Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Practical Data Analysis

You're reading from  Practical Data Analysis

Product type Book
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Pages 360 pages
Edition 1st Edition
Languages
Author (1):
Hector Cuesta Hector Cuesta
Profile icon Hector Cuesta
Toc

Table of Contents (24) Chapters close

Practical Data Analysis
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started 2. Working with Data 3. Data Visualization 4. Text Classification 5. Similarity-based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Disease with Cellular Automata 10. Working with Social Graphs 11. Sentiment Analysis of Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with IPython and Wakari Setting Up the Infrastructure Index

The epidemic models


When we want to describe how a pathogen or a disease is spread into a population, we need to create a model using mathematical, statistical, or computational tools. The most common model used in the epidemiology is SIR (susceptible, infected, and recovered) model, which was formulated in the paper A Contribution to the Mathematical Theory of Epidemics by McKendrick and Kermack published in 1927.

In the models presented in this chapter, we assume a closed population (without births or deaths) and that the demographics and socio-economic variables do not affect the spread of the disease.

The SIR model

The SIR epidemiological model describes the course of an infectious disease, as we can see in the following figure. Starting with a susceptible population (S), which comes into contact with an infected population (I), where the individual remains infected and once the infection period has passed, the individual is then in the recovered state (R):

In this chapter we will use two...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}