Unit | Biostatistics

The Biostatistics unit specialises in collaborative, basic and applied statistical research in the fields of epidemiology, parasitology and infection biology. Primary areas of application include malaria, anaemia, neglected diseases, HIV, mortality, cancer and environmental epidemiology. Our research is mainly funded by the Swiss National Foundation (SNSF), the Gates Foundation, and an European Research Council (ERC) Advanced 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 also leads Swiss TPH's scientific support services. We provide consulting services for study design, data management, statistical analysis, biomathematics and bioinformatics, as well as software development. Clients come from within and outside Swiss TPH. Read more about our Data Services.

Teaching

We are actively engaged in teaching Statistics and Epidemiology to undergraduate medical students, as well as Master's and PhD students, in both the University of Basel's curriculum and external courses. The unit is involved in the Swiss Master of Public Health Programme, the European Course in Tropical Epidemiology, and the Postgraduate Programme for University Professionals in Insurance Medicine.

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