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To maximize the usefulness of groundwater flow models for the protection of aquifers and abstraction wells, it is necessary to identify and decrease the uncertainty associated with the major parameters such as permeability. To do this, there is a need to develop set of estimates representing subsurface heterogeneity or representative soil permeability estimates. Here, we use a coupled Random Field and extended Theory of Porous Media (eTPM) simulation to develop a robust model with a good predictive ability that reduces uncertainty. The coupled model is then validated with a physical sandbox experiment. Uncertainty is reduced by using 500 realisations of the permeability parameter using the eTPM approach. A multi-layer contaminant transport scenario with varying permeabilities, similar to what could be expected with shallow alluvial sediments, is simulated. The results show that the contaminant arrival time could be strongly affected by random field realizations of permeability compared with a modelled homogenous permeability parameter. The breakthrough time for heterogeneous permeabilities is shorter than the homogeneous condition. Using the 75% confidence interval (CI), the average contaminant concentration shows 4.4% variation from the average values of the considered area and 8.9% variation in the case of a 95% confidence interval.

Background: The in vivo single cell gel electrophoresis assay (“comet assay”) is a widespread and sensitive method to detect direct DNA damage in various tissues. Several regulatory frameworks include the comet assay as a standard genotoxicity assay for the prediction of potential human[for full text, please go to the a.m. URL], 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)

Since 2017, applicants with an academic degree in natural sciences or in the field of “life sciences” have the opportunity to participate in the three years international PhD program “Epidemiology & Clinical Research” at the University of Duisburg-Essen. The PhD program consists of an accompanying program comprising 300 teaching units (one teaching unit of 45 minutes each) and the work on own research projects. The accompanying course program focuses on lectures and practical exercises in epidemiology, biostatistics, statistical analysis programs, medicine for non-physicians, and soft skills courses. The dissertation can be submitted as a monograph or as a compilation of three peer-reviewed publications (including at least two first authorships). Finally, the PhD program concludes with the successful defense of the dissertation., Seit 2017 besteht die Möglichkeit für Bewerber mit einem Abschluss in einem naturwissenschaftlichen Studiengang bzw. einem Studiengang aus dem Bereich der Lebenswissenschaften, an dem dreijährigen internationalen PhD-Programm „Epidemiology & Clinical Research“ an der Universität Duisburg-Essen teilzunehmen. Das PhD-Programm besteht aus einem 300 Unterrichtseinheiten (eine Unterrichtseinheit à 45 Minuten) umfassenden Begleitprogramm und der Tätigkeit an eigenen Forschungsprojekten. Schwerpunkte des Begleitprogramms sind u.a. Vorlesungen und Übungen in Epidemiologie, Biostatistik, statistische Analyseprogramme, Medizin für Nicht-Mediziner und Soft-Skills-Kursen. Die Dissertationsschrift kann als Monographie oder als Zusammenstellung von drei peer reviewed Publikationen (mindestens zwei Erstautorenschaften) eingereicht werden. Das PhD-Programm schließt mit der erfolgreichen Verteidigung der Dissertation ab., GMS Medizinische Informatik, Biometrie und Epidemiologie; 16(1):Doc04

Introduction: Perfluorooctanoic Acid (PFOA) is suspected to have various adverse effects on human health, in particular on foetal development. In 2006, elevated PFOA concentrations in drinking water have been observed in several areas of North Rhine-Westphalia (NRW), Germany. The PerSpat-Project[for full text, please go to the a.m. URL], 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

The PerSpat-Project aims to integrate spatial statistics and environmental health and was established a) to evaluate the applicability of different statistical approaches for spatial alignment and b) to investigate associations among Perfluorooctanoic Acid (PFOA) in drinking water and birth outcome.[for full text, please go to the a.m. URL], 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Introduction: Adjustment for confounding variables in observational studies is still the most essential task faced by epidemiological researchers. In 1999 Greenland et al. proposed the DAG (directed acyclic graph)-approach as a non-parametric tool for confounder identification in epidemiology. This [zum vollständigen Text gelangen Sie über die oben angegebene URL], GMDS 2015; 60. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Einleitung und Fragestellung: Der Vergleich zweier Messmethoden gestaltet sich als statistische Herausforderung, wenn einige der Beobachtungen unterhalb einer Bestimmungs- oder Nachweisgrenze liegen und somit nicht quantifizierbar sind. In diesem Beitrag wird dargestellt, wie die Bland-Altman-Methode[for full text, please go to the a.m. URL], GMDS 2014; 59. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

INGARCH models for time series of counts arising, e.g., in epidemiology or finance assume the observations to be Poisson distributed conditionally on the past, with the conditional mean being an affine-linear function of the previous observations and the previous conditional means. We model outliers within such processes, assuming that we observe a contaminated process with additive Poisson distributed contamination, affecting each observation with a small probability. Our particular concern are additive outliers, which do not enter the dynamics of the process and can represent measurement artifacts and other singular events influencing a single observation. Retrospective analysis of such outliers is difficult within a non-Bayesian framework since the uncontaminated values entering the dynamics of the process at contaminated time points are unobserved. We propose a Bayesian approach to outlier modeling in INGARCH processes, approximating the posterior distribution of the model parameters by application of a componentwise Metropolis-Hastings algorithm. Analyzing real and simulated data sets, we find Bayesian outlier detection with non-informative priors to work well in practice when there are some outliers in the data. © 2013, Springer Science+Business Media New York. 25 2 365 374 Cited By :5

Einleitung: Aus Tierversuchen sind reproduktions- und entwicklungstoxische Wirkungen perfluorierter Verbindungen bekannt. Die Ergebnisse der wenigen humanepidemiologischen Studien hingegen sind widersprüchlich. Während einige Autoren negative Assoziationen zwischen den Perfluoroctansäure[for full text, please go to the a.m. URL], GMDS 2013; 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)