ORIGINAL ARTICLES

Evaluation of implementation quality of schistosomiasis surveillance programmes in surveillance provinces of China in 2024

  • GUO Suying ,
  • LI Yinlong ,
  • LI Shizhen ,
  • DANG Hui ,
  • ZHANG Lijuan ,
  • HE Junyi ,
  • YANG Fan ,
  • ZHU Hongqing ,
  • JIA Tiewu ,
  • QIN Zhiqiang ,
  • FENG Ting ,
  • DENG Wangping ,
  • LV Chao ,
  • YANG Ying ,
  • HAO Yuwan ,
  • SUN Junling ,
  • CAO Chunli ,
  • XU Jing ,
  • LI Shizhu
Expand
  • 1 National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Center for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
    2 Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing 102206, China
    3 School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China

Received date: 2025-02-10

  Revised date: 2025-03-25

  Online published: 2025-10-09

Supported by

Key Discipline Project of the Three-Year Initiative Plan for Strengthening Public Health System Construction in Shanghai (2023-2025)(GWVI-11.1-12);National Science Foundation of China(82073619)

Abstract

Objective To understand and evaluate the implementation quality and problems of current schistosomiasis surveillance programmes in China, so as to provide insights into facilitating schistosomiasis surveillance programme. Methods In October to December, 2024, a total of 22 counties (county-level cities or districts, hereinafter referred to as “counties”) were sampled using a quota sampling method from 13 provinces (autonomous regions, municipalities, hereinafter referred to as “provinces”) where national schistosomiasis surveillance programmes were implemented. Based on Information technology―Evaluation indicators for data quality (GB/T 36344-2018) and the expert meeting method, evaluation indicators were proposed to assess the quality of the surveillance programmes, including standardization, integrity, accuracy, consistency, and timeliness. A total of 50 subjects’ serum samples, 30 Kato-Katz slides (all slides were examined if less than 30 slides collected from residents were available), and 10 snail survey environments were sampled from each survey county for re-reviews. The indicator scores were analyzed using the equal weighting method, and the average scores and the coincidence rates of serum and etiologic re-review samples were calculated. In addition, the difference in the average score was compared with rank sum test between elimination, nonendemic areas and non-elimination areas. Results The 22 evaluation counties included 7 surveillance counties and 2 nonendemic counties in schistosomiasis elimination provinces, and 13 epidemic surveillance counties in non-elimination provinces. The average score was (9.04 ± 0.79) points in 22 evaluation counties, and (8.92 ± 0.76) points in surveillance counties in non-elimination provinces and (9.22 ± 0.83) points in surveillance and nonendemic counties in elimination provinces (Z = -0.889, P > 0.05). The average scores for standardization, integrity, accuracy, consistency, and timeliness of schistosomiasis surveillance programmes were (1.86 ± 0.35), (1.73 ± 0.46), (1.77 ± 0.43), (1.95 ± 0.21), and (1.73 ± 0.46) points in 22 survey counties, respectively. Among the survey counties, there were 3 counties with insufficient surveillance funds, 6 with incomplete original records of snail surveys, 3 with inconsistent qualitative between original and re-review results of 7 serum samples, 3 with inaccurate snail monitoring results (including longitude and latitude of snail surveillance, and snail survey diagram), 1 with inconsistent original data with total numbers in statistical tables, and 6 with failure in timely data update, entry, and management. Conclusion The quality of national schistosomiasis surveillance programmes is high in surveillance counties in China; however, the timeliness and standardization remain to be further improved. Sustainable fund and material supports and improved capability through training among monitoring professionals are required to ensure the quality of surveillance programmes.

Cite this article

GUO Suying , LI Yinlong , LI Shizhen , DANG Hui , ZHANG Lijuan , HE Junyi , YANG Fan , ZHU Hongqing , JIA Tiewu , QIN Zhiqiang , FENG Ting , DENG Wangping , LV Chao , YANG Ying , HAO Yuwan , SUN Junling , CAO Chunli , XU Jing , LI Shizhu . Evaluation of implementation quality of schistosomiasis surveillance programmes in surveillance provinces of China in 2024[J]. CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES, 2025 , 43(4) : 489 -496 . DOI: 10.12140/j.issn.1000-7423.2025.04.007

References

[1] Zhou XN, Wang LY, Chen MG, et al. The public health significance and control of schistosomiasis in China: Then and now[J]. Acta Trop, 2005, 96(2/3): 97-105.
[2] 詹思延. 流行病学[M]. 8版. 北京: 人民卫生出版社, 2017.
  Zhan SY. Epidemiology[M]. 8th ed. Beijing: People’s Medical Publishing House, 2017. (in Chinese)
[3] 张利娟, 何君逸, 杨帆, 等. 2023年全国血吸虫病防治进展[J]. 中国血吸虫病防治杂志, 2024, 36(3): 221-227.
  Zhang LJ, He JY, Yang F, et al. Progress of schistosomiasis control in China in 2023[J]. Chin J Schisto Control, 2024, 36(3): 221-227. (in Chinese)
[4] 周晓农. 我国血吸虫病的监测与预警[J]. 中国血吸虫病防治杂志, 2009, 21(5): 341-344.
  Zhou XN. Surveillance and forecast of schistosomiasis transmission in China[J]. Chin J Schisto Control, 2009, 21(5): 341-344. (in Chinese)
[5] 党辉, 李银龙, 吕山, 等. 《全国血吸虫病监测方案(2020年版)》释义[J]. 热带病与寄生虫学, 2020, 18(3): 133-137.
  Dang H, Li YL, Lv S, et al. Interpretation for National Surveillance Plan of Schistosomiasis (version 2020)[J]. J Trop Dis Parasitol, 2020, 18(3): 133-137. (in Chinese)
[6] 国家市场监督管理总局国家标准化管理委员会. 信息技术数据质量评价指标: GB/T 36344—2018[S]. 北京: 中国标准出版社, 2018: 2-5.
  State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. Information technology―Evaluation indicators for data quality: GB/T 36344-2018[S]. Beijing: Standards Press of China, 2018: 2-5. (in Chinese)
[7] 周晓农, 朱泽林, 涂宏, 等. 《加快实现消除血吸虫病目标行动方案(2023—2030年)》解读[J]. 中国血吸虫病防治杂志, 2024, 36(1): 7-12.
  Zhou XN, Zhu ZL, Tu H, et al. Interpretation of the Action Plan to Accelerate the Elimination of Schistosomiasis in China(2023-2030)[J]. Chin J Schisto Control, 2024, 36(1): 7-12. (in Chinese)
[8] 王应东. GPS误差分析和精度控制[J]. 测绘与空间地理信息, 2011, 34(6): 235-236.
  Wang YD. GPS error analysis and precision control[J]. Geomat Spatial Inf Technol, 2011, 34(6): 235-236. (in Chinese)
[9] 国家疾病预防控制局, 国家卫生健康委员会, 国家发展和改革委员会, 等. 关于建立健全智慧化多点触发传染病监测预警体系的指导意见[J]. 中国病毒病杂志, 2024, 14(6): 518-520.
  National Disease Control and Prevention Administration, National Health Commission, National Development and Reform Commission, et al. National Health Commission, National Development and Reform Commission, Guiding opinions on establishing and improving the intelligent multi-point trigger infectious disease monitoring and early warning system[J]. Chin J Viral Dis, 2024, 14(6): 518-520. (in Chinese)
[10] Shen Y, Liu YH, Krafft T, et al. Progress and challenges in infectious disease surveillance and early warning[J]. Med Plus, 2025, 2(1): 100071.
[11] 许静, 曹淳力, 吕山, 等. 血吸虫病防治这10年: 进展与挑战[J]. 中国血吸虫病防治杂志, 2022, 34(6): 559-565, 579.
  Xu J, Cao CL, Lü S, et al. Schistosomiasis control in China from 2012 to 2021: Progress and challenges[J]. Chin J Schisto Control, 2022, 34(6): 559-565, 579. (in Chinese)
[12] 张丽, 尹建海, 夏志贵. 中国防止疟疾输入再传播的成效与挑战分析[J]. 中国热带医学, 2024, 24(4): 365-371.
  Zhang L, Yin JH, Xia ZG. Analysis of effectiveness and challenges in preventing the re-establishment of malaria transmission in China[J]. China Trop Med, 2024, 24(4): 365-371. (in Chinese)
[13] 何君逸, 李仕祯, 杨帆, 等. 血吸虫病消除五省消除复核后疫情监测结果分析[J]. 中国寄生虫学与寄生虫病杂志, 2024, 42(5): 601-607.
  He JY, Li SZ, Yang F, et al. Analysis of surveillance results on schistosomiasis prevalence post-reassessment of elimination in five provinces under schistosomiasis elimination program[J]. Chin J Parasitol Parasit Dis, 2024, 42(5): 601-607. (in Chinese)
[14] 郭苏影, 李银龙, 李仕祯, 等. 2020—2022年全国血吸虫病监测点流动人群血清流行病学特征分析[J]. 中国寄生虫学与寄生虫病杂志, 2024, 42(6): 694-700.
  Guo SY, Li YL, Li SZ, et al. Serological epidemic characteristics of transient population at national schistosomiasis surveillance sites of China, 2020-2022[J]. Chin J Parasitol Parasit Dis, 2024, 42(6): 694-700. (in Chinese)
[15] 张键锋, 孙乐平, 杨坤, 等. 江苏省血吸虫病查病质控体系的构建与应用Ⅰ县级人员血清学检测能力[J]. 中国血吸虫病防治杂志, 2013, 25(5): 457-461.
  Zhang JF, Sun LP, Yang K, et al. Establishment and application of quality control system for detection of schistosomiasis in Jiangsu Province I Ability of serological detection among county-level personnel[J]. Chin J Schisto Control, 2013, 25(5): 457-461. (in Chinese)
[16] 朱蓉, 秦志强, 冯婷, 等. 全国血吸虫病监测点现场病原学检测效果及质控评估[J]. 中国血吸虫病防治杂志, 2013, 25(1): 11-15.
  Zhu R, Qin ZQ, Feng T, et al. Assessment of effect and quality control for paracitological tests in national schistosomiasis surveillance sites[J]. Chin J Schisto Control, 2013, 25(1): 11-15. (in Chinese)
[17] 何君逸, 李仕祯, 邓王平, 等. 我国血吸虫病防治机构能力建设现状调查[J]. 中国血吸虫病防治杂志, 2024, 36(1): 67-73.
  He JY, Li SZ, Deng WP, et al. Capacity building in schistosomiasis control institutions in China: A cross-sectional study[J]. Chin J Schisto Control, 2024, 36(1): 67-73. (in Chinese)
[18] 郝瑜婉, 田添, 朱泽林, 等. 全国疾控机构重点寄生虫病防治能力建设现状分析[J]. 中国寄生虫学与寄生虫病杂志, 2024, 42(1): 83-90.
  Hao YW, Tian T, Zhu ZL, et al. Current situation of capacity building for key parasitic diseases control in CDCs of China[J]. Chin J Parasitol Parasit Dis, 2024, 42(1): 83-90. (in Chinese)
[19] 俞铖航, 郑彬. 基于AHP模糊综合评判法的寄生虫病标准制定选择的研究[J]. 中国卫生标准管理, 2019, 10(9): 7-11.
  Yu CH, Zheng B. Research of FCE based on AHP in formulation of the parasitic disease standard[J]. China Health Stand Manag, 2019, 10(9): 7-11. (in Chinese)
[20] 夏蒙, 周杰, 程湘晖, 等. 基于加权秩和比法综合评价湖南省血吸虫病监测质量控制体系[J]. 疾病监测, 2024, 39(1): 85-90.
  Xia M, Zhou J, Cheng XH, et al. A comprehensive evaluation of quality control system for schistosomiasis surveillance in Hunan based on weighted rank-sum ratio method[J]. Dis Surveillance, 2024, 39(1): 85-90. (in Chinese)
Outlines

/

〈 〉