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17 - Health Risk Analysis for Risk-Management Decision-Making

Published online by Cambridge University Press:  05 June 2012

Anthony (tony) Cox Jr.
Affiliation:
Cox Associates and University of Colorado
Ralph F. Miles Jr.
Affiliation:
California Institute of Technology
Detlof von Winterfeldt
Affiliation:
University of Southern California
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Summary

ABSTRACT. Health risk assessment offers a framework for applying scientific knowledge and data to improve “rational” (consequence-driven) risk-management decision making when the consequences of alternative decisions are uncertain. It does so by clarifying both: (a) The probable consequences of alternative decisions (usually represented by conditional probabilities of different consequences occurring, given specified current information and probabilistic risk models); and (b) How current uncertainties about probable consequences might change as more information is gathered. This chapter summarizes methods, principles, and high-level procedures for using scientific data (e.g., biological and epidemiological knowledge) (1) to assess and compare the probable human health consequences of different exposures to hazards (i.e., sources of risk); (2) to predict likely changes in exposures and risks caused by alternative risk-management interventions; and (3) to evaluate and choose among interventions based on their probable health consequences. The usual goal of these methods is to identify and select actions or interventions that will cause relatively desirable probability distributions of human health consequences in affected populations. We discuss the steps of hazard identification (including causal analysis of data), exposure assessment, causal dose-response modeling, and risk and uncertainty characterization for improving health risk-management decision making.

Public health risk analysis deals with decisions about which of a set of available risk-management interventions (usually including the status quo or “do-nothing” option) should be implemented. For example, should cell phone use in cars be banned? Under what conditions, if any, should cattle be imported from countries with low levels of diseases such as BSE?

Type
Chapter
Information
Advances in Decision Analysis
From Foundations to Applications
, pp. 325 - 350
Publisher: Cambridge University Press
Print publication year: 2007

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References

Aliferis, C., Tsamardinos, I., and Statnikov, A. (2003). Hiton. A novel Markov Blanket algorithm for optimal variable selection. AMIA Annual Symposium Procedings, 21–25.Google ScholarPubMed
Andrieu, C., Freitas, N., Doucet, A., and Jordan, M. I. (2003). An introduction to MCMC for machine learning. Machine Learning, 50, 5–43. http://citeseer.ist.psu.edu/andrieu03introduction.html. Accessed 10/31/2006.CrossRefGoogle Scholar
Barbour, A. D., and Mansson, M. A. (2002) Compound Poisson approximation. The Annals of Probability, 30 (3), 1492–1537.Google Scholar
Burmaster, D. E., and Anderson, P. D. (1994). Principles of good practice for the use of Monte Carlo techniques in human health and ecological risk assessments. Risk Analysis, 14, 77–81.CrossRefGoogle ScholarPubMed
Buzby, J. C., Roberts, T., Jordan Lin, C. T., and MacDonald, J. M. (1996). Bacterial Foodborne Disease: Medical Costs and Productivity Losses. USDA, Economic Research Service, Agricultural Economics Report # 741. http://www.ers.usda.gov/publications/Aer741/. Accessed 10/31/2006.
Cassin, M. H., Paoli, G. M., and Lammerding, A. M. (1998). Simulation modeling for microbial risk assessment. Journal of Food Protection, 61, 1560–1566.CrossRefGoogle ScholarPubMed
Chang, K. C., and Tian, Z., (2002). Efficient inference for mixed Bayesian networks. http://citeseer.ist.psu.edu/570208.html. Accessed 10/31/2006.
Cheng, J., Greiner, R., Kelly, J., Bell, D., and Liu, W. (2001). Learning Bayesian Networks from Data: An Information-Theory Based Approach. http://citeseer.ist.psu.edu/628344.html. Accessed 10/31/2006.
Choi, B. C., and Noseworthy, A. L. (1992). Classification, direction, and prevention of bias in epidemiologic research. Journal of Occupational Medicine, 34 (3), 265–271.CrossRefGoogle ScholarPubMed
Cox, L. A. (2001). Risk Analysis: Foundations, Models, and Methods. Boston: Kluwer Academic.Google Scholar
Deeks, J. J., Dinnes, J., D'Amico, R., Sowden, A. J., Sakarovitch, C., Song, F., Petticrew, M., and Altman, D. G. (2003). International Stroke Trial Collaborative Group; European Carotid Surgery Trial Collaborative Group. Evaluating nonrandomised intervention studies. Health Technology Assessment, 7(27), ⅲ–ⅹ, 1–173.Google Scholar
FAO/WHO. (2001). Joint FAO/WHO Expert Consultation on Risk Assessment of Microbiological Hazards in Foods: Risk characterization of Salmonella spp in eggs and broiler chickens and Listeria monocytogenes in ready-to-eat foods. FAO Headquarters, Rome, Italy 30 April–4 May. http://www.who.int/foodsafety/publications/micro/en/may2001.pdf Accessed 10/31/2006.
FDA-CFSAN (2002). U.S. Food and Drug Administration Center for Food Safety and Applied Nutrition. Initiation and Conduct of All ‘Major’ Risk Assessments within a Risk Analysis Framework. http://www.cfsan.fda.gov/~dms/rafw-toc.html. Accessed 11/02/2006.
FDA-CFSAN. (2003). FDA/Center for Food Safety and Applied Nutrition USDA/Food Safety and Inspection Service Centers for Disease Control and Prevention. Quantitative Assessment of Relative Risk to Public Health from Foodborne Listeria monocytogenes Among Selected Categories of Ready-to-Eat Foods. Appendix 3. September. http://vm.cfsan.fda.gov/~dms/lmr2-a3.html. Accessed 10/31/2006.
Feldman, R. A. (1998). Confounding factors in observational and intervention studies. Ital J Gastroenterol. Hepatol., 30 (3), S248–253.Google ScholarPubMed
Freedman, D. A. (2004). Graphical models for causation, and the identification problem. Eva Rev., 28 (4), 267–293.CrossRefGoogle ScholarPubMed
Frey, L., Fisher, D., Tsamardinos, I., Aliferis, C., and Statnikov, A. (2003). Identifying Markov Blankets with Decision Tree Induction. http://citeseer.ist.psu.edu/frey03identifying.html. Accessed 10/31/2006.
Friedman, N., and Goldszmidt, M. (1996). Learning Bayesian Networks With Local Structure. http://citeseer.ist.psu.edu/friedman96learning.html. Accessed 10/31/2006.
Friedman, C., Reddy, S., Samual, M., Marcus, R., Bender, J., Desai, S., Shiferaw, B., Helfrick, D., Carter, M., Anderson, B., Hoekstra, M., and the EIP Working Group. (2000). Risk Factors for Sporadic Campylobacter Infections in the United States: A Case-Control Study on FoodNet Sites. 2nd International Conference on Emerging Infectious Diseases. Atlanta, GA. July.
Green, P. J. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. http://citeseer.ist.psu.edu/green95reversible.html Accessed 10/31/2006.
Greenland, S. (1989). Modeling and variable selection in epidemiologic analysis. American Journal of Public Health, 79(3), 340–349.CrossRefGoogle ScholarPubMed
Greenland, S., and Brumback, , , B. (2002). An overview of relations among causal modeling methods. International Journal of Epidemiology, 31 (5), 1030–1037.CrossRefGoogle Scholar
Greenland, S., and Morgenstern, , , H. (2001). Confounding in health research. Annual Review of Public Health, 22, 189–212.CrossRefGoogle ScholarPubMed
Guatama, T., and Van Hulle, M. M. (2003). Surrogate-Based Test For Granger – Causality. http://citeseer.ist.psu.edu/588339.html. Accessed 10/31/2006.
Haas, C. N., Rose, J. B., and Gerba, C. P. (1999). Quantitative Microbial Risk Assessment. New York: John Wiley & Sons, Chapter 7, cf. p. 293.Google Scholar
Hartemink, A. J., Gifford, D. K., Jaakkola, T. S., and Young, R. A. (2001). Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks. Pac Symp Biocomput., 422–433.Google ScholarPubMed
Hazen, G (2003). Multiattribute Structure for QALYs. http://fisher.osu.edu/~butler_267/DAPapers/WP030018.pdf. Accessed 11/02/2006.
Ibrahim, J. G., Chen, M.-H., Lipsitz, S. R., and Herring, A. H. (2005). Missing-data methods for generalized linear models: A comparative review. Journal of the American Statistical Association, 100(469), 332–346.CrossRefGoogle Scholar
Janson, S. (1994). Coupling and Poisson Approximation. http://citeseer.ist.psu.edu/janson94coupling.html. Accessed 11/2/2006.
Kang, S. H., Kodell, R. L., and Chen, J. J. (2000). Incorporating model uncertainties along with data uncertainties in microbial risk assessment. Regul Toxicol Pharmacol, 32(1), 68–72.CrossRefGoogle ScholarPubMed
Keiding, N., and Budtz-Jorgensen, E. (2004). The Precautionary Principle and statistical approaches to uncertainty. Int J Occup Med Environ Health, 17(1), 147–151.Google ScholarPubMed
Lange, K. (2003). Applied Probability. New York: Springer.Google Scholar
Maclure, M. (1990). Multivariate refutation of aetiological hypotheses in nonexperimental epidemiology. Int J Epidemiol, 19(4), 782–787.CrossRefGoogle Scholar
Maclure, M. (1991), Taxonomic axes of epidemiologic study designs: a refutationist perspective. J Clin Epidemiol., 44(10), 1045–1053.CrossRefGoogle ScholarPubMed
Mather, F. J., White, L. E., Langlois, E. C., Shorter, C. F., Swalm, C. M., Shaffer, J. G., Hartley, W. R. (2004). Statistical methods for linking health, exposure, and hazards. Environ Health Perspect., 112(14), 1440–1445.CrossRefGoogle ScholarPubMed
Miloslavsky, M., and Laan, M. (2003). Fitting of mixtures with unspecified number of components using cross validation distance estimate. Computational Statistics and Data Analysis, 41(3–4), 413–428.CrossRefGoogle Scholar
Miyamoto, J. M. (1999). Quality-adjusted life years (QALY) utility models under expected utility and rank dependent utility assumptions. J Math. Psychol., 43(2), 201–237.CrossRefGoogle ScholarPubMed
Owens, D. K., Shachter, R. D., and Nease, R. F. Jr. (1997). Representation and analysis of medical decision problems with influence diagrams. Medical Decision Making., Jul–Sep; 17(3):241–62.CrossRefGoogle ScholarPubMed
Patton, D. E. (1993).The ABCs of risk assessment. EPA Journal, 19(1), 10–15. http://www.bethel.edu/~kisrob/hon301k/readings/risk/RiskEPA/riskepa1.html Accessed 11/02/2006.Google Scholar
Pearl, J. (2002). Causal Inference in the Health Sciences: A Conceptual Introduction. Health Services Outcomes Research Methodology 2:189–220, http://citeseer.ist.psu.edu/599949.html. Accessed 11/02/2006CrossRefGoogle Scholar
Richardson, S., and Green, P. J. (1997). On Bayesian analysis of mixtures with an unknown number of components. http://citeseer.ist.psu.edu/richardson97bayesian.html. Accessed 11/02/2006.
Romano, J. P., and Wolf, M. (2005). Exact and approximate stepdown methods for multiple hypothesis testing. Journal of the American Statistical Association, 100(469), 94–108.CrossRefGoogle Scholar
Savitz, D. A., Greenland, S., Stolley, P. D., and Kelsey, J. L. (1990). Scientific standards of criticism: A reaction to “Scientific standards in epidemiologic studies of the menace of daily life,” by A. R. Feinstein. Epidemiology, 1(1), 78–83.CrossRefGoogle ScholarPubMed
Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. New York: Chapman & Hall.CrossRefGoogle Scholar
Shipley, B. (2000). Cause and Correlation in Biology. A User's Guide to Path Analysis, Structural Equations and Causal Inference. Cambridge University Press.CrossRefGoogle Scholar
Stephens, M. (2000). Bayesian analysis of mixture models with an unknown number of components – an alternative to reversible jump methods. Ann. Statist., 28, (1), 40–74.CrossRefGoogle Scholar
Swanson, N. R., Ozyildirim, A., and Pisu, M. (2001). A comparison of alternative causality and predictive accuracy tests in the presence of integrated and co-integrated economic variables. http://citeseer.ist.psu.edu/427252.html. Accessed 11/2/2006.
Thompson, K. M., Burmaster, D. E., and Crouch, E. A.(1992). Monte Carlo techniques for quantitative uncertainty analysis in public health risk assessments. Risk Analysis, 1, 53–63.CrossRefGoogle Scholar
Tsamardinos, I., Aliferis, C., and Statnikov, A. (2003). Time and Sample Efficient Discovery of Markov Blankets and Direct Causal Relations. http://citeseer.ist.psu.edu/tsamardinos03time.html. Accessed 11/02/2006.
Viallefont, V., Raftery, A. E., and Richardson, S. (2001). Variable selection and Bayesian model averaging in case-control studies. Stat Med., 20(21), 3215–3230.CrossRefGoogle ScholarPubMed
Vose, D. J. (2000). Risk Analysis: A Quantitative Guide (2nd ed.). New York: John Wiley & Sons.Google Scholar
Wang, D., Zhang, W., and Bakhai, A. (2004). Comparison of Bayesian model averaging and stepwise methods for model selection in logistic regression. Stat Med., 23(22), 3451–3467.CrossRefGoogle ScholarPubMed
WHO/FAO. (2002). Risk assessments of Salmonella in eggs and broiler chickens – Interpretative Summary and Full Report. http://www.fao.org/docrep/005/y4393e/y4393e00.htm. Accessed 11/02/2006.
Williamson, J. (2005). Bayesian Nets and Causality Philosophical and Computational Foundations. Oxford, UK: Oxford University Press.Google Scholar
Yokota, F., and Thompson, K. M. (2004). Value of information analysis in environmental health risk-management decisions: Past, present, and future. Risk Analysis, 24(3), 635–650.CrossRefGoogle ScholarPubMed

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