The model proves it: social distancing works

Understand the spread of infectious diseases Covid-19: the model demonstrates – social distancing works

04.11.2020 | Author / Publisher: Dr. Kathrin Kottke * / Dr. Ilka Ottleben

Avoiding social contact and keeping away from each other is difficult, but it is considered an effective way to protect yourself and others from infection with the SARS-CoV-2 coronavirus. Not everyone adheres to it, and critics even question the effectiveness of this relatively simple measure. But physicists from Westfälische Wilhelms-Universität Münster have now shown in model simulations that the number of Covid 19 infections is significantly decreasing due to “social distancing”.

Münster – Following the global epidemic of Covid-19 disease caused by the new coronavirus SARS-CoV-2, scientists around the world are working at full speed on infectious disease research. This applies not only to virologists, but also to physicists who develop mathematical models to describe the spread of epidemics. Such models are important in order to test the effects of various measures to contain the disease – such as face masks, closures of public buildings and shops, or the notorious “social distancing”, ie keeping a distance to avoid contagion. These models often serve as a basis for political decisions and reinforce the legitimacy of the measures taken.

Understand the spread of infectious diseases

Physicists Michael te Vrugt, Jens Bickmann and Prof. Dr. Raphael Wittkowski from the Institute for Theoretical Physics and the Center for Soft Nanosciences of the Westfälische Wilhelms-Universität Münster (WWU) have developed a new model for the spread of contagious diseases. Raphael Wittkowski’s working group deals with statistical physics, that is, the description of systems consisting of a large number of particles. Among other things, physicists use the “functional theory of dynamic density” (DDFT), a method developed in the 1990s that allows for the description of interacting particles.

At the start of the corona pandemic, they thought that the same method would be useful for describing the spread of disease. “People who practice social distancing – who try to keep their distance from each other – can in principle be imagined as particles that repel each other because, for example, they have the same electrical charge,” explains the first author Michael te Vrugt. “So you can perhaps apply theories describing repulsive particles to people who keep their distance from each other.”

How social distancing works

Based on this idea, they developed the so-called “SIR-DDFT model”, which combines the SIR model (a well-known theory for describing the spread of infectious diseases) with DDFT. The resulting theory describes people who can infect each other, but who also keep their distance from each other. “It also allows us to describe the space hotspots of infected people and thus to better understand the dynamics of so-called ‘superspreader events’ such as the Heinsberg carnival or après-ski in Ischgl,” adds co-author Jens Bickmann. The study results have now been published in the journal Nature Communications.

The extent of social distancing is then described by the strength of the repulsive interaction. “This means that the theory can also be used to test the effects of social distancing by simulating an epidemic with different parameter values ​​that describe the strength of the interaction,” says study leader Raphael Wittkowski.

Simulations show that the number of infections actually decreases significantly due to social distancing. The model thus reproduces the well-known “Flatten-The-Curve-Effect”, in which the curve describing the trend over time in the number of patients becomes considerably flatter due to the maintenance of distances. Compared to existing theories, the new model has the advantage that the effects of social interactions can be modeled explicitly.

Originalpublikation: M. te Vrugt, J. Bickmann, R. Wittkowski (2020). Effects of social distancing and isolation on epidemic spread modeled by functional theory of dynamic density. Nature Communications, DOI: 10.1038 / s41467-020-19024-0

* Dr. K. Kottke: Westfälische Wilhelms-Universität Münster, 48149 Münster

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