Unit | Biostatistics

The Biostatistics unit engages in collaborative, basic and applied statistical research in the fields of epidemiology, parasitology and infection biology. Primary areas of applications involve malaria, anaemia, neglected diseases, HIV, mortality, cancer and environmental epidemiology. Research is mainly funded by Swiss National Foundation (SNSF), Bill and Melinda Gates Foundation (BMGF) and a European research Council (ERC) Advance Grant.

Major areas of methodological research

  • Spatio-temporal modelling for disease burden estimation and surveillance
  • Diagnostic error evaluation
  • Cohort data modelling
  • Exposure modelling
  • Causal inference
  • Meta analysis
  • Bayesian computation


The unit leads Swiss TPH's scientific support services. This service is provided in collaboration with the Public Health Computing group and includes consulting for study design, data management support, statistical analysis, consulting in the fields of biomathematics and bioinformatics, and software development. Clients come from within Swiss TPH and externally. Read more about our Data Services


The unit is also heavily engaged in teaching Statistics and Epidemiology to medical undergraduates, MSc students and PhD students, both in curricular courses of the University of Basel and in external courses. The Unit is involved in Swiss Master of Public Health Programme, European Course in Tropical Epidemiology and Postgraduate Programme for University Professionals in Insurance Medicine.

Statistics and epidemiology teaching is provided within the programs of the University of Basel. Within this program we organise the following courses:

Bapolisi W.A et al. Engaging men in women's empowerment: impact of a complex gender transformative intervention on household socio-economic and health outcomes in the eastern Democratic Republic of the Congo using a longitudinal survey. BMC Public Health. 2024;24(1):443. DOI: 10.1186/s12889-024-17717-5

Boz S et al. A cohort analysis of residential radon exposure and melanoma incidence in Switzerland. Environ Res. 2024;243:117822. DOI: 10.1016/j.envres.2023.117822

Fairbanks E.L et al. Inference for entomological semi-field experiments: fitting a mathematical model assessing personal and community protection of vector-control interventions. Comput Biol Med. 2024;168:107716. DOI: 10.1016/j.compbiomed.2023.107716

Plass D et al. Estimating the burden of disease due to lead, PFAS, phthalates, cadmium, pyrethroids and bisphenol A using HBM4EU data – test of feasibility and first results for selected countries: European Topic Centre on Human Health and the Environment, 2024

Probst-Hensch N et al. Long-term trajectories of densely reported depressive symptoms during an extended period of the COVID-19 pandemic in Switzerland: social worries matter. Compr Psychiatry. 2024;130:152457. DOI: 10.1016/j.comppsych.2024.152457