Researchers Present Findings on Role of Google Search Early in COVID-19 Pandemic

Non-generic queries in the online tool Google Trends may yield better insight into health information-seeking behavior, according to a new study by researchers from the George Washington University (GW).

Google TrendsTM analyzes the popularity of top Google queries geographically and longitudinally. More recently it has been used as a surveillance and retrospective epidemiological tool to study the impact of COVID-19 around the world. However, studies focusing on the pandemic’s impact in the United States have been lacking, according to the researchers.

"What's interesting about Google Trends is that it is a free platform that allows researchers like me to assess information-seeking behavior from a big data perspective," said King John Pascual, a third-year MD student at the GW School of Medicine and Health Sciences (SMHS) and first author on the study. "Just like with any big-data platform, if you have the right research questions, it can be a powerful epidemiological tool."

The study, conducted by Pascual and his mentor Ali Pourmand, MD, MPH, professor of emergency medicine at SMHS, utilized Google Trends to assess the extent of the public’s perceived exposure to COVID-19 as it relates to disease prevalence during the early phase of the pandemic in the U.S. The team collected four weeks of search volume index (SVI) data from March 2020.

Out of the five queries analyzed, two that signal perceived exposure to the virus, "How do I get tested for coronavirus?" or "Do I have coronavirus?" had statistically significant differences in mean SVI between states with the highest and lowest numbers of COVID-19 cases. Generic queries such as "What is coronavirus?" or "How is coronavirus spread?" that do not necessarily reflected perceived exposure to the virus were not associated with the number of COVID-19 cases. The study findings imply how analyzing specific phrases, in lieu of those borne out by general interest, may yield more meaningful data about perceived exposure to a communicable disease on a population level.

"Early access to population health data is crucial and potentially lifesaving," said Pascual. "Digital tools such as Google Trends may help bridge the gap in knowledge and transparency."

The findings will be available 24/7 on demand during the Research Forum at the American College of Emergency Physicians annual conference, the world’s largest emergency medicine conference, Oct. 26-29. The abstract is also published in the supplement to the November 2020 issue of the Annals of Emergency Medicine: els-jbs-prod-cdn.jbs.elsevierhealth.com/pb/assets/raw/Health%20Advance/journals/ymem/YMEM764Sfinalv2.pdf

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...