Influenza-like illness(ILI)is an acute respiratory infection caused by various pathogens.However,the epidemiologic characteristics of ILI pathogens in Jiangsu province are unclear.To better understand the ILI etiology...Influenza-like illness(ILI)is an acute respiratory infection caused by various pathogens.However,the epidemiologic characteristics of ILI pathogens in Jiangsu province are unclear.To better understand the ILI etiology,the characteristics of the pathogens from nasopharyngeal swab samples of patients with ILI collected from 2012 to 2016 in 6 hospitals in Jiangsu province were studied.The pathogens,including influenza virus,respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),herpes simplex virus(HSV),human coronavirus(hCoV),Streptococcus pneumoniae and Haemophilus influenzae,were detected by real-time PCR.At least one pathogen was identified in 1334 of the patients(40.23%).Among viruses,HRV,influenza A virus(Flu A),ADV and RSV were the most frequently detected.ADV was the only pathogen that was distributed evenly in different years and regions(P>0.05).The etiological distribution varied in different age groups.Streptococcus pneumoniae was the most common pathogen in co-infections with a co-detection rate of 64.57%(319/494).The spectrum of etiologies could help to estimate disease burden and provide guidance for vaccination.展开更多
Background Influenza is an acute respiratory infectious disease with a significant global disease burden.Additionally,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have in...Background Influenza is an acute respiratory infectious disease with a significant global disease burden.Additionally,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have introduced uncertainty to the spread of influenza.However,comparative studies on the performance of innovative models and approaches used for influenza prediction are limited.Therefore,this study aimed to predict the trend of influenza-like illness(ILI)in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance.Methods The generalized additive model(GAM),deep learning hybrid model based on Gate Recurrent Unit(GRU),and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA—GARCH)model were established to predict the trends of ILI 1-,2-,3-,and 4-week-ahead in Beijing,Tianjin,Shanxi,Hubei,Chongqing,Guangdong,Hainan,and the Hong Kong Special Administrative Region in China,based on sentinel surveillance data from 2011 to 2019.Three relevant metrics,namely,Mean Absolute Percentage Error(MAPE),Root Mean Squared Error(RMSE),and R squared,were calculated to evaluate and compare the goodness of fit and robustness of the three models.Results Considering the MAPE,RMSE,and R squared values,the ARMA—GARCH model performed best,while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China.Additionally,the models’predictive performance declined as the weeks ahead increased.Furthermore,blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting.Conclusions Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model.Therefore,in the future,the ARMA—GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones,thereby contributing to influenza control and prevention efforts.展开更多
Objective： To investigate Chinese medicine （CM） patterns and epidemiological characters of patients with influenza-like illness （ILI） syndromes in clinics in China. Methods： A prospective multi-center observatio...Objective： To investigate Chinese medicine （CM） patterns and epidemiological characters of patients with influenza-like illness （ILI） syndromes in clinics in China. Methods： A prospective multi-center observational epidemiology survey on the clinical CM patterns of ILI and its prevalence was conducted from September 2009 to April 2010. A unified survey questionnaire was developed for data collection of ILI symptoms and CM pattems. Totally 45 hospitals from 22 provinces, municipality cities and autonomous regions of China participated this study. The collected data were input by EPI-data v3.1 and analyzed by SPSS 18.0, which included descriptive analysis and Chi-square test for group comparison. Results： A total of 5,967 ILI patients were included in the study. The proportion of the 18-34 aged group （56.2%） was the largest; students （41.0%） were more than other occupations. Majority of the patients had the wind-heat invading Lung （Fei） syndrome （76%）, while in Southwest China mainly wind-heat invading Lung syndrome and wind-cold tightening the exterior syndrome occurred. The typical symptoms of ILI were ranked as fatigue （80.9%）, cough （72.2%）, sore throat （67.2%）, muscular soreness （67.1%）, headache （65.4%）, aversion to cold （60.1%）, thirst （55.1%） and nasal obstruction （48.1%）. Conclusions： The ILl patients in clinics were mainly teenagers and young adults. In regard to CM syndrome, wind-heat invading Lung syndrome prevailed in all regions except the Southwest China. The characteristics of CM syndrome of ILl patients may be relevant to age and region distribution.展开更多
Background Some research groups have hypothesized that human rhinoviruses （HRVs） delayed the circulation of the 2009 pandemic influenza A（H1N1） virus （A（H1N1）pdm09） at the beginning of Autumn 2009 in France.Th...Background Some research groups have hypothesized that human rhinoviruses （HRVs） delayed the circulation of the 2009 pandemic influenza A（H1N1） virus （A（H1N1）pdm09） at the beginning of Autumn 2009 in France.This study aimed to evaluate the relationship between HRV and A（H1N1）pdm09 in pediatric patients with influenza-like illness in Beijing,China.Methods A systematic analysis to detect A（H1N1）pdm09 and seasonal influenza A virus （FLU A） was performed on 4 349 clinical samples from pediatric patients with influenza-like illness during the period June 1,2009 to February 28,2010,while a one-step real-time RT-PCR （rRT-PCR） assay was used to detect HRV in 1 146 clinical specimens selected from those 4 349 specimens.Results During the survey period,only one wave of A（H1N1）pdm09 was observed.The percentage of positive cases for A（H1N1）pdm09 increased sharply in September with a peak in November 2009 and then declined in February 2010.Data on the monthly distribution of HRVs indicated that more HRV-positive samples were detected in September （2.2％） and October （3.3％）,revealing that the peak of HRV infection in 2009 was similar to that of other years.Among the 1 146 specimens examined for HRVs,21 （1.8％） were HRV-positive,which was significantly lower than that reported previously in Beijing （15.4％ to 19.2％） （P ＜0.01）.Overall,6 samples were positive for both A（H1N1）pdm09 and HRV,which represented a positive relative frequency of 1.60％ and 2.08％ HRV,considering the A（H1N1）pdm09-positive and-negative specimens,respectively.The odds ratio was 0.87 （95％ CI 0.32; 2.44,P=0.80）.Conclusions HRVs and A （H1N1）pdm09 co-circulated in this Chinese population during September and October 2009,and the HRV epidemic in 2009 did not affect A（H1N1）pdm09 infection rates in Beijing,China as suggested by other studies.However,the presence of A（H1N1）pdm09 might explain the unexpected reduction in the percentage of HRV positive cases during the period studied.展开更多
目的分析2019—2023年河南省流感样病例(influenza like illness,ILI)监测结果,为流感防控提供依据。方法通过中国流感监测系统收集2019年1月至2023年12月河南省22家国家级流感监测哨点医院和19家网络实验室报告的ILI,描述性分析ILI流...目的分析2019—2023年河南省流感样病例(influenza like illness,ILI)监测结果,为流感防控提供依据。方法通过中国流感监测系统收集2019年1月至2023年12月河南省22家国家级流感监测哨点医院和19家网络实验室报告的ILI,描述性分析ILI流行特征和流感病毒病原型别变化。结果2019—2023年河南省哨点医院共报告ILI 1279248例,ILI占门急诊病例就诊总数的比例为2.24%。0~<5岁组报告ILI 699485例(54.68%),所占比例最高,但阳性率最低(12.43%);15~<25岁组报告61004例(4.77%),阳性率最高(38.98%)。共检测ILI标本87918份,流感核酸阳性17825份,阳性率为20.27%。流行优势毒株2019年第一季度、2023年第一季度为H1NI,2022年秋季和2023年冬季为H3N2。2019—2020监测年度为H3N2和Bv,2020—2021监测年度阳性检出数极少、无流行,2021—2022监测年度为Bv。2020—2023年均未检出By。结论2019—2023年河南省流感具有明显的冬春季高峰,2022年出现夏季流行小高峰,2020—2021年流感流行水平极低。H3N2、H1N1和Bv交替成为流行优势株。展开更多
基金supported by the Jiangsu Provincial Major Science & Technology Demonstration Project (No.BE2017749)the Jiangsu Province Science & Technology Demonstration Project for Emerging Infectious Diseases Control and Prevention (No.BE2015714)
文摘Influenza-like illness(ILI)is an acute respiratory infection caused by various pathogens.However,the epidemiologic characteristics of ILI pathogens in Jiangsu province are unclear.To better understand the ILI etiology,the characteristics of the pathogens from nasopharyngeal swab samples of patients with ILI collected from 2012 to 2016 in 6 hospitals in Jiangsu province were studied.The pathogens,including influenza virus,respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),herpes simplex virus(HSV),human coronavirus(hCoV),Streptococcus pneumoniae and Haemophilus influenzae,were detected by real-time PCR.At least one pathogen was identified in 1334 of the patients(40.23%).Among viruses,HRV,influenza A virus(Flu A),ADV and RSV were the most frequently detected.ADV was the only pathogen that was distributed evenly in different years and regions(P>0.05).The etiological distribution varied in different age groups.Streptococcus pneumoniae was the most common pathogen in co-infections with a co-detection rate of 64.57%(319/494).The spectrum of etiologies could help to estimate disease burden and provide guidance for vaccination.
基金The Special Fund for Health Development Research of Beijing(2021-1G-3013)the Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2021-I2M-1-044)the Bill&Melinda Gates Foundation(INV-024911).
文摘Background Influenza is an acute respiratory infectious disease with a significant global disease burden.Additionally,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have introduced uncertainty to the spread of influenza.However,comparative studies on the performance of innovative models and approaches used for influenza prediction are limited.Therefore,this study aimed to predict the trend of influenza-like illness(ILI)in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance.Methods The generalized additive model(GAM),deep learning hybrid model based on Gate Recurrent Unit(GRU),and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA—GARCH)model were established to predict the trends of ILI 1-,2-,3-,and 4-week-ahead in Beijing,Tianjin,Shanxi,Hubei,Chongqing,Guangdong,Hainan,and the Hong Kong Special Administrative Region in China,based on sentinel surveillance data from 2011 to 2019.Three relevant metrics,namely,Mean Absolute Percentage Error(MAPE),Root Mean Squared Error(RMSE),and R squared,were calculated to evaluate and compare the goodness of fit and robustness of the three models.Results Considering the MAPE,RMSE,and R squared values,the ARMA—GARCH model performed best,while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China.Additionally,the models’predictive performance declined as the weeks ahead increased.Furthermore,blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting.Conclusions Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model.Therefore,in the future,the ARMA—GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones,thereby contributing to influenza control and prevention efforts.
基金Supported by the H1N1 Influenza of the Clinical Study of Traditional Chinese Medicine Management Project by State Administration of Traditional Chinese Medicine,China(No.200907001-2B)
文摘Objective： To investigate Chinese medicine （CM） patterns and epidemiological characters of patients with influenza-like illness （ILI） syndromes in clinics in China. Methods： A prospective multi-center observational epidemiology survey on the clinical CM patterns of ILI and its prevalence was conducted from September 2009 to April 2010. A unified survey questionnaire was developed for data collection of ILI symptoms and CM pattems. Totally 45 hospitals from 22 provinces, municipality cities and autonomous regions of China participated this study. The collected data were input by EPI-data v3.1 and analyzed by SPSS 18.0, which included descriptive analysis and Chi-square test for group comparison. Results： A total of 5,967 ILI patients were included in the study. The proportion of the 18-34 aged group （56.2%） was the largest; students （41.0%） were more than other occupations. Majority of the patients had the wind-heat invading Lung （Fei） syndrome （76%）, while in Southwest China mainly wind-heat invading Lung syndrome and wind-cold tightening the exterior syndrome occurred. The typical symptoms of ILI were ranked as fatigue （80.9%）, cough （72.2%）, sore throat （67.2%）, muscular soreness （67.1%）, headache （65.4%）, aversion to cold （60.1%）, thirst （55.1%） and nasal obstruction （48.1%）. Conclusions： The ILl patients in clinics were mainly teenagers and young adults. In regard to CM syndrome, wind-heat invading Lung syndrome prevailed in all regions except the Southwest China. The characteristics of CM syndrome of ILl patients may be relevant to age and region distribution.
基金This study was supported by the grants from the National Natural Science Foundation of China （No. 30872153） and the Beijing Outstanding Personnel Training Grant from the Beijing Municipal Committee for Science and Technology （No. 2006A63）.Acknowledgements： We would like to thank all the doctors and nurses in the Department of Emergency and the Outpatient Department at the Affiliated Children＇s Hospital of the Capital Institute of Pediatrics for collecting specimens from patients and information from their parents.
文摘Background Some research groups have hypothesized that human rhinoviruses （HRVs） delayed the circulation of the 2009 pandemic influenza A（H1N1） virus （A（H1N1）pdm09） at the beginning of Autumn 2009 in France.This study aimed to evaluate the relationship between HRV and A（H1N1）pdm09 in pediatric patients with influenza-like illness in Beijing,China.Methods A systematic analysis to detect A（H1N1）pdm09 and seasonal influenza A virus （FLU A） was performed on 4 349 clinical samples from pediatric patients with influenza-like illness during the period June 1,2009 to February 28,2010,while a one-step real-time RT-PCR （rRT-PCR） assay was used to detect HRV in 1 146 clinical specimens selected from those 4 349 specimens.Results During the survey period,only one wave of A（H1N1）pdm09 was observed.The percentage of positive cases for A（H1N1）pdm09 increased sharply in September with a peak in November 2009 and then declined in February 2010.Data on the monthly distribution of HRVs indicated that more HRV-positive samples were detected in September （2.2％） and October （3.3％）,revealing that the peak of HRV infection in 2009 was similar to that of other years.Among the 1 146 specimens examined for HRVs,21 （1.8％） were HRV-positive,which was significantly lower than that reported previously in Beijing （15.4％ to 19.2％） （P ＜0.01）.Overall,6 samples were positive for both A（H1N1）pdm09 and HRV,which represented a positive relative frequency of 1.60％ and 2.08％ HRV,considering the A（H1N1）pdm09-positive and-negative specimens,respectively.The odds ratio was 0.87 （95％ CI 0.32; 2.44,P=0.80）.Conclusions HRVs and A （H1N1）pdm09 co-circulated in this Chinese population during September and October 2009,and the HRV epidemic in 2009 did not affect A（H1N1）pdm09 infection rates in Beijing,China as suggested by other studies.However,the presence of A（H1N1）pdm09 might explain the unexpected reduction in the percentage of HRV positive cases during the period studied.
文摘目的分析2019—2023年河南省流感样病例(influenza like illness,ILI)监测结果,为流感防控提供依据。方法通过中国流感监测系统收集2019年1月至2023年12月河南省22家国家级流感监测哨点医院和19家网络实验室报告的ILI,描述性分析ILI流行特征和流感病毒病原型别变化。结果2019—2023年河南省哨点医院共报告ILI 1279248例,ILI占门急诊病例就诊总数的比例为2.24%。0~<5岁组报告ILI 699485例(54.68%),所占比例最高,但阳性率最低(12.43%);15~<25岁组报告61004例(4.77%),阳性率最高(38.98%)。共检测ILI标本87918份,流感核酸阳性17825份,阳性率为20.27%。流行优势毒株2019年第一季度、2023年第一季度为H1NI,2022年秋季和2023年冬季为H3N2。2019—2020监测年度为H3N2和Bv,2020—2021监测年度阳性检出数极少、无流行,2021—2022监测年度为Bv。2020—2023年均未检出By。结论2019—2023年河南省流感具有明显的冬春季高峰,2022年出现夏季流行小高峰,2020—2021年流感流行水平极低。H3N2、H1N1和Bv交替成为流行优势株。
