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 2024, Pietermaritzburg (South Africa) ranked first in the crime index among African cities, with a rating of roughly ** index points. The six most dangerous areas on the continent were South African cities. 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). South Africa’s crime situation According to the crime index ranking, ************ was the most dangerous country in Africa in 2023, followed by ***************** and ******. Murder and organized crime are particularly widespread in South Africa. In 2023, the country had one of the highest murder rates globally, registering around ** homicides per 100,000 inhabitants. Moreover, South Africa’s crime scene is also characterized by the presence of organized criminal activities, for which the country ranked third in Africa. Reflecting these high levels of crime, a survey conducted in 2023 showed that around ** percent of South Africans were worried about crime and violence in the country. Crime risks in Africa The African continent hosts some of the most dangerous places worldwide. In 2023, *********** and the ******************************** were the least peaceful countries in Africa, according to the Global Peace Index. Worldwide, they ranked fourth and fifth, respectively, behind Afghanistan, Yemen, and Syria. Terrorism is a leading type of crime perpetrated in Africa. Home to Boko Aram, Nigeria is among the countries with the highest number of terrorism-related deaths globally. Furthermore, Burkina Faso had the highest number of fatalities in the world. Human trafficking is also widespread, predominantly in West Africa. The most common forms of exploitation of victims of trafficking in persons are forced labor and sexual exploitation.

Study conducted from 2012-2015 on the most dangerous places for pedestrians in Texas.

Turks and Caicos Islands saw a murder rate of ***** per 100,000 inhabitants, making it the most dangerous country for this kind of crime worldwide as of 2024. Interestingly, El Salvador, which long had the highest global homicide rates, has dropped out of the top 29 after a high number of gang members have been incarcerated. Meanwhile, Colima in Mexico was the most dangerous city for murders. 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 Afghanistan or Syria. A different definition of murder in these circumstances could change the rate significantly in some countries. Causes of death Also, noteworthy is that murders are usually not random events. In the United States, the circumstances of murders are most commonly arguments, followed by narcotics incidents and robberies. Additionally, murders are not a leading cause of death. Heart diseases, strokes and cancer pose a greater threat to life than violent crime.

In this web map created I wanted to focus on the state of New Jersey since 2 of its cities are very high in crime in the United States. Camden and Trenton in Particular are the highest crime rates in New Jersey. I was able to create this web map by showing the police departments in the most dangerous parts of the cities which is shown by the darker the red gets the more dangerous it gets in these parts of the state

This is a breakdown of every arrest effected in NYC by the NYPD during the current year. This data is manually extracted every quarter and reviewed by the Office of Management Analysis and Planning. Each record represents an arrest effected in NYC by the NYPD and includes information about the type of crime, the location and time of enforcement. In addition, information related to suspect demographics is also included. This data can be used by the public to explore the nature of police enforcement activity. Please refer to the attached data footnotes for additional information about this dataset.

This table contains data on the rate of violent crime (crimes per 1,000 population) for California, its regions, counties, cities and towns. Crime and population data are from the Federal Bureau of Investigations, Uniform Crime Reports. Rates above the city/town level include data from city, university and college, county, state, tribal, and federal law enforcement agencies. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Ten percent of all deaths in young California adults aged 15-44 years are related to assault and homicide. In 2010, California law enforcement agencies reported 1,809 murders, 8,331 rapes, and over 95,000 aggravated assaults. African Americans in California are 11 times more likely to die of assault and homicide than Whites. More information about the data table and a data dictionary can be found in the About/Attachments section.

In 2024, South Africa ranked first in the crime index among African countries, with a score of **** index points. Nigeria was the second most dangerous country on the continent, obtaining **** points. The index evaluates the overall crime levels in a specific country. Several African countries scored between ** and ** points, indicating high crime levels. Escalating concerns: South Africans worry about crime and violence In 2024, South Africa had one of the highest proportions of respondents expressing concerns about crime and violence compared to other countries participating in an online study. Throughout the period examined, the percentage of participants worried about violence peaked at ** percent in March 2023. The escalating levels of violent crime currently witnessed in the country has caused this significant rise in concerned respondents. South Africa's organized crime landscape In 2023, South Africa ranked the ************* in organized crime compared to its African counterparts. The continent's most prevalent organized criminal activity was **************************************. Moreover, from a regional perspective, Southern African countries had the lowest organized crime rate.

Deze datasets komen voort uit het project Dangerous Cities. Voor achtergrondinformatie en structuur van de databestanden (metadata) zie de gedeponeerde PDF.Background and research questionsUCL Architecture’s Space Syntax Laboratory, which focuses on crime and urban design, concluded that there was ‘no correlation between crime and density, only a poor correlation between affluence and crime, but a very strong correlation between layout type and all kinds of crime, with traditional street patterns [relatively straight streets] the best and the most modern hierarchical layouts the worst’ (Hillier 2004). These results, regularly reprised by criminologists, have, however, never been tested in an historical context, which is what this project aims to do.DatasetTwo case studies have been selected: Amsterdam and Leiden, 1850–1913, based on the Arrondissementsrechtbank (Noord-Hollands Archief Haarlem) and Kantongerecht (Nationaal Archief The Hague) archives, respectively. Judicial registers in these archives detail c. 50,000 individuals charged for Amsterdam and 10,000 for Leiden from the mid-19th century onwards. Two types of information have been recorded, the personal details of the charged (name, age, civil status and employment) and details of the crime (where, what, when). These registers are an excellent source for a systematic analysis using databases and GIS applications, but they have rarely been studied.

Staff calculated the most dangerous intersection within each city using the Weighted Severity Index. Out of the 47 communities within the TMA, 34 cities had at least one recorded crash during the study period. Norman, Oklahoma City, and Midwest City had the most dangerous intersections. The city of Noble had two intersections that tied for most severe intersection.

Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

The violent crime rate measures the number of Part 1 crimes identified as being violent (homicide, rape, aggravated assault, and robbery) that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police Department Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

This project used a 2019 crimes dataset (crimes which are dangerous to the victims) to create a hotspot map for dangerous crimes in Philadelphia to see the geographic locations that have more violent crime. A hotspot map was also made for shooting victims in Philadelphia to give more weight for fatal crimes. Theoretically, the places where the two of these overlap would be the most dangerous portions of the city. The different census tracts of the city are then enriched to determine where areas of lower income (and therefore lower housing cost) would be. Finally, buffers are created around the University of Pennsylvania, Temple, and La Salle University for evaluating safety.Notable Modules Used: Python: pandas, numpy, matplotlib ArcGIS: create_buffers, find_hot_spots, enrich_layer

From 2013 to 2017, there were 1,466 recorded bicycle and pedestrian crashes. Using the Weighted Severity Index, staff calculated the top 10 most dangerous intersections for bicyclists and pedestrians. Out of the top 10 most dangerous intersections, seven of them were located within Oklahoma City. Two of the intersections were in Moore and one was in Norman.

Dataset

This dataset was created by SEUNGJO2

Contents

This study used crime count data from the Pittsburgh, Pennsylvania, Bureau of Police offense reports and 911 computer-aided dispatch (CAD) calls to determine the best univariate forecast method for crime and to evaluate the value of leading indicator crime forecast models. The researchers used the rolling-horizon experimental design, a design that maximizes the number of forecasts for a given time series at different times and under different conditions. Under this design, several forecast models are used to make alternative forecasts in parallel. For each forecast model included in an experiment, the researchers estimated models on training data, forecasted one month ahead to new data not previously seen by the model, and calculated and saved the forecast error. Then they added the observed value of the previously forecasted data point to the next month's training data, dropped the oldest historical data point, and forecasted the following month's data point. This process continued over a number of months. A total of 15 statistical datasets and 3 geographic information systems (GIS) shapefiles resulted from this study. The statistical datasets consist of Univariate Forecast Data by Police Precinct (Dataset 1) with 3,240 cases Output Data from the Univariate Forecasting Program: Sectors and Forecast Errors (Dataset 2) with 17,892 cases Multivariate, Leading Indicator Forecast Data by Grid Cell (Dataset 3) with 5,940 cases Output Data from the 911 Drug Calls Forecast Program (Dataset 4) with 5,112 cases Output Data from the Part One Property Crimes Forecast Program (Dataset 5) with 5,112 cases Output Data from the Part One Violent Crimes Forecast Program (Dataset 6) with 5,112 cases Input Data for the Regression Forecast Program for 911 Drug Calls (Dataset 7) with 10,011 cases Input Data for the Regression Forecast Program for Part One Property Crimes (Dataset 8) with 10,011 cases Input Data for the Regression Forecast Program for Part One Violent Crimes (Dataset 9) with 10,011 cases Output Data from Regression Forecast Program for 911 Drug Calls: Estimated Coefficients for Leading Indicator Models (Dataset 10) with 36 cases Output Data from Regression Forecast Program for Part One Property Crimes: Estimated Coefficients for Leading Indicator Models (Dataset 11) with 36 cases Output Data from Regression Forecast Program for Part One Violent Crimes: Estimated Coefficients for Leading Indicator Models (Dataset 12) with 36 cases Output Data from Regression Forecast Program for 911 Drug Calls: Forecast Errors (Dataset 13) with 4,936 cases Output Data from Regression Forecast Program for Part One Property Crimes: Forecast Errors (Dataset 14) with 4,936 cases Output Data from Regression Forecast Program for Part One Violent Crimes: Forecast Errors (Dataset 15) with 4,936 cases. The GIS Shapefiles (Dataset 16) are provided with the study in a single zip file: Included are polygon data for the 4,000 foot, square, uniform grid system used for much of the Pittsburgh crime data (grid400); polygon data for the 6 police precincts, alternatively called districts or zones, of Pittsburgh(policedist); and polygon data for the 3 major rivers in Pittsburgh the Allegheny, Monongahela, and Ohio (rivers).

The data are provided are the Maryland Statistical Analysis Center (MSAC), within the Governor's Office of Crime Control and Prevention (GOCCP). MSAC, in turn, receives these data from the Maryland State Police's annual Uniform Crime Reports.

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

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The purpose of this research was to examine the influence of neighborhood social disorganization on the risk of homicide victimization, with focus on how community effects changed once individual-level characteristics were considered. This research integrated concepts from social disorganization theory, a neighborhood theory of criminal behavior, with concepts from lifestyle theory and individual theory of criminal behavior, by having examined the effects of both neighborhood-level predictors of disadvantage and individual attributes which may compel that person to behave in certain ways. The data for this secondary analysis project are from the 2004-2012 National Center for Health Statistics' (NCHS) National Health Interview Survey (NHIS) linked National Death Index-Multiple Causes of Death (MDC) data, which provided individual-level data on homicide mortality. Neighborhood-level (block group) characteristics of disadvantage that existed within each respondent's place of residence from the 2005-2009 and 2008-2012 American Community Surveys were integrated using restricted geographic identifiers from the NHIS. As a syntax-only study, data included as part of this collection includes 38 SAS Program (syntax) files that were used by the researcher in analyses of external restricted-use data. The data are not included because they are restricted archival data from the NHIS from the Centers for Disease Control and Prevention combined with publicly available American Community Survey (ACS) block group level data.