tetano
Editor, Senior Moderator
Front Big Data
. 2022 Dec 15;5:1051386.
doi: 10.3389/fdata.2022.1051386. eCollection 2022.
The effects of long COVID-19, its severity, and the need for immediate attention: Analysis of clinical trials and Twitter data
Arinjita Bhattacharyya[SUP] 1 [/SUP], Anand Seth[SUP] 2 [/SUP], Shesh Rai[SUP] 3 [/SUP]
Affiliations
Abstract
Background: The coronavirus disease 2019 (COVID-19) has been declared a pandemic since March 2020 by the World Health Organization; identifying the disease progression, predicting patient outcomes early, the possibility of long-term adverse events through effective modeling, and the use of real-world data are of immense importance to effective treatment, resource allocation, and prevention of severe adverse events of grade 4 or 5.
Methods: First, we raise awareness about the different clinical trials on long COVID-19. The trials were selected with the search term "long COVID-19" available in ClinicalTrials.gov. Second, we curated the recent tweets on long-haul COVID-19 and gave an overview of the sentiments of the people. The tweets obtained with the query term #long COVID-19 consisted of 8,436 tweets between 28 August 2022 and 06 September 2022. We utilized the National Research Council (NRC) Emotion Lexicon method for sentiment analysis. Finally, we analyze the retweet and favorite counts are associated with the sentiments of the tweeters via a negative binomial regression model.
Results: Our results find that there are two types of clinical trials being conducted: observational and interventional. The retweet counts and favorite counts are associated with the sentiments and emotions, such as disgust, joy, sadness, surprise, trust, negative, and positive.
Conclusion: We need resources and further research in the area of long COVID-19.
Keywords: COVID-19; PASC; Twitter; clinical trials; coronavirus; long-COVID-19; negative binomial regression.
. 2022 Dec 15;5:1051386.
doi: 10.3389/fdata.2022.1051386. eCollection 2022.
The effects of long COVID-19, its severity, and the need for immediate attention: Analysis of clinical trials and Twitter data
Arinjita Bhattacharyya[SUP] 1 [/SUP], Anand Seth[SUP] 2 [/SUP], Shesh Rai[SUP] 3 [/SUP]
Affiliations
- PMID: 36588926
- PMCID: PMC9797990
- DOI: 10.3389/fdata.2022.1051386
Abstract
Background: The coronavirus disease 2019 (COVID-19) has been declared a pandemic since March 2020 by the World Health Organization; identifying the disease progression, predicting patient outcomes early, the possibility of long-term adverse events through effective modeling, and the use of real-world data are of immense importance to effective treatment, resource allocation, and prevention of severe adverse events of grade 4 or 5.
Methods: First, we raise awareness about the different clinical trials on long COVID-19. The trials were selected with the search term "long COVID-19" available in ClinicalTrials.gov. Second, we curated the recent tweets on long-haul COVID-19 and gave an overview of the sentiments of the people. The tweets obtained with the query term #long COVID-19 consisted of 8,436 tweets between 28 August 2022 and 06 September 2022. We utilized the National Research Council (NRC) Emotion Lexicon method for sentiment analysis. Finally, we analyze the retweet and favorite counts are associated with the sentiments of the tweeters via a negative binomial regression model.
Results: Our results find that there are two types of clinical trials being conducted: observational and interventional. The retweet counts and favorite counts are associated with the sentiments and emotions, such as disgust, joy, sadness, surprise, trust, negative, and positive.
Conclusion: We need resources and further research in the area of long COVID-19.
Keywords: COVID-19; PASC; Twitter; clinical trials; coronavirus; long-COVID-19; negative binomial regression.