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_68
Snippet: Prior work has shown that variance in incidence increases on the approach towards 478 disease emergence. However, our work highlights that this property is not a result from 479 critical slowing down theory as first expected. We have shown it is a consequence of the 480 counting process that can approximate incidence-type data. As such, we demonstrated 481 that the variance in incidence is expected to follow the mean in incidence. In particular, .....
Document: Prior work has shown that variance in incidence increases on the approach towards 478 disease emergence. However, our work highlights that this property is not a result from 479 critical slowing down theory as first expected. We have shown it is a consequence of the 480 counting process that can approximate incidence-type data. As such, we demonstrated 481 that the variance in incidence is expected to follow the mean in incidence. In particular, 482 the variance will increase on the approach to disease emergence, but will notably 483 decrease before a disease elimination threshold. We applied these findings to two 484 systems of disease elimination and verified that variance of incidence exhibits a 485 decreasing trend on the approach, following the behaviour of the mean and 486 contradicting critical slowing down theory.
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