CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES >

2019 , Vol. 37 >Issue 1: 87 - 91

DOI: https://doi.org/10.12140/j.issn.1000-7423.2019.01.016

ORIGINAL ARTICLES

Prediction of Cryptosporidium spp. infection in rural residents of Binyang County, Guangxi by non-equidistant grey model GM(1,1)

  • Ning XU ,
  • Lin-hua TANG ,
  • Yan-yan JIANG ,
  • Yu-juan SHEN ,
  • Sheng-kui CAO ,
  • Hua LIU ,
  • Jian-hai YIN ,
  • Yi-chao YANG ,
  • Zhi-hua JIANG ,
  • Wei LI ,
  • Xiao-qin GAN ,
  • Jia-guang ZHAO ,
  • Wei-jie ZHENG ,
  • Li WANG ,
  • Rong ZHANG ,
  • Jian-ping CAO
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  • 1 National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai 200025, China
    2 Guangxi Center for Disease Control and Prevention, Nanning 530000, China
    3 Center for Disease Control and Prevention of Binyang County, Binyang, 530400, China
    4 National Center for Rural Water Supply Technical Guidance, Chinese Center for Disease Control and Prevention, Beijing 102200, China

Received date: 2018-11-05

  Online published: 2019-03-18

Supported by

Supported by the Chinese Special Program for Scientific Research of Public Health(No. 201502021)，the National Science and Technology Major Project(No. 2018ZX10201002-009-004, No. 2018ZX10713001)and the Fourth Round of Three-Year Public Health Action Plan of Shanghai, China(No. 15GWZK0101)

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Abstract

Objective To establish a prediction model for Cryptosporidium spp. infection in rural residents of Binyang County, Guangxi Zhuang Autonomous Region (Guangxi) so as to provide reference for the development of prevention and control measures. Methods In 2014, 2016, 2017 and 2018, the rural residents of Binyang County were selected by stratified cluster random sampling, and the fecal samples were collected from selected participants for detecting Cryptosporidium spp. infection using an immunological test strip method. The non-equidistant grey model GM(1,1) was established to predict the prevalence of Cryptosporidium spp. infection in 2019 and 2020 in this region based on the prevalence data collected from the survey in 2014, 2016, 2017 and 2018. The model effect was tested using residual test, correlation test and the posterior deviation test. Results The prevalence of Cryptosporidium spp. infection in the selected rural residents of Binyang County was 2.9% (57/2 000) in 2014, 1.5% (15/1 030) in 2016, 1.1% (11/1 027) in 2017 and 0.6% (6/1 004) in 2018. The prediction model for prevalence of Cryptosporidium spp. infection in this region was established accordingly as: （0）（ki + 1） = -（1 - e0.289 1Δki + 1）e-0.289 1Δki+ 1. Based on this model the fitted prevalence of Cryptosporidium spp. infection in this region in 2014, 2016, 2017 and 2018 were 2.9%, 1.5%, 1.0% and 0.7%, respectively, which are closed correlated with the actual prevalence values (r = 0.667 7) with absolute errors of 0.000 0, -0.001 6, 0.136 8 and -0.121 4 and the relative errors of 0.000 0, 0.001 1, 0.124 4 and 0.202 3, respectively, with the posterior variance ratio C = 0.106 8 and the posterior probability P = 1.00. Based on this model, the prevalence of Cryptosporidium spp. infection in Binyang County are predicted as 0.5% in 2019 and 0.4% in 2020. Conclusion A non-equidistant grey model GM(1,1) is established to predict the prevalence of Cryptosporidium spp. infection. The model has high prediction accuracy and good fitting effect. The predicted results show that the infection rate of Cryptosporidium spp. in rural residents of Binyang County is decreasing.

Key words： Cryptosporidium spp.; Non-equidistant grey model GM(1,1); Prediction; Residents in rural areas; Binyang County; Guangxi Zhuang Autonomous Region

Cite this article

Ning XU , Lin-hua TANG , Yan-yan JIANG , Yu-juan SHEN , Sheng-kui CAO , Hua LIU , Jian-hai YIN , Yi-chao YANG , Zhi-hua JIANG , Wei LI , Xiao-qin GAN , Jia-guang ZHAO , Wei-jie ZHENG , Li WANG , Rong ZHANG , Jian-ping CAO . Prediction of Cryptosporidium spp. infection in rural residents of Binyang County, Guangxi by non-equidistant grey model GM(1,1)[J]. CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES, 2019 , 37(1) : 87 -91 . DOI: 10.12140/j.issn.1000-7423.2019.01.016

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