GCRI · Health Nexus
Health system continuity
A health system keeps working through a shock when its staff, power, water, medicines, data and referral routes hold together long enough for essential care to continue. Continuity fails at the weakest of these dependencies, often far from the hazard itself. This page sets out how disruption develops and propagates through services, how continuity is measured, and what the evidence serves for the institutions that must keep care running.
Health system continuity on the record.
Health system continuity: how the risk develops.
Hospitals, staff, power and essential 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.
Dependencies fail in sequence
A facility depends on grid power, piped water, medical oxygen, fuel, communications and supply deliveries. Losing one rarely stops care at once: generators, stored water and buffer stock buy time, and the binding constraint is whichever buffer runs out first.
The workforce is the first buffer
Staff absorb surges through overtime, redeployment and task shifting, but illness, displacement, caring duties and unpaid salaries erode that capacity. A system that loses staff loses services even when its buildings and supplies are intact.
Essential services are crowded out
During an epidemic or disaster, routine immunisation, maternal care, chronic disease management and mental health services are deferred or abandoned. The indirect harm from interrupted care appears later than the direct harm of the shock and is counted less often.
Disruption compounds across shocks
A system still recovering from one event meets the next with depleted staff, stock and finance. Heat during an outbreak, or conflict during a flood, stacks the pressures, and recovery lengthens with each overlapping shock.
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
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- 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
- 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
- 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
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
Health services keep running only if their inputs do.
| Domain | How it couples here | What to watch |
|---|---|---|
| Energy | Power for theatres, intensive care, oxygen and cold chains. See grid disruption and recovery. | Backup autonomy in hours; facilities without reliable electricity |
| Water | Safe water for clinical care, sterilisation and dialysis. See water utilities. | Water storage at facilities in days of use |
| Food | Nutrition for inpatients and therapeutic feeding programmes. | Supply interruptions of therapeutic foods |
| Biodiversity | Medicinal resources and disease ecology shift with ecosystem change. | Vector range change near facilities |
WHO’s Health Emergency and Disaster Risk Management Framework (2019) and its operational framework for climate resilient and low carbon health systems (2023) describe continuity as a property of the whole system: workforce, supplies, facilities, information and finance. Continuity is measured by service volumes against baseline, for example essential services tracked during the COVID-19 pandemic.
Surveillance and capacity board.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Continuity evidence and contributions.
Continuity analyses are designed for the Country Quarterly series. Decisions on health services stay with ministries of health and providers; the Global Centre for Risk and Innovation (GCRI) assesses no facility. Service-volume series would carry NS-3 identifiers under the proposed Nexus Standards, using aggregated data only.
- Service disruption records from past emergencies.
- Facility continuity plans and their exercise results.
- Workforce absence data during shocks, aggregated.
Model health system continuity 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 |
|---|---|---|---|---|
| Essential health service disruption | percent of tracer services reported disrupted | per survey round | Key informant national and facility surveys | REPORTED |
| Routine service volume against expected | ratio of observed to expected visits | monthly | Routine health information systems such as DHIS2 | ESTIMATED |
| Facilities with reliable electricity and water | percent of facilities | per assessment | Facility surveys such as SARA and SPA | OBSERVED |
| Backup power and water endurance | hours of autonomous operation | per facility | Facility asset registers | Published statistics |
| Health worker density | doctors, nurses and midwives per ten thousand population | annual | National health workforce accounts | Published statistics |
| Unfilled shifts | percent of rostered shifts unfilled | weekly | Hospital human resources records | OBSERVED |
| Tracer medicine stock-out | percent of facilities reporting a stock-out | monthly | Logistics management information systems | REPORTED |
| Bed occupancy and surge capacity | percent occupied; additional beds deployable | daily | Hospital bed management systems | OBSERVED |
The sector signature of health system continuity.
The sectors health system continuity 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 pulse surveys on continuity of essential health services | National reports of service disruption, its causes and mitigation across tracer services | Published records, WHO terms of use |
| DHIS2 national health information systems | Routine facility reporting of service volumes, stock and workforce | By agreement with each ministry of health |
| WHO SARA and DHS Service Provision Assessment surveys | Facility readiness: power, water, equipment, staff, diagnostics and medicines | Terms per survey programme |
| WHO National Health Workforce Accounts | Health workforce stock, distribution and flows by cadre | Open, attribution, WHO terms of use |
| WHO HeRAMS | Functionality, accessibility and service availability of facilities in emergencies | By agreement; public summaries |
| WHO Global Health Expenditure Database | Health spending by source of financing and function | Open, attribution, WHO terms of use |
How health system continuity 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 system continuity: 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 | Which essential services must be protected first in a shock, and with what reserve capacity | Tracer-service disruption patterns; dependency maps; workforce and stock buffers by district |
| Hospital boards and managers | Where to invest first: backup power, water storage, oxygen supply or surge staffing | Endurance hours by dependency; stress tests by facility and scenario |
| Finance ministries and development partners | How much contingency financing keeps services running, and how fast it must flow | Continuity scenarios with service losses stated apart from the direct impacts of the shock |
| WHO regional offices and national public health institutes | Where to deploy surge teams and supplies when several countries are affected at once | Comparable continuity evidence across countries, with reporting completeness labelled |
Outputs this topic produces
- Dependency maps of facilities on power, water, oxygen, staff and supplies
- Continuity stress tests for outbreak, heat, flood and outage scenarios
- Expected-against-observed service tracking with reporting completeness stated
- Health-system resilience briefs prepared for review by ministries
What experts ask.
Continuity starts from services, not buildings.
- Which services are essential, and for how long can each be interrupted before harm occurs?
- What does each essential service depend on, including dependencies outside the health sector?
- How long can backup power, water storage, oxygen and medicine stocks sustain operations?
- Can enough staff reach the facility and work safely during the event?
- How do neighbouring facilities absorb diverted patients, and what happens when they are affected too?
Mechanisms and drivers.
Hospitals are designed with redundancy, but redundancy is usually sized for single failures of limited duration. Extended or compound events, such as a regional outage during a heatwave, can exhaust backup fuel, overheat equipment and wards, and coincide with a surge in patients. Small dependencies with no substitute, such as a single medical gas supplier or a laboratory information system, can halt whole departments.
Workforce is often the binding constraint. Staff are themselves affected by the event, may be unable to travel, and fatigue quickly under surge conditions. Continuity also degrades gradually rather than failing outright: elective activity is cancelled first, then standards of care are adjusted, and harm accumulates among patients whose treatment is delayed.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Facility dependency mapping | Which services rely on which utilities, suppliers and systems | Depends on accurate internal data that facilities may not hold or share |
| Business impact and maximum tolerable outage analysis | How long each service can be interrupted | Tolerances are judgements and vary with case mix |
| Exercises and after-action reviews | How plans perform with real people | Exercises rarely test long or compound disruptions |
| Discrete-event and agent-based simulation | Queues, bed occupancy and staff load under surge | Results are sensitive to behavioural assumptions |
| Routine activity and outcome data | Deferred care and excess harm after events | Attribution to the disruption needs careful causal design |
How it is studied, and what the methods cannot say.
- 01Epidemiology and public health scienceSurveillance design and evaluation · Nowcasting under reporting delayApplied here
- 02Complex systems and agent-based modellingContact and mobility networks · Cascades across health and infrastructureApplied here
- 03Probability and statisticsSurvey-weighted and small-area estimation · Expected baselines for excess mortalityApplied here
- 04Data engineering, interoperability and stewardshipLinking health information systems · Privacy-preserving publicationApplied here
- 05Causal inference and impact evaluationEvaluating public health measures · Exposure-response for heat and airApplied 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.
- Health Emergency and Disaster Risk Management Framework (WHO, 2019)
- Operational framework for building climate resilient and low carbon health systems (WHO, 2023)
- Hospital Safety Index: guide for evaluators, second edition (WHO and PAHO, 2015)
- NS-3, NXS-GRX (canonical data, provenance and risk) record UNIs, a proposed standard
Where this page leads across the Consortium.
Questions and answers.
What is an essential health service?
Why measure the indirect effects of a shock?
How long can a hospital run without grid power?
Does Health Nexus tell hospitals what to do?
Is continuity the same as emergency preparedness?
Does Health Nexus assess individual hospitals?
Which services are usually treated as essential?
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