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A two-stage cluster sampling method using gridded population data, a GIS, and Google EarthTM imagery in a population-based mortality survey in Iraq

机译:在伊拉克基于人口的死亡率调查中,使用网格化人口数据,GIS和Google Earth TM 图像进行的两阶段整群抽样方法

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Background Mortality estimates can measure and monitor the impacts of conflict on a population, guide humanitarian efforts, and help to better understand the public health impacts of conflict. Vital statistics registration and surveillance systems are rarely functional in conflict settings, posing a challenge of estimating mortality using retrospective population-based surveys. Results We present a two-stage cluster sampling method for application in population-based mortality surveys. The sampling method utilizes gridded population data and a geographic information system (GIS) to select clusters in the first sampling stage and Google Earth TM imagery and sampling grids to select households in the second sampling stage. The sampling method is implemented in a household mortality study in Iraq in 2011. Factors affecting feasibility and methodological quality are described. Conclusion Sampling is a challenge in retrospective population-based mortality studies and alternatives that improve on the conventional approaches are needed. The sampling strategy presented here was designed to generate a representative sample of the Iraqi population while reducing the potential for bias and considering the context specific challenges of the study setting. This sampling strategy, or variations on it, are adaptable and should be considered and tested in other conflict settings.
机译:背景死亡率估计数可以衡量和监测冲突对人口的影响,指导人道主义工作,并有助于更好地了解冲突对公共健康的影响。生命统计登记和监视系统很少在冲突环境中起作用,这对使用基于人群的回顾性调查估算死亡率构成了挑战。结果我们提出了一种两阶段的整群抽样方法,用于基于人口的死亡率调查。采样方法利用网格化的人口数据和地理信息系统(GIS)在第一采样阶段选择聚类,并利用Google Earth TM图像和采样网格在第二采样阶段选择住户。该采样方法于2011年在伊拉克进行的家庭死亡率研究中实施。描述了影响可行性和方法质量的因素。结论在基于人群的回顾性死亡率研究中,抽样是一个挑战,需要在常规方法上进行改进的替代方法。本文介绍的抽样策略旨在生成具有代表性的伊拉克人口样本,同时减少产生偏见的可能性,并考虑研究环境的具体挑战。这种采样策略或其上的变体具有适应性,应在其他冲突环境中进行考虑和测试。

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