Seasonal autoregressive moving average model-based prediction of bacteriophage dysentery incidence trends in Xinjiang
10.3969/j.issn.1006-2483.2023.05.006
- VernacularTitle:基于季节自回归移动平均模型的新疆细菌性痢疾发病趋势预测
- Author:
Ting WANG
1
;
Xiangyan HE
2
,
3
Author Information
1. School of Public Health , Xinjiang Medical University , Urumqi , Xinjiang 830054 , China
2. People'
3. s Hospital of Xinjiang Uygur Autonomous Region, Urumqi , Xinjiang 830001 , China
- Publication Type:Journal Article
- Keywords:
SARIMA;
Bacillary dysentery;
Morbidity prediction
- From:
Journal of Public Health and Preventive Medicine
2023;34(5):30-34
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the epidemiological characteristics of bacillary dysentery in Xinjiang from 2005-2018, to explore the feasibility and applicability of seasonal autoregressive moving average model to predict the incidence pattern of bacillary dysentery in Xinjiang, and to provide a scientific basis for decision-making in the prevention and control of bacillary dysentery. Methods Descriptive analysis was used to analyze the epidemiological characteristics of bacillary dysentery, and Python software was used to construct a SARIMA model and predict the incidence trend. Results The average annual reported incidence rate of bacillary dysentery in Xinjiang from 2005-2018 was 35.71/100 000, with peak incidence concentrated in June-October. The difference in the incidence rate of bacillary dysentery among the age groups was statistically significant (χ2=145605.90, P<0.001), with a larger proportion of illnesses in the 0-5 and >60 years age groups. The resulting model was SARIMA (0,1,2)(0,1,1)12 with all parameters statistically significant (P<0.05). The Ljung-Box Q test (LBQ) was performed on the residual series and the difference was not statistically significant (LBQ=0.68, P=0.41), i.e., the residual series was white noise. The relative errors of the predicted and observed values ranged from 3.29% to 75.32%, with a mean relative error of 11.34%. The optimal SARIMA model constructed was used to predict the incidence trend from 2019 based on monthly incidence data of bacillary dysentery from 2005-2018, which showed a year-on-year decline in incidence. Conclusion The SARIMA (0,1,2)(0,1,1)12 model has good accuracy in predicting the incidence of bacillary dysentery in Xinjiang and can be used for medium-term prediction of the disease.
