Fitting an Epidemiological Model to Transmission Dynamics of COVID-19
Abstract
A rapid increase in daily new cases was reported in the world from February 19 to April 3, 2020. In this study, a susceptible-infected-recovered-dead (SIRD) was developed to analyse the dynamics of the global spread of COVID-19 during the above-mentioned period of time. The values of the model parameters fitted the reported data were estimated by minimizing the sum of squared errors using the Levenberg-Marquardt optimization algorithm. A time-dependent infection rate was considered. The set of differential equations in the model was solved using the fourth order Runge-Kutta method. It was observed that a time-dependent parameter gives a better fit to a dynamic data. Based on the fitted model, the average value of basic reproduction number (\textit{R0}) for COVID-19 trasmission was estimated to be 2.8 which shows that the spread of COVID-19 disease in the world was growing exponentially. This may indicate that the control measures implemented worldwide could not decrease the COVID-19 transmission.
Keywords
COVID-19, Epidemic, SIRD model, Model parameters, Reported data, Worldwide
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