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Health and biosecurity

Health systemic risk is the chance that an outbreak, a supply shock or a slow threat such as antimicrobial resistance overwhelms detection and care. It also strains the social systems that keep people able to isolate, work and eat.

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01Contents

Health and biosecurity in six parts.

In this dossier6 parts
  1. 01Three mandatesThe field, seen three ways
  2. 02The systemic questionSurge capacity, supply chains and the time to detect
  3. 03FrameworksInternational law and assessment frameworks
  4. 04CouplingsWhere health risk meets other fields
  5. 05GroundingThe methods behind the field
  6. 06SourcesWhere this page’s references lead
02Three mandates

The field, seen three ways.

GRF

Governance and dialogue

Health and Biosecurity Governance.

GRA

Financial understanding

Insurance Nexus.

03Geography

Environmental exposure worldwide.

Population density, daytime surface heat and haze across the world, 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
VIIRS Global Flood Product (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite detection; clouds leave gaps
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite detection; clouds leave gaps. 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
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

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 the world.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
  • 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
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024

04The systemic question

Surge capacity, supply chains and the time to detect.

The consequence of an outbreak depends less on the pathogen than on three things. How quickly it is detected. How much surge capacity care and laboratories have. Whether supply chains for diagnostics, medicines and protective equipment hold when every country needs them at once. Most of these are capacities that can be assessed in advance.

  • Detection: event-based and indicator-based surveillance, genomic sequencing access, reporting timeliness.
  • Response: health-workforce surge, intensive-care capacity, laboratory throughput.
  • Supply: concentration of active pharmaceutical ingredient production and of medical countermeasure manufacturing.
  • Society: sick pay, social protection and trust, which set whether public health measures are followed.
05Simulator

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.

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
4.58 per 1,000 a day
Day of the peak
163
Share ever infected
55%
Places reached
100%
Reproduction number under measures
1.50
Numbers, methods and sources
DayNew infections per 1,000Cumulative infected (%)
00.000.0
170.020.0
340.180.1
510.550.8
681.082.2
851.824.7
1022.598.5
1193.2313.5
1363.8519.5
1534.4426.6
1704.5234.4
1873.9341.6
2043.1747.6
2212.3352.2
2381.4255.4

Methods

  1. SEIR compartments Kermack and McKendrick (1927), Proc. R. Soc. A 115
  2. Metapopulation coupling by mobility Balcan and others (2009), PNAS 106
  3. Small-world network Watts and Strogatz (1998), Nature 393
  4. Modelling infectious diseases Keeling and Rohani (2008), Princeton University Press
  5. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  6. 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
SEIR on a network of places. Illustrative teaching model: it runs on the values set by the controls, not on measured data. 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).

Across the six pillars, led by Nexus Consortium

06Frameworks

International law and assessment frameworks.

Framework or bodyWhat it governs or supplies
International Health Regulations (2005), with the amendments adopted in 2024Core capacities, notification duties and the pandemic emergency category
WHO Pandemic AgreementAdopted in 2025; it opens for signature only after its pathogen access and benefit-sharing annex is adopted
IHR Monitoring and Evaluation Framework (SPAR, Joint External Evaluation)Self-assessment and voluntary external evaluation of capacities
One Health Joint Plan of ActionCoordination across human, animal, plant and environmental health
07Twin and cascade simulator

Model health and biosecurity as a system. Run the cascade.

Assembled from the Nexus Standards area profile Global and systemic risk: 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

  • Dam failure
  • Financial contagion
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Mass displacement (set off downstream)
  • Widespread power outage (set off downstream)
  • Water supply shortfall (set off downstream)
  • Sovereign debt crisis (set off downstream)
  • Currency crisis (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-14 Conformance and crosswalk to external standards
  • NRS-H120 Hazard family: Structural fragility of interconnected systems (NHS-1 sys.fragility)
  • NRS-C6 Systemic and cascading risk
  • NRS-H61 Hazard family: Cascading failure (NHS-1 sys.cascade)
  • NRS-H62 Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)
  • NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)
  • NRS-H60 Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)

Observation

  • INFORM Risk Index (listed for reference)
  • World Bank Open Data and World Development Indicators API (listed for reference)
  • IMF data services (WEO, IFS, FSI via SDMX) (listed for reference)
  • Direct economic loss attributed to disasters in relation to global GDP
  • Macroeconomic Dashboard

Example geography

  • Bangladesh: 134 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
  • Surface soil moisture (SMAP), NASA GIBS
08Couplings

Where health risk meets other fields.

  • Nature: land-use change and wildlife trade shape spillover risk.
  • Food: animal disease and nutrition status set exposure and vulnerability.
  • Climate: heat and vector range shifts.
  • Work and society: the capacity of households to follow public health measures.

The science sits on Health Nexus; methods start from epidemiology.

09Sector signature

The sector signature of health and biosecurity.

The sectors health and biosecurity touches and how strongly they depend on each other: what a study has to observe and model together.

Select corners · hover lines6 / 15 relations

Signature

Health and its partners

Health gives workforce for operations to infrastructure (0.3), farm labour to food (0.3) and utility workforce to water (0.2).

W · E · I · F · H · B

Sectors
4 of 6
Relations
6 of 15
Coupling
0.42 share of total

Strongest relations in play

  • Water → Food · irrigation0.8
  • Food → Health · nutrition0.7
  • Infrastructure → Water · pipes, dams and treatment works0.6
  • Water → Health · drinking water and sanitation0.7
Teaching values for a typical city-region, not measurements for any place. Coupling is the summed strength of the relations in play, as a share of all fifteen.
10Grounding

The methods behind the field.

11Sources

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.

12Questions

Questions and answers.

Why does GCRI host field gateways?
GCRI hosts the shared references of the Consortium, including the STEM Commons and the field gateways, so each field has one place that links all three institutions’ work.
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