Tijs W. Alleman, Jan M. Baetens
arXiv 16 Jan 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2401.08442 · PDF · DOI · OpenAlex · Extracted main text
During the COVID-19 pandemic, governments faced the challenge of managing population behavior to prevent their healthcare systems from collapsing. Sweden adopted a strategy centered on voluntary sanitary recommendations while Belgium resorted to mandatory measures. Their consequences on pandemic progression and associated economic impacts remain insufficiently understood. This study leverages the divergent policies of Belgium and Sweden during the COVID-19 pandemic to relax the unrealistic -- but persistently used -- assumption that social contacts are not influenced by an epidemic's dynamics. We develop an epidemiological-economic co-simulation model where pandemic-induced behavioral changes are a superposition of voluntary actions driven by fear, prosocial behavior or social pressure, and compulsory compliance with government directives. Our findings emphasize the importance of early responses, which reduce the stringency of measures necessary to safeguard healthcare systems and minimize ensuing economic damage. Voluntary behavioral changes lead to a pattern of recurring epidemics, which should be regarded as the natural long-term course of pandemics. Governments should carefully consider prolonging lockdown longer than necessary because this leads to higher economic damage and a potentially higher second surge when measures are released. Our model can aid policymakers in the selection of an appropriate long-term strategy that minimizes economic damage.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Ludvigsson, J. F (2020) The first eight months of Sweden's COVID-19 strategy and the key actions and actors that were involved | 0.941 | 6 | 3 | 83% |
| 2 | Nigmatulina, K. R. & Larson, R. C (2009) Living with influenza: Impacts of government imposed and voluntarily selected interventions | 0.843 | 4 | 3 | 75% |
| 3 | Arthur, R. F., Jones, J. H., Bonds, M. H., Ram, Y. & Feldman, M. W (2021) Adaptive social contact rates induce complex dynamics during epidemics | 0.843 | 4 | 3 | 75% |
| 4 | Haw, D. J. et al (2022) Optimizing social and economic activity while containing sars-cov-2 transmission using daedalus | 0.843 | 5 | 3 | 60% |
| 5 | Luyten, J. & Schokkaert, E (2021) Belgium's response to the COVID-19 pandemic | 0.843 | 3 | 3 | 100% |
| 6 | Bavel, J. J. V. et al (2020) Using social and behavioural science to support COVID-19 pandemic response | 0.794 | 6 | 4 | 50% |
| 7 | Alleman, T. W., Stevens, C. V. & Baetens, J. M (2023) pySODM: Simulating and optimizing dynamical models in Python 3 self | 0.737 | 3 | 3 | 67% |
| 8 | Alleman, T. W., Rollier, M., Vergeynst, J. & Baetens, J. M (2023) A stochastic mobility-driven spatially explicit SEIQRD COVID-19 model with VOCs, seasonality, and vaccines self | 0.727 | 13 | 3 | 38% |
| 9 | Alleman, T. W. et al (2021) Assessing the effects of non-pharmaceutical interventions on sars-cov-2 transmission in Belgium by means of an extended SEIQRD m… self | 0.693 | 12 | 3 | 33% |
| 10 | Socialstyrelsen (2023) Weekly hospital incidence Sweden | 0.644 | 4 | 2 | 50% |
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