Background: Pedestrian and cyclist injuries are a major concern globally, but especially in low-income countries. Locally conducted research is needed to measure the size of the problem and advise policy on road safety interventions. We wanted to investigate the precise circumstances of these injuries in Lilongwe, Malawi and to identify risk factors for severe injuries.

Methods: Cross-sectional study of all adult pedestrian and cyclist injuries presenting to a large central hospital. This was a sub-study of a larger study with all types of road users included. All patients provided detailed information about the incidents leading to injury and were tested for alcohol.

Results: There were 222 pedestrians, 183 bicycle riders and 42 bicycle passengers among the 1259 adult road traffic injury victims that were treated at Kamuzu Central Hospital during a 90-day period in 2019. Of these injuries, 60.2% occurred while the victim was walking/cycling along the road and 22.3% when the victim was trying to cross the road. The majority of the victims were men (89.1%). Helmet use for bicyclists was almost non-existent. Only 1 patient had used reflective devices when injured in the dark, despite 44.7% of these injuries occurring in reduced light conditions. There was an increased risk for serious and fatal injuries for pedestrians compared with bicyclists, and also compared with all types of road users. Patients injured in rural areas and those hit by lorries were more severely injured. Consuming alcohol before being injured was associated with more severe injuries in bicyclists. Being injured while crossing the road at painted zebra crossings was associated with an increased risk of serious and potentially fatal injuries.

Conclusion: This study identified important risk factors for severe injuries in pedestrians and cyclists. Implications for preventive measures are presented in a Haddon Matrix.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364799PMC
http://dx.doi.org/10.4314/mmj.v32i4.4DOI Listing

Publication Analysis

Top Keywords

pedestrian cyclist
12
cyclist injuries
12
injuries
9
adult pedestrian
8
injuries lilongwe
8
lilongwe malawi
8
cross-sectional study
8
risk factors
8
factors severe
8
central hospital
8

Similar Publications

Conflict resolution behavior of autonomous vehicles at intersections under mixed traffic environment.

Accid Anal Prev

March 2025

Department of Civil and Environmental Engineering, Michigan State University, Lansing, MI 48910, USA. Electronic address:

Navigating intersections is a major challenge for autonomous vehicles (AVs) because of the complex interactions between different roadway user types, conflicting movements, and diverse operational and geometric features. This study investigated intersection-related AV-involved traffic conflicts by analyzing the Arogoverse-2 motion forecasting dataset to understand the driving behavior of AVs at intersections. The conflict scenarios were categorized into AV-involved and no AV conflict scenarios.

View Article and Find Full Text PDF

Assessing e-scooter rider safety perceptions in shared spaces: Evidence from a video experiment in Sweden.

Accid Anal Prev

March 2025

Civil Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom. Electronic address:

Shared spaces prioritise the role of micromobility in urban environments by separating vulnerable road users from motorised vehicles, aiming to enhance both actual and perceived safety. However, the presence of various transport modes, such as pedestrians, cyclists and e-scooters, with differing navigation behaviours, increases the heterogeneity of these spaces and impacts the perception of safety. Despite the increasing use of e-scooters, the safety perceptions of e-scooter riders remain largely underexplored in the literature.

View Article and Find Full Text PDF

Existing 3D object detection frameworks in sensor-based applications heavily rely on large-scale annotated data to achieve optimal performance. However, obtaining such annotations from sensor data-like LiDAR or image sensors-is both time-consuming and costly. Semi-supervised learning offers an efficient solution to this challenge and holds significant potential for sensor-driven artificial intelligence (AI) applications.

View Article and Find Full Text PDF

Background: China has the highest number of road injury deaths in the world. The aim of this study was to determine the long-term incidence and mortality trends of road injuries in China between 1990 and 2019 and to make projections up to 2030.

Methods: Incident and death data were extracted from the Global Burden of Disease (GBD) 2019 study and population data were extracted from the GBD 2019 and World Population Prospects 2019 studies.

View Article and Find Full Text PDF

Objective: Understanding and modeling baseline driving safety risk in dense urban areas represents a crucial starting point for automated driving system (ADS) safety impact analysis. The purpose of this study was to leverage naturalistic vulnerable road user (VRU) collision data to quantify collision rates, crash severity, and injury risk distributions in the absence of objective injury outcome data.

Methods: From over 500 million vehicle miles traveled, a total of 335 collision events involving VRUs were video verified and reconstructed (126 pedestrians, 144 cyclists, and 65 motorcyclists).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!