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Epidemics = models and data using R /

Bjornstad, Ottar N.

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Epidemics = models and data using R /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Epidemics/ by Ottar N. Bjornstad.
Reminder of title:	models and data using R /
Author:	Bjornstad, Ottar N.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xv, 387 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Epidemics - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-12056-5
ISBN:	9783031120565

Epidemics = models and data using R /
Bjornstad, Ottar N.

Epidemicsmodels and data using R /[electronic resource] :by Ottar N. Bjornstad. - Second edition. - Cham :Springer International Publishing :2023. - xv, 387 p. :ill., digital ;24 cm. - Use R!,2197-5744. - Use R!..

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.

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.

ISBN: 9783031120565

Standard No.: 10.1007/978-3-031-12056-5doiSubjects--Topical Terms:

3627129
Epidemics
--Data processing.

LC Class. No.: RA652.2.D38 / B5 2023

Dewey Class. No.: 614.40285

Epidemics = models and data using R /
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100 1 $a Bjornstad, Ottar N. $3 3627128
245 1 0 $a Epidemics $h [electronic resource] : $b models and data using R / $c by Ottar N. Bjornstad.
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300 $a xv, 387 p. : $b ill., digital ; $c 24 cm.
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505 0 $a 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.
520 $a 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.
650 0 $a Epidemics $x Data processing. $3 3627129
650 0 $a Communicable diseases $x Data processing. $3 1085147
650 0 $a R (Computer program language) $3 784593
650 1 4 $a Biostatistics. $3 1002712
650 2 4 $a Epidemiology. $3 568544
650 2 4 $a Diseases. $3 618693
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