Twitter has considerable capacity for health education and proves to be an efficient and accessible communication tool in the coronavirus disease-19 (COVID-19) pandemic. Although many stakeholders saturate Twitter with COVID-19–related information, it remains unknown who disseminates information most efficaciously. COVID-19–related tweets were obtained from Twitter accounts of health agencies, governmental authorities, universities, scientific journals, medical associations, and celebrities. Posts' impact was measured with the nominal and relative (%followers) number of likes and retweets. A sentiment analysis was conducted.We have identified 17,331 COVID-19–related tweets posted by 338 accounts in >4 months since the virus began to spread. The largest number of likes was received by tweets of celebrities (median nominal, relative likes; 14,918, 0.036 percent), politicians (259, 0.174 percent), and health agencies (231, 0.007 percent). Most retweeted messages were also posted by celebrities (2,366, 0.005 percent), health agencies (130, 0.004 percent), and politicians (55, 0.041 percent). Retweets and likes peaked in March 2020, and the overall sentiment of the tweets was growing steadily. Whereas celebrities and politicians posted positive messages, the scientific and health authorities often employed a negative vocabulary. The posts with positive sentiment gained more likes and relative likes than nonpositive. During the pandemic, the tweets of celebrities and politicians related to COVID-19 outperform those coming from health and scientific institutions. Active engagement of Twitter influencers may help key messages go viral.

The reports suggesting a beneficial effect of nicotine on coronavirus disease 2019 (COVID-19) severity may encourage smoking. We aimed to analyze tweets on COVID-19 and smoking coming from casual Twitter users and Twitter accounts representing the tobacco industry. We collected tweets on COVID-19 and smoking from January 1 to May 1, 2020, using Twitter application programming interface. We analyzed sentiment, likes, or retweet to followers ratios, and the posts coming from the casual users to find pieces of news that could affect the discourse. Tweets coming from industry were analyzed manually. We analyzed n = 33,890 tweets on COVID-19 and smoking. The sentiment of tweets was negative, hitting a nadir in mid-March, but became less negative in April when preprints suggesting benefits from smoking on COVID-19 were released. Similar trends were observed for the ratios of likes or retweets to followers. We found 58 messages from the tobacco industry concerning COVID-19. Twenty-two (37.9 percent) mentioned the efforts of tobacco companies to support the development of a COVID-19 vaccine. Two tweets included Food and Drug Administration statements that there is no evidence that vaping increases the risk of COVID-19. The occurrence of preprints suggesting benefits of smoking in COVID-19 might increase sentiment and reactions to tweets on tobacco products and the virus. The authors of potentially controversial articles should restrain from the promotion of their results before the completion of the peer-review process. Twitter presents a convenient tool to monitor e-discourse during a health crisis. The research community should monitor the tobacco industry's social media.

We aimed to rank the most common locations of pain among Google users globally and locally and analyze secular and seasonal trends in pain-related searches in the years 2004–2019. We used data generated by Google Trends (GT) to identify and analyze global interest in topics (n = 24) related to locations of pain and how these progressed over time. We analyzed secular trends and time series decomposition to identify seasonal variations. We also calculated the interest in all topics with reference to the relative search volume (RSV) of “Abdominal pain”. Google users were most commonly interested in “Headache” (1.30 [times more frequently than “Abdominal pain”]), “Abdominal pain” (1.00), and “Back pain” (0.84). “Headache” was the most frequent search term in n = 41 countries, while “Abdominal pain” was the most frequent term in n = 27 countries. The interest in all pain-related topics except “Dyspareunia” increased over time. The sharpest increase was observed for “Abdominal pain” (5.67 RSV/year), and “Toothache” (5.52 RSV/year). Most of the topics revealed seasonal variations. Among pain-related topics, “Headache,” “Abdominal pain,” and “Back pain” interested most Google users. GT is a novel tool that allows retrospective investigation of complaints among Internet users.

The internet provides access to information about dietary supplements and allows their easy purchase. We aimed to rank the interest of Google users in dietary supplements and to determine the changes that occurred in their popularity from 2004 to 2019. We used Google Trends to generate data over time on regional interest in dietary supplements (n = 200). We categorized each included supplement and calculated the interest in all topics in proportion to the relative search volume (RSV) of “lutein”. We analyzed the trends over time of all topics and categories. Globally, the topics with the highest popularity were “magnesium”, which was 23.72 times more popular than “lutein”, “protein” (15.22 times more popular), and “iron” (15.12). The categories of supplements receiving most interest were protein (9.64), mineral (5.24), and vitamin (3.47). The RSV of seven categories of topics (amino acid, bacterial, botanical, fiber, mineral, protein, and vitamin) increased over time while two categories (enzyme and fat or fatty acid) saw a drop in their RSV. Overall, 119 topics saw an increase in interest over time, 19 remained stable, and 62 saw interest in them decrease. Google Trends provides insights into e-discourse and enables analysis of the differences in popularity of certain topics across countries and over time.

Background: There is a limited amount of data on the safety profile of the COVID-19 vector vaccine Gam-COVID-Vac (Sputnik V). Previous infodemiology studies showed that social media discourse could be analyzed to assess the most concerning adverse events (AE) caused by drugs. Objective: We aimed to investigate mild AEs of Sputnik V based on a participatory trial conducted on Telegram in the Russian language. We compared AEs extracted from Telegram with other limited databases on Sputnik V and other COVID-19 vaccines. We explored symptom co-occurrence patterns and determined how counts of administered doses, age, gender, and sequence of shots could confound the reporting of AEs. Methods: We collected a unique dataset consisting of 11,515 self-reported Sputnik V vaccine AEs posted on the Telegram group, and we utilized natural language processing methods to extract AEs. Specifically, we performed multilabel classifications using the deep neural language model Bidirectional Encoder Representations from Transformers (BERT) “DeepPavlov,” which was pretrained on a Russian language corpus and applied to the Telegram messages. The resulting area under the curve score was 0.991. We chose symptom classes that represented the following AEs: fever, pain, chills, fatigue, nausea/vomiting, headache, insomnia, lymph node enlargement, erythema, pruritus, swelling, and diarrhea. Results: Telegram users complained mostly about pain (5461/11,515, 47.43%), fever (5363/11,515, 46.57%), fatigue (3862/11,515, 33.54%), and headache (2855/11,515, 24.79%). Women reported more AEs than men (1.2-fold, P<.001). In addition, there were more AEs from the first dose than from the second dose (1.1-fold, P<.001), and the number of AEs decreased with age (β=.05 per year, P<.001). The results also showed that Sputnik V AEs were more similar to other vector vaccines (132 units) than with messenger RNA vaccines (241 units) according to the average Euclidean distance between the vectors of AE frequencies. Elderly Telegram users reported significantly more (5.6-fold on average) systemic AEs than their peers, according to the results of the phase 3 clinical trials published in The Lancet. However, the AEs reported in Telegram posts were consistent (Pearson correlation r=0.94, P=.02) with those reported in the Argentinian postmarketing AE registry. Conclusions: After the Sputnik V vaccination, Russian Telegram users reported mostly pain, fever, and fatigue. The Sputnik V AE profile was comparable with other vector COVID-19 vaccines. Discussion on social media could provide meaningful information about the AE profile of novel vaccines.