Census Administrative & Service Provision District Profiles 2022
South Africa, 2022
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zaf-statssa-casd-2022-v1
Census Administrative & Service Provision District Profiles 2022
CASD 2022
| Name | Country code |
|---|---|
| South Africa | zaf |
| Type | Identifier |
|---|---|
| DOI | https://doi.org/10.25828/wafz-wj19 |
This dataset is a national spatial data product derived from South Africa’s Census 2022 and designed to support the analysis of population and household characteristics within service delivery and administrative reporting districts created by StatsSA. Released by StatsSA as the Census 2022 Special District Layer Product, the dataset provides spatial boundary files and geographic codes for administrative and service delivery districts used for planning and reporting in South Africa. Administrative and service delivery districts are education districts, health districts, magisterial districts (and their sub-magisterial divisions), and police districts. The purpose of providing data at these levels is to enable the integration of official Census 2022 data with operational planning geographies used by public institutions, thereby improving evidence-based planning, service targeting, and interdepartmental comparisons.
The dataset includes data on demographic distribution, household composition, social conditions, and the spatial allocation of public services. The primary reasons for producing district-level data were:
- to make the Census 2022 results usable within real-world service delivery situations
- to reveal how population and household patterns differ across districts
- to enable Census data to better inform planning, policy formulation, and resource allocation and monitoring.
Census/enumeration data [cen]
Households and individuals
Version
v1.1: Edited, anonymised data for public distribution
2026-04-01
DataFirst
Scope
Because the COVID-19 pandemic affected key phases of geography frame finalisation and data collection of the census, a multi-mode data collection approach was adopted. Three methods of data collection were used in this census, namely: face to face computer assisted personal interview (CAPI); computer assisted telephone interview (CATI); and computer-assisted web interview (CAWI).
Coverage
The geographic scope of the data is national coverage
The lowest level of geographic aggregation of the data is administrative and service delivery district
South African Census 2022 covered every person present in South Africa on the Census reference night, midnight of 2-3 February 2022 including all de jure household members and residents of institutions.
| West | East | South | North |
|---|---|---|---|
| 14.062712 | 33.090851 | -35.101934 | -22.105999 |
Producers and sponsors
| Name | Affiliation |
|---|---|
| Statistics South Africa | Government of South Africa |
Study authorization
1999, 2024
| Agency name | Affiliation | Abbreviation |
|---|---|---|
| Statistics South Africa | Government of South Africa | StatsSA |
Statistics SA is authorised to collect data by the Statistics Act 1999 and the Statistics Amendment Act of 2024
Sampling
Coverage errors are a measure of how many persons or households were missed or counted more than once in the census.
The final net coverage error rate relative to the final true population of 61,4 million persons is 31,1%. The final net coverage error rate relative to the final true population of 19,3 million households is 30,5%.
Data Collection
| Start | End |
|---|---|
| 2022-02-02 | 2022-05 |
Cross-section [cross section]
| Name | Affiliation | Abbreviation | Role |
|---|---|---|---|
| Statistics South Africa | Government of South Africa | StatsSA | Data collectors and producers |
Data processing
DataFirst prepared the Census Administrative & Service Provision District Profiles 2022 tables downloaded from Stats SA’s website and standardised the file names so that each data file could be easily identified and managed. Using R, DataFirst linked each Excel table to the corresponding official district boundary shapefile and appended higher-level geographic identifiers, such as district municipality and province, to every record. As part of this step, district names were standardised to ensure consistent matching across files, unnecessary columns with total were removed, and the revised tables were written back to Excel. DataFirst then used Stata to import the cleaned tables, assign consistent and self-explanatory variable names, apply descriptive variable labels, and save the final datasets. The accompanying R script documents the geographic matching and enrichment process, while the Stata do-file documents the variable renaming and labelling process.
Data appraisal
Content errors indicate the quality of key characteristics in the census. With respect to content errors, six variables were tested for consistency in terms of the responses that were recorded in the Census and the Post-enumeration Survey (PES) 2022. The aggregated index of inconsistency was 7,5% for population group, 8,2% for sex, and 13,6% for age group, indicating a high level of agreement. The aggregated index of inconsistency for marital status was 23,0%, relationship to head of household was 34,8%, and country of birth was 42,3%, indicating moderate rates of agreement.
Access policy
DataFirst data repository
Statistics South Africa's Isibalo site
Depositor information
| Name | Abbreviation | Affiliation | URL |
|---|---|---|---|
| Statistics South Africa | StatsSA | Government of South Africa | https://www.statssa.gov.za |
2025-08-25
Distributor information
| Organization name | Affiliation | URL |
|---|---|---|
| DataFirst | University of Cape Town | https://www.datafirst.uct.ac.za |
2026
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | https://support.data1st.org | support@data1st.org |
Creative Commons CC-BY 4.0 attribution license
Statistics South Africa. Census Administrative & Service Provision District Profiles 2022 [dataset]. Version 1. Pretoria: StatsSA and DataFirst [producers], 2025. Cape Town: DataFirst [distributor], 2026. DOI: https://doi.org/10.25828/wafz-wj19
Researchers agree to cite the data in their publications using the recommended citation in this metadata record, including the DOI (unique dataset identifier)
Researchers agree to send DataFirst a link to any research publication based on the data
Contacts
| Name | URL | |
|---|---|---|
| DataFirst Support | support@data1st.org | https://www.support@data1st.org |
Metadata production
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| DataFirst | DF | University of Cape Town | Metadata producer |
2026-04-01
Metadata version
Version 1