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Estimating the burden of road traffic crashes in Uganda using police and health sector data sources
  1. Kennedy Maring Muni1,
  2. Albert Ningwa2,
  3. Jimmy Osuret2,
  4. Esther Bayiga Zziwa2,
  5. Stellah Namatovu2,
  6. Claire Biribawa2,
  7. Mary Nakafeero2,
  8. Milton Mutto2,
  9. David Guwatudde3,
  10. Patrick Kyamanywa4,
  11. Olive Kobusingye2
  1. 1Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA
  2. 2Department of Disease Control and Environmental Health, Makerere University College of Health Sciences, Kampala, Uganda
  3. 3Department of Epidemiology & Biostatistics, Makerere School of Public Health, Kampala, Uganda
  4. 4School of Health Sciences, Kampala International University, Bushenyi, Uganda
  1. Correspondence to Dr Kennedy Maring Muni, Epidemiology, University of Washington School of Public Health, Seattle, WA 98125-7752, USA; maring.muni{at}gmail.com

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.

  • burden of disease
  • descriptive epidemiology
  • motor vehicle - non traffic
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Footnotes

  • Contributors All authors conceived the question and study design. SN and AN supervised data collection. KMM, MN and AN conducted statistical analysis. All authors contributed to the writing. All authors read and approved the final version of the manuscript for publication.

  • Funding This work was supported by a grant (# VN 81204847) from the German Federal Ministry of Education and Research (BMBF).

  • Map disclaimer The depiction of boundaries on the map(s) in this article do not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. The map(s) are provided without any warranty of any kind, either express or implied.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Ethics approval Study approval was obtained from Makerere University School of Public Health (approval #: 469) and the Uganda National Council for Science and Technology (registration #: SS 4319. The heads of the respective police and health facilities approved access to data.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available on reasonable request. The corresponding author can work with any interested investigators to secure approval from relevant authorities (the Uganda Police and Ministry of Health) to reuse the dataset for research.

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