Computational Modeling of Infectious Disease
With Applications in Python
- 1st Edition - February 14, 2023
- Imprint: Academic Press
- Author: Chris von Csefalvay
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 5 3 8 9 - 4
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 5 8 3 7 - 0
Computational Modeling of Infectious Disease: With Applications in Python provides an illustrated compendium of tools and tactics for analyzing infectious diseases using cuttin… Read more
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Request a sales quoteComputational 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.
- Connects computational infectious disease analysis to state-of-the-art data science
- Conveys ideas on epidemiology and infectious disease modeling in a clear, accessible way
- Provides code examples to elucidate best practices
Researchers and practicing infectious disease forecasters/modelers; data scientists integrating a model of an infectious disease into their existing frameworks; computational scientists who need to understand the underlying logic of infectious disease models; Infectious disease specialists who need solid quantitative grounding for their research. Graduate students in virology, infectious disease medicine, quantitative biology, quantitative ecology, and epidemiology; infectious disease forecasters at public health authorities, hospitals, regulatory bodies
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- List of figures
- References
- Biography
- Chris von Csefalvay
- Foreword
- Preface
- References
- 1: Introduction
- Abstract
- 1.1. Why we model infectious disease
- 1.2. A brief history of the discipline
- 1.3. What this book is about
- 1.4. The computational mindset
- 1.5. Who this book is for
- 1.6. What this book is not about
- 1.7. How to use this book
- 1.8. Definitions, computational examples, and practice notes
- References
- 2: Simple compartmental models
- Abstract
- 2.1. The intuition of compartmental models
- 2.2. Modeling mortality and vital dynamics
- 2.3. Models of immunity
- 2.4. Models with latent periods, asymptomatic infection, and carrier states
- 2.5. Empirical parameter estimation
- References
- 3: Host factors
- Abstract
- 3.1. Heterogeneity of transmission risk
- 3.2. Continuous and semicontinuous heterogeneities
- References
- 4: Host-vector and multihost systems
- Abstract
- 4.1. Pure vector-borne diseases
- 4.2. Zoonotic disease
- References
- 5: Multipathogen dynamics
- Abstract
- 5.1. Multipathogen systems with cross-immunity
- 5.2. Multipathogen systems without cross-immunity
- References
- 6: Modeling the control of infectious disease
- Abstract
- 6.1. Modeling vaccination
- 6.2. Duration and effectiveness of vaccine-induced immunity
- 6.3. Isolation and quarantine
- References
- 7: Temporal dynamics of epidemics
- Abstract
- 7.1. Equilibrium states and stability analysis
- 7.2. Seasonality and periodicity in infectious diseases
- 7.3. Temporal forcing
- References
- 8: Spatial dynamics of epidemics
- Abstract
- 8.1. Spatial lattice models
- 8.2. Computational geospatial infectious disease analysis
- References
- 9: Agent-based modeling
- Abstract
- 9.1. The fundamentals of agent-based modeling
- 9.2. Agent-based models of disease control
- 9.3. Agent-based models of mobility
- References
- A: Fundamentals of Python syntax
- A.1. Executing Python
- A.2. Basic syntactic rules
- A.3. Identifiers and variables
- A.4. Functions
- A.5. Control flow and operations
- A.6. Collections and iterables
- A.7. Arithmetics and basic operations
- A.8. Program structure
- A.9. Object-oriented programming
- A.10. Ancillary tools
- A.11. Beyond the standard library
- A.12. Where to find help
- References
- References
- Index
- Edition: 1
- Published: February 14, 2023
- No. of pages (Paperback): 476
- No. of pages (eBook): 476
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780323953894
- eBook ISBN: 9780323958370
Cv
Chris von Csefalvay
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.
Affiliations and expertise
Vice-President for Special Projects, Starschema Inc., VA, USARead Computational Modeling of Infectious Disease on ScienceDirect