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Epidemic control by social distancing and vaccination: Optimal strategies and remarks on the COVID-19 Italian response policy.
d'Onofrio, Alberto; Iannelli, Mimmo; Manfredi, Piero; Marinoschi, Gabriela.
Afiliação
  • d'Onofrio A; Dipartimento di Matematica, Informatica e Geoscienze, Università di Trieste, Via Alfonso Valerio 12, Edificio H2bis, 34127 Trieste, Italy.
  • Iannelli M; Department of Mathematics, University of Trento, Via Sommarive 14, 38123 Trento, Italy.
  • Manfredi P; Dipartimento di Economia e Management, University of Pisa, Via Ridolfi 10, 56124 Pisa, Italy.
  • Marinoschi G; Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics, Romanian Academy, Bucharest, Romania.
Math Biosci Eng ; 21(7): 6493-6520, 2024 Jul 03.
Article em En | MEDLINE | ID: mdl-39176405
ABSTRACT
After the many failures in the control of the COVID-19 pandemic, identifying robust principles of epidemic control will be key in future preparedness. In this work, we propose an optimal control model of an age-of-infection transmission model under a two-phase control regime where social distancing is the only available control tool in the first phase, while the second phase also benefits from the arrival of vaccines. We analyzed the problem by an ad-hoc numerical algorithm under a strong hypothesis implying a high degree of prioritization to the protection of health from the epidemic attack, which we termed the "low attack rate" hypothesis. The outputs of the model were also compared with the data from the Italian COVID-19 experience to provide a crude assessment of the goodness of the enacted interventions prior to the onset of the Omicron variant.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Vacinação / Pandemias / Distanciamento Físico / SARS-CoV-2 / COVID-19 Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Math Biosci Eng Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Vacinação / Pandemias / Distanciamento Físico / SARS-CoV-2 / COVID-19 Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Math Biosci Eng Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália
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