Time Series Modeling and Forecasting of Drug-Related Deaths in Iran (2014-2016).
Drug abuse
Forecasting
Poisoning
Time series
Trend
Journal
Addiction & health
ISSN: 2008-4633
Titre abrégé: Addict Health
Pays: Iran
ID NLM: 101582275
Informations de publication
Date de publication:
Jul 2023
Jul 2023
Historique:
received:
20
06
2021
accepted:
08
09
2021
medline:
29
11
2023
pubmed:
29
11
2023
entrez:
29
11
2023
Statut:
ppublish
Résumé
Investigating the temporal variations and forecasting the trends in drug-related deaths can help prevent health problems and develop intervention programs. The recent policy in Iran is strongly focused on deterring drug use and replacing illicit drugs with legal ones. This study aimed to investigate drug-related deaths in Iran in 2014-2016 and forecast the death toll by 2019. In this longitudinal study, Box-Jenkins time series analysis was used to forecast drug-related deaths. To this end, monthly counts of drug-related deaths were obtained from March 2014 to March 2017. After data processing, to obtain stationary time series and examine the stability assumption with the Dickey-Fuller test, the parameters of the Autoregressive Integrated Moving Averages (ARIMA) model were determined using autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs. Based on Akaike statistics, ARIMA (0, 1, 1) was selected as the best-fit model. Moreover, the Dickey-Fuller test was used to confirm the stationarity of the time series of transformed observations. The forecasts were made for the next 36 months using the ARIMA (0,1,2) model and the same confidence intervals were applied to all months. The final extracted data were analyzed using R software, Minitab, and SPSS-23. According to the Iranian Ministry of Health and the Legal Medicine Organization, there were 8883 drug-related deaths in Iran from March 2014 to March 2017. According to the time series findings, this count had an upward trend and did not show any seasonal pattern. It was forecasted that the mean drug-related mortality rate in Iran would be 245.8 cases per month until 2019. This study showed a rising trend in drug-related mortality rates during the study period, and the modeling process for forecasting suggested this trend would continue until 2019 if proper interventions were not instituted.
Sections du résumé
Background
UNASSIGNED
Investigating the temporal variations and forecasting the trends in drug-related deaths can help prevent health problems and develop intervention programs. The recent policy in Iran is strongly focused on deterring drug use and replacing illicit drugs with legal ones. This study aimed to investigate drug-related deaths in Iran in 2014-2016 and forecast the death toll by 2019.
Methods
UNASSIGNED
In this longitudinal study, Box-Jenkins time series analysis was used to forecast drug-related deaths. To this end, monthly counts of drug-related deaths were obtained from March 2014 to March 2017. After data processing, to obtain stationary time series and examine the stability assumption with the Dickey-Fuller test, the parameters of the Autoregressive Integrated Moving Averages (ARIMA) model were determined using autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs. Based on Akaike statistics, ARIMA (0, 1, 1) was selected as the best-fit model. Moreover, the Dickey-Fuller test was used to confirm the stationarity of the time series of transformed observations. The forecasts were made for the next 36 months using the ARIMA (0,1,2) model and the same confidence intervals were applied to all months. The final extracted data were analyzed using R software, Minitab, and SPSS-23.
Findings
UNASSIGNED
According to the Iranian Ministry of Health and the Legal Medicine Organization, there were 8883 drug-related deaths in Iran from March 2014 to March 2017. According to the time series findings, this count had an upward trend and did not show any seasonal pattern. It was forecasted that the mean drug-related mortality rate in Iran would be 245.8 cases per month until 2019.
Conclusion
UNASSIGNED
This study showed a rising trend in drug-related mortality rates during the study period, and the modeling process for forecasting suggested this trend would continue until 2019 if proper interventions were not instituted.
Identifiants
pubmed: 38026723
doi: 10.34172/ahj.2023.1277
pmc: PMC10658097
doi:
Types de publication
Journal Article
Langues
eng
Pagination
149-155Informations de copyright
© 2023 Kerman University of Medical Sciences.
Déclaration de conflit d'intérêts
Competing Interests The authors declare that they have no conflict of interest.
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