Author: Emma Southall; Michael J. Tildesley; Louise Dyson
Title: Prospects for detecting early warning signals in discrete event sequence data: application to epidemiological incidence data Document date: 2020_4_2
ID: dp4qv77q_11
Snippet: In this paper we focus on the application of EWS to disease elimination where there is a 111 limited understanding on how time series statistics of incidence data behaves on the 112 approach towards this threshold. We consider two simple models, where disease 113 elimination is forced with different mechanisms, to explore how EWS of disease 114 elimination behave for prevalence and incidence data. To demonstrate the broadness of 115 our results, .....
Document: In this paper we focus on the application of EWS to disease elimination where there is a 111 limited understanding on how time series statistics of incidence data behaves on the 112 approach towards this threshold. We consider two simple models, where disease 113 elimination is forced with different mechanisms, to explore how EWS of disease 114 elimination behave for prevalence and incidence data. To demonstrate the broadness of 115 our results, we additionally present a comparative case study to the analytical results (SDEs) that describe the analytical behaviour of prevalence in these systems.
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