Association of Online Search Trends With Vaccination in the United States: June 2020 Through May 2021.

Stagnating COVID-19 vaccination rates and vaccine hesitancy remain a threat to public health. Improved strategies for real-time tracking and estimation of population-level behavior regarding vaccinations are needed. The aim of this study was to evaluate whether online search trends for COIVD-19 and influenza mirror vaccination rates. State-level weekly fraction of online searches for top vaccination-related search terms and CDC vaccination data were obtained from June 1, 2020, to May 31, 2021. Next, trends in online search and vaccination data for COVID-19 and influenza were analyzed for visual and quantitative correlation patterns using Spearman's rank correlation analysis. Online searches in the US for COVID-19 vaccinations increased 2.71-fold (95% CI: 1.98-3.45) in the 4 weeks after the FDA emergency authorization compared to the precedent 4 weeks. In March-April 2021, US online searches reached a plateau that was followed by a decline of 83.3% (95% CI: 31.2%-135.3%) until May 31, 2021. The timing of peaks in online searches varied across US states. Online searches were strongly correlated with vaccination rates (r=0.71, 95% CI: 0.45 - 0.87), preceding actual reported vaccination rates in 44 of 51 states. Online search trends preceded vaccination trends by a median of 3.0 weeks (95% CI: 2.0-4.0 weeks) across all states. For influenza vaccination searches, seasonal peaks in September-October between 2016-2020 were noted. Influenza search trends highly correlated with the timing of actual vaccinations for the 2019-2020 (r=0.82, 95% CI: 0.64 - 0.93) and 2020-2021 season (r=0.91, 95% CI: 0.78 - 0.97). Search trends and real-world vaccination rates are highly correlated. Temporal alignment and correlation levels were higher for influenza vaccinations; however, only online searches for COVID-19 vaccination preceded vaccination trends. These findings indicate that US online search data can potentially guide public health efforts, including policy changes and identifying geographical areas to expand vaccination campaigns.

Twitter and Facebook posts about COVID-19 are less likely to spread misinformation compared to other health topics.

The COVID-19 pandemic brought widespread attention to an "infodemic" of potential health misinformation. This claim has not been assessed based on evidence. We evaluated if health misinformation became more common during the pandemic. We gathered about 325 million posts sharing URLs from Twitter and Facebook during the beginning of the pandemic (March 8-May 1, 2020) compared to the same period in 2019. We relied on source credibility as an accepted proxy for misinformation across this database. Human annotators also coded a subsample of 3000 posts with URLs for misinformation. Posts about COVID-19 were 0.37 times as likely to link to "not credible" sources and 1.13 times more likely to link to "more credible" sources than prior to the pandemic. Posts linking to "not credible" sources were 3.67 times more likely to include misinformation compared to posts from "more credible" sources. Thus, during the earliest stages of the pandemic, when claims of an infodemic emerged, social media contained proportionally less misinformation than expected based on the prior year. Our results suggest that widespread health misinformation is not unique to COVID-19. Rather, it is a systemic feature of online health communication that can adversely impact public health behaviors and must therefore be addressed.

Characterizing Self-Reports of Self-Identified Patient Experiences with Methadone Maintenance Treatment on an Online Community during COVID-19.

Background: The coronavirus disease (COVID-19) pandemic has impacted patients receiving methadone maintenance treatment (MMT) through opioid treatment programs (OTPs), especially because of the unique challenges of the care delivery model. Previously, documentation of patient experiences during emergencies often comes years after the fact, in part because there is a substantial data void in real-time. Methods: We extracted 308 posts that mention COVID-19 keywords on r/methadone, an online community for patients receiving MMT to share information, on Reddit occurring between January 31, 2020 and September 30, 2020. 215 of these posts self-report an impact to their MMT. Using qualitative content analysis, we characterized the impacts described in these posts and identified four emergent themes describing patients' experience of impacts to MMT during COVID-19. Results: The themes included (1) 54.4% of posts reporting impediments to accessing their methadone, (2) 28.4% reporting impediments to accessing physicial OTPs, (3) 19.5% reporting having to self-manage their care, and (4) 4.7% reporting impediments to accessing OTP providers and staff. Conclusions: Patients described unanticipated consequences to one-size-fits-all policies that are unevenly applied resulting in suboptimal dosing, increased perceived risk of acquiring COVID-19 at OTPs, and reduced interaction with OTP providers and staff. While preliminary, these results are formative for follow-up surveillance metrics for patients of OTPs as well as digitally-mediated resource needs for this online community. This study serves as a model of how social media can be employed during and after emergencies to hear the lived experiences of patients for informed emergency preparedness and response.

Telehealth in the COVID-19 Era: A Balancing Act to Avoid Harm.

The telehealth revolution in response to COVID-19 has increased essential health care access during an unprecedented public health crisis. However, virtual patient care can also limit the patient-provider relationship, quality of examination, efficiency of health care delivery, and overall quality of care. As we witness the most rapidly adopted medical trend in modern history, clinicians are beginning to comprehend the many possibilities of telehealth, but its limitations also need to be understood. As outcomes are studied and federal regulations reconsidered, it is important to be precise in the virtual patient encounter approach. Herein, we offer some simple guidelines that could assist health care providers and clinic schedulers in determining the appropriateness of a telehealth visit by considering visit types, patient characteristics, and chief complaint or disease states.