Volume 4, Issue 4 (Summer - In Progress 2019)                   HDQ 2019, 4(4): 4-4 | Back to browse issues page

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Omidi M, Jafari Eskandari M, Raeisi S, Shojaei A A. Application of a Statistical Model to Forecast Drowning Deaths in Iran. HDQ. 2019; 4 (4) :4-4
URL: http://hdq.uswr.ac.ir/article-1-249-en.html
1- , OOMMIIDDII@GMAIL.COM
Abstract:   (68 Views)
Background/aim:  One of the indicators for measuring the development of a country is its death rate caused by accidents and disasters. Every year, many people in Iran are drowned for various reasons. The aim of this study was to predict the trend of drowning mortality in Iran using statistical models.
Method: This research was a longitudinal study using time-series data of drowning deaths obtained from the Iranian Legal Medicine Organization during 2005-2017. The Autoregressive Integrated Moving Average (ARIMA) model was used for forecasting, which is based on the Box-Jenkins method consisting of the Autoregressive (AR) model, Moving Average (MA) model, and Autoregressive Moving Average (ARMA) model. Data were analyzed by ITSM software.
Results: A total of 14,127 people have died due to drowning in Iran, during 2005-2017, with an average death toll of 1,086 people per year. In 2017, the highest number of deaths caused by drowning was recorded in Khuzestan province (n=161) and the lowest number was related to the South Khorasan province (n=1). Estimates of the drowning trend indicated that the number of drowning deaths in Iran will continue to decline in the coming years.
Conclusion: The high accuracy of prediction using the Box-Jenkins method indicates its effectiveness for experts and managers to predict drowning death rates.
     
Type of Study: Research | Subject: General
Received: 2019/02/20 | Accepted: 2019/10/1

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