This paper argues that machine learning and epidemiology are on collision course over causation. The discipline of epidemiology lays great emphasis on causation, while ML research does not. Some epidemiologists have proposed imposing what amounts to a causal constraint on ML in epidemiology, requiring it either to engage in causal inference or restrict itself to mere projection. We whittle down the issues to the question of whether causal knowledge is necessary for underwriting predictions about the outcomes of public health interventions. (...) While there is great plausibility to the idea that it is, conviction that something is impossible does not by itself motivate a constraint to forbid trying. We disambiguate the possible motivations for such a constraint into definitional, metaphysical, epistemological, and pragmatic considerations and argue that “Proceed with caution” is the outcome of each. We then argue that there are positive reasons to proceed, albeit cautiously. Causal inference enforces existing classification schema prior to the testing of associational claims, but associations and classification schema are more plausibly discovered in a back-and-forth process of gaining reflective equilibrium. ML instantiates this kind of process, we argue, and thus offers the welcome prospect of uncovering meaningful new concepts in epidemiology and public health—provided it is not causally constrained. (shrink)

This paper investigates the representation of authors with different linguistic backgrounds in academic publishing. We first review some common rebuttals of concerns about linguistic injustice. We then analyze 1039 authors of philosophy journals, primarily selected from the 2015 Leiter Report. While our data show that Anglophones dominate the output of philosophy papers, this unequal distribution cannot be solely attributed to language capacities. We also discover that ethics journals have more Anglophone authors than logic journals and that most authors are affiliated (...) with English-speaking universities, suggesting other factors may also play significant roles. Moreover, some interesting results are revealed when we combine the factor of sex with place of affiliation and linguistic background. It indicates that while certain linguistic injustice is inevitable in academic publishing, it may be more complex than thought. We next introduce Broadbent’s :457–476, 2012, Philosophy of epidemiology, Palgrave Macmillan, New York, 2013, Stud Hist Philos Biol Biomed Sci 48:250–257, 2014) contrastive account of causation to give a causal explanation of our findings. Broadbent’s account not only well characterizes the multifaceted causality in academic publishing but also provides a methodological guideline for further investigation. (shrink)

The recent Ebola virus disease outbreak in Western African countries has raised questions regarding the feasibility of adopting conventional trial designs such as randomized controlled trials for conducting experimental trials in the midst of a fatal epidemic. In the context of Ebola ça Suffit trial conducted in Guinea for testing the efficacy and effectiveness of rVSV–ZEBOV, a candidate vaccine, I argue that the trial design and the methodologies adopted for the trial have been rightly chosen for their ethical appropriateness and (...) social utilities rather than only epistemic advantages. In this paper, I propose and defend the view that in varying scientific research contexts, it is entirely legitimate that non-epistemic values may be prioritized over epistemic considerations. Two vital methodological choices scientists should make while designing a clinical trial are: the choice of appropriate control group and the choice of appropriate randomization. Given this background, I show that the choice of delayed vaccination arm as the control group over placebo control group and the choice of cluster randomization over individually controlled randomization for conducting Ebola ça Suffit trial are perfect instances of such a scenario where addressing social and ethical issues have been justifiably prioritized over epistemic values so that the research in a specific scientific context could be conducted in a socially relevant manner. (shrink)

Christopher Boorse’s Health care ethics: an introduction, Temple University Press, Philadelphia, pp 359–393, 1987; in Humber, Almeder, Totowa What is disease?, Humana Press, New York City, pp 1–134, 1997; J Med Philos, 39:683–724, 2014) Bio-Statistical Theory comprehends diseases in terms of departures from natural norms, which involve an objectively describable deviation from the proper physiological or psychological functioning of parts of the human organism. I argue that while recent revisions and additional considerations shield the BST from a number of issues (...) raised by critics, they give rise to significant new challenges. These are related to the attribution of epistemic authority, the possibility of multiple concepts in the authoritative literature, and the framing of BST as “philosophical explication.” The conclusion is that, in its current form, the BST is unable to provide a robust framework for a naturalist classification. (shrink)

Philosophy of epidemiology has recently emerged as a distinct branch of philosophy. The field will surely benefit from pluralism, reflected in the broad range of topics and perspectives in this special issue. Here, I argue that a healthy pluralistic field of philosophy of epidemiology has social responsibilities that require the field as a whole to engage actively with research on social determinants of health and health disparities. Practicing epidemiologists and the broader community of public health scientists have gradually acknowledged that (...) much of their attention ought to be paid to these, i.e. inequitable between-population health variations that largely reflect the world’s inequitable distribution of resources and social conditions. The paper illustrates how and why health disparities and social determinants of health, through no ill will, become de facto secondary concerns in Alex Broadbent’s field-defining Philosophy of Epidemiology, showing the ease with which these topics can be incidentally sidelined. As means for philosophy of epidemiology to meet its social responsibility obligations, I suggest philosophy of epidemiology expand its attention to two particular lines research. First, the paper discusses Geoffrey Rose’s concept of “causes of incidence”—causes of disparities between populations—and argues for the importance of engaging with these causes. Second, the paper argues for the value of engaging with Bruce Link and Jo Phelan’s “fundamental causes” model of how flexible social resources serve as buffers from harms, generating a plethora of shifting and locally-contingent health effects. (shrink)

This article examines the relationship between the precautionary principle and the well-known Hill criteria of causation. Some have charged that the Hill criteria are anti-precautionary because the...

In this paper, we use the case of the COVID-19 pandemic in Europe to address the question of what kind of knowledge we should incorporate into public health policy. We show that policy-making during the COVID-19 pandemic has been biomedicine-centric in that its evidential basis marginalised input from non-biomedical disciplines. We then argue that in particular the social sciences could contribute essential expertise and evidence to public health policy in times of biomedical emergencies and that we should thus strive for (...) a tighter integration of the social sciences in future evidence-based policy-making. This demand faces challenges on different levels, which we identify and discuss as potential inhibitors for a more pluralistic evidential basis. (shrink)

The use of big data to investigate the spread of infectious diseases or the impact of the built environment on human wellbeing goes beyond the realm of traditional approaches to epidemiology, and includes a large variety of data objects produced by research communities with different methods and goals. This paper addresses the conditions under which researchers link, search and interpret such diverse data by focusing on “data mash-ups”—that is the linking of data from epidemiology, biomedicine, climate and environmental science, which (...) is typically achieved by holding one or more basic parameters, such as geolocation, as invariant. We argue that this strategy works best when epidemiologists interpret localisation procedures through an idiographic perspective that recognises their context-dependence and supports a critical evaluation of the epistemic value of geolocation data whenever they are used for new research purposes. Approaching invariants as strategic constructs can foster data linkage and re-use, and support carefully-targeted predictions in ways that can meaningfully inform public health. At the same time, it explicitly signals the limitations in the scope and applicability of the original datasets incorporated into big data collections, and thus the situated nature of data linkage exercises and their predictive power. (shrink)

This article is an introduction to the Synthese Special Issue, Philosophy of Epidemiology. The overall goals of the issue are to revisit the state of philosophy of epidemiology and to provide a forum for new voices, approaches, and perspectives in the philosophy of epidemiology literature. The introduction begins by drawing on Geoffrey Rose’s work on how to conceptualize and design interventions for populations, rather than individuals. It then goes on to highlight some themes that emerged in the articles that make (...) up the issue: philosophy of epidemiology and epidemiological theory—what they are and what they ought to be, pluralism in measurement and causal attribution, epistemic and non-epistemic values in disputes epidemiological practices, decentering philosophy of epidemiology’s Eurocentrism, letting pragmatism guide uses of big data in epidemiology, and revisiting the lessons of classic texts in epidemiological causal inference. The introduction concludes with comments on a philosophy of epidemiology debate we see on, regarding the politics of philosophy of epidemiology. (shrink)

There are many tangled normative and technical questions involved in evaluating the quality of software used in epidemiological simulations. In this paper we answer some of these questions and offer practical guidance to practitioners, funders, scientific journals, and consumers of epidemiological research. The heart of our paper is a case study of the Imperial College London covid-19 simulator, set in the context of recent work in epistemology of simulation and philosophy of epidemiology.

Christopher Boorse’s bio-statistical theory of health and disease argues that the central discipline on which theoretical medicine relies is physiology. His theory has been much discussed but little has been said about its focus on physiology or, conversely, about the role that other biomedical disciplines may play in establishing a theoretical concept of health. Since at least the 1950s, epidemiology has gained in strength and legitimacy as an independent medical science that contributes to our knowledge of health and disease. Indeed, (...) it not only provides important information about disease distribution and aetiology, but the risk-factor approach it employs seems to challenge BST’s binary conception of health and disease. The objective of the article is to show, firstly, how important information deriving from descriptive and analytical epidemiology forms part of our contemporary medical concepts of health and disease, and secondly, that these elements are not taken into account by BST in a satisfactory way. The article’s central contention, therefore, is that if the project of defining the theoretical concept of health is to be maintained, more importance should be accorded to the contribution made by epidemiology—alongside physiology—in defining health. (shrink)

What kind of a thing are chronic diseases? Are they objects, bundles of signs and symptoms, properties, processes, or fictions? Rather than using concept analysis—the standard approach to disease in the philosophy of medicine—to answer this metaphysical question, I use a bottom-up, inductive approach. I argue that chronic diseases are bodily states or properties—often dispositional, but sometimes categorical. I also investigate the nature of related pathological entities: pathogenesis, etiology, and signs and symptoms. Finally, I defend my view against alternate accounts (...) of the nature of disease. (shrink)

Simple extrapolation is the orthodox approach to extrapolating from clinical trials in evidence-based medicine: extrapolate the relative effect size from the trial unless there is a compelling reason not to do so. I argue that this method relies on a myth and a fallacy. The myth of simple extrapolation is the idea that the relative risk is a ‘golden ratio’ that is usually transportable due to some special mathematical or theoretical property. The fallacy of simple extrapolation is an unjustified argument (...) from ignorance: we conclude that the relative effect size is transportable in the absence of evidence to the contrary. In short, simple extrapolation is a deeply problematic solution to the problem of extrapolation. (shrink)

Medicine is often thought of as a science of the body, but it is also a science of data. In some contexts, it can even be asserted that data drive health. This article focuses on a key piece of data technology central to contemporary practices of medicine: the medical record. By situating the medical record in the perspective of its history, we inquire into how the kinds of data that are kept at sites of clinical encounter often depend on informational (...) requirements that originate well outside of the clinic, in particular in health insurance records systems. Although this dependency of today's electronic medical records on billing requirements is widely lamented by clinical providers, its history remains little studied. Following the archaeology of medicine developed by Michel Foucault in The Birth of the Clinic and expanding his methodology in light of more recent contributions to the field of media archaeology, this article excavates some of the underexplored technological conditions that help constitute today's electronic medical record. If in some contexts, it is true that data drive health, then an archaeology of medical records helps reveal how health insurance records often impact clinical care and, by extension, health and disease. (shrink)

Cancer—and scientific research on cancer—raises a variety of compelling philosophical questions. This entry will focus on four topics, which philosophers of science have begun to explore and debate. First, scientific classifications of cancer have as yet failed to yield a unified taxonomy. There is a diversity of classificatory schemes for cancer, and while some are hierarchical, others appear to be “cross-cutting,” or non-nested. This literature thus raises a variety of questions about the nature of the disease and disease classification. Second, (...) philosophers of science have historically taken the aim of science to be arriving at true theories. However, scientists studying cancer come from a variety of disciplines, with different scientific as well as practical aims. Perhaps it is not surprising, then, that historians and philosophers of science do not seem to agree on how best to characterize the aim and structure of cancer research; it is far from clear whether the appropriate characterization of the aim is arriving at true theories, or even whether the proper units of analysis are “theories”, or instead, “models”, “explanatory frameworks”, “research programs”, “paradigms”, or perhaps, “experimental traditions”. With the rise of “big data” science—such as the Cancer Genome Atlas Project (or TCGA)—and “systems” approaches to the study of disease, both philosophers and historians of science are rethinking how best to describe and explain these distinctive kinds of scientific inquiry. -/- Third, cancer is in part a byproduct of our developmental and life history, as well as our evolutionary history. Cancer progression can be compared to a reversion of development, or, to the evolution of multicellularity. Thus, cancer raises intriguing questions about how we conceive of “functions”, “development”, and the role of our evolutionary history and particularly, selective trade-offs, in vulnerability to disease. -/- Last but not least, cancer research provides a case study for consideration of the roles of values at the science-policy interface. Epidemiological and toxicological research on cancer’s causes informs toxics law and regulatory policy, which raises a variety of questions about the nature of evidence and inductive risk in such contexts. (shrink)