Alex Broadbent

In this article I seek to say what it is for something to count as a neglected disease. I argue that neglect should be defined in terms of efforts at prevention, mitigation and cure, and not solely in terms of research dollars per disability-adjusted life-year. I further argue that the trend towards multifactorialism and risk factor thinking in modern epidemiology has lent credibility to the erroneous view that the primary problem with neglected diseases is a lack of research. A more restrictive contrastive model of disease is endorsed as better suited to the definition of neglected disease.

Commonly we distinguish the strike of a match, as a cause of the match lighting, from the presence of oxygen, as a mere condition. In this paper I propose an account of this phenomenon, which I call causal selection. I suggest some reasons for taking causal selection seriously, and indicate some shortcomings of the popular contrastive approach. Chief among these is the lack of an account of contrast choice. I propose that contrast choice is often just the counterfactual scenario in which the effect does not occur: I suggest that if c causes e, then if e hadn't occurred, c wouldn't have occurred. I argue that this is a necessary condition on causation which causes meet but mere conditions fail.

This paper seeks to determine the significance, if any, of epidemiological evidence to prove the specific causation element of liability in negligence or other relevant torts—in particular, what importance can be attached to a relative risk > 2, where that figure represents a sound causal inference at the general level. The paper discusses increased risk approaches to epidemiological evidence and concludes that they are a last resort. The paper also criticizes the proposal that the probability of causation can be estimated with reference to the RR, such that RR > 2 is necessary and sufficient for causation. It is argued, following arguments by Sander Greenland and others, that RR > 2 is not necessary for proof of specific causation, except under restrictive biological assumptions that are not known to be satisfied for any important disease, and therefore must never be required. However, the paper argues that in some circumstances RR > 2 can be sufficient to prove causation at law. This position is defended against the widely held judicial and academic view that epidemiological evidence must be accompanied by something else, particular to the case at hand, if it is to have probative force for specific causation. It is argued that far from being epistemically irrelevant, to achieve correct and just outcomes it is in fact mandatory to take epidemiological evidence into account in deciding specific causation. Failing to consider such evidence when it is available leads to error and injustice. The conclusion is that in certain circumstances epidemiological evidence of RR > 2 is not necessary to prove specific causation but that it is sufficient. This “sufficiency” is confined to circumstances where there is no other evidence, as a way of getting clear on what the epidemiological evidence says. Once we have worked out what it says, this must be weighed against the other relevant evidence, if there is any.

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms.

When is a cause of a cause of an effect also a cause of that effect? The right answer is either Sometimes or Always. In favour of Always, transitivity is considered by some to be necessary for distinguishing causes from redundant non-causal events. Moreover transitivity may be motivated by an interest in an unselective notion of causation, untroubled by principles of invidious discrimination. And causal relations appear to add up like transitive relations, so that the obtaining of the overarching relation is not independent of the obtaining of the intermediaries. On the other hand, in favour of Sometimes, often we seem not to treat events that are very spatiotemporally remote from an effect as its causes, even when connected to the effect in question by a chain of counterfactual or chance-raising dependence. Moreover cases of double prevention provide counterexamples to causal transitivity even over short chains. According to the argument of this paper, causation is non-transitive. Transitizing causation provides no viable account of causal redundancy. An unselective approach to causation may motivate resisting the distance counterexamples to transitivity, but it does not help with double prevention, and even makes it more intractable. The strongest point in favour of transitivity is the adding up of causal relations, and this is the point that extant non-transitizing analyses have not adequately addressed. I propose a necessary condition on causation that explains the adding up phenomenon. In doing so it also provides a unifying explanation of distance and double prevention counterexamples to transitivity.

This paper takes it as a premise that a distinction between matters of fact and of law is important in the causal inquiry. But it argues that separating factual and legal causation as different elements of liability is not the best way to implement the fact/law distinction. What counts as a cause-in-fact is partly a legal question; and certain liability-limiting doctrines under the umbrella of “legal causation” depend on the application of factual-causal concepts. The contrastive account of factual causation proposed in this paper improves matters. This account more clearly distinguishes matters of fact from matters of law within the cause-in-fact inquiry. It also extends the scope of cause-in-fact to answer some questions currently answered by certain doctrines of legal causation—doctrines that, it is argued, are more naturally seen as applications of our ordinary causal concept than as noncausal liability-limiting devices.

We are pleased to once again present to the readers of Theoretical Medicine and Bioethics papers from the Philosophy of Medicine Roundtable. Previous issues have followed the 3rd and 4th Roundtables, and the current issue presents a selection from the more than 20 papers presented at the 5th Philosophy of Medicine Roundtable, which took place in New York, at Columbia University, in November 2013. Like its predecessors, held in Birmingham, AL, Rotterdam, and San Sebastian, this Roundtable attracted speakers from around the world. It also featured keynote presentations from Rita Charon of Columbia University and Ross Upshur of the University of Toronto.It may seem somewhat odd to feature a special issue on philosophy of medicine in a journal that effectively has philosophy of medicine in its title. However, a review of the contents of this journal and similar ones, such as the Journal of Medicine and Philosophy, will quickly reveal such an issue’s purpose. The dominant content of these j ..

If there is any value in the idea that disease is something other than the mere absence of health then that value must lie in the way that diseases are classified. This paper offers further development of a view advanced previously, the 'contrastive model' of disease: it develops the account to handle asymptomatic disease ; and in doing so it relates the model to a broadly biostatistical view of health. The developments are prompted by considering cancers featuring viruses as prominent causes, since these appear to amount to cases where the prescriptions of the contrastive model could be followed, but aren't. The resulting irrelevance objection claims that the contrastive model is irrelevant to medical science and practice. The paper seeks to rebut the irrelevance objection.