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.

The United States had, by far, the highest homicide rate of the G7 countries between 2000 and 2023. In 2023, it reached 5.76 homicides per 100,000 inhabitants, a decrease from 6.78 in 2021. By comparison, Canada, the G7 nation with the second-highest homicide rate, had 1.98 homicides per 100,000 inhabitants in 2023. Out of each G7 nation, Japan had the lowest rate with 0.23 homicides per 100,000 inhabitants.

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

California reported the largest number of homicides to the FBI in 2023, at 1,929 for the year. Texas recorded the second-highest number of murders, with 1,845 for the year. Homicide victim demographics There were a total of 19,252 reported homicide cases in the U.S. in 2023. When looking at murder victims by gender and ethnicity, the vast majority were male, while just over half of the victims were Black or African American. In addition, homicide victims in the United States were found most likely to be between the ages of 20 and 34 years old, with the majority of victims aged between 17 to 54 years old. Are murders up? In short, no – since the 1990s the number of murders in the U.S. has decreased significantly. In 1990, the murder rate per 100,000 people stood at 9.4, and stood at 5.7 in 2023. It should be noted though that the number of homicides increased slightly from 2014 to 2017, although figures declined again in 2018 and 2019, before ticking up once more in 2020 and 2021. Despite this decline, when viewed in international comparison, the U.S. murder rate is still notably high. For example, the Canadian homicide rate stood at 1.94 in 2023, while the homicide rate in England and Wales was even lower.

Pueblo, Colorado, was the United States city that experienced the largest surge in its gun homicide rate in 2021, with an increase of 119 percent compared to the previous year. Pueblo was followed by the Texan city of Amarillo and its growth of 117 percent in the homicide rate, while Michigan's Lansing endured an increment of 112 percent.

Homicide Reduction Partnership, a collaborative effort to reduce violent crime through strategic prevention and focused enforcement. With this new partnership, MPD will focus resources and intelligence-led policing strategies in collaboration with local and federal law enforcement and criminal justice partners, DC government agencies, and community partners.The Homicides Reduction Partnership (HRP) will focus on reducing violent crime within four Police Service Areas throughout the entire 2022 calendar year. These areas include PSAs 603, 604, 706 and 708, which accounted for 21% of all murders city-wide in 2021. The objective of the HRP is to use a “whole of government” approach to reduce violent crime, have a positive impact on the community’s perception of safety and security, and increase trust among residents in the police and DC government. By committing an entire year, the goal is to sustain success after the conclusion of the initiative.For more information visit https://dc.gov/release/mayor-bowser-announces-new-year-round-partnership-focused-violent-crime

Note: Due to a system migration, this data will cease to update on March 14th, 2023. The current projection is to restart the updates on or around July 17th, 2023.Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov

Number of homicide victims, by method used to commit the homicide (total methods used; shooting; stabbing; beating; strangulation; fire (burns or suffocation); other methods used; methods used unknown), Canada, 1974 to 2024.

The UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2021 dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

The rate of homicides by firearm as reported in the Part 1 crime data per 1,000 residents in an area. Source: Baltimore Police DepartmentYears Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.

Number, rate and percentage changes in rates of homicide victims, Canada, provinces and territories, 1961 to 2024.

Source: https://www.denvergov.org/opendata/dataset/city-and-county-of-denver-crime

Description

This dataset includes criminal offenses in the City and County of Denver for the previous five calendar years plus the current year to date. The data is based on the National Incident Based Reporting System (NIBRS) which includes all victims of person crimes and all crimes within an incident. The data is dynamic, which allows for additions, deletions and/or modifications at any time, resulting in more accurate information in the database. Due to continuous data entry, the number of records in subsequent extractions are subject to change. Crime data is updated Monday through Friday.

Disclaimer

The information provided here regarding public safety in Denver are offered as a courtesy by the City and County of Denver. By downloading this data, you acknowledge that you have read and understand the Disclaimer below and agree to be bound by it. Certain information is omitted, in accordance with legal requirements and as described more fully in this Disclaimer.

All materials contained on this site are distributed and transmitted "as is," without any representation as to completeness or accuracy and without warranty or guarantee of any kind. The City and County of Denver is not responsible for any error or omission on this site or for the use or interpretation of the results of any research conducted here.

About Crime Data

The Denver Police Department strives to make crime data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. Data on this site are updated Monday through Friday, adding new incidents and updating existing data with information gathered through the investigative process.

Not surprisingly, crime data become more accurate over time, as new incidents are reported and more information comes to light during investigations.

Crimes that occurred at least 30 days ago tend to be the most accurate, although records are returned for incidents that happened yesterday. This dynamic nature of crime data means that content provided here today will probably differ from content provided a week from now. Likewise, content provided on this site will probably differ somewhat from crime statistics published elsewhere by the City and County of Denver, even though they draw from the same database.

Withheld Data

In accordance with legal restrictions against identifying sexual assault and child abuse victims and juvenile perpetrators, victims, and witnesses of certain crimes, this site includes the following precautionary measures: (a) Addresses of sexual assaults are not included. (b) Child abuse cases, and other crimes which by their nature involve juveniles, or which the reports indicate involve juveniles as victims, suspects, or witnesses, are not reported at all.

Crimes that are initially reported, but that are later determined not to have occurred, are called "unfounded" offenses. These incidents are excluded once they have been designated as unfounded.

About Crime Locations

Crime locations reflect the approximate locations of crimes but are not mapped to actual property parcels. Certain crimes may not appear on maps if there is insufficient detail to establish a specific, mappable location.

Overview:

This project aims to investigate the potential correlation between the Gross Domestic Product (GDP) of approximately 190 countries for the years 2021 and 2023 and their corresponding crime ratings. The crime ratings are represented on a scale from 0 to 10, with 0 indicating minimal or null crime activity and 10 representing the highest level of criminal activity.

Dataset:

The dataset used in this project comprises GDP data for the years 2021 and 2023 for around 190 countries, sourced from reputable international databases. Additionally, crime rating scores for the same countries and years are collected from credible sources such as governmental agencies, law enforcement organizations, or reputable research institutions.

Methodology:

• Data Collection: GDP data for 2021 and 2023, along with crime rating scores, are gathered for approximately 190 countries.
• Data Preprocessing: The collected data is cleaned and standardized to ensure consistency and compatibility across different datasets.
• Analysis: Statistical methods and data visualization techniques are employed to explore the potential relationship between GDP and crime ratings.
• Interpretation: Findings from the analysis are interpreted to determine the strength and direction of any observed correlations between GDP and crime ratings.
• Conclusion: Based on the analysis results, conclusions are drawn regarding the existence and significance of the relationship between GDP and crime ratings.

Expected Outcomes:

Identification of any significant correlations or patterns between GDP and crime ratings across different countries. Insights into the potential socioeconomic factors influencing crime rates and their relationship with economic indicators like GDP. Implications for policymakers, law enforcement agencies, and researchers in understanding the dynamics between economic development and crime prevalence.

Since 2021, the homicide rate in Port-au-Prince has been on the rise. In 2024, Haiti's most populous city and capital had a homicide rate of ****** cases per 100,000 inhabitants.

The National Incident-Based Reporting System (NIBRS) is a part of the Uniform Crime Reporting Program (UCR), administered by the Federal Bureau of Investigation (FBI). In the late 1970s, the law enforcement community called for a thorough evaluative study of the UCR with the objective of recommending an expanded and enhanced UCR program to meet law enforcement needs into the 21st century. The FBI fully concurred with the need for an updated program to meet contemporary needs and provided its support, formulating a comprehensive redesign effort. Following a multiyear study, a "Blueprint for the Future of the Uniform Crime Reporting Program" was developed. Using the "Blueprint," and in consultation with local and state law enforcement executives, the FBI formulated new guidelines for the Uniform Crime Reports. The National Incident-Based Reporting System (NIBRS) was implemented to meet these guidelines. NIBRS data as formatted by the FBI are stored in a single file. These data are organized by various segment levels (record types). There are six main segment levels: administrative, offense, property, victim, offender, and arrestee. Each segment level has a different length and layout. There are other segment levels which occur with less frequency than the six main levels. Significant computing resources are necessary to work with the data in its single-file format. In addition, the user must be sophisticated in working with data in complex file types. While it is convenient to think of NIBRS as a hierarchical file, its structure is more similar to a relational database in that there are key variables that link the different segment levels together. NIBRS data are archived at ICPSR as 11 separate data files per year, which may be merged by using linkage variables. Prior to 2013 the data were archived and distributed as 13 separate data files, including three separate batch header record files. Starting with the 2013 data, the FBI combined the three batch header files into one file. Consequently, ICPSR instituted new file numbering for the data. NIBRS data focus on a variety of aspects of a crime incident. Part 2 (formerly Part 4), Administrative Segment, offers data on the incident itself (date and time). Each crime incident is delineated by one administrative segment record. Also provided are Part 3 (formerly Part 5), Offense Segment (offense type, location, weapon use, and bias motivation), Part 4 (formerly Part 6), Property Segment (type of property loss, property description, property value, drug type and quantity), Part 5 (formerly Part 7), Victim Segment (age, sex, race, ethnicity, and injuries), Part 6 (formerly Part 8), Offender Segment (age, sex, and race), and Part 7 (formerly Part 9), Arrestee Segment (arrest date, age, sex, race, and weapon use). The Batch Header Segment (Part 1, formerly Parts 1-3) separates and identifies individual police agencies by Originating Agency Identifier (ORI). Batch Header information, which is contained on three records for each ORI, includes agency name, geographic location, and population of the area. Part 8 (formerly Part 10), Group B Arrest Report Segment, includes arrestee data for Group B crimes. Window Segments files (Parts 9-11, formerly Parts 11-13) pertain to incidents for which the complete Group A Incident Report was not submitted to the FBI. In general, a Window Segment record will be generated if the incident occurred prior to January 1 of the previous year or if the incident occurred prior to when the agency started NIBRS reporting. As with the UCR, participation in NIBRS is voluntary on the part of law enforcement agencies. The data are not a representative sample of crime in the United States. Recognizing many differences in computing resources and that many users will be interested in only one or two segment levels, ICPSR has decided to make the data available as multiple files. Each NIBRS segment level in the FBI's single-file format has been made into a separate rectangular ASCII data file. Linkage (key) variables are used to perform analyses that involve two or more segment levels. If the user is interested in variables contained in one segment level, then the data are easy to work with since each segment level file is simply a rectangular ASCII data file. Setup files are available to read each segment level. Also, with only one segment level, the issue of

AUSTIN POLICE DEPARTMENT DATA DISCLAIMER Please read and understand the following information. This dataset contains a record of incidents that the Austin Police Department responded to and wrote a report. Please note one incident may have several offenses associated with it, but this dataset only depicts the highest level offense of that incident. Data is from Report On dates of January 1 through December 31, 2021. This dataset is updated weekly. Understanding the following conditions will allow you to get the most out of the data provided. Due to the methodological differences in data collection, different data sources may produce different results. This database is updated weekly, and a similar or same search done on different dates can produce different results. Comparisons should not be made between numbers generated with this database to any other official police reports. Data provided represents only calls for police service where a report was written. Totals in the database may vary considerably from official totals following investigation and final categorization. Therefore, the data should not be used for comparisons with Uniform Crime Report statistics. The Austin Police Department does not assume any liability for any decision made or action taken or not taken by the recipient in reliance upon any information or data provided. Pursuant to section 552.301 (c) of the Government Code, the City of Austin has designated certain addresses to receive requests for public information sent by electronic mail. For requests seeking public records held by the Austin Police Department, please submit by utilizing the following link: https://apd-austintx.govqa.us/WEBAPP/_rs/(S(0auyup1oiorznxkwim1a1vpj))/supporthome.aspx

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This dataset represents the concatenated version of the NCVS on a collection year basis for 1992-2021. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred.For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 38429.

The Calls for Service dataset includes police service requests for which patrol officers, traffic officers, bike officers and, on occasion, detectives will be dispatched to public safety response. It also includes self-initiated calls for service where an officer witnesses a violation or suspicious activity for which they would respond. This item represents a consolidated item of all records.Why the Datasets are Organized into Separate Layers In January of 2022, the Tempe Police Department completed a major transition in how crimes data is reported, moving from the FBI Uniform Crime Report program to the enhanced National-Incident Based Reporting System, or NIBRS. NIBRS is now the required reporting method for the FBI. The Uniform Crime Report (UCR) Program's traditional Summary Reporting System (SRS) was limited in comparison to NIBRS, which offers more detailed data collection that provides a deeper understanding of crime and its circumstances. NIBRS captures a wider range of details on crime incidents and can reflect separate offenses occurring during the same event, including information on victims, known offenders, relationships between victims and offenders, arrestees, and property involved in the crimes. With greater specificity in reporting offenses, NIBRS provides for more accurate and detailed crime-related information, and helps give context to specific crime issues while affording greater analytic capability of crime. Below is the link to Tempe-specific NIBRS reports. Use the drop-down filters to select Tempe PD, the year, and the type of report. Because of these differences, trends and numbers between the two systems should not be directly compared. That’s why we treat 2022 and later (NIBRS) separately from 2021 and earlier (UCR). To make the older data easier to browse, we grouped the data from 2021 and earlier into year ranges instead of showing it all at once. This helps with performance and loading speed due to the large count of records. For detailed guidance on interpreting calls for service data, as well as data scope and limitations, please refer to the User Guide.Data DictionaryAdditional InformationContact Email: PD_DataRequest@tempe.govContact Phone: N/ALink: N/AData Source: Versaterm Informix RMSData Source Type: Informix and/or SQL ServerPreparation Method: Automated processPublish Frequency: DailyPublish Method: Automatic