electricsheepafrica/africa-sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024

--- annotations_creators: - no-annotation language_creators: - found language: - en license: cc-by-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - tabular-classification task_ids: [] tags: - africa - humanitarian - hdx - electric-sheep-africa - affected-population - conflict-violence - disability - displacement - elderly - gender-and-age-disaggregated-data-gadd - gender-based-violence-gbv - internally-displaced-persons-idp - moz pretty_name: "Mozambique: Survey for Inclusive Rapid Assessment (SIRA)" dataset_info: splits: - name: train num_examples: 18408 - name: test num_examples: 4602 --- # Mozambique: Survey for Inclusive Rapid Assessment (SIRA) **Publisher:** Light for the World · **Source:** [HDX](https://data.humdata.org/dataset/sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024) · **License:** `cc-by` · **Updated:** 2025-07-22 --- ## Abstract # SIRA Dataset for disability and older age - Cabo Delgado, Mozambique ## Background The Survey for Inclusive Rapid Assessment (SIRA) Dataset for disability and older age was collected in May 2024 in Pemba (urban) and Metuge (rural) localities of Cabo Delgado, Mozambique, as part of the Data that Matters project funded by Elrha. Stratified clustered random sampling was used in this survey, the aim of which is to assess the barriers and enablers people face in accessing humanitarian assistance, in particular persons with disabilities and older persons. ## The Data The dataset consists of: * SIRA Dataset #1. Household-level data: locality, household size, displacement status, registration * SIRA Dataset #2. Individual-level data: sex, age, education, health, employment * SIRA Dataset #3. Individual-level data: Washington Group (WG) questions taken from short (WG_SS), extended (WG-ES) of questions and child functioning modules (0-4 and 5-17 years). Questions include functioning domains associated with mental health. * SIRA Dataset #4. Individual-level data: barriers in accessing humanitarian assistance for i) distributions, ii) services, iii) livelihood opportunities, iv) sexual, maternal and reproductive health, v) safety and security. The datasets can be merged via the respondent identifier "indID", with "hhID" allowing to group individuals linked to a common household. Each row in this dataset represents household-level survey responses. Data was last updated on HDX on 2025-07-22. Geographic scope: **MOZ**. *Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).* --- ## Dataset Characteristics | | | |---|---| | **Domain** | Public health | | **Unit of observation** | Household-level survey responses | | **Rows (total)** | 23,011 | | **Columns** | 9 (0 numeric, 9 categorical, 0 datetime) | | **Train split** | 18,408 rows | | **Test split** | 4,602 rows | | **Geographic scope** | MOZ | | **Publisher** | Light for the World | | **HDX last updated** | 2025-07-22 | --- ## Variables **Geographic** — `respsex` (2. Female, 1. Male), `barrierwhy` (2. Fear of attack, harrassement, aggression, 16. I don't face any of these barriers, 1. I do not know where the service or support is available or who can help). **Demographic** — `hhid` (cyojyxolvhxlq6hb, c83s42tlvumb61w3, chi8xz2lvm8328ea), `respage` (16 to 50, 51 and above, 0 to 15). **Identifier / Metadata** — `indid` (cjfmoimlvz25w5u9, cpjg383lvw0sz7ka, cr2t7iylvxkz4t24), `esa_source` (HDX), `esa_processed` (2026-04-18). **Other** — `barrierwhich` (SRH, Services, Fear), `barrierwhere` (1. Food, 2. Family planning, 1. Water). --- ## Quick Start ```python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() ``` --- ## Schema | Column | Type | Null % | Range / Sample Values | |---|---|---|---| | `hhid` | object | 0.0% | cyojyxolvhxlq6hb, c83s42tlvumb61w3, chi8xz2lvm8328ea | | `indid` | object | 0.0% | cjfmoimlvz25w5u9, cpjg383lvw0sz7ka, cr2t7iylvxkz4t24 | | `respsex` | object | 0.0% | 2. Female, 1. Male | | `respage` | object | 0.0% | 16 to 50, 51 and above, 0 to 15 | | `barrierwhich` | object | 0.0% | SRH, Services, Fear | | `barrierwhere` | object | 0.0% | 1. Food, 2. Family planning, 1. Water | | `barrierwhy` | object | 0.0% | 2. Fear of attack, harrassement, aggression, 16. I don't face any of these barriers, 1. I do not know where the service or support is available or who can help | | `esa_source` | object | 0.0% | HDX | | `esa_processed` | object | 0.0% | 2026-04-18 | --- ## Numeric Summary | Column | Min | Max | Mean | Median | |---|---|---|---|---| _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 Light for the World 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](https://data.humdata.org/dataset/sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024) for the publisher's own methodology notes and caveats. --- ## Citation ```bibtex @dataset{hdx_africa_sira_disability_and_older_age_dataset_metuge_and_pemba_cabo_delgado_mozambique_may_2024, title = {Mozambique: Survey for Inclusive Rapid Assessment (SIRA)}, author = {Light for the World}, year = {2025}, url = {https://data.humdata.org/dataset/sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024}, 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.*annotations_creators: - 无标注 language_creators: - 公开获取 language: - 英语 license: 知识共享署名4.0（CC BY 4.0） multilinguality: - 单语言 size_categories: - 10000 < 样本数 < 100000 source_datasets: - 原始数据集 task_categories: - 表格分类 task_ids: [] tags: - 非洲 - 人道主义 - 人道主义数据交换平台（HDX） - 非洲电羊（Electric Sheep Africa） - 受影响人口 - 冲突暴力 - 残疾 - 流离失所 - 老年群体 - 按性别与年龄细分数据（Gender-and-Age-Disaggregated Data, GADD） - 基于性别的暴力（Gender-Based Violence, GBV） - 境内流离失所者（Internally Displaced Persons, IDP） - 莫桑比克（MOZ） pretty_name: "莫桑比克：包容性快速评估调查（SIRA）" dataset_info: splits: - name: 训练集 num_examples: 18408 - name: 测试集 num_examples: 4602 # 莫桑比克：包容性快速评估调查（SIRA） **发布方：** 世界光明组织（Light for the World） · **数据源：** [人道主义数据交换平台（Humanitarian Data Exchange，HDX）](https://data.humdata.org/dataset/sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024) · **授权协议：** `cc-by` · **更新时间：** 2025-07-22 --- ## 摘要 # 莫桑比克德尔加杜角省残疾与老年群体SIRA数据集 ## 背景 本面向残疾与老年群体的包容性快速评估调查（SIRA）数据集采集于2024年5月，采集地点为莫桑比克德尔加杜角省的彭巴（城市）与梅图热（农村）地区，作为由Elrha资助的"重要数据"项目的一部分。本次调查采用分层整群随机抽样方法，旨在评估人们在获取人道主义援助过程中面临的障碍与促进因素，特别是残疾人群体与老年群体。 ## 数据集内容 本数据集包含以下4个子集： * SIRA数据集#1：家庭层面数据，包含所在地区、家庭规模、流离失所状态、登记情况 * SIRA数据集#2：个体层面数据，包含性别、年龄、受教育程度、健康状况、就业情况 * SIRA数据集#3：个体层面数据，包含取自简短版（WG_SS）、扩展版（WG-ES）的华盛顿小组（Washington Group, WG）问题，以及儿童功能模块（0-4岁与5-17岁）。所涉问题涵盖与心理健康相关的功能领域。 * SIRA数据集#4：个体层面数据，包含获取人道主义援助时面临的障碍，具体分为：i) 物资分发、ii) 服务获取、iii) 生计机会、iv) 性健康、孕产妇健康与生殖健康、v) 安全保障。 所有数据集可通过受访者标识符"indID"进行合并，同时可通过"hhID"将隶属于同一家庭的个体进行分组。 本数据集的每一行均代表家庭层面的调查回复。该数据最近一次在人道主义数据交换平台（HDX）上的更新时间为2025-07-22。地理覆盖范围：**莫桑比克（MOZ）**。 *本数据集已由[非洲电羊（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica)整理为适合机器学习使用的Parquet格式。* --- ## 数据集特征 | | | |---|---| | **领域** | 公共卫生 | | **观测单元** | 家庭层面的调查回复 | | **总行数** | 23011 | | **列数** | 9（0个数值型、9个分类型、0个日期时间型） | | **训练集划分** | 18408行 | | **测试集划分** | 4602行 | | **地理覆盖范围** | 莫桑比克（MOZ） | | **发布方** | 世界光明组织（Light for the World） | | **HDX最后更新时间** | 2025-07-22 | --- ## 变量分类 **地理相关** — `respsex`（取值：2. 女性，1. 男性）、`barrierwhy`（取值：2. 遭遇袭击、骚扰或攻击的恐惧，16. 未面临任何障碍，1. 不知道服务或支持的获取渠道或协助对象）。 **人口统计相关** — `hhid`（示例值：cyojyxolvhxlq6hb、c83s42tlvumb61w3、chi8xz2lvm8328ea）、`respage`（取值：16至50岁、51岁及以上、0至15岁）。 **标识符/元数据** — `indid`（示例值：cjfmoimlvz25w5u9、cpjg383lvw0sz7ka、cr2t7iylvxkz4t24）、`esa_source`（HDX）、`esa_processed`（2026-04-18）。 **其他** — `barrierwhich`（取值：SRH、Services、Fear）、`barrierwhere`（取值：1. 食品、2. 计划生育、1. 饮用水）。 --- ## 快速上手 python from datasets import load_dataset ds = load_dataset("electricsheepafrica/africa-sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024") train = ds["train"].to_pandas() test = ds["test"].to_pandas() print(train.shape) train.head() --- ## 数据 Schema | 列名 | 数据类型 | 空值占比 | 取值范围/示例值 | |---|---|---| | `hhid` | 字符串型 | 0.0% | cyojyxolvhxlq6hb、c83s42tlvumb61w3、chi8xz2lvm8328ea | | `indid` | 字符串型 | 0.0% | cjfmoimlvz25w5u9、cpjg383lvw0sz7ka、cr2t7iylvxkz4t24 | | `respsex` | 字符串型 | 0.0% | 2. 女性，1. 男性 | | `respage` | 字符串型 | 0.0% | 16至50岁、51岁及以上、0至15岁 | | `barrierwhich` | 字符串型 | 0.0% | SRH、Services、Fear | | `barrierwhere` | 字符串型 | 0.0% | 1. 食品、2. 计划生育、1. 饮用水 | | `barrierwhy` | 字符串型 | 0.0% | 2. 遭遇袭击、骚扰或攻击的恐惧，16. 未面临任何障碍，1. 不知道服务或支持的获取渠道或协助对象 | | `esa_source` | 字符串型 | 0.0% | HDX | | `esa_processed` | 字符串型 | 0.0% | 2026-04-18 | --- ## 数值型统计 | 列名 | 最小值 | 最大值 | 均值 | 中位数 | |---|---|---|---| _无数值型列。_ --- ## 数据整理流程 原始数据通过CKAN API从HDX下载并转换为Parquet格式。对列名进行了小写转换，并统一调整为蛇形命名法（snake_case）。将常见的缺失值标记（`N/A`、`null`、`none`、`-`、`unknown`、`no data`、`#N/A`）统一替换为`NaN`。本数据集以固定随机种子（42）按照80/20的比例划分为训练集与测试集，并保存为Snappy压缩格式的Parquet文件。 --- ## 局限性说明 - 本数据源自世界光明组织，尚未由非洲电羊（Electric Sheep Africa）进行独立验证。 - 自动化清洗无法修正原始数据收集中的错报值、定义不一致或抽样偏差问题。 - 请查阅[原始HDX数据集页面](https://data.humdata.org/dataset/sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024)以获取发布方提供的方法论说明与注意事项。 --- ## 引用格式 bibtex @dataset{hdx_africa_sira_disability_and_older_age_dataset_metuge_and_pemba_cabo_delgado_mozambique_may_2024, title = {莫桑比克：包容性快速评估调查（SIRA）}, author = {世界光明组织（Light for the World）}, year = {2025}, url = {https://data.humdata.org/dataset/sira-disability-and-older-age-dataset-metuge-and-pemba-cabo-delgado-mozambique-may-2024}, note = {由非洲电羊（Electric Sheep Africa）重新打包以适配机器学习使用（https://huggingface.co/electricsheepafrica）} } --- *[非洲电羊（Electric Sheep Africa）](https://huggingface.co/electricsheepafrica) — 非洲机器学习数据集基础设施。尼日利亚拉各斯。*