Trend change and prediction of nosocomial infection prevalence in China based on grey GM (1,1) model
Jiang Xuejin1， Li Yang2， Ding Honghong3，Lü Min1，Sun Jihua1
1 Binzhou Medical University Hospital, Binzhou 256603, China;
2 Binzhou Center for Disease Control and Prevention, Binzhou 256603, China;
3 Binzhou Maternal and Child Health Hospital, Binzhou 256603, China
Abstract：Objective To understand the trend of nosocomial infection prevalence in China, and to predict the nosocomial infection prevalence in hospitals of different scales in China with the gray GM (1,1) model, so as to provide data support and new ideas for prevention and control of nosocomial infection.Methods Descriptive epidemiological method was used to analyze the trend of nosocomial infection prevalence in China. The grey GM (1,1) model was constructed with data on nosocomial infection prevalence in China from 2008 to 2016, and the model was validated with data from 2018 to 2020. The constructed grey GM (1,1) model was used to predict the prevalence of nosocomial infection in China from 2022 to 2024.Results The prevalence of nosocomial infection in China showed a downward trend. The prevalence of nosocomial infection increased with the increase of hospital scales. The grey GM (1,1) model for the prevalence of nosocomial infection has good accuracy and high fitting effect. In 2024, the prevalence of nosocomial infection in China, in hospitals with<300 beds, in hospitals with 300-599 beds, in hospitals with 600-899 beds, and in hospitals with≥ 900 beds can be reduced to 1.00%, 0.49%, 0.90%, 1.13%, and 2.05%, respectively.Conclusion The prevention and control effect of nosocomial infection in China is obvious, and the grey GM (1,1) model has a good prediction effect on the prevalence of nosocomial infection in China.
姜雪锦，李阳，丁红红，吕敏，孙吉花. 基于灰色GM（1,1）模型的我国医院感染患病率变化趋势及预测[J]. 中国医院统计, 2024, 31(2): 87-89.
Jiang Xuejin， Li Yang， Ding Honghong，Lü Min，Sun Jihua. Trend change and prediction of nosocomial infection prevalence in China based on grey GM (1,1) model. journal1, 2024, 31(2): 87-89.
