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)

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 meaning does epidemiological evidence have for the individual? In evidence-based medicine, epidemiological evidence measures the patient’s risk of the outcome or the change in risk due to an intervention. The patient’s risk is commonly understood as an individual probability. The problem of understanding epidemiological evidence and risk thus becomes the challenge of interpreting individual patient probabilities. I argue that the patient’s risk is interpreted ontically, as a propensity. After exploring formidable problems with this interpretation in the medical context, I (...) propose an epistemic reinterpretation of individual patient probabilities as credences. On this view, epidemiological evidence informs medical uncertainty. (shrink)

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)

Epidemiological models have played a central role in the COVID-19 pandemic, particularly when urgent decisions were required and available evidence was sparse. They have been used to predict the evolution of the disease and to inform policy-making. In this paper, we address two kinds of epidemiological models widely used in the pandemic, namely, compartmental models and agent-based models. After describing their essentials—some real examples are invoked—we discuss their main strengths and weaknesses. Then, on the basis of this analysis, we make (...) a comparison between their respective merits concerning three different goals: prediction, explanation, and intervention. We argue that there are general considerations which could favour any of those sorts of models for obtaining the aforementioned goals. We conclude, however, that preference for particular models must be grounded case-by-case since additional contextual factors, as the peculiarities of the target population and the aims and expectations of policy-makers, cannot be overlooked. (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 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 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)

Epidemiological studies usually do not pose high risk to participants. At the same time they provide valuable knowledge and improve public and individual health. In many countries, studies involving human subjects are subject to ethics review. Research shows that the process of obtaining ethical approval from institutional research boards or research ethics committees is sometimes costly, time-consuming and seriously delays important research projects. In this article we consider arguments against and in favor of ethics review of epidemiological studies. On the (...) one hand, it seems that minimal risk epidemiological studies should not be a subject to ethics review, since any delay of an important study has its death toll and health costs. In this perspective, the calculus of costs and benefits supports rejecting the whole existing approach. Nevertheless, we argue that institutional research boards or ethics research committees protect research participants from wrongs and up till now are the best tools of social and political control over the research enterprise. (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)

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)

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)

In a scenario characterized by unpredictable developments, such as the recent COVID-19 pandemic, epidemiological models have played a leading part, having been especially widely deployed for forecasting purposes. In this paper, two real-world examples of modeling are examined in support of the proposition that science can convey inconsistent as well as genuinely perspectival representations of the world. Reciprocally inconsistent outcomes are grounded on incompatible assumptions, whereas perspectival outcomes are grounded on compatible assumptions and illuminate different aspects of the same object (...) of interest. In both cases, models should be viewed as expressions of specific assumptions and unconstrained choices on the part of those designing them. The coexistence of a variety of models reflects a primary feature of science, namely its pluralism. It is herein proposed that recent over-exposure to science’s inner workings and disputes such as those pertaining to models, may have led the public to perceive pluralism as a flaw—or more specifically, as disunity or fragmentation, which in turn may have been interpreted as a sign of unreliability. In conclusion, given the inescapability of pluralism, suggestions are offered as to how to counteract distorted perceptions of science, and thereby enhance scientific literacy. (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)

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)

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)

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)

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)

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. (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.

Contemporary infectious disease surveillance systems aim to employ the speed and scope of big data in an attempt to provide global health security. Both shifts - the perception of health problems through the framework of global health security and the corresponding technological approaches – imply epistemological changes, methodological ambivalences as well as manifold societal effects. Bringing current findings from social sciences and public health praxis into a dialogue, this conversation style contribution points out several broader implications of changing disease surveillance. (...) The conversation covers epidemiological issues such as the shift from expert knowledge to algorithmic knowledge, the securitization of global health, and the construction of new kinds of threats. Those developments are detailed and discussed in their impacts for health provision in a broader sense. (shrink)

ArgumentThe paper argues that epidemic surveillance and state-building were closely interconnected in interwar Poland. Starting from the paper technology of weekly epidemiological reporting it discusses how the reporting scheme of Polish epidemics came into being in the context of a typhus epidemic in 1919–20. It then shows how the statistics regarding nation-wide epidemics was put into practice. It is only when we take into account these practices that we can understand the epidemiological order the statistics produced. The preprinted weekly report (...) form registered Jews and Christians separately. Yet, the imagined national epidemiological space that emerged from it hardly took notice of this separation. Rather, the category that differentiated Polish epidemiological space in medical discourse was the capacity of contributing to the state-making practices of epidemic surveillance. This category divided Poland into two regions: a civilized and modern western region and a backward and peripheral eastern region. (shrink)

This article describes contrasting ideas for a set of topics in epidemiological thinking. The premise underlying this contribution to the special edition is that researchers develop their epidemiological thinking over time through interactions with other researchers who have a variety of in-practice commitments, such as to kinds of cases and methods of analysis, and not simply to a philosophical framework for explanation. I encourage discussants from philosophy and epidemiology to draw purposefully from across a range of topics and contrasting (...) positions, and thereby pursue critical thinking in the sense of understanding ideas and practices better when we examine them in relation to alternatives. After an initial topic concerning practices for developing epidemiological literacy, a number of conceptual steps follow—the characterization of the very phenomena we might be concerned with, the scope and challenges of the field of epidemiology, the formulation of categories—before linking associations, predictions, causes and interventions and examining the confounding of purported links. Building on that conceptual basis, the remaining topics consist of issues or angles of analysis related to the complexities of inequalities within and between populations, context, and changes over the life course. The organization of topics derives from a graduate course that I teach that aims for epidemiological literacy, not technical ability in statistical formulas and data analysis, and shares the underlying premise and critical thinking goals of this article. During the topic-by-topic description, some assertions about explanation and intervention emerge, notably, that epidemiological–philosophical discussion about causality often leaves unclear or unexamined whether a modifiable factor shown to have been associated with a difference in the data from past observations should be thought of as factor that, when modified, would generate that difference going forward. The article concludes with a “Limitations of this Study” section that teases out different kinds of description–prescription relationship that are implied in undertaking philosophy of epidemiology and identifies some other considerations that are implied but not emphasized by this article. (shrink)

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)

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)

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)

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 morbidity of tick‐borne encephalitis (TBE) varies yearly by as much as 10‐fold among the people of Western Siberia. This long‐term variation is dependent on many factors such as the density of the tick populations, the prevalence of TBE virus (TBEV) among sub‐adult ticks, the yearly virulence of the TBEV, and prophylactic measures. Here we highlight the role of small mammal hosts in the circulation of TBEV through the ecosystem. Refining classical models of non‐viremic horizontal transmission, we emphasize the recently (...) understood fact that the physiological and immunological status of the small mammal hosts affects the tick and virus‐host interactions. In addition to its theoretical interest, our approach may lead to some practical improvements in the precision of epidemiological forecasts and perhaps in forestalling the severity of outbreaks of TBE, or, at least, in forewarning medical authorities and the general public of impending TBE outbreaks. (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)

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)

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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)

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)

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)

The challenges posed by chronic illness have pointed out to epidemiologists the multifactorial complex nature of disease causality. This notion has been referred to as a web of causality. This web extends theoretically beyond risk markers. It includes determinants of emergence/non-emergence of disease. This web of determinants is a form of complex system. Due to its complexity, the determinants within such system are not linked to each others in a linear, predictable manner only. Predictability is possible only on a short-term (...) basis, and unpredictability sets in over the long run. Understanding such a system of determinants calls for articulation and testing of complex models which synthesize our knowledge of multiple determinants at many scales, both biological and otherwise. Given the complexity of this web and existing knowledge about the nonlinearity of such systems, the following question is posed: Can the challenge of studying causality be adequately addressed if emphasis continues to be placed on using tools and methods that are geared towards looking at such system from a linear paradigm? Or is it time to add to the epidemiologic research agenda the notion of nonlinearity and its relevant form of analytical approaches that are being tested in other disciplines? Furthermore, the question posed here applies as well to the study of determinants of health. Addressing determinants of heath adds further complexity to our task. (shrink)