This codebase is used for a mathematical disease spread model of COVID-19 community spread between ICE detention
centers and surrounding counties or communities. See LICENSE for usage.
The primary usage of this codebase is as a part of the UCLA Law COVID-19 Behind Bars Data Project.
This SEIR model is known as a deterministic, mean-field, compartmental disease model in which a population can be modeled via compartments depending on their current disease state: S (susceptible), E (exposed), I (infectious), R (recovered or removed). Although there are many other types of disease models, the deterministic, compartmental, mean-field model here is one of the primary simple methods.
For more detail, technical documentation for this model can be found here.
The file analysis.py contains example usage for running the model and plotting with real data, including
a snippet used for the plots in the relevent article (link TBD).
The SEIR model code can be found in model.seir_model.
Sample figure of the model fit to real county and detention data, plotted with a prediction of employee case rates:
