HonorsCapstone

Description:

This project is a cross-section of multiple disciplines in mathematics as well as computer science. In particular, it incorporates differential equations and data analysis to create a model, in the Python coding language, to estimate the spread of COVID-19. The model used for the simulation is a self-generated SIRDSV deterministic compartmental model. I converted the SIR model to fit the current context with COVID-19. The data is found from multiple sources and is manipulated to fit in the model. The main program, as a whole, gathers the data, manipulates the data, checks the accuracy of the model, estimates the spread of COVID-19 in the next thirty days, and then finally estimates the spread of COVID-19 in one hundred days with a logarithmic decreased change in stringency/contact rate. The model proves to be accurate in most cases and only partially breaks down over a long period of time and with changing rates and probabilities.