Mayo Clinic says Google searches could help predict Covid-19 hot spots

Analyzing Google web searches could be a useful way of helping predict the next Covid-19 hot spots, according to a new study from Mayo Clinic.

The study, published this week in Mayo Clinic Proceedings, found “strong correlations” between keyword searches — such as “coronavirus symptoms” and “loss of smell” — and outbreaks in various parts of the U.S.

Because the correlations could be observed days before the first reported cases in some areas, researchers believe the information could be valuable to helping public health agencies prepare much more rapidly.

Dr. Mohamed Bydon, A Mayo neurosurgeon and the study’s lead author, said that could potentially mean using the data to better allocate resources such as testing, personal protective equipment, and medications.

"If you wait for the hot spots to emerge in the news media coverage, it will be too late to respond effectively," said Dr. Bydon. "In terms of national preparedness, this is a great way of helping to understand where future hot spots will emerge."

According to Mayo, the Google Trends data is being added as another variable in the Clinic’s Covid-19 tracking tool. The interactive platform reports the the latest data for every county in America, along with insight on how to assess risk and plan accordingly.

Cover graphic: screenshot / Google