Calling all computational model developers! Big-data competition opens to help children at risk for severe COVID-19

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BARDA and its HHS partners launched a data challenge competition today to develop algorithms (computational models) that could help healthcare providers predict which of their pediatric patients with COVID-19 are likely to develop severe COVID-19 complications, including conditions such as multisystem inflammatory syndrome in children (MIS-C).

MIS-C is a rare but serious condition associated with COVID-19 in which different body parts become inflamed, including the heart, lungs, kidneys, brain, skin, eyes, or gastrointestinal organs. More than 4,100 cases of MIS-C had been reported to the Centers for Disease Control and Prevention, and 37 children in the U.S. have died from the condition.

While children infected with SARS-CoV-2 are less likely to develop severe illness compared with adults, children are still at risk of developing severe illness and complications from COVID-19. About 1 in 3 children hospitalized with COVID-19 in the United States were admitted to the intensive care unit, similar to the rate among adults. Healthcare providers need to know which pediatric patients will progress to moderate or severe COVID-19 to treat early and improve pediatric patient outcomes, potentially saving lives.

The challenge is sponsored by BARDA, in partnership with two institutes from the National Institutes of Health – the National Institute of Health’s National Center for Advancing Translational Sciences (NCATS) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) – along with the Health Resources and Services Administration’s (HRSA) Maternal and Child Health Bureau. The challenge will be administered by Sage Bionetworks.

Challenge participants must develop, train, and validate computational models to predict pediatric patients at risk for hospitalization, need for ventilation, and cardiovascular interventions, utilizing de-identified electronic health record data available through NCATS’ National COVID Cohort Collaborative (N3C) Data Enclave. The N3C Data Enclave is a central, harmonized data repository that represents electronic health records from more than 55 health centers across the U.S. To protect patient privacy, de-identified data provides information useful to researchers without revealing any information that could identify individual patients.

The total cash prize purse is $200,000 split among up to three winners. Winners also may be eligible to apply for follow on funding support and in-kind services from BARDA for further technology development and clinical evaluation.

To learn more about the challenge, including challenge rules, eligibility, criteria for winning entries, data enclave use requirements, and how to register to join the N3C consortium, visit the page. Because fully registering for the N3C consortium can take several weeks, potential participants are encouraged to review the requirements, rules, criteria, and timelines for each competition phase as soon as possible.

Last Updated: August 20, 2021