有限制图区域的小区域分析方法:海地太子港火器伤害的探索性地理空间分析。

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International Journal of Health Geographics Pub Date : 2023-08-18 DOI:10.1186/s12942-023-00337-4
Athanasios Burlotos, Tayana Jean Pierre, Walter Johnson, Seth Wiafe, Michelle Joseph
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引用次数: 0

摘要

背景:海地太子港市正在经历枪支伤害的流行,造成了很高的发病率和死亡率。尽管如此,关于这个话题的科学文献很少。地理空间研究可为利益攸关方提供信息,并有助于应对当前的火器伤害流行病。然而,传统的小区域地理空间方法难以在太子港实施,因为该地区的测绘渗透率有限。本研究的目的是评估太子港地理空间分析的可行性,试图了解在此背景下地理空间研究的具体局限性,并探索在太子港最大的公立医院就诊的患者火器伤害的地理空间流行病学。结果:为了克服有限的映射渗透率,将多个数据源组合在一起。非正式开发社区的边界由众包平台OpenStreetMap使用Thiessen多边形估算。人口统计是根据先前公布的卫星估算数据得出的,并汇总到社区一级。2019年11月22日至2020年12月31日期间在太子港最大的公立医院就诊的枪支伤害病例进行了地理编码,并汇总到社区一级。使用Global Moran’s I测试、local Moran’s I测试和SaTScan软件进行聚类分析。结果表明,城市内火器伤害风险具有显著的地理空间自相关性。聚类分析确定了该市枪支伤害负担最高的地区。结论:通过采用新颖的邻域估算方法并结合多种数据来源,可以在太子港进行地理空间研究。确定了枪支伤害的地理空间集群,并获得了社区水平的相对风险估计。虽然进入遭受枪支伤害负担最重的社区仍然受到限制,但这些地理空间方法可以继续为利益攸关方提供信息,以应对太子港日益严重的枪支伤害负担。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Small area analysis methods in an area of limited mapping: exploratory geospatial analysis of firearm injuries in Port-au-Prince, Haiti.

Background: The city of Port-au-Prince, Haiti, is experiencing an epidemic of firearm injuries which has resulted in high burdens of morbidity and mortality. Despite this, little scientific literature exists on the topic. Geospatial research could inform stakeholders and aid in the response to the current firearm injury epidemic. However, traditional small-area geospatial methods are difficult to implement in Port-au-Prince, as the area has limited mapping penetration. Objectives of this study were to evaluate the feasibility of geospatial analysis in Port-au-Prince, to seek to understand specific limitations to geospatial research in this context, and to explore the geospatial epidemiology of firearm injuries in patients presenting to the largest public hospital in Port-au-Prince.

Results: To overcome limited mapping penetration, multiple data sources were combined. Boundaries of informally developed neighborhoods were estimated from the crowd-sourced platform OpenStreetMap using Thiessen polygons. Population counts were obtained from previously published satellite-derived estimates and aggregated to the neighborhood level. Cases of firearm injuries presenting to the largest public hospital in Port-au-Prince from November 22nd, 2019, through December 31st, 2020, were geocoded and aggregated to the neighborhood level. Cluster analysis was performed using Global Moran's I testing, local Moran's I testing, and the SaTScan software. Results demonstrated significant geospatial autocorrelation in the risk of firearm injury within the city. Cluster analysis identified areas of the city with the highest burden of firearm injuries.

Conclusions: By utilizing novel methodology in neighborhood estimation and combining multiple data sources, geospatial research was able to be conducted in Port-au-Prince. Geospatial clusters of firearm injuries were identified, and neighborhood level relative-risk estimates were obtained. While access to neighborhoods experiencing the largest burden of firearm injuries remains restricted, these geospatial methods could continue to inform stakeholder response to the growing burden of firearm injuries in Port-au-Prince.

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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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