Social contact patterns following the COVID-19 pandemic: a snapshot of post-pandemic behaviour from the CoMix study.

The COVID-19 pandemic led to unprecedented changes in behaviour. To estimate if these persisted, a final round of the CoMix social contact survey was conducted in four countries at a time when all societal restrictions had been lifted for several months. We conducted a survey on a nationally representative sample in the UK, Netherlands (NL), Belgium (BE), and Switzerland (CH). Participants were asked about their contacts and behaviours on the previous day. We calculated contact matrices and compared the contact levels to a pre-pandemic baseline to estimate R0. Data collection occurred from 17 November to 7 December 2022. 7477 participants were recruited. Some were asked to undertake the survey on behalf of their children. Only 14.4 % of all participants reported wearing a facemask on the previous day. Self-reported vaccination rates in adults were similar for each country at around 86 %. Trimmed mean recorded contacts were highest in NL with 9.9 (95 % confidence interval [CI] 9.0-10.8) contacts per person per day and lowest in CH at 6.0 (95 % CI 5.4-6.6). Contacts at work were lowest in the UK (1.4 contacts per person per day) and highest in NL at 2.8 contacts per person per day. Other contacts were also lower in the UK at 1.6 per person per day (95 % CI 1.4-1.9) and highest in NL at 3.4 recorded per person per day (95 % CI 43.0-4.0). The next-generation approach suggests that R0 for a close-contact disease would be roughly half pre-pandemic levels in the UK, 80 % in NL and intermediate in the other two countries. The pandemic appears to have resulted in lasting changes in contact patterns expected to have an impact on the epidemiology of many different pathogens. Further post-pandemic surveys are necessary to confirm this finding.

Flexible Bayesian estimation of incubation times.

The incubation period is of paramount importance in infectious disease epidemiology as it informs about the transmission potential of a pathogenic organism and helps to plan public health strategies to keep an epidemic outbreak under control. Estimation of the incubation period distribution from reported exposure times and symptom onset times is challenging as the underlying data is coarse. We develop a new Bayesian methodology using Laplacian-P-splines that provides a semi-parametric estimation of the incubation density based on a Langevinized Gibbs sampler. A finite mixture density smoother informs a set of parametric distributions via moment matching and an information criterion arbitrates between competing candidates. Algorithms underlying our method find a natural nest within the EpiLPS package, which has been extended to cover estimation of incubation times. Various simulation scenarios accounting for different levels of data coarseness are considered with encouraging results. Applications to real data on COVID-19, MERS and Mpox reveal results that are in alignment with what has been obtained in recent studies. The proposed flexible approach is an interesting alternative to classic Bayesian parametric methods for estimation of the incubation distribution.

Addressing current limitations of household transmission studies by collecting contact data.

Modeling studies of household transmission data have helped characterize the role of children in influenza and COVID-19 epidemics. However, estimates from these studies may be biased since they do not account for the heterogeneous nature of household contacts. Here, we quantified the impact of contact heterogeneity between household members on the estimation of child relative susceptibility and infectivity. We simulated epidemics of SARS-CoV-2-like and influenza-like infections in a synthetic population of 1,000 households assuming heterogeneous contact levels. Relative contact frequencies were derived from a household contact study according to which contacts are more frequent in the father-mother pair, followed by the child-mother, child-child, and finally child-father pairs. Child susceptibility and infectivity were then estimated while accounting for heterogeneous contacts or not. When ignoring contact heterogeneity, child relative susceptibility was underestimated by approximately 20% in the two disease scenarios. Child relative infectivity was underestimated by 20% when children and adults had different infectivity levels. These results are sensitive to our assumptions of European-style household contact patterns; but they highlight that household studies collecting both disease and contact data are needed to assess the role of complex household contact behavior on disease transmission and improve estimation of key biological parameters.

Potential determinants of the decline in mpox cases in Belgium: a behavioral, epidemiological and seroprevalence study.

OBJECTIVE: The 2022 mpox epidemic reached a peak in Belgium and the rest of Europe in July 2022, after which it unexpectedly subsided. This study investigates epidemiological, behavioral, and immunological factors behind the waning of the epidemic in Belgium. METHODS: We investigated temporal evolutions in the characteristics and behavior of mpox patients using national surveillance data and data from a prospective registry of mpox patients in the Institute of Tropical Medicine (Antwerp). We studied behavioral changes in the population at risk using a survey among HIV-pre-exposure prophylaxis (PrEP) users. We determined the seroprevalence of anti-orthopoxvirus antibodies among HIV-PrEP users across four time points in 2022. RESULTS: Mpox patients diagnosed at the end of the epidemic had less sexual risk behavior compared to those diagnosed earlier: they engaged less in sex at mass events, had fewer sexual partners and were less likely to belong to the sexual network's central group. Among HIV-PrEP users there were no notable changes in sexual behavior. Anti-orthopoxvirus seroprevalence did not notably increase before the start of national vaccination campaigns. CONCLUSION: The observed changes in group immunity and behavior in the population at greater risk of exposure to mpox seem unable to explain the waning of the mpox epidemic. A change in the profile of mpox patients might have contributed to the decline in cases.

Estimating Partnership Duration among MSM in Belgium-A Modeling Study.

Mathematical modeling is widely used for describing infection transmission and evaluating interventions. The lack of reliable social parameters in the literature has been mentioned by many modeling studies, leading to limitations in the validity and interpretation of the results. Using data from the European MSM Internet survey 2017, we developed a network model to describe sex acts among MSM in Belgium. The model simulates daily sex acts among steady, persistent casual and one-off partners in a population of 10,000 MSM, grouped as low- or high-activity by using three different definitions. Model calibration was used to estimate partnership duration and homophily rates to match the distribution of cumulative sex partners over 12 months. We estimated an average duration between 1065 and 1409 days for steady partnerships, 4-6 and 251-299 days for assortative high- and low-activity individuals and 8-13 days for disassortative persistent casual partnerships, respectively, varying across the three definitions. High-quality data on social network and behavioral parameters are scarce in the literature. Our study addresses this lack of information by providing a method to estimate crucial parameters for network specification.

Understanding the Influence of Host Radiation on Symbiont Speciation through Parasites of Species Flocks.

(Adaptive) radiations have attracted evolutionary biologists for a long time as ideal model systems to study patterns and processes of often rapid speciation. However, whereas a wealth of (sometimes already genome-scale) data is available for host radiations, very few studies target the patterns of diversification in their symbionts, even though they would be excellent models to study symbiont speciation. Our review summarizes what little is known about general patterns of symbiont diversification in often iconic adaptive host radiations and to what extent these patterns are dependent on the evolutionary trajectories of their hosts. We identify research gaps that need to be addressed in the future and discuss the potential of approaches not yet typically used in these study systems, such as epidemiological disease modeling and new omics technologies, for significantly advancing our understanding of these complex eco-evolutionary relationships.

Social contacts in Switzerland during the COVID-19 pandemic: Insights from the CoMix study.

To mitigate the spread of SARS-CoV-2, the Swiss government enacted restrictions on social contacts from 2020 to 2022. In addition, individuals changed their social contact behavior to limit the risk of COVID-19. In this study, we aimed to investigate the changes in social contact patterns of the Swiss population. As part of the CoMix study, we conducted a survey consisting of 24 survey waves from January 2021 to May 2022. We collected data on social contacts and constructed contact matrices for the age groups 0-4, 5-14, 15-29, 30-64, and 65 years and older. We estimated the change in contact numbers during the COVID-19 pandemic to a synthetic pre-pandemic contact matrix. We also investigated the association of the largest eigenvalue of the social contact and transmission matrices with the stringency of pandemic measures, the effective reproduction number (Re), and vaccination uptake. During the pandemic period, 7084 responders reported an average number of 4.5 contacts (95% confidence interval, CI: 4.5-4.6) per day overall, which varied by age and survey wave. Children aged 5-14 years had the highest number of contacts with 8.5 (95% CI: 8.1-8.9) contacts on average per day and participants that were 65 years and older reported the fewest (3.4, 95% CI: 3.2-3.5) per day. Compared with the pre-pandemic baseline, we found that the 15-29 and 30-64 year olds had the largest reduction in contacts. We did not find statistically significant associations between the largest eigenvalue of the social contact and transmission matrices and the stringency of measures, Re, or vaccination uptake. The number of social contacts in Switzerland fell during the COVID-19 pandemic and remained below pre-pandemic levels after contact restrictions were lifted. The collected social contact data will be critical in informing modeling studies on the transmission of respiratory infections in Switzerland and to guide pandemic preparedness efforts.

An Efficient Approach to Nowcasting the Time-varying Reproduction Number.

Estimating the instantaneous reproduction number ( ) in near real time is crucial for monitoring and responding to epidemic outbreaks on a daily basis. However, such estimates often suffer from bias due to reporting delays inherent in surveillance systems. We propose a fast and flexible Bayesian methodology to overcome this challenge by estimating while taking into account reporting delays. Furthermore, the method naturally takes into account the uncertainty associated with the nowcasting of cases to get a valid uncertainty estimation of the nowcasted reproduction number. We evaluate the proposed methodology through a simulation study and apply it to COVID-19 incidence data in Belgium.

The impact of quality-adjusted life years on evaluating COVID-19 mitigation strategies: lessons from age-specific vaccination roll-out and variants of concern in Belgium (2020-2022).

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.

Lack of functional TCR-epitope interaction is associated with herpes zoster through reduced downstream T cell activation.

The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4+ T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients. Single-cell RNA and TCR sequencing of VZV-specific T cells shows that T cell activation pathways are significantly decreased after stimulation with VZV peptides in convalescent HZ patients. TCR clustering indicates that TCRs from HZ patients co-cluster more often together than TCRs from controls. Collectively, our results suggest that not only lower VZV-specific TCR diversity but also reduced functional TCR affinity for VZV-specific proteins in HZ patients leads to lower T cell activation and consequently affects the susceptibility for viral reactivation.

Characterising information gains and losses when collecting multiple epidemic model outputs.

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.

Who acquires infection from whom? A sensitivity analysis of transmission dynamics during the early phase of the COVID-19 pandemic in Belgium.

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.

Safety and Immunogenicity of the Heterologous 2-Dose Ad26.ZEBOV, MVA-BN-Filo Vaccine Regimen in Health Care Providers and Frontliners of the Democratic Republic of the Congo.

BACKGROUND: In response to recent Ebola epidemics, vaccine development against the Zaire ebolavirus (EBOV) has been fast-tracked in the past decade. Health care providers and frontliners working in Ebola-endemic areas are at high risk of contracting and spreading the virus. METHODS: This study assessed the safety and immunogenicity of the 2-dose heterologous Ad26.ZEBOV, MVA-BN-Filo vaccine regimen (administered at a 56-day interval) among 699 health care providers and frontliners taking part in a phase 2, monocentric, randomized vaccine trial in Boende, the Democratic Republic of Congo. The first participant was enrolled and vaccinated on 18 December 2019. Serious adverse events were collected up to 6 months after the last received dose. The EBOV glycoprotein FANG ELISA (Filovirus Animal Nonclinical Group enzyme-linked immunosorbent assay) was used to measure the immunoglobulin G-binding antibody response to the EBOV glycoprotein. RESULTS: The vaccine regimen was well tolerated with no vaccine-related serious adverse events reported. Twenty-one days after the second dose, an EBOV glycoprotein-specific binding antibody response was observed in 95.2% of participants. CONCLUSIONS: The 2-dose vaccine regimen was well tolerated and led to a high antibody response among fully vaccinated health care providers and frontliners in Boende.

Cohort-based smoothing methods for age-specific contact rates.

The use of social contact rates is widespread in infectious disease modeling since it has been shown that they are key driving forces of important epidemiological parameters. Quantification of contact patterns is crucial to parameterize dynamic transmission models and to provide insights on the (basic) reproduction number. Information on social interactions can be obtained from population-based contact surveys, such as the European Commission project POLYMOD. Estimation of age-specific contact rates from these studies is often done using a piecewise constant approach or bivariate smoothing techniques. For the latter, typically, smoothness is introduced in the dimensions of the respondent's and contact's age (i.e., the rows and columns of the social contact matrix). We propose a smoothing constrained approach-taking into account the reciprocal nature of contacts-introducing smoothness over the diagonal (including all subdiagonals) of the social contact matrix. This modeling approach is justified assuming that when people age their contact behavior changes smoothly. We call this smoothing from a cohort perspective. Two approaches that allow for smoothing over social contact matrix diagonals are proposed, namely (i) reordering of the diagonal components of the contact matrix and (ii) reordering of the penalty matrix ensuring smoothness over the contact matrix diagonals. Parameter estimation is done in the likelihood framework by using constrained penalized iterative reweighted least squares. A simulation study underlines the benefits of cohort-based smoothing. Finally, the proposed methods are illustrated on the Belgian POLYMOD data of 2006. Code to reproduce the results of the article can be downloaded on this GitHub repository https://github.com/oswaldogressani/Cohort_smoothing.

Reflections On Epidemiological Modeling To Inform Policy During The COVID-19 Pandemic In Western Europe, 2020-23.

We reflect on epidemiological modeling conducted throughout the COVID-19 pandemic in Western Europe, specifically in Belgium, France, Italy, the Netherlands, Portugal, Switzerland, and the United Kingdom. Western Europe was initially one of the worst-hit regions during the COVID-19 pandemic. Western European countries deployed a range of policy responses to the pandemic, which were often informed by mathematical, computational, and statistical models. Models differed in terms of temporal scope, pandemic stage, interventions modeled, and analytical form. This diversity was modulated by differences in data availability and quality, government interventions, societal responses, and technical capacity. Many of these models were decisive to policy making at key junctures, such as during the introduction of vaccination and the emergence of the Alpha, Delta, and Omicron variants. However, models also faced intense criticism from the press, other scientists, and politicians around their accuracy and appropriateness for decision making. Hence, evaluating the success of models in terms of accuracy and influence is an essential task. Modeling needs to be supported by infrastructure for systems to collect and share data, model development, and collaboration between groups, as well as two-way engagement between modelers and both policy makers and the public.

Population age and household structures shape transmission dynamics of emerging infectious diseases: a longitudinal microsimulation approach.

Host population demographics and patterns of host-to-host interactions are important drivers of heterogeneity in infectious disease transmission. To improve our understanding of how population structures and changes therein influence disease transmission dynamics at the individual and population level, we model a dynamic age- and household-structured population using longitudinal microdata drawn from Belgian census and population registers. At different points in time, we simulate the spread of a close-contact infectious disease and vary the age profiles of infectiousness and susceptibility to reflect specific infections (e.g. influenza and SARS-CoV-2) using a two-level mixing model, which distinguishes between exposure to infection in the household and exposure in the community. We find that the strong relationship between age and household structures, in combination with social mixing patterns and epidemiological parameters, shape the spread of an emerging infection. Disease transmission in the adult population in particular is to a large degree explained by differential household compositions and not just household size. Moreover, we highlight how demographic processes alter population structures in an ageing population and how these in turn affect disease transmission dynamics across population groups.

Exploring the impact of population ageing on the spread of emerging respiratory infections and the associated burden of mortality.

BACKGROUND: Increasing life expectancy and persistently low fertility levels have led to old population age structures in most high-income countries, and population ageing is expected to continue or even accelerate in the coming decades. While older adults on average have few interactions that potentially could lead to disease transmission, their morbidity and mortality due to infectious diseases, respiratory infections in particular, remain substantial. We aim to explore how population ageing affects the future transmission dynamics and mortality burden of emerging respiratory infections. METHODS: Using longitudinal individual-level data from population registers, we model the Belgian population with evolving age and household structures, and explicitly consider long-term care facilities (LTCFs). Three scenarios are presented for the future proportion of older adults living in LTCFs. For each demographic scenario, we simulate outbreaks of SARS-CoV-2 and a novel influenza A virus in 2020, 2030, 2040 and 2050 and distinguish between household and community transmission. We estimate attack rates by age and household size/type, as well as disease-related deaths and the associated quality-adjusted life-years (QALYs) lost. RESULTS: As the population is ageing, small households and LTCFs become more prevalent. Additionally, families with children become smaller (i.e. low fertility, single-parent families). The overall attack rate slightly decreases as the population is ageing, but to a larger degree for influenza than for SARS-CoV-2 due to differential age-specific attack rates. Nevertheless, the number of deaths and QALY losses per 1,000 people is increasing for both infections and at a speed influenced by the share living in LTCFs. CONCLUSION: Population ageing is associated with smaller outbreaks of COVID-19 and influenza, but at the same time it is causing a substantially larger burden of mortality, even if the proportion of LTCF residents were to decrease. These relationships are influenced by age patterns in epidemiological parameters. Not only the shift in the age distribution, but also the induced changes in the household structures are important to consider when assessing the potential impact of population ageing on the transmission and burden of emerging respiratory infections.

Key performance indicators of COVID-19 contact tracing in Belgium from September 2020 to December 2021.

The goal of tracing, testing, and quarantining contacts of infected individuals is to contain the spread of infectious diseases, a strategy widely used during the COVID-19 pandemic. However, limited research exists on the effectiveness of contact tracing, especially with regard to key performance indicators (KPIs), such as the proportion of cases arising from previously identified contacts. In our study, we analyzed contact tracing data from Belgium collected between September 2020 and December 2021 to assess the impact of contact tracing on SARS-CoV-2 transmission and understand its characteristics. Among confirmed cases involved in contact tracing in the Flemish and Brussels-Capital regions, 19.1% were previously identified as close contacts and were aware of prior exposure. These cases, referred to as 'known' to contact tracing operators, reported on average fewer close contacts compared to newly identified individuals (0.80 versus 1.05), resulting in fewer secondary cases (0.23 versus 0.28). Additionally, we calculated the secondary attack rate, representing infections per contact, which was on average lower for the 'known' cases (0.22 versus 0.25) between December 2020 and August 2021. These findings indicate the effectiveness of contact tracing in Belgium in reducing SARS-CoV-2 transmission. Although we were unable to quantify the exact number of prevented cases, our findings emphasize the importance of contact tracing as a public health measure. In addition, contact tracing data provide indications of potential shifts in transmission patterns among different age groups associated with emerging variants of concern and increasing vaccination rates.

Impact of the COVID-19 pandemic on community antibiotic consumption in the EU/European Economic Area: a changepoint analysis.

OBJECTIVES: A decrease in community antibiotic consumption in Europe has been observed during the COVID-19 pandemic. The magnitude of this decrease, how fast after the outbreak it occurred, whether it was sustained during the pandemic and whether the seasonal variation in antibiotic consumption was affected, have not yet been evaluated in detail. METHODS: Data on community antibiotic consumption were available from the European Surveillance of Antimicrobial Consumption Network for 28 EU/European Economic Area (EEA) countries between 2010 and 2021. Antibiotic consumption was expressed as DDDs per 1000 inhabitants per day (DID). The impact of the pandemic on antibiotic consumption was investigated using descriptive statistics and non-linear mixed changepoint models for quarterly and yearly data. RESULTS: The decrease in overall antibiotic consumption between 2019 and 2020 (-3.4 DID; -18.6%) was mainly due to a decrease in the consumption of penicillins [Anatomical Therapeutic Chemical (ATC) code J01C] (-1.9 DID; -23.0%), other ß-lactam antibacterials (J01D) (-0.6 DID; -25.8%) and macrolides, lincosamides and streptogramins (J01F) (-0.5 DID; -17.4%) and was sustained during 2021. The changepoint analysis of yearly data (28 countries) estimated a decrease of 3.3 DID in overall antibiotic consumption (J01) between 2019 and 2020. The analysis of quarterly data (16 countries) estimated a decrease in overall antibiotic consumption (J01) of 4.0 DID and a decrease in seasonal variation of 1.2 DID between the first and second quarters of 2020. CONCLUSIONS: The changepoint analysis indicated a significant, sudden and steep decrease in community antibiotic consumption in the EU/EEA immediately after the start of the COVID-19 outbreak in Europe, as well as a decrease in its seasonal variation.

The direct disease burden of COVID-19 in Belgium in 2020 and 2021.

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.