Causality assessments principles

While risk assessment in the context of protecting public health has been performed for many years, it is the 1983 U.S. National Academy of Sciences Report (Committee on the Institutional Means for Assessment of Risks to Public Health Commission on Life Sciences National Research Council 1983) that has served as the tenet for practicing risk assessors (see Chapter 1). Risk assessment was defined as the characterization of the potential adverse health effects of human exposures to environmental hazards. The predictive aspect of risk assessment was set by the use of the word potential. A fundamental expectation of the risk assessment process was that it should attempt to accm-ately predict adverse effects before there is evidence of disease in the population. Thus, risk assessment goes beyond the mere description of epidemiological and clinical case-control studies. In that report, the committee defined logical components of a risk assessment which still serve as guiding principles today. They were and are (a) hazard assessment or the qualitative determination that a stressor poses a hazard as evidence by causal evidence of an ill effect,... 

A major source of confusion in the media relates to how science tries to separate unavoidable death due to natural causes from avoidable death due to modem drugs or chemicals. This is the field of risk assessment and is a crucial function of our regulatory agencies. Confusion and unnecessary anxiety arise from the complexity of the underlying science, misinterpretation of the meaning of scientific results, and a lack of understanding of the basic principles of probability, statistics, and causal inference (assigning cause and effect to an event). 

In this paper, Section 2 introduces the principles of Bayesian method and the inference of BBN. Section 3 describes the structure of the Bayesian causal modeling in the R MM system and the approaches of reliability assessment and maintenance decision-making. In Section 4, both the main functions and the implementation of the generic R MM system are provided to show the wide application scopes. Finally, Section 6 gives some conclusions. 

---