Our COVID-19 Research on analysis of competing strains published in Nature Scientific Reports

The work analyzes the competition among viral strains using our developed temporal interaction-driven contagion model. We consider two and three competing pathogens and show the conditions under which a slower pathogen will remain active and create a second wave infecting most of the population. We then show that when the duration of the encounters is considered, the spreading dynamics change significantly. Our results indicate that when considering airborne diseases, it might be crucial to consider the duration of temporal meetings to model the spread of pathogens in a population. The paper can be found here: https://rdcu.be/cPonP.

The code for the project is freely available from our Github: https://github.com/ScanLab-ossi/covid-simulation.

The work was led by SCANLab's RA Alex Abbey and our PI Osnat Mokryn, in collaboration with Prof. Yuval Shahar from Ben-Gurion University.