Abstract: Objective　To investigate the capability for distinguishing between the morphology of Oncomelania hupensis and Tricula snails and its influencing factors among schistosomiasis control professionals in Yunnan Province, so as to evaluate the interference of Tricula snails with O. hupensis surveys. Methods　O. hupensis and Tricula snails were sampled from 9 schistosomiasis⁃endemic counties (districts) in Yunnan Province. The capability for distinguishing between O. hupensis and Tricula snails was evaluated using online questionnaire surveys and field blind tests among schistosomiasis control professionals, and the proportions of correct judgment, misjudgment and missed judgment were calculated. Univariate and multivariate logistic regression models were created using the software SPSS 25.0, and factors affecting the proportion of correct judgments of O. hupensis snails were identified among schistosomiasis control professionals. Results　Questionnaire surveys and field blind tests showed that the overall proportions of correct judgments of O. hupensis snails were 56.77% (2 305/4 060) and 68.28% (1 556/2 279) among schistosomiasis control professionals in Yunnan Province, respectively. Univariate logistic regression analysis of online questionnaire surveys identified gender [odds ratio (OR) = 1.244, 95% confidential interval (CI): (1.073, 1.441), P < 0.05], professional title [OR = 0.628, 1.741, 95% CI: (0.453, 0.871), (1.109, 2.734), both P < 0.05], working duration [OR = 0.979, 95% CI: (0.971, 0.987), P < 0.05] and classification of schistosomiasis epidemics in endemic foci [OR = 1.410, 0.293, 0.523, 95% CI: (1.103, 1.804), (0.237, 0.361), (0.416, 0.657), both P < 0.05] as factors affecting the proportion of correct judgments of O. hupensis snails among schistosomiasis control professionals in Yunnan Province, and multivariate logistic regression analysis after adjustments showed that the proportion of O. hupensis snail misjudgments was 1.179 times higher among male schistosomiasis control professionals than among females [OR = 1.179, 95% CI: (1.006, 1.382), P < 0.05], and 1.474 times higher among schistosomiasis control professionals in schistosomiasis⁃elimination areas with snails than in areas without snails [OR = 1.474, 95% CI: (1.145, 1.898), P < 0.05], and the proportions of missed judgments of O. hupensis snails were 0.284 [OR = 0.284, 95% CI: (0.225, 0.359), P < 0.05] and 0.523 times [OR = 0.523, 95% CI: (0.412, 0.664), P < 0.05] higher among schistosomiasis control professionals in transmission⁃interruption areas with snails and schistosomiasis⁃elimination areas with snails than in schistosomiasis⁃elimination areas without snails. Univariate logistic regression analysis of field blind tests showed identified age [OR = 2.381, 95% CI: (1.677, 3.381), P < 0.05], professional title [OR = 1.688, 95% CI: (1.103, 2.582), P < 0.05］, working duration [OR = 0.970, 95% CI: (0.956, 0.984), P < 0.05] and classification of schistosomiasis epidemics in endemic foci [OR = 0.262, 0.593, 95% CI: (0.188, 0.364), (0.420, 0.837), both P < 0.05] as factors affecting the proportion of correct judgments of O. hupensis snails among schistosomiasis control professionals in Yunnan Province, and multivariate logistic regression analysis after adjustments showed the proportions of missed judgments of O. hupensis snails were 0.263 [OR = 0.263, 95% CI: (0.176, 0.394), P < 0.05] and 0.604 times [OR = 0.604, 95% CI: (0.416, 0.875), P < 0.05] higher among schistosomiasis control professionals in transmission⁃interruption areas with snails and schistosomiasis⁃elimination areas with snails than in schistosomiasis⁃elimination areas without snails. Conclusions　Schistosomiasis control professionals in Yunnan Province have a low accuracy rate for distinguishing between the morphology of O. hupensis and Tricula snails, and gender and classification of schistosomiasis epidemics in endemic foci are factors that affect their ability to distinguish. The presence of Tricula snails causes a high degree of interference with O. hupensis surveys in O. hupensis snail⁃infested areas of Yunnan Province. Reinforced training for distinguishing between O. hupensis and Tricula snails is required among schistosomiasis control professionals in Yunnan Province.

Key words: Oncomelania hupensis, Tricula, Differentiation, Misjudgment, Missed judgement, Yunnan Province

摘要： 目的　评价云南省血吸虫病防治（血防）专业人员对钉螺与拟钉螺形态差异的鉴别能力，并分析其影响因素，评估拟钉螺对钉螺调查工作的干扰程度。方法　在云南省9个血吸虫病流行县（市、区）采集钉螺和拟钉螺，利用线上问卷调查和实物盲测两种方法调查血防专业人员对两种螺的鉴别能力，统计判断正确率、误判率和漏判率。采用统计软件SPSS 25.0建立单因素及多因素logistic回归分析模型，分析影响血防专业人员钉螺判断正确率的因素。结果　问卷调查和实物盲测结果显示，云南省血防专业人员钉螺判断总正确率分别为56.77%（2 305/4 060）和68.28%（1 556/2 279）。线上问卷调查单因素logistic回归分析结果显示，性别［比值比（odds ratio，OR） = 1.244，95%可信区间（confidence interval，CI）：（1.073，1.441），P < 0.05］、职称［OR = 0.628、1.741，95% CI：（0.453，0.871）、（1.109，2.734），P均< 0.05］、工作年限［OR = 0.979，95% CI：（0.971，0.987），P < 0.05］和血吸虫病流行地区达标分类［OR = 1.410、0.293、0.523，95% CI：（1.103，1.804）、（0.237，0.361）、（0.416，0.657），P均< 0.05］是云南省血防专业人员钉螺鉴别正确率的影响因素。校正后经多因素logistic回归分析发现，男性血防专业人员发生误判的概率是女性的1.179倍［OR = 1.179，95% CI：（1.006，1.382），P < 0.05］，消除有螺地区血防专业人员发生误判的概率是消除无螺地区的1.474倍［OR = 1.474，95% CI：（1.145，1.898），P < 0.05］，传播阻断有螺地区和消除有螺地区血防专业人员发生漏判的概率分别是消除无螺地区的0.284倍［OR = 0.284，95% CI：（0.225，0.359），P < 0.05］和0.523倍［OR = 0.523，95% CI：（0.412，0.664），P < 0.05］。现场实物盲测单因素回归分析结果显示，年龄［OR = 2.381，95% CI：（1.677，3.381），P < 0.05］、职称［OR = 1.688，95% CI：（1.103，2.582），P < 0.05］、工作年限［OR = 0.970，95% CI：（0.956，0.984），P < 0.05］和血吸虫病流行地区达标分类［OR = 0.262、0.593，95% CI：（0.188，0.364）、（0.420，0.837），P均< 0.05］是云南省血防专业人员钉螺鉴别正确率的影响因素。校正后经多因素logistic回归分析发现，传播阻断有螺地区和消除有螺地区血防专业人员发生漏判的概率分别是消除无螺地区的0.263倍［OR = 0.263，95% CI：（0.176，0.394），P < 0.05］和0.604倍［OR = 0.604，95% CI：（0.416，0.875），P < 0.05］。结论　云南省血防专业人员对钉螺和拟钉螺鉴别正确率不高，性别和血吸虫病流行地区达标类型是影响鉴别能力的因素。云南省有螺环境拟钉螺对钉螺调查工作造成的干扰程度较高，需加强该省血防专业人员对钉螺与拟钉螺的鉴别培训。

关键词: 钉螺, 拟钉螺, 鉴别, 误判, 漏判, 云南省