Mathematical Modelling of the Impact of Non-Pharmacological Strategies to Control the COVID-19 Epidemic in Portugal
| Autor: | Baltazar Nunes, Maria Luísa Morgado, Paula Patrício, Constantino P. Caetano, João F. Pereira |
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| Přispěvatelé: | DM - Departamento de Matemática, CMA - Centro de Matemática e Aplicações, Comprehensive Health Research Centre (CHRC) - Pólo ENSP, Centro de Investigação em Saúde Pública (CISP/PHRC), Escola Nacional de Saúde Pública (ENSP) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Infecções Respiratórias
2019-20 coronavirus outbreak Coronavirus disease 2019 (COVID-19) General Mathematics Investigação em Políticas de Saúde Control (management) contact matrices Epidemic models law.invention 03 medical and health sciences 0302 clinical medicine law Mathematical Modelling Pandemic Computer Science (miscellaneous) QA1-939 030212 general & internal medicine mathematical modelling Engineering (miscellaneous) Non pharmacological SEIR type compartmental model 030304 developmental biology 0303 health sciences Portugal Lift (data mining) epidemiological models COVID-19 Transmission (mechanics) Geography Epidemiological Models Non-Pharmacological Strategies SEIR Type Compartmental Model Disease transmission Mathematics Demography |
| Zdroj: | Mathematics, Vol 9, Iss 1084, p 1084 (2021) Mathematics Volume 9 Issue 10 |
| ISSN: | 2227-7390 |
| Popis: | This article belongs to the Special Issue Mathematical Biology: Developments in Epidemic and Endemic Models 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 (R(t)) 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 R(t) = 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. The authors acknowledge financial support from the Fundação para a Ciência e Tecnologia—FCT through project 692 2ª edição Research 4 covid, project name Projeção do Impacte das medidas Não-farmacológicas de Controlo e mitigação da epidemia de COVID-19 em Tempo ReaL (COVID-19 in-CTRL). The first author also acknowledges FCT within the PhD grants “DOCTORATES 4 COVID-19”, number 2020.10172.BD. The second author also acknowledges FCT within projects UIDB/04621/2020 and UIDP/04621/2020. The third author also acknowledges FCT within the Strategic Project UIDB/00297/2020 (Centro de Matemática e Aplicações, FCT NOVA). info:eu-repo/semantics/publishedVersion |
| Databáze: | OpenAIRE |
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