The exhaustive information about non-communicable diseases associated with COVID-19 and severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) are getting easier to find in the literature. H...

Background: Accessibility to the immense collection of studies on noncommunicable diseases related to coronavirus disease of 2019 (COVID‐ 19) and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is an immediate focus of researchers. However, there is a scarcity of information about chronic obstructed pulmonary disease (COPD), which is associated with a high rate of infection in COVID‐19 patients. Moreover, by combining the effects of the SARS‐CoV‐2 on COPD patients, we may be able to overcome formidable obstacles factors, and diagnosis influencers. Materials and Methods: A retrospective study of 280 patients was conducted at DHQ Hospital Muzaffargarh in Punjab, Pakistan. Negative binomial regression describes the risk of fixed successive variables. The association is described by the Cox proportional hazard model and the model coefficient is determined through log‐likelihood observation. Patients with COPD had their survival and mortality plotted on Kaplan–Meier curves. Results: The increased risk of death in COPD patients was due to the effects of variables such as cough, lower respiratory tract infection (LRTI), tuberculosis (TB), and body‐aches being 1.369, 0.693, 0.170, and 0.217 times higher at (95% confidence interval [CI]: 0.747–1.992), (95% CI: 0.231–1.156), (95% CI: 0.008–0.332), and (95% CI: −0.07 to 0.440) while it decreased 0.396 in normal condition. Conclusion: We found that the symptoms of COPD (cough, LRTI, TB, and bodyaches) are statistically significant in patients who were most infected by SARS‐CoV‐2. KEYWORDS COPD, COVID‐19, Cox proportional hazard model and negative binomial distribution, SARS‐CoV‐2

This study focuses on implementing a group acceptance sampling plan (GASP) for simultaneous inspection of objects with complex lifespan patterns described by the odd exponential logarithmic (OEL) Fr
echet distribution. The inspiration from the proposed model stems from the challenges posed by the objects that exhibited right-skewed, j-shaped, reversed j-shaped and nearly symmetric densities, along with decreasing and increasing hazard rates. A mathematical function is derived to identify key points in the distribution, crucial for designing the inspection process based on factors like testing duration and acceptable risk levels. Performance is assessed across various quality levels, with a simulation study providing insights into parameter changes. The results are clarified via visual representations. The minimum ratios of actual to expected lifespan at specific risk levels, utilizing real-world data to validate the approach are computed. Finally, a comparison is driven in the quest of highlighting the efficacy and versatility of the proposed acceptance sampling plan (ASP) under the inverse log-logistic and generalized exponential (GE) models.