CRA: COMMUNITY RISK ASSESSMENT

WHY It’s needed.

Smart use of (big) data will positively impact faster & more (Cost) effective humanitarian aid. Contributing to open data, data analysis and capacity building in governments & NGO’s are essential to increase the understanding of humanitarian data.  51o has created the Community Risk Assesment CRA Dashboard to quickly identify the geographic areas that are most affected by a humanitarian disaster or crisis and, within those areas, the people that are most in affected. The 510 Community Risk Assessment Dashboard forms a data preparedness solution to help reach those affected faster and more efficiently.

HOW:

Data Collection & Data Integration:

All relevant pre-disaster data sources on a detailed geographical level are collected and integrated, focusing on indicators inspired by the INFORM risk-framework with three main components: This Data Preparedness saves time by haveing all these sources readily available and easily accessible before an impending disaster.

1: LONG-TERM HAZARD RISK (BASED ON HISTORICAL EVENTS):

E.G. Malawi Flood & Drought Risk

2: VULNERABILITY:

E.G. Malawi Poverty

3: LACK OF COPING CAPACITY:

E.G. Malawi Remoteness Distance to Nearest hospital

 

CRA uses the Inform Framework and applies it to the various admin levels in the country.

 

Where INFORM makes risk comparable across countries, the 510 CRA Dashboard looks to prioritise smaller areas or communities, for this reason we have been adding data sets that refer to the differnt admin areas per country.

For example in Malawi the top admin unit is District (of which there are 32). In the 510 dashboard you can go down two more admin levels to TA Traditional Autorities (of which there are 367) and we are currently updateing information on the GVH Group Village Head (of which there are 9133) and is the lowest admin level of Malawi.

WHERE:

The scope of the Community Risk assesment dashboard is global. Using Open Street Map as a base with global open data sources built on top. As our project base grows we will add more countries over time.

FULL: For these countries a complete set of indicators has been collected across all risk-components, to give a reliable indication of risk per area. More and better data collection will improve the risk index further.

The Philippines

Malawi

Peru

BASIC: For these countries a first minimal set of indicators has been collected across all risk-components. The purpose is to give rough first insights of spread of risk over the country, but mainly to show stakeholders what is possible. This is only the starting point. More and better data collection is to follow.

Ecuador

Ethiopia

Kenya

Mozambique

Nepal

Uganda

Zambia

TEMPLATE: For these countries only the Administrative Boundaries and the Population are included. The infrastructure is all there to start uploading risk datasets.

Benin

Mali

Sri Lanka

Vietnam

WHEN:

The first version of the Dashboard was created in 2016 together with  The Philippine Red Cross

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