hubs: # NOTE: to add a new organization: # 1. copy and paste this example # 2. replace the example: key with a slug for your organization # 3. update the values below example: logo: /includes/img/example-logo.png name: “Example Organization” description: | A description of the organization, which can include mission and funding. hubs: # a list of hubs that require a name, description, contact, and license # — REQUIRED — - name: “Name of Hub” description: | A description that can span multiple lines # from admin.json contact: - name: “hub-info-person” email: “hub-info@example.com” license: “License Name (e.g MIT License)” # — OPTIONAL —- repo: “example-org/hub-name” # must be slug, not URL aws: “aws-bucket-name” # from your admin.json insights: https://example.org/hub-insights/ forecasts: https://example.org/hub-insights/forecasts.html evals: https://example.org/hub-insights/evals.html count: 5 # number of models submitted (this is automatically updated if your hub is public) # archived_dirs: glob patterns (one * per segment) for directories whose # rows should be counted alongside the standard model-output / target-data. # archived_dirs: # - “Previous_Rounds//model-output” # - ”Previous_Rounds//target-data” hubverse: logo: /brand/logo/logo-with-text.png name: “The hubverse” hubs: - name: “Archival COVID-19 Forecast Hub (2020–2024)” description: “Original submissions to the COVID-19 Forecast Hub, reformatted to align with the hubverse format.” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “hubverse-org/covid19-forecast-hub-archive” license: “MIT License” count: 127 - name: “Archival FluSight hub (2015–2019)” description: “Original submission to FluSight, reformatted to align with the hubverse format.” contact: - name: “Luke Mullany” email: “Luke.Mullany@jhuapl.edu” repo: “hubverse-org/flusight_hub_archive” license: “MIT License” aws: “uscdc-flusight-hub-v1” count: 99 reichlab-modeldev: logo: /includes/img/reichlab.png name: “Reich Lab” hubs: - name: “Variant Nowcast Model Development Retrospective Hub” description: “Hub hosting retrospective model development for the UMass teams’s submission to the U.S. SARS-CoV-2 Variant Nowcast Hub.” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “reichlab/variant-nowcast-model-dev-retro” license: “MIT License” count: 13 - name: “Flusion Retrospective Hub” description: “Hub hosting model outputs generated in retrospective analyses for the UMass-flusion model submitted to FluSight.” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “reichlab/flusion/tree/main/retrospective-hub” license: “MIT License” count: 9 - name: “Flusion Submissions Hub” description: “Hub hosting model outputs generated in real time for weekly model submissions for the UMass-flusion model submitted to FluSight.” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “reichlab/flusion/tree/main/submissions-hub” license: “MIT License” count: 8 - name: “Forecast Sandbox” description: “Hub serving as a sandbox/testbed for experimental FluSight forecasts before and during the 2025/2026 respiratory virus forecasting season.” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “reichlab/forecast-sandbox-2025-2026” license: “MIT License” count: 25 - name: “MetroCast Sandbox” description: “Hub serving as a sandbox/testbed for experimental Flu MetroCast forecasts before and during the 2025/2026 respiratory virus forecasting season.” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “reichlab/metrocast-sandbox-2025-2026” license: “MIT License” count: 7 reichlab-training: logo: /includes/img/reichlab.png name: “Reich Lab” hubs: - name: “SISMID ILI Forecasting Sandbox” description: “Sandbox hub providing an environment for training, research, or benchmarking purposes. This hub was created for the 2025 SISMID course on Nowcasting and Forecasting Infectious Disease Dynamics (https://nfidd.github.io/sismid).” contact: - name: “Nick Reich” email: “nick@umass.edu” repo: “reichlab/sismid-ili-forecasting-sandbox” license: “MIT License” count: 21 epiengage: logo: /includes/img/epiengage.png name: “epiENGAGE” hubs: - name: “Variant Nowcast Hub” description: | A repository to store COVID-19 variant nowcasts collected as a modeling hub. contact: - name: Nick Reich email: nick@umass.edu repo: reichlab/variant-nowcast-hub license: MIT License aws: “covid-variant-nowcast-hub” insights: https://reichlab.io/variant-nowcast-hub-dashboard/explore.html evals: https://reichlab.io/variant-nowcast-hub-dashboard/eval.html count: 11 - name: “Flu MetroCast Hub” description: “The Flu MetroCast Hub is a modeling hub with the goal ofcity- and county-level forecasts of influenza. The hub is led by the epiENGAGE team from UT-AustinUMass-Amherst, as a part of the CDC Insight Net program.” contact: - name: “epiENGAGE Flu MetroCast Team” email: epiengage@austin.utexas.edu aws: reichlab-flu-metrocast-hub repo: reichlab/flu-metrocast license: MIT License forecasts: https://reichlab.io/metrocast-dashboard/forecast.html evals: https://reichlab.io/metrocast-dashboard/eval.html count: 16 ai4casting: logo: /includes/img/ai4casting.png name: “AI4Casting (U of Guelph)” hubs: - name: “Hospitalization Forecast Hub” description: | Public Health Ontario’s Ontario Respiratory Virus Tool Data monitors the capacity of hospitals, helping policymakers and health professionals gauge the burden of disease on the healthcare system. It tracks real-time bed utilization, enabling effective planning for resource allocation, particularly during times of heightened disease outbreaks. contact: - name: Siddhesh Suresh Kadam email: skadam@uoguelph.ca repo: ai4castinghub/hospitalization-forecast license: MIT License forecasts: https://4castinghub.uoguelph.ca/hospitalization/ count: 12 - name: “RVDSS Forecast Hub” description: | RVDSS is a national surveillance system that collects and reports data on the detection of respiratory viruses, including RSV (Respiratory Syncytial Virus), SARS-CoV-2 (COVID-19), and Influenza. Through laboratory-confirmed positive tests, the system helps track the spread of these viruses, offering essential data to support public health measures, pandemic preparedness, and disease control. contact: - name: Siddhesh Suresh Kadam email: skadam@uoguelph.ca repo: ai4castinghub/rvdss-forecast license: MIT License forecasts: https://4castinghub.uoguelph.ca/respiratory-virus-detections/ count: 15 smhct: logo: /includes/img/smh_logo.png name: “Scenario Modeling Hub Coordination Team” hubs: - name: “COVID-19 Scenario Modeling Hub” description: “The COVID-19 Scenario Modeling Hub aims to examine the impact changes in behavior and control, new variants, and vaccination a 3-month to 2-year time period, depending on the round. ” contact: - name: Scenario Modeling Hub Coordination Team email: scenariohub@midasnetwork.us repo: midas-network/covid19-scenario-modeling-hub license: MIT License insights: https://covid19scenariomodelinghub.org/ count: 12 - name: “Flu Scenario Modeling Hub” description: “The Flu Scenario Modeling Hub aims to anticipate the impact of in vaccination coverage and effectiveness, prior population , and dominant subtypes over the course of each influenza . ” contact: - name: Scenario Modeling Hub Coordination Team email: scenariohub@midasnetwork.us repo: midas-network/flu-scenario-modeling-hub license: MIT License insights: https://fluscenariomodelinghub.org count: 16 - name: “RSV Scenario Modeling Hub” description: “The RSV Scenario Modeling Hub aims to project the impacts of new vaccines monoclonal antibodies over the course of each RSV season. ” contact: - name: Scenario Modeling Hub Coordination Team email: scenariohub@midasnetwork.us repo: midas-network/rsv-scenario-modeling-hub license: MIT License insights: https://rsvscenariomodelinghub.org count: 18 - name: “COVID-19 Scenario Modeling Hub - Research” description: “The COVID-19 Research Scenario Modeling Hub intended to encourage modeling to specific COVID-19 research questions. Specific focus areas in the pipeline revisiting whether we could have projected the heterogeneities observed early stages of the pandemic and whether better modeling may have been to inform action to reduce these heterogeneities. Additional research topics follow. ” contact: - name: Scenario Modeling Hub Coordination Team email: scenariohub@midasnetwork.us repo: midas-network/covid19-smh-research license: MIT License count: 7 uscdc: name: “US Centers for Disease Control and Prevention” logo: /includes/img/cdc.jpg hubs: - name: “FluSight Forecast Hub” description: | This project collects forecasts for weekly new hospitalizations due to confirmed influenza. contact: - name: FluSight Forecast Hub email: flusight@cdc.gov repo: cdcepi/FluSight-forecast-hub license: “MIT License” aws: cdcepi-flusight-forecast-hub forecasts: https://reichlab.io/flusight-dashboard/forecast.html evals: https://reichlab.io/flusight-dashboard/eval.html count: 95 - name: “COVID-19 Forecast Hub” description: | A repository run by the US CDC to collect forecasts of weekly incident COVID-19 hospital admissions. contact: - name: COVID-19 Forecast Hub email: covidhub@cdc.gov repo: CDCgov/covid19-forecast-hub license: Apache License 2.0 aws: covid19-forecast-hub forecasts: https://reichlab.io/covidhub-dashboard/forecast.html evals: https://reichlab.io/covidhub-dashboard/eval.html count: 22 - name: “RSV Forecast Hub” description: “A repository run by the US CDC to collect forecasts of weekly new hospitalizations and the percentage of emergency department visits due to RSV. ” contact: - name: RSV Hub email: rsvhub@cdc.gov repo: CDCgov/rsv-forecast-hub license: Apache License 2.0 count: 9 - name: “Paraguay Forecast Hub” description: “The Paraguay Forecast Hub is designed to collect forecast data for weekly severe acute respiratory infection (SARI) hospitalizations during 2024 season in Paraguay.” contact: - name: Paraguay Forecast Hub email: opp8@cdc.gov - name: “WHO FluNet Hub” description: “An effort to produce -1 to 4 week ahead forecasts using the World Health FluNet surveillance data for Australia, Brazil, Chile, South , and Thailand.” contact: - name: WHO FluNet Hub email: opp8@cdc.gov ecdc: name: “European Centre for Disease Prevention and Control (ECDC)” logo: /includes/img/ecdc.png hubs: - name: “RespiCast Syndromic Indicators” contact: - name: European Centre for Disease Prevention and Control (ECDC) email: european.modelling.hub@ecdc.europa.eu description: | The European Syndromic Indicators Forecasting Hub collates weekly forecasts on Influenza-Like-Illness (ILI) and Acute Respiratory Infection (ARI) incidence in EU/EEA countries. repo: european-modelling-hubs/RespiCast-SyndromicIndicators license: CC-BY 4.0 license forecasts: https://respicast.ecdc.europa.eu/forecasts/?disease=4&target=1 evals: https://respicast.ecdc.europa.eu/evaluations/?disease=4&target=1 count: 28 - name: “European Covid-19 Forecasting Hub” contact: - name: European Centre for Disease Prevention and Control (ECDC) email: european.modelling.hub@ecdc.europa.eu description: | The European Covid-19 Forecasting Hub collates weekly forecasts on Covid-19 Hospital Admissions in EU/EEA countries. repo: european-modelling-hubs/RespiCast-Covid19 license: CC-BY 4.0 license forecasts: https://respicast.ecdc.europa.eu/forecasts/?disease=5 evals: https://respicast.ecdc.europa.eu/evaluations/?disease=5 count: 19 - name: “RespiCompass - ECDC’s Respiratory Diseases Scenario Hub” contact: - name: European Centre for Disease Prevention and Control (ECDC) email: european.modelling.hub@ecdc.europa.eu description: | RespiCompass is a platform dedicated to hosting and sharing scenario modelling results for respiratory pathogens. This initiative is funded and led by the European Centre for Disease Prevention and Control (ECDC). RespiCompass develops and applies multi-model analyses through international modelling collaboration. repo: european-modelling-hubs/RespiCompass license: CC-BY 4.0 license insights: https://respicompass.ecdc.europa.eu/insights/ count: 25 archived_dirs: - “Previous_Rounds//model-output” - ”Previous_Rounds//target-data” ecdc-archival: name: “European Centre for Disease Prevention and Control (ECDC)” logo: /includes/img/ecdc.png hubs: - name: “Archival RespiCast Influenza Hub (2023–2024)” contact: - name: European Centre for Disease Prevention and Control (ECDC) email: european.modelling.hub@ecdc.europa.eu description: “This repository archives the forecasts computed during season 2023/2024. ” repo: european-modelling-hubs/flu-forecast-hub_archive license: CC-BY 4.0 license count: 16 - name: “Archival RespiCast ARI Hub (2023–2024)” contact: - name: European Centre for Disease Prevention and Control (ECDC) email: european.modelling.hub@ecdc.europa.eu description: | This repository archives the forecasts computed during season 2023/2024. repo: european-modelling-hubs/ari-forecast-hub_archive license: CC-BY 4.0 license count: 12 cadph: logo: /includes/img/cadph.png name: California Department of Public Health hubs: - name: West Nile Virus Forecasting Hub contact: - name: West Nile Virus Forecasting Hub email: modeling@cdph.ca.gov description: | This is an open (by request) forecasting challenge to predict monthly West Nile virus (WNV) total disease cases in select California counties in 2024 in the months of May through December. This is the first iteration of a California county-specific Forecasting Challenge. repo: cdphmodeling/wnvca-2024 license: CC-BY 4.0 license count: 25 accidda: logo: /includes/img/accidda.png name: Atlantic Coast Center for Infectious Disease Dynamics and Analytics description: | The Atlantic Coast Center for Infectious Disease Dynamics and Analytics is devoted to rapid, coordinated response to infectious disease threats through innovative modeling techniques, enhanced data integration, and training a new generation of public health experts. hubs: - name: NC DHHS / ACCIDDA Forecasting Collaboration description: | Flu Forecasts for NC DHHS. Two models (influpaint + a mechanistic dual strain model). Similar than Flusight but using state health data for Flu, COVID-19 and RSV as targets instead. We run a lean hubverse structure, where most of our repository is hubverse compliant but not all. It allows us to leverage the amazing hubverse tools which have been instrumental in this collaboration. contact: - name: Sara Loo email: sloo2@jhmi.edu - name: Matthew Mietchen email: mietchen@unc.edu insights: https://www.respilens.com/ count: 2 acefa: logo: /includes/img/acefa.png name: Australia-Aotearoa Consortium for Epidemic Forecasting & Analytics description: | ACEFA aims to support the timely, effective response to epidemic diseases in Australia through real-time data analytics, modelling, and forecasting. hubs: - name: Australia-Aotearoa Forecasting Hub description: | The Australia–Aotearoa Forecasting Hub collects submissions of forecasted daily case incidence for SARS-CoV-2, RSV, and influenza virus. As an experimental target, the hub also collects submissions of predicted epidemic peak size and timing for each of these pathogens. contact: - name: Emily Kay email: emily.kay@unimelb.edu.au hopkinsidd: logo: /includes/img/hopkinsidd.png name: “Johns Hopkins University Infectious Disease Dynamics Group” hubs: - name: “Archival US RSV Forecast Hub 2024–2025” description: | This repository was designed to collect forecast data for the 2024-2025 RSV Forecast Hub run by Johns Hopkins University Infectious Disease Dynamics Group. This project collected forecasts for weekly new hospitalizations due to confirmed RSV. contact: - name: Shaun Truelove email: shauntruelove@jhu.edu repo: HopkinsIDD/rsv-forecast-hub license: MIT License count: 9 dailypartita: logo: /includes/img/dailypartita.png name: “Guangzhou Laboratory” hubs: - name: “GZlab China COVID-19 Forecast Hub” description: | This collaborative hub is designed to collect real-time probabilistic nowcasts and forecasts of weekly SARS-CoV-2 positivity rates from the Chinese sentinel hospital surveillance network (data from China CDC). contact: - name: Kaixin Yang email: yang_kaixin@gzlab.ac.cn repo: dailypartita/China-COVID-19-Forecast-Hub forecasts: https://dailypartita.github.io/China-COVID-19-Forecast-Dashboard/forecast.html evals: https://dailypartita.github.io/China-COVID-19-Forecast-Dashboard/eval.html license: MIT License count: 9 sjfox: logo: /includes/img/Northern_Arizona_U_logo.png name: “Northern Arizona University” hubs: - name: “ATSF2026 Training Hub” description: “This is a sandbox hub used to teach programming and forecasting techniques to undergraduate and students as part of the Applied Time Series Forecasting course at Northern Arizona University. are asked to produce weekly 4-week-ahead forecasts for five seasons of weighted influenza-like illness the HHS and National level.” contact: - name: Spencer J Fox email: Spencer.Fox@nau.edu repo: sjfox/ATSF2026 license: MIT License count: 27 insightnet: logo: /includes/img/insightnet.png name: “Insight Net” description: | Insight Net is a national network of centers working to improve our collective ability to understand, predict, prepare for, and respond to infectious disease threats through collaboration between analytic experts and public health departments. hubs: - name: “BVBD Modeling Hub” description: | This modeling hub has been built to collect outbreak size estimates of the Bundibugyo (Ebola) virus outbreak in 2026. contact: - name: Nick Reich email: nick@umass.edu license: MIT License repo: “InsightNet-US/BDBV-Modeling-Hub” aws: bdbv-modeling-hub count: 5 —
The Paraguay Forecast Hub is designed to collect forecast data for weekly new severe acute respiratory infection (SARI) hospitalizations during 2024 influenza season in Paraguay.
An effort to produce -1 to 4 week ahead forecasts using the World Health Organization FluNet surveillance data for Australia, Brazil, Chile, South Africa, and Thailand.
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 COVID-19 Research Scenario Modeling Hub 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 heterogeneities observed during early stages of the pandemic and whether better modeling may have been able to inform action to reduce these heterogeneities. Additional research topics may follow.
The Flu MetroCast Hub is a modeling hub with the goal of collecting city- and county-level forecasts of influenza activity. The hub is led by the epiENGAGE team from UT-Austin and UMass-Amherst, as a part of the CDC Insight Net program.
Public Health Ontario’s Ontario Respiratory Virus Tool Data monitors the capacity of hospitals, helping policymakers and health professionals gauge the burden of disease on the healthcare system. It tracks real-time bed utilization, enabling effective planning for resource allocation, particularly during times of heightened disease outbreaks.
RVDSS is a national surveillance system that collects and reports data on the detection of respiratory viruses, including RSV (Respiratory Syncytial Virus), SARS-CoV-2 (COVID-19), and Influenza. Through laboratory-confirmed positive tests, the system helps track the spread of these viruses, offering essential data to support public health measures, pandemic preparedness, and disease control.
European Centre for Disease Prevention and Control (ECDC)
28 models submitted
RespiCast Syndromic Indicators
The European Syndromic Indicators Forecasting Hub collates weekly forecasts on Influenza-Like-Illness (ILI) and Acute Respiratory Infection (ARI) incidence in EU/EEA countries.
RespiCompass is a platform dedicated to hosting and sharing scenario modelling results for respiratory pathogens. This initiative is funded and led by the European Centre for Disease Prevention and Control (ECDC). RespiCompass develops and applies multi-model analyses through international modelling collaboration.
This is an open (by request) forecasting challenge to predict monthly West Nile virus (WNV) total disease cases in select California counties in 2024 in the months of May through December. This is the first iteration of a California county-specific Forecasting Challenge.
Atlantic Coast Center for Infectious Disease Dynamics and Analytics
The Atlantic Coast Center for Infectious Disease Dynamics and Analytics is devoted to rapid, coordinated response to infectious disease threats through innovative modeling techniques, enhanced data integration, and training a new generation of public health experts.
2 models submitted
NC DHHS / ACCIDDA Forecasting Collaboration
Flu Forecasts for NC DHHS. Two models (influpaint + a mechanistic dual strain model). Similar than Flusight but using state health data for Flu, COVID-19 and RSV as targets instead. We run a lean hubverse structure, where most of our repository is hubverse compliant but not all. It allows us to leverage the amazing hubverse tools which have been instrumental in this collaboration.
Australia-Aotearoa Consortium for Epidemic Forecasting & Analytics
ACEFA aims to support the timely, effective response to epidemic diseases in Australia through real-time data analytics, modelling, and forecasting.
Australia-Aotearoa Forecasting Hub
The Australia–Aotearoa Forecasting Hub collects submissions of forecasted daily case incidence for SARS-CoV-2, RSV, and influenza virus. As an experimental target, the hub also collects submissions of predicted epidemic peak size and timing for each of these pathogens.
This collaborative hub is designed to collect real-time probabilistic nowcasts and forecasts of weekly SARS-CoV-2 positivity rates from the Chinese sentinel hospital surveillance network (data from China CDC).
Insight Net is a national network of centers working to improve our collective ability to understand, predict, prepare for, and respond to infectious disease threats through collaboration between analytic experts and public health departments.
5 models submitted
BVBD Modeling Hub
This modeling hub has been built to collect outbreak size estimates of the Bundibugyo (Ebola) virus outbreak in 2026.
Johns Hopkins University Infectious Disease Dynamics Group
9 models submitted
Archival US RSV Forecast Hub 2024–2025
This repository was designed to collect forecast data for the 2024-2025 RSV Forecast Hub run by Johns Hopkins University Infectious Disease Dynamics Group. This project collected forecasts for weekly new hospitalizations due to confirmed RSV.
Sandbox hub providing an environment for training, research, or benchmarking purposes. This hub was created for the 2025 SISMID course on Nowcasting and Forecasting Infectious Disease Dynamics (https://nfidd.github.io/sismid).
This is a sandbox hub used to teach programming and forecasting techniques to undergraduate and graduate students as part of the Applied Time Series Forecasting course at Northern Arizona University. Students are asked to produce weekly 4-week-ahead forecasts for five seasons of weighted influenza-like illness at the HHS and National level.
US Centers for Disease Control and Prevention
Scenario Modeling Hub Coordination Team
epiENGAGE
AI4Casting (U of Guelph)
European Centre for Disease Prevention and Control (ECDC)
California Department of Public Health
Atlantic Coast Center for Infectious Disease Dynamics and Analytics
Australia-Aotearoa Consortium for Epidemic Forecasting & Analytics
Guangzhou Laboratory
Insight Net
The hubverse
Johns Hopkins University Infectious Disease Dynamics Group
Reich Lab
Northern Arizona University