ABSTRACT
When the nation is facing a great downfall of economic activities leading to many disturbances in the daily life of people, savings and investment plan can hold the hands of employees belonging to private sector from financial fall down. The present study exposes the savings and investment preferences of private sector employees due to the effect of COVID-19 pandemic. As information shows that salary reduction and job termination have become common events in private sector due to the present pandemic, it becomes necessary to understand how far the pandemic has influenced their savings and investment. Likert scale and Garret ranking are two statistical tools used in the study to analyse major influencing factors of COVID-19 pandemic and the mostly preferred factor by the private sector employees. The study concludes that this pandemic has a significant influence leading to deregulating existing plans as well as decline in proportion of savings and investments.
ABSTRACT
The importance of small and medium-sized enterprises (SMEs) are important in a nation's economic development. In the middle of the COVID-19 pandemic, this study seeks to analyze the employment happiness of employees in various SME enterprises through the mediation of corporate initiatives. It focuses on the elements of job satisfaction and their effects on employees' total job satisfaction, as well as the mediation effect of satisfaction with organizational Covid-19 responses. The conclusion indicates that job security, a relationship with the supervisor, benefits opportunities, and working circumstances are the most influential elements contributing to job satisfaction. However, all aspects except job security influence satisfaction with organizational answers to Covid-19. The outcome also indicates the moderating effect of organizational reactions to the Covid-19 epidemic on promotion possibilities and employee satisfaction. For SMEs, the nature of business operations, the workplace culture, and the level of job satisfaction have undergone a major change. Therefore, the purpose of this study was primarily to evaluate the impact of factors such as working conditions, salary and advancement, job security, fairness, and relationships with coworkers and supervisors on job satisfaction. This study provides a complete analysis of the job satisfaction indices of the pharmaceutical industry, the elements producing discontent, and recommendations for their improvement. © 2022, International Forum of Management Scholars. All rights reserved.
ABSTRACT
Physical distancing and visiting restrictions during the COVID-19 pandemic posed significant challenges in providing timely medical care in nursing homes. The rising number of new COVID-19 cases created hardship in providing scheduled and non-urgent care visits. Virtual visits were pivotal in providing patient care. However, the additional responsibility of facilitating virtual visits for both social and clinical purposes further constrained the ability of nursing home staff to provide care. The critical deficiency of the workforce, rising numbers of new cases, and required triage of patients have been significant barriers to regularly scheduled care. We hypothesize that regular non-COVID-19 services in the evaluated nursing home facilities were lower than COVID-19 visits during this period. Our goal is to show the types of services affected during the pandemic. In this study, we analyzed 563 virtual visits during the COVID-19 pandemic in three nursing home facilities in Michigan from December 2020 through February 2022. Upon analyzing the types of services and trends, our results revealed that the number of COVID-19 related visits (68) was significantly lower than non-COVID-19 related visits (485), refuting our hypothesis. This illustrates that routine care could still be delivered during the pandemic. Additionally, the overall number of virtual visits declined steadily over the study period. This trend could suggest an increase of in-person services or a decrease in COVID-19 cases. The decline could also be related to the barriers faced by the nursing home workforce considering the time and additional responsibility of monitoring a virtual visit.
ABSTRACT
Machine Learning methods have been used to combat COVID-19 since the pandemic has started in year 2020. In this regard, most studies have focused on detecting and identifying the characteristics of SARS-CoV-2, especially via image processing. Some studies have applied machine learning for contact tracing to minimise the transmission of COVID-19 cases. Limited work has, however, reported on how geospatial features have an influence on the transmission of COVID-19 and formation of clusters at local scale. Therefore, this paper has aimed to study the importance of geospatial features that had resorted to COVID-19 cluster formation in Kuala Lumpur, Malaysia in year 2021. Several datasets were used in this work, which have included the address details of confirmed positive COVID-19 cases and the details of nearby residential areas and Points of Interest (POI) located within the federal territory of Kuala Lumpur. The datasets were pre-processed and transformed into an analytical dataset for conducting empirical investigations. Various feature selection methods were applied, including the Boruta Algorithm, Chi-square (Chi2) Test, Extra Trees Classifier (ETC), Recursive Feature Elimination (RFE) method, and Deep Learning Autoencoder (DLA). Detailed investigations on the top-n features were performed to elicit a set of optimal features. Subsequently, several machine learning models were trained using the optimal features, including Logistic Regression (LR), Random Forest Classifier (RFC), Naïve Bayes Classifier (NBC), and Extreme Gradient Boosting (XGBoost). It was revealed that Boruta produced the optimal number of features with n = 96, whereas RFC achieved the best prediction results compared to other classifiers, with around 95% accuracy. Consequently, the findings in this paper help to recognize the geospatial features that have impacts on the formation of COVID-19 and other infectious disease clusters at local scale. © 2022, Success Culture Press. All rights reserved.
ABSTRACT
Particulate matters having diameters of 2.5 micrometers or less (PM2.5) have been linked with life threatening health issues worldwide. Data centric approach to ascertain the patterns in the propagation of PM2.5 materials in the atmosphere of a region can help policy makers take informed decisions to take proper action. In this paper, we analyze and identify seasonal, hourly, and regional patterns of PM2.5 propagation in Bangladesh from 2017 to 2020 using the Berkeley Earth dataset. We observe that the concentration of PM2.5 particles has a nationwide median value of about 50 mu gm(-3), which is unhealthy for sensitive individuals. The concentration varies seasonally and diurnally. We observe that the concentrations of PM2.5 in the air is around five times more in winter than in summer. The mean PM2.5 concentration inside Dhaka is significantly worse around 70 mu gm(-3), which is 1.25 times than the average concentration throughout Bangladesh. We also observe average concentration dropped during the covid-19 pandemic due to lockdown. Using cross correlation analysis, we observed how spikes in PM2.5 concentration levels in one zone may correspond with peaked concentrations in a different zone a few hours later, indicating that air currents may cause the particles to move in certain directions. Our exploratory analysis serves as the first cross-country data centric study of the state and propagation patterns of PM2.5 particles within Bangladesh and our findings can serve as foundation for further research on the topic.
ABSTRACT
Multiple chronic medical conditions are common to patients served by the community mental health (CMH) system. Medical diseases are present in at least 50% of all patients with psychiatric conditions, and severe mental disorders are associated with significant physical comorbidity and mortality. Early data show that individuals with preexisting multiple chronic conditions have a higher mortality risk when they are symptomatic with COVID-19. Although mitigation guidelines and recommendations are constantly being reviewed and updated, we found no specific recommendations targeting the vulnerable population who use CMH systems or the publicly funded and managed behavioral health entities which serve them. We reviewed the Centers for Disease Control and Prevention guidelines regarding infection control in health care facilities that provide ambulatory care, including behavioral health clinics, as well as reviewed recent population outcomes data. We posit that the population served by the CMH systems is a higher-risk cohort than the general population and offer recommendations for effective infection prevention strategies specific to this population.
ABSTRACT
The way Covid-19 pandemic is being understood and addressed makes it a spectacle in the Debordian sense, in which all the social relations are mediated through images and appearances. Where even the desire of a safe and healthy life is dealt not with dignity, and effective, accessible healthcare, but through virtual images. Such a spectacle, in turn, creates a world that would be connected more, while the people would live a fragmented life on which they will increasingly lose their control. © 2020 Economic and Political Weekly. All rights reserved.