Illustrative: a hexagonal population grid where a wave rises, peaks and recovers from seeded outbreaks
Risk Academy, led by the Nexus Consortium · Health and Society · Department of Global Health Security
Transmission models, real-time estimation and forecasts for preparedness
Epidemic modelling and forecasting
A preparedness decision needs more than a curve: it needs an estimate of transmission now, a forecast with its uncertainty and scenarios for what interventions would change.
- Department
- Department of Global Health Security
- Courses
- In preparation
- Levels
- In development
- Labs
- In development
- Compartmental models (SIR, SEIR) with interventions
- Real-time estimation of the reproduction number
- Nowcasting and reporting delays
- Ensemble forecasting and forecast hubs
- Scenario modelling for policy
- Network and agent-based transmission models
- Wastewater and genomic surveillance as model inputs
- Vaccination and capacity planning
- Communicating model uncertainty
Build a twin of any place
Search any place or open the world; the layers and generators follow epidemic modelling and forecasting on the planet map, the globe and in 3D.
- Terrain 191 to 315 m
- 950 hospitals
- 26,073,018 people in the box, 2020
- Population density, GPW v4.11 (2020): read live when the 3D twin opens
- Air quality, Copernicus CAMS via Open-Meteo (hourly, 5 days): read live when the 3D twin opens
- Nitrogen dioxide column, TROPOMI (Sentinel-5P): read live when the 3D twin opens
- Surface air temperature, AIRS (daily, day): read live when the 3D twin opens
- Urban heat island, summer daytime 2013: read live when the 3D twin opens
- Built-up and settlement extent, HBASE 2010: read live when the 3D twin opens
Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and – zoom, 0 resets, V steps through the views, Escape clears.
Flat plan of the same data: relief as contours from the inline grid, the WorldPop count grid as cells, the mapped hospitals and the numbers below. The 3D twin opens on devices that can draw it, once its data and code have been checked.
The boundaries, names and designations shown do not imply any judgement on the legal status of any territory, or any endorsement or acceptance of such boundaries. Countries: Natural Earth (public domain).
Environmental exposure in India
Haze, nitrogen dioxide, dust, surface heat by day and night, and where people live, over India.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 2
Environmental exposure
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Environmental exposure, framed on India.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONETSources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- MODIS and VIIRS atmosphere products, NASA LANCE and LAADS DAAC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- OMI nitrogen dioxide (Aura) and OMPS aerosol index (Suomi NPP), NASA; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- MERRA-2 reanalysis, NASA Global Modeling and Assimilation Office; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (12 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
- Surface dust PM2.5, monthly mean: MERRA-2, NASA GMAO / GES DISC · July 2026
- Land surface temperature, night, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
The subject, methods and measures and debates and bodies
The field and its scope
For analysts and modellers who must estimate transmission in real time, produce forecasts a response team can act on, and state the uncertainty honestly to people who will make decisions from it.
Quantities and units
Methods and their limits
Each method is listed with what it assumes and where it fails.
What the field debates
Bodies that set practice, and the data they publish
Bodies and standards are named so learners can find and apply their published work; the Academy teaches their use and links to the publisher, and no affiliation is implied.
From yesterday's case count to today's R: reporting delays, ascertainment and the nowcast
The reproduction number estimated from reported cases is only as good as the correction for two gaps between infection and the data: the share of infections ever recorded, and the days between infection and the report; left uncorrected, a growing epidemic always looks smaller and slower than it is.
Sources: Cori, Ferguson, Fraser and Cauchemez, A new framework and software to estimate time-varying reproduction numbers during epidemics (2013); Gostic and others, Practical considerations for measuring the effective reproductive number (2020); Wallinga and Teunis, Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures (2004); Bracher, Ray, Gneiting and Reich, Evaluating epidemic forecasts in an interval format (2021).
How epidemic modelling and forecasting connects the sectors
Select corners to build a signature, then hover a line to read what each sector gives and receives.
Context
Pandemic
Workforce absence ripples from clinics into grid operations, logistics and farm labour.
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.41 share of total
Strongest relations in play
- Energy → Infrastructure · power for transport and telecoms0.8
- Food → Health · nutrition0.7
- Infrastructure → Health · access to care0.5
- Energy → Food · fertiliser, machinery and cold chains0.5
Research and evidence, with learning
Research and tools
Research and preprints as they are published, by discipline, with the faculty's other tools.
The hub lists the newest research and preprints for Epidemic modelling and forecasting, each with its source and date. Open the research hub
Courses in this discipline
Courses for this discipline are in development; until they open, study it through the connected courses and open lessons below.
The course catalogue lists every open course of the Academy.
How Epidemic modelling and forecasting is taught, as a process you can run
Press Play to run this process from this page's own data.
Practice, learning and connections
How technology helps and what risk it brings
Achievements in this discipline
Course achievements
One for each course with this as its primary discipline, earned when you pass the course's assessed activities.
Department: Global Health Security
Earn two discipline achievements in the Department of Global Health Security. In development.
An achievement is a record of the learning completed and assessed here. How recognition works.
Where the subject is practised
A field platform page on this subject is in development.
The two Foundry systems where it is practised
- FoundryNXS-EWS systemEpidemic forecasts are judged by how they verifyForecast Verification room
- NXS-DSS systemIntervention options are compared as scenariosScenarios room
Foundry system pages describe what each system and its rooms are designed to do; the courses teach the methods these systems apply.
Across the ecosystem
Take part in Health and Society
Start from who you are.
Core references and where to begin
Start with Kermack, then Cori, then Gostic.
Questions, answers and key terms
Is study here free?
What does completing a course give me?
Where do the data and the places come from?
How do I take part beyond the courses in epidemic modelling and forecasting?
Key terms
Effective reproduction number
The average number of secondary infections caused by one infected person at a given time, written Rt.
SEIR model
A compartmental model that divides a population into susceptible, exposed, infectious and recovered.
Nowcasting
Estimating the current state of an epidemic while accounting for delays in reporting.
Forecast hub
A platform that collects, scores and combines forecasts from many modelling teams.
Contribute evidence from this page.
Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
Around Epidemic modelling and forecasting
Prepare with a related course
Open courses in connected disciplines teach the methods this discipline will build on.