Modeling the dynamics of the COVID-19 population in Australia: a probabilistic analysis

Ali Eshragh; Saed Alizamir; Peter Howley; Elizabeth Stojanovski

doi:10.1371/journal.pone.0240153

Modeling the dynamics of the COVID-19 population in Australia: a probabilistic analysis

Ali Eshragh^*, Saed Alizamir, Peter Howley, Elizabeth Stojanovski

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

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Abstract

The novel coronavirus COVID-19 arrived on Australian shores around 25 January 2020. This paper presents a novel method of dynamically modeling and forecasting the COVID-19 pandemic in Australia with a high degree of accuracy and in a timely manner using limited data; a valuable resource that can be used to guide government decision-making on societal restrictions on a daily and/or weekly basis. The "partially-observable stochastic process"used in this study predicts not only the future actual values with extremely low error, but also the percentage of unobserved COVID-19 cases in the population. The model can further assist policy makers to assess the effectiveness of several possible alternative scenarios in their decision-making processes.

Original language	English
Article number	e0240153
Pages (from-to)	1-19
Number of pages	19
Journal	PLoS ONE
Volume	15
Issue number	10
DOIs	https://doi.org/10.1371/journal.pone.0240153
Publication status	Published - 2 Oct 2020
Externally published	Yes

Bibliographical note

Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

A correction exists for this article and can be found in PLoS ONE (2022) Vol 17(8) art. e0272762 at doi: 10.1371/journal.pone.0272762

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10.1371/journal.pone.0240153Licence: CC BY

Publisher version (open access)Final published version, 1.86 MBLicence: CC BY

Cite this

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Modeling the dynamics of the COVID-19 population in Australia: a probabilistic analysis

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