Stationary Distribution Markov Chain for COVID-19 Pandemic

https://doi.org/10.47194/ijgor.v1i2.25

Authors

  • Audi Achmad University of Padjadjaran
  • Mahrudinda Mahrudinda University of Padjadjaran
  • Budi Ruchjana University of Padjadjaran
  • Sudradjat Supian University of Padjadjaran

Keywords:

COVID-19, Stochastic Processes, Stationary Distribution Markov Chain

Abstract

Coronavirus disease (COVID-19) is a new disease found in the late 2019. The first case was reported on December 31, 2019 in Wuhan, China and spreading all over the countries. The disease was quickly spread to all over the countries. There are 206.900 cases confirmed by March 18, 2020 causing 8.272 death. It was predicted that the number of confirmed cases will continue to increase. On January 30, 2020, WHO declared this as pandemic for the 6th time ever since the swine influenza. There are a lot of researchers which discuss pandemic spreading caused by virus with mathematical modelling. In this paper, we discuss a long-term prediction over the COVID-19 spreading using stationary distribution markov chain. The goal is to analyze the prediction of infected people in long-term by analyzing the COVID-19 daily cases in an observation interval. By analyzing the daily cases of COVID-19 in Indonesia from March 2nd, 2020 until November 1st, 2020, result shown that 53.91% of probability that the COVID-19 daily case will incline in long-term, 44.86% of chance will decline, and 1.23% of chance will stagnant.

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Published

2020-02-10

Issue

Vol. 1 No. 2 (2020): International Journal of Global Operations Research (IJGOR), May 2020

Section

Articles
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