Modelling and optimal control of multi strain epidemics, with application to COVID-19
Modelling and optimal control of multi strain epidemics, with application to COVID-19
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.
Arruda, Edilson F.
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Das, Shyam S.
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Dias, Claudia Mazza
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Pastore, Dayse H.
50335f89-5fe1-4f90-9b7d-59647d652942
16 September 2021
Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Das, Shyam S.
b5e8d90c-67b9-4d49-979e-d75e385eaf24
Dias, Claudia Mazza
95b06278-5b4f-4b12-aa33-68a096f4a436
Pastore, Dayse H.
50335f89-5fe1-4f90-9b7d-59647d652942
Arruda, Edilson F., Das, Shyam S., Dias, Claudia Mazza and Pastore, Dayse H.
(2021)
Modelling and optimal control of multi strain epidemics, with application to COVID-19.
PLoS ONE, 16 (9 September), [e0257512].
(doi:10.1371/journal.pone.0257512).
Abstract
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.
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PlosOne(2021)
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Accepted/In Press date: 2 September 2021
Published date: 16 September 2021
Additional Information:
Funding Information:
Funding:Thisstudywaspartlysupportedby Conselho Nacional de Desenvolvimento Cientı ´ fico e Tecnolo ´ gico-CNPq,undergrant311075/2018-5 andbyCoordenac ¸ãodeAperfeic ¸oamentode Pessoal de Nı ´vel Superior—Brasil (CAPES) [FinanceCode001].
Publisher Copyright:
© 2021 Arruda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Local EPrints ID: 451483
URI: http://eprints.soton.ac.uk/id/eprint/451483
ISSN: 1932-6203
PURE UUID: bba1e592-688d-4917-9611-1c430c500efc
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Date deposited: 30 Sep 2021 16:34
Last modified: 17 Mar 2024 04:04
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Author:
Edilson F. Arruda
Author:
Shyam S. Das
Author:
Claudia Mazza Dias
Author:
Dayse H. Pastore
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