Google search activity can help predict COVID-19 outbreaks, studies show

Researchers are examining Google search data's potential to predict COVID-19 outbreaks so hospitals and public health departments can better anticipate case surges.

A study published Feb. 8 in npj Digital Medicine analyzed Google searches for COVID-19 symptoms early in the pandemic, using the types of symptoms entered and frequency of such searches to predict peaks in COVID-19 cases up to 17 days in advance. 

The "COVID-19 score" developed in the study is updated weekly in Public Health England’s pandemic surveillance reports. 

Another study published Feb. 4 in Social Network Analysis and Mining looked at search data's indications of mobility to see whether users were practicing COVID-19 lockdown precautions (such as searching for takeout) or living life as usual (such as searching for gyms or movie tickets). 

"Our goal was to capture the underlying social dynamics of an unprecedented pandemic using alternative data sources that are new to infectious disease epidemiology," Anasse Bari, PhD, one of the study authors, said in a news release. "When someone searches the closing time of a local bar or looks up directions to a local gym, they give some insight into what future risks they may have."

More articles on data analytics: 
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Immunizations expert accuses CDC, Deloitte of stealing her idea for vaccination tracking system
Some self-reported CDC data fueling the anti-vaccination movement


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