Estimating the burden of road traffic crashes in Uganda using police and health sector data sources.

burden of disease descriptive epidemiology motor vehicle - non traffic

Journal

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
ISSN: 1475-5785
Titre abrégé: Inj Prev
Pays: England
ID NLM: 9510056

Informations de publication

Date de publication:
30 Mar 2020
Historique:
received: 14 01 2020
revised: 09 03 2020
accepted: 14 03 2020
entrez: 2 4 2020
pubmed: 2 4 2020
medline: 2 4 2020
Statut: aheadofprint

Résumé

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). 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. 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%). Using both police and health sector data gives more robust estimates for the road traffic burden in Uganda than using either source alone.

Sections du résumé

BACKGROUND 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 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 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 CONCLUSIONS
Using both police and health sector data gives more robust estimates for the road traffic burden in Uganda than using either source alone.

Identifiants

pubmed: 32229535
pii: injuryprev-2020-043654
doi: 10.1136/injuryprev-2020-043654
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Kennedy Maring Muni (KM)

Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA maring.muni@gmail.com.

Albert Ningwa (A)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Jimmy Osuret (J)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Esther Bayiga Zziwa (EB)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Stellah Namatovu (S)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Claire Biribawa (C)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Mary Nakafeero (M)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Milton Mutto (M)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

David Guwatudde (D)

Department of Epidemiology & Biostatistics, Makerere School of Public Health, Kampala, Uganda.

Patrick Kyamanywa (P)

School of Health Sciences, Kampala International University, Bushenyi, Uganda.

Olive Kobusingye (O)

Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda.

Classifications MeSH