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Universal Statistics of Incubation Periods and Other Detection Times via Diffusion Models

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Abstract

We suggest an explanation of typical incubation times statistical features based on the universal behavior of exit times for diffusion models. We give a mathematically rigorous proof of the characteristic right skewness of the incubation time distribution for very general one-dimensional diffusion models. Imposing natural simple conditions on the drift coefficient, we also study these diffusion models under the assumption of noise smallness and show that the limiting exit time distributions in the limit of vanishing noise are Gaussian and Gumbel. Thus, they match the existing data as well as the other existing models do. The character of our models, however, allows us to argue that the features of the exit time distributions that we describe are universal and manifest themselves in various other situations where the times involved can be described as detection or halting times, for example response times studied in psychology.

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Acknowledgements

The author is grateful to Charles Peskin and Percy Deift for bringing Ottino-Löffler et al. (2017a) to his attention. He also thanks them for stimulating discussions and encouragement.

Funding

Funding was provided by National Science Foundation (Grant No. DMS-1811444).

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Correspondence to Yuri Bakhtin.

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Bakhtin, Y. Universal Statistics of Incubation Periods and Other Detection Times via Diffusion Models. Bull Math Biol 81, 1070–1088 (2019). https://doi.org/10.1007/s11538-018-00558-w

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