In 2022, ** percent of all reported human trafficking victims were trafficked for sexual exploitation, a substantial decline compared to the ** to ** percent range reported in most years between 2008 and 2018. Since 2011, approximately ** percent of victims have consistently been trafficked for forced labor.

In 2020, men made up the majority of people convicted for human trafficking in every world region except two. The most notable exception was Central Asia, where ** percent were women. The other exception was East Asia and the Pacific, where ** percent were women.

Since 2004, a higher share of the victims of trafficking are men and children. While around ***** in **** of the victims in 2004 were women, the share had fallen to less than ** percent in 2022. By comparison, the share of victims who were men had increased by *** percentage points. Moreover, ** percent of the trafficking victims were children.

Between 2017 and 2020, most of the detected victims of human trafficking in the world were found within their own country. This was the case for 60 percent of the victims in 2020. Moreover, nearly 20 percent were detected within the same region, while 16 percent were trafficked to another region not nearby.

The number of human trafficking cases decreased in Peru in 2020. From ***** cases registered between January and November of 2018, the number of reported crimes fell to *** in the first nine months of 2020. In the year of the onset of COVID-19, this could be a result of the quarantine restrictions imposed or due to underreporting. In 2017, almost ***** human trafficking cases were brought to the Peruvian authorities.

Series Name: Detected victims of human trafficking for other purposes by age and sex (number)Series Code: VC_HTF_DETVOPRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 16.2.2: Number of victims of human trafficking per 100,000 population, by sex, age and form of exploitationTarget 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of childrenGoal 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levelsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Sociodemographic profile of victims in the period 2010–2020 (n = 87003).

Series Name: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number)Series Code: VC_HTF_DETVFLRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 16.2.2: Number of victims of human trafficking per 100,000 population, by sex, age and form of exploitationTarget 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of childrenGoal 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levelsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

In 2023, ** percent of labor traffickers in the United States forced their victims to work in agriculture. The most common industry for labor trafficking was domestic work, with ** percent of cases in 2020.

A large majority of the human trafficking victims trafficked for forced sexual exploitation were women. In total, more than ** percent of the detected victims in 2022 were either women or girls. On the other hand, around ** percent of those trafficked for forced labor were men.

A table showing the number of complaints and measures taken against owners of offices specialized in employing domestic workers for the year 2020 A table showing the number of cases related to human trafficking for the year 2020 A table showing the number of non-Jordanian workers that have been seized and the appropriate action taken against them for the year 2020 A table showing the measures taken to combat child labor for the year 2020 A table showing the number of labor complaints received by the Ministry of Labor for the year 2020

The Department of Justice Canada has contracted community-based research to better understand the lives of individuals involved in the sex trade. The former 2014 legislation, Bill C-36, the Protection of Communities and Exploited Persons Act, also known as the “Nordic” model or approach, targets purchasers of sexual services and third parties who profit from others’ sexual services. Under this legislation, providers of sexual services are not criminalized, but are instead viewed as requiring support and not punishment (Department of Justice Canada 2014). With this important distinction at the forefront of this approach, the Measures Addressing Prostitution Initiative (MAPI) was created to aid sexual service providers to exit the sex trade. This program received multi-year funding from 2015-2016 to 2020-2021. A major aspect of this initiative was to provide funding to organizations within the not-for-profit sector to support individuals within the sex trade with wrap-around services, such as housing, healthcare, therapy, addictions treatment, family reunification, and life skills programs. The 2022 publication of A Review of the Measures to Address Prostitution Initiative (MAPI) (Badets and Wichmann 2022) was based on data collected by the thirteen (13) organizations that provided support services. The data collected included basic demographics, services used, and some outcomes. While the report provides some information on people seeking support from these organizations, there remains a lack of qualitative data about the lives of sexual service providers. Voice Found was one of the thirteen (13) organizations that received funding from MAPI; and this charity has a mandate to provide services to those who are at risk of, who have been, or who are being trafficked. This includes both sex and labour trafficking, but for the scope of this research, only survivors of sex trafficking were included. The data collected by Voice Found provides many insights into the lives of their clients at the time of first being trafficked, during trafficking, their experiences as they exited, and what has helped or may have helped them through this time. The intention of this project was to provide a more complete picture of the why and how of both entering and exiting sex trafficking.

As of August 2020, ** percent of countries had specific legislation on trafficking in persons that covered most or all forms of trafficking. This is a huge increase from December 2003, when only ** percent of countries offered such legislation.

In 2020 and 2021, the number of minors who were victims of trafficking decreased significantly. This is probably due to the restrictions imposed by the coronavirus (COVID-19) pandemic, which also affected the number of administrative controls carried out. In 2023, there were 8 victims, compared to 12 in 2022.

There are significant regional differences concerning the forms of exploitation of victims of human trafficking in the world. In 2022, ** percent of the trafficking victims in Sub-Saharan Africa were trafficked for forced labor. In Central America and the Caribbean, more than ** percent were trafficked for sexual exploitation.

In Belgium, the Federal Police registers a steady number of human trafficking cases. Around ********************* cases are reported each year. In 2022, *** human trafficking cases were registered, and 126 economic trafficking cases were registered in Belgium in 2020. In comparison, the neighboring country of the Netherlands registered *** human trafficking cases in 2021.

Human trafficking under Belgian law

Human trafficking refers to the exploitation of individuals for profit. Exploitation covers prostitution, infantile pornography, begging, organ harvesting, forced crime, and forced labor. Confusion is often made between human trafficking, illegal immigration, and smuggling. The latter describes the act of aiding the illegal entry of a person into a country.

An international consensus on the definition of human trafficking was crucial due to this confusion. Thus, the European Union and the United Nations found common ground: Besides exploitation, human trafficking’s definition today rests on two other key elements: acts and means. Acts can be recruiting, transporting, transferring or housing. Whereas means refer to threats, violence, constraint, and deceit. In 2005, Belgium adapted its law to reflect this consensus.

Belgium compromises protecting the victims and fighting criminal organizations. The country offers victim protection in return for their collaboration with the authorities. For this, reporting the offense is mandatory.

Victims of human trafficking in Belgium

Since the early ‘90s, Belgium delivers a residency permit to human trafficking victims. For this, the victim must withdraw from exploitation and attend support centers. Three centers specialize in welcoming and supporting victims. They provide psychological and medical care, administrative help, and legal advice. These centers are in the three big Belgian cities: Brussels, Antwerp, and Liège. Placement in a secret location shelter is also offered when needed.

The first set of data is secondary data on child exploitation in Zimbabwe that the project collected from the NGO partner, CLZ. The data was collected through a 24 hour helpline and is in the form of summaries of the conversations held with the individuals who called CLZ to report cases of child abuse and exploitation. The second set of data is secondary data that we collected from our NGO partner organisation, LJI. This is based on the organisation’s human trafficking interception work in Zimbabwe, which involves placing monitors at strategic transit points to identify and stop trafficking as it occurs.

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

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 dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow 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.

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: All businesses identified as victims in CPD data have been removed from this dataset.

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.”

Note: In some instances, the police department'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 recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

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.

This CSV of 2020 Part 1 crime data contains data for multiple police departments in St. Louis County. Data is included for each precinct within St. Louis County as well as all areas that the St. Louis County Police Department and the St. Louis County Park Rangers patrol. Additionally, data is included for the following police departments in St. Louis County: Ballwin, Bel Nor, Bel Ridge, Bella Villa, Bellefontaine Neighbors, Breckenridge Hills, Brentwood, Country Club Hills, Chesterfield, Clayton, Crestwood, Creve Coeur, Des Peres, Ellisville, Eureka, Frontenac, Hillsdale, Kirkwood, Ladue, Lakeshire, Moline Acres, Maplewood, Normandy, Olivette, Overland (starting in March 2020), Pagedale, Riverview, Richmond Heights, Rock Hill, Saint Louis County, Shrewsbury, St. John, Sunset Hills, Town & Country, Velda City, Webster Groves, and Woodson Terrace.The Part 1 Crimes included in this file are homicide/non-negligent manslaughter, rape, robbery, aggravated assault, burglary, larceny, motor vehicle theft. Arson and human trafficking are not included in the 2020 data file.Included columns:UCRCOUNT: Coded as 1 or -1. 1 indicates a crime that was reported during the given month, and the -1 refers to any crime that was subtracted or unfounded from a previous reporting period. COMPLAINTYEAR: Year of the complaintCOMPLAINTNUM: departmental complaint numberUCR_OFFENSE: string of the UCR crimeUCR_CRIME_CODE: number code that corresponds to the UCR offenseTYPE: Person=homicide, robbery, aggravated assault, and rape. Property=burglary, larceny, and motor vehicle theftMONTH: The month that the crime data was submitted to the State of Missouri.YEAR: Year data was submitted to the State of MissouriDT_CALLREC: Date and time that the call for the crime was receivedD_OCCURRED: date that the crime occurredDOW_OCCURRED: day of the week that the crime occurredZONE: geographical zone where the crime occurredADDRESS: address of the crime, excluded for rapes and human trafficking casesPRECINCT: The precinct where the crime occurred. For St. Louis County PD: North County Precinct, Central County Precinct, Affton Southwest Precinct, South County Precinct, City of Fenton Precinct, City of Wildwood Precinct, West County Precinct, City of Jennings Precinct, MetroLink Police Unit. For Ellisville PD: East and West.PREMISE: The premise of the crime (eg. residential, business, etc.)REPORTING_JURIS: The jurisdiction that reported this data to the State of Missouri (Saint Louis County Parks data is reported by Saint Louis County).FOR_JURIS: The jurisdiction the data is for. This will either be a municipality name, MetroLink, or Saint Louis County.X: Longitude. If UCRCOUNT=-1 this field is blank. Additionally, if address is redacted this field will be blank.Y: Latitude: If UCRCOUNT=-1 this field is blank. Additionally, if address is redacted this field will be blank.

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