ABSTRACT
Sumatra Island is the third largest island with the second largest population in Indonesia which has the following eight provinces: Aceh, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu and Lampung. The connectivity of these eight provinces in the economic field is very strong. This encourages high mobility between these provinces. During this Covid-19 pandemic, the high mobility between provinces affects the level of spread of Covid-19 on the island of Sumatra. The central government ordered local governments to implement a community activity restriction program called PPKM. In this article, a study is conducted on the impact of the PKKM program on the spread of Covid 19 on the island of Sumatra, Indonesia. The spread of Covid-19 is modeled using the Susceptible-Infected-Recovered-Death (SIRD) model which considers the mobility factor of the population. The model parameters were estimated using Approximate Bayesian Computation (ABC). The results of the study using this model show that the application of PKKM in several provinces in Sumatra can reduce the level of spread of COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The current outbreak of coronavirus disease (COVID-19) has become a global issue to its quick and widespread over the world, including in Indonesia. More than 60% of positive cases came from Java island, therefore the proposed model focused on six provinces in this area. We developed a discrete-time stochastic epidemic model, such as Spatial-SIRD model, associated with the mobility of people by public transportation (air and land). Model parameters were estimated by fitting the data of October 22nd – 28th, 2020 and November 8th-November 14th, 2020 with the model. At the beginning of the estimation process, we used the coefficient of regression from the observation to estimate the range of parameters. Afterward, the order statistics method was carried out to determine the best parameters so we could forecast the number of infectious of each province. The SIR model was created by applying the regression rate of infection parameters before and after the long holiday from October 28 to November 1, 2020. The effect of this long holiday was that it could increase the number of cases so that there was a difference in the rate of infection. © IEOM Society International.