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      Impact of the revised Unified Federal Traffic Law on crash casualties in Abu Dhabi Emirate: Interrupted time series analysis

      research-article
      Heliyon
      Elsevier
      Interrupted time series (ITS), Casualty rates, Traffic safety, Intervention analysis, ARIMA, Black point

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          Abstract

          In recent years, different developing countries have shown growing interest in enacting road safety policies. However, research on their effectiveness in reducing crashes, injuries, and deaths is limited. This study evaluated the impact of traffic safety measures introduced in the revised Unified Federal Traffic Law in the Emirates of Abu Dhabi (AD) and the United Arab Emirates (UAE) on crash and casualty reductions. In particular, it examines the 2009 enactment of the black-point system. To the best of our knowledge, this is the first study to consider this topic in a desert or UAE context. Box–Tiao intervention analysis was used to examine monthly AD police data from January 2007 to December 2013. The analysis utilized a dynamic programming approach to test for structural changes in the AD casualty data and empirically confirm the presence and exact location of breakpoints (intervention time). The interrupted time-series analysis results indicated a significant drop in casualty rates post-intervention. Since the intervention, the AD has witnessed a slow downward trend in the crash casualty rate. These findings confirm the effectiveness of the implemented safety measures. They provide quality information to authorities regarding implementing and adopting life-saving interventions and road safety management.

          Highlights

          • Road safety plans require reliable intervention efficacy measures.

          • Road safety interventions in the UAE rarely use evidence-based research.

          • Revised UAE road safety measures are evaluated using interrupted time series methods.

          • Abu Dhabi Emirate road safety investment reduced crashes.

          • Abu Dhabi casualty rates have declined since 2009.

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          Most cited references32

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          Intervention Analysis with Applications to Economic and Environmental Problems

          G. BOX, G. Tiao (1975)
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            strucchange: AnRPackage for Testing for Structural Change in Linear Regression Models

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              How to do (or not to do) ... Assessing the impact of a policy change with routine longitudinal data.

              A lack of good quality evidence on the effect of alternative social policies in low- and middle-income countries has been recently underlined and the value of randomized trials increasingly advocated. However, it is also acknowledged that randomization is not always feasible or politically acceptable. Analyses using longitudinal data series before and after an intervention can also deliver robust results and such data are often reasonably easy to access. Using the example of evaluating the impact on utilization of a change in health financing policy, this article explains how studies in the literature have often failed to address the possible biases that can arise in a simple analysis of routine longitudinal data. It then describes two possible statistical approaches to estimate impact in a more reliable manner and illustrates in detail the more simple method. Advantages and limitations of this quasi-experimental approach to evaluating the impact of health policies are discussed.
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                02 April 2024
                15 April 2024
                02 April 2024
                : 10
                : 7
                : e28990
                Affiliations
                [1]College of Business and Economics, United Arab Emirates University, Al Ain, United Arab Emirates
                Article
                S2405-8440(24)05021-7 e28990
                10.1016/j.heliyon.2024.e28990
                11002656
                38596078
                26bec6e2-e30c-4a89-91ae-8d99c8b04f9f
                © 2024 The Author

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 17 June 2023
                : 22 March 2024
                : 27 March 2024
                Categories
                Research Article

                interrupted time series (its),casualty rates,traffic safety,intervention analysis,arima,black point

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