Lauren Sinnenberg

Bio: Lauren Sinnenberg is an academic researcher from Brigham and Women's Hospital. The author has contributed to research in topics: Medicine & Heart failure. The author has an hindex of 8, co-authored 16 publications receiving 517 citations. Previous affiliations of Lauren Sinnenberg include Rockefeller University & Harvard University.

Twitter as a Tool for Health Research: A Systematic Review

Abstract: Background. Researchers have used traditional databases to study public health for decades. Less is known about the use of social media data sources, such as Twitter, for this purpose.Objectives. To systematically review the use of Twitter in health research, define a taxonomy to describe Twitter use, and characterize the current state of Twitter in health research.Search methods. We performed a literature search in PubMed, Embase, Web of Science, Google Scholar, and CINAHL through September 2015.Selection criteria. We searched for peer-reviewed original research studies that primarily used Twitter for health research.Data collection and analysis. Two authors independently screened studies and abstracted data related to the approach to analysis of Twitter data, methodology used to study Twitter, and current state of Twitter research by evaluating time of publication, research topic, discussion of ethical concerns, and study funding source.Main results. Of 1110 unique health-related articles mentioning Twi...

Identification of Racial Inequities in Access to Specialized Inpatient Heart Failure Care at an Academic Medical Center.

Abstract: Background: Racial inequities for patients with heart failure (HF) have been widely documented. HF patients who receive cardiology care during a hospital admission have better outcomes. It is unkno...

Twitter as a Potential Data Source for Cardiovascular Disease Research.

Abstract: Importance As society is increasingly becoming more networked, researchers are beginning to explore how social media can be used to study person-to-person communication about health and health care use. Twitter is an online messaging platform used by more than 300 million people who have generated several billion Tweets, yet little work has focused on the potential applications of these data for studying public attitudes and behaviors associated with cardiovascular health. Objective To describe the volume and content of Tweets associated with cardiovascular disease as well as the characteristics of Twitter users. Design, Setting, and Participants We used Twitter to access a random sample of approximately 10 billion English-language Tweets originating from US counties from July 23, 2009, to February 5, 2015, associated with cardiovascular disease. We characterized each Tweet relative to estimated user demographics. A random subset of 2500 Tweets was hand-coded for content and modifiers. Main Outcomes and Measures The volume of Tweets about cardiovascular disease and the content of these Tweets. Results Of 550 338 Tweets associated with cardiovascular disease, the terms diabetes (n = 239 989) and myocardial infarction (n = 269 907) were used more frequently than heart failure (n = 9414). Users who Tweeted about cardiovascular disease were more likely to be older than the general population of Twitter users (mean age, 28.7 vs 25.4 years; P P Conclusions and Relevance Twitter offers promise for studying public communication about cardiovascular disease.

Trends in US Heart Transplant Waitlist Activity and Volume During the Coronavirus Disease 2019 (COVID-19) Pandemic.

Abstract: Importance Solid organ transplants have declined significantly during the coronavirus disease (COVID-19) pandemic in the US. Limited data exist regarding changes in heart transplant (HT). Objective To describe national and regional trends in waitlist inactivations, waitlist additions, donor recovery, and HT volume during COVID-19. Design, Setting, and Participants This descriptive cross-sectional study used publicly available data from the United Network for Organ Sharing and US Centers for Disease Control and Prevention, using 8 prespecified United Network for Organ Sharing regions. Adult (18 years or older) HT candidates listed and deceased donors recovered between January 19 to May 9, 2020. Exposures COVID-19 pandemic. Main Outcomes and Measures Changes in waitlist inactivations, waitlist additions, deceased donor recovery, and transplant volumes from the pre–COVID-19 (January 19-March 15, 2020) to the COVID-19 era (March 15-May 9, 2020). Density mapping and linear regression with interrupted time series analysis were used to characterize changes over time and changes by region. Results During the COVID-19 era, there were 600 waitlist inactivations compared with 343 during the pre-COVID era (75% increase). Waitlist additions decreased from 637 to 395 (37% reduction). These changes were most profound in the Northeast and Great Lakes regions with high rates of COVID-19. Deceased donor recovery decreased by 26% from 1878 to 1395; the most significant decrease occurred in the North Midwest despite low COVID-19 prevalence. Heart transplant volumes were significantly reduced across all regions except the Northwest. The largest decrease was seen in the Northeast where COVID-19 case rates were highest. From the pre–COVID-19 era to the COVID-19 era, there was significant regional variation in waitlist additions (eg, 69% decrease in the Northeast vs 8.5% increase in the South Midwest;P Conclusions and Relevance Heart transplant volumes have been significantly reduced in recent months, even in regions with a lower prevalence of COVID-19 cases. This has been accompanied by increased waitlist inactivations, decreased waitlist additions, and decreased donor recovery. Future studies are needed to determine if the COVID-19 pandemic is associated with changes in waitlist mortality.

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.

Abstract: Background: The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world’s health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately. Objective: This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic. Methods: Leveraging a set of tools (Twitter’s search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms (“corona,” “2019-nCov,” and “COVID-19”), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic. Results: Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings). Conclusions: Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.

What social media told us in the time of COVID-19: a scoping review.

Abstract: With the onset of the COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak from November, 2019, to November, 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social media platforms and COVID-19. These themes focused on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID-19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos. Furthermore, our Review emphasises the paucity of studies on the application of machine learning on data from COVID-19-related social media and a scarcity of studies documenting real-time surveillance that was developed with data from social media on COVID-19. For COVID-19, social media can have a crucial role in disseminating health information and tackling infodemics and misinformation.