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Article(id=1241065983201309447, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241065978004557893, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410504, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730304000000, receivedDateStr=2024-10-31, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773822788286, onlineDateStr=2026-03-18, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773822788286, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773822788286, creator=13701087609, updateTime=1773822788286, updator=13701087609, issue=Issue{id=1241065978004557893, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='4', pageStart='577', pageEnd='768', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773822787047, creator=13701087609, updateTime=1773823194927, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241067688831808347, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241065978004557893, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241067688831808348, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241065978004557893, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=731, endPage=735, ext={EN=ArticleExt(id=1241065983566213908, articleId=1241065983201309447, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis of the incidence rate and spatial characteristics of echinococcosis in Tibet Autonomous Region, 2019-2023, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the incidence rate, spatial trends and clustering characteristics of the echinococcosis in Tibet Autonomous Region from 2019 to 2023, with the aim of providing a scientific basis for the formulation of targeted prevention and control strategies.

Methods

Utilizing the echinococcosis surveillance data from Tibet Autonomous Region between 2019 and 2023, χ2 tests were conducted using SPSS 25.0 software to compare differences between groups. ArcGIS 10.8 software was used for spatial trend surface analysis and spatial autocorrelation analysis.

Results

From 2019 to 2023, a total of 508 074 individuals were screened in Tibet Autonomous Region, with 460 new cases of echinococcosis identified, resulting in an annual average incidence rate of 0.091%. Significant differences in incidence rates were observed between different years and regions. Spatial trend analysis revealed a higher incidence in the west and lower in the east, with a higher incidence in the middle and lower incidence at both ends in the north-south direction. Spatial autocorrelation analysis indicated that high-high clustering areas were concentrated in southwestern Tibet, while low-low clustering areas were concentrated in central and southern Tibet.

Conclusion

From 2019 to 2023, the incidence of echinococcosis in Tibet Autonomous Region exhibited significant spatial trends and clustering characteristics. It is recommended to strengthen surveillance in southwestern Tibet, assess the epidemiological situation, and explore prevention and control models suitable for this region to reduce the high incidence of echinococcosis.

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目的

分析2019—2023年西藏自治区棘球蚴病发病率及其空间趋势和聚集特征，为制定针对性的防控策略提供科学依据。

方法

利用西藏自治区2019—2023年棘球蚴病监测数据，采用SPSS 25.0软件进行χ2检验比较组间差异，利用ArcGIS 10.8软件进行空间趋势面和空间自相关分析。

结果

在2019—2023年间，西藏自治区共筛查508 074人，发现棘球蚴病新病例460例，年均发病率为0.091%。不同年度及地区间发病率差异显著。空间趋势分析显示，发病率西高东低，南北方向上中间高两端低。空间自相关分析揭示，高-高聚类区主要集中在藏西南部，低-低聚类区则集中在藏中南部。

结论

2019—2023年间，西藏自治区棘球蚴病发病率呈现出显著的空间趋势及聚集性特征。建议加强藏西南部地区监测，评估流行态势，探索适合该地区的防控工作模式，以降低棘球蚴病高发态势。

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贡桑曲珍，E-mail：
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=rRMr8XOxGCXcc8yXOaDdLw==, magXml=BYMhIUmf7bXFSicGp8gs1Q==, pdfUrl=null, pdf=iktgHuJDo2alqxLdVTqXiw==, pdfFileSize=1028879, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=D0QyTqz6bFDd+75cmdrQrQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=haGLbwiT64poWYWTYtVzBg==, mapNumber=null, authorCompany=null, fund=null, authors=

艾佳佳（1991—），女，硕士，主治医师，研究方向：寄生虫病防治研究

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2.国家卫生健康委包虫病防治研究重点实验室
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艾佳佳（1991—），女，硕士，主治医师，研究方向：寄生虫病防治研究

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艾佳佳（1991—），女，硕士，主治医师，研究方向：寄生虫病防治研究

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Infectious Diseases of Poverty, 2019, 8(1): 29., articleTitle=Epidemiological survey of echinococcosis in Tibet Autonomous Region of China, refAbstract=null), Reference(id=1241065998044951029, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, doi=null, pmid=null, pmcid=null, year=2018, volume=36, issue=1, pageStart=26, pageEnd=29, 34, url=null, language=null, rfNumber=[18], rfOrder=23, authorNames=白玛央金, 韩帅, 何瑞峰, journalName=中国寄生虫学与寄生虫病杂志, refType=null, unstructuredReference=白玛央金，韩帅，何瑞峰，等．西藏自治区4种生产类型地区人群棘球蚴病流行情况[J].中国寄生虫学与寄生虫病杂志，2018, 36(1):26-29, 34．, articleTitle=西藏自治区4种生产类型地区人群棘球蚴病流行情况, refAbstract=null), Reference(id=1241065999546511865, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, doi=null, pmid=null, pmcid=null, year=2018, volume=36, issue=1, pageStart=26, pageEnd=29, 34, url=null, language=null, rfNumber=[18], rfOrder=24, authorNames=Bai MYJ, Han S, He RF, journalName=Chinese Journal of Parasitology and Parasitic Diseases, refType=null, unstructuredReference=Bai MYJ, Han S, He RF, et al. Prevalence of hydatid disease in regions of four production types inTibet Autonomous Region[J]. Chinese Journal of Parasitology and Parasitic Diseases, 2018, 36(1): 26-29, 34. (In Chinese), articleTitle=Prevalence of hydatid disease in regions of four production types inTibet Autonomous Region, refAbstract=null), Reference(id=1241065999672340991, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, doi=null, pmid=null, pmcid=null, year=2006, volume=84, issue=9, pageStart=714, pageEnd=721, url=null, language=null, rfNumber=[19], rfOrder=25, authorNames=Yang YR, Sun T, Li ZZ, journalName=Bulletin of the World Health Organization, refType=null, unstructuredReference=Yang YR, Sun T, Li ZZ, et al. Community surveys and risk factor analysis of human alveolar and cystic echinococcosis in Ningxia Hui Autonomous Region, China[J]. Bulletin of the World Health Organization, 2006, 84(9): 714-721., articleTitle=Community surveys and risk factor analysis of human alveolar and cystic echinococcosis in Ningxia Hui Autonomous Region, China, refAbstract=null), Reference(id=1241065999806558728, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, doi=null, pmid=null, pmcid=null, year=2023, volume=16, issue=1, pageStart=181, pageEnd=null, url=null, language=null, rfNumber=[20], rfOrder=26, authorNames=Ma T, Wang Q, Hao MM, journalName=Parasites & Vectors, refType=null, unstructuredReference=Ma T, Wang Q, Hao MM, et al. Epidemiological characteristics and risk factors for cystic and alveolar echinococcosis in China: an analysis of a National population-based field survey[J]. 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(In Chinese), articleTitle=Analysis of the characteristics of the spatial distribution of human echinococciasis in the Tibet Autonomous Region, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1241065986741302123, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, xref=1., ext=[AuthorCompanyExt(id=1241065986745496428, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, companyId=1241065986741302123, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Parasitic Disease Control Institute of Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region 850000, China), AuthorCompanyExt(id=1241065986753885037, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, companyId=1241065986741302123, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.西藏自治区疾病预防控制中心寄生虫病防治所，西藏自治区 拉萨市 850000)]), AuthorCompany(id=1241065986854548340, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, xref=2., ext=[AuthorCompanyExt(id=1241065986862936950, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, companyId=1241065986854548340, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.国家卫生健康委包虫病防治研究重点实验室)]), AuthorCompany(id=1241065987026514815, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, xref=3., ext=[AuthorCompanyExt(id=1241065987039097728, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, companyId=1241065987026514815, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.吉林大学公共卫生学院)])], figs=[ArticleFig(id=1241065992571384044, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=EN, label=Fig.1, caption=Spatial distribution of echinococcosis incidence in Tibet Autonomous Region from 2019 to 2023, figureFileSmall=gBf8F2Kz32P7S9WQqMCuaQ==, figureFileBig=D0QyTqz6bFDd+75cmdrQrQ==, tableContent=null), ArticleFig(id=1241065992693018868, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=CN, label=图1, caption=2019—2023年西藏自治区棘球蚴病发病率空间分布

注：标准地图审图号: GS (2024) 0650号。

, figureFileSmall=gBf8F2Kz32P7S9WQqMCuaQ==, figureFileBig=D0QyTqz6bFDd+75cmdrQrQ==, tableContent=null), ArticleFig(id=1241065992932094213, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=EN, label=Fig.2, caption=Trend surface analysis of echinococcosis incidence in Tibet Autonomous Region from 2019 to 2023, figureFileSmall=T9UcY5bf/H1lu/FDl4LZMw==, figureFileBig=uC4ij75EcXxmm+gbJFWGkw==, tableContent=null), ArticleFig(id=1241065993045340431, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=CN, label=图2, caption=2019—2023年西藏自治区棘球蚴病发病率的趋势面分析, figureFileSmall=T9UcY5bf/H1lu/FDl4LZMw==, figureFileBig=uC4ij75EcXxmm+gbJFWGkw==, tableContent=null), ArticleFig(id=1241065993133420825, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=EN, label=Fig.3, caption=LISA cluster map of echinococcosis incidence in Tibet Autonomous Region from 2019 to 2023, figureFileSmall=ybgwkOjpO5iinUrY3cgLBA==, figureFileBig=YxbWzh4rS7UM6R1vAE+hgg==, tableContent=null), ArticleFig(id=1241065993234084129, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=CN, label=图3, caption=2019—2023年西藏自治区棘球蚴病发病率LISA聚类图, figureFileSmall=ybgwkOjpO5iinUrY3cgLBA==, figureFileBig=YxbWzh4rS7UM6R1vAE+hgg==, tableContent=null), ArticleFig(id=1241065993347330349, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=EN, label=Table 1, caption=

Incidence of echinococcosis in Tibet Autonomous Region from 2019 to 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
年份拉萨市日喀则市山南市林芝市
筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）
201916 2882(0.012)46 01021(0.046)25 5283(0.012)14 2032(0.014)
202011 4953(0.026)22 076102(0.462)26 7964(0.015)7 60510(0.131)
20218 4767(0.083)21 63534(0.157)14 2982(0.014)8 3152(0.024)
20225 1400(0.000)15 96634(0.213)8 2241(0.012)4 7525(0.105)
20238 4727(0.083)21 65826(0.120)12 5822(0.016)8 5903(0.035)
合计Total49 87119(0.038)127 345217(0.170)87 42812(0.014)43 46522(0.051)
年份昌都市那曲市阿里地区合计
筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）
201922 15213(0.059)25 21118(0.071)15 72310(0.064)165 11569(0.042)
202013 91111(0.079)15 7557(0.044)1009165(0.644)107 729202(0.188)
202112 1753(0.025)22 38418(0.080)8 97111(0.123)96 25477(0.080)
20223 3821(0.030)9 4471(0.011)5 0044(0.080)51 91546(0.089)
202311 1192(0.018)1777712(0.068)6 86314(0.204)87 06166(0.076)
合计Total62 73930(0.048)90 57456(0.062)46 652104(0.223)508 074460(0.091)
), ArticleFig(id=1241065993485742387, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=CN, label=表1, caption=

2019—2023年西藏自治区棘球蚴病发病情况

, figureFileSmall=null, figureFileBig=null, tableContent=
年份拉萨市日喀则市山南市林芝市
筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）
201916 2882(0.012)46 01021(0.046)25 5283(0.012)14 2032(0.014)
202011 4953(0.026)22 076102(0.462)26 7964(0.015)7 60510(0.131)
20218 4767(0.083)21 63534(0.157)14 2982(0.014)8 3152(0.024)
20225 1400(0.000)15 96634(0.213)8 2241(0.012)4 7525(0.105)
20238 4727(0.083)21 65826(0.120)12 5822(0.016)8 5903(0.035)
合计Total49 87119(0.038)127 345217(0.170)87 42812(0.014)43 46522(0.051)
年份昌都市那曲市阿里地区合计
筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）		筛查数新发病例数
（发病率，%）
201922 15213(0.059)25 21118(0.071)15 72310(0.064)165 11569(0.042)
202013 91111(0.079)15 7557(0.044)1009165(0.644)107 729202(0.188)
202112 1753(0.025)22 38418(0.080)8 97111(0.123)96 25477(0.080)
20223 3821(0.030)9 4471(0.011)5 0044(0.080)51 91546(0.089)
202311 1192(0.018)1777712(0.068)6 86314(0.204)87 06166(0.076)
合计Total62 73930(0.048)90 57456(0.062)46 652104(0.223)508 074460(0.091)
), ArticleFig(id=1241065995008274752, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=EN, label=Table 2, caption=

Results of global spatial autocorrelation analysis for echinococcosis incidence in Tibet Autonomous Region from 2019 to 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
年Moran IZ得分P值模式
20190.0942.3850.017聚类 Clustered
20200.1216.187<0.001聚类 Clustered
20210.1643.701<0.001聚类 Clustered
2022////
20230.1965.007<0.001聚类 Clustered
), ArticleFig(id=1241065995159269703, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983201309447, language=CN, label=表2, caption=

2019—2023年西藏自治区棘球蚴病发病率全局空间自相关结果

, figureFileSmall=null, figureFileBig=null, tableContent=
年Moran IZ得分P值模式
20190.0942.3850.017聚类 Clustered
20200.1216.187<0.001聚类 Clustered
20210.1643.701<0.001聚类 Clustered
2022////
20230.1965.007<0.001聚类 Clustered
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2019—2023年西藏自治区棘球蚴病发病率及其空间特征分析
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艾佳佳 1, 2, 3 , 季笑遥 1, 2 , 白玛央金 1, 2 , 郑晶莹 3 , 白杨 3 , 朱畅 3 , 次仁拉姆 1, 2 , 贡桑曲珍 1, 2
现代预防医学 | 疾病预防控制 2025,52(4): 731-735
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现代预防医学 | 疾病预防控制 2025, 52(4): 731-735
2019—2023年西藏自治区棘球蚴病发病率及其空间特征分析
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艾佳佳1, 2, 3, 季笑遥1, 2, 白玛央金1, 2, 郑晶莹3, 白杨3, 朱畅3, 次仁拉姆1, 2, 贡桑曲珍1, 2
作者信息
  • 1.西藏自治区疾病预防控制中心寄生虫病防治所，西藏自治区 拉萨市 850000
  • 2.国家卫生健康委包虫病防治研究重点实验室
  • 3.吉林大学公共卫生学院

    • 艾佳佳（1991—），女，硕士，主治医师，研究方向：寄生虫病防治研究

通讯作者:

贡桑曲珍，E-mail：
Analysis of the incidence rate and spatial characteristics of echinococcosis in Tibet Autonomous Region, 2019-2023
Jia-jia AI1, 2, 3, Xiao-yao JI1, 2, BAIMA Yang-Jin1, 2, Jing-ying ZHENG3, Yang BAI3, Chang ZHU3, Cirenlamu1, 2, Gongsangquzhen1, 2
Affiliations
  • Parasitic Disease Control Institute of Tibet Autonomous Region Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region 850000, China
出版时间: 2025-02-25 doi: 10.20043/j.cnki.MPM.202410504
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摘要
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目的

分析2019—2023年西藏自治区棘球蚴病发病率及其空间趋势和聚集特征，为制定针对性的防控策略提供科学依据。

方法

利用西藏自治区2019—2023年棘球蚴病监测数据，采用SPSS 25.0软件进行χ2检验比较组间差异，利用ArcGIS 10.8软件进行空间趋势面和空间自相关分析。

结果

在2019—2023年间，西藏自治区共筛查508 074人，发现棘球蚴病新病例460例，年均发病率为0.091%。不同年度及地区间发病率差异显著。空间趋势分析显示，发病率西高东低，南北方向上中间高两端低。空间自相关分析揭示，高-高聚类区主要集中在藏西南部，低-低聚类区则集中在藏中南部。

结论

2019—2023年间，西藏自治区棘球蚴病发病率呈现出显著的空间趋势及聚集性特征。建议加强藏西南部地区监测，评估流行态势，探索适合该地区的防控工作模式，以降低棘球蚴病高发态势。

棘球蚴病  /  空间自相关  /  空间趋势  /  发病率
Objective

To analyze the incidence rate, spatial trends and clustering characteristics of the echinococcosis in Tibet Autonomous Region from 2019 to 2023, with the aim of providing a scientific basis for the formulation of targeted prevention and control strategies.

Methods

Utilizing the echinococcosis surveillance data from Tibet Autonomous Region between 2019 and 2023, χ2 tests were conducted using SPSS 25.0 software to compare differences between groups. ArcGIS 10.8 software was used for spatial trend surface analysis and spatial autocorrelation analysis.

Results

From 2019 to 2023, a total of 508 074 individuals were screened in Tibet Autonomous Region, with 460 new cases of echinococcosis identified, resulting in an annual average incidence rate of 0.091%. Significant differences in incidence rates were observed between different years and regions. Spatial trend analysis revealed a higher incidence in the west and lower in the east, with a higher incidence in the middle and lower incidence at both ends in the north-south direction. Spatial autocorrelation analysis indicated that high-high clustering areas were concentrated in southwestern Tibet, while low-low clustering areas were concentrated in central and southern Tibet.

Conclusion

From 2019 to 2023, the incidence of echinococcosis in Tibet Autonomous Region exhibited significant spatial trends and clustering characteristics. It is recommended to strengthen surveillance in southwestern Tibet, assess the epidemiological situation, and explore prevention and control models suitable for this region to reduce the high incidence of echinococcosis.

Echinococcosis  /  Spatial autocorrelation  /  Spatial trend  /  Incidence rate
艾佳佳, 季笑遥, 白玛央金, 郑晶莹, 白杨, 朱畅, 次仁拉姆, 贡桑曲珍. 2019—2023年西藏自治区棘球蚴病发病率及其空间特征分析. 现代预防医学, 2025 , 52 (4) : 731 -735 . DOI: 10.20043/j.cnki.MPM.202410504
Jia-jia AI, Xiao-yao JI, BAIMA Yang-Jin, Jing-ying ZHENG, Yang BAI, Chang ZHU, Cirenlamu, Gongsangquzhen. Analysis of the incidence rate and spatial characteristics of echinococcosis in Tibet Autonomous Region, 2019-2023[J]. Modern Preventive Medicine, 2025 , 52 (4) : 731 -735 . DOI: 10.20043/j.cnki.MPM.202410504
正文
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棘球蚴病又称包虫病，是由棘球绦虫幼虫引起的一种人畜共患病，在人类罹患的三种棘球蚴病类型中，囊性棘球蚴病(cystic echinococcosis, CE)和泡性棘球蚴病(alveolar echinococcosis, AE) 因其广泛的地理分布及对医疗系统和经济的深远影响而备受关注。相比之下，多囊棘球蚴病较为罕见，主要局限于中美洲和南美洲地区[1]。棘球蚴病不仅严重威胁人类健康，还给社会造成了巨大的经济损失和疾病负担。据估算，全球范围内，CE和AE每年导致的疾病负担分别为1 009 662和666 433伤残调整寿命年(disability adjusted life years，DALY)[2-3]。我国棘球蚴病疾病负担为322 398 DALY, 其中西藏自治区负担最重，达到了99 667 DALY[4]。2016年的一项调查显示西藏自治区为我国棘球蚴病流行最严重的地区，人群患病率高达1.66% [5]，进一步凸显了该区域棘球蚴病防控的紧迫性和重要性。然而，当前研究多集中于患病状况及影响因素，难以动态捕捉疾病演变及实时评估防控效果。因此，分析棘球蚴病发病率显得尤为迫切，对全面理解疾病动态及优化防控策略至关重要。近年来，空间分析方法在棘球蚴病流行病学研究中应用增多，成功揭示了棘球蚴病的地理分布特征和流行趋势[6]。这些成果对棘球蚴病防控具有重要指导意义。本研究运用空间流行病学方法，深入探究了西藏自治区棘球蚴病发病率的空间趋势及聚集情况，旨在为未来棘球蚴病的预防策略与措施制定提供科学依据。
1　资料与方法
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1.1　资料来源
本研究的数据来源于西藏自治区棘球蚴病监测系统中2019—2023年数据。病例的诊断严格参照《包虫病诊断标准》（WS257-2006）执行。西藏自治区县级地图来源于国家地理信息公共服务平台，审图号为GS（2024）0650号。
1.2　研究方法
1.2.1　空间趋势面分析
空间趋势面分析是一种从全局视角探究观测值的地理分布特征及其局部变化趋势的统计学方法。因变量 Z根据表示 2D 坐标的自变量X和Y进行建模，其中X轴表示东西方向，Y轴表示南北方向[7]。在本研究中，我们将西藏自治区不同县（区）的经纬度坐标及其对应的棘球蚴病发病率数据投影至三维散点图上，直观地呈现不同地理位置的发病率及其在平面上的空间变化趋势。
1.2.2　全局空间自相关分析
全局空间自相关分析是一种评估整个研究区域中变量的空间分布模式和特征的空间统计分析方法，该方法主要使用全局莫兰指数(Moran I )来描述研究区域内的整体空间分布。
Moran I取值范围为-1到1。I>0 表示正空间自相关，I<0 表示负空间自相关，I=0 表示没有空间相关性，呈随机分布[8]。Moran I 的计算公式如下[9]：
其中，n代表县（区）的数量，xi和xj分别代表来自单位索引i和j的自相关指标, 是平均值，wij是空间权重矩阵。
1.2.3　局部空间自相关分析
局部空间自相关分析是一种空间统计分析技术，旨在探究特定研究区域内变量空间分布的局部特征和模式。该技术常采用局部莫兰指数，以揭示单个位置与其相邻位置间的自相关性，进而表明特定聚类及其类型。这些空间聚类可呈现为高-高、高-低、低-高和低-低四种模式[10]。通过LISA（Local Indicators of Spatial Association，局部空间自相关指标）聚类图呈现出局部地区棘球蚴病发病率的关联性。计算公式如下[11]：
在上述公式中n, xi, xj, wij,跟公式（1）中所表达的意思相同。
1.3　统计学方法
采用SPSS 25.0软件进行χ2检验以比较不同年份和地区间棘球蚴病发病率的差异，采用ArcGIS 10.8软件进行空间趋势面及空间自相关分析。所有统计分析的检验水准均设定为α=0.05。
2　结果
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2.1　棘球蚴病发病情况
2019—2023年间，西藏自治区共筛查508 074人，新发棘球蚴病病例460人，年均发病率为0.091%。2019年发病率最低，为0.042%，2020年发病率最高，为0.188%，2019—2023年各年的发病率差异有统计学意义(χ2 =158.66, P<0.001)。阿里地区发病率最高，为0.223%，山南市发病率最低，为0.019%，不同地区发病率差异有统计学意义(χ2=280.95, P<0.001)。表1。
2.2　棘球蚴病的空间分布及趋势
以县为单位，2019—2023年棘球蚴病发病率居前5的县（区）依次为巴青县(0.548%)、仲巴县（2020年发病率8.571%）、仲巴县（2021年发病率0.736%）、左贡县(0.781%)和仲巴县（2023年发病率1.763%）。图1。
2019—2023年（除2022年由于缺失数据的县（区）较多，不能进行趋势面分析）全区在东西方向上呈现西高东低，南北方向上呈现中间高两端低的趋势。图2。
2.3　全局空间自相关
2019—2023年（除2022年由于缺失数据的县（区）太多，无法进行全局空间自相关分析）Moran I均大于0，其数值范围在0.094~0.196之间(且P值均<0.05)，表明各年棘球蚴病发病率均呈空间正相关。表2。
2.4　空间聚集性
2019年棘球蚴病发病率高-高聚类区为巴青县、聂荣县、丁青县；低-低聚类区较多，主要集中在藏中南部地区。2020年高-高聚类区为革吉县、措勤县、仲巴县，低-低聚类区较多，主要集中在藏中南部地区。2021年高-高聚类区增多，包括措勤县、仲巴县、昂仁县、萨嘎县、吉隆县，低-低聚类区减少，转移到了藏东南部地区。2023年只存在高-高和低-高聚类区，其中，高-高聚类区为措勤县、仲巴县。从整体来看，高-高聚类区主要集中在藏西南部地区，而低-低聚类区主要集中在藏中南部地区，所有年份的高-高聚类区周围都检测到低-高聚类区，除改则县外，其余高-低聚类区均聚集在低-低聚类区周围。见图3。
3　讨论
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2019—2023年间，西藏自治区棘球蚴病年均发病率为0.091%，这一数据与青海省2016—2022年发病率相近[12]。其中，发病率2019年最低，2020年最高，原因是2017—2018年西藏自治区开展了棘球蚴病全人群筛查工作，所有病例在这两年均被发现，导致2019年新发病例减少。由于棘球蚴病潜伏期较长，再加上设备的更新，前期感染的病例在2020年发病，发病率升高[13]。而随着棘球蚴病综合防治各项工作的顺利实施，且取得实效，自2021年开始，发病率逐渐下降[14-16]。说明西藏自治区近年来棘球蚴病流行情况有所缓解。
阿里地区棘球蚴病发病率最高，山南市最低。这与Li等人[17] 2019年的研究结果基本一致。从县（区）层面看，藏西南部县域发病率较高，其中，仲巴县最为严重，应引起防控人员高度重视，尽快找出高发原因，改良现有防控措施。空间趋势面分析揭示，2019 至 2023年，棘球蚴病发病率在东西方向上呈现西高东低，南北方向上表现为中部高于两端的趋势。这一空间分布格局可能归因于多重因素的综合作用。具体而言，西部地区多为高海拔县域，且以牧区为主，家畜和犬的数量较多，另外，这些区域普遍缺乏清洁水源，为棘球蚴病的流行提供了有利的环境条件，导致疫情形势严峻[18-20]。因此，我们建议将棘球蚴病的防控重点聚焦于西部地区。首先，要加强规范屠宰场建设；其次，应严格限制犬只数量，实行犬只栓养制度；同时，加大安全饮用水改水工程的投入力度；最后，应强化健康宣传教育工作，培养当地居民形成健康的生活习惯。南北方向上的差异可能归因于中部地区的拉萨市作为西藏自治区经济、文化和交通中心，人口流动性大，医疗资源丰富，使得更多的棘球蚴病例能够被及时发现和诊断。与此同时，北部地区的那曲市自2017年起，实施了一系列有效的棘球蚴病综合防治措施，并取得了显著成效，该地区棘球蚴病的流行得到有效控制[14]。
2019年棘球蚴病发病率高-高聚类区位于藏北部地区，这一发现与贡桑曲珍等人[21] 2018年的一项研究结果相吻合。自2020年，高-高聚类区向西南转移，说明藏北部地区流行形式有所好转[14]，藏西南部地区流行形势不容乐观，这与上述研究结果一致。低-低聚类区主要集中在藏中南部地区，可能是因为这些区域的县（区）海拔偏低，以农业为主，牲畜数量少，不利于棘球蚴病在这些区域的传播。此外，值得注意的是，高-低聚类区多出现在低-低聚类区周边，提示我们应加强对这些县的监控与管理，以防止棘球蚴病向低风险区扩散。同时，低-高聚类区则集中分布在高-高聚类区附近，说明这些区域存在潜在的疾病传播风险，建议加强对这些县界流浪犬的管控及家畜检验检疫工作，防止周边高风险区病变宿主流入，从而有效控制棘球蚴病的传播与蔓延。
综上所述，2019—2023年西藏自治区棘球蚴病发病率存在显著的空间趋势及聚集性，藏西南部为高危险区。建议在今后的防治工作中，应加强西南部地区的监测工作，及时分析和评估流行态势，在现有防治措施的基础上，摸索一套适合西南部地区防治的工作模式，力争降低高发态势。
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2025年第52卷第4期
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doi: 10.20043/j.cnki.MPM.202410504
  • 接收时间：2024-10-31
  • 首发时间：2026-03-18
  • 出版时间：2025-02-25
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  • 收稿日期：2024-10-31
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    1.西藏自治区疾病预防控制中心寄生虫病防治所，西藏自治区 拉萨市 850000
    2.国家卫生健康委包虫病防治研究重点实验室
    3.吉林大学公共卫生学院

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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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