Computational Modeling of Infectious Disease: With Applications in Python provides an illustrated compendium of tools and tactics for analyzing infectious diseases using cutting-edge computational methods. From simple S(E)IR models, and through time series analysis and geospatial models, this book is both a guided tour through the computational analysis of infectious diseases and a quick-reference manual. Chapters are accompanied by extensive practical examples in Python, illustrating applications from start to finish. This book is designed for researchers and practicing infectious disease forecasters, modelers, data scientists, and those who wish to learn more about analysis of infectious disease processes in the real world.
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Maße
Höhe: 228 mm
Breite: 152 mm
Dicke: 24 mm
Gewicht
ISBN-13
978-0-323-95389-4 (9780323953894)
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Schweitzer Klassifikation
Born in Budapest, Hungary, Chris von Csefalvay was educated at Oxford, Leiden and Cardiff. A data scientist by background, he has advised enterprises, NGOs and governments on the use of computational tools and Big Data to manage the challenges of public health in a rapidly changing world. He joined Starschema Inc. in 2018, serving as Vice-President for Special Projects. He is a Fellow of the Royal Society for Public Health.
Autor*in
Vice-President for Special Projects, Starschema Inc., VA, USA
1. Introduction
2. Simple compartmental models
3. Modeling host factors
4. Host-vector and multi-host systems
5. Multi-pathogen systems
6. Modeling the control of infectious disease
7. Temporal dynamics of infectious disease
8. Spatial models of infectious disease
9. Agent-based models
