ABSTRACT
COVID-19 significantly impacted the teaching-learning-assessment activities in many medical schools. In this article, we discuss the impact of COVID-19 on the Yong Loo Lin School of Medicine, National University of Singapore, focusing on paediatric training and the adaptations of the system and the people. The school developed strategies to promptly disseminate information and safety measures to protect all its staff and students. By leveraging on the school’s infrastructure for technology-enabled learning, good-quality medical training and reliable assessments were able to be carried out swiftly. The paediatric curriculum was crafted based on these principles, and it provided distance-based learning with live and interactive sessions to teach core clinical skills. The faculty also tapped on standardised patients to provide consistent and life-like scenarios. Measures were implemented to minimise challenges with technology-enabled learning. Collectively, efforts from the staff, support from the leadership and students’ adaptations tremendously helped to ease the transition.
ABSTRACT
Introduction: The anaesthetic management for surgeries during the COVID-19 pandemic has posed unique challenges. Safety of all healthcare workers is an additional concern along with heightened risk to patients during General Anesthesia (GA). COVID-19 pneumonia and aerosol generation may be exacerbated during airway intervention and GA. We aimed to assess the change in the mode of anaesthesia due to the pandemic. Methods: A research consortium led by WHO Collaboration Centre for Research in Surgical Care Delivery in Low and Middle Income countries, India, conducted this retrospective cross-sectional study in 12 hospitals across the country.We compared the anaesthesia preferences during pandemic (April 2020) to a corresponding pre pandemic period (April 2019) Results: A total of 636 out of 2,162 (29.4%) and 156 out of 927 (16.8%) surgeries were performed under GA in April 2019 and April 2020 respectively, leading to a fall of 13% in usage of GA. A 5% reduction in GA and a 12% increase in the usage of regional anaesthesia was observed for cesarean sections. There was no significant change in anesthesia for laparotomies and fracture surgeries. However, 14% increase in GA usage was observed in surgeries for local soft tissue infections and necrotic tissues. Conclusion: Though overall usage of GA reduced marginally, the change was mainly contributed by anesthesia for caesarean births. The insignificant change in anaesthesia for other surgeries may be attributed to the lack of facilities for spinal anaesthesia and may reflect the risk taking behaviour of healthcare professionals in COVID-19 pandemic.
ABSTRACT
On November 09, 2020, Pfizer and BioNtech announced vaccine efficacy results, possibly providing hope during the COVID-19 pandemic. Correspondingly, vaccine-related information was shared on social media platforms, including Twitter. The present research aims to investigate tonal shift resulting from this important pandemic-related event using automatic text analysis of Twitter Tweets. We examined 209,939 tweets before, and 203,490 tweets after the vaccine announcement. Pennebaker’s linguistic inquiry word count (LIWC) was used to detect tonal shifts via analytic thinking (which reflects logical thinking), clout (reflects expertise), authentic (reflects disclosure), and emotional tone (reflects emotional valence). Results indicated a decrease in authentic score implying a more guarded form of disclosure, while an increase in clout score suggests more sharing from expert users. The change was negligible for analytical thinking and emotional tone, suggesting users’ mentality towards the pandemic was not affected. Overall, results suggest a minimal shift in tone on Twitter, even in the face of the good news about the vaccine announcement. © 2021, Springer Nature Switzerland AG.
ABSTRACT
The World Health Organization declared COVID-19 as a pandemic on 11 March 2020 due to its rapid spread worldwide. This work-in-progress paper aims to uncover topics related to COVID-19 discussed on Twitter. Using topic modelling, we analyzed two weeks of tweets (11 March–25 March 2020) in English and found 17 latent topics, covering a broad range of issues such as health and economic impact, political and legislative responses, prevention measures, as well as disruption to individuals’ daily lives. The results of this preliminary study show a helpful step to understand public communications about the virus and thus inform health practitioners to propose effective safety measures against COVID-19. © 2020, Springer Nature Switzerland AG.