四川省壤塘县细粒棘球蚴病流行区的划分
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摘要
细粒棘球蚴病是一种由细粒棘球绦虫的幼虫寄生于动物或人体内而致病的重要人兽共患寄生虫病。细粒棘球绦虫能适应多种宿主,其分布遍及世界各个大陆,涉及到极地、温带、亚热带和热带地区。细粒棘球蚴病的流行程度在世界各地有很大的差异,即使在较小的范围内其流行程度也有很大的差别。目前认为影响棘球蚴病流行程度的因素有生物、环境和社会等方面,如果能够了解这些因素如何具体影响其流行,那么将有助于对细粒棘球蚴病传播与流行的认识,同时也将为棘球蚴病的防治工作提供更好地支持。
本研究在四川省壤塘县进行现场研究,以行政村为单位收集了当地牦牛细粒棘球蚴病的流行数据、牧业生产数据以及家庭养犬数据等相关资料,并根据牦牛患病情况,将行政村划分为不同程度的流行区。利用遥感和地理信息系统提取了研究地区相应的自然环境数据包括高程与全天年平均地表温度,同时结合现场收集的牧业生产数据及养犬数据,利用累积logistic回归分析了影响细粒棘球蚴病流行程度的因素,初步建立了预测模型。
在所调查的35个行政村中,春季死亡牦牛中的细粒棘球蚴患病率最高达71%,在其中流行程度较高的15个行政村中平均患病率达到(32.49±23.236)%。本研究根据牦牛感染细粒棘球绦虫的情况同时结合现场访问牧民所获得信息,将35个行政村大致分成了4类地区：Ⅰ类地区,重度流行区；Ⅱ类地区,中度流行区;Ⅲ类地区,为低流行区；Ⅳ类地区,流行强度很低的地区或疑似流行区。
利用单因素方差分析,分别分析了户均牲畜数、户均犬数、高程及全天年平均地表温度在不同流行区的差别。分析结果表明：在不同的流行区,户均牲畜数的差别有统计学意义(F=5.834,P=0.003),即流行程度高的地区户均牲畜数大于其它流行区：户均犬数和高程都有随着流行程度降低而减小的整体趋势,然而单因素分析发现其差别并无统计学意义(F=1.328,P=0.283；F=0.758,P=0.526)；全天年平均地表温度在不同的流行程度地区之间的差别无统计学意义(F=0.822,P=0.492)。
利用累积logistic回归进一步分析了影响细粒棘球蚴病流行程度的因素,发现户均牲畜数、高程、户均犬数与流行程度正相关,经检验系数有统计学意义。年平均地表温度与流行程度为负相关。引入交互效应后,发现高程与全天年平均地表温度的交互作用在模型中有统计学意义,使得模型的调整类R2达到59%,次序相关指标和谐对占82%。
以上分析结果显示,细粒棘球蚴病的流行是一个复杂的过程,受到生物、环境、社会等因素的共同影响,这些因素的相互作用对其流行起着重要的作用。同时也说明,细粒棘球蚴病的流行涉及到生态学、环境学与流行病学等学科知识,需要借鉴不同的领域知识来研究。以前类似的研究也表明,利用多学科、多因素的研究方法,最终能够发现这些规律。
Cystic echinococcosis is a severe zoonitic disease caused by the metacestode Echinococcus granulosus.The parasite has a world-wide geographic distribution and occurs in all continents including circumpolar, temperate, subtropical and tropical zones. Within the endemic zones, the prevalence of the parasite varies from sporadic to high whereas. The endemicity degree of echinococcosis is influenced by various factors including biological, environmental and social factors. If we could know how these factors influence the levels of it endemicity, it may help a better understanding of the transmission and support the echinococcosis control work.
The study was conducted in Rangtang County, Sichuan Province. Data related to cystic echinococcosis were collected, including the prevalence of Echinococcus granulosus in yaks died during the spring, livestock production, dog number and other related material. Administrative villages were divided into different classes according to the prevalence of cystic echinococcosis infected yaks died during the spring. Altitude and mean land surface temperature of the study sites were extracted from remote sensing images. The relation between the prevalence of cystic echinococcosis and potential influencing factors including environment and livestock was analyzed with cumulative logistic regression analysis. A prediction model was developed.
The highest prevalence in yaks died during the spring was 71% among the 35 administrative villages surveyed. The mean prevalence in the 15 villages with highest prevalences was (32.49±23.24)%. The 35 administrative villages were classfied into the following 4 categories according to the prevalence in yaks died during the spring and information from local people:Class 1, highly endemic; Class 2, moderately endemic; Class 3, endemic; Class 4, sporadic or suspected.
Statistical analysis of the survey data by the univariate analysis demonstrated that mean livestock number per family was significantly different in statistics between the 4 classes(F=5.834, P=0.003).There was no significant difference in mean dog number per family, altitude and mean land surface temperature, however there was a downtrend following the descent of endemic intensity.
Cumulative logistic regression was used to determine factors that combine best to provide favorable conditions for the endemicity degree of echinococcosis. The mean livestock number per family, mean dog number per family and altitude were found to be positively correlated with endemic intensity. Mean land surface temperature was negatively correlated with endemic intensity. The interaction between mean land surface temperature and altitude was also found to be related to endemic intensity. Max-rescaled R-square and rank correlation index of the prediction model was 59% and 82%, respectively.
This study showed that the transmission of Echinococcus granulosus was a complicated process, influenced by the biological, environmental and social factors. The prediction model in ever study suggested that the pattern how these factors influence the transmission of Echinococcus granulosus could be demonstrated by using an appropriate interdisciplinary approach, and may proved a new clue and scientific basis for selecting a suitable strategy for echinococcosis control.
本研究在四川省壤塘县进行现场研究,以行政村为单位收集了当地牦牛细粒棘球蚴病的流行数据、牧业生产数据以及家庭养犬数据等相关资料,并根据牦牛患病情况,将行政村划分为不同程度的流行区。利用遥感和地理信息系统提取了研究地区相应的自然环境数据包括高程与全天年平均地表温度,同时结合现场收集的牧业生产数据及养犬数据,利用累积logistic回归分析了影响细粒棘球蚴病流行程度的因素,初步建立了预测模型。
在所调查的35个行政村中,春季死亡牦牛中的细粒棘球蚴患病率最高达71%,在其中流行程度较高的15个行政村中平均患病率达到(32.49±23.236)%。本研究根据牦牛感染细粒棘球绦虫的情况同时结合现场访问牧民所获得信息,将35个行政村大致分成了4类地区：Ⅰ类地区,重度流行区；Ⅱ类地区,中度流行区;Ⅲ类地区,为低流行区；Ⅳ类地区,流行强度很低的地区或疑似流行区。
利用单因素方差分析,分别分析了户均牲畜数、户均犬数、高程及全天年平均地表温度在不同流行区的差别。分析结果表明：在不同的流行区,户均牲畜数的差别有统计学意义(F=5.834,P=0.003),即流行程度高的地区户均牲畜数大于其它流行区：户均犬数和高程都有随着流行程度降低而减小的整体趋势,然而单因素分析发现其差别并无统计学意义(F=1.328,P=0.283；F=0.758,P=0.526)；全天年平均地表温度在不同的流行程度地区之间的差别无统计学意义(F=0.822,P=0.492)。
利用累积logistic回归进一步分析了影响细粒棘球蚴病流行程度的因素,发现户均牲畜数、高程、户均犬数与流行程度正相关,经检验系数有统计学意义。年平均地表温度与流行程度为负相关。引入交互效应后,发现高程与全天年平均地表温度的交互作用在模型中有统计学意义,使得模型的调整类R2达到59%,次序相关指标和谐对占82%。
以上分析结果显示,细粒棘球蚴病的流行是一个复杂的过程,受到生物、环境、社会等因素的共同影响,这些因素的相互作用对其流行起着重要的作用。同时也说明,细粒棘球蚴病的流行涉及到生态学、环境学与流行病学等学科知识,需要借鉴不同的领域知识来研究。以前类似的研究也表明,利用多学科、多因素的研究方法,最终能够发现这些规律。
Cystic echinococcosis is a severe zoonitic disease caused by the metacestode Echinococcus granulosus.The parasite has a world-wide geographic distribution and occurs in all continents including circumpolar, temperate, subtropical and tropical zones. Within the endemic zones, the prevalence of the parasite varies from sporadic to high whereas. The endemicity degree of echinococcosis is influenced by various factors including biological, environmental and social factors. If we could know how these factors influence the levels of it endemicity, it may help a better understanding of the transmission and support the echinococcosis control work.
The study was conducted in Rangtang County, Sichuan Province. Data related to cystic echinococcosis were collected, including the prevalence of Echinococcus granulosus in yaks died during the spring, livestock production, dog number and other related material. Administrative villages were divided into different classes according to the prevalence of cystic echinococcosis infected yaks died during the spring. Altitude and mean land surface temperature of the study sites were extracted from remote sensing images. The relation between the prevalence of cystic echinococcosis and potential influencing factors including environment and livestock was analyzed with cumulative logistic regression analysis. A prediction model was developed.
The highest prevalence in yaks died during the spring was 71% among the 35 administrative villages surveyed. The mean prevalence in the 15 villages with highest prevalences was (32.49±23.24)%. The 35 administrative villages were classfied into the following 4 categories according to the prevalence in yaks died during the spring and information from local people:Class 1, highly endemic; Class 2, moderately endemic; Class 3, endemic; Class 4, sporadic or suspected.
Statistical analysis of the survey data by the univariate analysis demonstrated that mean livestock number per family was significantly different in statistics between the 4 classes(F=5.834, P=0.003).There was no significant difference in mean dog number per family, altitude and mean land surface temperature, however there was a downtrend following the descent of endemic intensity.
Cumulative logistic regression was used to determine factors that combine best to provide favorable conditions for the endemicity degree of echinococcosis. The mean livestock number per family, mean dog number per family and altitude were found to be positively correlated with endemic intensity. Mean land surface temperature was negatively correlated with endemic intensity. The interaction between mean land surface temperature and altitude was also found to be related to endemic intensity. Max-rescaled R-square and rank correlation index of the prediction model was 59% and 82%, respectively.
This study showed that the transmission of Echinococcus granulosus was a complicated process, influenced by the biological, environmental and social factors. The prediction model in ever study suggested that the pattern how these factors influence the transmission of Echinococcus granulosus could be demonstrated by using an appropriate interdisciplinary approach, and may proved a new clue and scientific basis for selecting a suitable strategy for echinococcosis control.
引文
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[11]Pedro M, Schantz PM. Echinococcosis:a review[J]. Int J Infect Dis.2009,13 (2):125-133.
[2]Primo Arambulo Ⅲ. Public health importance of cystic echinococcosis in Latin America [J]. Acta Tropica,1997,67(1-2):113-114.
[3]Craig PS, Larreu E. Control of cystic echinococcosis/hydatidosis:1863-2002[J].Adv Parasitol,2006,61:448-450.
[4]Craig PS, McManus DP, Lightowlers MW, et al. Prevention and control of cystic echinococcosis[J].Lancet Infect Dis,2007,7(6):385-394.
[5]李雍龙管晓虹.人体寄生虫学[M].第6版. 北京：人民卫生出版社,2006：157-158.
[6]Eckert J, Gemmell MA, Soulsby EJL棘球蚴病/包虫病监测预防控制指南[M].第1版. 新疆：地方病通报编辑部,1988：440.
[7]Gemmell MA, Roberts MG, Beard TC, et al. Epidemiology. WHO/OIE Manual on Echinococcosis in Humans and Animals:a Public Health Problem of Global Concern, 2001,143-194.
[8]Eckert J, Schantz PM, Gasser PR, et al. Geographic distribution and prevalence. WHO/OIE Manual on Echinococcosis in Humans and Animals:a Public Health Problem of Global Concern,2001,100-134.
[9]孟贺巴特,江莉,柴君杰.新疆包虫病手术病例回顾性调查公报(1951—1990年)[J].地方病通报,1992,7(3)：135-140.
[10]许祺隆.我国西部地区重大寄生虫病的危害及对防治工作的反思[J].中国寄生虫病防治杂志,2002,15(1)：1-3.
[11]柴君杰,叶尔江,常青,等.新疆包虫病流行病学基线的调查研究Ⅱ.家犬和绵羊中细粒棘球绦虫感染[J].地方病通报,1989,4(4)：9-13.
[12]何多龙.青海省包虫病流行与防治[J].中国人畜共患病杂志,2000,16(4)：101-103.
[13]肖保平,李丽,夏清.宁夏人体重要寄生虫病现况调查与研究[M].银川：宁夏人民出版社,2004.1-8.
[14]杨炬,刘天锡.包虫病流行病学研究进展[J].宁夏医学杂志,2008,30(4)：378-379.
[15]叶尔江·苏里唐,江莉.我国棘球蚴病防治研究进展[J].中国寄生虫学与寄生虫病杂志,2000,18(3)：179-181.
[16]Eckert J, Deplazes P, Craig PS, et al. Echinococcosis in animals:clinical aspects,diagnosis and treatment. WHO/OIE Manual on Echinococcosis in Humans and Animals:a Public Health Problem of Global Concern,2001,72-99.
[17]Thompson RCA, McManus DP. Aetiology:parasite and life-cycles. WHO/OIE Manual on Echinococcosis in Humans and Animals:a Public Health Problem of Global Concern, 2001,1-15.
[18]Romig T, Dinkel A, Mackenstedt U. The present situation of echinococcosis in Europe[J]. Parasitol Int,2006,55 Suppl:187-191.
[19]Wang Q, Vuitton DA, Xiao XF, et al. Pasture types and Echinococcus multilocularis, Tibetan communities. Emerg Infect Dis,2006,12(6):1008-1010..
[20]Pedro M, Schantz PM. Echinococcosis:a review[J]. Int J Infect Dis.2009,13(2):125-133.
[21]宋涛,温浩,王云海。哈巴县铁克乡人群包虫病B超诊断调查报告[J].地方病通报,1999,14(3)：48-49.
[21]Danson FM, Craig PS, Man W, et al. Landscape dynamics and risk modelling of human alveolar echinococcosis. Photogramm Eng Remote Sensing.2004,70 (3):359-366.
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