Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China
Background: China is confronted with the significant menace posed by hemorrhagic fever with renal syndrome (HFRS). Nevertheless, the long-term spatial-temporal variations, regional prevalence patterns, and fundamental determinants' mechanisms for HFRS remain inadequately elucidated. Methods: Ne...
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Elsevier
2024-06-01
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| Series: | One Health |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S235277142400051X |
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| author | Bo Wen Zurong Yang Shaolong Ren Ting Fu Rui Li Mengwei Lu Xiaoang Qin Ang Li Zhifu Kou Zhongjun Shao Kun Liu |
| author_facet | Bo Wen Zurong Yang Shaolong Ren Ting Fu Rui Li Mengwei Lu Xiaoang Qin Ang Li Zhifu Kou Zhongjun Shao Kun Liu |
| author_sort | Bo Wen |
| collection | DOAJ |
| description | Background: China is confronted with the significant menace posed by hemorrhagic fever with renal syndrome (HFRS). Nevertheless, the long-term spatial-temporal variations, regional prevalence patterns, and fundamental determinants' mechanisms for HFRS remain inadequately elucidated. Methods: Newly diagnosed cases of HFRS from January 2004 to December 2019 were acquired from the China Public Health Science Data repository. We used Age-period-cohort and Bayesian Spacetime Hierarchy models to identify high-risk populations and regions in mainland China. Additionally, the Geographical Detector model was employed to quantify the determinant powers of significant driver factors to the disease. Results: A total of 199,799 cases of HFRS were reported in mainland China during 2004–2019. The incidence of HFRS declined from 1.93 per 100,000 in 2004 to 0.69 per 100,000 in 2019. The incidence demonstrated an inverted U-shaped trend with advancing age, peaking in the 50–54 age group, with higher incidences observed among individuals aged 20–74 years. Hyperendemic areas were mainly concentrated in the northeastern regions of China, while some western provinces exhibited a potential upward trend. Geographical detector model identified that the spatial variations of HFRS were significantly associated with the relative humidity (Q = 0.36), forest cover (Q = 0.26), rainfall (Q = 0.18), temperature (Q = 0.16), and the surface water resources (Q = 0.14). Conclusions: This study offered comprehensive examinations of epidemic patterns, identified high-risk areas quantitatively, and analyzed factors influencing HFRS transmission in China. The findings may contribute to the necessary implementations for the effective prevention and control of HFRS. |
| first_indexed | 2024-04-24T10:57:57Z |
| format | Article |
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| language | English |
| last_indexed | 2024-04-24T10:57:57Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
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| series | One Health |
| spelling | doaj.art-dffec43c77c04124a2653314b28243cf2024-04-12T04:45:27ZengElsevierOne Health2352-77142024-06-0118100725Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in ChinaBo Wen0Zurong Yang1Shaolong Ren2Ting Fu3Rui Li4Mengwei Lu5Xiaoang Qin6Ang Li7Zhifu Kou8Zhongjun Shao9Kun Liu10Department of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of China; Lintong Rehabilitation and Convalescent Centre, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of ChinaDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of China; Corresponding authors at: 169 Chang-Le Street, Xincheng District, Xi'an, Shaanxi 710032, People's Republic of China.Department of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China; Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, People's Republic of China; Corresponding authors at: 169 Chang-Le Street, Xincheng District, Xi'an, Shaanxi 710032, People's Republic of China.Background: China is confronted with the significant menace posed by hemorrhagic fever with renal syndrome (HFRS). Nevertheless, the long-term spatial-temporal variations, regional prevalence patterns, and fundamental determinants' mechanisms for HFRS remain inadequately elucidated. Methods: Newly diagnosed cases of HFRS from January 2004 to December 2019 were acquired from the China Public Health Science Data repository. We used Age-period-cohort and Bayesian Spacetime Hierarchy models to identify high-risk populations and regions in mainland China. Additionally, the Geographical Detector model was employed to quantify the determinant powers of significant driver factors to the disease. Results: A total of 199,799 cases of HFRS were reported in mainland China during 2004–2019. The incidence of HFRS declined from 1.93 per 100,000 in 2004 to 0.69 per 100,000 in 2019. The incidence demonstrated an inverted U-shaped trend with advancing age, peaking in the 50–54 age group, with higher incidences observed among individuals aged 20–74 years. Hyperendemic areas were mainly concentrated in the northeastern regions of China, while some western provinces exhibited a potential upward trend. Geographical detector model identified that the spatial variations of HFRS were significantly associated with the relative humidity (Q = 0.36), forest cover (Q = 0.26), rainfall (Q = 0.18), temperature (Q = 0.16), and the surface water resources (Q = 0.14). Conclusions: This study offered comprehensive examinations of epidemic patterns, identified high-risk areas quantitatively, and analyzed factors influencing HFRS transmission in China. The findings may contribute to the necessary implementations for the effective prevention and control of HFRS.http://www.sciencedirect.com/science/article/pii/S235277142400051XHemorrhagic fever with renal syndromeSpatial-temporal patternsRisk factorsChina |
| spellingShingle | Bo Wen Zurong Yang Shaolong Ren Ting Fu Rui Li Mengwei Lu Xiaoang Qin Ang Li Zhifu Kou Zhongjun Shao Kun Liu Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China One Health Hemorrhagic fever with renal syndrome Spatial-temporal patterns Risk factors China |
| title | Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China |
| title_full | Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China |
| title_fullStr | Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China |
| title_full_unstemmed | Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China |
| title_short | Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China |
| title_sort | spatial temporal patterns and influencing factors for hemorrhagic fever with renal syndrome a 16 year national surveillance analysis in china |
| topic | Hemorrhagic fever with renal syndrome Spatial-temporal patterns Risk factors China |
| url | http://www.sciencedirect.com/science/article/pii/S235277142400051X |
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