Disease Risk Visualization: A Grid-based Simulation

Posted on November 2, 2014 by


How worried should we be about Ebola in the US?  In order to answer that question for myself, I created a simple simulation that can be used to visualize the spread and mortality of various diseases.


These simulations are for visualization purposes only.  The conditions of the simulation do not represent real world conditions, and therefore the results cannot be assumed to predict real disease outcomes.  I am not an epidemiologist or medical doctor.


This simulation models the spread and mortality of each disease based on two factors:

  1. The Basic Reproduction Number (BRN): “In epidemiology the basic reproduction number of an infection an be thought of as the number of cases one case generates on average over the course of its infectious period, in an otherwise uninfected population.” — wikipedia
  2. The Case Fatality Risk (CFR): “In epidemiology, a case fatality risk (CFR) is the proportion of deaths within a designated population of “cases” (people with a medical condition), over the course of the disease.” — wikipedia

The simulation first initializes a 100 x 100 population of cells where each cell represents one healthy person.  We then randomly infect 10 people in the grid with the disease.  The simulator iterates until the disease runs its course through the population. It each iteration we check at each cell to see if a neighboring cell/person is infected, if so, that cell will become infected with a probability based on the BRN.  Once infected, the person will die with a probability equal to the CFR.

Ebola West Africa 2014 (as of Nov 1 2014)

Ebola US 2014 (as of Nov 1 2014)

HIV Africa

Source: STDAware.com/geo/oklahoma/okc.

SARS 2003