In 2025, Pietermaritzburg in South Africa ranked as the world's most dangerous city with a crime rate of 82 per 100,000 inhabitants. Five of the 10 cities with the highest crime rates worldwide are found in South Africa. The list does not include countries where war and conflict exist. South Africa dominates crime statistics When looking at crime rates, among the 10 most dangerous cities in the world, half of them are found in South Africa. The country is struggling with extremely high levels of inequality, and is struggling with high levels of crime and power outages, harming the country's economy and driving more people into unemployment and poverty. Crime in Latin America On the other hand, when looking at murder rates, Latin America dominates the list of the world's most dangerous countries. Violence in Latin America is caused in great part by drug trafficking, weapons trafficking, and gang wars.

In 2023, around 3,640.56 violent crimes per 100,000 residents were reported in Oakland, California. This made Oakland the most dangerous city in the United States in that year. Four categories of violent crimes were used: murder and non-negligent manslaughter; forcible rape; robbery; and aggravated assault. Only cities with a population of at least 200,000 were considered.

In 2022, the New Orleans-Metairie, LA metro area recorded the highest homicide rate of U.S. cities with a population over 250,000, at **** homicides per 100,000 residents, followed by the Memphis, TN-MS-AR metro area. However, homicide data was not recorded in all U.S. metro areas, meaning that there may be some cities with a higher homicide rate. St. Louis St. Louis, which had a murder and nonnegligent manslaughter rate of **** in 2022, is the second-largest city by population in Missouri. It is home to many famous treasures, such as the St. Louis Cardinals baseball team, Washington University in St. Louis, the Saint Louis Zoo, and the renowned Gateway Arch. It is also home to many corporations, such as Monsanto, Arch Coal, and Emerson Electric. The economy of St. Louis is centered around business and healthcare, and boasts ten Fortune 500 companies. Crime in St. Louis Despite all of this, St. Louis suffers from high levels of crime and violence. As of 2023, it was listed as the seventh most dangerous city in the world as a result of their extremely high murder rate. Not only does St. Louis have one of the highest homicide rates in the United States, it also reports one of the highest numbers of violent crimes. Despite high crime levels, the GDP of the St. Louis metropolitan area has been increasing since 2001.

In 2024, Pietermaritzburg in South Africa ranked first in the crime index among African cities, scoring **** index points. The six most dangerous areas on the continent were South African cities. Furthermore, Pretoria and Johannesburg followed, with a score of **** and **** points, respectively. The index estimates the overall level of crime in a specific territory. According to the score, crime levels are classified as very high (over 80), high (60-80), moderate (40-60), low (20-40), and very low (below 20). Contact crimes are common in South Africa Contact crimes in South Africa include violent crimes such as murder, attempted murder, and sexual offenses, as well as common assault and robbery. In fiscal year 2022/2023, the suburb of Johannesburg Central in the Gauteng province of South Africa had the highest number of contact crime incidents. Common assault was the main contributing type of offense to the overall number of contact crimes. Household robberies peak in certain months In South Africa, June, July, and December experienced the highest number of household robberies in 2023. June and July are the months that provide the most hours of darkness, thus allowing criminals more time to break in and enter homes without being detected easily. In December, most South Africans decide to go away on holiday, leaving their homes at risk for a potential break-in. On the other hand, only around ** percent of households affected by robbery reported it to the police in the fiscal year 2022/2023.

In 2024, the highest homicide rate among 22 Latin American and Caribbean countries surveyed was in Haiti, with around 62 murders committed per 100,000 inhabitants. Trinidad and Tobago came in second, with a homicide rate of 46, while Honduras ranked seventh, with 25. In the same year, the lowest rate was recorded in El Salvador, with a homicide rate of 1.9 per 100,000 inhabitants. A violence-ridden region Violence and crime are some of the most pressing problems affecting Latin American society nowadays. More than 40 of the 50 most dangerous cities in the world are located in this region, as well as one of the twenty countries with the least peace in the world according to the Global Peace Index. Despite governments’ large spending on security and high imprisonment rates, drug and weapon trafficking, organized crime, and gangs have turned violence into an epidemic that affects the whole region and a solution to this issue appears to be hardly attainable. The cost of violence in Mexico Mexico stands out as an example of the great cost that violence inflicts upon a country, since beyond claiming human lives, it also affects everyday life and has a negative impact on the economy. Mexicans have a high perceived level of insecurity, as they do not only fear becoming victims of homicide, but also of other common crimes, such as assault or rape. Such fear prevents people from performing everyday activities, for instance, going out at night, taking a taxi or going to the movies or the theater. Furthermore, the economic toll of violence in Mexico is more than considerable. For example, the cost of homicide and violent crime amounted to 2099.8 and 1778.1 billion Mexican pesos in 2023, respectively.

Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2024.

There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

In 2023, the metropolitan city of Milan ranked first in terms of crime rate, as it recorded 7,100 felonies per 100,000 inhabitants. Furthermore, the provinces of Rome and Florence followed with around 6,000 cases reported. In Milan, burglaries in shops and thefts were much more common than in any other Italian provinces. Frequent car thefts The Southern province of Barletta-Andria-Trani, in the region of Apulia, was the place in Italy with the highest rate of stolen cars. Roughly 697 cases per every 100,000 residents were registered in 2019. Catania had the second-largest rate with about 656 reports. Nationwide, the three most frequently stolen car models belonged to Fiat, the leading Italian vehicle manufacturer. Moreover, a Lancia car model ranked fourth. This company was also part of the Fiat Group, which, however, only sells vehicles in Italy. Mafia associations  In the last years, the number of mafia associations in Italy experienced a decline. However, there are still dozens of mafia-type organizations in the country. The Southern region of Campania was the place faced with the largest amount of crime associations. In total, 67 of such crimes were reported in Campania in 2019.

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

This study of violent incidents among middle- and high-school students focused not only on the types and frequency of these incidents, but also on their dynamics -- the locations, the opening moves, the relationship between the disputants, the goals and justifications of the aggressor, the role of third parties, and other factors. For this study, violence was defined as an act carried out with the intention, or perceived intention, of physically injuring another person, and the "opening move" was defined as the action of a respondent, antagonist, or third party that was viewed as beginning the violent incident. Data were obtained from interviews with 70 boys and 40 girls who attended public schools with populations that had high rates of violence. About half of the students came from a middle school in an economically disadvantaged African-American section of a large southern city. The neighborhood the school served, which included a public housing project, had some of the country's highest rates of reported violent crime. The other half of the sample were volunteers from an alternative high school attended by students who had committed serious violations of school rules, largely involving illegal drugs, possession of handguns, or fighting. Many students in this high school, which is located in a large city in the southern part of the Midwest, came from high-crime areas, including public housing communities. The interviews were open-ended, with the students encouraged to speak at length about any violent incidents in school, at home, or in the neighborhood in which they had been involved. The 110 interviews yielded 250 incidents and are presented as text files, Parts 3 and 4. The interview transcriptions were then reduced to a quantitative database with the incident as the unit of analysis (Part 1). Incidents were diagrammed, and events in each sequence were coded and grouped to show the typical patterns and sub-patterns in the interactions. Explanations the students offered for the violent-incident behavior were grouped into two categories: (1) "justifications," in which the young people accepted responsibility for their violent actions but denied that the actions were wrong, and (2) "excuses," in which the young people admitted the act was wrong but denied responsibility. Every case in the incident database had at least one physical indicator of force or violence. The respondent-level file (Part 2) was created from the incident-level file using the AGGREGATE procedure in SPSS. Variables in Part 1 include the sex, grade, and age of the respondent, the sex and estimated age of the antagonist, the relationship between respondent and antagonist, the nature and _location of the opening move, the respondent's response to the opening move, persons present during the incident, the respondent's emotions during the incident, the person who ended the fight, punishments imposed due to the incident, whether the respondent was arrested, and the duration of the incident. Additional items cover the number of times during the incident that something was thrown, the respondent was pushed, slapped, or spanked, was kicked, bit, or hit with a fist or with something else, was beaten up, cut, or bruised, was threatened with a knife or gun, or a knife or gun was used on the respondent. Variables in Part 2 include the respondent's age, gender, race, and grade at the time of the interview, the number of incidents per respondent, if the respondent was an armed robber or a victim of an armed robbery, and whether the respondent had something thrown at him/her, was pushed, slapped, or spanked, was kicked, bit, or hit with a fist or with something else, was beaten up, was threatened with a knife or gun, or had a knife or gun used on him/her.

In undertaking this data collection, the principal investigators sought to determine (1) whether police enforcement against drug crimes, specifically heroin crimes, had any influence on the rates of nondrug crimes, and (2) what effect intensive law enforcement programs against drug dealers had on residents where those programs were operating. To achieve these objectives, data on crime rates for seven successive years were collected from police records of 30 cities in Massachusetts. Data were collected for the following offenses: murder, rape, robbery, assault, larceny, and automobile theft. The investigators also interviewed a sample of residents from 3 of those 30 cities. Residents were queried about their opinions of the most serious problem facing people today, their degree of concern about being victims of crime, and their opinions of the effectiveness of law enforcement agencies in handling drug problems.

The average for 2017 based on 79 countries was 105 robberies per 100,000 people. The highest value was in Costa Rica: 1587 robberies per 100,000 people and the lowest value was in Oman: 1 robberies per 100,000 people. The indicator is available from 2003 to 2017. Below is a chart for all countries where data are available.

Police recorded crime figures by Police Force Area and Community Safety Partnership areas (which equate in the majority of instances, to local authorities).

This research study analysed the crime rate spatially and it examined the relationship between crime and spatial factors in Saudi Arabia. It reviewed the related literature that has utilised crime mapping techniques, such as Geographic Information Systems (GIS) and remote sensing (RS); these techniques are a basic part of effectively helping security and authority agencies by providing them with a clear perception of crime patterns and a surveillance direction to track and tackle crime. This study analysed the spatial relationships between crime and place, immigration, changes in urban areas, weather and transportation networks. The research study was divided into six parts to investigate the correlation between crime and these factors. The first part of the research study examined the relationship between crime and place across the 13 provinces of Saudi Arabia using GIS techniques based on population density in order to identify and visualise the spatial distributions of national and regional crime rates for drug crimes, thefts, murders, assaults, and alcohol-related and ‘outrageous crimes’ (offences against Islam) over a 10-year period from 2003 to 2012. Social disorganisation theory was employed to guide the study and explain the diversity in crime patterns across the country. The highest rates of overall crimes were identified in the Northern Borders Province and Jizan, which are located in the northern and southern regions of the country, respectively; the eastern area of the country was found to have the lowest crime rate. Most drug offences occurred in the Northern Borders Province and Jizan; high rates of theft were recorded in the Northern Borders Province, Jouf Province and Makkah Province, while the highest rates of homicide occurred in Asir Province. The second part of the research study aimed to determine the trends of overall crime in relation to six crime categories: drug-related activity, theft, murder, assault, alcohol-related crimes and outrageous or sex-related crimes, in Saudi Arabia’s 13 provinces over a 10-year period from 2003 to 2012. The study analysed the spatial and temporal changes of criminal cases. Spatial changes were used to determine the differences over the time period of 2003–2012 to show the provincial rates of change for each crime category. Temporal changes were used to compute the trends of the overall crime rate and crimes in the six categories per 1,000 people per year. The results showed that the overall crime rate increased steadily until 2008; thereafter it decreased in all areas except for the Northern Borders Province and Jizan, which recorded the highest crime rates throughout the study period. We have explained that decrease in terms of changes in wages, support for the unemployed and service improvements, which were factors that previous studies also emphasised as being the primary cause for the decrease. This study includes a detailed discussion to contribute to the understanding of the changes in the crime rates in these categories throughout this period in the 13 provinces of Saudi Arabia. The third part of the research study aimed to explain the effects of immigration on the overall crime rate in the six most significant categories of crime in Saudi Arabia, which are drug-related activity, theft, murder, assault, alcohol-related crimes and outrageous crimes, during a 10-year period from 2003 to 2012, in all 13 administrative provinces. It also sought to identify the provinces most affected by the criminal activities of immigrants during this period. No positive association between immigrants and criminal cases was found. It was clearly visible that the highest rate of overall criminal activities was in the south, north and Makkah areas, where there is a high probability of illegal immigrants. This finding supports the basic criminological theory that areas with high levels of immigrants also experience high rates of crime. The study’s results provide recommendations to the Saudi government, policy-makers, decision-makers and immigration authorities, which could assist in reducing crimes perpetrated by immigrants. In the fourth part of the research study, urban areas were examined in relation to crime rates. Urban area expansion is one of the most critical types of worldwide change, and most urban areas are experiencing increased population growth and infrastructure development. Urban change leads to many changes in the daily activities of people living within an affected area. Many studies have suggested that urbanisation and crime are related. However, those studies focused on land uses, types of land use and urban forms, such as the physical features of neighbourhoods, roads, shopping centres and bus stations. It is very important for criminologists and urban planning decision-makers to understand the correlation between urban area expansion and crime. In this research, satellite images were used to measure urban expansion over a 10-year period; the study tested the correlations between these expansions and the number of criminal activities within these specific areas. The results show that there is a measurable relationship between urban expansion and criminal activities. The findings support the crime opportunity theory as one possibility, which suggests that population density and crime are conceptually related. Moreover, the results show that the correlations are stronger in areas that have undergone greater urban growth. This study did not evaluate many other factors that might affect the crime rate, such as information on the spatial details of the population, city planning, economic considerations, the distance from the city centre, the quality of neighbourhoods, and the number of police officers. However, this research will be of particular interest to those who aim to use remote sensing to study crime patterns. The fifth part of the research study investigated the impacts of weather on crime rates in two different cities: Riyadh and Makkah. While a number of studies have examined climate influences on crime and human behaviour by investigating the correlation between climate and weather elements, such as temperature, humidity and precipitation, and crime rates, few studies have focused on haze as a weather element and its correlation with crime. This research examined haze as a weather variable to investigate its effects on criminal activity and compare its effects with those of temperature and humidity. Monthly crime data and monthly weather records were used to build a regression model to predict crime cases based on three weather factors using temperature, humidity and haze values. This model was applied to two provinces in Saudi Arabia with different types of climates: Riyadh and Makkah. Riyadh Province is a desert area in which haze occurs approximately 17 days per month on average. Makkah Province is a coastal area where it is hazy an average of 4 days per month. A measurable relationship was found between each of these three variables and criminal activity. However, haze had a greater effect on theft, drug-related crimes and assault in Riyadh Province than temperature and humidity. Temperature and humidity were the efficacious variables in Makkah Province, while haze had no significant influence in that region. Finally, the sixth part of the research study examined the influence of the quality and extent of road networks on crime rates in both urban and rural areas in Jizan Province, Saudi Arabia. We performed both Ordinary Least Squares regression (OLS) and Geographically Weighted Regression (GWR) where crime rate was the dependent variable and paved (sealed) roads, non-paved (unsealed/gravel) roads and population density were the explanatory variables. Population density was a control variable. The findings reveal that, across all 14 districts in that province, the districts with better quality paved road networks had lower rates of crime than the districts with unpaved roads. Furthermore, the more extensive the road networks, the lower the crime rate whether or not the roads were paved. These findings concur with those reported in studies conducted in other countries, which revealed that rural areas are not always the safe, crime-free places they are often believed to be. This research contributes knowledge about the geographical information of criminal movement, and it offers some conceivable reasons for crime rates and patterns in relation to the spatial factors and the socio-cultural perspectives of Saudi Arabian life. More geographical research is still needed in terms of criminology, which will provide a better understanding of crime patterns, particularly in Saudi Arabia, and across the globe, where the spatial distribution of criminal cases is an essential base in crime research. Furthermore, additional studies are needed to investigate the complex interventions of the effect of different spatial variables on crime and the uncertainties correlation with the impact of environmental factors. This can help predict the impact of socioeconomic and environmental factors. The greater part of such an investigation will enhance the understanding of crime patterns, which is imperative for advancing a framework that can be used to address crime reduction and crime prevention.

This dataset contains individual-level homicide and non-fatal shooting victimizations, including homicide data from 1991 to the present, and non-fatal shooting data from 2010 to the present (2010 is the earliest available year for shooting data). This dataset includes a "GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized-access dataset, but with "UNKNOWN" in the shooting column.

Each row represents a single victimization, i.e., a unique event when an individual became the victim of a homicide or non-fatal shooting. Each row does not represent a unique victim—if someone is victimized multiple times there will be multiple rows for each of those distinct events.

The dataset is refreshed daily, but excludes the most recent complete day to allow the Chicago Police Department (CPD) time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

A version of this dataset with additional crime types is available by request. To make a request, please email dataportal@cityofchicago.org with the subject line: Violence Reduction Victims Access Request. Access will require an account on this site, which you may create at https://data.cityofchicago.org/signup.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset. For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.” Officer-involved shootings are not included.

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Note: In some instances, CPD's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most reliable crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: Homicide victims names are delayed by two weeks to allow time for the victim’s family to be notified of their passing.

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Note: This dataset includes variables referencing administrative or political boundaries that are subject to change. These include Street Outreach Organization boundary, Ward, Chicago Police Department District, Chicago Police Department Area, Chicago Police Department Beat, Illinois State Senate District, and Illinois State House of Representatives District. These variables reflect current geographic boundaries as of November 1st, 2021. In some instances, current boundaries may conflict with those that were in place at the time that a given incident occurred in prior years. For example, the Chicago Police Department districts 021 and 013 no longer exist. Any historical violent crime victimization that occurred in those districts when they were in existence are marked in this dataset as having occurred in the current districts that expanded to replace 013 and 021."

In 2023, the state with the highest crime rate in the United States per 100,000 inhabitants was New Mexico. That year, the crime rate was ******** crimes per 100,000 people. In comparison, New Hampshire had the lowest crime rate at ****** crimes per 100,000 people. Crime rate The crime rate in the United States has generally decreased over time. There are several factors attributed to the decrease in the crime rate across the United States. An increase in the number of police officers and an increase in income are some of the reasons for a decrease in the crime rate. Unfortunately, people of color have been disproportionately affected by crime rates, as they are more likely to be arrested for a crime versus a white person. Crime rates regionally The District of Columbia had the highest rate of reported violent crimes in the United States in 2023 per 100,000 inhabitants. The most common crime clearance type in metropolitan counties in the United States in 2020 was murder and non-negligent manslaughter. The second most dangerous city in the country in 2020 was Detroit. Detroit has faced severe levels of economic and demographic declines in the past years. Not only has the population decreased, the city has filed for bankruptcy. Despite the median household income increasing, the city still struggles financially.

The National Initiative for Building Community Trust and Justice (the National Initiative) is a joint project of the National Network for Safe Communities, the Center for Policing Equity, the Justice Collaboratory at Yale Law School, and the Urban Institute, designed to improve relationships and increase trust between communities and law enforcement. Funded by the Department of Justice, this mixed-methods evaluation aimed to assess outcomes and impacts in six cities that participated in the National Initiative, which include Birmingham, AL; Fort Worth, TX; Gary, IN; Minneapolis, MN; Pittsburgh, PA; and Stockton, CA. The data described herein represent two waves of surveys of residents living in the highest-crime, lowest-income residential street segments in the six National Initiative cities. The first wave was conducted between September 2015 and January 2016, and the second wave was conducted between July and October 2017. Survey items were designed to measure neighborhood residents' perceptions of their neighborhood conditions--with particular emphases on neighborhood safety, disorder, and victimization--and perceptions of the police as it relates to procedural justice, police legitimacy, officer trust, community-focused policing, police bias, willingness to partner with the police on solving crime, and the law. The data described herein are from pre- and post-training assessment surveys of officers who participated in three trainings: 1) procedural justice (PJ) conceptual training, which is the application of PJ in the context of law enforcement-civilian interactions, as well as its role in mitigating historical tensions between law enforcement and communities of color; 2) procedural justice tactical, which provided simulation and scenario-based exercises and techniques to operationalize PJ principles in officers' daily activities; and 3) implicit bias, which engaged officers in critical thought about racial bias, and prepared them to better identify and handle identity traps that enable implicit biases. Surveys for the procedural justice conceptual training were fielded between December 2015 and July 2016; procedural justice tactical between February 2016 and June 2017; and implicit bias between September 2016 and April 2018. Survey items were designed to measure officers' understanding of procedural justice and implicit bias concepts, as well as officers' levels of satisfaction with the trainings.

In 2020, the capital city Caracas ranked third in the ranking of most violent Venezuelan metropolises, with a murder rate of nearly ** per 100,000 inhabitants. The list was headed by Cumaná with a homicide rate of *****.

The city states of Berlin, Hamburg and Bremen were the states with the three highest crime rates in Germany in 2020, while the federal state of Bavaria had the lowest. Urban areas generally have higher crime rates than rural ones, making it difficult to compare Germany's three city states with the much larger federal states, which typically cover quite large areas. The federal state with the highest crime rate was Saxony-Anhalt at 7996 crimes per 100 thousand people, compared with the German average of 6209.

In Europe, the Baltic countries of Latvia and Lithuania had the highest and third highest homicide rates respectively in 2022. Latvia had the highest rate at over four per 100,000 inhabitants. Meanwhile, the lowest homicide rate was found in Liechtenstein, with zero murders The most dangerous country worldwide Saint Kitts and Nevis is the world's most dangerous country to live in in terms of murder rate. The Caribbean country had a homicide rate of 65 per 100,000 inhabitants. Nine of the 10 countries with the highest murder rates worldwide are located in Latin America and the Caribbean. Whereas Celaya in Mexico was listed as the city with the highest murder rate worldwide, Colima in Mexico was the city with the highest homicide rate in Latin America, so the numbers vary from source to source. Nevertheless, several Mexican cities rank among the deadliest in the world when it comes to intentional homicides. Violent conflicts worldwide Notably, these figures do not include deaths that resulted from war or a violent conflict. While there is a persistent number of conflicts worldwide, resulting casualties are not considered murders. Partially due to this reason, homicide rates in Latin America are higher than those in countries such as Ukraine or the DR Congo. A different definition of murder in these circumstances could change the rate significantly.