GCRI · Health Nexus
Healthcare infrastructure
Hospitals and clinics must stay safe, standing and functioning when they are needed most: in earthquakes, floods, storms, heat, fires and conflict. Their resilience depends on location, on the structure, on non-structural elements such as equipment and utilities, and on how quickly they recover after damage. This page sets out how facilities fail and recover, how their safety is assessed, and what the evidence serves for the institutions that build and operate them.
Healthcare infrastructure in seven parts.
- 01The questionHealthcare infrastructure: how the risk develops
- 02CouplingsA hospital is a small city that depends on every lifeline
- 03Reports, standards and contributionsInfrastructure evidence and contributions
- 04IndicatorsWhat is measured, and how well
- 05SourcesWhere the evidence comes from
- 06DecisionsWho decides, and what the evidence serves
- 07Core questionsWhat experts ask
Healthcare infrastructure: how the risk develops.
Facility resilience and recovery. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Location sets the exposure
Facilities built on flood plains, low coasts, unstable slopes or near active faults carry that hazard for their whole working life. Siting decisions made decades earlier constrain what retrofitting can achieve.
Non-structural failure stops care
A building can stand while care stops: generators flood in basements, ceilings and medical gas lines fall, equipment topples and water tanks rupture. Non-structural elements fail at lower hazard intensities than structures and are cheaper to protect.
Functional dependencies lie outside
A hospital depends on roads for staff and patients, and on grid power, water mains, telecommunications and supply deliveries. A facility undamaged by a flood can still be unreachable or without water.
Recovery is its own process
After damage, recovery depends on assessment, repair finance, procurement and staff returning. Temporary facilities and referral to other sites bridge the gap, and recovery time differs by facility and by service line.
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
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. 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
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 · ESA Copernicus Sentinel-5P TROPOMI · 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
- 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): ESA Copernicus Sentinel-5P TROPOMI (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).
- 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
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
A hospital is a small city that depends on every lifeline.
| Domain | How it couples here | What to watch |
|---|---|---|
| Energy | Reliable electricity is a precondition of most care; many facilities in low-income settings lack it, as documented in the 2023 joint report of WHO, the World Bank, SEforALL and IRENA on electricity access in health-care facilities. | Facilities with reliable electricity |
| Water | On-site storage bridges supply interruptions. See water utilities. | Days of water storage |
| Food | Kitchens and supply stores need cold storage. | Food storage continuity |
| Biodiversity | Site selection and green design reduce flood and heat exposure. | Facilities in flood zones |
Facility safety is assessed with the WHO and PAHO Hospital Safety Index (second edition, 2015), which scores structural, non-structural and functional safety. WHO guidance on climate resilient and environmentally sustainable health care facilities (2020) adds climate hazards and environmental performance.
Health supply continuity.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Health supply continuity
Healthcare infrastructure · Province B · Month 10
Tracer commodities
| Oral rehydration salts | 1.0 | 5 | 6 | Low |
| First-line antibiotic | 0.7 | 14 | 12 | Low |
| Insulin | 4 | 4 | 10 | Adequate |
| Rapid diagnostic tests | 0.3 | 6 | 7 | Critical |
Order in transit
- Order
- PO-77959
- Route
- Port of entry to central store
- ETA
- 16 days
- Cold chain
- Monitored
Facilities stocked out by district
Infrastructure evidence and contributions.
Facility resilience studies are designed for the Country Systems Risk and Resilience series. Safety assessments are done by national teams trained in the index; the Global Centre for Risk and Innovation (GCRI) conducts none as an authority. Useful contributions: assessment results that a ministry chooses to publish, and facility performance in past events.
A cascade through interdependent networks.
A hazard footprint takes out co-located assets in every layer; fragmentation, dependency between layers and overload of the survivors then spread the failure. The 3D view separates the layers by depth. Teaching model with stated illustrative values, not a prediction. The map on this page shows Africa; the model itself is not tied to a place.
Controls
- Assets per layer
- 18
- Hazard footprint
- 8% of area
- Assets that depend on another layer
- 60%
- Spare capacity (tolerance)
- 30%
Readouts
- Assets hit by the hazard
- 17%
- Assets still working
- 17%
- Amplification of the initial damage
- 5.0 times
- Steps to settle
- 3
Numbers, methods and sources
| Step | Hospitals working (%) | Power working (%) | Water working (%) |
|---|---|---|---|
| 0 | 78 | 83 | 89 |
| 1 | 39 | 28 | 56 |
| 2 | 17 | 11 | 28 |
| 3 | 17 | 11 | 22 |
Methods
- Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
- Overload cascades Motter and Lai (2002), Physical Review E 66
- Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
- Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
- Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
- 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:
- Major roads Natural Earth
- Railways Natural Earth
- Seaports Natural Earth
- Airports Natural Earth
- Urban extents Natural Earth
- Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
- Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Health Nexus in Foundry
- Tested at Health Nexus in Universe
- Codified in Health and Biosecurity in Standards
- Published in Health Nexus in Reports
- Taught in Faculty of Health and Society in Academy
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 |
|---|---|---|---|---|
| Hospital Safety Index category | safety category from the index | per assessment | Hospital Safety Index assessments | Published statistics |
| Facilities in hazard zones | count of facilities by hazard class | per update | Facility locations on hazard maps | ESTIMATED |
| Facility functionality after an event | percent of facilities fully, partially or not functioning | per event | HeRAMS and rapid assessments | REPORTED |
| Population losing access after an event | persons beyond a travel-time threshold | per event | Access models with damaged roads and facilities | MODELLED |
| Time to restore services | days by service line | per event | Facility recovery records | REPORTED |
| Attacks on health care | incidents; facilities affected | continuous | WHO Surveillance System for Attacks on Health Care | REPORTED |
| Deferred maintenance and retrofit backlog | cost of deferred works, local currency | annual | Capital asset registers | Published statistics |
Model healthcare infrastructure 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
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 |
|---|---|---|
| National master facility lists | Authoritative facility identifiers, locations and service types | By agreement; some published as open data |
| Healthsites.io | Open map of health facilities built on OpenStreetMap | Open Database Licence (ODbL) |
| WHO HeRAMS | Facility status, damage and service availability in emergencies | By agreement; public summaries |
| WHO Surveillance System for Attacks on Health Care | Attacks on facilities, transport, personnel and patients in emergencies | Public dashboard, WHO terms of use |
| Copernicus Emergency Management Service | Rapid damage and flood mapping after disasters | Free and open, attribution |
| GEM global seismic hazard map | Seismic hazard for assessing facility exposure | Attribution, non-commercial, share-alike (CC BY-NC-SA) |
| JRC global river flood hazard maps | River flood extent and depth by return period | Free and open, attribution |
How healthcare infrastructure 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 healthcare infrastructure: 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 and capital planning units | Where to build, relocate or retrofit facilities, and in what order | Exposure profiles; Hospital Safety Index results; access loss scenarios |
| Hospital boards and facility managers | Which non-structural and utility protections to fund first | Dependency maps; failure modes by hazard; recovery times by service line |
| Disaster management agencies | Which facilities will remain reachable and functioning in an event, and where to send patients | Access loss scenarios; facility functionality reports |
| Humanitarian health clusters and WHO country offices | Where temporary facilities and mobile services are needed after damage or attack | HeRAMS functionality; attacks on health care; population without access |
Outputs this topic produces
- Facility exposure profiles by hazard with location uncertainty stated
- Functional dependency maps for power, water, access and supplies
- Access loss scenarios after facility or road failure
- Recovery and retrofit evidence for capital planning
What experts ask.
Infrastructure questions follow a hazard through a building to a service.
- Where are health facilities located relative to flood plains, fault lines, coasts and wildfire zones?
- How do structural and non-structural elements, such as ceilings, equipment and pipes, perform in a hazard?
- Which building systems, such as ventilation, cooling and medical gases, are most critical to keep running?
- How quickly can a damaged facility restore services, and where do patients go meanwhile?
- How should new and refurbished facilities be designed and sited for future hazards?
Mechanisms and drivers.
Hospitals can lose function without structural collapse. Non-structural damage, such as fallen equipment, broken pipes or failed lifts, and the loss of utilities are common causes of evacuation. Overheating can make wards and operating theatres unusable and damage medicines and equipment.
Recovery depends on the availability of engineers, parts and temporary facilities, and on the condition of the surrounding area. Facilities built decades ago may not reflect current hazard knowledge, and hazard patterns are changing with the climate, so siting and design decisions made now will be tested by conditions different from the past.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Hazard exposure mapping of facilities | Which facilities sit in hazard zones | Facility location and attribute data can be incomplete |
| Structural and non-structural assessment | How buildings and systems would perform | Requires on-site inspection and engineering expertise |
| Fragility and functionality models | Likely loss of function at given hazard intensities | Models generalise from limited observed damage |
| Post-event damage and recovery studies | What actually failed and how long recovery took | Each event is different; lessons need careful transfer |
How it is studied, and what the methods cannot say.
- 01Complex systems and agent-based modellingContact and mobility networks · Cascades across health and infrastructureApplied here
- 02Data engineering, interoperability and stewardshipLinking health information systems · Privacy-preserving publicationApplied here
- 03Probability and statisticsSurvey-weighted and small-area estimation · Expected baselines for excess mortalityApplied here
- 04Epidemiology and public health scienceSurveillance design and evaluation · Nowcasting under reporting delayApplied 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.
- Energizing health: accelerating electricity access in health-care facilities (WHO, World Bank, SEforALL and IRENA, 2023)
- Hospital Safety Index: guide for evaluators, second edition (WHO and PAHO, 2015)
- WHO guidance for climate resilient and environmentally sustainable health care facilities (WHO, 2020)
Questions and answers.
What is a safe hospital?
Why focus on non-structural elements?
Can open maps replace a master facility list?
What does safe hospital mean in this context?
Is retrofitting existing facilities worthwhile?
Does Health Nexus inspect buildings?
Contribute evidence from this page.
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