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A new predictive model helps identify those at risk for severe COVID-19

 E-Mail Researchers at the Buck Institute analyzed data from the COVID-19 Symptom Tracker app used by 3 million people in the United Kingdom, adding the use of immunosuppressant medication, use of a mobility aid, shortness of breath, fever, and fatigue to the list of symptoms and comorbidities that increase the risk for severe COVID-19. Results are published in the Even though there are established risk factors for severe COVID-19 there are no good predictors that enable healthcare providers, or even those who have tested positive, to assess who should seek advanced medical care, says Buck Institute Associate Professor David Furman, PhD, the senior scientist who led the study. We are glad to add to the efforts underway around the world to determine how to best care for those infected by the coronavirus.

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