Epidemiology

Were governments justified in imposing lockdowns to contain the spread of the COVID-19 pandemic? We argue that a convincing answer to this question is to date wanting, by critically analyzing the factual basis of a recent paper, “How Government Leaders Violated Their Epistemic Duties During the SARS-CoV-2 Crisis” (Winsberg et al. 2020). In their paper, Winsberg et al. argue that government leaders did not, at the beginning of the pandemic, meet the epistemic requirements necessitated to impose lockdowns. We focus on (...) Winsberg et al.’s contentions that knowledge about COVID-19 and resultant projections were inadequate; that epidemiologists were biased in their estimates of relevant figures; that there was insufficient evidence supporting the efficacy of lockdowns; and that lockdowns cause more harm than good. We argue that none of these claims are sufficiently supported by evidence, thus impairing their case against lockdowns, and leaving open the question of whether lockdowns were justified. (shrink)

Models may not only represent, but also influence their targets in important ways. While models’ ability to influence outcomes has been studied in relation to economic models, often under the label “performativity”, we argue that this phenomenon also pertains to epidemiological models, such as those used for forecasting the trajectory of the COVID-19 pandemic. After identifying three ways in which a model by the COVID-19 Response Team at Imperial College London (Ferguson et al. 2020) may have influenced scientific advice, policy, (...) and individual responses, we consider the implications of epidemiological models’ performative capacities. We argue, first, that performativity may impair models’ ability to successfully predict the course of an epidemic; and second, that it provides an additional respect in which these models can be successful, namely by changing the course of an epidemic. (shrink)

A large part of contemporary phenomenology of medicine has been devoted to accounts of health and illness, arguing that they contribute to the improvement of healthcare. Less focus has been paid to the issue of prevention of disease and the associated difficulty of adhering to health-promoting behaviours, which is arguably of equal importance. This article offers a phenomenological account of this disease prevention, focusing on how we – as embodied beings – engage with health-promoting behaviours. It specifically considers how we (...) engage with oral hygiene regimes to prevent periodontitis and why we are not good at it. The article suggests that poor adherence to health-promoting behaviours can be explained with reference to the concept of the absent body, as prevention of disease is generally concerned with pre-symptomatic illness experience. The final section contains a discussion of some strategies for the improvement of disease prevention based on this viewpoint. (shrink)

In the ongoing pandemic, death statistics influence people’s feelings and government policy. But when does COVID-19 qualify as the cause of death? As philosophers of medicine interested in conceptual clarification, we address the question by analyzing the World Health Organization’s rules for the certification of death. We show that for COVID-19, WHO rules take into account both facts and values.

Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment – such as a vaccine – given to one individual may affect the infection outcomes of others. Epidemiologists have proposed causal estimands to quantify effects of interventions under contagion using a two-person partnership model. These simple conceptual models have helped researchers develop causal estimands relevant to clinical evaluation of vaccine effects. However, many of these partnership models are formulated under structural assumptions that preclude realistic (...) infectious disease transmission dynamics, limiting their conceptual usefulness in defining and identifying causal treatment effects in empirical intervention trials. In this paper, we propose causal intervention effects in two-person partnerships under arbitrary infectious disease transmission dynamics, and give nonparametric identification results showing how effects can be estimated in empirical trials using time-to-infection or binary outcome data. The key insight is that contagion is a causal phenomenon that induces conditional independencies on infection outcomes that can be exploited for the identification of clinically meaningful causal estimands. These new estimands are compared to existing quantities, and results are illustrated using a realistic simulation of an HIV vaccine trial. (shrink)

Although every emerging infectious disease occurs in a unique context, the behaviour of previous pandemics offers an insight into the medium- and long-term outcomes of the current threat. Where an informative historical analogue exists, epidemiologists and policymakers should consider how the insights of the past can inform current forecasts and responses.

The novel coronavirus disease is regarded as one of the most imminent disease outbreaks which threaten public health on various levels worldwide. Because of the unpredictable outbreak nature and the virus’s pandemic intensity, people are experiencing depression, anxiety, and other strain reactions. The response to prevent and control the new coronavirus pneumonia has reached a crucial point. Therefore, it is essential—for safety and prevention purposes—to promptly predict and forecast the virus outbreak in the course of this troublesome time to have (...) control over its mortality. Recently, deep learning models are playing essential roles in handling time-series data in different applications. This paper presents a comparative study of two deep learning methods to forecast the confirmed cases and death cases of COVID-19. Long short-term memory and gated recurrent unit have been applied on time-series data in three countries: Egypt, Saudi Arabia, and Kuwait, from 1/5/2020 to 6/12/2020. The results show that LSTM has achieved the best performance in confirmed cases in the three countries, and GRU has achieved the best performance in death cases in Egypt and Kuwait. (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)

We investigate the effects of self-protection awareness on the spread of disease from the aspect of resource allocation behavior in populations. To this end, a resource-based epidemiological model and a self-awareness-based resource allocation model in complex networks are proposed, respectively. First of all, we study the coupled disease-awareness dynamics in complex networks with fixed degree heterogeneity. Through extensive Monte Carlo simulations, we find that overall the self-awareness inhibits the spread of disease. More importantly, the influence of the self-awareness on the (...) spreading dynamics can be divided into three phases. In phase I, the self-awareness is relatively small and the outbreak of the epidemic can not be suppressed effectively. While, in phase II, the epidemic size is significantly reduced. Finally, in phase III, there is a sufficiently large value of self-awareness, the disease cannot outbreak anymore. Further, we study the impact of degree heterogeneity on the coupled disease-awareness dynamics and find that the network heterogeneity plays the role of “double-edged sword” in that it can either suppress or promote the epidemic spreading. Specifically, when the basic infection rate is relatively small, it promotes the spread of disease under the condition that there is a relatively small self-awareness. While, when the basic infection rate is relatively large, it inhibits the outbreak of epidemic at a relatively small self-awareness; in turn, it promotes the outbreak of epidemic at a relatively large self-awareness. (shrink)

The Global Burden of Disease Study is one of the largest-scale research collaborations in global health, producing critical data for researchers, policy-makers, and health workers about more than 350 diseases, injuries, and risk factors. Such an undertaking is, of course, extremely complex from an empirical perspective. But it also raises complex ethical and philosophical questions. In this volume, a group of leading philosophers, economists, epidemiologists, and policy scholars identify and discuss these philosophical questions. 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 help us to improve global health. (shrink)

In recent decades, social and behavioral scientists have begun to explore how and why human beings thrive or flourish and to consider whether traits indicative of thriving or flourishing may themselves influence physical well-being. This stands in contrast to the historical tendency in these fields to focus on pathology: mental illness, psychological dysfunction, deviant behavior, social problems, and so on. In epidemiology, too, the influence of pathology is seen in a tacit emphasis on risk factors for disease outcomes and for (...) rates of morbidity and mortality, as opposed to, say, protective factors promotive of good health. Methodologically, there is nothing substantial that would prohibit looking at the world... (shrink)

This chapter suggests that descriptive epidemiological studies like the Global Burden of Disease Study can usefully be divided into four tasks: describing individuals’ health states over time, assessing their health states under a range of counterfactual scenarios, summarizing the information collected, and then packaging it for presentation. The authors show that each of these tasks raises important and challenging ethical questions. They comment on some of the philosophical issues involved in measuring health states, attributing causes to health outcomes, choosing the (...) counterfactual against which to assess causes, aggregating and summarizing complex information across multiple domains, discounting, age-weighting, handling fetal deaths, measuring health inequalities, representing uncertainty, and assessing personal responsibility for health outcomes. (shrink)

In the present study we analyze if the risk concept of the hegemonic epidemiologychanges its nature in purportedly alternative currents as ecoepidemiology and socialepidemiology focused in multilevel analysis.We analyze the way this concept is distinguishedin every current and its relationship with other epidemiologic key notions as cause. We findthat the risk concept and the notion of cause remain relatively unchanged among the differentcurrents even when there is some theoretical discussion about the complexity of multilevelsystems and other explanations for the events. (...) Finally we discuss some consequences aboutthe appropriation of the risk concept in multiple interventions in the health field. We indicatethat the fragmented nature of the risk concept is problematic because it can make thesocial aspects of the disease considered only in a functional perspective. Alternatively to thatwe develop the vulnerability concept as a knowledge framed in a hermeneutical perspective.The vulnerability concept acts as a mediator knowledge between epidemiology and theinterventions in the health field. In the same way we point out some concerns from the anthropologicalfield about the simplification of social senses and omission of meanings aboutthe health of the communities. (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)

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 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 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)

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)

Problem setting. Studying the factors that determine health shows that medicine is important along with biogenetic and environmental factors. However, the leading factors of health in modern conditions are the level and quality of life of people, the level of their health culture and lifestyle. This increases the role of researches on social and cultural conditions and determinants of health in the framework of not only medical sciences, but also the sociology of medicine, health and disease, wellness studies. Recent research (...) and publications analysis. Development of the sociology of medicine and health has received significant support after the report of the Minister of Health of Canada M. Lalonde, “A new perspective on the health of Canadians”, in which new strategies of forming a culture of public health and improving the quality of life and people’s well-being were proposed. Sociological analysis of the problems of health and the development of healthcare has been significantly developed in the works of such researchers in Western Europe and North America, as R. Dubo, Т. MacKeown, V. Navarro, I. Illich, E. Friedson, I. Zola, S. Szreter, A. Williams, R. Stevens, K. Winter, A. Titmonas, N. Gail, C. Lafontaine, E. Annandale, D. Mechanic, G. Weiss, K. White, S. Blum, D. Black, H. Freeman, S. Levine, F. Wolinsky, J. Gable, M. Elston, N. Hart, J. Travis and others. Such Russian and Ukrainian scientists have contributed to the development of the sociology of medicine and health, as V. Lupandin, A. Izutkin, A. Sahno, J. Lisicin, N. Vinogradov, V. Dil’man, I. Brehman, G. Caregorodcev, V. Dimov, V. Kochenov, I. Zhuravleva, N. Grigor’eva, K. Habibulin, A. Reshetnikov, E. Dmitrieva, N. Antonova, G. Apanasenko, V. Petlenko, L. Sushhenko, I. Gorbas’, G. Slabkij, V. Moskalenko, T. Gruzeva, O. Cimbrovskij, N. Panina, Y. Golovaha, O. Balakireva, N. Ringach, R. Levin, I. Venirchuk, N. Soboleva, G. Chepurko and others. Paper objective. Consideration of the main problems of modern sociology of health and healthcare as the objects of sociological research. Paper main body. Problem field of the sociology of health and medicine has a wide range of different aspects of the study of values, knowledge, ideas, norms, as well as indicators, conditions and factors of health, its pathologies at the individual, group, national and global levels. Sociology studies the development of healthcare system and medical services from an institutional point of view, considering it as a modern complex institutional phenomenon. An important aspect of sociological analysis of this institution are the manifestations of socio-economic, territorial, gender, ethnic inequality in access to medical care, health improvement and health culture. The manifestations of subnational and global gaps in access to medical care and health improvement are considered by experts as the most acute problems of modern health care. Sociological approach involves understanding the inter-institutional relations of the development of medical and healthcare through the study of their economic, political, legal, cultural, vocational, scientific, technical, information and communicative manifestations. In Ukraine, the sociology of medicine and health shows achievements in the empirical field of research and is progressively developing within the framework of academic science and universities in the medical and sports fields. Actual problems of sociological analysis of the state of health and its preservation are studies of causes of high morbidity and mortality, low birth rates, gender analysis of health and causes of morbidity, issues of the quality and accessibility of medical services, the effectiveness of health care reform, prospects for the development of insurance medicine in Ukraine, ways to increase public health culture. Conclusions of the research. Modern sociology makes an important contribution to health management as a comprehensive area of modern science about problems of public and individual health, institutional foundations of healthcare, trends and prospects for the transformation of medicine and health culture in the context of globalization and internetization of society and implementation of sustainable development strategies. The development of sociology of medicine and health is an important element in the scientific, informational and analytical support of effective policies in the field of maintaining health, improving the welfare of society and people’s happiness. (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)

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)

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 current mental health care psychiatric conditions are defined as compilations of symptoms. These symptom-based disease categories have been severely criticised as contingent and boundless, facilitating the rise to epidemic proportions of such conditions as depression. In this article we look beyond symptoms and stress the role of epidemiology in explaining the current situation. By analysing the parallel development of cardiovascular disease and depression management in Finland, we argue, firstly, that current mental health care shares with the medicine of chronic (...) somatic conditions an attachment to risk factor epidemiology, which accentuates risk and prevention in disease management. However, secondly, due to the symptom-based definitions of psychiatric conditions, depression management cannot differentiate properly between symptoms, signs and risk factors such as, for example, cardiovascular medicine, but treats symptoms as signs or risk factors in contexts of treatment and prevention. Consequently, minor at-risk conditions have become difficult to separate from proper cases of depression. (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)

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)

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)

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 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)

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)

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)

It is widely accepted that the way information transfers across networks depends importantly on the structure of the network. Here, we show that the mechanism of information transfer is crucial: in many respects the effect of the specific transfer mechanism swamps network effects. Results are demonstrated in terms of three different types of transfer mechanism: germs, genes, and memes. With an emphasis on the specific case of transfer between sub-networks, we explore both the dynamics of each of these across networks (...) and a measure of their comparative fitness. Germ and meme transfer exhibit very different dynamics across linked networks. For germs, measured in terms of time to total infection, network type rather than degree of linkage between sub-networks is the primary factor. For memes or belief transfer, measured in terms of time to consensus, it is the opposite: degree of linkage trumps network type in importance. The dynamics of genetic information transfer is unlike either germs or memes. Transfer of genetic information is robust across network differences to which both germs and memes prove sensitive. We also consider function: how well germ, gene, and meme transfer mechanisms can meet their respective objectives of infecting the population, mixing and transferring genetic information, and spreading a message. A shared formal measure of fitness is introduced for purposes of comparison, again with an emphasis on linked sub-networks. Meme transfer proves superior to transfer by genetic reproduction on that measure, with both memes and genes superior to infection dynamics across all networks types. What kinds of network structure optimize fitness also differ among the three. Both germs and genes show fairly stable fitness with added links between sub-networks, but genes show greater sensitivity to the structure of sub-networks at issue. Belief transfer, in contrast to the other two, shows a clear decline in fitness with increasingly connected networks. When it comes to understanding how information moves on networks, our results indicate that questions of information dynamics on networks cannot be answered in terms of networks alone. A primary role is played by the specific mechanism of information transfer at issue. We must first ask about how a particular type of information moves. (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)

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)

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)

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)

Beyond belief change and meme adoption, both genetics and infection have been spoken of in terms of information transfer. What we examine here, concentrating on the specific case of transfer between sub-networks, are the differences in network dynamics in these cases: the different network dynamics of germs, genes, and memes. Germs and memes, it turns out, exhibit a very different dynamics across networks. For infection, measured in terms of time to total infection, it is network type rather than degree of (...) linkage between sub-networks that is of primary importance. For belief transfer, measured in terms of time to consensus, it is degree of linkage rather than network type that is crucial. Genes model each of these other dynamics in part, but match neither in full. For genetics, like belief transfer and unlike infection, network type makes little difference. Like infection and unlike belief, on the other hand, the dynamics of genetic information transfer within single and between linked networks are much the same. In ways both surprising and intriguing, transfer of genetic information seems to be robust across network differences crucial for the other two. (shrink)

In this paper we make a simple theoretical point using a practical issue as an example. The simple theoretical point is that robustness is not 'all or nothing': in asking whether a system is robust one has to ask 'robust with respect to what property?' and 'robust over what set of changes in the system?' The practical issue used to illustrate the point is an examination of degrees of linkage between sub-networks and a pointed contrast in robustness and fragility between (...) the dynamics of (1) contact infection and (2) information transfer or belief change. Time to infection across linked sub-networks, it turns out, is fairly robust with regard to the degree of linkage between them. Time to infection is fragile and sensitive, however, with regard to the type of sub-network involved: total, ring, small world, random, or scale-free. Aspects of robustness and fragility are reversed where it is belief updating with reinforcement rather than infection that is at issue. In information dynamics, the pattern of time to consensus is robust across changes in network type but remarkably fragile with respect to degree of linkage between sub-networks. These results have important implications for public health interventions in realistic social networks, particularly with an eye to ethnic and socio-economic sub-communities, and in social networks with sub-communities changing in structure or linkage. (shrink)

In order to understand the transmission of a disease across a population we will have to understand not only the dynamics of contact infection but the transfer of health-care beliefs and resulting health-care behaviors across that population. This paper is a first step in that direction, focusing on the contrasting role of linkage or isolation between sub-networks in (a) contact infection and (b) belief transfer. Using both analytical tools and agent-based simulations we show that it is the structure of a (...) network that is primary for predicting contact infection—whether the networks or sub-networks at issue are distributed ring networks or total networks (hubs, wheels, small world, random, or scale-free for example). Measured in terms of time to total infection, degree of linkage between sub-networks plays a minor role. The case of belief is importantly different. Using a simplified model of belief reinforcement, and measuring belief transfer in terms of time to community consensus, we show that degree of linkage between sub-networks plays a major role in social communication of beliefs. Here, in contrast to the case of contract infection, network type turns out to be of relatively minor importance. What you believe travels differently. In a final section we show that the pattern of belief transfer exhibits a classic power law regardless of the type of network involved. (shrink)

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)

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)

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)

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)

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)

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)