Abstract
During the abrupt outbreak of the COVID-19 pandemic, the public health system of most of the world’s nations has been tested. However, it is the concern of governments and other responsible entities to provide the correct statistics and figures to take any practicable necessary steps such as allocation of the requisite quarantine operations, calculation of the needed number of places in hospitals, determination of the extent of personal security, and determining the degree of isolation of infectious people, among others. Where the statistical literature supposes that a model governs every real phenomenon, once we know the model, we can evaluate the dilemma. Therefore, in this article, we compare the COVID-19 pandemic dynamics of two neighboring Arabic countries, Egypt and Saudi Arabia, to provide a framework to arrange appropriate quarantine activities. A new generalized family of distributions is developed to provide the best description of COVID-19 daily cases and data on daily deaths in Egypt and Saudi Arabia. Some of the mathematical properties of the proposed family are studied.
Highlights
In the past few months, the COVID-19 pandemic has dominated the world and the international health community
After computing the model parameters’ values, we can show how the proposed model provides the best description of COVID-19 daily cases data and COVID19 daily deaths data
We considered the graphical sketching of the estimated pdf (Epdf), the estimated cdf (Ecdf), the probability–probability (PP) plot, and the quantile–quantile (QQ) plot
Summary
In the past few months, the COVID-19 pandemic has dominated the world and the international health community. Zhao et al [4] compared the COVID-19 pandemic dynamics of two neighboring Asian countries, Iran and Pakistan, and developed a new statistical model describing data on COVID-19 daily deaths in Iran and Pakistan. Mathematics 2021, 9, 827 Mathematics 2021, 9, 827 continuous distributions were constructed by expanding other common continuo2usofd1is3tributions; see, for example, Alzaatreh and Famoye [14], Al-Babtain et al [15], Jayakumar and Mathew [16], Cordeiro et al [17], Oluyede et al [18], Mansour and Mahdy [19], dMifafeurreynat aept parlo. Poisson distribution, which with zero truncated Poisson is a compound distribution distribution This depends ddiiffffeerreennttmmooddeellsshhaavveebbeeeennbbuuiillttttooaaccccoommpplliisshhtthhiissmmiissssiioonn..PPooiissssoonnddiissttrriibbuuttiioonniissoonneeooff tthhee mmoosstt ffaammoouuss mmooddeellss tthhaatt aallssoo pprroovviiddeess aa ffaammiillyy ooff ddiissttrriibbuuttiioonn. −1 k ρ 1 − e−α − ρ k g(x)exp(−(k + 1)αG(x))
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