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AbstractThe 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.

In their 2022 paper, Kensbock, Alkærsig, and Lomberg provide compelling evidence of an increased risk in treated depressive, anxiety, and stress-related disorders within workplaces, associated with the introduction of new hires who either have treated disorders themselves or are hired from workplaces with an increased prevalence of treated disorders. The authors interpret these findings as evidence of a "contagion" effect for psychiatric disorders, illustrative of workplace spread of disorder that may affect the mental health of employees. In this commentary, we contextualize these findings through psychiatric epidemiology. The evidence provided by Kensbock and colleagues is consistent with a long history of evidence in psychiatric and social epidemiology illustrating that many health outcomes are affected by those in our social networks and that psychiatric disorders, in particular, evidence spatial and temporal autocorrelation as well as social network spread that can be best conceptualized through well-known infectious disease principles. Thus, there is a large empirical literature that supports the findings of Kensbock, Alkærsig, and Lomberg. That said, the findings should not be overinterpreted; they fit some patterns of previous literature and known facts about psychiatric disorders, but not all. They also must be appropriately situated within the literature on workplace determinants of mental well-being more generally and, in particular, the global movements to situate the rights of workers with mental illness for employment protections and safe working conditions.

AbstractThis paper primarily argues that Epidemiology is Ecosystem Science. It will not only explore this notion in detail but will also relate it to the argument that Classical Chinese Medicine was/is Ecosystem Science. Ecosystem Science (as instantiated by Epidemiology) and Ecosystem Science (as instantiated by Classical Chinese Medicine) share these characteristics: (a) they do not subscribe to the monogenic conception of disease; (b) they involve multi variables; (c) the model of causality presupposed is multi-factorial as well as non-linear.

This course was developed by the Centers for Disease Control and Prevention (CDC) as a self-study course. Continuing education is available for certified public health educators, nurses, physicians, pharmacists, veterinarians, and public health professionals. This course covers basic epidemiology principles, concepts, and procedures useful in the surveillance and investigation of health-related states or events. It is designed for federal, state, and local government health professionals and private sector health professionals who are responsible for disease surveillance or investigation. A basic understanding of the practices of public health and biostatistics is recommended. The course materials consist of six lessons. Each lesson presents instructional text interspersed with relevant exercises that apply and test knowledge and skills gained. ; Lesson One: Introduction to epidemiology -- Lesson Two: Summarizing data -- Lesson Three: Measures of risk -- Lesson Four: Displaying Public health data -- Lesson Five: Public health surveillance -- Lesson Six: Investigating an outbreak - Glossary ; Also available via the World Wide Web as an Acrobat .pdf file (6.01 MB, 511 p.). ; Includes bibliographical references.

"The field of infectious disease epidemiology has been front-and-center for the past few years. With the COVID-19 pandemic, an opportunity arose to provide "armchair epidemiologists" with a deeper understanding of the population-level impacts of infectious diseases, and the tools available to control them. This field has its own unique culture and set of tools and rules. We will utilize a whole new vocabulary in this book, from how to consider transmission-with the idea of a disease reproductive rate-to how disease is dispersed or clustered, and to how to design a study. As the reader will see, infectious disease epidemiologists seek to learn who is sick, why they are sick, and when and where they became sick"--

▪ Abstract  Over the past decade anthropologists and epidemiologists have begun to move beyond the "benign neglect" that characterized their prior relationship. Some of the most important collaborations between these disciplines concern themes of culture change and stress, social stratification, and the unpacking of other social and cultural variables. Anthropologists have criticized and expanded epidemiological notions of risk and vulnerability. Multidisciplinary teams of anthropologists and epidemiologists have constructed new measures and used multiple methods to increase the validity of their results. Disputes about classification have also linked the two disciplines. Collaborative projects between anthropologists and epidemiologists are leading to more nuanced and accurate descriptions of human behavior and more appropriate and effective interventions. Epidemiological techniques and ideas are also being used for anthropological ends, because disease often spreads along the framework of social structure. These many forms of collaboration create the foundations of a cultural epidemiology.