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让牧民“被看见”:用于游牧人群健康监测的地理空间方法。

Making Pastoralists Count: Geospatial Methods for the Health Surveillance of Nomadic Populations.

机构信息

Stanford University School of Medicine, Stanford, California.

Department of Anthropology, Pennsylvania State University.

出版信息

Am J Trop Med Hyg. 2019 Sep;101(3):661-669. doi: 10.4269/ajtmh.18-1009.

DOI:10.4269/ajtmh.18-1009
PMID:31436151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6726942/
Abstract

Nomadic pastoralists are among the world's hardest-to-reach and least served populations. Pastoralist communities are difficult to capture in household surveys because of factors including their high degree of mobility over remote terrain, fluid domestic arrangements, and cultural barriers. Most surveys use census-based sampling frames which do not accurately capture the demographic and health parameters of nomadic populations. As a result, pastoralists are "invisible" in population data such as the Demographic and Health Surveys (DHS). By combining remote sensing and geospatial analysis, we developed a sampling strategy designed to capture the current distribution of nomadic populations. We then implemented this sampling frame to survey a population of mobile pastoralists in southwest Ethiopia, focusing on maternal and child health (MCH) indicators. Using standardized instruments from DHS questionnaires, we draw comparisons with regional and national data finding disparities with DHS data in core MCH indicators, including vaccination coverage, skilled birth attendance, and nutritional status. Our field validation demonstrates that this method is a logistically feasible alternative to conventional sampling frames and may be used at the population level. Geospatial sampling methods provide cost-affordable and logistically feasible strategies for sampling mobile populations, a crucial first step toward reaching these groups with health services.

摘要

游牧民是世界上最难接触和服务最少的人群之一。由于其在偏远地区高度流动、家庭安排灵活以及文化障碍等因素,牧民社区很难在家庭调查中被捕捉到。大多数调查使用基于人口普查的抽样框架,这些框架无法准确捕捉游牧人口的人口和健康参数。因此,在人口数据(如人口与健康调查 (DHS))中,游牧民是“看不见的”。通过将遥感和地理空间分析相结合,我们开发了一种抽样策略,旨在捕捉游牧人口的当前分布情况。然后,我们实施了这个抽样框架来调查埃塞俄比亚西南部的一个流动牧民群体,重点关注母婴健康 (MCH) 指标。我们使用 DHS 问卷中的标准化工具,与区域和国家数据进行比较,发现核心 MCH 指标与 DHS 数据存在差异,包括疫苗接种覆盖率、熟练接生率和营养状况。我们的实地验证表明,这种方法是对传统抽样框架的可行替代方案,并且可以在人口层面上使用。地理空间抽样方法为抽样流动人口提供了经济实惠且可行的策略,这是向这些群体提供卫生服务的关键第一步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/776e07386595/tpmd181009f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/8f30cd61e4a1/tpmd181009f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/90cfa99f20fd/tpmd181009f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/776e07386595/tpmd181009f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/8f30cd61e4a1/tpmd181009f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/90cfa99f20fd/tpmd181009f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c64/6726942/776e07386595/tpmd181009f3.jpg

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