Causal inference in medicine--decision making

In the field of occupational medicine, either when we consider some preventive plans or when we make decisions to compensate for occupational diseases, it has been necessary to discuss causality between work and disease. Furthermore, epidemiologic causality has recently been used in risk assessment in occupational and environmental settings. We have shown that the law of causality in medicine is recognized as probability and continuous variables. Such a law of causality has been recognized in the same way as probability in physics, too, and has been regarded as a model of science. Physicists and mathematicians had claimed the importance of probability in causal inference as well as the principle of uncertainty before it was discovered. We, then, explained Etiologic Fraction (EF), Attributable Proportion for the Exposed Population (APE), Probability of Causation (PC), and so on. The PC has been used to ascertain the conditional probability in an individual case of a disease having been caused by a particular prior exposure, by using the experience of exposed populations to determine the appropriate relative risk, and this has been used for compensation for exposed cases. Next the applicability of information from a population to individuals was presented. Third, we provided a brief historical aspect of epidemiology. The evolutions in Epidemiology have been very rapid, so we pointed out that, in Japan, we could observe many incommensurable phenomena in epidemiologists and physicians depending on the era which was studied by them. Fourth, we discussed judgement and political application based on epidemiologic evidence, using Yanagimoto's classification is also taken or not should be estimated and compared. We presented several examples of reasoning in judgements. Lastly, we discussed several tasks and assignments for the future of epidemiology.