We use a generative discrete Markov chain to model the progress of an infectious disease in a population. It assumes that everyone within a certain radius of an infected person is susceptible, and there is a certain probability of being infected. The input parameters are the locations of all individuals, radius of infection, probability of being infected on a given day, how long an infected person is infectious. You can seed the simulator with a the number and positions of currently infected individuals. The data directory contains household information for Memphis.
TODO:
- Layer information about severity
- Add testing regime
- Add ability to estimate parameters from observed data