| Popis: |
Background: Traffic accidents (TA) are one of the leading causes of mortality in Saudi Arabia. Despite the state efforts to combat this issue, a dearth of knowledge on TA's spatial and temporal patterns in Saudi Arabia is present.This study aims to detect significant Spatio-temporal TA casualties' hotspots to increase the understanding of moralities and injuries' trends.Methods: We used machine-learning models to detect the significant temporal anomalies in casualties. Afterwards, we performed spatial analysis (Local Moran's I, Getis-Ord Gi*) to detect Spatio-temporal hotspot in casualties.Results: TA casualties are steadily declining. However, annual spikes in the month of Ramadan are present. Spatial analysis suggests that TA casualties are associated with population count and location. Urban centers have higher casualties due to high population count. Aggregating TA casualties per capita shows that these regions have in reality the lowest rates of casualties, and rural regions in the north are more impacted by TA. |
