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

Muhammad Ahsan-Ul-HaqMukhtar AhmedJaveria ZafarPedro Luiz Ramos
Published in: Annals of data science (2021)
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 R 2 goodness-of-fit measures. Results indicate that Weibull distribution provides generally the best-fit probability distribution.
Keyphrases
  • coronavirus disease
  • sars cov
  • respiratory syndrome coronavirus
  • healthcare
  • mental health
  • physical activity
  • machine learning
  • electronic health record
  • health information
  • big data
  • climate change