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April 16, 2020

Predictive Mathematical Models of the COVID-19 Pandemic

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Abstract

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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Authors

Nicholas P. Jewell

London School of Hygiene & Tropical Medicine

Joseph A. Lewnard

Berkeley College

Britta L. Jewell

San Francisco General Hospital

Journals

JAMA

Actions

Institutions

University of California, Berkeley

Imperial College London

London School of Hygiene & Tropical Medicine

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Jewell et al. (Thu,) studied this question.

synapsesocial.com/papers/69df0c495fcfdd352559179a — DOI: https://doi.org/10.1001/jama.2020.6585

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Strategies for containing an emerging influenza pandemic in Southeast Asia· 2005 · 1,878 citations

Also consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

What makes an academic paper useful for health policy?· 2015 · 205 citations
Special report: The simulations driving the world’s response to COVID-19· 2020 · 481 citations
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe· 2020 · 700 citations
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China· 2020 · 51,774 citations
Strategies for containing an emerging influenza pandemic in Southeast Asia· 2005 · 1,878 citations

Predictive Mathematical Models of the COVID-19 Pandemic

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

Cite this study

Also consider

Also consider