Abstract
COVID-19 vaccines have been approved for children of age five and older in many countries. However, there is an ongoing debate as to whether children should be vaccinated and at what priority. In this work, we use mathematical modeling and optimization to study how vaccine allocations to different age groups effect epidemic outcomes. In particular, we consider the effect of extending vaccination campaigns to include the vaccination of children. When vaccine availability is limited, we consider Pareto-optimal allocations with respect to competing measures of the number of infections and mortality and systematically study the trade-offs among them. In the scenarios considered, when some weight is given to the number of infections, we find that it is optimal to allocate vaccines to adolescents in the age group 10-19, even when they are assumed to be less susceptible than adults. We further find that age group 0-9 is included in the optimal allocation for sufficiently high values of the basic reproduction number.
Original language | English |
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Article number | e1009872 |
Pages (from-to) | e1009872 |
Journal | PLoS Computational Biology |
Volume | 18 |
Issue number | 2 |
DOIs | |
State | Published - 25 Feb 2022 |
Keywords
- Adolescent
- Adult
- COVID-19 Vaccines
- COVID-19/epidemiology
- Child
- Child, Preschool
- Health Care Rationing/statistics & numerical data
- Humans
- Infant
- Infant, Newborn
- Mass Vaccination/methods
- Models, Statistical
- Young Adult
All Science Journal Classification (ASJC) codes
- Genetics
- Ecology, Evolution, Behavior and Systematics
- Cellular and Molecular Neuroscience
- Molecular Biology
- Ecology
- Computational Theory and Mathematics
- Modelling and Simulation