European Parliament Library

Data science for infectious disease data analytics, an introduction with R., Lily Wang

Summary
"Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered coronavirus disease (COVID-19). The primary emphasis of this book will be the data science procedure in epidemiological studies, including data wrangling, visualization, interpretation, predictive modeling, and inference, which is of immense importance due to increasingly diverse and nonexperimental data across a wide range of fields. The knowledge and skills readers gain from this book are also transferable to other areas, such as public health, business analytics, environmental studies, or spatio-temporal data visualization and analysis in general. Aimed at readers with an undergraduate knowledge of mathematics and statistics, this book is an ideal introduction to the development and implementation of data science in epidemiology"-- Provided by publisher
Table Of Contents
1 Introduction -- 2 Data Wrangling -- 3 Data Visualization with R Package "ggplot2" -- 4 Interactive Visualization -- 5 R Shiny -- 6 Interactive Geospatial Visualization -- 7 Epidemic Modeling -- 8 Compartment Models -- 9 Time Series Analysis of Infectious Disease Data -- 10 Regression Methods -- 11 Neural Networks -- 12 Hybrid Models
Language
eng
Literary Form
non fiction
Copyright
Physical Description
1 online resource (420 pages)
Specific Material Designation
remote
Form Of Item
online
Isbn
9781000643060

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