Innovative Methods for Estimating the Prevalence of Labor Trafficking: A Comparison of Time-Location and Network Sampling Studies on a Construction Worker Population

Accurate measurements of HIV prevalence and associated risk factors among hidden and high-risk groups are vital for program planning and implementation. However, only two sampling methods are purported to provide representative estimates for populations without sampling frames: time-location sampling (TLS) and respondent-driven sampling (RDS). Each method is subject to potential biases and questionable reliability. In this paper, we evaluate surveys designed to estimate HIV prevalence and associated risk factors among people who inject drugs (PWID) sampled through TLS versus RDS. In 2012, males aged ≥16years who reported injecting drugs in the previous month and living in Haiphong, Vietnam, were sampled using TLS or RDS. Data from each survey were analyzed to compare HIV prevalence, related risk factors, socio-demographic characteristics, refusal estimates, and time and expenditures for field implementation. TLS (n = 432) and RDS (n = 415) produced similarly high estimates for HIV prevalence. Significantly lower proportions of PWID sampled through RDS received methadone treatment or met an outreach worker. Refusal estimates were lower for TLS than for RDS. Total expenditures per sample collected and number of person-days of staff effort were higher for TLS than for RDS. Both survey methods were successful in recruiting a diverse sample of PWID in Haiphong. In Vietnam, surveys of PWID are conducted throughout the country; although the refusal estimate was calculated to be much higher for RDS than TLS, RDS in Haiphong appeared to sample PWID with less exposure to services and required fewer financial and staff resources compared with TLS.

In this paper, I discuss some of the wider uses of adaptive and network sampling designs. Three uses of sampling designs are to select units from a population to make inferences about population values, to select units to use in an experiment, and to distribute interventions to benefit a population. The most useful approaches for inference from adaptively selected samples are design-based methods and Bayesian methods. Adaptive link-tracing network sampling methods are important for sampling populations that are otherwise hard to reach. Sampling in changing populations involves temporal network or spatial sampling design processes with units selected both into and out of the sample over time. Averaging or smoothing fast-moving versions of these designs provides simple estimates of network-related characteristics. The effectiveness of intervention programs to benefit populations depends a great deal on the sampling and assignment designs used in spreading the intervention.

This article reports on the perceptions and experiences with labor trafficking of farmworkers, stakeholders, and law enforcement representatives in North Carolina. We found a sizeable number of farmworkers who had experienced labor trafficking violations, albeit with a convenience sample; and community agencies reported stories of labor trafficking victimization. However, most of the state and local law enforcement agencies that we attempted to contact simply ignored our requests for information about labor trafficking or reported no evidence of such victimization. Notwithstanding the sample limitations, we found a general lack of awareness of agricultural labor trafficking problems among law enforcement officials in our surveyed jurisdictions. We question whether our current law enforcement system will ever be in a position to effectively enforce the anti-labor-trafficking law; and suggest an alternative specialized mechanism be established.

The construction industry appears to experience high rates of labor trafficking and other labor exploitation. Additionally, anecdotal evidence suggests that workplace abuses and exploitation are particularly common among construction workers who work in recovery and reconstruction work in post-natural disaster settings. This study, part of a larger study focused on estimating the prevalence of labor trafficking among construction workers in Houston, explores whether there is a difference in the rate of experiencing labor trafficking among construction workers who have worked in post-disaster settings from those who have not. This study finds that the rate of lifetime labor trafficking prevalence among workers with post-disaster experience is more than twice that of construction workers who have not worked in these settings. We explore differences in the types of exploitation reported between these groups and differences of individual and employment characteristics between workers who have and have not worked in post-disaster environments.

Human trafficking is a hidden domestic and international problem of unknown numbers and unsubstantiated estimates. Most research on labor trafficking has focused on known cases through conducting stakeholder interviews and reviewing police and court case files. This limited prior research suggests that demographic characteristics and level of acculturation may impact one’s risk for labor trafficking victimization. However, these relationships have not been consistently demonstrated. The current research explores two primary research questions: (1) how prevalent is labor trafficking and other labor exploitation among farmworkers in North Carolina; and (2) do individual-level characteristics or circumstances place a person at greater risk of labor trafficking or other labor exploitation. This was accomplished by conducting 380 inperson interviews with migrant farmworkers in North Carolina. We used three strategies to identify migrant farmworkers: (1) attendance at community events; (2) lists of labor camps known to advocacy organizations; and (3) other public venues farmworkers visit. Based on descriptive statistics and a logistic regression analysis, we present results on the extent of farmworker abuse and exploitation, and discuss future research in this area.

Introduction - Antonela Arhin and Ato Quayson Foreword: Corporate Liability for Violations of International Human Rights Law - Mohamed Y. Mattar 1. Trafficking for Labour Exploitation: Getting the Responses Right - Roger Plant 2. The Commodification of Human Smuggling and Trafficking - Louise Shelley 3. Child Labour Migrants or Victims of Labour Trafficking: A Segmental Approach - Antonela Arhin 4. Displacing Childhood: Labour Exploitation and Child Trafficking in Sport - Darragh McGee 5. Labor Migration, Human Trafficking and Multinational Corporations within the ECOWAS Region: challenges and opportunities - Ndioro Ndiaye 6. Adults or Children? The Case of Trafficking of Children for Purposes of Exploitative Labour in the Fishing Industry in Ghana - Daniel Kweku Sam 7. Doing Canada's Dirty Work: A Critical Analysis of Law and Policy to Address Labour Exploitation Trafficking - Bethany Hastie 8. Minimum Wage -An Ally in the Fight Against Human Trafficking for Labour Exploitation? - Anne Pawletta and Philipp Schwertmann 9. Responding to Labour Trafficking: Suggestions from Experiences of Local Service Providers - Amy Stevens, Romesh Hettiarachchi and Sung Hyun Yun 10. The Programmatic Approach to combating Trafficking in Human Beings - Ruud Hilgers

Time-location sampling (TLS), also called time-space sampling or venue-based sampling is a sampling technique widely used in populations at high risk of infectious diseases. The principle is to reach individuals in places and at times where they gather. For example, men who have sex with men meet in gay venues at certain times of the day, and homeless people or drug users come together to take advantage of services provided to them (accommodation, care, meals). The statistical analysis of data coming from TLS surveys has been comprehensively discussed in the literature. Two issues of particular importance are the inclusion or not of sampling weights and how to deal with the frequency of venue attendance (FVA) of individuals during the course of the survey. The objective of this article is to present TLS in the context of sampling theory, to calculate sampling weights and to propose design-based inference taking into account the FVA. The properties of an estimator ignoring the FVA and of the design-based estimator are assessed and contrasted both through a simulation study and using real data from a recent cross-sectional survey conducted in France among drug users. We show that the estimators of prevalence or a total can be strongly biased if the FVA is ignored, while the design-based estimator taking FVA into account is unbiased even when declarative errors occur in the FVA.

Conditional estimation of exponential random graph models from snowball sampling designs

Research on human trafficking faces many challenges, one of which is the lack of consistent measurement. Although there have been efforts throughout the world to collect primary data, researchers have not come close to finding a common set of measures that can be applied consistently in counting trafficking activities or victimization experiences. The development of a common data-collection instrument, especially one that is appealing to researchers in different countries, is no easy task. The authors present one such example in this article, for all to comment on and improve. This instrument, created a few years ago in an empirical study on labour trafficking in the United States of America, is intended for use in large-scale surveys by persons engaged in research or gathering data for estimating prevalence. The instrument has received excellent empirical validation, including item response analysis, and has been adopted in a few other studies. While the instrument is still in need of improvement, the authors would like to publicize their efforts so that others may draw lessons from and build upon what has been accomplished. Although individual circumstances may vary, human trafficking shares sufficient commonalities to allow standardized measurement. A common instrument is a crucial step towards meaningful international or cross-regional comparison, which is sorely missing in the current policy discourse on human trafficking.

Ecological interaction networks are a valuable approach to understanding plant-pollinator interactions at the community level. Highly structured daily activity patterns are a feature of the biology of many flower visitors, particularly provisioning female bees, which often visit different floral sources at different times. Such temporal structure implies that presence/absence and relative abundance of specific flower-visitor interactions (links) in interaction networks may be highly sensitive to the daily timing of data collection. Further, relative timing of interactions is central to their possible role in competition or facilitation of seed set among coflowering plants sharing pollinators. To date, however, no study has examined the network impacts of daily temporal variation in visitor activity at a community scale. Here we use temporally structured sampling to examine the consequences of daily activity patterns upon network properties using fully quantified flower-visitor interaction data for a Kenyan savanna habitat. Interactions were sampled at four sequential three-hour time intervals between 06:00 and 18:00, across multiple seasonal time points for two sampling sites. In all data sets the richness and relative abundance of links depended critically on when during the day visitation was observed. Permutation-based null modeling revealed significant temporal structure across daily time intervals at three of the four seasonal time points, driven primarily by patterns in bee activity. This sensitivity of network structure shows the need to consider daily time in network sampling design, both to maximize the probability of sampling links relevant to plant reproductive success and to facilitate appropriate interpretation of interspecific relationships. Our data also suggest that daily structuring at a community level could reduce indirect competitive interactions when coflowering plants share pollinators, as is commonly observed during flowering in highly seasonal habitats.

Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently the case, for example, in the monitoring and study of massive, online social networks. We study the problem of how to estimate the degree distribution - an object of fundamental interest - of a true underlying network from its sampled network. In particular, we show that this problem can be formulated as an inverse problem. Playing a key role in this formulation is a matrix relating the expectation of our sampled degree distribution to the true underlying degree distribution. Under many network sampling designs, this matrix can be defined entirely in terms of the design and is found to be ill-conditioned. As a result, our inverse problem frequently is ill-posed. Accordingly, we offer a constrained, penalized weighted least-squares approach to solving this problem. A Monte Carlo variant of Stein's unbiased risk estimation (SURE) is used to select the penalization parameter. We explore the behavior of our resulting estimator of network degree distribution in simulation, using a variety of combinations of network models and sampling regimes. In addition, we demonstrate the ability of our method to accurately reconstruct the degree distributions of various sub-communities within online social networks corresponding to Friendster, Orkut and LiveJournal. Overall, our results show that the true degree distributions from both homogeneous and inhomogeneous networks can be recovered with substantially greater accuracy than reflected in the empirical degree distribution resulting from the original sampling.

Diabetic patients' surveys have to deal with the lack of proper formal sampling frames. For survey researches at the community level, often some partial sampling frames such as medical centres or households to which a person is linked are available. These frames can be used to draw a network sample. At a selected household, the adult occupants are asked to report on the occurrence of the characteristics not only in them but also in their siblings. Using this network sampling design, the total number of people with diabetics can be estimated with lower variance than conventional procedures. The design is illustrated by an analysis of the network data of Nafiu (2007) in a survey to estimate the population of diabetic patients in Niger State, Nigeria. Two estimators: Hansen-Hurwitz estimator and Horvitz-Thompson estimator were considered; and the results were obtained using a program written in Microsoft Visual C++ programming language. Keywords: Graph, Sampling Frame, Households, Hansen-Hurwitz estimator and Horvitz-Thompson estimatorJORIND Vol. 5 (2) 2007: pp. 2-2

To assess the feeding practices and behaviors of women and young children participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), USDA currently funds the longitudinal WIC Infant and Toddler Feeding Practices Study-2 (WIC ITFPS-2). In 2013, the study used time-location sampling (TLS) to enroll a cohort of infants who participated in WIC around birth. The children are subsequently followed across their first six years of life, regardless of their participation in WIC, with an additional follow-up at age nine years. A woman may enroll her child in WIC either during pregnancy or postpartum. For this study, a representative sample of infants enrolled in WIC was desired. Because the associations between WIC prenatal support and education and feeding practices and behaviors are substantively important to this study, the sample needed to include both women enrolling their children prenatally and women enrolling their children postnatally. For prenatal WIC enrollees, we attempted to complete a prenatal interview with the mother prior to the child's birth. This paper describes the TLS approach used and the challenges addressed in implementation of the sample design and selection for the WIC ITFPS-2. Our approach generated a probability sample (subject to site geographic and size exclusions) using a stratified, multistage design, but there were challenges at each stage of selection. First, a WIC site was selected, and then newly enrolled WIC participants were sampled within selected sites during predetermined recruitment windows based on the site's average flow of new WIC enrollees. We discuss issues faced, including overcoming incomplete lists of individual WIC sites and discrepancies between projected new WIC enrollment counts and actual flow of new WIC enrollments during the recruitment period.

A state-wide analysis of characteristics and predictors of dual system involvement among child victims of human trafficking

The current academic discourse examining human trafficking is lacking in focus on survivors with a disability. The increased likelihood of abuse experienced by people with a disability is well documented in the research literature, and a small body of research indicates heightened sex trafficking victimization of minor girls with a disability. Yet, very little research specifically examines sex and/or labor trafficking of people with a disability, and no systematic research analyzes prosecuted cases of trafficking with disability as the focal point of analysis. Drawing from a content analysis of 18 federal and 17 state cases of human trafficking, the current study specifically aimed to increase our understandings of sex and labor trafficking involving survivors with a disability. The findings revealed the following patterns and themes: 1) the type of trafficking experienced (sex, labor, or both), 2) whether state level or federal cases 3) the types of disabilities identified among trafficking survivors, 4) the nature of the relationship between traffickers and survivors, 5) methods of recruitment, 6) case outcomes; and 7) demographic characteristics of traffickers and survivors (e.g., gender/citizenship). Implications include prevention efforts in the form of developmentally grounded sex education and healthy relationships curriculum for survivors with an intellectual disability, as well as specialized anti-trafficking training for those in legal, healthcare, and social services that is inclusive of people with a disability.