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 COVID-19's rapidly spread in Indonesia is a serious concern for government. Various government policies, such as large-scale social restrictions, which is called as PSBB, and the imposing restrictions on community activities, be called as PPKM, have been applied to slow the spread of COVID-19. These policies were supposed to control people activities in many areas, especially that will invite the crowd happening. In this paper, the control charts be explored to obtain the overview of the daily new COVID-19 cases number, which is considered as a production process. The proportion of positive COVID-19 cases be observed and monitored using P-control chart. The data used is from the specimen COVID-19 test in DKI Jakarta Province, since April 2020 to January 2021. It is obtained that the process of daily new COVID-19 cases number has not been statistically controlled. It is detected some mean shifts of proportion in some point of times. Several findings indicate an upward trend, suggesting that the proportion of positive cases COVID-19 is rising. The public's conduct in Jakarta has served as a model for the government in designing policies to tackle the spread of Covid-19. However, due to the high mobility of Jakarta residents and its lack of consistency in the region, the COVID-19 process still remained out of control. © 2022 American Institute of Physics Inc.. All rights reserved.
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.
ABSTRACT
The movement of positive people Coronavirus Disease that was discovered in 2019 (Covid-19), written 2019-nCoV, from one location to another has a great opportunity to transmit the virus to more people. High-risk locations for transmission of the virus are public transportations, one of which is the train, because many people take turns in or together inside. One of the policies of the government is physical distancing, then followed by large-scale social restrictions. The keys to the policy are distance and movement. The most famous transportation used for the movement of people among provinces on Java is train. Here a Generalized Space Time Autoregressive (GSTAR) model is applied to forecast infected case of 2019-nCoV for 6 provinces in Java. The specialty of this model is the weight matrix as a tool to see spatial dependence. Here, the modified Inverse Distance Weight matrix is proposed as a combination of the population ratio factor with the average distance of an inter-provincial train on the island of Java. The GSTAR model (1; 1) can capture the pattern of daily cases increase in 2019-nCoV, evidenced by representative results, especially in East Java, where the increase in cases is strongly influenced by other provinces on the island of Java. Based on the Mean Squares of Residuals, it is obtained that the modified matrix gives better result in both estimating (in-sample) and forecasting (out-sample) compare with the ordinary matrix.