Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018
Abstract Despite the considerable efforts made to address the issue of brucellosis worldwide, its prevalence in dairy products continues to be difficult to estimate and represents a significant public health concern globally. The aim of the present study was to gain a better understanding of the epi...
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Nature Portfolio
2025-03-01
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| author | Yuan Zhao Dongfeng Pan Yanfang Zhang Lixu Ma Hong Li Jingjing Li Shanghong Liu Peifeng Liang |
| author_facet | Yuan Zhao Dongfeng Pan Yanfang Zhang Lixu Ma Hong Li Jingjing Li Shanghong Liu Peifeng Liang |
| author_sort | Yuan Zhao |
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| description | Abstract Despite the considerable efforts made to address the issue of brucellosis worldwide, its prevalence in dairy products continues to be difficult to estimate and represents a significant public health concern globally. The aim of the present study was to gain a better understanding of the epidemiology of this disease in mainland China. We set out to investigate the annual spatial distribution and potential hotspots of the disease. Data on the incidence rate of brucellosis from 2012 to 2018 was obtained from the China Disease Control and Prevention Information System (CDCIS). ArcGIS 10.6 software was employed to perform kriging interpolation analysis and to create a predictive distribution map for brucellosis. Additionally, SaTScan software was utilized to conduct spatial-temporal scanning analysis to identify potential spatial-temporal changes in the incidence rate of brucellosis in China. There is a seasonal trend in the incidence of brucellosis in China, with higher rates observed during the warm season, particularly peaking in May. The results of the exploratory analysis of kriging data indicate that the average incidence map, generated using the second-order Gaussian semi-variance model with log-kriging interpolation, demonstrates the highest accuracy. Spatial and temporal clustering analyses reveal a primary clustering area centered in Heilongjiang, along with three secondary clustering areas located in Tibet, Shanxi, and Hubei. Additionally, the predictive distribution map for brucellosis in China, along with the analysis of the scanning statistic, indicates that the high-incidence area is situated in the northwest region of mainland China, although there is a noticeable trend of shifting towards the south. There are distinct spatial patterns of brucellosis in China. In high-incidence areas, it is essential to allocate additional resources for prevention and control to effectively contain the spread of brucellosis epidemics. In low-incidence areas, it is vital to promptly identify favorable factors that can help mitigate the occurrence of brucellosis. |
| format | Article |
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| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-e017e09a5f7c4c679ef21da580a32f742025-08-20T02:59:27ZengNature PortfolioScientific Reports2045-23222025-03-0115111210.1038/s41598-025-91769-4Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018Yuan Zhao0Dongfeng Pan1Yanfang Zhang2Lixu Ma3Hong Li4Jingjing Li5Shanghong Liu6Peifeng Liang7Public Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityDepartment of Emergency, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityPublic Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityPublic Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityPublic Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityPublic Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityPublic Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityPublic Health Center, People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical UniversityAbstract Despite the considerable efforts made to address the issue of brucellosis worldwide, its prevalence in dairy products continues to be difficult to estimate and represents a significant public health concern globally. The aim of the present study was to gain a better understanding of the epidemiology of this disease in mainland China. We set out to investigate the annual spatial distribution and potential hotspots of the disease. Data on the incidence rate of brucellosis from 2012 to 2018 was obtained from the China Disease Control and Prevention Information System (CDCIS). ArcGIS 10.6 software was employed to perform kriging interpolation analysis and to create a predictive distribution map for brucellosis. Additionally, SaTScan software was utilized to conduct spatial-temporal scanning analysis to identify potential spatial-temporal changes in the incidence rate of brucellosis in China. There is a seasonal trend in the incidence of brucellosis in China, with higher rates observed during the warm season, particularly peaking in May. The results of the exploratory analysis of kriging data indicate that the average incidence map, generated using the second-order Gaussian semi-variance model with log-kriging interpolation, demonstrates the highest accuracy. Spatial and temporal clustering analyses reveal a primary clustering area centered in Heilongjiang, along with three secondary clustering areas located in Tibet, Shanxi, and Hubei. Additionally, the predictive distribution map for brucellosis in China, along with the analysis of the scanning statistic, indicates that the high-incidence area is situated in the northwest region of mainland China, although there is a noticeable trend of shifting towards the south. There are distinct spatial patterns of brucellosis in China. In high-incidence areas, it is essential to allocate additional resources for prevention and control to effectively contain the spread of brucellosis epidemics. In low-incidence areas, it is vital to promptly identify favorable factors that can help mitigate the occurrence of brucellosis.https://doi.org/10.1038/s41598-025-91769-4Human brucellosisChinaDynamic seriesKriging interpolationSpatial-temporal scanning |
| spellingShingle | Yuan Zhao Dongfeng Pan Yanfang Zhang Lixu Ma Hong Li Jingjing Li Shanghong Liu Peifeng Liang Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018 Scientific Reports Human brucellosis China Dynamic series Kriging interpolation Spatial-temporal scanning |
| title | Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018 |
| title_full | Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018 |
| title_fullStr | Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018 |
| title_full_unstemmed | Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018 |
| title_short | Spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland China from 2012 to 2018 |
| title_sort | spatial interpolation and spatiotemporal scanning analysis of human brucellosis in mainland china from 2012 to 2018 |
| topic | Human brucellosis China Dynamic series Kriging interpolation Spatial-temporal scanning |
| url | https://doi.org/10.1038/s41598-025-91769-4 |
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