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.
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Table of Contents
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
