PubMed COVID-19 Clinical Care

CONCLUSIONS: There was no difference in effectiveness and safety of casirivimab and imdevimab antibody cocktail in the patients infected with SARS-CoV-2 delta or omicron.

CONCLUSIONS: Cross-country differences suggest that local governments' support for COVID-19 prevention policies can influence populations' vaccine attitudes. These findings provide insight for policymakers to develop interventions aiming to increase

Vaccines have proven useful in curbing contagion from new strains of the SARS-CoV-2 virus. However, equitable vaccine allocation continues to be a significant challenge worldwide, necessitating a comprehensive allocation strategy incorporating

As SARS-CoV-2 emerged as a global threat in early 2020, China enacted rapid and strict lockdown orders to prevent introductions and suppress transmission. In contrast, the United States federal government did not enact national orders. State and

CONCLUSION: This study noted that there is a significant impact of COVID-19 on health professionals in terms of their social and mental health aspects. The social impact experienced by health professionals is an important predictor of their mental

CONCLUSIONS: The factors associated with adverse job outcomes among nurses-intent to leave, reduced clinical hours, travel nursing, or recent departure-consistently align with issues that predated the pandemic. Few nurses cite COVID as the primary

No abstract

The coronavirus disease (COVID-19) continued to strike as a highly infectious and fast-spreading disease in 2020 and 2021. As the research community actively responded to this pandemic, we saw the release of many COVID-19-related datasets and

Growing Up in Ireland (GUI) is the national longitudinal study of children and young people in the Republic of Ireland and has followed two cohorts for over ten years to date: Cohort '98 who were recruited into the study at age nine years and Cohort

Current remote monitoring of COVID-19 patients relies on manual symptom reporting, which is highly dependent on patient compliance. In this research, we present a machine learning (ML)-based remote monitoring method to estimate patient recovery from