1.Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition)
Jianling FAN ; Tiejun WANG ; Pengfei YANG ; Keke DING ; Xiaoning HAO ; Sunfang JIANG ; Ankang LÜ ; Jianping LU ; Sheng RONG ; Weibin SHI ; Shengwei SUN ; Yan TAN ; Qilei TU ; Zhiping WANG ; Bing WANG ; Jianyun WANG ; Weijian WANG ; Yan WANG ; Qun XU ; Chenli ZHANG ; Fan ZHANG ; Ping ZHANG ; Yansong ZHENG ; Jieru ZHOU ; Dan CHEN ; Jiaoyang ZHENG
Chinese Journal of Clinical Medicine 2025;32(6):1097-1111
Obesity, as a chronic recurrent disease, has become a major public health challenge in China. To implement the requirements of the Healthy China Initiative (2019—2030), under domestic guidelines or consensus statements on overweight and obesity, and in alignment with the latest scientific advances globally, the Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition) was developed. This protocol was drafted by the Health Management Center of Shanghai Changzheng Hospital and formulated through multiple rounds of deliberation by experts in China’s health examination quality control field. The protocol establishes unified standards for screening facilities, personnel qualifications, and measurement or testing procedures. It defines specific screening items, outlines a standardized screening pathway, and sets requirements for the final medical review, ensuring the scientific validity, effectiveness, and safety of the screening process. The implementation of this protocol will enhance the consistency of weight management practices for adults across health examination institutions and strengthen the quality control of overweight and obesity screening programs.
2.Toxicokinetics of Chlorfenapyr and Its Metabolites in Rats
Wen-Yan LI ; Jin-Feng ZHAO ; Wei-Chen LIU ; Shi-Jing LÜ ; Jia-Xin ZHANG ; Xu-Dong ZHANG ; Zhi-Wen WEI ; Ke-Ming YUN ; Chao ZHANG
Journal of Forensic Medicine 2025;41(4):380-386
Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.
3.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
4.Clinical Value of CD44 mRNA and CD24 mRNA and Protein Expression Levels in Placental Tissue of Patients with Severe Preeclampsia
Lingling TENG ; Guangzhen MA ; Ke SHI ; Yingxin LÜ ; Jing XU
Journal of Modern Laboratory Medicine 2024;39(1):43-48
Objective To explore clinical value of the expression levels of cell surface transmembrane glycoprotein molecule 44(CD44)mRNA,cell surface transmembrane glycoprotein molecule 24(CD24)mRNA,and protein in the placenta of severe preeclampsia(SPE)patients.Methods The SPE patients who were delivered by cesarean section in the Second People's Hospital of Liaocheng from June 2019 to June 2022 were further divided into 45 patients in early onset SPE group(gestational age≤34 weeks)and 55 patients in late onset SPE group(gestational age>34 weeks)according to the different gestational age.The control group consisted of 100 normal cases in the same period.The expression of CD44 and CD24 in placenta of SPE patients was detected by fluorescent quantitative PCR and immunohistochemistry,Pearson method was used to analyze the difference of their expression levels and their correlation with the clinical characteristics of SPE disease,and multivariate logistic regression was used to analyze the influencing factors of SPE.Results Compared with the control group,the expression levels of CD44 mRNA(0.55±0.12 vs 1.02±0.33)and CD24 mRNA(0.68±0.19 vs 1.05±0.11)in SPE placental tissues decreased significantly,the differences were statistically significant(t=13.385,16.853,P<0.05).The immunohistochemical staining results showed that CD44 and CD24 were mostly negative or weakly positive in the SPE group placental tissue,while they were mostly positive in the control group,the positive rates of CD44 and CD24 in the SPE placental tissue were lower than those in the control group,and the differences were statistically significant(χ2=9.696,14.346,P<0.05).Compared to the early onset SPE group,the expression levels of CD44(0.65±0.17 vs 0.42±0.11)and CD24(0.77±0.23 vs 0.58±0.13)mRNA in placental tissue of late onset SPE were higher,and the differences were statistically significant(t=7.830,4.932,P<0.05).Compared with the control group,the BMI,systolic blood pressure,diastolic blood pressure,urinary protein,Cr,LDH and BUN were significantly increased in SPE group(t=5.360~30.241,all P<0.05).In SPE group,the gestational age was earlier,the MPV and ALB were lower,the newborn's birth length was shorter,and the body weight than control group,the differences were statistically great(t=3.232~11.109,all P<0.05).The expression of CD44 and CD24 in SPE placenta was positively correlated(r=0.698,P<0.05),the expression of CD44 in SPE placenta was positively correlated with CD24,gestational week of delivery,MPV and neonatal birth length(r=0.611,0.639,0.612,0.465,all P<0.05),and was negatively correlated with systolic blood pressure,urinary protein and LDH(r=-0.604,-0.569,-0.593,all P<0.05).The expression of CD24 was positively correlated with gestational age,MPV and newborn birth length(r=0.605,0.584,0.640,all P<0.05),and was negatively correlated with systolic blood pressure,urinary protein and LDH(r=-0.637,-0.593,-0.561,all P<0.05).The results of logistic regression analysis showed that MPV(95%CI:1.429~4.350),urinary protein(95%CI:1.529~2.709),and LDH(95%CI:1.425~3.932)were all independent risk factors for SPE(all P<0.05).High levels of CD44(95%CI:0.561~0.940)and CD24(95%CI:0.495~0.814)were independent protective factors for SPE(P<0.05).Conclusion The low expression levels of CD44 and CD24 in placenta of SPE patients are independent protective factors of SPE,which can provide direction for the follow-up treatment of SPE.
5.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
6.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
7.Schistosomiasis control in China from 2012 to 2021: progress and challenges
Jing XU ; Chun-li CAO ; Shan LÜ ; Shi-zhu LI ; Xiao-nong ZHOU
Chinese Journal of Schistosomiasis Control 2022;34(6):559-565
Schistosomiasis has been endemic in China for more than 2 000 years, which causes huge morbidity, social and economic burdens. Guided by the national specific strategic programs and criteria for schistosomiasis, tremendous achievements have been gained for schistosomiasis elimination in China. This paper reviews the progress of schistosomiasis control and endemic status of schistosomiasis in China during the period from 2012 to 2021, analyzes the challenges to achieve the goal of schistosomiasis elimination in China by 2030, and proposes suggestions for future schistosomiasis control programs.
8.Analysis of the new WHO guideline to accelerate the progress towards elimination of schistosomiasis in China.
Zhao Yu GUO ; Jia Xin FENG ; Li Juan ZHANG ; Yi Biao ZHOU ; Jie ZHOU ; Kun YANG ; Yang LIU ; Dan Dan LIN ; Jian Bing LIU ; Yi DONG ; Tian Ping WANG ; Li Yong WEN ; Min Jun JI ; Zhong Dao WU ; Qing Wu JIANG ; Song LIANG ; Jia Gang GUO ; Chun Li CAO ; Jing XU ; Shan LÜ ; Shi Zhu LI ; Xiao Nong ZHOU
Chinese Journal of Schistosomiasis Control 2022;34(3):217-222
On February 2022, WHO released the evidence-based guideline on control and elimination of human schistosomiasis, with aims to guide the elimination of schistosomiasis as a public health problem in disease-endemic countries by 2030 and promote the interruption of schistosomiasis transmission across the world. Based on the One Health concept, six evidence-based recommendations were proposed in this guideline. This article aims to analyze the feasibility of key aspects of this guideline in Chinese national schistosomiasis control program and illustrate the significance to guide the future actions for Chinese national schistosomiasis control program. Currently, the One Health concept has been embodied in the Chinese national schistosomiasis control program. Based on this new WHO guideline, the following recommendations are proposed for the national schistosomiasis control program of China: (1) improving the systematic framework building, facilitating the agreement of the cross-sectoral consensus, and building a high-level leadership group; (2) optimizing the current human and livestock treatments in the national schistosomiasis control program of China; (3) developing highly sensitive and specific diagnostics and the framework for verifying elimination of schistosomiasis; (4) accelerating the progress towards elimination of schistosomiasis and other parasitic diseases through integrating the national control programs for other parasitic diseases.
China/epidemiology*
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Disease Eradication
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Humans
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Public Health
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Schistosomiasis/prevention & control*
;
World Health Organization
9.Sharing the WHO guideline on control and elimination of human schistosomiasis to achieve the goal of schistosomiasis elimination in China.
Tian Ping WANG ; Shan LÜ ; Zhi Qiang QIN ; Yi Biao ZHOU ; Yang LIU ; Li Yong WEN ; Jia Gang GUO ; Jing XU ; Shi Zhu LI ; Guang Ming ZHANG ; Shi Qing ZHANG
Chinese Journal of Schistosomiasis Control 2022;34(3):235-240
Currently, the national schistosomiasis control program of China is moving from transmission interruption to elimination, and there are multiple challenges during the stage moving towards the progression of schistosomiasis elimination, including a high difficulty in shrinking snail-infested areas, unstable achievements for infectious source control, imperfect surveillance system and a reduction in schistosomiasis control and administration. Based on the core suggestions proposed in the 2022 WHO guideline on control and elimination of human schistosomiasis, recommendations on schistosomiasis surveillance system building, development of novel diagnostics, adjustment of the schistosomiasis control strategy and maintaining and improvements of the schistosomiasis control capability are proposed for the national schistosomiasis control program of China in the new era according to the actual status of schistosomiasis control in China. Formulation of the national schistosomiasis control strategy and goal from One Health perspective, verification of transmission interruption and elimination of schistosomiasis, precision implementation of schistosomiasis control interventions with adaptations to local circumstances, development and application of highly sensitive and specific diagnostics are recommended for elimination of schistosomiasis in China. In addition, the implementation of the 2022 WHO guideline on control and elimination of human schistosomiasis may guide the elimination of schistosomiasis in China.
Animals
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China/epidemiology*
;
Goals
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Humans
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Schistosomiasis/prevention & control*
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Snails
;
World Health Organization
10.Prediction of trends for fine-scale spread of Oncomelania hupensis in Shanghai Municipality based on supervised machine learning models.
Yan Feng GONG ; Zhuo Wei LUO ; Jia Xin FENG ; Jing Bo XUE ; Zhao Yu GUO ; Yan Jun JIN ; Qing YU ; Shang XIA ; Shan LÜ ; Jing XU ; Shi Zhu LI
Chinese Journal of Schistosomiasis Control 2022;34(3):241-251
OBJECTIVE:
To predict the trends for fine-scale spread of Oncomelania hupensis based on supervised machine learning models in Shanghai Municipality, so as to provide insights into precision O. hupensis snail control.
METHODS:
Based on 2016 O. hupensis snail survey data in Shanghai Municipality and climatic, geographical, vegetation and socioeconomic data relating to O. hupensis snail distribution, seven supervised machine learning models were created to predict the risk of snail spread in Shanghai, including decision tree, random forest, generalized boosted model, support vector machine, naive Bayes, k-nearest neighbor and C5.0. The performance of seven models for predicting snail spread was evaluated with the area under the receiver operating characteristic curve (AUC), F1-score and accuracy, and optimal models were selected to identify the environmental variables affecting snail spread and predict the areas at risk of snail spread in Shanghai Municipality.
RESULTS:
Seven supervised machine learning models were successfully created to predict the risk of snail spread in Shanghai Municipality, and random forest (AUC = 0.901, F1-score = 0.840, ACC = 0.797) and generalized boosted model (AUC= 0.889, F1-score = 0.869, ACC = 0.835) showed higher predictive performance than other models. Random forest analysis showed that the three most important climatic variables contributing to snail spread in Shanghai included aridity (11.87%), ≥ 0 °C annual accumulated temperature (10.19%), moisture index (10.18%) and average annual precipitation (9.86%), the two most important vegetation variables included the vegetation index of the first quarter (8.30%) and vegetation index of the second quarter (7.69%). Snails were more likely to spread at aridity of < 0.87, ≥ 0 °C annual accumulated temperature of 5 550 to 5 675 °C, moisture index of > 39% and average annual precipitation of > 1 180 mm, and with the vegetation index of the first quarter of > 0.4 and the vegetation index of the first quarter of > 0.6. According to the water resource developments and township administrative maps, the areas at risk of snail spread were mainly predicted in 10 townships/subdistricts, covering the Xipian, Dongpian and Tainan sections of southern Shanghai.
CONCLUSIONS
Supervised machine learning models are effective to predict the risk of fine-scale O. hupensis snail spread and identify the environmental determinants relating to snail spread. The areas at risk of O. hupensis snail spread are mainly located in southwestern Songjiang District, northwestern Jinshan District and southeastern Qingpu District of Shanghai Municipality.
Animals
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Bayes Theorem
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China/epidemiology*
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Ecosystem
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Gastropoda
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Supervised Machine Learning

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