Predicting COVID-19 new cases in California with Google Trends data and a machine learning approach.

Background: Google Trends data can be a valuable source of information for health-related issues such as predicting infectious disease trends.

Objectives: To evaluate the accuracy of predicting COVID-19 new cases in California using Google Trends data, we develop and use a GMDH-type neural network model and compare its performance with a LTSM model.

Methods: We predicted COVID-19 new cases using Google query data over three periods.