Scenario Modeling Hub
This Scenario Modeling Hub (SMH), is a community effort designed to produce medium and longer-term scenario projections to guide pandemic and epidemic response. These scenarios are designed in association with decision makers to address areas of uncertainty in public health decision-making. Long-term scenario projections support comparison of potential outbreak trajectories under different scenarios of what “might” happen, as opposed to offering specific, unconditional estimates of what “will” happen.
The SMH is organized by “rounds” responding to specific public health questions. For each round, the SMH coordination team creates scenarios designed to explore a range of possible futures along two dimensions – for example, vaccination timing and the emergence of a new variant. Multiple modeling teams use methods of their choosing to project what might happen in these possible futures. Models from these individual groups are then combined mathematically to develop consensus models – known as ensembles – which are more accurate and consistent than any of the individual models.
The model and ensemble projections are summarized and available on the Scenario Modeling Hub website. For example, the COVID-19 round 19 was focused on comparing different timing and population targets in vaccination campaigns between April 27, 2025 and April 25, 2026. This round found that compared to no vaccination, vaccination of high-risk groups reduces hospitalizations by 13% (8-17%) and deaths by 16% (11-23%), vaccination for all age groups increases these reductions to 116,000 (69,000-163,000) hospitalizations and 9,000 (5,000-12,000) deaths averted (Figure 1). For more information and details, please consult the COVID-19 Scenario Modeling Hub.
The SMH was created during the COVID-19 pandemic, building on the experiences of Multi-Model Outbreak Decision Support (MMODS) and the COVID-19 Forecast Hub and evolved to provide projections for COVID-19, Influenza and RSV in the US, along with research efforts aimed at projections across heterogeneous publications and in the initial phases in an emerging pandemic.
Those interested to participate, please email us at scenariohub@midasnetwork.us.
The SMH efforts have evolved into several specific areas of concentration:
The COVID-19 Scenario Modeling Hub aims to examine the impact of changes in behavior and control, new variants, and vaccination over a 3-month to 2-year time period, depending on the round.
The FLU Scenario Modeling Hub aims to anticipate the impact of changes in vaccination coverage and effectiveness, prior population immunity, and dominant subtypes over the course of each influenza season.
The RSV Scenario Modeling Hub aims to project the impacts of new vaccines and monoclonal antibodies over the course of each RSV season.
The COVID-19 Research Scenario Modeling Hub is intended to encourage modeling to address specific COVID-19 research questions.
Specific focus areas in the pipeline include revisiting whether we could have projected the disparities observed during early stages of the pandemic and whether
better modeling may have been able to inform action to reduce these disparities.
Additional research topics may follow.
The Pandemic cryptic phase modeling hub modeling rounds will develop modeling capabilities to address the early stages of a new pandemic in situations of limited data and high uncertainty. We will consider the emergence of a hypothetical pathogen as a case study.