Benjamin Smart

This book, inspired by public health policymaking during the Covid-19 pandemic, proposes an innovative capacities-based approach to understanding health at all levels of biological complexity - including at the level of the population. This capacities approach to health is applied to various issues within the philosophy of public health, including the goal of public health, evidence-based public health, the metaphysics of epidemics, public health ethics, and decolonizing public health. The author advocates for greater attention to be paid to the contextual conditions in which public health policies are to be implemented, for a public health principlism grounded by the enhancement of emergent capacities of populations and those of their members, and for the elimination of contributory injustice in medicine and public health policy. This book is essential reading for all scholars, researchers and advanced students of the philosophy of public health, health ethics, and public health policy.

Unbefriended patients are those with decisional impairments who lack family or friends to serve as healthcare surrogates. When such patients cannot make decisions, the court typically appoints a professional guardian to make choices aligned with the patient’s values and preferences. However, this case report illustrates ethical challenges that can arise when professional guardians disregard the patient’s authentic wishes. In this case study, the 38-year-old unbefriended African American male patient expressed fears about traumatic resuscitation efforts and ultimately desired de-escalation of care, which the guardian was hesitant to honor despite confirmed decision-making capacity. The guardian quickly reversed a new do-not-resuscitate order when the patient later changed his mind. Decisions about aggressive interventions like a colostomy were significantly delayed while awaiting final judgments involving the guardian’s supervisors and the judicial system. The case highlights pitfalls with guardians defaulting to treatment escalation without sufficiently engaging with ethical standards or eliciting the patient’s narrative identity, leading to inconsistent surrogate decisions. We propose that more robust reforms are needed, including enhanced training of guardians in ethical decision-making, and we present other means to facilitate best practices in proxy decision-making.

In this concluding chapter we describe our view how different kinds of information are integrated in order to arrive at causal explanation in population health science. In particular, such information comes from individuals and populations (target), from epidemiology and the bench sciences (method), and from observation and experiment (manipulation). We discuss recent “systems” approaches in biology, medicine, and epidemiology in the section on “method” and the question what it is about “manipulation” that convinces many of its capability to support causal inference. In the final section, we look at complexity versus simplicity and suggest that the simplification inherent in epidemiological evidence generation may be an asset, not a liability.

In this chapter, we introduce the concept of Health Data Science and define its three domains: technology, analytics, and conceptual. In the technology domain, we drill down from computer science via health informatics to public health informatics. The analytics domain includes biostatistics, bioinformatics, epidemiology, and simulation. In the conceptual domain, we introduce the philosophy of information, and of health and causation. Taken together, these domains provide the theoretical backdrop for the remainder of the book.

Having discussed the metaphysics of disease etiology in Chap. 3, in this chapter we discuss a number of important epistemological problems concerning causal inference in medicine and population health informatics. With origins tracing back to at least the eighteenth century, the problem of induction (that is, the problem of justifying inferences from observed data to likely future or unobserved outcomes) is one of the most discussed issues in the philosophical literature. Given that causal inference plays such a large role in the health sciences and that all causal inferences are inductive in kind, we take a detailed look at how those working in the health sciences go about identifying, and justifying their causal claims. With this in mind, we examine Austin Bradford Hill’s heuristics for causal inference in epidemiology, and argue that the postulation of criteria such as Hill’s is nothing but a replacement of one dilemma with another: why should it be easier to identify the truth condition of the heuristics, than identifying the truth condition of the relationship between exposure and effect if they were hard-and-fast criteria? We conclude by asking whether genuine medical knowledge is possible. We outline a number of historically popular responses to the ultimate question in epistemology: “what is knowledge”, and demonstrate the profound effect one’s answer to that question has on the ability to claim medical knowledge of any form.

In this chapter we provide a philosophical discussion of the nature of causation, as applied to the investigation of disease etiology and preventive and curative interventions. This chapter is primarily an exercise in metaphysics and conceptual analysis, in which we analyze existing concepts of causation dating back to David Hume’s eighteenth century empiricism, right up to the public health-specific analysis provided by Kenneth Rothman, and the more recent dispositionalist ontologies of Stephen Mumford and Rani Lill Anjum. We argue that different metaphysical concepts of causation are implicit in different research methodologies in the medical sciences. We relate J. L. Mackie’s “Inus condition” metaphysic of causation to Rothman’s epidemiologic account of disease etiology, and go on to discuss “The counterfactual account of causation”. The latter is often used by epidemiologists as an alternative nomenclature of the “potential outcomes approach” to causal inference. We will show why this is the case, and identify differences between this strategy for causal inference in public health and the popular philosophical view. We conclude that the concepts of causation employed in the health sciences are integral to their practice, whether used consciously or unconsciously, and that a clear insight into the nature of the metaphysical and conceptual schemes underlying the etiological process would help all those working in the medicine and public health.

In the previous chapters we have focused on metaphysical and epistemological concepts of causation, in medicine and population health. In this chapter, we discuss risk estimation, the focus of public health informatics methods. First, we introduce the concepts of risk and prediction. We contrast individual and population risk and discuss why using quantitative risk estimates in individuals is problematic. We describe methods for risk estimation in population health science and conclude with the proposal that risk estimation is giving a causal explanation in population health science.

This chapter revolves around the idea that knowledge is generated from data. We briefly describe Ackoff’s hierarchy, which starts with data and proceeds via information to knowledge, understanding and wisdom. In contrast, we propose to de-emphasize understanding and wisdom, and to insert evidence between information and knowledge. We outline a framework that takes data as raw symbols, which morph into information when contextualized. Information becomes evidence when compared to relevant standards. Evidence is used to test hypotheses and is transformed into knowledge by consensus. As quality checkpoints for the transition between levels we offer relevance, robustness, repeatability, and reproducibility.

The goal of this book is to take a first step towards a framework for causal explanation in public/population health informatics and analytics. We first provide an introduction to the concepts of public health informatics (PHI) and population health informatics (PopHI). Next, we introduce the general approach we take – the etiological stance – and the idea that risk and causation are two ways of looking at etiology, the process of illness occurrence. We offer a brief description of how the discussion of causation and causal inference in epidemiology relates to concepts in philosophy of science and contrast deterministic folk psychology of causation with a pragmatic perspective built on probabilistic concepts of causation. Finally, we clarify the agenda of this book with a focus on what it is not about and give a roadmap of the remaining chapters.

Of all the positions that have amassed intellectual traction within the philosophy of science in the previous decades, it is scientific pluralism that is most often pitted against Karl Popper’s image of the sciences. In fact, many card-carrying scientific pluralists explicitly distance their philosophies from Popper’s critical rationalism. Particularly, they consider pluralism about scientific theories or explanations to be in opposition to falsificationism. In this paper we shall critically re-examine this claim and the relation of Popper’s philosophy to millennial scientific pluralism. Following Kellert and colleagues, we distinguish two flavours of scientific pluralism: radical and modest. For both flavours, we examine congruities between pluralism and Popper’s work. While we acknowledge crucial differences, we argue that these tend to be overstated, and that there is much room for fruitful exchange. More specifically, we highlight that Popper endorses and embraces plurality with respect to many types of scientifically relevant entities including theories, models, and practices; and we qualify Popper’s purported fixation on truth as the only objective of science.

Philosophy of Medicine has for a long time been preoccupied with analyzing the concepts of health, disease and illness. Relatively speaking, the concept of medicine itself has received very little attention. This paper is a contribution to the relatively neglected debate about the nature of medicine. Building on the work of Alex Broadbent (Broadbent, 2018a, b), Chadwin Harris (Harris, 2018) and Thaddeus Metz (Metz, 2018), in this paper I question the persuasiveness of Broadbent’s account of the “core business” of medicine, The Inquiry Thesis, and propose an alternative: a revised version of The Curative Thesis, which I coin The Best Available Intervention Thesis. Crudely, this suggests that Medicine is the sustained and organised effort to determine and prescribe the best available treatment (curative or preventative) for patients.

Slowly, we are gaining a deeper understanding of the persisting psychological trauma experienced by students at colonial universities, and beginning to recognize that the Eurocentric curricula and pedagogies must change if students such as the “born-frees” in post-Apartheid South Africa are to flourish. In this article, I present a sub-Saharan African concept of “the ethical teacher,” and use this to ground a “ubiquitous action-reaction” teaching model. I use these concepts to develop a decolonized pedagogy – a teaching methodology that avoids a number of harmful colonial teaching practices in philosophy. I suggest a number of novel ways of accommodating a “decolonized education” with a view to inspiring teachers of philosophy in colonial countries globally. I propose a new, malleable pedagogical model that is particularly useful in the colonial context, since its uniqueness lies in the African ethical framework that grounds it. However, I contend that philosophy educators globally will benefit from taking the principles proposed in this article seriously.

Many necessitarians about cause and law (Armstrong 1983; Mumford 2004; Bird 2007) have argued that Humeans are unable to justify their inductive inferences, as Humean laws are nothing but the sum of their instances. In this paper I argue against these necessitarian claims. I show that Armstrong is committed to the explanatory value of Humean laws (in the form of universally quantified statements), and that contra Armstrong, brute regularities often do have genuine explanatory value. I finish with a Humean attempt at a probabilistic justification of induction, but this fails due to its assumption that the proportionality syllogism is justified. Although this attempt fails, I nonetheless show that the Humean is at least as justified in reasoning inductively as Armstrong.

This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.

In this paper I untangle a recent debate in the philosophy of epidemiology, focusing in particular on the Potential Outcomes Approach to causation. As the POA strategy includes the quantification of ‘contrary-to-fact’ outcomes, it is unsurprising that it has been likened to the counterfactual analysis of causation briefly proposed by David Hume, and later developed by David Lewis. However, I contend that this has led to much confusion. Miguel Hernan and Sarah Taubman have recently argued that meaningful causal inferences cannot be drawn from obesity. This paper prompted Alex Broadbent to criticise the POA conception of causation, accusing two of the four theses its proponents are committed to, of circularity and falsity. Here I scrutinise Broadbent’s claims, and suggest that a Popperian approach to causal inference in epidemiology diffuses both of his objections. However, I move on to argue that the POA’s commitment to granting only manipulable conditions causal-status, renders the position implausible as a conceptual analysis of causation. That said, I conclude that the strategy the POA employs is an effective tool for effect-measurement in intervention-cases; if it is a conceptual analysis of causation at all, it must be restricted to the causal analysis of manipulable conditions. The POA’s failure to successfully demarcate causal from non-causal conditions simpliciter should therefore not be viewed as a serious threat.

Some time ago, Joel Katzav and Brian Ellis debated the compatibility of dispositional essentialism with the principle of least action. Surprisingly, very little has been said on the matter since, even by the most naturalistically inclined metaphysicians. Here, we revisit the Katzav–Ellis arguments of 2004–05. We outline the two problems for the dispositionalist identified Katzav in his 2004 , and claim they are not as problematic for the dispositional essentialist at it first seems – but not for the reasons espoused by Ellis

Take open-future Humeanism to comprise the following four tenets: (T1) that truth supervenes on a mosaic of local particular matters of fact; (T2) that there are no necessary connections between distinct existences; (T3) that there is a dynamic present moment; and (T4) that there are no future facts; that is, contingent propositions about the future obtain truth values only when their referents are actualised. Prima facie this is a deeply problematic metaphysic for the Humean, since given that the widely accepted Humean conception takes all truths (inclusive of nomological truths) to supervene on an omnitemporal mosaic of local particular matters of fact, if there are no future facts, then the Humean can neither provide laws of nature, nor justify many everyday inductive inferences. However, I argue that this eternalist metaphysic is in tension with at least one of Hume’s central metaphysical claims concerning causation, e.g. that causal regularities may cease to hold at any time. In this paper I propose and defend one possible open-future Humean metaphysic which admits of “true-to-Hume” causal and nomological facts. Furthermore, although I am happy to concede that induction is problematic for the open-future Humean, I demonstrate that it poses no greater threat to the open-future conception than it does to the popular Lewisian conception of natural law.

Identifying the necessary and sufficient conditions for individuating and classifying diseases is a matter of great importance in the fields of law, ethics, epidemiology, and of course, medicine. In this paper, I first propose a means of achieving this goal, ensuring that no two distinct disease-types could correctly be ascribed to the same disease-token. I then posit a metaphysical ontology of diseases—that is, I give an account of what a disease is. This is essential to providing the most effective means of interfering with disease processes. Following existing work in the philosophy of medicine and epidemiology (primarily Christopher Boorse; Caroline Whitbeck; Alexander Broadbent), philosophy of biology (Joseph LaPorte; D.L. Hull), conditional analyses of causation (J.L. Mackie; David Lewis), and recent literature on dispositional essentialism (Stephen Mumford and Rani Anjum; Alexander Bird), I endorse a dispositional conception of disease. Following discussion of various conceptions of disease-identity, their relations to the clinical and pathological effects of the diseases in question, and how diseases are treated, I conclude (i) that diseases should be individuated by their causes, and (ii) that diseases are causal processes best seen as simultaneously acting sequences of mutually manifesting dispositions