At the start of the pandemic, Luc Coffeng and his colleague Sake de Vlas (both working from home, obviously) spent up to one hundred hours a week developing a mathematical model that would show us how infection rates would rise or fall, depending on which kind of policy the government would implement.
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“We particularly wanted to find out whether it would be possible to rescind the lockdown order and, if so, when. To that end, we performed calculations for particular strategies, such as relaxing the restrictions nation-wide or in individual regions. Thankfully, they decided against that, but it was useful to work out whether it would be effective in the first place,” says Coffeng.
When Coffeng and De Vlas appeared on the Op1 TV show to share their findings, it became obvious to everyone that the pandemic would last for a very long time without vaccines. The study results provided a possible way out, but also caused quite a stir. For instance, Coffeng received many e-mails from complete strangers after his appearance on the show, expressing everything from sincere interest to downright bonkers conspiracy theories. “I also had a few discussions on Twitter. It taught me to choose carefully on which people to expend my energy, as it’s all too easy to waste a lot of time and energy having those discussions.”
Nevertheless, these interactions with the public helped inspire him to simulate people’s behaviour during the pandemic. Having been awarded a fellowship by the Royal Netherlands Academy of Arts and Sciences (KNAW)’s Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS), Coffeng and several social scientists will embark this autumn on an effort to develop a new mathematical model.
The scientists will seek to determine how human behaviour can affect the development of a pandemic and vice versa. People’s behaviour determines how an infectious disease spreads and how well its spread can be controlled. At the same time, the pandemic also affects people’s behaviour – for instance, in terms of their views of the disease, or fear of the disease, or their social networks. “What I wish to focus on is a model in which people try to work out what is the best type of conduct for their particular situation, based on their past experiences, preferences and habits.”
Coffeng can then use these types of models to simulate specific networks that are in touch with each other. “People who are more alike in terms of their preferences and behaviours will probably try and see each other more often, meaning the network itself will evolve, thanks to infectious diseases and human behaviour. And these clusters then play a part in the spread of and fight against the infectious disease itself.”
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Coffeng particularly hopes that the development of this mathematical model will teach us new, general lessons on how to control infectious diseases, and also hopes that it will be able to be used in the future, when the next epidemic breaks out. “Our work mostly consists of performing calculations on how best to stage interventions in populations where all sorts of people interact. At the start of the pandemic, in particular, something like this could have gone a long way towards controlling the spread of the disease. I basically view this pandemic as a case study of sorts. It’s a unique situation on which we’ve collected a unique amount of data, both regarding the infection and regarding the behaviour of people in the Netherlands.”
The study not only focuses on COVID-19 in the Netherlands. It also involves data collected in Uganda to analyse the tropical infectious disease malaria, which has been around for much longer. “It’s useful to reflect on such processes, because these types of diseases are on the list of diseases that must be eliminated. And obviously, the challenge inherent in elimination is as follows: the less common the disease becomes, the less support there will be for tackling those final residual cases.”
A flight of starlings
Coffeng last practised as a doctor in the hospital in 2008. After working at the Acute Psychiatry unit for eight months, he realised he needed more technology and creativity in his job. He mainly found them in mathematical modelling and epidemiology, which formed the subject of his PhD research project.
Coffeng particularly likes the complexity of infectious diseases and of disease control because he feels that it arises from very basic rules that are easy to simulate. “Take, for instance, a flight of starlings in the sky. One very basic rule is that one starling will always keep just enough distance from the next, and they’ll all move more or less in the same direction. But when we see a cloud of starlings fly together of an evening, we’ll see them whirling around in the most gorgeous way, with no individual starling having the faintest idea of what he’s doing or how it’s done. Infectious diseases and disease control basically work the same way, because you can’t predict complex patterns across the entire population in advance, based on simple rules about how you and I interact.”
Coffeng believes that he continues to be motivated to some extent by the degree in medicine he once did, as well. “It’s important to me that I contribute to public health, and I think this job allows me to do so.”