Data Availability for Road Crash Valuation in Low- and Middle-Income Countries: A Case Study in Uganda

Road traffic crash valuation is essential for understanding the economic and social impacts of road safety, especially in low- and middle-income countries (LMICs) where data constraints hinder effective policymaking. This study aims to enhance the understanding of data requirements for road safety valuation in LMICs, using Uganda as a case study. Due to the absence of a unified crash database, secondary data were collected through institutional reports, interviews with key personnel, and referrals to access unpublished datasets. This study examines key cost components for effective valuation and explores three main methods: Restitution Cost, Human Capital, and Willingness-to-Pay, highlighting their data requirements and constraints in the LMIC context. It identifies existing data sources, evaluates their accessibility and relevance, and maps stakeholders involved in data collection and management. Despite challenges such as fragmented data and underreporting, this study underscores the importance of accurate crash valuation for evidence-based policymaking and resource allocation. The findings offer actionable recommendations to improve data collection, integration, and accessibility, highlighting the need for unified databases and standardised terminologies. By addressing these gaps, Uganda and other LMICs can reduce road crash impacts, enhance safety outcomes, and foster sustainable socio-economic development, contributing to global road safety efforts.