Malta had the lowest rate of road fatalities in the European Union in 2021. That year, 1,000 more people lost their lives on roads in the European Union, up by about five percent between 2020 and 2021.

In 2022, around ** people per * million inhabitants died as a result of road accidents in Chile. New Zealand, with around seven fatalities per * million inhabitants, was second in the ranking.

This statistic displays the number of road traffic fatalities in European countries per 100,000 inhabitants in 2017. According to the data, Norway had the lowest number of road fatalities in 2017 with only 2 fatalities per 100,000 inhabitants, while Serbia had the worst road safety with 8.2 road deaths per 100,000 inhabitants in 2017.

The World Health Organization Database provides data on road traffic deaths for the years 2013 and 2016 for all countries. It shows the estimated number of road traffic deaths and the estimated road traffic death rate per 100,000 population.

The statistic represents the number of road fatalities per billion vehicle kilometers traveled in selected countries in 2015. In 2015, there were around ***** road fatalities per billion vehicle kilometers traveled in the United States.

Turkey TR: Road Fatalities: Per One Million Vehicle-km data was reported at 15.204 Ratio in 2022. This records a decrease from the previous number of 16.269 Ratio for 2021. Turkey TR: Road Fatalities: Per One Million Vehicle-km data is updated yearly, averaging 19.949 Ratio from Dec 2015 (Median) to 2022, with 8 observations. The data reached an all-time high of 29.999 Ratio in 2015 and a record low of 15.204 Ratio in 2022. Turkey TR: Road Fatalities: Per One Million Vehicle-km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Turkey – Table TR.OECD.ITF: Road Traffic and Road Accident Fatalities: OECD Member: Annual. [COVERAGE] ROAD FATALITIES A road fatality is any person killed immediately or dying within 30 days as a result of an injury accident, excluding suicides. A killed person is excluded if the competent authority declares the cause of death to be suicide, i.e. a deliberate act to injure oneself resulting in death. For countries that do not apply the threshold of 30 days, conversion coefficients are estimated so that comparison on the basis of the 30-day definition can be made. ROAD TRAFFIC Road traffic is any movement of a road vehicle on a given road network. When a road vehicle is being carried on another vehicle, only the movement of the carrying (active mode) is considered. [COVERAGE] ROAD TRAFFIC Data come from odometer readings and include all motor vehicle movements on the territory, irrespective of the country of registration.

The average for 2019 based on 12 countries was 19.05 deaths per 100,000 people. The highest value was in Venezuela: 39 deaths per 100,000 people and the lowest value was in Peru: 13.6 deaths per 100,000 people. The indicator is available from 2000 to 2019. Below is a chart for all countries where data are available.

This statistic represents the number of motor vehicle crash fatalities per 100,000 population in 2016, with a breakdown by major country. In Belgium, there were some **** fatalities per 100,000 population from road crashes.

Vietnam VN: Mortality Caused by Road Traffic Injury: per 100,000 People data was reported at 24.000 Number in 2015. This records an increase from the previous number of 23.500 Number for 2010. Vietnam VN: Mortality Caused by Road Traffic Injury: per 100,000 People data is updated yearly, averaging 23.300 Number from Dec 2000 (Median) to 2015, with 4 observations. The data reached an all-time high of 24.000 Number in 2015 and a record low of 22.200 Number in 2005. Vietnam VN: Mortality Caused by Road Traffic Injury: per 100,000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Health Statistics. Mortality caused by road traffic injury is estimated road traffic fatal injury deaths per 100,000 population.; ; World Health Organization, Global Status Report on Road Safety.; Weighted average;

Objective: Road crashes are considered as the eighth leading causes of death. There is a wide disparity in crash severity and law enforcement efficiency among low-, medium-, and high-income countries. It would be helpful to review the crash severity trends in these countries, identify the vulnerable road users, and understand the law enforcement effectiveness in devising efficient road safety improvement strategies. Method: The crash severity, fatality rate among various age groups, and law enforcement strategies of 10 countries representing low-income (i.e., India and Morocco), medium-income (i.e. Argentina, South Korea, and Greece), and high-income (i.e., Australia, Canada, France, the UK, and the United States) are studied and compared for a period of 5 years (i.e., 2008 to 2012). The critical parameters affecting road safety are identified and correlated with education, culture, and basic compliance with traffic safety laws. In the process, possible road safety improvement strategies are identified for low-income countries. Results: The number of registered vehicles shows an increasing trend for low-income countries as do the crash rate and crash severity. Compliance related to seat belt and helmet laws is high in high-income countries. In addition, recent seat belt– and helmet-related safety programs in middle-income countries helped to curb fatalities. Noncompliance with safety laws in low-income countries is attributed to education, culture, and inefficient law enforcement. Conclusion: Efficient law enforcement and effective safety education taking into account cultural diversity are the key aspects to reduce traffic-related injuries and fatalities in low-income countries like India.

This database that can be used for macro-level analysis of road accidents on interurban roads in Europe. Through the variables it contains, road accidents can be explained using variables related to economic resources invested in roads, traffic, road network, socioeconomic characteristics, legislative measures and meteorology. This repository contains the data used for the analysis carried out in the papers:

1. Calvo-Poyo F., Navarro-Moreno J., de Oña J. (2020) Road Investment and Traffic Safety: An International Study. Sustainability 12:6332. https://doi.org/10.3390/su12166332

2. Navarro-Moreno J., Calvo-Poyo F., de Oña J. (2022) Influence of road investment and maintenance expenses on injured traffic crashes in European roads. Int J Sustain Transp 1–11. https://doi.org/10.1080/15568318.2022.2082344

3. Navarro-Moreno, J., Calvo-Poyo, F., de Oña, J. (2022) Investment in roads and traffic safety: linked to economic development? A European comparison. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-022-22567

The file with the database is available in excel.

DATA SOURCES

The database presents data from 1998 up to 2016 from 20 european countries: Austria, Belgium, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Latvia, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden and United Kingdom. Crash data were obtained from the United Nations Economic Commission for Europe (UNECE) [2], which offers enough level of disaggregation between crashes occurring inside versus outside built-up areas.

With reference to the data on economic resources invested in roadways, deserving mention –given its extensive coverage—is the database of the Organisation for Economic Cooperation and Development (OECD), managed by the International Transport Forum (ITF) [1], which collects data on investment in the construction of roads and expenditure on their maintenance, following the definitions of the United Nations System of National Accounts (2008 SNA). Despite some data gaps, the time series present consistency from one country to the next. Moreover, to confirm the consistency and complete missing data, diverse additional sources, mainly the national Transport Ministries of the respective countries were consulted. All the monetary values were converted to constant prices in 2015 using the OECD price index.

To obtain the rest of the variables in the database, as well as to ensure consistency in the time series and complete missing data, the following national and international sources were consulted:

Eurostat [3]

Directorate-General for Mobility and Transport (DG MOVE). European Union [4]

The World Bank [5]

World Health Organization (WHO) [6]

European Transport Safety Council (ETSC) [7]

European Road Safety Observatory (ERSO) [8]

European Climatic Energy Mixes (ECEM) of the Copernicus Climate Change [9]

EU BestPoint-Project [10]

Ministerstvo dopravy, República Checa [11]

Bundesministerium für Verkehr und digitale Infrastruktur, Alemania [12]

Ministerie van Infrastructuur en Waterstaat, Países Bajos [13]

National Statistics Office, Malta [14]

Ministério da Economia e Transição Digital, Portugal [15]

Ministerio de Fomento, España [16]

Trafikverket, Suecia [17]

Ministère de l’environnement de l’énergie et de la mer, Francia [18]

Ministero delle Infrastrutture e dei Trasporti, Italia [19–25]

Statistisk sentralbyrå, Noruega [26-29]

Instituto Nacional de Estatística, Portugal [30]

Infraestruturas de Portugal S.A., Portugal [31–35]

Road Safety Authority (RSA), Ireland [36]

DATA BASE DESCRIPTION

The database was made trying to combine the longest possible time period with the maximum number of countries with complete dataset (some countries like Lithuania, Luxemburg, Malta and Norway were eliminated from the definitive dataset owing to a lack of data or breaks in the time series of records). Taking into account the above, the definitive database is made up of 19 variables, and contains data from 20 countries during the period between 1998 and 2016. Table 1 shows the coding of the variables, as well as their definition and unit of measure.

Table. Database metadata

Code

Variable and unit

fatal_pc_km

Fatalities per billion passenger-km

fatal_mIn

Fatalities per million inhabitants

accid_adj_pc_km

Accidents per billion passenger-km

p_km

Billions of passenger-km

croad_inv_km

Investment in roads construction per kilometer, €/km (2015 constant prices)

croad_maint_km

Expenditure on roads maintenance per kilometer €/km (2015 constant prices)

prop_motorwa

Proportion of motorways over the total road network (%)

populat

Population, in millions of inhabitants

unemploy

Unemployment rate (%)

petro_car

Consumption of gasolina and petrol derivatives (tons), per tourism

alcohol

Alcohol consumption, in liters per capita (age > 15)

mot_index

Motorization index, in cars per 1,000 inhabitants

den_populat

Population density, inhabitants/km2

cgdp

Gross Domestic Product (GDP), in € (2015 constant prices)

cgdp_cap

GDP per capita, in € (2015 constant prices)

precipit

Average depth of rain water during a year (mm)

prop_elder

Proportion of people over 65 years (%)

dps

Demerit Point System, dummy variable (0: no; 1: yes)

freight

Freight transport, in billions of ton-km

ACKNOWLEDGEMENTS

This database was carried out in the framework of the project “Inversión en carreteras y seguridad vial: un análisis internacional (INCASE)”, financed by: FEDER/Ministerio de Ciencia, Innovación y Universidades–Agencia Estatal de Investigación/Proyecto RTI2018-101770-B-I00, within Spain´s National Program of R+D+i Oriented to Societal Challenges.

Moreover, the authors would like to express their gratitude to the Ministry of Transport, Mobility and Urban Agenda of Spain (MITMA), and the Federal Ministry of Transport and Digital Infrastructure of Germany (BMVI) for providing data for this study.

REFERENCES

1. International Transport Forum OECD iLibrary | Transport infrastructure investment and maintenance.

2. United Nations Economic Commission for Europe UNECE Statistical Database Available online: https://w3.unece.org/PXWeb2015/pxweb/en/STAT/STAT_40-TRTRANS/?rxid=18ad5d0d-bd5e-476f-ab7c-40545e802eeb (accessed on Apr 28, 2020).

3. European Commission Database - Eurostat Available online: https://ec.europa.eu/eurostat/data/database (accessed on Apr 28, 2021).

4. Directorate-General for Mobility and Transport. European Commission EU Transport in figures - Statistical Pocketbooks Available online: https://ec.europa.eu/transport/facts-fundings/statistics_en (accessed on Apr 28, 2021).

5. World Bank Group World Bank Open Data | Data Available online: https://data.worldbank.org/ (accessed on Apr 30, 2021).

6. World Health Organization (WHO) WHO Global Information System on Alcohol and Health Available online: https://apps.who.int/gho/data/node.main.GISAH?lang=en (accessed on Apr 29, 2021).

7. European Transport Safety Council (ETSC) Traffic Law Enforcement across the EU - Tackling the Three Main Killers on Europe’s Roads; Brussels, Belgium, 2011;

8. Copernicus Climate Change Service Climate data for the European energy sector from 1979 to 2016 derived from ERA-Interim Available online: https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-european-energy-sector?tab=overview (accessed on Apr 29, 2021).

9. Klipp, S.; Eichel, K.; Billard, A.; Chalika, E.; Loranc, M.D.; Farrugia, B.; Jost, G.; Møller, M.; Munnelly, M.; Kallberg, V.P.; et al. European Demerit Point Systems : Overview of their main features and expert opinions. EU BestPoint-Project 2011, 1–237.

10. Ministerstvo dopravy Serie: Ročenka dopravy; Ročenka dopravy; Centrum dopravního výzkumu: Prague, Czech Republic;

11. Bundesministerium für Verkehr und digitale Infrastruktur Verkehr in Zahlen 2003/2004; Hamburg, Germany, 2004; ISBN 3871542946.

12. Bundesministerium für Verkehr und digitale Infrastruktur Verkehr in Zahlen 2018/2019. In Verkehrsdynamik; Flensburg, Germany, 2018 ISBN 9783000612947.

13. Ministerie van Infrastructuur en Waterstaat Rijksjaarverslag 2018 a Infrastructuurfonds; The Hague, Netherlands, 2019; ISBN 0921-7371.

14. Ministerie van Infrastructuur en Milieu Rijksjaarverslag 2014 a Infrastructuurfonds; The Hague, Netherlands, 2015; ISBN 0921- 7371.

15. Ministério da Economia e Transição Digital Base de Dados de Infraestruturas - GEE Available online: https://www.gee.gov.pt/pt/publicacoes/indicadores-e-estatisticas/base-de-dados-de-infraestruturas (accessed on Apr 29, 2021).

16. Ministerio de Fomento. Dirección General de Programación Económica y Presupuestos. Subdirección General de Estudios Económicos y Estadísticas Serie: Anuario estadístico; NIPO 161-13-171-0; Centro de Publicaciones. Secretaría General Técnica. Ministerio de Fomento: Madrid, Spain;

17. Trafikverket The Swedish Transport Administration Annual report: 2017; 2018; ISBN 978-91-7725-272-6.

18. Ministère de l’Équipement, du T. et de la M. Mémento de statistiques des transports 2003; Ministère de l’environnement de l’énergie et de la mer, 2005;

19. Ministero delle Infrastrutture e dei Trasporti Conto Nazionale delle

Fatality Analysis Reporting System (FARS) was created in the United States by the National Highway Traffic Safety Administration (NHTSA) to provide an overall measure of highway safety, to help suggest solutions, and to help provide an objective basis to evaluate the effectiveness of motor vehicle safety standards and highway safety programs.

FARS contains data on a census of fatal traffic crashes within the 50 States, the District of Columbia, and Puerto Rico. To be included in FARS, a crash must involve a motor vehicle traveling on a trafficway customarily open to the public and result in the death of a person (occupant of a vehicle or a non-occupant) within 30 days of the crash. FARS has been operational since 1975 and has collected information on over 989,451 motor vehicle fatalities and collects information on over 100 different coded data elements that characterizes the crash, the vehicle, and the people involved.

FARS is vital to the mission of NHTSA to reduce the number of motor vehicle crashes and deaths on our nation's highways, and subsequently, reduce the associated economic loss to society resulting from those motor vehicle crashes and fatalities. FARS data is critical to understanding the characteristics of the environment, trafficway, vehicles, and persons involved in the crash.

NHTSA has a cooperative agreement with an agency in each state government to provide information in a standard format on fatal crashes in the state. Data is collected, coded and submitted into a micro-computer data system and transmitted to Washington, D.C. Quarterly files are produced for analytical purposes to study trends and evaluate the effectiveness highway safety programs.

Content

There are 40 separate data tables. You can find the manual, which is too large to reprint in this space, here.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.nhtsa_traffic_fatalities.[TABLENAME]. Fork this kernel to get started.

Acknowledgements

This dataset was provided by the National Highway Traffic Safety Administration.

Indonesia Number of Road Accident: Killed: Bali data was reported at 521.000 Person in 2017. This records an increase from the previous number of 461.000 Person for 2016. Indonesia Number of Road Accident: Killed: Bali data is updated yearly, averaging 544.000 Person from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 739.000 Person in 2014 and a record low of 262.000 Person in 2003. Indonesia Number of Road Accident: Killed: Bali data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Transport and Telecommunication Sector – Table ID.TA005: Number of Road Accident.

An overall decline in the number of road deaths in Russia was observed from 2007, when the highest volume of road fatalities was recorded countrywide in the given timeframe. The temporary growth of five percent between 2010 and 2012 was followed by a significant drop in the number of incidences over the following years. Namely, the count of road deaths in the country reduced nearly twofold by 2020 relative to the 2012 figures, measuring at 16,152 cases in the last observed period.

Mortality rate and causes of death in Russia   

Mortality rate has been gradually declining since 2000 in Russia, yet it remained greater than the rates measured prior to the 1990s. Even though road accidents were not the major cause of fatalities in the country, roughly 183 thousand residents were reported being injured in road traffic incidents in 2020. The coronavirus (COVID-19) outbreak at the beginning of 2020 ranked Russia as one of the most affected worldwide. The coronavirus-related mortality rate, nonetheless, was measured significantly lower than in most countries with a somewhat similar number of disease cases.

General outlook   

Despite the fact that road fatalities have been in decline in Russia, the country was listed second by road mortality worldwide after Georgia in 2017. The most significant decline in road death rates among the European countries was recorded in Norway in the same year.

In 2020, just under 2,400 individuals were killed in motor vehicle accidents in Italy, down from more than 3,000 in 2019. This was the lowest value on record since the peak in 2006. Safety measures Many information devices have been placed across the motorway system to offer a better service. Furthermore, rest facilities may contribute to reducing the risk of fatigue and tiredness when driving long distances. The number of motorway rest facilities labeled "snack bars" stands at around 400 units. The number of rest facilities with nursery rooms and showers increased too, as has the number of pet parks. Safety in Europe
The rate of road deaths in Europe was highest in Romania in 2020. That year, the country recorded 85 deaths per million population, slightly below the 2019 level. Italy reached an average spot in this ranking. The number of traffic deaths in Italy is the highest in the region of Lombardy.

This statistic shows the number of road traffic fatalities in selected Scandinavian countries from 2007 to 2017. Out of the three displayed countries, Norway had the lowest traffic fatality rate in 2017, amounting to ** deaths per one million inhabitants. The corresponding figure for Sweden was ** deaths, while in Denmark, on average ** death per one million inhabitants occurred. Over the years, all three Scandinavian countries recorded a general decline in road traffic fatalities.

Highways Statistics: Traffic Accidents: Wounded Victims: Paraná data was reported at 5,601.000 Unit in 2017. This records a decrease from the previous number of 5,764.000 Unit for 2016. Highways Statistics: Traffic Accidents: Wounded Victims: Paraná data is updated yearly, averaging 6,512.500 Unit from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 7,098.000 Unit in 2012 and a record low of 2,884.000 Unit in 1998. Highways Statistics: Traffic Accidents: Wounded Victims: Paraná data remains active status in CEIC and is reported by Brazilian Association of Highway Concessionaires. The data is categorized under Brazil Premium Database’s Automobile Sector – Table BR.RAW008: Highways Statistics: Traffic Accidents. The Brazilian Association of Highway Concessionaires-ABCR represents the highway concession sector.

As of February 2025, road traffic fatalities of motorcyclists in Thailand accounted for ** percent of the total road traffic fatalities involving cars and motorcycles. The majority of road traffic fatalities in the country at that time involved male drivers.