GRF · Health and Biosecurity Governance
Vaccine and medical supply governance
In a health emergency, vaccines, diagnostics, therapeutics and protective equipment must be developed, approved, made and delivered at speed. Manufacturing is concentrated in a few countries, and allocation becomes a political contest. This page sets out how medical countermeasure governance works and where it fails, the records that show access and supply, and who decides.
How the work runs.
Countermeasure supply governance
Vaccine and medical supply governance · Supply coordination cell · Quarter 3
Countermeasures
| Antivirals | 11 | In place | Priority groups |
| Diagnostics | 2 | Renewing | By positivity |
| Protective equipment | 14 | In place | By facility tier |
Allocation principle
- Basis
- need and risk
- Equity check
- Done
- Decision
- Ministry of health
- Record
- published
Fig.Countermeasure supply governance: example names and illustrative values, not a record or a live system.
Vaccine and medical supply governance: how the risk develops.
Access, procurement authority and resilience. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Manufacturing is concentrated
A few countries and firms produce most vaccines and key inputs. Export restrictions and advance purchases by wealthy states leave others waiting.
Regulatory capacity sets pace
Countries without mature regulators rely on WHO prequalification or reliance pathways. Duplicated reviews and unclear emergency use rules delay access.
Advance purchase decides allocation
Contracts signed before products exist reserve supply for those who can pay and bear risk. Pooled mechanisms depend on donors and on manufacturers honouring commitments.
Last mile limits delivery
Cold chain, workforce and demand decide whether doses become vaccinations. Supply without delivery capacity leads to expiry and waste.
Environmental exposure in Southern Africa.
Population density, daytime surface heat and night lights over Southern 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
Keyboard, with the map focused
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Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
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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 Southern 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 · U.S. Geological Survey · NOAA GOES-East ABI GeoColorSources 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
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (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 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
- 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.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Live: NOAA GOES-East ABI GeoColor (CIRA). 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
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
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 |
|---|---|---|---|---|
| Regulatory system maturity level | WHO Global Benchmarking maturity level | on assessment | WHO records | Published statistics |
| Vaccine doses delivered per population | doses per hundred people | monthly in emergencies | WHO and UNICEF dashboards | REPORTED |
| Time from first approval to first delivery by income group | days | per product | Market and regulatory records | ESTIMATED |
| Regional manufacturing capacity | doses per year | periodic | Industry and agency surveys | REPORTED |
| Export restrictions on medical goods | count of measures | during emergencies | Trade monitoring | REPORTED |
| Doses expired before use | count | per campaign | Programme records | REPORTED |
When measures start, and how much they buy.
How the start day and the strength of contact measures change the size and timing of the peak and the share ever infected, the trade-off a public health decision weighs. Teaching model with stated illustrative values, not a prediction. The map on this page shows Southern 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
- 4.21 per 1,000 a day
- Day of the peak
- 215
- Share ever infected
- 50%
- 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 | 0.01 | 0.0 |
| 34 | 0.14 | 0.1 |
| 51 | 0.42 | 0.6 |
| 68 | 0.77 | 1.6 |
| 85 | 1.20 | 3.3 |
| 102 | 1.67 | 5.8 |
| 119 | 2.22 | 9.1 |
| 136 | 2.78 | 13.4 |
| 153 | 3.08 | 18.4 |
| 170 | 3.24 | 23.8 |
| 187 | 3.61 | 29.6 |
| 204 | 4.08 | 36.2 |
| 221 | 4.15 | 43.3 |
| 238 | 3.33 | 49.7 |
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 and Biosecurity Governance in Foundry
- Tested at Health and Biosecurity Governance in Universe
- Codified in Health and Biosecurity in Standards
- Published in Health and Biosecurity Governance in Reports
- Taught in Faculty of Health and Society in Academy
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 Prequalification and Global Benchmarking Tool records | Prequalified products and regulator maturity levels | Free, WHO terms |
| UNICEF Supply Division market dashboards | Vaccine supply, prices and deliveries | Free to read, UNICEF terms |
| Gavi and COVAX records | Allocation and delivery of vaccines | Free to read, terms to check |
| WTO trade monitoring on medical goods | Trade measures affecting medical products | Free, WTO terms |
| African Medicines Agency and regional regulatory records | Regional regulatory cooperation | Public records, terms per agency |
From mandate to evaluation, by pillar.
The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction. The map on this page shows Southern Africa; the model itself is not tied to a place.
- Mandate and problem framing Competent authority (outside the programme)
A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009) - Evidence and system model Foundry
The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2 - Options appraised with scenarios Foundry
Instruments are compared under scenarios, with uncertainty shown. Hood (1983) - Exercise with stakeholders Universe
The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3 - Standard or guidance drafted Nexus Standards
What works is codified as a standard or guidance, open to comment. Nexus Standards process - Decision by the authority Competent authority (outside the programme)
The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009) - Capacity and training Risk Academy
Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2 - Monitoring and public report Reports
Indicators are published with sources, limits and corrections. OECD (2014), principle 5 - Evaluation and revision Nexus Standards
Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)
Methods
- Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
- Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Health and Biosecurity Governance in Foundry
- Tested at Health and Biosecurity Governance in Universe
- Codified in Health and Biosecurity in Standards
- Published in Health and Biosecurity Governance in Reports
- Taught in Faculty of Health and Society in Academy
Who decides, and what the evidence serves.
Health and Biosecurity Governance 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 regulatory authorities | Whether and how to authorise products in an emergency | Reliance pathways and comparable decisions |
| Health ministries and procurement agencies | What to buy, when and through which mechanism | Supply, price and delivery records |
| Governments of manufacturing countries | Whether to restrict exports or share supply | Trade measure records and their effects |
| Boards of Gavi, CEPI and similar bodies | How to allocate funds and doses | Allocation records and evaluations |
Outputs this topic produces
- Comparative notes on allocation mechanisms in past emergencies
- Guide to regulatory reliance and prequalification
- Dialogue briefs on regional manufacturing
- Questions for governments on advance purchase and sharing commitments
Exercise a cascade in vaccine and medical supply governance with the people who decide.
Assembled from the Nexus Standards area profile Health security and One Health: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. 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
What experts ask.
The questions concern access, authority and resilience.
- Who has authority to purchase and allocate countermeasures, nationally and through regional or international mechanisms?
- How are allocation priorities set, and are they transparent and fair?
- How do export restrictions and advance purchase agreements affect access for others?
- How is regulatory authorisation coordinated across countries in emergencies?
- Where is manufacturing capacity located, and how can it be diversified?
How vaccine and medical supply governance is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Policy instrument matrix
The kinds of instrument available on vaccine and medical supply governance, by level of government and cooperation.
| Instrument type | Local | National | Regional | Global |
|---|---|---|---|---|
| Regulatory | Zoning, building codes | Laws, standards, licensing | Harmonised rules | Conventions and treaties |
| Economic | Local levies, grants | Budget lines, taxes, insurance schemes | Risk pools, regional funds | Financing mechanisms |
| Information | Local warnings | Disclosure, early warning, statistics | Data sharing arrangements | Global monitoring and reporting |
| Institutional | Local committees | Lead agencies, coordination councils | Regional bodies and secretariats | Multilateral mandates |
| Cooperative | Community agreements | Partnership compacts | Memoranda and joint programmes | Agreements and joint commitments |
Mechanisms and drivers.
Manufacturing capacity for vaccines and many medicines is concentrated in a limited number of countries and firms. In emergencies, countries with purchasing power and domestic production can secure supply first, while others wait. Pooled procurement and regional manufacturing are among the responses to this inequity.
Regulatory processes determine how quickly products reach people. Reliance on assessments by trusted regulators and emergency procedures can speed access but require trust and capacity. Allocation frameworks must balance health need, risk of exposure, protection of health workers and equity.
Why now: the WHO Pandemic Agreement (2025) addresses equitable access and supply chains, with a pathogen access and benefit-sharing annex negotiated separately. The platform is designed to convene regulators, procurers and manufacturers' associations on supply arrangements under precompetitive rules.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Procurement and contract analysis | Terms of purchase and supply | Many contracts are confidential |
| Allocation framework comparison | How priorities are set | Implementation may differ from frameworks |
| Supply-chain mapping | Concentration and dependencies | Firm-level data is limited |
| Regulatory reliance analysis | How regulators cooperate | Practices are changing |
How it is studied, and what the methods cannot say.
- 01Molecular and life sciencesCountermeasure development pathways · Biosafety risk assessmentApplied here
- 02Policy, institutional and decision scienceComparing emergency health law · Tracing review recommendations · Mapping cooperationApplied here
- 03Epidemiology and public health scienceEarly outbreak parameters · Equity in outcomes · Evaluating measuresApplied here
Questions and answers.
What is WHO prequalification?
What is regulatory reliance?
Why did vaccine access differ between countries?
Why were countermeasures distributed unequally in past emergencies?
What is pooled procurement?
Does the platform procure or allocate medical supplies?
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