About me

I'm an Infectious Disease Modeller currently working as group leader Quantitative and Predictive Infectious Disease Modelling at the Institute for Infection Prevention and Hospital Epidemiology, University Medical Center Freiburg, Germany.

Originally from the Netherlands, I studied Biomedical Sciences (BSc) and Biology (MSc) at the University of Amsterdam, before doing my PhD research at the Centre for Infectious Disease Control at the National Institute for Public Health and the Environment (RIVM) in combination with the department of Medical Microbiology at the University Medical Center Groningen, University of Groningen, where I received my PhD with distinction on 24 February 2014.

My PhD research focuses on the structure of contact networks formed by patient shared between health-care institutions and their role in the spread of antibiotic-resistant bacteria and healthcare-associated pathogens. After my PhD I continued this work in Groningen and later within the Modernising Medical Microbiology (MMM) group at the Nuffield Department of Medicine, University of Oxford, UK, researching the design of efficient surveillance schemes for healthcare-associated pathogens based on these networks, as well as the effects of hospitals' network positions on incidence, genetic population structure, and introductions of resistant bacteria in hospitals.

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.

Tjibbe Donker

A selection of my publications


Siebler L, Rathje T, Calandri M, Stergiaropoulos K, Donker T, et al. A coupled experimental and statistical approach for an assessment of SARS-CoV-2 infection risk at indoor event locations. BMC Public Health 2023;23 (1), 1394

Donker T, The dangers of using large language models for peer review. The Lancet Infectious Diseases 2023;23 (7), 781

Scheithauer S, Dilthey A, Bludau A, Ciesek S, Corman V, Donker T, et al. Etablierung der Genomischen Erreger-Surveillance zur Stärkung des Pandemie-und Infektionsschutzes in Deutschland. Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz 2023;66 (4), 443-449

Budgell E, Davies T, Donker T, Hopkins S, Wyllie D, et al., Impact of hospital antibiotic use on patient-level risk of death among 36,124,372 acute and medical admissions in England. Journal of Infection 2022;84 (3)

Donker T, Bürkin FM, Wolkewitz M, Haverkamp C, Christoffel D, et al. Navigating hospitals safely through the COVID-19 epidemic tide: predicting case load for adjusting bed capacity. Infection Control & Hospital Epidemiology 2021;42 (6), 653-658

Donker T. Modelling how antimicrobial resistance spreads between wards. Elife 2020;9, e64228

Knight GM, Davies NG, Colijn C, Coll F, Donker T, et al. Mathematical modelling for antibiotic resistance control policy: do we know enough? BMC infectious diseases 2019;19, 1-9

Donker T,  Smieszek T, Henderson KL, Walker TM, Hope R, et al. Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting. Plos one 2019;14 (7), e0219994

Donker T, Henderson KL, Hopkins KL, Dodgson AR, Thomas S, et al.The relative importance of large problems far away versus small problems closer to home: insights into limiting the spread of antimicrobial resistance in England. BMC Medicine. 2017;15(1):86

Donker T, Smieszek T, Henderson KL, Johnson AP, Walker AS, Robotham JV. Measuring distance through dense weighted networks: The case of hospital-associated pathogens. PLoS Computational Biology. 2017;13(8):e1005622

Donker T, Reuter S, Scriberras J, Reynolds R, Brown NM, et al. Population genetic structuring of methicillin-resistant Staphylococcus aureus clone EMRSA-15 within UK reflects patient referral patterns. Microbial Genomics. 2017;3(7).

Chang H-H, Dordel J, Donker T, Worby CJ, Feil EJ, et al. Identifying the effect of patient sharing on between-hospital genetic differentiation of methicillin-resistant Staphylococcus aureus. Genome Medicine. 2016;8(1).

Donker T, Bosch T, Ypma RJF, Haenen APJ, van Ballegooijen WM, et al. Monitoring the spread of meticillin-resistant Staphylococcus aureus in The Netherlands from a reference laboratory perspective. Journal of Hospital Infection. 2016;93(4):366-374

Reuter S, Török ME, Holden MTG, Reynolds R, Raven KE, et al. Building a genomic framework for prospective MRSA surveillance in the United Kingdom and the Republic of Ireland. Genome Research. 2016;26(2):263-270

Yan X, Schouls LM, Pluister GN, Tao X, Yu X, et al. The population structure of Staphylococcus aureus in China and Europe assessed by multiple-locus variable number tandem repeat analysis; clues to geographical origins of emergence and dissemination. Clinical Microbiology and Infection. 2016;22(1)

Donker T, Ciccolini M, Wallinga J, Kluytmans JA, Grundmann H, Friedrich AW. Analyse van patiëntstromen: De basis voor regionale bestrijding van gevaarlijke infecties [Analysis of patient flows: basis for regional control of antibiotic resistance]. Nederlands tijdschrift voor geneeskunde. 2015; 159

Ciccolini M, Donker T, Grundmann H, Bonten MJM, Woolhouse MEJ. Efficient surveillance for healthcare-associated infections spreading between hospitals. Proceedings of the National Academy of Sciences. 2014 Jan 27;1–6.

Donker T, Wallinga J, Grundmann H. Dispersal of antibiotic-resistant high-risk clones by hospital networks: changing the patient direction can make all the difference. Journal of Hospital Infection. 2014 Jan;86(1):34–41.

Glasner C, Albiger B, Buist G, et al. Carbapenemase-producing Enterobacteriaceae in Europe: a survey among national experts from 39 countries, February 2013. Euro surveillance. 2013 July;18(28):1–7.

Ypma RJF, Donker T, van Ballegooijen WM, Wallinga J. Finding Evidence for Local Transmission of Contagious Disease in Molecular Epidemiological Datasets. PLoS ONE. 2013 Jul 26;8(7):e69875.

Ciccolini M, Donker T, Köck R, et al. Infection prevention in a connected world: The case for a regional approach. International Journal of Medical Microbiology; 2013 Mar;

Te Beest DE, Wallinga J, Donker T, Van Boven M (2013) Estimating the Generation Interval of Influenza A (H1N1) in a Range of Social Settings Epidemiology 24(2): 244-250. doi:10.1097/EDE.0b013e31827f50e8.

Greenland K, Whelan J, Fanoy E, Borgert M, Hulshof K, Yap K-B, Swaan C, Donker T, van Binnendijk R, de Melker H, Hahné S (2012) Mumps outbreak among vaccinated university students associated with a large party, the Netherlands, 2010 Vaccine 30(31): 4676–4680. doi:10.1016/j.vaccine.2012.04.083

Donker T, Wallinga J, Slack R, Grundmann H (2012) Hospital Networks and the Dispersal of Hospital-Acquired Pathogens by Patient Transfer PLoS ONE 7(4): e35002. doi:10.1371/journal.pone.0035002

Donker T, van Boven M, van Ballegooijen WM, van 't Klooster TM, Wielders CC, Wallinga J (2011) Nowcasting pandemic influenza A/H1N1 2009 hospitalizations in the Netherlands European Journal of Epidemiology 26(3): 195-201. doi:10.1007/s10654-011-9566-5

van Boven M, Donker T, van der Lubben M, van Gageldonk-Lafeber RB, te Beest DE, et al. (2010) Transmission of Novel Influenza A(H1N1) in Households with Post-Exposure Antiviral Prophylaxis. PLoS ONE 5(7): e11442. doi:10.1371/journal.pone.0011442

Donker T, Wallinga J, Grundmann H (2010) Patient Referral Patterns and the Spread of Hospital-Acquired Infections through National Health Care Networks. PLoS Comput Biol 6(3): e1000715. doi:10.1371/journal.pcbi.1000715

Grundmann H, Aanensen DM, van den Wijngaard CC, Spratt BG, Harmsen D, et al. (2010) Geographic Distribution of Staphylococcus aureus Causing Invasive Infections in Europe: A Molecular-Epidemiological Analysis. PLoS Med 7(1): e1000215. doi:10.1371/journal.pmed.1000215

van 't Klooster TM, Wielders CC, Donker T, Isken L, Meijer A, van den Wijngaard CC, van der Sande MA, van der Hoek W (2010) Surveillance of Hospitalisations for 2009 Pandemic Influenza A(H1N1) in the Netherlands, 5 June - 31 December 2009. Euro Surveill. 15(2):pii=19461

Vriend H, Hahné S, Donker T, Meijer A, Timen A, van Steenbergen J, Osterhaus A, van der Sande M, Koopmans M, Wallinga J, Coutinho R, het Nederlandse nieuwe influenza A(H1N1)-onderzoeksteam (2009) De nieuwe influenza A(H1N1)-epidemie in Nederland. NTVG Vol. 153, A969

Hahné S, Donker T, Meijer A, Timen A, van Steenbergen J, Osterhaus A, van der Sande M, Koopmans M, Wallinga J, Coutinho R, the Dutch New Influenza A(H1N1)v Investigation Team. Epidemiology and control of influenza A(H1N1)v in the Netherlands: the first 115 cases. Euro Surveill. 2009;14(27):pii=19267

Curriculum vitae

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


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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Name: Tjibbe Donker