Tracking Asymptomatic Cases in Children

A simulation study from researchers at the Yale School of Public Health suggests that early detection of asymptomatic COVID-19 in children would be as effective as vaccination at containing the virus.

The results, derived from a detailed computer model, show that restricting vaccine access to adults would not be sufficient to stop the pandemic from worsening. In fact, without a concerted effort to trace the virus before symptoms appear, vaccination rates would have to be far higher than rates at the time the study was conducted to contain outbreaks in the short term. The study, led by Alison Galvani, Ph.D., the Burnett and Stender Families Professor of Epidemiology and the director of the Center for Infectious Disease Modeling and Analysis at YSPH, was published in JAMA Network Open.

Without the typical markers of infection, children and adults can pass on the virus without knowing it—a potent contributor to worldwide disease rates. Tracking this “silent” transmission can be an effective way of controlling the coronavirus, especially through routine testing at schools and other settings.

Indeed, the researchers found, identifying just 11% of all silent cases in children within two days of infection and 14% within three days could significantly mitigate the spread of the disease even with a majority of adults being unvaccinated. Data from the model also suggest that the speed of identification is more important than the proportion of cases discovered.

“Therefore,” they wrote, “enhancing the capacity for rapid tracing of contacts of symptomatic individuals is critical to mitigating disease transmission.”

Since gaps still remain in scientists’ understanding of the vaccines’ effects on children, this approach could become an effective tool to keep communities safe as vaccination drives and clinical trials continue, the researchers wrote.