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Simulating the spread of COVID-19 with BioDynaMo

Added: Over a year ago by CERN

In the wake of the COVID-19 pandemic, understanding how the virus spreads is crucial for governments when deciding on mobility restrictions, implementation of lockdown, and protective materials usage. Capable of simulating a large number of agents, platforms such as BioDynaMo are making a difference by sharpening our knowledge of crowd behaviour.

Originally designed to simulate the behaviour of billions of cells under specified environmental conditions, the BioDynaMo engine showed interesting potential for creating agent-based systems for the simulation of human behaviours, allowing epidemiologists to model different epidemic scenarios. Within the scope of the CERN against COVID-19 task force, this open-source software could be easily modified to simulate how the SARS-CoV-2 virus spreads through a population.

First started as a CERN openlab project, BioDynaMo received seed funding from the CERN Medical Applications budget of 233 000 CHF over 5 years in order to improve its scalability and performances. At the peak of the first wave of the pandemic, the Medical Applications (MA) section in CERN’s Knowledge Transfer group further supported BioDynaMo. Its network enabled a collaboration with the University of Geneva’s Institute of Global Health for the implementation of a COVID-19 localised spreading model. Also, the MA section assisted the team in getting a grant from the European Open Science Cloud (EOSC) to develop the model yet more.

The project is expected to provide valuable insights to help the scientific community in their studies, as well as governments in their decision making. Also, its visually appealing models have an educational value as they clearly underline the benefit of sensible social behaviour to prevent the spread of the disease.

Beyond the coronavirus pandemic, the know-how gathered from this project is useful to counter similar viruses and future outbreaks. As such, the trove of experimental data gathered from the current pandemic can be used to tune models and simulations to be more precise next time.

Finally, the project will contribute to the EOSC Portal Catalogue and Marketplace by providing a service, openly accessible to the scientific community to predict the virus’ behaviour, and study how quarantines, confinements and social distancing influence the spreading panorama.

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