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

Refugees by country of origin per 100,000 people

See all data and research on:
MigrationWar & Peace

What you should know about this indicator

A refugee is a person in need of international protection, who had to flee their home country because of serious threats against which the authorities of their home country cannot or will not protect them.

How is this data described by its producer?

Refugees include individuals recognized under the 1951 Convention relating to the Status of Refugees, its 1967 Protocol, the 1969 Organization of African Unity (OAU) Convention Governing the Specific Aspects of Refugee Problems in Africa, the refugee definition contained in the 1984 Cartagena Declaration on Refugees as incorporated into national laws, those recognized in accordance with the UNHCR Statute, individuals granted complementary forms of protection, and those enjoying temporary protection.

The refugee population also includes people in refugee-like situations.

Refugees by country of origin per 100,000 people
who fled their country of origin and are in need of international protection. This data is given per 100,000 people in their country of origin and shows how many people fled a country as a proportion of its current population.
Source
UNHCR (2025); Population based on various sources (2024) – with major processing by Our World in Data
Last updated
July 3, 2025
Next expected update
July 2026
Date range
1960–2024
Unit
people per 100,000 inhabitants

Related research and writing

Sustainable development goal 10: Reduced Inequalities

Reduce inequality within and among countries

Our World in Data team

Sources and processing

This data is based on the following sources

UNHCR – Refugee Population Statistics Database

The database contains information about forcibly displaced populations spanning more than 70 years of statistical activities. It covers displaced populations such as refugees, asylum-seekers and internally displaced people, including their demographics. Stateless people are also included, most of who have never been displaced. The database also reflects the different types of solutions for displaced populations such as repatriation or resettlement.

It includes UNHCR data collected through its annual statistical activities with some data going back as far as 1951, the year UNHCR was created.

Retrieved on
July 3, 2025
Retrieved from
https://www.unhcr.org/refugee-statistics/download/?v2url=e7088f
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.
Refugee Population Statistics Database, UNHCR, 2024 (https://www.unhcr.org/refugee-statistics/)

The database contains information about forcibly displaced populations spanning more than 70 years of statistical activities. It covers displaced populations such as refugees, asylum-seekers and internally displaced people, including their demographics. Stateless people are also included, most of who have never been displaced. The database also reflects the different types of solutions for displaced populations such as repatriation or resettlement.

It includes UNHCR data collected through its annual statistical activities with some data going back as far as 1951, the year UNHCR was created.

Retrieved on
July 3, 2025
Retrieved from
https://www.unhcr.org/refugee-statistics/download/?v2url=e7088f
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.
Refugee Population Statistics Database, UNHCR, 2024 (https://www.unhcr.org/refugee-statistics/)

Various sources – Population

Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.

You can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources

Retrieved on
July 11, 2024
Retrieved from
https://ourworldindata.org/population-sources
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.
The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources

Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.

You can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources

Retrieved on
July 11, 2024
Retrieved from
https://ourworldindata.org/population-sources
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.
The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources

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
  • The United Nations High Commissioner for Refugees (UNHCR) collects data on refugee populations for each country of origin and country of asylum separately. To calculate the total number of refugees living in a country, we sum up the data from all origin countries. To calculate the total number of refugees from a country, we sum up the data from all asylum countries.
  • To calculate the number of refugees per 1,000 or 100,000 people in a country, we divide the number of refugees by the total population of the country (for the same year) and multiply by the factor. The population estimates come from a long-run dataset maintained by Our World in Data.
  • We remove refugee populations where the country of origin and country of asylum are the same, as refugees are defined as people who have fled their country and crossed an international border. We also remove asylum seekers where the country of origin and country of asylum are the same.
  • We remove data for China after 2020 due to a large data discontinuity.

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: Refugees by country of origin per 100,000 people”, part of the following publication: Fiona Spooner, Tuna Acisu, Simon van Teutem, Hannah Ritchie, Esteban Ortiz-Ospina, Marcel Gerber, and Max Roser (2022) - “Migration”. Data adapted from UNHCR, Various sources. Retrieved from https://archive.ourworldindata.org/20260316-170751/grapher/number-of-refugees-per-100000.html [online resource] (archived on March 16, 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:

UNHCR (2025); Population based on various sources (2024) – with major processing by Our World in Data

Full citation

UNHCR (2025); Population based on various sources (2024) – with major processing by Our World in Data. “Refugees by country of origin per 100,000 people” [dataset]. UNHCR, “Refugee Population Statistics Database Annual statistics for 2024”; Various sources, “Population” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260316-170751/grapher/number-of-refugees-per-100000.html (archived on March 16, 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/number-of-refugees-per-100000.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/number-of-refugees-per-100000.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/number-of-refugees-per-100000.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/number-of-refugees-per-100000.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/number-of-refugees-per-100000.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/number-of-refugees-per-100000.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/number-of-refugees-per-100000.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/number-of-refugees-per-100000.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear