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

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

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

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their (...) hypotheses. I argue that the mechanistic stance is indeed a bad methodology for causal inference. However, I detach and defend a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms. (shrink)

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

Staphylococcus aureus ST45 is a major global MRSA lineage with huge strain diversity and a high clinical impact. It is one of the most prevalent carrier lineages but also frequently causes severe invasive disease, such as bacteremia. Little is known about its evolutionary history. In this study, we used whole-genome sequencing to analyze a large collection of 451 diverse ST45 isolates from 6 continents and 26 countries. De novo-assembled genomes were used to understand genomic plasticity and to perform coalescent analyses. (...) The ST45 population contained two distinct sublineages, which correlated with the isolates’ geographical origins. One sublineage primarily consisted of European/North American isolates, while the second sublineage primarily consisted of African and Australian isolates. Bayesian analysis predicted ST45 originated in northwestern Europe about 500 years ago. Isolation time, host, and clinical symptoms did not correlate with phylogenetic groups. Our phylogenetic analyses suggest multiple acquisitions of the SCCmec element and key virulence factors throughout the evolution of the ST45 lineage. (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)

Background: Respiratory syncytial virus (RSV) is one of the major viruses that cause respiratory infections in all generations, not only in neonates and infants. There is a limited number of reports on serological epidemiology of RSV subgroups A and B. Neutralizing test (NT) antibody reflects protective immunity but bothersome. Sero-epidemiological study should be performed using practical NT method. Methods: Two wild-type viruses subgroups A and B, isolated in 2013, and the Long strain was used as the challenge viruses. NT (...) antibody with 100% inhibition of cytopathic effect (CPE) was examined. A total of 91 serum samples obtained from 0 to 12 years subjects without RSV infection who visited our hospital with some health problems and 121 sera obtained from healthy subjects in different age groups were used. Serological epidemiology of subgroups A and B was investigated in this study using new NT methods. Results: 1) A simple and practical NT method was developed. 2) The NT antibody titer was lowest in <1 year of age (5 × 21.70 ± 2.03 against subgroup A and 5 × 20.85 ± 1.31 against subgroup B) and increased in 3 years of age or older, and high antibody titers were maintained during school age. 3) A slight difference was observed in the NT antibody titers against subgroups A and Bin young children <3 years, but not after 3 years of age, reflecting the repeated infections. 4) Specific IgG antibody against RSV was measured. The IgG EIA values decreased with age. No association was observed between IgG EIA and NT titers. Conclusions: A simple NT assay method was developed in the present study. By the age of 3 years, high NT antibody titers were observed and maintained until 12 years. The IgG (EIA) values decreased with age. No association was observed between IgG (EIA) and NT titers. (shrink)

The COVID-19 pandemic might be regarded as an example of a risky situation that demands proper action and decision-making in the absence of full information. It is noticeable, however, that scientists have divided into two camps concerning the best way of dealing with the very situation. Some of them have relied on mathematical models and typically proposed restrictive measures, while the others opted for the evidence-based approach and typically recommended more relaxed measures. I argue in this paper that practical possibilities (...) (or impossibilities) have been considerably neglected in those debates and current decisionmaking, especially by the proponents of mathematical epidemiology. (shrink)

What makes beliefs thrive? In this paper, we model the dissemination of bona fide science versus pseudoscience, making use of Dan Sperber's epidemiological model of representations. Drawing on cognitive research on the roots of irrational beliefs and the institutional arrangement of science, we explain the dissemination of beliefs in terms of their salience to human cognition and their ability to adapt to specific cultural ecologies. By contrasting the cultural development of science and pseudoscience along a number of dimensions, we gain (...) a better understanding of their underlying epistemic differences. Pseudoscience can achieve widespread acceptance by tapping into evolved cognitive mechanisms, thus sacrificing intellectual integrity for intuitive appeal. Science, by contrast, defies those deeply held intuitions precisely because it is institutionally arranged to track objective patterns in the world, and the world does not care much about our intuitions. In light of these differences, we discuss the degree of openness or resilience to conceptual change (evidence and reason), and the divergent ways in which science and pseudoscience can achieve cultural “success”. (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)

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)

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)

The hygiene hypothesis offers an explanation for the correlation, well-established in the industrialized nations of North and West, between increased hygiene and sanitation, and increased rates of asthma and allergies. Recent studies have added to the scope of the hypothesis, showing a link between decreased exposure to certain bacteria and parasitic worms, and increased rates of depression and intestinal auto- immune disorders, respectively. What remains less often discussed in the research on these links is that women have higher rates than (...) men of asthma and allergies, as well as many auto-immune disorders, and also depression. The current paper introduces a feminist understanding of gender socialization to the epidemiological and immunological picture. That standards of cleanliness are generally higher for girls than boys, especially under the age of five when children are more likely to be under close adult supervision, is a robust phenomenon in industrialized nations, and some research points to a cross- cultural pattern. I conclude that, insofar as the hygiene hypothesis successfully identifies standards of hygiene and sanitation as mediators of immune health, then attention to the relevant patterns of gender socialization is important. The review also makes clear that adding a feminist analysis of gender socialization to the hygiene hypothesis helps explain variation in morbidity rates not addressed by other sources and responds to a number of outstanding puzzles in current research. Alternative explanations for the sex differences in the relevant morbidity rates are also discussed (e.g., the effects of estrogens). Finally, new sources of evidence for the hygiene hypothesis are suggested in the form of cross-cultural and other natural experiments. (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)

Proponents of evidence-based medicine have argued convincingly for applying this scientific method to medicine. However, the current methodological framework of the EBM movement has recently been called into question, especially in epidemiology and the philosophy of science. The debate has focused on whether the methodology of randomized controlled trials provides the best evidence available. This paper attempts to shift the focus of the debate by arguing that clinical reasoning involves a patchwork of evidential approaches and that the emphasis on (...) evidence hierarchies of methodology fails to lend credence to the common practice of corroboration in medicine. I argue that the strength of evidence lies in the evidence itself, and not the methodology used to obtain that evidence. Ultimately, when it comes to evaluating the effectiveness of medical interventions, it is the evidence obtained from the methodology rather than the methodology that should establish the strength of the evidence. (shrink)

I propose an approach that expands philosophical views of scientific change, on the basis of an analysis of contemporary biomedical research and recent developments in the philosophy of scientific change. Focusing on the establishment of the exposome in epidemiology as a case study and the role of data as a context for contrasting views on change, I discuss change at conceptual, methodological, material, and social levels of biomedical epistemology. Available models of change provide key resources to discuss this type (...) of change, but I present the need for an approach that models transfer, alignment, and influence as key processes of change. I develop this as a pragmatic approach to scientific change, where processes might change substantially depending on specific circumstances, thus contributing to and complementing the debate on a crucial epistemological issue. (shrink)

In this article I seek to say what it is for something to count as a neglected disease. I argue that neglect should be defined in terms of efforts at prevention, mitigation and cure, and not solely in terms of research dollars per disability-adjusted life-year. I further argue that the trend towards multifactorialism and risk factor thinking in modern epidemiology has lent credibility to the erroneous view that the primary problem with neglected diseases is a lack of research. A (...) more restrictive contrastive model of disease is endorsed as better suited to the definition of neglected disease. (shrink)

In ontological terms, what can we learn from the current state of the art in Epidemiology? Applying the Quinean criterion of ontological commitment, we can learn that there are several fundamental entities for the theory to work. One is a virus type entity, in which the (in)famous Coronavirus is a particular case. In metaphysical terms, this entity can, in principle, be understood in several ways. One of those ways, apparently, and perhaps intuitively, is the notion of object. Applying the (...) metametaphysical method of Unavailable Metaphysical Stories, we found that Epidemiology is incompatible with an object metaphysics. (shrink)

Recent epidemiological reports of associations between socioeconomic status and epigenetic markers that predict vulnerability to diseases are bringing to light substantial biological effects of social inequalities. Here, we start the discussion of the moral consequences of these findings. We firstly highlight their explanatory importance in the context of the research program on the Developmental Origins of Health and Disease (DOHaD) and the social determinants of health. In the second section, we review some theories of the moral status of health inequalities. (...) Rather than a complete outline of the debate, we single out those theories that rest on the principle of equality of opportunity and analyze the consequences of DOHaD and epigenetics for these particular conceptions of justice. We argue that DOHaD and epigenetics reshape the conceptual distinction between natural and acquired traits on which these theories rely and might provide important policy tools to tackle unjust distributions of health. (shrink)

Recent epidemiological research on the social determinants of health has been used to attack an important framework, associated with Norman Daniels, that depicts healthcare as special. My aim is to rescue the idea that healthcare has special importance in society, although specialness will turn out to be mainly limited to clinical care. I build upon the link between Daniels's theory and the work of John Rawls to develop a conception of public justification liberalism that is suitable to the field of (...) justice and health. I argue that, from the perspective of public justification liberalism, (clinical) healthcare deserves special status. (shrink)

Epidemiological crisis during recrudescence of pandemic like COVID-19 may stir fear and anxiety leading to prejudices against people and communities, social isolation and stigma. Such behavioral change may wind up into increased hostility, chaos and unnecessary social disruptions. A qualitative exploratory approach was utilized to conduct an extensive review of secondary literature. The case-studies were gathered from academic literature like articles, opinions and perspective pieces published in journals and in grey literature like publications in humanitarian agencies and media reports. Grey (...) literature was included in the scope as the COVID-19 situation is still evolving. I discuss some of the mechanisms of stigmatization and how social connectedness and empathetic understandings can be a way out of negative stereotyping and discrimination met out to the sufferer of the communicable diseases as COVID-19. Empathetic understanding paves a way to approach a problem from the perspective of ‘we’ not limiting one only to ‘I’. The moment when we make an approach from ‘I’ to ‘We’ actually then we embark on a journey of illness to wellness. Keywords: COVID-19, pandemic, stigma, discrimination, mental health, empathy, India, Face-to-face communication, social distancing, suicide. (shrink)

The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green honeymoon (...) between health and sustainability caused by AI, it should aim for a lasting marriage. To this end, we conclude by proposing that, in the upcoming years, it could be valuable and necessary to promote more interconnected health, call for environmental cost transparency, and increase green responsibility. (shrink)

In this study, screening positive for probable depression was common among undergraduate students at the University of the Witwatersrand, Johannesburg, South Africa and associated with sociodemographic and selected behavioral factors. These findings call for strengthening the awareness and use of counselling services among undergraduate students.

Lockdowns were a morally and medically appropriate anti-contagion policy to stop the spread of Covid. However, lockdowns came with considerable costs. Specifically, lockdowns imposed harms and losses upon the young in order to benefit the elderly, who were at the highest risk of severe illness and death from Covid. This represented a shifting of the (epidemiological) burden of Covid for the elderly to a systemic burden of lockdown upon the young. This article argues that even if lockdowns were a morally (...) permissible response to Covid, the harms and losses they imposed on the young ground a claim of compensation. I defend an intergenerational compensation argument that defends a claim for an egalitarian intergenerational transfer to compensate the young for the harms of lockdown. (shrink)

This essay frames systemic patterns of mental abuse against women of color and Indigenous women on Turtle Island (North America) in terms of larger design-of-distribution strategies in settler colonial societies, as these societies use various forms of social power to distribute, reproduce, and automate social inequalities (including public health precarities and mortality disadvantages) that skew socio-economic gain continuously toward white settler populations and their descendants. It departs from traditional studies in gender-based violence research that frame mental abuses such as gaslighting--commonly (...) understood as mental manipulation through lying or deceit--stochastically, as chance-driven interpersonal phenomena. Building on structural analyses of knowledge in political epistemology (Dotson 2012, Berenstain 2016), political theory (Davis and Ernst 2017), and Indigenous social theory (Tuck and Yang 2012), I develop the notion of cultural gaslighting to refer to the social and historical infrastructural support mechanisms that disproportionately produce abusive mental ambients in settler colonial cultures in order to further the ends of cultural genocide and dispossession. I conclude by proposing a social epidemiological account of gaslighting that a) highlights the public health harms of abusive ambients for minority populations, b) illuminates the hidden rules of social structure in settler colonial societies, and c) amplifies the corresponding need for structural reparations. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

This paper has two objectives 1) to study the influence of digital and new technology on COVID-19 diagnosis and healthcare 2) To propose the integral guideline solutions of the infectious disease for the future. COVID-19 stands for corona (CO), virus (VI), disease (D), or SARS-CoV-2, is a respiratory virus first identified in December 2019 in Wuhan, China(WHO, 2019). It is an epidemiological crisis that caused the deaths and sudden destruction of wealth and health of people around the world. Many countries (...) responded to the crisis with what could only be called urgent prevention and treatment. In the 21st century, our society is based on digital and new technology that can control and prevent the COVID-19 pandemics. However, these ways for solving the problem of COVID-19 pandemics are rising an epistemological crisis too. There are some problems with the COVID-19 diagnosis. From Buddhist philosophy perspective, COVID-19 teaches us the coronavirus is causing us to experience some heightened forms of the three marks of our existence which are the impermanence (aniccā), the suffering (duḥkha), and the non-self (anatta). The establishment of scientific expertise and innovation has shown its value and educating the public about testing, diagnosis, communication, treatment, and vaccine development technology for prevention the of infectious diseases in the future. (shrink)

The available resources for global health assistance are far outstripped by need. In the face of such scarcity, many people endorse a principle according to which highest priority should be given to the worst off. However, in order for this prioritarian principle to be useful for allocation decisions, policy-makers need to know what it means to be badly off. In this article, we outline a conception of disadvantage suitable for identifying the worst off for the purpose of making health resource (...) allocation decisions. According to our total advantage view: the worst off are those who have the greatest total lifetime disadvantage; advantage foregone due to premature death should be treated in the same way as other ways of being disadvantaged at a time; how badly off someone is depends on the actual outcomes that will befall her without intervention, not her prospects at a time; and all significant forms of disadvantage count for determining who is worst off, not just disadvantage relating to health. We conclude by noting two important implications of the total advantage view: first, that those who die young are among the globally worst off, and second, that the epidemiological shift in the global burden of disease from communicable to non-communicable diseases should not lead to a corresponding shift in global health spending priorities. (shrink)

Background: Socio-epidemiological data of dental caries helps to plan effective community interventions. Objective: To estimate the prevalence and assess the experience of dental caries among school going adolescents in a rural area of Bangladesh. Methods: A cross-sectional study was donein Sylhet District in Bangladesh, between January and December of 2014. Students of class VIII, IX and X, aged 12-16 years were taken for the study. A total of 90 studentswere divided into 12-14 years and 15-16 years age groups using simple (...) random sampling technique. A pre-designed, self-administered questionnaire was used for demographic survey. Students were examined for dental caries. Assessment of Experience of dental caries was done by Decayed, Missing and Filled teeth (DMFT) index. Results: The mean age of the respondents was 14.37±0.50 years. Females were 68(75.6%) and males were 22(24.4%). 31(34.4%), 30 (33.3%) and 29(32.2%) were from VIII, IX and X respectively. The older age group (15-16 years) had more decayed teeth than that of 12-14 years group (2.28 vs. 1.46; p=0.04). The mean DMFT score was lower in male compared to female (1.43 vs. 2.30; p>0.05).There was significant difference in the total DMFT score among the classes (p=0.009). Mean DMFT score was 1.88. Caries prevalence was 42.2% in the maxillary arch and 58.9% in the mandibular arch. Among males, the mandibular arch showed a higher caries level (63.64%) than the maxillary arch (40%), while in females, in maxillary and mandibular archeswere 42.64% and 42.65% respectively (p>0.05). Conclusion: 64.4% of the study population had dental caries with male predominance; mandibular arch was more involved. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Many epidemics consist in individuals spreading infection to others. From the population perspective, they also have population characteristics important in modeling, explaining, and intervening in epidemics. I analyze epidemiology’s contemporary population perspective through the example of epidemics by examining two central principles attributed to Geoffrey Rose: a distinction between the causes of cases and the causes of incidence, and between “high-risk” and “population” strategies of prevention. Both principles require revision or clarification to capture the sense in which they describe (...) distinct perspectives on the same phenomenon, each perspective capturing a different level of contrastive analysis. (shrink)

This paper defends a distinctly liberal approach to public health ethics and replies to possible objections. In particular, I look at a set of recent proposals aiming to revise and expand liberalism in light of public health's rationale and epidemiological findings. I argue that they fail to provide a sociologically informed version of liberalism. Instead, they rest on an implicit normative premise about the value of health, which I show to be invalid. I then make explicit the unobvious, republican background (...) of these proposals. Finally, I expand on the liberal understanding of freedom as non-interference and show its advantages over the republican alternative of freedom as non-domination within the context of public health. The views of freedom I discuss in the paper do not overlap with the classical distinction between negative and positive freedom. In addition, my account differentiates the concepts of freedom and autonomy and does not rule out substantive accounts of the latter. Nor does it confine political liberalism to an essentially procedural form. (shrink)

Abstract: The emergence of the novel coronavirus (COVID-19) in 2019 has presented the world with an unprecedented global health crisis. The rapid and widespread transmission of the virus has strained healthcare systems, disrupted economies, and challenged societies. In response to this monumental challenge, the intersection of technology and healthcare has become a focal point for innovation. This research endeavors to leverage the capabilities of Artificial Neural Networks (ANNs) to develop an advanced predictive model for forecasting the spread of COVID-19. It (...) involves the collection, analysis, and integration of diverse datasets encompassing epidemiological, clinical, and social factors that influence the virus's dissemination. (shrink)

Genetically engineered (GE) insects, such as the GE OX513A Aedes aegypti mosquitoes, have been designed to suppress their wild-type populations so as to reduce the transmission of vector-borne diseases in humans. Apart from the ecological and epidemiological uncertainties associated with this approach, such biotechnological approaches may be used by individual governments or the global community of nations to avoid addressing the underlying structural, systemic causes of those infections... We discuss here key ethical questions raised by the use of GE mosquitoes, (...) with the aim of fostering discussion between the public, researchers, policy makers, healthcare organizations, and regulatory agencies at the local, national, and international levels. We affect that goal by outlining a procedural approach to decision-making about the use of the “biotechnology” that goes beyond “community engagement.” The protocol we advocate for entails informed deliberations and decision-making at the community level. It is designed to ensure that the voices of the marginalized and vulnerable groups that would be disproportionately affected by the decision are heard during the community-wide discussions. Moreover, we make the case that the values embedded in the risk assessment should be identified so that the community can make an informed decision about the use of GE insects. In addition, we advocate for the involvement of a variety of actors whose responsibility would be to ensure that the community has the opportunity to make an informed decision based on deliberations about the use of the “biotechnology.”. (shrink)

"Correlation is not causation" is one of the mantras of the sciences—a cautionary warning especially to fields like epidemiology and pharmacology where the seduction of compelling correlations naturally leads to causal hypotheses. The standard view from the epistemology of causation is that to tell whether one correlated variable is causing the other, one needs to intervene on the system—the best sort of intervention being a trial that is both randomized and controlled. In this paper, we argue that some purely (...) correlational data contains information that allows us to draw causal inferences: statistical noise. Methods for extracting causal knowledge from noise provide us with an alternative to randomized controlled trials that allows us to reach causal conclusions from purely correlational data. (shrink)

Racial disparities in health outcomes have recently become a flashpoint in the debate about the value of race as a biological concept. What role, if any, race has in the etiology of disease is a philosophically and scientifically contested topic. In this article, I expand on the insights of the new mechanistic philosophy of science to defend a mechanism discovery approach to investigating epidemiological racial disparities. The mechanism discovery approach has explanatory virtues lacking in the populational approach typically employed in (...) the study of race and biomedicine. The explanatory constraints that form an integral part of the new mechanistic approach enable mechanism discovery to avoid the epistemic and normative shortcomings of the populational approach. The methodology of mechanism discovery can fruitfully be extended to the treatment and reversal of epidemiological racial disparities. (shrink)

This dissertation explores the idea and ethics of vaccination for the sake of others. It conceptually distinguishes four different kinds of vaccination—self-protective, paternalistic, altruistic, and indirect—based on who receives the primary benefits of vaccination and who ultimately makes the vaccination decision. It describes the results of focus group studies that were conducted to investigate what people who might get vaccinated altruistically think of this idea. It also applies the different kinds of vaccination to ethical issues surrounding COVID-19, such as lockdown (...) measures, routine or mandatory vaccination of healthy children, and the ethical justification of restrictive measures for unvaccinated people. A more general philosophical account of vaccination ethics is ultimately developed, which is based not on moral duties, but on the moral reasons that people may have to get vaccinated for the sake of others. It is argued that such reasons may be stronger or weaker, depending on various factors related to the vaccines in question and the specific epidemiological circumstances. (shrink)

Recent debates in psychopathy studies have articulated concerns about false-positives in assessment and research sampling. These are pressing concerns for research progress, since scientific quality depends on sample quality, that is, if we wish to study psychopathy we must be certain that the individuals we study are, in fact, psychopaths. Thus, if conventional assessment tools yield substantial false-positives, this would explain why central research is laden with discrepancies and nonreplicable findings. This paper draws on moral psychology in order to develop (...) tentative theory-driven exclusion criteria applicable in research sampling. Implementing standardized procedures to discriminate between research participants has the potential to yield more homogenous and discrete samples, a vital prerequisite for research progress in etiology, epidemiology, and treatment strategies. (shrink)

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, pathogenesis, (...) diagnosis, prevention, and treatment. We emphasize CIDO development relevant to COVID-19. (shrink)

Cultural Attraction Theory (CAT), also referred to as cultural epidemiology, is an evolutionary theory of culture. It provides conceptual tools and a theoretical framework for explaining why and how ideas, practices, artifacts and other cultural items spread and persist in a community and its habitat. It states that cultural phenomena result from psychological or ecological factors of attraction.

This paper examines the complex research landscape of contemporary suicidology from a philosophy of science perspective. I begin by unpacking the methods, concepts, and assumptions of some of the prominent approaches to studying suicide causation, including psychological autopsy studies, epidemiological studies, biological studies, and qualitative studies. I then analyze the different ways these approaches partition the causes of suicide, with particular emphasis on the ways they conceptualize the domain of mental disorder. I argue that these different ways of partitioning the (...) causal space and conceptualizing mental disorder result in incommensurabilities between the approaches. These incommensurabilities restrict the degrees to which the different approaches can be integrated, thus lending support to explanatory pluralism in the study of suicide causation. They also shed light on some of the philosophical underpinnings of the disagreement between mainstream suicidology and the emerging area of critical suicidology. (shrink)

Healthcare systems across the globe are struggling with increasing costs and worsening outcomes. This presents those responsible for overseeing healthcare with a challenge. Increasingly, policymakers, politicians, clinical entrepreneurs and computer and data scientists argue that a key part of the solution will be ‘Artificial Intelligence’ (AI) – particularly Machine Learning (ML). This argument stems not from the belief that all healthcare needs will soon be taken care of by “robot doctors.” Instead, it is an argument that rests on the classic (...) counterfactual definition of AI as an umbrella term for a range of techniques that can be used to make machines complete tasks in a way that would be considered intelligent were they to be completed by a human. Automation of this nature could offer great opportunities for the improvement of healthcare services and ultimately patients’ health by significantly improving human clinical capabilities in diagnosis, drug discovery, epidemiology, personalised medicine, and operational efficiency. However, if these AI solutions are to be embedded in clinical practice, then at least three issues need to be considered: the technical possibilities and limitations; the ethical, regulatory and legal framework; and the governance framework. In this article, we report on the results of a systematic analysis designed to provide a clear overview of the second of these elements: the ethical, regulatory and legal framework. We find that ethical issues arise at six levels of abstraction (individual, interpersonal, group, institutional, sectoral, and societal) and can be categorised as epistemic, normative, or overarching. We conclude by stressing how important it is that the ethical challenges raised by implementing AI in healthcare settings are tackled proactively rather than reactively and map the key considerations for policymakers to each of the ethical concerns highlighted. (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits (...) of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

The environment can elicit biological responses such as oxidative stress (OS) and inflammation as a consequence of chemical, physical, or psychological changes. As population studies are essential for establishing these environment-organism interactions, biomarkers of OS or inflammation are critical in formulating mechanistic hypotheses. By using examples of stress induced by various mechanisms, we focus on the biomarkers that have been used to assess OS and inflammation in these conditions. We discuss the difference between biomarkers that are the result of a (...) chemical reaction (such as lipid peroxides or oxidized proteins that are a result of the reaction of molecules with reactive oxygen species) and those that represent the biological response to stress, such as the transcription factor NRF2 or inflammation and inflammatory cytokines. The high-throughput and holistic approaches to biomarker discovery used extensively in large-scale molecular epidemiological exposome are also discussed in the context of human exposure to environmental stressors. We propose to consider the role of biomarkers as signs and to distinguish between signs that are just indicators of biological processes and proxies that one can interact with and modify the disease process. (shrink)

Standard objections to the notion of a hedged, or ceteris paribus, law of nature usually boil down to the claim that such laws would be either 1) irredeemably vague, 2) untestable, 3) vacuous, 4) false, or a combination thereof. Using epidemiological studies in nutrition science as an example, I show that this is not true of the hedged law-like generalizations derived from data models used to interpret large and varied sets of empirical observations. Although it may be ‘in principle impossible’ (...) to construct models that explicitly identify all potential causal interferers with the relevant generalization, the view that our failure to do so is fatal to the very notion of a cp-law is plausible only if one illicitly infers metaphysical impossibility from epistemic impossibility. I close with the suggestion that a model-theoretic approach to cp-laws poses a problem for recent attempts to formulate a Mill-Ramsey-Lewis theory of cp-laws. (shrink)

Identifying the necessary and sufficient conditions for individuating and classifying diseases is a matter of great importance in the fields of law, ethics, epidemiology, and of course, medicine. In this paper, I first propose a means of achieving this goal, ensuring that no two distinct disease-types could correctly be ascribed to the same disease-token. I then posit a metaphysical ontology of diseases—that is, I give an account of what a disease is. This is essential to providing the most effective (...) means of interfering with disease processes. Following existing work in the philosophy of medicine and epidemiology (primarily Christopher Boorse; Caroline Whitbeck; Alexander Broadbent), philosophy of biology (Joseph LaPorte; D.L. Hull), conditional analyses of causation (J.L. Mackie; David Lewis), and recent literature on dispositional essentialism (Stephen Mumford and Rani Anjum; Alexander Bird), I endorse a dispositional conception of disease. Following discussion of various conceptions of disease-identity, their relations to the clinical and pathological effects of the diseases in question, and how diseases are treated, I conclude (i) that diseases should be individuated by their causes, and (ii) that diseases are causal processes best seen as simultaneously acting sequences of mutually manifesting dispositions. (shrink)