Since May, Maria Barbarossa has been a FIAS Fellow and research group leader within Loewe's focus area CMMS (Center for Multiscale Modeling in Life Sciences). Her work is dedicated to the development of mathematical models and methods for understanding multiscale processes in immunology and the dynamics of epidemics. In this interview, she talks about her career and her current research on the COVID-19 epidemic.
Your background is in Mathematics. How did you come to work on biological topic?
During my studies at the TU Munich I dealt with applications of mathematics, especially in biology. During this time I also had my first contacts and collaborations in research projects with biologists and biochemists of the Helmholtz Zentrum Munich. The interdisciplinary nature of my work and the idea of using mathematics to investigate the life sciences is fascinating to me. Biological questions are so complex that they can inspire new mathematical approaches - often these can lead the way to new results.
Have you focused your research on the spread of epidemics since your time in Munich?
Not much. In Munich I have mainly worked on the modelling of quorum sensing, i.e. the communication between bacteria. My PhD topic was not data-related - I was concerned with the properties of a special class of differential equations (delay equations) that could find applications in population dynamics. After my PhD I moved to Hungary, to the Bolyai Institute of the University of Szeged, where a group around Gergely Röst is working on the coupling between the theory of delay equations and the modelling of the spread of infectious diseases. I have been particularly interested in the propagation dynamics of diseases that do not grant lifelong immunity, such as pertussis. In 2014 the Ebola epidemic in Africa occurred. Together with the Hungarian group we have been working on modelling the impact of control measures. After I transferred to the University of Heidelberg at the end of 2015, I also had the opportunity to deal with immunology topics and worked on the early diagnosis of sepsis. In this context, since 2019 I have been leading a project on the description of biochemical regulatory networks in immune cells – which could be affected by infection and/or inflammation.
When did you start to work on the spread of the new coronavirus?
SARS-CoV-2 attracted the attention of the mathematical community relatively early. The first papers for the Chinese outbreak came out in early February. Together with my group and colleagues from Research Centre Jülich, I was mainly concerned - in depth - with the German situation when the number of cases in Germany increased rapidly. Our first results appeared at the end of March - and we are still working very intensively on the topic .
What is the difference to previous research, e.g. on the spread of the Ebola virus, compared to research on Covid-19?
With Ebola, we conducted our studies rather retrospectively, i.e. when the epidemic was almost over and the introduction of the control measure could be reconstructed. In that case we predicted the possible second wave of Ebola, which arrived in 2018. The Ebola virus has been known and researched since the seventies, therefore much about the characteristics of the virus is known today. In the case of Covid-19, we are working more in real time. We follow the epidemic's spread from the beginning, try to embed the possible introduction/enforcement or relaxation of control measures into the models by numerical simulations and estimate their effect. Moreover, we are dealing with SARS-CoV-2 (the virus that causes Covid), a virus that is still poorly known. There is yet much to learn about the virus and the disease itself. For example, in Covid-19, asymptomatic cases, i.e. infected persons who do not show symptoms, seem to play an important role in the transmission of the virus.
What factors must be taken into account when simulating epidemics?
There are many factors that could be taken into account. We are particularly interested in the dynamics of propagation in the population, i.e. how fast does a virus spread and how could this be controlled. For instance, we ask ourselves whether there could be repeated outbreaks, or according to which criteria it would be best to distribute a potential vaccine. The mathematical methods that we use are flexible - the questions that we want to answer are nevertheless specific to a particular pathogen or disease. In the case of Covid-19, for example, the age structure of the population seems to play an important role. There are also geographical factors (urban vs. rural areas), but above all the behavior of the population or the security precautions taken by the government are crucial to determine the speed at which a virus spreads.
In our simulations we consider several scenarios that describe different assumptions and we use these for model predictions.
How accurate are these simulations?
Our forecasts are quite reliable for a short time (2-3 weeks into the future). The further we want to look into the future, the more uncertainties and dynamic factors (e.g. behavior of the population, reaction of policymakers) play a role. For this reason we track our models and update our forecasts regularly.
How is it to deal with infectious diseases professionally at the moment? Aren't you overwhelmed by it when your own work is suddenly present 24 hours a day?
At the latest when the virus hit Italy (my home country) so hard I was very touched. But I don't think that's any different from people who don't work in this field. At the moment COVID-19 is present for all of us, affecting private and working life. Working on modelling the spread of the virus can also be reassuring - we have the advantage that our simulations allow us to look a bit into the future.
You have become a Fellow at FIAS as of May 2020. What do you hope for from your work here?
I find the FIAS a very exciting scientific institution and look forward to the exchange with new colleagues from different disciplines.
What will be the main focus of your research at FIAS?
In my subproject within Loewe's CMMS focus, I will develop mathematical models and methods that contribute to the understanding of multiscale processes in immunology and the dynamics of infectious diseases. While Covid-19 is a priority at the moment and determines a large part of my research, its study could lead to excellent progress for the CMMS project. In addition, the topic can be very well combined with my sepsis research. Indeed, even though any infection can lead to sepsis, patients with a severe course of COVID-19 seem to develop sepsis particularly frequently.
More information about Maria Barbarossa can be found on her Fellow profile
More about the CMMS project can be found on the project page
More information about the LOEWE initiative of the state of Hessen can be found on ProLoewe.de
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