OBJECTIVES: Since March 2020, the Sars-Cov-2 virus has caused a global pandemic of acute respiratory infections and subsequent new pathologies including "Long covid" (LC), characterized by persistent symptoms weeks or months post-infection. Uniquely, this disease was described by patients on social networks concurrent with scientific community discovery. Existing studies predominantly focus on severe hospitalized cases, underlining the need to describe LC occurrence in patients treated by GPs, first medical contacts, regardless of infection severity.

Our study aims to scrutinize the predominant symptoms of LC by amalgamating diverse real-world data, including data collected during patients' medical follow-ups and social network contributions.

METHODS: Two data sources are compared. Firstly, LC related posts from French-language social networks between January 2020 and August 2021 using the Brandwatch® tool have been harvested, identifying symptoms via the MedDRA dictionary. An automated language processing algorithm filtered messages detailing actual medical experiences, creating an analysis corpus of 5,364 users (6,484 messages). Secondly, a retrospective observational study on THIN® France's health database was conducted, identifying 73,338 patients suffering from LC within six months of their acute infection between March 2020 and March 2022.

RESULTS: Both data sources revealed similar LC symptom categories. Asthenia, dyspnea, anxiety, headache, and abnormal state sensation were common symptoms reported on social networks. In contrast, asthenia, depression, anxiety, respiratory symptoms (cough), and pain complaints were most often reported in initial medical consultations for LC, with half of the patients reporting more than two symptoms.

CONCLUSIONS: The comparison of real-world data from two distinct sources, namely unstructured qualitative data from social networks and structured quantitative data from the THIN® database, highlights the symptomatology of LC. This synergy underscores the value of diverse data sources in enhancing our understanding of this emergent pathology.