Modelling and optimal control of multi strain epidemics, with application to COVID-19

被引:56
作者
Arruda, Edilson F. [1 ]
Das, Shyam S. [3 ]
Dias, Claudia M. [3 ]
Pastore, Dayse H. [2 ]
机构
[1] Univ Southampton, Southampton Business Sch, Dept Decis Analyt & Risk, Southampton, Hants, England
[2] Fed Ctr Technol Educ Celso Suckow Fonseca, Dept Basic & Gen Disciplines, Rio De Janeiro, RJ, Brazil
[3] Univ Fed Rural Rio de Janeiro, Multidisciplinary Inst, Grad Program Math & Computat Modeling, Nova Iguacu, RJ, Brazil
关键词
SARS-COV-2;
D O I
10.1371/journal.pone.0257512
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Reinfection and multiple viral strains are among the latest challenges in the current COVID-19 pandemic. In contrast, epidemic models often consider a single strain and perennial immunity. To bridge this gap, we present a new epidemic model that simultaneously considers multiple viral strains and reinfection due to waning immunity. The model is general, applies to any viral disease and includes an optimal control formulation to seek a trade-off between the societal and economic costs of mitigation. We validate the model, with and without mitigation, in the light of the COVID-19 epidemic in England and in the state of Amazonas, Brazil. The model can derive optimal mitigation strategies for any number of viral strains, whilst also evaluating the effect of distinct mitigation costs on the infection levels. The results show that relaxations in the mitigation measures cause a rapid increase in the number of cases, and therefore demand more restrictive measures in the future.
引用
收藏
页数:18
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