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

Emily Howerton (), Lucie Contamin, Luke C. Mullany, Michelle Qin, Nicholas G. Reich, Samantha Bents, Rebecca K. Borchering, Sung-mok Jung, Sara L. Loo, Claire P. Smith, John Levander, Jessica Kerr, J. Espino, Willem G. Panhuis, Harry Hochheiser, Marta Galanti, Teresa Yamana, Sen Pei, Jeffrey Shaman, Kaitlin Rainwater-Lovett, Matt Kinsey, Kate Tallaksen, Shelby Wilson, Lauren Shin, Joseph C. Lemaitre, Joshua Kaminsky, Juan Dent Hulse, Elizabeth C. Lee, Clifton D. McKee, Alison Hill, Dean Karlen, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Xinyue Xiong, Ana Pastore y Piontti, Alessandro Vespignani, Erik T. Rosenstrom, Julie S. Ivy, Maria E. Mayorga, Julie L. Swann, Guido España, Sean Cavany, Sean Moore, Alex Perkins, Thomas Hladish, Alexander Pillai, Kok Toh, Ira Longini, Shi Chen, Rajib Paul, Daniel Janies, Jean-Claude Thill, Anass Bouchnita, Kaiming Bi, Michael Lachmann, Spencer J. Fox, Lauren Ancel Meyers, Ajitesh Srivastava, Przemyslaw Porebski, Srini Venkatramanan, Aniruddha Adiga, Bryan Lewis, Brian Klahn, Joseph Outten, Benjamin Hurt, Jiangzhuo Chen, Henning Mortveit, Amanda Wilson, Madhav Marathe, Stefan Hoops, Parantapa Bhattacharya, Dustin Machi, Betsy L. Cadwell, Jessica M. Healy, Rachel B. Slayton, Michael A. Johansson, Matthew Biggerstaff, Shaun Truelove, Michael C. Runge, Katriona Shea, Cécile Viboud () and Justin Lessler ()
Additional contact information
Emily Howerton: The Pennsylvania State University
Lucie Contamin: University of Pittsburgh
Luke C. Mullany: Johns Hopkins University Applied Physics Lab
Michelle Qin: Harvard University
Nicholas G. Reich: University of Massachusetts Amherst
Samantha Bents: National Institutes of Health Fogarty International Center
Rebecca K. Borchering: The Pennsylvania State University
Sung-mok Jung: University of North Carolina at Chapel Hill
Sara L. Loo: Johns Hopkins University
Claire P. Smith: Johns Hopkins University
John Levander: University of Pittsburgh
Jessica Kerr: University of Pittsburgh
J. Espino: University of Pittsburgh
Willem G. Panhuis: National Institute of Allergy and Infectious Diseases
Harry Hochheiser: University of Pittsburgh
Marta Galanti: Columbia University
Teresa Yamana: Columbia University
Sen Pei: Columbia University
Jeffrey Shaman: Columbia University
Kaitlin Rainwater-Lovett: Johns Hopkins University Applied Physics Lab
Matt Kinsey: Johns Hopkins University Applied Physics Lab
Kate Tallaksen: Johns Hopkins University Applied Physics Lab
Shelby Wilson: Johns Hopkins University Applied Physics Lab
Lauren Shin: Johns Hopkins University Applied Physics Lab
Joseph C. Lemaitre: University of North Carolina at Chapel Hill
Joshua Kaminsky: Johns Hopkins University
Juan Dent Hulse: Johns Hopkins University
Elizabeth C. Lee: Johns Hopkins University
Clifton D. McKee: Johns Hopkins University
Alison Hill: Johns Hopkins University
Dean Karlen: University of Victoria
Matteo Chinazzi: Northeastern University
Jessica T. Davis: Northeastern University
Kunpeng Mu: Northeastern University
Xinyue Xiong: Northeastern University
Ana Pastore y Piontti: Northeastern University
Alessandro Vespignani: Northeastern University
Erik T. Rosenstrom: North Carolina State University
Julie S. Ivy: North Carolina State University
Maria E. Mayorga: North Carolina State University
Julie L. Swann: North Carolina State University
Guido España: University of Notre Dame
Sean Cavany: University of Notre Dame
Sean Moore: University of Notre Dame
Alex Perkins: University of Notre Dame
Thomas Hladish: University of Florida
Alexander Pillai: University of Florida
Kok Toh: Northwestern University
Ira Longini: University of Florida
Shi Chen: University of North Carolina at Charlotte
Rajib Paul: University of North Carolina at Charlotte
Daniel Janies: University of North Carolina at Charlotte
Jean-Claude Thill: University of North Carolina at Charlotte
Anass Bouchnita: University of Texas at El Paso
Kaiming Bi: University of Texas at Austin
Michael Lachmann: Santa Fe Institute
Spencer J. Fox: University of Georgia
Lauren Ancel Meyers: University of Texas at Austin
Ajitesh Srivastava: University of Southern California
Przemyslaw Porebski: University of Virginia
Srini Venkatramanan: University of Virginia
Aniruddha Adiga: University of Virginia
Bryan Lewis: University of Virginia
Brian Klahn: University of Virginia
Joseph Outten: University of Virginia
Benjamin Hurt: University of Virginia
Jiangzhuo Chen: University of Virginia
Henning Mortveit: University of Virginia
Amanda Wilson: University of Virginia
Madhav Marathe: University of Virginia
Stefan Hoops: University of Virginia
Parantapa Bhattacharya: University of Virginia
Dustin Machi: University of Virginia
Betsy L. Cadwell: Centers for Disease Control and Prevention
Jessica M. Healy: Centers for Disease Control and Prevention
Rachel B. Slayton: Centers for Disease Control and Prevention
Michael A. Johansson: Centers for Disease Control and Prevention
Matthew Biggerstaff: Centers for Disease Control and Prevention
Shaun Truelove: Johns Hopkins University
Michael C. Runge: U.S. Geological Survey Eastern Ecological Science Center
Katriona Shea: The Pennsylvania State University
Cécile Viboud: National Institutes of Health Fogarty International Center
Justin Lessler: University of North Carolina at Chapel Hill

Nature Communications, 2023, vol. 14, issue 1, 1-15

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-42680-x

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