【摘要】 目的 分析2006—2024年玉林市百日咳流行病学特征和时空聚集性，为百日咳防控提供科学依据。方法 收集2006—2024年玉林市百日咳报告发病信息、人口数据、疫苗接种情况等，运用空间自相关分析和时空扫描分析评估百日咳的时空聚集性，运用R语言4.5.0进行发病趋势分析及免疫史等的统计分析。结果 2006—2024年玉林市共报告百日咳病例805例，报告发病率为0.00/10万～10.37/10万，年均报告发病率为0.75/10万；2018年后玉林市百日咳报告发病数总体呈上升趋势（Z=23.298,P<0.05）。报告发病数在2018年开始增多，2019年出现小高峰，2024年1—7月快速增长。兴业县（1.32/10万）、玉州区（1.28/10万）年均报告发病率较高。病例以散居儿童为主，占56.15%;0～<1岁占比最高，为44.72%。805例病例中，有免疫史病例占62.48%，无免疫史病例占35.78%,3～<18月龄病例接种率（48.70%）偏低。全局空间自相关分析显示无聚集性（P值均>0.05）；局部空间自相关分析发现“H-L”和“L-H”聚集形式的局部区域。时空扫描分析探测到2024年以兴业县、福绵区、陆川县、容县为中心的聚集区。结论 玉林市百日咳报告发病数总体呈上升趋势，存在时空聚集性。今后应加强重点地区和人群的防控，优化百日咳疫苗免疫策略，提高疫苗接种率。更多还原

【Abstract】 Objective To analyze the epidemiological characteristics and spatiotemporal clustering of pertussis in Yulin from 2006 to 2024, so as to provide a scientific basis for pertussis prevention and control. Methods Onset information, demographic data, and vaccination status, etc., concerning reported pertussis cases in Yulin from 2006 to 2024 were collected. Spatial auto-correlation analysis and spatiotemporal scanning analysis were adopted to evaluate spatiotemporal clustering of pertussis. The R language 4.5.0 software was employed for onset trend analysis and statistical analyses of immunization history, etc. Results A total of 805 cases of pertussis were reported in Yulin from 2006 to 2024, with the reported morbidity from 0.00/100 000 to 10.37/100 000, and the average annual reported morbidity was 0.75/100 000, showing an overall upward trend of reported onset cases of pertussis in Yulin after 2018(Z=23.298, P<0.05). The number of reported onset cases increased in 2018, showed a small peak in 2019, and increased rapidly from January to July in 2024. The average annual morbidity was higher in Xingye county(1.32/100 000) and Yuzhou district(1.28/100 000). Most of the cases were scattered children, accounting for 56.15%. 0-<1 year old accounted for the highest proportion(44.72%). Among the 805 cases, 62.48% had immunization history and 35.78% did not have. The vaccination rate of the cases aged 3-<18 months(48.70%) was on the low side. Global spatial auto-correlation analysis revealed that there was no clustering(all P>0.05). Local spatial auto-correlation analysis identified local areas of “high-low” and “lowhigh” clustering forms. Spatiotemporal scanning analysis detected the clustering areas centered in Xingye county, Fumian district, Luchuan county and Rongxian county in 2024. Conclusions The reported onset cases of pertussis in Yulin is increasing with notable spatiotemporal clustering. It is necessary to strengthen the prevention and control of pertussis in key areas and populations, optimize the immunization strategy of pertussis vaccine, and increase the vaccination rate.更多还原