Paper 2

Title: Prediction of Number of Cases of 2019 Novel Coronavirus (COVID-19) Using Social Media Search Index
Author: Qin, L.
Publication date: Apr 5, 2020
Journal: International Journal of Environmental Research and Public Health,
Aim: This study investigated the correlation between the number of new cases of COVID-19 and the search index for a popular social network in China
Methods: Social media search indexes (SMSI) for dry cough, fever, chest distress, coronavirus, and pneumonia to predict new suspected COVID-19 case numbers from 20 January 2020 to 9 February 2020.
Results: The new suspected COVID-19 case numbers correlated significantly with the lagged series of SMSI. SMSI could be detected 6–9 days earlier than new suspected cases of COVID-19.
Conclusion: SMSI could be an effective early predictor for the number of COVID-19 infections.
Link to paper: Prediction of Number of Cases of 2019 Novel Coronavirus (COVID-19) Using Social Media Search Index