Survival dynamical systems: individual-level survival analysis from population-level epidemic models.

Abstract:

:In this paper, we show that solutions to ordinary differential equations describing the large-population limits of Markovian stochastic epidemic models can be interpreted as survival or cumulative hazard functions when analysing data on individuals sampled from the population. We refer to the individual-level survival and hazard functions derived from population-level equations as a survival dynamical system (SDS). To illustrate how population-level dynamics imply probability laws for individual-level infection and recovery times that can be used for statistical inference, we show numerical examples based on synthetic data. In these examples, we show that an SDS analysis compares favourably with a complete-data maximum-likelihood analysis. Finally, we use the SDS approach to analyse data from a 2009 influenza A(H1N1) outbreak at Washington State University.

journal_name

Interface Focus

journal_title

Interface focus

authors

KhudaBukhsh WR,Choi B,Kenah E,Rempała GA

doi

10.1098/rsfs.2019.0048

subject

Has Abstract

pub_date

2020-02-06 00:00:00

pages

20190048

issue

1

eissn

2042-8898

issn

2042-8901

pii

rsfs20190048

journal_volume

10

pub_type

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