Article(id=1240738484370076640, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202501214, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736611200000, receivedDateStr=2025-01-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773744706479, onlineDateStr=2026-03-17, pubDate=1746806400000, pubDateStr=2025-05-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773744706479, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773744706479, creator=13701087609, updateTime=1773744706479, updator=13701087609, issue=Issue{id=1240738480549065614, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='9', pageStart='1537', pageEnd='1728', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773744705569, creator=13701087609, updateTime=1773744787657, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240738824918192654, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240738824922386959, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1700, endPage=1704, ext={EN=ArticleExt(id=1240738484688843768, articleId=1240738484370076640, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Comprehensive assessment of the risk of dengue fever importation and local transmission in Guangxi from ASEAN countries, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To provide a scientific basis for the formulation of effective prevention and control strategies by assessing the risk of dengue fever importation and local transmission in Guangxi from ASEAN countries by 2025.

Methods

Relevant information was collected and organized. The risk of dengue case importation from ASEAN countries was calculated using the Poisson distribution. Based on previous studies on local transmission risk assessment indicators for dengue fever, various factors influencing local transmission were assigned values. The local transmission risk was analyzed and evaluated through quantitative indicators, and the severity of local transmission consequences was qualitatively assessed using an expert consultation method.

Results

There were significant regional differences in the risk of dengue cases being imported from ASEAN countries across the 14 prefecture-level cities in Guangxi from January to December. Nanning and Guilin had a year-round risk of “high” or “very high” for external importation;five cities, including Qinzhou, had “medium” or “high” risk; five cities, including Liuzhou, had “low” or “medium” risk; and Hezhou and Laibin had “very low” or “low” risk. If cases were imported, the risk of local transmission in the 14 prefecture-level cities in Guangxi was assessed as “low” for January to March and December; in April, all cities except Baise were “low”, while others were“medium”; from May to October, the risk was “medium”; in November, four cities including Liuzhou were “low”, while the others were “medium”. Based on comprehensive expert consultations, the risk of dengue importation and local transmission in Guangxi’s 14 prefecture-level cities was assessed as “medium” for 2025.

Conclusion

Due to its geographical location and close exchanges with ASEAN countries, Guangxi faces a higher risk of dengue fever importation and local transmission. The 14 prefecture-level cities should develop dengue prevention and control measures based on the characteristics of dengue importation and the dynamic changes in monitoring indicators, tailored to local conditions and timing, to effectively manage dengue outbreaks.

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目的

通过评估2025年广西面临东盟国家登革热疫情输入及本地传播的风险,为制定有效的防控策略提供科学依据。

方法

收集整理相关信息,采用Poisson分布计算东盟国家登革热病例输入风险,借鉴既往登革热本地传播风险评估指标体系研究结果,对影响登革热本地传播的各个因素进行赋值,通过量化指标分析和评价本地传播风险,采用专家会商法对本地传播后果的严重性进行定性评估。

结果

广西14个设区市1—12月从东盟国家输入登革热病例的风险存在明显的地区差异,南宁市、桂林市全年境外输入风险为高或极高;钦州市等五市为中等或高;柳州市等五市为低或中等;贺州市、来宾市为极低或低。如有病例输入,广西14个设区市1—3月、12月本地传播风险为低;4月除百色市为低外,其他市为中等;5—10月均为中等;11月柳州等四市为低,其余为中等。经专家会商综合研判,2025年广西14个设区市登革热输入和本地传播风险为中等。

结论

广西由于其地理位置和与东盟国家密切的交流,面临较高的登革热疫情输入和本地传播风险,14个设区市应根据辖区登革热输入特点及监测指标的动态变化,因地、因时制定登革热防控措施,科学防控登革热疫情。

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梁羡篁,E-mail:
林玫,E-mail:;梁羡篁与林玫为共同通信作者
, 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=RLG7ZvHVb2GH4uP3cS6aqQ==, magXml=mKcxrQlYsKQ03XW6I9M9cA==, pdfUrl=null, pdf=vV0TBLjP5QS2Kbdg8CtbsQ==, pdfFileSize=740813, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=Ur1x3VVBC4802jhZUSM1Pw==, mapNumber=null, authorCompany=null, fund=null, authors=

任美璇(1985—),女,硕士,副主任医师,研究方向:传染病控制、卫生应急管理

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Epidemiological analysis of dengue fever in Fuzhou city from 2016 to 2021[J]. Journal of Tropical Medicine,2023, 23(6): 860-862, 866.(In Chinese), articleTitle=Epidemiological analysis of dengue fever in Fuzhou city from 2016 to 2021, refAbstract=null)], funds=[Fund(id=1241081880485876585, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, awardId=S2018063, language=CN, fundingSource=广西医疗卫生适宜技术开发与推广应用项目(S2018063), fundOrder=null, country=null), Fund(id=1241081880586539888, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, awardId=202001, language=CN, fundingSource=中心资助青年科技工作者科研课题(202001), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241081871669449133, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, xref=1., ext=[AuthorCompanyExt(id=1241081871682032048, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, companyId=1241081871669449133, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi 530028, China), AuthorCompanyExt(id=1241081871690420657, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, companyId=1241081871669449133, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.广西壮族自治区疾病预防控制中心,广西 南宁 530028)]), AuthorCompany(id=1241081871812055485, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, xref=2., ext=[AuthorCompanyExt(id=1241081871820444094, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, companyId=1241081871812055485, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.广西重大传染病防控与生物安全应急响应重点实验室,广西 南宁 530028)])], figs=[ArticleFig(id=1241081878015431464, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, language=EN, label=Table 1, caption=

Score scale for risk assessment of local transmission of dengue imported cases in Guangxi

, figureFileSmall=null, figureFileBig=null, tableContent=
评估指标权重系数指标解释和评分标准资料来源
媒介分布情况0.039 3是否有白纹伊蚊或埃及伊蚊分布:是=1分,否=0分常规监测
蚊媒密度0.040 9布雷图指数(BI):BI<5=0分,5≤BI<10 =0.5分,10≤BI<20=0.75分,
≥20=1分
常规监测
降雨量:月降雨量100~300 mm=0.5分,300~400 mm=0.25分,低于100 mm
气候条件0.037 7或高于400 mm=0分;本月温度:月均25~30 ℃=0.5分,20~24 ℃或31~广西统计年鉴
32 ℃=0.25分,否则=0分
流行季节0.040 9是否为登革热流行季节:是=1分,否=0分常规监测
既往疫情情况0.036 0是否有本地病例报告:无报告=0分,1~4例=0.25分,5~9例=0.5分,10~
99例=0.75分,≥100例=1分
中国疾病预防控制信息系统
人员流动情况0.063 7月均迁徙指数:<1=0分,1~3=0.5分,>3=1分百度迁徙指数
人员密度0.060 4人口密度:人口密度<100人/km2=0分,人口密度100~300人/ km2=0.5分,人
口密度>300人/km2=1分
广西统计年鉴
健康宣教0.042 6以百度资讯指数替代,按1-资讯指数/1 000计分百度资讯指数
防蚊情况0.049 2以既往病例防蚊灭蚊情况替代,按1-防蚊率计分登革热流行病学个案调查表
以生活垃圾清运量及城市绿化率替代,生活垃圾清运量:日人均生活垃圾清
家居环境0.045 9运量≤0.6 kg/(人/d)=0.5分,否则=0分;绿化率:城市绿化率≥40%=0分,40%广西统计年鉴
>绿化率≥25%=0.25分,<25%=0.5分
媒介监测与报告0.044 3定期开展蚊媒监测并通报:是=0分,否=1分通报记录
媒介监测结果利用0.048 5是否根据蚊媒监测结果开展灭蚊工作:是=0分,否=1分工作记录
建立长效灭蚊机制0.046 4是否建立长效灭蚊机制:是=0分,否=1分预案方案
环境治理措施0.042 2国家卫生城市:按1-县区级国家卫生城市占比计分政府报告
诊疗与发现能力0.096 6发病到诊断时间间隔:3~4 d=0.5分,4~5 d=0.75,>5 d=1分,<3 d=
0分,无病例则用平均值代替
中国疾病预防控制信息系统
病例管理情况0.086 1所有病例是否防蚊隔离治疗:是=0分,否=1分中国疾病预防控制信息系统
分析与评估0.027 4是否建立专题风险评估机制:是=0分,否=1分工作记录
突发事件处置能力0.029 5根据专题调查结果,按(1-规范处置指数)计分专项调查
应急物资储备0.027 4应急物资储备专项调查:足够=0分,稍显不足=0.5分,缺乏=1分专项调查
快速灭蚊机制0.031 6是否建立快速灭蚊机制:是=0分,否=1分预案方案
社区干预能力0.031 6查阅历史疫情处理情况判断,公众配合社区开展人工发现并清除积水等清除
蚊媒孳生地活动=0分,否则=1分
中国疾病预防控制信息系统
联防联控情况0.031 6是否建立联防联控机制:是=0分,否=1分预案方案
), ArticleFig(id=1241081878216758064, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, language=CN, label=表1, caption=

广西登革热病例输入引起本地传播疫情风险评估评分量表

, figureFileSmall=null, figureFileBig=null, tableContent=
评估指标权重系数指标解释和评分标准资料来源
媒介分布情况0.039 3是否有白纹伊蚊或埃及伊蚊分布:是=1分,否=0分常规监测
蚊媒密度0.040 9布雷图指数(BI):BI<5=0分,5≤BI<10 =0.5分,10≤BI<20=0.75分,
≥20=1分
常规监测
降雨量:月降雨量100~300 mm=0.5分,300~400 mm=0.25分,低于100 mm
气候条件0.037 7或高于400 mm=0分;本月温度:月均25~30 ℃=0.5分,20~24 ℃或31~广西统计年鉴
32 ℃=0.25分,否则=0分
流行季节0.040 9是否为登革热流行季节:是=1分,否=0分常规监测
既往疫情情况0.036 0是否有本地病例报告:无报告=0分,1~4例=0.25分,5~9例=0.5分,10~
99例=0.75分,≥100例=1分
中国疾病预防控制信息系统
人员流动情况0.063 7月均迁徙指数:<1=0分,1~3=0.5分,>3=1分百度迁徙指数
人员密度0.060 4人口密度:人口密度<100人/km2=0分,人口密度100~300人/ km2=0.5分,人
口密度>300人/km2=1分
广西统计年鉴
健康宣教0.042 6以百度资讯指数替代,按1-资讯指数/1 000计分百度资讯指数
防蚊情况0.049 2以既往病例防蚊灭蚊情况替代,按1-防蚊率计分登革热流行病学个案调查表
以生活垃圾清运量及城市绿化率替代,生活垃圾清运量:日人均生活垃圾清
家居环境0.045 9运量≤0.6 kg/(人/d)=0.5分,否则=0分;绿化率:城市绿化率≥40%=0分,40%广西统计年鉴
>绿化率≥25%=0.25分,<25%=0.5分
媒介监测与报告0.044 3定期开展蚊媒监测并通报:是=0分,否=1分通报记录
媒介监测结果利用0.048 5是否根据蚊媒监测结果开展灭蚊工作:是=0分,否=1分工作记录
建立长效灭蚊机制0.046 4是否建立长效灭蚊机制:是=0分,否=1分预案方案
环境治理措施0.042 2国家卫生城市:按1-县区级国家卫生城市占比计分政府报告
诊疗与发现能力0.096 6发病到诊断时间间隔:3~4 d=0.5分,4~5 d=0.75,>5 d=1分,<3 d=
0分,无病例则用平均值代替
中国疾病预防控制信息系统
病例管理情况0.086 1所有病例是否防蚊隔离治疗:是=0分,否=1分中国疾病预防控制信息系统
分析与评估0.027 4是否建立专题风险评估机制:是=0分,否=1分工作记录
突发事件处置能力0.029 5根据专题调查结果,按(1-规范处置指数)计分专项调查
应急物资储备0.027 4应急物资储备专项调查:足够=0分,稍显不足=0.5分,缺乏=1分专项调查
快速灭蚊机制0.031 6是否建立快速灭蚊机制:是=0分,否=1分预案方案
社区干预能力0.031 6查阅历史疫情处理情况判断,公众配合社区开展人工发现并清除积水等清除
蚊媒孳生地活动=0分,否则=1分
中国疾病预防控制信息系统
联防联控情况0.031 6是否建立联防联控机制:是=0分,否=1分预案方案
), ArticleFig(id=1241081878439056191, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, language=EN, label=Table 2, caption=

Risk probability of dengue fever imported from ASEAN countries to 14 cities in Guangxi

, figureFileSmall=null, figureFileBig=null, tableContent=
地区风险概率
1月2月3月4月5月6月7月8月9月10月11月12月
南宁市0.920.870.800.740.840.900.960.970.940.900.960.86
柳州市0.330.270.220.190.250.300.400.440.350.310.390.26
桂林市0.930.880.810.750.850.910.970.980.940.910.960.87
梧州市0.170.140.110.090.130.160.210.240.180.160.200.13
北海市0.580.490.420.360.460.530.660.700.600.540.650.48
防城港市0.810.730.650.580.690.770.880.910.830.780.870.72
钦州市0.650.570.480.430.530.610.740.780.670.620.720.55
贵港市0.630.540.460.410.500.590.720.750.650.590.700.53
玉林市0.250.200.170.140.180.230.310.340.260.230.290.20
百色市0.360.300.240.210.270.330.430.470.380.330.420.29
贺州市0.180.150.120.100.130.170.230.250.190.170.220.14
河池市0.280.230.190.160.210.250.340.370.300.260.330.22
来宾市0.040.030.030.020.030.040.060.060.050.040.050.03
崇左市0.670.590.500.450.550.630.760.800.700.640.740.57
), ArticleFig(id=1241081878564885323, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, language=CN, label=表2, caption=

东盟国家登革热输入广西14个设区市风险概率

, figureFileSmall=null, figureFileBig=null, tableContent=
地区风险概率
1月2月3月4月5月6月7月8月9月10月11月12月
南宁市0.920.870.800.740.840.900.960.970.940.900.960.86
柳州市0.330.270.220.190.250.300.400.440.350.310.390.26
桂林市0.930.880.810.750.850.910.970.980.940.910.960.87
梧州市0.170.140.110.090.130.160.210.240.180.160.200.13
北海市0.580.490.420.360.460.530.660.700.600.540.650.48
防城港市0.810.730.650.580.690.770.880.910.830.780.870.72
钦州市0.650.570.480.430.530.610.740.780.670.620.720.55
贵港市0.630.540.460.410.500.590.720.750.650.590.700.53
玉林市0.250.200.170.140.180.230.310.340.260.230.290.20
百色市0.360.300.240.210.270.330.430.470.380.330.420.29
贺州市0.180.150.120.100.130.170.230.250.190.170.220.14
河池市0.280.230.190.160.210.250.340.370.300.260.330.22
来宾市0.040.030.030.020.030.040.060.060.050.040.050.03
崇左市0.670.590.500.450.550.630.760.800.700.640.740.57
), ArticleFig(id=1241081878699103054, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, language=EN, label=Table 3, caption=

Risk probability of local transmission caused by imported dengue fever cases in 14 cities of Guangxi

, figureFileSmall=null, figureFileBig=null, tableContent=
地区风险概率
1月2月3月4月5月6月7月8月9月10月11月12月
南宁市0.100.100.070.380.460.480.490.540.590.550.330.27
柳州市0.070.070.070.330.380.400.420.420.490.460.290.20
桂林市0.070.070.070.330.390.400.610.570.540.470.280.19
梧州市0.070.070.080.420.500.530.640.630.670.620.440.22
北海市0.070.070.070.470.560.580.610.590.680.640.460.25
防城港市0.080.080.080.350.450.480.510.440.570.530.340.23
钦州市0.080.080.080.380.450.450.460.510.520.510.320.23
贵港市0.070.070.080.390.460.460.450.550.550.520.340.25
玉林市0.070.070.080.390.470.490.460.520.590.520.340.25
百色市0.070.070.080.290.390.400.380.400.470.460.260.17
贺州市0.080.080.080.330.410.420.420.420.480.590.320.20
河池市0.080.080.080.320.400.420.420.420.420.450.290.20
来宾市0.080.080.080.350.440.440.460.460.430.500.310.23
崇左市0.070.070.080.320.430.450.450.450.450.500.310.22
), ArticleFig(id=1241081878837515095, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738484370076640, language=CN, label=表3, caption=

登革热病例输入广西14个设区市引起本地传播风险概率

, figureFileSmall=null, figureFileBig=null, tableContent=
地区风险概率
1月2月3月4月5月6月7月8月9月10月11月12月
南宁市0.100.100.070.380.460.480.490.540.590.550.330.27
柳州市0.070.070.070.330.380.400.420.420.490.460.290.20
桂林市0.070.070.070.330.390.400.610.570.540.470.280.19
梧州市0.070.070.080.420.500.530.640.630.670.620.440.22
北海市0.070.070.070.470.560.580.610.590.680.640.460.25
防城港市0.080.080.080.350.450.480.510.440.570.530.340.23
钦州市0.080.080.080.380.450.450.460.510.520.510.320.23
贵港市0.070.070.080.390.460.460.450.550.550.520.340.25
玉林市0.070.070.080.390.470.490.460.520.590.520.340.25
百色市0.070.070.080.290.390.400.380.400.470.460.260.17
贺州市0.080.080.080.330.410.420.420.420.480.590.320.20
河池市0.080.080.080.320.400.420.420.420.420.450.290.20
来宾市0.080.080.080.350.440.440.460.460.430.500.310.23
崇左市0.070.070.080.320.430.450.450.450.450.500.310.22
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广西面临东盟国家登革热疫情输入及本地传播风险的综合评估
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任美璇 1 , 熊绮梦 1 , 周健宇 1 , 黄元华 1 , 何为涛 1 , 唐洁霞 1 , 林玫 1, 2 , 梁羡篁 1
现代预防医学 | 疾病预防控制 2025,52(9): 1700-1704
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现代预防医学 | 疾病预防控制 2025, 52(9): 1700-1704
广西面临东盟国家登革热疫情输入及本地传播风险的综合评估
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任美璇1, 熊绮梦1, 周健宇1, 黄元华1, 何为涛1, 唐洁霞1, 林玫1, 2 , 梁羡篁1
作者信息
  • 1.广西壮族自治区疾病预防控制中心,广西 南宁 530028
  • 2.广西重大传染病防控与生物安全应急响应重点实验室,广西 南宁 530028
  • 任美璇(1985—),女,硕士,副主任医师,研究方向:传染病控制、卫生应急管理

通讯作者:

梁羡篁,E-mail:
林玫,E-mail:;梁羡篁与林玫为共同通信作者
Comprehensive assessment of the risk of dengue fever importation and local transmission in Guangxi from ASEAN countries
Mei-xuan REN1, Qi-meng XIONG1, Jian-yu ZHOU1, Yuan-hua HUANG1, Wei-tao HE1, Jie-xia TANG1, Mei LIN1, 2 , Xian-huang LIANG1
Affiliations
  • Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi 530028, China
出版时间: 2025-05-10 doi: 10.20043/j.cnki.MPM.202501214
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目的

通过评估2025年广西面临东盟国家登革热疫情输入及本地传播的风险,为制定有效的防控策略提供科学依据。

方法

收集整理相关信息,采用Poisson分布计算东盟国家登革热病例输入风险,借鉴既往登革热本地传播风险评估指标体系研究结果,对影响登革热本地传播的各个因素进行赋值,通过量化指标分析和评价本地传播风险,采用专家会商法对本地传播后果的严重性进行定性评估。

结果

广西14个设区市1—12月从东盟国家输入登革热病例的风险存在明显的地区差异,南宁市、桂林市全年境外输入风险为高或极高;钦州市等五市为中等或高;柳州市等五市为低或中等;贺州市、来宾市为极低或低。如有病例输入,广西14个设区市1—3月、12月本地传播风险为低;4月除百色市为低外,其他市为中等;5—10月均为中等;11月柳州等四市为低,其余为中等。经专家会商综合研判,2025年广西14个设区市登革热输入和本地传播风险为中等。

结论

广西由于其地理位置和与东盟国家密切的交流,面临较高的登革热疫情输入和本地传播风险,14个设区市应根据辖区登革热输入特点及监测指标的动态变化,因地、因时制定登革热防控措施,科学防控登革热疫情。

风险评估  /  登革热  /  输入性传染病
Objective

To provide a scientific basis for the formulation of effective prevention and control strategies by assessing the risk of dengue fever importation and local transmission in Guangxi from ASEAN countries by 2025.

Methods

Relevant information was collected and organized. The risk of dengue case importation from ASEAN countries was calculated using the Poisson distribution. Based on previous studies on local transmission risk assessment indicators for dengue fever, various factors influencing local transmission were assigned values. The local transmission risk was analyzed and evaluated through quantitative indicators, and the severity of local transmission consequences was qualitatively assessed using an expert consultation method.

Results

There were significant regional differences in the risk of dengue cases being imported from ASEAN countries across the 14 prefecture-level cities in Guangxi from January to December. Nanning and Guilin had a year-round risk of “high” or “very high” for external importation;five cities, including Qinzhou, had “medium” or “high” risk; five cities, including Liuzhou, had “low” or “medium” risk; and Hezhou and Laibin had “very low” or “low” risk. If cases were imported, the risk of local transmission in the 14 prefecture-level cities in Guangxi was assessed as “low” for January to March and December; in April, all cities except Baise were “low”, while others were“medium”; from May to October, the risk was “medium”; in November, four cities including Liuzhou were “low”, while the others were “medium”. Based on comprehensive expert consultations, the risk of dengue importation and local transmission in Guangxi’s 14 prefecture-level cities was assessed as “medium” for 2025.

Conclusion

Due to its geographical location and close exchanges with ASEAN countries, Guangxi faces a higher risk of dengue fever importation and local transmission. The 14 prefecture-level cities should develop dengue prevention and control measures based on the characteristics of dengue importation and the dynamic changes in monitoring indicators, tailored to local conditions and timing, to effectively manage dengue outbreaks.

Risk assessment  /  Dengue fever  /  Imported infectious diseases
任美璇, 熊绮梦, 周健宇, 黄元华, 何为涛, 唐洁霞, 林玫, 梁羡篁. 广西面临东盟国家登革热疫情输入及本地传播风险的综合评估. 现代预防医学, 2025 , 52 (9) : 1700 -1704 . DOI: 10.20043/j.cnki.MPM.202501214
Mei-xuan REN, Qi-meng XIONG, Jian-yu ZHOU, Yuan-hua HUANG, Wei-tao HE, Jie-xia TANG, Mei LIN, Xian-huang LIANG. Comprehensive assessment of the risk of dengue fever importation and local transmission in Guangxi from ASEAN countries[J]. Modern Preventive Medicine, 2025 , 52 (9) : 1700 -1704 . DOI: 10.20043/j.cnki.MPM.202501214
登革热是由登革病毒引起的蚊媒传染病,广泛流行于东南亚、西太平洋和美洲等130多个国家和地区[1-2]。自2021年以来,全球登革热病例数呈逐年增加态势,流行区域持续扩大,截至2024年8月,全球已累积报告1 230万例登革热病例,几乎是2023年全年报告病例的两倍,这不仅造成了巨大的经济、社会和健康负担[1-3],也成为了全球性的公共卫生问题。气候变化、跨国旅行、地方环境和个人卫生是促进登革热快速地理传播的主要因素[1-3]。在全球化日益加深的今天,我国也面临着登革热输入和本地传播的风险,其中东南亚和南亚国家是主要输入来源国[4],包括广西在内的6省发生了因输入病例导致的规模性疫情[4-5],对居民健康和地方经济都造成了不同程度的损害[6]。广西作为中国-东盟经济贸易桥头堡以及21世纪海上丝绸之路和丝绸之路经济带有机衔接的重要门户,随着我国与东盟国家人员和货物往来的进一步深入,登革热病例跨国传播的风险将进一步升高[6]。为了及时预警和处置登革热疫情,本研究拟通过定量和定性风险评估相结合的方法,对2025年1—12月东盟国家登革热病例输入广西及引发本地传播的风险进行评估,为登革热防控策略和措施制定提供依据。
通过世界卫生组织官网(WHO)、广西统计年鉴、城市统计年鉴、广西旅游局、南宁海关、中国疾病预防控制信息系统查阅既往东盟国家登革热疫情情况及人口数[7]、广西14个设区市人口密度以及气候条件、环境、绿化率、东盟国家入境人数、既往病例输入和本地疫情等基础信息。采用Web Scraping与API集成技术结合的方式来实时获取第三方平台的网页动态数据信息,利用Python编程语言及其数据处理与分析库编制数据处理与分析程序,对网页数据进行清洗、整合、转换以及解析HTML/JSON格式的数据,再通过正则表达式、XPath等技术,从复杂的网页结构中准确提取所需信息并完成数据的去重、异常值处理以及缺失值填充,建立基础信息数据库。
各设区市应急物资储备情况、突发公共卫生事件应对能力、传染病防控机制、蚊媒密度等信息通过各市疾控中心监测分析报告、工作报告或专题调查获得。
由于东盟国家登革热的月发病率低于1‰,因此可以认为每月东盟国家入境广西的人员中发病数X近似服从泊松分布。其中,n代表东盟国家入境人数,π表示入境人员感染登革热的概率,那么,病例输入的概率P输入可以通过公式P输入=[1-P(X=0)]计算,即通过计算入境人员中没有发病的概率的补集,得到登革热病例输入的可能性。因泊松分布的概率质量函数为,其中λ=nπ为泊松分布的平均发病数。将X=0代入上述公式,得到,因此,病例输入的可能性P输入可以表示为。2025年东盟国家入境广西14个设区市的人数通过计算近10年入境人数平均增长率估算,入境人员感染概率通过2024年东盟国家登革热发病率估算。
事件发生风险等级根据WHO给出的风险事件发生可能性示例[8]判定,即发生概率P值:(1)P≥0.95,几乎肯定事件会发生,等级为极高;(2)0.7≤P≤0.94,事件很可能发生,等级为高;(3)0.3≤P≤0.69,事件可能会发生,等级为中等;(4)0.05≤P≤0.29,事件不太可能发生,等级为低;(5)P<0.05,事件极不可能发生,等级为极低。
采用中国疾控关于登革热输入与传播指标体系研究成果[4]构建广西登革热本地传播风险的评估指标。采用层次分析法[9-11]构建层次结构模型和计算各评估指标的权重,采用查阅文献及专家会商的方式制定评分标准,获得登革热输入病例引起本地传播风险评分量表,见表1
根据量表评分标准,采用Python编程语言编制应用程序,将获得的指标原始值导入程序,按照程序既定的计算规则进行赋值并根据赋值结果计算风险分值R=W1×S1+ W2×S2+……+ Wn×Sn,其中W为评估指标权重,S为评估指标赋值。本地传播的可能性等级也参照WHO的“风险事件发生可能性示例”划分为5个等级。
参照WHO“事件发生后果严重性定义示例”及“风险判断矩阵”[812-13],采用专家会商法组织蚊媒、传染病、应急管理专家对本地传播疫情发生后的后果严重性进行定性风险评估,并对事件的风险等级进行评价。
广西14个设区市1—12月东盟国家登革热病例输入概率见表2。按照WHO风险等级划分,2025年1—12月,南宁市(0.74~0.97)、桂林市(0.75~0.98)境外登革热病例输入概率较高,风险等级为高或极高;防城港市(0.58~0.91)、崇左市(0.45~0.80)、钦州市(0.43~0.78)、北海市(0.36~0.70)、贵港市(0.41~0.75)境外输入概率中等,风险等级为中等或高;百色市(0.21~0.47)、柳州市(0.19~0.44)、河池市(0.16~0.37)、玉林市(0.14~0.34)、梧州市(0.09~0.24)、贺州市(0.10~0.25)境外输入概率较低,风险等级为低或中等;来宾市(0.02~0.06)境外输入概率极低,风险等级为极低或低。
广西14个设区市1—12月因登革热病例输入导致本地传播的风险概率见表3。广西14个设区市1—3月、12月风险分值在0.07~0.27之间,发生登革热本地传播的风险低;4月除百色市(0.29)传播风险为低外,其他13个设区市风险分值在0.32~0.47之间,本地传播风险中等;5—10月14个设区市风险分值在0.38~0.68之间,本地传播风险中等;11月柳州市(0.29)、桂林市(0.28)、河池市(0.29)、百色市(0.26)本地传播风险为低,其他地区风险分值在0.31~0.46之间,本地传播风险中等。
通过对2025年1—12月广西14个设区市东盟国家登革热输入与本地传播风险进行定量和定性风险评估,结果揭示了登革热疫情发生风险的空间分布特征,在人口密集且国际交往频繁的城市及其周边地区、出入境口岸地区将面临较高的输入风险,临近热带海洋的桂南地区发生本地传播风险总体较其他地区高,经专家会商,如发生登革热本地疫情,老人、儿童、孕妇等特殊人群由于身体免疫力相对较低或存在特殊生理状态,抵抗力较弱,感染后病情可能较重,为控制本地疫情,需要政府投入额外的费用进行大规模灭蚊,动员社区来控制疫情扩散,会对群众生产和生活造成一定的影响,综合专家研判,本地传播疫情发生后的后果严重性为“中等”,各地区应在辖区风险月份对登革热予以重点关注,采取综合性的防控措施控制本地传播风险。
传染病风险评估是通过识别和评估传染病发生过程中的潜在风险和薄弱环节,提出应对措施的一种辅助决策工具。作为公共卫生领域的一项重要工作,对于提升传染病疫情早期监测预警能力,有效防范和应对公共卫生风险,保障公众健康和降低传播风险具有至关重要的意义,是推动疾控事业高质量发展的重要组成部分[12]。传染病风险评估是一个复杂而多维的过程,它通常采用定量、定性或定量和定性相结合的方法开展[12-13],以适应不同情境下的需求。在日常工作中,由于评估时限、指标获取难度等客观条件限制,专家会商法等定性方法常被作为主要手段,这种方法能够快速有效地进行风险评估和应对,在疫情暴发初期或面对新型传染病时尤为适用。然而,专家会商过程中受专家团队的多样性及其专业视角差异的影响,导致评估结果的准确性和客观性可能受限,风险评估结果可能会有所不同,且不同地区、不同时间的评估结果往往难以直接比较。为应对这些局限性,定量风险评估方法得以发展并广泛应用。定量风险评估通过数理统计的方式对风险因素进行量化,采用收集到的直接或间接指标估计风险值,并根据风险分值范围进行风险分析和评价。由于风险分值的计算来源于客观指标,因此能够避免受专家主观影响造成的偏倚,确保评估结果稳定性。此外,定量风险评估方法具备考虑更多变量和因素的优势,从而能够给出更为全面的风险评估结果。通过将风险进行量化处理,不同地区和不同时间之间的风险等级可以直接进行比较和优先级排序。这种评估方法确保了结果在各种时间和情境下都具备一致性,对于决策者制定长期规划和进行风险管理至关重要。特别是在防控资源有限的情况下,它能够帮助识别高风险区域和重点人群,从而优化资源配置,确保防控措施的高效性和针对性[13]
本研究通过定量与定性相结合的方式,评估2025年东盟国家登革热病例输入广西及引发本地传播的风险。结果表明,南宁市等综合贸易交通枢纽城市、桂林市等国际旅游城市以及钦州市、北海市、防城港市、崇左市等沿边沿海地区登革热境外输入的风险较其他地区高,提示在入境人员感染概率相同的情况下,各市应根据辖区人员流动特点、与东盟国家经济交往情况,因地制宜开展针对性的防控措施,如口岸地区密切关注主要入境国家登革热疫情态势,并在流行季节加强对出入境人员的健康宣教和病例筛查,及时发现输入病例,实现关口前移;综合性城市及旅游城市加强交通、商业中心、接待场馆、旅游景点、老旧城区等重点场所的环境治理,清除蚊媒孳生地,降低本地传播风险。本地传播风险分值结果表明,虽然在5—10月14个设区市的本地传播风险均为中等,但各市风险分值呈现逐月增加的态势,在7—10月达最大值,与广西历史监测结果相符[5],也与其他省份研究结果相近[14-19];在相同月份,广西南部地区的风险分值总体高于其他地区,提示在制定防控措施时,各地应根据辖区地理气候特点、风险指标的动态变化和薄弱环节,在高风险月份提高关注度,适时调整本辖区的风险管理措施,如通过加强健康宣教、增加发热门诊和加强病原学检测等方式提高病例的发现能力,降低本地传播风险。
定量风险评估在传染病预警与管理中扮演着关键角色,但其准确性高度依赖于数据的质量和完整性。本次登革热境外输入及本地传播风险研究中,部分指标采用了估算值、替代值或历史值,这些数据并非实时数据。因此,评估指标的准确性存在一定程度的不确定性,导致风险分值的结果可能出现偏差,这是定量评估方法的局限性所在[13]。定量评估依赖于大量长期稳定且准确的数据来源,因而这种方法并不适用于新发传染病或需要快速响应的风险评估场景。评估结果可能高估或低估实际风险,这取决于所用数据的时效性与准确性。若采用的估算值或历史值无法全面反映当前疫情的实际情况,例如当地登革热的发病率、人口流动、蚊虫密度等关键因素发生变化,那么风险评估的结果便可能出现偏倚,当实际值高于估算值或历史值时,评估结果将低估实际风险;反之则可能高估风险。高估风险可能导致资源过度配置,低估风险则可能延误关键防控措施的及时实施。需要指出的是,虽然评估是基于特定年份的数据和情境进行的,但其预测能力并不仅限于2025年。评估方法本身具有通用性,它的有效性受到数据更新频率和疫情变化速度的双重影响,只要更新相关数据和信息,该方法即可应用于其他年/月份的风险评估。如果疫情发展迅速,而评估所依据的数据未能及时更新,那么无论预测时间设定为哪一年,其准确性都会大打折扣。为了提升传染病预警能力,未来的研究重点应放在构建一个数据稳定且易于获取的风险评估指标体系上。这一体系需能够实时获取并转化风险分值,从而实现动态、快速的定量风险评估。借助信息技术的强大支持,我们可以期待在不久的将来,能够更精准、更及时地应对新发传染病带来的挑战,有效降低其对社会公共卫生安全的威胁。
  • 广西医疗卫生适宜技术开发与推广应用项目(S2018063)
  • 中心资助青年科技工作者科研课题(202001)
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2025年第52卷第9期
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doi: 10.20043/j.cnki.MPM.202501214
  • 接收时间:2025-01-12
  • 首发时间:2026-03-17
  • 出版时间:2025-05-10
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  • 收稿日期:2025-01-12
基金
广西医疗卫生适宜技术开发与推广应用项目(S2018063)
中心资助青年科技工作者科研课题(202001)
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    1.广西壮族自治区疾病预防控制中心,广西 南宁 530028
    2.广西重大传染病防控与生物安全应急响应重点实验室,广西 南宁 530028

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梁羡篁,E-mail:
林玫,E-mail:;梁羡篁与林玫为共同通信作者
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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