Author:
Ding Xiafei,Ma Yue,Tang Jiachen
Abstract
Novel tuberculosis pneumonia, caused by COVID-19, has become the most serious epidemic in the world today. In times of rampant epidemics, many countries adopt policies that restrict civil liberties, and predictive models can provide advice on the best time to predict when restrictions will begin and end, as well as provide data to support other epidemic prevention policies. In this paper, the authors will use the existing literature as well as research findings to predict the prevalence of COVID-19. This paper firstly analyzes and optimizes the models developed in the literature, mainly involving Markov Chain models. The data summarized in the literature are also analyzed and integrated, and many studies combine models other than Markov Chain for combination. Finally, the evaluation methods for each model are summarized.
Publisher
Darcy & Roy Press Co. Ltd.
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