A new computational analysis shows that people under the age of 20 are half as likely to contract COVID-19 as adults, and they are less likely to infect others. Itai Dattner of the University of Haifa in Israel and his colleagues presented these findings in the open access journal PLOS Computional Biology.
Earlier research found that compared with adults, the symptoms of children and the clinical course of COVID-19 are different. Others report that the rate of children diagnosed is lower compared to older age groups. However, only a few studies have compared the modes of transmission among age groups, and their conclusions are uncertain.
In order to better understand the susceptibility and infectiousness of children, Dattner and colleagues fitted mathematical and statistical models of transmission in the family to the COVID-19 test result data set of Bnei Brak, a densely populated city in Israel. The data set covers 637 families, and their members have been tested for active infection by PCR in the spring of 2020. Some people have also received serological tests for SARS-CoV-2 antibodies.
By adjusting the model parameters to fit the data, the researchers found that people under 20 are 43% susceptible compared to people over 20. It is estimated that the infectivity is about 63% of adults, and children are also unlikely to spread COVID-19 to other people. The researchers also found that, despite being actually infected, children are more likely than adults to get negative PCR results.
These findings can explain reports from around the world that children are diagnosed at a lower rate than adults. They can help guide the mathematical modeling of COVID-19 dynamics, public health policies and control measures. Future computing research may explore communication dynamics in other environments, such as nursing homes and schools.