tetano
Editor, Senior Moderator
PLoS One
. 2020 Oct 2;15(10):e0240153.
doi: 10.1371/journal.pone.0240153. eCollection 2020.
Modeling the dynamics of the COVID-19 population in Australia: A probabilistic analysis
Ali Eshragh[SUP] 1 2 [/SUP], Saed Alizamir[SUP] 3 [/SUP], Peter Howley[SUP] 1 [/SUP], Elizabeth Stojanovski[SUP] 1 [/SUP]
Affiliations
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.
. 2020 Oct 2;15(10):e0240153.
doi: 10.1371/journal.pone.0240153. eCollection 2020.
Modeling the dynamics of the COVID-19 population in Australia: A probabilistic analysis
Ali Eshragh[SUP] 1 2 [/SUP], Saed Alizamir[SUP] 3 [/SUP], Peter Howley[SUP] 1 [/SUP], Elizabeth Stojanovski[SUP] 1 [/SUP]
Affiliations
- PMID: 33007054
- DOI: 10.1371/journal.pone.0240153
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.