Predicting COVID-19 progression in hospitalized patients in Belgium from a multi-state model.

Objectives: To adopt a multi-state risk prediction model for critical disease/mortality outcomes among hospitalised COVID-19 patients using nationwide COVID-19 hospital surveillance data in Belgium. Materials and methods: Information on 44,659 COVID-19 patients hospitalised between March 2020 and June 2021 with complete data on disease outcomes and candidate predictors was used to adopt a multi-state, multivariate Cox model to predict patients' probability of recovery, critical [transfer to intensive care units (ICU)] or fatal outcomes during hospital stay. Results: Median length of hospital stay was 9 days (interquartile range: 5-14). After admission, approximately 82% of the COVID-19 patients were discharged alive, 15% of patients were admitted to ICU, and 15% died in the hospital. The main predictors of an increased probability for recovery were younger age, and to a lesser extent, a lower number of prevalent comorbidities. A patient's transition to ICU or in-hospital death had in common the following predictors: high levels of c-reactive protein (CRP) and lactate dehydrogenase (LDH), reporting lower respiratory complaints and male sex. Additionally predictors for a transfer to ICU included middle-age, obesity and reporting loss of appetite and staying at a university hospital, while advanced age and a higher number of prevalent comorbidities for in-hospital death. After ICU, younger age and low levels of CRP and LDH were the main predictors for recovery, while in-hospital death was predicted by advanced age and concurrent comorbidities. Conclusion: As one of the very few, a multi-state model was adopted to identify key factors predicting COVID-19 progression to critical disease, and recovery or death.

Predicting COVID-19 progression in hospitalized patients in Belgium from a multi-state model

Objectives To adopt a multi-state risk prediction model for critical disease/mortality outcomes among hospitalised COVID-19 patients using nationwide COVID-19 hospital surveillance data in Belgium. Materials and methods Information on 44,659 COVID-19 patients hospitalised between March 2020 and June 2021 with complete data on disease outcomes and candidate predictors was used to adopt a multi-state, multivariate Cox model to predict patients' probability of recovery, critical [transfer to intensive care units (ICU)] or fatal outcomes during hospital stay. Results Median length of hospital stay was 9 days (interquartile range: 5–14). After admission, approximately 82% of the COVID-19 patients were discharged alive, 15% of patients were admitted to ICU, and 15% died in the hospital. The main predictors of an increased probability for recovery were younger age, and to a lesser extent, a lower number of prevalent comorbidities. A patient's transition to ICU or in-hospital death had in common the following predictors: high levels of c-reactive protein (CRP) and lactate dehydrogenase (LDH), reporting lower respiratory complaints and male sex. Additionally predictors for a transfer to ICU included middle-age, obesity and reporting loss of appetite and staying at a university hospital, while advanced age and a higher number of prevalent comorbidities for in-hospital death. After ICU, younger age and low levels of CRP and LDH were the main predictors for recovery, while in-hospital death was predicted by advanced age and concurrent comorbidities. Conclusion As one of the very few, a multi-state model was adopted to identify key factors predicting COVID-19 progression to critical disease, and recovery or death.

Challenges of data sharing in European Covid-19 projects: A learning opportunity for advancing pandemic preparedness and response.

The COVID-19 pandemic saw a massive investment into collaborative research projects with a focus on producing data to support public health decisions. We relay our direct experience of four projects funded under the Horizon2020 programme, namely ReCoDID, ORCHESTRA, unCoVer and SYNCHROS. The projects provide insight into the complexities of sharing patient level data from observational cohorts. We focus on compliance with the General Data Protection Regulation (GDPR) and ethics approvals when sharing data across national borders. We discuss procedures for data mapping; submission of new international codes to standards organisation; federated approach; and centralised data curation. Finally, we put forward recommendations for the development of guidelines for the application of GDPR in case of major public health threats; mandatory standards for data collection in funding frameworks; training and capacity building for data owners; cataloguing of international use of metadata standards; and dedicated funding for identified critical areas.

Estimated Global Proportions of Individuals With Persistent Fatigue, Cognitive, and Respiratory Symptom Clusters Following Symptomatic COVID-19 in 2020 and 2021.

Importance: Some individuals experience persistent symptoms after initial symptomatic SARS-CoV-2 infection (often referred to as Long COVID). Objective: To estimate the proportion of males and females with COVID-19, younger or older than 20 years of age, who had Long COVID symptoms in 2020 and 2021 and their Long COVID symptom duration. Design, Setting, and Participants: Bayesian meta-regression and pooling of 54 studies and 2 medical record databases with data for 1.2 million individuals (from 22 countries) who had symptomatic SARS-CoV-2 infection. Of the 54 studies, 44 were published and 10 were collaborating cohorts (conducted in Austria, the Faroe Islands, Germany, Iran, Italy, the Netherlands, Russia, Sweden, Switzerland, and the US). The participant data were derived from the 44 published studies (10 501 hospitalized individuals and 42 891 nonhospitalized individuals), the 10 collaborating cohort studies (10 526 and 1906), and the 2 US electronic medical record databases (250 928 and 846 046). Data collection spanned March 2020 to January 2022. Exposures: Symptomatic SARS-CoV-2 infection. Main Outcomes and Measures: Proportion of individuals with at least 1 of the 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after SARS-CoV-2 infection in 2020 and 2021, estimated separately for hospitalized and nonhospitalized individuals aged 20 years or older by sex and for both sexes of nonhospitalized individuals younger than 20 years of age. Results: A total of 1.2 million individuals who had symptomatic SARS-CoV-2 infection were included (mean age, 4-66 years; males, 26%-88%). In the modeled estimates, 6.2% (95% uncertainty interval [UI], 2.4%-13.3%) of individuals who had symptomatic SARS-CoV-2 infection experienced at least 1 of the 3 Long COVID symptom clusters in 2020 and 2021, including 3.2% (95% UI, 0.6%-10.0%) for persistent fatigue with bodily pain or mood swings, 3.7% (95% UI, 0.9%-9.6%) for ongoing respiratory problems, and 2.2% (95% UI, 0.3%-7.6%) for cognitive problems after adjusting for health status before COVID-19, comprising an estimated 51.0% (95% UI, 16.9%-92.4%), 60.4% (95% UI, 18.9%-89.1%), and 35.4% (95% UI, 9.4%-75.1%), respectively, of Long COVID cases. The Long COVID symptom clusters were more common in women aged 20 years or older (10.6% [95% UI, 4.3%-22.2%]) 3 months after symptomatic SARS-CoV-2 infection than in men aged 20 years or older (5.4% [95% UI, 2.2%-11.7%]). Both sexes younger than 20 years of age were estimated to be affected in 2.8% (95% UI, 0.9%-7.0%) of symptomatic SARS-CoV-2 infections. The estimated mean Long COVID symptom cluster duration was 9.0 months (95% UI, 7.0-12.0 months) among hospitalized individuals and 4.0 months (95% UI, 3.6-4.6 months) among nonhospitalized individuals. Among individuals with Long COVID symptoms 3 months after symptomatic SARS-CoV-2 infection, an estimated 15.1% (95% UI, 10.3%-21.1%) continued to experience symptoms at 12 months. Conclusions and Relevance: This study presents modeled estimates of the proportion of individuals with at least 1 of 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after symptomatic SARS-CoV-2 infection.

Burden of Disease of COVID-19: Strengthening the Collaboration for National Studies.

Objectives: Quantifying the combined impact of morbidity and mortality is a key enabler to assessing the impact of COVID-19 across countries and within countries relative to other diseases, regions, or demographics. Differences in methods, data sources, and definitions of mortality due to COVID-19 may hamper comparisons. We describe efforts to support countries in estimating the national-level burden of COVID-19 using disability-adjusted life years. Methods: The European Burden of Disease Network developed a consensus methodology, as well as a range of capacity-building activities to support burden of COVID-19 studies. These activities have supported 11 national studies so far, with study periods between January 2020 and December 2021. Results: National studies dealt with various data gaps and different assumptions were made to face knowledge gaps. Still, they delivered broadly comparable results that allow for interpretation of consistencies, as well as differences in the quantified direct health impact of the pandemic. Discussion: Harmonized efforts and methodologies have allowed for comparable estimates and communication of results. Future studies should evaluate the impact of interventions, and unravel the indirect health impact of the COVID-19 crisis.

Burden of Disease of COVID-19: Strengthening the Collaboration for National Studies

Objectives Quantifying the combined impact of morbidity and mortality is a key enabler to assessing the impact of COVID-19 across countries and within countries relative to other diseases, regions, or demographics. Differences in methods, data sources, and definitions of mortality due to COVID-19 may hamper comparisons. We describe efforts to support countries in estimating the national-level burden of COVID-19 using disability-adjusted life years. Methods The European Burden of Disease Network developed a consensus methodology, as well as a range of capacity-building activities to support burden of COVID-19 studies. These activities have supported 11 national studies so far, with study periods between January 2020 and December 2021. Results National studies dealt with various data gaps and different assumptions were made to face knowledge gaps. Still, they delivered broadly comparable results that allow for interpretation of consistencies, as well as differences in the quantified direct health impact of the pandemic. Discussion Harmonized efforts and methodologies have allowed for comparable estimates and communication of results. Future studies should evaluate the impact of interventions, and unravel the indirect health impact of the COVID-19 crisis.

Insights into the association of ACEIs/ARBs use and COVID-19 prognosis: a multistate modelling study of nationwide hospital surveillance data from Belgium

ObjectivesThe widespread use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) by patients with chronic conditions raised early concerns on the potential exacerbation of COVID-19 severity and fatality. Previous studies addressing this question have used standard methods that may lead to biased estimates when analysing hospital data because of the presence of competing events and event-related dependency. We investigated the association of ACEIs/ARBs’ use with COVID-19 disease outcomes using time-to-event data in a multistate setting to account for competing events and minimise bias.SettingNationwide surveillance data from 119 Belgian hospitals.ParticipantsMedical records of 10 866 patients hospitalised from 14 March 2020to 14 June 2020 with a confirmed SARS-CoV-19 infection and information about ACEIs/ARBs’ use.Primary outcome measureMultistate, multivariate Cox-Markov models were used to estimate the hazards of patients transitioning through health states from admission to discharge or death, along with transition probabilities calculated by combining the baseline cumulative hazard and regression coefficients.ResultsAfter accounting for potential confounders, there was no discernable association between ACEIs/ARBs’ use and transfer to intensive care unit (ICU). Contrastingly, for patients without ICU transfer, ACEIs/ARBs’ use was associated with a modest increase in recovery (HR 1.07, 95% CI 1.01 to 1.13, p=0.027) and reduction in fatality (HR 0.83, 95% CI 0.75 to 0.93, p=0.001) transitions. For patients transferred to ICU admission, no evidence of an association between ACEIs/ARBs’ use and recovery (HR 1.16, 95% CI 0.97 to 1.38, p=0.098) or in-hospital death (HR 0.91, 95% CI 0.73 to 1.12, p=0.381) was observed. Male gender and older age were significantly associated with higher risk of ICU admission or death. Chronic cardiometabolic comorbidities were also associated with less recovery.ConclusionsFor the first time, a multistate model was used to address magnitude and direction of the association of ACEIs/ARBs’ use on COVID-19 progression. By minimising bias, this study provided a robust indication of a protective, although modest, association with recovery and survival.

Food Choice Motives and COVID-19 in Belgium.

To investigate the main motives driving dietary intake changes potentially introduced by preventive measures to address the pandemic, an online survey, using a 36-item Food Choice Questionnaire applied for the period before (the year 2019) and during (2020-2021) the pandemic, was distributed between July and October 2021 among adult residents from Belgium. A total of 427 eligible respondents, the majority Dutch-speaking, were included for analyses. The importance of nine motives for food choices, including health, mood, convenience, sensory appeal, natural content, price, weight control, familiarity and ethical concerns, was assessed by scoring from 1 to 5, and comparing mean scores from the during period with the before period. Sensory appeal was the most important food choice motive before (mean score of 4.02 ± 0.51) and during (3.98 ± 0.48) the pandemic. Convenience and health also ranked among the main motives, with health observed to become more important during the pandemic (3.69 ± 0.60 during vs. 3.64 ± 0.59 before). Additionally, mean scores of mood (3.41 ± 0.71 vs. 3.32 ± 0.58), natural content (3.35 ± 0.84 vs. 3.26 ± 0.85) and weight control (3.33 ± 0.79 vs. 3.25 ± 0.76) were significantly higher during as compared to before. The extent of change in the level of importance for natural content was smaller with increasing age, and for health larger for urban areas, but for other motives there were no significant differences across population subgroups. Changes in the level of importance were observed in both directions, while a moderate share of respondents declared no change, suggesting some persistence of food choice motives. Further activities within public health monitoring should be considered to fully understand the COVID-19 implications on food choice motives together with people's food behaviors and consumption.

The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic.

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI's application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act swiftly and thereby enhance containment of outbreaks.

Unravelling data for rapid evidence-based response to COVID-19: a summary of the unCoVer protocol.

INTRODUCTION: unCoVer-Unravelling data for rapid evidence-based response to COVID-19-is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic. METHODS AND ANALYSIS: From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients' baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded. ETHICS AND DISSEMINATION: After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer's activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.

Evaluation of the Food Choice Motives before and during the COVID-19 Pandemic: A Cross-Sectional Study of 1232 Adults from Croatia.

The coronavirus disease 2019 pandemic brought changes to almost every segment of our lives, including dietary habits. We present one among several studies, and the first on the Croatian population, aiming at investigating changes of food choice motives before and during the pandemic. The study was performed in June 2021 as an online-based survey, using a 36-item Food Choice Questionnaire applied for both the periods before and during the pandemic. The final sample consisted of 1232 adults living in Croatia. Sensory appeal was ranked as the number one most important food choice motive before, whereas health was ranked as the number one most important food choice motive during the pandemic. Ethical concern was reported as the least important food choice motive both before and during the pandemic. In women, natural content (p = 0.002), health, convenience, price, weight control, familiarity, and ethical concern (all p < 0.001) became more important during the pandemic, while price (p = 0.009), weight control, familiarity, and ethical concern (all p < 0.001) became more relevant for men. All together, these can be considered favorable changes toward optimal diets and may result in beneficial influences on health and lifestyle. Education strategies and efficiently tackling misinformation are prerequisites for informed food choice, which will ensure long-lasting positive effects of such changes.

The Burden of Malnutrition and Fatal COVID-19: A Global Burden of Disease Analysis.

Background: Although reasonable to assume, it is not yet clear whether malnourished countries are at higher risk for severe or fatal coronavirus disease 2019 (COVID-19). This study aims to identify the countries where prevalent malnutrition may be a driving factor for fatal disease after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods: Using estimates from the Global Burden of Disease 2019, country-level burden of malnutrition was quantified using four indicators: death rates for child growth failure (underweight, stunting, and/or wasting) and years lived with disability (YLD) attributed to iron and vitamin A deficiencies and high body mass index (BMI). Global mortality descriptors of the ongoing COVID-19 pandemic were extracted from the European Centre for Disease Prevention and Control, and case fatality ratios (CFRs) were calculated introducing a lag time of 10 weeks after the first death of a confirmed case. Bivariate analyses for 172 countries were carried out for malnutrition indicators and fatal COVID-19. Correlations between burden indicators were characterized by Spearman's rank correlation coefficients (ρ) and visually by scatterplots. Restricted cubic splines and underlying negative binomial regressions adjusted for countries' age-structure, prevalent chronic comorbidities related to COVID-19, population density, and income group were used to explore non-linear relationships. Results: Stratified by the World Bank income group, a moderate positive association between YLD rates for iron deficiency and CFRs for COVID-19 was observed for low-income countries (ρ = 0.60, p = 0.027), whereas no clear indications for the association with child growth failure, vitamin A deficiency, or high BMI were found (ρ < 0.30). Countries ranking high on at least three malnutrition indicators and presenting also an elevated CFR for COVID-19 are sub-Saharan African countries, namely, Angola, Burkina Faso, Chad, Liberia, Mali, Niger, Sudan, and Tanzania, as well as Yemen and Guyana. Conclusions: Population-level malnutrition appears to be related to increased rates of fatal COVID-19 in areas with an elevated burden of undernutrition, such as countries in the Sahel strip. COVID-19 response plans in malnourished countries, vulnerable to fatal COVID-19, should incorporate food security, nutrition, and social protection as a priority component in order to reduce COVID-19 fatality.

Correction to: Population vulnerability to COVID-19 in Europe: a burden of disease analysis.

[This corrects the article DOI: 10.1186/s13690-020-00433-y.].

Population vulnerability to COVID-19 in Europe: a burden of disease analysis.

BACKGROUND: Evidence has emerged showing that elderly people and those with pre-existing chronic health conditions may be at higher risk of developing severe health consequences from COVID-19. In Europe, this is of particular relevance with ageing populations living with non-communicable diseases, multi-morbidity and frailty. Published estimates of Years Lived with Disability (YLD) from the Global Burden of Disease (GBD) study help to characterise the extent of these effects. Our aim was to identify the countries across Europe that have populations at highest risk from COVID-19 by using estimates of population age structure and YLD for health conditions linked to severe illness from COVID-19. METHODS: Population and YLD estimates from GBD 2017 were extracted for 45 countries in Europe. YLD was restricted to a list of specific health conditions associated with being at risk of developing severe consequences from COVID-19 based on guidance from the United Kingdom Government. This guidance also identified individuals aged 70 years and above as being at higher risk of developing severe health consequences. Study outcomes were defined as: (i) proportion of population aged 70 years and above; and (ii) rate of YLD for COVID-19 vulnerable health conditions across all ages. Bivariate groupings were established for each outcome and combined to establish overall population-level vulnerability. RESULTS: Countries with the highest proportions of elderly residents were Italy, Greece, Germany, Portugal and Finland. When assessments of population-level YLD rates for COVID-19 vulnerable health conditions were made, the highest rates were observed for Bulgaria, Czechia, Croatia, Hungary and Bosnia and Herzegovina. A bivariate analysis indicated that the countries at high-risk across both measures of vulnerability were: Bulgaria; Portugal; Latvia; Lithuania; Greece; Germany; Estonia; and Sweden. CONCLUSION: Routine estimates of population structures and non-fatal burden of disease measures can be usefully combined to create composite indicators of vulnerability for rapid assessments, in this case to severe health consequences from COVID-19. Countries with available results for sub-national regions within their country, or national burden of disease studies that also use sub-national levels for burden quantifications, should consider using non-fatal burden of disease estimates to estimate geographical vulnerability to COVID-19.