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About this data

Homicide rates over the long term
Homicides per 100,000 people, combining historical estimates compiled by Eisner (2014) with death-certificate data from the WHO Mortality Database.
Source
Eisner (2014); WHO Mortality Database (2026) – processed by Our World in Data
Last updated
October 15, 2026
Date range
1250–2023
Unit
homicides per 100,000 people

Related research and writing

Featured image for the article on the different homicide data sources. Stylized lines that all go down.

Homicide data: how sources differ and when to use which one

Bastian Herre and Fiona Spooner

Explore charts that include this data

Sources and processing

This data is based on the following sources

Eisner – From swords to words: Does macro-level change in self-control predict long-term variation in levels of homicide?

The homicide rate data shown here is taken from Table 4 on pages 80-81 in Eisner (2014). In the table homicide rate estimates are given for a range of years, we present data for the mid-point year here. For example, if data is given for 1200-1299 we show this as 1250.

Dataset notes:

  • For 1775 and 1862 the data for Switzerland are for the canton of Zurich only.
  • From 1825 onwards the estimates for Corsica and Sardinia are for Sardinia only.
Retrieved on
January 6, 2025
Retrieved from
https://doi.org/10.1086/677662
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.
Eisner, M. (2014). From swords to words: Does macro-level change in self-control predict long-term variation in levels of homicide? In M. Tonry (Ed.), Why crime rates fall and why they don't (Vol. 43, Crime and Justice: A review of research). Chicago: University of Chicago Press.

The homicide rate data shown here is taken from Table 4 on pages 80-81 in Eisner (2014). In the table homicide rate estimates are given for a range of years, we present data for the mid-point year here. For example, if data is given for 1200-1299 we show this as 1250.

Dataset notes:

  • For 1775 and 1862 the data for Switzerland are for the canton of Zurich only.
  • From 1825 onwards the estimates for Corsica and Sardinia are for Sardinia only.
Retrieved on
January 6, 2025
Retrieved from
https://doi.org/10.1086/677662
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.
Eisner, M. (2014). From swords to words: Does macro-level change in self-control predict long-term variation in levels of homicide? In M. Tonry (Ed.), Why crime rates fall and why they don't (Vol. 43, Crime and Justice: A review of research). Chicago: University of Chicago Press.

WHO Mortality Database

The WHO mortality database is a collection death registration data including cause-of-death information from member states.

Where they are collected, death registration data are the best source of information on key health indicators, such as life expectancy, and death registration data with cause-of-death information are the best source of information on mortality by cause, such as maternal mortality and suicide mortality.

WHO requests from all countries annual data by age, sex, and complete ICD code (e.g., 4-digit code if the 10th revision of ICD was used). Countries have reported deaths by cause of death, year, sex, and age for inclusion in the WHO Mortality Database since 1950.

The WHO only includes data, which are properly coded according to the International Classification of Diseases (ICD). Today the database is maintained by the WHO Division of Data, Analytics and Delivery for Impact (DDI) and contains data from over 120 countries and areas. Data reported by member states and selected areas are displayed in this portal’s interactive visualizations if the data are reported to the WHO mortality database in the requested format and at least 65% of deaths were recorded in each country and year.

Retrieved on
October 14, 2026
Retrieved from
https://platform.who.int/mortality
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.
WHO Division of Data, Analytics and Delivery for Impact (DDI), World Health Organization (2026)

The WHO mortality database is a collection death registration data including cause-of-death information from member states.

Where they are collected, death registration data are the best source of information on key health indicators, such as life expectancy, and death registration data with cause-of-death information are the best source of information on mortality by cause, such as maternal mortality and suicide mortality.

WHO requests from all countries annual data by age, sex, and complete ICD code (e.g., 4-digit code if the 10th revision of ICD was used). Countries have reported deaths by cause of death, year, sex, and age for inclusion in the WHO Mortality Database since 1950.

The WHO only includes data, which are properly coded according to the International Classification of Diseases (ICD). Today the database is maintained by the WHO Division of Data, Analytics and Delivery for Impact (DDI) and contains data from over 120 countries and areas. Data reported by member states and selected areas are displayed in this portal’s interactive visualizations if the data are reported to the WHO mortality database in the requested format and at least 65% of deaths were recorded in each country and year.

Retrieved on
October 14, 2026
Retrieved from
https://platform.who.int/mortality
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.
WHO Division of Data, Analytics and Delivery for Impact (DDI), World Health Organization (2026)

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

All homicide rate estimates from before 1950 are taken from: Table 4 in Eisner, M. (2014) “From Swords to Words: Does Macro-Level Change in Self-Control Predict Long-Term Variation in Levels of Homicide?” In Why Crime Rates Fall and Why They Don’t, edited by Michael Tonry. Vol. 43 of Crime and Justice: A Review of Research, edited by Michael Tonry. Chicago: University of Chicago Press.

In Eisner (2014) homicide rates are given for a range of years - we allocate the homicide rate at the midpoint of the given period. Our data-management and -visualization system can currently only observations that happen in a particular year (or day), therefore we can't store the time-information as presented by the original source and instead allocate the observation the midpoint of the given period.

Historical estimates of homicide rates are derived from national vital statistics and judicial archives. The older data is often fragmented and subject to a number of biases including: geographic bias, incomplete records, changing age structure, wound treatment, and the lethality of weapons.

This variable is a combination of homicide rate estimates from Eisner (2014) and the WHO Mortality Database. For the following countries we use Eisner (2014) before the given date and the WHO Mortality Database for all later datapoints:

  • 1950: France, Ireland, Netherlands

  • 1951: Italy, Spain, Sweden, Switzerland

  • 1954: Belgium

  • 1990: Germany

For Corsica and Sardinia; England and Wales and Sweden and Finland all datapoints are from Eisner (2014).

All other datapoints not specified above are sourced from the WHO Mortality Database.

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: Homicide rates over the long term”. Our World in Data (2026). Data adapted from Eisner, WHO Mortality Database. Retrieved from https://archive.ourworldindata.org/20261015-225347/grapher/homicide-rates-across-western-europe.html [online resource] (archived on October 15, 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:

Eisner (2014); WHO Mortality Database (2026) – processed by Our World in Data

Full citation

Eisner (2014); WHO Mortality Database (2026) – processed by Our World in Data. “Homicide rates over the long term” [dataset]. Eisner, “From swords to words: Does macro-level change in self-control predict long-term variation in levels of homicide?”; WHO Mortality Database, “WHO Mortality Database” [original data]. Retrieved October 18, 2026 from https://archive.ourworldindata.org/20261015-225347/grapher/homicide-rates-across-western-europe.html (archived on October 15, 2026).

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Data URL (CSV format)
https://ourworldindata.org/grapher/homicide-rates-across-western-europe.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/homicide-rates-across-western-europe.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/homicide-rates-across-western-europe.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/homicide-rates-across-western-europe.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/homicide-rates-across-western-europe.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

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

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