Stationary distribution Markov chain for Covid-19 pandemic

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, World Health Organization (WHO) declared this as Public Health Emergency of International Concern (PHEIC). 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 aim of this paper 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 worldwide from December 31, 2019 until April 16, 2020, result shows that 61.43% of probability that the Covid-19 daily case will incline in long-term, 32.14% of chance will decline, and 6.43% of chance will stagnant.