Search

Background: When formulating and evaluating COVID-19 vaccination strategies, an emphasis has been placed on preventing severe disease that overburdens healthcare systems and leads to mortality. However, more conventional outcomes such as quality-adjusted life years (QALYs) and inequality indicators are warranted as additional information for policymakers. Methods: We adopted a mathematical transmission model to describe the infectious disease dynamics of SARS-COV-2, including disease mortality and morbidity, and to evaluate (non)pharmaceutical interventions. Therefore, we considered temporal immunity levels, together with the distinct transmissibility of variants of concern (VOCs) and their corresponding vaccine effectiveness. We included both general and age-specific characteristics related to SARS-CoV-2 vaccination. Our scenario study is informed by data from Belgium, focusing on the period from August 2021 until February 2022, when vaccination for children aged 5-11 years was initially not yet licensed and first booster doses were administered to adults. More specifically, we investigated the potential impact of an earlier vaccination programme for children and increased or reduced historical adult booster dose uptake. Results: Through simulations, we demonstrate that increasing vaccine uptake in children aged 5-11 years in August–September 2021 could have led to reduced disease incidence and ICU occupancy, which was an essential indicator for implementing non-pharmaceutical interventions and maintaining healthcare system functionality. However, an enhanced booster dose regimen for adults from November 2021 onward could have resulted in more substantial cumulative QALY gains, particularly through the prevention of elevated levels of infection and disease incidence associated with the emergence of Omicron VOC. In both scenarios, the need for non-pharmaceutical interventions could have decreased, potentially boosting economic activity and mental well-being. Conclusions: When calculating the impact of measures to mitigate disease spread in terms of life years lost due to COVID-19 mortality, we highlight the impact of COVID-19 on the health-related quality of life of survivors. Our study underscores that disease-related morbidity could constitute a significant part of the overall health burden. Our quantitative findings depend on the specific setup of the interventions under review, which is open to debate or should be contextualised within future situations. [ABSTRACT FROM AUTHOR]

Background: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rapidly spread over the world and caused tremendous impacts on global health. Understanding the mechanism responsible for the spread of this pathogen and the impact of specific factors, such as human mobility, will help authorities to tailor interventions for future SARS-CoV-2 waves or newly emerging airborne infections. In this study, we aim to analyze the spatio-temporal transmission of SARS-CoV-2 in Belgium at municipality level between January and December 2021 and explore the effect of different levels of human travel on disease incidence through the use of counterfactual scenarios. Methods: We applied the endemic-epidemic modelling framework, in which the disease incidence decomposes into endemic, autoregressive and neighbourhood components. The spatial dependencies among areas are adjusted based on actual connectivity through mobile network data. We also took into account other important factors such as international mobility, vaccination coverage, population size and the stringency of restriction measures. Results: The results demonstrate the aggravating effect of international travel on the incidence, and simulated counterfactual scenarios further stress the alleviating impact of a reduction in national and international travel on epidemic growth. It is also clear that local transmission contributed the most during 2021, and municipalities with a larger population tended to attract a higher number of cases from neighboring areas. Conclusions: Although transmission between municipalities was observed, local transmission was dominant. We highlight the positive association between the mobility data and the infection spread over time. Our study provides insight to assist health authorities in decision-making, particularly when the disease is airborne and therefore likely influenced by human movement. [ABSTRACT FROM AUTHOR]

Superspreading events play an important role in the spread of several pathogens, such as SARS-CoV-2. While the basic reproduction number of the original Wuhan SARS-CoV-2 is estimated to be about 3 for Belgium, there is substantial inter-individual variation in the number of secondary cases each infected individual causes—with most infectious individuals generating no or only a few secondary cases, while about 20% of infectious individuals is responsible for 80% of new infections. Multiple factors contribute to the occurrence of superspreading events: heterogeneity in infectiousness, individual variations in susceptibility, differences in contact behavior, and the environment in which transmission takes place. While superspreading has been included in several infectious disease transmission models, research into the effects of different forms of superspreading on the spread of pathogens remains limited. To disentangle the effects of infectiousness-related heterogeneity on the one hand and contact-related heterogeneity on the other, we implemented both forms of superspreading in an individual-based model describing the transmission and spread of SARS-CoV-2 in a synthetic Belgian population. We considered its impact on viral spread as well as on epidemic resurgence after a period of social distancing. We found that the effects of superspreading driven by heterogeneity in infectiousness are different from the effects of superspreading driven by heterogeneity in contact behavior. On the one hand, a higher level of infectiousness-related heterogeneity results in a lower risk of an outbreak persisting following the introduction of one infected individual into the population. Outbreaks that did persist led to fewer total cases and were slower, with a lower peak which occurred at a later point in time, and a lower herd immunity threshold. Finally, the risk of resurgence of an outbreak following a period of lockdown decreased. On the other hand, when contact-related heterogeneity was high, this also led to fewer cases in total during persistent outbreaks, but caused outbreaks to be more explosive in regard to other aspects (such as higher peaks which occurred earlier, and a higher herd immunity threshold). Finally, the risk of resurgence of an outbreak following a period of lockdown increased. We found that these effects were conserved when testing combinations of infectiousness-related and contact-related heterogeneity. Author summary: To investigate the effect of different sources of superspreading on disease dynamics, we implemented superspreading driven by heterogeneity in infectiousness and heterogeneity in contact behavior into an individual-based model for the transmission of SARS-CoV-2 in the Belgian population. We compared the impact of both forms of superspreading in a scenario without interventions as well as in a scenario in which a period of strict social distancing (i.e. a lockdown) is followed by a period of partial release. We found that both forms of superspreading have very different effects. On the one hand, increasing the level of infectiousness-related heterogeneity led to less outbreaks being observed following the introduction of one infected individual in the population. Furthermore, final outbreak sizes decreased, and outbreaks became slower, with lower and later peaks, and a lower herd immunity threshold. Finally, the risk for resurgence of an outbreak following a period of lockdown also decreased. On the other hand, when contact-related heterogeneity was high, this also led to smaller final sizes, but caused outbreaks to be more explosive regarding other aspects (such as higher peaks that occurred earlier). The herd immunity threshold also increased, as did the risk of resurgence of outbreaks. [ABSTRACT FROM AUTHOR]

• Measles incidence peaks despite well-established vaccination and high vaccine uptake. • Closing immunity gaps is important to improve rapid responsiveness to outbreaks. • Investigation of age-specific humoral immunity levels using seroprevalence data. Vaccine-preventable diseases, such as measles, have been re-emerging in countries with moderate to high vaccine uptake. It is increasingly important to identify and close immunity gaps and increase coverage of routine childhood vaccinations, including two doses of the measles-mumps-rubella vaccine (MMR). Here, we present a simple cohort model relying on a Bayesian approach to evaluate the evolution of measles seroprevalence in Belgium using the three most recent cross-sectional serological survey data collections (2002, 2006 and 2013) and information regarding vaccine properties. We find measles seroprevalence profiles to be similar for the different regions in Belgium. These profiles exhibit a drop in seroprevalence in birth cohorts that were offered vaccination at suboptimal coverages in the first years after routine vaccination has been started up. This immunity gap is observed across all cross-sectional survey years, although it is more pronounced in survey year 2013. At present, the COVID-19 pandemic could negatively impact the immunization coverage worldwide, thereby increasing the need for additional immunization programs in groups of children that are impacted by this. Therefore, it is now even more important to identify existing immunity gaps and to sustain and reach vaccine-derived measles immunity goals. [ABSTRACT FROM AUTHOR]

Several important aspects related to SARS-CoV-2 transmission are not well known due to a lack of appropriate data. However, mathematical and computational tools can be used to extract part of this information from the available data, like some hidden age-related characteristics. In this paper, we present a method to investigate age-specific differences in transmission parameters related to susceptibility to and infectiousness upon contracting SARS-CoV-2 infection. More specifically, we use panel-based social contact data from diary-based surveys conducted in Belgium combined with the next generation principle to infer the relative incidence and we compare this to real-life incidence data. Comparing these two allows for the estimation of age-specific transmission parameters. Our analysis implies the susceptibility in children to be around half of the susceptibility in adults, and even lower for very young children (preschooler). However, the probability of adults and the elderly to contract the infection is decreasing throughout the vaccination campaign, thereby modifying the picture over time. Author summary: Basic transmission dynamic characteristics of SARS-CoV-2, such as the probability of acquiring infection when exposed ("susceptibility"), and the probability of transmitting infection when infected ("infectiousness") may be age-dependent. We present a computational method to estimate these age-specific characteristics using Belgian social contact and surveillance data. We found that children are less susceptible to infection than adults, with the former experiencing 20% to 50% of the susceptibility in adults, while the infectiousness is more difficult to discern. The force of infection (probability of acquiring infection per unit time) decreases over time for the oldest age groups first, following the roll-out of the vaccination campaign which targeted the elderly first. [ABSTRACT FROM AUTHOR]

Background: The burden of cardiovascular diseases (CVDs) greatly varies between and within countries. Low- and middle-income countries (LMICs) and vulnerable communities of high-income countries (HIC) share disproportionately higher burden. Evidence is limited on the level of CVD knowledge and risk perception in vulnerable communities. Hence, in this study, we assessed the level of CVD knowledge, risk perception and change intention towards physical activity and healthy diet among vulnerable communities in Antwerp, Belgium and Nottingham, England. Furthermore, we investigated the socioeconomic disparities particularly in the Antwerp setting.Method: A cross-sectional study was performed among 1,424 adults (958 in Antwerp and 466 in Nottingham) aged 18 or older among selected vulnerable communities. Districts or counties were selected based on socioeconomic and multiple deprivation index. A stratified random sampling was used in Antwerp, and purposive sampling in Nottingham. We determined the level of CVD knowledge, risk perception and intention towards a healthy lifestyle in Antwerp and Nottingham using a percentage score out of 100. To identify independent socioeconomic determinants in CVD knowledge, risk perception, intention to PA and healthy diet, we performed multilevel multivariable modeling using the Antwerp dataset.Results: The mean knowledge percent score was 75.4 in Antwerp and 69.4 in Nottingham, and only 36.5% and 21.1% of participants respectively, had good CVD knowledge (scored 80% or above). In the multivariable analysis using the Antwerp dataset, level of education was significantly associated with (1) CVD knowledge score (Adjusted β = 0.11, 95%CI: 0.03, 0.18), (2) risk perception (0.23, 95%CI: 0.04, 0.41), (3) intention to physical activity (PA) (0.51, 95%CI: 0.35, 0.66), and (4) healthy diet intention (0.54, 95%CI: 0.32, 0.75). Furthermore, those individuals with a higher household income had a better healthy diet intention (0.44, 95%CI: 0.23, 0.65). In contrast, those who were of non-European origin scored lower on intention to have a healthy diet (-1.34, 95%CI:-2.07, -0.62) as compared to their European counterparts. On average, intention to PA was significantly higher among males (-0.43, 95%CI:-0.82, -0.03), whereas females scored better on healthy diet intention (2.02, 95%CI: 1.46, 2.57).Conclusions: Knowledge towards CVD risks and prevention is low in vulnerable communities. Males have a higher intention towards PA while females towards a healthy diet and it also greatly varies across level of education. Moreover, those born outside Europe and with low household income have lower healthy diet intention than their respective counterparts. Hence, CVD preventive interventions should be participatory and based on a better understanding of the individuals' socioeconomic status and cultural beliefs through active individual and community engagement. [ABSTRACT FROM AUTHOR]

Introduction: The incidence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in the Belgian community is mainly estimated based on test results of patients with coronavirus disease (COVID-19)-like symptoms. The aim of this study was to investigate the evolution of the SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) positivity ratio and distribution of viral loads within a cohort of asymptomatic patients screened prior hospitalization or surgery, stratified by age category. Materials/Methods: We retrospectively studied data on SARS-CoV-2 real-time RT-PCR detection in respiratory tract samples of asymptomatic patients screened pre-hospitalization or pre-surgery in nine Belgian hospitals located in Flanders over a 12-month period (1 April 2020–31 March 2021). Results: In total, 255925 SARS-CoV-2 RT-PCR test results and 2421 positive results for which a viral load was reported, were included in this study. An unweighted overall SARS-CoV-2 real-time RT-PCR positivity ratio of 1.27% was observed with strong spatiotemporal differences. SARS-CoV-2 circulated predominantly in 80+ year old individuals across all time periods except between the first and second COVID-19 wave and in 20–30 year old individuals before the second COVID-19 wave. In contrast to the first wave, a significantly higher positivity ratio was observed for the 20–40 age group in addition to the 80+ age group compared to the other age groups during the second wave. The median viral load follows a similar temporal evolution as the positivity rate with an increase ahead of the second wave and highest viral loads observed for 80+ year old individuals. Conclusion: There was a high SARS-CoV-2 circulation among asymptomatic patients with a predominance and highest viral loads observed in the elderly. Moreover, ahead of the second COVID-19 wave an increase in median viral load was noted with the highest overall positivity ratio observed in 20–30 year old individuals, indicating they could have been the hidden drivers of this wave. [ABSTRACT FROM AUTHOR]

Background: In 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.Methods: We 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.Results: Our 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.Conclusions: Contacts 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. [ABSTRACT FROM AUTHOR]

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. The COVID-19 pandemic caused many governments to impose policies restricting social interactions. Here, the authors implement an age-specific, individual-based model with data on social contacts for the Belgian population and investigate the effect of non-pharmaceutical interventions. [ABSTRACT FROM AUTHOR]

Despite advances in the healthcare system, cardiovascular diseases (CVDs) are still an important public health problem with disparities in the burden within and between countries. Studies among the adult population documented that socioeconomic and environmental factors play a role in the incidence and progression of CVDs. However, evidence is scarce on the socioeconomic determinants and the interplay with behavioral risks among older adults. Therefore, we identified socioeconomic and behavioral determinants of CVDs among older adults. Our sample consisted of 14,322 people aged 50 years and above from Belgium and France who responded to the waves 4, 5, 6 and/or 7 of the Survey of Health Ageing and Retirement in Europe. The effect of determinants on the occurrence of CVD was examined using a Generalized Estimating Equation (GEE) approach for binary longitudinal data. The overall rate of heart attack was 8.3%, which is 7.6% in Belgium and 9.1% in France. Whereas, 2.6% and 2.3% in Belgium and France, respectively, had experienced stroke. In the multivariable GEE model, older age [AOR: 1.057, 95%CI: 1.055–1.060], living in large cities [AOR: 1.14, 95%CI: 1.07–1.18], and retirement [AOR: 1.21, 95%CI: 1.16–1.31] were associated with higher risk of CVD. Furthermore, higher level of education [AOR: 0.82, 95%CI: 0.79–0.90], upper wealth quantile [AOR: 0.82, 95%CI: 0.76–0.86] and having social support [AOR: 0.81, 95%CI: 0.77–0.84] significantly lowers the odds of having CVD. A higher hand grip strength was also significantly associated with lower risk of CVD [AOR: 0.987, 95%CI: 0.984–0.990]. This study demonstrated that older adults who do not have social support, live in big cities, belong to the lowest wealth quantile, and have a low level of education have a higher likelihood of CVD. Therefore, community-based interventions aimed at reducing cardiovascular risks need to give more emphasis to high-risk retired older adults with lower education, no social support and those who live in large cities. [ABSTRACT FROM AUTHOR]

Objectives: To investigate whether prior exposure to non-fluoroquinolone antibiotics increases the risk of fluoroquinolone resistance in Escherichia coli.Methods: This was a secondary analysis of data collected retrospectively in a case-control study linking microbiological test results (isolated bacteria and their susceptibility) of urine samples routinely collected from primary, secondary and tertiary care patients in Belgium with information on prior antibiotic use at the patient level up to 1 year previously.Results: In urine samples from 6125 patients, 7204 E. coli isolates were retrieved [1949 fluoroquinolone-resistant isolates (cases) and 5255 fluoroquinolone-susceptible isolates (controls)]. After adjusting for potential confounders (including fluoroquinolone use) and correcting for multiple testing there were lower odds of fluoroquinolone resistance in E. coli isolates after exposure to cefazolin (OR = 0.65; 95% CI = 0.52-0.81; P = 0.00014) and higher odds after exposure to trimethoprim/sulfamethoxazole (OR = 1.56; 95% CI = 1.23-1.97; P =0.00020) or nitrofurantoin (OR = 1.50; 95% CI = 1.23-1.84; P =0.000083). A sensitivity analysis excluding samples with antibiotic use during the 6 months prior to the sampling date confirmed the higher odds of fluoroquinolone resistance after exposure to trimethoprim/sulfamethoxazole and nitrofurantoin.Conclusions: Assuming no residual confounding or other biases, this study suggests that exposure to non-fluoroquinolone antibiotics, i.e. trimethoprim/sulfamethoxazole and nitrofurantoin, might be causally related to fluoroquinolone resistance in E. coli isolates from urinary samples. Future prospective research is needed to confirm non-fluoroquinolone antibiotics as potential drivers of fluoroquinolone resistance. [ABSTRACT FROM AUTHOR]

Frailty models have been developed to quantify both heterogeneity as well as association in multivariate time-to-event data. In recent years, numerous shared and correlated frailty models have been proposed in the survival literature allowing for different association structures and frailty distributions. A bivariate correlated gamma frailty model with an additive decomposition of the frailty variables into a sum of independent gamma components was introduced before. Although this model has a very convenient closed-form representation for the bivariate survival function, the correlation among event- or subject-specific frailties is bounded above which becomes a severe limitation when the values of the two frailty variances differ substantially. In this article, we review existing correlated gamma frailty models and propose novel ones based on bivariate gamma frailty distributions. Such models are found to be useful for the analysis of bivariate survival time data regardless of the censoring type involved. The frailty methodology was applied to right-censored and left-truncated Danish twins mortality data and serological survey current status data on varicella zoster virus and parvovirus B19 infections in Belgium. From our analyses, it has been shown that fitting more flexible correlated gamma frailty models in terms of the imposed association and correlation structure outperforms existing frailty models including the one with an additive decomposition. [ABSTRACT FROM AUTHOR]

Rubella is usually a mild disease for which infections often pass by unnoticed. In approximately 50% of the cases, there are no or only few clinical symptoms. However, rubella contracted during early pregnancy could lead to spontaneous abortion, to central nervous system defects, or to one of a range of other serious and debilitating conditions in a newborn such as the congenital rubella syndrome. Before the introduction of mass vaccination, rubella was a common childhood infection occurring all over the world. However, since the introduction of rubella antigen-containing vaccines, the incidence of rubella has declined dramatically in high-income countries. Recent large-scale mumps outbreaks, one of the components in the combined measles-mumps-rubella vaccine, occurring in countries throughout Europe with high vaccination coverage, provide evidence of pathogen-specific waning of vaccine-induced immunity and primary vaccine failure. In addition, recent measles outbreaks affecting populations with suboptimal vaccination coverages stress the importance of maintaining high vaccination coverages. In this paper, we focus on the assessment of rubella outbreak risk using a previously developed method to identify geographic regions of high outbreak potential. The methodology relies on 2006 rubella seroprevalence data and vaccination coverage data from Belgium and information on primary and secondary vaccine failure obtained from extensive literature reviews. We estimated the rubella outbreak risk in Belgium to be low, however maintaining high levels of immunisation and surveillance are of utmost importance to avoid future outbreaks. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Background: Our work was motivated by the need to, given serum availability and/or financial resources, decide on which samples to test in a serum bank for different pathogens. Simulation-based sample size calculations were performed to determine the age-based sampling structures and optimal allocation of a given number of samples for testing across various age groups best suited to estimate key epidemiological parameters (e.g., seroprevalence or force of infection) with acceptable precision levels in a cross-sectional seroprevalence survey.Methods: Statistical and mathematical models and three age-based sampling structures (survey-based structure, population-based structure, uniform structure) were used. Our calculations are based on Belgian serological survey data collected in 2001-2003 where testing was done, amongst others, for the presence of Immunoglobulin G antibodies against measles, mumps, and rubella, for which a national mass immunisation programme was introduced in 1985 in Belgium, and against varicella-zoster virus and parvovirus B19 for which the endemic equilibrium assumption is tenable in Belgium.Results: The optimal age-based sampling structure to use in the sampling of a serological survey as well as the optimal allocation distribution varied depending on the epidemiological parameter of interest for a given infection and between infections.Conclusions: When estimating epidemiological parameters with acceptable levels of precision within the context of a single cross-sectional serological survey, attention should be given to the age-based sampling structure. Simulation-based sample size calculations in combination with mathematical modelling can be utilised for choosing the optimal allocation of a given number of samples over various age groups. [ABSTRACT FROM AUTHOR]

Age-related heterogeneity in a host population, whether due to how individuals mix and contact each other, the nature of host–pathogen interactions defining epidemiological parameters, or demographics, is crucial in studying infectious disease dynamics. Compartmental models represent a popular approach to address the problem, dividing the population of interest into a discrete and finite number of states depending on, for example, individuals' age and stage of infection. We study the corresponding linearised system whose operator, in the context of a discrete-time model, equates to a square matrix known as the next generation matrix. Performing formal perturbation analysis of the entries of the aforementioned matrix, we derive indices to quantify the age-specific variation of its dominant eigenvalue (i.e., the reproduction number) and explore the relevant epidemiological information we can derive from the eigenstructure of the matrix. The resulting method enables the assessment of the impact of age-related population heterogeneity on virus transmission. In particular, starting from an age-structured SEIR model, we demonstrate the use of this approach for COVID-19 dynamics in Belgium. We analyse the early stages of the SARS-CoV-2 spread, with particular attention to the pre-pandemic framework and the lockdown lifting phase initiated as of May 2020. Our results, influenced by our assumption on age-specific susceptibility and infectiousness, support the hypothesis that transmission was only influenced to a small extent by children in the age group [ 0 , 18) and adults over 60 years of age during the early phases of the pandemic and up to the end of July 2020. • Sensitivity analysis to assess age-structure on SARS-CoV-2 transmission in Belgium. • We developed age-specific indices quantifying the impact on the reproduction number. • We found the under-18 and over-60 age groups to play a marginal role in transmission. • The analysis spots the importance of asymptomatic infections for COVID-19. • The developed methodology can assist in containment policy design. [ABSTRACT FROM AUTHOR]

Background: Collaborative comparisons and combinations of epidemic models are used as policy-relevant evidence during epidemic outbreaks. In the process of collecting multiple model projections, such collaborations may gain or lose relevant information. Typically, modellers contribute a probabilistic summary at each time-step. We compared this to directly collecting simulated trajectories. We aimed to explore information on key epidemic quantities; ensemble uncertainty; and performance against data, investigating potential to continuously gain information from a single cross-sectional collection of model results., Methods: We compared projections from the European COVID-19 Scenario Modelling Hub. Five teams modelled incidence in Belgium, the Netherlands, and Spain. We compared July 2022 projections by incidence, peaks, and cumulative totals. We created a probabilistic ensemble drawn from all trajectories, and compared to ensembles from a median across each model's quantiles, or a linear opinion pool. We measured the predictive accuracy of individual trajectories against observations, using this in a weighted ensemble. We repeated this sequentially against increasing weeks of observed data. We evaluated these ensembles to reflect performance with varying observed data., Results: By collecting modelled trajectories, we showed policy-relevant epidemic characteristics. Trajectories contained a right-skewed distribution well represented by an ensemble of trajectories or a linear opinion pool, but not models' quantile intervals. Ensembles weighted by performance typically retained the range of plausible incidence over time, and in some cases narrowed this by excluding some epidemic shapes., Conclusions: We observed several information gains from collecting modelled trajectories rather than quantile distributions, including potential for continuously updated information from a single model collection. The value of information gains and losses may vary with each collaborative effort's aims, depending on the needs of projection users. Understanding the differing information potential of methods to collect model projections can support the accuracy, sustainability, and communication of collaborative infectious disease modelling efforts., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Burden of disease estimates have become important population health metrics over the past decade to measure losses in health. In Belgium, the disease burden caused by COVID-19 has not yet been estimated, although COVID-19 has emerged as one of the most important diseases. Therefore, the current study aims to estimate the direct COVID-19 burden in Belgium, observed despite policy interventions, during 2020 and 2021, and compare it to the burden from other causes., Methods: Disability-adjusted life years (DALYs) are the sum of Years Lived with Disability (YLDs) and Years of Life Lost (YLLs) due to disease. DALYs allow comparing the burden of disease between countries, diseases, and over time. We used the European Burden of Disease Network consensus disease model for COVID-19 to estimate DALYs related to COVID-19. Estimates of person-years for (a) acute non-fatal disease states were calculated from a compartmental model, using Belgian seroprevalence, social contact, hospital, and intensive care admission data, (b) deaths were sourced from the national COVID-19 mortality surveillance, and (c) chronic post-acute disease states were derived from a Belgian cohort study., Results: In 2020, the total number of COVID-19 related DALYs was estimated at 253,577 [252,541 - 254,739], which is higher than in 2021, when it was 139,281 [136,704 - 142,306]. The observed COVID-19 burden was largely borne by the elderly, and over 90% of the burden was attributable to premature mortality (i.e., YLLs). In younger people, morbidity (i.e., YLD) contributed relatively more to the DALYs, especially in 2021, when vaccination was rolled out. Morbidity was mainly attributable to long-lasting post-acute symptoms., Conclusion: COVID-19 had a substantial impact on population health in Belgium, especially in 2020, when COVID-19 would have been the main cause of disease burden if all other causes had maintained their 2019 level., (© 2023. BioMed Central Ltd., part of Springer Nature.)

BackgroundTo control epidemic waves, it is important to know the susceptibility to SARS-CoV-2 and its evolution over time in relation to the control measures taken.AimTo assess the evolving SARS-CoV-2 seroprevalence and seroincidence related to the first national lockdown in Belgium, we performed a nationwide seroprevalence study, stratified by age, sex and region using 3,000-4,000 residual samples during seven periods between 30 March and 17 October 2020.MethodsWe analysed residual sera from ambulatory patients for IgG antibodies against the SARS-CoV-2 S1 protein with a semiquantitative commercial ELISA. Weighted seroprevalence (overall and by age category and sex) and seroincidence during seven consecutive periods were estimated for the Belgian population while accommodating test-specific sensitivity and specificity.ResultsThe weighted overall seroprevalence initially increased from 1.8% (95% credible interval (CrI): 1.0-2.6) to 5.3% (95% CrI: 4.2-6.4), implying a seroincidence of 3.4% (95% CrI: 2.4-4.6) between the first and second collection period over a period of 3 weeks during lockdown (start lockdown mid-March 2020). Thereafter, seroprevalence stabilised, however, significant decreases were observed when comparing the third with the fifth, sixth and seventh period, resulting in negative seroincidence estimates after lockdown was lifted. We estimated for the last collection period mid-October 2020 a weighted overall seroprevalence of 4.2% (95% CrI: 3.1-5.2).ConclusionDuring lockdown, an initially small but increasing fraction of the Belgian population showed serologically detectable signs of exposure to SARS-CoV-2, which did not further increase when confinement measures eased and full lockdown was lifted.

BackgroundCOVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.AimWe examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.MethodsThe relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.ResultsIn the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.DiscussionDuring the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.

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., (Copyright © 2021. Published by Elsevier B.V.)

Valid and reliable measurement of an individual's knowledge and risk perception is pivotal to monitor and evaluate the effectiveness of interventions aimed at preventing cardiovascular diseases (CVDs). The recently developed Attitudes and Beliefs about Cardiovascular Disease (ABCD) knowledge and risk questionnaire is shown to be valid in England. In this study, we evaluated the psychometric properties of the modified and Dutch (Flemish)-translated ABCD questionnaire using both the classical test and item response theory (IRT) analysis. We conducted a community-based survey among 525 adults in Antwerp city, Belgium. We assessed the item- and scale-level psychometric properties and validity indices of the questionnaire. Parameters of IRT, item scalability, monotonicity, item difficulty and discrimination, and item fit statistics were evaluated. Furthermore, exploratory and confirmatory factorial validity, and internal consistency measures were explored. Descriptive statistics showed that both the knowledge and risk scale items have sufficient variation to differentiate individuals' level of knowledge and risk perception. The overall homogeneity of the knowledge and risk subscales was within the acceptable range (> 0.3). The exploratory and confirmatory factor analyses of the risk scale supported a three-factor solution corresponding to risk perception (F1), perceived benefits and intention to change physical activity (F2), and perceived benefit and intention to change healthy dietary habit (F3). The two parametric logistic (2-PL) and rating scale models showed that the item infit and outfit values for knowledge and risk subscales were within the acceptable range (0.6 to 1.4) for most of the items. In conclusion, this study investigated the Dutch (Flemish) version of the ABCD questionnaire has good psychometric properties to assess CVD related knowledge and risk perception in the adult population. Based on the factor loadings and other psychometric properties, we suggested a shorter version, which has comparable psychometric properties.

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.

Objectives: To investigate whether prior exposure to non-fluoroquinolone antibiotics increases the risk of fluoroquinolone resistance in Escherichia coli., Methods: This was a secondary analysis of data collected retrospectively in a case-control study linking microbiological test results (isolated bacteria and their susceptibility) of urine samples routinely collected from primary, secondary and tertiary care patients in Belgium with information on prior antibiotic use at the patient level up to 1 year previously., Results: In urine samples from 6125 patients, 7204 E. coli isolates were retrieved [1949 fluoroquinolone-resistant isolates (cases) and 5255 fluoroquinolone-susceptible isolates (controls)]. After adjusting for potential confounders (including fluoroquinolone use) and correcting for multiple testing there were lower odds of fluoroquinolone resistance in E. coli isolates after exposure to cefazolin (OR = 0.65; 95% CI = 0.52-0.81; P = 0.00014) and higher odds after exposure to trimethoprim/sulfamethoxazole (OR = 1.56; 95% CI = 1.23-1.97; P =0.00020) or nitrofurantoin (OR = 1.50; 95% CI = 1.23-1.84; P =0.000083). A sensitivity analysis excluding samples with antibiotic use during the 6 months prior to the sampling date confirmed the higher odds of fluoroquinolone resistance after exposure to trimethoprim/sulfamethoxazole and nitrofurantoin., Conclusions: Assuming no residual confounding or other biases, this study suggests that exposure to non-fluoroquinolone antibiotics, i.e. trimethoprim/sulfamethoxazole and nitrofurantoin, might be causally related to fluoroquinolone resistance in E. coli isolates from urinary samples. Future prospective research is needed to confirm non-fluoroquinolone antibiotics as potential drivers of fluoroquinolone resistance., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.)