Although epidemiology as a scientific study of disease in populations claimed an independent disciplinary status already in the mid–nineteenth century, its history in the twentieth century can be seen as a continuous and often contentious attempt to define the field’s social and intellectual boundaries vis-à-vis a variety of neighboring scientific fields and public health practices. In a period dominated by laboratory biomedical sciences, epidemiologists repeatedly tried to spell out how their discipline met the requirements of scientificity despite its focus on (...) disease as a collective phenomenon and its reliance on nonlaboratory methods. This article asks about the relationship between the changing institutional and intellectual contexts of British epidemiological practice and the epidemiologists’attempts to define both science in general and epidemiology in particular. An examination of the epidemiologists’boundary-making endeavors is also used to reflect on the circumstances in which scientists engage in the discourse of disciplinary demarcations. (shrink)

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)

Epidemiology is a science of disease which specifies rates (illness prevalences, incidences, distributions, etc.). Evolution is a science of life which specifies changes (gene frequencies, generations, forms, function, etc.). Evolutionary Epidemiology is a synthesis of these two sciences which combines the empirical power of classical methods in genetical epidemiology with the interpretive capacities of neo-darwinian evolutionary genetics. In particular, prevalence rates of genetical diseases are important data points when reformulated for the purpose of analysis in terms of their evolutionary frequencies. (...) Traits which exceedprevalences beyond the rates of mutation (in Hardy-Weinberg calculations) or evidence unusualrange of phenotypic reaction are of special interest. This is because traits which did not confer advantages in the environment of evolutionary adaptation cannot accede, through natural selection, to anything but low rates of genomic prevalence.Evolutionary epidemiology is, in all of medicine, of particular promise in ongoing efforts to better understand psychopathology. Many complexities of phenotypic adjustment arise when new developmental demands are placed on an old genome. The new and complex biosocial ecology of human mass society now evokes different phenotypes than those in the prehistorical ecology to which the genome is structurally and functionally better adapted. Some of these new phenotypes are darwinian failures. In this paper, the theoretical implications of evolutionary epidemiology are extended and some tentative points of clinical application (particularly to psychiatry) are offered. (shrink)

The importance of legal epidemiology in public health law research has undoubtedly grown over the last five years. Scholars and practitioners together have developed guidance on best practices for the field, including: placing emphasis on transdisciplinary collaborations; creating valid, reliable, and repeatable research; and publishing timely products for use in decision-making and change. Despite the energy and expertise researchers have brought to this important work, they name significant challenges in marshalling the diverse skill sets, quality controls, and funding to implement (...) legal epidemiology activities. The Centers for Disease Control and Prevention has worked to develop cross-cutting research and translation on issues of national priority in legal epidemiology, and has explored ways to overcome some of these challenges. As such, this article describes a case study of the use of law to characterize states' prior authorization policies regarding medication used to treat attention-deficit/hyperactivity disorder, a central component of a broader effort to improve behavior therapy options for young children with ADHD. This article highlights the types of legal epidemiology work we have undertaken, the application of this work to an emerging public health problem, and the lessons learned in creating impactful research for the field. (shrink)

Epidemiology is a science of disease which specifies rates . Evolution is a science of life which specifies changes . ‘Evolutionary Epidemiology’ is a synthesis of these two sciences which combines the empirical power of classical methods in genetical epidemiology with the interpretive capacities of neo-darwinian evolutionary genetics. In particular, prevalence rates of genetical diseases are important data points when reformulated for the purpose of analysis in terms of their evolutionary frequencies. Traits which exceedprevalences beyond the rates of mutation or (...) evidence unusualrange of phenotypic reaction are of special interest. This is because traits which did not confer advantages in the environment of evolutionary adaptation cannot accede, through natural selection, to anything but low rates of genomic prevalence.Evolutionary epidemiology is, in all of medicine, of particular promise in ongoing efforts to better understand psychopathology. Many complexities of phenotypic adjustment arise when new developmental demands are placed on an ‘old’ genome. The new and complex biosocial ecology of human mass society now evokes different phenotypes than those in the prehistorical ecology to which the genome is structurally and functionally better adapted. Some of these new phenotypes are darwinian failures. In this paper, the theoretical implications of evolutionary epidemiology are extended and some tentative points of clinical application are offered. (shrink)

Written by epidemiologists, ethicists and legal scholars, this book provides an in-depth account of the moral problems that often confront epidemiologists, including both theoretical and practical issues. The first edition has sold almost three thousand copies since it was published in 1996. This edition is fully revised and includes three new chapters:Ethical Issues in Public Health Practice, Ethical Issues in Genetic Epidemiology, and Ethical Issues in International Health Research and Epidemiology. These chapters collectively address important developments of the past decade. (...) Three chapters from the first edition have also been reorganized: Ethicall Optimized Study Deisgns in Epidemiology, Ethical Issues in Epidemiologic Research with Children, and The Ethics of Epidemiologic Research with Older Populations. Instead of standing alone, these chapters have been integrated into chapters on informed consent, confidentiality and privacy protection, and community-based intervention studies. (shrink)

Epidemiologists’ discussions on causation are not always very enlightening with regard to the notion of ‘cause’ in epidemiology. Epidemiologists rightly work from a science-based approach to causation in epidemiology, but largely disagree about the matter. Disagreement may be partly due to confusion of the question of useful concepts for causal inference in epidemiological practice with the question of the metaphysical presuppositions of causal concepts used in epidemiology. In other words, epidemiologists seem to confuse the practical results of epidemiological research at (...) the population level with the metaphysical views about the reality of disease causation at the individual level in their writings on causation. (shrink)

How is scientific data used to represent phenomena and as evidence for claims about phenomena? In this paper, I propose that a specific type of claims – evidential claims – is involved in data practices to define and restrict the representational and evidential content of a dataset. I present an account of data practices in the epidemiology of the exposome based on the notion of evidential claims, which helps unpack the approaches, assumptions and warrants that connect different stages of research. (...) I identify three different strategies to generate different types of evidential claims in this case. The macro strategy, which individuates the dataset that serves as the initial evidential space for research. The micro strategy, which is used to generate evidential claims about the microscopic and individual component of target phenomena. The association strategy, that uses evidence from the other strategies to identify a dataset as representation of the different levels and relations of exposure and disease. Differentiating between these strategies sheds light on the multi-faceted landscape of biomedical research on environment and health; and the roles of data and evidence in the process of inquiry. (shrink)

Toxic speech inflicts damage to mental and physical health. This process can be chronic or acute, temporary or permanent. Understanding how toxic speech inflicts these harms requires both an account of linguistic practices and, because language is inherently social, tools from epidemiology. This paper explores what we can learn from two epidemiological models: a common source model that emphasizes poisons, and a propagated transmission model that better fits contagions like viruses.

Epidemiology is a field torn between practices of surveillance and methods of analysis. Since the onset of COVID-19, epidemiological expertise has been mostly identified with the first, as dashboards of case and mortality rates took centre stage. However, since its establishment as an academic field in the early 20th century, epidemiology’s methods have always impacted on how diseases are classified, how knowledge is collected, and what kind of knowledge was considered worth keeping and analysing. Recent advances in digital epidemiology, this (...) article argues, are not just a quantitative expansion of epidemiology’s scope, but a qualitative extension of its analytical traditions. Digital epidemiology is enabled by deep and digital phenotyping, the large-scale re-purposing of any data scraped from the digital exhaust of human behaviour and social interaction. This technological innovation is in need of critical examination, as it poses a significant epistemic shift to the production of pathological knowledge. This article offers a critical revision of the key literature in this budding field to underline the extent to which digital epidemiology is envisioned to redefine the classification and understanding of disease from the ground up. Utilising analytical tools from science and technology studies, the article demonstrates the disruptive expectations built into this expansion of epidemiological surveillance. Given the sweeping claims and the radical visions articulated in the field, the article develops a tentative critique of what I call a fantasy of pathological omniscience; a vision of how data-driven engineering seeks to capture and resolve illness in the world, past, present and future. (shrink)

Epidemiologists’ discussions on causation are not always very enlightening with regard to the notion of ‘cause’ in epidemiology. Epidemiologists rightly work from a science-based approach to causation in epidemiology, but largely disagree about the matter. Disagreement may be partly due to confusion of the question of useful concepts for causal inference in epidemiological practice with the question of the metaphysical presuppositions of causal concepts used in epidemiology. In other words, epidemiologists seem to confuse the practical results of epidemiological research at (...) the population level with the metaphysical views about the reality of disease causation at the individual level in their writings on causation. (shrink)

Over the past two decades, the epidemic of HIV/AIDS has challenged the public health community to fundamentally rethink the framework for preventing infectious diseases. While much progress has been made on the biomedical front in treatments for HIV infection, prevention still relies on behaviour change. This book documents and explains the remarkable breakthroughs in behavioural research design that have emerged to confront this new challenge: the study of partnership networks.Traditionally, public health research focused on the "knowledge, attitudes, and practices " (...) of individuals, an approach designed for understanding health-related behaviour like seat-belt wearing and cigarette smoking. For HIV and other sexually transmitted infections, however, there are at least two people involved in transmission. This may not seem like a big difference, but in fact it changes everything. First, it means that your risk depends on your partners -- and on their partners, and their partners: it depends on your position in the network of partnerships. Consider, for example, the rise of infections among monogamous women. Second, it means that individuals are not free to simply change their behaviour -- condom use, or abstinence, needs to be negotiated with a partner. both the epidemiology of risk and constraints to behaviour are therefore a function of the partnership network. And our ability to design effective prevention strategies depends on our ability to measure and summarize that network. Using the traditional research designs, you would not see this network at all -- you would only see the unconnected nodes. They key to solving this problem lies in Network Analysis, before now a relatively obscure subfield in Sociology.For empirical studies of networks to become feasible, however, many problems had to be solved. This book documents the rapid progress that has been made. It brings together eight pioneering studies that have sought to map the networks that spread infection around the world. Each chapter reviews the questions that drove the study, the changes in methodology that were needed to implement the network survey, the mistakes and successes encountered, and the central findings that the network design made possible. An introduction provides an overview of network survey design, a glossary provides a summary of network terminology, and example questionnaires from each study provide a template for further research. This is a unique and valuable resource for the international public health research community. (shrink)

The present article identifies how social determinants of health raise two categories of philosophical problems that also fall within the smaller domain of ethics; one set pertains to the philosophy of epidemiology, and the second set pertains to the philosophy of health and social justice. After reviewing these two categories of ethical concerns, the limited conclusion made is that identifying and responding to social determinants of health requires inter-disciplinary reasoning across epidemiology and philosophy. For the reasoning used in epidemiology to (...) be sound, for its scope and (moral) purpose as a science to be clarified as well as for social justice theory to be relevant and coherent, epidemiology and philosophy need to forge a meaningful exchange of ideas that happens in both directions. (shrink)

Applying a medical conception of toxicity to speech practices, this paper calls for an epidemiology of discursive toxicity. Toxicity highlights the mechanisms by which speech acts and discursive practices can inflict harm, making sense of claims about harms arising from speech devoid of slurs, epithets, or a narrower class I call ‘deeply derogatory terms.’ Further, it highlights the role of uptake and susceptibility, and so suggests a framework for thinking about damage variation. Toxic effects vary depending on one’s epistemic position, (...) access, and authority. An inferentialist account of discursive practice plus a dynamic view of the power of language games offers tools to analyze the toxic power of speech acts. A simple account of language games helps track changes in our discursive practices. Identifying patterns contributes to an epidemiology of toxic speech, which might include tracking increasing use of derogatory terms, us/them dichotomization, terms of isolation, new essentialisms, and more. Using this framework, I analyze some examples of speech already said to be toxic, working with a rough concept of toxicity as poison. Finally, exploring discursive toxicity pushes us to find ways that certain discursive practices might “inoculate” one to absorbing toxic messages, or less metaphorically, block one’s capacity to make toxic inferences, take deontic stances that foster toxicity, etc. (shrink)

Social epidemiology has made a powerful case that health determined not just by individual-level factors such as our genetic make-up, access to medical services, or lifestyle choices, but also by social conditions, including the economy, law, and culture. Indeed, at the level of populations, evidence suggests that these “structural” factors are thepredominantinfluences on health. Legal scholars in public health, including those in the health and human rights movement, have contended that human rights, laws, and legal practices are powerfully linked to (...) health. Social epidemiology and health-oriented legal scholarship are complementary in their focus and their research needs. Legal scholarship has identified plausible ways in which legal and human rights factors could be influencing health, but empirical evidence has been limited. (shrink)

The paper examines definitions of ‘cause’ in the epidemiological literature. Those definitions all describe causes as factors that make a difference to the distribution of disease or to individual health status. In the philosophical jargon, causes in epidemiology are difference-makers. Two claims are defended. First, it is argued that those definitions underpin an epistemology and a methodology that hinge upon the notion of variation, contra the dominant Humean paradigm according to which we infer causality from regularity. Second, despite the fact (...) that causes be defined in terms of ‘difference-making’, this cannot fixes the causal metaphysics. Causality in epidemiology ought to be interpreted according to the epistemic theory. In this approach relations are deemed causal depending on the evidence and on the available methods. Indeed, evidence to establish causal claims requires difference-making considerations; furthermore, those definitions of cause reflect the ‘variational’ epistemology and methodology of epidemiology. (shrink)

Social epidemiology has made a powerful case that health determined not just by individual-level factors such as our genetic make-up, access to medical services, or lifestyle choices, but also by social conditions, including the economy, law, and culture. Indeed, at the level of populations, evidence suggests that these “structural” factors are the predominant influences on health. Legal scholars in public health, including those in the health and human rights movement, have contended that human rights, laws, and legal practices are powerfully (...) linked to health. Social epidemiology and health-oriented legal scholarship are complementary in their focus and their research needs. Legal scholarship has identified plausible ways in which legal and human rights factors could be influencing health, but empirical evidence has been limited. (shrink)

In this paper I apply the epidemiological model of the spread of beliefs and how they become cultural representations to the field of fallacies. The model suggests that beliefs tend to replicate as a virus does in a potential epidemic, and those strains that are dominant in a given socio-cultural sphere become cultural representations. My ultimate aim is to denounce the fact that some presumptive argumentation schemes are widely applied as definitive arguments, but turn out to be instances of common (...) and traditional fallacies. Moreover, some such fallacies have managed to colonise the human mind and become cultural representations in society today. Adopting the approach I advocate here, we could say that the fallacy has become a belief, which has then managed to replicate like a virus, and finally the fallacy has become a cultural representation. One of the great harms that results from this process is that it is very difficult to open up effective lines of argument that expose the fallacious nature of these new and perverse cultural representations. (shrink)

In their 2008 paper, Persson and Savulescu suggest that for moral bioenhancement (MBE) to be effective at eliminating the danger of ‘ultimate harm’ the intervention would need to be compulsory. This is because those most in need of MBE would be least likely to undergo the intervention voluntarily. By drawing on concepts and theories from epidemiology, this paper will suggest that MBE may not need to be universal and compulsory to be effective at significantly improving the collective moral standing of (...) a human populace and reducing the threat of ultimate harm. It will identify similarities between the mechanisms that allow biological contagions (such as a virus) and behaviours (such as those concerned with ethical and unethical actions) to develop, spread, and be reinforced within a population. It will then go onto suggest that, just as with the epidemiological principle of herd immunity, if enough people underwent MBE to reach a minimum threshold then the incidence and spread of immoral behaviours could be significantly reduced, even in those who have not received MBE. (shrink)

Cultural epidemiology is a theoretical framework that enables historical studies to be informed by cognitive science. It incorporates insights from evolutionary psychology (viz. cultural evolution is constrained by universal properties of the human cognitive apparatus that result from biological evolution) and from Darwinian models of cultural evolution (viz. population thinking: cultural phenomena are distributions of resembling items among a community and its habitat). Its research program includes the study of the multiple cognitive mechanisms that cause the distribution, on a cultural (...) scale, of representations and material cultural items. By a detailed analysis of the social cognitive causal chain that occurred in the past, one can find out – and specify – which are the factors of attraction that account for cultural stability as well as historical cultural change. After reviewing recent research and developments in cognitive history, I present the concept of cultural attractor and explain why cultural attractors are historically variable. In doing so, I emphasize the role of historically constituted cognitive mechanisms, which account for much of historical cultural developments. I argue that the framework of cultural epidemiology can better account for these important historical phenomena than either evolutionary psychology accounts of culture or dual inheritance theory. I conclude that describing and explaining the history of cultural attractors is a good research goal for historians. (shrink)

Since at least the mid-1970s, public health and law enforcement officials have conducted joint or parallel investigations of both health problems possibly associated with criminal intent and crimes having particular health dimensions. However, the anthrax and other terrorist attacks of fall 2001 have dramatically underscored the needs that public health and law enforcement officials have for a clear understanding of the goals and methods each discipline uses in investigating such problems, including and especially the potential use of biologic agents as (...) weapons of mass destruction. Recognition of these needs has prompted some experts to call for the application of “forensic epidemiology” to such problems. Even before the attacks of fall 2001, other problems, such as the detection of the West Nile Virus in the United States and concerns that the emergence of this infectious agent was the consequence of a deliberate act, raised novel challenges to the combined interests of public health and criminal investigators. (shrink)

Since at least the mid-1970s, public health and law enforcement officials have conducted joint or parallel investigations of both health problems possibly associated with criminal intent and crimes having particular health dimensions. However, the anthrax and other terrorist attacks of fall 2001 have dramatically underscored the needs that public health and law enforcement officials have for a clear understanding of the goals and methods each discipline uses in investigating such problems, including and especially the potential use of biologic agents as (...) weapons of mass destruction. Recognition of these needs has prompted some experts to call for the application of “forensic epidemiology” to such problems. Even before the attacks of fall 2001, other problems, such as the detection of the West Nile Virus in the United States and concerns that the emergence of this infectious agent was the consequence of a deliberate act, raised novel challenges to the combined interests of public health and criminal investigators. (shrink)

The epidemiologist Bradford Hill famously argued that in epidemiology, specificity of association (roughly, the fact that an environmental or behavioral risk factor is associated with just one or at most a few medical outcomes) is strong evidence of causation. Prominent epidemiologists have dismissed Hill’s claim on the ground that it relies on a dubious `one-cause one effect’ model of disease causation. The paper examines this methodological controversy, and argues that specificity considerations do have a useful role to play in causal (...) inference in epidemiology. More precisely, I argue that specificity considerations help solve a pervasive inferential problem in contemporary epidemiology: the problem of determining whether an exposure-outcome correlation might be due to confounding by a social factor. This examination of specificity has interesting consequences for our understanding of the methodology of epidemiology. It highlights how the methodology of epidemiology relies on local tools designed to address specific inference problems peculiar to the discipline, and shows that observational causal inference in epidemiology can proceed with little prior knowledge of the causal structure of the phenomenon investigated. I also argue that specificity of association cannot (despite claims to the contrary) be entirely explained in terms of Woodward’s well-known concept of “one-to-one” causal specificity. This is because specificity as understood by epidemiologists depends on whether an exposure (or outcome) is associated with a `heterogeneous’ set of variables. This dimension of heterogeneity is not captured in Woodward’s notion, but is crucial for understanding the evidential import of specificity of association. (shrink)

Epidemiology is a core science of public health, focusing on research related to the distribution and determinants of both positive and adverse health states and events and on application of knowledge gained to improve public health. The American College of Epidemiology (ACE) is a professional organization devoted to the professional practice of epidemiology. As part of that commitment, and in response to concerns for more explicit attention to core values and duties of epidemiologists in light of emerging issues and increased (...) scrutiny of epidemiology, the College developed, adopted, and published a set of Ethics Guidelines. The structure of the ACE ethics guidelines is in four parts: (1) a brief statement of core values and duties of epidemiologists, coupled with the virtues important to professional practice; (2) concise statements of key duties and obligations; (3) exposition of the duties and obligations with more applications; and (4) a brief summary and conclusion. The Guidelines have been published on the ACE website and in the official College journal Annals of Epidemiology. The guidelines contain (and maintain) core elements that define the discipline of epidemiology and its fundamental duties, but they are also intended to be dynamic and evolving, responsive to a changing professional and social environment. (shrink)

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Recent approaches to the social epistemology of belief formation have appealed to an epidemiological model, on which the mechanisms explaining how we form beliefs from our society or community along the lines of infectious disease. More specifically, Alvin Goldman (2001) proposes an etiology of (social) belief along the lines of an epistemological epidemiology. On this “contagion model,” beliefs are construed as diseases that infect people via some socio-epistemic community. This paper reconsiders Goldman’s epidemiological approach in terms of epistemic trust. By (...) focusing on beliefs as diseases, Goldman misconstrues and underestimates the central role that epistemic trust plays in their formation (maintenance, revision, etc.). I suggest that we put trust, accordingly, as the center of an epidemiological model of social doxology—epistemic trust, rather than beliefs, is the disease with which one is infected. So, contra Goldman, beliefs themselves aren’t the disease—they are symptoms. Trust, on this approach, can be viewed as a pathology. This point connects Annette Baier’s (1994) work on moral trust—taking a cue from her “pathologies of trust.” The real pathology centered in social doxology is the epistemic trust manifested by those beliefs. Accordingly, I shall explore (and tentatively defend) an epidemiological model for such “pathological” epistemic trust inspired by Baier’s work on moral trust, one which can more adequately account for the infectious epistemic trust at work in social belief formation. (shrink)

This paper primarily argues that Epidemiology is Ecosystem Science. It will not only explore this notion in detail but will also relate it to the argument that Classical Chinese Medicine was/is Ecosystem Science. Ecosystem Science and Ecosystem Science share these characteristics: they do not subscribe to the monogenic conception of disease; they involve multi variables; the model of causality presupposed is multi-factorial as well as non-linear.

In current philosophical discussions on evidence in the medical sciences, epidemiology has been used to exemplify a specific version of evidential pluralism. According to this view, known as the Russo–Williamson Thesis, evidence of both difference-making and mechanisms is produced to make causal claims in the health sciences. In this paper, I present an analysis of data and evidence in epidemiological practice, with a special focus on research on the exposome, and I cast doubt on the extent to which evidential pluralism (...) holds in this case. I start by focusing on the claim that molecular data allows for the production of mechanistic evidence. On the basis of a close look at the ways in which molecular data is used in exposome research, I caution against interpretations in terms of mechanistic evidence. Secondly, I expand my critical remarks on the thesis by addressing the conditions under which data is categorised as evidence in exposome research. I argue that these show that the classification of a dataset as a type of evidence is dependent on the ways in which the data is used. This is in contrast with the approach of evidential pluralism, where evidence is classified in different types on the basis of its intrinsic properties. Finally, I come back to what I consider the core of the thesis and suggest that the epidemiological research analysed in the paper indicates different interpretations of evidential pluralism and its applicability in the health sciences. (shrink)

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. (shrink)

To an increasing extent ethical controversies affect and sometimes obstruct public health work and epidemiological research. In order to improve communication between the concerned parties a model for identification and analysis of ethical conflicts in individual-based research has been worked out in co-operation between epidemiologists and moral philosophers. The model has two dimensions. One dimension specifies relevant ethical principles (as beneficence, non-maleficence, autonomy and justice). The other dimension specifies the groups of persons involved in the conflict under consideration (for example: (...) the study-population, individuals who may benefit from the results, the researchers and their personnel, the community at large). The model has been applied to the problem of legitimacy of case-register research and to problems in psychiatric health services research as well as epidemiological research. (shrink)

This article examines how digital epidemiology and eHealth coalesce into a powerful health surveillance system that fundamentally changes present notions of body and health. In the age of Big Data and Quantified Self, the conceptual and practical distinctions between individual and population body, personal and public health, surveillance and health care are diminishing. Expanding on Armstrong’s concept of “surveillance medicine” to “quantified self medicine” and drawing on my own research on the symbolic power of statistical constructs in medical encounters, this (...) article explores the impact of digital health surveillance on people’s perceptions, actions and subjectivities. It discusses the epistemic confusions and paradoxes produced by a health care system that increasingly treats patients as risk profiles and prompts them to do the same, namely to perceive and manage themselves as a bundle of health and security risks. Since these risks are necessarily constructed in reference to epidemiological data that postulate a statistical gaze, they also construct or make-up disembodied “individuals on alert”. (shrink)

Epidemiology relies upon a broad interpretation of determinism. This paper discusses analogies with the evolution of the concept of cause in physics, and analyzes the classical nine criteria proposed by Sir Austin Bradford Hill for causal assessment. Such criteria fall into the categories of enumerative induction, eliminative induction, deduction and analogy. All of these four categories are necessary for causal assessment and there is no natural hierarchy among them, although a deductive analysis of the study design is preliminary to any (...) assessment. (shrink)

Clinical research must be understood to be the foundation of scientific medicine of the clinical type. But the essence of scientific clinical medicine remains a matter of profound confusion, even in clinical academia, and so does the essence of clinical research. The confusion now revolves, principally, around ‘clinical epidemiology’. We address clinical research in the meaning of quintessentially ‘applied’ clinical research, which we take to be the foundation of the scientific knowledge base of clinical medicine, of gnosis (dia‐, etio‐, pro‐) (...) in it. More specifically, we address the essence, priorities, and status quo of this research – and argue that the requisite theory of this is not a matter of ‘clinical epidemiology’ but of theory of clinical research endogenous to clinical (rather than epidemiological) academia. (shrink)

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)

Ethical challenges in genomic epidemiology are the direct result of novel tools used to confront scientific challenges in the field. An orders-of-magnitude increase in scale of genetic data collection has created the need for establishing diffuse international partnerships, sometimes across developed- and developing-world countries, with ramifications for assigning research ownership, distributing intellectual property rights, and encouraging capacity-building. Meanwhile, the fact that genomic epidemiological research is so far upstream in the pipeline of therapy development has implications for the privacy rights of (...) research participants and for a rigorous definition of valid informed consent, particularly in resource-poor settings. From these scientific underpinnings, we distill out two main categories of ethical issues: (1) How should researchers ensure that the subjects of research are appropriately protected? and (2) What is the structure of an equitable and fair system for distributing the financial and scientific rewards of research? We attempt to delineate the contours of specific problems in each category and propose steps toward solutions with reference to a particular project, known as gMap.net, that focuses on genomic epidemiological studies of malaria. (shrink)

Background: The purpose of the current study was to assess the prevalence of sleep disturbances among Chinese people during the COVID-19 pandemic in a large national survey, analyze the relationship between sleep disturbances and mental health status, and explore the influencing factors of the relationship between sleep disturbances and mental health status.Methods: An online survey was accessed by 19,740 people throughout China from February 14 to 21, 2020. The survey included the Depression Anxiety Stress Scale-21 to measure psychological distress and (...) two questions about sleep disturbances. Logistic regression analyses and moderation analysis were performed.Results: Among the 14,505 respondents included in analyses, 3,783 reported sleep disturbances at least 3 days during the past week. Sleep disturbances increased the risk of depression, anxiety, and stress. Gender, age, education, occupation, frequency of attending to epidemic information, nervousness about supplies, receiving provisions of living necessities from the service department during the outbreak, number of correct responses to questions about the epidemic, and isolation/quarantine affected the risk of mental health problems among participants experiencing sleep disturbances. A moderation analysis found that sleep problems were more likely to affect depression, anxiety, and stress scores in men than women during the COVID-19 outbreak.Conclusion: During the COVID-19 outbreak, 26.08% people surveyed experienced sleep disturbances, and the presence of sleep disturbances was positively related to depression, anxiety, and stress, especially among front-line anti-epidemic workers, younger people, people living in isolation/quarantine, people with a college or greater education, and males. (shrink)