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Causation in Population Health Informatics and Data Science

  • 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

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-ix
  2. Introduction

    • Olaf Dammann, Benjamin Smart
    Pages 1-14
  3. Health Data Science

    • Olaf Dammann, Benjamin Smart
    Pages 15-26
  4. The Metaphysics of Illness Causation

    • Olaf Dammann, Benjamin Smart
    Pages 27-41
  5. Causal Inference in Population Health Informatics

    • Olaf Dammann, Benjamin Smart
    Pages 43-61
  6. Making Population Health Knowledge

    • Olaf Dammann, Benjamin Smart
    Pages 63-77
  7. Population Risk

    • Olaf Dammann, Benjamin Smart
    Pages 79-98
  8. Integrating Evidence

    • Olaf Dammann, Benjamin Smart
    Pages 99-115
  9. Conclusion and Invite

    • Olaf Dammann, Benjamin Smart
    Pages 117-118
  10. Back Matter

    Pages 119-134

About this book

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.

Authors and Affiliations

  • Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, USA

    Olaf Dammann

  • The African Centre for Epistemology and Philosophy of Science, University of Johannesburg, Johannesburg, South Africa

    Benjamin Smart

About the authors

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.

Dr Benjamin Smart is senior lecturer at The University of Johannesburg, and a founder member of The African Centre for Epistemology and Philosophy of Science. He was awarded a PhD in metaphysics by The University of Nottingham in 2012, before lecturing philosophy at The University of Birmingham (2012-2015). Smart has published widely on causation, laws of nature, and on the philosophy of health and disease.

Bibliographic Information

  • Book Title: Causation in Population Health Informatics and Data Science

  • Authors: Olaf Dammann, Benjamin Smart

  • DOI: https://doi.org/10.1007/978-3-319-96307-5

  • Publisher: Springer Cham

  • eBook Packages: Medicine, Medicine (R0)

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Hardcover ISBN: 978-3-319-96306-8Published: 09 November 2018

  • Softcover ISBN: 978-3-030-07174-5Published: 12 January 2019

  • eBook ISBN: 978-3-319-96307-5Published: 29 October 2018

  • Edition Number: 1

  • Number of Pages: IX, 134

  • Number of Illustrations: 14 b/w illustrations, 1 illustrations in colour

  • Topics: Health Informatics, Health Informatics, Logic, Epidemiology

Buy it now

Buying options

eBook USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access