Causation in Population Health Informatics and Data Science, 1st ed. 2019

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.

Olaf Dammann, M.D. (U Hamburg, ’90), S.M. Epidemiology (Harvard, ’97) is Professor of Public Health and Community Medicine, Pediatrics, and Ophthalmology at Tufts University School of Medicine in Boston, USA. He is also Editor-in-Chief Emeritus of PEDIATRIC RESEARCH, the publication of the International Pediatric Research Foundation. His research interests include the elucidation of risk factors for brain damage and retinopathy in preterm newborns, the theory of risk and causation in biomedical and population health research, and the development of computational chronic disease models. He has received grant support from the National Institutes of Health and the European Union. His bibliography lists more than 200 publications.

Reviews intersections between epidemiology, public health, computation, informatics, and science philosophy

Suggests a new theory for the integration of epidemiology, public health, computation, informatics, and science philosophy to improve public health research

Evaluates how informatics and computational approaches can aid the identification of causal associations in the health sciences