sir_ode
sir_ode,
a Python code which
sets up the ordinary differential equations (ODE) which
simulate the spread of a disease
using the Susceptible/Infected/Recovered (SIR) model.
We consider the evolution of a disease epidemic in a population of
N people.
We assume that the patients can be classified as Susceptible, Infected or
Recovering, with the properties that:

Susceptible: A patient who has never been infected with the
disease. A susceptible patient can become infected, with
an infectivity coefficient alpha.

Infected: A patient who was susceptible, and has now contracted
the disease. Infected patients can spread the disease to susceptible
patients. An infected patient can become recovered, with recovery
coefficient beta.

Recovered: A patient who was infectious, but has recovered.
Such patients cannot contract the disease, and cannot transmit it.
A recovered patient can become susceptible, with
susceptibility coefficient gamma.
Licensing:
The computer code and data files described and made available on this web page
are distributed under
the GNU LGPL license.
Languages:
sir_ode is available in
a MATLAB version and
an Octave version and
a Python version..
Related Data and codes:
python_ode,
Python codes which
sets up various systems of ordinary differential equations (ODE).
Reference:

Dianne OLeary,
Models of Infection: Person to Person,
Computing in Science and Engineering,
Volume 6, Number 1, January/February 2004.

Dianne OLeary,
Scientific Computing with Case Studies,
SIAM, 2008,
ISBN13: 9780898716665,
LC: QA401.O44.
Source Code:
Last revised on 29 October 2020.