YouTube: Is It a Reliable Source of Nutrition Information on COVID-19 Pandemic?

Data on the nutrition-related misinformation about COVID-19 are limited. This study analysed the quality and accuracy of the nutrition information available on YouTube about current COVID-19 pandemic as well as assessed the content of the videos. YouTube was searched using the terms "nutrition and COVID-19" in Turkish on 1 February 2021. Videos were filtered according to relevancy, and the first 280 videos were analysed. A total of 218 videos were reviewed and classified as "misleading" or "relevant" depending on the information provided. The transparency, utility, reliability, and accuracy of video contents were assessed. The videos attracted a cumulative 6,258,694 views. There were 178 (81.7%) fully relevant and 40 (18.3%) misleading videos. Approximately 80% of the videos shared by health professionals were relevant videos. Government organisations only shared relevant videos. Relevant videos had higher reliability, accuracy, and quality than misleading videos. The nutrition-related content of COVID-19 videos is suboptimal on YouTube. As the COVID-19 pandemic worsens, and nutrition could improve immunity, health professionals and educational and government organisations need to engage more in the spread of nutrition-related COVID-19 information to Internet platforms based on nutrition guidelines and the latest scientific evidence. This will be a practical and immediately implementable public health strategy to effectively spread the right information.

Diagnostic Efficacy of COVID-19 Rapid Antigen Detection Card in Diagnosis of SARS-CoV-2.

Introduction The rapid surge of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) cases globally makes it essential for rapid diagnosis of coronavirus disease 2019 (COVID-19). Real-time reverse-transcription polymerase chain reaction (rtRT-PCR) remains as the gold standard to detect COVID-19 cases because of its greater sensitivity and specificity. However, because of its prolonged turnaround time and technical expertise, recommendations have been made to employ the use of rapid diagnostic test for rapid diagnosis and to curb the spread of the disease. Methods This prospective study was performed in a tertiary COVID-19 care hospital located amidst the semi-urban settings. Both nasopharyngeal and throat swabs collected from the COVID 19 suspected study participants were subjected to both COVID 19 rtRT-PCR and rapid antigen testing. Results Of the total 599 samples tested by rtRT-PCR, 310 (52%) were positive and 289 (48%) tested negative for SARS-CoV-2. Of the 599 samples tested by rapid antigen test (RAT), 230 (38%) were positive and 369 (62%) were negative. The overall sensitivity and specificity of our study kit was found to be 74.19 and 100%, respectively. The sensitivity of the RAT greatly overlaps with the viral load which is determined by the cycle threshold (CT) values of SARS-CoV-2, E gene, and RdRp gene. Conclusion RAT yields rapid results within a short-turnaround time and found to be cost effective. Therefore, this test can be adopted in areas with rapid surge in SARS-CoV-2 cases which can help to rapidly identify the positive cases and to implement isolation and infection control measures.

A Comparative Study on Bacterial Co-Infections and Prevalence of Multidrug Resistant Organisms among Patients in COVID and Non-COVID Intensive Care Units.

Introduction: Secondary bacterial infections have been reported in majority of patients hospitalized with coronavirus disease 2019 (COVID-19). A study of the antimicrobial susceptibility profiles of these bacterial strains revealed that they were multidrug resistant, demonstrating their resistance to at least three classes of antimicrobial agents including beta-lactams, fluoroquinolones and aminoglycosides. Bacterial co-infection remains as an important cause for high mortality in patients hospitalized with COVID-19. Methods: In our study, we conducted a retrospective comparative analysis of bacterial co-infections and the antimicrobial resistance profile of bacterial isolates obtained from inpatients admitted in COVID-19 and non-COVID-19 intensive care units. The goal was to obtain the etiology and antimicrobial resistance of these infections for more accurate use of antimicrobials in clinical settings. This study involved a total of 648 samples collected from 356 COVID-19 positive patients and 292 COVID-19 negative patients admitted in the intensive care unit over a period of six months from May to October 2020. Results: Among the co-infections found, maximum antimicrobial resistance was found in Acinetobacter species followed by Klebsiella species in both the ICU's. Incidence of bacterial co-infection was found to be higher in COVID-19 intensive care patients and most of these isolates were multidrug resistant strains. Conclusion: Therefore, it is important that co-infections should not be underestimated and instead be made part of an integrated plan to limit the global burden of morbidity and mortality during the SARS-CoV-2 pandemic and beyond.

Convolutional neural network based CT scan classification method for COVID-19 test validation.

Given the novel corona virus discovered in Wuhan, China, in December 2019, due to the high false-negative rate of RT-PCR and the time-consuming to obtain the results, research has proved that computed tomography (CT) has become an auxiliary One of the essential means of diagnosis and treatment of new corona virus pneumonia. Since few COVID-19 CT datasets are currently available, it is proposed to use conditional generative adversarial networks to enhance data to obtain CT datasets with more samples to reduce the risk of over fitting. In addition, a BIN residual block-based method is proposed. The improved U-Net network is used for image segmentation and then combined with multi-layer perception for classification prediction. By comparing with network models such as AlexNet and GoogleNet, it is concluded that the proposed BUF-Net network model has the best performance, reaching an accuracy rate of 93%. Using Grad-CAM technology to visualize the system's output can more intuitively illustrate the critical role of CT images in diagnosing COVID-19. Applying deep learning using the proposed techniques suggested by the above study in medical imaging can help radiologists achieve more effective diagnoses that is the main objective of the research. On the basis of the foregoing, this study proposes to employ CGAN technology to augment the restricted data set, integrate the residual block into the U-Net network, and combine multi-layer perception in order to construct new network architecture for COVID-19 detection using CT images. -19. Given the scarcity of COVID-19 CT datasets, it is proposed that conditional generative adversarial networks be used to augment data in order to obtain CT datasets with more samples and therefore lower the danger of overfitting.

Assessment of COVID-19 risk and prevention effectiveness among spectators of mass gathering events.

There is a need to evaluate and minimize the risk of novel coronavirus infections at mass gathering events, such as sports. In particular, to consider how to hold mass gathering events, it is important to clarify how the local infection prevalence, the number of spectators, the capacity proportion, and the implementation of preventions affect the infection risk. In this study, we used an environmental exposure model to analyze the relationship between infection risk and infection prevalence, the number of spectators, and the capacity proportion at mass gathering events in football and baseball games. In addition to assessing risk reduction through the implementation of various preventive measures, we assessed how face-mask-wearing proportion affects infection risk. Furthermore, the model was applied to estimate the number of infectors who entered the stadium and the number of newly infected individuals, and to compare them with actual reported cases. The model analysis revealed an 86-95% reduction in the infection risk due to the implementation of face-mask wearing and hand washing. Under conditions in which vaccine effectiveness was 20% and 80%, the risk reduction rates of infection among vaccinated spectators were 36% and 96%, respectively. Among the individual measures, face-mask wearing was particularly effective, and the infection risk increased as the face-mask-wearing proportion decreased. A linear relationship was observed between infection risk at mass gathering events and the infection prevalence. Furthermore, the number of newly infected individuals was also dependent on the number of spectators and the capacity proportion independent of the infection prevalence, confirming the importance of considering spectator capacity in infection risk management. These results highlight that it is beneficial for organisers to ensure prevention compliance and to mitigate or limit the number of spectators according to the prevalence of local infection. Both the estimated and reported numbers of newly infected individuals after the events were small, below 10 per 3-4 million spectators, despite a small gap between these numbers.

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.

Assessment of COVID-19 prevention and protection measures in hospitals.

This paper aims to develop an assessment framework for the Covid-19 prevention and protection measures in hospitals. The conceptual model is developed by using fifty-four attributes, fifteen criteria, and three enablers. The multi-grade fuzzy approach is used to develop the assessment framework, and Importance Performance Analysis (IPA) identifies the weaker attributes in the case organization. The case hospital's preventive and safety measures assessment level is 8.05, which is 'very highly focused on protection measures,' and fourteen weaker attributes were identified. The case hospital management should focus on the guidelines of Covid-19 preventive and protection measures, strict protocols, regular audits, education and training of the staff, and active surveillance. Case hospital managers should also focus on staffing and timings, the formulation of policies, and abiding by those policies without any fail. This proposed assessment model is a new initiative in-hospital assessment in preventive and safety measures in the healthcare sector during the Covid-19 era. This framework will enable hospital managers as a continuous assessment tool to improve their Covid-19 prevention operations.

Psychological Impact and Compliance with Staying at Home of the Public to COVID-19 Outbreak during Chinese Spring Festival.

In December 2019, COVID-19 was reported in Wuhan, China. Most of the studies related to the psychological impact and compliance with staying at home due to COVID-19 focused on ten days or one month after the initial "stay-at-home" phase of the COVID-19 pandemic. The early psychological impact and behavior change to COVID-19 during the Chinese Spring Festival (the start time for recommendations to stay at home) is uncertain. In this study, people from 23 provinces in China were recruited to participate in an online survey, using Credamo. Psychological impact and compliance with staying at home were evaluated by a self-designed and validated questionnaire. The results indicated that anxiety was the most often reported feeling (mean: 3.69), followed by sadness (mean: 3.63). Participants employed in foreign-owned companies were most likely to express anxiety and sadness. Overall, 61.8% of participants reported hardly going out, whereas 2.4% said they frequently went out during the initial "stay-at-home" phase of the COVID-19 pandemic. Participants with higher levels of anxiety and sadness were most likely to stay at home against the spread of COVID-19, as were female gender. This survey is an important study of the first reaction to staying at home during the initial "stay-at-home" phase coinciding with Chinese Spring Festival. Our findings identified factors associated with higher level of psychological impact and better compliance with staying at home recommendations during Chinese Spring Festival. The findings can be used to formulate precaution interventions to improve the mental health of vulnerable groups and high uptake of policy during the COVID-19 epidemic.

Proposing a fungal metabolite-flaviolin as a potential inhibitor of 3CLpro of novel coronavirus SARS-CoV-2 identified using docking and molecular dynamics.

The novel SARS-CoV-2 is the etiological agent causing the Coronavirus disease 2019 (COVID-19), which continues to become an inevitable pandemic outbreak. Over a short span of time, the structures of therapeutic target proteins for SARS-CoV-2 were identified based on the homology modelled structure of similar virus, SARS-CoV that transmitted rapidly in 2003. Since the outset of the disease, the research community has been looking for a potential drug lead. Out of all the known resolved structures related to SARS-CoV-2; 3-chymotrypsin (3 C) like protease (3CLpro) is considered as an attractive anti-viral drug compound on the grounds of its role in viral replication and probable non-interactive competency to bind to any viral host protein. To the best of our knowledge, till date only one compound has been identified and tested in-vitro as a potent inhibitor of 3CLpro protein, addressed as N3 (PubChem Compound CID: 6323191) and is known to bind irreversibly to 3CLpro suppressing its activity. Using computational approach, we intend to identify a probable natural fungal metabolite to interact and inhibit 3CLpro. Here after performing docking and molecular dynamics of various small molecules derived as a secondary metabolite from fungi, we propose Flaviolin as potent inhibitor of 3CLpro of novel Coronavirus SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Meticulous assessment of natural compounds from NPASS database for identifying analogue of GRL0617, the only known inhibitor for SARS-CoV2 papain-like protease (PLpro) using rigorous computational workflow.

The latest global outbreak of 2019 respiratory coronavirus disease (COVID-19) is triggered by the inception of novel coronavirus SARS-CoV2. If recent events are of any indicators of the epidemics of past, it is undeniable to state a fact that the SARS-CoV2 viral infection is highly transmissible with respect to its previously related SARS-CoV's. Papain-like protease (PLpro) is an enzyme that is required by the virus itself for replicating into the host system; and it does so by processing its polyproteins into a functional replicase complex. PLpro is also known for downregulating the genes responsible for producing interferons, an essential family of molecules produced in response to viral infection, thus making this protein an indispensable drug target. In this study, PLpro inhibitors were identified through high throughput structure-based virtual screening approach from NPASS natural product library possessing ~ 35,000 compounds. Top five hits were scrutinised based on structural aromaticity and ability to interact with a key active site residue of PLpro, Tyr268. For second level of screening, the MM-GBSA End-Point Binding Free Energy Calculation of the docked complexes was performed, which identified Caesalpiniaphenol A as the best hit. Caesalpiniaphenol A not only possess a double ring aromatic moiety but also has lowest minimum binding energy, which is at par with the control GRL0617, the only known inhibitor of SARS-CoV2 PLpro. Details of the Molecular Dynamics (MD) simulation and ADMET analysis helped to conclusively determine Caesalpiniaphenol A as potentially an inhibitor of SARS-CoV2 PLpro.

Case fatality rates of COVID-19 across the globe: are the current draconian measures justified?

Aim: The current study assessed the case fatality rate (CFR) across different income level countries of the world, and the virulence pattern of COVID-19, against the backdrop of panic and uncertainty faced by many governments, who are trying to impose draconian containment measures to control the outbreak. Subjects and Methods: Data on confirmed cases and number of deaths due to coronavirus infection were retrieved from the WHO as on 30 March 2020, and examined for the various income level countries, per the World Bank criteria. The CFR was calculated country-wise and estimated for the various groups such as low, lower-middle, upper-middle, and high-income, and the data was analyzed. Results: The overall CFR for the high income countries was 5.0%, compared with a CFR of 2.8% for low-income countries. The upper-middle-income countries showed a CFR of 4.3%, while the lower-middle-income countries stood at 3.7%. The results from our study predict that the maximum CFR in high-income countries will be contained at approximately 5% (95% CI). The CFR for the low, lower-middle, and upper-middle-income countries will range between 2.8 and 4.3% (95% CI). Conclusion: COVID-19, irrespective of its transmissibility, produces a lower CFR compared with that of SARS-Cov and MERS-Cov, although COVID-19 has infected eight times more countries than MERS-Cov and SARS-Cov, and caused a higher number of deaths. The nation-wide lockdown measures to prevent the spread of the virus may be reconsidered, given the hardships for the population and their impact on the economic system.

Negative and positive psychological experience of frontline nurses in combatting COVID-19: A qualitative study.

AIMS: To qualitatively explore potential experience among frontline nurses who had been fighting against the COVID-19 infection since the outbreak. BACKGROUND: Disasters are often sudden and uncertain. Since the COVID-19 outbreak in Wuhan city, local frontline nurses had been responsible for treatment of COVID-19 for several months. Qualitative study was required to assess complex multi-component psychological experiences among frontline nurses. METHODS: Twenty local frontline nurses were recruited from a designated hospital of COVID-19 treatment. We conducted semi-structured interview using phenomenological method. Descriptive phenomenological method was applied for thematic analysis. RESULTS: Twenty female frontline nurses (aged 24 to 43 years old) were interviewed. Two broader themes, negative and positive, were identified. Negative experience included refusal and helpless (refusal to work at frontline, shortage of confidence in working and helpless), fear and anxiety, excessive miss, and other health issues. Positive experience included improved interpersonal relationship, sublimation of personal faith and strength, changes in understanding meaning of life and new possibility. CONCLUSION: Both positive and negative psychological response were observed, which can provide evidence based clues for making essential strategies and policy. IMPLICATIONS FOR NURSING MANAGEMENT: Understand subjective experience of frontline nurses can establish evidence for development of effective psychological intervention. Nursing administrator should consider the nurses' psychological experience comprehensively to promote psychological growth and lower post-traumatic psychological burden.

Transmission of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) through infant feeding and early care practices: A systematic review.

BACKGROUND: Perinatal practices such as breast-feeding, kangaroo mother care, rooming-in, and delayed cord clamping have varied by institution during the COVID-19 pandemic. The goal of this systematic review was to examine the success of different practices in preventing viral transmission between SARS-CoV-2 positive mothers and their infants. METHODS: Electronic searches were performed in the Ovid MEDLINE, Ovid Embase, Cochrane Library, EBSCOhost CINAHL Plus, Web of Science, and Scopus databases. Studies involving pregnant or breastfeeding patients who tested positive for SARS-CoV-2 by RT-PCR were included. Infants tested within 48 hours of birth who had two tests before hospital discharge were included. Infants older than one week with a single test were also included. RESULTS: Twenty eight studies were included. In the aggregated data, among 190 breastfeeding infants, 22 tested positive for SARS-CoV-2 (11.5%), while 4 of 152 (2.63%) among bottle-fed (Fisher's exact test p = 0.0006). The positivity rates for roomed in infants (20/103, 19.4%) were significantly higher than those isolated (5/300, 1.67%) (P < 0.0001). There was no significant difference in positivity rate among infants who received kangaroo care (25%vs 9%, p = 0.2170), or delayed cord clamping (3.62%vs 0.9%, p = 0.1116). CONCLUSIONS: Lack of robust studies involving large patient population does not allow meaningful conclusions from this systematic review. Aggregated data showed increased positivity rates of SARS-CoV-2 among infants who were breast fed and roomed-in. There were no differences in SARS-CoV-2 positivity rates in infants received skin to skin care or delayed cord clamping.

Repurposing the antibacterial drugs for inhibition of SARS-CoV2-PLpro using molecular docking, MD simulation and binding energy calculation.

Papain-like protease (nsp-3; non-structural protein) of novel corona virus is an ideal target for developing drugs as it plays multiple important functions for viral growth and replication. For instance, role of nsp-3 has been recognized in cleavage of viral polyprotein; furthermore, in infected host it weakens the immune system via downregulating the production of type I interferon. This downregulation is promoted by removal of ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from interferon-responsive factor 3 (IRF3) protein. Among known inhibitors of SARS-CoV-PLpro GRL0617 is by far the most effective inhibitor. As PLpro of SARS-CoV2 is having more than 80% similarity with SARS-CoV-PLpro, GRL0617 is reported to be effective even against SARS-CoV2. Owing to this similarity, certain key amino acids remain the same/conserved in both proteins. Among conserved amino acids Tyr268 for SARS-CoV2 and Tyr269 for SARS-CoV produce important hydrophobic interactions with aromatic rings of GRL0617. Here, in this study antibacterial compounds were collected from ZINC database, and they were filtered to select compounds that are having similar structural features as GRL0617. This filtered library of compound was then docked with SARS-CoV and CoV2-PLpro. Five hits were noted that were able to interact with Tyr268 (SARS-CoV2) and Tyr269 (SARS-CoV). Further, best hit 2-(2-((benzofuran-2-carboxamido)methyl)-5-methoxy-1H-indol-1-yl)acetic acid (ZINC44459905) was studied using molecular dynamic simulation where stability of protein-ligand complex as well as stability of produced interactions was noted.

COVIDSAVIOR: A Novel Sensor-Fusion and Deep Learning Based Framework for Virus Outbreaks.

The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furthermore, the presented system also facilitates a variety of notifications, such as an alarm, if an individual is not wearing a mask and detects thermal temperature beyond the standard body temperature threshold, such as 98.6°F (37°C). Design/methodology/approach-The presented deep Learning and sensor-fusion-based approach can also detect an individual in with or without mask situations and provide appropriate notification to the security personnel by raising the alarm. Moreover, the smart tunnel is also equipped with a thermal sensing unit embedded with a camera, which can detect the real-time body temperature of an individual concerning the prescribed body temperature limits as prescribed by WHO reports. Findings-The investigation results validate the performance evaluation of the presented smart face-mask and thermal scanning mechanism. The presented system can also detect an outsider entering the building with or without mask condition and be aware of the security control room by raising appropriate alarms. Furthermore, the presented smart epidemic tunnel is embedded with an intelligent algorithm that can perform real-time thermal scanning of an individual and store essential information in a cloud platform, such as Google firebase. Thus, the proposed system favors society by saving time and helps in lowering the spread of coronavirus.

Public perception towards medical waste generated in the environment during the COVID-19 pandemic in Eastern Province, Saudi Arabia.

Airborne droplets and contaminated surfaces are the main routes for the epidemic virus outbreak that causes the novel coronavirus. To reduce virus spread, people wear face masks and gloves daily, which massively increases the amount of waste generated in the environment. Also, the inappropriate disposal of used masks and gloves in communities may boost the spread of the novel coronavirus. However, no studies have been conducted to evaluate a public perception regarding the management of generated masks and gloves during the global health threat. Therefore, this paper proposes a study of public awareness, attitudes, and practices towards gloves and masks generated during the novel coronavirus pandemic in Saudi Arabia. The study showed that most of the participants (74%) have adequate awareness regarding the proper way to dispose of used masks and gloves, with 76% showing positive attitudes toward waste management. Gender shows a significant correlation with the regulations of medical waste collection and disposal (r = 0.169, p = 0.0001), and the consideration of the effective disposal of COVID-19 waste management as a collective responsibility of the community (r = 0.158, p = 0.0001). Also, the study shows that the majority of participants were aware on the availability of regulations for the collection and disposal of biomedical waste. Moreover, it demonstrates that public awareness regarding the attitude and measures taken by regional municipalities to reduce the spread of coronavirus has a significant positive correlation (r = 0.279, p = 0.0001). The study further recognized that the effective management of contagious wastes significantly protects the public against the improper practices of wastes disposal generated during the novel coronavirus pandemic.

SEIAQRDT model for the spread of novel coronavirus (COVID-19): A case study in India.

COVID-19 is a global pandemic declared by WHO. This pandemic requires the execution of planned control strategies, incorporating quarantine, self-isolation, and tracing of asymptomatic cases. Mathematical modeling is one of the prominent techniques for predicting and controlling the spread of COVID-19. The predictions of earlier proposed epidemiological models (e.g. SIR, SEIR, SIRD, SEIRD, etc.) are not much accurate due to lack of consideration for transmission of the epidemic during the latent period. Moreover, it is important to classify infected individuals to control this pandemic. Therefore, a new mathematical model is proposed to incorporate infected individuals based on whether they have symptoms or not. This model forecasts the number of cases more accurately, which may help in better planning of control strategies. The model consists of eight compartments: susceptible (S), exposed (E), infected (I), asymptomatic (A), quarantined (Q), recovered (R), deaths (D), and insusceptible (T), accumulatively named as SEIAQRDT. This model is employed to predict the pandemic results for India and its majorly affected states. The estimated number of cases using the SEIAQRDT model is compared with SIRD, SEIR, and LSTM models. The relative error square analysis is used to verify the accuracy of the proposed model. The simulation is done on real datasets and results show the effectiveness of the proposed approach. These results may help the government and individuals to make the planning in this pandemic situation.

Sensitivity and elasticity analysis of novel corona virus transmission model: A mathematical approach.

The deadly corona virus continues to pound the globe mercilessly compelling mathematical models and computational simulations which might prove effective tools to enable global efforts to estimate key transmission parameters involved in the system. We propose a mathematical model using a set of non-linear differential equations to account for the spread of the COVID-19 infection with special compartment class isolation or quarantine and estimate the model parameters by fitting the model with reported data of the ongoing pandemic situation in India. The basic reproduction number is defined and local stability analysis is carried out at each equilibrium point in terms of the reproduction number R 0 . The model is fitted mathematically and makes the data India specific. Additionally, we examined sensitivity analysis of the model. These outcomes recommend how to control the spread of corona, keeping in mind contact and recovery rate. Also we have investigated the elasticity of the basic reproduction number as a measure of control parameters of the dynamical system. Numerical simulations were also done to show that the proposed model is valid for the type and spread of the outbreak which happened in India.

Post COVID-19 vaccination neuromyelitis optica spectrum disorder: Case report & MRI findings.

There are rising concerns among the medical community and the public regarding the side effects of different vaccines developed throughout the world and their short and long-term effects, particularly COVID19 vaccines. Most notably, post-vaccination demyelinating diseases such as acute disseminated encephalomyelitis, transverse myelitis, and multiple sclerosis relapses have been reported. We present a case of a 32-year-old male who presented with a 2 weeks history of acute confusional state and imbalance 1 week after receiving the second dose of COVID19 vaccination. MRI findings showed typical distribution of neuromyelitis optica spectrum disorder and the patient was positive for AQP4 IgG. The pathogenesis behind developing neuromyelitis optica and vaccines is still unknown. Few case reports have been reported of post-vaccination neuromyelitis optica spectrum disorder but to our knowledge, this would be the first case published of neuromyelitis optica following exposure to COVID19 vaccine.

Impact of Coronavirus Diseases on Liver Enzymes.

Introduction Coronavirus disease 2019 (COVID-19) affects various organs including lungs, brain, and eyes. Very limited data is available related to the effect of COVID-19 on liver. This study is conducted to determine the impact of COVID-10 on liver by measuring the frequency of participants with deranged liver enzymes in patients diagnosed with COVID-19. Methods This cross-sectional study was conducted in a COVID-19 unit of a tertiary care hospital in Pakistan from February 2021 to June 2021. A total of 900 patients admitted with COVID-19 were enrolled in the study after seeking informed consent. After enrollment, taking history and vitals, 5 mL blood was drawn via phlebotomy and sent to the laboratory to test for C-reactive protein, lactate dehydrogenase, and liver enzymes. Results Overall 141 (28.2%) participants had a minimum of one deranged liver enzyme. The most commonly deranged liver enzyme found was alanine transaminase (ALT), both in males (19.9%) and females (21.3%), followed by aspartate transaminase (male: 18.3% and female: 20.3%). Serum total bilirubin was deranged in both males (8.4%) and females (8.3%). There was no significant difference in the gender-wise prevalence of deranged liver enzymes.  Conclusion Liver enzymes are frequently deranged in patients admitted with COVID-19. Liver enzymes should be regularly monitored during the course of management of COVID-19, as various medications used in the treatment of COVID-19 may further deteriorate liver enzymes and may cause long-term damage.