About

The COVID-19 pandemic has highlighted the importance of disease models for situational awareness, decision-making, and planning. Experience in domains from weather to infectious diseases, has shown that synthesizing results from multiple models gives more reliable projections than results from any one model alone. Single model projections are particularly problematic for emerging infections where there is considerable uncertainty about basic epidemiological parameters (such as the proportion of asymptomatic individuals and the waning of immunity), the transmission process, future policies and their impact, and population behavior. Combining outputs from multiple models can be particularly crucial for scenario projections several months into the future; these projections address what could happen under a particular set of circumstances (including but not limited to interventions, changes in disease epidemiology, and/or population behavior). The COVID-19 Scenario Modeling Hub (SMH) was created in December 2020 to provide multiple rounds of real-time, long-term scenario projections in the US for the federal and local health authorities, other decision makers and public health experts, and the general public. Notably, SMH projections were used to guide the expansion of the primary COVID-19 vaccine schedule to school-age children in 2021, and booster recommendations in fall 2022. Since the inception of the COVID-19 Scenario Modeling Hub, we have launched a series of companion hubs to address other important public health needs and scientific questions. Active hubs include the Flu Scenario Modeling Hub (launched August 2022), the RSV Scenario Modeling Hub (launched October 2023) and the COVID-19 Research Scenario Modeling Hub (launched March 2024).

The Scenario Modeling Hub built on prior pandemic efforts to look at short-term forecasting (as exemplified by the COVID-19 Forecast Hub , which combines the predictions of over 30 models ), the Multiple Models for Outbreak Decision Support (MMODS) comparison of the impact of COVID-19 interventions in the early stages of the pandemic, as well as prior multi-model forecasting efforts for flu , dengue , and Ebola , (see also a comparison of multiple models for Ebola interventions and Influenza interventions ). An overview of some key Hubs can be found here.

Please consult the home page of each Scenario Modeling Hub to explore past scenario projections, visit the associated GitHub repository, and learn how to participate.

Additional Resources

  • Special Issue in Epidemics featuring articles by contributing teams: https://www.sciencedirect.com/journal/epidemics/special-issue/10HZPZ2MRPX
    Two articles in particular regarding the operations of the Hub and its impacts:

    • Loo, S. L., Howerton, E., Contamin, L., et al. (2024). The US COVID-19 and Influenza Scenario Modeling Hubs: delivering long-term projections to guide policy. Epidemics, 46, 100738. DOI: https://doi.org/10.1016/j.epidem.2023.100738
    • Borchering, R. K., Healy, J. M., Cadwell, B. L., Johansson, M. A., Slayton, R. B., Wallace, M., & Biggerstaff, M. (2023). Public health impact of the US Scenario Modeling Hub. Epidemics, 44, 100705. DOI: https://doi.org/10.1016/j.epidem.2023.100705

  • COVID-19 Scenario Modeling Hub Round 17 results used in the ACIP decision to authorize boosters to all age groups leading up to winter 2023:

    • Jung, S. M., Loo, S. L., Howerton, E., et al. (2023). Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the US COVID-19 Scenario Modeling Hub. medRxiv.

  • Principles in SMH scenario design:

    • Runge, M. C., Shea, K., Howerton, E., et al. (2023). Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design. medRxiv.

  • COVID-19 Scenario Modeling Hub evaluation analyses are presented in:

    • Emily Howerton, Lucie Contamin, Luke C. Mullany, Michelle Qin, Nicholas G. Reich, Samantha Bents, Rebecca K. Borchering, et al. 2023. Evaluation of the US COVID-19 Scenario Modeling Hub for Informing Pandemic Response under Uncertainty. Nature Communications 14 (1): 7260. DOI: https://doi.org/10.1038/s41467-023-42680-x .

  • Biggerstaff et al. 2022 talks about how the CDC used the Scenario Modeling Hub during the pandemic in March 2022; Clinical Infectious diseases:

    • M. Biggerstaff, R. B. Slayton, M. A. Johansson, J. C. Butler, Improving Pandemic Response: Employing Mathematical Modeling to Confront Coronavirus Disease 2019. Clin Infect Dis. 2022 Mar 9;74(5):913-917. DOI: https://dx.doi.org/10.1093/cid/ciab673

  • COVID-19 Scenario Modeling Hub Round 14/15 results used in the ACIP decision to authorize the bivalent booster in fall 2022 on November 11, 2022; MMWR:

    • Rosenblum HG, Wallace M, Godfrey M, et al. Interim Recommendations from the Advisory Committee on Immunization Practices for the Use of Bivalent Booster Doses of COVID-19 Vaccines — United States, October 2022. MMWR Morb Mortal Wkly Rep 2022;71:1436–1441.DOI: https://dx.doi.org/10.15585/mmwr.mm7145a2

  • Inputs on Advisory Committee on Immunization Practices and Vaccines and Related Biological Products Advisory Committee meetings 2021-2022:

  • COVID-19 Scenario Modeling Hub Round 9 results published in January 2023; Lancet Regional Health - Americas:

    • R. K. Borchering, et al., Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: A multi-model study. Lancet Reg Health Am 17, 100398 (2023). DOI: https://doi.org/10.1016/j.lana.2022.100398

  • COVID-19 Scenario Modeling Hub Round 6/7 results published in June 2022; eLife:

    • S. Truelove, et al., Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination. eLife 11, e73584 (2022). DOI: https://doi.org/10.7554/eLife.73584

  • COVID-19 Scenario Modeling Hub Round 4 results published in May 14, 2021; MMWR:

    • Borchering RK, Viboud C, Howerton E, et al., Modeling of Future COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Rates and Nonpharmaceutical Intervention Scenarios — United States, April–September 2021. MMWR Morb Mortal Wkly Rep 2021; 70:719–724. DOI: https://dx.doi.org/10.15585/mmwr.mm7019e3