School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, Texas, USA.
School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, Texas, USA
BMJ Glob Health. 2023 May;8(5). doi: 10.1136/bmjgh-2023-012315.
While efforts to understand and mitigate road traffic injury (RTI) occurrence have long been underway in high-income countries, similar projects in low/middle-income countries (LMICs) are frequently hindered by institutional and informational obstacles. Technological advances in geospatial analysis provide a pathway to overcome a subset of these barriers, and in doing so enable researchers to create actionable insights in the pursuit of mitigating RTI-associated negative health outcomes. This analysis develops a parallel geocoding workflow to improve investigation of low-fidelity datasets common in LMICs. Subsequently, this workflow is applied to and evaluated on an RTI dataset from Lagos State, Nigeria, minimising positional error in geocoding by incorporating outputs from four commercially available geocoders. The concordance between outputs from these geocoders is evaluated, and spatial visualisations are generated to provide insight into the distribution of RTI occurrence within the analysis region. This study highlights the implications of geospatial data analysis in LMICs facilitated by modern technologies on health resource allocation, and ultimately, patient outcomes.
尽管高收入国家长期以来一直在努力了解和减轻道路交通伤害（RTI）的发生，但类似的低/中收入国家（LMICs）项目经常受到制度和信息障碍的阻碍。地理空间分析技术的进步为克服其中一部分障碍提供了途径，使研究人员能够在追求减轻与 RTI 相关的负面健康结果方面创造可行的见解。本分析开发了一种并行地理编码工作流程，以改进对 LMIC 中常见的低保真数据集的调查。随后，该工作流程应用于并在来自尼日利亚拉各斯州的 RTI 数据集上进行了评估，通过整合来自四个商业地理编码器的输出，最大限度地减少地理编码中的位置误差。评估这些地理编码器输出之间的一致性，并生成空间可视化，以深入了解分析区域内 RTI 发生的分布情况。本研究强调了现代技术促进的 LMIC 中地理空间数据分析对卫生资源分配的影响，最终对患者的治疗结果产生影响。
