This is the first study to comprehensively report the presence, distribution of serotypes and virulence genes, antimicrobial susceptibility and DNA fingerprints of Klebsiella pneumoniae (KP) from intestinal tract of diarrhoea patients of China. Distribution of virulence genes, antimicrobial resistance spectrum, and relationship between virulence genes and antimicrobial resistance are clarified. It will be of great public health significance to estimate the prevalence of KP in faeces of diarrhoea patients, and to provide a theoretical foundation for the traceability, prevention and control, and reasonable treatment of infections caused by this bacterium.
The early identification and prediction of Hand-foot-and-Mouth diseases (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regionsd due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used Generalized Additive Model (GAM) to evaluate effects of weather factors on HFMD cases. Then, GAM, Support Vectors Regression (SVR) and Random Forest Regression (RFR) models are used to compare predictive results. Annual average incidence was 129.72/100,000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases, and based on predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help the public health agencies implement prevention and control measures in advance.
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