Methods in Clinical Epidemiology (MICLEP)
Ausgewählte Publikationen:
Hazard, D., Grodd, M., Walzer, D., Biever, P., Rieg, S., & Wolkewitz, M. (2025). How to avoid time-related types of bias in the analysis of clinical infectious diseases: demonstration and methods. Clinical Microbiology and Infection. (https://doi.org/10.1016/j.cmi.2025.04.005)
Martinuka, O., le Cessie, S., & Wolkewitz, M. (2025). Target trial emulation framework: mitigating methodological challenges and application in COVID-19 treatment evaluation studies. Clinical Microbiology and Infection. (https://doi.org/10.1016/j.cmi.2025.04.027)
Lottes M, Grodd M, Grabenhenrich L, Wolkewitz M. Assessing the impact of Delta and Omicron in German intensive care units: a retrospective, nationwide multistate analysis. BMC Health Serv Res. 2024 Sep 23;24(1):1107. doi:10.1186/s
Martinuka O, Hazard D, Marateb HR, Maringe C, Mansourian M, Rubio-Rivas M, Wolkewitz M. Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data. BMC Med Res Methodol. 2023 Sep 2;23(1):197. doi: 10.1186/s12874-023-02001-8. PMID: 37660025; PMCID:PMC10474639.
Staus P, von Cube M, Hazard D, Doerken S, Ershova K, Balmford J, Wolkewitz M. Inverse Probability Weighting Enhances Absolute Risk Estimation in Three Common Study Designs of Nosocomial Infections. Clin Epidemiol. 2022 Sep14;14:1053-1064. doi: 10.2147/CLEP.S357494. PMID: 36134385; PMCID: PMC9482967.
Doerken S, Metsini A, Buyet S, Wolfensberger A, Zingg W, Wolkewitz M. Estimating incidence and attributable length of stay of healthcare-associated infections-Modeling the Swiss point-prevalence survey. Infect Control Hosp Epidemiol. 2022 Aug;43(8):1022-1031. doi: 10.1017/ice.2021.295. Epub 2021 Aug 5. PMID: 34348807.
Martinuka O, von Cube M, Wolkewitz M. Methodological evaluation of bias in observational coronavirus disease 2019 studies on drug effectiveness. Clin Microbiol Infect. 2021 Jul;27(7):949-957. doi: 10.1016/j.cmi.2021.03.003. Epub 2021 Apr 1. PMID: 33813117; PMCID: PMC8015394.
von Cube M, Grodd M, Wolkewitz M, Hazard D, Wengenmayer T, Canet E, Lambert J. Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information. Crit Care Med. 2021 Jan 1;49(1):e11-e19. doi:10.1097/CCM.0000000000004741. PMID: 33148952; PMCID: PMC7737851.
Rieg S, von Cube M, Kalbhenn J, Utzolino S, Pernice K, Bechet L, Baur J, Lang CN, Wagner D, Wolkewitz M, Kern WV, Biever P; COVID UKF Study Group. COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany. PLoS One. 2020 Nov 12;15(11):e0242127. doi:10.1371/journal.pone.0242127. PMID: 33180830; PMCID: PMC7660518.
Wolkewitz M, Lambert J, von Cube M, Bugiera L, Grodd M, Hazard D, White N, Barnett A, Kaier K. Statistical Analysis of Clinical COVID-19 Data: A Concise Overview of Lessons Learned, Common Errors and How to Avoid Them. Clin Epidemiol. 2020 Sep 3;12:925-928. doi: 10.2147/CLEP.S256735. PMID: 32943941; PMCID: PMC7478365.


- Statistische Methoden in der Krankenhausepidemiologie
- Multistadien Modelle
- Mathematische Modellierung von Epidemien

- Multistadien Modelle
- Konkurrierende Risiken
- Kausale Inferenz
- Gewichtungsdesigns für Kohorten

- Diagnostische Studien
- Beobachtungsstudien
- Konkurrierende Risiken
- Prädiktionsmodelle

- Beobachtungsstudien
- Kausale Inferenz
- Multistadien Modelle
- Konkurrierende Risiken
- Sensitivitätsanalysen für unbeobachtete Störfaktoren
- Statistische beratung
- Bioinformatik

Dr. Zeytu Gashaw Asfaw
- Multistadienmodellierung und konkurrierende Risiken
- Analyse wiederkehrender Ereignisse
- Längsschnittanalyse
- Bayesianische Datenanalyse
- Vorhersagen mittels Maschinellen Lernens

- Vorhersagen mittels Maschinellen Lernens
- Multistadienmodellierung & konkurrierende Risiken
- Krankenhausepidemiologie
Eugenia Messuti