# 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  ### Shelter In Place - Partial Adherence  ### Limit Travel - Partial Adherence  ### Vaccinate, Shelter - Partial Adherence, Variable Drip  ## 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](https://github.com/khuevu/pygames/tree/master/bouncingball), 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. My contribution for Git learning task