Astrophysics and epidemiology – how do they go together? The contact between the Center for Space and Habitability CSH and the Institute for Social and Preventive Medicine ISPM was established in 2018, as Kevin Heng, director of CSH, explains: "Oscar Franco, who was the new director at ISPM then, and I had various discussions to explore a possible collaboration. Christian Althaus was also present at one of these meetings. That's how we met." The COVID-19 pandemic then expedited the collaboration between astrophysicist Heng and epidemiologist Althaus to such an extent that they were not only jointly involved in two studies on COVID-19, but they have now institutionalized the cross-faculty collaboration on the new INPUT platform. 

Planet and human populations can be described similarly

Astrophysics and epidemiology have little in common at first glance. Kevin Heng admits without hesitation how surprised he was that they got along so well right from the start. Althaus, who has been working at ISPM for 10 years, has a PhD in theoretical biology and says: "Of course I have adopted the epidemiology mindset in the meantime, but thanks to my basic scientific training, I find it easy to exchange ideas with experts in chemistry or physics." 

From a methodological point of view, there are certainly overlaps between the two branches of research. Kevin Heng says: "What I find particularly beautiful about the natural sciences is that the language of nature is ultimately that of mathematics. Because our mathematical equations describe how nature works." For example, Kevin Heng has found that the mathematical equations describing the chemical processes in the atmosphere of exoplanets are similar to those used to describe the transmission of infectious diseases. Christian Althaus adds: "In astrophysics, for example, simulation models are used to investigate how molecules on distant planets react with each other and form compounds. We use a very similar methodology based on the same mathematical principles in epidemiology to investigate how infectious diseases are transmitted." 

However, the two research areas are similar in other respects as well. "In astronomy, we look at large collections, so-called populations, of objects in the sky. They can be populations of galaxies, stars or planets." Statements about these populations are then made at statistical level. And in epidemiology too, data is considered at population level, and evaluated statistically. "So you could say that we use the same tools of statistical analysis and modeling to understand both celestial objects and human health," says Kevin Heng.  
 

Bundling of expertise in handling large amounts of data

In both astrophysics and epidemiology, researchers have to deal with an enormous amount of data. The collaboration between CSH and ISPM has now been institutionalized and the INPUT platform founded to bundle expertise in this field and to use synergies. INPUT stands for "Interfaculty Platform for Data and Computational Science". The platform is managed by Christian Althaus. He says: "We are already working on current projects, but we really want to grow as a platform and cooperate with other institutes and faculties. After all, many branches of research work with large amounts of data and model-based simulations." Kevin Heng adds: "The spirit of the platform is to look for different fields of research which at first glance do not appear to have much in common, but which show a close similarity in the application of modelling and statistics." For example, David Ginsbourger from the Institute for Mathematical Statistics and Insurance (IMSV) is already on board with INPUT.

As Althaus explains, researchers from the University of Bern have already been able to make an important contribution to understanding the pandemic this year. "And now I hope that with INPUT we will be able to work on other topics beyond infectious diseases that are of great importance today on a global level, such as "planetary health", i.e. the state of health of human civilization and its environment in terms of global coexistence, ecology and climate," Althaus continues. This requires a comprehensive understanding of a large amount of data or computer simulations that are used to model complex systems. "We want to gain an understanding of the pressing issues of the future so that the right answers can be found," Althaus concludes.