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FAMU Epidemiologist Talks Predictive Models, And Why They Should Be Taken With A Grain Of Salt

Special to WFSU

Last week, Tallahassee Memorial Healthcare published predictive models regarding COVID-19 hospitalizations in the region. The “most likely” model predicts 361 daily hospital admission, peaking at the end of May. Its best case, nearly 230 admissions per day in mid-June. (Both models are pictured at the bottom of this story)

Dr. C. Perry Brown, professor of epidemiology at Florida A&M University’s Institute of Public Health, is on a board that assists the Florida Department of Health with its modeling. He spoke with WFSU's Ryan Dailey about modeling – and why every predictive model should be taken with a grain of salt.

Questions, with timestamps:

0:20 - You’ve looked over the TMH models – what can you tell us about how those were drawn up?

2:03 - Is there a reason why, as a hospital, you would want to find a worst case?

2:36  - Could you explain your involvement with the Department of Health, and how their modeling process works?

4:00 - You made the statement, “All models are wrong” – what do you mean by that?

Credit Tallahassee Memorial HealthCare
This predictive model, run by University of Pennsylvania Medical School, shows a possible "best case" scenario of hospitalizations at Tallahassee Memorial HealthCare amid the COVID-19 pandemic. TMH published the models Thursday, April 9, 2020
Credit Tallahassee Memorial HealthCare
This predictive model, run by University of Pennsylvania Medical School, shows a "most likely" scenario of hospitalizations at Tallahassee Memorial HealthCare amid the COVID-19 pandemic. TMH published the models Thursday, April 9, 2020

Ryan Dailey is a reporter/producer for WFSU/Florida Public Radio. After graduating from Florida State University, Ryan went into print journalism working for the Tallahassee Democrat for five years. At the Democrat, he worked as a copy editor, general assignment and K-12 education reporter.