Epidemiology

Epidemiology is the core discipline underlying health research. Measuring health, identifying causes of ill health, and intervening to improve health are all key tenets of the discipline. Concerned with the “who,” “when,” “why,” and “where” of health, epidemiology is essential in informing clinical decision-making through evidence-based medicine. Traditionally the study of the occurrence and distribution of disease and determinants, epidemiology is a dynamic discipline that is increasingly being applied in differing disciplines, even beyond health. This chapter is designed as a (...) basic introduction to epidemiology, the terminology used, and the principles in epidemiologic practice. Using public health as a framework, this chapter will also give an overview of both the traditional and more contemporary applications of epidemiology. (shrink)

One need only look in any newspaper and observe the flourishing market in promises of good health through diets or ways of inhabiting the earth to find evidence that the “configurationist model,” suggested by Charles Rosenberg in 1992 to characterize one archetypal response to explain epidemics in the history of the West, is still very much alive. For Rosenberg, in the long history of attempts to explain epidemic diseases, two fundamental approaches existed and often coexisted in the West: contamination and (...) configuration. While the former, reductionist and monocausal, consisted in the “idea of person-to-person contagion, of the transmission of some morbid material from one individual to another,” the latter implies “a vision of health as a balanced, integrated, and value-imparting relationship between humankind and its environment.” From the eighteenth through the mid-nineteenth century, configurationist arguments, refined notably in miasma theory, clearly dominated medical and nonmedical thinking in Europe and North America. For the adherents of this theory, epidemic diseases could be caused by a very wide range of environmental factors: topography, air, water, food, miasmas, or garbage. By the end of the nineteenth century, this approach, which focused more on factors from the social environment, like urbanization, working conditions, and poor education, was undermined by germ theory, which directed medical opinion toward contamination in “its modern, laboratory-oriented guise.” However, as Rosenberg states, “an interest in environmental determinants of health and disease remained alive and in continued dialogue with the new bacteriological etiology.” The contributions in this volume dealing with views on health, the natural environment, and disease in nineteenth- and twentieth-century Europe confirm this last statement. We argue that, in present times, the notion of “exposome,” coined by Christopher Paul Wild and defined as a person’s global exposure to the environmental factors potentially altering health and leading to our modern epidemics of chronic diseases, relates to this long history of Western medical thinking that focuses on the role of the environment to account for health and disease. Taking this long run of history into account, this books addresses the issue of how humankind has observed, imagined, and conceptualized the links between the environment and health in a broad geographical framework. (shrink)

Epidemiology is an essential tool of public health, which largely relies on collection, collation, analysis and interpretation of data and actions based on the information gleaned from the data. Such data-intensive processes lead to unique ethical issues relating to autonomy of the data generator, privacy, confidentiality and justice. In this chapter, we attempt to describe the ethical issues in data handling in epidemiology using two examples, public health surveillance and Big Data analytics in digital epidemiology. One of the unique ethical (...) issues that arises in public health surveillance is the difficulty in operationalizing autonomy, as any individual refusing to share surveillance data will compromise the effectiveness of the surveillance. The need to balance the benefits of health security with the risks of infringement into individual privacy and confidentiality lies as the undercurrent of the ethics of public health surveillance. Big Data analytics is becoming increasingly popular in public health. The rich variety of the data, while offering chances of multilevel, multivariate analysis of disease models, also raises concern of biases in data collection due to huge variations in the sources of the data. The high velocity of the data also throws open opportunities for rapid analysis and interventions to improve population health. The power of Big Data analytics needs to be harnessed with the important ethical principles of public health in mind. (shrink)

In this paper, I argue that visualization and the use of figures represent genuine heuristic, knowledge-enhancing tools in scientific inquiry; in fact, visualization shows a distinctive ability in producing genuinely new knowledge by filling theoretical gaps and in solving problems. I show, then, how visualization can be rightfully appraised as a plausible model for the growth of knowledge, gaining a paramount importance when used at the frontier of research. Unrelated here to the notion of intuition, visualization is treated as an (...) ampliative inference and, being obviously related to figures and vision it is also a way of representing knowledge: this double function justifies it as a non-trivial heuristic device, not replaceable by axiomatic-deductive reasoning. A case study is proposed, regarding the London cholera epidemic, spread between August and September 1854. I show how the recourse to dot maps and a “primitive” version of network Voronoi diagrams as instruments of inquiry helped in filling the then existing theoretical gaps consisting in the ignorance of the existence and action of bacteria in disease transmission. Visualization, on the one hand, acted as an effective problem-solving activity, as it permitted the formulation of a successful strategy to stop the spreading of the epidemic; on the other, through the identification of new causes responsible for the spreading of the epidemic, it allowed to surpass the critical theoretical gap at the frontier of epidemiological knowledge. (shrink)

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

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)

In political philosophy and in economics, unfair inequality is usually assessed between individuals, nowadays often on luck-egalitarian grounds. You have more than I do and that's unfair. By contrast, in epidemiology and sociology, unfair inequality is traditionally assessed between groups. More is concentrated among people of your class or race than among people of mine, and that's unfair. I shall call this difference the egalitarian ‘divorce’. Epidemiologists, and their ‘divorce lawyers’ Paula Braveman, Norman Daniels, and Iris Marion Young, explain that (...) not every inequality between individuals is an inequity. Only inequality between social status groups is unfair. Only such inequality stems from problems like partiality, discrimination, oppression, inequality-related population health problems, and unfair distribution of prospects. And it alone is actionable. By contrast, inequality between individuals, e.g. in longevity, is natural, inevitable, less important, or otherwise less informative — not unjust. In ‘divorce trial’ mode, I respond to epidemiologists that group inequalities lack the intrinsic disvalue that they ascribe them. They may be instrumentally or contingently bad or wrong, not essentially so. I then shift to ‘remarriage’: although group inequalities lack intrinsic badness or wrongness, for multiple reasons they remain useful to measure. (shrink)

This paper poses the question of whether people have a duty to participate in digital epidemiology. While an implied duty to participate has been argued for in relation to biomedical research in general, digital epidemiology involves processing of non-medical, granular and proprietary data types that pose different risks to participants. We first describe traditional justifications for epidemiology that imply a duty to participate for the general public, which take account of the immediacy and plausibility of threats, and the identifiability of (...) data. We then consider how these justifications translate to digital epidemiology, understood as an evolution of traditional epidemiology that includes personal and proprietary digital data alongside formal medical datasets. We consider the risks imposed by re-purposing such data for digital epidemiology and propose eight justificatory conditions that should be met in justifying a duty to participate for specific digital epidemiological studies. The conditions are then applied to three hypothetical cases involving usage of social media data for epidemiological purposes. We conclude with a list of questions to be considered in public negotiations of digital epidemiology, including the application of a duty to participate to third-party data controllers, and the important distinction between moral and legal obligations to participate in research. (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)

This paper considers an important recent contribution by Miguel Hernán to the ongoing debate about causal inference in epidemiology. Hernán rejects the idea that there is an in-principle epistemic distinction between the results of randomized controlled trials and observational studies: both produce associations which we may be more or less confident interpreting as causal. However, Hernán maintains that trials have a semantic advantage. Observational studies that seek to estimate causal effect risk issuing meaningless statements instead. The POA proposes a solution (...) to this problem: improved restrictions on the meaningful use of causal language, in particular “causal effect”. This paper argues that new restrictions in fact fail their own standards of meaningfulness. The paper portrays the desire for a restrictive definition of causal language as positivistic, and argues that contemporary epidemiology should be more realistic in its approach to causation. In a realist context, restrictions on meaningfulness based on precision of definition are neither helpful nor necessary. Hernán’s favoured approach to causal language is saved from meaninglessness, along with the approaches he rejects. (shrink)

In this essay, I argue that Ted Poston's theory of explanatory coherentism is well-suited as a tool for causal explanation in the health sciences, particularly in epidemiology. Coherence has not only played a role in epidemiology for more than half a century as one of Hill's viewpoints, it can also provide background theory for the development of explanatory systems by integrating epidemiologic evidence with a diversity of other error-independent data. I propose that computational formalization of Hill's viewpoints in an explanatory (...) coherentist framework would provide an excellent starting point for a formal epistemological (knowledge-theoretical) project designed to improve causal explanation in the health sciences. As an example, I briefly introduce Paul Thagard's ECHO system and offer my responses to possible objections to my proposal. (shrink)

The impending implementation of pre-exposure prophylaxis has prompted complicated bioethical and public health ethics concerns regarding the moral distribution of antiretroviral medications to ostensibly healthy populations as a form of HIV prevention when millions of HIV-positive people still lack access to ARVs globally. This manuscript argues that these questions are, in part, concerns over the ethics of the knowledge production practices of epidemiology. Questions of distribution, and their attendant cost-benefit calculations, will rely on a number of presupposed, and therefore, normatively (...) cultural assumptions within the science of epidemiology specifically regarding the ability of epidemiologic surveillance to produce accurate maps of HIV throughout national populations. Specifically, ethical questions around PrEP will focus on who should receive ARVs given the fact that global demand will far exceed supply. Given that sexual transmission is one of the main modes of HIV transmission, these questions of ‘who’ are inextricably linked to knowledge about sexual personhood. As a result, the ethics of epidemiology, and how the epidemiology of HIV in particular conceives, classifies and constructs sexual populations will become a critical point of reflection and contestation for bioethicists, health activists, physicians, nurses, and researchers in the multi-disciplinary field of global health. This paper examines how cultural conundrums within the fields of bioethics and public health ethics are directly implicated within the ethics of PrEP, by analyzing the problems of population inaugurated by the construction of the men who have sex with men epidemiologic category in the specific national context of South Africa. (shrink)

In this issue of the Journal, Dundas et al. (Am J Epidemiol. 2014;180(2):197–207) apply a hitherto infrequent multilevel analytical approach: multiple membership multiple classification (MMMC) models. Specifically, by adopting a life-course approach, they use a multilevel regression with individuals cross-classified in different contexts (i.e., families, early schools, and neighborhoods) to investigate self-reported health and mental health in adulthood. They provide observational evidence suggesting the relevance of the early family environment for launching public health interventions in childhood in order to improve (...) health in adulthood. In their analyses, the authors distinguish between specific contextual measures (i.e., the association between particular contextual characteristics and individual health) and general contextual measures (i.e., the share of the total interindividual heterogeneity in health that appears at each level). By doing so, they implicitly question the traditional probabilistic risk factor epidemiology including classical “neighborhood effects” studies. In fact, those studies use simple hierarchical structures and disregard the analysis of general contextual measures. The innovative MMMC approach properly responds to the call for a multilevel eco-epidemiology against a widespread probabilistic risk factors epidemiology. The risk factors epidemiology is not only reduced to individual-level analyses, but it also embraces many current “multilevel analyses” that are exclusively focused on analyzing contextual risk factors. (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)

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)

Despite its phenomenal success since its inception in the early nineteen-nineties, the evidence-based medicine movement has not succeeded in shaking off an epistemological critique derived from the experiential or tacit dimensions of clinical reasoning about particular individuals. This critique claims that the evidence-based medicine model does not take account of tacit knowing as developed by the philosopher Michael Polanyi. However, the epistemology of evidence-based medicine is premised on the elimination of the tacit dimension from clinical judgment. This is demonstrated through (...) analyzing the dichotomy between clinical and statistical intuition in evidence-based medicine’s epistemology of clinical reasoning. I argue that clinical epidemiology presents a more nuanced epistemological model for the application of statistical epidemiology to the clinical context. Polanyi’s theory of tacit knowing is compatible with the model of clinical reasoning associated with clinical epidemiology, but not evidence-based medicine. (shrink)

The general goal is to encourage informal logicians and those interested in applied epistemology to look at epidemiology as a paradigmatic science crucially dependant on argumentation to justify its claims. Three specific goals are: 1. exemplify applied epistemology by looking critically at causal argumentation in epidemiology, 2. show that justification of causal claims in epidemiology is a form of “argument to the best explanation,” 3. show that there could be a symbiotic relationship between epidemiology and work in various applied reasoning (...) disciplines such as argumentation and “applied epistemology.”. (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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My conviction is that the matters addressed in this volume are of transcendental importance if we are to face up to the challenges of the 1990s and beyond. How, for instance, are we to cope with a truly ecological approach to public health and all its concomitant changes of risk groups worldwide unless there is a full appre ciation of the popUlation perspective throughout the health establishment? The global village has achieved a measure of interdependence requiring recognition by all concerned (...) with the health of both individuals and communities that there is an urgent need to share our knowledge and deploy our resources in the best interests of people everywhere. The history of public health initiatives, the origins of epidemiology, and the tragic separation-virtually a divorce--of public health from medicine recounted in the chapters that follow argue strongly for an early rapprochement. Health professionals who complement each other's knowledge and skills can be reunited through their common reliance on epidemiology as a major fundamental science for the entire health enterprise. Henceforth, epidemiology should be ranked in importance with cellular and molecular biology, immunology, and the social and systems sciences; all are essential if we are to cope with the vast array of diseases and disorders that face us in both the developed and developing worlds. We need more first-rate laboratory scientists, clinicians, nurses, aides, village health work ers, and managers committed to serving the public. (shrink)

Background: Both the Council for International Organization of Medical Sciences and the Helsinki Declaration emphasize that the potential benefits of research should outweigh potential harms; consequently, some work has been conducted on participants' perception of benefits in therapeutic research. However, there appears to be very little work conducted with participants who have joined non-therapeutic research. This work was done to evaluate participants' perception of benefits in a genetic epidemiological study by examining their perception of the potential benefits of enrollment.Methods: In-depth (...) interviews lasting between 45 and 60 minutes were conducted with a convenient sample of 25 ill patients and 25 healthy accompanying relatives enrolled in a genetic epidemiological study of tuberculosis. Recorded interviews were transcribed and analyzed using content analysis.Results: Participants perceived that research was beneficial and some of the benefits included the generation of new knowledge, finding the cause of diseases, as well as the control, eradication and prevention of disease. Some thought that research was risky whilst others thought that the benefits outweighed the risks.Conclusion: Participants perceived research to be beneficial and most of them thought that, though it was risky, the benefits outweighed the risks. It is our view that researchers need to give serious consideration to participant's perception of benefits in designing their consent forms, to see to the fulfillment of achievable goals. (shrink)

ArgumentSince the 1970s, Danish population registries were increasingly used for research purposes, in particular in the health sciences. Linked with a large number of disease registries, these data infrastructures became laboratories for the development of both information technology and epidemiological studies. Denmark's system of population registries had been centralized in 1924 and was further automated in the 1960s, with individual identification numbers introduced in 1968. The ubiquitous presence of CPR-numbers in administrative routines and everyday lives created a continually growing data (...) archive of the entire population. The resulting national-level database made possible unprecedented record linkage, a feature epidemiologists and biomedical scientists used as a resource for population health research. The specific assemblages that emerged with their practices of data mining were constitutive of registry-based epidemiology as a style of thought and of a distinct relationship between science, citizens, and the state that emerged as “Scandinavian.”. (shrink)

Application of evolutionary principles to epidemiological problems indicates that cultural characteristics influence the evolution of parasite virulence by influencing the success of disease transmission from immobilized, infected hosts. This hypothesis is supported by positive correlations between virulence and transmission by biological vectors, water, and institutional attendants. The general evolutionary argument is then applied to the causes and consequences of increased virulence for three diseases: cholera, influenza and AIDS.

We study the SIS and SIRI epidemic models discussing different approaches to compute the thresholds that determine the appearance of an epidemic disease. The stochastic SIS model is a well known mathematical model, studied in several contexts. Here, we present recursively derivations of the dynamic equations for all the moments and we derive the stationary states of the state variables using the moment closure method. We observe that the steady states give a good approximation of the quasi-stationary states of the (...) SIS model. We present the relation between the SIS stochastic model and the contact process introducing creation and annihilation operators. For the spatial stochastic epidemic reinfection model SIRI, where susceptibles S can become infected I, then recover and remain only partial immune against reinfection R, we present the phase transition lines using the mean field and the pair approximation for the moments. We use a scaling argument that allow us to determine analytically an explicit formula for the phase transition lines in pair approximation. (shrink)

The Global Burden of Disease Study (GBD) is one of the largest-scale research collaborations in global health, distilling a wide range of health information to provide estimates and projections for more than 350 diseases, injuries, and risk factors in 195 countries. Its results are a critical tool informing researchers, policy-makers, and others working to promote health around the globe. A study like the GBD is, of course, extremely complex from an empirical perspective. But it also raises a large number of (...) complex ethical and philosophical questions that have been explored in a series of collaborations over the past twenty years among epidemiologists, philosophers, economists, and policy scholars. The essays in this volume address issues of current and urgent concern to the GBD and other epidemiological studies, including rival understandings of causation, the aggregation of complex health data, temporal discounting, age-weighting, and the valuation of health states. The volume concludes with a set of chapters discussing how epidemiological data should and should not be used. Better appreciating the philosophical dimensions of a study like the GBD can make possible a more sophisticated interpretation of its results, and it can improve epidemiological studies in the future, so that they are better suited to produce results that can help us to improve global health. (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)

Chagas disease or American trypanosomiasis is an important health problem in Latin America. Due to the mobility of Latin American population around the world, countries without vector presence started to report disease cases. We developed a deterministic compartmental model in order to gain insights into the disease dynamics in a scenario without vector presence, considering congenital transmission and transmission by blood transfusion. The model was used to evaluate the epidemiological effect of control measures. It was applied to demographic data from (...) Spain and sensitivity analysis was performed on model parameters associated with control strategies. (shrink)

In this paper, I aim to identify the different cognitive, contextual and social values involved in epidemiological research on Chagas disease. As it is considered as a ‘neglected tropical disease’ by the World Health Organization, I will try to unfold the many senses of ‘neglected’ and in which sense different non-cognitive values can be manifested in research on this disease through a pluralism of disciplines and methods. The point of departure of this investigation is a model that explains the dynamics (...) of scientific activity. The model is the one developed by Hugh Lacey, based on the notion of strategies of research, in which scientific research has to be socially framed. I will try to show that the social, political and economic conditions of certain populations, which define their ‘neglected’ character, constitute a perspective that needs to be considered in epidemiological research. Finally, this perspective is defined in the moment of adoption of strategies of research that reflects the social and ethical values adopted by scientists in Chagas disease investigations. (shrink)

Since the second half of the twentieth century, biomedical research has made increasing use of epidemiological methods to establish empirical evidence on a population level. This paper is about practices with data in epidemiological research, based on a case study in Denmark. I propose an epistemology of record linkage that invites exploration of epidemiological studies as heterogeneous assemblages. Focusing on data collecting, sampling and linkage, I examine how data organisation and processing become productive beyond the context of their collection. The (...) case study looks at how a local population database established in 1976 to investigate possibilities for the prevention of cardiovascular disease is used thirty years later to test hypotheses on the aetiology of breast cancer. For two breast cancer investigations based on the same core data set, I follow the underlying record linkage practice and describe how research objects such as molecular markers become relevant with respect to public health through information networking. Epidemiological association studies function as tools that performatively enrol different contexts into statistical risk estimation, thereby configuring options for research as well as for clinical testing and public health policy. (shrink)

Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining (...) whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population. (shrink)

Christopher Boorse's biostatistical 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)

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)

Medical theory and practice in the second half of the 20th century were transformed by the idea of risk, and, in particular, by the concept of the "risk factor." Many historians have described how the concept of the risk factor emerged in the actuarial science of the life insurance industry in the early 20th century and entered medicine through the Framingham Heart Study, specifically with its July 1961 article, "Factors of Risk in the Development of Coronary Heart Disease," in the (...) Annals of Internal Medicine. This story, while plausible, is incorrect.New techniques of digital history enable a new kind of research: full-text searching of publications in medicine, public health, and other... (shrink)

The episodes of cowpox inoculation (1798) and rabies preventive treatment (1885) are celebrated as the landmark of modern medicine. Paradoxically, these two advances have been accomplished without any theoretical breakthrough in the understanding of immunity. Going further, they were made possible by a long past of empirical procedures among which smallpox inoculation played an outstanding role. The paper explores the paradox of 'Immunization without Immunology' and Pasteur's reconstruction of the past, through his successful use of a metaphor. 'Vaccine', originally linked (...) to the jennerian method, was meant by Pasteur to designate a general program of virus attenuation. The paper investigates the scientific factors accounting for why viruses played such a leading role in immunization. The longlasting immunity, the easy transmission from man to man characteristic of smallpox allowing in vivo experimentation, may explain how crude procedures of early immunizers shaped scientific ideologies and strategies of public health and family initiated modern 'vaccinology'. (shrink)