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The problem of detrending when analysing potential indicators of disease elimination
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Dessavre, Adjani Gama, Southall, Emma, Tildesley, Michael J. and Dyson, Louise (2019) The problem of detrending when analysing potential indicators of disease elimination. Journal of Theoretical Biology, 481 . pp. 183-193. doi:10.1016/j.jtbi.2019.04.011 ISSN 0022-5193.
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Official URL: https://doi.org/10.1016/j.jtbi.2019.04.011
Abstract
As we strive towards the elimination of many burdensome diseases, the question of when intervention efforts may cease is increasingly important. It can be very difficult to know when prevalences are low enough that the disease will die out without further intervention, particularly for diseases that lack accurate tests. The consequences of stopping an intervention prematurely can put back elimination efforts by decades. Critical slowing down theory predicts that as a dynamical system moves through a critical transition, deviations from the steady state return increasingly slowly. We study two potential indicators of disease elimination predicted by this theory, and investigate their response using a simple stochastic model. We compare our dynamical predictions to simulations of the fluctuation variance and coefficient of variation as the system moves through the transition to elimination. These comparisons demonstrate that the primary challenge facing the analysis of early warning signs in timeseries data is that of accurately ‘detrending’ the signal, in order to preserve the statistical properties of the fluctuations. We show here that detrending using the mean of even just four realisations of the process can give a significant improvement when compared to using a moving window average. Taking this idea further, we consider a ‘metapopulation’ model of an endemic disease, in which infection spreads in various separated areas with some movement between the subpopulations. We successfully predict the behaviour of both variance and the coefficient of variation in a metapopulation by using information from the other subpopulations to detrend the system.
Item Type: | Journal Article | |||||||||
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Subjects: | Q Science > QA Mathematics R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics | |||||||||
Library of Congress Subject Headings (LCSH): | Communicable diseases -- Prevention -- Statistics, Time-series analysis | |||||||||
Journal or Publication Title: | Journal of Theoretical Biology | |||||||||
Publisher: | Elsevier | |||||||||
ISSN: | 0022-5193 | |||||||||
Official Date: | November 2019 | |||||||||
Dates: |
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Volume: | 481 | |||||||||
Page Range: | pp. 183-193 | |||||||||
DOI: | 10.1016/j.jtbi.2019.04.011 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||
Date of first compliant deposit: | 30 April 2019 | |||||||||
Date of first compliant Open Access: | 30 April 2019 | |||||||||
RIOXX Funder/Project Grant: |
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