Deadly Coronavirus Research Articles

The Covid-19 Pandemic: The deadly coronavirus outbreak, Second Edition

The Covid-19 Pandemic: The deadly coronavirus outbreak, Second Edition

Developing and Implementing an IoT Managed by Electronic Devices for Covid Patient Monitoring via a Secured Communication System

End of 2019 had seen global spread of the deadly coronavirus (SARS-CoV-2) pandemic, which kills people, puts a large portion of the world in danger, and poses a serious threat to all of the world's nations. Leading medical professionals are working extremely hard to identify the virus, develop treatments for it, and create the vaccines that are required to stop and limit its spread. This study intends to develop a low-cost electronic health system to observe patients with covid infections and lessen the work required of clinicians. An enhanced approach for remote health monitoring in hospitals or detention facilities is offered by the internet of things (IoT). The IoT keeps and displays the patient's medical data via a web browser or through specialized apps that offer remote treatment once the sensors collect it. When a patient is in danger, the system offers immediate action to send alarms by email and SMS and to rapidly provide drugs to the patient. Doctors will be updated on each patient's condition thanks to this message.

Predictive Healthcare Analysis of Pakistan’s COVID-19 Pandemic Using Data Mining and Time Series Modelling

The novel coronavirus (COVID-19) has significantly spread worldwide and has come up with new challenges to the research community. This forced many affected countries to take stringent measures such as complete lockdown, shutting down businesses and trade, and travel restrictions, which has had a tremendous economic impact. Pakistan has also faced five waves of the deadly coronavirus. Therefore, having knowledge and foresight about how a country can contain the spread of COVID-19 will be of paramount importance to the government, policymakers, business partners, and entrepreneurs. In order to forecast the COVID-19 pandemic's spread, we apply AI-based forecasting models such as time series ARIMA, LSTM, fb Prophet, and VAR. These methods aid in informing public health authorities and policymakers' decisions about how to combat the pandemic. This paper demonstrates the promising potential of the time series model in forecasting COVID-19 cases and highlights the superior performance of the time series compared to the LSTM.

Using ICT Tools and Technological Applications in this Era of the COVID-19 Pandemic to Facilitate Learning

Abstract The globe is shaken by the abrupt emergence of the deadly Coronavirus Disease 2019 (COVID-19) pandemic. The global education system has been put to the test by this circumstance, which compelled educators to quickly adopt Information & Communication Technology (ICT) tools and technologies to support instruction. Although, great attempts are made by scholars to study the implications of Coronavirus Disease 2019 on the higher education curricular, there is dearth of previous studies regarding the impact of Information & Communication Technology tools and technological applications to foster learning amid Coronavirus Disease 2019 outbreak. This exploratory study therefore uses a meta-synthesis approach and visited relevant literatures as lens to primarily examine the need to use Information & Communication Technology tools and technology applications to enhance learning in the Coronavirus Disease 2019 age. The research also shed some insight on the difficulties involved with employing Information & Communication Technology tools and technical applications to aid learning in times of pandemic and catastrophes, and it offers potential answers to educational institutions on how to handle these complications. The study’s findings suggest that Information & Communication Technology tools and technologies are the magic bullet for optimizing learning in times of disaster like the Coronavirus Disease 2019 pandemic. The study also shows that by overcoming some technical and financial obstacles like high cost of technology devices, electricity problems, lack of expertise, etc., the lessons learnt from the abrupt and compulsory adoption of Information & Communication Technology tools and technologies to lessen the negative effects of the disaster on learning amid Coronavirus Disease 2019 global emergency will help create new opportunities for the use of blended learning approaches to meet the needs of the Coronavirus Disease 2019 disruption and future learning deliveries.

A recombination-resistant genome for live attenuated and stable PEDV vaccines by engineering the transcriptional regulatory sequences.

Coronaviruses are important pathogens of humans and animals, and vaccine developments against them are imperative. Due to the ability to induce broad and prolonged protective immunity and the convenient administration routes, live attenuated vaccines (LAVs) are promising arms for controlling the deadly coronavirus infections. However, potential recombination events between vaccine and field strains raise a safety concern for LAVs. The porcine epidemic diarrhea virus (PEDV) remodeled TRS (RMT) mutant generated in this study replicated efficiently in both cell culture and in pigs and retained protective immunogenicity against PEDV challenge in pigs. Furthermore, the RMT PEDV was resistant to recombination and genetically stable. Therefore, RMT PEDV can be further optimized as a backbone for the development of safe LAVs.

What is the Digitalised Curriculum for?

The emergence of the deadly corona virus, popularly known as COVID-19, caused a hasty and ill-prepared paradigm shift in higher education institutions. Formerly reliant on the face-to-face mode of teaching and learning, the need for physical distancing recommended by the World Health Organization forced them to adopt a digitalised curriculum. This article exploreswhether the digitalised curriculum adopted by a higher education institution in Lesotho was for qualification, socialisation and/ or subjectification. In other words, it investigates which propositions are influenced by the digitalised curriculum. Purposive sampling was used to select five studies conducted in Lesotho during/post the COVID-19 pandemic. The tree three rings theory was used to frame the study, with thematic analysis through critical discourse analysis employed to analyse the data. The findings suggest that, to some extent, the use of a learning management system favours qualification at the expense of both socialisation and subjectification. In addition, the digital divide was glaringly evident in the adoption of online learning. Formal incorporation of social media sites is recommended to enable students to socialise with prescribed content and to utilise their unique experiences with digital technologies to achieve their prescribed goals.

Digital-Twins-Based Internet of Robotic Things for Remote Health Monitoring of COVID-19 Patients

The deadly coronavirus disease (COVID-19) has highlighted the importance of remote health monitoring (RHM). The digital twins (DTs) paradigm enables RHM by creating a virtual replica that receives data from the physical asset, representing its real-world behavior. However, DTs use passive internet of things (IoT) sensors, which limit their potential to a specific location or entity. This problem can be addressed by using the internet of robotic things (IoRT), which combines robotics and IoT, allowing the robotic things (RTs) to navigate in a particular environment and connect to IoT devices in the vicinity. Implementing DTs in IoRT, creates a virtual replica (virtual twin) that receives real-time data from the physical RT (physical twin) to mirror its status. However, DTs require a user interface for real-time interaction and visualization. Virtual reality (VR) can be used as an interface due to its natural ability to visualize and interact with DTs. This research proposes a real-time system for RHM of COVID-19 patients using the DTs-based IoRT and VR-based user interface. It also presents and evaluates robot navigation performance, which is vital for remote monitoring. The virtual twin (VT) operates the physical twin (PT) in the real environment (RE), which collects data from the patient-mounted sensors and transmits it to the control service to visualize in VR for medical examination. The system prevents direct interaction of medical staff with contaminated patients, protecting them from infection and stress. The experimental results verify the monitoring data quality (accuracy, completeness, timeliness) and high accuracy of PT’s navigation.

An Empirical Study on Impact of Emotional Intelligence on Patient Satisfaction

This study investigates the impact of emotional intelligence (EI) on patient satisfaction during covid-19 pandemic.Emotional intelligence is recognized as a vital concern for managing customer relationships post covid-19 times. During covid-19 situation people were in a severe psychological stress. They were busy in engaging themselves to shield from the effects of deadly corona virus. Those who affected by covid-19 virus faced many psychological fears which lead them to fall in a trauma condition. Many people admitted in hospitals irrespective of age and gender which indicated the harness of virus. The pandemic not only bulldozed the respiratory fitness but also the psychological fitness of people. The panic created by covid-19 virus lead to many emotional fears especially among the patients who admitted in hospitals during the pandemic period. The Health care workers, who worked really hard to save the lives of people despite of the fatal fears of the Covid-19. The essential element in managing people stress is emotional intelligence. This research work entitles to find the impact of emotional intelligence of people affected by covid-19 on their satisfaction. It’s a cross sectional study conducted on 252 patients (covid-19) on convenience sampling basis. The study highlighted the association between patients emotional intelligence, patients stress during covid-19 and patient satisfaction.

Second-Wave Effects of Covid’19 Pandemic on Transportation Business: Keke-Napep and Motor-Cycle Transport Systems in Asaba Metropolis, Nigeria

Transnational, global trades, investments, travels amongst other drivers of globalization helped to reverberate the deadly coronavirus pandemic from Wuhan, China across the world like whirl fire. In order to contain the infectious spread of the pandemic and mitigate its negative effects on macro-economic variables, World Health Organization, WHO designed Covid-19 protocols that are being enforced by governments and people of the world. It is on this account that the study examined the Second wave effect of Covid’19 pandemic on transportation business: Keke-Napep and Motor-cycle transport systems in Asaba metropolis, Nigeria. The main objective is to determine empirically the real impact of the pandemic on rural land transport business. The study employed structured questionnaire and interview methods to generated data from the 250 respondents selected using census sampling technique. Out of the 250 sets of questionnaire administered, 235 (94%) were retrieved while 15 (6%) were rejected. The statistical tools used for analyzing data were correlation and multiple regression techniques. Findings were that covid’19 pandemic negatively affected rural land transport business. The study concludes that the coronavirus pandemic caused a contraction in transport business. It is therefore recommended that, there is need for government to relax the stringent covid’19 protocols to allow economic activities to resume again. Campaigns on safety and hygiene should be intensified so that the populace will imbibe the culture of general cleanliness and personal hygiene amongst others.

IMPACT OF COVID-19 ON BREAST CANCER SCREENING PROGRAM (BCSP) IN INDIA

In the past three years, covid-19 viruses have spread rapidly worldwide, while low and middle-income countries were affected mostly so far. Emergency limits were imposed due to the rapid infection and significant mortality rates. Only emergency medical treatments are available during these shutdowns and lockdowns in India. All non-emergency treatments, such as Breast Cancer Screening Program (BCSP), have been temporarily halted due to the huge number of deaths caused by coronavirus. However, the ability of BC screening programs to improve survival rates while lowering mortality rates has been well demonstrated. Suspension may result in poorer outcomes for patients with BC. In this regard, early detection and treatment are critical for increased survival and long-term quality of life. Thus, we have taken breast cancer patients' data for the last six years i.e. from 2016 to 2021 in India to properly evaluate and analyze for our research. Assessing recent results for various features from, modeled evaluations can aid pandemic responses. Besides that, we proposed a novel method that implements the EDA technique to graphically represent BC patients' data. This experiment was done using Python programming language on Jupyter 6.4.3 platform. We found the sudden rise of BC patients from lakhs to millions in 2019. This signifies the deadly coronavirus has greatly affected people during the pandemic days when people are more serious about this virus rather than screening their breasts.

IMPACT OF COVID-19 ON BREAST CANCER SCREENING PROGRAM (BCSP) IN INDIA

In the past three years, covid-19 viruses have spread rapidly worldwide, while low and middle-income countries were affected mostly so far. Emergency limits were imposed due to the rapid infection and significant mortality rates. Only emergency medical treatments are available during these shutdowns and lockdowns in India. All non-emergency treatments, such as Breast Cancer Screening Program (BCSP), have been temporarily halted due to the huge number of deaths caused by coronavirus. However, the ability of BC screening programs to improve survival rates while lowering mortality rates has been well demonstrated. Suspension may result in poorer outcomes for patients with BC. In this regard, early detection and treatment are critical for increased survival and long-term quality of life. Thus, we have taken breast cancer patients' data for the last six years i.e. from 2016 to 2021 in India to properly evaluate and analyze for our research. Assessing recent results for various features from, modeled evaluations can aid pandemic responses. Besides that, we proposed a novel method that implements the EDA technique to graphically represent BC patients' data. This experiment was done using Python programming language on Jupyter 6.4.3 platform. We found the sudden rise of BC patients from lakhs to millions in 2019. This signifies the deadly coronavirus has greatly affected people during the pandemic days when people are more serious about this virus rather than screening their breasts.

A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media

Coronaviruses are a well-established and deadly group of viruses that cause illness in both humans and animals. The novel type of this virus group, named COVID-19, was firstly reported in December 2019, and, with the passage of time, coronavirus has spread to almost all parts of the world. Coronavirus has been the cause of millions of deaths around the world. Furthermore, many countries are struggling with COVID-19 and have experimented with various kinds of vaccines to eliminate the deadly virus and its variants. This survey deals with COVID-19 data analysis and its impact on human social life. Data analysis and information related to coronavirus can greatly help scientists and governments in controlling the spread and symptoms of the deadly coronavirus. In this survey, we cover many areas of discussion related to COVID-19 data analysis, such as how artificial intelligence, along with machine learning, deep learning, and IoT, have worked together to fight against COVID-19. We also discuss artificial intelligence and IoT techniques used to forecast, detect, and diagnose patients of the novel coronavirus. Moreover, this survey also describes how fake news, doctored results, and conspiracy theories were spread over social media sites, such as Twitter, by applying various social network analysis and sentimental analysis techniques. A comprehensive comparative analysis of existing techniques has also been conducted. In the end, the Discussion section presents different data analysis techniques, provides future directions for research, and suggests general guidelines for handling coronavirus, as well as changing work and life conditions.

Leadership and power dynamics in crisis management: implication for brain-drain behaviour – Singaporean government experience during Covid-19

PurposeThis study explored how the Singaporean government responded to the Covid-19 pandemic crisis from early January 2020 to the end of May of the same year. It evaluated the capability of Singapore's leadership management in a crisis during the peak and ravaging period of the Covid-19 pandemic.Design/methodology/approachThe study utilised a systematic design analysis approach, analysing Singaporean cases on the Covid-19 crisis using a systematic and narrative approach to underscore the country's response to the pandemic attack from January 2020 to May 2020.FindingsAgainst the backdrop of Singapore's peculiar political system of government dominated by the ruling People's Action Party (PAP) and culture of bureaucracy, the government has increasingly executed several control measures, including strict travel bans, contact tracing, the circuit breaker–lockdown, mask-wearing, social distancing orders as well as financial support to businesses and employees from top to the bottom in the country. However, the treatment and health issues of the migrant workers in the dormitories continue to be the major concern among academics and scholars. At the same time, policy inadequacies truncate the excellent measure of Singapore's response to Covid-19. The case point review concluded that the mortality rate in Singapore remains low compared to other nations of the world. Singapore's case points unveil fundamental learning that an excellent leadership-driven harmonised strategic model is essential for crisis management in any society. The finding of the analysis demonstrated that Singapore adopted a contingency and value-based leadership model to advance good governance and tackle the spread of the deadly coronavirus in its country.Originality/valueThe study has demonstrated a profound analysis that has not been conducted hitherto. Investigation of the Singapore case point is not a popular analysis among Nigerian scholars. Therefore, from Nigeria's perspective, the study has showcased the good and the wrong sides of a coin in Singapore's leadership and power dynamic in crisis management.

I Can’t Abandon My Father: Covid-19 and Lay Caregiving at the Crossroads in the Eastern Regional Hospital of Ghana.

Lay caregivers play very important roles in the care of sick relations. This primordial support appears to be universal but manifests itself in different ways and circumstances. Ghanaian public health institutions, especially, depend very much on lay caregivers in the management of in-patients. However, with the emergence of Covid-19, and the fear of nosocomial infections one expects less involvement of lay caregivers; looms large. This fear has been heightened by the presence of the deadly corona virus pandemic. In spite of the respectable volume of works on lay caregivers, there is dearth of literature on the factors that influence relations to provide care in the clinical set-up in spite of the care given by the professional cohort and the possible threats to health of lay caregivers. This is the classic case of a clash between health professionals and non-professionals in the performance of tasks with the same goal orientation: to assist the sick to get out of their sick role. This hospital ethnographic study which focused on the Koforidua Regional Hospital, explored the compelling socio-cultural factors that influence lay caregiving in the hospital environment. The study is especially relevant in the midst of the Covid-19 pandemic. The study involved interviews with patients in a medical ward, health professionals and lay caregivers in the regional hospital. The study revealed that lay caregivers, among other reasons, are influenced by socio-cultural factors such as reciprocity and kinship moral obligations, and the perceived poor attitude of the health staff towards patients. Institutionally, although the medical staff found lay involvement unwelcome, shortage of staff, the severity of a patient’s condition, and lack of certain facilities make lay involvement a ‘tolerated nuisance.’

Swadeshi Versus Global Brands: Mapping the Efficacy of the Self-reliance Invocation

A lot of things have changed since the deadly Coronavirus attack the world has changed upside down. There are changes in systems and operations of business, reforms in economic and financial policies all over the world and so in India. After the local pitch in support of local business by honourable Prime Minister of India, ‘go vocal for local’, as a step towards atmanirbhar economy, on one hand there are consumers who are prepared to buy only domestic brands while on the other hand some are unwilling to give up global brands completely or selectively. At this instance, it will be interesting to study the willingness of consumers to adopt swadeshi and give up global brands for some chosen product and service categories like electronics, apparels, FMCG, restaurants and services apps. This study was primary in nature. EFA and regression analysis were employed for analysing the data. The results suggested that nationalism and anti-China sentiments have a significant impact on consumer inclination for swadeshi Brands. Hence Government, Entrepreneurs and Industrialist must take suitable actions to use these sentiments for increasing the acceptability of domestic brands and hence invocate Atmnirbhar Bharat (Self Reliant India).

Artificial intelligence centric scientific research on COVID-19: an analysis based on scientometrics data

With the spread of the deadly coronavirus disease throughout the geographies of the globe, expertise from every field has been sought to fight the impact of the virus. The use of Artificial Intelligence (AI), especially, has been the center of attention due to its capability to produce trustworthy results in a reasonable time. As a result, AI centric based research on coronavirus (or COVID-19) has been receiving growing attention from different domains ranging from medicine, virology, and psychiatry etc. We present this comprehensive study that closely monitors the impact of the pandemic on global research activities related exclusively to AI. In this article, we produce highly informative insights pertaining to publications, such as the best articles, research areas, most productive and influential journals, authors, and institutions. Studies are made on top 50 most cited articles to identify the most influential AI subcategories. We also study the outcome of research from different geographic areas while identifying the research collaborations that have had an impact. This study also compares the outcome of research from the different countries around the globe and produces insights on the same.

A Modified Artificial Neural Network (ANN)-Based Time Series Prediction of COVID-19 Cases from Multi-Country Data

The deadly Corona virus that first appeared in a seafood market in the Wuhan city of China in December 2019 has been causing global distress by claiming lives and collapsing economies. Given its serious nature, there is an urgent need to understand the virus’s future trajectory. The current study predicts the next day confirmed, death and recovery cases of COVID-19 pandemic for India, Italy, Spain, and the USA by using a modified multilayer neural network (MMLNN) model. The spread of the COVID-19 data is collected from the Kaggle website for the period of 22nd January 2020 to 20th April 2020 (i.e., for 90 days). The predicted figures of the spread of the disease have been estimated and compared with the actual values. Higher precision of the estimates has been observed from the MMLNN model compared to the conventional multilayer neural network (MLANN) model. Specifically, the MMLNN model does faster and more efficient training of the data resulting in less error. The paper forecasts the next day figures (i.e., for 21st April) for all the three cases and does the comparison of the results with the actual values reported. A deviation of 6% is obtained for India, and for the other three countries the deviation is below 3.5%. Given the high accuracy predictive power, the authors recommend that the MMLNN model can be integrated into the health policy of the countries that are struggling with the spread of the virus. Specifically, a decision on health policies such as restrictions on movement can be based on the short-range predictions of the spread of the virus infection.

Smart Face Masks for COVID-19 Pandemic Management: A Concise Review of Emerging Architectures, Challenges and Future Research Directions

Smart sensing technology has been playing tremendous roles in digital healthcare management over time with great impacts. Lately, smart sensing has awoken the world by the advent of smart face masks (SFMs) in the global fight against the deadly Coronavirus (Covid-19) pandemic. In turn, a number of research studies on innovative SFM architectures and designs are emerging. However, there is currently no study that has systematically been conducted to identify and comparatively analyze the emerging architectures and designs of SFMs, their contributions, socio-technological implications, and current challenges. In this article, we investigate the emerging SFMs in response to Covid-19 pandemic and provide a concise review of their key features and characteristics, design, smart technologies, and architectures. We also highlight and discuss the socio-technological opportunities posed by the use of SFMs and finally present directions for future research. Our findings reveal four key features that can be used to evaluate SFMs to include reusability, self-power generation ability, energy awareness and aerosol filtration efficiency. We discover that SFM has potential for effective use in human tracking, contact tracing, disease detection and diagnosis or in monitoring asymptotic populations in future pandemics. Some SFMs have also been carefully designed to provide comfort and safety when used by patients with other respiratory diseases or comorbidities. However, some identified challenges include standards and quality control, ethical, security and privacy concerns.

Effects of acceptance of enlightenment on COVID-19 transmission using homotopy perturbation method

The deadly Corona virus disease has had a significantly devastating impact on the general public, necessitating the study of transmission dynamics. A mathematical model of a non-linear differential equation for COVID-19 infection is investigated with the effects of some basic factors, such as the acceptance of enlightenment to avoid being exposed and the acceptance of enlightenment to go for vaccination. The basic reproduction number, which determines the disease’s spread, is calculated. The local and global stability analyses of the model are carried out. The sensitivity analysis is also computed. Numerical simulation using the homotopy perturbation method demonstrates the effect of the acceptance of enlightenment on the population. Our results indicate that when the populace accepts vaccination, the rate at which COVID-19 spreads reduces.

The Conundrum of Corruption During a Coronavirus Lockdown in Zimbabwe: Lessons for Social Work

ABSTRACT Faced with the serious threat of the deadly coronavirus, governments of different nations were swift to respond to the pandemic by declaring national lockdowns. Having confirmed fewer than ten cases of coronavirus that had tested positive, Zimbabwe called for a national lockdown which initially lasted three weeks before declaring it ‘indefinite’. Despite the fact that the lockdown declared in Zimbabwe was in the interest of public health, anecdotal evidence indicates that there has been an inextricable nexus between the lockdown and increased corrupt tendencies. This paper, which is a product of qualitative research, utilised a narrative research approach and documentary analysis to explicate the relationship between Zimbabwe’s coronavirus lockdown and corruption. The paper looks at the different forms of corruption that occurred during the coronavirus lockdown in Zimbabwe and the implication of these on the well-being and welfare of economically vulnerable groups. In conclusion, the paper indicates the role that can be played by pro-human rights professionals such as social workers in the fight against corruption during emergency times to ensure transparency and accountability.