PropertyValue
?: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.
?:arxiv_id
  • 2005.12455
?:creator
?:doi
  • 10.1371/journal.pone.0240153
?:doi
?:journal
  • PLoS_One
?:license
  • cc-by
?:pdf_json_files
  • document_parses/pdf_json/bbb8e065313d1c791ea4dbeb7fede02e25449903.json; document_parses/pdf_json/4bbfc42fb72c8d0ef9f90b9d4829f6af6f7554b5.json
?:pmc_json_files
  • document_parses/pmc_json/PMC7531857.xml.json
?:pmcid
?:pmid
?:pmid
  • 33007054.0
?:publication_isRelatedTo_Disease
?:sha_id
?:source
  • ArXiv; Medline; PMC
?:title
  • Modeling the dynamics of the COVID-19 population in Australia: A probabilistic analysis
?:type
?:year
  • 2020-10-02

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