Random time transformation analysis of Covid19 2020

Speaker: Isaac Meilijson
Tel Aviv University

Date: Jun 18, 2020 at 14:30

Abstract: The SIR epidemiological equations model new affected and removed cases as roughly proportional to the current number of infected cases. An alternative that has been considered in the literature will be adopted, in which the number of new affected cases is proportional to the \(\alpha\) power of the number of infected cases. After arguing that \(\alpha = 1\) models exponential growth while \(\alpha <1\) models polynomial growth, a simple method for parameter estimation in differential equations subject to noise, the random-time transformation RTT of Bassan, Meilijson, Marcus and Talpaz 1997, will be reviewed and applied in an attempt to settle the question as to the nature of Covid19.

Venue: Online via Zoom
Coordinators: Prof. Joaquín Fontbona & Prof. Daniel Remenik