Epidemiological Methods

Epidemiological research depends on sound study design, thorough study conduct and appropriate analytic techniques to generate valid and meaningful results. The Epidemiological Methods Group is supporting the study planning and is leading the data analyses of the department's research projects.


Our research focuses on understanding and predicting the occurrence and control of different tropical diseases, including vector-borne diseases, snakebites and infectious diseases close to elimination. We develop and apply mathematical models to a range of conditions, with research topics spanning from statistical inference methodology, real-time prediction modelling to disease transmission dynamics. Beyond that, our group is engaged in the development and application of statistical methods accounting for methodological challenges arising in resource-poor settings, e.g. selection biases and suitable randomization strategies for cluster-randomized trials.

The research group is supporting the following national and international training courses:

  • Modules in basic epidemiology and statistics for health professionals and medical doctors at BNITM (Tropenkurs für medizinisches Fachpersonal, Diplomkurs Tropenmedizin)
  • Modules in Epidemiology & Control of Infectious diseases in outbreak settings (EPICID, TropEd network - master in international public health)
  • Module in epidemiology (BNITM Leibniz Center Infection Graduate School, PhD program)
  • Introductory course on study conduct and data analyses (National Institute of Public Health, NIOPH at Vientiane University, Lao PDR)
  • Introductory course on epidemiology and statistics (Kumasi Centre for Collaborative Research in Tropical Medicine, KCCR in Kumasi, Ghana)

For further information, please contact:

Ralf Krumkamp

Ralf Krumkamp studied Public Health and Epidemiology, and holds a DrPH from the University of Bremen. He worked on the evaluation of health system preparedness of different European and Asian countries for the control of epidemic and pandemic-prone infectious diseases. Currently, he is analysing observational epidemiological studies on different tropical diseases using mathematical models, machine learning techniques and modern epidemiological methods.

Eva Lorenz

Eva Lorenz holds a diploma degree in Medical Informatics and a PhD in Biostatistics and Epidemiology from the University of Heidelberg. She has experience in the development, application and dissemination of statistical methods for complex multivariable model building focussing on exposure variables with a probability mass at zero and methodological aspects on cluster-randomized trials.

Zu sehen ist ein freundlicher, selbstbewusster und erfahrener Forscher aus dem europäischen Raum.
Head of Department

Prof. Dr. Jürgen May

Telefon: +49 40 285380-402

E-Mail: may@bnitm.de

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