Abstract: Objective　To investigate the feasibility of constructing the risk index of Echinococcus infection based on the classification of echinococcosis lesions, so as to provide insights into the management of echinococcosis. Methods　The imaging data of echinococcosis cases were collected from epidemiological surveys of echinococcosis in China from 2012 to 2016, and the detection of incident echinococcosis cases was captured from the annual echinococcosis prevention and control reports across provinces (autonomous regions) and Xinjiang Production and Construction Corps in China from 2017 to 2022. After echinococcosis lesions were classified, a risk index of Echinococcus infection was constructed based on the principle of discrete distribution marginal probability and multi⁃group classification data tests. The correlation between the risk index of Echinococcus infection and the detection of incident echinococcosis cases was evaluated in the provinces (autonomous regions and corps) from 2017 to 2022, and the correlations between the short⁃ and medium⁃term risk indices and between the medium⁃ and long⁃term risk indices of Echinococcus infection were examined using a univariate linear regression model. Results　A total of 4 014 echinococcosis cases in China from 2012 to 2016 were included in this study. The short⁃, medium⁃ and long⁃term risk indices of E. granulosus infection varied in echinococcosis⁃endemic provinces (autonomous regions and corps) of China ([χ2] = 4.12 to 708.65, all P values < 0.05), with high short⁃ (0.058), medium⁃ (0.137) and long⁃term risk indices (0.104) in Tibet Autonomous Region, and the short⁃, medium⁃ and long⁃term risk indices of E. multilocularis infection varied in echinococcosis⁃endemic provinces (autonomous regions and corps) of China ([χ2] = 6.74 to 122.60, all P values < 0.05), with a high short⁃term risk index in Sichuan Province (0.016) and high medium⁃ (0.009) and long⁃term risk indices in Qinghai Province (0.018). There were no significant correlations between the risk index of E. granulosus infection and the detection of incident cystic echinococcosis cases during the study period (t = -0.518 to 2.265, all P values > 0.05), and strong correlations were found between the risk indices of E. multilocularis infection and the detection of incident alveolar echinococcosis cases (including mixed type) in 2018, 2020, 2021, 2022, during the period from 2017 through 2020, from 2017 through 2021, from 2017 through 2022 (all r values > 0.7, t = 2.521 to 3.692, all P values < 0.05). Linear regression models were established between the risk index of E. multilocular infection and the detection of alveolar echinococcosis cases (including mixed type), and the models were all statistically significant (b = 0.214 to 2.168, t = 2.458 to 3.692, F = 6.044 to 13.629, all P values < 0.05). The regression coefficients for the correlations between the medium⁃ and short⁃term, and between the long⁃ and medium⁃term risk indices of E. granulosus infection were 2.339 and 0.765, and the regression coefficients for the correlations between the medium⁃ and short⁃term, and between the long⁃ and medium⁃term risk indices of E. multilocular infection were 0.280 and 1.842, with statistical significance seen in both the regression coefficients and regression models (t = 16.479 to 197.304, F = 271.570 to 38 928.860, all P values < 0.05). Conclusions　The risk index of Echinococcus infection has been successfully established based on the classification of echinococcosis lesions, which may provide insights into the prevention and control, prediction, diagnosis and treatment, and classified management of echinococcosis.

Key words: Echinococcosis, Lesion classification, Risk index, Correlation analysis, Regression analysis

摘要： 目的　分析基于棘球蚴病病灶分型构建棘球蚴感染风险指数的可行性，从而为棘球蚴病防控提供参考。方法 收集2012—2016年我国棘球蚴病流行病学调查中棘球蚴病病例病灶影像学资料及2017—2022年我国棘球蚴病防治工作年报中各流行省（自治区）及新疆生产建设兵团棘球蚴病新发现病例检出率数据。对棘球蚴病病灶进行分型后，参考离散分布边际概率原理和多分组分类数据检验方法构建棘球蚴感染风险指数。对该指数与2017—2022年各流行省（自治区）和新疆生产建设兵团棘球蚴病新发现病例检出率数据进行相关性分析，建立单因素线性回归模型分析近期与中期、中期与远期棘球蚴感染风险指数间关系。结果　本研究累计纳入2012—2016年我国棘球蚴病病例4 014例。我国各棘球蚴病流行省（自治区）、新疆生产建设兵团间细粒棘球蚴近期、中期和远期感染风险指数均不相同（[χ2] = 4.12 ~ 708.65，P均< 0.05），其中西藏自治区近期（0.058）、中期（0.137）和远期（0.104）细粒棘球蚴感染风险指数均较高；多房棘球蚴近期、中期和远期感染风险指数均不相同（[χ2] = 6.74 ~ 122.60，P均< 0.05），其中四川省近期感染风险指数（0.016）较高，青海省中期（0.009）、远期（0.018）感染风险指数较高。细粒棘球蚴感染风险指数与新发现病例检出率相关性均无统计学意义（t = -0.518 ~ 2.265，P均> 0.05）；多房棘球蚴各期感染风险指数与2018、2020、2021、2022、2017—2020、2017—2021、2017—2022年泡型（含混合型）棘球蚴病新发现病例检出率均呈强相关（r均> 0.7，t = 2.521 ~ 3.692，P均< 0.05）。对多房棘球蚴各期感染风险指数与泡型（含混合型）棘球蚴病新发现病例检出率建立线性回归模型，均有统计学意义（b = 0.214 ~ 2.168，t = 2.458 ~ 3.692，F = 6.044 ~ 13.629，P均< 0.05）。中期与近期、远期与中期细粒棘球蚴感染风险指数间回归系数分别为2.339和0.765，中期与近期、远期与中期多房棘球蚴感染风险指数间回归系数分别为0.280和1.842，回归系数与回归模型均有统计学意义（t = 16.479 ~ 197.304，F = 271.570 ~ 38 928.860，P均< 0.05）。结论　成功建立了一种基于棘球蚴病病灶分型的棘球蚴感染风险指数，可望为棘球蚴病防控、预测、诊疗和分类管理提供参考。 　

关键词: 棘球蚴病, 病灶分型, 风险指数, 相关分析, 回归分析