GCRI · Health Nexus
Health equity
Health risk is not shared equally. Exposure to hazards, vulnerability to their effects and access to care differ by income, place, gender, age, disability, ethnicity and migration status, and these differences compound one another. This page sets out how health inequities arise and widen under stress, how they are measured without hiding people in averages, and what disaggregated evidence serves for the institutions responsible for universal health coverage.
Health equity on the record.
Health equity: how the risk develops.
Unequal exposure and access to services. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Exposure follows disadvantage
Lower-income households more often live on flood plains, in heat islands, beside polluting sources and in informal settlements without safe water. The same hazard does more harm where exposure and vulnerability coincide.
Access depends on distance and cost
Travel time, transport cost, user fees, opening hours and language decide whether care is used. Out-of-pocket spending pushes households into hardship or leads them to forgo care, and both widen gaps.
Averages hide the gap
National indicators can improve while some groups fall behind. Disaggregation by wealth, place, sex and other dimensions reveals who is being left behind, and it needs sample sizes and identifiers that many systems lack.
Shocks widen inequities
Disasters and epidemics cut income, disrupt services and displace people, and the least resourced recover slowest. Without deliberate protection, each shock leaves the social gradient in health steeper than before.
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
- 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
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
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 · 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
- 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.
- 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
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
Inequity concentrates exposure across every domain.
| Domain | How it couples here | What to watch |
|---|---|---|
| Water | Households without safely managed water bear the first effects of supply failure. See drinking water and sanitation. | Service ladder by wealth quintile |
| Energy | Energy poverty limits heating, cooling and safe cooking. | Clean cooking access by income |
| Food | Food insecurity and poor diets track income. See food security and access. | Cost of a healthy diet relative to income |
| Biodiversity | Communities dependent on natural resources lose most when ecosystems degrade. | Natural resource dependence of livelihoods |
The Commission on Social Determinants of Health (2008) set the frame: health inequities follow the conditions in which people are born, grow, live, work and age. WHO’s Health Equity Assessment Toolkit computes summary measures of inequality, such as the difference and ratio between subgroups, and WHO’s world report on social determinants of health equity (2025) updates the evidence.
Heat-health and equity watch.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Heat-health and equity watch
Health equity · Summer season · District 4
Daily maximum temperature
Outreach to at-risk groups
| People over 75 living alone | 1061 | 40 | On track |
| Outdoor workers | 2143 | 66 | Behind |
| Care homes | 16 | 92 | On track |
Actions
- A-1Open cooling centres, district 4Civil protectiontoday
- A-2Adjust outdoor work hoursLabour inspectorate1 d
Equity evidence and how communities take part.
Disaggregated analyses are designed for the Country Systems Risk and Resilience series and the Evidence Brief series. Small subgroups are suppressed rather than reported with misleading precision. Communities can contribute accounts of access barriers and corrections to how they are described, through consent-aware routes.
Model health equity 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
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 |
|---|---|---|---|---|
| UHC service coverage index | index from zero to one hundred | biennial | SDG indicator 3.8.1 from tracer service data | ESTIMATED |
| Catastrophic health spending | percent of households above the spending threshold | per survey | Household budget surveys, SDG indicator 3.8.2 | ESTIMATED |
| Travel time to the nearest health facility | minutes | per update | Friction surfaces with facility locations | MODELLED |
| Wealth gap in skilled birth attendance | percentage-point difference between richest and poorest quintiles | per survey | DHS and MICS household surveys | ESTIMATED |
| Subnational under-five mortality | deaths per thousand live births | annual | Surveys and vital registration with small-area models | MODELLED |
| Population in hazard zones by deprivation | persons | per update | Gridded population, hazard layers and deprivation indices | ESTIMATED |
| Completeness of disaggregated reporting | percent of indicators reported by sex, age and place | annual | Health information system audits | REPORTED |
The sector signature of health equity.
The sectors health equity touches and how strongly they depend on each other: what a study has to observe and model together.
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
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 Health Inequality Data Repository | Health indicators disaggregated by dimensions of inequality | Open, attribution, WHO terms of use |
| Demographic and Health Surveys and UNICEF MICS | Household data by wealth, residence, education and sex | Free with registration, terms per survey |
| World Bank Health Equity and Financial Protection Indicators | Service coverage and financial protection by wealth quintile | Free and open, attribution (CC BY 4.0) |
| Malaria Atlas Project accessibility surfaces | Modelled travel time to health facilities | Free and open, attribution (CC BY 4.0) |
| WorldPop | Gridded population by age and sex | Free and open, attribution (CC BY 4.0) |
| Global Data Lab Subnational Human Development Index | Subnational development, education and health indices | Free, attribution, terms of use |
How health equity 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 health equity: 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 |
|---|---|---|
| Ministries of health | Where to place new facilities, outreach and staff to close coverage gaps | Access maps with modelled travel time; disaggregated coverage with uncertainty |
| Health financing agencies and insurers | Which groups need fee exemptions or subsidised coverage to avoid financial hardship | Catastrophic and impoverishing spending by quintile and region |
| Local governments and public health agencies | Which neighbourhoods need priority in heat, flood and outbreak plans | Exposure overlays with deprivation and service access |
| National statistics offices | Which identifiers and sample designs are needed to report by population group | Completeness audits of disaggregated reporting |
Outputs this topic produces
- Access maps of travel-time and cost barriers by population group
- Disaggregated health profiles with sampling uncertainty stated
- Overlays of hazard exposure, deprivation and service gaps
- Equity evidence for proposed investments and measures, prepared for review
What experts ask.
Equity work asks who bears the harm and why.
- Which groups are most exposed to a hazard, and which are most sensitive to it?
- Who can reach essential services in time, and who cannot?
- How do income, housing, occupation, disability, age, gender and legal status shape outcomes?
- Do emergency measures and service changes reduce or widen existing gaps?
- Whose data is missing, and what does that hide?
Mechanisms and drivers.
Differences in health outcomes arise from differences in exposure (for example, crowded or poorly insulated housing during heat), sensitivity (underlying conditions that are themselves unequally distributed) and capacity to cope (savings, paid leave, transport, information). These social determinants interact, so disadvantage compounds.
Access to care is shaped by distance, cost, opening hours, language, discrimination and trust. When services are disrupted, people with fewer alternatives lose access first and regain it last, and the burden of deferred care falls hardest on those who already had the least.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Health services access analysis | Travel time and cost to services by area and population group | Road networks and facility data may be outdated; travel modes vary |
| Disaggregated surveillance and outcome data | Differences in illness and death between groups | Many systems do not record ethnicity, disability or migration status consistently |
| Small-area deprivation indices | Where disadvantage is concentrated | Area averages can hide differences within neighbourhoods |
| Participatory and qualitative research | Barriers people actually face | Findings are context-specific and need careful generalisation |
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
- 03Causal inference and impact evaluationEvaluating public health measures · Exposure-response for heat and airApplied here
- 04Data engineering, interoperability and stewardshipLinking health information systems · Privacy-preserving publicationApplied 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.
Questions and answers.
What is the difference between inequality and inequity?
Why not simply report national averages?
How accurate are travel-time maps?
Is inequality in health the same as inequity?
Why are access maps useful?
How is sensitive group data protected?
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