Disease is everywhere. Everyone experiences disease, everyone knows somebody who is, or has been diseased, and disease-related stories hit the headlines on a regular basis. Many important issues in the philosophy of disease, however, have received remarkably little attention from philosophical thinkers. This book examines a number of important debates in the philosophy of medicine, including 'what is disease?', and the roles and viability of concepts of causation, in clinical medicine and epidemiology. Where much of the existing literature targets conceptual analyses of health and disease, this book provides the reader with an insight into these debates, and develops plausible alternative accounts. The author explores a range of related subjects, discussing a host of interesting philosophical questions within clinical medicine, pathology and epidemiology. In the second part of the book, the author examines the concepts of causation employed by clinicians and pathologists, how one should classify diseases, and whether the epidemiologist's models for inferring the causes of disease are all they're cracked up to be.

Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.