Published on in Vol 6, No 12 (2022): December
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/40825, first published
.
State-Level COVID-19 Symptom Searches and Case Data: Quantitative Analysis of Political Affiliation as a Predictor for Lag Time Using Google Trends and Centers for Disease Control and Prevention Data
State-Level COVID-19 Symptom Searches and Case Data: Quantitative Analysis of Political Affiliation as a Predictor for Lag Time Using Google Trends and Centers for Disease Control and Prevention Data
1 City, Culture, and Community, Department of Sociology, Tulane University, New Orleans, LA, United States