Our World
in Data
Oxford Martin School logoUniversity of Oxford logoGlobal Change Data Lab logo
Data

Forms of homelessness included in available statistics

See all data and research on:
HomelessnessPoverty

What you should know about this indicator

  • The IGH Global Framework captures three broad categories of people who may be considered homeless, defined as "lacking access to minimally adequate housing". These categories are (1) People without accommodation, (2) People living in temporary or crisis accommodation, and (3) People living in severely inadequate or insecure accommodation.
  • Among the first category, people without accommodation, the IGH Framework distinguishes (1A) People sleeping in the streets or in other open spaces, (1B) People sleeping in public roofed spaces or buildings not intended for human habitation, (1C) People sleeping in their cars, rickshaws, open fishing boats and other forms of transport, and (1D) "Pavement dwellers" - individuals or households who live on the street in a regular spot, usually with some form of makeshift cover.
  • Among the second category, people living in temporary or crisis accommodation, the IGH Framework distinguishes (2A) People staying in night shelters, (2B) People living in homeless hostels and other types of temporary accommodation, (2C) Women and children living in refuges for those fleeing domestic violence, (2D) People living in camps provided for "internally displaced people", and (2E) People living in camps or reception centres/temporary accommodation for asylum seekers, refugees and other immigrants.
  • Among the third category, people living in severely inadequate or insecure accommodation, the IGH Framework distinguishes (3A) People sharing with friends and relatives on a temporary basis, (3B) People living under threat of violence, (3C) People living in cheap hotels, bed and breakfasts and similar, (3D) People squatting in conventional housing, (3E) People living in conventional housing that is unfit for human habitation, (3F) People living in trailers, caravans and tents, (3G) People living in extremely overcrowded conditions, and (3H) People living in non-conventional buildings and temporary structures, including those living in slums/informal settlements.
  • Within the framework, IGH targets programs and research primarily toward those in Category 1 and in a subset of Category 2 (2A-2C).
  • We only consider the data from the source that is at most five years old.
Forms of homelessness included in available statistics
The category of the IGH Framework that the homelessness data falls under.
Source
Institute of Global Homelessness (2024) – with major processing by Our World in Data
Last updated
July 5, 2024
Next expected update
May 2026
Date range
2001–2024

Related research and writing

A dark blue background with a lighter blue world map superimposed over it. Yellow text that says Homelessness by Our World in Data

Homelessness

Bastian Herre and Pablo Arriagada

Sources and processing

This data is based on the following sources

Institute of Global Homelessness – Homelessness - Better Data Project

Mapping and measuring homelessness as a global phenomenon has never been done, due in part to differing definitions of homelessness and varying methods for data collection which render side-by-side comparisons impossible. In order to showcase the difference between definitions and methodologies and to spotlight gaps in the data, the Ruff Institute of Global Homelessness's Better Data Project reviewed publicly available information from government sources, nongovernmental organizations, intergovernmental organizations, and news media reports. We found that the data varied widely from country to country, with vast differences in the quality, transparency, accuracy, and reliability of the enumeration.

We have called this experiment the Better Data Project, as we recognize that much of global homelessness data is outdated, not collected best practices, and not comparable across countries. Without standardized definitions and consistent methodologies, current measures of homelessness are incomplete, and policy-makers lack adequate and timely information about the scale of the problem. The goal of the data visualization is to demonstrate the gaps and issues of the data and where and how countries can align on definition and methodologies, improving over time.

Only then will we be able to accurately track the effectiveness of strategies that address homelessness and answer the question, “how many people are experiencing homelessness globally?”

Retrieved on
July 5, 2024
Retrieved from
https://ighomelessness.org/global-homeless-data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Institute of Global Homelessness (2024). Better Data Project Homeless Data

Mapping and measuring homelessness as a global phenomenon has never been done, due in part to differing definitions of homelessness and varying methods for data collection which render side-by-side comparisons impossible. In order to showcase the difference between definitions and methodologies and to spotlight gaps in the data, the Ruff Institute of Global Homelessness's Better Data Project reviewed publicly available information from government sources, nongovernmental organizations, intergovernmental organizations, and news media reports. We found that the data varied widely from country to country, with vast differences in the quality, transparency, accuracy, and reliability of the enumeration.

We have called this experiment the Better Data Project, as we recognize that much of global homelessness data is outdated, not collected best practices, and not comparable across countries. Without standardized definitions and consistent methodologies, current measures of homelessness are incomplete, and policy-makers lack adequate and timely information about the scale of the problem. The goal of the data visualization is to demonstrate the gaps and issues of the data and where and how countries can align on definition and methodologies, improving over time.

Only then will we be able to accurately track the effectiveness of strategies that address homelessness and answer the question, “how many people are experiencing homelessness globally?”

Retrieved on
July 5, 2024
Retrieved from
https://ighomelessness.org/global-homeless-data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Institute of Global Homelessness (2024). Better Data Project Homeless Data

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

We have simplified the original version of the IGH Framework Category in order to make the metric more clear in a chart. Regardless of the subcategories, we classify the homelessness data into these categories:

  • "No accommodation" refers to mentions to the category 1 of the IGH Framework.
  • "Temporary and crisis accommodation" refers to mentions to the category 2 of the IGH Framework.
  • "Severely inadequate accommodation" refers to mentions to the category 3 of the IGH Framework.
  • "None or temporary" refers to mentions to the categories 1 and 2 of the IGH Framework.
  • "None or inadequate" refers to mentions to the categories 1 and 3 of the IGH Framework.
  • "Temporary or inadequate" refers to mentions to the categories 2 and 3 of the IGH Framework.
  • "None, temporary or inadequate" refers to mentions to the categories 1, 2 and 3 of the IGH Framework.
  • "Not enough information" refers to the cases where the definition does not align or provide enough detail for IGH Framework classification.

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Forms of homelessness included in available statistics”, part of the following publication: Bastian Herre and Pablo Arriagada (2024) - “Homelessness”. Data adapted from Institute of Global Homelessness. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/forms-of-homelessness-included-in-available-statistics.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Institute of Global Homelessness (2024) – with major processing by Our World in Data

Full citation

Institute of Global Homelessness (2024) – with major processing by Our World in Data. “Forms of homelessness included in available statistics” [dataset]. Institute of Global Homelessness, “Homelessness - Better Data Project” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/forms-of-homelessness-included-in-available-statistics.html (archived on March 4, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Download full data

Includes all entities and time points

Download displayed data

Includes only the entities and time points currently visible in the chart

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/forms-of-homelessness-included-in-available-statistics.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear