Johns Hopkins Researchers Develop App Aimed To Identify Potential COVID-19 Hotspots
BALTIMORE (WJZ) -- Identifying the next COVID-19 outbreak might seem impossible, but doctors and engineers at Johns Hopkins University are developing an app which they hope will come close.
The new COVID-19 tracker app aims to become an early warning system that predicts potential coronavirus hotspots before they get out of hand.
It's called "COVID Control" and asks users to input their temperature and answer four questions associated with symptoms of the virus.
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Dr. Frank Curriero is a professor at Johns Hopkins Bloomberg School of Public Health.
"Not only could we build a dashboard and map the results of people putting in with their temperatures, but we can apply some analytics to go beyond the map," he said. "And that whole idea about identifying these clusters, or anomalous hot spots of high temperatures, that would be a leading edge to an emerging COVID cluster."
Researchers said, with the information they get from users, they'll be able to predict areas which may be vulnerable to an outbreak.
This can help determine where crucial resources go and allow for a more targeted approach to prevention efforts.
Dr. Robert Stevens is an associate professor at Johns Hopkins.
"With the data, we can alert health authorities, government officials, of it looks like in this county, it looks to be, a high probability of an outbreak occurring in the future, maybe with one or two weeks notice before that outbreak occurs," Stevens said.
The brains behind this operation is Dr. Stevens, Dr. Curriero and Dr. Ralph Etienne-Cummings, together with their Johns Hopkins students.
They said the only way for this app to work, though, is if people participate, whether you're sick or not.
"And then they would make it part of their routine in the morning, when they wake up while brushing their teeth, the measure their temperature into the system," Etienne-Cummings said.
The researchers said they're going to compare the data they collect through their app with confirmed COVID-19 cases to get a sense of how accurate this tool is.
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