A research team at the University of California, San Diego (UCSD) says it has refined and improved the predictions of Google Flu Trends (GFT).
The researchers report using social network analysis and combining the power of GFT's big data with traditional flu-monitoring data from the U.S. Centers for Disease Control and Prevention (CDC).
"Our innovation is to construct a network of ties between different U.S. health regions based on information from the CDC," says UCSD doctoral student Michael Davidson.
The team considered which places in previous years reported the flu at about the same time. "That told us which regions of the country have the strongest ties, or connections, and gave us the analytic power to improve Google's predictions," Davidson says.
The researchers say they can predict the spread of flu a week into the future with as much accuracy as GFT can display levels of infection right now. "We hope our method will be implemented by epidemiologists and data scientists, to better target prevention and treatment efforts, especially during epidemics," Davidson says.
From UCSD News (CA)
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