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With the coronavirus disease 2019 (COVID-19) vaccine still not authorized for use in most of the pediatric population, reducing infection in children is important and identifying asymptomatic and presymptomatic infections could be key.
Two of the key ways that coronavirus disease 2019 (COVID-19) has been transmitted includes the presymptomatic period as well as asymptomatic cases. Children have been one of the major drivers of those silent forms of transmission. Most children are also not able to get COVID-19 vaccines. A simulation investigation in JAMA Network Open looks how much identifying silent COVID-19 infections could reduce the disease burden in a way similar to vaccination in adults.1
The investigators used an age-structured disease transmission model to simulate the effect of interventions in reducing the attack rates over the course of 1 year. The population in the simulation was representative of US demographics, from the most recent US census, and included 6 age groups: 0 to 4 years, 5 to 10 years, 11 to 18 years, 19 to 49 years, 50 to 64, and 65 years or older.
The simulation found that with a targeted approach that was able to identify 11% of silent infections among children within 2 days of infection and 14% within 3 days of infection would reduce the attack rates to less than 5% with 40% vaccination coverage in adults. However, if the there is no detection of silent infection in children, in order to have the same attack rates, there would need to be a vaccination coverage of ≥81% among children, which can’t be done at this time, in addition to the 40% vaccination coverage in adults.
The investigators concluded that an approach that involved rapid identification of COVID-19 infection in children in conjunction with adult vaccination led to significantly diminished disease burden. Additionally, they concluded that without an interruption in silent infections the vaccination of adults is not likely to contain COVID-19 outbreaks in the near future.
1. Moghadas S, Fitzpatrick M, Shoukat A, Zhang K, Galvani A. Simulated identification of silent COVID-19 infections among children and estimated future infection rates with vaccination. JAMA Netw Open. 2021;4(4):e217097. doi:10.1001/jamanetworkopen.2021.7097