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Research project

European Homicide Monitor

The European Homicide Monitor (EHM) offers a standardized framework for countries and regions to compare homicide characteristics, patterns and trends.

Contact
Marieke Liem
Funding
European Union European Union
Partners

Swedish National Council for Crime Prevention (Brå), the National Research Institute of Legal Policy (now the Institute of Criminology and Legal Policy at the University of Helsinki)

Homicides are crimes involving the most severe types of violence. Homicides lead to high social costs due to loss of life and human suffering, which is why they are assigned substantial resources in connection to criminal investigations, court cases and the implementation of penal sanctions. Homicides in the European countries constitute a crime type with a relatively small dark figure. This makes them particularly suitable for international comparisons and a relatively good indicator of the development in violent crime in general.

The European Homicide Monitor (EHM) began as a three-year pilot project financed by the European Union in 2009-2011. It sought to provide a four-year epidemiology (2003-2006) of homicides in Finland, the Netherlands and Sweden. The study was conducted by the Swedish National Council for Crime Prevention (Brå), the National Research Institute of Legal Policy (now the Institute of Criminology and Legal Policy at the University of Helsinki) and Leiden University. These parties now constitute the EHM steering committee (represented by Janne Kivivuori, Martti Lehti, Sven Granath, Nora Markwalder and Marieke Liem).

The initial EHM database combined data from the Finnish Homicide Monitor, the Dutch Homicide Monitor, and the Swedish Brå homicide database into a the European Homicide Monitor, allowing for detailed analyses on case, victim and perpetrator level. The main EHM manual, and the main findings of the first comparative analyses, were published in 2011 under the title Homicide in Finland, the Netherlands and Sweden (Granath et al. 2011).

The aim of creating the European Homicide Monitor was to construct a comparable EHM data format based on already existing national homicide monitors. In the pilot-study, a mutual coding manual was created that can be adopted by others interested in homicide data collection at non-aggregated level for scientific purposes. The idea of EHM was to give standardized comparability for countries to compare homicide patterns and to enable individual and incident level analysis. By ensuring that all (future) participants prepare their data in a similar format, the EHM format allows for comparing results cross-nationally. 

The EHM initiative is still active today, and has expanded by including additional countries and additional years available for analyses. In addition to the 2003-2006 EHM data, participating countries have ready-made datasets in EHM format, which could be ‘shared and merged’ for comparative analyses. Due to national differences in legislation, national EHM files are presently stored separately. As data are structured in a standardized way, joint analysis currently takes place by sharing syntaxes. 

The architecture of the EHM is based on three main principles. First, the EHM is a general homicide monitor. It includes all types of victims and incidents. This is a considerable asset since it allows analysts to compare various homicide types. Second, the EHM allows for disaggregating overall homicide patterns and trends. This helps to specify which sub-types of homicide account for possible general patterns such as national differentials and even cross-national trends. Third, the EHM system is open: new countries can join by adopting the coding system.  

The EHM generally relies on information from the police, official criminal justice records, autopsy reports, newspaper articles, and auxiliary public domain sources, although there are slight variations between participating countries in terms of data sources used. It has been left to each participating country to decide on a hierarchy which best fits the goal of having the highest quality data possible, based on which types of documents are considered the most reliable. 

The EHM offers numerous possibilities for future research, including studying seldom occurring homicide types, assessing the influence of individual characteristics and examining the data from a law-oriented perspective concerning judicial definitions and sentencing practices.

All project partners are committed to continuing the work on the EHM by gathering data nationally and combining data at regular intervals. The project partners hope that other research institutions will find an interest in the results and the data used in this study and that other member states will compile national data in the format used in the project, laying the foundations for a European Homicide Monitor that includes as many European countries as possible, since it provides a unique data source for research and could be an important part of European research infrastructure, helping both policy targeting and evaluating what works in homicide prevention.

The data in the EHM dataset are based on data that have been collected and coded in existing national homicide monitors in Finland, the Netherlands, Sweden and Switzerland. The variables in national homicide monitors, or more commonly the variable values, required recoding. When the recoding was completed the national homicide datasets where merged into an international dataset.

Finland

Data for the Finnish Homicide Monitor (FHM) are based on information produced during preliminary police investigations, and collected directly by the chief investigator on a standard electronic form. The database contains information on the main characteristics of the crime, the victims and the main perpetrator. It also contains information related to the investigation of the crime and information on the behavior of the suspects after the crime and during the investigation. The number of internal variables in the questionnaire (questions addressed to the chief investigator about the incident, victim or offender) is about is 146.

Netherlands

Data for the Dutch Homicide Monitor Homicide data from the Netherlands stem from three sources: media reports, police data and court files. Media reports on homicides are retrieved from the Dutch Associated Press and LexisNexis. These reports are completed and verified with digitalized national police data on homicide events. Third, homicide data are completed and verified by assessing hard-copy court files, which include the criminal proceedings of the case, interview excerpts with suspects, relatives and witnesses and, in several cases, forensic mental health reports.

Sweden

Data on homicide from Sweden are collated by the Swedish National Council for Crime Prevention. The data include all cases known to the authorities. All assessments of cases are based on police files, the verdicts from the court and records of a forensic psychiatric examination when such an examination had been carried out.  

Switzerland

The Swiss Homicide Database (SHD) is part of a research project realized by the Universities of Lausanne, Zurich and St. Gallen and sponsored by the Swiss National Science Foundation SNF. The first part of this project started in 2001 and was limited to four cantons in the French-speaking part of Switzerland (Vaud, Neuchâtel, Valais and Fribourg).  After completion of this first SNF-project, the SNF sponsored an extension of the project to all Swiss cantons. The extended Swiss project differs only slightly from the original project. To shorten the already complex data collection process, only completed homicides were included in the data collection, excluding attempts that were previously considered. Data are based on autopsy registries from legal medicine institutes and completed by police and court files. The most recent research project conducted by the University of St. Gallen and again sponsored by the SNF allowed to update data on homicide for all cantons until the year 2014.

Dutch Caribbean

In its current form, the Dutch Caribbean Homicide Monitor (DCHM) covers homicides that have taken place in Curacao, between 2014 – 2018. The DCHM consists of 228 variables, of which approximately 20 variables reflect the local culture and context. Data in the DCHM is based on information provided by the Infocell Caribbean (ICCA) , part of the Dutch Police based in Rotterdam. ICCA maintains a list that includes all homicides, attempted homicides and violent incidents that took place in the Dutch Caribbean region from 2000 onwards. Further, legal files on prosecuted homicides stemming from the Public Prosecution Office have been consulted, as well as so-called “criminal cards”, reflecting the perpetrator’s or victim’s criminal history. A fourth source includes local newspaper articles that have been used for verification and additional detail.

Variables in the European Homicide Monitor

Database structure

The original EHM consists of 85 variables including characteristics of the incident, the victim, and the perpetrator. Each single homicide incident in the EHM is uniquely identified by a case number. Perpetrators and victims are linked to a case number, and in addition, uniquely identified by a serial number. Each row in the data therefore based represents a perpetrator or a victim. Further, it is indicates for each individual (for both perpetrators and victims) if they are considered a principal perpetrator or victim, neither or unknown. Also, the number of victims and perpetrators per homicide incident is scored.

Incident characteristics

For every incident, the database includes information on the date of homicide, the year the incident was reported to the police, and year, month and day of the week it was committed. Also, it includes whether the homicide incident took place on a public holiday. Further, data is available on whether the homicide took place in a urban or rural area and in what area of the country concerned, using the NUTS-classification set by Eurostat.

Per homicide incident, information on the circumstances is available, such as the time of day the homicide is committed, and within how many days the homicide was discovered by who made it known to the police. Moreover, the EHM collects data on the presence of eye witnesses to the homicide, and the time it took for police to arrest the perpetrator(s). For each victim, information is scored on the time of death in hours of the day, and whether the victim had used violence against perpetrator during the homicide event. Lastly, it collects information on whether any other crimes (besides the homicidal act) have been committed against the victim or perpetrator. 

In terms of locus delicti and modus operandi of the homicide incident the EHM captures information on the crime scene and whether it was committed in the same area as the victim and/or perpetrator lived in. As for the modus operandi, the type of method used to kill the victim (classified according to the ICD-10) is indicated. Additional variables indicate the use of the type and illegality of the firearm used, and the number and placement of stabs in case knives were used. 

Perpetrator and victim characteristics

For all individuals involved in the homicide incident, the EHM states the relationship between the victim and the perpetrator. In case of multiple victims and perpetrators, the relationship may differ. The coding system further captures the type of homicide, in reference to the relationship between perpetrators and victims and homicide motive.

For all perpetrators and victims, information on basic socio-demographic variables is collected, such as their age and gender, the country of birth of all individuals and of their parents, and citizenship. Further, data is collected on the civil status of individuals, whether they have children, their housing situation, professional status and level of education at the time of the homicide.

In addition, for both perpetrators and victims, data are available on addiction and use of alcohol and drug use at the time of the homicide. Also, the EHM collects data on the existence of previous threats prior to the homicide incident by victims directed at perpetrator or vice versa, and similarly for violent behavior prior to the homicide. Lastly, the EHM includes variables on a history of mental illness or history of violence.

Also, for every perpetrator, it is scored whether the perpetrator committed (a) suicide (attempt) following the homicide, and if so, within what time frame and by what method. In addition, data are collected on the criminal history and the number and type of officially recorded previous convictions.

Criminal procedure

With regard to the investigation following the homicide incident, the EHM reflects whether homicide is investigated as a murder or manslaughter by the police, and if the case is considered cleared by arrest or exceptionally cleared. Lastly, it allows for collecting data on the prosecution, conviction and sentencing stages.

Modular Additions

Modular additions to the standard part of EHM variables may be made, while keeping the EHM-structure as a starting point. These additions include country specific variables (as has been done in the Dutch Caribbean Homicide Monitor); variables on the role of drugs or external datasets. 

Modular Addition on the Role of Drugs

In order to expand the existing EHM with specific drug-related, Goldstein’s conceptual framework has been applied, designed to gain a deeper understanding of the relationship between drugs and homicide. This is an optional module to the EHM. In 2018, a first pilot-study  was undertaken to test the feasibility of integrating additional variables related to drugs,  by re-examining cases in Finland (2014-2015), Sweden (2013-2014) and the Netherlands (2012-2016). Added variables attempt to capture Goldstein’s tripartite framework, and reflect psychopharmacological violence, economic-compulsive violence and systemic violence (see Tables 2-4 below).

Table 1. General drug-related variables

For psychopharmacological homicide, additional variables reflect the type of drugs and the amount of drugs the victim and/or perpetrator had been using, and whether these drugs were (il)legal. In order to determine whether cases of (robbery) homicides constitute economic-compulsive violence, additional variables reflected what the perpetrator intended to steal. Finally, new variables allowed us to close assess the nature of systemic violence, occurring within the broader criminal milieu during the sale and distribution of drugs.

Table 2. Variables related to psychopharmacological homicide
Table 3. Variables related to economic-compulsive homicide
Table 4. Variables related to systemic homicide

Articles

Kivivuori, J. & Lehti, M. (2011). Homicide in Finland and Sweden. In Michael Tonry & Tapio Lappi-Seppälä (eds): Crime and Justice in Scandinavia. Crime and Justice – A Review of Research. University of Chicago Press, Chicago, pp. 109–198.

Kivivuori, J. & Lehti, M. (2012). Social Correlates of Intimate Partner Homicide in Finland: Distinct or Shared With Other Homicide Types? Homicide Studies 16:1, 60–77.

Kivivuori, J. & Suonpää, K. & Lehti, M. (2014). Patterns and Theories of European homicide Research. European Journal of Criminology 11:5, 530-531.

Lehti, M. & Kääriäinen, J. & Kivivuori, J. (2012). The Declining Number of Child Homicides in Finland, 1960–2009. Homicide Studies 16:1, 3–22.

Liem, M., Suonpää, K., Lehti, M., Kivivuori, J., Granath, S., Walser, S., & Killias, M. (2018). Homicide clearance in Western Europe. European Journal of Criminology, 1477370818764840.

Liem, M., van Buuren, J., de Roy van Zuijdewijn, J., Schönberger, H., & Bakker, E. (2018). European Lone Actor Terrorists Versus “Common” Homicide Offenders: An Empirical AnalysisHomicide Studies22(1), 45-69.

Liem, M., Ganpat, S., Granath, S., Hagstedt, J., Kivivuori, J., Lehti, M., & Nieuwbeerta, P. (2013). Homicide in Finland, the Netherlands, and Sweden: First findings from the European homicide monitorHomicide Studies17(1), 75-95.

Tiihonen, J., Lehti M., Aaltonen M., Kivivuori J., Kautiainen H., Virta L.J., Hoti F., Tanskanen A. & Korhonen P. (2015). Psychotropic drugs and homicide: a prospective cohort study from Finland. World Psychiatry 14:2, 245-247.

Books

Liem, M., & Pridemore, W. A. (Eds.). (2011). Handbook of European homicide research: Patterns, explanations, and country studies. New York: Springer.

Reports

Granath, S. & Hagstedt, J. & Kivivuori, J. & Lehti, M. & Ganpat, S. & Liem, M. & Nieuwbeerta, P. (2011). Homicide in Finland, the Netherlands and Sweden. A First Study on the European Homicide Monitor Data. Swedish Council for Crime Prevention, Research Report 2011:5, Stockholm.

Liem, M. C. A., van Buuren, G. M., & Schönberger, H. J. M. (2018). Cut from the same cloth? Lone Actor Terrorists versus Common Homicide Offenders. ICCT-Research papers9, 22.

Liem, M. C. A., Kivivuori, J. K. A., Lehti, M., Granath, S., & Schönberger, H. (2017). Les homicides conjugaux en Europe: résultats provenant du European Homicide Monitor [Intimate Partner Homicide in Europe: Findings from the European Homicide Monitor]. Cahiers de la Sécurité et de la Justice41, 13.

Presentations

Kivivuori, J (2011). Towards a European Homicide Monitor : The Future of EHM. Stockholm Criminology Symposium, June 14, 2011.

Kivivuori, J & Lehti, M (2017). European Homicide Monitor: The Challenge for a Joint Database on Lethal Violence in Europe. International Conference on Homicide, French National Observatory of Crime and Criminal Justice (ONDRP), Paris 22 May 2017.

Liem, M. (2016) Femicide in Europe. 3rd International Conference on Governance, Crime and Justice Statistics. UNODC. Merida, Mexico.

Liem, M. (2018) The European Homicide Monitor. 4th International Conference on Governance, Crime and Justice Statistics. UNODC. Lima, Peru

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