A spatial autocorrelation analysis of road traffic accidents by severity using Moran's I spatial statistics: a study from Nepal 2019-2022

基于莫兰指数空间统计量的道路交通事故严重程度空间自相关性分析:一项来自尼泊尔2019-2022年的研究

阅读:1

Abstract

BACKGROUND: Road traffic accidents (RTAs) are a significant global public health issue, leading to injuries, fatalities, and substantial economic losses. In Nepal, RTAs are a major concern, with notable regional variations in incidence and severity. This study analyzed the spatial distribution and types of road traffic injuries in Nepal from Fiscal Year (FY) 2019-2020 to 2021-2022, focusing on the impact of road types and geographic factors. METHODS: The study covers all 77 districts of Nepal, incorporating diverse geographic and climatic regions. Data on RTAs, including fatal and non-fatal injuries, were obtained from the Kathmandu Valley Traffic Police Office, Nepal. Spatial analysis was conducted using Quantum GIS (QGIS) and GeoDa software. Univariate and bivariate risk factor analyses were performed using Moran's I statistics to detect spatial autocorrelation in RTA severity. RESULTS: The overall fatality rate increased from 7.70 to 9.89 per 100,000 population from FY 2019-2020 to 2021-2022. However, spatial clustering of crashes showed a decline over the years. In FY 2019-2020 (Moran's I; 0.276, p-value; 0.001), moderate clustering was observed, which weakened in the subsequent years (Moran's I; 0.127, p-value; 0.002), with a near-random distribution by FY 2021-2022 (Moran's I; -0.015, p-value; 0.457). The analysis of crash severity revealed significant variations across districts, with high fatality rates in remote areas like Mustang and Mugu, and low rates in districts such as Manang. ROAD NETWORK ANALYSIS: The study examined the impact of different road types on RTA severity. Bitumen (BT) roads showed a negative correlation with RTA rates, while Earthen Roads (ER) were positively associated with higher RTA rates. Hot-spot and cold-spot clusters were identified for each road type, highlighting higher or lower RTA severity areas. CONCLUSION: This study provides valuable insights into the spatial patterns of RTAs in Nepal and the influence of road types on accident severity. The findings emphasize the need for targeted road safety interventions and infrastructure improvements, particularly in high-risk areas. By understanding spatial distributions and road network impacts, policymakers can better address road safety challenges and reduce the incidence of RTAs in Nepal.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。