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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Bibliographic Details
Published inJAMA Vol. 323; no. 19; pp. 1893 - 1894
Main Authors Jewell, Nicholas P, Lewnard, Joseph A, Jewell, Britta L
Format Journal Article Web Resource
LanguageEnglish
Published United States American Medical Association 19.05.2020
Subjects
Betacoronavirus
Coronavirus Infections - epidemiology
Coronavirus Infections - mortality
Coronaviruses
COVID-19
Forecasting
Humans
Mathematical models
Models, Theoretical
Pandemics
Pneumonia, Viral - epidemiology
Pneumonia, Viral - mortality
SARS-CoV-2
United States - epidemiology
United States
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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.
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