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The role of immunosuppressive therapy on SARS-CoV-2 infection risk and COVID-19 severity remains unclear in unvaccinated solid organ transplant recipients. We included 1957 organ transplant recipients between July 2020 and April 2021 to analyze whether baseline immunosuppressive therapy and other risk factors are associated with SARS-CoV-2 infection and severe COVID-19. In total, 247 (12.6%) had SARS-CoV-2 (defined as positive nasopharyngeal swab and/or positive antibody titer). Of these, 57 (23.1%) had severe COVID-19, defined as oxygen supplementation, intensive care unit admission or death. Multivariable analysis identified diabetes (hazard ratio (HR) 1.39 (95% confidence interval (CI) 1.05-1.83)), chronic lung disease (HR 1.71 (95% CI 1.13-2.60)) and contact with a COVID-19 positive individual (HR 3.61 (95% CI 2.61-4.99) as independent risk factors for SARS-CoV-2 infection. There was no association between immunosuppressive therapy and infection risk. Severe COVID-19 was multivariably associated with hypertension (OR 5.45 (95% CI 1.66-17.84)), chronic kidney disease (OR 3.55 (95% CI 1.75-7.19)), corticosteroid use (OR 2.93 (95% CI 1.03-2.55)) and having a COVID-19 positive housemate (OR 6.77 (95% CI 2.65-17.28)). In conclusion, baseline corticosteroid use, but no other immunosuppressive agent, is independently associated with severe COVID-19 in unvaccinated SOT recipients after correction for hypertension, chronic kidney disease, housemates affected by COVID-19 and transplant type., (© 2024. The Author(s).)

Background: Over the past four years, the COVID-19 pandemic has exerted a profound impact on public health, including on mortality trends. This study investigates mortality patterns in Belgium by examining all-cause mortality, excess mortality, and cause-specific mortality., Methods: We retrieved all-cause mortality data from January 1, 2009, to December 31, 2022, stratified by age group and sex. A linear mixed model, informed by all-cause mortality from 2009 to 2019, was used to predict non-pandemic all-cause mortality rates in 2020-2022 and estimate excess mortality. Further, we also analyzed trends in cause-specific and premature mortality., Results: Different all-cause mortality patterns could be observed between the younger (<45 years) and older age groups. The impact of the COVID-19 pandemic was particularly evident among older age groups. The highest excess mortality occurred in 2020, while a reversal in this trend was evident in 2022. We observed a notable effect of COVID-19 on cause-specific and premature mortality patterns over the three-year period., Conclusions: Despite a consistent decline in COVID-19 reported mortality over this three-year period, it remains imperative to meticulously monitor mortality trends in the years ahead., (© 2024. The Author(s).)

Background: Coronavirus disease 2019 (COVID-19) caused a high burden of sick leave worldwide. Long-term sick leave for COVID-19 may be longer than for other influenza-like syndromes. The real impact of long COVID on absenteeism remains uncertain., Aims: To investigate the burden of sick leave, especially >12 weeks, in Belgian workers with a positive polymerase chain reaction (PCR) test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from July 2020 to September 2021 and to compare these figures with sick leave for other infectious diseases., Methods: We coupled a database of SARS-CoV-2-positive workers and workers who were absent for other infections with objective absence data. Predictors of prolonged sickness were evaluated by negative binomial regression, Cox proportional hazards regression and ordinal logistic regression., Results: The study population involved 2569 workers who tested positive for SARS-CoV-2 and 392 workers who were absent for other infectious diseases. In total, 16% (95% CI 14-17%) of workers with a positive SARS-CoV-2 test had no sick leave registered. Fourteen out of 1000 (95% CI 9-20‰) workers with absenteeism for COVID-19 experienced sick leave >12 weeks as compared to 43 out of 1000 workers (95% CI 3-69‰) with absenteeism due to other infections. When including PCR-positive workers without sick leave, the prevalence of long-term sick leave decreased to 12 per 1000 (95% CI8-17‰). Long-term sick leave was associated with older age, high previous sick leave and low educational level., Conclusions: The prevalence of long-term sick leave was lower than estimated in earlier investigations regardless of worrying reports about post-COVID-19 syndrome., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objectives: Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic., Methods: We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model., Results: Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions., Conclusions: This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends., 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 Author(s). Published by Elsevier Ltd.. All rights reserved.)

One of the key tools to understand and reduce the spread of the SARS-CoV-2 virus is testing. The total number of tests, the number of positive tests, the number of negative tests, and the positivity rate are interconnected indicators and vary with time. To better understand the relationship between these indicators, against the background of an evolving pandemic, the association between the number of positive tests and the number of negative tests is studied using a joint modeling approach. All countries in the European Union, Switzerland, the United Kingdom, and Norway are included in the analysis. We propose a joint penalized spline model in which the penalized spline is reparameterized as a linear mixed model. The model allows for flexible trajectories by smoothing the country-specific deviations from the overall penalized spline and accounts for heteroscedasticity by allowing the autocorrelation parameters and residual variances to vary among countries. The association between the number of positive tests and the number of negative tests is derived from the joint distribution for the random intercepts and slopes. The correlation between the random intercepts and the correlation between the random slopes were both positive. This suggests that, when countries increase their testing capacity, both the number of positive tests and negative tests will increase. A significant correlation was found between the random intercepts, but the correlation between the random slopes was not significant due to a wide credible interval., Competing Interests: The authors declare that no competing interests exist., (Copyright: © 2024 De Witte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The COVID-19 pandemic led to sustained surveillance efforts, which made unprecedented volumes and types of data available. In Belgium, these data were used to conduct a targeted and regular assessment of the epidemiological situation. In addition, management tools were developed, incorporating key indicators and thresholds, to define risk levels and offer guidance to policy makers. Categorizing risk into various levels provided a stable framework to monitor the COVID-19 epidemiological situation and allowed for clear communication to authorities. Although translating risk levels into specific public health measures has remained challenging, this experience was foundational for future evaluation of the situation for respiratory infections in general, which, in Belgium, is now based on a management tool combining different data sources., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 De Muylder, Laisnez, Stefani, Boulouffe, Faes, Hammami, Hubin, Molenberghs, Sans, van de Konijnenburg, Van der Borght, Brondeel, Stassijns and Lernout.)

Background: Transmission of SARS-CoV-2 from donor to recipient is a clinically relevant risk for developing severe COVID-19 after lung transplantation (LTx). This risk of iatrogenic transmission can be reduced by timely detection of viral RNA or antigen in samples of bronchoalveolar lavage (BAL) fluid obtained at the time of lung procurement. We aimed to retrospectively evaluate the detection of SARS-CoV-2 RNA or antigen in BAL fluid samples using three point-of-care tests (POCTs)., Methods: BAL fluid samples came from patients hospitalized in an intensive care unit during the COVID-19 pandemic. These pandemic samples were scored as positive or negative for SARS-CoV-2 by a RT-qPCR comparator assay for orf1ab. Three commercially available POCTs were then evaluated: cobas SARS-CoV-2 & Influenza A/B assay with the cobas Liat RT-qPCR system (Roche Diagnostics), ID NOW COVID-19 and COVID-19 2.0 (Abbott), and SARS-CoV-2 Rapid Antigen Test (RAT) (Roche Diagnostics). Samples from the pre-pandemic era served as negative controls., Results: We analyzed a total of 98 BAL fluid samples, each from a different patient: 58 positive pandemic samples (orf1ab Ct<38), 20 putatively negative pandemic samples (orf1ab Ct≥38), and 20 pre-pandemic samples. Univariate logistic regression shows that the probability of detection was highest for cobas Liat, followed by ID NOW, and then RAT. Of clinical relevance, cobas Liat detected SARS-CoV-2 RNA in 30 of the 31 positive pandemic samples that were collected within 10 days after RT-qPCR diagnosis of SARS-CoV-2 infection. None of the 20 pre-pandemic samples had a false-positive result for any POCT., Conclusions: POCTs enable the detection of SARS-CoV-2 RNA or antigen in BAL fluid samples and may provide additional information to decide if donor lungs are suitable for transplantation. Detection of respiratory pathogens with POCTs at the time of donor lung procurement is a potential strategy to increase safety in LTx by preventing iatrogenic transmission and severe postoperative infections., Competing Interests: Declaration of Competing Interest The authors declare they have no competing interests., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Purpose: Policymakers have struggled to maintain SARS-CoV-2 transmission at levels that are manageable to contain the COVID-19 disease burden while enabling a maximum of societal and economic activities. One of the tools that have been used to facilitate this is the so-called "COVID-19 pass". We aimed to document current evidence on the effectiveness of COVID-19 passes, distinguishing their indirect effects by improving vaccination intention and uptake from their direct effects on COVID-19 transmission measured by the incidence of cases, hospitalizations, and deaths., Methods: We performed a scoping review on the scientific literature of the proposed topic covering the period January 2021 to September 2022, in accordance with the PRISMA-ScR guidelines for scoping reviews., Results: Out of a yield of 4,693 publications, 45 studies from multiple countries were retained for full-text review. The results suggest that implementing COVID-19 passes tends to reduce the incidence of cases, hospitalizations, and deaths due to COVID-19. The use of COVID-19 passes was also shown to improve overall vaccination uptake and intention, but not in people who hold strong anti-COVID-19 vaccine beliefs., Conclusion: The evidence from the literature we reviewed tends to indicate positive direct and indirect effects from the use of COVID-19 passes. A major limitation to establishing this firmly is the entanglement of individual effects of multiple measures being implemented simultaneously., (© 2023. The Author(s).)

Introduction: COVID-19 remains a major concern globally. Therefore, it is important to evaluate COVID-19's rapidly changing trends. The fractal dimension has been proposed as a viable method to characterize COVID-19 curves since epidemic data is often subject to considerable heterogeneity. In this study, we aim to investigate the association between various socio-demographic factors and the complexity of the COVID-19 curve as quantified through its fractal dimension., Methods: We collected population indicators data (ethnic composition, socioeconomic status, number of inhabitants, population density, the older adult population proportion, vaccination rate, satisfaction, and trust in the government) at the level of the statistical sector in Belgium. We compared these data with fractal dimension indicators of COVID-19 incidence between 1 January - 31 December 2021 using canonical correlation analysis., Results: Our results showed that these population indicators have a significant association with COVID-19 incidences, with the highest explanatory and predictive power coming from the number of inhabitants, population density, and ethnic composition., Conclusion: It is important to monitor these population indicators during a pandemic, especially when dealing with targeted interventions for a specific population., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Natalia, Faes, Neyens, Hammami and Molenberghs.)

In the COVID-19 pandemic, workplace transmission plays an important role. For this type of transmission, the longitudinal 14-day incidence curve of SARS-CoV-2 infections per economic sector is a proxy. In Belgium, a census of confirmed 14-day incidences per NACE-BEL sector level three is available from September 2020 until June 2021, encompassing two waves of infections. However, these high-dimensional data, with a relatively small number of NACE-BEL sectors, are challenging to analyze. We propose a nonlinear Gaussian-Gaussian model that combines parametric and semi-parametric elements to describe the incidence curves with a small set of meaningful parameters. These parameters are further analyzed with conventional statistical methods, such as CCA and linear models, to provide insight into predictive characteristics of the first wave for the second wave. Those nonlinear models classify economic sectors into three groups: sectors with two regular waves of infections, sectors with only a first wave and sectors with a more irregular profile, which may indicate a clear effect of COVID-19 vaccination. The Gaussian-Gaussian model thus allows for analyzing and comparing incidence curves and to bring out key characteristics of such curves. Finally, we consider in which other settings the proposed approach could be applied, together with possible pitfalls., (© 2022 The International Biometric Society.)

Objective: To examine if personal and comparative optimism, perceived effectiveness, and moralization of vaccination predict people's decision to get vaccinated., Methods: We measured self-reported vaccination decisions in a five-wave longitudinal study ( N ≍ 5,000/wave) in Belgium over a six months period (December 2020-May 2021) during the COVID-19 pandemic. Among the predictors were demographic factors, personal and comparative optimism for three aspects of COVID-19 (infection, severe disease, good outcome), perceived effectiveness of vaccination, and the extent to which vaccination is being viewed in prosocial terms (altruism, civic spirit) versus as instrumental in one's self-interest (common sense, concern about one's health)., Results: The actual availability of vaccines changed people's outlook on vaccination. Marked differences emerged in vaccination decision between linguistic-cultural regions (Flemish Region, Walloon Region, Brussels Capital Region). Personal and comparative optimism predicted vaccination decisions to different extents depending on participants' age and on whether the optimism was for infection, severe disease, or a good outcome. In older participants, vaccination decision was mostly predicted by personal optimism; in younger participants, it was mostly predicted by comparative optimism. Moralizing vaccination predicted a lower likelihood of a positive vaccination decision, that is, higher vaccine hesitancy or refusal, particularly in older participants., Conclusions: Assessments of risk perception serving to inform vaccination campaigns should differentiate between expectations concerning the risk of infection and expectations concerning the outcome of an infection. Public health messages should address comparative optimism, particularly when targeting younger populations. Contrary to popular belief, moralizing vaccination may reduce the willingness to get vaccinated. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Background: During the COVID-19 pandemic, the CoMix study, a longitudinal behavioral survey, was designed to monitor social contacts and public awareness in multiple countries, including Belgium. As a longitudinal survey, it is vulnerable to participants' "survey fatigue", which may impact inferences., Methods: A negative binomial generalized additive model for location, scale, and shape (NBI GAMLSS) was adopted to estimate the number of contacts reported between age groups and to deal with under-reporting due to fatigue within the study. The dropout process was analyzed with first-order auto-regressive logistic regression to identify factors that influence dropout. Using the so-called next generation principle, we calculated the effect of under-reporting due to fatigue on estimating the reproduction number., Results: Fewer contacts were reported as people participated longer in the survey, which suggests under-reporting due to survey fatigue. Participant dropout is significantly affected by household size and age categories, but not significantly affected by the number of contacts reported in any of the two latest waves. This indicates covariate-dependent missing completely at random (MCAR) in the dropout pattern, when missing at random (MAR) is the alternative. However, we cannot rule out more complex mechanisms such as missing not at random (MNAR). Moreover, under-reporting due to fatigue is found to be consistent over time and implies a 15-30% reduction in both the number of contacts and the reproduction number ([Formula: see text]) ratio between correcting and not correcting for under-reporting. Lastly, we found that correcting for fatigue did not change the pattern of relative incidence between age groups also when considering age-specific heterogeneity in susceptibility and infectivity., Conclusions: CoMix data highlights the variability of contact patterns across age groups and time, revealing the mechanisms governing the spread/transmission of COVID-19/airborne diseases in the population. Although such longitudinal contact surveys are prone to the under-reporting due to participant fatigue and drop-out, we showed that these factors can be identified and corrected using NBI GAMLSS. This information can be used to improve the design of similar, future surveys., (© 2023. The Author(s).)

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., (© 2023. The Author(s).)

The rapid spread of COVID-19 worldwide led to the implementation of various non-pharmaceutical interventions to limit transmission and hence reduce the number of infections. Using telecom-operator-based mobility data and a spatio-temporal dynamic model, the impact of mobility on the evolution of the pandemic at the level of the 581 Belgian municipalities is investigated. By decomposing incidence, particularly into within- and between-municipality components, we noted that the global epidemic component is relatively more important in larger municipalities (e.g., cities), while the local component is more relevant in smaller (rural) municipalities. Investigation of the effect of mobility on the pandemic spread showed that reduction of mobility has a significant impact in reducing the number of new infections., 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 © 2023 Elsevier Ltd. All rights reserved.)

To monitor the COVID-19 epidemic in Cuba, data on several epidemiological indicators have been collected on a daily basis for each municipality. Studying the spatio-temporal dynamics in these indicators, and how they behave similarly, can help us better understand how COVID-19 spread across Cuba. Therefore, spatio-temporal models can be used to analyze these indicators. Univariate spatio-temporal models have been thoroughly studied, but when interest lies in studying the association between multiple outcomes, a joint model that allows for association between the spatial and temporal patterns is necessary. The purpose of our study was to develop a multivariate spatio-temporal model to study the association between the weekly number of COVID-19 deaths and the weekly number of imported COVID-19 cases in Cuba during 2021. To allow for correlation between the spatial patterns, a multivariate conditional autoregressive prior (MCAR) was used. Correlation between the temporal patterns was taken into account by using two approaches; either a multivariate random walk prior was used or a multivariate conditional autoregressive prior (MCAR) was used. All models were fitted within a Bayesian framework., 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 © 2023 Elsevier Ltd. All rights reserved.)

During the coronavirus disease 2019 pandemic, individuals relied heavily on media sources to stay informed about the disease and public health measures. However, differences exist in the type and frequency of news media consumption, which can be linked to their perceived vulnerability to disease. In this longitudinal study, 1000 Flemish (Belgium) individuals were followed from March 2020 until September 2020, focussing on the evolution in perceived vulnerability to disease (i.e. perceived infectability and germ aversion). Media consumption significantly impacts perceived germ aversion; heavy consumers of commercial media reported greater germ aversion than light consumers of these media. The evolution of germ aversion among individuals from March to August depends on their gender, living environment, age and possibility to work from home. Furthermore, the evolution of perceived infectability depends on the age and living environment of the respondent. These findings may interest policy makers and media professionals to anticipate how anxieties regarding contracting an infectious disease evolve over time and how individual characteristics affect this evolution., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Rates and modulators of SARS-CoV-2 vaccine nonresponse and breakthrough infections remain unclear in serially vaccinated transplant recipients. In a prospective, mono-centric, observational study, 1878 adult solid organ and hematopoietic cell transplant recipients, with prior SARS-CoV-2 vaccination, were included between March 2021 and February 2022. SARS-CoV-2 anti-spike IgG antibodies were measured at inclusion and details on SARS-CoV-2 vaccine doses and infection were collected. No life-threatening adverse events were reported after a total of 4039 vaccine doses. In transplant recipients without prior SARS-CoV-2 infection (n = 1636), antibody response rates ranged widely, from 47% in lung transplant to 90% in liver transplant and 91% in hematopoietic cell transplant recipients after third vaccine dose. Antibody positivity rate and levels increased after each vaccine dose in all types of transplant recipients. In multivariable analysis, older age, chronic kidney disease and daily dose of mycophenolate and corticosteroids were negatively associated with antibody response rate. Overall rate of breakthrough infections was 25.2% and mainly (90.2%) occurred after third and fourth vaccine dose. Lung transplant recipients had the highest rates of severe breakthrough infection (10.5%) and death (2.5%). In multivariable analysis, older age, daily dose of mycophenolate and corticosteroids were associated with severe breakthrough infection. Transplant recipients with infection before first vaccine dose (n = 160) had higher antibody response rates and levels after each vaccine dose, and a significantly lower overall rate of breakthrough infections compared to those without prior infection. Antibody response after SARS-CoV-2 vaccination and rate of severe breakthrough infections vary largely between different transplant types and are modulated by specific risk factors. The observed heterogeneity supports a tailored approach against COVID-19 in transplant recipients., (© 2023 Wiley Periodicals LLC.)

Understanding the local dynamics of COVID-19 transmission calls for an approach that characterizes the incidence curve in a small geographical unit. Given that incidence curves exhibit considerable day-to-day variation, the fractal structure of the time series dynamics is investigated for the Flanders and Brussels Regions of Belgium. For each statistical sector, the smallest administrative geographical entity in Belgium, fractal dimensions of COVID-19 incidence rates, based on rolling time spans of 7, 14, and 21 days were estimated using four different estimators: box-count, Hall-Wood, variogram, and madogram. We found varying patterns of fractal dimensions across time and location. The fractal dimension is further summarized by its mean, variance, and autocorrelation over time. These summary statistics are then used to cluster regions with different incidence rate patterns using k-means clustering. Fractal dimension analysis of COVID-19 incidence thus offers important insight into the past, current, and arguably future evolution of an infectious disease outbreak., (© 2023. The Author(s).)

The Corona Virus Disease (COVID-19) pandemic has increased mortality in countries worldwide. To evaluate the impact of the pandemic on mortality, the use of excess mortality rather than reported COVID-19 deaths has been suggested. Excess mortality, however, requires estimation of mortality under nonpandemic conditions. Although many methods exist to forecast mortality, they are either complex to apply, require many sources of information, ignore serial correlation, and/or are influenced by historical excess mortality. We propose a linear mixed model that is easy to apply, requires only historical mortality data, allows for serial correlation, and down-weighs the influence of historical excess mortality. Appropriateness of the linear mixed model is evaluated with fit statistics and forecasting accuracy measures for Belgium and the Netherlands. Unlike the commonly used 5-year weekly average, the linear mixed model is forecasting the year-specific mortality, and as a result improves the estimation of excess mortality for Belgium and the Netherlands., (© 2021 The International Biometric Society.)

In this commentary to Dattner et al. (Israel J Health Policy Res. 11:22, 2022), we highlight similarities and differences in the role that biostatistics and biostatisticians have been playing in the COVID-19 response in Belgium and Israel. We bring out implications and opportunities for our field and for science. We argue that biostatistics has an important place in the multidisciplinary COVID-19 response, in terms of research, policy advice, and science and public communication. In Belgium, biostatisticians located in various institutes, collaborated with epidemiologists, vaccinologists, infectiologists, immunologists, social scientists, and government policy makers to provide rapid and science-informed policy advice. Biostatisticians, who can easily be mobilized to work together in pandemic response, also played a role in public communication., (© 2023. The Author(s).)

This work presents a joint spatial modeling framework to improve estimation of the spatial distribution of the latent COVID-19 incidence in Belgium, based on test-confirmed COVID-19 cases and crowd-sourced symptoms data as reported in a large-scale online survey. Correction is envisioned for stochastic dependence between the survey's response rate and spatial COVID-19 incidence, commonly known as preferential sampling, but not found significant. Results show that an online survey can provide valuable auxiliary data to optimize spatial COVID-19 incidence estimation based on confirmed cases in situations with limited testing capacity. Furthermore, it is shown that an online survey on COVID-19 symptoms with a sufficiently large sample size per spatial entity is capable of pinpointing the same locations that appear as test-confirmed clusters, approximately 1 week earlier. We conclude that a large-scale online study provides an inexpensive and flexible method to collect timely information of an epidemic during its early phase, which can be used by policy makers in an early phase of an epidemic and in conjunction with other monitoring systems., (© 2022 Wiley-VCH GmbH.)

Rationale: Research on health-related self-uniqueness beliefs suggested that these beliefs might predict adherence to precautions against COVID-19., Objective: We examined if comparative optimism (believing that one is less at less than others), self-superiority (believing that one already adheres better to precautions than others), and egocentric impact perception (believing that adverse events affect oneself more than others) predicted intended adherence to precautions., Method: We measured self-reported intentions, optimism for self and others, perceived past adherence by self and others, and perceived impact of the measures and the disease on self and others in a 5-wave longitudinal study in December 2020-May 2021 (N ≈ 5000/wave). The sample was in key respects representative for the Belgian population. We used joint models to examine the relationship between self-uniqueness beliefs and intended adherence to the precautions., Results: Believing that COVID-19 would affect one's own life more than average (egocentric impact perception) was associated with higher intentions to adhere to precautions, as was believing that the precautions affected one's life less than average (allocentric impact perception). Self-superiority concerning past adherence to precautions and comparative optimism concerning infection with COVID-19 were associated with higher intended adherence, regardless of whether their non-comparative counterparts (descriptive norm, i.e., perceived adherence to precautions by others, and personal optimism, respectively) were controlled for. Comparative optimism for severe disease and for good outcome were associated with lower intended adherence if personal optimism was not controlled for, but with higher intended adherence if it was controlled for., Conclusion: Self-uniqueness beliefs predict intended adherence to precautions against COVID-19, but do so in different directions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

From the beginning of the COVID-19 pandemic, researchers advised policy makers to make informed decisions towards the adoption of mitigating interventions. Key easy-to-interpret metrics applied over time can measure the public health impact of epidemic outbreaks. We propose a novel method which quantifies the effect of hospitalizations or mortality when the number of COVID-19 cases doubles. Two analyses are used, a country-by-country analysis and a multi-country approach which considers all countries simultaneously. The new measure is applied to several European countries, where the presence of different variants, vaccination rates and intervention measures taken over time leads to a different risk. Based on our results, the vaccination campaign has a clear effect for all countries analyzed, reducing the risk over time. However, the constant emergence of new variants combined with distinct intervention measures impacts differently the risk per country., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Petrof et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Belgium is a geographically small country bordered by The Netherlands, France, Germany, and Luxembourg, with intense transborder mobility, defined as mobility in the border regions with neighboring countries. It is therefore of interest to examine how the 14-day COVID-19 confirmed case incidence in the border regions is influenced by that of the adjacent regions in the neighboring countries and thus, whether and how it differs from that in the adjacent non-border regions within Belgium. To this end, the 14-day COVID-19 confirmed case incidence is studied at the level of Belgian provinces, well-defined border areas within Belgium, and adjacent regions in the neighboring countries. Auxiliary information encompasses work-related border traffic, travel rates, the proportion of people with a different nationality, the stringency index of the non-pharmaceutical interventions, and the degree of urbanization at the level of the municipality. Especially in transnational urbanized areas such as between the Belgian and Dutch provinces of Limburg and between the Belgian province of Antwerp and the Dutch province of North Brabant, the impact on incidence is visible, at least at some points in time, especially when the national incidences differ between neighboring countries. In contrast, the intra-Belgian language border regions show very little transborder impact on the incidence curves, except around the Brussels capital region, leading to various periods where the incidences are very different in the Dutch-speaking north and the French-speaking south of Belgium. Our findings suggest that while travel restrictions may be needed at some points during a pandemic, a more fine-grained approach than merely closing national borders may be considered. At the same time, in border regions with considerable transborder mobility, it is recommended to coordinate the non-pharmaceutical interventions between the authorities of the various countries overlapping with the border region. While this seems logical, there are clear counterexamples, e.g., where non-essential shops, restaurants, and bars are closed in one country but not in the neighboring country.

Healthcare workers (HCWs) are known to be at higher risk of developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections although whether these risks are equal across all occupational roles is uncertain. Identifying these risk factors and understand SARS-CoV-2 transmission pathways in healthcare settings are of high importance to achieve optimal protection measures. We aimed to investigate the implementation of a voluntary screening program for SARS-CoV-2 infections among hospital HCWs and to elucidate potential transmission pathways though phylogenetic analysis before the vaccination era. HCWs of the University Hospital of Liège, Belgium, were invited to participate in voluntary reverse transcriptase-polymerase chain reaction (RT-PCR) assays performed every week from April to December 2020. Phylogenetic analysis of SARS-CoV-2 genomes were performed for a subgroup of 45 HCWs. 5095 samples were collected from 703 HCWs. 212 test results were positive, 15 were indeterminate, and 4868 returned negative. 156 HCWs (22.2%) tested positive at least once during the study period. All SARS-CoV-2 test results returned negative for 547 HCWs (77.8%). Nurses (p < 0.05), paramedics (p < 0.05), and laboratory staff handling respiratory samples (p < 0.01) were at higher risk for being infected compared to the control non-patient facing group. Our phylogenetic analysis revealed that most positive samples corresponded to independent introduction events into the hospital. Our findings add to the growing evidence of differential risks of being infected among HCWs and support the need to implement appropriate protection measures based on each individual’s risk profile to guarantee the protection of both HCWs and patients. Furthermore, our phylogenetic investigations highlight that most positive samples correspond to distinct introduction events into the hospital.

Soon after SARS-CoV-2 emerged in late 2019, Belgium was confronted with a first COVID-19 wave in March-April 2020. SARS-CoV-2 circulation declined in the summer months (late May to early July 2020). Following a successfully trumped late July-August peak, COVID-19 incidence fell slightly, to then enter two successive phases of rapid incline: in the first half of September, and then again in October 2020. The first of these coincided with the peak period of returning summer travelers; the second one coincided with the start of higher education's academic year. The largest observed COVID-19 incidence occurred in the period 16-31 October, particularly in the Walloon Region, the southern, French-speaking part of Belgium. We examine the potential association of the higher education population with spatio-temporal spread of COVID-19, using Bayesian spatial Poisson models for confirmed test cases, accounting for socio-demographic heterogeneity in the population. We find a significant association between the number of COVID-19 cases in the age groups 18-29 years and 30-39 years and the size of the higher education student population at the municipality level. These results can be useful towards COVID-19 mitigation strategies, particularly in areas where virus transmission from higher education students into the broader community could exacerbate morbidity and mortality of COVID-19 among populations with prevalent underlying conditions associated with more severe outcomes following infection., Competing Interests: The authors have declared that no competing interests exist.

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.

Some occupational sectors, such as human health and care, food service, cultural and sport activities, have been associated with a higher risk of SARS-CoV-2 infection than other sectors. To curb the spread of SARS-CoV-2, it is preferable to apply targeted non-pharmaceutical interventions on selected economic sectors, rather than a full lockdown. However, the effect of these general and sector-specific interventions on the virus circulation has only been sparsely studied. We assess the COVID-19 incidence under different levels of non-pharmaceutical interventions per economic activity during the autumn 2020 wave in Belgium. The 14-day incidence of confirmed COVID-19 cases per the Statistical Classification of Economic Activities in the European Community (NACE-BEL) sector is modelled by a longitudinal Gaussian-Gaussian two-stage approach. This is based on exhaustive data on all employees in all sectors. In the presence of sanitary protocols and minimal non-pharmaceutical interventions, many sectors with close contact with others show considerably higher COVID-19 14-day incidences than other sectors. The effect of stricter non-pharmaceutical interventions in the general population and non-essential sectors is seen in the timing of the peak incidence and the width and height of the post-peak incidence. In most sectors incidences returned to higher levels after the peak than before and this decrease took longer for the health and care sector. Sanitary protocols for close proximity occupations may be sufficient during periods of low-level virus circulation, but progressively less with increasing circulation. Stricter general and sector-specific non-pharmaceutical interventions adequately decrease COVID-19 incidences, even in close proximity in essential sectors under solely sanitary protocols.

Background: In Belgium, schools closed during the first lockdown in March 2020, with a partial reopening in May. They fully reopened in September. During the summer, infections started to increase in the general population, speeding up in September. Some measures were taken to limit social contacts but those were insufficient to mitigate the exponential rise of infections in October. Children were still receiving all lessons at school at that time and it was questioned whether this position was tenable. We systematically compared the benefits and harms of closing primary and secondary schools and developed a recommendation., Methods: A multidisciplinary panel, including school pupils and teachers, educational experts, clinicians and researchers, produced this recommendation in compliance with the standards for trustworthy rapid guidelines. The recommendation is based on data collected through national surveillance or studies from Belgium, and supported by a rapid literature review., Results: Closing schools during the first lockdown probably resulted in a large learning delay and possibly led to more cases of child abuse. We are uncertain about the effect on the infection rate, hospitalisations, transmission rates, mental health of children, teachers and parents. The panel concluded that the balance of benefits and harms of closing schools clearly shifts against closing schools. Detrimental effects are even worse for vulnerable children. This recommendation is affected by the local virus circulation., Conclusion: The guideline panel issues a strong recommendation against closing schools when the virus circulation is low to moderate, and a weak recommendation against closing schools when the virus circulation is high. It does not apply when the school system cannot function due to lack of teachers, too many children who are at home or a shortage of support services. As the results of international studies are consistent with Belgian study results, this recommendation may also be relevant internationally., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Starting from historic reflections, the current SARS-CoV-2 induced COVID-19 pandemic is examined from various perspectives, in terms of what it implies for the implementation of non-pharmaceutical interventions, the modeling and monitoring of the epidemic, the development of early-warning systems, the study of mortality, prevalence estimation, diagnostic and serological testing, vaccine development, and ultimately clinical trials. Emphasis is placed on how the pandemic had led to unprecedented speed in methodological and clinical development, the pitfalls thereof, but also the opportunities that it engenders for national and international collaboration, and how it has simplified and sped up procedures. We also study the impact of the pandemic on clinical trials in other indications. We note that it has placed biostatistics, epidemiology, virology, infectiology, and vaccinology, and related fields in the spotlight in an unprecedented way, implying great opportunities, but also the need to communicate effectively, often amidst controversy., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)