The Effect of Road Traffic Fatality Rate on Road Users in Ghana

Hesse, Christian A.; Ofosu, John B.

doi:10.19026/rjms.7.2207

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…This implies that the risk of dying as a result of road traffic fatality in Greater Accra is relatively low, recording an average rate of 5.7 road traffic fatalities per 100 accidents. Thus, out of every 100 road traffic accidents in the Greater Accra, about 6 of the victims are likely to die (Hesse and Ofosu, 2015). Table 8 show that there is strong positive correlation between the parameter estimates of the modified Smeed's model and the fatality indices.…”

Section: (Iii) Random Slope Model Mmentioning

confidence: 97%

Assessing the Risk of Road Traffic Fatalities Across Sub-Populations of a Given Geographical Zone, Using a Modified Smeed’s Model

Hesse¹,

Oduro²,

Ofosu³

et al. 2016

IJSP

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Smeed (1949) provided a regression model for estimating road traffic fatalities (RTFs). In this paper, a modified form of Smeed's (1949) model is proposed for which it is shown that the multiplicative error term is less than that of Smeed's original model for most situations. Based on this Modified Smeed's model, Bayesian and multilevel methods are developed to assess the risk of road traffic fatalities across sub populations of a given geographical zone. These methods consider the parameters of the Smeed's model to be random variables and therefore make it possible to compute variances across space provided there is significant intercept variation of the regression equation across such regions. Using data from Ghana, the robustness of the Bayesian estimates was indicated at low sample sizes with respect to the Normal, Laplace and Cauchy prior distributions. Thus the Bayesian and Multilevel methods performed at least as well as the traditional method of estimating parameters and beyond this were able to assess risk differences through variability of these parameters in space.

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Section: (Iii) Random Slope Model Mmentioning

confidence: 97%

Assessing the Risk of Road Traffic Fatalities Across Sub-Populations of a Given Geographical Zone, Using a Modified Smeed’s Model

Hesse¹,

Oduro²,

Ofosu³

et al. 2016

IJSP

View full text Add to dashboard Cite

show abstract

“…is was necessary because of the use of fatalities per 100 casualties index (F.I.) as a requirement for characterization and comparison of the extent and risk of road traffic fatality [57,58]. Consequently, age group (x 1 ) was coded as follows: 0-5 years ≡ 7, 6-15 years ≡ 5, 16-25 years ≡ 3, 26-35 years ≡ 1, 36-45 years ≡ 2, 46-55 years ≡ 4, 56-65 years ≡ 6, and over 65 years ≡ 8.…”

Section: Data Processing and Analysismentioning

confidence: 99%

Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana

2022

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Road traffic carnages are global concerns and seemingly on the rise in Ghana. Several risk factors have been studied as associated with road traffic fatalities. However, inadequate road traffic fatality (RTF) data and inconsistent probability outcomes for RTF remain major challenges. The objective of this study was to illustrate and estimate probability models that can predict road traffic fatalities. We relied on 66,159 recorded casualties who were involved in road traffic accidents (RTAs) in Ghana from 2015 to 2019. Three generalized linear models, namely, logistic regression, probit regression, and linear probability model, were used for the analysis. We found that gender and age groups have significant effects in predicting the probability of road traffic fatality for all three models. Through a likelihood ratio test, however, it was determined that the logit regression model produced consistent probabilities of traffic fatalities which are very close to the actual probability values across the age groups and gender, compared to the other two models. Thus, we recommend intensified campaign for the use of seat belts in vehicles, targeted at the aged and male users of road transport, to reduce the possibility of death in any RTA.

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The Effect of Age on Road Traffic Fatality Index in Ghana

Hesse¹,

Ofosu²,

Darkwah³

2016

IJSP

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In this paper, data on road traffic casualties by age groups, from 2009 to 2013, will be used. Using published road traffic casualty statistics from the National Road Safety Commission of Ghana, a 2  8 contingency table is used to determine whether road traffic casualty and age group are independent. A one factor analysis of variance tests shall be used to conduct a comparative analysis of the rate of road traffic fatalities per 100 casualties across the various age groups in Ghana. A multiple comparison test, using the Fisher least significance difference (LSD) method, shall be conducted to determine which pairs of age groups are significantly different.The study will show that road traffic casualty is not independent of age group. The analysis of variance will show that there are significant differences in road traffic fatality indices (fatality per 100 casualties) among various age groups in Ghana. The risks of dying in a road traffic accident among children under 6 years and older population who are over 65 years are both significantly higher than those of other age groups. This points to the fact that, although smaller number of children under 6 years and older population who are over 65 years die in road traffic accidents each year, more and more people as a proportion of the recorded number of casualties, are being killed through road traffic accidents among these two categories of age groups. Thus, the probability of being killed in a fatal road traffic accident is significantly high in each of these two age groups.

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The Effect of Road Traffic Fatality Rate on Road Users in Ghana

Cited by 3 publications

References 8 publications

Assessing the Risk of Road Traffic Fatalities Across Sub-Populations of a Given Geographical Zone, Using a Modified Smeed’s Model

Assessing the Risk of Road Traffic Fatalities Across Sub-Populations of a Given Geographical Zone, Using a Modified Smeed’s Model

Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana

The Effect of Age on Road Traffic Fatality Index in Ghana

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