Main description:

Describes the entire data science procedure of how the infectious disease data are collected, curated, visualized, and fed to predictive models, which facilitates effective communication between data sources, scientists, and decision-makers.
Describes practical concepts of infectious disease data and provides particular data science perspectives.
Overview of the unique features and issues of infectious disease data and how they impact epidemic modeling and projection.
Introduces various classes of models and state-of-the-art learning methods to analyze infectious diseases data with valuable insights on how different models and methods could be connected.

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