The Effects of Long COVID-19, its Severity, and the Need for Immediate Attention: Analysis of Clinical Trials and Twitter data

ABSTRACT

The coronavirus disease 2019 (COVID-19) has been declared a pandemic since March 2020 by the World Health Organisation (WHO). The infection pathway follows symptoms of fever, cough, shortness of breath, dyspnea, and severe cases that lead to hospitalization, emergency life support, and even death. Identifying the disease progression and predicting patient outcomes early, precisely predicting the possibility of long-term adverse events through effective modeling, and use of real-world data such as longitudinal clinical trial data, electronic health records data, and health insurance data are of immense importance to effective treatment, resource allocation, and prevention of severe adverse events (SAE) of grades four or five. The main goal of the study is threefold. Firstly, we raise awareness about the different clinical trials that are being conducted concurrently on Long covid-19, and how these are beneficial. Secondly, we analyze the recent tweets on Long haul covid-19 and give an overview of the sentiments of the opinion of the people. Finally, we analyze the sentiment scores and find if they are associated with the demographics of the tweeters via a negative binomial regression model. The trials were selected with long Covid-19 available in ClinicalTrials.Gov. Also, the tweets obtained with the term #long covid-19 consisted of 8436 tweets. We utilized the NRC Emotion Lexicon method for sentiment analysis is a list of English words and their associations with eight basic emotions (anger, fear, anticipation, trust, surprise, sadness, joy, and disgust) and two sentiments (negative and positive) (11). We obtained a matrix of sentiment scores, as well as retweet counts and favorite counts which were analyzed. We regressed the retweet counts and the favorite counts with the sentiment scores and find if they are associated with the emotions and sentiments of the tweeters via a negative binomial regression model since the outcome variable is count data. Our results find that there are two types of clinical trials (a total of 298) being conducted 1)observational and b) interventional. The details about enrollment, time to completion, clinical trial phases, etc., are discussed. Sentiment analysis with the NRC method of the tweets shows that there are both positive and negative sentiments. The retweet counts and favorite counts are associated with the sentiments and emotions such as disgust, joy, sadness, surprise, trust, negative, positive, etc. Finally, to conclude we need resources, and further research needs to be conducted in this area of long Covid-19.