  The temporal dynamics of social interactions were shown to influence the
spread of disease. Here, we model the conditions of progression and competition
for several viral strains, exploring various levels of cross-immunity over
temporal networks. We use our interaction-driven contagion model and
characterize, using it, several viral variants. Our results, obtained on
temporal random networks and on real-world interaction data, demonstrate that
temporal dynamics are crucial to determining the competition results. 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.
