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Workflow

Explore map data

Scan the municipality map built from the data currently loaded in NGO Finder.

Workflow

Compare municipalities

Line up places side by side to compare the service records currently mapped in NGO Finder.

Workflow

Download data

Export our current municipality dataset as CSV for analysis and reporting.

Workflow

Read methods

Review the assumptions, matching logic, and data limits behind the current model.

Workflow

Ask a question

Search the research knowledge base by methods, legal process, support, and source.

Workflow

Browse glossary

Look up GBV and research terms with definitions and source references.

Research paths

Move between national context, evidence, our municipal data, and place pages

Use these pages together: start with the national baseline, move into the knowledge base, then inspect ranked municipalities and open local profiles.

National GBV baseline

Read the national context layer that explains how the research should be interpreted.

Research knowledge base

Browse source-linked answers on methods, pathways, legal process, and interpretation.

Our municipal data

Filter the municipality data currently loaded in NGO Finder before opening detail pages.

Municipality directory

Browse all municipality research profiles directly when you already know the places you want to inspect.

Shared map view

Open the choropleth built from the data we currently have

The interactive municipality map now lives on its own page so this overview can stay lighter and easier to browse. It reflects the municipality-level service data currently loaded into NGO Finder, not a complete picture of every service on the ground.

Open Our Map Data

Top 20 municipalities in our current dataset by population

Compare the largest municipalities in the NGO Finder dataset and see how many NGOs, police stations, and hospitals or clinics are currently mapped per 10,000 people.

Top 20 municipalities in our current data

Rank
1 City of Johannesburg

Gauteng

 4803262 0.74 356 total services 0.29 140 total 0.20 96 total 0.25 120 total
2 City of Cape Town

Western Cape

 4772846 0.96 457 total services 0.40 190 total 0.34 164 total 0.22 103 total
3 eThekwini

KwaZulu-Natal

 4239901 0.35 150 total services 0.13 54 total 0.09 38 total 0.14 58 total
4 Ekurhuleni

Gauteng

 4066691 0.20 80 total services 0.09 35 total 0.08 31 total 0.03 14 total
5 City of Tshwane

Gauteng

 4040315 0.42 171 total services 0.18 73 total 0.12 50 total 0.12 48 total
6 Nelson Mandela Bay

Eastern Cape

 1190496 0.87 104 total services 0.25 30 total 0.23 27 total 0.39 47 total
7 Buffalo City

Eastern Cape

 975255 0.98 96 total services 0.23 22 total 0.33 32 total 0.43 42 total
8 Emfuleni

Gauteng

 945650 0.29 27 total services 0.23 22 total 0.02 2 total 0.03 3 total
9 Polokwane

Limpopo

 843459 0.83 70 total services 0.20 17 total 0.14 12 total 0.49 41 total
10 City of Mbombela

Mpumalanga

 818925 0.76 62 total services 0.21 17 total 0.10 8 total 0.45 37 total
11 The Msunduzi

KwaZulu-Natal

 817725 1.00 82 total services 0.31 25 total 0.20 16 total 0.50 41 total
12 Mangaung

Free State

 811431 1.27 103 total services 0.30 24 total 0.37 30 total 0.60 49 total
13 Bushbuckridge

Mpumalanga

 750821 0.09 7 total services 0.01 1 total 0.03 2 total 0.05 4 total
14 Nkomazi

Mpumalanga

 591928 0.14 8 total services 0.02 1 total 0.03 2 total 0.08 5 total
15 Fetakgomo Tubatse

Limpopo

 575960 0.10 6 total services 0.00 0 total 0.02 1 total 0.09 5 total
16 Thulamela

Limpopo

 575929 0.17 10 total services 0.10 6 total 0.02 1 total 0.05 3 total
17 Rustenburg

North West

 562315 1.00 56 total services 0.16 9 total 0.18 10 total 0.66 37 total
18 Local Municipality of Madibeng

North West

 522566 0.23 12 total services 0.06 3 total 0.11 6 total 0.06 3 total
19 Newcastle

KwaZulu-Natal

 507710 0.08 4 total services 0.06 3 total 0.00 0 total 0.02 1 total
20 Makhado

Limpopo

 502452 0.30 15 total services 0.10 5 total 0.14 7 total 0.06 3 total
See more filters in our municipal data

Ways to explore it

Explore our data, analysis, and context

Use the map, our municipal data, and methodology together: the map helps spot patterns, the data view helps compare municipalities, and the detail pages make it easier to inspect the underlying local picture.

Map Of Our Current Data

Open the dedicated choropleth map built from the municipality service data we currently have.

Open map →

Our Municipal Data

Compare the municipality data currently loaded in NGO Finder using service counts and services per 10,000 people.

Open rankings →

Research Methodology

Review the data sources, caveats, assumptions, and limits behind the current analysis.

Read methodology →

Compare Municipalities

Build a side-by-side municipality set for service counts, per-10k metrics, mapped cities, and caveats.

Start comparison →

National GBV Baseline

Read national prevalence, help-seeking, disability, and methodology context from the HSRC study.

Open context layer →

Research Knowledge Base

Search source-linked answers by methods, service pathways, legal process, support, and interpretation.

Open knowledge base →

Methodology and Limits

How to read and reuse this shared work

This page combines municipality population data currently loaded in NGO Finder with our mapped service database. At the moment, the app is using municipality population figures stored as 2022 population data, together with municipality boundaries imported from a 2018 boundary file. Service density is shown as the number of NGOs, police stations, and hospitals or clinics per 10,000 residents so others can understand both the usefulness and the limits of the current dataset.

Methodology

  • Population is assigned at municipality level and used to calculate services per 10,000 people.
  • Service counts come from the NGO Finder database, grouped into NGOs, police stations, and hospitals or clinics.
  • Municipality matching depends on city-to-municipality mappings, so results are only as strong as those mappings.
  • The choropleth map is intended as a directional overview of the data currently loaded into NGO Finder, not a complete census of services.

Challenges and Limits

  • Coverage may be incomplete because some services may be missing from the database, newly opened, duplicated, or already closed.
  • Population changes over time, so current on-the-ground demand may differ from the population figures used here.
  • This version does not measure service quality, capacity, staffing, operating hours, accessibility, or specialization.
  • A large hospital and a small hospital are currently counted equally, which can flatten important differences in real service availability.
  • People often travel across municipal boundaries for care, but this view mostly attributes services to the municipality they are mapped into.

What Researchers Should Keep In Mind

  • Treat these results as a screening layer for hypothesis generation, not as a final measure of need or service adequacy.
  • Low service density may reflect true undersupply, but it can also reflect data gaps, boundary effects, or outdated records.
  • Comparisons are more meaningful when combined with local knowledge, field verification, deprivation indicators, transport access, and population change over time.
  • Future improvements should include service quality weighting, recency checks, closure detection, and stronger validation against external administrative datasets.

Phase 2

Next research directions

The next phase should move beyond simple counts and make the research more useful for policy work, service planning, and stronger data interpretation.

Quality and Capacity Weighting

Weight services by size, staffing, specialization, operating hours, and actual service capacity instead of counting every facility equally.

Stronger Demand Signals

Add deprivation, transport access, rurality, safety, and population change so service need can be compared against service supply.

Data Freshness and Validation

Track closures, new openings, verification dates, and external reference datasets to improve confidence in the research outputs.