How Community-Level Data Can Transform DRR

Holistic Disaster Risk Reduction

As natural disasters rise with climate change, stakeholders from the regional to local levels are racing to prepare their neighborhoods. The data these stakeholders rely on for decision-making is often limited to administrative-level aggregates or environmental data on historical shocks, lacking the nuance and resolution needed to effectively design solutions that are tailored to individual communities’ challenges.

The Solution 

Using the International Panel on Climate Change (IPCC) framework, Fraym produces a three-part approach to climate vulnerability to inform local-level disaster risk reduction (DRR) strategies:

1. Exposure: reflects the strength and frequency of extreme weather, pulling on remotely sensed and household survey data to see what climate shocks communities have experienced in the past.
2. Sensitivity: represents factors that could spark or worsen the impact of a climate shock. Fraym weaves multiple indicators, including socioeconomic vulnerability, food and water security, and community structure.
3. Adaptive capacity: includes social, human, financial, and physical capital indicators. Fraym data models a range of variables that drive this measure, such as gender equality, financial access, and borrowing measures, distance to key infrastructure, presence of community support organizations, and others

Implementing Data for DRR

With a neighborhood-level understanding of risk, Fraym transforms administrative-level statistics into a nuanced portrait of communities’ resources, needs, and potential. We quantify and visualize who is at risk and where to advocate for DRR political leadership, policies, and legislation.

Fraym’s policy simulations take these baselines further by modeling the impact of specific government action. By combining detailed programmatic steps with Fraym’s population data, we can estimate policy outcomes on multiple dimensions including efficacy and public receptivity.

Zooming in on your area of interest, we can quickly identify places to target for intervention across various DRR approaches:

• Areas where sensitivity is driving vulnerability require support to bolster the most vulnerable; opportunities to address poverty and food insecurity in the short term are essential in these neighborhoods.

• In the long term, low adaptive capacity signals opportunities to invest in measures to improve gender equality, physical infrastructure, and community support systems. Pairing Fraym data on gender norms, household concerns, and media channels can transform these priorities into action.

DRR requires localized, cross-cutting data on the populations that stakeholders are trying to reach. Climate shocks exacerbate long-standing, complex challenges specific to individual communities. Visualizing these vulnerabilities with new data reveals localized nuance that’s actionable, reliable, and targeted.