Epidemics : models and data using R / Ottar N. Bjørnstad.
2022
RA652.2.D38
Linked e-resources
Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Epidemics : models and data using R / Ottar N. Bjørnstad.
Author
Bjørnstad, Ottar N.
Edition
2nd ed.
ISBN
9783031120565 (electronic bk.)
3031120566 (electronic bk.)
9783031120558
3031120558
3031120566 (electronic bk.)
9783031120558
3031120558
Publication Details
Cham : Springer, 2022.
Language
English
Description
1 online resource (386 p.).
Item Number
10.1007/978-3-031-12056-5 doi
Call Number
RA652.2.D38
Dewey Decimal Classification
614.40285
Summary
This book is designed to be a practical study in infectious disease dynamics. It offers an easy-to-follow implementation and analysis of mathematical epidemiology. It focuses on recent case studies in order to explore various conceptual, mathematical, and statistical issues. The dynamics of infectious diseases shows a wide diversity of pattern. Some have locally persistent chains-of-transmission, others persist spatially in consumer-resource metapopulations. Some infections are prevalent among the young, some among the old and some are age-invariant. Temporally, some diseases have little variation in prevalence, some have predictable seasonal shifts and others exhibit violent epidemics that may be regular or irregular in their timing. Models and models-with-data have proved invaluable for understanding and predicting this diversity, and thence help improve intervention and control. Using mathematical models to understand infectious disease, dynamics has a very rich history in epidemiology. The field has seen broad expansions of theories as well as a surge in real-life application of mathematics to dynamics and control of infectious disease. The chapters of Epidemics: Models and Data Using R have been organized as follows: chapters 1-10 is a mix and match of models, data and statistics pertaining to local disease dynamics; chapters 11-13 pertains to spatial and spatiotemporal dynamics; chapter 14 highlights similarities between the dynamics of infectious disease and parasitoid-host dynamics; Finally, chapters 15 and 16 overview additional statistical methodology useful in studies of infectious disease dynamics. This book can be used as a guide for working with data, models and models-and-data to understand epidemics and infectious disease dynamics in space and time. All the code and data sets are distributed in the epimdr2 R package to facilitate the hands-on philosophy of the text.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 4, 2023).
Series
Use R!
Available in Other Form
Epidemics
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
All Resources
Table of Contents
Chapter 1. Introduction
Chapter 2. SIR
Chapter 3. R0
Chapter 4. FoI and age-dependent incidence
Chapter 5. Seasonality
Chapter 6. Time Series Analysis
Chapter 7. TSIR
Chapter 8
Trajectory Matching
Chapter 9. Stability and Resonant Periodicity
Chapter 10. Exotica
Chapter 11. Spatial Dynamics
Chapter 12. Transmission on Networks
Chapter 13. Spatial and Spatiotemporal Patterns
Chapter 14. Parasitoids
Chapter 15. Non-Independent Data
Chapter 16. Quantifying In-Host Patterns
Bibliography
Index.
Chapter 2. SIR
Chapter 3. R0
Chapter 4. FoI and age-dependent incidence
Chapter 5. Seasonality
Chapter 6. Time Series Analysis
Chapter 7. TSIR
Chapter 8
Trajectory Matching
Chapter 9. Stability and Resonant Periodicity
Chapter 10. Exotica
Chapter 11. Spatial Dynamics
Chapter 12. Transmission on Networks
Chapter 13. Spatial and Spatiotemporal Patterns
Chapter 14. Parasitoids
Chapter 15. Non-Independent Data
Chapter 16. Quantifying In-Host Patterns
Bibliography
Index.