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Alexandria Engineering Journal ; 61(12):11787-11802, 2022.
Article in English | Web of Science | ID: covidwho-1914097


The fractional derivative is an advanced category of mathematics for real-life problems. This work focus on the investigation of 2nd wave of the Corona virus in India. We develop a time fractional order COVID-19 model with effects of the disease which consist of a system of fractional differential equations. The fractional-order COVID-19 model is investigated with AtanganaBaleanu-Caputo fractional derivative. Also, the deterministic mathematical model for the Omicron effect is investigated with different fractional parameters. The fractional-order system is analyzed qualitatively as well as verified sensitivity analysis. Fixed point theory is used to prove the existence and uniqueness of the fractional-order model. Analyzed the model locally as well as globally using Lyapunov first and second derivative. Boundedness and positive unique solutions are verified for the fractional-order model of infection of disease. The concept of fixed point theory is used to interrogate the problem and confine the solution. Solutions are derived to investigate the influence of fractional operator which shows the impact of the disease on society. Simulation has been made to understand the behavior of the virus.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University This is an open access article under the CC BY license ( 4.0/).

Ibnosina J. Med. Biomed. Sci. ; 13(3):127-135, 2021.
Article in English | Web of Science | ID: covidwho-1458916


Background: In March 2020, Saudi Arabia (KSA) experienced a coronavirus disease 2019 (COVID-19) outbreak. The mitigation strategy aimed to reduce both the impact on vulnerable groups and the risk of admission to the intensive care unit (ICU). Risk factors, such as sequential organ failure, comorbidities, ventilation, and mortality, have not been described in different settings of care. Materials and Methods: A multicenter, retrospective chart review of 220 adults with COVID-19 admitted to the ICU included demographics and ICU admission factors (e.g., quick sequential organ failure assessment (qSOFA) score, ventilator status, comorbidities, days from laboratory confirmation to ICU admission, and days from hospitalization to ICU admission). Regression was utilized to identify predictors of need for mechanical ventilation (MV) and mortality in ICU patients. Results: ICU admission, COVID-19 hospital mortality, and ventilator-associated mortality rates were 26.5%, 44%, and 30.5%, respectively. The mean patients' age was 30 years. Across four cities, Jeddah patients were at the highest risk of MV (<0.001). Within the 1st day of hospitalization, without lymphocytopenia, non-Saudi patients with a qSOFA score of 2 and 3 were at the highest risk of ventilation (odds ratio [OR], 3.9;95% confidence interval [CI], 1.72-8.66;OR, 11.4;95% CI, 2.35-55.47;and OR, 6.1;95% CI, 1.0-37.33, respectively). Moreover, within the same period of hospital stay, mechanically-ventilated patients with a qSOFA score of 3 who received antiviral medications were significantly at the higher risk of death (OR, 2.8.4;95% CI, 1.44-5.64;OR, 13.1;95% CI, 1.23-39.68;and OR, 2.2;95% CI, 1.14-4.14, respectively). Conclusions: The 1st day of hospitalization, along with an assessment of the dyspnea status using the qSOFA score, is the window of opportunity for minimizing ICU admission risk. Neither lymphocytopenia nor comorbidities are associated with the risk of mechanical ventilation. Factors were also discussed. Reviews are needed on the indications for the use of antiviral agents, intubation, and ventilation in hospitalized patients. </p>