Google searches on covid19 symptoms may predict site for next outbreak
By Fabian Flyboi
4 weeks ago
Google Searches for COVID-19 Symptoms May Predict Site of Next Outbreak
Written by Fabian Flyboi on September 26, 2020
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Researchers want to know if Google searches can predict where the coronavirus is spreading. Pekic / Getty Images
- New research looked at whether we may be able to predict where the second outbreak will occur based on Google searches of common COVID-19 symptoms.
- Researchers used Google Trends to measure interest in specific GI symptoms related to COVID-19 to gauge actual incidence of COVID-19.
- A problem with this type of data is that there’s potential for selection bias, which means the results are not indicative of the whole population.
As the United States heads into the colder months, you may be hearing chatter about a new surge of COVID-19 as people congregate indoors.
New research looked at whether we may be able to predict where the second outbreak will occur based on Google searches of common COVID-19 symptoms.
According to a new study published by the American Gastroenterological Association, research shows that increased internet search interest for gastrointestinal (GI) symptoms may be predicting COVID-19 outbreaks in the United States.
Researchers used Google Trends to measure interest in specific GI symptoms related to COVID-19 to gauge actual incidence of the disease. Data was 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
The research found that Google search interest in 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 incidence of COVID-19 in the first 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 as the optimal gap between increase in search volume and increased caseload.”
“This is not the first time Google searches have been used to predict epidemics,” said Dr. Elena Ivanina, gastroenterologist, Lenox Hill Hospital.
She’s referring to the 2008 Google Flu Trends (GFT), a project that was designed to study trending Google searches related to flu symptoms to predict flu outbreaks approximately 2 weeks before the Centers for Disease Control and Prevention (CDC). The studyTrusted Source was published in the journal Nature, and was Google’s attempt to use big data methods to predict real-time flu trends.
Unfortunately, the project missed the mark. Search terms picked by GFT did not 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 pointing out the potential of using online searches for health-seeking information as a way to understand the transmission of the H1N1 influenza — a novel pandemic — there has been a lot of interest in harnessing the power of search engine 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 pointed out that Google’s Flu Trends, which was later taken down, was predicting more than twice the number of doctor visits for influenza-like illness than the CDC was reporting,” she said.
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