Dataset Information

Simulated Identification of Silent COVID-19 Infections Among Children and Estimated Future Infection Rates With Vaccination.

ABSTRACT:

Importance

A significant proportion of COVID-19 transmission occurs silently during the presymptomatic and asymptomatic stages of infection. Children, although important drivers of silent transmission, are not included in the current COVID-19 vaccination campaigns.

Objective

To estimate the benefits of identifying silent infections among children as a proxy for their vaccination.

Design, setting, and participants

This study used an age-structured disease transmission model, parameterized with census data and estimates from published literature, to simulate the estimated synergistic effect of interventions in reducing attack rates during the course of 1 year among a synthetic population representative of the US demographic composition. The population included 6 age groups of 0 to 4, 5 to 10, 11 to 18, 19 to 49, 50 to 64, and 65 years or older based on US census data. Data were analyzed from December 12, 2020, to February 26, 2021.

Exposures

In addition to the isolation of symptomatic cases within 24 hours of symptom onset, vaccination of adults was implemented to reach a 40% to 60% coverage during 1 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 that would suppress future attack rates to less than 5%.

Results

In the base-case scenarios with an effective reproduction number Re = 1.2, a targeted approach that identifies 11% of silent infections among children within 2 days and 14% within 3 days after infection would bring attack rates to less than 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 (≥81%) of this age group, in addition to 40% vaccination coverage of adults. The estimated 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. These findings suggest that without measures to interrupt transmission chains from silent infections, vaccination of adults is unlikely to contain the outbreaks in the near term.

SUBMITTER: Moghadas SM

PROVIDER: S-EPMC8065378 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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. To investigate the benefits of identifying silent infections among children as a proxy for their vaccination. 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. A synthetic population representative of the United States (US) demographics. Six age groups of 0-4, 5-10, 11-18, 19-49, 50-64, 65+ years based on US census data. 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. The combinations of proportion and speed for detecting silent infections among children which would suppress future attack rates below 5%. In the base-case scenarios with an effective reproduction number Re = 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. 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.

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