Discrete Erlang-2 distribution and its application to leukemia and COVID-19

Via the survival discretization method, this research revealed a novel discrete one-parameter distribution known as the discrete Erlang-2 distribution (DE2). The new distribution has numerous surprising improvements over many conventional discrete distributions, particularly when analyzing excessively dispersed count data. Moments and moments-generating functions, a few descriptive measures (central tendency and dispersion), monotonicity of the probability mass function, and the hazard rate function are just a few of the statistical aspects of the postulated distribution that have been developed. The single parameter of the DE2 distribution was estimated via the maximum likelihood technique. Real-world datasets, leukemia and COVID-19, were applied to analyze the effectiveness of the recommended distribution. © 2023 the Author(s), licensee AIMS Press.

A novel nonparametric mixture model for the detection pattern of COVID-19 on Diamond Princess cruise

The outbreak of COVID-19 on the Diamond Princess cruise ship has attracted much attention. Motivated by the PCR testing data on the Diamond Princess, we propose a novel cure mixture nonparametric model to investigate the detection pattern. It combines a logistic regression for the probability of susceptible subjects with a nonparametric distribution for the detection of infected individuals. Maximum likelihood estimators are proposed. The resulting estimators are shown to be consistent and asymptotically normal. Simulation studies demonstrate that the proposed approach is appropriate for practical use. Finally, we apply the proposed method to PCR testing data on the Diamond Princess to show its practical utility.

Classical and Bayesian Inference for the Inverse Lomax Distribution Under Adaptive Progressive Type-II Censored Data with COVID-19 Application

In this paper, we consider the classical and the Bayesian inferences for unknown parameters of inverse Lomax distribution and their corresponding survival characteristics under the adaptive progressive type-II censoring scheme. In the classical setup, first we obtain the maximum likelihood estimates for the unknown shape parameter of the distribution and its corresponding survival characteristics. Further, we consider symmetric and asymmetric loss functions for the estimation of shape parameter and its corresponding survival characteristics under the Bayesian paradigm. The performances of various derived estimators were recorded using Markov chain Monte Carlo simulation technique for different sample sizes. Finally,a COVID-19 mortality data set is provided to illustrate the computation of various estimators. © 2022 River Publishers.

Logistic regression analysis for studying the impact of home quarantine on psychological health during COVID-19 in Saudi Arabia

During the Coronavirus disease (COVID-19) period, the world witnessed a complete closure of all aspects of social life, and people must go for home quarantine to limit the spread of Corona virus disease. This study aims to use multiple logistic regression model (MLR) to identify the impact of home quarantine on psychological stability of individuals and its relationship to various factors. Maximum likelihood is used to estimate the parameters of MLR. Hosmer-Lemeshow method and Wald statistic are calculated to assess the significance of MLR. Cross sectional study was carried out and MLR was fitted to the collected data. This study applied to 846 residents of Makkah region during the COVID-19 period. High percentage of respondents felt psychological stability during the period of home quarantine. Logistic regression model showed that education level and psychological disorders during home quarantine were the significant risk factors for psychological stability during COVID-19. In addition, the positive impact of the home quarantine that people became more attention to their health, more interested to self-development and the families become close to each other. On the other hand, people on private employee or unemployed had psychological disorders more than others due to home quarantine and decrease their income. (C) 2022 THE AUTHOR. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.

Using Social Media Campaigns to Activate Electronic Volunteering Platforms during COVID-19 Pandemic

We design and implement an advertising campaign using social media to encourage people to volunteer on online platforms as well as identify the effectiveness of online marketing in informing people and encouraging them to participate in volunteer platforms. It is shown that the expected turnout of young people to volunteer work through social networking platforms and awareness of the epidemic reduced its prevalence rate. © 2022, Natural Sciences Publishing. All rights reserved.