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CN 34-1304/RISSN 1674-3679

Volume 28 Issue 2
Feb.  2024
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Article Contents
LIU Lisha, ZHANG Ning, LI Xuan, DUAN Chunyuan, JIA Xinjing, ZHANG Wenyi, JIA Ruizhong, GUO Jinpeng, WANG Binbing, WANG Yong. Spatiotemporal and epidemiological characteristics of mumps in Anhui Province, 2010-2021[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 146-151. doi: 10.16462/j.cnki.zhjbkz.2024.02.004
Citation: LIU Lisha, ZHANG Ning, LI Xuan, DUAN Chunyuan, JIA Xinjing, ZHANG Wenyi, JIA Ruizhong, GUO Jinpeng, WANG Binbing, WANG Yong. Spatiotemporal and epidemiological characteristics of mumps in Anhui Province, 2010-2021[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(2): 146-151. doi: 10.16462/j.cnki.zhjbkz.2024.02.004

Spatiotemporal and epidemiological characteristics of mumps in Anhui Province, 2010-2021

doi: 10.16462/j.cnki.zhjbkz.2024.02.004
LIU Lisha and ZHANG Ning contributed equally to this article
Funds:

National Natural Science Foundation of China 12031010

National Science and Techrolclogy Major Poject 2018ZX10713003

More Information
  • Corresponding author: WANG Yong, E-mail: ywang7508@sina.com
  • Received Date: 2023-07-27
  • Rev Recd Date: 2023-10-24
  • Available Online: 2024-03-30
  • Publish Date: 2024-02-10
  •   Objective  This study aimed to analyze the temporal, spatial, and population distribution and spatiotemporal clustering characteristics of mumps in Anhui Province from 2010 to 2021, understand its epidemiological pattern, and to provide a basis for the development of prevention and control strategies.  Methods  The reported cases of mumps in Anhui Province from 2010 to 2021 were collected from the Anhui Provincial Center for Disease Control and Prevention. ArcGIS 10.8, Geoda 1.20, and SaTScan 10.1.2 were used to conduct descriptive epidemiological, spatial auto-correlation, and spatiotemporal scanning analyses of mumps in Anhui Province.  Results  The annual average incidence of mumps was 23.08/100 000 in Anhui Province during 2010-2021, with two peak epidemic periods. The chi-square trend test for incidence showed a downward trend with the years (χ2 =10 287.75, P < 0.001). The sex ratio of males to females was 1.67∶1. The highest proportions of cases were aged 5- < 15 years (68.91%) and students (67.89%). Additionally, the two seasonal peaks of mumps occurred from weeks 14 to 28 and from week 46 to week 4 of the following year. The spatial auto-correlation analysis results showed that except for 2012, 2014, and 2015, the Moran′s I indexes indicated positive spatial correlations (P < 0.05). The spatiotemporal scan analysis identified a total of ten clusters, of which the first clustering area was distributed in 26 districts and counties of Anhui Province, with a clustering period of 2011―2013, a radius of 144 km and a log likelihood ratio (LLR) value of 7 803.80.  Conclusions  Based on the findings, there is a cyclical pattern and declining trend of mumps in Anhui Province. In the future, disease surveillance and early warnings for susceptible populations and hotspots should continue to be strengthened to prevent and control the prevalence of mumps.
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  • [1]
    Grennan D. Mumps [J]. JAMA, 2019, 322(10): 1022. DOI: 10.1001/jama.2019.10982.
    [2]
    李兰娟, 任红. 传染病学[M]. 8版. 北京: 人民卫生出版社, 2013: 73-74.

    Li LJ, Ren H. Infectious diseases [M]. 8th ed. Beijing: People′s Medical Publishing House, 2013: 73-74.
    [3]
    朱佳佳. 中国流行性腮腺炎时空分布及时间序列模型研究[D]. 长沙: 湖南师范大学, 2019.

    Zhu JJ. Study on temporal and spatial distribution and time series model of mumps in China [D]. Changsha: Hunan Normal University, 2019.
    [4]
    中华人民共和国卫生部. 流行性腮腺炎诊断标准: WS 270―2007 [S]. 北京: 人民卫生出版社, 2008: 1-2.

    Ministry of Health of the People′s Republic of China. Diagnostic criteria for mumps: WS 270-2007 [S]. Beijing: People′s Medical Publishing House, 2008: 1-2.
    [5]
    冯军, 吴晓华, 李石柱, 等. 空间统计分析方法及相关软件在传染病研究中的应用[J]. 中国血吸虫病防治杂志, 2011, 23(2): 217-220. DOI: 10.3969/j.issn.1005-6661.2011.02.034.

    Feng J, Wu XH, Li SZ, et al. Application of spatial statistical analysis methods and related analytic softwares in research of infectious diseases [J]. Chin J Schisto Control, 2011, 23(2): 217-220. DOI: 10.3969/j.issn.1005-6661.2011.02.034.
    [6]
    Tang XY, Geater A, McNeil E, et al. Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004-2014: flexibly shaped scan statistics [J]. BMC Infect Dis, 2017, 17(1): 243. DOI: 10.1186/s12879-017-2357-1.
    [7]
    Tango T, Takahashi K. A flexibly shaped spatial scan statistic for detecting clusters [J]. Int J Health Geogr, 2005, 4: 11. DOI: 10.1186/1476-072X-4-11.
    [8]
    李平, 王富珍, 杨宏, 等. 中国2004―2021年流行性腮腺炎流行病学特征和时空聚集性[J]. 中国疫苗和免疫, 2023, 29(1): 19-24. DOI: 10.19914/j.CJVI.2023004.

    Li P, Wang FZ, Yang H, et al. Epidemiological characteristics and spatial-temporal clustering of mumps in China, 2004-2021 [J]. Chinese Journal Vaccines and Immunization, 2023, 29(1): 19-24. DOI: 10.19914/j.CJVI.2023004.
    [9]
    李婷婷, 田余红, 齐筱倩, 等. 2005―2012年合肥市蜀山区流行性腮腺炎的流行病学特征分析[J]. 安徽医学, 2013, 34(12): 1843-1846. DOI: 10.3969/j.issn.1000-0399.2013.12.042.

    Li TT, Tian YH, Qi XQ, et al. Analysis on epidemiological characteristics of mumps in Shushan district of Hefei from 2005 to 2012 [J]. Anhui Medical Journal, 2013, 34(12): 1843-1846. DOI: 10.3969/j.issn.1000-0399.2013.12.042.
    [10]
    蒋蕊鞠, 殷琼洲, 徐明珏, 等. 2004―2018年全国流行性腮腺炎发病特征及重点防控人群分析[J]. 中国当代儿科杂志, 2019, 21(5): 441-444. DOI: 10.7499/j.issn.1008-8830.2019.05.008.

    Jiang RJ, Yin QZ, Xu MJ, et al. Epidemiological characteristics of mumps in China from 2004 to 2018 and key population for prevention and control [J]. Chin J Contemp Pediatr, 2019, 21(5): 441-444. DOI: 10.7499/j.issn.1008-8830.2019.05.008.
    [11]
    Hamami D, Cameron R, Pollock KG, et al. Waning immunity is associated with periodic large outbreaks of mumps: a mathematical modeling study of Scottish data [J]. Front Physiol, 2017, 8: 233. DOI: 10.3389/fphys.2017.00233.
    [12]
    Sun X, Tang FY, Hu Y, et al. High risk of mumps infection in children who received one dose of mumps-containing vaccine: waning immunity to mumps in children aged 2-5 years from kindergartens in Jiangsu Province, China [J]. Hum Vaccin Immunother, 2020, 16(7): 1738-1742. DOI: 10.1080/21645515.2019.1708162.
    [13]
    Peng Y, Wang P, Kong DG, et al. Epidemiological characteristics and spatiotemporal analysis of mumps at township level in Wuhan, China, 2005-2019 [J]. Epidemiol Infect, 2023, 151: e63. DOI: 10.1017/S0950268823000304.
    [14]
    Lin CY, Su SB, Peng CJ, et al. The incidence of mumps in Taiwan and its association with the meteorological parameters: an observational study [J]. Medicine, 2021, 100(37): e27267. DOI: 10.1097/MD.0000000000027267.
    [15]
    Yu GQ, Yang RC, Wei Y, et al. Spatial, temporal, and spatiotemporal analysis of mumps in Guangxi Province, China, 2005-2016 [J]. BMC Infect Dis, 2018, 18(1): 360. DOI: 10.1186/s12879-018-3240-4.
    [16]
    李润滋. 山东省流行性腮腺炎时空分布与气象因素关系研究[D]. 济南: 山东大学, 2017.

    Li RZ. Study on the relationship between temporal and spatial distribution of mumps and meteorological factors in Shandong Province [D]. Jinan: Shandong University, 2017.
    [17]
    崔光辉, 蒋薇薇. 2015―2020年合肥市蜀山区流行性腮腺炎流行特征分析[J]. 公共卫生与预防医学, 2022, 33(5): 114-117. DOI: 10.3969/j.issn.1006-2483.2022.05.027.

    Cui GH, Jiang WW. Epidemic characteristics of mumps in Shushan District of Hefei City in 2015-2020 [J]. J Pub Health Prev Med, 2022, 33(5): 114-117. DOI: 10.3969/j.issn.1006-2483.2022.05.027.
    [18]
    薛晓嘉. 山东省呼吸道传染病的时空分布特征及其与气象干旱的关系[D]. 泰安: 泰山医学院, 2018.

    Xue XJ. Temporal and spatial distribution characteristics of respiratory infectious diseases in Shandong Province and its relationship with meteorological drought [D]. Taian: Taishan Medical University, 2018.
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