MD, PhD, DTMH
Internist-infectious diseases specialist,
Professor International Health,
Radboud University Medical Center,
Radboud Center for Infectious Diseases,
Nijmegen, The Netherlands
Since more than 30 years Prof van der Ven has been working in the field of infectious diseases, as a clinician, teacher and researcher. His clinical work covers 38 years’ experience, including mployment as tropical doctor as well as university internist-infectious diseases. He has committed himself to basic and translational research, both in the Netherlands as well as in low and middle income countries, supervised over 45 PhD candidates, originating from Europe, Africa and Asia. Focus of his research and teaching is susceptibility and management of infectious diseases.
The past years Prof van der Ven was in function as Professor International Health and head infectious diseases department Radboud University Medical centre, Nijmegen, the Netherlands. Since 2020 he is Emeritus Professor International Health Radboud University Medical Centre Peer-reviewed publications (out of 319 papers, H index 50)
Antimicrobial resistance (AMR) is one of the biggest threats to global health and is fuelled, among others, by the misuse and overuse of antimicrobial drugs. Diagnostics are a key tool to address the spread of AMR: a simple test flagging the presence or absence of bacterial infections can dramatically cut antibiotic overuse. Complete blood count (CBC) with leukocyte differentiation is currently the most used technique to screen for the presence of infection. New generation haematology analysers have improved capacity to detect phenotypical changes in leukocyte sub-sets, leading to a more comprehensive panel of blood cell makers and thereby also to the diagnostic software algorithm tested in this manuscript – the Infection Manager System (IMS) – designed to differentiate bacterial from viral infections. A diagnostic accuracy study was thereafter performed in Burkina Faso to test the accuracy of the IMS, alongside standard malaria diagnostics, to detect bacteraemia in a malaria endemic setting, and compare its accuracy to CRP and PCT. IMS showed a high negative predictive value to detect bacterial infections and may be a promising tool to assist clinicians in their decision to prescribe or withhold antibiotics in patients with AFI.