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 the Swiss National Foundation (SNSF), the Gates Foundation 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

Services

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
 

Teaching

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

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

Latest Publications

All Publications

Alidou S et al. Risk factors associated with urogenital schistosomiasis: a multilevel assessment approach using an Oversampling Schistosomiasis Survey (SOS) community-based, Plateaux region, Togo 2022. BMJ Public Health. 2025;3(1):e001304. DOI: 10.1136/bmjph-2024-001304

Angelakis A, Nyawanda B.O, Vounatsou P. Modeling sparse Rift Valley fever incidence data: a Bayesian perspective on zero-inflated self-exciting and autoregressive models. BMC Infect Dis. 2025;25:1221. DOI: 10.1186/s12879-025-11506-0

Keita B.M et al. Piloting the Schistosomiasis Practical and Precision Assessment approach in five health districts of the N'zérékoré region, Republic of Guinea. PLoS Negl Trop Dis. 2025;19(10):e0013413. DOI: 10.1371/journal.pntd.0013413

Kim J, Vounatsou P, Chun B.C. Distribution and risk factors of scrub typhus in South Korea, from 2013 to 2019: bayesian spatiotemporal analysis. JMIR Public Health Surveill. 2025;11:e68437. DOI: 10.2196/68437

Nyawanda B.O et al. Geostatistical analysis to guide treatment decisions for soil-transmitted helminthiasis control in Uganda. PLoS Negl Trop Dis. 2025;19(9):e0013467. DOI: 10.1371/journal.pntd.0013467