Modeling COVID-19 mortality data in four countries using odd generalized exponential Kumaraswamy-Inverse exponential distribution

Abstract

This study aims to introduce an optimum model to assess the COVID-19 death rate in Saudi Arabia, Canada, Italy, and Mexico. A novel five-parameter lifetime distribution termed the Odd generalized exponential Kumaraswamy-inverse exponential distribution is presented by combining the Kumaraswamy-inverse exponential distribution with the odd generalized exponential generator. The theoretical features of the new distribution, as well as its reliability functions, moments, and order statistics are investigated. The odd generalized exponential Kumaraswamy-inverse exponential distribution is of special importance since its density has a variety of symmetric and asymmetric forms. Furthermore, the graphs of the hazard rate function exhibit various asymmetrical shapes such as decreasing, increasing, and upside-down bathtub shapes, and inverted J-shapes making The Odd generalized exponential Kumaraswamy-inverse exponential distribution suitable for modeling hazards behaviors more likely to be observed in practical settings like human mortality, and biological applications. The proposed distribution parameters are estimated using the maximum likelihood approach and its effectiveness is demonstrated through both numerical study and applications to four COVID-19 mortality rate data sets. The Odd generalized exponential Kumaraswamy-inverse exponential distribution provides the best fit to COVID-19 data compared to other extended forms of the Kumaraswamy and inverse exponential distributions which may attract wider applications in different fields.