Data in action: a decade of remote, rapid damage assessments

As disasters grow more frequent and severe, the need for fast, reliable information in the immediate aftermath has never been greater. Governments, development partners and humanitarian agencies need to quickly understand the scale and nature of the impact so they can take informed action, mobilize resources and support recovery. Yet, traditional damage assessments can take weeks, and sometimes months, to complete. 

The Global Rapid Post-Disaster Damage Estimation (GRADE) approach was developed in 2015 to address this gap, delivering timely, credible estimates of disaster damage that can target response and recovery. Between 2015 and November 2024, GRADE had been used in 66 disasters across 54 countries, helping governments and partners respond faster and more effectively to crises.

What is GRADE?

GRADE is a remote, desk-based damage assessment methodology developed by the World Bank and the Global Facility for Disaster Reduction and Recovery’s (GFDRR) analytics thematic area, with financing support from Japan’s Ministry of Finance, through the Japan-World Bank Program for Mainstreaming Disaster Risk Management in Developing Countries. 

The framework uses a combination of disaster risk modeling techniques, and analysis of historical and damage data, census and socioeconomic survey data, satellite imagery, and social media feeds to produce preliminary damage estimates, often within 2-3 weeks of a disaster. GRADE results often provide the first detailed data-driven analysis of what was damaged, where, and at what scale, so that governments and task teams can rapidly make critical recovery decisions.

When compared with 17 events in which other damage assessments were also conducted, such as Post-Disaster Damage and Needs Assessments (PDNAs) and other similar detailed assessments, GRADE estimates were 88-90% aligned with the overall physical damage results of other infield assessments. Differences in results are usually due to variations in methodologies and key assumptions, timing of assessments, and/or availability of data, as explained in the report published in 2025, “A Review of the Global Rapid Post-Disaster Damage Estimation (GRADE) Assessments: The Frontier in Rapid Post-Disaster Damage Estimations for Developing Countries.” 

A decade of rapid, reliable assessments

This level of accuracy has allowed GRADE to be used by the World Bank and development partners to inform financing decisions including accessing World Bank’s International Development Association’s (IDA) Crisis Response Window (CRW), triggering Catastrophe Deferred Drawdown Options (Cat DDOs), and prioritizing early recovery investments. Within the World Bank over the last five years, GRADE assessments have enabled African countries to leverage $1.74 billion from the CRW, allowing financing to be released quickly to support recovery, response and reconstruction.

Over the past 10 years, GRADE has supported responses to earthquakes, floods, tropical cyclones, volcanic eruptions, landslides, and more recently, human-induced disasters. Some of these have required GRADE to go beyond standard approaches, due to their levels of complexity. For instance:

• In Indonesia, a M7.5 earthquake struck Central Sulawesi on September 28, 2018, resulting in compounded hazards (ground shaking, tsunami and mudflow impacts) that caused 4,300 deaths and damage to 14,650 buildings. The GRADE report delivered 11 days after the earthquake informed the World Bank’s decision to release up to $1 billion to supplement relief and reconstruction efforts in the disaster-affected areas. Alongside the written analysis, it included a Keyhole Markup Language Zipped (KMZ) file—a geospatial map package that allowed decision makers to visualize hazard impacts and damaged areas in Google Earth. This rapid visual evidence helped to better illustrate the complications and impacts caused by the run-on hazards in this event, while Indonesia’s National Disaster Management Authority worked on a more detailed, ground-based building damage assessment completed four months later.
• In Ukraine, GRADE was adapted to assess conflict-related damage to residential, private and public infrastructure between February 24 to March 31, 2022. The GRADE-estimated damage to buildings and infrastructure during this period amounted to $59.2 billion, more than 120% of Ukraine’s projected 2022 budget. These results were used in the World Bank’s approach paper for the ministerial roundtable discussions held during the 2022 World Bank–International Monetary Fund Spring Meetings.

Looking ahead: evolving for impact

As the frequency and severity of disasters increase, GRADE continues to evolve with an eye towards:

• Smarter analytics: Integrating AI and machine learning to improve detection and classification of damage.
• Sector-specific modules: Developing tailored approaches for critical sectors like transport, health, education, and energy.
• National capacity building: Supporting governments to internalize GRADE tools and expertise for faster, localized assessments.

The GRADEs conducted over the past decade have also contributed to the amassing of extensive databases on building exposure, vulnerabilities and hazards. These can be mined for further analyses and insights on the impact of disaster events across sectors. 

Levels of damage to key sectors across hazards (derived from GRADE-related databases)

For governments, GRADE provides a fast, reliable starting point for recovery. For World Bank teams and other development partners, it offers a credible, cost-effective foundation for determining financing and engagement strategies. In an era where disasters are more frequent, complex, and costly, tools like GRADE are essential for smarter, swifter responses. 

Source : World Bank