Emerging application of Google Trends searches on “conjunctivitis” for tracing the course of COVID-19 pandemic

Abstract

Purpose: The aim of the present study was to use Google Trends for evaluating the association between the internet searches of the term “conjunctivitis” and the daily new cases of COVID-19. Methods: The relative search volume (RSV) of conjunctivitis from January 1 to April 16, 2019 (control group), January 1 to April 16, 2020 (first wave), and October 1 to December 31, 2020 (second wave) was obtained using Google Trends in Italy, France, United Kingdom, and United States. The number of COVID-19 daily new cases in the same countries were retrieved from Worldometer. Lag time correlation analyses were performed to evaluate the relationship between RSV and daily new cases (Pearson’s correlation coefficient). Results: During the first wave, the lagged RSV of conjunctivitis was significantly correlated with the number of COVID-19 daily new cases in all investigated countries. The highest correlation coefficients were obtained with a lag of 16 days in Italy ( R = 0.868), 18 days in France ( R = 0.491), 15 days in United Kingdom ( R = 0.883), and 14 days in United States ( R = 0.484) (all p < 0.001). Conversely, no significant correlations were found in the second wave and in the control group. Conclusion: Google Trends searches on conjunctivitis were significantly correlated with COVID-19 daily new cases during the first wave in Italy, France, United Kingdom, and United States, with a lag of 14–18 days. Repeating the analysis for the second wave, however, no significant correlations were found in any of the investigated countries.