An Analysis of Self-reported Longcovid Symptoms on Twitter
Abstract
Objectives
A majority of patients suffering from acute COVID-19 are expected to recover symptomatically and functionally. However there are reports that some people continue to experience symptoms even beyond the stage of acute infection. This phenomenon has been called longcovid.
Study design
This study attempted to analyse symptoms reported by users on twitter self-identifying as longcovid.
Methods
The search was carried out using the twitter public streaming application programming interface using a relevant search term.
Results
We could identify 89 users with usable data in the tweets posted by them. A majority of users described multiple symptoms the most common of which were fatigue, shortness of breath, pain and brainfog/concentration difficulties. The most common course of symptoms was episodic.
Conclusions
Given the public health importance of this issue, the study suggests that there is a need to better study post acute-COVID symptoms.
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