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Activity Number: 319 - Innovative Approaches to the Study of an Epidemic
Type: Contributed
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #309696
Title: Survival Dynamical Systems: Individual-Level Survival Analysis from Population-Level Epidemic Models
Author(s): Wasiur KhudaBukhsh* and Boseung Choi and Eben Kenah and Grzegorz Rempala
Companies: Ohio State University, Mathematical Biosciences Institute and Korea University and The Ohio State University and The Ohio State University
Keywords: SIR epidemics; Survival analysis; Dynamical systems; Mean-field methods; Survival dynamical systems; Compartmental models

Motivated by the classical Susceptible-Infected-Recovered (SIR) epidemic models proposed by Kermack and Mckendrick, we consider a class of stochastic compartmental dynamical systems with a notion of partial ordering among the compartments. We call such systems uni-directional Mass Transfer Models (MTMs). We show that there is a natural way of interpreting a uni-directional MTM as a Survival Dynamical System (SDS) that is described in terms of survival functions instead of population counts. This SDS interpretation allows us to employ tools from survival analysis to address various issues with data collection and statistical inference of unidirectional MTMs. In particular, we propose and numerically validate a statistical inference procedure based on SDS-likelihoods.

We use the SIR model as a running example to illustrate the ideas. We demonstrate how these ideas are applied in response to COVID-19 outbreak in the state of Ohio and also, at the national level in USA, Italy, China.

Authors who are presenting talks have a * after their name.

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