Analyzing Web Searches Can Help Experts Predict, Respond to COVID-19 Hot Spots

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Web-based analytics have demonstrated their value in predicting the spread of infectious disease, and a new study from Mayo Clinic indicates the value of analyzing Google web searches for keywords related to COVID-19.

Web-based analytics have demonstrated their value in predicting the spread of infectious disease, and a new study from Mayo Clinic indicates the value of analyzing Google web searches for keywords related to COVID-19.

Strong correlations were found between keyword searches on the internet search engine Google Trends and COVID-19 outbreaks in parts of the U.S., according to a study published in Mayo Clinic Proceedings. These correlations were observed up to 16 days prior to the first reported cases in some states.

"Our study demonstrates that there is information present in Google Trends that precedes outbreaks, and with predictive analysis, this data can be used for better allocating resources with regards to testing, personal protective equipment, medications and more," says Mohamad Bydon, M.D., a Mayo Clinic neurosurgeon and principal investigator at Mayo's Neuro-Informatics Laboratory.

"The Neuro-Informatics team is focused on analytics for neural diseases and neuroscience. However, when the novel coronavirus emerged, my team and I directed resources toward better understanding and tracking the spread of the pandemic," says Dr. Bydon, the study's senior author. "Looking at Google Trends data, we found that we were able to identify predictors of hot spots, using keywords, that would emerge over a six-week timeline."

Read more at Mayo Clinic

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