Guidance Note on Using the Probabilistic Country Risk Profiles for Disaster Risk Management is a guidance note / technical guidance document published in 2020 by CIMA Research Foundation, in the context of the programme “Building Disaster Resilience to Natural Hazards in Sub-Saharan African Regions, Countries and Communities.” The project was funded by the European Union and linked to the work of UNDRR on disaster risk management and probabilistic risk assessment.
Key insights:
The guidance note explains how probabilistic country risk profiles can be used to support disaster risk management, development planning, climate adaptation, preparedness, recovery, financing, education, risk communication, and land-use planning.
The document focuses on country risk profiles developed for 16 African countries under the Sub-Saharan Africa disaster resilience programme. These profiles assess flood and drought risks at national and sub-national levels.
The risk profiles use a probabilistic risk assessment methodology, meaning they do not only look at past disasters, but also model possible future events, including rare but high-impact disasters that may not yet have occurred.
The profiles estimate disaster risk by combining hazard, exposure, vulnerability, and capacity, following the general risk equation: Risk = Hazard × Exposure × Vulnerability / Capacity.
The guidance explains that probabilistic risk assessment is often seen as too technical, but it should be understood as a risk diagnosis tool. It helps governments understand where risk is concentrated, which sectors are most exposed, and how future climate change may alter risk patterns.
The profiles assess two climate scenarios: current climate conditions, based on observed climate data from 1979 to 2018, and projected climate conditions for 2051 to 2100, using the IPCC RCP 8.5 scenario.
The guidance highlights that these profiles are useful because they quantify disaster impacts in economic and human terms. They can show expected losses by country, sector, region, population group, and future climate scenario.
Two important metrics are emphasized: Annual Average Loss (AAL), which estimates the expected average yearly loss from disasters, and Probable Maximum Loss (PML), which estimates losses from severe events with specific return periods.
The document explains that probabilistic risk profiles can support policy coherence for disaster risk reduction by giving different ministries and institutions a shared evidence base. This helps align disaster risk reduction with development, climate adaptation, budgeting, and sectoral planning.
The guidance shows how the profiles can inform national development plans by identifying regions and sectors where future disaster risk could undermine development goals. The Zambia case study illustrates how projected drought risk could affect agriculture, crop losses, livestock, and GDP in drought-affected regions.
The profiles can also support National Adaptation Plans by identifying priority sectors, regions, and vulnerable groups most exposed to climate-related risks. This helps connect climate adaptation with disaster risk reduction.
For DRR strategies and mainstreaming, the guidance explains that risk profiles can help define objectives, monitoring indicators, geographic priorities, and capacity-building needs.
For preparedness and emergency response planning, the profiles can help governments allocate preparedness resources to sectors and regions likely to face higher disaster impacts. They can also support the evaluation of preparedness levels and corrective actions.
For recovery planning, the profiles can guide recovery investments, medium- and long-term reconstruction, and prioritization across sectors and regions.
The document also stresses the importance of risk communication. Probabilistic risk information can support awareness raising, dialogue between institutions and citizens, and behaviour change, but it needs to be translated into accessible messages.
For education, the profiles can support disaster risk reduction in teaching, learning, school safety, and safe school environments.
For land-use planning, the guidance explains that the profiles can help planners identify provinces or areas likely to face the highest disaster impacts, supporting strategic land-use decisions and spatial planning.
For disaster contingency funds, the profiles can provide governments with evidence on likely losses under different disaster scenarios and return periods. This can support financial planning and disaster risk financing decisions.
For cost-benefit analysis, the profiles can help calculate the benefits of risk reduction measures by estimating the losses that could be avoided if a specific intervention is implemented.
The summary table on page 9 is especially useful because it links each application area to practical uses of the risk profile, including policy coherence, national development planning, adaptation planning, DRR strategies, preparedness, recovery, communication, education, land-use planning, contingency funds, and cost-benefit analysis.
Main message: Probabilistic country risk profiles are not only technical documents; they are practical decision-making tools. When properly understood and adapted, they can help governments move from general awareness of disaster risk to evidence-based planning, budgeting, investment, preparedness, recovery, and climate adaptation. Their main value is that they translate complex risk into usable information on expected losses, affected populations, vulnerable sectors, and geographic priorities.
