GCRI · Disaster Resilience and Recovery
Preparedness and continuity
Preparedness is the knowledge, plans, stocks and capacities that let governments, services, businesses and households respond to a disaster and recover. Continuity planning applies the same idea to the critical functions of an organisation. This page sets out how preparedness is built and how it decays, how capacity is measured, and what evidence serves the authorities and operators who must be ready.
Preparedness and continuity on the record.
Preparedness and continuity: how the risk develops.
Organisational capacity and continuity. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Stocks and capacities age
Prepositioned supplies expire, equipment breaks, trained staff move on and contact lists go out of date. Preparedness that is not maintained loses value quietly between events.
Plans assume conditions
Plans rely on roads, power, communications and staff being available. When a disaster removes those conditions, plans written for normal circumstances stall.
Coordination is built before it is needed
Agencies that have never worked together lose time agreeing roles during a response. Standing arrangements, shared procedures and joint exercises save that time.
Critical functions depend on others
A hospital, water utility or government office continues only if its suppliers, staff and premises do. Continuity planning that ignores these dependencies fails when they fail.
Hazards now in the Philippines.
Population density, flood water, active fires and true-colour imagery over the Philippines, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 4
Hazards now, for this page
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.
Hazards now, framed on the Philippines.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 · NASA HLS S30Sources 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
- 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
- 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.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Observed (EO): NASA HLS S30 (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).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- 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 (20 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
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 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
Preparedness depends on continuity in every lifeline.
- EnergyCouplingBackup power decides how long critical services hold.What to watchBackup autonomy in hours
- WaterCouplingEmergency water supply plans bridge outages.What to watchAlternative supply arrangements
- HealthCouplingHealth continuity plans protect essential services.What to watchEssential services maintained
Preparedness findings are designed for the Country Quarterly series. Continuity practice follows ISO 22301; plans are only as good as their last exercise.
- Continuity plans with exercise results.
- Records of backup performance in real outages.
Anticipatory action console.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Anticipatory action console
Preparedness and continuity · Province C · Monsoon season
Protocol
- Readinessforecast lead 10 d
- Activationlead 3 d
- Early actions72 h window
- Responseif event
- Learningreview
River forecast at trigger gauge
Pre-agreed actions
| Cash to at-risk households | 72 h | 47 | Yes |
| Livestock evacuation | 48 h | 13 | Partial |
| Shelter kits | 72 h | 23 | Yes |
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 |
|---|---|---|---|---|
| Contingency plans tested in the last cycle | percent of plans | annual | Exercise and plan review records | REPORTED |
| Prepositioned relief stocks | units of items against planning figures | quarterly | Logistics records | REPORTED |
| Emergency operations centres with backup power and communications | count | annual | Facility assessments | OBSERVED |
| Critical services with continuity plans | percent of designated critical services | annual | Continuity programme records | DECLARED |
| Trained responders | count by role per population | annual | Training registers | REPORTED |
| Stock past expiry | percent of stock items | quarterly | Inventory records | OBSERVED |
Hazard to loss: the exceedance curve.
How often a given loss is exceeded, from a Gumbel hazard, a lognormal fragility and a protection standard; the area under the curve is the average annual loss. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Philippines; the model itself is not tied to a place.
Controls
- Typical annual hazard intensity (location)
- 1.00 intensity index
- Spread of extremes (scale)
- 0.80 intensity index
- Intensity at which half the value is lost
- 4.00 intensity index
- Dispersion of vulnerability
- 0.55
- Share of value in the hazard footprint
- 40%
- Protection standard (return period)
- 50 years
Readouts
- Average annual loss
- 0.51% of value
- Loss at 1 in 100 years
- 24.5% of value
- Loss at 1 in 250 years
- 28.4% of value
- Intensity at 1 in 100 years
- 4.68 intensity index
Numbers, methods and sources
| Return period (years) | Intensity (intensity index) | Loss (% of value) |
|---|---|---|
| 1 | 0.09 | 0.00 |
| 2 | 1.27 | 0.00 |
| 4 | 1.91 | 0.00 |
| 7 | 2.47 | 0.00 |
| 13 | 3.00 | 0.00 |
| 24 | 3.51 | 0.00 |
| 44 | 4.02 | 0.00 |
| 82 | 4.53 | 23.55 |
| 154 | 5.03 | 26.44 |
| 287 | 5.53 | 28.87 |
| 536 | 6.03 | 30.88 |
| 1,000 | 6.53 | 32.53 |
Methods
- Gumbel extreme-value hazard Gumbel (1958), Statistics of Extremes, Columbia University Press
- Lognormal fragility (vulnerability) FEMA (2003), HAZUS-MH Technical Manual
- Exceedance-probability curve and average annual loss Grossi and Kunreuther (2005), Catastrophe Modeling, Springer
- Levee effect Di Baldassarre and others (2013), Socio-hydrology, HESS 17
- 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:
- Rivers Natural Earth
- Urban extents Natural Earth
- Cities Natural Earth
- Earthquakes M4.5+, past week (USGS) U.S. Geological Survey · register usgs.earthquake.summary-feeds
- Rain rate, last half hour (IMERG) NASA GPM IMERG Early · register nasa.gibs.context-live-layers
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo) Open-Meteo.com (CC BY 4.0), Copernicus GloFAS · register open-meteo.public-pages
- Built-up and settlement extent, 2010 (HBASE, Landsat) CIESIN/Columbia, NASA SEDAC HBASE · register sedac.context-urban-layers
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Disaster Resilience and Recovery in Foundry
- Tested at Disaster Resilience and Recovery in Universe
- Codified in Hazards and Disaster Risk Reduction in Standards
- Published in Disaster Resilience and Recovery in Reports
- Taught in Faculty of Hazards, Disasters and Resilience in Academy
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 |
|---|---|---|
| Sendai Framework Monitor | National reporting on preparedness-related indicators | Public, UN terms of use |
| IFRC GO platform | Emergency appeals, operations and preparedness information from Red Cross and Red Crescent Societies | Public, IFRC terms (to check) |
| OCHA Humanitarian Data Exchange | Shared datasets on emergencies, populations and logistics | Open, licence per dataset |
| ISO 22301 and ISO 22313 | Requirements and guidance for business continuity management | Licensed standards, purchase required |
| National civil protection and emergency management plans | Published plans, roles and capacities | Public records, licence per government |
Model preparedness and continuity as a system. Run the cascade.
Assembled from the Nexus Standards area profile Business continuity and resilience: 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
- Dam failure
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-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-K36Domain pack profile: Critical infrastructure (DOMAIN-036)NRS-H107Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)NRS-H120Hazard family: Structural fragility of interconnected systems (NHS-1 sys.fragility)NRS-X8Operational resilience and business continuityNRS-H56Hazard family: Conflict-induced harm (NHS-1 soc.conflict-induced)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)
Observation
- NASA Black Marble night-time lights (VNP46) (listed for reference)
- OpenStreetMap planet and replication (listed for reference)
- Number of disruptions to basic services attributed to disasters
Example geography
- Europe: 113 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
- Surface soil moisture (SMAP), NASA GIBS
Who decides, and what the evidence serves.
Disaster Resilience and Recovery 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 |
|---|---|---|
| National disaster management authorities | Which capacities, stocks and plans to maintain and where | Capacity reviews; prepositioning analyses |
| Operators of critical services | Which functions must continue and what they depend on | Continuity dependency reviews |
| Local governments | How to organise local emergency operations and shelters | Facility assessments; local capacity evidence |
Outputs this topic produces
- Preparedness capacity reviews for national and local authorities
- Prepositioning analyses that place stocks against hazard and access
- Continuity dependency reviews for critical services
- Plan maintenance checklists with review triggers
How preparedness and 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.
Uncertainty bands
How far the outlook for preparedness and continuity could spread, shown as ranges rather than a single line.
- Central estimate
- median of the ensemble
- Ranges
- likely and very likely, in IPCC calibrated language
- Ensemble
- members, scenarios and initial conditions stated
- Read with
- the sensitivity of the result to each input
What experts ask.
Specialists in preparedness and continuity focus on whether arrangements hold when tested.
- Which functions must continue in a crisis, and what do they depend on?
- Do plans reflect how people and systems actually behave under stress?
- How are responsibilities divided between agencies, and where do gaps and overlaps sit?
- How are staff, supplies, facilities and data kept available when normal arrangements fail?
- How is preparedness sustained between disasters, when attention and budgets move elsewhere?
Why plans fail at the seams.
Plans often assume that people will be available, that communications will work, that suppliers will deliver and that other agencies will do their part. In real events, staff are themselves affected, networks are congested or down, suppliers face the same disruption and agencies interpret their roles differently. Failures cluster at interfaces: between levels of government, between public and private operators, and between emergency services and the organisations that run water, power and health care.
Continuity depends on knowing dependencies in advance, on redundancy and substitutes for critical inputs, and on people who have practised their roles together. Preparedness also decays: staff move on, contact lists age and equipment is not maintained. Regular exercise and review are what keep a plan alive.
How the evidence is built, and where it stops.
- 01
Capacity assessment
Structured review of plans, resources and arrangements. Self-assessment tends to overstate readiness.
- 02
Dependency mapping
Mapping inputs to essential functions with operations research. Hidden dependencies often emerge only in events or exercises.
- 03
After-action review
Structured learning from events and exercises. Lessons are often recorded but not implemented.
- 04
Comparative case research
Comparing how similar organisations fared, with social and behavioural science. Context limits how far findings transfer.
How it is studied, and what the methods cannot say.
- 01Decision analysis under uncertaintyCost-benefit of risk reduction · Acting on forecasts · Recovery prioritisationApplied here
- 02Optimisation and operations researchPrepositioning relief supplies · Evacuation and shelter planning · Restoration sequencingApplied here
- 03Geospatial information systemsExposure mapping · Rapid damage assessment · Common operational dataApplied here
- 04Social and behavioural scienceWarning response surveys · Participatory risk assessment · Social vulnerability analysisApplied 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 disaster preparedness?
What is business continuity planning?
Why test plans?
What is the difference between preparedness and continuity?
Can preparedness be measured?
Does the platform review my organisation's plan?
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