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Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.

Authors :
Howerton E
Contamin L
Mullany LC
Qin M
Reich NG
Bents S
Borchering RK
Jung SM
Loo SL
Smith CP
Levander J
Kerr J
Espino J
van Panhuis WG
Hochheiser H
Galanti M
Yamana T
Pei S
Shaman J
Rainwater-Lovett K
Kinsey M
Tallaksen K
Wilson S
Shin L
Lemaitre JC
Kaminsky J
Hulse JD
Lee EC
McKee CD
Hill A
Karlen D
Chinazzi M
Davis JT
Mu K
Xiong X
Pastore Y Piontti A
Vespignani A
Rosenstrom ET
Ivy JS
Mayorga ME
Swann JL
España G
Cavany S
Moore S
Perkins A
Hladish T
Pillai A
Ben Toh K
Longini I Jr
Chen S
Paul R
Janies D
Thill JC
Bouchnita A
Bi K
Lachmann M
Fox SJ
Meyers LA
Srivastava A
Porebski P
Venkatramanan S
Adiga A
Lewis B
Klahn B
Outten J
Hurt B
Chen J
Mortveit H
Wilson A
Marathe M
Hoops S
Bhattacharya P
Machi D
Cadwell BL
Healy JM
Slayton RB
Johansson MA
Biggerstaff M
Truelove S
Runge MC
Shea K
Viboud C
Lessler J
Source :
Nature communications [Nat Commun] 2023 Nov 20; Vol. 14 (1), pp. 7260. Date of Electronic Publication: 2023 Nov 20.
Publication Year :
2023

Abstract

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.<br /> (© 2023. The Author(s).)

Details

Language :
English
ISSN :
2041-1723
Volume :
14
Issue :
1
Database :
MEDLINE
Journal :
Nature communications
Publication Type :
Academic Journal
Accession number :
37985664
Full Text :
https://doi.org/10.1038/s41467-023-42680-x