No abstract

We present an ecosystem approach to analyze open‐source data to identify populations vulnerable to human trafficking and to reveal underlying causal relationships. In the case of Bangladesh, our analysis suggests combinations of indicators that are highly predictive of human trafficking. The traditional narrative that poverty and unemployment are the main drivers for human trafficking may be an oversimplification. We find many areas where vulnerability is highest within lower‐middle to middle‐class societies with (a) moderate levels of income and education, (b) adherence to traditional gender norms of a male‐dominated patriarchal society, and (c) access to an urban center.