Optimization of vaccination for COVID-19 in the midst of a pandemic
Abstract
During the Covid-19 pandemic a key role is played by vaccination to combat the virus. There are many possible policies for prioritizing vaccines, and different criteria for optimization: minimize death, time to herd immunity, functioning of the health system. Using an age-structured population compartmental finite-dimensional optimal control model, our results suggest that the eldest to youngest vaccination policy is optimal to minimize deaths. Our model includes the possible infection of vaccinated populations. We apply our model to real-life data from the US Census for New Jersey and Florida, which have a significantly different population structure. We also provide various estimates of the number of lives saved by optimizing the vaccine schedule and compared to no vaccination.
Additional Information
© 2022 American Institute of Mathematical Sciences. The authors acknowledge the support of the NSF CMMI project # 2033580 "Managing pandemic by managing mobility". R.W., S.T.M. and B.P. acknowledge the support of the Joseph and Loretta Lopez Chair endowment.Attached Files
Submitted - 2203.09502.pdf
Supplemental Material - 034e5a88-63b3-4957-8e63-cbdb3f76920a.xls
Supplemental Material - 393ec09c-e307-4681-b7a1-287a9e52fc7f.xls
Supplemental Material - 5564b0f2-8e2b-47d6-a3e7-b445e0a6ec94.xls
Files
Additional details
- Eprint ID
- 115242
- Resolver ID
- CaltechAUTHORS:20220622-933053900
- NSF
- CMMI-2033580
- Created
-
2022-06-24Created from EPrint's datestamp field
- Updated
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2022-06-28Created from EPrint's last_modified field
- Caltech groups
- COVID-19