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BMC Infectious Diseases
Published in: BMC Infectious Diseases 1/2023

Open Access 01-12-2023 | Research

Epidemiological characteristics and spatio-temporal analysis of brucellosis in Shandong province, 2015–2021

Authors: Xiaolin Yu, Ming Fang, Yan Li, Jianmei Yu, Lixiao Cheng, Shujun Ding, Zengqiang Kou

Published in: BMC Infectious Diseases | Issue 1/2023

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Abstract

Background

Brucellosis is one of the major public health problems in China, it not only causes huge economic losses to the society, but also threatens the human’s physical and mental health. The reported cases of brucellosis in Shandong province were at a high level, therefore, it is necessary for us to understand the epidemic characteristics and distribution trend of Brucellosis in Shandong province. This study aims to describe the epidemiological characteristics and spatial clustering characteristics of brucellosis in Shandong Province, provide a reference for the scientific prevention and control.

Methods

Human brucellosis data in Shandong province from 2015 to 2021 were obtained from the China Information System for Disease Control and Prevention, the data were analyzed by descriptive epidemiological methods, spatial autocorrelation analysis and spatial-temporal cluster analysis methods use ArcGIS and SaTScan software, the results were presented in ArcMap.

Results

A total of 22,251 human cases of brucellosis were reported, the annual incidence ranged between 2.41/100,000 and 4.07/100,000 from 2015 to 2021 in Shandong province, incidence has been decreasing year by year, while there was a significant increase in 2021. The distribution of brucellosis was of a seasonal trend, mainly concentrating during March to August. The age of the cases was mainly concentrated in the 30–74 age ranges, the average annual incidence rate was significantly higher in males than in females. The spatial analysis showed that the epidemics were mainly concentrated in the north and southwest. For the spatial autocorrelation analysis, a high global autocorrelation was observed at the county level, and the high–high clusters mainly distributed in the north and southwest region. For the spatio-temporal scanning, the most likely cluster areas mainly distributed in the north area, and then gradually moved southward, and the radius of clustered narrowed.

Conclusions

Human brucellosis remains a common challenge, particularly in northern region in spring and summer. More disease prevention and control measures should be taken in high-risk populations, and such higher-risk susceptible areas to reduce the incidence of brucellosis and ensure the health of the people.
Literature
1.
Sulayman S, Bora RS, Sabir J, et al. Brucellosis: current status of the disease and future perspectives. Postepy Mikrobiologii. 2020;59(4):337–44.
2.
Pappas G, Akritidis N, Bosilkovski M, Tsianos E, Brucellosis. N Engl J Med. 2005;352(22):2325–36.PubMed
3.
Haque N, Bari MS, Hossain MA, et al. An overview of brucellosis. Mymensingh Med J. 2011;20(4):742–7.PubMed
4.
Zheng R, Xie S, Lu X, et al. A systematic review and Meta-analysis of epidemiology and clinical manifestations of human brucellosis in China. Biomed Res Int. 2018;2018:5712920.PubMedPubMedCentral
5.
Seleem MN, Boyle SM, Sriranganathan N. Brucellosis: a re-emerging zoonosis. Vet Microbiol. 2010;140(3–4):392–8.PubMed
6.
Godfroid J, Al Dahouk S, Pappas G, Roth F, Matope G, Muma J, Marcotty T, Pfeiffer D, Skjerve E. A “One Health” surveillance and control of brucellosis in developing countries: moving away from improvisation. Comp Immunol Microbiol Infect Dis. 2013;36(3):241–8.PubMed
7.
Dean AS, Crump L, Greter H, Schelling E, Zinsstag J. Global burden of human brucellosis: a systematic review of disease frequency. PLoS Negl Trop Dis. 2012;6(10):e1865.PubMedPubMedCentral
8.
Pappas G, Papadimitriou P, Akritidis N, Christou L, Tsianos EV. The new global map of human brucellosis. Lancet Infect Dis. 2006;6(2):91–9.PubMed
9.
Chen QL. Spatial-temporal analysis of the prevalence of brucellosis in my country and research on the health-related quality of life of patients [D]. Chinese Center for Disease Control and Prevention; 2017.
10.
Lai S, Zhou H, Xiong W, et al. Changing epidemiology of human brucellosis, China, 1955–2014. Emerg Infect Dis. 2017;23(2):184–94.PubMedPubMedCentral
11.
Flahaut B, Mouchart M, Martin ES, Thomas I. The local spatial autocorrelation and the kernel method for identifying black zones: a comparative approach. Accid Anal Prev. 2003;35(6):991–1004.PubMed
12.
Mattsson BJ, Zipkin EF, Gardner B, Blank PJ, Sauer JR, Royle JA. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage. PLoS ONE. 2013;8:e55097.PubMedPubMedCentral
13.
Viladomat J, Mazumder R, Mcinturff A, McCauley DJ, Hastie T. Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach. Biometrics. 2014;70(2):409–18.PubMedPubMedCentral
14.
Tillé Y, Dickson MM, Espa G, Giuliani D. Measuring the spatial balance of a sample: a new measure based on the Moran’s I index. Spat Stat. 2018;23:182–92.
15.
Mao Y, Zhang N, Zhu B, Liu J, He R. A descriptive analysis of the Spatio-temporal distribution of intestinal infectious diseases in China. BMC Infect Dis. 2019;19(1):766.PubMedPubMedCentral
16.
Xiao-Ni H, Wei-Wei Z, Dan-Feng S, Hong L, Lian-Di Z, Bao-Guo L. Spatial pattern analysis of heavy metals in Beijing agricultural soils based on spatial autocorrelation statistics. Inter J Env Res Pub Heal. 2011;8:2074–89.
17.
Anselin L. Local indicators of spatial association-LISA. Geogr Anal. 1995;27:93–115.
18.
Erkihun T, Amsalu T, Yihunie A. Spatial distribution and determinants of acute respiratory infection among under-five children in Ethiopia: ethiopian demographic health survey 2016. PLoS ONE. 2019;14(4):e0215572.
19.
Zhang H, Yang L, Li L, Xu G, Zhang X. The epidemic characteristics and spatial autocorrelation analysis of hand, foot and mouth disease from 2010 to 2015 in Shantou, Guangdong, China. BMC Public Health. 2019;19(1):998.PubMedPubMedCentral
20.
T Waldhör. The spatial autocorrelation coefficient Moran’s I under heteroscedasticity. Stat Med. 2010;15(7–9):887–92.
21.
Anselin L. Local Indicator of spatial AssociationLISA. GeogrAnal. 2010;27(2):93–115.
22.
Kulldorff M. A spatial scan statistic. Commun Stat TheoryMethods. 1997;26:1481–96.
23.
Kulldorff M, Heffernan R, Hartman J, et al. A space-time permutation scan statistic for Disease Outbreak Detection. PLoS Med. 2005;2(3):e59.PubMedPubMedCentral
24.
Jones SG, Martin K, Philip B. Influence of spatial resolution on space-time disease cluster detection. PLoS ONE. 2012;7:e48036.PubMedPubMedCentral
25.
Kulldorff M, Huang L, Pickle L, Duczmal L. An elliptic spatial scan statistic. Stat Med. 2006;25(22):3929–43.PubMed
26.
Kleinman KP, Abrams AM, Kulldorff M, Platt R. A model-adjusted space–time scan statistic with an application to syndromic surveillance. Epidemiol Infect. 2005;133(3):409–19.PubMedPubMedCentral
27.
Hunachew B, Wakgari D, Abera K, Delia G. Spatial, temporal, and spatio-temporal analysis of under-five diarrhea in southern Ethiopia. Trop Med Health. 2018;46:18.
28.
Sluydts V, Heng S, Coosemans M, Van Roey K, Gryseels C, Canier L, et al. Spatial clustering and risk factors of malaria infections in Ratanakiri Province, Cambodia. Malar J. 2014;13:387.PubMedPubMedCentral
29.
Zhu B, Liu J, Fu Y, Zhang B, Mao Y. Spatio-temporal epidemiology of viral hepatitis in China (2003–2015): implications for prevention and control policies. Int J Environ Res Public Health. 2018;15(4):661.PubMedPubMedCentral
30.
Kulldorff M, Feuer EJ, Miller BA, Freedman LS. Breast cancer clusters in the northeast United States: a geographic analysis. Am J Epidemiol. 1997;146(2):161–70.PubMed
31.
Liu MY, Li QH, Zhang YJ, Ma Y, Liu Y, Feng W, et al. Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005–2015. Infect Dis Poverty. 2018;7:106.PubMedPubMedCentral
32.
Wang LY, Zhang WY, Ding F, Hu WB, Magalhaes RJ, Sun HL, et al. Spatio-temporal patterns of japanese encephalitis in China, 2002–2010. PLoS Negl Trop D. 2013;7:e2285.
33.
Rubach MP, Halliday JE, Cleaveland S, Crump JA. Brucellosis in low-income and middle-income countries. Curr Opin Infect Dis. 2013;26(5):404–12.PubMedPubMedCentral
34.
Li F, He F, Sun J, Zhai Y, Jiang J, Lin J. Spatial and temporal analysis of severe fever with thrombocytopenia syndrome in Zhejiang Province, China, 2011–2015. J Infect Dev Ctries. 2019;13(1):35–43.PubMed
35.
Caprarelli G, Fletcher S. A brief review of spatial analysis concepts and tools used for mapping, containment and risk modelling of infectious diseases and other illnesses. Parasitology. 2014;141(5):581–601.PubMed
36.
Cui BY, Jiang H. Epidemiology of brucellosis in China, 2005–2016. Disease Surveillance. 2016;31(12):1018–22.
37.
Shuman EK. Global climate change and infectious diseases. [J]. Int J Occup Environ Med. 2010;2(1):1061–3.
38.
Liang PF, Zhao Y, Zhao JH, Pan DF, Guo ZQ. Human distribution and spatial-temporal clustering analysis of human brucellosis in China from 2012 to 2016. Infect Dis Poverty. 2020;9(1):142.PubMedPubMedCentral
39.
Maryam D, Youcef S, Adrian M, et al. Human brucellosis caused by raw dairy products: a review on the occurrence, major risk factors and prevention. IntJ Food Microbiol. 2018;292:39.
40.
Glikman D. Human brucellosis in Israel-the Saga continues. Isr Med Assoc J. 2019;21:52–3.PubMed
41.
Peng C, Li YJ, Huang DS, Guan P. Spatial-temporal distribution of human brucellosis in mainland China from 2004 to 2017 and an analysis of social and environmental factors. Environ Health Prev Med. 2020;25(1):1.PubMedPubMedCentral
42.
Li Y, Li X, Liang S, Fang L, Cao W. Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China. BMC Infect Dis. 2013;13:547.PubMedPubMedCentral
43.
Wang Y, Xu C, Zhang S, Wang Z, Zhu Y, Yuan J. Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018. Sci Rep. 2018;8(1):15901.PubMedPubMedCentral
44.
Park MY, Lee CS, Choi YS, Park SJ, Lee JS, Lee HB. A sporadic outbreak of human brucellosis in Korea. J Korean Med Sci. 2005;20(6):941–6.PubMedPubMedCentral
45.
Pakzad R, Pakzad I, Safiri S, et al. Spatio-temporal analysis of brucellosis incidence in Iran from 2011 to 2014 using GIS. Int J Infect Dis. 2018;67:129–36.PubMed
46.
Ahmadkhani M, Alesheikh AA. Space-time analysis of human brucellosis considering environmental factors in Iran. Asian Pac J Trop Disease. 2017;7(5):257–65.
47.
Li YJ, Li XL, Liang S, Fang LQ, Cao WC. Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China. BMC Infect Dis. 2013;1:547.
48.
Zhang J, Sun GQ, Sun XD, Hou Q, Li MT, Huang BX, et al. Prediction and control of brucellosis transmission of dairy cattle in Zhejiang Province, China. PLoS ONE. 2014;9(11):e108592.PubMedPubMedCentral
49.
Zhou K, Wu B, Pan H, et al. ONE Health Approach to address zoonotic brucellosis: a Spatio-temporal Associations Study between Animals and humans. Front Vet Sci. 2020;7:521.PubMedPubMedCentral
Metadata
Title
Epidemiological characteristics and spatio-temporal analysis of brucellosis in Shandong province, 2015–2021
Authors
Xiaolin Yu
Ming Fang
Yan Li
Jianmei Yu
Lixiao Cheng
Shujun Ding
Zengqiang Kou
Publication date
01-12-2023
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2023
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-023-08503-6

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