Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 10 Next »

 Field examples


Prioritize WASH needs through a WASH severity mapping

When facing a disaster, people have different level of needs based on their location and type. Some communities are more affected than others, some are more resilient than others. They also face variable risks for human life (ex: acutely malnourished children are more at risk of dying from diarrhoea than healthy adults displaced by flood). Response cannot reach all people in need, so needs must be prioritized, to know which areas and groups should be considered for response analysis and targeting. This process is called needs severity mapping. Coordination platforms first undertake sectoral severity mapping, later consolidated by OCHA in an intersectoral severity mapping. There is no standard methodology to prioritize needs, although OCHA may propose one at country level. Some common approaches are presented below:

  • Use a severity scale based on one or several WASH indicators (ex: access to water). Each administrative level are ranked from 1 to 6, from “No problem” (ex: from 90 to 100% have access) to “catastrophic problem” (ex: from 0 to 15% have access). Indicators can be weighted, considering for example that access to water is more important than access to hygiene NFI. Keep in mind that multi-indicator weighting system can quickly become very complex and lose relevancy. OCHA usually provides a standard weighting system for the response to harmonize the process.
  • Use a severity scale, including also non-WASH indicator, such as “risk to flood”, or “risk of malnutrition”, once again using an indicator weighting system.
  • Classifying administrative level from the lowest to highest WASH PIN number, or by the % of PIN as compared to the whole population.
  • Rank the needs severity of each administrative level by comparing PIN numbers with estimated risks for human life (ex: people at risk of outbreak are prioritized, as they may quickly die without intervention).
  • Information regarding local capacities (example: in that region, there is a well-equipped hospital where people affected by cholera can be treated correctly) can also be factored-in in the analysis if they are available.

When there is a large geographical area to be mapped with many administrative levels, it quickly becomes impossible to cross several indicators with a qualitative approach. In this case, analytical tools to integrate several indicators must be used. Two examples are presented below:

  • INFORM software (http://www.inform-index.org/About-us)
  • 1000Minds software: a simple and transparent method to identify vulnerable populations. Without the need to shape available data to fit pre-defined weights, the software undertakes a multi-criteria analysis on the data that is available at the time of the emergency. 1000minds software has been identified as a valuable tool to identify vulnerable populations in an easy, flexible and transparent way. In the Key Guidance and Tools section of this page can be found the “WASH Prioritization Tool”, which contains a WASH-specific step-by-step manual to use 1000Minds to calculate the needs/priorities of the affected population, as well as example datasets and results from Somalia.

A severity map can finally be designed, and used to show concentration of needs based on geographic locations. Regardless of the approach taken, the process and results of the exercise should be documented and available to other Clusters and WASH partners.

Refer to the 2015 IASC Humanitarian Needs comparison tools for more details on integrated severity mapping


  • No labels