After 25 years As a pediatric infectious disease specialist, Asunción Mejías is all too familiar with the deadly unpredictability of respiratory syncytial virus (RSV), a hospital-causing infection up to 80,000 children under 5 years old each year in the U.S.
“It’s a disease that can change very quickly,” says Mejias, who works at St. Jude Children’s Research Hospital in Memphis, Tennessee. “I’ve always told my colleagues that for every two children who are admitted, one can go to the ICU in the next three hours and the other can go home the next day. It’s totally unpredictable.”
RSV infections are very common, so much so that almost every child will have one before the age of 2. Most children experience cold-like symptoms, such as coughing and sneezing, but some can develop severe lung disease – RSV is responsible for More than 100,000 child deaths Every year, 100,000 deaths occur worldwide, of which almost half affect babies under 6 months of age.
The problem is that, aside from some known risk factors, such as premature birth and preexisting lung disease, it’s hard to know which children will be most affected. “Eighty percent of children who end up in the hospital with RSV appear completely healthy,” Mejias says. “They were born full-term and have no risk factors for severe disease.”
Around the world, different research groups are attempting to train machine learning algorithms or develop statistical models that can indicate which children are most vulnerable to RSV. Drawing on vast databases of electronic medical records, these tools aim to identify clusters of risk factors that can help predict which children are most likely to be hospitalized for an infection. Health care providers can then use this information to prioritize children at higher risk for vaccines and other preventive measures.
Earlier this year, respiratory epidemiologist Tina Hartert and her colleagues at Vanderbilt University developed One of those tools Using a statistical model to identify a set of 19 risk factors for RSV, after training it on data from more than 400,000 babies in Tennessee’s Medicaid program, “it allows you to calculate an individual baby’s risk at birth,” Hartert says.
Some of the variables used in the tool are not surprising. Prenatal smoking, for example, It is known Lung development in the fetus can be affected, making the baby more vulnerable to viral pneumonia, while low-birth-weight babies already lack the strength to breathe normally. However, in many cases, Hartert says it is a combination of different risk factors that converge to make a child vulnerable. “Assessing only individual factors leaves out many babies at risk,” she says.
In 2023, regulators in the US Approved a vaccine This is a vaccine called Abrysvo, designed to be administered to mothers between 32 and 36 weeks of pregnancy, with the aim of ensuring that babies are born with protective antibodies against RSV. approved a drug called Beyfortus, a laboratory-made protein called a monoclonal antibody, which can be administered through a single injection to provide protection before the winter RSV season.