
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 quote- 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
- Imprint: Academic Press
- No. of pages: 476
- Language: English
- Paperback ISBN: 9780323953894
- eBook ISBN: 9780323958370
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