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Article ; Online: Did an effect of kidney transplantation on COVID-19 mortality go unnoticed due to selection bias?

Neyens, Thomas

Transplant international : official journal of the European Society for Organ Transplantation

2021 Volume 34, Issue 5, Page(s) 773–775

MeSH term(s)	COVID-19 ; Humans ; Kidney Transplantation/adverse effects ; Organ Transplantation ; Risk Factors ; SARS-CoV-2 ; Selection Bias
Language	English
Publishing date	2021-05-21
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	639435-8
ISSN	1432-2277 ; 0934-0874
ISSN (online)	1432-2277
ISSN	0934-0874
DOI	10.1111/tri.13880
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Article ; Online: Simulation-based assessment of the performance of hierarchical abundance estimators for camera trap surveys of unmarked species

Bollen Martijn / Casaer Jim / Beenaerts Natalie / Neyens Thomas

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 13

Abstract: Abstract Knowledge on animal abundances is essential in ecology, but is complicated by low detectability of many species. This has led to a widespread use of hierarchical models (HMs) for species abundance, which are also commonly applied in the context ... ...

Abstract	Abstract Knowledge on animal abundances is essential in ecology, but is complicated by low detectability of many species. This has led to a widespread use of hierarchical models (HMs) for species abundance, which are also commonly applied in the context of nature areas studied by camera traps (CTs). However, the best choice among these models is unclear, particularly based on how they perform in the face of complicating features of realistic populations, including: movements relative to sites, multiple detections of unmarked individuals within a single survey, and low detectability. We conducted a simulation-based comparison of three HMs (Royle-Nichols, binomial N-mixture and Poisson N-mixture model) by generating groups of unmarked individuals moving according to a bivariate Ornstein–Uhlenbeck process, monitored by CTs. Under a range of simulated scenarios, none of the HMs consistently yielded accurate abundances. Yet, the Poisson N-mixture model performed well when animals did move across sites, despite accidental double counting of individuals. Absolute abundances were better captured by Royle-Nichols and Poisson N-mixture models, while a binomial N-mixture model better estimated the actual number of individuals that used a site. The best performance of all HMs was observed when estimating relative trends in abundance, which were captured with similar accuracy across these models.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Comparison of Items and Constructs of Standardized Health-Related Quality of Life and Mental Well-Being Measures.

Mao, Zhuxin / Crèvecoeur, Jonas / Pepermans, Koen / Kind, Paul / Neyens, Thomas / Beutels, Philippe

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research

2024 Volume 27, Issue 4, Page(s) 478–489

Abstract: Objectives: This study aimed to explore the internal constructs of the concepts being measured by EQ-5D-5L (a health-related quality of life measure that can produce preference-based utility values) and the 12-item General Health Questionnaire (GHQ-12, ... ...

Abstract	Objectives: This study aimed to explore the internal constructs of the concepts being measured by EQ-5D-5L (a health-related quality of life measure that can produce preference-based utility values) and the 12-item General Health Questionnaire (GHQ-12, a mental well-being measure) and to understand to what extent the items of EQ-5D-5L and GHQ-12 associate with each other. Methods: We used data from 12 701 respondents participating in a Belgian survey in 2022. Correlation coefficients between GHQ-12 and EQ-5D-5L were calculated at both the aggregate and item levels. Multidimensional scaling, exploratory factor analysis, and regression models were performed to investigate the underlying constructs that are associated with the items. Results: Despite a moderate correlation (0.39) between the EQ-5D-5L and GHQ-12 total scores, only a trivial or weak correlation (<0.3) was observed between the first 4 EQ-5D-5L items and any GHQ-12 item. Multidimensional scaling and exploratory factor analysis showed the first 4 EQ-5D-5L dimensions were clustered together with EuroQol visual analog scale and positively phrased GHQ-12 items were close to each other, whereas EQ-anxiety/depression and negatively phrased GHQ-12 items were grouped with overall life satisfaction. In the regression models, not all GHQ-12 items had a significant coefficient to predict EQ-5D-5L responses. Conclusions: To the best of our knowledge, we present the first comparison of items and underlying constructs of GHQ-12 and EQ-5D-5L. The results showed that GHQ-12 can only partially predict the responses of EQ-5D-5L and the 2 instruments measure different constructs. Researchers should carefully consider conceptual legitimacy while applying the mapping technique and consider sensitivity analyses for the mapping estimates.
MeSH term(s)	Humans ; Quality of Life ; Psychometrics ; Mental Health ; Surveys and Questionnaires ; Depression ; Health Status
Language	English
Publishing date	2024-01-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	1471745-1
ISSN	1524-4733 ; 1098-3015
ISSN (online)	1524-4733
ISSN	1098-3015
DOI	10.1016/j.jval.2024.01.005
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Article ; Online: A linear mixed model to estimate COVID‐19‐induced excess mortality

Verbeeck, Johan / Faes, Christel / Neyens, Thomas / Hens, Niel / Verbeke, Geert / Deboosere, Patrick / Molenberghs, Geert

Biometrics. 2023 Mar., v. 79, no. 1 p.417-425

2023

Abstract: 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, ... ...

Abstract	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.
Keywords	COVID-19 infection ; autocorrelation ; mortality ; pandemic ; statistical models ; Belgium ; Netherlands
Language	English
Dates of publication	2023-03
Size	p. 417-425.
Publishing place	John Wiley & Sons, Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	213543-7
ISSN	0099-4987 ; 0006-341X
ISSN	0099-4987 ; 0006-341X
DOI	10.1111/biom.13578
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Article ; Online: The doubling effect of COVID-19 cases on key health indicators.

Petrof, Oana / Fajgenblat, Maxime / Neyens, Thomas / Molenberghs, Geert / Faes, Christel

PloS one

2022 Volume 17, Issue 11, Page(s) e0275523

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; COVID-19/epidemiology ; COVID-19/prevention & control ; Pandemics/prevention & control ; Public Health ; Administrative Personnel ; Europe/epidemiology
Language	English
Publishing date	2022-11-23
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0275523
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The COVID-19 wave in Belgium during the Fall of 2020 and its association with higher education.

Natalia, Yessika Adelwin / Faes, Christel / Neyens, Thomas / Molenberghs, Geert

PloS one

2022 Volume 17, Issue 2, Page(s) e0264516

Abstract: 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, ...

Abstract	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.
MeSH term(s)	Adolescent ; Adult ; Belgium ; COVID-19/epidemiology ; Humans ; Incidence ; Pandemics ; Prevalence ; Students ; Universities ; Young Adult
Language	English
Publishing date	2022-02-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0264516
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Fractal dimension based geographical clustering of COVID-19 time series data.

Natalia, Yessika Adelwin / Faes, Christel / Neyens, Thomas / Chys, Pieter / Hammami, Naïma / Molenberghs, Geert

Scientific reports

2023 Volume 13, Issue 1, Page(s) 4322

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Fractals ; Time Factors ; COVID-19/epidemiology ; Geography ; Belgium/epidemiology
Language	English
Publishing date	2023-03-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-30948-7
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Article ; Online: Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium.

Natalia, Yessika Adelwin / Faes, Christel / Neyens, Thomas / Hammami, Naïma / Molenberghs, Geert

Frontiers in public health

2023 Volume 11, Page(s) 1249141

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Humans ; Aged ; Fractals ; Belgium/epidemiology ; COVID-19/epidemiology ; Cluster Analysis ; Risk Factors
Language	English
Publishing date	2023-11-03
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1249141
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Article ; Online: Measuring individual‐level trait diversity: a critical assessment of methods

Olusoji, Oluwafemi D. / Barabás, György / Spaak, Jurg W. / Fontana, Simone / Neyens, Thomas / De Laender, Frederik / Aerts, Marc

Oikos. 2023 Apr., v. 2023, no. 4 p.e09178-

2023

Abstract: Individual‐level trait diversity has been identified as an essential component of trait diversity (TD), influencing community assembly and structure. Traditionally, one employs trait diversity indices to measure facets of individual‐level trait diversity ...

Abstract	Individual‐level trait diversity has been identified as an essential component of trait diversity (TD), influencing community assembly and structure. Traditionally, one employs trait diversity indices to measure facets of individual‐level trait diversity (divergence, richness and evenness). However, the application of species‐level trait diversity indices to individual‐level traits data and their implications have not been adequately studied. Thus, we examined the possible challenges of using four commonly used multi‐trait TD indices: Rao's quadratic entropy (Rao), functional dispersion (FDis), functional evenness (FEve) and functional richness (FRic); two indices primarily developed to measure individual‐level trait diversity: trait evenness distribution (TED‐for evenness) and trait onion peeling (TOP‐for richnness); and a modified version of TED (TEDM‐for evenness). Additionally, we considered an index that integrates both evenness and richness by generalizing ordinary Hill indices for traits (coined HIT). We measured individual‐level trait diversity with these indices using simulated traits data and experimental data from a growth experiment with cyanobacteria. Comparing the observed trends from the indices with the expected trends, we observed that only the trait divergence indices (FDis and Rao) produced the expected trends in the simulation scenarios and experimental data. TED and TEDM are not robust against the number of individuals used, and FEve is not sensitive to some changes in the location of individuals in the trait space. Also, TOP proved to be a discontinuous function dependent on the number of individuals, and FRic did not produce the anticipated trend when changes in the trait space did not affect the edges of the trait space. HIT did produce the anticipated changes, but it was only reliable when many individuals were sampled. In summary, applying these individual‐level trait diversity indices to quantify anything except trait divergence may lead to misinterpretation of the original situation of trait distribution in the trait space if their specific properties are not adequately considered.
Keywords	Cyanobacteria ; community structure ; dispersions ; entropy ; onion peels ; sampling
Language	English
Dates of publication	2023-04
Publishing place	Blackwell Publishing Ltd
Document type	Article ; Online
Note	JOURNAL ARTICLE
ZDB-ID	207359-6
ISSN	0030-1299
ISSN	0030-1299
DOI	10.1111/oik.09178
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Article: Change in COVID19 outbreak pattern following vaccination in long-term care facilities in Flanders, Belgium

Crèvecoeur, Jonas / Hens, Niel / Neyens, Thomas / Larivière, Ynke / Verhasselt, Bruno / Masson, Hanna / Theeten, Heidi

Vaccine. 2022 Sept. 07,

2022

Abstract: Long term care facilities for elderly (LTCFs) in Europe encountered a high disease burden at the start of the COVID-19 pandemic. Therefore, these facilities were the first to receive COVID-19 vaccines in many European countries. A limited COVID-19 ... ...

Abstract	Long term care facilities for elderly (LTCFs) in Europe encountered a high disease burden at the start of the COVID-19 pandemic. Therefore, these facilities were the first to receive COVID-19 vaccines in many European countries. A limited COVID-19 vaccine supply early 2021 resulted in a majority of residents and healthcare workers (HCWs) in LTCFs being vaccinated compared to a minority in the general population. This study exploits this imbalance to assess the efficiency of COVID-19 vaccination in containing outbreaks in LTCFs. Exploratory statistics were performed using data from a COVID-19 surveillance system covering all 842 LTCFs in Flanders (the northern region of Belgium). The number and size of COVID-19 outbreaks in LTCFs were compared (1) before and after introducing vaccines and (2) with the status of the pandemic in the general population. Based on individual data from 15 LTCFs, the infection rate and symptoms of vaccinated and unvaccinated residents and HCWs were compared during a COVID-19 outbreak. 95.8% of the residents and 90.9% of the HCWs in Flemish LTCFs were vaccinated before May 30, 2021. Before vaccine introduction, residents in LTCFs were 10 times more likely to test positive for COVID-19 than the general population of Flanders. This ratio reversed after vaccination. Furthermore, after vaccination fewer and shorter outbreaks were observed involving fewer residents. During these outbreaks, vaccinated and unvaccinated residents were equally likely to test positive, but positive vaccinated residents were less likely to develop severe symptoms. In contrast, unvaccinated HCWs were more likely to test positive. In the first half of 2021, two-dose vaccination was highly efficient in preventing and containing outbreaks in LTCFs, reducing COVID-19 hospitalizations and deaths. The high likelihood of unvaccinated HCWs to be involved in COVID-19 outbreaks in vaccinated LTCFs emphasizes the importance of vaccinating HCWs.
Keywords	COVID-19 infection ; burden of disease ; elderly ; long term care ; monitoring ; pandemic ; statistics ; vaccination ; vaccines ; Belgium
Language	English
Dates of publication	2022-0907
Publishing place	Elsevier Ltd
Document type	Article
Note	Pre-press version
ZDB-ID	605674-x
ISSN	1873-2518 ; 0264-410X
ISSN (online)	1873-2518
ISSN	0264-410X
DOI	10.1016/j.vaccine.2022.09.028
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