Predictive Mathematical Modelling of the Total Number of COVID-19 Cases for Indonesia (Journal of Environmental Microbiology and Toxicology, 2020)
In the current article, we showcase various growth models like Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in the fitting and analysis of the COVID-19 epidemic trend as of 15 July 2020 in Indonesia in the form of the total number of SARS-CoV-2 infections. The MMF model was proved as the suitable model with the highest adjusted R2 value and lowest RMSE value. The Accuracy and Bias Factors values were near to unity (1.0). The parameters obtained from the MMF model consist of maximum growth rate (Âµm) (log) of 0.025 (95% CI from 0.020 to 0.028), curve constant (ï¤) that affects the inflection point of 0.770 (95% CI from 0.691 to 0.849), lower asymptote value (ï¢) of 0.297 (95% CI from 0.229 to 0.365) and maximal total number of cases (ymax) of 4,634,469 (95% CI from 1,967,886 to 15,417,005). The MMF forecast that the total number of cases in Indonesia on the coming 15th of August and 15th of September 2020 will be 113,179 (95% CI of 103,477 to 123,790) and 154,235 (95% CI of 136,542 to 174,220), respectively. The predictive capability of the model applied in this paper is likely a reliable tool for epidemiologist to monitor and evaluate the severity of COVID-19 death cases in Indonesia in few months to come. Undoubtedly, the models will be reexamined after every few months in the event unwarranted phenomena lead to an exponential increase or wave of new infection.
Keywords: COVID-19, total infection, pandemic, mathematical model, MMF