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Methods in Clinical Epidemiology (MICLEP)

COVID-19 Forschung

Methodische Artikel:

Martinuka, O., Hazard, D., Marateb, H. R., Maringe, C., Mansourian, M., Rubio-Rivas, M., & Wolkewitz, M. (2023). Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data. BMC medical research methodology, 23(1), 197. (https://doi.org/10.1186/s12874-023-02001-8)

Grodd, M., Rissom, P. F., Lottes, M., Refisch, L., Lorenz, F., Fischer, M., ... & Wolkewitz, M. (2023). Retrospektive Evaluation eines Prognosemodells für die Bettenbelegung durch COVID-19-Patientinnen und-Patienten auf deutschen Intensivstationen. (https://edoc.rki.de/handle/176904/11139)

Montcho, Y., Nalwanga, R., Azokpota, P., Doumatè, J. T., Lokonon, B. E., Salako, V. K., ... & Glèlè Kakaï, R. (2023). Assessing the Impact of Vaccination on the Dynamics of COVID-19 in Africa: A Mathematical Modeling Study. Vaccines, 11(4), 857. (https://doi.org/10.3390/vaccines11040857)

Lokonon, B. E., Montcho, Y., Klingler, P., Tovissodé, C. F., Glèlè Kakaï, R., & Wolkewitz, M. (2023). Lag-time effects of vaccination on SARS-CoV-2 dynamics in German hospitals and intensive-care units. Frontiers in Public Health, 11, 1085991. (https://doi.org/10.3389/fpubh.2023.1085991)

Martinuka, O., Cube, M. V., Hazard, D., Marateb, H. R., Mansourian, M., Sami, R., ... & Wolkewitz, M. (2023). Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19. Life, 13(3), 777. (https://doi.org/10.3390/life13030777)

Montcho, Y., Klingler, P., Lokonon, B. E., Tovissodé, C. F., Glèlè Kakaï, R., & Wolkewitz, M. (2023). Intensity and lag-time of non-pharmaceutical interventions on COVID-19 dynamics in German hospitals. Frontiers in Public Health, 11, 1087580. (https://doi.org/10.3389/fpubh.2023.1087580)

Hazard, D. Y., Grodd, M., Makoudjou, A., Lozano, S., Prunotto, A., Tippmann, P., ... & Wolkewitz, M. (2023). Concurrent analysis of hospital stay durations and mortality of emerging severe acute respiratory coronavirus virus 2 (SARS-CoV-2) variants using real-time electronic health record data at a large German university hospital. Antimicrobial Stewardship & Healthcare Epidemiology, 3(1), e88. (https://doi.org/10.1017/ash.2023.153)

Refisch, L., Lorenz, F., Riedlinger, T., Taubenböck, H., Fischer, M., Grabenhenrich, L., Wolkewitz, M., Binder, H. & Kreutz, C. (2022). Data-driven prediction of COVID-19 cases in Germany for decision making. BMC medical research methodology, 22(1), 1-13. (https://doi.org/10.1186/s12874-022-01579-9)

Grodd, M., Refisch, L., Lorenz, F., Fischer, M., Lottes, M., Hackenberg, M., Kreutz C., Grabenhenrich, L., Binder H.  & Wolkewitz, M. (2022). Forecasting models to guide intensive care COVID-19 capacities in Germany. Medizinische Klinik, Intensivmedizin und Notfallmedizin (https://doi.org/10.1007/s00063-022-00903-x)

Wolkewitz, M., & Martinuka, O. (2022, January). Response to “Overlooked Shortcomings of Observational Studies of Interventions in Coronavirus Disease 2019: An Illustrated Review for the Clinician” by Tleyjeh et al. In Open forum infectious diseases (Vol. 9, No. 1, p. ofab614). US: Oxford University Press. (https://doi.org/10.1093/ofid/ofab614)

Marateb, H. R., Ziaie Nezhad, F., Mohebian, M. R., Sami, R., Haghjooy Javanmard, S., Dehghan Niri, F., ... Wolkewitz, M. & Binder, H. (2021). Automatic classification between COVID-19 and non-COVID-19 pneumonia using symptoms, comorbidities, and laboratory findings: The Khorshid COVID Cohort Study. Frontiers in Medicine, 8, 768467. (https://doi.org/10.3389/fmed.2021.768467)

Marateb, H. R., von Cube, M., Sami, R., Haghjooy Javanmard, S., Mansourian, M., Amra, B., ... & Wolkewitz, M. (2021). Absolute mortality risk assessment of COVID-19 patients: the Khorshid COVID Cohort (KCC) study. BMC medical research methodology, 21(1), 1-9. (https://doi.org/10.1186/s12874-021-01340-8)

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: (2021). Additional insights on the modelling of the COVID-19 clinical progression using multi-state methodology. American Journal of Epidemiology. (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)

Medizinische Artikel:

Mortensen, V. H., Mygind, L. H., Schønheyder, H. C., Staus, P., Wolkewitz, M., Kristensen, B., & Søgaard, M. (2023). Excess length of stay and readmission following hospital-acquired bacteraemia: a population-based cohort study applying a multi-state model approach. Clinical Microbiology and Infection, 29(3), 346-352. (https://doi.org/10.1016/j.cmi.2022.09.004)

Renk, H., Dulovic, A., Seidel, A., Becker, M., Fabricius, D., Zernickel, M., ... & Elling, R. (2022). Robust and durable serological response following pediatric SARS-CoV-2 infection. Nature communications, 13(1), 1-11. (https://doi.org/10.1038/s41467-021-27595-9)

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)


Prof. Dr. Martin Wolkewitz

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

Dr. Derek Hazard

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

Dr. Susanne Weber

  • Diagnostische Studien
  • Beobachtungsstudien
  • Konkurrierende Risiken
  • Prädiktionsmodelle

Dr. Klaus Kaier

  •  Gesundheitsökonomie

M. Sc. Marlon Grodd

  • Multistadien Modelle
  • Komplexe klinische Studien
  • Stichprobenkalkulation

M.Sc. Paulina Staus

  • Kommunikation zwischen medizinischen/biologischen ForscherInnen und StatistikerInnen

  • Gewichtungsmethoden

M. Sc. Oksana Martinuka

  • Kausale Inferenz
  • Inverse-probability weights

Dr. Lars Bugiera

  • Rekurrente Ereignisse
  • Multistadien Modelle
  • Symmetrie und Eindeutigkeit von Lösungen nicht-lokaler PDEs

Dr. Maja von Cube

  • Multistadien Modelle
  • Kausale Inferenz
  • Dynamische Prognose

Dipl. -Math. Maren Eckert

  • Diagnostische Genauigkeitsstudien
  • Personalisierte Medizin