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Assessing the impact of forced and voluntary behavioral changes on economic-epidemiological co-dynamics: A comparative case study between Belgium and Sweden during the 2020 COVID-19 pandemic

Tijs W. Alleman, Jan M. Baetens

TL;DR

This paper tackles how forced and voluntary behavioral changes shape economic-epidemiological co-dynamics during the COVID-19 pandemic. It introduces the epinomic co-simulation, which fuses a spatial, age-structured disease model with a dynamic production network and a collective-memory based voluntary-behavior feedback, calibrated to Belgium and Sweden with a single parameter set. The study demonstrates that early, partly voluntary responses can limit healthcare stress with lower economic damage, while delayed or overly prolonged lockdowns may backfire economically and epidemiologically; memory effects can induce oscillatory epidemic patterns, and spatial seeding alters the trade-offs between health outcomes and economic activity. These insights offer a practical, open-source tool for policymakers to design long-term strategies that minimize economic damage while maintaining healthcare capacity, though the model currently abstracts certain factors (vaccination, VOCs) and focuses on two countries. The work provides a rigorous counterfactual framework and highlights the importance of geography, timing, and the nature of behavioral changes in managing pandemics.

Abstract

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.

Assessing the impact of forced and voluntary behavioral changes on economic-epidemiological co-dynamics: A comparative case study between Belgium and Sweden during the 2020 COVID-19 pandemic

TL;DR

This paper tackles how forced and voluntary behavioral changes shape economic-epidemiological co-dynamics during the COVID-19 pandemic. It introduces the epinomic co-simulation, which fuses a spatial, age-structured disease model with a dynamic production network and a collective-memory based voluntary-behavior feedback, calibrated to Belgium and Sweden with a single parameter set. The study demonstrates that early, partly voluntary responses can limit healthcare stress with lower economic damage, while delayed or overly prolonged lockdowns may backfire economically and epidemiologically; memory effects can induce oscillatory epidemic patterns, and spatial seeding alters the trade-offs between health outcomes and economic activity. These insights offer a practical, open-source tool for policymakers to design long-term strategies that minimize economic damage while maintaining healthcare capacity, though the model currently abstracts certain factors (vaccination, VOCs) and focuses on two countries. The work provides a rigorous counterfactual framework and highlights the importance of geography, timing, and the nature of behavioral changes in managing pandemics.

Abstract

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.
Paper Structure (27 sections, 49 equations, 32 figures, 22 tables)

This paper contains 27 sections, 49 equations, 32 figures, 22 tables.

Table of Contents

  1. Methods
  2. Epinomic model
  3. Scenarios
  4. Results and discussion
  5. Conclusions
  6. Demography, mobility, and employment in Belgium and Sweden
  7. NACE Rev. 2 classification
  8. Social contact data
  9. Detailed model description
  10. Overview
  11. Collective memory feedback model
  12. Disease transmission model
  13. Production network model
  14. Introduction
  15. Model overview and parameters
  16. ...and 12 more sections

Figures (32)

  • Figure 1: Schematic representation of the epinomic model.
  • Figure 2: Time course (b) and phase trajectory (c) of voluntary behavioral changes in response to a hypothetical surge of the hospital load (a).
  • Figure 3: (top row) Daily new covid-19 hospitalizations per 100000.0 inhabitants in Belgium and Sweden. (bottom row) Percentage of gross aggregated output and labor compensation retained during the pandemic, as compared to the first quarter of 2020. The horizontal arrows denote the periods with severe social restrictions (lockdown), along with their subsequent release in Belgium.
  • Figure 4: Simulated IC load per 100000.0 inhabitants and percentage labor income as compared to before the covid-19 pandemic, for Belgium. Policies range a strict lockdown as implemented in Belgium (P1) to voluntary recommendations as implemented in Sweden (P4b) (Table \ref{['tab:scenarios_policies_BE']}).
  • Figure 5: Simulated IC load in Belgium and Sweden during one year. Both governments impose a lockdown to counter the initial epidemic. The lockdown is then maintained for 2 (blue), 3 (green), 4 (orange) and 5 months (black). We use grey background shading to indicate the period of government intervention, though the shade does not refer to lockdown strictness. After releasing the lockdown, no measures are in place.
  • ...and 27 more figures