GRF · Health and Biosecurity Governance
One health policy
Most emerging infectious diseases in people come from animals, and antimicrobial resistance spreads between people, animals and the environment. One Health is the approach that links human, animal, plant and environmental health governance so that threats are detected and prevented where they begin. This page sets out how One Health policy works and fails, the records that show it, and the institutions that decide.
One health policy in seven parts.
- 01The questionOne health policy: how the risk develops
- 02IndicatorsWhat is measured, and how well
- 03SourcesWhere the evidence comes from
- 04DecisionsWho decides, and what the evidence serves
- 05Core questionsWhat experts ask
- 06MechanismsMechanisms and drivers
- 07Methods and dataHow it is studied, and where the methods stop
One health policy: how the risk develops.
Cross-sector stewardship and coordination. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Spillover begins at interfaces
Land-use change, wildlife trade and intensive livestock bring people and animals into closer contact. Pathogens cross where these interfaces are least monitored.
Sectors work apart
Health, agriculture and environment ministries have separate laws, budgets and surveillance systems. Without joint mechanisms, signals in animals do not reach human health authorities in time.
Antimicrobials select resistance
Antibiotic use in human medicine, livestock and aquaculture selects resistant bacteria that move between sectors through food, water and contact.
Prevention is underfunded
Preventing spillover produces no visible event, so it competes poorly for funds against response. Benefits fall across sectors that do not share budgets.
Environmental exposure in Southern Africa.
Population density, daytime surface heat and haze 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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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
- 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
- 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 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
- Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 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 |
|---|---|---|---|---|
| National One Health coordination mechanism | yes or no, with mandate | on change | National records and Quadripartite tracking | DECLARED |
| Antimicrobial resistance national action plan status | categorical | annual | Tracking AMR Country Self-assessment Survey | DECLARED |
| Antimicrobial use in animals | milligrams per population correction unit | annual | WOAH ANIMUSE database | REPORTED |
| Zoonotic disease events reported | count | annual | WOAH WAHIS | Published statistics |
| Joint risk assessments across sectors | count | annual | National records | REPORTED |
| Resistance rates for priority pathogens | percent resistant isolates | annual | WHO GLASS | REPORTED |
IHR event governance desk.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
IHR event governance desk
One health policy · National IHR focal point · Event EV-8229
Event handling
- Signaldetected
- Verifywith source
- AssessAnnex 2
- Notifywithin 24 h
- Respondmeasures
- Reviewafter action
Annex 2 questions
- Serious public health impact?
- Possibly
- Unusual or unexpected?
- Yes
- Risk of international spread?
- Assessing
- Risk of travel or trade restriction?
- Low
Core capacities
self-assessment score vs target
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 |
|---|---|---|
| Tracking AMR Country Self-assessment Survey (TrACSS) | Country progress on AMR action plans | Free, Quadripartite terms |
| WOAH World Animal Health Information System (WAHIS) | Animal disease reports from national veterinary services | Free, WOAH terms |
| WOAH ANIMUSE | Antimicrobial use in animals by country | Free to read, WOAH terms |
| WHO Global Antimicrobial Resistance and Use Surveillance System (GLASS) | Resistance and use data in human health | Free, WHO terms |
| IPBES workshop report on biodiversity and pandemics | Assessment of links between nature loss and pandemic risk | Free, IPBES terms |
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
- 5.60 per 1,000 a day
- Day of the peak
- 129
- 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 | 0.27 | 0.2 |
| 51 | 0.81 | 1.2 |
| 68 | 1.54 | 3.2 |
| 85 | 2.64 | 6.7 |
| 102 | 4.07 | 12.5 |
| 119 | 5.33 | 20.6 |
| 136 | 5.50 | 30.0 |
| 153 | 4.64 | 38.7 |
| 170 | 3.70 | 45.7 |
| 187 | 2.77 | 51.2 |
| 204 | 1.69 | 54.9 |
| 221 | 0.84 | 57.0 |
| 238 | 0.37 | 57.9 |
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
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 |
|---|---|---|
| Health, agriculture and environment ministries | How to coordinate surveillance, planning and budgets | Mechanism designs and joint assessment practice |
| Veterinary services | How antimicrobial use in animals is regulated and monitored | Use data and comparable regulations |
| Wildlife and land-use authorities | How to reduce spillover risk at interfaces | Evidence on drivers and comparable measures |
| Quadripartite organisations' governing bodies | What joint priorities and support to provide | Country progress records |
Outputs this topic produces
- Comparative notes on One Health coordination mechanisms
- Guide to AMR surveillance across human, animal and environmental sectors
- Dialogue briefs on spillover prevention policy
- Questions for ministries on joint surveillance and budgets
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
What experts ask.
The questions concern coordination without merging mandates.
- Which agencies hold responsibility for zoonoses, antimicrobial resistance, food safety and environmental contamination?
- Is there a formal mechanism, such as a joint committee or legal duty, for them to coordinate?
- How is surveillance data shared between human, animal and environmental sectors?
- How are joint priorities funded when budgets are sectoral?
- How are farmers, communities and Indigenous knowledge holders involved?
Exercise a cascade in one health policy 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
Mechanisms and drivers.
Sectoral organisation is the main obstacle. Each agency answers to its own minister and legislation and measures success differently. Coordination often depends on individuals and lapses when they move. Formal mechanisms, joint plans and shared data platforms make cooperation more durable.
International organisations covering human health, animal health, food and agriculture, and the environment have committed to joint One Health work, and many countries have national action plans, particularly on antimicrobial resistance. Implementation varies widely with resources and political priority.
Why now: the Quadripartite One Health Joint Plan of Action (2022 to 2026) reaches the end of its period, and zoonotic and antimicrobial risks still fall between human, animal and environmental agencies. The platform is designed to convene those agencies on shared triggers and roles, and record what each will do.
Who a decision on one health policy reaches.
The sectors a policy on one health policy has to coordinate: a choice in one ministry lands in the others.
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
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Institutional mapping | Mandates and overlaps between agencies | Formal mandates do not show actual coordination |
| Policy and legal analysis | Instruments that require or enable coordination | Implementation may lag the text |
| Evaluation of national action plans | Progress against commitments | Indicators are often process rather than outcome |
| Network analysis of information flows | Who shares data with whom | Data on informal flows is scarce |
How one health policy 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 one health policy, 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 |
How it is studied, and what the methods cannot say.
- 01Epidemiology and public health scienceEarly outbreak parameters · Equity in outcomes · Evaluating measuresApplied here
- 02Molecular and life sciencesCountermeasure development pathways · Biosafety risk assessmentApplied here
- 03Policy, institutional and decision scienceComparing emergency health law · Tracing review recommendations · Mapping cooperationApplied here
Questions and answers.
What is One Health?
Who are the Quadripartite?
Why is antimicrobial resistance a One Health problem?
Why is One Health hard to put into practice?
Is antimicrobial resistance a One Health issue?
What does a working One Health mechanism look like?
Does the platform coordinate national agencies?
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