Epidemiological characteristics of varicella after class C management and vaccination strategy in Nanjing, China

MA Tao; DING Songning; CHEN Cong; YAN Zikang; WANG Junjun; WANG Hengxue; HU Yang; GU Runhui; DING Jie; LIU Huihui

doi:10.16462/j.cnki.zhjbkz.2024.04.004

Volume 28 Issue 4

Apr. 2024

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2024 > 28(4): 393-401

MA Tao, DING Songning, CHEN Cong, YAN Zikang, WANG Junjun, WANG Hengxue, HU Yang, GU Runhui, DING Jie, LIU Huihui. Epidemiological characteristics of varicella after class C management and vaccination strategy in Nanjing, China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(4): 393-401. doi: 10.16462/j.cnki.zhjbkz.2024.04.004

Citation:

MA Tao, DING Songning, CHEN Cong, YAN Zikang, WANG Junjun, WANG Hengxue, HU Yang, GU Runhui, DING Jie, LIU Huihui. Epidemiological characteristics of varicella after class C management and vaccination strategy in Nanjing, China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(4): 393-401. doi: 10.16462/j.cnki.zhjbkz.2024.04.004

Citation:

MA Tao, DING Songning, CHEN Cong, YAN Zikang, WANG Junjun, WANG Hengxue, HU Yang, GU Runhui, DING Jie, LIU Huihui. Epidemiological characteristics of varicella after class C management and vaccination strategy in Nanjing, China[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(4): 393-401. doi: 10.16462/j.cnki.zhjbkz.2024.04.004

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Epidemiological characteristics of varicella after class C management and vaccination strategy in Nanjing, China

doi: 10.16462/j.cnki.zhjbkz.2024.04.004

MA Tao¹,
DING Songning¹,
CHEN Cong^{2, 3},
YAN Zikang¹,
WANG Junjun¹,
WANG Hengxue¹,
HU Yang¹,
GU Runhui¹,
DING Jie^{1
,
,},
LIU Huihui^{4
,
,}

1.
Department of Acute Infectious Disease Control and Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing 210003, China
2.
Department of Immunization Program, Wujin District Center for Disease Control and Prevention, Changzhou 213100, China
3.
Jiangsu Field Epidemiology Training Program, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
4.
Department of Education and Training, Chinese Center for Disease Control and Prevention, Beijing 102206, China

Funds:

Nanjing Medical Science and Technology Development Program YKK22190

Nanjing Key Medical Specialty Ningwei Science and Education [2018] No.7

More Information

Corresponding author: DING Jie, E-mail: yu2an2002@163.com; LIU Huihui, E-mail: liuhh@chinacdc.cn
Received Date: 2023-08-31
Rev Recd Date: 2024-01-05

Available Online: 2024-05-17

Publish Date: 2024-04-10

Abstract

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.
- Varicella,
- Incidence trend,
- Epidemiologic characteristics,
- Spatial clustering,
- Prevention and control strategy

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References(33)

References

[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.htm Ma 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.