Human Trafficking Statistics: Human trafficking remains a pervasive global issue, with millions of individuals subjected to exploitation and abuse each year. According to recent statistics, an estimated 25 million people worldwide are victims of human trafficking, with the majority being women and children. This lucrative criminal industry generates profits of over $150 billion annually, making it one of the most profitable illegal trades globally. As market research analysts, it's imperative to understand the scale and impact of human trafficking to develop effective strategies for prevention and intervention. Efforts to combat human trafficking have intensified in recent years, driven by increased awareness and advocacy. However, despite these efforts, the problem persists, with trafficking networks adapting to evade law enforcement and exploit vulnerabilities in communities. Through comprehensive data analysis and research, we can uncover trends, identify high-risk areas, and develop targeted interventions to disrupt trafficking networks and support survivors. In this context, understanding human trafficking statistics is crucial for informing policy decisions, resource allocation, and collaborative efforts to combat this grave violation of human rights. Editor’s Choice Every year, approximately 4.5 billion people become victims of forced sex trafficking. Two out of three immigrants become victims of human trafficking, regardless of their international travel method. There are 5.4 victims of modern slavery for every 1000 people worldwide. An estimated 40.3 million individuals are trapped in modern-day slavery, with 24.9 million in forced labor and 15.4 million in forced marriage. Around 16.55 million reported human trafficking cases have occurred in the Asia Pacific region. Out of 40 million human trafficking victims worldwide, 25% are children. The highest proportion of forced labor trafficking cases occurs in domestic work, accounting for 30%. The illicit earnings from human trafficking amount to approximately USD 150 billion annually. The sex trafficking industry globally exceeds the size of the worldwide cocaine market. Only 0.4% of survivors of human trafficking cases are detected. Currently, there are 49.6 million people in modern slavery worldwide, with 35% being children. Sex trafficking is the most common type of trafficking in the U.S. In 2022, there were 88 million child sexual abuse material (CSAM) files reported to the National Center for Missing and Exploited Children (NCMEC) tip line. Child sex trafficking has been reported in all 50 U.S. states. Human trafficking is a USD 150 billion industry globally. It ranks as the second most profitable illegal industry in the United States. 25 million people worldwide are denied their fundamental right to freedom. 30% of global human trafficking victims are children. Women constitute 49% of all victims of global trafficking. In 2019, 62% of victims in the US were identified as sex trafficking victims. In the same year, US Department of Health and Human Services (HHS) grantees reported that 68% of clients served were victims of labor trafficking. Human traffickers in the US face a maximum statutory penalty of 20 years in prison. In France, 74% of exploited victims in 2018 were victims of sex trafficking. You May Also Like To Read Domestic Violence Statistics Sexual Assault Statistics Crime Statistics FBI Crime Statistics Referral Marketing Statistics Prison Statistics GDPR Statistics Piracy Statistics Notable Ransomware Statistics DDoS Statistics Divorce Statistics

In 2023, a total of ******* victims of human trafficking were identified worldwide, the highest figure recorded during the observed period and an increase of over ****** compared to the previous year. The number of identified victims has risen sharply over the past decade, reflecting a troubling global trend.

In 2023, the highest number of victims of human trafficking was found in South and Central Asia, reaching an estimated **** million victims. The second highest number of victims was found in Europe. Reporting on human trafficking varies from year to year due to the nature of the crime.

Between 2003 and 2022, women were the majority of sex trafficking victims in almost every world region. In Southern Europe, ** percent of people forced to engage in sex against their will were women. Australia and New Zealand was the only region where men constituted a larger share of sex trafficking victims, with ** percent.

This research project developed and fully documented a method to estimate the number of females and males trafficked for the purposes of sexual and labor exploitation from eight countries (Colombia, Ecuador, El Salvador, Guatemala, Mexico, Nicaragua, Peru, and Venezuela) into the United States at the Southwest border. The model utilizes only open source data. This research represents the first phase of a two-phase project and Provides a conceptual framework for identifying potential data sources to estimate the number of victims at different stages in traffickingDevelops statistical models to estimate the number of males and females at risk of being trafficked for sexual and labor exploitation from the eight countries, and the number of males and females actually trafficked for sex and laborIncorporates into the estimation models the transit journey of trafficking victims from the eight countries to the southwest border of the United StatesDesigns the estimation models such that they are highly flexible and modular so that they can evolve as the body of data expands Utilizes open source data as inputs to the statistical model, making the model accessible to anyone interested in using itPresents preliminary estimates that illustrate the use of the statistical methodsIlluminates gaps in data sources. The data included in this collection are the open source data which were primarily used in the models to estimate the number of males and females at risk of being trafficked.

In 2023, a total of ***** human traffickers were convicted worldwide, an increase of approximately ***** compared to the previous year. However, the number of convictions remains lower than levels recorded prior to the COVID-19 pandemic.

What is the Counter-Trafficking Data Collaborative?

The Counter-Trafficking Data Collaborative is the first global data hub on human trafficking, publishing harmonized data from counter-trafficking organizations around the world. Launched in November 2017, the goal of CTDC is to break down information-sharing barriers and equip the counter-trafficking community with up to date, reliable data on human trafficking.

The global victim of trafficking dataset

The CTDC global victim of trafficking dataset is the largest of its kind in the world, and currently exists in two forms. The data are based on case management data, gathered from identified cases of human trafficking, disaggregated at the level of the individual. The cases are recorded in a case management system during the provision of protection and assistance services, or are logged when individuals contact a counter-trafficking hotline. The number of observations in the dataset increases as new records are added by the contributing organizations. The global victim of trafficking dataset that is available to download from the website in csv format has been mathematically anonymized, and the complete, non k-anonymized version of the dataset is displayed throughout the website through visualizations and charts showing detailed analysis.

Where do the data come from?

The data come from a variety of sources. The data featured in the global victim of trafficking dataset come from the assistance activities of the contributing organizations, including from case management services and from counter-trafficking hotline logs.

How are the global datasets created?

Each dataset has been created through a process of comparing and harmonizing existing data models of contributing partners and data classification systems. Initial areas of compatibility were identified to create a unified system for organizing and mapping data to a single standard. Each contributing organization transforms its data to this shared standard and any identifying information is removed before the datasets are made available.

How is the individual-level data protected?

Step 1

Counter-trafficking case data contains highly sensitive information, and maintaining privacy and confidentiality is of paramount importance for CTDC. For example, all explicit identifiers, such as names, were removed from the global victim dataset and some data such as age has been transformed into age ranges. No personally identifying information is transferred to or hosted by CTDC, and organizations that want to contribute are asked to anonymize in accordance to the standards set by CTDC.

Step 2

In addition to the safeguard measures outlined in step 1 the global victim dataset has been anonymized to a higher level, through a mathematical approach called k-anonymization. For a full description of k-anonymization, please refer to the definitions page.

IOM collects and processes data in accordance to its own Data Protection Policy. The other contributors adhere to relevant national and international standards through their policies for collecting and processing personal data.

How to interpret the data?

These data reflect the victims assisted/identified/referred/reported to the contributing organizations, which may not represent all victims identified within a country. Nevertheless, the larger the sample size for a given country (or, the more victims displayed on the map for a given country), the more representative the data are likely to be of the identified victim of trafficking population.

A larger number of identified victims of trafficking does not imply that there is a larger number of undetected victims of trafficking (i.e. a higher prevalence of trafficking).

In addition, samples of identified victims of trafficking cannot be considered random samples of the wider population of victims of trafficking (which includes unidentified victims), since counter-trafficking agencies may be more likely to identify some trafficking cases rather than others. However, with this caveat in mind, the profile of identified victims of trafficking tends to be considered as indicative of the profile of the wider population, given that the availability of other data sources is close to zero.

How does human trafficking case data relate to prevalence data?

There are currently no global or regional estimates of the prevalence of human trafficking. National estimates have been conducted in a few countries but they are also based on modelling of existing administrative data from identified cases and should therefore only be considered as basic baseline estimates. Historically, producing estimates of the prevalence of trafficking based on the collection of new primary data through surveys, for example, has been difficult. This is due to trafficking’s complicated legal definition and the challenges of a...

In 2023, nearly ****** human trafficking prosecutions were reported worldwide, over ************** more than in 2022. However, the figure still fell short of the record set in 2015, when ****** prosecutions were recorded.

This study was conducted to explore the effects prostitution legislation has on sex trafficking rates. This issue holds paramount importance in the fields of legal studies and human rights. By leveraging advanced machine learning techniques to analyze data from the Counter-Trafficking Data Collaborative (CTDC), encompassing 180 countries, this study aims to uncover the relationship between various prostitution legislation types and sex trafficking occurrences. The exploration begins with extensive cleaning, merging, and filtering of the CTDC dataset, integrating it with prostitution legislation data from the World Population Review. This process ensures a harmonized dataset that accurately reflects the global landscape of sex trafficking in relation to legislative frameworks. The machine learning model initially concentrated on prostitution legislation as a key variable but evolved to include a broader range of factors like registration year, population, growth rate, gender, and citizenship. This expansion was crucial in developing a more accurate and holistic model.This study offered a nuanced exploration of the impact of prostitution legislation on sex trafficking, employing sophisticated data analysis and machine learning models to parse through extensive data. The advanced RandomForestClassifier was key in the research, achieving an 87% accuracy rate for predicting instances of sex trafficking and demonstrating the need to incorporate diverse predictive features. Notably, the analysis emphasized the importance of the legislative feature in accurately predicting sex trafficking, despite the inclusion of other variables to improve overall model precision. These findings underscore the significance of a multifaceted approach, considering factors like demographics and socio-economic indicators, to gain a comprehensive understanding of sex trafficking trends.Complementing the machine learning insights, a logistic regression model scrutinized the specific effects of different legislative approaches on sex trafficking. The analysis revealed that legislative frameworks such as legalization, abolitionism, decriminalization, and neo-abolitionism have a considerable influence on reducing sex trafficking rates, suggesting their potential as effective legal strategies. Alternantively, prohibition legislation is found to corrrelate with significantly higher sex trafficking rates. These results serve as a critical resource for policymakers and advocates engaged in the development of informed, evidence-based approaches to address the global challenge of sex trafficking.

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.

Series Name: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number)Series Code: VC_HTF_DETVFLRelease Version: 2021.Q2.G.03 This dataset is 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/

Financial overview and grant giving statistics of Fight Fight Injustice and Global Human Trafficking Inc.

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/

The purpose of this study was to develop and fully document methods to estimate the number of females and males trafficked for the purposes of sexual and labor exploitation from eight countries (Colombia, Ecuador, El Salvador, Guatemala, Mexico, Nicaragua, Peru, and Venezuela) into the United States at the southwest border.

An estimated 30 million people are subject to modernday slavery, including forced labor and sexual exploitation. Moreover, the trafficking of human beings is one of the fastest growing transnational criminal activities. Not only is it an abuse of the human rights of the victims involved, but it also incurs social, political, and economic costs for the countries it most impacts. Providing first an overview of the global phenomenon of modern-day slavery, this paper proceeds to study the Greater Mekong Subregion for whose states human trafficking represents a serious challengeone which requires a well-coordinated response to, among other measures, scrutinize labor contracts in risk economic sectors, enhance interstate cooperation, and more effectively identify and prosecute human traffickers.

license: apache-2.0 tags: - africa - sustainable-development-goals - world-health-organization - development

  Detected victims of human trafficking (per 100 000 population) - Female





  Dataset Description

This dataset provides country-level data for the indicator "16.2.2 Detected victims of human trafficking (per 100 000 population) - Female" across African nations, sourced from the World Health Organization's (WHO) data portal on Sustainable Development Goals… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/detected-victims-of-human-trafficking-female-for-african-countries.

license: apache-2.0 tags: - africa - sustainable-development-goals - world-health-organization - development

  Detected victims of human trafficking for other purposes (per 100 000 population) - Male





  Dataset Description

This dataset provides country-level data for the indicator "16.2.2 Detected victims of human trafficking for other purposes (per 100 000 population) - Male" across African nations, sourced from the World Health Organization's (WHO) data portal on… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/detected-victims-of-human-trafficking-for-other-purposes-mal-for-african-countries.

These datasets contain information on child labor and forced labor worldwide from ILAB’s three flagship reports: Findings on the Worst Forms of Child Labor; List of Goods Produced by Child Labor or Forced Labor ; and List of Products Produced by Forced or Indentured Child Labor. There are 14 tables containing data from the 2015 and 2016 reporting cycle and 11 tables from the 2014 reporting cycle. This information is also available in ILAB’s new app, Sweat & Toil: Child Labor, Forced Labor, and Human Trafficking Around the World. For more information, see ILAB’s International Child Labor and Forced Labor Reports page: http://www.dol.gov/ilab/reports/child-labor/.

Agriculture and farming was the most common industry of work for people trafficked for forced labor worldwide. Nearly 30 percent of the victims were forced to work in this industry. Moreover, 28 percent were working in the fishing industry, meaning that agriculture, forestry, and fishing by far was the most common industry for victims of human trafficking between 2012 and 2020. 40 percent of the trafficking victims in the world were trafficked for forced labor.

Some existing human trafficking research examines how trafficking laws and regulations deter traffickers. This research, however, pays little attention to how states’ freedom of movement policies influences human trafficking. Existing policy debates suggest two possible effects. Europe’s experiences with open borders have led to claims that freedom of movement decreases the likelihood that traffickers are detected, thus making human trafficking in and out of states more likely. By contrast, movement restrictions could create an environment where people become more vulnerable to traffickers. We utilize data from 182 countries from 2001 to 2017 to test whether freedom of movement increases or decreases human trafficking flows. We find that it is necessary, theoretically and empirically, to consider freedom of foreign movement both locally and in a state’s neighborhood because freedom of movement increases human trafficking when the local and neighborhood practices diverge from each other.