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RSV Can Be a Killer. New Tools Are Identifying the Most At-Risk Kids
RSV infects almost every child before they turn 2, and kills more than 100,000 infants worldwide each year. Machine learning and statistical models are identifying those most at risk.
Earlier this year, respiratory epidemiologist Tina Hartert and her colleagues at Vanderbilt University developed one such tool using a statistical model to identify a set of 19 risk factors for RSV, after training it on data from more than 400,000 infants on the Tennessee Medicaid program. Vartiainen has developed a tool similar to Hartert’s, called RSV Risk, based on a number of clinical measurements including birth weight, mother’s age, family history, and whether a child was born with conditions such as congenital heart defects. While the digital tools developed so far are intended to inform medical decisions such as immunizations shortly after a child is born, Mejías predicts that, in the coming years, there could also be more advanced options to screen children when they are admitted to hospital with a serious RSV infection.
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