应用非等间距灰色模型GM(1,1)预测广西宾阳县农村居民隐孢子虫感染趋势

doi:10.12140/j.issn.1000-7423.2019.01.016

中国寄生虫学与寄生虫病杂志 ›› 2019, Vol. 37 ›› Issue (1): 87-91.doi: 10.12140/j.issn.1000-7423.2019.01.016

应用非等间距灰色模型GM(1,1)预测广西宾阳县农村居民隐孢子虫感染趋势

徐宁¹(), 汤林华¹, 姜岩岩¹, 沈玉娟¹, 曹胜魁¹, 刘华¹, 尹建海¹, 杨益超², 蒋智华², 李伟³, 甘晓琴³, 赵甲光³, 郑卫杰³, 王丽⁴, 张荣⁴, 曹建平^1,^*()

1 中国疾病预防控制中心寄生虫病预防控制所,国家热带病研究中心,世界卫生组织热带病合作中心,科技部国家级热带病国际联合研究中心,卫生部寄生虫病原与媒介生物学重点实验室,上海 200025
2 广西壮族自治区疾病预防控制中心,南宁530000
3 广西壮族自治区宾阳县疾病预防控制中心,宾阳 530400
4 中国疾病预防控制中心农村改水技术指导中心,北京 102200

收稿日期:2018-11-05 出版日期:2019-02-28 发布日期:2019-03-18
通讯作者: 曹建平
作者简介:
作者简介：徐宁（1994-）,女,硕士研究生,从事寄生虫病研究。E-mail：xuning1022@foxmail.com
基金资助:
国家公益性卫生行业科研专项（No. 201502021）;国家科技重点专项（No. 2018ZX10201002-009-004,No. 2018ZX10713001）;上海市公共卫生三年行动计划第四轮（No. 15GWZK0101）

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

Ning XU¹(), Lin-hua TANG¹, Yan-yan JIANG¹, Yu-juan SHEN¹, Sheng-kui CAO¹, Hua LIU¹, Jian-hai YIN¹, Yi-chao YANG², Zhi-hua JIANG², Wei LI³, Xiao-qin GAN³, Jia-guang ZHAO³, Wei-jie ZHENG³, Li WANG⁴, Rong ZHANG⁴, Jian-ping CAO^1,^*()

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:2018-11-05 Online:2019-02-28 Published:2019-03-18
Contact: Jian-ping CAO
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)

摘要/Abstract

摘要：

目的建立隐孢子虫感染率预测模型,预测广西壮族自治区（广西）宾阳县农村居民隐孢子虫感染率,为制定防控措施提供参考依据。方法 2014、2016、2017和2018年分别采用分层整群随机抽样的方法抽取宾阳县农村居民,收集符合条件居民的粪样进行隐孢子虫免疫试纸条检测,获得该县各年农村居民隐孢子虫感染率。根据宾阳县2014、2016、2017和2018年隐孢子虫感染率,建立非等间距灰色模型GM(1,1)以预测2019年和2020年该县农村居民隐孢子虫感染率。模型检验采用残差检验、关联度检验和后验差检验。结果广西宾阳县2014、2016、2017和2018年农村居民隐孢子虫感染率分别为2.9%（57/2 000）、1.5%（15/1 030）、1.1%（11/1 027）和0.6%（6/1 004）。隐孢子虫感染率预测模型为：^（0）(k_i _{+ 1}) = -(1 - e^{0.289 1Δ}^ki^{+ 1})e^{-0.289 1Δ}^ki^{+ 1}。应用该模型获得2014、2016、2017和2018年宾阳县农村居民隐孢子虫感染率的拟合值分别为2.9%、1.5%、1.0%和0.7%,预测模型的绝对误差分别为0.000 0、-0.001 6、0.136 8和-0.121 4,相对误差分别为0.000 0、0.001 1、0.124 4和0.202 3。关联度r = 0.667 7,后验方差比C = 0.106 8,后验概率P = 1.00。2019和2020年宾阳县农村居民隐孢子虫感染率的预测值分别为0.5%和0.4%。结论建立了隐孢子虫感染率的非等间距灰色模型GM(1,1),该模型预测精度较高,拟合效果较好。预测宾阳县农村居民隐孢子虫感染率呈下降趋势。

关键词: 隐孢子虫, 非等间距灰色模型GM(1,1), 预测, 农村居民, 宾阳县, 广西壮族自治区

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）（k_i _{+ 1}） = -（1 - e^{0.289 1Δ}^ki^{+ 1}）e^{-0.289 1Δ}^ki^{+ 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

中图分类号:

R531.5

徐宁, 汤林华, 姜岩岩, 沈玉娟, 曹胜魁, 刘华, 尹建海, 杨益超, 蒋智华, 李伟, 甘晓琴, 赵甲光, 郑卫杰, 王丽, 张荣, 曹建平. 应用非等间距灰色模型GM(1,1)预测广西宾阳县农村居民隐孢子虫感染趋势[J]. 中国寄生虫学与寄生虫病杂志, 2019, 37(1): 87-91.

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.

图/表 3

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参考文献 14

[1]	张炳翔, 俞慧, 张莉莉, 等. 云南省腹泻患者圆孢子虫和隐孢子虫感染情况调查分析[J]. 中国寄生虫学与寄生虫病杂志, 2002, 20(2): 106-108.
[2]	张尚瑞, 沈玉娟, 王斌, 等. 上海某动物园灵长类动物隐孢子虫感染情况[J]. 中国寄生虫学与寄生虫病杂志, 2017, 35(2): 136-139.
[3]	Checkley W, White AC Jr, Jaganath D, et al. A review of global burden, novel diagnostics, therapeutics, and vaccine targets for Cryptosporidium[J]. Lancet Infect Dis, 2015, 15(1): 85-94.
[4]	Vugia D, Cronquist A, Cartter M, et al. Preliminary FoodNet Data on the incidence of infection with pathogens transmitted commonly through food--10States, 2008[J]. MMWR Morb Mortal Wkly Rep, 2009, 58(13): 333-337.
[5]	中华人民共和国卫生部. GB 5749-2006 生活饮用水卫生标准[S]. 北京: 中国标准出版社, 2006.
[6]	Kotloff KL, Nataro JP, Blackwelder WC, et al. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case-control study[J]. Lancet, 2013, 382(9888): 209-222.
[7]	Squire SA, Ryan U.Cryptosporidium and Giardia in Africa: current and future challenges[J]. Parasit Vectors, 2017, 10(1): 195.
[8]	王东, 张媛媛. 大蒜素和阿奇霉素治疗隐孢子虫感染小鼠的效果观察[J]. 中国寄生虫学与寄生虫病杂志, 2013, 31(6): 477-479.
[9]	Abubakar I, Aliyu SH, Arumugam C, et al. Prevention and treatment of cryptosporidiosis in immunocompromised patients[J]. Cochrane Database Syst Rev, 2007(1): CD004932.
[10]	邓聚龙. 灰色动态模型(GM)及在粮食长期预测中的应用[J]. 大自然探索, 1984, 3: 37-43.
[11]	王钟羡, 吴春笃, 史雪荣. 非等间距序列的灰色模型[J]. 数学的实践与认识, 2003, 33(10): 16-20.
[12]	赛晓勇, 闫永平, 徐德忠, 等. 应用灰色动态模型预测血吸虫病病情[J]. 中国地方病学杂志, 2005, 24(2): 39-41.
[13]	周宁, 董笑月, 柏建芸, 等. 天津市艾滋病流行趋势灰色模型预测[J]. 中华预防医学杂志, 2009, 43(8): 742-743.
[14]	杨亚丽, 樊俏荣, 周敏, 等. 2008-2015年甘肃省孕产妇死亡率分析及预测[J]. 中国生育健康杂志, 2017, 28(3): 251-252.

模型精度等级Model precision grade	P	C
好Good	> 0.95	< 0.350 0
合格Qualified	> 0.80	< 0.500 0
勉强合格Barely qualified	> 0.70	< 0.650 0
不合格Unqualified	≤ 0.70	≥0.650 0

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[8]	贾丁, 但佳明, 孙燕, 罗静怡, 朱子琦, 张雪萍, 刘海峰, 周紫峣, 马晓平, 彭广能, 钟志军. 四川省奶牛犊牛隐孢子虫流行情况及其分子特性分析[J]. 中国寄生虫学与寄生虫病杂志, 2019, 37(4): 422-427.
[9]	曹胜魁, 姜岩岩, 袁忠英, 徐梦, 曹建平, 杨益超, 沈玉娟. 广西宾阳县和灵山县水源隐孢子虫和蓝氏贾第鞭毛虫污染调查[J]. 中国寄生虫学与寄生虫病杂志, 2018, 36(6): 597-601.
[10]	徐宁, 尹建海, 沈玉娟, 刘华, 曹建平. 隐孢子虫和蓝氏贾第鞭毛虫分子流行病学研究进展[J]. 中国寄生虫学与寄生虫病杂志, 2018, 36(6): 661-666.
[11]	汲蕊, 梁瑞文, 管志玉, 李瑞芳, 付玉荣, 王红艳. 氧化苦参碱对微小隐孢子虫感染小鼠肠黏膜Toll样受体的影响[J]. 中国寄生虫学与寄生虫病杂志, 2018, 36(5): 455-460.
[12]	汲蕊, 梁瑞文, 管志玉, 李瑞芳, 付玉荣, 王红艳. TLR4/NF-κB信号通路在微小隐孢子虫感染中的作用机制[J]. 中国寄生虫学与寄生虫病杂志, 2018, 36(4): 361-366.
[13]	闫帅, 严萍, 莫筱瑾, 徐斌, 张颋, 胡薇, 詹若挺, 叶萍. 细粒棘球绦虫乳酸脱氢酶B细胞表位的预测及鉴定[J]. 中国寄生虫学与寄生虫病杂志, 2017, 35(6): 554-558.
[14]	方芬, 刘喆, 王桂军, 徐前明. Toll样受体4诱导感染微小隐孢子虫的小鼠树突状细胞功能的体外研究[J]. 中国寄生虫学与寄生虫病杂志, 2017, 35(3): 265-269.
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应用非等间距灰色模型GM(1,1)预测广西宾阳县农村居民隐孢子虫感染趋势

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

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年份Year	感染率/%Infection rate /%	拟合值及预测值/% Fitted and predicted prevalence/%	绝对误差Absolute error	相对误差Relative errors	平均绝对误差Mean absolute error	关联度Correlation degree	后验方差比Posterior variance ratio	后验概率Posterior probability
2014	2.9	2.9	0.000 0	0.000 0
2016	1.5	1.5	-0.001 6	0.001 1
2017	1.1	1.0	0.136 8	0.124 4	0.065 0	0.667 7	0.106 8	1.00
2018	0.6	0.7	-0.121 4	0.202 3
2019	-	0.5	-	-
2020	-	0.4	-	-