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The impact of vaccination on the evolution of COVID-19 in Portugal.
Machado, Beatriz; Antunes, Liliana; Caetano, Constantino; Pereira, João F; Nunes, Baltazar; Patrício, Paula; Morgado, M Luísa.
  • Machado B; School of Science and Technology, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, Vila Real 5001-801, Portugal.
  • Antunes L; Departamento de Epidemiologia, Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA), Lisbon 1649-016, Portugal.
  • Caetano C; Departamento de Epidemiologia, Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA), Lisbon 1649-016, Portugal.
  • Pereira JF; Center for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, Lisbon 1049-001, Portugal.
  • Nunes B; School of Science and Technology, University of Trás-os-Montes e Alto Douro, UTAD, Quinta de Prados, Vila Real 5001-801, Portugal.
  • Patrício P; Departamento de Epidemiologia, Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA), Lisbon 1649-016, Portugal.
  • Morgado ML; Departamento de Epidemiologia, Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA), Lisbon 1649-016, Portugal.
Math Biosci Eng ; 19(1): 936-952, 2022 01.
Article in English | MEDLINE | ID: covidwho-1551673
ABSTRACT
In this work we use simple mathematical models to study the impact of vaccination against COVID-19 in Portugal. First, we fit a SEIR type model without vaccination to the Portuguese data on confirmed cases of COVID-19 by the date of symptom onset, from the beginning of the epidemic until the 23rd January of 2021, to estimate changes in the transmission intensity. Then, by including vaccination in the model we develop different scenarios for the fade-out of the non pharmacological intervention (NPIs) as vaccine coverage increases in the population according to Portuguese vaccination goals. We include a feedback function to mimic the implementation and relaxation of NPIs, according to some disease incidence thresholds defined by the Portuguese health authorities.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Experimental Studies / Observational study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: Math Biosci Eng Year: 2022 Document Type: Article Affiliation country: Mbe.2022043

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Epidemics / COVID-19 Type of study: Experimental Studies / Observational study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: Math Biosci Eng Year: 2022 Document Type: Article Affiliation country: Mbe.2022043