Epidemiological characteristics of dengue fever outbreaks in Nanning, Guangxi Zhuang Autonomous Region in 2014 and 2019
-
摘要:
目的 分析广西壮族自治区南宁市2014年和2019年两次登革热暴发疫情的特点,为当地登革热防控提供参考。 方法 收集南宁市2014年和2019年登革热暴发疫情病例资料,采用描述性流行病学方法,比较病例在时间分布、人群分布、空间分布的特点。 结果 2014年首例病例发病日期是6月13日,病例数到达25.00%、50.00%、75.00%、100.00%的时间分别是9月27日、10月4日、10月15日和12月8日,单日发病最高峰是38例(9月28日);2019年首例病例发病日期是4月9日,病例数到达25.00%、50.00%、75.00%、100.00%的时间分别是9月29日、10月9日、10月19日和12月13日,单日发病最高峰是36例(10月1日)。 2014年病例女性占比58.45%,2019年无性别差异;2014年病例20~39岁年龄段占比53.19%,2019年病例年龄≥60岁的老年人占比15.97%;2014年病例职业分布商业或服务类占比33.52%,2019年病例职业分布家务或待业占比25.86%;2014年商业或服务类病例最早引发登革热疫情,2019年各职业类型病例在时间先后顺序上无明显差异。 2014年病例将近50.00%集中在兴宁区(347例,48.06%) ,其次西乡塘区(235例,32.55%);2019年病例相对集中在江南区(451例,42.11%),其次西乡塘区(298例,27.82%)。 结论 南宁市两次登革热暴发疫情时间分布模式相似,但人群、空间分布特点明显不同,提示疫情发生风险具普遍性,应注重落实防控措施。 Abstract:Objective To analyze the epidemiological characteristics of dengue fever outbreaks in 2014 and 2019 in Nanning, Guangxi Zhuang Autonomous Region and provide reference for local dengue fever prevention and control. Methods The incidence data of dengue fever outbreaks in Nanning in 2014 and 2019 were collected, and descriptive epidemiological analysis was conducted to compare the time, population and spatial distributions of dengue fever cases in the two outbreaks. Results In 2014 outbreak, the first case occurred on June 13, and the number of cases reached its 25.00%, 50.00%, 75.00% and 100.00% on September 27, October 4, October 15 and December 8, respectively, and the daily incidence peak was on September 28 (38 cases). In 2019 outbreak, the first case occurred on April 9, and the number of cases reached its 25.00%, 50.00%, 75.00% and 100.00% on September 29, October 9, October 19 and December 13 respectively. The daily incidence peak was on October 1 (36 cases). The majority of cases in 2014 outbreak were women, but there was no gender specific difference in 2019. The cases in 2014 are more concentrated in the 20–39 age group. There were slightly more elderly cases in 2019. In 2014, the most cases were business or service categories but the most cases were housework or unemployed in 2019. Business or service cases caused the earliest dengue outbreak in 2014. However, none of the occupational types shows earlier in dengue outbreak in 2019. Nearly half of the cases in 2014 were concentrated in Xingning district with a total of 347 cases (48.06%), followed by Xixiangtang district, with a total of 235 cases (32.55%). The cases in 2019 were relatively concentrated in Jiangnan district, with a total of 451 cases (42.11%), followed by Xixiangtang district with a total of 298 cases (27.82%). Conclusion Although the time distribution of the dengue outbreaks in 2014 and 2019 were similar, the characteristics of population distribution and spatial distribution are significantly different. Indicating the popularity of epidemic risks and the need to focus on implementing prevention and control measures. -
Key words:
- Nanning /
- Dengue fever /
- Outbreak
-
表 1 南宁市2014年和2019年登革热病例人群分布情况[人(%)]
Table 1. Population distribution of dengue fever cases in Nanning in 2014 and 2019
项目 2014年 2019年 χ2值 P值 病例数 构成比(%) 病例数 构成比(%) 性别 9.683 0.002 男性 300 41.55 525 49.02 女性 422 58.45 546 50.98 年龄组(岁) 17.359 0.001 0~ 51 7.06 92 8.59 20~ 384 53.19 481 44.91 40~ 212 29.36 327 30.53 ≥60 75 10.39 171 15.97 职业 118.825 <0.001 幼托前儿童 8 1.11 3 0.28 幼托儿童 4 0.55 2 0.19 学生 36 4.99 92 8.59 干部职员 46 6.37 101 9.43 医务人员 9 1.25 21 1.96 教师 18 2.49 25 2.33 工人 42 5.82 94 8.78 民工 14 1.94 44 4.11 农民 26 3.60 74 6.91 商业或服务类 242 33.52 184 17.18 家务或待业 151 20.91 277 25.86 离退休人员 76 10.53 123 11.48 其他 16 2.22 21 1.96 不详 34 4.71 10 0.93 诊断类型 0.210 0.647 临床诊断 128 17.73 199 18.58 实验室诊断 594 82.27 872 81.42 病例分类 4.766 0.029 输入性病例 13 1.80 38 3.55 本地病例 709 98.20 1033 96.45 合计 722 100.00 1071 100.00 -
[1] Abualamah WA, Akbar NA, Banni HS, et al. Forecasting the morbidity and mortality of dengue fever in KSA: a time series analysis (2006–2016)[J]. J Taibah Univ Med Sci, 2021, 16(3): 448–455. DOI: 10.1016/j.jtumed.2021.02.007. [2] World Health Organization. Dengue bulletin (volume 41, December 2020)[R]. Geneva: WHO, 2021. [3] Zeng ZL, Zhan J, Chen LY, et al. Global, regional, and national dengue burden from 1990 to 2017: a systematic analysis based on the global burden of disease study 2017[J]. eClinicalMedicine, 2021, 32: 100712. DOI: 10.1016/j.eclinm.2020.100712. [4] 李晋涛. 登革热防治研究进展[J]. 第三军医大学学报,2019,41(19):1902–1907. DOI:10.16016/j.1000−5404.201909095.Li JT. Advances in prevention and control for dengue fever[J]. J Army Med Univ, 2019, 41(19): 1902–1907. DOI: 10.16016/j.1000−5404.201909095. [5] 宁丹, 孙九峰, 彭志强, 等. 广东省登革热流行概况与流行特征[J]. 华南预防医学,2017,43(4):368–372. DOI: 10.13217/j.scjpm.2017.0368.Ning D, Sun JF, Peng ZQ, et al. Epidemiological overview and characteristics of dengue fever in Guangdong[J]. South China J Prev Med, 2017, 43(4): 368–372. DOI: 10.13217/j.scjpm.2017.0368. [6] 王晶, 唐振柱, 林玫, 等. 南宁市首起登革热暴发疫情处置及成本效益分析[J]. 中国媒介生物学及控制杂志,2017,28(3):258–261. DOI: 10.11853/j.issn.1003.8280.2017.02.016.Wang J, Tang ZZ, Lin M, et al. Management and cost-effectiveness analysis of the first dengue fever outbreak in Nanning city, 2014[J]. Chin J Vector Biol Control, 2017, 28(3): 258–261. DOI: 10.11853/j.issn.1003.8280.2017.02.016. [7] 刘牧文, 孙昼, 考庆君, 等. 2017-2019年浙江省杭州市登革热流行特征和时空聚集性分析[J]. 疾病监测,2022,37(4):481–486. DOI: 10.3784/jbjc.202106300379.Liu MW, Sun Z, Kao QJ, et al. Spatiotemporal distribution of dengue fever in Hangzhou, Zhejiang, 2017−2019[J]. Dis Surveill, 2022, 37(4): 481–486. DOI: 10.3784/jbjc.202106300379. [8] 曾小平, 陈琴, 王明昌, 等. 海口市2019年登革热本地和输入病例流行病学特征比较[J]. 中国热带医学,2021,21(8):779–783. DOI:10.13604/j.cnki.46−1064/r.2021.08.13.Zeng XP, Chen Q, Wang MC, et al. Comparison of epidemiological characteristics of local and imported cases of dengue fever in Haikou, 2019[J]. China Trop Med, 2021, 21(8): 779–783. DOI: 10.13604/j.cnki.46−1064/r.2021.08.13. [9] 王亮, 秦剑秋, 尹刘江, 等. 南宁市37例登革病毒1型E基因系统进化分析[J]. 现代预防医学,2021,48(5):921–924.Wang L, Qin JQ, Yin LJ, et al. Phylogenetic analysis on the E gene of 37 DENV-I virus in Nanning[J]. Mod Prev Med, 2021, 48(5): 921–924. [10] Guzman MG, Harris E. Dengue[J]. Lancet, 2015, 385(9966): 453–465. DOI: 10.1016/S0140−6736(14)60572−9. [11] Sun JM, Luo SY, Lin JF, et al. Inapparent infection during an outbreak of dengue fever in Southeastern China[J]. Viral Immunol, 2012, 25(6): 456–460. DOI: 10.1089/vim.2012.0039. [12] 蒋力云, 刘远, 苏文哲, 等. 广州市2010-2019年4型登革热病例流行特征及其病毒E基因[J]. 中华疾病控制杂志,2021,25(11):1360–1364. DOI: 10.16462/j.cnki.zhjbkz.2021.11.022.Jiang LY, Liu Y, Su WZ, et al. Epidemiology of dengue virus serotype 4 cases and E gene analysis of dengue virus in Guangzhou province from 2010 to 2019[J]. Chin J Dis Control Prev, 2021, 25(11): 1360–1364. DOI: 10.16462/j.cnki.zhjbkz.2021.11.022. [13] 黎祖秋, 汤洪洋, 屈志强, 等. 2015-2018年南宁市登革热媒介伊蚊监测结果分析和登革热风险评估[J]. 应用预防医学,2018,24(6):415–420. DOI:10.3969/j.issn.1673−758X.2018.06.001.Li ZQ, Tang HY, Qu ZQ, et al. Analysis of surveillance results of dengue vector Aedes mosquitoes and assessment the risk of dengue fever in Nanning in 2015−2018[J]. Appl Prev Med, 2018, 24(6): 415–420. DOI: 10.3969/j.issn.1673−758X.2018.06.001. [14] World Health Organization. Dengue: guidelines, for diagnosis, treatment, prevention and control[M]. Geneva: World Health Organization, 2009. -