RESTORE: Realistic forecasting, control and preparedness for coming COVID-19 waves
My role: Co-investigator
Project period: 2020–2021
FWO COVID-19 Project · G0G2920N
Research summary
RESTORE brought together mathematical modelling, epidemiological data and interdisciplinary expertise to support Belgium’s response to the COVID-19 pandemic. The project aimed to anticipate future epidemic waves, assess the consequences of control measures and help healthcare institutions and policymakers prepare for changing hospital demand. It provided the starting point for a broader interuniversity collaboration involving research groups across Belgium.
A central component was the development and comparison of mathematical models describing SARS-CoV-2 transmission and its consequences for hospital admissions. These models used Belgian hospitalisation, mortality, serological and social-contact data, alongside information on settings such as nursing homes. Different modelling approaches captured complementary aspects of the epidemic. Combining their outputs in an ensemble allowed the consortium to examine how conclusions depended on model structure and assumptions.
As a co-investigator, I contributed to the mathematical modelling and collaborative scenario analyses. Our work included a stochastic compartmental model of the Belgian epidemic, described in Abrams et al. (2021), which formed one of the modelling approaches used in the RESTORE reports. Related collaborative research examined geographical transmission patterns, lockdown and exit strategies, and the potential effects of contact tracing and household bubbles.
The consortium produced successive reports exploring how changes in social mixing and intervention measures could affect future hospital admissions. As the epidemic evolved, the analyses incorporated vaccination and the emergence of the Alpha variant. These scenarios examined the interaction between vaccination progress and the timing of relaxation measures, highlighting the potential for renewed pressure on healthcare services if transmission increased before sufficient protection had accumulated.
The reports presented conditional projections under explicit assumptions, allowing alternative policy options to be compared while acknowledging uncertainty about future behaviour, vaccination and viral evolution. RESTORE connected methodological research with rapidly changing public-health questions and established a collaborative framework for comparing models and communicating epidemic scenarios.
Related publications
- Abrams et al. (2021) — Modelling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories. Epidemics, 35, 100449.
- Coletti et al. (2021) — A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies. BMC Infectious Diseases.
- Willem et al. (2021) — The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19. Nature Communications, 12, 1524.