Publication
Title
A data-driven metapopulation model for the Belgian COVID-19 epidemic : assessing the impact of lockdown and exit strategies
Author
Abstract
Background In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks. Methods We analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown. Results Our model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period. Conclusions Contacts during leisure activities are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment of social contacts in the population is therefore crucial to adjust to evolving behavioral changes that can affect epidemic diffusion.
Language
English
Source (journal)
BMC infectious diseases. - London
Publication
London : 2021
ISSN
1471-2334
DOI
10.1186/S12879-021-06092-W
Volume/pages
21 :1 (2021) , 12 p.
Article Reference
503
ISI
000656075700001
Pubmed ID
34053446
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Translational and Transdisciplinary research in Modeling Infectious Diseases (TransMID).
Epidemic intelligence to minimize 2019-nCoV's public health, economic and social impact in Europe (EpiPose).
Realistic forecasting, control and preparedness for coming COVID-19 waves (RESTORE).
The stride towards health economic evaluation with individual-based models integrating transmission dynamics, stochasticity and uncertainty.
CalcUA as central calculation facility: supporting core facilities.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 28.06.2021
Last edited 21.11.2024
To cite this reference