Optimal strategy for a dose-escalation vaccination against COVID-19 in refugee camps

Qinyue Zheng, Xinwei Wang*, Qiuwei Pan, Lei Wang

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
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An immunogenic and safe vaccine against COVID-19 for use in the healthy population will become available in the near future. In this paper, we aim to determine the optimal vaccine administration strategy in refugee camps considering maximum daily administration and limited total vaccine supply. For this purpose, extended SEAIRD compartmental models are established to describe the epidemic dynamics with both single-dose and double-dose vaccine administration. Taking the vaccination rates in different susceptible compartments as control variables, the optimal vaccine administration problems are then solved under the framework of nonlinear constrained optimal control problems. To the best of our knowledge, this is the first paper that addresses an optimal vaccine administration strategy considering practical constraints on limited medical care resources. Numerical simulations show that both the single-dose and double-dose strategies can successfully control COVID-19. By comparison, the double-dose vaccination strategy can achieve a better reduction in infection and death, while the single-dose vaccination strategy can postpone the infection peak more efficiently. Further studies of the influence of parameters indicate that increasing the number of medical care personnel and total vaccine supply can greatly contribute to the fight against COVID-19. The results of this study are instructive for potential forthcoming vaccine administration. Moreover, the work in this paper provides a general framework for developing epidemic control strategies in the presence of limited medical resources.

Original languageEnglish
Pages (from-to)9288-9310
Number of pages23
JournalAIMS Mathematics
Issue number5
Publication statusPublished - 9 Mar 2022

Bibliographical note

The authors are grateful for the National Key Research and Development Plan (2019YFB1706502); the Natural Science Foundation of Shandong Province (ZR2020QG055); the National Natural Science Foundation of China (12102077); the Fundamental Research Funds for the Central Universities (DUT20YG125).

Publisher Copyright: © 2022 the Author(s), licensee AIMS Press.


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