Improving Triage for COVID-19 Patients by Predicting the Timing of Clinical Outcomes

Read our paper in PLoS Pathogens describing our work to develop a computational model that uses immunological and standard clinical biomarkers to predict patient outcomes. We found that data collected during hospitalization—including spike-protein antibody levels as well as white blood cell, neutrophil, and lymphocyte counts—more accurately predicted whether or not COVID-19 patients would live or die.

Co-led by Gorka Lasso in the lab (Team).

See more here.