Impact of the COVID-19 pandemic on healthcare workers’ families

Helou, Mariana; Osta, Nour El; Husni, Rola

doi:10.12998/wjcc.v10.i27.9964

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…By harnessing IoT data and semantic technologies, the system provides actionable insights in real time, enabling proactive management of COVID-19 outbreaks. This capability is proven through a rigorous comparative analysis against existing methods, highlighting SDSIF's superior predictive accuracy and early warning capabilities [38,[40][41][42].…”

Section: Proactive Data-driven Management Of Covid-19 Outbreaksmentioning

confidence: 99%

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SEIR‐driven semantic integration framework: Internet of Things‐enhanced epidemiological surveillance in COVID‐19 outbreaks using recurrent neural networks

Sarin,

Singh,

Kumar

et al. 2024

IET Cyber-Phy Sys Theory & Ap

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With the current COVID‐19 pandemic, sophisticated epidemiological surveillance systems are more important than ever because conventional approaches have not been able to handle the scope and complexity of this global emergency. In response to this challenge, the authors present the state‐of‐the‐art SEIR‐Driven Semantic Integration Framework (SDSIF), which leverages the Internet of Things (IoT) to handle a variety of data sources. The primary innovation of SDSIF is the development of an extensive COVID‐19 ontology, which makes unmatched data interoperability and semantic inference possible. The framework facilitates not only real‐time data integration but also advanced analytics, anomaly detection, and predictive modelling through the use of Recurrent Neural Networks (RNNs). By being scalable and flexible enough to fit into different healthcare environments and geographical areas, SDSIF is revolutionising epidemiological surveillance for COVID‐19 outbreak management. Metrics such as Mean Absolute Error (MAE) and Mean sqḋ Error (MSE) are used in a rigorous evaluation. The evaluation also includes an exceptional R‐squared score, which attests to the effectiveness and ingenuity of SDSIF. Notably, a modest RMSE value of 8.70 highlights its accuracy, while a low MSE of 3.03 highlights its high predictive precision. The framework's remarkable R‐squared score of 0.99 emphasises its resilience in explaining variations in disease data even more.

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Section: Proactive Data-driven Management Of Covid-19 Outbreaksmentioning

confidence: 99%

“…Addressing these challenges demands ongoing collaboration among domain experts, data scientists, and ontologists to refine ontology design, enhance data interoperability, and mitigate potential limitations in SDSIF's semantic integration capabilities. [40][41][42].…”

Section: Limitation Of Sdsif Modelmentioning

confidence: 99%

SEIR‐driven semantic integration framework: Internet of Things‐enhanced epidemiological surveillance in COVID‐19 outbreaks using recurrent neural networks

Sarin,

Singh,

Kumar

et al. 2024

IET Cyber-Phy Sys Theory & Ap

View full text Add to dashboard Cite

show abstract

“…An enormous burden on healthcare services has been caused by the COVID-19 pandemic, a health emergency [6][7][8]. Medical professionals dealing with COVID-19 patients encounter many difficulties amid this unprecedented epidemic.…”

Section: The Effect Of Covid 19 On Health Workersmentioning

confidence: 99%

“…The COVID-19 pandemic has placed a significant burden on healthcare services, leading to various difficulties for medical professionals caring for COVID-19 patients [6,7,24]. Research has highlighted the high rates of burnout, psychological stress, and the need for attention to the mental well-being of healthcare workers (HCWs) [9].…”

Section: Servant Leadershipmentioning

confidence: 99%

The Role of Servant Leadership in Supporting the Health Workforce during COVID 19

Abdulai

2023

AJMAH

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The COVID-19 pandemic has had a profound impact on healthcare workers worldwide. These individuals have been on the front lines, risking their health and safety to care for patients. However, the emotional toll of the pandemic cannot be overlooked. Healthcare workers are not only dealing with the physical demands of their jobs but also the psychological stress and anxiety that comes with caring for patients during a global crisis. Effective leadership is crucial in every organization, however, some organizations such as healthcare need leaders who are capable of inspiration and psychological safety. This is because health workers endure so much stress and anxiety resulting from the concerns and empathic connection with their clients. Servant leadership, an emerging leadership style, is particularly suitable during crises, such as the recent COVID-19 pandemic. Servant leadership is a style that focuses on serving the needs of others and prioritizing their well-being. This leadership approach is particularly suited to the healthcare industry, where the well-being of patients and staff is of utmost importance. Servant leaders create a culture of psychological safety, where healthcare workers feel supported and valued. This includes ensuring that healthcare workers have access to personal protective equipment, providing emotional support and counselling services, and recognizing and appreciating their efforts. To put the effect of servant leadership into perspective, this article highlights some effects of COVID-19 on health workers and follows up to present a view on how servant leaders would mitigate the effects on the workers. Current and future managers of the healthcare system should undertake training on servant leadership to serve the workers well for the ultimate benefit of the organization.

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“…Interestingly, cholangiopathy, characterized by cholestasis and structural abnormalities of bile duct, has been reported in post-COVID-19 patients, who recovered from severe and critical disease. 4,5…”

Section: Introductionmentioning

confidence: 99%

Association Covid-19 and Liver Injury : A Systematic Review

Giovani,

Monica Carissa,

Priska Adelin

2024

JARMHS

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Background: Most COVID-19 patients present with typical respiratory symptoms (i.e., cough, dyspnea) and fever. However, abnormal liver function is often developed in patients with COVID-19, and liver injury has been related with severe disease. Liver damage ranges from mild asymptomatic elevation of liver enzymes to severe liver injury, while a few cases of acute liver failure have also been reported. The aim: This study aims to show association COVID-19 and liver injury. Methods: By comparing itself to the standards set by the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020, this study was able to show that it met all of the requirements. So, the experts were able to make sure that the study was as up-to-date as it was possible to be. For this search approach, publications that came out between 2013 and 2023 were taken into account. Several different online reference sources, like Pubmed and SagePub, were used to do this. It was decided not to take into account review pieces, works that had already been published, or works that were only half done. Result: In the PubMed database, the results of our search brought up 44 articles, whereas the results of our search on SagePub brought up 334 articles. The results of the search conducted for the last year of 2013 yielded a total 7 articles for PubMed and 111 articles for SagePub. The result from title screening, a total 4 articles for PubMed and 46 articles for SagePub. In the end, we compiled a total of 10 papers. We included five research that met the criteria. Conclusion: COVID-19-associated liver injury is caused by the cumulative effects of multiple factors, including hepatotropic SARS-CoV-2, drug-induced liver injury, hypoxic reperfusion, immune stress and inflammatory factor storms.

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Impact of the COVID-19 pandemic on healthcare workers’ families

Cited by 5 publications

References 9 publications

SEIR‐driven semantic integration framework: Internet of Things‐enhanced epidemiological surveillance in COVID‐19 outbreaks using recurrent neural networks

SEIR‐driven semantic integration framework: Internet of Things‐enhanced epidemiological surveillance in COVID‐19 outbreaks using recurrent neural networks

The Role of Servant Leadership in Supporting the Health Workforce during COVID 19

Association Covid-19 and Liver Injury : A Systematic Review

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