Kevin Brand, University of Ottawa
Associate Professor
Management
Ottawa, Ontario
kbrand@uottawa.ca
Office:
(613) 562-5800 ext. 1852
Expert In
Bio/Research
Prof. Brand's expertise is in human health risk assessment. His research applies mathematical modeling, uncertainty analysis, and decision analysis to better understand and better implement the components (such as exposure response assessment, and inter-species extrapolations) that are integral t...
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Bio/Research
Prof. Brand's expertise is in human health risk assessment. His research applies mathematical modeling, uncertainty analysis, and decision analysis to better understand and better implement the components (such as exposure response assessment, and inter-species extrapolations) that are integral to human health risk assessments (HRA). In recent years he has studied the methods for burden of disease and health valuation (linking them with HRA methods). Prof. Brand is an expert in uncertainty analysis, specializing in Monte-Carlo methods.
His applications of these methods have extended beyond uncertainty analysis to include (Bayesian) numerical methods for pooling information, and value of information analysis. In more recent research he has applied standard mathematical approximation techniques to a standard demography tool, namely the life-table. He has used the resulting approximations to effectively "break-open" the black-box calculations that characterize the Cause-Modified life-table. His follow-up work suggests that these heuristics and inter-relationships will help bring greater coherence, and in some cases greater rigor, to the disparate approaches that have been used (by various disciplines) to forecast long term population health impacts.
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His applications of these methods have extended beyond uncertainty analysis to include (Bayesian) numerical methods for pooling information, and value of information analysis. In more recent research he has applied standard mathematical approximation techniques to a standard demography tool, namely the life-table. He has used the resulting approximations to effectively "break-open" the black-box calculations that characterize the Cause-Modified life-table. His follow-up work suggests that these heuristics and inter-relationships will help bring greater coherence, and in some cases greater rigor, to the disparate approaches that have been used (by various disciplines) to forecast long term population health impacts.
Click to Shrink <<