New research to find efficient strategies for prevention of epidemics
Assistant Professor at ITU, Jonas Juul, receives a Novo Nordisk Foundation Data Science Investigator grant of DKK 6.5 million for a project that aims to improve statistical methods for predicting outbreaks of infections.
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Written 26 February, 2025 08:49 by Mette Strange Mortensen
What can we as a society learn from the COVID-19 pandemic that closed the world in 2020? This will be investigated in a new project led by Jonas Juul, who is Assistant Professor at the IT University of Copenhagen. Denmark was one of the countries that tested the most, and therefore, we have a unique database for looking into the development of the epidemic and this will hopefully improve our disease control during the next epidemic.
“The project is inspired by some of the problems we faced during the COVID-19 pandemic. During the pandemic, I finished my PhD in physics, where I among other things, examined progress of diseases, and I ended up working for The State Serum Institute with prediction of infection rates. There were some things that I noticed could be done better. For example, how we statistically tried to calculate how many infected people there would be tomorrow, in a week or in two weeks. This project will, among other things, strengthen the statistical methods that we use for predicting infection outbreaks,” says Jonas Juul.
The project consists of three different parts. The first part is about improving statistical methods that are used for predicting how diseases spread, the second part is looking into which methods for prevention and control of disease are more effective in what situations, and the third part is about figuring out how COVID-19 spread during the pandemic.
“In my work, during the pandemic, I noticed that certain disease control methods were better in some situations than others. Contact tracing is a great example of this. If a small group of people in Denmark suddenly has mpox, it is about containing the outbreak as quickly as possible. Therefore, it makes sense to contact trace, but if the infection has spread to 10% of the population, it is expensive to contact trace all cases. So, we want to investigate when these different strategies are efficient,” says Jonas Juul.
How did the disease spread?
The big dataset, we have in Denmark, does not only say something about, who was infected when. The many test data were analyzed so that we now know exactly which covid variant people had at which time. The researchers want to use these data to develop new statistical methods, which will be able to say something about how infection with respiratory infections spread.
“We want to use all these data from the COVID-19 pandemic to understand how respiratory infections spread within society. By understanding this we hope to be able to tell whether initiatives such as closing the schools had the effect that fewer parents got infected, and thereby also fewer infected grandparents,” says Jonas Juul, “all these data, we have access to, are of course completely anonymized.”
Not just for the next COVID-19 pandemic
It is said that the COVID-19 pandemic is a centennial event. But with climate change and changed ways of living in parts of the world the risk of a pandemic will be increased:
“We constantly see small outbreaks of Ebola and mpox. Even though the project is based on data from the COVID-19 pandemic, it will also be possible to use it to look at the development of other respiratory infections. Therefore, we hope that we can use our research to contribute to bringing down the infection rate in other disease outbreaks,” says Jonas Juul, “our hope is that our research can contribute to decreasing the number of infections and deaths and ease the financial burden of epidemics and pandemics on society.”
The project is entitled InForM: Inference, Forecasting, and Mitigation of future pandemics and runs for five years. It is a collaboration between the IT University of Copenhagen, Statistics Denmark and The State Serum Institute.
Theis Duelund Jensen, Press Officer, phone +45 2555 0447, email