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The paper presents a novel statistical approach for analyzing the daily coronavirus case and fatality statistics. The survival discretization method was used to generate a two-parameter discrete distribution. The resulting distribution is referred to as the "Discrete Marshall–Olkin Length Biased Exponential (DMOLBE) distribution". Because of the varied forms of its probability mass and failure rate functions, the DMOLBE distribution is adaptable. We calculated the mean and variance, skewness, kurtosis, dispersion index, hazard and survival functions, and second failure rate function for the suggested distribution. The DI index demonstrates that the proposed model can represent both over-dispersed and under-dispersed data sets. We estimated the parameters of the DMOLBE distribution. The behavior of ML estimates is checked via a comprehensive simulation study. The behavior of Bayesian estimates is checked by generating 10,000 iterations of Markov chain Monte Carlo techniques, plotting the trace, and checking the proposed distribution. From simulation studies, it was observed that the bias and mean square error decreased with an increase in sample size. To show the importance and flexibility of DMOLBE distribution using two data sets about deaths due to coronavirus in China and Pakistan are analyzed. The DMOLBE distribution provides a better fit than some important discrete models namely the discrete Burr-XII, discrete Bilal, discrete Burr-Hatke, discrete Rayleigh distribution, and Poisson distributions. We conclude that the new proposed distribution works well in analyzing these data sets. The data sets used in the paper was collected from 2020 year. [ABSTRACT FROM AUTHOR]

The present work is considered to investigate the sources, concentration, and composition of polycyclic aromatic hydrocarbons (PAHs) and associated health risk assessment of road dust in Riyadh City, Saudi Arabia. The study region included an urban area, strongly affected by traffic, a bare and an industrial area. A total of 50 locations were selected for sampling and 16 different PAHs were determined. The concentration of PAHs in road dust and their estimated lifetime average daily dose (LADD) for adults (human) ranged from 0.01 to 126 ng g−1 and 1950 to 16,010 mg kg−1 day−1, respectively. The ADDing was calculated separately for children (>6), teenagers (6−12), and adults (>12) for all PAHs with each collected sample. Moreover, the average daily exposure dose by ingestion (ADDing) and average daily exposure dose by dermal absorption (ADDder) were more in children (<6 years) as compared to teenagers (6−12 years) and adults (>12 years). Likewise, total equivalency factor based on BaP (TEQBaP) calculations pointed out that PAHs having more benzene rings or having high molecular weight showed high TEQBaP as compared to low molecular weight PAHs. The data revealed that the children population is at high risk for asthma, respiratory and cardiovascular diseases, and immunity suppression as compared to adults in the particular area of investigated region. These outcomes of this study can be used to deliver significant policy guidelines concerning habitants of the area for possible measures for controlling PAHs contamination in Riyadh City to protect human health and to ensure environmental sustainability.