Application of SARIMA in predicting outbreaks of hospital-acquired infection in a tertiary psychiatric hospital
10.11816/cn.ni.2025-241942
- VernacularTitle:SARIMA在某三级精神专科医院医院感染发病预测中的应用
- Author:
Mengwei ZHANG
1
;
Hongwei WANG
1
;
Mei GU
1
;
Lunan XIAO
1
Author Information
1. 阜阳市第三人民医院医院感染管理科,安徽阜阳 236015
- Publication Type:Journal Article
- Keywords:
Hospital-acquired infection;
Seasonal auto regressive integrated moving average model;
Time series a-nalysis;
Psychiatric hospital;
Prediction
- From:
Chinese Journal of Nosocomiology
2025;35(16):2499-2503
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To construct a Seasonal Autoregressive Integrated Moving Average(SARIMA)model based on the incidences of hospital-acquired infections(HAIs),and provide a reference for the prevention and control of HAI in such hospitals.METHODS The incidences of HAIs in a tertiary psychiatric hospital from Jan.2016 to Aug.2024 were collected by the Weining Hospital Infection Information Management software and paper-based HAI reporting cards.The incidence rates from 2016 to 2023 were analyzed and a SARIMA model was established.The incidence rates from Jan.to Aug.2024 were predicted,and the accuracy of the SARIMA model was evaluated based on the actual measured values.RESULTS From 2016 to 2023,a total of 98,075 patients were admitted,including 936 patients who developed HAIs,with an incidence rate of 0.95％ranged from 0.79％to 1.23％.The time series plot from 2016 to 2023 did not meet the requirements for sequence stability.After differ-entiating the original data,analyzing the correlation plot(ACF)and partial autocorrelation plot(PACF),and con-ducting multiple assessments and verifications,it was finally determined that SARIMA(1,1,1)(1,1,1)12,SA-RIM A(1,1,1)(1,1,0)12,ARIMA(1,1,1)(0,1,0)12,and SARIMA(1,1,1)(0,1,1)12 were the alterna-tive models.The Ljung-Box Q test was used to retain the models with P＞0.05 that met the sequence with white noise and the minimum Bayesian Information Criterion(BIC)value was obtained,it was determined that SARIMA(1,1,1)(0,1,1)12 was the optimal model.When validated with Jan.to Aug.2024 HAI incidence data,the infection rates predicted by SARIMA(1,1,1)(0,1,1)12 model remained within the 95％confidence interval,indicating high prediction accuracy.CONCLUSION SARIMA model can effectively predict the monthly HAI incidences in a tertiary psychiatric hospital,and it plays an role in the decision-making of HAI prevention and control in psychiatric inpatients.
