GCRI · Health Nexus
Infectious threats
An outbreak becomes an emergency when a pathogen spreads faster than the systems that detect, characterise and contain it. Readiness depends on surveillance that sees early, laboratories that confirm, and evidence that is honest about what is not yet known. This page sets out how infectious threats emerge and spread, how they are detected and assessed, and how uncertainty is carried into the decisions of public health authorities.
Infectious threats on the record.
Infectious threats: how the risk develops.
Outbreak readiness, surveillance and uncertainty. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Detection lags transmission
Cases appear in surveillance only after infection, symptoms, care-seeking, testing and reporting. Each step adds delay and loses cases, so early counts describe the past and undercount the present.
Contact and immunity shape spread
Spread depends on the pathogen’s transmissibility, the timing of infectiousness, population immunity and contact patterns. Mobility, crowding and mass gatherings connect local chains of transmission into regional and international ones.
Pathogens evolve under pressure
Variants with altered transmissibility, severity or immune escape arise and are selected. Genomic surveillance detects them, but only where sequencing capacity exists and samples and data are shared promptly.
Outbreaks cascade into other systems
Surges strain hospitals and staff, travel and trade restrictions disrupt supply chains, and absenteeism reaches food, energy and transport. Public trust and the quality of information shape behaviour, and so the course of the outbreak itself.
Environmental exposure in Africa.
Population density, daytime surface heat and haze over Africa, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Environmental exposure, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS NOAA-20 Deep Blue AOD (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 2 km grid
- Uncertainty
- Satellite measure of haze, smoke and dust through the whole air column on the day shown; an exposure indicator, not ground-level PM2.5, an air quality index or a health warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- OMI Aura (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-10
- Resolution
- about 2 km grid
- Uncertainty
- Satellite column of nitrogen dioxide in the lower atmosphere on the day shown, mostly from combustion; not a ground-level concentration or a health warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
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 Africa.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 EONET · ESA Copernicus Sentinel-5P TROPOMI · NASA JPL OPERA DIST-ALERTSources 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 hexagonal cells where shown (modified). NASA open data
- 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 hexagonal 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 hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Observed (EO): ESA Copernicus Sentinel-5P TROPOMI (contains modified Copernicus Sentinel data 2026). 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).
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). 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).
- 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 (14 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
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
How epidemics travel through water, food, energy and nature.
| Domain | How it couples here | What to watch |
|---|---|---|
| Water | Cholera and other waterborne diseases follow failures of water and sanitation. See drinking water and sanitation. | Outbreaks after floods and supply failures |
| Food | Food-borne outbreaks follow cold chain and hygiene failures; lockdowns disrupt food access. | Food-borne outbreak investigations |
| Energy | Vaccine cold chains and hospital surge capacity need reliable power. | Cold chain equipment functionality |
| Biodiversity | Vector ranges shift with climate and land use. See ecosystem integrity. | Vector surveillance at range margins |
The legal frame changed in 2024 and 2025. Amendments to the International Health Regulations adopted by the World Health Assembly in June 2024, in force from September 2025, introduced a pandemic emergency alert level. The WHO Pandemic Agreement was adopted in May 2025; its annex on pathogen access and benefit-sharing is under negotiation and the agreement opens for signature only after that annex is adopted.
Transmission is described by the basic and effective reproduction numbers (dimensionless), the serial interval in days and the case fatality ratio, each estimated with uncertainty that is largest early in an outbreak.
Surveillance and capacity board.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Infectious threat evidence and its boundaries.
Preparedness and modelling studies are designed for the Scenario and Stress-Test series. The Global Centre for Risk and Innovation (GCRI) declares no emergency and issues no health advice; WHO and national public health authorities hold those mandates. Epidemic models would carry NS-12 cards under the proposed Nexus Standards. Useful contributions: retrospective model evaluations and preparedness exercise records.
SEIR on a network of places.
An outbreak seeded in one place spreads through a small-world network by the share of contacts people make elsewhere; play it to see the order of arrival and how the timing of measures moves the peak. Teaching model with stated illustrative values, not a prediction. The map on this page shows Africa; the model itself is not tied to a place.
Controls
- Basic reproduction number R0
- 2.5
- Latent period
- 3.0 days
- Infectious period
- 5.0 days
- Share of contacts made in other places
- 8%
- Places in the network
- 24
- Measures start on day
- 40
- Contact reduction from measures
- 40%
- Days simulated
- 240 days
Readouts
- Peak new infections
- 6.20 per 1,000 a day
- Day of the peak
- 158
- Share ever infected
- 58%
- Places reached
- 100%
- Reproduction number under measures
- 1.50
Numbers, methods and sources
| Day | New infections per 1,000 | Cumulative infected (%) |
|---|---|---|
| 0 | 0.00 | 0.0 |
| 17 | 0.02 | 0.0 |
| 34 | 0.16 | 0.1 |
| 51 | 0.47 | 0.7 |
| 68 | 0.85 | 1.8 |
| 85 | 1.44 | 3.8 |
| 102 | 2.39 | 7.0 |
| 119 | 3.70 | 12.2 |
| 136 | 5.13 | 19.8 |
| 153 | 6.13 | 29.6 |
| 170 | 5.82 | 39.9 |
| 187 | 4.15 | 48.4 |
| 204 | 2.29 | 53.8 |
| 221 | 1.07 | 56.5 |
| 238 | 0.46 | 57.7 |
Methods
- SEIR compartments Kermack and McKendrick (1927), Proc. R. Soc. A 115
- Metapopulation coupling by mobility Balcan and others (2009), PNAS 106
- Small-world network Watts and Strogatz (1998), Nature 393
- Modelling infectious diseases Keeling and Rohani (2008), Princeton University Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Cities Natural Earth
- Airports Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Health Nexus in Foundry
- Tested at Health Nexus in Universe
- Codified in Health and Biosecurity in Standards
- Published in Health Nexus in Reports
- Taught in Faculty of Health and Society in Academy
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Notified cases by date of onset | cases | daily or weekly | Indicator-based surveillance | REPORTED |
| Time-varying reproduction number | dimensionless | weekly | Transmission models on onset and case data | ESTIMATED |
| Test positivity | percent of tests positive | weekly | Laboratory reporting | OBSERVED |
| Sequencing coverage | percent of confirmed cases sequenced | weekly | Genomic surveillance and public repositories | OBSERVED |
| Timeliness of detection, notification and response | days between emergence, detection, notification and response | per event | Event records against national timeliness targets | REPORTED |
| Influenza-like illness and severe acute respiratory infection | consultations or admissions per hundred thousand population | weekly | Sentinel surveillance in GISRS | OBSERVED |
| Case fatality risk | percent of confirmed cases with known outcome | per event | Line lists with outcome follow-up | ESTIMATED |
| Excess mortality | deaths above expected | weekly or monthly | Vital registration against modelled baselines | ESTIMATED |
Model infectious threats as a system. Run the cascade.
Assembled from the Nexus Standards area profile Health security and One Health: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Antimicrobial resistance
- Tuberculosis surge (set off downstream)
- Typhoid and paratyphoid fever (set off downstream)
- Health-system overload (set off downstream)
Systems and couplings
- Health security and One Health
- Biological hazard standards Mechanism
- Biodiversity and nature risk standards Common driver
- Food and agriculture risk standards Mechanism
- Global and systemic risk Cascade
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H83Hazard family: Health system capacity failure (NHS-1 health.system)NRS-H42Hazard family: Rare and persistent human infections (NHS-1 health.other-human)NRS-H41Hazard family: Animal-to-human spillover (NHS-1 health.zoonotic)NRS-H43Hazard family: Livestock and aquaculture epizootics (NHS-1 health.animal-health)NRS-D3Humanitarian response and resilient recoveryNRS-H46Hazard family: Environmental and product harm to people (NHS-1 health.harm)
Observation
- WHO Disease Outbreak News (listed for reference)
- WAHIS animal health events (listed for reference)
- WorldPop gridded population (listed for reference)
- International Health Regulations capacity and health emergency preparedness
- Percentage of bloodstream infections due to selected antimicrobial-resistant organisms
Example geography
- West Africa: 59 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| WHO Disease Outbreak News | Public reports on acute public health events | Public records, WHO terms of use |
| WHO GISRS: FluNet and FluID | Virological and epidemiological influenza surveillance from national influenza centres | Open, attribution, WHO terms of use |
| GISAID | Influenza and coronavirus genomes with sampling metadata | Registered access under the GISAID database access agreement |
| INSDC sequence archives and Nextstrain | Open pathogen sequences and phylogenetic analyses | Free and unrestricted; open, attribution |
| ECDC Surveillance Atlas and Africa CDC epidemic intelligence reports | Regional surveillance data and weekly event reports | Open, attribution, terms per agency |
| ProMED and HealthMap | Event-based signals from media, professional networks and informal reports | Terms per service |
| Global.health | De-identified case line lists for selected outbreaks | Open, attribution (CC BY 4.0) |
How infectious threats is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in infectious threats: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Who decides, and what the evidence serves.
Health Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| National public health institutes | Whether a signal is a true event, and what investigation and response it warrants | Signal verification trail; line lists; nowcasts with their uncertainty |
| IHR National Focal Points | Whether an event meets the criteria for notification to WHO under the IHR decision instrument | Event assessments with the evidence for each criterion labelled |
| Hospital systems | How much surge capacity to activate, and when | Admission scenarios by region with confidence bands |
| Ministries of health and cabinets | Which public health and social measures to apply, adjust or lift, and for how long | Transmission estimates; evidence on the effects of measures with its limits; cascade scenarios |
Outputs this topic produces
- Outbreak situation evidence with reporting delays and completeness stated
- Nowcasts and short-term scenarios with their skill reported
- Genomic context for emerging variants and lineages
- Readiness evidence read against IHR core capacities
What experts ask.
Most decisions about outbreaks are made before the facts are settled.
- Is an unusual signal a real outbreak, and how fast is it growing?
- How transmissible and how severe is the pathogen, and for whom?
- How much transmission occurs before symptoms appear?
- What effect would testing, isolation, vaccination or other measures have, and at what social cost?
- When does health-system demand exceed capacity?
Mechanisms and drivers.
Transmission depends on the pathogen’s biology, contact patterns between people, immunity in the population and the environment. The reproduction number summarises how many people each case infects on average; when it stays above one, case numbers grow. Mobility, crowding, seasonality and human behaviour change the reproduction number over time.
Severity depends on age, underlying conditions, access to care and how stretched the health system is. A pathogen of moderate severity can still overwhelm hospitals if it spreads widely, which is why the indirect harm from disrupted services can rival the direct harm of the infection.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Indicator and event-based surveillance | Unusual clusters and trends from reports, laboratories and media | Reporting delays, under-ascertainment and changing testing practice |
| Genomic surveillance | Variants, transmission chains and introductions | Uneven sequencing capacity and sampling bias |
| Compartmental and agent-based models | Scenarios of spread and the effect of interventions | Highly sensitive to uncertain parameters early in an outbreak |
| Nowcasting and short-term forecasting | Current and near-future trends corrected for reporting delay | Reliable only over short horizons |
| Serological surveys | How many people have been infected | Antibody waning and test performance complicate interpretation |
How it is studied, and what the methods cannot say.
- 01Epidemiology and public health scienceSurveillance design and evaluation · Nowcasting under reporting delayApplied here
- 02Probability and statisticsSurvey-weighted and small-area estimation · Expected baselines for excess mortalityApplied here
- 03Molecular and life sciencesGenomic surveillance of pathogens · Cross-species linkage in One HealthApplied here
- 04Complex systems and agent-based modellingContact and mobility networks · Cascades across health and infrastructureApplied here
- 05Data engineering, interoperability and stewardshipLinking health information systems · Privacy-preserving publicationApplied here
- 06Causal inference and impact evaluationEvaluating public health measures · Exposure-response for heat and airApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
- International Health Regulations (2005), amendments adopted by the World Health Assembly in 2024 and in force from September 2025 (WHO)
- WHO Pandemic Agreement, adopted by the World Health Assembly in May 2025, with the pathogen access and benefit-sharing annex under negotiation (WHO)
- WHO Disease Outbreak News
- WHO Global Antimicrobial Resistance and Use Surveillance System (GLASS)
- NS-12, Software, model and AI/ML artefacts, a proposed standard
Questions and answers.
Why do early outbreak numbers change so much?
What is the difference between a forecast and a scenario?
What is a public health emergency of international concern?
Does Health Nexus issue outbreak alerts?
Are outbreak models predictions?
Why do early estimates change so much?
Does Health Nexus publish outbreak alerts?
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