Projecting the transition of COVID-19 burden towards the young population while vaccines are rolled out: a modelling study

Objectives SARS-CoV-2 infection causes most cases of severe illness and fatality in older age groups. In China, over 99% of individuals aged ⩾12 years have been fully vaccinated against COVID-19 (albeit with vaccines developed against historical lineages), while 65.0% children aged 3–11 years have been vaccinated their first doses (as of November 12, 2021). Here, we aimed to assess whether, in this vaccination landscape, the importation of Delta variant infections could shift the COVID-19 burden from adults to children. Methods We developed an age-structured susceptible-infectious-removed model of SARS-CoV-2 transmission dynamics to simulate epidemics triggered by the importation of Delta variant infections and project the age-specific incidence of SARS-CoV-2 infections, cases, hospitalisations, intensive care unit (ICU) admissions, and deaths. Results In the context of the vaccination programme targeting individuals aged ≥12 years (as it was the case until mid-October 2021), and in the absence of non-pharmaceutical interventions, the importation of Delta variant infections could have led to widespread transmission and substantial disease burden in mainland China, even with vaccination coverage as high as 97% across the eligible age groups. Extending the vaccination roll-out to include children aged 3–11 years (as it was the case since the end of October 2021) is estimated to dramatically decrease the burden of symptomatic infections and hospitalisations within this age group (54% and 81%, respectively, when considering a vaccination coverage of 99%), but would have a low impact on protecting infants (aged 0–2 years). Conclusions Our findings highlight the importance of including children among the target population and the need to strengthen vaccination efforts by increasing vaccine effectiveness. ### Competing Interest Statement H.Y. received research funding from Sanofi Pasteur, GlaxoSmithKline, Yichang HEC Changjiang Pharmaceutical Company, Shanghai Roche Pharmaceutical Company, and SINOVAC Biotech Ltd. M.A. received research funding from Seqirus. Except for research funding from SINOVAC Biotech Ltd, which is related to the data analysis of clinical trials of immunogenicity and safety of CoronaVac, the others are not related to COVID-19. All the other authors have no competing interests. ### Funding Statement This study was supported by grants from the Key Program of the National Natural Science Foundation of China (82130093) and the National Institute for Health Research (NIHR) (grant no. 16/137/109) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The data and code that support the findings of this study will be made available on GitHub upon the acceptance of this manuscript.