Analysis and forecasting of road traffic mortalities in Azad Jammu and Kashmir

Author:

Navid Feroze ,Kamran Abbas ,Sumaira Rashid ,Azhar Saleem

Abstract

Objective: To analyse road traffic accident mortalities in a geographical region. Method: The retrospective study was conducted in Azad Jammu and Kashmir based on secondary data from 2004 to 2017 collected from the police department. Duncan’s multiple range test was used to assess the trends in road traffic accident fatalities with respect to districts and divisions. Different goodness-of-fit criteria were used to compare the performance of different regression models to analyse road traffic accident mortalities with respect to vehicle ownership. The parsimonious time series model was used to forecast the future trends of road traffic accident mortalities. R 3.6.0 software was used for data analysis. Results: There were 5263 major road traffic accidents during the period studied, causing 2317 deaths and 12963 injuries. The number of mortalities in Mirpur division was 923(39.8%), in Muzaffarabad 794(34.3%), and inss Poonch 600(25.9%). The rates of road traffic accident mortalities per 100,000 population increased up to year 2010 and dropped slowly afterwards (Figure 1C). Some disparities were noted among different districts and divisions with respect to road traffic accident mortalities. Based on different goodness-of-fit criteria, the Smeed’s model was found to be the most efficient model to analyse the trends of road traffic accident mortalities with respect to vehicle ownership (Table 1). The forecast for road traffic accident mortalities exhibited some fluctuations in the start and a uniform trend afterwards (Figure 6). Conclusion: Disparities in road traffic accident fatalities across different districts and divisions of Azad Jammu and Kashmir were observed. Though the rate of road traffic accident mortality was seen to be decreasing since 2010, the situation is for behind compared to the global Sustainable Development Goals. Key Words: RTA mortalities, Smeed’s model, Time series.

Publisher

Pakistan Medical Association

Subject

General Medicine

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