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

Muhammad Ahsan-Ul-Haq; Mukhtar Ahmed; Javeria Zafar; Pedro Luiz Ramos

doi:10.1007/s40745-021-00338-9

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

Ann Data Sci. 2022;9(1):141-152. doi: 10.1007/s40745-021-00338-9. Epub 2021 May 4.

Authors

Muhammad Ahsan-Ul-Haq¹, Mukhtar Ahmed², Javeria Zafar¹, Pedro Luiz Ramos³

Affiliations

¹ College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan.
² School of Statistics, Minhaj University Lahore, Lahore, Pakistan.
³ Institute of Mathematical Science and Computing, University of São Paulo, São Carlos, SP Brazil.

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; Goodness-of-fit; Lifetime distributions.