The Global Centre for Risk and Innovation (GCRI)
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.
GCRI · Established · service level R0
Health equity is the absence of unfair and avoidable differences in health among groups of people. Exposure to hazards, vulnerability and access to care differ by income, place, gender, age, disability, ethnicity and migration status, and shocks widen these gaps. Disaggregated data stops averages hiding the people most at risk.
How far each division sits from a large city, with the roads and airports that carry patients and supplies, shown for Nepal as an example geography for this subject.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Health equity · Summer season · District 4
| People over 75 living alone | 1061 | 40 | On track |
| Outdoor workers | 2143 | 66 | Behind |
| Care homes | 16 | 92 | On track |
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.
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.
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.
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.
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.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Health inequity | A difference in health that is unnecessary, avoidable and unjust, as distinct from any measurable inequality. |
| Universal health coverage | All people having access to the quality health services they need without financial hardship; SDG target 3.8. |
| Catastrophic health spending | Out-of-pocket health spending above a set share of household consumption or income; SDG indicator 3.8.2. |
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 topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
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 |
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 |
Equity work asks who bears the harm and why.
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.
| 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 generalization |
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.