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Estimation of death counts and associated standard errors is of greatimportance in armed conflict such as the ongoing violence in Syria, as well ashistorical conflicts in Guatemala, Per\'u, Colombia, Timor Leste, and Kosovo.For example, statistical estimates of death counts were cited as importantevidence in the trial of General Efra\'in R\'ios Montt for acts of genocide inGuatemala. Estimation relies on both record linkage and multiple systemsestimation. A key first step in this process is identifying ways to partitionthe records such that they are computationally manageable. This step isreferred to as blocking and is a major challenge for the Syrian database sinceit is sparse in the number of duplicate records and feature poor in itsattributes. As a consequence, we propose locality sensitive hashing (LSH)methods to overcome these challenges. We demonstrate the computationalsuperiority and error rates of these methods by comparing our proposed approachwith others in the literature. We conclude with a discussion of many challengesof merging LSH with record linkage to achieve an estimate of the number ofuniquely documented deaths in the Syrian conflict.

Blocking Methods Applied to Casualty Records from the Syrian Conflict