AI-Enabled Refugee Forecasting for Uganda's Displacement Crisis Response Mechanism (DCRM)

Overview

Uganda's Displacement Crisis Response Mechanism (DCRM) is the world's first displacement risk financing mechanism, developed as a component of the Development Response to Displacement Impact Project (DRDIP) implemented by the Government of Uganda's Office of the Prime Minister. The DCRM integrates an artificial intelligence forecasting model developed by the World Bank to predict refugee inflows into Uganda from the Democratic Republic of Congo and South Sudan, enabling anticipatory public service scale-up in refugee-hosting districts before large population movements materialise.

The AI forecasting model is a machine-learning system that ingests over 90 independent variables spanning hundreds of dimensions across economic, social, natural, and built environments. Specifically, the model analyses conflict indicators, economic activity data, climate and vegetation monitoring data, food and market price information, built infrastructure assessments, and online language sentiment and volume regarding conflict, gender, and governance discourse drawn from news and social media sources. A distinctive feature of the model's design is its incorporation of perception-based information alongside concrete measurable data, reflecting the recognition that human displacement behaviour is driven not only by objective conditions but also by perceptions of change. The model was trained and tested using UNHCR daily refugee arrival data covering the period from 2014 to 2023, with separate models calibrated for arrivals from South Sudan and the Democratic Republic of Congo. When tested on unseen data, the model demonstrated over 80 percent accuracy in forecasting changes in future volumes of refugee inflows, producing predictions approximately four to six months ahead of actual arrivals.

The DCRM operates through a rules-based, pre-financed mechanism that prearranges contingency funding and pre-agrees intervention protocols before displacement shocks occur. A formal DCRM handbook, adopted by the Government of Uganda, outlines the guiding principles and operational processes for activation, including the use of need indices that measure the ratio of persons to public service facilities across refugee-hosting districts, identifying areas with the greatest per-capita service gaps. When the AI model forecasts significant refugee inflows or when actual inflows exceed pre-agreed thresholds, the mechanism is triggered and funds are disbursed to eligible host districts for rapid scale-up of public services. The activation process follows a transparent, needs-based, and pre-agreed procedure for sector and district selection, ensuring proportionate allocation based on documented needs rather than ad-hoc responses. Government officials retain decision authority throughout the disbursement process; the AI forecasts inform but do not determine funding decisions.

The DCRM has been activated twice. The first pilot activation occurred in 2021, disbursing approximately USD 1.2 million to two host districts. The second activation in 2023 was substantially larger, disbursing USD 3.3 million across all 13 eligible refugee-hosting districts, nearly triple the pilot amount. The 2023 activation prioritised water infrastructure investments in response to drought conditions that had placed additional stress on existing water sources in host communities. Both activations funded scale-up of public services in water access, health centre capacity, and classroom expansion. The mechanism also incorporates object classification models applied to satellite imagery for robust displacement impact assessment as part of its advanced data collection approach.

The DCRM is funded through the DRDIP project, which represents approximately USD 50 million in IDA financing from the World Bank to the Government of Uganda, with a pre-financed contingency allocation of USD 4.5 million dedicated to the DCRM component. Additional support has been provided by the World Bank-administered Multi-Donor Trust Fund for Forced Displacement and the PROSPECTS Partnership, with funding from the Kingdom of the Netherlands. The mechanism leverages Uganda's progressive refugee policies, which grant refugees rights to employment, land allocation, and access to national public services, integrating displacement response within the national development framework rather than treating it as a separate humanitarian exercise.

The initiative represents a shift from reactive to anticipatory humanitarian and development response. By enabling governments to build water points, expand health facilities, and construct classrooms before refugees arrive, the DCRM has contributed to reducing tension between refugee and host communities, strengthening community resilience, and enabling more efficient resource allocation. The World Bank has noted that the AI model is adaptable for predicting and explaining other development challenges beyond displacement, such as poverty levels and macro-fiscal pressures, suggesting potential for broader application of the forecasting approach within social protection systems.

Classification

Programme Details

The DCRM is a rules-based, pre-financed contingency funding mechanism embedded within the Development Response to Displacement Impact Project (DRDIP). It prearranges funds and pre-agrees intervention protocols to enable rapid public service scale-up in refugee-hosting districts when displacement thresholds are breached or forecast.

Implementation Details

Risk & Oversight

Deployment & Outcomes

Sources

1. SRC-001-UGA-001 Financial Protection Forum (2023). 'According to Plan: Second Activation of Uganda's Displacement Crisis Response Mechanism (DCRM)'. Washington, DC: World Bank SPJ Platform. Available at: https://www.financialprotectionforum.org/blog/according-to-plan-second-activation-of-ugandas-displacement-crisis-response-mechanism-dcrm (Accessed 24 March 2026).
   https://www.financialprotectionforum.org/blog/according-to-plan-second-activation-of-ugandas-displacement-crisis-response-mechanism-dcrm
2. SRC-006-UGA-001 World Bank (2019). 'Machine Learning in Uganda Brings the Power of Risk Financing to Strengthen Refugee and Host Community Resilience'. Nasikiliza blog. Available at: https://blogs.worldbank.org/nasikiliza/machine-learning-uganda-brings-power-risk-financing-strengthen-refugee-and-host (Accessed 24 March 2026).
   https://blogs.worldbank.org/nasikiliza/machine-learning-uganda-brings-power-risk-financing-strengthen-refugee-and-host
3. SRC-002-UGA-001 World Bank (2020). 'Data-Driven Development Response to Displacement Crisis in Uganda: The Displacement Crisis Response Mechanism'. Washington, DC: World Bank. Available at: https://documents1.worldbank.org/curated/en/472101606119818621/pdf/Data-Driven-Development-Response-to-Displacement-Crisis-in-Uganda-The-Displacement-Crisis-Response-Mechanism.pdf (Accessed 24 March 2026).
   https://documents1.worldbank.org/curated/en/472101606119818621/pdf/Data-Driven-Development-Response-to-Displacement-Crisis-in-Uganda-The-Displacement-Crisis-Response-Mechanism.pdf
4. SRC-005-UGA-001 World Bank (2021). 'How AI Can Support Anticipatory Action to Address Forced Displacement'. Development for Peace blog. Available at: https://blogs.worldbank.org/en/dev4peace/how-ai-can-support-anticipatory-action-to-address-forced-displac (Accessed 24 March 2026).
   https://blogs.worldbank.org/en/dev4peace/how-ai-can-support-anticipatory-action-to-address-forced-displac
5. SRC-003-UGA-001 World Bank (2025). 'AI-Powered Refugee Forecasting: Preparing for Refugee Movements Before They Happen'. Washington, DC: World Bank. Available at: https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/ai-powered-refugee-forecasting-preparing-for-refugee-movements-before-they-happen (Accessed 24 March 2026).
   https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/ai-powered-refugee-forecasting-preparing-for-refugee-movements-before-they-happen
6. SRC-004-UGA-001 World Bank (2025). 'AI-Powered Refugee Forecasting' [one-pager]. Washington, DC: World Bank. Available at: https://thedocs.worldbank.org/en/doc/4d816aaea9713abd30f63c6b92e1e79b-0090082025/original/AI-Powered-refugee-forecasting.pdf (Accessed 24 March 2026).
   https://thedocs.worldbank.org/en/doc/4d816aaea9713abd30f63c6b92e1e79b-0090082025/original/AI-Powered-refugee-forecasting.pdf