Abstract
BackgroundIn 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.MethodsWe 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.ResultsOur 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.ConclusionsContacts 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.
Highlights
In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree
We present a scenario analysis of possible re-opening strategies easing lockdown measures based on a data-driven metapopulation model for Belgium for COVID-19 [11]
We assume that case isolation affects both symptomatic and asymptomatic individuals and we present our results in terms of a synthetic quantity, the parameter α, that is the percentage of individuals entering the symptomatic/asymptomatic class (Ia, Ims and Iss) that are effectively isolated
Summary
In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. After imposing a lockdown on March 14th [8] , the Belgian government curtailed some of these measures with a plan for a gradual reopening over several weeks, starting from the 4th of May. The absence of substantial population immunity after this first wave of COVID-19 in Belgium [9] increases the risk of subsequent large-scale outbreaks when interventions are relaxed which could result, when not contained, in new COVID-19 waves with large numbers of new confirmed cases and hospitalized persons. The absence of substantial population immunity after this first wave of COVID-19 in Belgium [9] increases the risk of subsequent large-scale outbreaks when interventions are relaxed which could result, when not contained, in new COVID-19 waves with large numbers of new confirmed cases and hospitalized persons In this context, data-driven models of disease spread can provide useful insights into the expected impact of easing nonpharmaceutical interventions [2, 6, 10]. We aim to identify which intervention strategies have the largest potential impact on disease spread, based on the scarce data available during the early stage of the pandemic
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