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Yi-Ting L, Xin-Ting C, Jin-Hua Z, Le-Ping S, Hai-Yong H, Li-Guang T, Ting F, Shi-Zhu L, Guang-Hui R, Tie-Wu J. [Approaches used for assessment of the burden of advanced schistosomiasis japonica: a comparative study]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2019; 31:280-284. [PMID: 31544407 DOI: 10.16250/j.32.1374.2019079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To compare the approaches used for the assessment of disability adjust life years (DALYs) for advanced schistosomiasis japonica, so as to provide scientific evidence for accurate assessment of the burden of advanced schistosomiasis japonica. METHODS The patients with advanced schistosomiasis japonica receiving treatment and assistance programs in Hunan Province in 2017 were enrolled, and the years lived with disability (YLD) for the patients with advanced schistosomiasis japonica was calculated using the common global burden of disease (GBD) estimation method, the modified GBD method with addition of common syndromes of advanced schistosomiasis japonica, and the quality of life assessment method. RESULTS The YLDs of patients with advanced schistosomiasis japonica, the mean YLDs per capita, and the percentages of YLD were 673.94, 728.77 person-years and 1 761.99 person-years; 0.181, 0.196 person-years and 0.474 person-years; and 10.61, 11.48 person-years per 100 thousand persons and 27.75 person-years per 100 thousand persons with the common GBD method, modified GBD method and the quality of life method, respectively. The YLDs of the patients with advanced schistosomiasis japonica in Hunan Province estimated with the modified GBD method and the quality of life method were 8.14% and 2.61 times higher than that with the common GBD method. Of the major symptoms included in the calculation, the 5 symptoms with the greatest contribution to the burden of advanced schistosomiasis japonica included ascites, moderate anemia, severe anemia, diarrhea and hematochezia. CONCLUSIONS The quality of life method may more comprehensively assess the YLDs in patients with advanced schistosomiasis japonica than the common and modified GBD methods.
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Affiliation(s)
- Li Yi-Ting
- National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
| | - Cai Xin-Ting
- Hunan Institution of Schistosomiasis control, China
| | - Zhu Jin-Hua
- Hunan Institution of Schistosomiasis control, China
| | - Sun Le-Ping
- Jiangsu Institute of Parasitic Diseases, China
| | | | - Tian Li-Guang
- National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
| | - Feng Ting
- National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
| | - Li Shi-Zhu
- National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
| | | | - Jia Tie-Wu
- National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, Shanghai 200025, China
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En-Li T, Zheng-Feng W, Wen-Ce Z, Shi-Zhu L, Yan L, Lin A, Yu-Chun C, Xue-Jiao T, Shun-Xian Z, Zhi-Sheng D, Chun-Li Y, Jia-Xu C, Wei H, Xiao-Nong Z, Li-Guang T. [Study on the ARIMA model application to predict echinococcosis cases in China]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2018. [PMID: 29536707 DOI: 10.16250/j.32.1374.2017173] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To predict the monthly reported echinococcosis cases in China with the autoregressive integrated moving average (ARIMA) model, so as to provide a reference for prevention and control of echinococcosis. METHODS SPSS 24.0 software was used to construct the ARIMA models based on the monthly reported echinococcosis cases of time series from 2007 to 2015 and 2007 to 2014, respectively, and the accuracies of the two ARIMA models were compared. RESULTS The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2015 was ARIMA (1, 0, 0) (1, 1, 0)12, the relative error among reported cases and predicted cases was -13.97%, AR (1) = 0.367 (t = 3.816, P < 0.001), SAR (1) = -0.328 (t = -3.361, P = 0.001), and Ljung-Box Q = 14.119 (df = 16, P = 0.590) . The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2014 was ARIMA (1, 0, 0) (1, 0, 1)12, the relative error among reported cases and predicted cases was 0.56%, AR (1) = 0.413 (t = 4.244, P < 0.001), SAR (1) = 0.809 (t = 9.584, P < 0.001), SMA (1) = 0.356 (t = 2.278, P = 0.025), and Ljung-Box Q = 18.924 (df = 15, P = 0.217). CONCLUSIONS The different time series may have different ARIMA models as for the same infectious diseases. It is needed to be further verified that the more data are accumulated, the shorter time of predication is, and the smaller the average of the relative error is. The establishment and prediction of an ARIMA model is a dynamic process that needs to be adjusted and optimized continuously according to the accumulated data, meantime, we should give full consideration to the intensity of the work related to infectious diseases reported (such as disease census and special investigation).
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Affiliation(s)
- Tan En-Li
- Department of Gerontal Respiratory Medicine, First Hospital of Lanzhou University, Lanzhou 730000, China
| | - Wang Zheng-Feng
- Second General Surgery Department, First Hospital of Lanzhou University, China
| | - Zhou Wen-Ce
- Second General Surgery Department, First Hospital of Lanzhou University, China
| | - Li Shi-Zhu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Lu Yan
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Ai Lin
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Cai Yu-Chun
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Teng Xue-Jiao
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Zhang Shun-Xian
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Dang Zhi-Sheng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | | | - Chen Jia-Xu
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Hu Wei
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China.,Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, China
| | - Zhou Xiao-Nong
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
| | - Tian Li-Guang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory for Parasitology and Vector Biology, National Health and Family Planning Commission, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases, China
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Qi W, Gai-Ge Y, Chun-Li Y, Xiu-Xia Z, Ying-Fang Y, Shun-Xian Z, Li-Guang T. [Prevalence of Entamoeba histolytica infection and its risk factors in Tengchong City, Yunnan Provine: a hospital-based study]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2018; 31:139-142. [PMID: 31184043 DOI: 10.16250/j.32.1374.2018253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To understand the infection status and risk factors of Entamoeba histolytica in inpatients in Tengchong City, Yunnan Province. METHODS A cross-sectional study was conducted in the inpatients in Tengchong People's Hospital, Yunnan Province. After obtaining the informed consent from the subjects, the stool samples were collected from 2016-07-01 to 2017-03-31, and nested polymerase chain reaction (PCR) was used to detect E. histolytica in the stool samples. Meanwhile, a structured questionnaire was used to record the demographic information and clinical symptoms for the patients. RESULTS Totally 507 cases were recruited, and the detection rate of E. histolytica was 1.97% (10/507, 95% CI: 1.07%-3.59%) in all subjects. There were no significant differences between the inpatients with and without E. histolytica infection in the height (Z = -0.40, P = 0.69), weight (Z = -0.34, P = 0.73), body mass index (Z = -0.40, P = 0.69) and age (Z = -1.48, P = 0.14). Chronic diarrhea (OR = 21.43, 95% CI: 5.04-91.23) and daily drinking water (OR = 11.28, 95% CI: 2.79-45.56) were relevant to E. histolytica infection. No significant association was observed between E. histolytica infection and the clinical symptoms, such as abdominal distension (OR = 0.70, 95% CI: 0.09-5.56), inappetence (OR = 0.50, 95% CI: 0.06-4.02), itchy skin (OR = 0.79, 95% CI: 0.10-6.38), perianal pruritus (OR = 1.74, 95% CI: 0.21-14.07), and constipation (OR = 0.91, 95% CI: 0.13-7.33). CONCLUSIONS E. histolytica infection is high in inpatients in Tengchong City, Yunnan Province, and chronic diarrhea and drinking unboiled water were highly correlated with E. histolytica infection.
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Affiliation(s)
- Wang Qi
- Maternal and Children Health Hospital of Hainan Province, Haikou 570206, China
| | - Yang Gai-Ge
- Guangzhou Women and Children Medical Care Center, Guangdong Province, China
| | | | - Zhan Xiu-Xia
- Maternal and Children Health Hospital of Hainan Province, Haikou 570206, China
| | - Yu Ying-Fang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, China
| | - Zhang Shun-Xian
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, China
| | - Tian Li-Guang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Tropical Diseases, Key Laboratory of Parasite and Vector Biology, National Health Commission, China
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