A numerical study of COVID-19 epidemic model with vaccination and diffusion.

The coronavirus infectious disease (or COVID-19) is a severe respiratory illness. Although the infection incidence decreased significantly, still it remains a major panic for human health and the global economy. The spatial movement of the population from one region to another remains one of the major causes of the spread of the infection. In the literature, most of the COVID-19 models have been constructed with only temporal effects. In this paper, a vaccinated spatio-temporal COVID-19 mathematical model is developed to study the impact of vaccines and other interventions on the disease dynamics in a spatially heterogeneous environment. Initially, some of the basic mathematical properties including existence, uniqueness, positivity, and boundedness of the diffusive vaccinated models are analyzed. The model equilibria and the basic reproductive number are presented. Further, based upon the uniform and non-uniform initial conditions, the spatio-temporal COVID-19 mathematical model is solved numerically using finite difference operator-splitting scheme. Furthermore, detailed simulation results are presented in order to visualize the impact of vaccination and other model key parameters with and without diffusion on the pandemic incidence. The obtained results reveal that the suggested intervention with diffusion has a significant impact on the disease dynamics and its control.

Knowledge, Perceptions, and Readiness of Telepharmacy among Hospital Pharmacists in Saudi Arabia.

Telepharmacy is a technology-based service that provides promoted services such as counseling, medication administration and compounding, drug therapy monitoring, and prescription review. It is unclear whether hospital pharmacists possess the necessary knowledge, attitudes, and willingness to practice telepharmacy. The current study sought to investigate Saudi Arabian hospital pharmacists' understanding, attitudes, and level of preparedness for telepharmacy services. A total of 411 pharmacists responded to the survey. Only 43.33% of the respondents agreed that telepharmacy is available in Saudi Arabia and 36.67% of the respondents agreed that patients in rural areas can have more medication access and information via telepharmacy. Only 29.33% of pharmacists agreed that telepharmacy improves patient medication adherence, and about 34.00% of the pharmacists agreed that telepharmacy saves patients money and time by eliminating the need for them to travel to healthcare facilities. This research found that hospital pharmacists were unsure of their level of knowledge, their attitude toward telepharmacy, and their willingness to incorporate it into their future pharmacy practices. To ensure that tomorrow's pharmacists have the skills they need to provide telepharmacy services, telepharmacy practice models must be incorporated into the educational programs that prepare them.

Non-SARS Non-MERS Human Coronaviruses: Clinical Characteristics and Outcome.

Human coronaviruses (HCoVs) have become evident sources of human respiratory infections with new emerging HCoVs as a significant cause of morbidity and mortality. The common four coronaviruses (229E, HKU1, NL63, and OC43) are known to cause respiratory illness in humans, but their clinical impact is poorly described in the literature. We analyzed the data of all patients who tested positive for at least one of the four HCoVs from October 2015 to January 2020 in a tertiary care center. HCoVs were detected in 1062 specimens, with an incidence rate of 1.01%, out of all documented respiratory illnesses. Detection of these viruses was reported sporadically throughout the years, with a peak of occurrence during winter seasons. OC43 had the highest incidence (53.7%), followed by NL63 (21.9%), HKU1 (12.6%), and 229E (11.8%). Most of these infections were community-acquired, with symptoms of both upper and lower respiratory tract. Co-detection with other viruses were observed, mostly with rhinovirus. 229E was the most frequent (26.4%) HCoV in patients requiring intensive care, while NL63 and 229E were the most common in patients requiring invasive ventilation. The highest 30-day mortality rate was observed in patients infected with 229E (6.4%). HCoVs are common circulating pathogens that have been present for decades, with 229E being the most virulent in this study cohort.

Factors Associated with Length of Hospital Stay among COVID-19 Patients in Saudi Arabia: A Retrospective Study during the First Pandemic Wave.

The COVID-19 pandemic severely affected healthcare systems and tested their preparedness. To date, the length of hospital stay (LoHS) and its factors among COVID-19 patients has not been thoroughly studied. Moreover, it is essential to identify the features of these patients. Adult COVID-19 patients in Saudi Arabia with complete electronic medical records and who were hospitalised for >1 day between 1 May 2020 and 30 July 2020 at one of two hospitals were considered for this retrospective cohort study. Descriptive statistics and multivariate generalized linear models were performed using the data. Of the patients, 34% were ≥50 years old and 80.14% were female. More than 70% had mild-to-moderate symptoms; 45% had either diabetes or hypertension. The median LoHS was 7.00 days (IQR: 3-11). Patients who were females, had either critical or severe disease, were on mechanical ventilation, had diabetes, and administered ceftriaxone had significantly longer LoHS (p < 0.05). Patients administered zinc sulphate had significantly shorter LoHS (p = 0.0008). During the first pandemic wave, COVID-19 patients were hospitalised for 7 days. Healthcare professionals should pay more attention to women, patients with diabetes, and those with severe or critical symptoms. Unnecessary use of ceftriaxone should be minimised, and zinc sulphate can be administered.

Comparison of the post-marketing safety profile between influenza and COVID-19 vaccines: An analysis of the vaccine adverse event reporting system.

The global coronavirus disease (COVID-19) epidemic can be partially managed by vaccines; however, the public must be informed about the safety of COVID-19 vaccines to avoid hesitancy. Therefore, it is important to know the safety profile of the COVID-19 vaccine by comparison to that of a well-known vaccine, such as the influenza vaccine. Hence, this retrospective descriptive study was conducted to evaluate and compare the number of adverse effects (AEs) reported to the Vaccine Adverse Event Reporting System (VAERS) for both COVID-19 and influenza vaccines, identify the most common AEs of each vaccine, and compare the frequency and outcomes of using COVID-19 and influenza vaccines in the U.S. population. Surveillance reports from 1st December 2020 to 8th October 2021 of both vaccines were retrieved from the U.S. VAERS. A total of 544,025 and 15,871 reports of post-COVID-19 and - influenza vaccine AEs were reported to the VAERS, respectively. Females reported > 58% and nearly 70% of influenza - and COVID-19 vaccine-associated AEs, respectively. The estimated incidence rates of AEs associated with COVID-19 and influenza vaccines in the U.S. were 1.36 and 0.12 per 1,000 persons, respectively. The incidence of AEs was higher among COVID-19 vaccine recipients than that among influenza vaccine recipients. COVID-19 vaccine recipients have a two-fold higher risk of mortality and life-threatening events than influenza vaccine recipients. However, most of the reported AEs were similar between the two vaccines in terms of symptoms.

Mathematical assessment of constant and time-dependent control measures on the dynamics of the novel coronavirus: An application of optimal control theory.

The coronavirus infectious disease (COVID-19) is a novel respiratory disease reported in 2019 in China. The COVID-19 is one of the deadliest pandemics in history due to its high mortality rate in a short period. Many approaches have been adopted for disease minimization and eradication. In this paper, we studied the impact of various constant and time-dependent variable control measures coupled with vaccination on the dynamics of COVID-19. The optimal control theory is used to optimize the model and set an effective control intervention for the infection. Initially, we formulate the mathematical epidemic model for the COVID-19 without variable controls. The model basic mathematical assessment is presented. The nonlinear least-square procedure is utilized to parameterize the model from actual cases reported in Pakistan. A well-known technique based on statistical tools known as the Latin-hypercube sampling approach (LHS) coupled with the partial rank correlation coefficient (PRCC) is applied to present the model global sensitivity analysis. Based on global sensitivity analysis, the COVID-19 vaccine model is reformulated to obtain a control problem by introducing three time dependent control variables for isolation, vaccine efficacy and treatment enhancement represented by u 1 ( t ) , u 2 ( t ) and u 3 ( t ) , respectively. The necessary optimality conditions of the control problem are derived via the optimal control theory. Finally, the simulation results are depicted with and without variable controls using the well-known Runge-Kutta numerical scheme. The simulation results revealed that time-dependent control measures play a vital role in disease eradication.

Modeling the dynamics of coronavirus with super-spreader class: A fractal-fractional approach.

Super-spreaders of the novel coronavirus disease (or COVID-19) are those with greater potential for disease transmission to infect other people. Understanding and isolating the super-spreaders are important for controlling the COVID-19 incidence as well as future infectious disease outbreaks. Many scientific evidences can be found in the literature on reporting and impact of super-spreaders and super-spreading events on the COVID-19 dynamics. This paper deals with the formulation and simulation of a new epidemic model addressing the dynamics of COVID-19 with the presence of super-spreader individuals. In the first step, we formulate the model using classical integer order nonlinear differential system composed of six equations. The individuals responsible for the disease transmission are further categorized into three sub-classes, i.e., the symptomatic, super-spreader and asymptomatic. The model is parameterized using the actual infected cases reported in the kingdom of Saudi Arabia in order to enhance the biological suitability of the study. Moreover, to analyze the impact of memory index, we extend the model to fractional case using the well-known Caputo-Fabrizio derivative. By making use of the Picard-Lindelöf theorem and fixed point approach, we establish the existence and uniqueness criteria for the fractional-order model. Furthermore, we applied the novel fractal-fractional operator in Caputo-Fabrizio sense to obtain a more generalized model. Finally, to simulate the models in both fractional and fractal-fractional cases, efficient iterative schemes are utilized in order to present the impact of the fractional and fractal orders coupled with the key parameters (including transmission rate due to super-spreaders) on the pandemic peaks.

Mathematical assessment of the dynamics of novel coronavirus infection with treatment: A fractional study.

In this paper, a mathematical model is formulated to study the transmission dynamics of the novel coronavirus infection under the effect of treatment. The compartmental model is firstly formulated using a system of nonlinear ordinary differential equations. Then, with the help of Caputo operator, the model is reformulated in order to obtain deeper insights into disease dynamics. The basic mathematical features of the time fractional model are rigorously presented. The nonlinear least square procedure is implemented in order to parameterize the model using COVID-19 cumulative cases in Saudi Arabia for the selected time period. The important threshold parameter called the basic reproduction number is evaluated based on the estimated parameters and is found R 0 ≈ 1.60 . The fractional Lyapunov approach is used to prove the global stability of the model around the disease free equilibrium point. Moreover, the model in Caputo sense is solved numerically via an efficient numerical scheme known as the fractional Adamas-Bashforth-Molten approach. Finally, the model is simulated to present the graphical impact of memory index and various intervention strategies such as social-distancing, disinfection of the virus from environment and treatment rate on the pandemic peaks. This study emphasizes the important role of various scenarios in these intervention strategies in curtailing the burden of COVID-19.

Perception of Parents Towards COVID-19 Vaccine for Children in Saudi Population.

Background Coronavirus disease 2019 (COVID-19) is a contagious disease that is caused by severe acute respiratory coronavirus 2 (SARS-CoV-2). With the rapid spread of this pandemic, vaccination has been a breakthrough solution. At the time of conducting the study, COVID-19 vaccines were only approved for adults 18 years and older. Therefore, the aim of the study was to assess the parents' likelihood of vaccinating their children once the recommendation for pediatric vaccination is established. Methods This was a cross-sectional study in which a self-administered survey was distributed to all parents visiting National Guard primary healthcare centers in Riyadh, Saudi Arabia. The questionnaires were distributed to parents attending primary care clinics. Data collected in the questionnaire include demographics (gender, marital status, educational level, and age), questions assessing parental perception towards the COVID-19 vaccine, and willingness to offer the vaccine to their children. Results A total of 333 respondents completed the survey with a response rate of 83.3%. Half of the participants were males and the other half were females with the majority (45.6%) aged between 31 and 40 years old. In terms of parental acceptability of vaccinating their children against COVID-19, 53.7% of the parents were willing to vaccinate their children as opposed to 27% who were reluctant to do so. Of those who refused, 97.5% and 96.6% cited lack of information and evidence, respectively, as the most common reasons for not accepting COVID-19 vaccine. We have found that age of the parents, especially those 31-40 years old, age of their children, especially 4-12 years old, and previous acceptance of the seasonal influenza vaccine were significantly associated with higher parental acceptability of COVID-19 vaccine. In contrast, gender, marital status and educational level were not statistically significant factors. Conclusion As COVID-19 spread globally and made people's lives in danger, vaccination became a highly important measure to halt the spread of the disease. Parents are now given the choice of protecting their beloved children from COVID-19 infection and its possible complications. Based on our findings, we noticed that majority of parents are going to vaccinate their children. In addition, some certain age groups of parents and children were significantly associated with decreased vaccine hesitancy to take the COVID-19 vaccine.