Social media for early characterization of pandemic symptoms: A qualitative analysis of patient-reported COVID-19 experiences.

BACKGROUND: Patients use social media forums to discuss their medical history and healthcare experiences, providing early insight into real-world patient experiences. We analyzed COVID-19 patient experiences from Reddit social media posts. METHODS: We extracted Reddit Application Programming Interface data for the subreddit/COVID-19 positive from March to August 2020 and selected users tagged as "Tested Positive" or "Tested Positive- Me" flair and who posted at least thirty times in any calendar month, excluding users who explicitly stated location outside of the U.S. For tested-positive patients (users), we created and reviewed individual case profiles summarizing their COVID-19 symptoms, testing, and medications or treatments. Data were imported to Nvivo qualitative analysis software and qualitative coding was conducted. FINDING: There were 31 759 posts and comments from 720 users in March to May 2020 (Q1) and 40 446 posts and comments from 1649 users from June to August 2020 (Q2). Final count of "Tested Positive" was 1296 users (280 in Q1 and 1016 in Q2). Across both quarters, frequently reported symptoms included sore throat, headaches, fevers, or chills. Loss of sense of smell or taste were reported by users in early March, prior to the inclusion of this symptom to the CDC list in April and GI-related symptoms and fatigue were reported in the March to May data, before they were added as a COVID-19 associated symptom in July 2020. Users also reported in-depth descriptions of their symptoms, motivations for testing, and long-term impacts such as post-viral fatigue. INTERPRETATION: Social media data can potentially serve as an early surveillance data source in a pandemic and offer preliminary insights into patient disease experiences.

A quantitative bias analysis of the confounding effects due to smoking on the association between fluoroquinolones and risk of aortic aneurysm.

PURPOSE: Epidemiologic studies consistently report an increased risk of aortic aneurysm (AA) among users of fluoroquinolones (FQ), but confounding by smoking could explain all or some of the observed risk. Therefore, to better elucidate the potential causal impact of FQ on AA, we quantitatively evaluated the potential confounding effect of smoking on this observed association. METHODS: We conducted a series of quantitative bias analyses using three previously published approaches: the E-value approach, the rule-out approach, and the array approach. We additionally conducted a numerical comparison between the rule-out approach and the E-value approach. RESULTS: For an apparent relative risk of 2, the E-value is 3.41, suggesting that smoking needs to be associated with both FQ and AA with a minimal magnitude of 3.41 to explain away the observed twofold FQ-AA association. The array approach found that the prevalence of smoking among FQ users would need to be at least 2.9 times higher (43%) than the nonusers (15%), assuming smoking increases the risk of AA by 7.6-fold. A numerical comparison demonstrated that the results from the rule-out approach are similar to that of the E-value approach when there is a lack of prior data on bias parameters. CONCLUSIONS: Using three different approaches, we demonstrate that the strengths of association between smoking and both FQ and AA need to be unusually strong to fully account for the twofold increased risk between FQ and AA. Therefore, it is unlikely that smoking alone would explain away the association reported in the epidemiologic studies.