Objective: To estimate the prevalence of helmet use among riders and pillion riders of motorcycles in the Tamale Metropolis of Ghana.Methods: Cross-sectional observations of helmet use were made at locations where traffic generally slowed down. Statistical analysis was carried out for variables by calculating chi-square (χ 2 ) tests to assess statistical significance.Results: A total of 3115 riders and 1058 pillion riders (passengers) were observed at 10 different sites. The overall helmet use for riders was 34.2 percent and that for pillion riders was 1.9 percent. Riders' helmet use rate was highest among the elderly (49.6%), followed by adults (34.3%) and lowest for young people (21.9%) and the observed percentage differences were significant (χ 2(2) = 67.1; p < .001). A marked difference (χ 2 (1) = 6.7; p = .0096) in helmet use was observed between riders riding within the central business district (CBD; 36.5%) and those outside the CBD (32.1%). Riders with at least one pillion rider (27.4%) were less likely to wear a helmet compared to riders riding alone without passengers (37.3%; χ 2(1) = 29.347; p < .001).Conclusion: Helmet use by motorcyclists in Ghana is generally low. There is a need for public awareness campaigns on the safety benefits of helmets to increase its prevalence in Ghana. The education on helmet use must be accompanied by sustained enforcement of the road traffic law by the traffic police to ensure compliance and change in attitudes.

We conducted an observational survey of seat belt use to determine the use rate of drivers and front-right passengers of vehicles in Kumasi, Ghana. Unobtrusive observations of seat belt use were made at 41 locations composed of signalized intersections and roundabouts where vehicles come to a halt or slow down considerably. The overall driver seat belt use rate was 17.6% compared to 4.9% for front-right passengers. Driver belt use was 33.2% for private cars, 9.0% for taxis, 8.3% for minibus (trotro), 13.1% for large buses and 9.7% for trucks. Overall seat belt use was higher for female drivers than for male drivers (44.8% versus 16.4%, p < .001), was lowest within the Central Business District (CBD) compared to the outskirts of the city (16.3% versus 21.0%, p < .001) and seat belt use rate increased with age. Passengers belted more often if drivers were belted, but about three-quarters of male passengers and 70-80% of female passengers were unbelted even when drivers were belted. In conclusion, the seat belt use rate was generally low in Kumasi, Ghana, and it is a function of occupant seating position, gender, vehicle type and usage, age group, and location setting. The results provide important preliminary data about seat belt use, particularly among male drivers and commercial vehicle occupant population. The study also suggests the need to develop effective strategies and programs that address low seat belt use in Ghana.

Crash Prediction Models (CPMs) have been used elsewhere as a useful tool by road Engineers and Planners.There is however no study on the prediction of road traffic crashes on rural highways in Ghana. The main objective of the study was to develop a prediction model for road traffic crashes occurring on the rural sections of the highways in the Ashanti Region of Ghana. The model was developed for all injury crashes occurring on selected rural highways in the Region over the three (3) year period 2005-2007. Data was collected from 76 rural highway sections and each section varied between 0.8 km and 6.7 km. Data collected for each section comprised injury crash data, traffic flow and speed data, and roadway characteristics and road geometry data. The Generalised Linear Model (GLM) with Negative Binomial (NB) error structure was used to estimate the model parameters. Two types of models, the 'core' model which included key exposure variables only and the 'full' model which included a wider range of variables were developed. The results show that traffic flow, highway segment length, junction density, terrain type and presence of a village settlement within road segments were found to be statistically significant explanatory variables (p b 0.05) for crash involvement. Adding one junction to a 1 km section of road segment was found to increase injury crashes by 32.0% and sections which had a village settlement within them were found to increase injury crashes by 60.3% compared with segments with no settlements. The model explained 61.2% of the systematic variation in the data. Road and Traffic Engineers and Planners can apply the crash prediction model as a tool in safety improvement works and in the design of safer roads. It is recommended that to improve safety, highways should be designed to by-pass village settlements and that the number of junctions on a highway should be limited to carefully designed ones.

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Having reliable estimates of the shortfalls in road traffic crash data is an important prerequisite for setting more realistic targets for crash/casualty reduction programmes and for a better appreciation of the socio-economic significance of road traffic crashes. This study was carried out to establish realistic estimates of the overall shortfall (under-reporting) in the official crash statistics in Ghana over an eight-year period (1997-2004). Surveys were conducted at hospitals and among drivers to generate relevant alternative data which were then matched against records in police crash data files and the official database. Overall shortfalls came from two sources, namely, 'non-reporting' and 'under-recording'. The results show that the level of non-reporting varied significantly with the severity of the crash from about 57% for property damage crashes through 8% for serious injury crashes to 0% for fatal crashes. Crashes involving cyclists and motorcyclists were also substantially non-reported. Under-recording on the other hand declined significantly over the period from an average of 37% in 1997-1998 to 27% in 2003-2004. Thus, the official statistics of road traffic crashes in Ghana are subject to significant shortfalls that need to be accounted for. Correction factors have therefore been suggested for adjusting the official data.