Objectives: This paper uses a social media platform, Reddit, to identify real-time experiences of people who use drugs during the COVID-19 lock-down.

Methods: Reddit is a popular and growing social media platform, providing a large, publicly available dataset necessary for high performance of machine learning and topic modeling techniques. We used opioid-related "subreddits," communities where Reddit users engage in conversations about drug use, to examine COVID-19-related content of posts and comments from March to May 2020. This paper investigates the latent topics of users' posts/comments using Latent Dirichlet Allocation, an unsupervised machine learning approach that uncovers the thematic structure of a document collection. We also examine how topics changed over time.

Results: The final dataset consists of 525 posts and 9284 comments, for a total of 9809 posts/comments (3756 posts/comments in r/opiates, 1641 in r/OpiatesRecovery, 1203 in r/suboxone, and 3209 in r/Methadone) among 2342 unique individuals. There were 5256 posts/comments in March; 3185 in April; and 1368 in May (until May 22). Topics that appeared most frequently in COVID-19-related discussions included medication for opioid use disorder experiences and access issues (22.6%), recovery (24.2%), and drug withdrawal (20.2%).

Conclusions: During the first three months of the COVID-19 pandemic, people who use drugs were impacted in several ways, including forced or intentional withdrawal, confusion between withdrawal and COVID-19 symptoms, take-home medication for opioid use disorder issues, and barriers to recovery. As the pandemic progresses, providers and policymakers should consider these experiences among people who use drugs during the early stage of the pandemic.