Persistent Symptoms of Severe and Critical COVID‑19: A Cross‑Sectional Study after more than 120 Days from Disease Onset

Objective: The objective of this study is to assess the prevalence and predictors of symptom persistence associated with severe and critical coronavirus disease-2019 (COVID-19) after more than 120 days from the onset of the disease. Materials and Methods: This is a single-center, cross-sectional study of 125 adults who were admitted to King Khalid University Hospital (Riyadh, Saudi Arabia) with severe and critical COVID-19 between March 4 and December 1, 2020. Telephone interviews were conducted between April 1 and May 31, 2021, to collect data on COVID-19 symptoms persisting after more than 120 days from the onset of the disease. All of the participants had been discharged from the hospital and had resumed their normal lives. Symptoms of COVID-19 that had not been present before the onset of the disease were considered to be persistent if participants confirmed their continued presence at the time of the interview. The impact of chronic disease on persistent symptoms was considered. Results: About 42.4% (53/125) of patients had at least one or more persistent symptoms;27.2% (34/125) had breathlessness, 5.6% (7/125) cough, and 4.8% (6/125) chest pain. These three symptoms had been present from the first presentation. Hair loss was reported by 14.4% (18/125), forgetfulness by 8% (10/125), difficulty in concentrating by 6.4% (8/125), and lack of energy by 4% (5/125). Those had manifested after more than 120 days from the symptom's onset. The major factors in suffering from persistent symptoms were intensive care unit (ICU) admission or/and fever (temperature >38°), or/and diarrhea. There was no correlation between persistent symptoms and chronic diseases. Conclusions: After more than 120 days from the confirmation of severe and critical COVID-19, more than one-third of discharged adults were found to have one or more persistent symptoms. These were mainly associated with the need for ICU admission, fever (temperature >38°), and diarrhea. More care needs to be given to COVID-19 patients in the presence of these factors and prolonged medical care would appear to be essential. © 2023 Journal of Nature and Science of Medicine ;Published by Wolters Kluwer - Medknow.

Vaccine Knowledge of Saudi Parents and Adherence to Immunization Schedule in Saudi Arabia

Objectives: Immunization is one of the best measures to limit the transition of infectious disease and disease severity. Despite that, vaccination programs are frequently affected by a delay in giving vaccines on time or ignorance and avoidance due to various reasons. Our study aimed to estimate the percentage of vaccination delay in our society and assess the level of parents' awareness about vaccine importance;finally, we will shed light on the effect of the coronavirus pandemic on the immunization schedule. Methods: This cross-sectional study was conducted in Dawadmi, Saudi Arabia, from May 2022 to August 2022. Data were collected from parents using a structured questionnaire. Vaccinations were considered delayed if they occurred more than 30 days after the designated time. Parents residing outside Dawadmi or older than 65 years were excluded. Results: Among 393 respondents, the majority were mothers, aged between 30-50 years. Overall, 88% adhered to the immunization schedule. Major reasons for delay were forgetting the vaccination date, unavailability of vaccines, and being busy at work. In comparison to the delayed group, parents who adhered to the immunization schedule were aware about its importance. Conclusions: The majority of parents adhered to the immunization schedule. The most common reason was forgetting the vaccine date. Other reasons were the lack of vaccines in Primary Health Care. The commonly delayed vaccines were the 4 and 9-months vaccines. The pandemic affected adherence to vaccination schedules.

EFL Vocabulary Acquisition through Reading Courses during Covid-19

This work aimed to explain how students at the College of Languages and Translation (CLT) managed to learn vocabulary through reading courses during the Covid-19 Pandemic. To this end, the researcher adopted a descriptive approach and collected the data mainly through a questionnaire. The sample included students of English at CLT, Imam Mohammad Ibn Saud Islamic University (IMSIU). Teachers and students found themselves forced to shift from traditional to virtual classes, so they resorted to another type of teaching that generally relied on online instruction. The findings showed that there were some difficulties initially, moving from traditional to virtual classes, where the students had to use their previous skills to acclimatize to the shift. The findings also showed that the teaching tools were not adequately available to fit the purpose of vocabulary learning. The researcher suggested using modern vocabulary apps such as Vocab Genius, WordUp, Vocabology, Vocabulary Builder, and Vocabulary App. © 2022 JJMLL Publishers/Yarmouk University. All Rights Reserved.

Efficacy Of Hydroxychloroquine Or Chloroquine As Anti-COVID-19, A Systematic Review

Chloroquine (CQ) and hydroxychloroquine (HCQ) have shown mixed effects in clinical studies of COVID-19 disease. We aimed to comprehensively assess how CQ and HCQ affected COVID-19 patient outcomes. Method(s): We combed through a wide range of archives, preprints, and grey literature up through the date of November 17, 2022. Using a random-effects model, we combined only the mortality estimates that had their effects accounted for. We summed up how CQ or HCQ affected viral clearance, ICU admission, and the need for mechanical ventilation. All of the databases MEDLINE, CINAHL, EMBASE, Web of Science, Google scholar, LILACS, and Scopus were searched electronically from their inceptions in the 1950s without regard to publication date or language availability up until November 2022. In total, 6 articles were used for the evaluation. Patients who are subjected to be treated with Chloroquine or Hydroxychloroquine against Corona viral infections Six randomised clinical trials (RCTs) met the criteria, therefore these findings can be considered. There is some evidence to show that HCQ is effective in lowering short-term mortality in COVID-19 hospitalised patients or the risk of hospitalisation in COVID-19 outpatients. Finally, these results should be taken into account in the follow-up care of patients who will be admitted for COVID-19 treatmen and may help in their clinical management. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

An assessment of the effectiveness of distance education based on student satisfaction at the University of Tabuk

Background: During the COVID-19 crisis, distance learning programs had to be used to maintain the continuity of education and the University of Tabuk (UT) was one of the universities that chose to use this method as an alternative to traditional education. It was, therefore, necessary to verify the quality of the educational outcomes of students while studying under these conditions. Our study aimed to measure the effectiveness of distance learning based on students' satisfaction with the quality of its outcomes in their academic achievement. Aim: To ensure the effectiveness of distance education by Assessment the students satisfaction in Tabuk University The study also will put recommendations to improve the student's satisfaction and the overall system in the distance education. Method: This study used a quantitative research approach. It used a descriptive research design in that the researchers described the effectiveness of distance education based on the students' levels of satisfaction. The participants in this study were students of Tabuk University from multiple disciplines.

Modelling to Covid-19 Data in Saudi Arabia Using: A New Xgamma Model

In this paper we introduce a new lifetime model called the Topp Leone xgamma distribution, a two-parameter distribution with a lot of versatilities. Among other things, we obtain quantiles, moments, stochastic ordering, and probability weighted moments. The suggested distribution's parameters are determined using the maximum likelihood estimation approach. For right-censored data, modified chi-square goodness-of-fit tests are developed. A complete simulation analysis is carried out to highlight the benefits of the proposed model and to confirm the goodness-of-fit test. The current study's theoretical results are applied to data from COVID-19 data in KSA.

Statistical Analysis of Covid-19 Pandemic in Saudi Arabia

COVID-19, a new coronavirus illness, initially reported in China in December 2019 has spread around the world. COVID-19 coronavirus has evolved into a worldwide health hazard, quickly infecting humans. Controlling the outbreak is crucial, and scientists have continued to look at potential treatments. COVID-19 can also be defeated with supportive treatment and hospital critical care services. COVID-19 might be avoided using statistical forecasting techniques. The purpose of this study is to create a forecasting model that could be used to predict the spread of COVID-19 in Saudi Arabia. An autoregressive (AR) integrated moving average (ARIMA) model was used to anticipate the number of deaths in three key Saudi Arabian regions: Riyadh, Eastern Region, and Qassim. According to our findings, the number of fatalities in Riyadh and Eastern Region was expected to decrease in August (2021), while the deaths in Qassim were expected to decrease in July (2021).

A New Model to Detect COVID-19 Coughing and Breathing Sound Symptoms Classification from CQT and Mel Spectrogram Image Representation using Deep Learning

Deep Learning is a relatively new Artificial Intelligence technique that has shown to be extremely effective in a variety of fields. Image categorization and also the identification of artefacts in images are being employed in visual recognition. The goal of this study is to recognize COVID-19 artefacts like cough and also breath noises in signals from realworld situations. The suggested strategy considers two major steps. The first step is a signal-to-image translation that is aided by the Constant-Q Transform (CQT) and a Mel-scale spectrogram method. Next, nine deep transfer models (GoogleNet, ResNet18/34/50/100/101, SqueezeNet, MobileNetv2, and NasNetmobile) are used to extract and also categorise features. The digital audio signal will be represented by the recorded voice. The CQT will transform a time-domain audio input to a frequency-domain signal. To produce a spectrogram, the frequency will really be converted to a log scale as well as the colour dimension will be converted to decibels. To construct a Mel spectrogram, the spectrogram will indeed be translated onto a Mel scale. The dataset contains information from over 1,600 people from all over the world (1185 men as well as 415 women). The suggested DL model takes as input the CQT as well as Melscale spectrograms derived from the breathing and coughing tones of patients diagnosed using the coswara-combined dataset. With the better classification performance employing cough sound CQT and a Mel-spectrogram image, the current proposal outperformed the other nine CNN networks. For patients diagnosed, the accuracy, sensitivity, as well as specificity were 98.9%, 97.3%, and 98.1%, respectively. The Resnet18 is the most reliable network for symptomatic patients using cough and breath sounds. When applied to the Coswara dataset, we discovered that the suggested model's accuracy (98.7%) outperforms the state-of-the-art models (85.6%, 72.9%, 87.1%, and 91.4%) according to the SGDM optimizer. Finally, the method as a main screening tool to try and identify COVID-19 by of disease transmission.

Awareness, knowledge, attitudes, and practices before the second wave of the COVID-19 pandemic in Saudi Arabia.

OBJECTIVE: The COVID-19 outbreak was first reported in Wuhan City, China in early December 2019. It was declared a pandemic by WHO in March 2020. This study aimed at assessing the knowledge, awareness, and attitudes of the general population in Saudi Arabia towards COVID-19, as well as its adherence to preventive measures and its willingness to take the vaccine. PATIENTS AND METHODS: This descriptive cross-sectional study involved an online sample of 7,188 participants (from five regions of Saudi Arabia) who completed a self-administered online-based questionnaire. They were recruited from 23 November 2020 to 29 November 2020 based on the nonprobability convenience sampling method. The self-administered questionnaire comprised four main sections: gathering information about participants' demographics, knowledge and awareness of COVID-19, participants' practices (hygiene and other) against infection, and vaccine acceptability. RESULTS: More than half of the study participants were knowledgeable about COVID-19. The mean scores were 10.4 (SD=3.44, range: 0-18 - with high scores indicating better knowledge or awareness) for knowledge and 6.1 (SD=2.26, range: 0-11) for awareness, indicating a need for more educational campaigns to improve the level of knowledge and awareness among the Saudi Arabian population about COVID-19. The mean score for attitude was 5 (SD=1.67, range: 0-8 - from 0=very pessimistic to 8=very optimistic), indicating moderate optimism. As for practices, the mean score was 7.8 (SD=1.57, range: 0-10), indicating good practices to prevent or control infection. Concerning acceptability of the COVID-19 vaccine, 63.8% of the participants agreed to take the vaccine if it was proven to be 95% effective. CONCLUSIONS: The findings of this study can help us designing effective measures against COVID-19 infections. Our results highlight the best practices adopted by the Saudi Arabian population, as well as those areas requiring improvement, including knowledge, attitudes, and practices against this disease.

Therapeutic potential of peptidomimetics as antiviral agents: short review on recent progress

The tug of war between viruses and humans existed for millions of years. The defensive mechanisms and rapid evolution of these viruses have made it difficult for researchers to progress in antiviral drug discovery. Therefore, this paper is intended to give an overview on reported drug targets via an insight on viral pathogenesis and the peptidomimetic-drugs reported till date against three most globally prevalent and deadly viruses: SARS-CoV-2, HIV, and HCV. The reason for selective illustration in this review is attributed to the proven record of antecedents reporting wide scope of peptidomimetics in development of antiviral drugs highlighting the ease of rapid mobilization of peptidomimetics for treatment of emerging viruses.

On Odd Perks-G Class of Distributions: Properties, Regression Model, Discretization, Bayesian and Non-Bayesian Estimation, and Applications

In this paper, we present a new univariate flexible generator of distributions, namely, the odd Perks-G class. Some special models in this class are introduced. The quantile function (QFUN), ordinary and incomplete moments (MOMs), generating function (GFUN), moments of residual and reversed residual lifetimes (RLT), and four different types of entropy are all structural aspects of the proposed family that hold for any baseline model. Maximum likelihood (ML) and maximum product spacing (MPS) estimates of the model parameters are given. Bayesian estimates of the model parameters are obtained. We also present a novel log-location-scale regression model based on the odd Perks–Weibull distribution. Due to the significance of the odd Perks-G family and the survival discretization method, both are used to introduce the discrete odd Perks-G family, a novel discrete distribution class. Real-world data sets are used to emphasize the importance and applicability of the proposed models. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Estimation method of mixture distribution and modeling of COVID-19 pandemic

The mathematical characteristics of the mixture of Lindley model with 2-component (2-CMLM) are discussed. In this paper, we investigate both the practical and theoretical aspects of the 2-CMLM. We investigate several statistical features of the mixed model like probability generating function, cumulants, characteristic function, factorial moment generating function, mean time to failure, Mills Ratio, mean residual life. The density, hazard rate functions, mean, coefficient of variation, skewness, and kurtosis are all shown graphically. Furthermore, we use appropriate approaches such as maximum likelihood, least square and weighted least square methods to estimate the pertinent parameters of the mixture model. We use a simulation study to assess the performance of suggested methods. Eventually, modelling COVID-19 patient data demonstrates the effectiveness and utility of the 2-CMLM. The proposed model outperformed the two component mixture of exponential model as well as two component mixture of Weibull model in practical applications, indicating that it is a good candidate distribution for modelling COVID-19 and other related data sets. © 2022 the Author(s), licensee AIMS Press.

Improving the Virtual Educational Platforms for the Deaf and Dumb under the Covid-19 Pandemic Circumstances

Arabic Sign Language (ArSL) is a language of communication between deaf dumb people in Arab countries. This study focuses on establishing a real-time speech conversion service into ArSL by 3D animation videos, to facilitate the learning process in virtual educational platforms. This study to help the deaf dumb students in distant learning under the Covid-19 pandemic. This study applied on the TEAMS platform. A database was created containing more than 550 ArSL videos from the Al-tarjuman application and connected it with the TEAMS platform. A Python was used to link the System units. After studying some related works that were concerned with the language of the deaf dumb, we found that some studies do not support real-time translation, has lack Arabic sign language translation, has limited DB, resulting in a low level of system performance, and use of high-cost devices such as gesture motion sensors 'Kinect and Leap Motion'. As future work, we will increase the words in the DB to improve the results. We advise researchers to contribute by working on merging the videos retrieved from the DB to make an integrated serial video. Also, adding a syntactic analysis stage to extract the sentence structure. © 2022 IEEE.

Public Perceptions Concerning Community Pharmacy Services in Jouf Region, Kingdom of Saudi Arabia in Reference to COVID-19 Pandemic

Aim/Background: The present study was aimed at investigating the public perceptions about extended services by community pharmacists in Jouf region of Saudi Arabia during COVID-19 pandemic. Design: Institutional based cross sectional prospective survey. The sample size was calculated by an online sample size calculator named Raosoft®️. The calculated sample for this study was 945 with a 5% error margin, confidence interval of 95%, the population size fixed at 200000. Study instrument: A 34-item self-administered questionnaire developed by an in-depth literature review and approved by the subject experts (professor, associate professor, assistant professor and lecturer) after suggestions and modification in the questionnaire, pretested to a small sample of thirty participants. The reliability scale applied to determine the alpha value of pretested sample. Results: Majority of the participants 83.6% were females, the frequency (1-3 times) of visit is highest (52.4%) for the participants with the main reason for visiting a particular pharmacy is close location (52.3%). The participants had positive perceptions towards the role of the pharmacist regarding feeling comfortable asking advice from the pharmacist, getting comprehensive consultation, having sufficient discussion time, communication with the pharmacist, getting answers for their questions, medication labeling and information about medication interactions and side effects. However, the participants had negative attitudes towards the medications prices and the diagnostic services such as lab tests provided by the community pharmacists. Public are of the opinion that the pharmacists are well aware of the COVID-19 pandemic playing a good role in counselling about the COVID-19, without any change in their behavior in the current situation. Conclusion: The study showed that there was positive public perceptions about the role of the community pharmacists and the practices and services offered by them. The study recommended increasing the public awareness about the role of the community pharmacists and the range of the services offered in the community pharmacies.

Covid-19 and its impact on education, social life, and mental health among medical students in Saudi Arabia

Background: As COVID-19 pandemic reached Saudi Arabia, emergency disaster protocols were implemented to control the spread of the virus, which resulted in limitations on all public movements, including the dosure of educational institutes. This study aimed to evaluate the impact of COVID-19 on education, social life, and mental health among medical students during COVID-19 restrictions. Methods: A cross-sectional study with a sample size of 1253 medical students from various universities in different regions in Saudi Arabia was conducted. Survey data were obtained from social media platforms using web-based self-administered questionnaires. Results: This study revealed large acceptance of online classes (64.1% of students), however, students reported less opportunities to both collaborate with colleagues, and ask questions during online dasses. Improved student's education skills including time management, self-monitoring for academic progress, access and using different types of information sources, and multitasking was demonstrated. Regarding effect of COVID-19 on students' social and habitual life, 52.9% reported satisfaction with utilization of their time, however, 52% stated socially not well connected, 36.3% never engage in physical activity, 42.4% reported increased body weight, and only 25% were able to sleep as usual. Social media platforms were at the fore front in using to overcome loneliness feeling and communicate with others. Conclusions: Positive impact of COVID-19 on education was demonstrated in terms of the large acceptance of online dasses and improvement of education skills. However, negative impact on social life was established including poor social communication, disturbed sleep habits and poor engagement in physical activity.

The challenges faced by Pharm.D students in online learning due to Covid-19 pandemic and its impact on their mental health in the Northern border Region of Saudi Arabia

Objective: The purpose of the survey was to gather information from students on their learning preferences prior to the COVID-19 outbreak, barriers to online education during the pandemic, and the mental and psychological effects of COVID-19 on students. Method: Applying Google Forms, a cross-sectional pharmacy student-targeted online questionnaire designed to develop. In order to ensure that only pharmacy students responded, an introductory opening inquiry of the program name used to select out non-pharmacy students. Following that, these few demographic questions are asked to the participant's present institution and program year in which the participants currently in. Results: A total 260 pharmacy students received the survey, out of total 186 replies were received from professional pharmacy students, resulting in a response rate of around 71.5%. Almost half of the students (94%) chose traditional face-to-face training, while 32.8% preferred a combination of online and face-to-face instruction, and only 16.7% liked online instruction alone. The difficulties to online education during the COVID-19 pandemic outbreak show that, Issues with in-person communication (23.7%), pandemic-related anxiety and stress (22%), time management (19.9%), experience in online education (16.7%). The majority of respondents (87%) intended to incorporate online knowledge gained during the COVID-19 pandemic outbreak into their teaching/learning techniques. During the COVID-19 epidemic, we discovered that practically all students were plagued by symptoms of sadness, anxiety, tension, and poor sleep quality, with the majority suffering from significant depression (31.2 %). Conclusion: This study concludes that most of the students are in favor of incorporation and applications of online learning experiences in teaching/learning practices garnered during pandemic. Furthermore, the majority of students had changed their behavior as a result of coronavirus, while nearly half of those polled experiencing an increase in anxiety and tension.

Corona Virus Disease 2019: Origin, Transmission, Diagnosis, Vaccine and Treatment: A Review Article

Corona virus is considered as the major pathogen that primarily threats the human respiratory system. Corona virus has been known to cause a systemic infection, which means affecting the entire body in its specific host. Moreover, natural recombination makes some of them capable to adapt greatly and jump the species barrier, causing pandemics or epidemics. Previous corona virus outbreaks that have been characterized as pathogens, caused a serious problem to public health including the Middle East respiratory syndrome (MERS)-CoV, and the severe acute respiratory syndrome (SARS)-CoV. In December 2019, the first case was reported. The emergence of Novel Corona virus named as Severe Acute Respiratory Syndrome Corona virus 2 (SARS-CoV-2), which is considered the causative agent of Corona Virus Disease 2019 (COVID-19). The genome of SARS-CoV-2 is 29.9 kb. In SARS-CoV-2 the conventional methods were used to detect any viral infectious which mainly depends on the computed tomography, serology and molecular tests. The commonly molecular technique used to detect the presence of SARS-CoV-2 is reverse-transcription polymerase chain reaction (RTPCR). However, there are several drugs available that have high antiviral activity against viruses especial SARS-CoV-2 as camostat mesylate and umifenovir. The mainly route of transmission is person-to-person contact with either symptomatic or asymptomatic patients. ORF8 is an accessory protein that considers one of the more rapidly evolving proteins in beta corona virus. There are many different functions of SARS-CoV-2 ORF8.

COVID-19 with stroke - Clinical characteristics and outcomes at King Abdulaziz Medical City, MNGHA, Riyadh, KSA

Objective: To present single center experience of stroke in COVID-19 patients from a tertiary care hospital in Saudi Arabia. Background: Coronavirus Disease-2019 (COVID-19) has affected millions of people across the world and has been associated with increased the risk of stroke. We report clinical characteristics and outcome of COVID-19 patients with stroke. Design/Methods: This is a single center, case series of COVID-19 patients with stroke presenting to King Abdulaziz Medical City, MNGHA, Riyadh, Saudi Arabia. Charts of stroke patients with COVID-19 admitted between March 1 and July 31, 2020 were reviewed. Results: We identified 12 patients with COVID presenting with stroke, of whom 10 (83%) were male with mean age of 57± 12 (range 32 - 82) years. Six (50%) patients were Saudi. Majority of patients 9 (75%) arrived to emergency room after 6 hours of stroke onset. Ten (83%) patients had mild to moderate stroke at presentation (NIHSS 0 - 15). Hemorrhagic stroke was seen in 5 (42%) patients, whereas 7 (58%) had ischemic stroke. Among patients with hemorrhagic stroke, multifocal hemorrhage was seen in 3 (60%), while 2 (40%) had deep basal ganglia hemorrhage. Hypertension was present in 10 (83%) patients and diabetes mellitus in 6 (50%). Median length of hospitalization was 17 (8 - 34) days, with 7 (63%) patients discharged home with good functional status, (mRS 0-2). Mortality was seen among 2 (29%) patients with ischemic stroke and one with hemorrhagic stroke. The mean age of patients who died was 67±13 compared to alive was 53±11years. Conclusions: In conclusion, ischemic stroke was more common among patients with COVID-19 and had higher mortality compared to patients with hemorrhagic stroke. The patient who died on an average were 10 years elder to others. Having diabetes, hypertension and higher severity of stroke at presentation were associated with poor outcome.

Pattern ofstroke admissions and management at king abdulaziz medical city, MNGHA, Riyadh, KSA during the COVID-19 pandemic

Objective: To describe the patterns of stroke admission and management during the period of COVID-19 pandemic at a tertiary care hospital in Saudi Arabia. Background: COVID-19 has affected access to healthcare. Due to travel restrictions and fear of COVID-19 infection, people avoided visiting hospitals during COVID-19 pandemic. Design/Methods: After IRB approval, admission data, clinical characteristics, and management of patients admitted to King Abdulaziz Medical City, MNGHA, Riyadh, KSA were analyzed. Results: A total of 105 patients were admitted between March 1, 2020 to June 30, 2020, with average of 26 admissions per month. In 2019, average admissions were 44 per month. Of the 105 patients, 69 (66%) were men. Mean age was 59.6 +/-13.3 years, 85 (81%) were Saudis. Majority, 62 (60%) of the patients presented after 6 hours of symptoms onset. Ischemic stroke or TIA was seen in 89 (85%) patients. Large vessel disease was seen in 25 (28%) patients, small vessel disease in 26 (29%), whereas stroke was of undetermined etiology in 23 (26%). Hypertension was the commonest vascular risk factors in 84 (80%) patients, followed by diabetes and ischemic heart disease in 65 (62%) and 18 (17%) respectively. Only 6 (6%) patients tested positive for COVID-19, of whom 5 were non-Saudis (p=<0.001). Stroke code was activated on 40 (38%), with mean time of 9.4 minutes. Intravenous thrombolysis and endovascular thrombectomy was performed in 5 (5%) patients each. Prior to this period, the rate of intravenous thrombolysis was about 12%. Mean door-to-needle (DTN) time was 63 +/- 22 minutes, whereas in 2019, it was 55 minutes. Conclusions: During peak months of COVID-19 in Saudi Arabia, monthly stroke admissions decreased by almost 40%, most patients presented after 6 hours of symptoms onset, fewer patients underwent intravenous thrombolysis or endovascular thrombectomy. There was slight increase in mean DTN time during this period.

Weighted generalized quasi lindley distribution: Different methods of estimation, applications for covid-19 and engineering data

Recently, a new lifetime distribution known as a generalized Quasi Lindley distribution (GQLD) is suggested. In this paper, we modified the GQLD and suggested a two parameters lifetime distribution called as a weighted generalized Quasi Lindley distribution (WGQLD). The main mathematical properties of the WGQLD including the moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis, stochastic ordering, median deviation, harmonic mean, and reliability functions are derived. The model parameters are estimated by using the ordinary least squares, weighted least squares, maximum likelihood, maximum product of spacing’s, Anderson-Darling and Cramer-von-Mises methods. The performances of the proposed estimators are compared based on numerical calculations for various values of the distribution parameters and sample sizes in terms of the mean squared error (MSE) and estimated values (Es). To demonstrate the applicability of the new model, four applications of various real data sets consist of the infected cases in Covid-19 in Algeria and Saudi Arabia, carbon fibers and rain fall are analyzed for illustration. It turns out that the WGQLD is empirically better than the other competing distributions considered in this study. © 2021 the Author(s), licensee AIMS Press.