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 Focusjournal_title
Interface focusauthors
KhudaBukhsh WR,Choi B,Kenah E,Rempała GAdoi
10.1098/rsfs.2019.0048subject
Has Abstractpub_date
2020-02-06 00:00:00pages
20190048issue
1eissn
2042-8898issn
2042-8901pii
rsfs20190048journal_volume
10pub_type
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