Author: Eshragh, Ali; Alizamir, Saed; Howley, Peter; Stojanovski, Elizabeth
Title: Modeling the Dynamics of the COVID-19 Population in Australia: A Probabilistic Analysis Cord-id: aad0yd53 Document date: 2020_5_26
ID: aad0yd53
Snippet: The novel Corona Virus 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 va
Document: The novel Corona Virus 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.
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