Logistic growth model and modified versions for the cumulative number of confirmed cases of COVID-19 in Saudi Arabia

Abstract

In this study, mathematical modeling is applied to investigate the epidemiology of COVID-19 in Saudi Arabia.  The aim was to estimate the cumulative number of infected cases using a logistic growth function and three modified models. The daily cumulative number of confirmed cases was collected from the online COVID-19 dashboard provided by the Ministry of Health. The period covered in this study began from 2^nd March until the 20^th August 2020. Data was fitted to the logistic growth function and three modified versions by using an online tool which implements the least squares estimate method. The results show all models fit significantly. The predictions from all these models are very similar and encouraging. According to the results the growth rate should decline from approximately 21^st Jun 2020 onwards and the maximum number of cumulative confirmed infected cases in Saudi Arabia would be around 324,000 predicting an end to the pandemic by April 2021.