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Internal displacement

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Internal displacement

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What you should know about this indicator

  • This chart shows the total number of internally displaced people living in a region at the end of the year.
  • A displaced person is included in this statistic if their displacement was forced/ involuntary, they have left their habitual residence and they have not crossed an international border.
  • IDMC provides rounded numbers to reflect the inherent uncertainty in displacement data. Figures equal or lower than 100,000 are rounded to two significant digits while figures above 100,000 are rounded to the nearest thousand.

How is this data described by its producer?

Internally displaced people

The total number of IDPs at a given time is referred to as a “stock” metric. It represents a static snapshot of the number of IDPs in a given location at a specific point in time.

For example, “Ten thousand people were still displaced at the end of the month” indicates how many people were displaced at a specific point in time (“at the end of the month”).

These numbers report on the total number of IDPs, or stock, at the end of a given year. Population movements such as internal displacements or births among IDP communities may increase it, while returns, cross-border flight and other outflows may decrease it.

Conflict and violence

Internal displacements triggered by conflict and violence include international armed conflict, non-international armed conflict, communal violence, crime-related violence, civilian-state violence and other forms of violence.

Disaster

Movements of people triggered by disasters are grouped into two categories: weather-related and geophysical. Weather-related displacements, for example, include hazards such as floods, droughts, landslides, storms – including cyclones and other storms –, wildfires and extreme temperatures. Geophysical displacements include, for example, earthquakes, volcanic eruptions and landslides.

Internally displaced people
are those who had to leave their homes because of violence or and have not crossed an international state border. This includes all individuals who are currently displaced, regardless of how many times they have been displaced.
Source
Internal Displacement Monitoring Centre (2026) – with minor processing by Our World in Data
Last updated
January 19, 2026
Next expected update
January 2027
Date range
2019–2024
Unit
people

Sources and processing

This data is based on the following sources

Internal Displacement Monitoring Centre – Global Internal Displacement Database (GIDD)

The GIDD is an annual dataset that provides validated and peer-reviewed estimates of internal displacement resulting from conflict and disasters. Conflict-related displacement figures are reported at the national level by calendar year, while disaster-related displacement is recorded at the event level. Since 2023, the dataset includes additional disaggregation by location, displacement cause, and event.

The GIDD captures both population flows (new displacements during the year) and stocks (total number of people living in displacement at the end of the year), covering the period from 1 January to 31 December.

Additional methodological notes, caveats, and information on historical revisions are available through the Public Figure Analysis API, which complements the main dataset with detailed contextual insights. This dataset is available since 2009 for conflict and 2008 for disaster induced displacement.

Retrieved on
January 19, 2026
Retrieved from
https://www.internal-displacement.org/database/displacement-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.
Internal Displacement Monitoring Centre. Global Internal Displacement Database. IDMC (2026). Available at: https://www.internal-displacement.org/database/displacement-data/ (Accessed: 2026-01-19).

The GIDD is an annual dataset that provides validated and peer-reviewed estimates of internal displacement resulting from conflict and disasters. Conflict-related displacement figures are reported at the national level by calendar year, while disaster-related displacement is recorded at the event level. Since 2023, the dataset includes additional disaggregation by location, displacement cause, and event.

The GIDD captures both population flows (new displacements during the year) and stocks (total number of people living in displacement at the end of the year), covering the period from 1 January to 31 December.

Additional methodological notes, caveats, and information on historical revisions are available through the Public Figure Analysis API, which complements the main dataset with detailed contextual insights. This dataset is available since 2009 for conflict and 2008 for disaster induced displacement.

Retrieved on
January 19, 2026
Retrieved from
https://www.internal-displacement.org/database/displacement-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.
Internal Displacement Monitoring Centre. Global Internal Displacement Database. IDMC (2026). Available at: https://www.internal-displacement.org/database/displacement-data/ (Accessed: 2026-01-19).

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
  • This figure is the sum of the number of people displaced due to conflict and violence and the number of people displaced due to disasters.
  • IDMC uses "N/A" to denote that no displacements or IDPs were recorded for that year. In our dataset, we convert these "N/A" values to 0 to make this more transparent and the data easier to interpret.

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: Internally displaced people”. Our World in Data (2026). Data adapted from Internal Displacement Monitoring Centre. Retrieved from https://archive.ourworldindata.org/20260813-133906/grapher/internal-displacement.html [online resource] (archived on August 13, 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:

Internal Displacement Monitoring Centre (2026) – with minor processing by Our World in Data

Full citation

Internal Displacement Monitoring Centre (2026) – with minor processing by Our World in Data. “Internally displaced people” [dataset]. Internal Displacement Monitoring Centre, “Global Internal Displacement Database (GIDD)” [original data]. Retrieved August 13, 2026 from https://archive.ourworldindata.org/20260813-133906/grapher/internal-displacement.html (archived on August 13, 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.

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Includes all entities and time points

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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/internal-displacement.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/internal-displacement.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/internal-displacement.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/internal-displacement.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/internal-displacement.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

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

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