Simulated identification of silent COVID-19 infections among children and estimated future infection rates with vaccination.

IMPORTANCE: A significant proportion of COVID-19 transmission occurs silently during the pre-symptomatic and asymptomatic stages of infection. Children, while being important drivers of silent transmission, are not included in the current COVID-19 vaccination campaigns. OBJECTIVE: To investigate the benefits of identifying silent infections among children as a proxy for their vaccination. DESIGN: This study used an age-structured disease transmission model, parameterized with census data and estimates from published literature, to simulate the synergistic effect of interventions in reducing attack rates over the course of one year. SETTING: A synthetic population representative of the United States (US) demographics. PARTICIPANTS: Six age groups of 0-4, 5-10, 11-18, 19-49, 50-64, 65+ years based on US census data. INTERVENTIONS: In addition to the isolation of symptomatic cases within 24 hours of symptom onset, vaccination of adults was implemented to reach a 40%-60% coverage over the course of one year with an efficacy of 95% against symptomatic and severe COVID-19. MAIN OUTCOMES AND MEASURES: The combinations of proportion and speed for detecting silent infections among children which would suppress future attack rates below 5%. RESULTS: In the base-case scenarios with an effective reproduction number R e = 1.2, a targeted approach that identifies 11% and 14% of silent infections among children within 2 or 3 days post-infection, respectively, would bring attack rates under 5% with 40% vaccination coverage of adults. If silent infections among children remained undetected, achieving the same attack rates would require an unrealistically high vaccination coverage (at least 81%) of this age group, in addition to 40% vaccination coverage of adults. The effect of identifying silent infections was robust in sensitivity analyses with respect to vaccine efficacy against infection and reduced susceptibility of children to infection. CONCLUSIONS AND RELEVANCE: In this simulation modeling study of a synthetic US population, in the absence of vaccine availability for children, a targeted approach to rapidly identify silent COVID-19 infections in this age group was estimated to significantly mitigate disease burden. Without measures to interrupt transmission chains from silent infections, vaccination of adults is unlikely to contain the outbreaks in the near term.