There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. We investigate the time from symptom onset to diagnosis and hospitalization or the length of stay (LoS) in the hospital, and whether there are differences in the population. Sciensano collected information on 14,618 hospitalized patients with COVID-19 admissions from 114 Belgian hospitals between 14 March and 12 June 2020. The distributions of different event times for different patient groups are estimated accounting for interval censoring and right truncation of the time intervals. The time between symptom onset and hospitalization or diagnosis are similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient (longest delay in age group 20–60 years) and whether or not the patient lives in a nursing home (additional 2 days for patients from nursing home). The median LoS in hospital varies between 3 and 10.4 days, with the LoS increasing with age. The hospital LoS for patients that recover is shorter for patients living in a nursing home, but the time to death is longer for these patients. Over the course of the first wave, the LoS has decreased.

Background In the first weeks of the COVID-19 epidemic in Belgium, a repetitive national serum collection was set up to monitor age-related exposure through emerging SARS-CoV-2 antibodies. First objective was to estimate the baseline seroprevalence and seroincidence using serial survey data that covered the start of a national lock-down period installed soon after the epidemic was recognized. Methods A prospective serial cross-sectional seroprevalence study, stratified by age, sex and region, started with two collections in April 2020. In residual sera taken outside hospitals and collected by diagnostic laboratories, IgG antibodies against S1 proteins of SARS-CoV-2 were measured with a semi-quantitative commercial ELISA. Seropositivity (cumulative, by age category and sex) and seroincidence over a 3 weeks period were estimated for the Belgian population. Findings In the first collection, IgG antibodies were detected in 100 out of 3910 samples, whereas in the second collection 193 out of 3391 samples were IgG positive. The weighted overall seroprevalence increased from 2.9% (95% CI 2.3 to 3.6) to 6.0% (95% CI 5.1 to 7.1), reflected in a seroincidence estimate of 3.1% (95% CI 1.9 to 4.3). Age-specific seroprevalence significantly increased in the age categories 20-30, 80-90 and ≥90. No significant sex effect was observed. Interpretation During the start of epidemic mitigation by lockdown, a small but increasing fraction of the Belgian population showed serologically detectable signs of exposure to SARS-CoV-2. Funding This independent researcher-initiated study acknowledges financial support from the Antwerp University Fund, the Flemish Research Fund, and European Horizon 2020.

The COVID-19 pandemic caused many governments to impose policies restricting social interactions. A controlled and persistent release of lockdown measures covers many potential strategies and is subject to extensive scenario analyses. Here, we use an individual-based model (STRIDE) to simulate interactions between 11 million inhabitants of Belgium at different levels including extended household settings, i.e., “household bubbles”. The burden of COVID-19 is impacted by both the intensity and frequency of physical contacts, and therefore, household bubbles have the potential to reduce hospital admissions by 90%. In addition, we find that it is crucial to complete contact tracing 4 days after symptom onset. Assumptions on the susceptibility of children affect the impact of school reopening, though we find that business and leisure-related social mixing patterns have more impact on COVID-19 associated disease burden. An optimal deployment of the mitigation policies under study require timely compliance to physical distancing, testing and self-isolation.

Background. The rising COVID-19 pandemic caused many governments to impose policies restricting social interactions. These policies have slowed down the spread of the SARS-CoV-2 virus to the extent that restric- tions can be gradually lifted. Models can be useful to assess the consequences of deconfinement strategies with respect to business, school and leisure activities. Methods. We adapted the individual-based model "STRIDE" to simulate interactions between the 11 million inhabitants of Belgium at the levels of households, workplaces, schools and communities. We calibrated our model to observed hospital incidence and seroprevalence data. STRIDE can explore contact tracing options and account for repetitive leisure contacts in extended household settings (so called "household bubbles") with varying levels of connectivity. Findings. Household bubbles have the potential to reduce the number of COVID-19 hospital admissions by up to 90%. The effectiveness of contact tracing depends on its timing, as it becomes futile more than 4 days after the index case developed symptoms. Assuming that children have a lower level of susceptibility and lower probability to experience symptomatic SARS-CoV-2 infection, (partial) school closure options have relatively little impact on COVID-19 burden. Interpretation. Not only the absolute number and intensity of physical contacts drive the transmission dynamics and COVID-19 burden, also their repetitiveness is influential. Contact tracing seems essential for a controlled and persistent release of lockdown measures, but requires timely compliance to testing, reporting and self-isolation. Rapid tracing and testing, and communication ensuring continued involvement of the population are therefore essential.

Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.

Mumps is a potentially severe viral infection. The incidence of mumps has declined dramatically in high-income countries since the introduction of mumps antigen-containing vaccines. However, recent large outbreaks of mumps in highly vaccinated populations suggest waning of vaccine-induced immunity and primary vaccine failure. In this paper we present a simple method for identifying geographic regions with high outbreak potential, demonstrated using 2006 mumps seroprevalence data from Belgium and Belgian vaccination coverage data. Predictions of the outbreak potential in terms of the effective reproduction number in future years signal an increased risk of new mumps outbreaks. Literature reviews on serological information for both primary vaccine failure and waning immunity provide essential information for our predictions. Tailor-made additional vaccination campaigns would be valuable for decreasing local pockets of susceptibility, thereby reducing the risk of future large-scale mumps outbreaks.

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BackgroundLarge measles and mumps outbreaks recently occurred throughout Europe and the United States. Aim: Our aim was to estimate and map the risk of resurgence for measles, mumps and rubella in France. Methods: We used a multi-cohort model combining seroprevalence information, vaccine coverage and social contact data. Results: The overall outbreak risk for France in 2018 was highest for mumps, remained significant for measles despite a recent measles outbreak and was low for rubella. Outbreak risks were heterogeneous between departments, as the effective reproduction numbers for 2018 ranged from 1.08 to 3.66. The seroprevalence, and therefore the risk of measles and rubella infection, differed significantly between males and females. There was a lower seroprevalence, and therefore a higher risk, for males. Infants of less than 1 year would be seriously affected in a future outbreak of measles, mumps or rubella, but the highest overall caseload contribution would come from teenagers and young adults (10–25 years old). Conclusions: The high risk for teenagers and young adults is of concern in view of their vulnerability to more severe measles, mumps and rubella disease and complications.