/python_epidemic_simulation

A crude simulation of an epidemic in Python with pygame visualization

Primary LanguagePythonMIT LicenseMIT

Python Epidemic Simulation

Summary

This is not a scientifically correct or rigorous simulation. It is used for programming learning purposes only!

This is a crude simulation of an edpidemic using Python and pygame.

The simulation consists of a 2-dimensional space in which a configurable number of epidemiological hosts move and transmit a contagious state with variable linear velocity.

Each host exists in a state of unexposed, infected, or recovered.

Demos

No Preventative Measures

No measures

Shelter In Place - Partial Adherence

Shelter in place

Limit Travel - Partial Adherence

Limit travel

Vaccinate, Shelter - Partial Adherence, Variable Drip

Reduce travel

Key simulation concepts:

Basic Laws

The laws below govern the simulation:

  • When initialized, a configured percentage of adherent hosts follow preventative measures.
  • Unless limited by preventative measures, hosts initialize traveling in a random direction in a specified range of speed.
  • If an unexposed and infected host come into contact, the unexposed host becomes infected
  • infected hosts, while contagious, gradually recover over time
  • All hosts survive
  • After a configurable period of time, an infected host becomes recovered
  • recovered hosts are not contagious

Preventative Measures

Several preventative measures can be simulated. A configurable percentage of the population adopting preventative measure can be chosen. Given a percentage of PREVENTATIVE_MEASURE_ADHERENCE, a random sample of the population is chosen to behave accordingly.

Shelter In Place

The SHELTER_IN_PLACE preventative measure sets the velocity of adhering hosts to 0 (permanent)

Vaccination

The VACCINATE_POP preventative measure provides the adhering hosts with a recovery multiplier. The vaccination for any host provides is a random value between 0 and VACCINATION_DRIP, which is added to the recovery constant for any host. VACCINATION_DRIP is intended to simulate the idea that of the percentage of units that adhere, each vaccinates at a variable time. Vaccination effect takes place immediately, even if a host is in unexposed state.

Limit Travel

The LIMIT_TRAVEL preventative measure sets the initial velocity of adhering hosts to 50%

Running

Manually run the simulation

Python 3 is required.

  • Install dependencies:

    • pip install -r requirements.txt

  • Customize parameters

    • Edit any of the provided values in constants.py to change boundary conditions.
    • the PreventativeMeasure.SELECTED array provides the active PreventativeMeasures

  • Run the simulation

    • python universe.py

A Makefile is provided for convenience.

Credits

Thank you to Vue Minh Khue's example, from which I adapted basic 2-dimensional particle interactions for simulating collisions between circular objects in pygame.

Improvements

Improvements, additions, and corrections to the simulation are welcome. Please create a pull request if you would like to contribue.