Predictive Mathematical Modelling of the Total Number of COVID-19 Cases for the Kingdom of Saudi Arabia (Journal of Environmental Microbiology and Toxicology, 2020)
Throughout this article, we discuss different development models such as Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang throughout fitting and evaluating the COVID-19 disease pattern in the context of the cumulative number of SARS-CoV-2 infection cases in the Kingdom of Saudi Arabia as of July 15th, 2020. The MMF model with the biggest adjusted R2 and the lowest RMSE values established to be the best. The Accuracy, as well as the Bias Factors, are found to have values close to unity (1.0). The parameters generated from the MMF model include the maximum growth rate (log) of 0.03 (95% CI from 0.030 to 0.036), curve constant (d) that affects the inflection point of 1.100 (95% CI from 1.029 to 1.171) and the highest possible number of cases (ymax) of 2,485,187 (95% CI from 1,468,970 to 4,204,419). The MMF model projected that COVID-19 will end in about 567 days (95% CI of 483 to 714) days from 15th of July 2020 centred on the lower bound of the 95% CI from the calculated maximum number of total cases (ymax).  The MMF assumed that the total number of cases for the Kingdom of Saudi Arabia on 15 August and 15 September 2020 would be 384,258 (95 per cent CI from 368,567 to 400,618) and 508,412 (95 per cent CI from 482,797 to 535,387) respectively.  The predictive ability of the model used in this study is an effective instrument for epidemiologists to track and assess the severity of COVID-19 in the Kingdom of Saudi Arabia over the coming months. Nevertheless, like any other model, due to the unpredictability of the COVID-19 situation locally and globally, these values must be taken with caution.
Keywords: SARS-CoV-2, COVID-19, Total number of cases, growth curve, MMF model