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Title: Analyzing web searches can help experts predict, respond to COVID-19 hot spots.
Author: The study was conducted in collaboration with the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery
Web-based analytics have demonstrated their value in predicting the spread of infectious disease according to the new study from Mayo Clinic indicates the value of analyzing Google web searches for keywords related to COVID-19.
There were strong correlations were found between keyword searches on the internet search engine Google Trends and COVID-19 outbreaks in parts of the U.S. These correlations were observed up to 16 days prior to the first reported cases in some states
The Studies demonstrate 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.
The study searched for 10 keywords that were chosen based on how commonly they were used and emerging patterns on the internet.
The keywords were:
COVID symptoms
Coronavirus symptoms
Sore throat+shortness of breath+fatigue+cough
Coronavirus testing center
Loss of smell
Face mask
Coronavirus vaccine
COVID stimulus check
Most of the keywords had moderate to strong correlations days before the first COVID-19 cases were reported in specific areas, with diminishing correlations following the first case.
The use of web search surveillance data is important as an adjunct for data science teams who are attempting to predict outbreaks and new hot spots in a pandemic. “Any delay in information could lead to missed opportunities to improve preparedness for an outbreak in a certain location.


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