Modelling COVID-19 exit strategies for policy makers in the United Kingdom
The potential of using less accurate tests as means of pandemic surveillance is missed, rather than providing reliable medical information about an individual. We investigate whether the additional information from non-diagnostic-quality mass testing can lead to the implementation of a quicker and lower risk exit strategy from lockdown.
Sebastian Vollmer
Professor for Applications of Machine Learning
My research interests lie at the interface of applied probability, statistical inference and machine learning.