Computational Differentiation Used for Epidemiology: Prediction and Approximation

by Devin Pratt

Submitted : Spring 2020

This is an analysis of the calculus-based computational model of infection rate in populations known as the SIR model.  Addressing the inherent inaccuracy of using assumptions and approximations in the modeling process, the question of whether this model is viable to be used as a basis for predicting and responding to infections diseases is posed.  Over the course of the research it has been found that the accuracy of SIR models is wanting and prone to discrepancy resulting in the model not being a viable source of information to respond to epidemic-scale disease.  Further, recommendations to amend this model and limit the amount of assumption required is posed as well as suggesting continuing the progress of derivative models of infection rate to benefit humanity.

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