Life Sciences - Research Groups

Mathematical Immuno-Epidemiology

Dr. Maria Barbarossa

The understanding of complex biological systems requires the reconstruction of multiscale processes, occurring on multiple spatial and temporal scales. 

Our group works at the development of analytical and computational techniques for the description of processes arising in immunology and infectious diseases. In particular, we work on

(i) in-host phenomena at intracellular level (e.g. signaling pathways), 

or at cellular level (e.g. interactions of immune cells with infected cells or tumor cells)

(ii) between-hosts dynamics (e.g. pathogen transmission and social dynamics)

and on the coupling of these two scales. This allows, for example, to capture the effects of individual immunity on epidemiological outbreaks in a population, or to study molecular mechanisms and events that influence the dynamic at cellular level (e.g. cell proliferation, death, functionality). 

Combining elements of nonlinear and infinite-dimensional dynamics with numerical simulations and optimization, we aim at both qualitative and quantitative understanding of biological phenomena. 

Fellow Detail

Research and Teaching


​ Our research work on COVID-19

  • MV Barbarossa, N Bogya, A Dénes, G Röst, H Vinod Varma, Zs Vizi, Fleeing lockdown and its impact on the size of epidemic outbreaks in the source and target regions - a COVID-19 lesson, preprint on Research Square (2020)
  • Fuhrmann, J., Barbarossa, M.V. The significance of case detection ratios for predictions on the outcome of an epidemic - a message from mathematical modelers. Arch Public Health 78, 63 (2020).
  • MV Barbarossa, J Fuhrmann, J Meinke, S Krieg, HV Varma, N Castelletti, and Th Lippert, Modeling the spread of COVID-19 in Germany: Early assessment and possible scenarios, PLoS ONE 15(9): e0238559preprint in medRxiv (2020)
  • MV Barbarossa, J Fuhrmann, J Heidecke, HV Varma, N Castelletti, J Meinke, S Krieg and Th Lippert, A first study on the impact of current and future control measures on the spread of COVID-19 in Germany, medRxiv (2020)

Mathematical Epidemiology

Mathematical models are used to describe the spread of infectious diseases in a population. Important information can be provided to public health by designing, evaluating and comparing different strategies to control an outbreak. 


  • new article accepted! our work on COVID-19 predictions for the early dynamics of the German outbreak was published in PLOS ONE (with J Fuhrmann, J Meinke, S Krieg, H Varma, N Castelletti and Th Lippert) (Aug 2020)
  • new article accepted! The significance of case detection ratios for predictions on the outcome of an epidemic (with J Fuhrmann), Archives of Publich Health (Juli 2020)
  • new article accepted! A mathematical view on head lice infestations (with N. Castelletti), Infectious Diseases Modeling (May 2020)