Modeling of COVID-19 Epidemic Growth Curve in Indonesia - Muhammad Fajar; Wahyudi Wahyudi (Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya, 2021)
Aim of this study is to make parametric modeling of the COVID-19 epidemic growth curve so that the maximum value and time at that point can be obtained from the cumulative cases of COVID-19. The data used in this study is the cumulative number of positive confirmed cases of COVID-19 from https://covid19.go.id/. The method used in this study is fitting data with the Logistic and Gompertz models. Result of this study are (1) the Logistic and Gompertz models are very fit in modeling the COVID-19 epidemic growth curve, indicated from the value of R2 (coefficient of determination) which reaches more than 99%; (2) From the Logistics model it is obtained that the estimated amount of the maximum cumulative case at the end of the COVID-19 epidemic is 7,714 positive confirmed cases, achieved in about 82 days (May 22, 2020) from Mar 2, 2020, when the first positive COVID-19 case was announced by the government; and (3) From the Gompertz model, it is obtained that the estimated maximum cumulative case at the end of the COVID-19 epidemic is 33,975 positive confirmed cases, achieved in about 152 days (Jul 30, 2020) from Mar 2, 2020. The results of this study can be used as input to the government to take steps in controlling the spread of COVID-19.