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Han X, Gao S, Xin Q, Yang M, Bi Y, Jiang F, Zeng Z, Kan W, Wang T, Chen Q, Chen Z. Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China. J Med Virol 2024; 96:e29373. [PMID: 38235541 DOI: 10.1002/jmv.29373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 12/06/2023] [Accepted: 12/25/2023] [Indexed: 01/19/2024]
Abstract
The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick-borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high-risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work.
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Affiliation(s)
- Xiaohu Han
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
| | - Shan Gao
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China
| | - Qing Xin
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
| | - Mingwei Yang
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China
| | - Yudan Bi
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
| | - Feng Jiang
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
| | - Zan Zeng
- Department of Vascular Surgery, The First Affiliated Hospital of the Navy Medical University, Shanghai, People's Republic of China
| | - Wei Kan
- Animal Disease Prevention and Control Center in Qinghai Province, Xining, People's Republic of China
| | - Tongyao Wang
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
| | - Qijun Chen
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
| | - Zeliang Chen
- Key Laboratory of Livestock Infectious Diseases, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning, People's Republic of China
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China
- Innovative Institute of Zoonoses, Inner Mongolia Minzu University, Tongliao, People's Republic of China
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YAO Z, ZHAI Y, WANG X, WANG H. Estimating the spatial distribution of African swine fever outbreak in China
by combining four regional-level spatial models. J Vet Med Sci 2023; 85:1330-1340. [PMID: 37899237 PMCID: PMC10788172 DOI: 10.1292/jvms.23-0146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 10/09/2023] [Indexed: 10/31/2023] Open
Abstract
The outbreaks of African Swine Fever (ASF) in China are ongoing, and the inadequate management of the pig supply chain is criticized. In the past four years, a series of preventive and control measures have been supplied national wide, while the outbreaks have not been terminated. This suggests the existing animal disease management at the district level may not be appropriate to control ASF under the current situation of the ASF outbreak in China. It is urgent to further describe real distribution areas of ASF in China. In this study, we combined four regional-scale models to predict the risk distribution of ASF in mainland China and identify risk factors related to ASF outbreaks. The results showed that the four regional-scale models were more accurate in predicting the ASF outbreaks than the nationwide scale model. The four regional-scale models identified the potential risk factors associated with ASF outbreaks, such as population density, pig density, land cover, temperature, and elevation factors. Moreover, seven clusters with high potential risk of ASF outbreaks were identified. Then, based on the results, we proposed more suitable prevention and control plans for ASF, which can assist the implementation of transport management policies within and between risk clusters.
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Affiliation(s)
- ZhenFei YAO
- Center of Conservation Medicine and Ecological Safety,
Northeast Forestry University, Heilongjiang, P.R. China
- College of Wildlife and Protected Area, Northeast
Forestry University, Heilongjiang, P.R. China
| | - YuJia ZHAI
- Center of Conservation Medicine and Ecological Safety,
Northeast Forestry University, Heilongjiang, P.R. China
- College of Wildlife and Protected Area, Northeast
Forestry University, Heilongjiang, P.R. China
| | - XiaoLong WANG
- Center of Conservation Medicine and Ecological Safety,
Northeast Forestry University, Heilongjiang, P.R. China
- College of Wildlife and Protected Area, Northeast
Forestry University, Heilongjiang, P.R. China
| | - HaoNing WANG
- School of Geography and Tourism, Harbin University,
Heilongjiang, P.R. China
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