Author:
Odusola Aina Olufemi,Jeong Dohyo,Malolan Chenchita,Kim Dohyeong,Venkatraman Chinmayee,Kola-Korolo Olusegun,Idris Olajide,Olaomi Oluwole Olayemi,Nwariaku Fiemu E.
Abstract
Abstract
Background
Sub-Saharan African countries, Nigeria inclusive, are constrained by grossly limited access to quality pre-hospital trauma care services (PTCS). Findings from pragmatic approaches that explore spatial and temporal trends of past road crashes can inform novel interventions. To improve access to PTCS and reduce burden of road traffic injuries we explored geospatial trends of past emergency responses to road traffic crashes (RTCs) by Lagos State Ambulance Service (LASAMBUS), assessed efficiency of responses, and outcomes of interventions by local government areas (LGAs) of crash.
Methods
Using descriptive cross-sectional design and REDcap we explored pre-hospital care data of 1220 crash victims documented on LASAMBUS intervention forms from December 2017 to May 2018. We analyzed trends in days and times of calls, demographics of victims, locations of crashes and causes of delayed emergency responses. Assisted with STATA 16 and ArcGIS pro we conducted descriptive statistics and mapping of crash metrics including spatial and temporal relationships between times of the day, seasons of year, and crash LGA population density versus RTCs incidence. Descriptive analysis and mapping were used to assess relationships between ‘Causes of Delayed response’ and respective crash LGAs, and between Response Times and crash LGAs.
Results
Incidences of RTCs were highest across peak commuting hours (07:00-12:59 and 13:00-18:59), rainy season and harmattan (foggy) months, and densely populated LGAs. Five urban LGAs accounted for over half of RTCs distributions: Eti-Osa (14.7%), Ikeja (14.4%), Kosofe (9.9%), Ikorodu (9.7%), and Alimosho (6.6%). On intervention forms with a Cause of Delay, Traffic Congestion (60%), and Poor Description (17.8%), had associations with LGA distribution. Two densely populated urban LGAs, Agege and Apapa were significantly associated with Traffic Congestion as a Cause of Delay. LASAMBUS was able to address crash in only 502 (36.8%) of the 1220 interventions. Other notable outcomes include: No Crash (false calls) (26.6%), and Crash Already Addressed (22.17%).
Conclusions
Geospatial analysis of past road crashes in Lagos state offered key insights into spatial and temporal trends of RTCs across LGAs, and identified operational constraints of state-organized PTCS and factors associated with delayed emergency responses. Findings can inform programmatic interventions to improve trauma care outcomes.
Funder
National Institutes of Health
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health
Reference40 articles.
1. WHO | Road Traffic Injuries. https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries Accessed 29 Jul 2023.
2. WHO | Estimated Road Traffic Death Rate (per 100 000 population). https://www.who.int/data/gho/data/indicators/indicator-details/GHO/estimated-road-traffic-death-rate-(per-100-000-population). Accessed 30 Jul 2023.
3. Nigeria Population 2023 (Live) https://worldpopulationreview.com/countries/nigeria-population. Accessed 5 Aug 2023.
4. National Bureau of Statistics. https://www.nigerianstat.gov.ng/index.php. Accessed 5 Aug 2023.
5. WHO. Decade of Action for Road Safety 2011–2020. https://www.who.int/groups/united-nations-road-safety-collaboration/decade-of-action-for-road-safety-2011-2020. Accessed 30 Jul 2023
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献