Here’s an interesting announcement for those data analytics and algorithm developers from a division of the U.S. Department of Health and Human Services (HHS).
While most children with COVID-19 are asymptomatic or have mild symptoms, healthcare providers have difficulty determining which of their pediatric patients will progress to moderate or severe COVID-19 early in the progression. Some of these patients develop multisystem inflammatory syndrome in children (MIS-C), a life-threatening inflammation of organs and tissues. Methods to distinguish children at risk for severe COVID-19 complications, including conditions such as MIS-C, are needed for earlier interventions to improve pediatric patient outcomes.
Based on that need, multiple HHS divisions are coming together for a data challenge competition that will leverage de-identified electronic health record data to develop, train and validate computational models that can predict severe COVID-19 complications in children, equipping healthcare providers with the information and tools they need to identify pediatric patients at risk.
More information about the effort, led by the Biomedical Advanced Research and Development Authority (BARDA), is available here.