(untitled) (Journal of Environmental Microbiology and Toxicology, 2020)
In this paper, we present different growth models such as Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in fitting and analyzing the epidemic trend of COVID-19 in the form of total number of infection cases of SARS-CoV-2 in Brazil as of 15th of July 2020. The MMF model was found to be the best model with the highest adjusted R2 value with the lowest RMSE value. The Accuracy and Bias Factors values were close to unity (1.0). The parameters obtained from the MMF model include maximum growth rate (log) of 0.026 (95% CI from 0.024 to 0.028), curve constant (d) that affects the inflection point of 1.094 (95% CI from 1.024 to 1.165) and maximal total number of cases (ymax) of 66,527,316 (95% CI from 35,156,044 to 143,548,943). The MMF predicted that the total number of cases for Brazil on the coming 15th of August and 15th of September 2020 will be 2,993,850 (95% CI of 3,407,196 to 2,630,649) and 4,676,829 (95% CI of 5,553,936 to 3,938,240), respectively. The predictive ability of the model utilized in this study is a powerful tool for epidemiologist to monitor and assess the severity of COVID-19 in Brazil in months to come. However, as with any other model, these values need to be taken with caution due to the unpredictability of the COVID-19 situation locally and globally.