Overview
- The 1st book that introduces the notion of systems epidemiology
- Comprehensive literature survey
- Detailed principles, methodologies, and illustrative examples, in both computational epidemiology and systems epidemiology
Part of the book series: Health Information Science (HIS)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Keywords
- Computational epidemiology
- Systems Epidemiology
- Age-Specific Transmission Dynamics
- Disease Transmission
- Contact Matrix
- Vaccination Decision Making
- Prioritized Intervention
- Prioritized Vaccine Allocation
- Game Theory
- Cost-and-Benefit Analysis
- Belief Theory
- Social Impact Theory
- Social Influence
- Social Media
- Data-Driven Modeling
- Complex Systems
About this book
Specifically, the book presents the basic concepts, related computational models, and tools that are useful for characterizing disease transmission dynamics with respect to a heterogeneous host population. In addition, it shows how to develop and apply computational methods to tackle the challenges involved in population-level intervention, such as prioritized vaccine allocation. A unique feature of this book is that its examination on the issues of vaccination decision-making is not confined only to the question of how to develop strategic policies on prioritized interventions, as it further approaches the issues from the perspective of individuals, offering a well integrated cost-benefit and social-influence account for voluntary vaccination decisions. One of the most important contributions of this book lies in it offers a blueprint on a novel methodological paradigm in epidemiology, namely, systems epidemiology, with detailed systems modeling principles, as well as practical steps and real-world examples, which can readily be applied in addressing future systems epidemiological challenges.
The book is intended to serve as a reference book for researchers and practitioners in the fields of computer science and epidemiology. Together with the provided references on the key concepts, methods, and examples being introduced, the book can also readily be adopted as an introductory text for undergraduate and graduate courses in computational epidemiology as well as systems epidemiology, and as training materials for practitioners and field workers.
Authors and Affiliations
About the authors
Dr. Shang Xia is currently an Associate Professor at the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention (NIPD, China CDC), which is also recognized as the Chinese Center for Tropical Diseases Research (CTDR), and WHO Collaborating Centre for Tropical Diseases. He also works as a member of Joint Research Laboratory for Intelligent Disease Surveillance and Control (a research partnership with Hong Kong Baptist University). He received his PhD degree in Computer Science from Hong Kong Baptist University (HKBU) in Hong Kong, having obtained MEng and BEng degrees from Shanghai Jiao Tong University (SJTU), China. He has completed his Postdoctoral Research Program in the Chinese Center for Diseases Control and Prevention (China CDC) in Beijing, China. He is the committee member of International Society of Geospatial Health (GnosisGIS). He has served as the section editors of BMC Infectious Diseases of Poverty (IDP), and Climate Change Research (in Chinese).
Bibliographic Information
Book Title: Computational Epidemiology
Book Subtitle: From Disease Transmission Modeling to Vaccination Decision Making
Authors: Jiming Liu, Shang Xia
Series Title: Health Information Science
DOI: https://doi.org/10.1007/978-3-030-52109-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-52107-3Published: 19 September 2020
eBook ISBN: 978-3-030-52109-7Published: 18 September 2020
Series ISSN: 2366-0988
Series E-ISSN: 2366-0996
Edition Number: 1
Number of Pages: XVIII, 113
Number of Illustrations: 30 b/w illustrations, 20 illustrations in colour
Topics: Health Informatics, Health Promotion and Disease Prevention, Epidemiology, Health Informatics, Computational Biology/Bioinformatics