Road injuries, labor productivity, and economic growth in Africa: A panel study

Background and Aims

Globally, millions of people suffer from road injuries, with Africa having the highest burden of road injury deaths. This public health problem has the potential to reduce labor productivity and hence hamper economic growth, especially on the African continent. This study, to the best of the authors' knowledge, therefore seeks to provide the first empirical evidence of the interaction or combined effect of road injuries and labor productivity on economic growth in African countries.

Methods

The study uses annual data on 45 African countries over the period, 2002 to 2019. The dynamic panel system generalized method of moments regression is used as the estimation technique.

Results

The findings show that the interaction of road injuries with labor productivity has a negative significant effect on economic growth in both the short-run (coefficient: -1.96, p < 0.01) and long-run (coefficient: -1.93, p < 0.01) periods.

Conclusion

There is a need to increase investment in road safety to reduce the prevalence of road injuries on the African continent.

Assessment of knowledge, attitude and practice of first aid among taxi operators in a Kampala City Taxi Park, Uganda: A cross-sectional study

INTRODUCTION

Road traffic accidents are among the leading causes of death in Uganda. Taxi operators are at a high risk of RTA and can potentially be first responders. This study, aimed to assess knowledge, attitude, and practice of first aid among taxi operators in the new taxi park, Kampala Uganda.

METHODS

A descriptive cross-sectional study was conducted in 2021 among taxi drivers and conductors in the New Taxi Park, Kampala City, Uganda. A semi-structured questionnaire was used to collect quantitative data from taxi operators after informed consent. Chi-square or Fisher's exact test and logistic regression were performed in STATA 16 to assess the association between first aid knowledge and demographics. P < 0.05 was statistically significant.

RESULTS

A total of 345 participants, majority males (n = 338, 98%) aged between 18 and 45 years (76.5%), were recruited. Although 97.7% (n = 337) had heard about first aid, only 19.4% (n = 67) had prior first aid training. Overall mean knowledge score was 40.1% (SD = 14.5%), with 29.9% (n = 103) having good knowledge (≥50%). Participants who had witnessed more than five accidents (aOR = 2.9, 95% CI = 1.7-4.8, p < 0.001), those with first aid kits (aOR = 1.7, 95% CI = 1.0-3.0, p = 0.38) were more likely to have good knowledge while those below post-secondary education level i.e., Primary (AOR = 0.2, 95% CI = 0.1-0.5, p ≤0.001) and secondary (aOR = 0.2, 95% CI = 0.1-0.6, p = 0.001), were less likely to have good knowledge. About 97% and 93% perceived first aid as important and were willing to undergo training, respectively; however, only 69% were willing to give first aid. Only 181(52.5%) had ever attended to accident victims.

CONCLUSION

Majority of taxi operators had poor first aid knowledge. Factors associated with good knowledge included level of education, number of accidents witnessed, having first aid kits. Although their attitudes were favorable, practice was poor. Comprehensive training and refresher courses can help increase first aid knowledge, and improving practice.

Spatial differentiation of road safety in Europe based on NUTS-2 regions

Road safety varies significantly across the regions in Europe. To understand the factors behind this differentiation and the effects they have, data covering 263 NUTS-2 (Nomenclature of Territorial Units for Statistics) regions across Europe (European Union and Norway) have been analysed. The assessment was made using Geographically Weighted Regression (GWR). As a dependent variable the Road Fatality Rate (RFR - number of fatalities in a given year per one million population of the region) was used. The GWR was developed from 2014 data and took account of variables that characterise economic, infrastructural and social development. The model was validated using 2016-2018 data. The following factors were found to be statistically significant: gross domestic product per person (GDPPC), number of passenger cars per inhabitant (MRPC), share of passenger vehicles (PPC), life expectancy at birth (LIFE), as well as variables related to the border of the regions, innerborder (IB) and outerborder (OB). Results suggest that the GWR has an advantage over the global linear model which does not address regional proximity. The model allows for identification of the differences in the level of road safety in regions, estimated on the basis of the RFR and the available data in Eurostat databases. This in turn allows for indicating regions in which activities to improve road safety should have the highest priority. The model shows a large spatial diversity of factors affecting the RFR, which indicates the need to take different actions to improve road safety depending on the region. The results suggest that the GWR model can be useful for predicting and more efficient management of road safety at the regional level in Europe.