A New Flexible Statistical Model: Simulating and Modeling the Survival Times of COVID-19 Patients in China

Xiaofeng Liu, Zubair Ahmad, Saima K. Khosa, M. Yusuf, Osama Abdulaziz Alamri, Walid Emam and Ahmed Mostafa Khalil

Complexity, 2021, vol. 2021, 1-16

Abstract: The spread of the COVID-19 epidemic, since December 2019, has caused much damage around the world, disturbed every aspect of daily life, and has become a serious health threat. The COVID-19 epidemic impacted nearly 150 countries around the globe between December 2019 and March 2020. Since December 2019, researchers have been trying to develop new suitable statistical models to adequately describe the behavior of this deadly pandemic. In this paper, a flexible statistical model has been proposed that can be used to model the lifetime events associated with this deadly pandemic. The new distribution is derived from the combination of an extended Weibull distribution and a trigonometric strategy referred to as the arcsine-X approach. Hence, the new model may be referred to as the arcsine new flexible extended Weibull model. The proposed model is capable of capturing five different behaviors of the hazard rate function. The model parameters are estimated via the maximum likelihood approach. Furthermore, a Monte Carlo study is conducted to assess the behavior of the estimators. Finally, the applicability of the new model is demonstrated using the data of fifty-three patients taken from a hospital in China.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:6915742

DOI: 10.1155/2021/6915742

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