Kennedy Maring Muni 1 , Albert Ningwa 2 , Jimmy Osuret 2 , Esther Bayiga Zziwa 2 , Stellah Namatovu 2 , Claire Biribawa 2 , Mary Nakafeero 2 , Milton Mutto 2 , David Guwatudde 3 , Patrick Kyamanywa 4 , Olive Kobusingye 2 Show Affiliations »
Abstract
BACKGROUND: In many low-income countries, estimates of road injury burden are derived from police reports, and may not represent the complete picture of the burden in these countries. As a result, WHO and the Global Burden of Diseases, Injuries and Risk Factors Project often use complex models to generate country-specific estimates. Although such estimates inform prevention targets, they may be limited by the incompleteness of the data and the assumptions used in the models. In this cross-sectional study, we provide an alternative approach to estimating road traffic injury burden for Uganda for the year 2016 using data from multiple data sources (the police, health facilities and mortuaries). METHODS: A digitised data collection tool was used to extract crash and injury information from files in 32 police stations, 31 health facilities and 4 mortuaries in Uganda. We estimated crash and injury burden using weights generated as inverse of the product of the probabilities of selection of police regions and stations. RESULTS: We estimated that 25 729 crashes occurred on Ugandan roads in 2016, involving 59 077 individuals with 7558 fatalities. This is more than twice the number of fatalities reported by the police for 2016 (3502) but lower than the estimate from the 2018 Global Status Report (12 036). Pedestrians accounted for the greatest proportion of the fatalities 2455 (32.5%), followed by motorcyclists 1357 (18%). CONCLUSIONS: Using both police and health sector data gives more robust estimates for the road traffic burden in Uganda than using either source alone. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.
BACKGROUND: In many low-income countries, estimates of road injury burden are derived from police reports, and may not represent the complete picture of the burden in these countries. As a result, WHO and the Global Burden of Diseases, Injuries and Risk Factors Project often use complex models to generate country-specific estimates. Although such estimates inform prevention targets, they may be limited by the incompleteness of the data and the assumptions used in the models. In this cross-sectional study, we provide an alternative approach to estimating road traffic injury burden for Uganda for the year 2016 using data from multiple data sources (the police, health facilities and mortuaries). METHODS: A digitised data collection tool was used to extract crash and injury information from files in 32 police stations, 31 health facilities and 4 mortuaries in Uganda. We estimated crash and injury burden using weights generated as inverse of the product of the probabilities of selection of police regions and stations. RESULTS: We estimated that 25 729 crashes occurred on Ugandan roads in 2016, involving 59 077 individuals with 7558 fatalities. This is more than twice the number of fatalities reported by the police for 2016 (3502) but lower than the estimate from the 2018 Global Status Report (12 036). Pedestrians accounted for the greatest proportion of the fatalities 2455 (32.5%), followed by motorcyclists 1357 (18%). CONCLUSIONS: Using both police and health sector data gives more robust estimates for the road traffic burden in Uganda than using either source alone. © Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.
Keywords:
burden of disease; descriptive epidemiology; motor vehicle - non traffic
Year: 2020
PMID： 32229535 DOI： 10.1136/injuryprev-2020-043654
Source DB: PubMed Journal: Inj Prev ISSN： 1353-8047 Impact factor: 2.399