1
|
Xiao P, Hao Y, Yuan Y, Ma W, Li Y, Zhang H, Li N. Emerging West African Genotype Chikungunya Virus in Mosquito Virome. Virulence 2025; 16:2444686. [PMID: 39715491 DOI: 10.1080/21505594.2024.2444686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 08/09/2024] [Accepted: 12/13/2024] [Indexed: 12/25/2024] Open
Abstract
We studied the viromes of three dominant mosquito species in Wenzhou, a coastal city in Zhejiang Province, using metavirome sequencing, with 18 viral families identified. Viral sequences were verified by RT-PCR. The JEV E gene was most closely related to the 1988 Korean strain. DENV sequences were most closely related to the 1997 Australian strain. CHIKV-E1-1 was most closely related to the 1983 Senegal strain and belonged to West African genotype CHIKV. Remarkably, this is the first time that a West African genotype of CHIKV has been detected in Zhejiang Province. Mutations in the CHIKV-E1-1 protein A226V may increase infectivity in Ae. albopictus. Three non-conservative mutations of CHIKV-E1-1 (D45H, D70H and V290D) may have an impact on the function. In conclusion, our study reveals the diversity of mosquito-borne viruses and potential emerging outbreaks in the southeast coastal region of China, providing new perspectives for mining the ecological characterization of other important arboviruses.
Collapse
Affiliation(s)
- Pengpeng Xiao
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| | - Yujia Hao
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| | - Yuge Yuan
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| | - Wenzhou Ma
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| | - Yiquan Li
- Academician Workstation of Jilin Province, Changchun University of Chinese Medicine, Changchun, China
| | - He Zhang
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Nan Li
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| |
Collapse
|
2
|
Zhang W, Liu Q, Ni J, Wang J, Gong Z. Negative binomial regression analysis of factors influencing the number of distinct mosquito species in Zhejiang Province, China, 2023. Sci Rep 2025; 15:10433. [PMID: 40140464 PMCID: PMC11947306 DOI: 10.1038/s41598-025-94288-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Accepted: 03/12/2025] [Indexed: 03/28/2025] Open
Abstract
Mosquito species have different breeding environment requirements, understanding how environmental factors affect mosquito populations can help characterize mosquito vector ecology and facilitate control strategies. This study investigated the number of different mosquito species captured by mosquito trapping lights in relation to landscape, habitat, month, and the number of trapping lights. Field mosquitoes were collected using mosquito trapping lights at five different habitat locations in each monitoring site in Zhejiang Province, China from April to November 2023. The monitoring data were summarized using Excel 2016. Single-factor analysis was conducted using the chi-square (χ2) test with SPSS 15.0 software, and multiple-factor analysis was performed using the negative binomial regression (NBR) model with Stata 16.0 software. The results indicated that landscape, habitat, and month all significantly impact the number of mosquitoes captured by mosquito trapping lights (P < 0.001). All regions in Zhejiang Province should develop targeted mosquito vector prevention and control strategies, taking into account local ecological conditions.
Collapse
Affiliation(s)
- Wenrong Zhang
- School of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Qinmei Liu
- Department of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Jing Ni
- School of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jinna Wang
- Department of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Zhenyu Gong
- Department of Communicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| |
Collapse
|
3
|
Sun B, Xu M, Jia L, Liu H, Li A, Hui L, Wang Z, Liu D, Yan Y. Genomic variants and molecular epidemiological characteristics of dengue virus in China revealed by genome-wide analysis. Virus Evol 2025; 11:veaf013. [PMID: 40135062 PMCID: PMC11934549 DOI: 10.1093/ve/veaf013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 02/10/2025] [Accepted: 03/15/2025] [Indexed: 03/27/2025] Open
Abstract
Since its first academic record in 1978, dengue epidemics have occurred in all provinces of China, except Xizang. The epidemiological and molecular features of the whole genome of dengue virus (DENV) have not yet been completely elucidated, interfering with prevention and control strategies for dengue fever in China. Here, we obtained 553 complete genomes of the four serotypes of DENV (DENV1-4) isolated in China from the GenBank database to analyze the phylogeny, recombination, genomic variants, and selection pressure and to estimate the substitution rates of DENV genomes. Phylogenetic analyses indicated that DENV sequences from China did not cluster together and were genetically closer to those from Southeast Asian countries in the maximum likelihood trees, indicating that DENV was not endemic in China. Thirty intra-serotype recombinant sequences were identified for DENV1-4, with the highest frequency in DENV4. Selection pressure analyses revealed that 13 codons under positive selection were located in the C, NS1, NS2A, NS3, and NS5 proteins. For DENV1 to DENV3, the substitution rates evaluated in this study were 9.23 × 10-4, 7.59 × 10-4, and 7.06 × 10-4 substitutions per site per year, respectively. These findings improve our understanding of the evolution of DENV in China.
Collapse
Affiliation(s)
- Bangyao Sun
- School of Medical Laboratory, Shandong Second Medical University, Baotong West Street 7166#, Weifang 261053, China
| | - Meng Xu
- CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
- Computational Virology Group, Center for Bacteria and Viruses Resources and Bioinformation, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Kaiyuan Avenue 190#, Guangzhou 510530, China
- University of Chinese Academy of Sciences,Yuquan Road 19#, Beijing 100049, China
| | - Lijia Jia
- CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
- Computational Virology Group, Center for Bacteria and Viruses Resources and Bioinformation, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
| | - Haizhou Liu
- CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
- Computational Virology Group, Center for Bacteria and Viruses Resources and Bioinformation, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
| | - Aixin Li
- School of Medical Laboratory, Shandong Second Medical University, Baotong West Street 7166#, Weifang 261053, China
| | - Lixia Hui
- School of Medical Laboratory, Shandong Second Medical University, Baotong West Street 7166#, Weifang 261053, China
| | - Zhitao Wang
- School of Life Science and Technology, Shandong Second Medical University, Baotong West Street 7166#, Weifang 261053, China
| | - Di Liu
- CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
- Computational Virology Group, Center for Bacteria and Viruses Resources and Bioinformation, Wuhan Institute of Virology, Chinese Academy of Sciences, Jinlong Street 262#, Wuhan 430207, China
| | - Yi Yan
- Department of Respiratory Medicine, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hong Kong Road 100#, Wuhan 430015,China
- Pediatric Respiratory Disease Laboratory, Institute of Maternal and Child Health, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hong Kong Road 100#, Wuhan 430015,China
| |
Collapse
|
4
|
Feng X, Jiang N, Zheng J, Zhu Z, Chen J, Duan L, Song P, Sun J, Zhang X, Hang L, Liu Y, Zhang R, Feng T, Xie B, Wu X, Hou Z, Chen M, Jiang J, Li S. Advancing knowledge of One Health in China: lessons for One Health from China's dengue control and prevention programs. SCIENCE IN ONE HEALTH 2024; 3:100087. [PMID: 39641122 PMCID: PMC11617290 DOI: 10.1016/j.soh.2024.100087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2024] [Accepted: 11/04/2024] [Indexed: 12/07/2024]
Abstract
Background The emergence of dengue fever has prompted significant public health responses, highlighting the need for a comprehensive understanding of One Health in addressing vector-borne diseases. China's experience in dengue control and prevention programs offers valuable insights into the successful integration of multidisciplinary strategies. Aims The review aims to: (1) systematically analyze lessons from China's dengue control and prevention programs, focusing on the integration of these efforts with the One Health approach; (2) underscore the reasons of optimizing the dengue control and prevention program; (3) highlight the alignment of China's dengue control strategies with the One Health framework; (4) contribute to global efforts in combating dengue, providing scientific evidence and strategic recommendations for other regions facing similar challenges. Results Through a comprehensive literature review and expert interviews, this study found China's approach to dengue control and prevention implemented through a hierarchical system led by the government, with collaborative efforts across multiple departments. This multi-sectoral collaboration mechanism enables the technical interventions well executed by health and disease control institutions, optimizing the integration of multiple cost-effeteness approaches, such as case management, early detection and outbreak response, reducing local transmission, and minimizing severe cases and fatalities. It was found that community participation and public health education have played a vital role in raising awareness, promoting personal protective measures, and enhancing the overall effectiveness of control efforts. The implementation of these integrated interventions has resulted in reduced dengue cases and improved capacity of outbreak response. China's dengue control strategies under the One Health framework, with focus on interdisciplinary collaboration, incorporated environmental and ecological interventions, which reduced mosquito breeding sites and improved sanitation. The findings of the review underscore the need for continuous improvement in early warning systems, scientific research, and the adoption of the One Health approach to address emerging challenges posed by climate change and the cross-border spread of infectious diseases. Conclusion China's dengue control and prevention programs provide a compelling case study for the effective application of the One Health approach. By systematically analyzing the integration of multidisciplinary strategies, this review reveals valuable lessons on optimizing public health responses to vector-borne diseases. The alignment of these strategies with One Health principles not only enhances the effectiveness of dengue control efforts in China but also offers a framework that can be adapted by other regions facing similar challenges. Ultimately, the insights gained from this analysis contribute to the global fight against dengue, emphasizing the need for collaborative and holistic approaches in public health initiatives.
Collapse
Affiliation(s)
- Xinyu Feng
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 20025, China
- One Health Center, Shanghai Jiao Tong University-The University of Edinburgh, Shanghai 20025, China
| | - Na Jiang
- College of Life Sciences, Inner Mongolia University, Hohhot Inner Mongolia 010021, China
| | - Jinxin Zheng
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 20025, China
- One Health Center, Shanghai Jiao Tong University-The University of Edinburgh, Shanghai 20025, China
| | - Zelin Zhu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Junhu Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Lei Duan
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
- School of Life Science, Fudan University, Shanghai 200438, China
| | - Peng Song
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Jiahui Sun
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Xiaoxi Zhang
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 20025, China
- One Health Center, Shanghai Jiao Tong University-The University of Edinburgh, Shanghai 20025, China
| | - Lefei Hang
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 20025, China
- One Health Center, Shanghai Jiao Tong University-The University of Edinburgh, Shanghai 20025, China
| | - Yang Liu
- Sichuan Center for Disease Control and Prevention, Chengdu 610041, Sichuan, China
| | - Renli Zhang
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518073, Guangdong, China
| | - Tiejian Feng
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518073, Guangdong, China
| | - Binbin Xie
- Hainan Tropical Disease Research Center, Haikou 570100, Hainan, China
| | - Xiaonen Wu
- Hainan Tropical Disease Research Center, Haikou 570100, Hainan, China
| | - Zhiying Hou
- Hainan Tropical Disease Research Center, Haikou 570100, Hainan, China
| | - Muxin Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
| | - Jinyong Jiang
- Yunnan International Joint Laboratory of Tropical Infectious Diseases, Yunnan Provincial Key Laboratory of Vector-Borne Diseases Control and Research, Yunnan Key Technology Innovation Team for Insect Borne Infectious Disease Prevention and Control, Yunnan Institute of Parasitic Diseases, Pu'er 665000, Yunan, China
| | - Shizhu Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Chinese Center for Tropical Diseases Research, Shanghai 200025, China
- NHC Key Laboratory for Parasitology and Vector Biology, Shanghai 200025, China
- WHO Collaborating Center for Tropical Diseases, Shanghai 200025, China
- National Center for International Research on Tropical Diseases, Shanghai 200025, China
| |
Collapse
|
5
|
Wu Y, Zhang C, Feng W, Fu S, Dong W, Wang J, Liu Q, Li T, Luo M, Gong Z. Development and field evaluation of a novel sugar bait device for controlling residential vector mosquitoes in Zhejiang Province, China. Front Vet Sci 2024; 11:1364740. [PMID: 38601912 PMCID: PMC11004449 DOI: 10.3389/fvets.2024.1364740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 03/18/2024] [Indexed: 04/12/2024] Open
Abstract
Background Mosquito-borne diseases pose serious public health threats in Zhejiang Province, China, and vector control is believed to be the primary method for reducing transmission. Due to severe resistance problems, effective and sustainable methods without chemical insecticides are urgently required to control mosquito vectors. Attractive toxic sugar baits (ATSB) are newly developed methods to control mosquitoes in recent decades with the core element sugar bait, which was invented according to the sugar-feeding behavior of mosquitoes. In this study, we developed a Novel Sugar Bait Device (NSBD) trap by combining sugar bait and physical adhesive capture technology. The study aimed to evaluate the effect of the NSBD trap on controlling mosquitoes in residential environments and to identify the optimal sugar solution concentration in the sugar bait of the NSBD for real use. Methods Four residential villages in Ningbo City with similar geographic environments and mosquito densities were selected for field trials in 2022. One village (site 1) was designated as the control group, and three villages (sites 2-4) served as the test groups to assess the effectiveness of NSBD traps with different sugar solution concentrations (6, 8, and 10%) in the sugar bait. Larval and adult mosquito densities were monitored monthly before and semi-monthly after the trials using the CDC light trap and larval pipette method. Results Before the trials, we monitored mosquito density for 3 months to confirm the baseline mosquito density among the four sites, and no statistical differences in adult and larval mosquitoes were found (adult, F = 3.047, p > 0.05; larvae, F = 0.436, p > 0.05). After the trials, all NCBD traps effectively controlled larval and adult mosquito densities, with the highest standard decrease rates of larval and adult mosquito densities at 57.80 and 86.31%, respectively, observed in site 4. The most suitable sugar solution concentration in the sugar bait was 10%. Conclusion NSBD traps effectively controlled mosquitoes in residential environments during field trials. Without the use of insecticides, this may be a promising choice for mosquito vector control to prevent mosquito-borne diseases.
Collapse
Affiliation(s)
- Yuyan Wu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Chuan Zhang
- Fenghua District Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Wei Feng
- Fenghua District Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Sanjun Fu
- Fenghua District Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Weibo Dong
- Fenghua District Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Jinna Wang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Qinmei Liu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Tianqi Li
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Mingyu Luo
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Zhenyu Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| |
Collapse
|
6
|
Wu Y, Wang J, Liu Q, Li T, Luo M, Gong Z. Practice of integrated vector surveillance of arthropod vectors, pathogens and reservoir hosts to monitor the occurrence of tropical vector-borne diseases in 2020 in Zhejiang Province, China. Front Vet Sci 2022; 9:1003550. [PMID: 36467661 PMCID: PMC9709469 DOI: 10.3389/fvets.2022.1003550] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 10/28/2022] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Vector-borne diseases have become one of the most serious local public health threats. Monitoring and controlling vectors are important means of controlling vector-borne diseases. However, traditional vector surveillance systems in China mainly monitor vector density, making its early-warning effect on vector-borne diseases weak. In this study, we applied an integrated surveillance system of multiple arthropod vectors and reservoir host containing ecology, etiology, and drug resistance monitoring to obtain better knowledge on vector populations and provide early warning of suspicious vector-borne infectious disease occurrence. METHODS An ecology surveillance of mosquitoes, rodents, ticks, and chigger mites, a pathogen infection survey on mosquitoes and rodents, and a drug resistance survey on Aedes albopictus were conducted in 12 cities in Zhejiang Province in 2020. RESULTS A total of 15,645 adult mosquitoes were collected at a density of 19.8 mosquitoes per Centers for Disease Control and Prevention light trap. Culex tritaeniorhynchus (72.76%) was the most abundant species. The Breteau index of Ae. albopictus was 13.11. The rodent density was 0.91 rodents per hundred traps; the most abundant species was Rattus norvegicus (33.73%). The densities of dissociate and ectoparasitic ticks were 0.79 ticks per hundred meters and 0.97 ticks per animal, respectively. The most abundant tick species was Haemaphysalis longicornis (56.38%). The density of chigger mites was 14.11 per rodent; two species were identified, with the most abundant species being Walchia spp. mite (68.35%). No flavivirus or alphavirus was found in mosquito etiology monitoring, whereas the positivity rates of hantavirus, the pathogenic bacteria Leptospira spp., Orientia tsutsugamushi, and Bartonella spp. detected in rodent etiology monitoring were 1.86, 7.36, 0.35 and 7.05%, respectively. Field populations of Ae. albopictus in Zhejiang Province were widely resistant to pyrethroids but sensitive to most insecticides tested, including organophosphorus and carbamate insecticides. CONCLUSION Integrated surveillance systems on multiple arthropod vectors (mosquitoes, ticks, mites) and animal reservoirs (rodents) can provide important information for the prevention and control of epidemic emergencies.
Collapse
Affiliation(s)
| | | | | | | | | | - Zhenyu Gong
- Department of Infectious Diseases Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| |
Collapse
|