Welcome to SanguinStats

Our Aim

SanguinStats is dedicated to advancing blood supply management through data analysis. Our group, comprised of experts in statistics, mathematics, and epidemiology from ten countries around the world, aims to improve blood supply operations by providing insights into various aspects of the blood supply chain.

Participants

Currently we have participants from:

• Australia
• Belgium
• Canada
• Denmark
• Finland
• France
• New Zealand
• South Africa
• Spain
• The Netherlands
• United Kingdom

Ongoing and Potential Future Projects

• Evaluation of historical changes in Hb-levels in the general population (forseen in 2026)
• Return probability (surival analysis) of donors (forseen in 2026)
• Predicting Hb-recovery after donation in repeat donors (Potential future project)

Past Projects and Publications

• Using donation activity time series from seven blood establishments, this study models long-term donation volume and makes future forecasts to be used in long-term blood donation management.
  • Long-term forecasting of blood donations using time series of donation activity: Findings from seven blood establishments. Asikainen T, Brits T, Swanevelder R, Garcia Erce JA, Malard L, Garcia-Martinez I, Welvaert M, Karki S, Lallukka T, Pothast M, Arvas M. Vox Sanguinis. 2026. https://doi.org/10.1111/vox.70229.
  Analysis code: https://github.com/FRCBS/donor-recruitment-prediction
• We retrospectively reassessed donor eligibility in seven countries using an alternative Hb-deferral strategy that considers a repeat donor eligible as long as their historical mean Hb is above the deferral threshold. This strategy may reduce low Hb deferrals by 30%-70%.
  • Potential benefits of an alternative haemoglobin deferral strategy evaluated in seven countries. Meulenbeld A et al. Vox Sang. 2026 Jan;121(1):26-34. https://doi.org/10.1111/vox.70131.
  Analysis code: https://github.com/Sanquin/SanguinStats---Donor-Deferral-project
• An evaluation of the performance of Machine Learning Hb-deferral prediction models trained in different blood bank settings, across all of these settings.
• "Predicting haemoglobin deferral using machine learning models: Can we use the same prediction model across countries?". Meulenbeld A, Toivonen J, Vinkenoog M, Brits T, Swanevelder R, de Clippel D, ... & Arvas M. Vox Sanguinis, 2024 119(7):758–763. https://doi.org/10.1111/vox.13643.
• The analysis code is freely available at https://github.com/FRCBS/Hb_predictor_container.
• An evaluation of the performance of various Machine Learning models in predicting donor Hb-deferral in different settings.
• "An international comparison of haemoglobin deferral prediction models for blood banking". Vinkenoog M, Toivonen J, Brits T, de Clippel D, Compernolle V, Karki S, ... & Janssen MP. Vox Sanguinis, 2023 118(6):430-439. https://doi.org/10.1111/vox.13426
• Both the ready-to-use container image (https://hub.docker.com/r/toivoja/hb-predictor) and its source code (https://github.com/FRCBS/Hb_predictor_container) are freely available through Dockerhub and Github respectively.

Contact

The chair and driving force of the SanguinStats group Mart Janssen has, very sadly, passed away. We will continue along the same way that he intended. If you are interested in our work, want to find out more about our group or join our monthly meeting, please feel free to contact .