What is meant with persistence time in stochastic models?

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I've been reading about epidemiological modeling using stochastic models (discrete/continuous Markov chains and stochastic differential equations). I've come across the term persistence time multiple time. (e.g. see this paper: https://www.sciencedirect.com/science/article/pii/S0040580903001047) But there is no explanation what exactly is meant with persistence time and I don't quite get it on my own. Is persistence time related to the amount of time the model spends in the quasi-stationary state?

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In the specific context of epidemiological and population models, persistence time refers to the time for which a given epidemic/population survived. This means the time from the first infection (in an epidemic) to the time till it dies out. You can think of this in the context of the coronavirus pandemic, right? We're all trying to figure out how long will it 'persist'. In terms of population models, persistence time refers to the time between the initial colonisation of a species and its eventual extinction.

However, the concept of persistence can be thought to be very general and you can get a good overview of persistence in stochastic processes and its different aspects in this very well written review: https://arxiv.org/abs/1304.1195