Brief career overview
During my PhD, I developed a novel way of looking at the spread of antimicrobial resistance (AMR), and in particular the spread of methicillin-resistant Staphylococcus aureus, by analysing the network of hospitals formed by patients exchanged between them. The position of a hospital in this network, as well as the regional structure of the entire network, greatly affect its risk of receiving AMR micro-organisms, showing that the control of AMR should be a collaborative effort, in particular within the regions of strongly connected hospitals.
During my post docs, I started looking at the optimal ways to utilise the network in order to prevent the spread of AMR between hospitals, for instance by designing sentinel surveillance strategies. These strategies can be made more efficient (i.e. detect an outbreak faster while testing fewer patients) by taking the hospital network position into account.
At the University of Oxford, I looked at unintended consequences of policy decisions on the spread of AMR, both for unrelated policy decisions and those aimed at reducing its spread. I found that a strategy of screening patients that previously have been admitted to a hospital assigned to a ‘high-risk’ list, based on a high AMR prevalence, can have adverse effects on AMR control. As this strategy is aimed at preventing introductions from other hospitals, the high-risk list often focusses on high-prevalence hospitals far away, while low-prevalence hospitals closer by will actually cause more introductions, because of the larger absolute number of exchanged patients.
Coming to Freiburg, I started building a framework to collect and compare healthcare networks from different countries in a systematic way. To that end, we designed together with colleagues from the EHESP (Rennes, France) and the CNAM (Paris, France), an R-package to allow the construction of hospital networks from raw patient data.
Next to my "regular" research interest, I have worked on numerous pandemic response projects, developing methods to compensate for reporting delays in epidemiological data (so-called nowcasting methods), as well as developing forecasting methods for e.g. ICU bed demand or consumable usage. For the latter, our group designed and developed a dashboard environment that allows individual German hospitals to produce bespoke bed demand forecast for the situation on their wards.
Work experience
01-04-2019 – present
Group leader - Quantitative and Predictive Infectious Disease Modelling
Institute for Infection Prevention and Hospital Epidemiology
University Medical Center Freiburg
Freiburg im Breisgau, Germany
01-02-2015 – 28-02-2019
Infectious Disease Modeller
Nuffield department of Medicine
University of Oxford
Oxford, United Kingdom
1-1-2014 – 31-12-2014
Post doc researcher
Department of Medical Microbiology
University Medical Center Groningen
Groningen, The Netherlands
1-9-2008 - 31-12-2013
PhD Student
Centre for Infectious Disease Control (CIb)
National Institute for Public Health and the Environment (RIVM)
Bilthoven, The Netherlands
1-10-2007 – 31-8-2008
Junior researcher
Theoretical Immunology
University of Utrecht
Utrecht, The Netherlands
Education
PhD “Disease transmission through hospital networks”
Completion date: 24-2-2014 (cum laude)
University of Groningen
MSc in Biology (cum laude): 6-10-2007
University of Amsterdam
BSc in Biomedical Sciences: 31-3-2006
University of Amsterdam
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