The United States COVID-19 Forecast Hub dataset
Estee Y. Cramer, Yuxin Huang, Yijin Wang, Evan L Ray, Matthew Cornell, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Aaron Gerding, Katie House, Dasuni Jayawardena, Abdul Hannan Kanji, Ayush Khandelwal, Khoa Le, Vidhi Mody, Vrushti Mody, Jarad Niemi, Ariane Stark, Apurv Shah, Nutcha Wattanchit, Martha Zorn, Nicholas G Reich, Tilmann Gneiting, Anja Mühlemann, Youyang Gu, Yixian Chen, Krishna Chintanippu, Viresh Jivane, Ankita Khurana, Ajay Kumar, Anshul Lakhani, Prakhar Mehrotra, Sujitha Pasumarty, Monika Shrivastav, Jialu You, Nayana Bannur, Ayush Deva, Sansiddh Jain, Mihir Kulkarni, Srujana Merugu, Alpan Raval, Siddhant Shingi, Avtansh Tiwari, Jerome White, Aniruddha Adiga, Benjamin Hurt, Bryan Lewis, Madhav Marathe, Akhil Sai Peddireddy, Przemyslaw Porebski, Srinivasan Venkatramanan, Lijing Wang, Maytal Dahan, Spencer J. Fox, Kelly Gaither, Michael Lachmann, Lauren Ancel Meyers, James G. Scott, Mauricio Tec, Spencer Woody, Ajitesh Srivastava, Tianjian Xu, Jeffrey C. Cegan, Ian Dettwiller, William P. England, Matthew W. Farthing, Glover George, Robert H. Hunter, Brandon J. Lafferty, Igor Linkov, Michael L. Mayo, Matthew Parno, Michael A. Rowland, Benjamin D. Trump, Samuel Chen, Stephen V. Faraone, Jonathan Hess, Christopher P. Morley, Asif Salekin, Dongliang Wang, Yanli Zhang‐James, T. M. Baer, Sabrina Corsetti, Marisa C. Eisenberg, Karl Falb, Yitao Huang, Emily T. Martin, Ella McCauley, Robert L. Myers, Tom Schwarz, Graham Gibson, Daniel Sheldon, Liyao Gao, Yi-An Ma, Dongxia Wu, Rose Yu, Xiaoyong Jin, Yuxiang Wang, Xifeng Yan, YangQuan Chen
Abstract
Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.