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Background: The SARS-CoV-2 pandemic led to the restructuring of traditional clinical activity;hence, globally, 58% of countries implemented the use of telemedicine to meet their healthcare needs. Background: To examine patients' satisfaction with telemedicine medical service and experience at the level of primary care in the Kingdom of Bahrain. Methods: A retrospective cross-sectional study was conducted on 335 patients who used teleconsultations in January 2022 in primary care. A validated questionnaire was modified to assess patients' satisfaction with teleconsultation medical services and experience during the COVID-19 pandemic. Results: A total of 315 responses were included in the final analysis (response rate 94%). Almost all expressed extreme satisfaction with the medical service as they were able to easily explain their medical problem over the phone and fully understood their illness after the consultation. They were also satisfied with the ability of the doctor to understand their problem, explain their treatment, and provide appropriate management over the phone. Over 90% were satisfied with the consultation time that it does not require transportation and would like to use it in the future. Sharing private or personal information over the phone received the lowest satisfaction rate (77.5%). Conclusion: The overall satisfaction expressed by respondents of this survey with the teleconsultation medical service and experience is very high. Such a result confirms that patients have a positive attitude towards telemedicine services in primary care and are willing to use it again and, therefore, must be adopted as a proactive strategy to ensure long-term sustainability.
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PurposeThis paper investigates the impact of global sentiment and various coronavirus disease 2019 (COVID-19)-related media coverage news (Media-Hype index;Panic Index;Media Coverage Index, infodemic index and coronavirus statistics) on the dynamics of bitcoin returns during the COVID-19 pandemic using an asymmetric framework.Design/methodology/approachThe authors use an asymmetric framework based on quantile regression (QR) and quantile-on-quantile regression.FindingsQR results show that COVID-19 panic news negatively affects bitcoin market returns at times of extreme bearish. However, COVID-19 bullish sentiment negatively impacts bitcoin market returns during bullish market conditions. Quantile-on-quantile approach's (QQA) empirical results show that the effects of COVID-19-related news on bitcoin returns were heterogeneous, mainly negative and varied across quantiles.Research limitations/implicationsThe authors find some significant differences regarding the impact of news on bitcoin return dynamics compared to stock markets, suggesting the safe-haven role of bitcoin against stock during the ongoing epidemic.Practical implicationsThe authors find some significant differences regarding the impact of news on bitcoin return dynamics compared to stock markets, suggesting the safe-haven role of bitcoin against stock during the ongoing epidemic.Originality/valueThis study contributes to understanding the dynamics of bitcoin returns using various COVID-19 media news.
ABSTRACT
BACKGROUND: Studying the genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may help determine outbreak clusters and virus transmission advantages to aid public health efforts during the pandemic. Thus, we tracked the evolution of SARS-CoV-2 by variant epidemiology, breakthrough infection, and patient characteristics as the virus spread during the Delta and Omicron waves. We also conducted phylogenetic analyses to assess modes of transmission. METHODS: Nasopharyngeal samples were collected from a cohort of 900 patients with positive polymerase chain reaction (PCR) test results confirming COVID-19 disease. Samples underwent real-time PCR detection using TaqPath assays. Sequencing was performed with Ion GeneStudio using the Ion AmpliSeq™ SARS-CoV-2 panel. Variant calling was performed with Torrent Suite™ on the Torrent Server. For phylogenetic analyses, the MAFFT tool was used for alignment and the maximum likelihood method with the IQ-TREE tool to build the phylogenetic tree. Data were analyzed using SAS statistical software. Analysis of variance or t tests were used to assess continuous variables, and χ2 tests were used to assess categorical variables. Univariate and multivariate logistic regression analyses were preformed to estimate odds ratios (ORs). RESULTS: The predominant variants in our cohort of 900 patients were non-variants of concern (11.1 %), followed by Alpha (4.1 %), Beta (5.6 %), Delta (21.2 %), and Omicron (58 %). The Delta wave had more male than female cases (112 vs. 78), whereas the Omicron wave had more female than male cases (311 vs. 208). The oldest patients (mean age, 43.4 years) were infected with non-variants of concern; the youngest (mean age, 33.7 years), with Omicron. Younger patients were mostly unvaccinated, whereas elderly patients were mostly vaccinated, a statistically significant difference. The highest risk for breakthrough infection by age was for patients aged 30-39 years (OR = 12.4, CI 95 %: 6.6-23.2), followed by patients aged 40-49 years (OR = 11.2, CI 95 %: 6.1-23.1) and then 20-29 years (OR = 8.2, CI 95 %: 4.4-15.4). Phylogenetic analyses suggested the interaction of multiple cases related to outbreaks for breakthrough infections, healthcare workers, and intensive care unit admission. CONCLUSION: The findings of this study highlighted several major public health ramifications, including the distribution of variants over a wide range of demographic and clinical variables and by vaccination status.