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1.
Front Immunol ; 13, 2022.
Article in English | PubMed Central | ID: covidwho-2198865

ABSTRACT

SARS-COV-2 is a virulent respiratory virus, first identified in China (Wuhan) at the end of 2019. Scientists and researchers are trying to find any possible solution to this deadly viral disease. Different drug source agents have been identified, including western medicine, natural products, and traditional Chinese medicine. They have the potential to counteract COVID-19. This virus immediately affects the liver and causes a decrease in oxygen levels. In this study, multiple vacciome approaches were employed for designing a multi-epitope subunit vaccine for battling against SARS-COV-2. Vaccine designing, immunogenicity, allergenic, and physico-chemical assessment were performed by using the vacciome approach. The vaccine design is likely to be antigenic and produce potent interactions with ACE2 and NSP3 receptors. The developed vaccine has also been given to in-silico cloning models and immune response predictions. A total number of 12 CTL and 12 HTL antigenic epitopes were predicted from three selected covid-19 virulent proteins (spike protein, nucleocapsid protein, and membrane proteins, respectively) based on C-terminal cleavage and MHC binding scores. These predicted epitopes were amalgamated by AYY and GPGPG linkers, and a β-defensins adjuvant was inserted into the N-terminus of this vaccine. This analysis shows that the recommended vaccine can produce immune responses against SARS-COV-2. Designing and developing of the mentioned vaccine will require further experimental validation.

2.
Health Sci Rep ; 6(1), 2023.
Article in English | PubMed Central | ID: covidwho-2172969

ABSTRACT

Crimean‐Congo hemorrhagic fever (CCHF) is an infection caused by a tick‐borne virus (genus: Nairovirus, family: Bunyaviridae). The most important vector for CCHF is the ixodid tick. Along with tick bite, direct contact with the virus‐affected animal is responsible for its spread. Pakistan witnessed its first case of CCHF in 1976 and has been a major victim of CCHF for years, but spikes in cases are seen after Eid‐ul‐Adha, an Islamic festival involving the sacrifice of cattle. The disease, in particular, is common among butchers, veterinarians, and livestock workers. From the start of this year till June 22, 2022, a total of four cases have been reported across the country. Pakistan faces major challenges in combating CCHF every year due to its specific geographical position and a majority of the population being involved with animal husbandry. There is no approved vaccine for its prevention. All these factors contribute to the burden on the already weakened healthcare system of Pakistan. Strict actions should be taken to contain the spread of the disease. The need of the hour is to engage the general population, raise awareness, and develop policies to ensure disease surveillance. This should be accompanied by fostering collaboration among animal and human health departments for efficient communication and early intervention. The focus should be on medical research to find an efficacious treatment and prophylaxis for the CCHF virus, which will be the cornerstone of future CCHF prevention and control strategies.

3.
Pakistan Journal of Medical and Health Sciences ; 16(11):99-102, 2022.
Article in English | EMBASE | ID: covidwho-2207088

ABSTRACT

Background: Almost everyone in society has been affected by the Covid epidemic.However, it has a different impact on individuals who have disabilities or special needs. People with special needs are more prone to this. Aim(s): To explore relationship between mental distress, perceived stress and resilience among special students during Covid-19 Method:Cross-sectional correlational research design was used to investigate the relationship between study variables. The total sample of n=250 special students consisted of 100(40%) females and 150(60%) with having age range from 15 to 30 years. The purposive sampling technique was employed to collect the data by using different research instruments Results:Results were drawn using correlation and multiple regression analyses. To explore gender differences, an independent t-test was computed. It was concluded that mental distress is negatively correlated with resilience and positively correlated with perceived stress. PraccticalImplication: This research would be helpfulfor the teachers of the special education centers, they train their how they develop resilience hence they may become emotionally stable and deal effectively with any worrisome circumstance well. It will help school administration of the special students'to conduct workshops on the resilience so that students could deal with their mental distress and perceived stress effectively. Conclusion(s): There was little published research on the variables examined in this study, particularly in Pakistan. To increase the body of knowledge, research on this subject must be done in Pakistan. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.

4.
Frontiers in Immunology ; 13:1034444, 2022.
Article in English | MEDLINE | ID: covidwho-2163020

ABSTRACT

Viruses are submicroscopic, obligate intracellular parasites that carry either DNA or RNA as their genome, protected by a capsid. Viruses are genetic entities that propagate by using the metabolic and biosynthetic machinery of their hosts and many of them cause sickness in the host. The ability of viruses to adapt to different hosts and settings mainly relies on their ability to create de novo variety in a short interval of time. The size and chemical composition of the viral genome have been recognized as important factors affecting the rate of mutations. Coronavirus disease 2019 (Covid-19) is a novel viral disease that has quickly become one of the world's leading causes of mortality, making it one of the most serious public health problems in recent decades. The discovery of new medications to cope with Covid-19 is a difficult and time-consuming procedure, as new mutations represent a serious threat to the efficacy of recently developed vaccines. The current article discusses viral mutations and their impact on the pathogenicity of newly developed variants with a special emphasis on Covid-19. The biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), its mutations, pathogenesis, and treatment strategies are discussed in detail along with the statistical data.

5.
IEEE Sensors Journal ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-2078238

ABSTRACT

The elderly population is growing, and the health care system is experiencing a strain on services provided to the elderly. The recent COVID-19 pandemic has increased this strain and has resulted in an increased risk of exposure during visits to elderly homes. Increasing the desire to provide technological solutions to counteract this. Currently, there lack reliable real-time non-invasive sensing systems. This paper makes use of Radio Frequency sensing, where signal propagation is observed in Channel State Information (CSI) reports on Activities of Daily Living (ADLs). Real-time data has been collected for three classifications, “movement”, “empty room”, and “no activity”. A filter is applied to reduce the noise of the CSI data. Then the mean, max, min, kurtosis, skew and standard deviation features are extracted from the CSI data. A machine learning model provides classification for the real-time monitoring system allowing detection of abnormalities in the expected ADLs of the elderly. The timing of classifications gives insight into the real-time capabilities of the system. The Random Forest algorithm is chosen to create the machine learning model based on accuracy and timing capabilities. The model was able to achieve an accuracy of 100 % on new unseen testing data with an average classification time of 7.31 milliseconds. IEEE

6.
4th International Conference on Innovative Computing (ICIC) ; : 360-+, 2021.
Article in English | Web of Science | ID: covidwho-1985467

ABSTRACT

Facemask detection is a need of time as we are suffering in a pandemic situation of COVID-19, and facemask is considered the best preventive measure to stop the rapid spread. The vast majority of the world population is still unvaccinated, especially young and kids. Moreover, despite the vaccination, people are still getting Covid positive, and the majority are due to the Delta variant. So, we still need to have strict SOP implementation. The best way is to have some autonomous system to monitor SOP compliance and alert the authority to take countermeasures. Many people wear the mask, but the mask is usually on the chin and does not serve the purpose because the facemask must cover the mouth and nose to stop the spread. This study has proposed the improved version of the YOLOv4 model for the robust detection of face masks and checks whether the mask is worn in the recommended way. 2D convolutions of Yolov4 are replaced with the spatially separable convolutional in YOLOv4 to reduce the parameters so that the model can work in real-time. We have achieved an accuracy of 86.61% in terms of proper mask-wearing. Unlike other proposed approaches, our model is not only detecting the mask but also determines that whether the mask is worn in the recommended manner.

7.
Defence Life Science Journal ; 7(2):63-70, 2022.
Article in English | Scopus | ID: covidwho-1924726

ABSTRACT

The COVID-19 outbreak has caused an impervious financial and psychological burden. Health care professionals, including oral health care workers, have been risking fighting the pandemic. The chief objective of the current study was to estimate the rates of prevalence of depression, stress, and anxiety among the oral health care professionals in Jammu and Udaipur city. The study was delineated as an online cross-sectional questionnaire-based research. It was mailed to different practitioners between May and July 2020, particularly those offered their services in COVID centers. The participants were to fill the self report questionnaires. Then, the parameters were measured using depression, anxiety, and stress scale 21(DASS 21) and Hamilton anxiety rating scale (HARS) to measure the degrees of depression, stress, and fear among the volunteers. The target population was divided into age groups between 23 to 28 years and over 28 years. Four hundred ninety responses were received and were considered for the study. The acquired data were analysed using IBM SPSSsoftware (windows version 23). The mean and standard deviations were calculated for stress, anxiety, depression using mentioned scale. The results were compared based on gender and age group. A statistically significant variance in stress level was found between male and female groups (p=0.002) and for the two age groups (p=0.001). Using the Hamilton anxiety rating scale, no statistically significant divergence could be seen among male and female participants. The current study showed stress, anxiety, and depressions were prevalent among health care workers working in COVID pandemic situations. Therefore, mental health status must be addressed, and issues must be resolved. © 2022, DESIDOC.

8.
15th International Conference on Information Technology and Applications, ICITA 2021 ; 350:207-217, 2022.
Article in English | Scopus | ID: covidwho-1844322

ABSTRACT

COVID-19 has been affecting people around the globe. It is affecting almost every country currently, according to the World Health Organization (WHO). This virus is transmitted to another person if an asymptomatic person makes close contact with the everyday person. There is no cure for this virus, and the only solution is social distancing and avoids the people doing these activities. In this paper, we proposed a system for detecting and recognizing the activities that violate social distancing. These activities involve handshakes and hugging. We implement a system that is capable of detecting and identifying multiple parallel activities. Temporal features are extracted for similar activities in 16 frames. We use the two models for this purpose: Faster RCNN for the detection and ResNet-50 to recognize the activities. First, Faster RCNN detects the group of people and that region of interest ROI saved and passes to the ResNet-50 to recognize the activities. We also generated our dataset on the local environment in multiple parallel activities. This system achieves the accuracy of 95.03% for the detection of testing dataset and recognition of multiple parallel activities 92.88% accuracy accomplished. The system used different public datasets and generated some local datasets for handshake and hugging activities. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

9.
Journal of the American College of Cardiology ; 79(9):2512, 2022.
Article in English | EMBASE | ID: covidwho-1768643

ABSTRACT

Background: Complete heart block (CHB) is a cardiac conduction disorder commonly due to age-related degeneration of the conduction system. Other etiologies include hypothyroidism, Lyme disease or COVID-19, infiltrative cardiomyopathy, myocarditis, and atrioventricular (AV) nodal blocking agents. Hyperthyroidism is an extremely rare cause of CHB. Case: We present the case of a 40-year-old previously healthy male who presented after two syncopal episodes. He denied any home medications, recreational drug use, or prior syncopal episodes. He did endorse worsening palpitations, heat intolerance, anxiety, insomnia and diarrhea for one month. Initial EKG was normal. Labs revealed an undetectable thyroid stimulating hormone (TSH), and high T4 of 3.26 ng/dL. Potassium was 3.1 mMol/L which was replaced to normal levels. In the emergency department, he had another syncopal episode. Telemetry showed a 20 second episode of CHB. Patient was admitted and started on methimazole. Decision-making: Labs showed positive TSH receptor antibodies and thyroid stimulating immunoglobulins, confirming a diagnosis of Graves’ disease. COVID-19 IgG antibodies were positive with negative COVID-19 PCR, indicative of remote COVID 19 infection. Cardiac MRI did not show any myocarditis or infiltrative disease, and otherwise revealed a structurally normal heart. Lyme disease antibodies were negative. Toxicology screen was negative. Thyroid ultrasound showed diffuse heterogeneity of the gland. 72 hour telemetry monitoring revealed no further conduction abnormalities. At this point, CHB wes attributed to hyperthyroidism. As this was reversible, and CHB resolved after initiation of methimazole, a permanent pacemaker was not placed. He was discharged with a 30-day event monitor which did not show any conduction abnormalities. Conclusion: This case highlights a rare sequela of hyperthyroidism induced CHB. Although the pathophysiology is not well understood, a proposed mechanism is the direct toxic effect of T3 leading to focal inflammation of the AV node. Further studies are needed to evaluate the pathophysiology and chronicity of this process, which will assist in the decision to implant a permanent pacemaker.

10.
Journal of Fiber Bioengineering and Informatics ; 14(3):173-188, 2021.
Article in English | Scopus | ID: covidwho-1626157

ABSTRACT

Coronavirus belongs to the novel virulent strains of the respiratory viruses. It is an invisible enemy having significant threats to human health. The major trouble is that the spread of coronavirus is not limited to its transmission from human to human (by contact, fomites, and droplets) but also continue to transmit from contaminated surfaces to humans. These infectious viruses can survive in different non-biocidal materials for a long time. Copper holds a significant position in different biological and biochemical processes because its ions Cu+2 and Cu+ can carry out oxidation, dioxygen transportation, and electron transference. It is a redox-active metal. It can convert into Cu+2 or Cu+ state by accepting or donating electrons. Reactive Oxygen Species (ROS) are generated on alloy surfaces. The redox reaction of copper (Cu+2 ↔ Cu+) along with the generation of ROS results in enhanced inactivation of the virus. In this review, the effectiveness of copper against coronaviruses has been explained. The denaturing of specific proteins of coronavirus by the interaction of copper and its ions has also been reported. Hence, the copper coated surfaces could be used in public areas. Furthermore, the review represents the different techniques used for the coating of copper on conductive and non-conductive surfaces. Copyright © 2021 Textile Bioengineering and Informatics Society.

11.
14th Textile Bioengineering and Informatics Symposium, TBIS 2021 ; : 157-167, 2021.
Article in English | Scopus | ID: covidwho-1513607

ABSTRACT

Coronavirus belongs to the novel virulent strains of respiratory viruses. It is an invisible enemy that is a significant threat to human health. The major problem in the spread of coronavirus is that transmission is not limited to human to human (by contact, fomites, and droplets), it can also be transmitted from contaminated surfaces to humans. These infectious viruses can survive in different non-biocidal materials for a long time. Copper holds a significant position in different biological and biochemical processes because its ions Cu+2 and Cu+ can carry out oxidation, dioxygen transportation, and electron transference. It is a redox-active metal. It can convert into Cu+2 or Cu+ state by accepting or donating electrons. Reactive Oxygen Species (ROS) are generated on alloy surfaces. The redox reaction of copper (Cu+2 ↔ Cu+) along with the generation of ROS results in enhanced inactivation of the virus. In this review, the effectiveness of copper against coronaviruses is explained. The denaturing of specific proteins of coronavirus by the interaction of copper and its ions has also been reported. Hence, copper coated surfaces can be used in public areas to inhibit the spread of the virus. Furthermore, the review represents the different techniques used for the coating of copper on conductive and non-conductive surfaces. © 2019 Textile Bioengineering and Informatics Symposium Proceedings 2021 - 14th Textile Bioengineering and Informatics Symposium, TBIS 2021. All rights reserved.

12.
International Journal of Advanced Computer Science and Applications ; 12(7):553-567, 2021.
Article in English | Scopus | ID: covidwho-1365856

ABSTRACT

Globally, COVID-19 already emerged in around 170 million confirmed cases of infected people and, as of May 31, 2021, affected more than 3.54 million deaths. This pandemic has given rise to numerous public health and socioeconomic issues, emphasizing the significance of unraveling the epidemic’s history and forecasting the disease’s potential dynamics. A variety of mathematical models have been proposed to obtain a deeper understanding of disease transmission mechanisms. Machine Learning (ML) models have been used in the last decade to identify patterns and enhance prediction efficiency in healthcare applications. This paper proposes a model to predict COVID-19 patients admission to the intensive care unit (ICU). The model is built upon robust known classification algorithms, including classic Machine Learning Classifiers (MLCs), an Artificial Neural Network (ANN) and ensemble learning. This model’s strength in predicting COVID-19 infected patients is shown by performance analysis of various MLCs and error metrics. Among other used ML models, the ANN model resulted in the highest accuracy, 97.9% over other models. Mean Squared Error showed that the ANN method had the lowest error (0.0809). In conclusion, this paper could be beneficial to ICU staff to predict ICU admission based on COVID-19 patients’ clinical characteristics. © 2021. All Rights Reserved.

13.
Annals of King Edward Medical University Lahore Pakistan ; 27(1):120-129, 2021.
Article in English | Web of Science | ID: covidwho-1353283

ABSTRACT

Background: After declaration of the Covid-19 as pandemic by WHO, like every country of the world Pakistan also took exceptional precautionary measure to control the spread and transmission of this virus. These measures included strict lockdowns, shutting down educational institutions, markets, shopping malls, airports and masjids. The study primarily aimed to assess the individuals' knowledge, attitude, behavioral practices to prevent coronavirus and its psychological impacts on their mental health but later researcher also conducted another post study. Factually, the economic crisis, holy month of Ramadan and Eid-ul-Fitar forced the authorities soften the lockdown. Consequently, after this relaxation, the patients of Covid-19 as well as the death rates increased exponentially in Punjab. Methods: A non-equivalent quasi-experimental research designed was used to conduct pre and post study. An online survey having standardized questions about the peoples' knowledge regarding Covid-19, attitudes, their behavioral practices to prevent it and in what manner covid effected their mental health was conducted. Moreover, it also includes the information for demographics of sample. The link was sent to the participants through email, WhatsApp, Social media, Twitter, Facebook and LinkedIn. Similarly, same procedure was followed in post-study, with the same participants, but after a gap of three weeks. Results: Data was analyzed by SPSS and t-test was applied to draw comparisons among the responses of pre and post study. Results revealed that peoples' knowledge and attitude towards Covid-19 remained same in both studies, however, their behavioral practices to prevent Covid-19 and psychological impacts on their mental health (i.e., stress, depression, fear) greatly reduced in post study as compared to the prestudy. Conclusion: The authorities should initiate the health education programs to improve the knowledge, attitude and behavioral practices regarding Covid-19 and to combat its psychological impact on mental health. Besides, it is highly recommended that authorities should take bold steps to enforce formal, or smart lockdown to take control over the situation or else get ready to filled up the graveyards. The situation can also be controlled by enforcing precautionary measures and re-inviting awareness.

14.
Journal of General Internal Medicine ; 36(SUPPL 1):S348-S349, 2021.
Article in English | Web of Science | ID: covidwho-1348945
15.
Ieee Access ; 9:100040-100049, 2021.
Article in English | Web of Science | ID: covidwho-1331655

ABSTRACT

Corona Virus is a pandemic, and the whole world is affected due to it. Apart from the vaccine, the only cure for this drastic disease is to follow the rules and regulations that avoid further spread. There are different mechanisms like (Social Distancing, Mask Detection, Human occupancy etc.) through which we can able to stop the spread of the coronavirus. In this paper, we proposed hotspot zone detection using the computer vision techniques of deep learning. We have defined the hotspot area as the particular region on which the person touches more than some specified threshold. We further mark that area to some specific color to help the authority take necessary action and disinfect that particular place. To implement this algorithm, we have utilized the human-object interaction concept. We have extracted the dataset of person classes from the publicly available dataset for the person detection and the self-generated dataset to train the algorithm. Different experiments on object detection algorithms (YOLO-v3, Faster RCNN, SSD) for person detection have been performed in this work. We achieved the maximum accuracy in real-time on the YOLO-v3 for person detection. Whereas we have marked the specific area using the template matching algorithm of computer vision techniques. Our proposed algorithm detects the persons and extracts the region of interest points on which the user draws the rectangle. Then we find the intersection over union ratio between the detected person and the region of interest of the marked area to make the decision. We have achieved 88.72% accuracy on person detection in the local environment. Whereas, for the whole system of human-object interaction for detecting the hotspot area zone, we have achieved 86.7% accuracy using the confusion matrix.

16.
Ieee Consumer Electronics Magazine ; 10(2):92-97, 2021.
Article in English | Web of Science | ID: covidwho-1119176

ABSTRACT

The period after the COVID-19 wave is called the Echo-period. Estimation of crowd size in an outdoor environment is essential in the Echo-period. Making a simple and flexible working system for the same is the need of the hour. This article proposes and evaluates a nonintrusive, passive, and cost-effective solution for crowd size estimation in an outdoor environment. We call the proposed system as LTE communication infrastructure based environment sensing or LTE-CommSense. This system does not need any active signal transmission as it uses LTE transmitted signal. So, this is a power-efficient, simple, low-footprint device. Importantly, the personal identity of the people in the crowd cannot be obtained using this method. First, the system uses practical data to determine whether the outdoor environment is empty or not. If not, it tries to estimate the number of people occupying the near range locality. Performance evaluation with practical data confirms the feasibility of this proposed approach.

17.
IEEE Consumer Electronics Magazine ; 2020.
Article in English | Scopus | ID: covidwho-900839

ABSTRACT

The period after the COVID-19 wave is called the Echo-period. Estimation of crowd size in an outdoor environment is essential in the Echo-period. Making a simple and flexible working system for the same is the need of the hour. This article proposes and evaluates a non-intrusive, passive, and cost-effective solution for crowd size estimation in an outdoor environment. We call the proposed system as LTE communication infrastructure based environment sensing or LTE-CommSense. This system does not need any active signal transmission as it uses LTE transmitted signal. So, this is a power-efficient, simple low footprint device. Importantly, the personal identity of the people in the crowd can not be obtained using this method. First, the system uses practical data to determine whether the outdoor environment is empty or not. If not, it tries to estimate the number of people occupying the near range locality. Performance evaluation with practical data confirms the feasibility of this proposed approach. IEEE

18.
Biosens Bioelectron ; 166: 112431, 2020 Oct 15.
Article in English | MEDLINE | ID: covidwho-654767

ABSTRACT

Last few decades, viruses are a real menace to human safety. Therefore, the rapid identification of viruses should be one of the best ways to prevent an outbreak and important implications for medical healthcare. The recent outbreak of coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus which belongs to the single-stranded, positive-strand RNA viruses. The pandemic dimension spread of COVID-19 poses a severe threat to the health and lives of seven billion people worldwide. There is a growing urgency worldwide to establish a point-of-care device for the rapid detection of COVID-19 to prevent subsequent secondary spread. Therefore, the need for sensitive, selective, and rapid diagnostic devices plays a vital role in selecting appropriate treatments and to prevent the epidemics. During the last decade, electrochemical biosensors have emerged as reliable analytical devices and represent a new promising tool for the detection of different pathogenic viruses. This review summarizes the state of the art of different virus detection with currently available electrochemical detection methods. Moreover, this review discusses different fabrication techniques, detection principles, and applications of various virus biosensors. Future research also looks at the use of electrochemical biosensors regarding a potential detection kit for the rapid identification of the COVID-19.


Subject(s)
Betacoronavirus , Biosensing Techniques/instrumentation , Clinical Laboratory Techniques/instrumentation , Coronavirus Infections/diagnosis , Electrochemical Techniques/instrumentation , Pneumonia, Viral/diagnosis , Viruses/isolation & purification , Animals , Betacoronavirus/isolation & purification , Betacoronavirus/pathogenicity , COVID-19 , COVID-19 Testing , Coronavirus Infections/virology , Equipment Design , Humans , Metal Nanoparticles/chemistry , Metal Nanoparticles/ultrastructure , Microscopy, Electron, Scanning , Pandemics , Pneumonia, Viral/virology , Point-of-Care Testing , SARS-CoV-2 , Viruses/pathogenicity
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