C
Christel Faes
Researcher at University of Hasselt
Publications - 231
Citations - 4423
Christel Faes is an academic researcher from University of Hasselt. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 30, co-authored 196 publications receiving 3426 citations. Previous affiliations of Christel Faes include Katholieke Universiteit Leuven.
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Journal ArticleDOI
A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies
Pietro Coletti,Pieter Libin,Pieter Libin,Pieter Libin,Oana Petrof,Lander Willem,Steven Abrams,Sereina A. Herzog,Christel Faes,Elise Kuylen,Elise Kuylen,James Wambua,Philippe Beutels,Philippe Beutels,Niel Hens,Niel Hens +15 more
TL;DR: In this article, the authors developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium.
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A high-dimensional joint model for longitudinal outcomes of different nature
TL;DR: The approach of Fieuws and Verbeke (Biometrics 2006) is extended in two ways: the method is applied to different types of outcomes and the full pseudo-likelihood expression is maximized at once, leading directly to unique estimates as well as direct application of pseudo- likelihood inference.
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SOCRATES-CoMix: a platform for timely and open-source contact mixing data during and in between COVID-19 surges and interventions in over 20 European countries.
Frederik Verelst,Lisa Hermans,Sarah Vercruysse,Amy Gimma,Pietro Coletti,Jantien A. Backer,Kerry L. M. Wong,James Wambua,Kevin van Zandvoort,Lander Willem,Laurens Bogaardt,Christel Faes,Christopher I Jarvis,Jacco Wallinga,W. John Edmunds,Philippe Beutels,Philippe Beutels,Niel Hens,Niel Hens +18 more
TL;DR: In this article, the authors collected contact mixing behavior in various phases of the COVID-19 pandemic in over 20 European countries and provided these timely, repeated observations using an online platform: SOCRATES-CoMix.
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Estimating the population prevalence and force of infection directly from antibody titres
Kaatje Bollaerts,Marc Aerts,Ziv Shkedy,Christel Faes,Y. Van der Stede,Philippe Beutels,Niel Hens,Niel Hens +7 more
TL;DR: The method is applied to estimate the Salmonella serological prevalence in pigs and the age-dependent force of infection using serological data on the Varicella-Zoster virus in humans using an underlying mixture model.
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Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.
Wondwosen Kassahun,Thomas Neyens,Geert Molenberghs,Geert Molenberghs,Christel Faes,Geert Verbeke,Geert Verbeke +6 more
TL;DR: Analysis of two datasets showed that accounting for the correlation, overdispersion, and excess zeros simultaneously resulted in a better fit to the data and, more importantly, that omission of any of them leads to incorrect marginal inference and erroneous conclusions about covariate effects.