Road Traffic Injury on Rural Roads in Tanzania: Measuring the Effectiveness of a Road Safety Program

Objective: Road traffic injuries (RTIs) are a major public health burden, especially in low- and middle-income countries. There is limited data on RTIs in low-volume, rural African settings. This study attempted to survey all individuals living in households within 200 m of two low-volume rural roads in Tanzania and to collect data on RTIs. Methods: Local communities and users of the Bago to Talawanda road (intervention site) and Kikaro to Mihuga road (control site) were targeted and received an intensive program of road safety measures tailored using the crash characteristics of the baseline sample. Demographic data on all household members were collected, and those individuals who suffered an RTI in the previous 3 months had comprehensive information collected about the crash characteristics and the socioeconomic impact. The follow-up data collection occurred nine months after the baseline data were collected. Results: The majority of crashes that caused an RTI involved a motorcycle (71%) and the majority of victims were male (82%) with an average age of 27. Injuries to the legs (55%) were most common and the average length of time away from normal activity was 27 (±33) days. RTI incidence at the intervention site increased during the course of the study (incidence before vs. incidence after) and was unchanged in the community control (incidence before vs. incidence after). Conclusion: The incidence of RTIs in the low-volume rural setting is unacceptably high and most commonly associated with motorcycles. The change in incidence is unreliable due to logistic restraints of the project and more research is needed to quantify the impact of various RTI prevention strategies in this setting. This study provides insight into road traffic injuries on low-volume rural roads, areas where very little research has been captured. Additionally, it provides a replicable study design for those interested in collecting similar data on low-volume rural roads.