Longitudinal Changes of COVID-19 Symptoms in Social Media: Observational Study

Abstract

Background In December 2019, the COVID-19 outbreak started in China and rapidly spread around the world. Many studies have been conducted to understand the clinical characteristics of COVID-19, and recently postinfection sequelae of this disease have begun to be investigated. However, there is little consensus on the longitudinal changes of lasting physical or psychological symptoms from prior COVID-19 infection. Objective This study aims to investigate and analyze public social media data from Reddit to understand the longitudinal impact of COVID-19 symptoms before and after recovery from COVID-19. Methods We collected 22,890 Reddit posts that were generated by 14,401 authors from March 14 to December 16, 2020. Using active learning and intensive manual inspection, 292 (2.03%) active authors, who were infected by COVID-19 and frequently reported disease progress on Reddit, along with their 2213 (9.67%) longitudinal posts, were identified. Machine learning tools to extract biomedical information were applied to identify COVID-19 symptoms mentioned in the Reddit posts. We then examined longitudinal changes in individual physiological and psychological characteristics before and after recovery from COVID-19 infection. Results In total, 58 physiological and 3 psychological symptoms were identified in social media before and after recovery from COVID-19 infection. From the analyses, we found that symptoms of patients with COVID-19 lasted 2.5 months. On average, symptoms appeared around a month before recovery and remained for 1.5 months after recovery. Well-known COVID-19 symptoms, such as fever, cough, and chest congestion, appeared relatively earlier in patient journeys and were frequently observed before recovery from COVID-19. Meanwhile, mental discomfort or distress, such as brain fog or stress, fatigue, and manifestations on toes or fingers, were frequently mentioned after recovery and remained as intermediate- and longer-term sequelae. Conclusions In this study, we showed the dynamic changes in COVID-19 symptoms during the infection and recovery phases of the disease. Our findings suggest the feasibility of using social media data for investigating disease states and understanding the evolution of the physiological and psychological characteristics of COVID-19 infection over time.

Telemedicine: A cornerstone of healthcare assistance during the SARS-Cov2 pandemic outbreak but also a great opportunity for the near future

“…Initially, the case fatality rate was calculated at approximately 6,5%; currently it is about 1,25%. The advent of vaccination and the frequent appearance of new variants led to a rapid and significant evolution of the epidemiological and clinical situation there so, the symptomatology of the new variants is milder and shorter than that of the old variants ( Malika, 2022 ; Mendiola-Pastrana, 2022 ; Sarabadani et al, 2022 ; Wise, 2022 ). The changes in these variants demonstrate how ongoing evolution in SARS-CoV-2 can drive changes in how the virus interacts with host cells ( Rando et al, 2021 ) and how the illness could change quickly.…”

Social Media Mining of Long-COVID Self-Medication Reported by Reddit Users: Feasibility Study to Support Drug Repurposing

“…The data extraction process was performed using Pushshift [ 25 ], which is a platform that collects Reddit data and has been available to researchers since 2015 [ 25 ]. The extracted data consist of posts and metadata from the subreddit “/r/covidlonghaulers,” which has already been used to explore LC symptoms [ 26 , 27 ]. This subreddit is actively moderated by specific users and provides a medium for LC-related discussions.…”

“…For instance, we captured conventional supplements (eg, vitamin supplements) or prescription medications (eg, antidepressants) that were discussed by users. ScispaCy provides several NER models related to medical issues [ 29 ] and was used to extract symptoms from LC Reddit posts [ 27 ]. In principle, two ScispaCy models are applicable for this purpose.…”

“…The second model is the Med7 model [ 31 ], which specifically focuses on drug extraction. Running both models together yielded the best results [ 27 ]. Negated substances were excluded from the extraction by considering negotiation terms.…”

Trend and co-occurrence network study of symptoms through social media: an example of COVID-19

“…15,16 Only a few studies analyzed the symptoms and their epidemic-related characteristics. [17][18][19] Moreover, these studies mainly conducted distribution and trend analyses in the early months of the pandemic rather than long-term, comprehensive investigations.…”