ABSTRACT
Injuries caused by Motor Vehicle crashes were ranked 10th among the leading causes of death and 9th among the leading cause of disability worldwide (World Health Organization, 2013). In developing countries 90% of disabilities are caused by road traffic crashes. In Namibia, The Motor Vehicle Accident Fund spends approximately N$ 22,6 million monthly towards medical expenses of people injured in crashes (Tjihenuna, 2015), causing a concern, to the victims, their families and affects the country’s economy at large. Efforts have been put in place by stakeholders to reduce road crashes, injuries and fatalities, despite these efforts the trend of crashes keeps on increasing yearly. The objectives of the study were to explore generalised linear models to establish risk factors associated with road traffic injuries in Namibia and develop strategies to guide policy on reduction of road traffic injuries.
The study was based on a quantitative cross sectional research design for all road crash injuries recorded from 2011 -2016 of secondary data from the MVA Fund database (21869), with number of injured persons per crash as the dependent variable.
Using the MASS and pscl packages in R version 3.3.2, six Generalised linear were explored: Poisson, Negative binomial, Zero inflated Poisson, Zero- inflated Negative Binomial, the Hurdle Poisson and the Hurdle negative binomial. The Akaike Information Criterion (AIC) and the Vuong’s test showed that the Hurdle Negative Binomial was the best.
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The probability of road traffic injuries (RTI) was inferred by the following variables: the crash type with vehicle to vehicle (OR=0.5, p
SHIYUKA, N (2021). Hurdle Negative Binomial Model For Motor Vehicle Crash Injuries In Namibia. Afribary. Retrieved from https://track.afribary.com/works/hurdle-negative-binomial-model-for-motor-vehicle-crash-injuries-in-namibia
SHIYUKA, NDILIMEKE "Hurdle Negative Binomial Model For Motor Vehicle Crash Injuries In Namibia" Afribary. Afribary, 28 Apr. 2021, https://track.afribary.com/works/hurdle-negative-binomial-model-for-motor-vehicle-crash-injuries-in-namibia. Accessed 27 Nov. 2024.
SHIYUKA, NDILIMEKE . "Hurdle Negative Binomial Model For Motor Vehicle Crash Injuries In Namibia". Afribary, Afribary, 28 Apr. 2021. Web. 27 Nov. 2024. < https://track.afribary.com/works/hurdle-negative-binomial-model-for-motor-vehicle-crash-injuries-in-namibia >.
SHIYUKA, NDILIMEKE . "Hurdle Negative Binomial Model For Motor Vehicle Crash Injuries In Namibia" Afribary (2021). Accessed November 27, 2024. https://track.afribary.com/works/hurdle-negative-binomial-model-for-motor-vehicle-crash-injuries-in-namibia