DrOliver Ratmann

Statistical machine learning and uncertainty quantification

We contribute to bespoke Bayesian methods, deep-learning methodologies, and research into uncertainty quantification. We collaborate with the Machine Learning and Global Health network and Imperial-X.


Pathogen phylogenetics in Africa

We develop statistical methods to analyse viral deep sequence data, covering phylogenetics, transmission flow analyses, time since infection estimation and drug resistance quantification. We collaborate with colleagues at the Department of Infectious Disease Epidemiology, the National University of Singapore, the Big Data Institute in Oxford, John's Hopkins University, the Rakai Health Sciences Institute, and many others.


Infectious disease transmission prevention

We develop ready-to-use, scalable tools towards pandemic preparedness and understanding disease transmission in real-time. We collaborate with the MRC Centre for Global Infectious Disease Analysis.


Global reference group on children affected by COVID-19

We innovate methods to quantify the number of children who lost their parents or caregivers to COVID-19. We contribute to global estimates and in-country analyses. We collaborate with the researchers at the CDC, the University of Oxford, UCL, UNAIDS, the WHO, the World Bank, and NGO's.


Rakai Health Science program in southern Uganda.

We contribute to major health analyses on trends and disparities in HIV, NCDs, human behaviour, and mobility based on longitudinal, population-based data and associated biobank from the Rakai Health Science program. We collaborate with partners at the Rakai Health Sciences Program, Makere University, and John's Hopkins University.


HIV transmission elimination initiative Amsterdam

We develop methods to reconstruct city-level spread of HIV. We collaborate with colleagues at Stichting HIV monitoring, the Amsterdam public health institute, Amsterdam hospitals, and NGOs. This research has been supported by the AIDSFonds.