Epidemiology

A large part of the contemporary phenomenology of medicine has been devoted to accounts of health and illness, arguing that they contribute to the improvement of health care. 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 regimens 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, because 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)

Research in pharmacogenomics and precision medicine has recently introduced the concept of Polygenic Scores (PGSs), namely, indexes that aggregate the effects that many genetic variants are predicted to have on individual disease risk. The popularity of PGSs is increasing rapidly, but surprisingly little attention has been paid to the idealisations they make about phenotypic development. Indeed, PGSs rely on quantitative genetics models and methods, which involve considerable theoretical assumptions that have been questioned on various grounds. This comes with epistemological and (...) ethical concerns about the use of PGSs in clinical decision-making. In this paper, I investigate to what extent idealisations in genetics models can impact the data gathering and clinical interpretation of genomics findings, particularly the calculation and predictive accuracy of PGSs. Although idealisations are considered ineliminable components of scientific models, they may be legitimate or not depending on the epistemic aims of a model. I thus analyse how various idealisations have been introduced in classical models and progressively readapted throughout the history of genetic theorising. Notably, this process involved important changes in the epistemic purpose of such idealisations, which raises the question of whether they are legitimate in the context of contemporary genomics. (shrink)

In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual shifts. First, we discuss the EXPOsOMICS (...) project, an attempt to integrate genomic and environmental data which suggests a reframing of the boundaries between external and internal environments. Second, we explore the MEDMI platform, whose efforts to combine health, environmental and climate data instantiate a reframing and expansion of environmental exposure. Third, we illustrate how extracting epidemiological insights from extensive social data collected by the CIDACS institute yields innovative attributions of causal power to environmental factors. Identifying these shifts highlights the benefits and opportunities of new environmental data, as well as the challenges that such tools bring to understanding and fostering health. It also emphasises the constraints that data selection and accessibility pose to scientific imagination, including how researchers frame key concepts in health-related research. (shrink)

During the Covid-19 pandemic, public policy was not driven by findings from public health research, but by politicians’ desire to pursue their own interests. The media and politicians inflamed mass hysteria and then imposed ill-considered lockdowns to “solve” the problem. Lockdowns not only failed to protect those at risk from the virus, but also caused enormous collateral damage. Public choice theory helps explaining this decision-making. -/- .

Bioethics, Volume 36, Issue 6, Page 687-698, July 2022.

To clarify the proper role of values in science, focusing on controversial expert responses to Covid-19, this article examines the status of (in)convenient hypotheses. Polarizing cases like health experts downplaying mask efficacy to save resources for healthcare workers, or scientists dismissing “accidental lab leak” hypotheses in view of potential xenophobia, plausibly involve modifying evidential standards for (in)convenient claims. Societies could accept that scientists handle (in)convenient claims just like nonscientists, and give experts less political power. Or societies could hold scientists to (...) a higher bar, by expecting them not to modify evidential standards to avoid costs only incidentally tied to error. (shrink)

COVID-19 began in China in December 2019. As of January 2021, over a hundred million instances had been reported worldwide, leaving a deep socio-economic impact globally. Current investigation studies determined that artificial intelligence (AI) can play a key role in reducing the effect of the virus spread. The prediction of COVID-19 incidence in different countries and territories is important because it serves as a guide for governments, healthcare providers, and the general public in developing management strategies to battle the disease. (...) The prediction proved beneficial in the early months of 2020 to alert nations and territories in danger of an outbreak, allowing them to take preventative measures. Despite the fact that the COVID-19 outbreak has expanded to practically every location on the planet, the prediction has value in terms of monitoring the intensity of the spread and recovery, as well as determining the likelihood of a sequel or tertiary epidemic. COVID-19, like influenza, could become a seasonal or recurring epidemic in the future. COVID-19 activity must so be predicted and monitored now and in the future. (shrink)

Public funders of health research have been widely criticized on the grounds that their allocations of funding for disease-specific research do not reflect the relative burdens imposed by different diseases. For example, the US National Institutes of Health spends a much greater fraction of its budget on HIV/AIDS research and a much smaller fraction on migraine research than their relative contribution to the US burden of disease would suggest. Implicit in this criticism is a normative claim: Insofar as the scientific (...) opportunities are equal, each patient merits research into their condition proportional to the burden of disease for which that condition is responsible. This claim—the proportional view—is widely accepted but has never been fully specified or defended. In this paper, I explain what is required to specify the view, attempt to do so in the most charitable way, and then critically evaluate its normative underpinnings. I conclude that a severity-weighted proportional view is defensible. I close by drawing out five key lessons of my analysis for health research priority-setting. (shrink)

Evidence-based medicine is a clinical decision making framework which makes claims about what physicians ought to do. Though heralded as the cutting edge of medical science evidence-based medicine is a value laden normative theory which implicitly depends on substantive views regarding what is morally good or right. In this paper, I provide an ethical analysis of evidence-based medicine. I consider its normative underpinnings in three ethical theories: utilitarianism, Kantian deontology, and virtue ethics. In the face of uncertainty, evidence-based medicine endorses (...) expected utility theory using the best available evidence in order to avoid doing more harm than good. In accordance with the Kantian respect for individuals as ends in themselves, evidence-based medicine calls for integrating the values and preferences of the patient. De-emphasizing intuition, clinical expertise, and pathophysiologic rationale emphasizes the need for the intellectual virtues of curiosity, critical thinking, and courage. Evidence-based medicine is a successful clinical practice that can be morally justified by all three major ethical theories. Although its focus on maximizing good health outcomes and integrating respect for individual patients has been emphasized, the role of the intellectual virtues in evidence- based medicine remains highly under-explored. (shrink)

The ethical question is whether university mask mandates should be relaxed. I argue that the use of face masks by healthy individuals has uncertain benefits, which potential harms may outweigh, and should therefore be voluntary. Systematic reviews by the World Health Organization (WHO) and Cochrane Acute Respiratory Infections concluded that the use of face masks by healthy individuals in the community lacks effectiveness in reducing viral transmission based on moderate-quality evidence. The only two randomized controlled trials of face masks published (...) during the pandemic found little to no benefit. Without high-quality evidence, it is difficult to justify a requirement rather than a recommendation. Notwithstanding, one might argue that the precautionary principle justifies mask mandates. If the precautionary principle can justify implementing mask mandates due to the risk of forgoing possible benefit, then it might also be able to justify not implementing mask mandates due to the risk of potential harm caused by the intervention. It is commonly thought that there is little to lose from the use of face masks, but this is not necessarily true. It is possible that masks have done more harm than good. (shrink)

Lockdowns, or modern quarantines, involve the use of novel restrictive non-pharmaceutical interventions (NPIs) to suppress the transmission of COVID-19. In this paper, I aim to critically analyze the emerging history and philosophy of lockdowns, with an emphasis on the communication of health evidence and risk for informing policy decisions. I draw a distinction between evidence-based and modeling-based decision-making. I argue that using the normative framework of evidence-based medicine would have recommended against the use of lockdowns. I first review the World (...) Health Organization’s evidence-based pandemic preparedness plans for respiratory viruses. I then provide a very brief history of COVID-19 modeling, which was cited as justification for the use of lockdowns in the U.K., the U.S., and much of the world. I focus on the so-called Imperial College model designed by Neil Ferguson et al. as well as the so-called Oxford model designed by José Lourenço et al. I analyze the evidence-based pandemic response known as ‘mitigation’, and I compare it with Ferguson et al.’s experimental strategy known as ‘suppression’. I summarize the strengths and weaknesses of these strategies based on their diametric aims and each model’s parametric assumptions. Based on my critical analysis of the suppression strategy, I attempt to expose what has been called the ‘logic of lockdowns’, which Sunetra Gupta of the Oxford model group has suggested is flawed. Finally, I consider Trisha Greenhalgh’s objection to evidence-based policy based on the precautionary principle, and I attempt to offer a response. I conclude with a brief narrative review of the emerging randomized evidence on restrictive NPIs, which seems to support my claim that mitigation was the strategy that would have been recommended by evidence-based medicine. If this is true, then COVID-19 modeling may serve as an important reminder of the enduring lesson of evidence-based medicine: that one should always ‘Trust the Evidence!’ for better health policy. (shrink)

For children, the collateral damage of the COVID-19 pandemic response has been considerable. In this paper, we use the framework of evidence-based medicine to argue that child abuse is another negative side effect of COVID-19 lockdowns. While it was certain that school closures would have profound social and economic costs, it remains uncertain whether they have any effect on COVID-19 transmission. There is emerging evidence that lockdowns significantly worsened child abuse on a global scale. Low-income and middle-income countries are particularly (...) vulnerable to increases in child abuse. The best available external evidence from systematic research during the pandemic demonstrates an increase in the risk of child maltreatment, an increase in child maltreatment hospitalisations and a concerning decrease in official child maltreatment referrals. The paradoxical phenomenon of increased hospitalisations and decreased reports is unlikely to be explained by a genuine decrease in child abuse. We conclude that lockdowns have an unacceptably high risk of negative side effects for children, as evidenced by child abuse, the true extent of which appears to be masked by lockdown-related disruptions to schools and other surveillance systems. The desire for a sense of security may be a tempting bias towards emphasising the resilience of children, but it is ethically problematic to push children towards abuse in the name of public health. It is our view that the collateral damage of prolonged school closures for society’s most vulnerable members is a powerful ethical consideration against any pandemic response which involves their use. (shrink)

How could the initial, drastic decisions to implement “lockdowns” to control the spread of COVID-19 infections be justifiable, when they were made on the basis of such uncertain evidence? We defend the imposition of lockdowns in some countries by first, and focusing on the UK, looking at the evidence that undergirded the decision, second, arguing that this provided us with sufficient grounds to restrict liberty given the circumstances, and third, defending the use of poorly-empirically-constrained epidemiological models as tools that can (...) legitimately guide public policy. (shrink)

With the limited initial availability of COVID-19 vaccines in the first months of 2021, decision-makers had to determine the order in which different groups were prioritized. Our aim was to find out what normative approaches to the allocation of scarce preventive resources were embedded in the national COVID-19 vaccination schedules. We systematically reviewed and compared prioritization regulations in 27 members of the European Union, the United Kingdom, and Israel. We differentiated between two types of priority categories: groups that have increased (...) infection fatality rate (IFR) compared to the average for the general population and groups chosen because their members experience increased risk of being infected (ROI). Our findings show a clear trend: all researched schedules prioritized criteria referring to IFR (being over 65 years old and coexisting health conditions) over the ROI criteria (eg occupation and housing conditions). This is surprising since, in the context of treatment, it is common and justifiable to adopt different allocation principles (eg introducing a saving more life-year approach or prioritizing younger patients). We discuss how utilitarian, prioritarian, and egalitarian principles can be applied to interpret normative differences between the allocation of curative and preventive interventions. (shrink)

The COVID-19 pandemic has made it especially visible that mortality data are a key component of epidemiological models, being a single indicator that provides information about various health aspects, such as disease prevalence and effectiveness of interventions, and thus enabling predictions on many fronts. In this paper we illustrate the interrelation between facts and values in death statistics, by analyzing the rules for death certification issued by the World Health Organization. We show how the notion of the underlying cause of (...) death can change in view of public health goals. This brings us to a general point about how non-epistemic factors, such as values and goals, are reflected in the choice of different measures in epidemiological models. We finally argue that this analysis is not only relevant from a theoretical point of view but also has important practical consequences. (shrink)

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 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)

We were slightly concerned, upon having read Eric Winsberg, Jason Brennan and Chris Surprenant’s reply to our paper “Were Lockdowns Justified? A Return to the Facts and Evidence”, that they may have fundamentally misunderstood the nature of our argument, so we issue the following clarification, along with a comment on our motivations for writing such a piece, for the interested reader.

Models not only represent but may also influence their targets in important ways. While models’ abilities to influence outcomes has been studied in the context of 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 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; but second, that it may provide an additional sense in which these models can be successful, namely by changing the course of an epidemic. (shrink)

Nyansa nye sika na w'akyekyere asie. One critical factor that has contributed to the spread of the virus COVID-19 and resulting illnesses and deaths is both the conceptual and the ethical confusion between the prioritization of individual rights over social duties. The adherence to the belief in the priority of rights over duties has motivated some individuals to refrain from social distancing and, as a result, has placed themselves and other individuals at serious risk to health and life. My argument (...) is that the ethical enjoinder of social duty possesses priority over the ethical value of individual rights especially in times of global crisis. I demonstrate this point by arguing that the concept of individual right is derivative from the concept of social duty and through the argument that the concept of social duty is more efficacious in addressing global threats to human life than is the concept of individual rights. What is needed is an in-depth revision of the moral ordering of rights and duties and a vision of the human being as inherently other directed with duties toward others. I shall examine two specific ethical systems, that of Confucian and African, Akan moral philosophy that exemplify such a revision of the moral order. (shrink)

The highly contagious 2019 novel coronavirus disease (COVID-19) outbreak has not only impacted health systems, economies, and governments, it has also rapidly grown into a global health crisis, which is now threatening the lives of millions of people globally. While, on one hand, medical institutions are critically attempting to find a cure, on the other hand, governments have introduced striking measures and policies to curtail the rapid spread of the disease. Although COVID-19 has achieved pandemic status and is predominantly viewed (...) as a biomedical issue, it is argued that it should also be treated as a psychological crisis. This paper also reviews the literature to examine and comment on the detrimental effects of isolation, which has been enforced as one of the primary preventative measures to manage the spread of COVID-19. This paper further outlines key recommendations that should be addressed across different levels to buffer against the known adverse effects of isolation, which is especially relevant for the current COVID-19 situation, where a large proportion of the global population is isolated, confined, and/or quarantined. (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)

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)

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)

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 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)

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)