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

Authors

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. van Panhuis, Harry Hochheiser, Marta Galanti, Teresa K Yamana, Sen Pei, Jeffrey L. Shaman, Kaitlin Rainwater-Lovett, Matt Kinsey, Kate Tallaksen, Shelby Wilson, Lauren Shin, Joseph C Lemaitre, Joshua Kaminsky, Juan Dent Hulse, Elizabeth C. Lee, Clif McKee, Alison Hill, Dean Karlen, Matteo Chinazzi, Jessica T Davis, Kunpeng Mu, Xinyue Xiong, Ana Pastore Piontti, Alessandro Vespignani, Erik T Rosenstrom, Julie S Ivy, Maria E Mayorga, Julie L Swann, Guido España, Sean Cavany, Sean Moore, Alex Perkins, Thomas J. Hladish, Alexander N. Pillai, Kok Ben Toh, Ira Longini Jr., Shi Chen, Rajib Paul, Daniel Janies, Jean-Claude Thill, Anass Bouchnita, Kaiming Bi, Michael Lachmann, Spencer Fox, Lauren Ancel Meyers, Ajitesh Srivastava, Przemyslaw Porebski, Srinivasan 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 Gunnels, Jessica M Healy, Rachel B. Slayton, Michael A Johansson, Matthew Biggerstaff, Shaun Truelove, Michael C. Runge, Katriona Shea, Cécile Viboud, Justin Lessler