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He D, Gu M, Wang X, Yan Y, Li Y, Wang X, Hu S, Liu X. Reintroduction of highly pathogenic avian influenza A H7N9 virus in southwestern China. Virus Genes 2023; 59:479-483. [PMID: 36781818 PMCID: PMC9924862 DOI: 10.1007/s11262-023-01974-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 01/29/2023] [Indexed: 02/15/2023]
Abstract
Highly pathogenic (HP) avian influenza A H7N9 virus has emerged in China since 2016. In recent years, it has been most prevalent in northern China. However, several strains of HP H7N9 reappeared in southwestern China (Yunnan Province) in 2021. As a result, we are wondering if these viruses have re-emerged in situ or been reintroduced. Here, we present phylogenetic evidence that the HP H7N9 viruses isolated in Yunnan emigrated from northern to southwestern China in 2020. The northern subregion of China has become a novel epicenter in HP H7N9 dissemination. Meanwhile, a cleavage motif re-emerged due to the T341I mutation, implying a parallel evolution. This cross-region transmission, which originated in non-adjacent provinces and traveled a great geographic distance in an unknown way, indicates that HP H7N9 dissemination did not halt in 2020, even under the shadow of the COVID-19 pandemic. Additional surveillance studies in poultry are required to determine the HP H7N9 virus's geographic distribution and spread.
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Affiliation(s)
- Dongchang He
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Min Gu
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Xiyue Wang
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Yayao Yan
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Yang Li
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Xiaoquan Wang
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Shunlin Hu
- grid.268415.cAnimal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China ,grid.268415.cJiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China
| | - Xiufan Liu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou, China. .,Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou, China. .,Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, China.
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2
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Shi Z, Wei L, Wang P, Wang S, Liu Z, Jiang Y, Wang J. Spatio-temporal spread and evolution of influenza A (H7N9) viruses. Front Microbiol 2022; 13:1002522. [PMID: 36187942 PMCID: PMC9520483 DOI: 10.3389/fmicb.2022.1002522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
The influenza A (H7N9) virus has been seriously concerned for its potential to cause an influenza pandemic. To understand the spread and evolution process of the virus, a spatial and temporal Bayesian evolutionary analysis was conducted on 2,052 H7N9 viruses isolated during 2013 and 2018. It revealed that the H7N9 virus was probably emerged in a border area of Anhui Province in August 2012, approximately 6 months earlier than the first human case reported. Two major epicenters had been developed in the Yangtze River Delta and Peral River Delta regions by the end of 2013, and from where the viruses have also spread to other regions at an average speed of 6.57 km/d. At least 24 genotypes showing have been developed and each of them showed a distinct spatio-temporal distribution pattern. Furthermore, A random forest algorithm-based model has been developed to predict the occurrence risk of H7N9 virus. The model has a high overall forecasting precision (> 97%) and the monthly H7N9 occurrence risk for each county of China was predicted. These findings provide new insights for a comprehensive understanding of the origin, evolution, and occurrence risk of H7N9 virus. Moreover, our study also lays a theoretical basis for conducting risk-based surveillance and prevention of the disease.
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3
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He D, Gu M, Wang X, Wang X, Li G, Yan Y, Gu J, Zhan T, Wu H, Hao X, Wang G, Hu J, Hu S, Liu X, Su S, Ding C, Liu X. Spatiotemporal Associations and Molecular Evolution of Highly Pathogenic Avian Influenza A H7N9 Virus in China from 2017 to 2021. Viruses 2021; 13:2524. [PMID: 34960793 PMCID: PMC8705967 DOI: 10.3390/v13122524] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 12/10/2021] [Accepted: 12/13/2021] [Indexed: 12/20/2022] Open
Abstract
Highly pathogenic (HP) H7N9 avian influenza virus (AIV) emerged in China in 2016. HP H7N9 AIV caused at least 33 human infections and has been circulating in poultry farms continuously since wave 5. The genetic divergence, geographic patterns, and hemagglutinin adaptive and parallel molecular evolution of HP H7N9 AIV in China since 2017 are still unclear. Here, 10 new strains of HP H7N9 AIVs from October 2019 to April 2021 were sequenced. We found that HP H7N9 was primarily circulating in Northern China, particularly in the provinces surrounding the Bohai Sea (Liaoning, Hebei, and Shandong) since wave 6. Of note, HP H7N9 AIV phylogenies exhibit a geographical structure compatible with high levels of local transmission after unidirectional rapid geographical expansion towards the north of China in 2017. In addition, we showed that two major subclades were continually expanding with the viral population size undergoing a sharp increase after 2018 with an obvious seasonal tendency. Notably, the hemagglutinin gene showed signs of parallel evolution and positive selection. Our research sheds light on the current epidemiology, evolution, and diversity of HP H7N9 AIV that can help prevent and control the spreading of HP H7N9 AIV.
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Affiliation(s)
- Dongchang He
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Min Gu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
| | - Xiyue Wang
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Xiaoquan Wang
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
| | - Gairu Li
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Yayao Yan
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Jinyuan Gu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Tiansong Zhan
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Huiguang Wu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Xiaoli Hao
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Guoqing Wang
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
| | - Jiao Hu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
| | - Shunlin Hu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
| | - Xiaowen Liu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
| | - Shuo Su
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China
| | - Chan Ding
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Department of Avian Diseases, Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai 200241, China
| | - Xiufan Liu
- Animal Infectious Disease Laboratory, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China
- Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonosis, Yangzhou University, Yangzhou 225009, China
- Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou 225009, China
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4
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Shan X, Wang Y, Song R, Wei W, Liao H, Huang H, Xu C, Chen L, Li S. Spatial and temporal clusters of avian influenza a (H7N9) virus in humans across five epidemics in mainland China: an epidemiological study of laboratory-confirmed cases. BMC Infect Dis 2020; 20:630. [PMID: 32842978 PMCID: PMC7449057 DOI: 10.1186/s12879-020-05345-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 08/13/2020] [Indexed: 12/31/2022] Open
Abstract
Background Avian influenza A (H7N9) virus was first reported in mainland China in 2013, and alarming in 2016–17 due to the surge across a wide geographic area. Our study aimed to identify and explore the spatial and temporal variation across five epidemics to reinforce the epidemic prevention and control. Methods We collected spatial and temporal information about all laboratory-confirmed human cases of A (H7N9) virus infection reported in mainland China covering 2013–17 from the open source. The autocorrelation analysis and intensity of cases were used to analyse the spatial cluster while circular distribution method was used to analyse the temporal cluster. Results Across the five epidemics, a total of 1553 laboratory-confirmed human cases with A (H7N9) virus were reported in mainland China. The global Moran’s I index values of five epidemic were 0.610, 0.132, 0.308, 0.306, 0.336 respectively, among which the differences were statistically significant. The highest intensity was present in the Yangtze River Delta region and the Pearl River Delta region, and the range enlarged from the east of China to inner provinces and even the west of China across the five epidemics. The temporal clusters of the five epidemics were statistically significant, and the peak period was from the end of January to April with the first and the fifth epidemic later than the mean peak period. Conclusions Spatial and temporal clusters of avian influenza A (H7N9) virus in humans are obvious, moreover the regions existing clusters may enlarge across the five epidemics. Yangtze River Delta region and the Pearl River Delta region have the spatial cluster and the peak period is from January to April. The government should facilitate the tangible improvement for the epidemic preparedness according to the characteristics of spatial and temporal clusters of patients with avian influenza A (H7N9) virus.
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Affiliation(s)
- Xuzheng Shan
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China.,Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yongqin Wang
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China
| | - Ruihong Song
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China
| | - Wen Wei
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Hongxiu Liao
- Transaction Management and Information Department, Panzhihua City Center for Disease Control and Prevention, Panzhihua, Sichuan, China
| | - Huang Huang
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China
| | - Chunqiong Xu
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China
| | - Lvlin Chen
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China
| | - Shiyun Li
- Prevention and Health Section, Affiliated Hospital, Chengdu University, Chengdu, Sichuan, China.
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5
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Martinez L, Cheng W, Wang X, Ling F, Mu L, Li C, Huo X, Ebell MH, Huang H, Zhu L, Li C, Chen E, Handel A, Shen Y. A Risk Classification Model to Predict Mortality Among Laboratory-Confirmed Avian Influenza A H7N9 Patients: A Population-Based Observational Cohort Study. J Infect Dis 2020; 220:1780-1789. [PMID: 31622983 DOI: 10.1093/infdis/jiz328] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 08/22/2019] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Avian influenza A H7N9 (A/H7N9) is characterized by rapid progressive pneumonia and respiratory failure. Mortality among laboratory-confirmed cases is above 30%; however, the clinical course of disease is variable and patients at high risk for death are not well characterized. METHODS We obtained demographic, clinical, and laboratory information on all A/H7N9 patients in Zhejiang province from China Centers for Disease Control and Prevention electronic databases. Risk factors for death were identified using logistic regression and a risk score was created using regression coefficients from multivariable models. We externally validated this score in an independent cohort from Jiangsu province. RESULTS Among 305 A/H7N9 patients, 115 (37.7%) died. Four independent predictors of death were identified: older age, diabetes, bilateral lung infection, and neutrophil percentage. We constructed a score with 0-13 points. Mortality rates in low- (0-3), medium- (4-6), and high-risk (7-13) groups were 4.6%, 32.1%, and 62.7% (Ptrend < .0001). In a validation cohort of 111 A/H7N9 patients, 61 (55%) died. Mortality rates in low-, medium-, and high-risk groups were 35.5%, 55.8, and 67.4% (Ptrend = .0063). CONCLUSIONS We developed and validated a simple-to-use, predictive risk score for clinical use, identifying patients at high mortality risk.
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Affiliation(s)
- Leonardo Martinez
- Department of Epidemiology and Biostatistics, College of Public Health, Athens.,Division of Infectious Diseases and Geographic Medicine, School of Medicine, Stanford University, California
| | - Wei Cheng
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xiaoxiao Wang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Feng Ling
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Lan Mu
- Department of Geography, University of Georgia, Athens
| | - Changwei Li
- Department of Epidemiology and Biostatistics, College of Public Health, Athens
| | - Xiang Huo
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Mark H Ebell
- Department of Epidemiology and Biostatistics, College of Public Health, Athens
| | - Haodi Huang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Limei Zhu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Chao Li
- Department of Epidemiology and Biostatistics, College of Public Health, Athens
| | - Enfu Chen
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, College of Public Health, Athens
| | - Ye Shen
- Department of Epidemiology and Biostatistics, College of Public Health, Athens
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6
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Li J, Chen C, Wei J, Huang H, Peng Y, Bi Y, Liu Y, Yang Y. Delayed peak of human infections and ongoing reassortment of H7N9 avian influenza virus in the newly affected western Chinese provinces during Wave Five. Int J Infect Dis 2019; 88:80-87. [PMID: 31499209 DOI: 10.1016/j.ijid.2019.09.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 08/29/2019] [Accepted: 09/02/2019] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES Eight additional provinces in western China reported human infections for the first time during the fifth wave of human H7N9 infections. The aim of this study was to analyze the epidemiological and virological characteristics of this outbreak. METHODS The epidemiological data of H7N9 cases from the newly affected western Chinese provinces were collected and analyzed. Full-length genome sequences of H7N9 virus were downloaded from the GenBank and GISAID databases, and phylogenetic, genotyping, and genetic analyses were conducted. RESULTS The peak of human infections in the newly affected western Chinese provinces was delayed by 4 months compared to the eastern Chinese provinces, and both low pathogenic (LP) and highly pathogenic (HP) H7N9-infected cases were found. The LP- and HP-H7N9 virus belonged to 10 different genotypes (including four new genotypes), of which G11 and G3 were the dominant genotypes, respectively. Almost all of these viruses originated from eastern and southern China and were most probably imported from neighboring provinces. Genetic characteristics of the circulating viruses were similar to those of the viruses from previously affected provinces during Wave Five. CONCLUSIONS A delayed peak of human infections was observed in the newly affected western Chinese provinces, and reassortment has been ongoing since the introduction of H7N9 viruses. This study highlights the importance of continued surveillance of the circulation and evolution of H7N9 virus in western China.
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Affiliation(s)
- Jin Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China; Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China
| | - Chuming Chen
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China
| | - Jinli Wei
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), Chinese Academy of Sciences, Beijing 100101, China
| | - Huaxin Huang
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China
| | - Yun Peng
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China
| | - Yuhai Bi
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), Chinese Academy of Sciences, Beijing 100101, China
| | - Yingxia Liu
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China; University of Chinese Academy of Sciences Medical School, Chinese Academy of Sciences, Beijing 101408, China.
| | - Yang Yang
- Shenzhen Key Laboratory of Pathogen and Immunity, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen 518112, China; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Institute of Microbiology, Center for Influenza Research and Early-warning (CASCIRE), Chinese Academy of Sciences, Beijing 100101, China.
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7
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Wang WH, Erazo EM, Ishcol MRC, Lin CY, Assavalapsakul W, Thitithanyanont A, Wang SF. Virus-induced pathogenesis, vaccine development, and diagnosis of novel H7N9 avian influenza A virus in humans: a systemic literature review. J Int Med Res 2019; 48:300060519845488. [PMID: 31068040 PMCID: PMC7140199 DOI: 10.1177/0300060519845488] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
H7N9 avian influenza virus (AIV) caused human infections in 2013 in China.
Phylogenetic analyses indicate that H7N9 AIV is a novel reassortant strain with
pandemic potential. We conducted a systemic review regarding virus-induced
pathogenesis, vaccine development, and diagnosis of H7N9 AIV infection in
humans. We followed PRISMA guidelines and searched PubMed, Web of Science, and
Google Scholar to identify relevant articles published between January 2013 and
December 2018. Pathogenesis data indicated that H7N9 AIV belongs to low
pathogenic avian influenza, which is mostly asymptomatic in avian species;
however, H7N9 induces high mortality in humans. Sporadic human infections have
recently been reported, caused by highly pathogenic avian influenza viruses
detected in poultry. H7N9 AIVs resistant to adamantine and oseltamivir cause
severe human infection by rapidly inducing progressive acute community-acquired
pneumonia, multiorgan dysfunction, and cytokine dysregulation; however,
mechanisms via which the virus induces severe syndromes remain unclear. An H7N9
AIV vaccine is lacking; designs under evaluation include synthesized peptide,
baculovirus-insect system, and virus-like particle vaccines. Molecular diagnosis
of H7N9 AIVs is suggested over conventional assays, for biosafety reasons.
Several advanced or modified diagnostic assays are under investigation and
development. We summarized virus-induced pathogenesis, vaccine development, and
current diagnostic assays in H7N9 AIVs.
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Affiliation(s)
- Wen-Hung Wang
- Division of Infectious Disease, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung.,Center for Infectious Disease and Cancer Research, Kaohsiung Medical University, Kaohsiung
| | - Esmeralda Merari Erazo
- Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung
| | - Max R Chang Ishcol
- Program in Tropical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung
| | - Chih-Yen Lin
- Center for Infectious Disease and Cancer Research, Kaohsiung Medical University, Kaohsiung.,Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung
| | - Wanchai Assavalapsakul
- Department of Microbiology, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
| | | | - Sheng-Fan Wang
- Center for Infectious Disease and Cancer Research, Kaohsiung Medical University, Kaohsiung.,Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung.,Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung
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8
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Lau SYF, Chen E, Wang M, Cheng W, Zee BCY, Han X, Yu Z, Sun R, Chong KC, Wang X. Association between meteorological factors, spatiotemporal effects, and prevalence of influenza A subtype H7 in environmental samples in Zhejiang province, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 663:793-803. [PMID: 30738260 DOI: 10.1016/j.scitotenv.2019.01.403] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 01/19/2019] [Accepted: 01/30/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND Human infection with the H7N9 virus has been reported recurrently since spring 2013. Given low pathogenicity of the virus in poultry, the outbreak cannot be noticed easily until a case of human infection is reported. Studies showed that the prevalence of influenza A subtype H7 in environmental samples is associated with the number of human H7N9 infection, with the latter associated with meteorological factors. Understanding the association between meteorological factors and the prevalence of H7 subtype in the environmental samples can shed light on how the virus propagates in the environment for disease control. METHOD Environmental samples and meteorological data (precipitation, temperature, relative humidity, sunshine duration, and wind speed) collected in Zhejiang province, China, during 2013-2017 were used. A Bayesian hierarchical binomial logistic spatiotemporal model which captures spatiotemporal effects was adopted to model the prevalence of H7 subtype with the meteorological factors. RESULTS The monthly overall prevalence of H7 subtype in the environmental samples was usually <30%. Compared with the odds at median, moderately low precipitation (49.19-115.60 mm), moderately long sunshine duration (4.22-9.25 h) and low temperature (<9.33 °C) were statistically significantly associated with a higher adjusted odds of detecting an H7-positive sample, whereas moderately high precipitation (119.51-146.85 mm), short and moderately short sunshine duration (<1.77 h; 4.00-4.17 h), and high temperature (>23.09 °C) were statistically significantly associated with a lower adjusted odds. The adjusted odds increased multiplicatively by 1.11 per 1% increase in relative humidity. CONCLUSION Since the prevalence of H7 subtype in environmental samples was associated with meteorological conditions and the number of human H7N9 infection, an environmental surveillance program which incorporates meteorological conditions in planning allows for early detection of the spread of the virus in the environment and better preparation for the outbreak in the human population.
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Affiliation(s)
- Steven Yuk-Fai Lau
- Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China.
| | - Enfu Chen
- Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China.
| | - Maggie Wang
- Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, No. 10, 2nd Yuexing Road, Nanshan District, Shenzhen, China.
| | - Wei Cheng
- Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China.
| | - Benny Chung-Ying Zee
- Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, No. 10, 2nd Yuexing Road, Nanshan District, Shenzhen, China.
| | - Xiaoran Han
- Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China
| | - Zhao Yu
- Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China.
| | - Riyang Sun
- Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China.
| | - Ka Chun Chong
- Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, No. 10, 2nd Yuexing Road, Nanshan District, Shenzhen, China.
| | - Xiaoxiao Wang
- Zhejiang Province Centre for Disease Control and Prevention, 3399 Binsheng Road, Binjiang District, Hangzhou, Zhejiang 310051, China.
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Rudraraju R, Subbarao K. Passive immunization with influenza haemagglutinin specific monoclonal antibodies. Hum Vaccin Immunother 2018; 14:2728-2736. [PMID: 29985756 DOI: 10.1080/21645515.2018.1489947] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The isolation of broadly neutralising antibodies against the influenza haemagglutinin has spurred investigation into their clinical potential, and has led to advances in influenza virus biology and universal influenza vaccine development. Studies in animal models have been invaluable for demonstrating the prophylactic and therapeutic efficacy of broadly neutralising antibodies, for comparisons with antiviral drugs used as the standard of care, and for defining their mechanism of action and potential role in providing protection from airborne infection.
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Affiliation(s)
- Rajeev Rudraraju
- a WHO Collaborating Centre for Reference and Research on Influenza and the Department of Microbiology and Immunology , The Peter Doherty Institute for Infection and Immunity , Melbourne , Australia
| | - Kanta Subbarao
- a WHO Collaborating Centre for Reference and Research on Influenza and the Department of Microbiology and Immunology , The Peter Doherty Institute for Infection and Immunity , Melbourne , Australia
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Adlhoch C, Brouwer A, Kuiken T, Mulatti P, Smietanka K, Staubach C, Muñoz Guajardo I, Verdonck F, Amato L, Baldinelli F. Avian influenza overview February - May 2018. EFSA J 2018; 16:e05358. [PMID: 32625951 PMCID: PMC7009712 DOI: 10.2903/j.efsa.2018.5358] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Between 16 February and 15 May 2018, three highly pathogenic avian influenza (HPAI) A(H5N6) and 11 HPAI A(H5N8) outbreaks in poultry holdings, one HPAI A(H5N6) and one HPAI A(H5N8) outbreak in captive birds, and 55 HPAI A(H5N6) wild bird events were reported in Europe. There is no evidence to date that HPAI A(H5N6) viruses circulating in Europe are associated with clades infecting humans. Fewer HPAI wild bird cases have been detected than during the same period of previous year. Most of mortality events among wild birds involved single birds and species listed in the revised list of target species for passive surveillance. Raptor species constitute 74% of the HPAI‐infected wild birds found dead. Those raptor species probably became infected by hunting or scavenging HPAI virus‐positive birds, and so raptor cases may predominate later in the course of an HPAI epidemic. Despite the important HPAI virus incursion via wild birds there have been few associated HPAI A(H5N6) outbreaks in poultry. Fifteen low pathogenic avian influenza (LPAI) outbreaks were reported in three Member States. The risk of zoonotic transmission to the general public in Europe is considered to be very low. The situation in Africa and the Middle East should be closely monitored with regards to HPAI A(H5N1) and A(H5N8). Uncontrolled spread of the virus and subsequent further genetic evolution in regions geographically connected to Europe may increase uncertainty and the risk for further dissemination of virus. Long‐distance migrating wild birds from southern Africa, e.g. the common tern (Sterna hirundo), may be included in targeted active surveillance schemes at a few priority locations in Europe in order to detect HPAI A(H5)‐infected migrating birds early. However, the risk of HPAI introduction from non‐EU countries via migratory wild birds to Europe is still considered to be much lower for wild birds crossing the southern borders than for those crossing the north‐eastern borders.
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