Spatial and spatio-temporal patterns of road traffic accident mortality in Bangladesh, 2022-2024: A district-level geospatial analysis.

OBJECTIVE

Road traffic accidents (RTAs) are a leading cause of injury deaths in Bangladesh, but local geographic patterns remain poorly understood. This study aimed to identify high- and low-risk districts for RTA mortality and track changes from 2022 to 2024 to inform targeted interventions.

METHODS

In this district-level ecological study, we analyzed DGHS official RTA mortality data across all 64 districts. Population-adjusted rates were computed; Moran's I and Getis-Ord Gi* assessed spatial autocorrelation for hotspots/coldspots; SaTScan detected space-time clusters.

RESULTS

Raw counts were randomly distributed, but adjusted rates showed significant dispersion (Moran's I = -0.143, p=0.006 in 2023), with high-risk districts bordering low-risk ones. Persistent northwestern spatial hotspots included Naogaon, Natore, and Bogra. Spatio-temporal analysis identified high-rate clusters in 2024 for Dhaka (RR 6.14, p=0.001) and Rajshahi (RR 10.07, p=0.001), alongside stable low-mortality clusters in northern (RR 0.07) and southern (RR 0.19) regions. Methodological limitations include the use of uniform population projection rates and the ecological design, which precludes causal inference.

CONCLUSION

RTA mortality reflects distinct local epidemics, not a uniform crisis. Geographic disparities support a precision public health approach, with prioritization of high-risk corridors and urban zones for targeted interventions, alongside investigation of protective factors in low-risk clusters.