Modeling of COVID-19 Cases in Pakistan Using Lifetime Probability Distributions

Muhammad Ahsan-ul-Haq (), Mukhtar Ahmed (), Javeria Zafar () and Pedro Luiz Ramos ()
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Muhammad Ahsan-ul-Haq: University of the Punjab
Mukhtar Ahmed: Minhaj University Lahore
Javeria Zafar: University of the Punjab
Pedro Luiz Ramos: University of São Paulo

Annals of Data Science, 2022, vol. 9, issue 1, No 8, 152 pages

Abstract: Abstract The Coronavirus Disease (COVID-19) is a respiratory disease that caused a large number of deaths all over the world since its outbreak. The World Health Organization (WHO) has declared the outbreak a global pandemic. The understanding of the random process related to the behavior infection of COVID-19 is an important health and economic problem. In the proposed study, we analyze the frequency of daily confirmed cases of COVID-19 using different two-parameter lifetime probability distributions. We consider the data from the period of March 11, 2020, to July 25, 2020, of Pakistan. We consider nine lifetime probability distributions for the analysis purpose and the selection of best fit was carried out using log-likelihood, AIC, BIC, RMSE, and R2 goodness-of-fit measures. Results indicate that Weibull distribution provides generally the best-fit probability distribution.

Keywords: Coronavirus; Daily confirmed cases; Data analysis; Lifetime distributions; Goodness-of-fit (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s40745-021-00338-9

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