Evaluating data-driven methods for short-term forecasts of cumulative SARS-CoV2 cases
Evaluating data-driven methods for short-term forecasts of cumulative SARS-CoV2 cases
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Publisher
San Francisco: Public Library of Science
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Language
English
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Publisher
San Francisco: Public Library of Science
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Contents
The WHO announced the epidemic of SARS-CoV2 as a public health emergency of international concern on 30th January 2020. To date, it has spread to more than 200 countries and has been declared a global pandemic. For appropriate preparedness, containment, and mitigation response, the stakeholders and policymakers require prior guidance on the propaga...
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Full title
Evaluating data-driven methods for short-term forecasts of cumulative SARS-CoV2 cases
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TN_cdi_plos_journals_2530362667
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2530362667
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ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0252147
