[Epidemic trends and predictive analysis of other infectious diarrhea in Jiangxi Province, 2017-2022]

Zhonghua Liu Xing Bing Xue Za Zhi. 2023 Oct 10;44(10):1641-1645. doi: 10.3760/cma.j.cn112338-20230421-00259.
[Article in Chinese]

Abstract

Objective: To analyze epidemic trends of other infectious diarrhea in Jiangxi Province from 2017 to 2022, and explore the application of autoregressive integrated moving average (ARIMA) model in the prediction of the incidence of other infectious diarrhea in Jiangxi Province, providing reference for the prediction and prevention and control of other infectious diarrhea. Methods: To conduct a descriptive epidemiological analysis of other infectious diarrhea cases in Jiangxi Province from 2017 to 2022, and establish an ARIMA model to predict the number of other infectious diarrhea cases in 2023. Results: From 2017 to 2022, Jiangxi Province reported 204 842 cases of other infectious diarrhea. The annual average reported incidence rate was 74.32/100 000. The cases were reported in each age group with obvious seasonal characteristics of the main peak. There were two peak periods of incidence in winter and spring (from January to March) and in summer and autumn (from July to September) and the peak value was higher in winter and spring. All parameters of the model ARIMA (0,1,2)(2,1,0)12 and ARIMA (1,0,0)(2,1,0)12 were statistically significant (P<0.05), and the minimum values of Bayesian information criterion were 13.83 and 9.12, respectively. The residual series were all white noise (P>0.05); The predicted value of the model is in good agreement with the actual value, and the predicted trend is consistent with the actual trend. The model has a good prediction effect. Conclusions: The other infectious diarrhea occurred in 2017-2022 was still the first case of notifiable disease in Jiangxi Province. The prevention and control situation cannot be ignored. Disease monitoring and health education for families of children under 3 years of age and scattered children among key populations for prevention and control should be strengthened during the epidemic season. The ARIMA model can be used for short-term prediction and trend analysis of other infectious diarrhea outbreaks in Jiangxi Province.

目的: 分析江西省2017-2022年其他感染性腹泻流行趋势,探讨自回归移动平均(ARIMA)模型在江西省其他感染性腹泻发病预测中的应用,为开展其他感染性腹泻预测和防控工作提供参考。 方法: 对江西省2017-2022年其他感染性腹泻病例进行描述性流行病学分析,建立ARIMA模型对2023年其他感染性腹泻发病数进行预测。 结果: 2017-2022年江西省累计报告其他感染性腹泻为204 842例,年均报告发病率为74.32/10万。全年龄段均有病例报告,发病呈明显的季节性特征,存在冬春季(1-3月)和夏秋季(7-9月)两个发病高峰,且冬春季峰值较高。ARIMA(0,1,2)(2,1,0)12和ARIMA(1,0,0)(2,1,0)12模型的各项参数均有统计学意义(P<0.05),且贝叶斯信息准则值最小分别为13.83和9.12,残差系列均为白噪声(P>0.05);模型预测值与实际值较为吻合,预测趋势与实际趋势一致,模型预测效果较好。 结论: 2017-2022年其他感染性腹泻发病仍居江西省法定传染病发病前列,防控形势不可忽视,应在流行季加强对防控重点人群≤3岁儿童和散居儿童家庭的疾病监测和健康宣教工作。ARIMA模型可用于江西省其他感染性腹泻发病的短期预测和趋势分析。.

Publication types

  • English Abstract

MeSH terms

  • Bayes Theorem
  • China / epidemiology
  • Diarrhea / epidemiology
  • Dysentery*
  • Forecasting
  • Humans
  • Incidence
  • Models, Statistical*