Methods in Clinical Epidemiology (MICLEP)
COVID-19 research
Methodological articles for observational studies:
Hazard, D., Kaier, K., von Cube, M., Lambert, J., & Wolkewitz, M. (2021). How to Quantify and Interpret Treatment Effects in Comparative Clinical Studies of COVID-19. Annals of internal medicine, 174(5), 731. (https://doi.org/10.7326/L20-1439)
Martinuka O, von Cube M and Wolkewitz M. "Methodological evaluation of bias in observational COVID-19 studies on drug effectiveness." Clinical Microbiology and Infection (2021) (https://doi.org/10.1016/j.cmi.2021.03.003).
Wolkewitz M, Binder H, Mañanas MA, Jordanic M, Khademi S, von Cube M, Reza Marateb H, Mansourian M (2021): Reliable Diagnosis and Prognosis of COVID-19. In V. Bajaj, G.R. Sinha (Ed.), Computer-aided Design and Diagnosis Methods for Biomedical Applications. (1st Ed., pp. 319-340) CRC Press. (https://doi.org/10.1201/9781003121152)
von Cube M, Wolkewitz M, Schumacher M, Hazard D: Additional insights on the modelling of the COVID-19 clinical progression using multi-state methodology. American Journal of Epidemiology, 2021; preprint ahead of print (https://doi.org/10.1093/aje/kwab044)
Donker, T, Buerkin, F, Wolkewitz, M, Haverkamp, C, Christoffel, D, Kappert, O, Hammer, T, Busch, HJ, Biever, P, Kalbhenn, J, Buerkle, H, Kern, W, Wenz, F, Grundmann, H (2020). Navigating hospitals safely through the COVID-19 epidemic tide: predicting case load for adjusting bed capacity. Infect Control Hosp Epidemiol,:1-14: https://www.cambridge.org/core/journals/infection-control-and-hospital-epidemiology/article/navigating-hospitals-safely-through-the-covid19-epidemic-tide-predicting-case-load-for-adjusting-bed-capacity/6D7E4D93419471B27BEA52AB1ECBD93D
Wolkewitz, M, Puljak, L (2020). Methodological challenges of analysing COVID-19 data during the pandemic. BMC Med Res Methodol, 20, 1:81: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-00972-6
Hazard, D., Kaier, K., von Cube, M., Grodd, M., Bugiera, L., Lambert, J., & Wolkewitz, M. (2020). Joint analysis of duration of ventilation, length of intensive care, and mortality of COVID-19 patients: a multistate approach. BMC Medical Research Methodology, 20, 206: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01082-z
Wolkewitz, M., Lambert, J., von Cube, M., Bugiera, L., Grodd, M., Hazard, D., White N., Barnett A. & Kaier, K. (2020). Statistical Analysis of Clinical COVID-19 Data: A Concise Overview of Lessons Learned, Common Errors and How to Avoid Them. Clinical epidemiology, 12, 925: https://www.dovepress.com/statistical-analysis-of-clinical-covid-19-data-a-concise-overview-of-l-peer-reviewed-article-CLEP
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. Critical Care Medicine, 2021; 49(1): E11-E19 (https://doi.org/10.1097/CCM.0000000000004741)
Medical articles:
Rieg, S., von Cube, M., Kalbhenn, J., Utzolino, S., Pernice, K., Bechet, L.,Johanna Baur, Corinna N. Lang, Dirk Wagner, Martin Wolkewitz, Winfried V. Kern, Paul Biever & COVID UKF Study Group. (2020). COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany. PloS one, 15(11), e0242127. (https://dx.plos.org/10.1371/journal.pone.0242127)


- Statistical methods in hospital epidemiology
- Multistate modelling
- Mathematical modelling of epidemics

- Multistate Modelling
- Competing Risks
- Causal Inference
- Cohort Weighting Designs

- Diagnostic studies
- Observational studies
- Competing Risiks
- Prediction models

- Health economics

- Multistate modelling
- Complex clinical trials
- Sample size calculations

- Diagnostic accuracy studies
- Personalized medicine

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Communication between medical/biological scientists and statisticians
- Weighting mechanisms

- Causal inference
- Inverse-probability weighting

Dr. Lars Bugiera
- Multistate Modelling
- Recurrent Events analysis
- Symmetry and Uniqueness in nonlocal elliptic PDEs

Dr. Maja von Cube
- Multistate modelling
- Causal inference
- Dynamic prediction