This paper presents a model for COVID19 in Mexico City. The data analyzed were considered from the appearance of the first case in Mexico until July 2021. In this first approximation the states considered were Susceptible, Infected, Hospitalized, Intensive Care Unit, Intubated, and Dead. As a consequence of the lack of coronavirus testing, the number of infected and dead people is underestimated, although the results obtained give a good approximation to the evolution of the pandemic in Mexico City. The model is based on a discrete-time Markov chain considering data provided by the Mexican government, the main objective is to estimate the transient probabilities from one state to another for the Mexico City case.
翻译:本文介绍了墨西哥城COVID19的模型,分析的数据是从墨西哥第一个病例出现到2021年7月为止。在第一个近似点中,所考虑的各州是可感知、感染、住院、重症护理、插管和死亡。由于缺乏科罗纳病毒检测,受感染和死亡的人数被低估了,尽管获得的结果对墨西哥城流行病的演变提供了很好的近似。考虑到墨西哥政府提供的数据,该模型以离散时间的Markov链为基础,主要目标是估计墨西哥城病例从一个州到另一个州的过渡概率。