ABSTRACT
Objective: to evaluate the effectiveness of Ivermectin and Atazanavir compared to placebo in the time to resolution of symptoms and duration of illness due to COVID-19. Method: observational, prospective, longitudinal, descriptive and analytical cohort study with symptomatic outpatients, followed for 06 months in two Basic Health Units for COVID-19 care in Teresina-Piaui, Brazil, from November to April 2021 identified by 1:1:1 random sampling. Reverse transcription polymerase chain reaction (RT-PCR) tests were performed for laboratory confirmation of suspected infection with the new coronavirus and sociodemographic and clinical evaluation. Results: of the 87 randomized patients, 62.1% (n=54) were male, with a mean age of 35.1 years, had a partner (53.9%), low income (50.6%), eutrophic (40.7%) and without health comorbidities (78.2%). There was no difference between the median time to resolution of symptoms, which was 21 days (IQR, 8-30) in the atazanavir group, 30 days (IQR, 5-90) in the ivermectin group compared with 14 days (IQR, 9-21) in the control group. At day 180, there was resolution of symptoms in 100% in the placebo group, 93.9% in the atazanavir group, and 95% in the ivermectin group. The median duration of illness was 8 days in all study arms. Conclusion: Treatment with atazanavir (6 days) and ivermectin (3 days) did not reduce the time to symptom resolution or the duration of illness among outpatients with mild COVID-19 compared to the placebo group. The results do not support the use of ivermectin and atazanavir for the treatment of mild to moderate COVID-19.
ABSTRACT
The emotional impact of the COVID-19 pandemic and ensuing social restrictions has been profound, with widespread negative effects on mental health. We made use of the natural language processing and large-scale Twitter data to explore this in depth, identifying emotions in COVID-19 news content and user reactions to it, and how these evolved over the course of the pandemic. We focused on major UK news channels, constructing a dataset of COVID-related news tweets (tweets from news organisations) and user comments made in response to these, covering Jan 2020 to April 2021. Natural language processing was used to analyse topics and levels of anger, joy, optimism, and sadness. Overall, sadness was the most prevalent emotion in the news tweets, but this was seen to decline over the timeframe under study. In contrast, amongst user tweets, anger was the overall most prevalent emotion. Time epochs were defined according to the time course of the UK social restrictions, and some interesting effects emerged regarding these. Further, correlation analysis revealed significant positive correlations between the emotions in the news tweets and the emotions expressed amongst the user tweets made in response, across all channels studied. Results provide unique insight onto how the dominant emotions present in UK news and user tweets evolved as the pandemic unfolded. Correspondence between news and user tweet emotional content highlights the potential emotional effect of online news on users and points to strategies to combat the negative mental health impact of the pandemic. © 2023 Simon L. Evans et al.
ABSTRACT
Media has played an important role in public information on COVID-19. But distressing news, e.g., COVID-19 death tolls, may trigger negative emotions in public, discouraging them from following the news, which, in turn, can limit the effectiveness of the media. To understand people’s emotional response to the COVID-19 news, we have investigated the prevalence of basic human emotions in around 19 million user responses to 1.7 million COVID-19 news posts on Twitter from (English-speaking) media across 12 countries from January 2020 to April 2021. We have used Latent Dirichlet Allocation (LDA) to identify news themes on Twitter. Also, the Robustly Optimized BERT Pretraining Approach (RoBERTa) model was used to identify emotions in the tweets. Our analysis of the Twitter data revealed that anger was the most prevalent emotion in user responses to the news coverage of COVID-19. That was followed by sadness, optimism, and joy, steadily over the period of the study. The prevalence of anger (in user responses) was higher for the news about authorities and politics while optimism and joy were more prevalent for the news about vaccination and educational impacts of COVID-19 respectively. The prevalence of sadness in user responses, however, was the highest for the news about COVID-19 cases and deaths and the impacts on the families, mental health, jails, and nursing homes.We also observed a higher level of anger in the user responses to the (COVID-19) news posted by the USA media accounts (e.g., CNN Politics, Fox News, MSNBC). Optimism, on the other hand, was found to be the highest for Filipino media accounts. Author