BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Epidemics: Models and Data Using R (Use R!)

Epidemics: Models and Data Using R (Use R!)

Epidemics: Models and Data Using R (Use R!)
Stock photo: cover may vary

Epidemics: Models and Data Using R (Use R!)

by Bj�rnstad, Ottar N

Add to wish list
  • New
New

Description

USA Edition . New. Brand New! Fast Delivery US Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Ask the seller a question Add to wish list
A$232.18
A$6.46 Delivery within USA
Standard delivery: 5 to 10 days
More delivery options
Ships from XLANCEBOOKS L.L.C. (Wyoming, United States)

Details

About XLANCEBOOKS L.L.C. Wyoming, United States

Biblio member since 2022

USA EDITION, 30 day return guarantee,

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from XLANCEBOOKS L.L.C.

Reader reviews for Epidemics: Models and Data Using R (Use R!)

From the publisher

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 richhistory 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.

From the rear cover

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, dynamicshas 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.

About the author

Ottar Bjornstad researches population dynamics of epidemiological and ecological outbreaks. Focal systems includes human infections like measles, whooping cough, rubella, SARS-CoV-2 and influenza; animal infections like rabies, hantavirus and distemper; and outbreaks of various insects of biomedical and agricultural concern. He has expertise in statistical and computational approaches to the study of spatiotemporal dynamics, including the development of a suite of statistical methods for the analysis of spatial and temporal data as implemented in various R packages. Dr. Bjornstad is a Distinguished Professor of Entomology and Biology holds the J. Lloyd & Dorothy Foehr Huck Chair of Epidemiology at the Pennsylvania State University and is an elected fellow of the Norwegian Academy of Science and Letters, American Association for the Advancement of Sciences and the Ecological Society of America.
tracking-