University of Florida develops COVID-19 hospitalization predictive model

Using mobile data, University of South Florida data scientists developed a predictive analytics model to examine where new COVID-19 patients will surge, according to a report from News Channel 8, an NBC affiliate.

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Three things to know:

1. Researchers at the university collected GPS data from 3.5 million mobile devices in the Tampa Bay area and compared it with admissions data from 50 local hospitals to test the model.

2. There was a correlation between mobilization and COVID-19 hospital admissions, according to the report. Twenty-one days after a spike in movement, the model showed an increase in hospitalization data.

3. The data shows mobility has been up 150 percent since the state enacted a stay-at-home order, and the volume of daily visits to dense locations grew 220 percent. After the mask mandate, data showed a 23 percent drop in unique location visits.

More articles on data analytics:
Western Michigan University plugs state COVID-19 data gap, starts archive
Tech issue blamed for discrepancy in Oklahoma’s COVID-19 case numbers: 5 notes
HHS’ COVID-19 dashboard is ‘designed to be above politics and manipulation’: 8 key notes

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