Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal
In this paper, we present an age-structured SEIR model that uses contact patterns to reflect the physical distance measures implemented in Portugal to control the COVID-19 pandemic. By using these matrices and proper estimates for the parameters in the model, we were able to ascertain the impact of...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-05-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/9/10/1084 |
id |
doaj-b5101ba61cfc42ed922e37e9a9b776ec |
---|---|
record_format |
Article |
spelling |
doaj-b5101ba61cfc42ed922e37e9a9b776ec2021-05-31T23:45:17ZengMDPI AGMathematics2227-73902021-05-0191084108410.3390/math9101084Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in PortugalConstantino Caetano0Maria Luísa Morgado1Paula Patrício2João F. Pereira3Baltazar Nunes4Instituto Nacional de Saúde Doutor Ricardo Jorge, 1649-016 Lisbon, PortugalCenter for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, 1049-001 Lisbon, PortugalCenter for Mathematics and Applications (CMA), FCT NOVA and Department of Mathematics, FCT NOVA, Quinta da Torre, 2829-516 Caparica, PortugalDepartment of Mathematics, University of Trás-os-Montes e Alto Douro, UTAD, 5001-801 Vila Real, PortugalInstituto Nacional de Saúde Doutor Ricardo Jorge, 1649-016 Lisbon, PortugalIn this paper, we present an age-structured SEIR model that uses contact patterns to reflect the physical distance measures implemented in Portugal to control the COVID-19 pandemic. By using these matrices and proper estimates for the parameters in the model, we were able to ascertain the impact of mitigation strategies employed in the past. Results show that the March 2020 lockdown had an impact on disease transmission, bringing the effective reproduction number (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">R</mi><mo>(</mo><mi>t</mi><mo>)</mo></mrow></semantics></math></inline-formula>) below 1. We estimate that there was an increase in the transmission after the initial lift of the measures on 6 May 2020 that resulted in a second wave that was curbed by the October and November measures. December 2020 saw an increase in the transmission reaching an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">R</mi><mo>(</mo><mi>t</mi><mo>)</mo></mrow></semantics></math></inline-formula> = 1.45 in early January 2021. Simulations indicate that the lockdown imposed on the 15 January 2021 might reduce the intensive care unit (ICU) demand to below 200 cases in early April if it lasts at least 2 months. As it stands, the model was capable of projecting the number of individuals in each infection phase for each age group and moment in time.https://www.mdpi.com/2227-7390/9/10/1084epidemiological modelsSEIR type compartmental modelCOVID-19mathematical modellingcontact matrices |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Constantino Caetano Maria Luísa Morgado Paula Patrício João F. Pereira Baltazar Nunes |
spellingShingle |
Constantino Caetano Maria Luísa Morgado Paula Patrício João F. Pereira Baltazar Nunes Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal Mathematics epidemiological models SEIR type compartmental model COVID-19 mathematical modelling contact matrices |
author_facet |
Constantino Caetano Maria Luísa Morgado Paula Patrício João F. Pereira Baltazar Nunes |
author_sort |
Constantino Caetano |
title |
Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal |
title_short |
Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal |
title_full |
Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal |
title_fullStr |
Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal |
title_full_unstemmed |
Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal |
title_sort |
mathematical modelling of the impact of non-pharmacological strategies to control the covid-19 epidemic in portugal |
publisher |
MDPI AG |
series |
Mathematics |
issn |
2227-7390 |
publishDate |
2021-05-01 |
description |
In this paper, we present an age-structured SEIR model that uses contact patterns to reflect the physical distance measures implemented in Portugal to control the COVID-19 pandemic. By using these matrices and proper estimates for the parameters in the model, we were able to ascertain the impact of mitigation strategies employed in the past. Results show that the March 2020 lockdown had an impact on disease transmission, bringing the effective reproduction number (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">R</mi><mo>(</mo><mi>t</mi><mo>)</mo></mrow></semantics></math></inline-formula>) below 1. We estimate that there was an increase in the transmission after the initial lift of the measures on 6 May 2020 that resulted in a second wave that was curbed by the October and November measures. December 2020 saw an increase in the transmission reaching an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">R</mi><mo>(</mo><mi>t</mi><mo>)</mo></mrow></semantics></math></inline-formula> = 1.45 in early January 2021. Simulations indicate that the lockdown imposed on the 15 January 2021 might reduce the intensive care unit (ICU) demand to below 200 cases in early April if it lasts at least 2 months. As it stands, the model was capable of projecting the number of individuals in each infection phase for each age group and moment in time. |
topic |
epidemiological models SEIR type compartmental model COVID-19 mathematical modelling contact matrices |
url |
https://www.mdpi.com/2227-7390/9/10/1084 |
work_keys_str_mv |
AT constantinocaetano mathematicalmodellingoftheimpactofnonpharmacologicalstrategiestocontrolthecovid19epidemicinportugal AT marialuisamorgado mathematicalmodellingoftheimpactofnonpharmacologicalstrategiestocontrolthecovid19epidemicinportugal AT paulapatricio mathematicalmodellingoftheimpactofnonpharmacologicalstrategiestocontrolthecovid19epidemicinportugal AT joaofpereira mathematicalmodellingoftheimpactofnonpharmacologicalstrategiestocontrolthecovid19epidemicinportugal AT baltazarnunes mathematicalmodellingoftheimpactofnonpharmacologicalstrategiestocontrolthecovid19epidemicinportugal |
_version_ |
1721416760544985088 |