> For the complete documentation index, see [llms.txt](https://standards.spdci.org/standards/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://standards.spdci.org/standards/dci-standards/early-warning-systems/wip-early-warning-systems-and-sp-system-interface/9.-ews/1.2-process/prs.ews.02-sp-system-share-aggregated-data-for-analysis.md).

# PRS.EWS.02: SP system share aggregated data for analysis

The aim of the [PRS.EWS.02: SP system share aggregated data for analysis](/standards/dci-standards/early-warning-systems/wip-early-warning-systems-and-sp-system-interface/9.-ews/1.2-process/prs.ews.02-sp-system-share-aggregated-data-for-analysis.md) process is to support disaster preparedness, anticipatory action planning, and response coordination through the exchange of aggregated social protection data with Early Warning Systems (EWS), disaster risk management authorities, or authorized coordination platforms. This process enables the use of non-personally identifiable information from social protection systems to improve risk analysis, vulnerability mapping, and the estimation of potential impacts on vulnerable populations exposed to forecasted hazards.

This process can be implemented during preparedness, monitoring, forecasting, or emergency response stages to strengthen risk-informed decision-making and facilitate coordinated anticipatory action planning before hazard impacts materialize. The process supports institutions in understanding the geographic distribution and characteristics of vulnerable populations, including households already enrolled in social protection programmes or identified through national registries.

The information shared through this process is aggregated at predefined administrative or geographic levels, such as district, municipality, community, or livelihood zone, depending on national data governance frameworks and operational requirements. The process does not require the exchange of personally identifiable information (PII), unless explicitly authorized under national legal and operational procedures.

This process is particularly important for the implementation of Impact-Based Early Warning Systems (IB-EWS). While traditional early warning systems primarily focus on forecasting the hazard itself, such as rainfall levels, flood probability, drought conditions, or storm intensity, IB-EWS aim to estimate the expected impacts of those hazards on people, livelihoods, infrastructure, and essential services. To generate meaningful impact-based analysis, hazard information must be combined with exposure and vulnerability data. Aggregated social protection data provides a critical source of vulnerability and socioeconomic information that can help identify which population groups are likely to be most affected, where they are located, and what forms of support may be required.

By integrating aggregated social protection data into IB-EWS processes, institutions can improve:

* Risk and impact modelling for vulnerable populations;
* Geographic prioritization of anticipatory actions;
* Estimation of households potentially requiring assistance;
* Trigger design for shock-responsive social protection programmes;
* Accessible and targeted warning dissemination strategies;
* Coordination between meteorological, disaster management, and social protection institutions.

This integration supports a shift from hazard-centric warning approaches toward people-centred and risk-informed anticipatory action frameworks. It enables governments and partners to move beyond understanding “what hazard is coming” to understanding “who is likely to be affected, where, and with what potential consequences.”

Depending on the country context and interoperability framework, this process may operate independently or alongside additional processes related to early warning notifications, beneficiary verification, dynamic targeting, case management, assistance delivery, or post-disaster assessments.

The Data Standards section outlines the different categories of aggregated information that may be shared as part of this process depending on operational requirements and data availability. These may include aggregated beneficiary counts by geographic area, demographic breakdowns, poverty or vulnerability indicators, disability inclusion statistics, livelihood classifications, social protection programme coverage, or historical assistance data. Additional contextual datasets, such as exposure estimates, hazard overlays, or socioeconomic indicators, may also be integrated to support comprehensive risk assessment and anticipatory action planning.


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