Predicting COVID-19 Incidence Using Anosmia and Other COVID-19 Symptomatology: Preliminary Analysis Using Google and Twitter

Objective: To determine the relative correlations of Twitter and Google Search user trends concerning smell loss with daily coronavirus disease 2019 (COVID-19) incidence in the United States, compared to other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) symptoms. To describe the effect of mass media communications on Twitter and Google Search user trends. Study Design: Retrospective observational study. Setting: United States. Subjects and Methods: Google Search and “tweet” frequency concerning COVID-19, smell, and nonsmell symptoms of COVID-19 generated between January 1 and April 8, 2020, were collected using Google Trends and Crimson Hexagon, respectively. Spearman coefficients linking each of these user trends to COVID-19 incidence were compared. Correlations obtained after excluding a short timeframe (March 22 to March 24) corresponding to the publication of a widely read lay media publication reporting anosmia as a symptom of infection was performed for comparative analysis. Results: Google searches and tweets concerning all nonsmell symptoms (0.744 and 0.761, respectively) and COVID-19 (0.899 and 0.848) are more strongly correlated with disease incidence than smell loss (0.564 and 0.539). Twitter users tweeting about smell loss during the study period were more likely to be female (52%) than users tweeting about COVID-19 more generally (47%). Tweet and Google Search frequency pertaining to smell loss increased significantly (>2.5 standard deviations) following a widely read media publication linking smell loss and SARS-CoV-2 infection. Conclusions: Google Search and tweet frequency regarding fever and shortness of breath are more robust indicators of COVID-19 incidence than anosmia. Mass media communications represent important confounders that should be considered in future analyses.