for irrigation, poor hygiene, and operating with a hygiene permit. Awareness of the source of irrigation water was low, but despite the high awareness of health risk, consumers did not prioritize health indicators when buying produce from vendors. Similarly, farmers' awareness of health risk did not influence their adoption of safer farm practices. The study recommends the promotion of interventions that would result in more direct benefits to producers and vendors, together with hygiene education and inspection, hygiene certification and enforcement of food safety byelaws in order to increase the uptake of the multi-barrier approach. 4PhD related documents 2014:

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Estimators of annual probability of infection for quantitative microbial risk assessment

Cited by 32 publications

References 20 publications

Drivers of Microbial Risk for Direct Potable Reuse and de Facto Reuse Treatment Schemes: The Impacts of Source Water Quality and Blending

Drivers of Microbial Risk for Direct Potable Reuse and de Facto Reuse Treatment Schemes: The Impacts of Source Water Quality and Blending

Guidelines for Use of the Approximate Beta‐Poisson Dose–Response Model

Wastewater use in urban agriculture: an exposure and risk assessment in Accra, Ghana

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