Blog | Treating human trafficking like a preventable disease: an approach towards more informed migration policy

December 19, 2018

By Francisca Sassetti, Visiting Research Assistant, UNU-CS

The Southeast Asia region has some of the highest rates of population mobility in the world, which are deeply connected to labor migration. The migration phenomenon seems to amplify as economic and political differences deepen between countries in the region. Differences in income, living standards and access to healthcare, made countries like Singapore, Malaysia and Thailand attractive destinations for migrant workers. For instance, in Thailand, the minimum daily wage is three times higher than in Myanmar. In conjunction with the increase of demand of low-skilled labor, this allowed for the rise of exploitative working conditions. Migrants leave their countries hoping for better working conditions, but some end up being trapped in human trafficking and exploitation [1].

According to the Global Slavery Index 2016, there are an estimated of 25 million people in situations of forced labor. When looking into the distribution per region, 1 in every 3 victims are in East Asia and the Pacific. Within Southeast Asia, Thailand is the main destination for victims of human trafficking coming from Cambodia, Lao P. D. R, and Myanmar.

Figure 1. Regional prevalence of forced labor in 2016        
Source: International Labor Organization (ILO) and Walk Free Foundation. 2017. Global Estimates of Modern Slavery: Forced Labor and Forced Marriage. Geneva.

For as much as these figures are shocking, these only represent estimates of the global and regional prevalence of human trafficking. Because human trafficking is largely underreported and unidentified – aggravated by the fact that victims are reluctant to come forward due to intimidation and fear of reprisals – data availability and accuracy are big challenges in fighting the problem [2]. Reports and studies don’t use standardized methodologies or common definitions for human trafficking beyond sex trafficking or sexual exploitation that is inclusive of forced labor. With such uncertainty surrounding the real magnitude of human trafficking, some authors question the actual value of such macro-level research data to inform policy [2]. Yet the biggest challenge to creating efficient policy to tackle human trafficking is the lack of availability of comprehensive data [8]

Furthermore, the reality in human trafficking, and more broadly labor exploitation, is very complex because it represents a continuum of experiences and situations that range from consensual and cooperative relationships to highly coercive and exploitative conditions [2] [4]. Skȓivánková’s continuum of exploitation allows to understand the range of situations that violate principles of decent work between the extremes of decent work and forced labor [4]. What starts as acceptable work for a migrant worker can progressively deteriorate into forced labor [2]. The continuum of exploitation leads to the forced labor as the most serious form of violation, in which the human trafficking process is the means to an end of forced labor [4]. The International Labor Organization (ILO)  developed the Indicators of Forced Labor in an attempt to capture this complex reality. A combination of indicators in a situation can suggest the existence of forced labor upon the assessment of the case of the individual worker, such as deception, intimidation and threats and debt bondage. These indicators are meant not only to help frontline responders (FLRs) with the identification of workers in situations of forced labor, but also reflect the variety of experiences within the continuum of exploitation. Although physical violence used to be a key indicator of forced labor, patterns of exploitation have changed to include more psychological coercion and debt bondage. Using the metaphor of a chameleon, exploitation has the stealthy ability to change its shapes and patterns [4]; it’s often camouflaged in psychological coercion such as deception, discrimination, constant threats to personal safety, and sexual harassment and abuse. But just because we don’t see it, it doesn’t mean it’s not there.

Yet the current approach towards identifying victims of human trafficking and labor exploitation relies on passive surveillance by surveillance sites, where there isn’t any active search for cases of victims. Passive surveillance is commonly used to detect vaccine-preventable diseases and relies on passive notification by local staff. Because the data is not consistently collected, and the surveillance sites aren’t carefully selected and monitored, this approach can miss out on key trends and patterns in the population. Not only is the data from macro-level research flawed – that serves as foundation for migration and development policies – but it results in ill-conceived approaches that rely on passive surveillance and consequently inefficient identification mechanisms [3]. Often a government’s initial response to trafficking is controlling migration instead of promoting safe migration through the protection of the rights of migrants.

As noted by Zimmerman, we find human trafficking and labor exploitation as public health issues with global magnitude [5]. In order to overcome the limitations of sound data availability and identification of initiatives in the current approach to fighting these issues, innovative and efficient solutions to inform policy are required. By adopting a sentinel surveillance approach, our research focuses on how technology can be used for the identification of victims of labor exploitation and human trafficking. Sentinel surveillance monitors the occurrence of specific conditions in the health level of a population overtime to detect any changes, and it’s often used to study disease rates in high-risk groups/cohorts, such as HIV or STDs, which are preventable. It’s relevant for cases where high-quality data are required about a disease that cannot be obtained through a passive system. But can treating human trafficking and labor exploitation like preventable diseases lead to more informed migration policy?

The identification of an HIV victim is just as imperceptible to the naked eye as today’s patterns of exploitation in human trafficking, which cannot be detected by only physical evidence. The invisible chains that bind victims into slavery can take the forms of psychological coercion, such as deception, discrimination, constant threats to personal safety, and sexual harassment and abuse [6]. That is why our research employs an active surveillance approach towards human trafficking and forced labor, that has proven to be successful in identifying HIV victims through the observation of high-risk groups in Thailand [7]. In human trafficking, these high-risk groups are migrant workers in the Thai fishing industry where there is high demand for low skilled workers to perform the so-called 3D jobs – dirty, dangerous and demeaning. Although the number of trafficked Thai workers has decreased, migrant workers coming from the Mekong River region are replacing them as victims.

Furthermore, we developed Apprise, a mobile application to support the identification of victims of trafficking and that we are currently piloting in Thailand. Although Apprise is installed on the FLR’s mobile phone, it’s a tool in the hands of the potential victim. The worker answers directly and privately in the app to an audio questionnaire where they can report exploitative work practices, which will then be used to develop a vulnerability rating, displaying any indicators of exploitation. The worker can also request help from the FLR if they wish.

We argue that, by using sentinel surveillance – responsible for successful health policies especially in identifying and reducing the incidence of HIV in high-risk populations – treating human trafficking and exploitation like a preventable disease can help overcome problems such as data uncertainty and quality and improve victim-identification mechanisms. We believe that not only Apprise has the potential to improve the identification of victims of human trafficking and forced labor, but also to help understand the chameleon of exploitation and the varied continuum of experiences and abuses that migrant workers are vulnerable to. Apprise can also provide high quality data through micro-level research to inform migration policy that can target and help groups of high-risk of exploitation, such as migrant workers.

To know more about Apprise, please visit https://cs.unu.edu/research/migrant-tech-apprise/
To know more about the migrant tech research project, please visit https://cs.unu.edu/research/migrant-tech/

Sources:

  • [1] Benach, J. et al.: Migration and “Low-Skilled” Workers in Destination Countries. PLOS Medicine. 8, 6, e1001043 (2011).
  • [2] Weitzer, R.: New Directions in Research on Human Trafficking. The ANNALS of the American Academy of Political and Social Science. 653, 1, 6–24 (2014).
  • [3] Feingold, D.: Trafficking in Numbers: The Social Construction of Human Trafficking Data. In: Andreas, P. and Greenhill, K.M. (eds.) Sex, Drugs and Body Counts: The Politics of Numbers in Global Crime and Conflict. pp. 46–74 Cornell University Press, Ithaca (2010).
  • [4] Skȓivánková, K.: Between decent work and forced labour: examining the continuum of exploitation. Joseph Rowntree Foundation, York, UK (2010).
  • [5] Zimmerman, C., Kiss, L.: Human trafficking and exploitation: A global health concern. PLOS Medicine. 14, 11, e1002437 (2017).
  • [6] Hopper E., Hidalgo J: Invisible Chains: Psychological Coercion of Human Trafficking Victims. Intercultural Human Rights Law Review 1: 185 (2006).
  • [7]Frericks, R., Ungchusak, K., Htoon, M., Detels, R.: HIV Sentinel Surveillance in Thailand – An Example for Developing Countries. Asia-Pacific Journal of Public Health Vol. 8 No. I, Los Angeles, USA (1995).
  • [8] UNODC, 2017. Trafficking in persons from Cambodia, Lao PDR and Myanmar to Thailand. Retrieved on November 15, 2018 from here.

Blog posts on this site reflects the views of respective authors in their individual capacities and not the views of UNU/UNU-CS.

Photo: Charloisporto/Pixabay

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