Some consequences of adopting a conditional deterministic causal model in epidemiology

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Abstract
One of the main tasks in public health science is to identify causes of diseases since prevention rests upon such knowledge. The concept of causation is one of the key concepts in science and practice and among epidemiologists two basically different ideas are used in the definition. One is a genuine probability explanation involving a black box element. The other definition is a counterfactual approach based upon conditional determinism. The view on how to define causes of diseases has implications for prevention, the understanding of some basic epidemiologic measures and how to approach study design and data analysis. The paper outline some of these consequences.

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