Predictive Mathematical Models of the COVID-19 Pandemic: Underlying Principles and Value of Projections
This Viewpoint discusses the challenges of accurately modeling the COVID-19 pandemic and reviews principles that will make some models more useful than others, such as use of granular local data when available, regular updating and revision, and specification of uncertainty around estimates.
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Published in | JAMA Vol. 323; no. 19; pp. 1893 - 1894 |
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Main Authors | , , |
Format | Journal Article Web Resource |
Language | English |
Published |
United States
American Medical Association
19.05.2020
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Subjects | |
Online Access | Get full text |
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Summary: | This Viewpoint discusses the challenges of accurately modeling the COVID-19 pandemic and reviews principles that will make some models more useful than others, such as use of granular local data when available, regular updating and revision, and specification of uncertainty around estimates. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0098-7484 1538-3598 |
DOI: | 10.1001/jama.2020.6585 |