Statistical Methods for Infectious Diseases

Department of Medical Statistics

The Department of Medical Statistics offers furthermore extensive knowledge in the field of statistical methods for infectious diseases. The expertise in the development and use of statistical methods in this field was acquired by Priv.-Doz. Dr. Steffen Unkel when he was working in the Department of Mathematics and Statistics at the Open University, Milton Keynes, United Kingdom, particularly on two research projects, namely

Inference for infectious diseases from multivariate serological survey data

In this project we developed new statistical methodology to analyse multivariate serological survey data and to quantify the levels of individual heterogeneities that are relevant for the transmission and spread of infectious diseases. Thus we derived better estimates of key infectious disease parameters relevant to vaccination policies such as reproduction numbers and critical immunization thresholds.

Key publications:

  • Unkel, S., Farrington, C. P., Whitaker, H. J. and Pebody, R. (2014): Time-varying frailty models and the estimation of heterogeneities in transmission of infectious diseases, Journal of the Royal Statistical Society Series C, Vol. 63, pp. 141-158.
  • Farrington, C. P., Whitaker, H. J., Unkel, S. and Pebody, R. (2013): Correlated infections: quantifying individual heterogeneity in the spread of infectious diseases, American Journal of Epidemiology, Vol. 177, pp. 474-486.

Methodological development of syndromic and laboratory statistical surveillance systems

Unusual clusters of disease must be detected rapidly for effective public health interventions to be introduced. Over the past two decades there has been a surge in interest in statistical methods for the early detection of infectious disease outbreaks. This growth in interest has given rise to much new methodological work, ranging across the spectrum of statistical methods. In this project we conducted a comprehensive literature review of the statistical approaches that have been proposed. Applications to both laboratory and syndromic surveillance data were provided in the review to illustrate the various methods.


  • Unkel, S., Farrington, C. P., Garthwaite, P. H., Robertson, C. and Andrews, N. (2012): Statistical methods for the detection of infectious disease outbreaks: a review, Journal of the Royal Statistical Society Series A, Vol. 175, pp. 49-82.

Further projects

Priv.-Doz. Dr. Steffen Unkel is also principal investigator of a 3-year grant project entitled ''Frailty modelling for multivariate current status data with applications in epidemiology'', which is funded by the German Research Foundation (DFG).

Furthermore, Professor Tim Friede and Priv.-Doz. Dr. Steffen Unkel currently collaborate with colleagues from the University Medical Center on two clinical studies in infectious diseases. These are


  • The aim of this study is to reduce the number of infections with toxin producing Clostridium difficile in geriatric clinics.
  • PI: Prof. Roland Nau, Geriatric Center, Evangeligical Hospital Göttingen-Weende (EKW) und Department for Neuropathology, University Medical Center Göttingen
  • Funding: Innovation fund for health service research of the G-BA


  • The aims of this study are (a) to evaluate the quality of neonatal colonisation screening for the prediction of infections, (b) to analyse the dependence between antibiotic therapy and colonisation evidence, and (c) to predict outbreaks of multi-resistant gram-negative pathogens.
  • PI: Prof. Simone Scheithauer, Central Department for Hospital Hygiene and Infectiology, University Medical Center Göttingen
  • Funding: Innovation fund for health service research of the G-BA


Wissenschaftlicher Mitarbeiter

PD Dr. Steffen Unkel

contact information


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