Coronavirus spread modeling

Like many articles online, this tutorial aims at giving some elements of understanding of the spread of Covid-19 pandemic for education purposes. Those 3 examples have been developed by our Malaisian partners from ByteCode.

Example 1 - Covid-19 Cases

This first example is leveraging the new importgui available in Scilab 6.1

Data on Covid 19 cases are available from Johns Hopkins Github https://github.com/CSSEGISandData/COVID-19/blob/master/csse_covid_19_data/csse_covid_19_time_series

The functions xtick2string & ytick2string are available in the IoT module from ByteCode.

Example 2 - Corona Virus Crown

This didactic example demonstrates the capabilities of the Image Processing and Computer Vision Toolbox from our partner ByteCode.

 

Example 3 - SIR Model for Spread of Disease

This dynamic model represents the population under 3 categories:

  1. Susceptible
  2. Infectious
  3. Recovered

 

SIR compartment model

"beta" is the transmission coefficient, "gamma" the recovery factor

For the full specification of the model, visit the wikipedia page on Compartmental models in epidemiology.

We modeled this dynamic behavior as followed with Xcos, based on the epidemy example of the book Modeling and Simulation in Scilab/Scicos:

 

日本人体写真-中国人体艺术