One of the goals of data analysis is to understand the system we are studying, and modeling is the natural way to understand a real-world phenomenon. A model is always a simplified version of the real thing. However, through modeling and simulation, we can try scenarios that are hard to reproduce, or are expensive or dangerous. We can then perform analysis, define thresholds, and provide the information needed to make decisions. In this chapter, we will model an infectious disease outbreak through a Cellular Automaton (CA) simulation implemented in JavaScript using D3.js. Finally, we will contrast the results of the simulation with the classical Ordinary Differential Equations (ODE).
This chapter will cover the following topics:
Introduction to epidemiology
The epidemic models
Modeling with cellular automatas
Implementing a SIRS model in CA with D3js