Giving Compass' Take:

• Noelle Toumey Reetz explains how researchers collected Twitter data to analyze self-reported symptoms of those experiencing long-term effects from COVID-19.

• How might Twitter data include self-report bias? Either way, why is it important for researchers to continue devising innovative approaches for studying the largely unknown effects of COVID-19? How can you help support these innovations?

• Find resources to guide you in supporting research on COVID-19.

Social media data is shedding light on the experiences of so-called “long-haulers,” people who remain sick long after being diagnosed with COVID-19, researchers report.

Experts know little about the clinical course of COVID-19. In the early days of the pandemic, clinicians did not believe coronavirus symptoms could persist past two or three weeks. Patients tended to either recover quickly or die from the infection.

In late July, the Centers for Disease Control and Prevention published a report acknowledging that in a third of patients—even young adults with no preexisting conditions—COVID-19 can result in prolonged illness.

Juan Banda, assistant professor of computer science at Georgia State University, has amassed one of the world’s largest publicly available datasets of COVID-19 Twitter chatter, made up of more than 602 million individual Tweets.

The researchers used the dataset to identify common symptoms shared by long-haulers, some of whom take months to recover. The work is important because clinical reports documenting long-term symptoms of COVID-19 are not accessible to the public.

“Clinical data is not easily available, and it does not always capture detailed follow-up of the patients,” Banda says. “However, those patients are sharing their experiences on social media, allowing us to study the progression of the disease based on self-reported experiences.”

The researchers analyzed Tweets that were published in May—more than 60 days after the start of the pandemic—through July. The 10 most commonly mentioned symptoms were malaise and fatigue, labored breathing, tachycardia or heart palpitations, chest pain, insomnia/sleep disorders, cough, headache, and joint pain or fever.

“We have demonstrated that researchers can leverage social media data, specifically from Twitter, to conduct long-term studies of self-reported symptoms,” Banda says.

Read the full article about Twitter data on COVID-19 by Noelle Toumey Reetz at Futurity.