UAntwerp is aiming to chart the spread of infectious diseases

Date: 21 February 2016

Introduction: Are schools right to close during flu pandemics? And should we really stay at home to stop an epidemic spreading further?

Over the next few years, Prof Niel Hens (UAntwerp/UHasselt) will be putting these questions and many more under the microscope thanks to European funding. Hens has just secured a grant of 1.6 million euros from the European Research Council.

A statistician at the universities of Antwerp and Hasselt, Prof Niel Hens is an expert in the development of mathematical models that can help predict the spread of infectious diseases. Research conducted by Hens and his colleagues has already shown, for example, that Belgians spend more time together socially on cold, dry weekdays – days on which the chances of virus transmission are consequently higher.

Recognising the importance of this research field, the European Research Council decided to approve Hens’s application for funding. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 682540. Thanks to the panel’s decision, the scientist will now be able to invest 1.6 million euros in his TransMID project – Transdisciplinary Research in Modelling Infectious Diseases – over the next five years.

Big step forward
There is a lot of work to be done. “We want to develop new statistical and mathematical models”, explains Hens. “These models should allow us to formulate answers to fundamental epidemiological questions. For example, imagine a pandemic breaks out and an infectious disease starts to spread from country to country. Is it a good idea for all schools to close?”

“Another example: there is a big difference between Antwerp and Hasselt if we look at numbers of inhabitants. But does that mean that someone living in Antwerp has more social contact and a higher chance of virus transmission as a result?”

The TransMID researchers focus mainly on diseases like pertussis (whopping cough), measles and cytomegalovirus. They make use of both sociological data and information retrieved from blood samples. “Ultimately, we want to develop a sort of toolbox with software which will help improve our predictions about how an infectious disease might spread,” says Hens. “If we succeed, it will mean a big step forward in public health.”