What Risk Factors to Cause Long COVID and Its Impact on Patient Survival Outcomes when Combined with the Effect from Organ Transplantation in the Acute COVID (preprint)

Background Coronavirus disease 2019 (COVID-19) in solid organ transplant (SOT) patients is associated with more severe outcomes than non-immunosuppressed hosts. However, exactly which risk factors cause Long COVID in acute COVID cases remains unknown. More importantly, the impact of Long COVID on patient survival remains understudied, especially when examined alongside the effect of SOT. Methods All patients have been identified with acute COVID in the National COVID Collaborative Cohort registry from July 1, 2020, to June 30, 2022. We compared patient demographics in Long COVID vs. those without Long COVID based on descriptive statistics. Multivariable logistics regressions were used to determine the factors related to the likelihood of developing Long COVID from a case of acute COVID. Multi-variables Cox regression was used to determine the time-to-event outcome of patient survival with Long COVID. Results This study reviewed data from a cohort of 6,416,500 acute COVID patients. Of that group, 31,744 (0.5%) patients developed Long COVID from ICD diagnosis. The mean (q1, q3) age was 39 (22, 57) years old, and 55% of patients were female. From this cohort, a total of 31,744 (1%) developed Long COVID and 43,565 (1%) had SOT, with a total of 698 SOT patients identified with Long COVID. Mean age of those with Long COVID was 52 (39, 64) years old and 64% of patients were female. Most of the SOT patients were kidney transplant recipients. From the Cox regression analysis of patient survival, there were many significant factors related to patient survival (death), with elderly SOT patients having a much higher hazard ratio of 27.8 (26.3, 29.4). Conclusion This study has identified the important risk factors that are more likely to cause Long COVID in an acute COVID cohort. We investigated hazard ratios of patient survival based on multivariable Cox models, which found that Long COVID had a more direct impact on survival in elderly patients and those with SOT.

MFS Design in Appstore-enabled Smart Featurephones for Low-literate, Marginalized Communities

Mobile Financial Services (MFS) has gained significant popularity during the COVID-19 pandemic, especially among marginalized and low-income, low-literate communities around the world. Such communities have not been traditionally considered while designing MFS services via smartphone apps or USSD services in featurephones. Financial constraints limit such end-users towards basic featurephones, where recent appstore support has made it possible to deploy app-based MFS solutions beyond USSD. This new featurephone platform is a relatively underexplored area in terms of addressing design issues related to aforementioned end-users while developing MFS solutions. Our work addresses this gap by presenting qualitative findings on barriers to technology access focused on MFS solutions in marginal communities. We present a prototype non-USSD, app-based solution on an appstore-supported featurephone platform designed via a human-centered approach. This work has the potential to increase the financial inclusivity of marginalized communities in cashless MFS transactions via low-cost, appstore-enabled featurephones. © 2023 ACM.

Computational Investigation of Hand Foot Mouth Disease Dynamics with Fuzziness

The first major outbreak of the severely complicated hand, foot and mouth disease (HFMD), primarily caused by enterovirus 71, was reported in Taiwan in 1998. HFMD surveillance is needed to assess the spread of HFMD. The parameters we use in mathematical models are usually classical mathematical parameters, called crisp parameters, which are taken for granted. But any biological or physical phenomenon is best explained by uncertainty. To represent a realistic situation in any mathematical model, fuzzy parameters can be very useful. Many articles have been published on how to control and prevent HFMD from the perspective of public health and statistical modeling. However, few works use fuzzy theory in building models to simulate HFMD dynamics. In this context, we examined an HFMD model with fuzzy parameters. A Non Standard Finite Difference (NSFD) scheme is developed to solve the model. The developed technique retains essential properties such as positivity and dynamic consistency. Numerical simulations are presented to support the analytical results. The convergence and consistency of the proposed method are also discussed. The proposed method converges unconditionally while the many classical methods in the literature do not possess this property. In this regard, our proposed method can be considered as a reliable tool for studying the dynamics of HFMD.

Smartphone-based point-of-care testing of the SARS-CoV-2: A systematic review.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus's worldwide pandemic has highlighted the urgent need for reliable, quick, and affordable diagnostic tests for comprehending and controlling the epidemic by tracking the world population. Given how crucial it is to monitor and manage the pandemic, researchers have recently concentrated on creating quick detection techniques. Although PCR is still the preferred clinical diagnostic test, there is a pressing need for substitutes that are sufficiently rapid and cost-effective to provide a diagnosis at the time of use. The creation of a quick and simple POC equipment is necessary for home testing. Our review's goal is to provide an overview of the many methods utilized to identify SARS-CoV 2 in various samples utilizing portable devices, as well as any potential applications for smartphones in epidemiological research and detection. The point of care (POC) employs a range of microfluidic biosensors based on smartphones, including molecular sensors, immunological biosensors, hybrid biosensors, and imaging biosensors. For example, a number of tools have been created for the diagnosis of COVID-19, based on various theories. Integrated portable devices can be created using loop-mediated isothermal amplification, which combines isothermal amplification methods with colorimetric detection. Electrochemical approaches have been regarded as a potential substitute for optical sensing techniques that utilize fluorescence for detection and as being more beneficial to the Minimizing and simplicity of the tools used for detection, together with techniques that can amplify DNA or RNA under constant temperature conditions, without the need for repeated heating and cooling cycles. Many research have used smartphones for virus detection and data visualization, making these techniques more user-friendly and broadly distributed throughout nations. Overall, our research provides a review of different novel, non-invasive, affordable, and efficient methods for identifying COVID-19 contagious infected people and halting the disease's transmission.

Sensitivity to Neutralizing Antibodies and Resistance to Type I Interferons in SARS-CoV-2 R.1 Lineage Variants, Canada.

Isolating and characterizing emerging SARS-CoV-2 variants is key to understanding virus pathogenesis. In this study, we isolated samples of the SARS-CoV-2 R.1 lineage, categorized as a variant under monitoring by the World Health Organization, and evaluated their sensitivity to neutralizing antibodies and type I interferons. We used convalescent serum samples from persons in Canada infected either with ancestral virus (wave 1) or the B.1.1.7 (Alpha) variant of concern (wave 3) for testing neutralization sensitivity. The R.1 isolates were potently neutralized by both the wave 1 and wave 3 convalescent serum samples, unlike the B.1.351 (Beta) variant of concern. Of note, the R.1 variant was significantly more resistant to type I interferons (IFN-α/ß) than was the ancestral isolate. Our study demonstrates that the R.1 variant retained sensitivity to neutralizing antibodies but evolved resistance to type I interferons. This critical driving force will influence the trajectory of the pandemic.

Vitamin D on COVID-19 Patients During the Pandemic, 2022. A Systematic Review and Meta-Analysis

Numerous connections between the level of vitamin D (Vit-D) and the novel coronavirus disease -19 (COVID-19) have surfaced during the pandemic. So, we conducted this systematic review and meta-analysis to explore the effect of Vit-D deficiency and its supplementation on the clinical outcomes of COVID-19 patients. We looked for relevant articles in Cochrane Library, Scopus, Web Science, PubMed, and EBSCO up until the end of 2022. The Open Meta Analyst software was used to analyze the extracted data. We classified them into two main categories based on their objectives. First, the studies that evaluated the effects of Vit-D deficiency in patients, and lastly, the studies that evaluated Vit-D as a supplement, both on mortality rate, hospitalization duration, ICU admission rate, and mechanical ventilation rate. A total of 8001 COVID-19 patients from 42 studies were included. A high serum Vit-D concentration compared to those with lower levels was associated with a significantly lower mortality rate (RR = 1.5, 95% CI = 1.11: 2.02, p = 0.01). According to the estimated effect of 18 studies, those who took Vit-D supplements had a significantly lower mortality rate, hospitalization duration, ICU admission rate, and mechanical ventilation rate than those who did not. The group receiving Vit-D doses between 50 000 to 100 000 IU had a significantly better clinical outcome compared to lower and higher doses. COVID-19 patients with normal Vit-D levels had significantly lower death rates than those with hypovitaminosis. Vit-D supplements in COVID-19 significantly improved clinical outcomes. Vit-D supplementation between 50 000 to 100 000 IU, in patients with COVID-19 significantly outperformed other doses in terms of mortality. © 2023 The Author(s). Published by Enviro Research Publishers.

Does misclassification of former tobacco smokers explain the 'smoker's paradox' in the risk of COVID-19? Insights from the Stockholm Public Health Cohort.

BACKGROUND: The association between tobacco smoking and the risk of COVID-19 and its adverse outcomes is controversial, as studies reported contrasting findings. Bias due to misclassification of the exposure in the analyses of current versus non-current smoking could be a possible explanation because former smokers may have higher background risks of the disease due to co-morbidity. The aim of the study was to investigate the extent of this potential bias by separating non-, former, and current smokers when assessing the risk or prognosis of diseases. METHODS: We analysed data from 43,400 participants in the Stockholm Public Health Cohort, Sweden, with information on smoking obtained prior to the pandemic. We estimated the risk of COVID-19, hospital admissions and death for (a) former and current smokers relative to non-smokers, (b) current smokers relative to non-current smokers, that is, including former smokers; adjusting for potential confounders (aRR). RESULTS: The aRR of a COVID-19 diagnosis was elevated for former smokers compared with non-smokers (1.07; 95% confidence interval (CI) =1.00-1.15); including hospital admission with any COVID-19 diagnosis (aRR= 1.23; 95% CI = 1.03-1.48); or with COVID-19 as the main diagnosis (aRR=1.23, 95% CI= 1.01-1.49); and death within 30 days with COVID-19 as the main or a contributory cause (aRR=1.40; 95% CI=1.00-1.95). Current smoking was negatively associated with risk of COVID-19 (aRR=0.79; 95% CI=0.68-0.91). CONCLUSIONS: Separating non-smokers from former smokers when assessing the disease risk or prognosis is essential to avoid bias. However, the negative association between current smoking and the risk of COVID-19 could not be entirely explained by misclassification.

Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

The application of fuzzy theory is vital in all scientific disciplines. The construction of mathematical models with fuzziness is little studied in the literature. With this in mind and for a better understanding of the disease, an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classical model of malaria transmission. The parameters beta and delta, being function of the malaria virus load, are considered fuzzy numbers. Three steady states and the reproduction number of the model are analyzed in fuzzy senses. A numerical technique is developed in a fuzzy environment to solve the studied model, which retains essential properties such as positivity and dynamic consistency. Moreover, numerical simulations are carried out to illustrate the analytical results of the developed technique. Unlike most of the classical methods in the literature, the proposed approach converges unconditionally and can be considered a reliable tool for studying malaria disease dynamics.

New Trends in Fuzzy Modeling Through Numerical Techniques

Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-to -person contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contra-dictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is consid-ered in this study. The equilibrium analysis and reproductive number are studied with fuzziness. Two numerical schemes forward Euler method and a nonstandard finite difference (NSFD) approach, are developed for the learned model, and the results of numerical simulations are presented. The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to support decision-making to design and develop control strategies.

Knowledge of Antibiotic Use and Antibiotic Resistance During the COVID-19 Pandemic Among Healthcare Professionals

Infections can be treated with antibiotics, which have also saved countless lives. But whenever antibiotics are administered, they run the risk of having negative side effects and fueling antibiotic resistance that was a significant public health issue. The current study aimed to describe healthcare workers' knowledge of antibiotic use and resistance during the COVID-19 epidemic in the city of Riyadh and included an online survey that was disseminated on social media. About 78% of the healthcare providers in the present study had an average knowledge score of more than 75%, so most of them had good knowledge. Most of the healthcare professionals in the present study had good knowledge about bacterial resistance and antibiotic use, but there was still a knowledge gap on antibiotic use. Therefore, it is crucial to raise their awareness by attending conferences, lectures, and workshops.

Acute STEMI : Before and During the COVID-19 Pandemic Single Center Study

Background: During COVID-19 pandemic, the pattern of hospital admissions for acute ST-elevation myocardial infarction (STEMI) has been changing, and increased mortality and morbidity is being noted in these patients. Patient may present with acute myocardial infarction, myocarditis simulating a presentation like STEMI, coronary spasm, myocardial injury not fulfilling the criteria of type 1 & type 2 acute MI and cardiomyopathy. In this study we have tried to determine some important differences among the patients presented with STEMI during The COVID-19 pandemic versus non-COVID-19 era. Method(s): This prospective observational study was carried out in National Heart Foundation Hospital & Research Institute from 8thMarch,2019 to 7th March, 2021. Total 2531 patients were included. The study populations were divided into two groups. Group I: Acute STEMI patients presenting during pre COVID period (n=1385). Group II: Acute STEMI patients presenting during COVID period (n=1146). COVID period was calculated from 8th march, 2020 onward as first case of COVID -19 was detected on that day in Bangladesh. All patients presented with Acute STEMI was included in the study however NSTEMI-ACS, Unstable angina were excluded from the study. Result(s): Male was predominant in both groups. Regarding risk factors Hypertension, Obesity and family H/O of CAD was statistically significant (p<0.05). Acute STEMI patients presented lately during COVID-19 period probably due to lock down& lack of transport facility. Regarding coronary artery disease severity, vessel score was more during COVID period. SV-CAD were more during pre COVID period while DV-CAD & TV-CAD were more during COVID period. Gensini score was also calculated among the study populations, it was 57.21+/-28.42 and 63.16+/- 40.43respectively in group I and group I, which was statistically significant. Regarding treatment options of the patients, primary PCI was less during COVID period, however medical management, elective PCI and Thrombolysis were more during COVID era. Regarding in hospital outcome, acute LVF, cardiogenic shock were more during COVID period which were also statistically significant. [Formula presented] [Formula presented] Conclusion(s): During COVID -19, STEMI patients presented lately in comparison to pre COVID period. Coronary artery Disease were more severe during COVID period as evaluated by Vessel Score & Gensini Score. During COVID -19 period majority of patients got medical management& routine PCI were done more in comparison to primary PCI. In Hospital outcome of STEMI was worse during COVID-19 period in terms of acute LVF & cardiogenic shock. [Formula presented] [Formula presented] [Formula presented]Copyright © 2023

ANALYZING DIGITAL DIVIDE AMONG UNIVERSITY STUDENTS OF PAKISTAN

An emergency shift to online education after Covid-19 brought many challenges for students and teachers, especially the university students living in the rural areas of Pakistan. So this study has focused on assessing the problems students faced while acquiring online education with special reference to the theoretical background of digital divide. It is a quantitative study which employed Heckman's treatment effect model to analyze the impact of digital divide on university students' performance. The results of the study indicate that online education further increases an already existing digital divide between have and have nots. Online education is a good alternate of face-to-face education in many cases however for ensuring maximum benefits of online education requires proper availability of gadgets and internet access along with training. Existing online education system in developing countries like Pakistan may be more suitable to teach theoretical subjects like social sciences which are subjective in nature however it is not much appropriate for teaching numerical subjects. The findings of the study direct a positive impact of digital divide due to the scarcity of necessary gadgets, internet access, family income, gender, field of study, age and location © 2023, Turkish Online Journal of Distance Education.All Rights Reserved.

Analytical review of Tiryaq-i-Wabai - A Unani panacea for the control of COVID-19.

Introduction: COVID-19 has affected the whole world drastically and led to a substantial loss of human life. Relentless research is underway to identify effective treatment to control the disease. Traditional systems are also being explored to search for a potent drug. Unani formulation 'Tiryaq-i-Wabai' has long been used in cholera, plague and other epidemic diseases. This review is aimed at analysing the possible role of Tiryaq-i-Wabai in the prevention and control of COVID-19. Methodology: Unani classical texts and Pharmacopoeias available in the library of Regional Research Institute of Unani Medicine, Chennai were reviewed to collect information related to epidemics, commonly prescribed drugs during epidemics, and therapeutic uses of Tiryaq-i-Wabai ingredients. ScienceDirect, Springer, PubMed and Google Scholar were searched to collect information regarding current pandemic and pharmacological activities of ingredients and phytoconstituents present in the formulation. The collected data was analyzed and interpreted. Results: Tiryaq-i-Wabai was found to be the most recommended prophylactic and curative drug during epidemics. The formulation ingredients, Sibr (Aloe vera (L.) Burm.f.), Murr Makki (Commiphora myrrha (T.Nees) Engl.) and Zafran (Crocus sativus L.) are categorized under Tiryaqi Advia (literally - antidote drugs) and are considered to be very effective in SARS related conditions. These ingredients have been reported to exhibit immunomodulatory, antioxidant, antiviral, antibacterial, antitussive, smooth muscle relaxant, antipyretic and anti-inflammatory activities corroborating the traditional use of Tiryaq-i-Wabai. Conclusion: Scientific data imply great potential and utility of the formulation which could be a possible alternative approach for the prevention and control of current and future pandemics.

The Psychological Impact of COVID-19 Pandemic on Persons with Multiple Sclerosis in Saudi Arabia.

OBJECTIVES: To evaluate, in a Saudi Arabian context, how the COVID-19 pandemic psychologically impacted persons with multiple sclerosis (PwMS). METHODS: A cross-sectional study was undertaken during the period from October 2021 to March 2022. 738 participants resident in the Kingdom of Saudi Arabia (KSA) completed a self-administered online questionnaire. The research focused on persons diagnosed with MS. RESULTS: Participant ages spanned from 18 to over 55. The mean was 36.1±12.9 years old. Four hundred eighty-nine (66.3%) of the 738 participants were female. Two hundred sixty-four (35.8%) were single. Four hundred twelve (55.8%) were married. Six hundred eighty-five (92.8%) had received a COVID-19 vaccine. Regarding MS duration, 117 (15.9%) had been diagnosed for less than 2 years, 171 (23.2%) for 2-5 years, while 251 (34%) had the condition for 10 or more years. Regarding psychological health, 11.2% of participants complained of minimal/no depression, 33.3% of mild depression, 28.3% of moderate depression, and 27.1% of moderately severe to severe depression symptoms. Concerning anxiety, 17.2% of participants reported minimal anxiety, 36.9% mild, 23.3% moderate, while 22.6% suffered from severe anxiety symptoms. CONCLUSION: A high prevalence of depression and anxiety was found, along with high prevalence of co-occurrence of these disorders among PwMS.

VECTOR AUTOREGRESSIVE INTEGRATING MOVING AVERAGE (VARIMA) MODEL OF COVID-19 PANDEMIC AND OIL PRICE

Purpose: A coronavirus associated with severe respiratory syndrome has created Coronavirus Disease 2019 (COVID-19), a highly contagious illness that affects the entire world population. On the other hand, COVID-19 is having a direct impact on human life because of its proliferation. So, the study's goal is to forecast and analyze the impact of the COVID-19 pandemic and the oil price utilizing multiple time series analysis methods (VARIMA model). Theoretical framework: Recent literature has reported that the multivariate time series is robust model for forecasting and analyzing dynamic relationship between series, while the univariate ARIMA model has been generalized to include vector variables, that is an extension of its capabilities. The VAR (p) model analyzes the interdependence between two or more series but does not take into account the impact of shocks at various time variable delays. Design/methodology/approach: This study uses VARMA (p, q) model which links a set of variables to their prior iterations as well as those of other variables and shocks to those same variables. Sample data concerning the COVID-19 pandemic and oil price was globally provided. It contains daily observations of them variables for the years 2020-2022. Findings: The best model is VARIMA (2,1,2), and the results shown that the oil price is not only influenced by itself but also influenced by the Covid-19 pandemic. Moreover, the standard error grows over time of the forecast. Research, Practical & Social implications: The best model is sound for short-term forecasting but unstable for long-term forecasting. Future researchers can integrate factors across areas. Include tourism demand and industry variables in modeling. Originality/value: Collecting COVID-19 pandemic data and oil price series in a modern model that is a multivariate time series model with a high predicted level of model accuracy between these variables in order to predict and analyze the effects between them series and estimate the interaction between these two series with the most recent data is the value of this study, and then offers merchants the chance to comprehend the forecasting of oil price throughout the covid-19 effects as well as the associated risks. © 2022 AOS-Estratagia and Inovacao. All rights reserved.

Effect of COVID-19 on severity of signs and symptoms of autoimmune diseases

It is an observational cross-sectional study, the data collected by convenience sampling method from 33 patients in the Ranya General Hospital and private clinics for follow-up patient's autoimmune diseases state in the Ranya city from the 10th November 2020 to the 20th May 2021 and the study included all the patients had autoimmune diseases that recovered from the COVID-19 disease. For the study materials, the data was collected by a questionnaire form that included demographic and autoimmune disease questions also questions about the patient's intensity of their autoimmune disease's signs and symptoms before and after they recovered from COVID-19. Determine patient's autoimmune disease signs and symptoms intensity based on the prescribed drug for a treat the autoimmune diseases which are changed by special doctors. Furthermore, the data were analysed by SPSS software to produce descriptive statistic measures and to find the difference between dependent categorical variables Sign tests were used but the Chi-square test was used for the categorical independent variables with regarding 0.05 as a significant critical value. The result reveals that the range of their age started from 42 to 74 years old with mean..standard deviation (57.3 .. 8.06) and most of the cases 15(45.5%) were between (55-65) years old, followed by less than 55 years old 13(39.4%) and more than 65 years old age 5(3.8%) cases respectively. Rheumatoid arthritis was a major type 16 (48.5%) of the autoimmune disease compared to other types, Ankylosing Spondylitis 8(24.2%) cases, and Ulcerative Colitis 6(18.2%) cases respectively while Crohn's disease was the minimum 3(9.1%) cases and before the got COVID-19 most of the cases 25(75.8%) had moderate intensity signs and symptoms of their autoimmune diseases and 8(24.2%) cases had severe signs and symptoms but after they recovered from the COVID-19 disease the rate of their signs and symptoms changed to mild 19(57.6%) and moderate 14(42.4%) intensity while severe intensity signs and symptoms were zero with highly significant differences (P-value 0.0001). Despite the current study concluded autoimmune disease patients recovered from the COVID-19 their autoimmune diseases signs and symptoms intensity decreased significantly but still further studies are needed with a bigger sample size to determine and explain this association.

The Impact of Bahrain's Adaptive Sports on Quality of Life

The importance of research and review of the advantages of physical exercise for humans and the importance of sports and the extent of its impact on the lives of individuals in various aspects. Bahrain Economic Vision 2030 consider sport is one of the most important factors to increase immunity in the human body, and that sport is important to confront COVID-19 and all diseases, so there are positives to the need to adhere to sports practices. Literature Review shows Public sector support for sport and physical activity unleash promote wellbeing and health, pursue positive social goals and promoting genders equality (Giulianotti et al. 2019) and how Physical activities enhance quality of life as exercise are very great for the general health and physical and psychological health of those who exercise regularly. (Shen et al. 2020).The method of the research is systematically literature review the articles related how sport enhancing quality of life, global initiatives regarding sport as social innovation and Bahrain overview about physical activity. In the Conclusion, Sport is one of the main things in a healthy person's life, which maintains public health and prevents diseases. Also, Bahrain 2030 vision improve health system by promoting and encouraging a healthy lifestyle by offering more attractive public spaces and modern facilities to boost sports activities. Finally, For future research academic institutions need to conduct researches about how sport can result outcomes beyond the playing field (Sanders et al. 2017;Camp 2020), what is the role of innovation in sport for development and peace to develop solutions for social challenges (Svensson and Cohen 2020). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Post-COVID-19 Syndrome Clinical Manifestations: A Systematic Review.

BACKGROUND: Coronavirus disease-2019 (COVID-19) is a global pandemic health problem that causes a wide spectrum of clinical manifestations and considerable mortality rates. Unfortunately, recovered patients who survive COVID-19 may continue to report a wide variety of clinical manifestations of multisystem affection such as pulmonary embolism, deep vein thrombosis, acute myocardial infarction, depression, anxiety, myalgia, dyspnea, and fatigue. OBJECTIVE: We aimed to summarize the current literature regarding the prevalence of post-COVID- 19 manifestations. METHODS: We conducted a systematic review of post-COVID-19 manifestations by searching MEDLINE via PubMed, Scopus, Web of Science (WOS), EBSCO, Wily, and World health organization (WHO) databases. Screening, study selection, data extraction, data synthesis, and quality assessment were made by two independent reviewers. RESULTS: Of 1,371 references, 817 references remained after removing duplicates. Reviews, case reports, commentaries, and any article containing non-original information were excluded. According to the eligibility criteria for this systematic review, 12 studies were included for qualitative synthesis. The overall prevalence of post-COVID-19 manifestations ranged from 35% to 90.5%. Fatigue, dyspnea, neuropsychological disorders, and pain were the most frequent post-COVID-19 symptoms. CONCLUSION: This systematic review showed that 35% to 90.5% of recovered patients who survive COVID-19 continue to have a wide variety of clinical manifestations, including fatigue, dyspnea, neuropsychological disorders, and pain as the most frequent post-COVID-19 symptoms.

Modeling of Computer Virus Propagation with Fuzzy Parameters

Typically, a computer has infectivity as soon as it is infected. It is a reality that no antivirus programming can identify and eliminate all kinds of viruses, suggesting that infections would persevere on the Internet. To understand the dynamics of the virus propagation in a better way, a computer virus spread model with fuzzy parameters is presented in this work. It is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity, which depends on the quantity of virus. Considering this, the parameters beta and gamma being functions of the computer virus load, are considered fuzzy numbers. Using fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical models. The essential features of the model, like reproduction number and equilibrium analysis, are discussed in fuzzy senses. Moreover, with fuzziness, two numerical methods, the forward Euler technique, and a nonstandard finite difference (NSFD) scheme, respectively, are developed and analyzed. In the evidence of the numerical simulations, the proposed NSFD method preserves the main features of the dynamic system. It can be considered a reliable tool to predict such types of solutions.