electricsheepasia/asia-humanitarian-needs-2022-multi-sectoral-needs-assessment-occ

occupied Palestinian territory (oPt) - 2022 Multi-Sectoral Needs Assessment

Publisher: REACH Initiative · Source: HDX · License: cc-by-igo · Updated: 2024-06-07

Abstract

The 2022 Multi-Sector Needs Assessment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA), aims to identify and assess multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entirety of the Occupied Palestinian Territories (oPt). The assessment is designed to directly inform joint humanitarian-development planning across the oPt through the provision of comprehensive, multi-sectoral data and inter-sectoral analysis. In particular, the MSNA serves as a critical information resource for Humanitarian Program Cycle (HPC) activities, principally the development of the Humanitarian Needs Overview (HNO) and the Humanitarian Response Plan.

All data collection activities for the MSNA were conducted by the Palestinian Central Bureau for Statistics (PCBS) and took place from May 30 to July 6. A total of 8,331 households were assessed, of which 4,152 were in the Gaza Strip and 4,179 in the West Bank, including 244 in East Jerusalem.

Analysis findings at the strata level, meaning the localities of the Gaza Strip, the governorates of the West Bank according to “Oslo Area”, East Jerusalem, and H2, are statistically representative with a 95% level of confidence and a +/- 9% margin of error. Findings at the governorate level, for both the West Bank and Gaza, are representative at a higher degree of accuracy.

Each row in this dataset represents tabular records. Data was last updated on HDX on 2024-06-07. Geographic scope: PSE.

Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).

Dataset Characteristics

Variables

Geographic — reach_opt_2022_msna_preliminary_analysis (Items, Project Background, Time Period for Data Collection).

Identifier / Metadata — unnamed_1 (Description, The Occupied Palestinian Territories (oPt) currently faces complex, multi-faceted challenges, which are predicated on decades of political and humanitarian crises. Palestinians in the West Bank and Gaza are experiencing the compounding effects of a diminishing economy, limited access to employment, and an overall decline in socioeconomic development opportunities. The COVID-19 pandemic and the May-2021 hostilities have caused further economic contraction and exacerbated ongoing humanitarian needs, whilst inhibiting opportunities for growth in the long term. The 2022 Multi-Sector Needs Assesment (MSNA), conducted by the REACH Initiative in close collaboration with the United Nations Office for the Coordination of Humanitarian Affairs (OCHA), aims to understand the multi-sectoral and sector-specific needs, circumstances, and vulnerabilities of households across the entirety of the oPt. Whilst recent assessments conducted in the oPt have fed into informing the sector, a gap remains with respect to granular multi-sectoral data highlighting linkages in sectoral needs and enabling an inter-sectoral analysis that reveals underlying vulnerability drivers. The current assessment is designed to support humanitarian actors in their development of the 2023 Humanitarian Needs Overview (HNO) and Humanitarian Response Plan (HRP), in addition to supporting humanitarian, development, and peace actors in their development and implementation of a nexus approach for the oPt., Household data collection took place from May 30 to July 06, 2022. A total of 8,331 households were assessed, including female-headed households and refugee households living in and out of United Nations Relief and Works Agency (UNRWA) refugee camps (official and unofficial)), esa_source (HDX), esa_processed (2026-05-06).

Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-humanitarian-needs-2022-multi-sectoral-needs-assessment-occ")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

Numeric Summary

No numeric columns.

Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

Limitations

• —Data originates from REACH Initiative and has not been independently validated by ESA.
• —Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

@dataset{hdx_asia_humanitarian_needs_2022_multi_sectoral_needs_assessment_occ,
  title     = {occupied Palestinian territory (oPt) - 2022 Multi-Sectoral Needs Assessment},
  author    = {REACH Initiative},
  year      = {2024},
  url       = {https://data.humdata.org/dataset/2022-multi-sectoral-needs-assessment-occupied-palestinian-territory-opt},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.