Enhancing Forced Displacement Simulations: Integrating Health Facilities for Automatically Generated Routes Networks

Abstract

This paper introduces a novel approach to supporting healthcare accessibility for refugees during their movement to camps in regions with limited infrastructure. We achieve this by integrating the density of healthcare facilities into route networks created by customized pruning algorithms. Through rigorous data analysis and algorithm development, our research aims to optimize healthcare delivery routes and enhance healthcare outcomes for displaced populations. Our findings highlight Visit Tracking route pruning as the most effective method, with an Averaged Relative Difference (ARD) of 0.3837. Particularly in scenarios involving healthcare facility integration, this method outperforms others, including the manual extracted route network (0.4902), Direct Distance pruning (0.3912), Triangle pruning (0.3913), and Sequential Distance pruning (0.7846). Despite the inherent limitations of our proposed method, such as data availability and computational complexity, these quantifiable results underscore its potential contributions to healthcare planning, policy development, and humanitarian assistance efforts worldwide.