A Partially Pooled NSUM Model: Detailed estimation of CSEM trafficking prevalence in Philippine municipalities

TL;DR

This paper presents a hierarchical Bayesian partially pooled NSUM model that improves estimation of CSEM trafficking prevalence at the municipal level in the Philippines, enabling more precise and resource-efficient policy planning.

Contribution

It introduces a novel partially pooled NSUM model that aggregates data across regions without increasing sample sizes, enhancing prevalence estimation accuracy.

Findings

Accurately estimated municipal-level CSEM trafficking prevalence in the Philippines.

Demonstrated the model's efficiency and precision over traditional methods.

Highlighted potential applications in social science and public health research.

Abstract

Effective policy and intervention strategies to combat human trafficking for child sexual exploitation material (CSEM) production require accurate prevalence estimates. Traditional Network Scale Up Method (NSUM) models often necessitate standalone surveys for each geographic region, escalating costs and complexity. This study introduces a partially pooled NSUM model, using a hierarchical Bayesian framework that efficiently aggregates and utilizes data across multiple regions without increasing sample sizes. We developed this model for a novel national survey dataset from the Philippines and we demonstrate its ability to produce detailed municipal-level prevalence estimates of trafficking for CSEM production. Our results not only underscore the model's precision in estimating hidden populations but also highlight its potential for broader application in other areas of social science and public health research, offering significant implications for resource allocation and intervention planning.