Global synthetic dataset analysis
Victim demographics
Trafficked persons in the Global Synthetic Dataset
From 2002 to 2022, the Counter Trafficking Data Collaborative (CTDC) partners recorded data on over 206,000 victims.[1] These data reflect the characteristics of the victims who are assisted, identified, referred, and/or reported to the contributing organisations, as well as details relating to their experience. The data are mainly collected through case management processes and hotlines.
Female victims, which represent about 74 per cent of victims, are registered around three times more frequently than males.[2] Around 43 per cent of trafficked persons are adults between 18 and 29 years of age. Adults are more frequently registered than children, who represent about 24 per cent of victims.
As regions of origin, Europe and Asia comprise 34 and 32 per cent of the victims, respectively, followed by the Americas and Africa, which together account for about 34 per cent. Most victims originate in Eastern Europe, Southeast Asia, North and Central America, and West Africa, comprising approximately 82 per cent of the registered victims. The remainder of the victims predominantly originate in other sub-regions of Asia and Africa.
Trafficked persons from Oceania constitute a very small proportion of victims, although this does not necessarily indicate a low prevalence of human trafficking in the region but may reflect the absence of viable data on this crime.
[1] This data story focuses on victims’ demographic profiles. Click here to delve into the types of exploitation, means of control, and regions of exploitation.
[2] The CTDC partners acknowledge diverse gender identities and expressions among trafficking victims; however, sex assigned at birth has been used for this data analysis unless otherwise indicated. This is to ensure consistency with initial data collection forms, which lacked fields for diverse identities. Also, the disclosure of smaller subsets of victims with diverse gender identities increases data protection risks due to the potential identification of individual cases.