Epidemiological characteristics of varicella after class C management and vaccination strategy in Nanjing, China
-
摘要:
目的 了解实施丙类管理和疫苗接种策略后，南京市水痘流行特征变化，初步分析防控措施效果，为改进防控策略提供科学依据。 方法 收集2013―2022年南京市水痘报告病例数据，利用Joinpoint回归模型分析报告发病率年度变化百分比(annual percent change，APC)和平均年度变化百分比(average annual percent change，AAPC)。利用R 4.2.0软件分析时间、人群和空间分布特征，探测空间聚集区域，比较水痘纳入丙类管理(2017―2018年)和疫苗接种后(2019―2022年)流行特征变化。 结果 共报告水痘病例87 538例，年均报告发病率为102.20/10万。2018年达到峰值228.64/10万(19 057例)，后持续下降至2022年的98.32/10万(9 262例)，下降了57.00%。2013―2018年、2018―2022年APC分别为71.47%(95% CI：41.96%~107.10%)、-15.36%(95% CI：-35.20%~10.54%)，2013―2022年AAPC为25.29%(95% CI：11.03%~41.37%)。2019―2022年病例年龄中位数[10(5，19)岁]高于2017―2018年[7(5，15)岁](P＜0.001)； < 15岁各年龄组发病率下降比例为57.46%~90.46%，年龄组发病高峰被削平。学生、幼托儿童和散居儿童占比由84.53%逐年下降至75.26%，其中幼托儿童由32.51%下降至28.85%，散居儿童由11.13%下降至5.55%。主城区报告发病率低于周边地区，采取疫苗接种策略后，一级聚集区由建邺、江北、雨花台、江宁区，转换为高淳区(均P＜0.001)。 结论 水痘纳入丙类管理提高了南京市水痘监测质量，通过实施扩大免疫接种策略，报告发病水平显著下降，人群和空间分布特征发生变化。 Abstract:Objective To understand the epidemiological characteristics of varicella in Nanjing after Class C management and vaccination strategy, analyzing the effect of prevention and control measures, providing scientific basis for improving the prevention and control strategy. Methods We collected reported varicella cases data from 2013 to 2022 in Nanjing and utilizied the Joinpoint regression model to calculate the annual percent change (APC) and the average annual percent change (AAPC) in incidence rates. We described the characteristics of temporal distribution, population distribution, spatial distribution and spatial clustering of varicella in Nanjing from 2013 to 2022 by R program, and compared the changes of epidemiological characteristics between the Class C management (2017-2018) and the vaccination strategy (2019-2022). Results A total of 87 538 varicella cases were reported. The average annual reported incidence was 102.20/100 000, with the peak of 228.64/100 000 (19 057 cases) in 2018, and declined to 98.32/100 000 (9 262 cases) in 2022, with a decrease of 57.00%. The APC from 2013 to 2018 and from 2018 to 2022 were 71.47% (95% CI: 41.96%-107.10%)、-15.36% (95% CI: -35.20%-10.54%), respectively, and the AAPC was 25.29% (95% CI: 11.03%-41.37%). The median age of cases in 2019-2022 [10 (5, 19)] was higher than that in 2017-2018 [7 (5, 15)] (P < 0.001), and the proportions of reported incidence reduction in each age groupunder 15 years old were between 57.46% and 90.46%, and the peak of incidence in the age group was reduced. The proportion of students, kindergarten children and scattered children decreased from 84.53% to 75.26%, among which the kindergarten children decreased from 32.51% to 28.85%, and the scattered children decreased from 11.13% to 5.55%. The incidence rate in the main urban areas were lower than that in the surrounding areas. After vaccination strategy, the most likely clusters changed from Jianye District, Jiangbei District, Yuhuatai District and Jiangning District to Gaochun District (P < 0.001). Conclusions The quality of varicella surveillance in Nanjing has been improved after class C management. After vaccination strategy, the reported incidence decreased significantly, and the population and spatial distribution characteristics changed. -
图 1 2013―2022年南京市报告水痘病例时间分布
A：年报告发病率和病例数趋势；B：分年月分布热力图；C：分地区月分布热力图。
Figure 1. Temporal distribution characteristics of varicella in Nanjing from 2013 to 2022
A: Trend of annual reported cases and incidence; B: Heat map by year and month; C: Monthly distribution heat map by districts.
图 2 2013―2022年南京市报告水痘病例人群特征分布
A：分性别年报告发病趋势；B：分性别年龄组报告病例数金字塔；C：分性别年龄组报告发病趋势；D：分年龄组年报告发病率热力图；E：分年职业构成百分比条图；F：病例职业构成。
Figure 2. Population distribution characteristics of varicella in Nanjing from 2013 to 2022
A: Trend of annual reported incidence by gender; B: Pyramid of reported cases by gender and age group; C: Trend of reported incidence by gender and age group; D: Heat map of annual reported incidence by age group; E: Annual occupational composition percentage bar chart; F: Occupational composition of cases.
图 3 2013―2022年南京市水痘报告发病率地区分布示意图
仅表示空间地理位置关系，不代表实际行政区划边界。
Figure 3. Schematic diagram for regional distribution of varicella reported incidence in Nanjing from 2013 to 2022
It only represents the spatial geographical relationship and does not represent the actual administrative boundaries.
图 4 2013―2022年南京市水痘空间聚集区域示意图
仅表示空间地理位置关系，不代表实际行政区划边界。
Figure 4. Schematic diagram of varicella spatial clustering area in Nanjing from 2013 to 2022
It only represents the spatial geographical relationship and does not represent the actual administrative boundaries.
表 1 2013―2022年南京市报告水痘病例空间聚集地区
Table 1. Spatial clustering of varicella in Nanjing from 2013 to 2022
年份
Year类型
Type地区
Districts观测值
Observed
value期望值
Expected
valueRR值
valueLLR值
valueP值
value2013 一级Most likely 江北Jiangbei 420 47 11.976 599.157 0.001 次级Secondary 雨花台Yuhuatai 120 74 1.669 12.588 0.001 2014 一级Most likely 江北Jiangbei 383 47 10.285 506.494 0.001 次级-1 Secondary-1 高淳Gaochun 148 89 1.719 17.125 0.001 次级-2 Secondary-2 雨花台Yuhuatai 134 84 1.650 13.482 0.001 次级-3 Secondary-2 六合Luhe 207 149 1.438 10.962 0.001 2015 一级Most likely 江北Jiangbei 509 66 9.517 642.173 0.001 次级-1 Secondary-1 浦口Pukou，江宁Jiangning 772 561 1.551 47.745 0.001 次级-2 Secondary-2 六合Luhe 306 211 1.515 20.800 0.001 次级-3 Secondary-3 高淳Gaochun 185 126 1.505 12.745 0.001 2016 一级Most likely 浦口Pukou，江北Jiangbei，江宁Jiangning 2 126 958 3.864 820.462 0.001 次级Secondary 六合Luhe 486 322 1.584 39.855 0.001 2017 一级Most likely 建邺Jianye，江北Jiangbei，雨花台Yuhuata，江宁Jiangning 5 191 3 068 2.529 1 005.001 0.001 次级Secondary 高淳Gaochun 1 111 494 2.415 305.261 0.001 2018 一级Most likely 建邺Jianye，江北Jiangbei，雨花台Yuhuatai，江宁Jiangning 9 929 6 516 2.094 1 282.553 0.001 次级Secondary 高淳Gaochun 1 706 1 021 1.738 204.236 0.001 2019 一级Most likely 建邺Jianye，江北Jiangbei，雨花台Yuhuatai，江宁Jiangning 9 228 6 505 1.829 834.810 0.001 次级Secondary 高淳Gaochun 1 443 1 005 1.472 89.422 0.001 2020 一级Most likely 江宁Jiangning，溧水Lishui，高淳Gaochun 4 521 2 978 1.871 500.109 0.001 次级Secondary 江北Jiangbei，六合Luhe 2 307 1 899 1.271 50.010 0.001 2021 一级Most likely 高淳Gaochun 863 488 1.838 124.324 0.001 次级Secondary 江北Jiangbei，栖霞Qixai，雨花台Yuhuatai，江宁Jiangning，六合Luhe 6 546 5 954 1.261 68.171 0.001 2022 一级Most likely 高淳Gaochun 677 426 1.637 66.485 0.001 次级Secondary 建邺Jianye，浦口Pukou，江北Jiangbei，雨花台Yuhuatai，六合Luhe 3 656 3 247 1.208 38.878 0.001 
下载: 导出CSV
-
[1] 陈宏标, 古子豪, 周小峰, 等. 广东省深圳市某区一起水痘暴发疫情调查和基于SEIR模型对疫情防控效果的评估[J]. 疾病监测, 2022, 37(6): 855-860. DOI: 10.3784/jbjc.202108300473.Chen HB, Gu ZH, Zhou XF, et al. Investigation of an outbreak of varicella in a district of Shenzhen and evaluation of control effect based on SEIR model[J]. Dis Surveill, 2022, 37(6): 855-860. DOI: 10.3784/jbjc.202108300473. [2] 王淼, 曾祥, 张一平, 等. 中国2007―2021年水痘突发公共卫生事件流行病学特征[J]. 中国疫苗和免疫, 2023, 29(3): 274-279. DOI: 10.19914/j.CJVI.2023046.Wang M, Zeng X, Zhang YP, et al. Epidemiological characteristics of varicella public health emergency events in China, 2007-2021[J]. Chinese Journal of Vaccines and Immunization, 2023, 29(3): 274-279. DOI: 10.19914/j.CJVI.2023046. [3] Huang JF, Wu YL, Wang MF, et al. The global disease burden of varicella-zoster virus infection from 1990 to 2019[J]. J Med Virol, 2022, 94(6): 2736-2746. DOI: 10.1002/jmv.27538. [4] 王铁强, 郑庆鸣, 吴云杰, 等. 广东省深圳市学龄儿童水痘病例的疾病经济负担调查[J]. 疾病监测, 2021, 36(10): 1092-1095. DOI: 10.3784/jbjc.202104130193.Wang TQ, Zheng QM, Wu YJ, et al. Investigation of economic burden caused by varicella in school aged children in Shenzhen[J]. Dis Surveill, 2021, 36(10): 1092-1095. DOI: 10.3784/jbjc.202104130193. [5] Feng H, Zhang HJ, Ma C, et al. National and provincial burden of varicella disease and cost-effectiveness of childhood varicella vaccination in China from 2019 to 2049: a modelling analysis[J]. Lancet Reg Health West Pac, 2022, 32: 100639. DOI: 10.1016/j.lanwpc.2022.100639. [6] 马涛, 谢国祥, 孙红敏, 等. 2006―2017年南京市水痘流行特征分析[J]. 现代预防医学, 2018, 45(13): 2312-2315, 2323. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201813003.htmMa T, Xie GX, Sun HM, et al. Epidemiological characteristics of varicella in Nanjing, China, 2006-2017[J]. Modern Preventive Medicine, 2018, 45(13): 2312-2315, 2323. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201813003.htm [7] 董蒲梅, 王淼, 刘燕敏. 2016―2019年中国水痘流行病学特征[J]. 中国疫苗和免疫, 2020, 26(4): 403-406. DOI: 10.19914/j.cjvi.2020.04.011.Dong PM, Wang M, Liu YM. Epidemiological characteristics of varicella in China, 2016-2019[J]. Chinese Journal of Vaccines and Immunization, 2020, 26(4): 403-406. DOI: 10.19914/j.CJVI.2020.04.011. [8] Zhang ZY, Liu N, Zhang J, et al. Epidemiological characteristics of Varicella under different immunisation strategies in Suzhou prefecture, Jiangsu Province[J]. Vaccines (Basel), 2022, 10(10): 1745. DOI: 10.3390/vaccines10101745. [9] 张夏晴, 吕勇, 王瑶, 等. 六安市2010―2022年水痘流行特征和水痘疫苗保护效果[J]. 中国疫苗和免疫, 2023, 29(3): 285-289. DOI: 10.19914/j.CJVI.2023048.Zhang XQ, Lv Y, Wang Y, et al. Epidemiological characteristics of varicella and effectiveness of varicella vaccine in Lu'an city, 2010 to 2022[J]. Chinese Journal of Vaccines and Immunization, 2023, 29(3): 285-289. DOI: 10.19914/j.CJVI.2023048. [10] 李轩, 卫宪钰, 张文义, 等. 水痘流行病学特征及影响因素研究进展[J]. 疾病监测, 2023, 38(7): 878-883. DOI: 10.3784/jbjc.202212280552.Li X, Wei XY, Zhang WY, et al. Progress in research of epidemiological characteristics and environmental influencing factors of varicella[J]. Dis Surveill, 2023, 38(7): 878-883. DOI: 10.3784/jbjc.202212280552. [11] Liu BQ, Li XP, Yuan L, et al. Analysis on the epidemiological characteristics of varicella and breakthrough case from 2014 to 2022 in Qingyang City[J]. Hum Vaccin Immunother, 2023, 19(2): 2224075. DOI: 10.1080/21645515.2023.2224075. [12] Wang HY, Liu F, Cao Y, et al. Epidemiological characteristics of varicella before and after the implementation of two-dose vaccination schedule in Chaoyang District, Beijing, 2007-2019[J]. J Infect, 2021, 83(5): 607-635. DOI: 10.1016/j.jinf.2021.07.035. [13] Xiu SX, Wang XW, Wang Q, et al. Impact of implementing a free varicella vaccination policy on incidence in Wuxi City, China: an interrupted time series analysis[J]. Epidemiol Infect, 2023, 151: e125. DOI: 10.1017/S0950268823001152. [14] 李爱华, 赵丹, 温小菁, 等. 2019―2021年北京市水痘流行情况及基因特征分析[J]. 中华预防医学杂志, 2022, 56(8): 1118-1122. DOI: 10.3760/cma.j.cn112150-20220514-00479.Li AH, Zhao D, Wen XJ, et al. Analysis on the epidemic characteristics and genetic characteristics of varicella in Beijing from 2019 to 2021[J]. Chin J Prev Med, 2022, 56(8): 1118-1122. DOI: 10.3760/cma.j.cn112150-20220514-00479. [15] Giglio N, Lasalvia P, Pawaskar M, et al. Trends in Varicella burden of disease following introduction of routine childhood Varicella vaccination in Argentina: a 12-year time series analysis[J]. Vaccines (Basel), 2022, 10(7): 1151. DOI: 10.3390/vaccines10071151. [16] Gao Z, Yang F, Qi F, et al. Evaluating the impact of universal varicella vaccination among preschool-aged children in Qingdao, China: an interrupted time-series analysis[J]. Hum Vaccin Immunother, 2022, 18(6): 2094641. DOI: 10.1080/21645515.2022.2094641. [17] Suzuki A, Nishiura H. Reconstructing the transmission dynamics of varicella in Japan: an elevation of age at infection[J]. PeerJ, 2022, 10: e12767. DOI: 10.7717/peerj.12767. [18] Xiao JP, Dai JY, Hu JX, et al. Co-benefits of nonpharmaceutical intervention against COVID-19 on infectious diseases in China: a large population-based observational study[J]. Lancet Reg Health West Pac, 2021, 17: 100282. DOI: 10.1016/j.lanwpc.2021.100282. [19] Suzuki A, Nishiura H. Seasonal transmission dynamics of varicella in Japan: the role of temperature and school holidays[J]. Math Biosci Eng, 2023, 20(2): 4069-4081. DOI: 10.3934/mbe.2023190. [20] 栾桂杰, 陈萌, 刘尧, 等. 山东省2019―2021年成年人和儿童水痘病例流行特征及临床表现的比较[J]. 中华流行病学杂志, 2023, 44(4): 587-591. DOI: 10.3760/cma.j.cn112338-20220906-00766.Luan GJ, Chen M, Liu Y, et al. Comparison of epidemic characteristics and clinical manifestation of chickenpox between adults and children in Shandong Province from 2019 to 2021[J]. Chin J Epidemiol, 2023, 44(4): 587-591. DOI: 10.3760/cma.j.cn112338-20220906-00766. [21] Zhang L, Ma W, Liu YB, et al. Analysis of sero-epidemiological characteristics of varicella in healthy children in Jiangsu Province, China[J]. BMC Infect Dis, 2018, 18(1): 563. DOI: 10.1186/s12879-018-3496-8. [22] 胡跃华, 罗旭飞, 吕萌, 等. 中国健康人群水痘-带状疱疹病毒抗体水平的Meta分析[J]. 中华流行病学杂志, 2021, 42(9): 1650-1661. DOI: 10.3760/cma.j.cn112338-20210308-00185.Hu YH, Luo XF, Lv M, et al. A Meta-analysis on varicella-zoster virus antibody levels in healthy population in China[J]. Chin J Epidemiol, 2021, 42(9): 1650-1661. DOI: 10.3760/cma.j.cn112338-20210308-00185. [23] Zhao D, Suo L, Lu LD, et al. Effect of earlier vaccination and a two-dose Varicella vaccine schedule on Varicella incidence - Beijing municipality, 2007-2018[J]. China CDC Wkly, 2021, 3(15): 311-315. DOI: 10.46234/ccdcw2021.085. [24] 索罗丹, 赵丹, 陈萌, 等. 北京市健康人群水痘-带状疱疹病毒血清抗体水平调查分析[J]. 中华预防医学杂志, 2022, 56(2): 108-113. DOI: 10.3760/cma.j.cn112150-20211221-01174.Suo LD, Zhao D, Chen M, et al. An investigation on serum antibody level of varicella-zoster virus in healthy population in Beijing[J]. Chin J Prev Med, 2022, 56(2): 108-113. DOI: 10.3760/cma.j.cn112150-20211221-01174. [25] Chen YW, Ma R, Zhang YY, et al. Effects of Varicella vaccine time of first dose and coverage of second dose - Beijing and Ningbo, China, 2012-2018[J]. China CDC Wkly, 2020, 2(36): 696-699. DOI: 10.46234/ccdcw2020.136. [26] 马涛, 周沁易, 丰罗菊, 等. 2011-2020年南京市恙虫病流行特征与空间聚集性分析[J]. 中华地方病学杂志, 2022, 41(5): 356-361. DOI: 10.3760/cma.j.cn231583-20210705-00226.Ma T, Zhou QY, Feng LJ, et al. Epidemiological characteristics and spatial clustering of scrub typhus in Nanjing from 2011 to 2020[J]. Chin J Endemiol, 2022, 41(5): 356-361. DOI: 10.3760/cma.j.cn231583-20210705-00226. [27] 马涛, 洪镭, 杜雪飞, 等. 2014―2019年南京市猩红热流行特征和时空聚集性[J]. 中华疾病控制杂志, 2021, 25(3): 346-351. DOI: 10.16462/j.cnki.zhjbkz.2021.03.018.Ma T, Hong L, Du XF, et al. Epidemiological characteristics and temporal-spatial clustering of scarlet fever in Nanjing from 2014 to 2019[J]. Chin J Dis Control Prev, 2021, 25(3): 346-351. DOI: 10.16462/j.cnki.zhjbkz.2021.03.018. [28] 许意清, 付志智, 周健宇, 等. 广西壮族自治区2014－2016年水痘疫情时空分布特征分析[J]. 中华流行病学杂志, 2017, 38(10): 1390-1393. DOI: 10.3760/cma.j.issn.0254-6450.2017.10.019.Xu YQ, Fu ZZ, Zhou JY, et al. Epidemiological characteristics on temporal-spatial distribution of varicella in Guangxi Zhuang Autonomous Region, 2014-2016[J]. Chin J Epidemiol, 2017, 38(10): 1390-1393. DOI: 10.3760/cma.j.issn.0254-6450.2017.10.019. [29] Lee YH, Choe YJ, Hwang SS, et al. Spatiotemporal distribution of varicella in the Republic of Korea[J]. J Med Virol, 2022, 94(2): 703-712. DOI: 10.1002/jmv.27434. [30] 丰达星, 肖占沛, 王文慧, 等. 2014－2019年河南省水痘报告病例空间分布特征[J]. 疾病监测, 2020, 35(11): 998-1002. DOI: 10.3784/j.issn.1003-9961.2020.11.009.Feng DX, Xiao ZP, Wang WH, et al. Spatiotemporal characteristic of varicella cases reported in Henan, 2014-2019[J]. Dis Surveill, 2020, 35(11): 998-1002. DOI: 10.3784/j.issn.1003-9961.2020.11.009. [31] 杨帆, 索罗丹, 苗良, 等. 北京市2剂次水痘疫苗免疫策略实施后疫苗安全性监测分析[J]. 中华预防医学杂志, 2018, 52(1): 91-93. DOI: 10.3760/cma.j.issn.0253-9624.2018.01.018.Yang F, Suo LD, Miao L, et al. Analysis on surveillance data of immunization safety for varicella vaccine after the immunization strategy implemented[J]. Chin J Prev Med, 2018, 52(1): 91-93. DOI: 10.3760/cma.j.issn.0253-9624.2018.01.018. [32] Ahern S, Walsh KA, Paone S, et al. Safety of varicella vaccination strategies: an overview of reviews[J]. Rev Med Virol, 2023, 33(2): e2416. DOI: 10.1002/rmv.2416. [33] Sun X, Dai CX, Wang K, et al. A dynamic compartmental model to explore the optimal strategy of Varicella vaccination: an epidemiological study in Jiangsu Province, China[J]. Trop Med Infect Dis, 2022, 8(1): 17. DOI: 10.3390/tropicalmed8010017. -
点击查看大图
图(4) / 表(1)
计量
- 文章访问数: 97
- HTML全文浏览量: 25
- PDF下载量: 16
- 被引次数: 0