Emergent effects of contact tracing robustly stabilize outbreaks

Covid-19 neither dissolved nor got out of control over a year. In many instances, the new daily cases exhibit an equilibrium at a meagre percentage of the population. Seemingly impossible due to the precise cancellation of positive and negative effects. Here, I propose models on real-world networks that capture the mysterious dynamics. I investigate the contact-tracing and related effects as possible causes. I differentiate the impact of contact-tracing into three--one direct and two emergent--effects: isolation of the documented patients direct infectees (descendants), isolation of non-descendant infectees, and temporary isolation of susceptible contacts. Contrary to expectation, isolation of descendants cannot stabilize an equilibrium; based on current data, the effect of the latter two are necessary and greater in effect overall. The reliance on emergent effects shows that even if contact-tracing is 100% efficient, its effect on the epidemic dynamics would be dependent. Moreover, This newly characterized dynamic claims that all outbreaks will eventually show such stable dynamics.