Vaccine effectiveness against transmission of alpha, delta and omicron SARS-COV-2-infection, Belgian contact tracing, 2021-2022.

OBJECTIVES: Vaccine effectiveness against transmission (VET) of SARS-CoV-2-infection can be estimated from secondary attack rates observed during contact tracing. We estimated VET, the vaccine-effect on infectiousness of the index case and susceptibility of the high-risk exposure contact (HREC). METHODS: We fitted RT-PCR-test results from HREC to immunity status (vaccine schedule, prior infection, time since last immunity-conferring event), age, sex, calendar week of sampling, household, background positivity rate and dominant VOC using a multilevel Bayesian regression-model. We included Belgian data collected between January 2021 and January 2022. RESULTS: For primary BNT162b2-vaccination we estimated initial VET at 96% (95%CI 95-97) against Alpha, 87% (95%CI 84-88) against Delta and 31% (95%CI 25-37) against Omicron. Initial VET of booster-vaccination (mRNA primary and booster-vaccination) was 87% (95%CI 86-89) against Delta and 68% (95%CI 65-70) against Omicron. The VET-estimate against Delta and Omicron decreased to 71% (95%CI 64-78) and 55% (95%CI 46-62) respectively, 150-200 days after booster-vaccination. Hybrid immunity, defined as vaccination and documented prior infection, was associated with durable and higher or comparable (by number of antigen exposures) protection against transmission. CONCLUSIONS: While we observed VOC-specific immune-escape, especially by Omicron, and waning over time since immunization, vaccination remained associated with a reduced risk of SARS-CoV-2-transmission.

Homologous and Heterologous Prime-Boost Vaccination: Impact on Clinical Severity of SARS-CoV-2 Omicron Infection among Hospitalized COVID-19 Patients in Belgium.

We investigated effectiveness of (1) mRNA booster vaccination versus primary vaccination only and (2) heterologous (viral vector-mRNA) versus homologous (mRNA-mRNA) prime-boost vaccination against severe outcomes of BA.1, BA.2, BA.4 or BA.5 Omicron infection (confirmed by whole genome sequencing) among hospitalized COVID-19 patients using observational data from national COVID-19 registries. In addition, it was investigated whether the difference between the heterologous and homologous prime-boost vaccination was homogenous across Omicron sub-lineages. Regression standardization (parametric g-formula) was used to estimate counterfactual risks for severe COVID-19 (combination of severity indicators), intensive care unit (ICU) admission, and in-hospital mortality under exposure to different vaccination schedules. The estimated risk for severe COVID-19 and in-hospital mortality was significantly lower with an mRNA booster vaccination as compared to only a primary vaccination schedule (RR = 0.59 [0.33; 0.85] and RR = 0.47 [0.15; 0.79], respectively). No significance difference was observed in the estimated risk for severe COVID-19, ICU admission and in-hospital mortality with a heterologous compared to a homologous prime-boost vaccination schedule, and this difference was not significantly modified by the Omicron sub-lineage. Our results support evidence that mRNA booster vaccination reduced the risk of severe COVID-19 disease during the Omicron-predominant period.

Evaluating methodological approaches to assess the severity of infection with SARS-CoV-2 variants: scoping review and applications on Belgian COVID-19 data.

BACKGROUND: Differences in the genetic material of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants may result in altered virulence characteristics. Assessing the disease severity caused by newly emerging variants is essential to estimate their impact on public health. However, causally inferring the intrinsic severity of infection with variants using observational data is a challenging process on which guidance is still limited. We describe potential limitations and biases that researchers are confronted with and evaluate different methodological approaches to study the severity of infection with SARS-CoV-2 variants. METHODS: We reviewed the literature to identify limitations and potential biases in methods used to study the severity of infection with a particular variant. The impact of different methodological choices is illustrated by using real-world data of Belgian hospitalized COVID-19 patients. RESULTS: We observed different ways of defining coronavirus disease 2019 (COVID-19) disease severity (e.g., admission to the hospital or intensive care unit versus the occurrence of severe complications or death) and exposure to a variant (e.g., linkage of the sequencing or genotyping result with the patient data through a unique identifier versus categorization of patients based on time periods). Different potential selection biases (e.g., overcontrol bias, endogenous selection bias, sample truncation bias) and factors fluctuating over time (e.g., medical expertise and therapeutic strategies, vaccination coverage and natural immunity, pressure on the healthcare system, affected population groups) according to the successive waves of COVID-19, dominated by different variants, were identified. Using data of Belgian hospitalized COVID-19 patients, we were able to document (i) the robustness of the analyses when using different variant exposure ascertainment methods, (ii) indications of the presence of selection bias and (iii) how important confounding variables are fluctuating over time. CONCLUSIONS: When estimating the unbiased marginal effect of SARS-CoV-2 variants on the severity of infection, different strategies can be used and different assumptions can be made, potentially leading to different conclusions. We propose four best practices to identify and reduce potential bias introduced by the study design, the data analysis approach, and the features of the underlying surveillance strategies and data infrastructure.

Opportunities for a population-based cohort in Belgium.

Population-based cohorts allow providing answers to a wide range of policy-relevant research questions. In Belgium, existing cohort-like initiatives are limited by their focus on specific population groups or specific topics, or they lack a true longitudinal design. Since 2016, consultations and deliberative processes have been set up to explore the opportunities for a population-based cohort in Belgium. Through these processes, several recommendations emerged to pave the way forward - i.e., to facilitate the establishment of administrative linkages, increase digitalisation, secure long-term financial and organisational efforts, establish a consortium of the willing, and identify and tackle ethical and legal bottlenecks. This comment summarizes these recommendations, as these opportunities should be explored in depth to consolidate the existing collaborations between different stakeholders, and refers to current initiatives that can further facilitate the establishment of a Belgian population-based cohort and, more generally, administrative and health data linkage and reuse for research and policy-making.

Severity of infection with the SARS-CoV-2 B.1.1.7 lineage among hospitalized COVID-19 patients in Belgium.

INTRODUCTION: The pathogenesis of COVID-19 depends on the interplay between host characteristics, viral characteristics and contextual factors. Here, we compare COVID-19 disease severity between hospitalized patients in Belgium infected with the SARS-CoV-2 variant B.1.1.7 and those infected with previously circulating strains. METHODS: The study is conducted within a causal framework to study the severity of SARS-CoV-2 variants by merging surveillance registries in Belgium. Infection with SARS-CoV-2 B.1.1.7 ('exposed') was compared to infection with previously circulating strains ('unexposed') in terms of the manifestation of severe COVID-19, intensive care unit (ICU) admission, or in-hospital mortality. The exposed and unexposed group were matched based on the hospital and the mean ICU occupancy rate during the patient's hospital stay. Other variables identified as confounders in a Directed Acyclic Graph (DAG) were adjusted for using regression analysis. Sensitivity analyses were performed to assess the influence of selection bias, vaccination rollout, and unmeasured confounding. RESULTS: We observed no difference between the exposed and unexposed group in severe COVID-19 disease or in-hospital mortality (RR = 1.15, 95% CI [0.93-1.38] and RR = 0.92, 95% CI [0.62-1.23], respectively). The estimated standardized risk to be admitted in ICU was significantly higher (RR = 1.36, 95% CI [1.03-1.68]) when infected with the B.1.1.7 variant. An age-stratified analysis showed that among the younger age group (≤65 years), the SARS-CoV-2 variant B.1.1.7 was significantly associated with both severe COVID-19 progression and ICU admission. CONCLUSION: This matched observational cohort study did not find an overall increased risk of severe COVID-19 or death associated with B.1.1.7 infection among patients already hospitalized. There was a significant increased risk to be transferred to ICU when infected with the B.1.1.7 variant, especially among the younger age group. However, potential selection biases advocate for more systematic sequencing of samples from hospitalized COVID-19 patients.

The InfAct proposal for a sustainable European health information infrastructure on population health: the Distributed Infrastructure on Population Health (DIPoH).

BACKGROUND: In Europe, data on population health is fragmented, difficult to access, project-based and prone to health information inequalities in terms of availability, accessibility and especially in quality between and within countries. This situation is further exacerbated and exposed by the recent COVID-19 pandemic. The Joint Action on Health Information (InfAct) that builds on previous works of the BRIDGE Health project, carried out collaborative action to set up a sustainable infrastructure for health information in the European Union (EU). The aim of this paper is to present InfAct's proposal for a sustainable research infrastructure, the Distributed Infrastructure on Population Health (DIPoH), which includes the setup of a Health Information Portal on population health to be maintained beyond InfAct's time span. METHODS: The strategy for the proposal was based on three components: scientific initiatives and proposals to improve Health Information Systems (HIS), exploration of technical acceptability and feasibility, and finally obtaining high-level political support.. The technical exploration (Technical Dialogues-TD) was assumed by technical experts proposed by the countries, and political guidance was provided by the Assembly of Members (AoM), which gathered representatives from Ministries of Health and Science of EU/EEA countries. The results from the AoM and the TD were integrated in the sustainability plan compiling all the major outputs of InfAct. RESULTS: The InfAct sustainability plan was organized in three main sections: a proposal of a new research infrastructure on population health (the DIPoH), new health information tools and innovative proposals for HIS, and a comprehensive capacity building programme. These activities were carried out in InfAct and are being further developed in the Population Health Information Research Infrastructure (PHIRI). PHIRI is a practical rollout of DIPoH facilitating and generating the best available evidence for research on health and wellbeing of populations as impacted by COVID-19. CONCLUSIONS: The sustainability plan received wide support from Member States and was recognized to have an added value at EU level. Nevertheless, there were several aspects which still need to be considered for the near future such as: (i) a commitment of stable financial and political support by Member States (MSs), (ii) the availability of resources at regional, national and European level to deal with innovations, and (iii) a more direct involvement from EU and international institutions such as the European Centre for Disease Prevention and Control (ECDC), the World Health Organization (WHO) and the Organisation for Economic Cooperation and Development OECD for providing support and sustainable contributions.

Vaccine effectiveness against onward transmission of SARS-CoV2-infection by variant of concern and time since vaccination, Belgian contact tracing, 2021.

BACKGROUND: During the first half of 2021, we observed high vaccine effectiveness (VE) against SARS-CoV2-infection. The replacement of the alpha-'variant of concern' (VOC) by the delta-VOC and uncertainty about the time course of immunity called for a re-assessment. METHODS: We estimated VE against transmission of infection (VET) from Belgian contact tracing data for high-risk exposure contacts between 26/01/2021 and 14/12/2021 by susceptibility (VEs) and infectiousness of breakthrough cases (VEi) for a complete schedule of Ad26.COV2.S, ChAdOx1, BNT162b2, mRNA-1273 as well as infection-acquired and hybrid immunity. We used a multilevel Bayesian model and adjusted for personal characteristics (age, sex, household), background exposure, calendar week, VOC and time since immunity conferring-event. FINDINGS: VET-estimates were higher for mRNA-vaccines, over 90%, compared to viral vector vaccines: 66% and 80% for Ad26COV2.S and ChAdOx1 respectively (Alpha, 0-50 days after vaccination). Delta was associated with a 40% increase in odds of transmission and a decrease of VEs (72-64%) and especially of VEi (71-46% for BNT162b2). Infection-acquired and hybrid immunity were less affected by Delta. Waning further reduced VET-estimates: from 81% to 63% for BNT162b2 (Delta, 150-200 days after vaccination). We observed lower initial VEi in the age group 65-84 years (32% vs 46% in the age group 45-64 years for BNT162b2) and faster waning. Hybrid immunity waned slower than vaccine-induced immunity. INTERPRETATION: VEi and VEs-estimates, while remaining significant, were reduced by Delta and waned over time. We observed faster waning in the oldest age group. We should seek to improve vaccine-induced protection in older persons and those vaccinated with viral-vector vaccines.

Incidence and Risk Factors of COVID-19 Vaccine Breakthrough Infections: A Prospective Cohort Study in Belgium.

The objective of this study was to investigate the incidence and risk factors associated with COVID-19 vaccine breakthrough infections. We included all persons ≥18 years that had been fully vaccinated against COVID-19 for ≥14 days, between 1 February 2021 and 5 December 2021, in Belgium. The incidence of breakthrough infections (laboratory confirmed SARS-CoV-2-infections) was determined. Factors associated with breakthrough infections were analyzed using COX proportional hazard models. Among 8,062,600 fully vaccinated adults, we identified 373,070 breakthrough infections with an incidence of 11.2 (95%CI 11.2-11.3)/100 person years. Vaccination with Ad26.COV2.S (HR1.54, 95%CI 1.52-1.56) or ChAdOx1 (HR1.68, 95%CI 1.66-1.69) was associated with a higher risk of a breakthrough infection compared to BNT162b2, while mRNA-1273 was associated with a lower risk (HR0.68, 95%CI 0.67-0.69). A prior COVID-19-infection was protective against a breakthrough infection (HR0.23, 95%CI 0.23-0.24), as was an mRNA booster (HR0.44, 95%CI 0.43-0.45). During a breakthrough infection, those who had a prior COVID-19 infection were less likely to have COVID-19 symptoms of almost all types than naïve persons. We identified risk factors associated with breakthrough infections, such as vaccination with adenoviral-vector vaccines, which could help inform future decisions on booster vaccination strategies. A prior COVID-19 infection lowered the risk of breakthrough infections and of having symptoms, highlighting the protective effect of hybrid immunity.

COVID-19 mortality, excess mortality, deaths per million and infection fatality ratio, Belgium, 9 March 2020 to 28 June 2020.

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.

Integrating technical and political views for a sustainable European Distributed Infrastructure on Population Health.

BACKGROUND: Non-Communicable diseases (NCD) are the main contributors to mortality and burden of disease. There is no infrastructure in Europe that could provide health information (HI) on Public Health monitoring and Health Systems Performance (HSP) for research and evidence-informed decision-making. Moreover, there was no EU and European Economic Area Member States (EU/EEA MSs) general consensus, on developing this initiative and guarantee its sustainability. The aim of this study is to analyze the integration of technical and political views made by the Joint Action on Health Information (InfAct; Information for Action) and the results obtained from those activities, in terms of advice and national and institutional support to develop an integrated and sustainable European Distributed Infrastructure on Population Health (DIPoH) for research and evidence-informed policy-making. METHODS: InfAct established two main boards, the Technical Dialogues (TDs) and the Assembly of Members (AoM), to provide a platform for discussion with EU/EEA MSs to establish a sustainable infrastructure for HI: 1) The TDs were composed by national technical experts (NTE) with the aim to discuss and provide feedback about scientific aspects, feasibility and EU-added value of the infrastructure proposed by InfAct. 2) The AoM gathered country representatives from Ministries of Health and Research at the highest political level, with the aim of providing policy-oriented advice for the future political acceptance, support, implementation, and development of InfAct's outcomes including DIPoH. The documentation provided for the meetings consisted in Fact-Sheets, where the main results, new methods and proposals were clearly exposed for discussion and assessment; altogether with more extended information of the DIPoH. The documentation was provided to national representatives within one more before each TD and AoM meeting. The Agenda and methodological approaches for each TD and AoM meeting consisted in the presentations of the InfAct outcomes extending the information provided in the Fact-Sheets; followed by a non-structured interaction, exchange of information, discussion and suggestions by the MSs representatives. The outcomes of the non-structured discussions were collected in Minutes of the TD and AoM meetings, and the final version was obtained with the consensus of all participants. Additionally, structured letters of political support were provided to the AoM representatives, for them to consider providing their MS written support for DIPoH. RESULTS: NTE, within the TDs, considered that DIPoH was useful for technical mutual learning and cooperation among and within countries; although they considered that the technical feasibility to uptake InfAct deliverables at the national and EU level was complex. The AoM focused on political support, resources, and expected MSs returns. The AoM representatives agreed in the interest of setting up an integrated and sustainable HI infrastructure and they considered DIPoH to be well-articulated and defined; although, some of them, expressed some barriers for providing DIPoH political support. The AoM representatives stated that the AoM is the most suitable way to inform EU MSs/ACs about future advances of DIPoH. Both boards provided valuable feedback to develop this infrastructure. Eleven countries and sixteen institutions supported the proposal, either by letters of political support or by signing the Memorandum of Understandings (MoU) and three countries, additionally, provided expression of financial commitment, for DIPoH to be added to the ESFRI 2021 roadmap. CONCLUSIONS: TDs and AoM were key forums to develop, advise, advocate and provide support for a sustainable European research infrastructure for Population Health.

A systematic review and meta-analysis of host genetic factors associated with influenza severity.

BACKGROUND: The severity of influenza disease can range from mild symptoms to severe respiratory failure and can partly be explained by host genetic factors that predisposes the host to severe influenza. Here, we aimed to summarize the current state of evidence that host genetic variants play a role in the susceptibility to severe influenza infection by conducting a systematic review and performing a meta-analysis for all markers with at least three or more data entries. RESULTS: A total of 34 primary human genetic association studies were identified that investigated a total of 20 different genes. The only significant pooled ORs were retrieved for the rs12252 polymorphism: an overall OR of 1.52 (95% CI [1.06-2.17]) for the rs12252-C allele compared to the rs12252-T allele. A stratified analysis by ethnicity revealed opposite effects in different populations. CONCLUSION: With exception for the rs12252 polymorphism, we could not identify specific genetic polymorphisms to be associated with severe influenza infection in a pooled meta-analysis. This advocates for the use of large, hypothesis-free, genome-wide association studies that account for the polygenic nature and the interactions with other host, pathogen and environmental factors.

Conceptual causal framework to assess the effect of SARS-CoV-2 variants on COVID-19 disease severity among hospitalized patients.

BACKGROUND: SARS-CoV-2 strains evolve continuously and accumulate mutations in their genomes over the course of the pandemic. The severity of a SARS-CoV-2 infection could partly depend on these viral genetic characteristics. Here, we present a general conceptual framework that allows to study the effect of SARS-CoV-2 variants on COVID-19 disease severity among hospitalized patients. METHODS: A causal model is defined and visualized using a Directed Acyclic Graph (DAG), in which assumptions on the relationship between (confounding) variables are made explicit. Various DAGs are presented to explore specific study design options and the risk for selection bias. Next, the data infrastructure specific to the COVID-19 surveillance in Belgium is described, along with its strengths and weaknesses for the study of clinical impact of variants. DISCUSSION: A well-established framework that provides a complete view on COVID-19 disease severity among hospitalized patients by combining information from different sources on host factors, viral factors, and healthcare-related factors, will enable to assess the clinical impact of emerging SARS-CoV-2 variants and answer questions that will be raised in the future. The framework shows the complexity related to causal research, the corresponding data requirements, and it underlines important limitations, such as unmeasured confounders or selection bias, inherent to repurposing existing routine COVID-19 data registries. TRIAL REGISTRATION: Each individual research project within the current conceptual framework will be prospectively registered in Open Science Framework (OSF identifier: https://doi.org/10.17605/OSF.IO/UEF29 ). OSF project created on 18 May 2021.

Vaccine effectiveness against infection and onwards transmission of COVID-19: Analysis of Belgian contact tracing data, January-June 2021.

In Belgium, high-risk contacts of an infected person were offered PCR-testing irrespective of their vaccination status. We estimated vaccine effectiveness (VE) against infection and onwards transmission, controlling for previous infections, household-exposure and temporal trends. We included 301,741 tests from 25 January to 24 June 2021. Full-schedule vaccination was associated with significant protection against infection. In addition, mRNA-vaccines reduced onward transmission: VE-estimates increased to >90% when index and contact were fully vaccinated. The small number of viral-vector vaccines included limited interpretability.

Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence-Belgium as a study case.

BACKGROUND: The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection. METHODS: To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio-temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence. RESULTS: Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence. CONCLUSION: Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.

The role of organizational characteristics on the outcome of COVID-19 patients admitted to the ICU in Belgium.

BACKGROUND: Several studies have investigated the predictors of in-hospital mortality for COVID-19 patients who need to be admitted to the Intensive Care Unit (ICU). However, no data on the role of organizational issues on patients' outcome are available in this setting. The aim of this study was therefore to assess the role of surge capacity organisation on the outcome of critically ill COVID-19 patients admitted to ICUs in Belgium. METHODS: We conducted a retrospective analysis of in-hospital mortality in Belgian ICU COVID-19 patients via the national surveillance database. Non-survivors at hospital discharge were compared to survivors using multivariable mixed effects logistic regression analysis. Specific analyses including only patients with invasive ventilation were performed. To assess surge capacity, data were merged with administrative information on the type of hospital, the baseline number of recognized ICU beds, the number of supplementary beds specifically created for COVID-19 ICU care and the "ICU overflow" (i.e. a time-varying ratio between the number of occupied ICU beds by confirmed and suspected COVID-19 patients divided by the number of recognized ICU beds reserved for COVID-19 patients; ICU overflow was present when this ratio is ≥ 1.0). FINDINGS: Over a total of 13,612 hospitalised COVID-19 patients with admission and discharge forms registered in the surveillance period (March, 1 to August, 9 2020), 1903 (14.0%) required ICU admission, of whom 1747 had available outcome data. Non-survivors (n = 632, 36.1%) were older and had more frequently various comorbid diseases than survivors. In the multivariable analysis, ICU overflow, together with older age, presence of comorbidities, shorter delay between symptom onset and hospital admission, absence of hydroxychloroquine therapy and use of invasive mechanical ventilation and of ECMO, was independently associated with an increased in-hospital mortality. Similar results were found in in in the subgroup of invasively ventilated patients. In addition, the proportion of supplementary beds specifically created for COVID-19 ICU care to the previously existing total number of ICU beds was associated with increased in-hospital mortality among invasively ventilated patients. The model also indicated a significant between-hospital difference in in-hospital mortality, not explained by the available patients and hospital characteristics. INTERPRETATION: Surge capacity organisation as reflected by ICU overflow or the creation of COVID-19 specific supplementary ICU beds were found to negatively impact ICU patient outcomes. FUNDING: No funding source was available for this study.

All-cause mortality supports the COVID-19 mortality in Belgium and comparison with major fatal events of the last century.

BACKGROUND: The COVID-19 mortality rate in Belgium has been ranked among the highest in the world. To assess the appropriateness of the country's COVID-19 mortality surveillance, that includes long-term care facilities deaths and deaths in possible cases, the number of COVID-19 deaths was compared with the number of deaths from all-cause mortality. Mortality during the COVID-19 pandemic was also compared with historical mortality rates from the last century including those of the Spanish influenza pandemic. METHODS: Excess mortality predictions and COVID-19 mortality data were analysed for the period March 10th to June 21st 2020. The number of COVID-19 deaths and the COVID-19 mortality rate per million were calculated for hospitals, nursing homes and other places of death, according to diagnostic status (confirmed/possible infection). To evaluate historical mortality, monthly mortality rates were calculated from January 1900 to June 2020. RESULTS: Nine thousand five hundred ninety-one COVID-19 deaths and 39,076 deaths from all-causes were recorded, with a correlation of 94% (Spearman's rho, p < 0,01). During the period with statistically significant excess mortality (March 20th to April 28th; total excess mortality 64.7%), 7917 excess deaths were observed among the 20,159 deaths from all-causes. In the same period, 7576 COVID-19 deaths were notified, indicating that 96% of the excess mortality were likely attributable to COVID-19. The inclusion of deaths in nursing homes doubled the COVID-19 mortality rate, while adding deaths in possible cases increased it by 27%. Deaths in laboratory-confirmed cases accounted for 69% of total COVID-19-related deaths and 43% of in-hospital deaths. Although the number of deaths was historically high, the monthly mortality rate was lower in April 2020 compared to the major fatal events of the last century. CONCLUSIONS: Trends in all-cause mortality during the first wave of the epidemic was a key indicator to validate the Belgium's high COVID-19 mortality figures. A COVID-19 mortality surveillance limited to deaths from hospitalised and selected laboratory-confirmed cases would have underestimated the magnitude of the epidemic. Excess mortality, daily and monthly number of deaths in Belgium were historically high classifying undeniably the first wave of the COVID-19 epidemic as a fatal event.

Low-dose hydroxychloroquine therapy and mortality in hospitalised patients with COVID-19: a nationwide observational study of 8075 participants.

Hydroxychloroquine (HCQ) has been largely used and investigated as therapy for COVID-19 across various settings at a total dose usually ranging from 2400 mg to 9600 mg. In Belgium, off-label use of low-dose HCQ (total 2400 mg over 5 days) was recommended for hospitalised patients with COVID-19. We conducted a retrospective analysis of in-hospital mortality in the Belgian national COVID-19 hospital surveillance data. Patients treated either with HCQ monotherapy and supportive care (HCQ group) were compared with patients treated with supportive care only (no-HCQ group) using a competing risks proportional hazards regression with discharge alive as competing risk, adjusted for demographic and clinical features with robust standard errors. Of 8075 patients with complete discharge data on 24 May 2020 and diagnosed before 1 May 2020, 4542 received HCQ in monotherapy and 3533 were in the no-HCQ group. Death was reported in 804/4542 (17.7%) and 957/3533 (27.1%), respectively. In the multivariable analysis, mortality was lower in the HCQ group compared with the no-HCQ group [adjusted hazard ratio (aHR) = 0.684, 95% confidence interval (CI) 0.617-0.758]. Compared with the no-HCQ group, mortality in the HCQ group was reduced both in patients diagnosed ≤5 days (n = 3975) and >5 days (n = 3487) after symptom onset [aHR = 0.701 (95% CI 0.617-0.796) and aHR = 0.647 (95% CI 0.525-0.797), respectively]. Compared with supportive care only, low-dose HCQ monotherapy was independently associated with lower mortality in hospitalised patients with COVID-19 diagnosed and treated early or later after symptom onset.