New Risk Management Findings from Griffith University Described (Guidelines for Use of the Approximate Beta-Poisson Dose-Response Model)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Current study results on Risk Management have been published. According to news reporting from Nathan, Australia, by VerticalNews journalists, research stated, "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 alpha > 0 and beta > 0, which involves the Kummer confluent hypergeometric function. Evaluation of a hypergeometric function is a computational challenge."

The news correspondents obtained a quote from the research from Griffith University, "Denoting P-I (d) as the probability of infection at a given mean dose d, the widely used dose-response model P-I (d) = 1 - (1 + d/beta)(-alpha) is an approximate formula for the exact beta-Poisson model. Notwithstanding the required conditions alpha << beta and beta >> 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 vertical bar (alpha) over cap, (beta) over cap) as a validity measure (r is a random variable that follows a gamma distribution; (alpha) over cap and (beta) over cap are the maximum likelihood estimates of alpha and beta in the approximate model); and the constraint conditions (beta) over cap > (22 (alpha) over cap)(0.50) for 0.02 <<(alpha)over cap > < 2 as a rule of thumb to ensure an accurate approximation (e.g., Pr(0 < r< 1 vertical bar <(alpha)over cap >, (beta) over cap) > 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 vertical bar (alpha) over cap, (beta) over cap), the better the approximation."

According to the news reporters, the research concluded: "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."

For more information on this research see: Guidelines for Use of the Approximate Beta-Poisson Dose-Response Model. Risk Analysis, 2017;37(7):1388-1402. Risk Analysis can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - www.wiley.com/; Risk Analysis - onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6924)

Our news journalists report that additional information may be obtained by contacting G. Xie, Griffith University, Smart Water Res Center, Nathan, Qld, Australia. Additional authors for this research include A. Roiko, H. Stratton, C. Lemckert, P.K. Dunn and K. Mengersen.

Keywords for this news article include: Nathan, Australia, Australia and New Zealand, Risk Management, Griffith University.

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