Last updated: 2025-04-17.
https://fluscenariomodelinghub.org/viz.html
Previous rounds (round 1 to round 1 of 2024-2025 (round 5)) are available in the Flu Scenario Modeling Hub - Archive GitHub Repository
Even the best models of infectious disease transmission struggle to give accurate forecasts at time scales greater than 3-4 weeks due to unpredictable drivers like changing policy environments, behavior change, development of new control measures, and stochastic events. However, policy decisions around the course of infectious diseases, particularly emerging and seasonal infections, often require projections in the time frame of months. The goal of long-term projections is to compare outbreak trajectories under different scenarios, as opposed to offering a specific, unconditional estimate of what “will” happen. As such, long-term projections can guide longer-term decision-making while short-term forecasts are more useful for situational awareness and guiding immediate response.
We have specified a set of scenarios and target outcomes to allow alignment of model projections for collective insights. Scenarios have been designed in consultation with academic modeling teams and government agencies (e.g., CDC).
This repository follows the guidelines and standards outlined by the hubverse, which provides a set of data formats and open source tools for modeling hubs.
The Flu Scenario Modeling Hub is open to any team willing to provide projections at the right temporal and spatial scales, with minimal gatekeeping. We only require that participating teams share point estimates and uncertainty bounds, along with a short model description and answers to a list of key questions about design. A major output of the projection hub is ensemble estimates of epidemic outcomes (e.g., infection, hospitalizations, and deaths), for different time points, intervention scenarios, and US jurisdictions.
Those interested to participate, please read the README file and email us at [email protected].
Model projections should be submitted via pull request to the data-processed folder of this GitHub repository. Technical instructions for submission and required file formats can be found here.
Future round information will be available in this section (TBA).
Groups interested in participating can submit model projections for each scenario in a PARQUET file formatted according to our specifications, and a metadata file with a description of model information. See here for technical submission requirements.
The target-data/ folder contains the target data in a hubverse compliant time-series format.
The data are automatically updated on Monday morning. The code to generate the
data is available in the src folder.
The past version of the time-series files are stored in the
auxiliary-data/target-data_archive
folder, with the date the data was archived append to the filename.
Weekly Hospital Respiratory Data (HRD) Metrics by Jurisdiction from the National Healthcare Safety Network (NHSN) will be used for incidence hospitalization target. The data are weekly.
The repository stores and updates additional data relevant to the Flu modeling efforts in the auxiliary-data/ folder:
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Reports: Reports from Flu Scenario Modeling Hub rounds results. Each report contains an executive summary with key messages and results, and analyses of ensemble and individual projections.
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Population and census data: National and State level name and fips code as used in the Hub and associated population size.
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Rounds: Information on ongoing round and previous round available in the repository
For more information, please consult the associated README file.
We aim to combine model projections into an ensemble.
We are grateful to the teams who have generated these scenarios. The groups have made their public data available under different terms and licenses. You will find the licenses (when provided) within the model-specific metadata files in the model-metadata directory. Please consult these licenses before using these data to ensure that you follow the terms under which these data were released.
All source code that is specific to the overall project is available under an open-source MIT license. We note that this license does NOT cover model code from the various teams or model scenario data (available under specified licenses as described above).
Those teams interested in accessing additional computational power should contact Katriona Shea at [email protected].
Additional resources might be available from the MIDAS Coordination Center, please contact [email protected] for information.
Scenario modeling groups are supported through grants to the contributing investigators.
The Scenario Modeling Hub site is supported by the MIDAS Coordination Center, NIGMS Grant U24GM132013 (2019-2024) and R24GM153920 (2024-2029) to the University of Pittsburgh.
- Shaun Truelove, Johns Hopkins University
- Cécile Viboud, NIH Fogarty
- Justin Lessler, University of North Carolina
- Sara Loo, Johns Hopkins University
- Lucie Contamin, University of Pittsburgh
- Emily Howerton, Penn State University
- Claire Smith, Johns Hopkins University
- Harry Hochheiser, University of Pittsburgh
- Katriona Shea, Penn State University
- Michael Runge, USGS
- Erica Carcelen, John Hopkins University
- Sung-mok Jung, University of North Carolina
- Jessi Espino, University of Pittsburgh
- John Levander, University of Pittsburgh
- Samantha Bents, NIH Fogarty
- Katie Yan, Penn State University
- Wilbert Van Panhuis, University of Pittsburgh
- Jessica Kerr, University of Pittsburgh
- Luke Mullany, Johns Hopkins University
- Kaitlin Lovett, John Hopkins University
- Michelle Qin, Harvard University
- Tiffany Bogich, Penn State University
- Rebecca Borchering, Penn State University