BACKGROUND: The Centers for Disease Control and Prevention (CDC) in United States initially alerted the public to three COVID-19 signs and symptoms-fever, dry cough, and shortness of breath. Concurrent social media posts reflected a wider range of symptoms of COVID-19 besides these three symptoms. Because social media data have a potential application in the early identification novel virus symptoms, this study aimed to explore what symptoms mentioned in COVID-19-related social media posts during the early stages of the pandemic. METHODS: We collected COVID-19-related Twitter tweets posted in English language between March 30, 2020 and April 19, 2020 using search terms of COVID-19 synonyms and three common COVID-19 symptoms suggested by the CDC in March. Only unique tweets were extracted for analysis of symptom terms. RESULTS: A total of 36 symptoms were extracted from 30,732 unique tweets. All the symptoms suggested by the CDC for COVID-19 screening in March, April, and May were mentioned in tweets posted during the early stages of the pandemic. DISCUSSION: The findings of this study revealed that many COVID-19-related symptoms mentioned in Twitter tweets earlier than the announcement by the CDC. Monitoring social media data is a promising approach to public health surveillance.
BACKGROUND: The Centers for Disease Control and Prevention (CDC) in United States initially alerted the public to three COVID-19 signs and symptoms-fever, dry cough, and shortness of breath. Concurrent social media posts reflected a wider range of symptoms of COVID-19 besides these three symptoms. Because social media data have a potential application in the early identification novel virus symptoms, this study aimed to explore what symptoms mentioned in COVID-19-related social media posts during the early stages of the pandemic. METHODS: We collected COVID-19-related Twitter tweets posted in English language between March 30, 2020 and April 19, 2020 using search terms of COVID-19 synonyms and three common COVID-19 symptoms suggested by the CDC in March. Only unique tweets were extracted for analysis of symptom terms. RESULTS: A total of 36 symptoms were extracted from 30,732 unique tweets. All the symptoms suggested by the CDC for COVID-19 screening in March, April, and May were mentioned in tweets posted during the early stages of the pandemic. DISCUSSION: The findings of this study revealed that many COVID-19-related symptoms mentioned in Twitter tweets earlier than the announcement by the CDC. Monitoring social media data is a promising approach to public health surveillance.
Authors: Caleb P Skipper; Katelyn A Pastick; Nicole W Engen; Ananta S Bangdiwala; Mahsa Abassi; Sarah M Lofgren; Darlisha A Williams; Elizabeth C Okafor; Matthew F Pullen; Melanie R Nicol; Alanna A Nascene; Kathy H Hullsiek; Matthew P Cheng; Darlette Luke; Sylvain A Lother; Lauren J MacKenzie; Glen Drobot; Lauren E Kelly; Ilan S Schwartz; Ryan Zarychanski; Emily G McDonald; Todd C Lee; Radha Rajasingham; David R Boulware Journal: Ann Intern Med Date: 2020-07-16 Impact factor: 25.391
Authors: Ari Z Klein; Arjun Magge; Karen O'Connor; Jesus Ivan Flores Amaro; Davy Weissenbacher; Graciela Gonzalez Hernandez Journal: J Med Internet Res Date: 2021-01-22 Impact factor: 5.428
Authors: Valentin Ritschl; Fabian Eibensteiner; Erika Mosor; Maisa Omara; Lisa Sperl; Faisal A Nawaz; Chandragiri Siva Sai; Merisa Cenanovic; Hari Prasad Devkota; Mojca Hribersek; Ronita De; Elisabeth Klager; Eva Schaden; Maria Kletecka-Pulker; Sabine Völkl-Kernstock; Harald Willschke; Christoph Aufricht; Atanas G Atanasov; Tanja Stamm Journal: JMIR Form Res Date: 2022-06-21