HealthTechnology

Google Searches for COVID-19 Symptoms May Predict Site of Next Outbreak

Updated 28 September, 2020 | 12:26 IST

New research verified whether we could even be able to predict where the second outbreak will occur supported Google searches of common COVID-19 symptoms.
Researchers used Google Trends to live interest in specific GI symptoms related to COVID-19 to measure the actual incidence of COVID-19.
A problem with this type of data is that there’s potential for selection bias, which suggests the results aren’t indicative of the whole population.
As the US heads into the colder months, you will be hearing chatter a couple of new surge of COVID-19 as people congregate indoors.

New research verified whether we could even be able to predict where the second outbreak will occur supported Google searches of common COVID-19 symptoms.

According to a replacement study published by the American Gastroenterological Association, research shows that increased internet search interest for gastrointestinal (GI) symptoms could even be predicting COVID-19 outbreaks within the US.

Researchers used Google Trends to live interest in specific GI symptoms related to COVID-19 to measure the actual incidence of the disease. Data were analyzed from 15 states over 13 weeks between Jan. 20 and April 20. Common GI symptoms related to COVID-19 include:

loss of taste
abdominal pain
loss of appetite
diarrhea
vomiting
The research found that Google search interest in the loss of taste, loss of appetite, and diarrhea increased 4 weeks before a spike in COVID-19 cases in most states.


“Our results show that Google searches for specific, common GI symptoms correlated with the incidence of COVID-19 within the primary weeks of the pandemic in five states with high disease burden,” said the report. “Our results suggest that increased search volume for common GI symptoms may predict COVID-19 case volume, with 4 weeks because of the optimal gap between the increase in search volume and increased caseload.”

Using big data to predict disease outbreaks
“This is not the primary time Google searches are used to predict epidemics,” said Dr. Elena Ivanina, gastroenterologist, Lenox Hill Hospital.

She’s concerning the 2008 Google Flu Trends (GFT), a project that was designed to review trending Google searches related to flu symptoms to predict flu outbreaks approximately 2 weeks before the Centers for Disease Control and Prevention (CDC). The study trusted Source was published within the journal Nature and was Google’s decision to use big data methods to predict real-time flu trends.

Unfortunately, the project missed the mark. Search terms picked by GFT didn’t reflect actual incidences of illness and repeatedly resulted in inflated cases across the country. Not only that, the project completely missed the 2009 H1N1 pandemic.

“Since a 2009 article in NatureTrusted Source remarking the potential of using online searches for health-seeking information as the way to know the transmission of H1N1 influenza — a totally unique pandemic — there has been plenty of interest in harnessing the power of program data to predict outbreaks of infectious diseases,” said Jennifer Horney, founding director of the epidemiology program at the University of Delaware.

“However, a 2014 article in Science acknowledged that Google’s Flu Trends, which was later taken down, was predicting quite twice the number of doctor visits for influenza-like illness than the CDC was reporting,” she said.

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