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WASH Severity Classification (WSC): Overview - WSC Light Northeast Nigeria, February 2022

Países
Nigeria
Fuentes
UNICEF
+ 2
Fecha de publicación
Origen
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Summary

The WASH Severity Classification (WSC) analysis of Northeast Nigeria found the situation to be extremely severe. 45 of the 60 analysed local government areas (LGAs) are classified in Phase 4 (Critical) due to severe public health conditions, namely a cholera outbreak that has been active since mid-2021 and elevated malnutrition levels. This is likely driven by poor access to improved sanitation, water quality issues, and low levels of access to basic hygiene. The remaining 15 LGAs are classified in Phase 3 (Crisis). Water, sanitation and hygiene (WASH) conditions are being driven by the ongoing conflict and insecurity, climate change and desertification, and associated displacement.

Methodology

The WASH Severity Classification (WSC) is a new interagency global initiative led by the Global WASH Cluster, the United Nations Children’s Fund (UNICEF), and IMPACT Initiatives. Developed at the global level through a participatory process, the WSC project aims to build a standardised approach to classifying the severity of WASH needs and vulnerabilities across contexts.

The findings presented in this report are the product of a WSC Light exercise conducted in January and February 2022. Unlike standard WSC implementations, the Light approach does not include a joint analysis workshop. Instead, with the support of key WASH partners in-country, a global team of WSC analysts identified, reviewed, and processed data sources pertaining to different areas of the WSC Analytical Framework.

The analysis considered relevant data collected from various sources that were dated from within six months prior to the exercise. Data was collated from a range of sources, including government databases, UN agency and NGO assessments. The full list of data sources used is provided at the end of the document (Annex 2). In accordance with the WSC Analysis Protocols, analysts iteratively analysed this information, producing severity classification for the 60 analysed LGAs and identifying the key factors driving the situation. The findings were then reviewed and validated by WASH experts in country.