Illustrative: event footprints crossing a portfolio, losses rising and the exceedance-probability curve

Risk Academy, led by the Nexus Consortium · Course catalogue · Hazards, Disasters and Resilience

Emergency Management and Recovery

Recovery, reconstruction and loss accounting

Recovery, reconstruction and loss accounting, taught twice over: as the working methods of the field and as its frontier since 2024, with labs on the Academy's tools, open data and the Nexus Standards.

Core course Frontier course

The discipline

01Core course · L2 Intermediate

Recovery, reconstruction and loss accounting: foundations and practice

This area covers what happens after a disaster: damage and loss assessment, post-disaster needs assessment, recovery planning and governance, reconstruction, and the recording of disaster losses over time.

Level
L2 Intermediate
Study time
about 24 hours (planning estimate)
Status
In authoring
Prerequisites
An L1 course in the area, or an entry review

Why now

Secondary perils now dominate insured losses, which matters for pricing, protection gaps and how loss databases weight frequent mid-sized events. Munich Re, Climate change presses on: Devastating wildfires and intense thunderstorms exacerbate losses for insurers, 13 January 2026

Learning outcomes

  1. Define post-disaster needs assessment and the other key terms of the discipline and use them correctly in a written case
  2. Explain damage, loss and needs assessment and disaster loss databases and accounting with a worked example and its source
  3. Apply the discipline's method to a documented case and explain each result with its source
  4. Analyse a named case against recovery planning and governance, stating evidence, date and limits

Modules

  1. Damage, loss and needs assessment
    • Damage, loss and needs assessment
    • Disaster loss databases and accounting
    • Recovery planning and governance
  2. Reconstruction and build back better
    • Reconstruction and build back better
    • Livelihood and economic recovery
    • Housing recovery
  3. Psychosocial recovery
    • Psychosocial recovery
    • Loss and damage in climate policy
  4. Lab: the discipline's method
    • A damage survey values destroyed assets; the time to rebuild them sets the output forgone while they are missing; damage plus losses plus an uplift for building back better is the recovery need; weighting the same loss by the income of those who bear it gives the well-being loss that the headline hides.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-C15 Loss, damage and impact accounting
  • NRS-D3 Humanitarian response and resilient recovery
  • NRS-M5 Method fabric: Consequence and loss

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C3 Hazard, exposure, vulnerability and capacity data
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C7 Early warning, triggers and anticipatory action
  • NRS-C8 Evidence, uncertainty and provenance

Assessment

  • 40%Lab recordWork the discipline's method through a documented case and explain each result with its source and date
  • 40%Case memoApply the discipline's methods to a named place or organisation, stating evidence and limits
  • 20%Key terms checkShort answers on the key terms, marked against the definitions

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Intermediate, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Munich Re, Climate change presses on: Devastating wildfires and intense thunderstorms exacerbate losses for insurers, 13 January 2026
  2. Hallegatte, Rentschler and Walsh, Building Back Better: Achieving Resilience through Stronger, Faster, and More Inclusive Post-Disaster Reconstruction, 2018
  3. Hallegatte, Vogt-Schilb, Bangalore and Rozenberg, Unbreakable: Building the Resilience of the Poor in the Face of Natural Disasters, 2017
  4. Olshansky, Hopkins and Johnson, Disaster and recovery: processes compressed in time, 2012
02Live map

Hazards now in Türkiye

Flood water, active fires, heavy rain and smoke, beside where people live, over Türkiye.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Hazards now

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 Türkiye.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 SurveySources 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 H3 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 H3 cells where shown (modified). NASA open data
  • 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 H3 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 H3 cells where shown (modified). NASA open data
  • GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 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 H3 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 H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • 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 H3 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 H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 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.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • 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.
  • 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

  • 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
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
  • Aerosol optical depth, daily: VIIRS NOAA-20 Deep Blue AOD, NASA LANCE · 13 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static

03How learning runs

How learning runs, as a process you can run

Select a scenario and press Play: course, pathway, practice, faculty, cells and record.

04What is changing

Frontier course · L3 advanced, programme courses and standards

Recovery, reconstruction and loss accounting: frontier methods

The methods, data, tools and studies that changed recovery, reconstruction and loss accounting between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Recovery, reconstruction and loss accounting: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

Secondary perils now dominate insured losses, which matters for pricing, protection gaps and how loss databases weight frequent mid-sized events. Munich Re, Climate change presses on: Devastating wildfires and intense thunderstorms exacerbate losses for insurers, 13 January 2026

Learning outcomes

  1. Explain what changed in recovery, reconstruction and loss accounting since 2024 and cite the studies, data or rules behind each change
  2. Reproduce Munich Re tallies 2025 natural disaster losses at 224 billion dollars on open data and state the uncertainty of the result
  3. Evaluate a 2024 to 2026 study: its question, data, method, limits and what it changes for practice
  4. Design an analysis that combines a frontier method with the faculty's instruments, and justify each choice

Modules

  1. Munich Re tallies 2025 natural disaster losses at 224 billion dollars
    • Munich Re estimated 2025 natural disaster losses at about 224 billion dollars, of which about 108 billion were insured; non-peak perils such as floods, severe storms and wildfires drove most losses, led by the Los Angeles fires.
    • Secondary perils now dominate insured losses, which matters for pricing, protection gaps and how loss databases weight frequent mid-sized events.
    • Munich Re, 13 January 2026
  2. Rapid estimate puts Hurricane Melissa damage in Jamaica at 8.8 billion dollars
    • A World Bank and IDB rapid post-disaster damage estimate (GRADE) put physical damage from Hurricane Melissa in Jamaica at 8.8 billion dollars, about 41% of 2024 GDP, mostly to housing and infrastructure; wider economic losses were excluded.
    • Rapid remote estimates now frame early recovery finance; users should treat them as first-order direct damage, ahead of full sectoral needs assessments.
    • World Bank, 19 November 2025
  3. NOAA retires its billion-dollar disasters database
    • NOAA announced that the US Billion-Dollar Weather and Climate Disasters product would be retired with no updates beyond calendar year 2024; archived reports and data for 1980–2024 remain available through NCEI.
    • Loss trend analyses relying on this series lose their public update path, so practitioners must document the break and find alternative loss data.
    • NOAA NESDIS, 8 May 2025
  4. Reproduction lab
    • Extend the discipline's method with one frontier method and compare its results
    • State the uncertainty and the limits of the result
    • Peer review against a shared checklist
  5. Technology that helps and the risks it carries
    • Drones, Earth observation, machine learning forecasting and cell broadcast warnings.
    • Telecom and positioning failure, and AI-generated misinformation in a crisis.

Labs with Academy tools

Nexus Standards

Teaches

  • NRS-C15 Loss, damage and impact accounting
  • NRS-D3 Humanitarian response and resilient recovery
  • NRS-M5 Method fabric: Consequence and loss

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C3 Hazard, exposure, vulnerability and capacity data
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C7 Early warning, triggers and anticipatory action
  • NRS-C8 Evidence, uncertainty and provenance

Assessment

  • 50%Method reproductionReproduce one frontier method on open data and state the uncertainty of the result
  • 30%Study reviewA critical review of a 2024 to 2026 study: question, data, method, limits, what it changes
  • 20%Peer reviewReview two other learners' reproductions against a shared checklist

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Expert, 5 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

References

  1. Munich Re, Climate change presses on: Devastating wildfires and intense thunderstorms exacerbate losses for insurers, 13 January 2026
  2. World Bank, World Bank, IDB, Estimate Hurricane Melissa Damage to Jamaica Totals All-Time-High of US$8.8 Billion, 19 November 2025
  3. NOAA NESDIS, Billion Dollar Weather and Climate Disasters, 8 May 2025
  4. Hallegatte, Rentschler and Walsh, Building Back Better: Achieving Resilience through Stronger, Faster, and More Inclusive Post-Disaster Reconstruction, 2018
  5. Hallegatte, Vogt-Schilb, Bangalore and Rozenberg, Unbreakable: Building the Resilience of the Poor in the Face of Natural Disasters, 2017
  6. Olshansky, Hopkins and Johnson, Disaster and recovery: processes compressed in time, 2012
05Take part

Take part in the work

Start from who you are.

06Questions

Questions, answers and key terms

Is the course free?
Yes. Every course and learning material of Risk Academy, led by the Nexus Consortium, is free to study, self-paced or with a cohort. Ordinary participation has no fee; paid work, internships and fellowships are separate arrangements.
What does completing a course give me?
A completion record: the course, its version, the date and what was assessed, private by default and shared by you. It stacks into discipline, department and programme achievements. A record states what was studied and assessed and does not certify competence; it is not a licence, a professional title or an employment status.
Where do the data and the places come from?
Every faculty teaches on a twin of a real place built from open data; each layer carries its provider, licence and date, and every result on the Academy states its source. Maps and figures are indicators for teaching, never an assessment of a place.
How do I take part beyond the course?
Form a competence cell of three to seven people, study a shared pathway, take a supervised assignment in the National Working Groups, or bring a cohort from your institution. For organisations.

Key terms

Term

Post-disaster needs assessment

A government-led assessment of damage, losses and recovery needs after a disaster.

Term

Damage and loss

Damage is the destruction of physical assets; loss is the change in economic flows that follows.

Term

Build back better

Using recovery and reconstruction to increase resilience through risk reduction.

Term

Disaster loss database

A systematic record of disaster events and their impacts over time and place.

ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

Risk Academy
Related

Around Recovery, reconstruction and loss accounting: courses

Risk Academy

Study recovery, reconstruction and loss accounting with us, or teach it

Every course is free and open. Institutions and experts can co-teach, host a cohort, contribute a lab or review a course before it opens.

Browse the course catalogue Partner with the Academy
Risk Academy

Courses · practice · credentials

Not for profit

Our articles, maps and twins are free to read and free to republish. Readers and partners keep it that way.

Support our work

Who funds us

Risk Academy is a not-for-profit institution. To ask who funds a piece of work, use the funding questions form.

Independence

Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.

Corrections policy

Licence

Articles: CC BY 4.0. Figures, maps, twins and data: CC BY 4.0. Other uses: ask through the permissions form.

Privacy choices