Rostampour F, Heidari M, Rashidi H, Faramarzi A, Shojaei S, Barati B, Mousavi S A
Department of Biostatistics and Epidemiology, Faculty of Medicine, Urmia University of Medical Sciences, Urmia, Iran.
Social Determinants of Health Research Center, Clinical Research Institute, Urmia University of Medical Science, Urmia, Iran.
Arch Razi Inst. 2024 Jun 30;79(3):651-658. doi: 10.32592/ARI.2024.79.3.651. eCollection 2024 Jun.
Scorpion stings pose a significant public health concern in Iran, resulting in approximately 45,000-50,000 cases and 19 deaths annually. The Khuzestan and Hormozgan provinces have the highest reported incidence rates, with an estimated 36,000 cases each year. This study focused on modeling the time series data of scorpion stings, specifically in Shoushtar City, from 2017 to 2022. Our objective was to investigate the presence of seasonality and long-term trends in the incidence of scorpion stings by utilizing advanced analytical techniques, such as the Autoregressive Integrated Moving Average (ARIMA) model. We applied the seasonal ARIMA model to fit a univariate time series of scorpion sting incidence. This study revealed a significant seasonal trend and an overall increase and decrease in scorpion sting cases during the study period. The best-fitting model for the available data was a seasonal ARIMA model in the form of ARIMA(0,0,1)(1,1,1)12. This model can forecast the frequency of scorpion sting cases in Southwestern Iran over the next two years. As a result, time series analysis can provide valuable insights into the patterns and trends of scorpion sting incidents, allowing for better planning and allocation of healthcare resources. By understanding the seasonal variations, proactive measures can be implemented to address the growing issue of scorpion stings in Iran effectively.
蝎子蜇伤在伊朗是一个重大的公共卫生问题，每年导致约45000-50000例病例和19人死亡。胡齐斯坦省和霍尔木兹甘省报告的发病率最高，每年估计有36000例病例。本研究重点对2017年至2022年期间蝎子蜇伤的时间序列数据进行建模，特别是在舒什塔尔市。我们的目标是利用自回归积分移动平均（ARIMA）模型等先进分析技术，调查蝎子蜇伤发病率的季节性和长期趋势。我们应用季节性ARIMA模型来拟合蝎子蜇伤发病率的单变量时间序列。本研究揭示了研究期间蝎子蜇伤病例的显著季节性趋势以及总体上的增减情况。可用数据的最佳拟合模型是ARIMA(0,0,1)(1,1,1)12形式的季节性ARIMA模型。该模型可以预测伊朗西南部未来两年蝎子蜇伤病例的发生频率。因此，时间序列分析可以为蝎子蜇伤事件的模式和趋势提供有价值的见解，有助于更好地规划和分配医疗资源。通过了解季节性变化，可以采取积极措施有效应对伊朗日益严重的蝎子蜇伤问题。
