Study Finds Link Between Googling Symptoms And COVID-19 Case
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Researchers sought to find patterns with Google searches that could predict coronavirus spread. Based on Google search trends for nine symptoms, the team suggests their model can estimate the number of COVID-19 cases across the United States up to three weeks ahead.

- Observing state-level patterns

The team analyzed information from three time-series datasets. The study period included 245 days starting from March 1, 2020, through October 31, 2020. The team analyzed data from 422 COVID-related symptoms and conditions. Data were categorized based on distinct patterns for COVID-19 cases and death.

When looking at patterns by states, the team's cluster analysis showed seven distinct patterns of COVID-19 spread across 51 states. However, when looking at the number of deaths, there were fewer data fluctuations with only five disjoint groups. One of the five disjoint groups was New York.

- COVID-19 patterns correlated with Google searches

The team next analyzed combined datasets to look for associations. Their analysis showed a stronger association between Google COVID-19 symptom search trends and COVID-19 cases than the number of COVID-19 deaths. The top 15 symptoms also differed when observing correlating Google searches with COVID-19 cases and deaths.

However, both associations had hypoxemia, ageusia, and anosmia as part of the top 5 googled symptoms. Of the 422 symptoms observed in the study, googling hypoxemia was the most correlated symptom to the number of COVID-19 cases and deaths.

- Study limitations

The study used datasets where the most recent data was from the end of October 2020. This would most likely fail to capture SARS-CoV-2's evolving variants. The data may not accurately portray the state of the current nation. Researchers cannot rule out extraneous factors that differ across states.

Source:
https://www.medrxiv.org/content/10.1101/2021.02.22.21252254v1
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