OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.

OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.

Objective: To comprehensively understand the disinfection quality of secondary and primary schools and kindergartens in Wuxi, so as to find out problems and to provide advice for improvement. Methods: Stratified random sampling method was applied in the investigation to select 73 schools and classes. The qualities of room air, surface of object, hand hygiene of staff, tableware, ultraviolet lamp and disinfectant in use (including bacterial contamination and concentration of chlorine-containing) were all tested. Results: A total of 2 563 samples were collected with the total disinfection qualified rate 88.02%. The qualified rates of kindergarten, primary and secondary schools were 87.89%, 90.67% and 85.83% respectively. The rates of Xishan and Jiangyin districts were 75.24% and 75.89% respectively. The quality of urban schools was better than the rural(χ 2=16.57, P<0.01). There was no statistical significance between public and private schools (χ 2=0.01, P=0.92). The rank of qualified rates of different objects was: bacterial contamination (100.00%) > room air (93.13%) > tableware (91.87%) > surface of object (89.40%) > ultraviolet lamp (84.00%) > concentration of chlorine-containing (73.68%) > hand hygiene of staff (73.53%). The quality of secondary schools was lower than kindergartens and primary schools in the aspects of room air and surface of object. Conclusion The disinfection quality of secondary and primary schools and kindergartens in Wuxi is good in general. More attention should be paid on hand hygiene, concentration of chlorine-containing and ultraviolet lamp. The qualities of room air and surface of object of secondary schools need to be improved.