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

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 o...

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Main Authors: Christian Akrong Hesse, Dominic Buer Boyetey, Albert Ayi Ashiagbor
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2022/1906533
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author Christian Akrong Hesse
Dominic Buer Boyetey
Albert Ayi Ashiagbor
author_facet Christian Akrong Hesse
Dominic Buer Boyetey
Albert Ayi Ashiagbor
author_sort Christian Akrong Hesse
collection DOAJ
description 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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spelling doaj-art-453493c53c82445c91e7e68eae268b872025-02-03T01:32:36ZengWileyComplexity1099-05262022-01-01202210.1155/2022/1906533Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in GhanaChristian Akrong Hesse0Dominic Buer Boyetey1Albert Ayi Ashiagbor2Department of Banking and FinanceDepartment of Sustainable Energy and ResourcesDepartment of Banking and FinanceRoad 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.http://dx.doi.org/10.1155/2022/1906533
spellingShingle Christian Akrong Hesse
Dominic Buer Boyetey
Albert Ayi Ashiagbor
Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana
Complexity
title Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana
title_full Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana
title_fullStr Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana
title_full_unstemmed Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana
title_short Predictive Probability Models of Road Traffic Human Deaths with Demographic Factors in Ghana
title_sort predictive probability models of road traffic human deaths with demographic factors in ghana
url http://dx.doi.org/10.1155/2022/1906533
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AT dominicbuerboyetey predictiveprobabilitymodelsofroadtraffichumandeathswithdemographicfactorsinghana
AT albertayiashiagbor predictiveprobabilitymodelsofroadtraffichumandeathswithdemographicfactorsinghana