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Causal Attribution, Counterfactuals and Disease Interventions

Woodward, James (2019) Causal Attribution, Counterfactuals and Disease Interventions. [Preprint]

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Abstract

This paper explores a number of interrelated issues that affect assessment of the global burden of disease: including what can be learned from attributions of particular episodes of death and disability to specific diseases (such as cancer and stroke) about the effects of interventions to remove or reduce the incidence of these diseases (disease interventions), and the use of counterfactuals in epidemiological causal reasoning—a methodology that is employed in the Global Burden of Disease project. It is argued that we can reliably predict the effects of such disease interventions from causal attribution data alone only when strong additional “independence” assumptions are satisfied. It also argued that in many realistic circumstances these assumptions are unlikely to hold, and that when they do not, additional information besides that provided by causal attribution data is needed in order to predict the effects of disease interventions. Among other things, one needs to explicitly model the causal relationships among different diseases or causes of death. This in turn requires frameworks, e.g. structural equations and directed graphs, that explicitly incorporate counterfactual information about what would happen if one were to intervene in various ways. Later sections discuss the sorts of variables that can or should figure in causal claims in epidemiology and the relevance of the epidemiological notions of excess and etiological fractions to predicting the results of disease interventions.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Woodward, Jamesjfw@pitt.sdu
Additional Information: This paper will appear as a chapter in Measuring the Global Burden of Disease: Philosophical Dimensions (Oxford University Press). Please quote from the published version.
Keywords: causation, causal attribution, disease, epidemiology
Subjects: General Issues > Causation
General Issues > Ethical Issues
Specific Sciences > Medicine
General Issues > Science and Policy
Depositing User: Jim Woodward
Date Deposited: 23 May 2019 11:38
Last Modified: 23 May 2019 11:38
Item ID: 16037
Subjects: General Issues > Causation
General Issues > Ethical Issues
Specific Sciences > Medicine
General Issues > Science and Policy
Date: May 2019
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/16037

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