Science

Google web searches can assist in predicting Covid-19 outbreaks: Study

Prashasti Awasthi Mumbai | Updated on October 22, 2020 Published on October 22, 2020

A new study has found that web-based analytics strongly assisted in predicting the transmission of infectious disease.

The study carried by Mayo Clinic and published in the journal Mayo Clinic Proceedings found a strong correlation between Google web searches and outbreaks in parts of the US.

These correlations were observed up to 16 days prior to the first reported cases in some states.

Mohamad Bydon, a Mayo Clinic neurosurgeon and principal investigator at Mayo’s Neuro-Informatics Laboratory, said in an official statement: “Our study demonstrates that there is information present in Google Trends that precede outbreaks, and with predictive analysis, this data can be used for better allocating resources with regards to testing, personal protective equipment, medications and more.”

“The neuro-informatics team is focussed 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,” Bydon, the study’s senior author, added.

Looking at Google Trends data, the study authors found that they were able to identify predictors of hot spots, using keywords, that would emerge over a six-week timeline.

Several studies have noted the role of Internet surveillance in early prediction of previous outbreaks such as H1N1 and the Middle East respiratory syndrome, as per the report published in the journal EurekAlert!

ALSO READ: Viewers of Covid-19 news on Fox TV more likely to be biased against Asians: Study

Keyword search

The new study searched for 10 keywords that were shortlisted based on how commonly they were used and emerging patterns on the Internet and in Google News at that time. The keywords were: COVID symptoms; coronavirus symptoms; sore throat+shortness of breath+fatigue+cough; coronavirus testing center; loss of smell; lysol; antibody; face mask; coronavirus vaccine; and 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.

Bydon explained: “Each of these keywords had varying strengths of correlation with case numbers. If we had looked at 100 keywords, we may have found even stronger correlations to cases. As the pandemic progresses, people will search for new and different information, so the search terms also need to evolve.”

The study mentioned that opting for traditional surveillance, including widespread testing and public health reporting, can lag behind the incidence of infectious disease. The need for more testing, and more rapid and accurate testing, is paramount in such adverse times.

Follow us on Telegram, Facebook, Twitter, Instagram, YouTube and Linkedin. You can also download our Android App or IOS App.

Published on October 22, 2020
This article is closed for comments.
Please Email the Editor