Examining the Conflict-Related Predictors and Spatiotemporal Dynamics of Attacks Against Humanitarian Assistance

Abstract

Around the world, attacks against humanitarian aid workers pose a pervasive and intransigent threat to health and human rights, but evidence about the complex factors that predict perpetrators' behavior as well as attack outcomes remains quite limited. While previous studies have addressed several aspects of local and global trends of attacks against humanitarian assistance, more evidence is also needed to understand the dynamics of recurrent incidents, small-scale attacks, as well as patterns of events across time and space; and how the observed trends are driven by conflict-related and contextual factors. In this dissertation, we investigate the predictors and spatiotemporal dynamics of attacks against humanitarian assistance from 1997 to 2022 using publicly-available datasets from the Aid Worker Security Database (AWSD, Humanitarian Outcomes, 2022) and the Armed Conflict Dataset version 22.0 (ACD; Glaeditsch et al., 2002; Davies et al., 2022).