This paper shows that the generalized logistic distribution model is derived from the SIR model under certain conditions. In the SIR model, there are uncertainties in predicting the final values for the number of infected population and the infectious parameter. However, by utilizing the information obtained from the generalized logistic distribution model, we can perform the SIR numerical computation more stably and more accurately. Applications to SARS and COVID-19 using this combined method are also introduced.
A Relationship Between SIR Model and Generalized Logistic Distribution with Applications to SARS and COVID-19