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Zhang L, Zhang Y, Duan W, Wu S, Sun Y, Ma C, Wang Q, Zhang D, Yang P. Using an influenza surveillance system to estimate the number of SARS-CoV-2 infections in Beijing, China, weeks 2 to 6 2023. Euro Surveill 2023; 28:2300128. [PMID: 36927716 PMCID: PMC10021470 DOI: 10.2807/1560-7917.es.2023.28.11.2300128] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
With COVID-19 public health control measures downgraded in China in January 2023, reported COVID-19 case numbers may underestimate the true numbers after the SARS-CoV-2 Omicron wave. Using a multiplier model based on our influenza surveillance system, we estimated that the overall incidence of SARS-CoV-2 infections was 392/100,000 population in Beijing during the 5 weeks following policy adjustment. No notable change occurred after the Spring Festival in early February. The multiplier model provides an opportunity for assessing the actual COVID-19 situation.
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Affiliation(s)
- Li Zhang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Yi Zhang
- General Administration of Customs (Beijing) International Travel Health Care Center, Dongcheng District, Beijing, China
| | - Wei Duan
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Shuangsheng Wu
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Ying Sun
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Chunna Ma
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Quanyi Wang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Daitao Zhang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
| | - Peng Yang
- Beijing Center for Disease Prevention and Control, Dongcheng District, Beijing, China
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Meng X, Zhao H, Ou R, Zeng Q, Lv H, Zhu H, Ye M. Epidemiological and Clinical Characteristics of Influenza Outbreaks Among Children in Chongqing, China. Front Public Health 2022; 10:760746. [PMID: 35493383 PMCID: PMC9051075 DOI: 10.3389/fpubh.2022.760746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 03/08/2022] [Indexed: 11/13/2022] Open
Abstract
Influenza is a global serious public health threat. Seasonal influenza among children in Chongqing has been a heavy health burden. To date, few studies have examined the spatial and temporal characteristics of influenza. This research sheds new light on correlating them with influenza outbreaks with data of over 5 years (2014–2018). All cluster outbreaks among preschool and school-age children reported in Chongqing were collected through the Public Health Emergency Management Information System. The demographical, epidemiological, and clinical data of the cases were analyzed. From 2014 to 2018, a total of 111 preschool- and school-based influenza-like illness outbreaks involving 3,549 cases were identified. Several clinical symptoms that were analyzed in this study showed significant contrast between influenza A and B. Spatial autocorrelation analysis over the 5-year data detected Xiushan district being the most likely cluster. The exploration of the spatial distribution and clinical characteristics of influenza cluster of children in Chongqing could help the effective implementation of health policies. Future studies should be conducted to monitor the outbreaks of influenza among children.
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Affiliation(s)
- Xuchen Meng
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
- Clinical College, Chongqing Medical University, Chongqing, China
| | - Han Zhao
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Rong Ou
- The Library, Chongqing Medical University, Chongqing, China
| | - Qing Zeng
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Huiqun Lv
- The Library, Chongqing Medical University, Chongqing, China
| | - Hua Zhu
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Mengliang Ye
- Department of Epidemiology and Health Statistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China
- *Correspondence: Mengliang Ye
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Li H, Chen Y, Machalaba CC, Tang H, Chmura AA, Fielder MD, Daszak P. Wild animal and zoonotic disease risk management and regulation in China: Examining gaps and One Health opportunities in scope, mandates, and monitoring systems. One Health 2021; 13:100301. [PMID: 34401458 PMCID: PMC8358700 DOI: 10.1016/j.onehlt.2021.100301] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/29/2021] [Accepted: 08/02/2021] [Indexed: 01/19/2023] Open
Abstract
Emerging diseases of zoonotic origin such as COVID-19 are a continuing public health threat in China that lead to a significant socioeconomic burden. This study reviewed the current laws and regulations, government reports and policy documents, and existing literature on zoonotic disease preparedness and prevention across the forestry, agriculture, and public health authorities in China, to articulate the current landscape of potential risks, existing mandates, and gaps. A total of 55 known zoonotic diseases (59 pathogens) are routinely monitored under a multi-sectoral system among humans and domestic and wild animals in China. These diseases have been detected in wild mammals, birds, reptiles, amphibians, and fish or other aquatic animals, the majority of which are transmitted between humans and animals via direct or indirect contact and vectors. However, this current monitoring system covers a limited scope of disease threats and animal host species, warranting expanded review for sources of disease and pathogen with zoonotic potential. In addition, the governance of wild animal protection and utilization and limited knowledge about wild animal trade value chains present challenges for zoonotic disease risk assessment and monitoring, and affect the completeness of mandates and enforcement. A coordinated and collaborative mechanism among different departments is required for the effective monitoring and management of disease emergence and transmission risks in the animal value chains. Moreover, pathogen surveillance among wild animal hosts and human populations outside of the routine monitoring system will fill the data gaps and improve our understanding of future emerging zoonotic threats to achieve disease prevention. The findings and recommendations will advance One Health collaboration across government and non-government stakeholders to optimize monitoring and surveillance, risk management, and emergency responses to known and novel zoonotic threats, and support COVID-19 recovery efforts.
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Affiliation(s)
- Hongying Li
- EcoHealth Alliance, New York, NY, United States of America
- School of Life Sciences, Faculty of Science, Engineering and Computing, Kingston University, London, United Kingdom
| | - Yufei Chen
- School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | | | - Hao Tang
- School of Veterinary Medicine, College of Science, Health, Engineering and Education, Murdoch University, Murdoch, WA, Australia
| | | | - Mark D. Fielder
- School of Life Sciences, Faculty of Science, Engineering and Computing, Kingston University, London, United Kingdom
| | - Peter Daszak
- EcoHealth Alliance, New York, NY, United States of America
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Wang W, Chen X, Wang Y, Lai S, Yang J, Cowling BJ, Horby PW, Uyeki TM, Yu H. Serological evidence of human infection with avian influenza A(H7N9) virus: a systematic review and meta-analysis. J Infect Dis 2020; 226:70-82. [PMID: 33119755 PMCID: PMC9373149 DOI: 10.1093/infdis/jiaa679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 10/23/2020] [Indexed: 11/18/2022] Open
Abstract
Background The extent of human infections with avian influenza A(H7N9) virus, including mild and asymptomatic infections, is uncertain. Methods We performed a systematic review and meta-analysis of serosurveys for avian influenza A(H7N9) virus infections in humans published during 2013–2020. Three seropositive definitions were assessed to estimate pooled seroprevalence, seroconversion rate, and seroincidence by types of exposures. We applied a scoring system to assess the quality of included studies. Results Of 31 included studies, pooled seroprevalence of A(H7N9) virus antibodies from all participants was 0.02%, with poultry workers, close contacts, and general populations having seroprevalence of 0.1%, 0.2%, and 0.02%, respectively, based on the World Health Organization (WHO)—recommended definition. Although most infections were asymptomatic, evidence of infection was highest in poultry workers (5% seroconversion, 19.1% seroincidence per 100 person-years). Use of different virus clades did not significantly affect seroprevalence estimates. Most serological studies were of low to moderate quality and did not follow standardized seroepidemiological protocols or WHO-recommended laboratory methods. Conclusions Human infections with avian influenza A(H7N9) virus have been uncommon, especially for general populations. Workers with occupational exposures to poultry and close contacts of A(H7N9) human cases had low risks of infection.
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Affiliation(s)
- Wei Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Xinhua Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yan Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Shengjie Lai
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Peter W Horby
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, UK
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, USA
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
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Mutations associated with egg adaptation of influenza A(H1N1)pdm09 virus in laboratory based surveillance in China, 2009–2016. BIOSAFETY AND HEALTH 2019. [DOI: 10.1016/j.bsheal.2019.02.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Shu Y, Song Y, Wang D, Greene CM, Moen A, Lee CK, Chen Y, Xu X, McFarland J, Xin L, Bresee J, Zhou S, Chen T, Zhang R, Cox N. A ten-year China-US laboratory collaboration: improving response to influenza threats in China and the world, 2004-2014. BMC Public Health 2019; 19:520. [PMID: 32326921 PMCID: PMC6696701 DOI: 10.1186/s12889-019-6776-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The emergence of severe acute respiratory syndrome (SARS) underscored the importance of influenza detection and response in China. From 2004, the Chinese National Influenza Center (CNIC) and the United States Centers for Disease Control and Prevention (USCDC) initiated Cooperative Agreements to build capacity in influenza surveillance in China.From 2004 to 2014, CNIC and USCDC collaborated on the following activities: 1) developing human technical expertise in virology and epidemiology in China; 2) developing a comprehensive influenza surveillance system by enhancing influenza-like illness (ILI) reporting and virological characterization; 3) strengthening analysis, utilization and dissemination of surveillance data; and 4) improving early response to influenza viruses with pandemic potential.Since 2004, CNIC expanded its national influenza surveillance and response system which, as of 2014, included 408 laboratories and 554 sentinel hospitals. With support from USCDC, more than 2500 public health staff from China received virology and epidemiology training, enabling > 98% network laboratories to establish virus isolation and/or nucleic acid detection techniques. CNIC established viral drug resistance surveillance and platforms for gene sequencing, reverse genetics, serologic detection, and vaccine strains development. CNIC also built a bioinformatics platform to strengthen data analysis and utilization, publishing weekly on-line influenza surveillance reports in English and Chinese. The surveillance system collects 200,000-400,000 specimens and tests more than 20,000 influenza viruses annually, which provides valuable information for World Health Organization (WHO) influenza vaccine strain recommendations. In 2010, CNIC became the sixth WHO Collaborating Centre for Influenza. CNIC has strengthened virus and data sharing, and has provided training and reagents for other countries to improve global capacity for influenza control and prevention.The collaboration's successes were built upon shared mission and values, emphasis on long-term capacity development and sustainability, and leadership commitment.
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Affiliation(s)
- Yuelong Shu
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, 102206 People’s Republic of China
| | - Ying Song
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Dayan Wang
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, 102206 People’s Republic of China
| | - Carolyn M. Greene
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Ann Moen
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - C. K. Lee
- On behalf of Emerging Disease Surveillance and Response (ESR), World Health Organization Western Pacific Region, Manila, Philippines
| | - Yongkun Chen
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, 102206 People’s Republic of China
| | - Xiyan Xu
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Jeffrey McFarland
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Li Xin
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, 102206 People’s Republic of China
| | - Joseph Bresee
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Suizan Zhou
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Tao Chen
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, 102206 People’s Republic of China
| | - Ran Zhang
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
| | - Nancy Cox
- Influenza Division, U.S. Centers for Disease Control and Prevention, WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Atlanta, GA 30333 USA
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Bai YL, Huang DS, Liu J, Li DQ, Guan P. Effect of meteorological factors on influenza-like illness from 2012 to 2015 in Huludao, a northeastern city in China. PeerJ 2019; 7:e6919. [PMID: 31110929 PMCID: PMC6501768 DOI: 10.7717/peerj.6919] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 04/06/2019] [Indexed: 01/04/2023] Open
Abstract
Background This study aims to describe the epidemiological patterns of influenza-like illness (ILI) in Huludao, China and seek scientific evidence on the link of ILI activity with weather factors. Methods Surveillance data of ILI cases between January 2012 and December 2015 was collected in Huludao Central Hospital, meteorological data was obtained from the China Meteorological Data Service Center. Generalized additive model (GAM) was used to seek the relationship between the number of ILI cases and the meteorological factors. Multiple Smoothing parameter estimation was made on the basis of Poisson distribution, where the number of weekly ILI cases was treated as response, and the smoothness of weather was treated as covariates. Lag time was determined by the smallest Akaike information criterion (AIC). Smoothing coefficients were estimated for the prediction of the number of ILI cases. Results A total of 29, 622 ILI cases were observed during the study period, with children ILI cases constituted 86.77%. The association between ILI activity and meteorological factors varied across different lag periods. The lag time for average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity were 2, 2, 1, 1 and 0 weeks, respectively. Average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity could explain 16.5%, 9.5%, 18.0%, 15.9% and 7.7% of the deviance, respectively. Among the temperature indexes, the minimum temperature played the most important role. The number of ILI cases peaked when minimum temperature was around -13 °C in winter and 18 °C in summer. The number of cases peaked when the relative humidity was equal to 43% and then began to decrease with the increase of relative humidity. When the humidity exceeded 76%, the number of ILI cases began to rise. Conclusions The present study first analyzed the relationship between meteorological factors and ILI cases with special consideration of the length of lag period in Huludao, China. Low air temperature and low relative humidity (cold and dry weather condition) played a considerable role in the epidemic pattern of ILI cases. The trend of ILI activity could be possibly predicted by the variation of meteorological factors.
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Affiliation(s)
- Ying-Long Bai
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.,Department of Child and Adolescent Health, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - De-Sheng Huang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.,Department of Mathematics, School of Fundamental Sciences, China Medical University, Shenyang, Liaoning, China
| | - Jing Liu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - De-Qiang Li
- Division of Infectious Disease Control, Huludao Municipal Center for Disease Control and Prevention, Huludao, Liaoning, China
| | - Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
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Ma MJ, Zhao T, Chen SH, Xia X, Yang XX, Wang GL, Fang LQ, Ma GY, Wu MN, Qian YH, Dean NE, Yang Y, Lu B, Cao WC. Avian Influenza A Virus Infection among Workers at Live Poultry Markets, China, 2013-2016. Emerg Infect Dis 2019; 24:1246-1256. [PMID: 29912708 PMCID: PMC6038753 DOI: 10.3201/eid2407.172059] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
We conducted a 3-year longitudinal serologic survey on an open cohort of poultry workers, swine workers, and general population controls to assess avian influenza A virus (AIV) seroprevalence and seroincidence and virologic diversity at live poultry markets (LPMs) in Wuxi City, Jiangsu Province, China. Of 964 poultry workers, 9 (0.93%) were seropositive for subtype H7N9 virus, 18 (1.87%) for H9N2, and 18 (1.87%) for H5N1. Of 468 poultry workers followed longitudinally, 2 (0.43%), 13 (2.78%), and 7 (1.5%) seroconverted, respectively; incidence was 1.27, 8.28, and 4.46/1,000 person-years for H7N9, H9N2, and H5N1 viruses, respectively. Longitudinal surveillance of AIVs at 9 LPMs revealed high co-circulation of H9, H7, and H5 subtypes. We detected AIVs in 726 (23.3%) of 3,121 samples and identified a high diversity (10 subtypes) of new genetic constellations and reassortant viruses. These data suggest that stronger surveillance for AIVs within LPMs and high-risk populations is imperative.
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Ma W, Huo X, Zhou M. The healthcare seeking rate of individuals with influenza like illness: a meta-analysis. Infect Dis (Lond) 2018; 50:728-735. [PMID: 30009680 DOI: 10.1080/23744235.2018.1472805] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
Abstract
BACKGROUND Not all individuals with Influenza like illness (ILI) seek healthcare. Knowing the proportion that do is important to evaluate the actual burden and fatality rate of ILI-relevant diseases, such as seasonal influenza and human infection with avian influenza. A number of studies have investigated the healthcare seeking rate, but the results varied from 0.16 to 0.85. We conducted this analysis for better understanding the healthcare seeking rate for ILI, and providing fundamental data for researchers in relevant fields. METHODS In this meta-analysis, a total of 799 articles, published as of 13 December 2016, were retrieved from Pubmed, Embase, Web of Science and Cochrane, and 11 of them were included after screening. The pooled estimates and factors which influence healthcare seeking rates were analysed. RESULTS The overall pooled healthcare seeking rate was 0.52 (95% CI: 0.46-0.59). The rate was significantly higher during the H1N1 pandemic in 2009 (0.61, 95% CI: 0.51-0.74), in children (0.56, 95% CI: 0.55-0.57) and in patients with documented fever (0.62, 95% CI: 0.53-0.72) than during non-pandemic periods (0.39, 95% CI: 0.33-0.45), in adults (0.45, 95% CI: 0.42-0.48) and in patients without documented fever (0.44, 95% CI: 0.38-0.50). Meta-regression indicated that these three factors could jointly explain 70.1% of the total heterogeneity among published studies. CONCLUSION The healthcare seeking rate of ILI patients is needed for estimation of the burden of ILI in the general population based on data from routine ILI sentinel surveillance systems.
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Affiliation(s)
- Wang Ma
- a School of Public Health , Nanjing Medical University , Nanjing , China
| | - Xiang Huo
- b Jiangsu Provincial Center for Disease Control and Prevention , Nanjing , China
| | - Minghao Zhou
- a School of Public Health , Nanjing Medical University , Nanjing , China.,b Jiangsu Provincial Center for Disease Control and Prevention , Nanjing , China
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11
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Jiang H, Wu P, Uyeki TM, He J, Deng Z, Xu W, Lv Q, Zhang J, Wu Y, Tsang TK, Kang M, Zheng J, Wang L, Yang B, Qin Y, Feng L, Fang VJ, Gao GF, Leung GM, Yu H, Cowling BJ. Preliminary Epidemiologic Assessment of Human Infections With Highly Pathogenic Avian Influenza A(H5N6) Virus, China. Clin Infect Dis 2018; 65:383-388. [PMID: 28407105 DOI: 10.1093/cid/cix334] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 04/10/2017] [Indexed: 01/21/2023] Open
Abstract
Background Since 2014, 17 human cases of infection with the newly emerged highly pathogenic avian influenza A(H5N6) virus have been identified in China to date. The epidemiologic characteristics of laboratory-confirmed A(H5N6) cases were compared to A(H5N1) and A(H7N9) cases in mainland China. Methods Data on laboratory-confirmed H5N6, H5N1, and H7N9 cases identified in mainland China were analyzed to compare epidemiologic characteristics and clinical severity. Severity of confirmed H5N6, H5N1 and H7N9 cases was estimated based on the risk of severe outcomes in hospitalized cases. Results H5N6 cases were older than H5N1 cases with a higher prevalence of underlying medical conditions but younger than H7N9 cases. Epidemiological time-to-event distributions were similar among cases infected with the 3 viruses. In comparison to a fatality risk of 70% (30/43) for hospitalized H5N1 cases and 41% (319/782) for hospitalized H7N9 cases, 12 (75%) out of the 16 hospitalized H5N6 cases were fatal, and 15 (94%) required mechanical ventilation. Conclusion Similar epidemiologic characteristics and high severity were observed in cases of H5N6 and H5N1 virus infection, whereas severity of H7N9 virus infections appeared lower. Continued surveillance of human infections with avian influenza A viruses remains an essential component of pandemic influenza preparedness.
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Affiliation(s)
- Hui Jiang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jianfeng He
- Guangdong Provincial Centre for Disease Control and Prevention, Guangzhou
| | - Zhihong Deng
- Hunan Provincial Centre for Disease Control and Prevention, Changsha
| | - Wen Xu
- Yunnan Provincial Centre for Disease Control and Prevention, Kunming
| | - Qiang Lv
- Sichuan Provincial Centre for Disease Control and Prevention, Chengdu
| | - Jin Zhang
- Anhui Provincial Centre for Disease Control and Prevention, Hefei
| | - Yang Wu
- Hubei Provincial Centre for Disease Control and Prevention, Wuhan
| | - Tim K Tsang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Min Kang
- Guangdong Provincial Centre for Disease Control and Prevention, Guangzhou
| | - Jiandong Zheng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing
| | - Lili Wang
- Institut Pasteur of Shanghai, Chinese Academy of Sciences
| | - Bingyi Yang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ying Qin
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing
| | - Luzhao Feng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing
| | - Vicky J Fang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - George F Gao
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences.,Chinese Center for Disease Control and Prevention, Beijing
| | - Gabriel M Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Xuhui District, Shanghai, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China
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12
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Yang X, Liu D, Wei K, Liu X, Meng L, Yu D, Li H, Li B, He J, Hu W. Comparing the similarity and difference of three influenza surveillance systems in China. Sci Rep 2018; 8:2840. [PMID: 29434230 PMCID: PMC5809380 DOI: 10.1038/s41598-018-21059-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 01/29/2018] [Indexed: 11/20/2022] Open
Abstract
Three main surveillance systems (laboratory-confirmed, influenza-like illness (ILI) and nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS)) have been used for influenza surveillance in China. However, it is unclear which surveillance system is more reliable in developing influenza early warning system based on surveillance data. This study aims to evaluate the similarity and difference of the three surveillance systems and provide practical knowledge for improving the effectiveness of influenza surveillance. Weekly influenza data for the three systems were obtained from March 2010 to February 2015. Spearman correlation and time series seasonal decomposition were used to assess the relationship between the three surveillance systems and to explore seasonal patterns and characteristics of influenza epidemics in Gansu, China. Our results showed influenza epidemics appeared a single-peak around January in all three surveillance systems. Time series seasonal decomposition analysis demonstrated a similar seasonal pattern in the three systems, while long-term trends were observed to be different. Our research suggested that a combination of the NIDRIS together with ILI and laboratory-confirmed surveillance is an informative, comprehensive way to monitor influenza transmission in Gansu, China. These results will provide a useful information for developing influenza early warning systems based on influenza surveillance data.
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Affiliation(s)
- Xiaoting Yang
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Dongpeng Liu
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Kongfu Wei
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Xinfeng Liu
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Lei Meng
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Deshan Yu
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Hongyu Li
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Baodi Li
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China
| | - Jian He
- Division of Infectious Disease, Gansu Provincial Centre for Disease Control and Prevention, Lanzhou, China.
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
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13
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ZHANG XINAN, ZOU LAN, CHEN JING, FANG YILE, HUANG JICAI, ZHANG JINHUI, LIU SANHONG, FENG GUANGTING, YANG CUIHONG, RUAN SHIGUI. AVIAN INFLUENZA A H7N9 VIRUS HAS BEEN ESTABLISHED IN CHINA. J BIOL SYST 2017. [DOI: 10.1142/s0218339017400095] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In March 2013, a novel avian-origin influenza A H7N9 virus was identified among human patients in China and a total of 124 human cases with 24 related deaths were confirmed by May 2013. From November 2013 to July 2017, H7N9 broke out four more times in China. A deterministic model is proposed to study the transmission dynamics of the avian influenza A H7N9 virus between wild and domestic birds and from birds to humans, and is applied to simulate the open data on numbers of the infected human cases and related deaths reported from March to May 2013 and from November 2013 to June 2014 by the Chinese Center for Disease Control and Prevention. The basic reproduction number [Formula: see text] is estimated and sensitivity analysis of [Formula: see text] in terms of model parameters is performed. Taking into account the fact that it broke out again from November 2014 to June 2015, from November 2015 to July 2016, and from October 2016 to July 2017, we believe that H7N9 virus has been well established in birds and will likely cause regular outbreaks in humans again in the future. Control measures for the future spread of H7N9 include (i) reducing the transmission opportunities between wild birds and domestic birds, (ii) closing or monitoring the retail live-poultry markets in the infected areas, and (iii) culling the infected domestic birds in the epidemic regions.
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Affiliation(s)
- XINAN ZHANG
- School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, P. R. China
| | - LAN ZOU
- Department of Mathematics, Sichuan University, Chengdu 610064, P. R. China
| | - JING CHEN
- Department of Mathematics, University of Miami, Coral Gables, FL 33146, USA
| | - YILE FANG
- Department of Electrical and Electronic Education, Huazhong University of Science and Technology, Wuchang Branch, Wuhan 430064, P. R. China
| | - JICAI HUANG
- School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, P. R. China
| | - JINHUI ZHANG
- Department of Applied Mathematics, Zhongyuan University of Technology, Zhengzhou 451191, P. R. China
| | - SANHONG LIU
- School of Mathematics and Statistics, Hubei University of Science and Technology, Xianning 437100, P. R. China
| | - GUANGTING FENG
- School of Mathematics and Quantitative Economics, Hubei University of Education, Wuhan 432025, P. R. China
| | - CUIHONG YANG
- School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, P. R. China
| | - SHIGUI RUAN
- School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, P. R. China
- Department of Mathematics, University of Miami, Coral Gables, FL 33146, USA
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14
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Zhou L, Tan Y, Kang M, Liu F, Ren R, Wang Y, Chen T, Yang Y, Li C, Wu J, Zhang H, Li D, Greene CM, Zhou S, Iuliano AD, Havers F, Ni D, Wang D, Feng Z, Uyeki TM, Li Q. Preliminary Epidemiology of Human Infections with Highly Pathogenic Avian Influenza A(H7N9) Virus, China, 2017. Emerg Infect Dis 2017; 23:1355-1359. [PMID: 28580900 PMCID: PMC5547798 DOI: 10.3201/eid2308.170640] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
We compared the characteristics of cases of highly pathogenic avian influenza (HPAI) and low pathogenic avian influenza (LPAI) A(H7N9) virus infections in China. HPAI A(H7N9) case-patients were more likely to have had exposure to sick and dead poultry in rural areas and were hospitalized earlier than were LPAI A(H7N9) case-patients.
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15
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Rafeek RAM, Divarathna MVM, Noordeen F. History and current trends in influenza virus infections with special reference to Sri Lanka. Virusdisease 2017; 28:225-232. [PMID: 29291207 DOI: 10.1007/s13337-017-0390-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 06/20/2017] [Indexed: 01/01/2023] Open
Abstract
The World Health Organization (WHO) estimates that approximately one billion people are infected and up to 500,000 people die from influenza each year in the world. Influenza is considered to be the greatest killer of the human populations, due to the 1918 Spanish flu, which killed millions around the world. Despite the effective treatment available against influenza, it still contributes to significant morbidity and mortality. Currently circulating influenza strains in humans include influenza A (H1N1)pdm09, influenza A (H3N2) and influenza B viruses, (B/Victoria and B/Yamagata). Influenza has been prevalent in Sri Lanka from 1969, since then it continued to cause morbidity and mortality in children and adults. The current global influenza surveillance network monitors the global influenza activity through WHO collaborating centres. The Medical Research Institute monitors and diagnoses influenza cases in the country as part of the WHO network laboratories. Vaccinations to high risk groups and antiviral therapy for the successful prevention of influenza have been practiced in Sri Lanka. This review highlights the impact of influenza on public health in Sri Lanka including the historical aspects, current diagnostic practices and prevention approaches in high risk individuals in the country.
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Affiliation(s)
- R A M Rafeek
- Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka
| | - M V M Divarathna
- Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka
| | - F Noordeen
- Department of Microbiology, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka
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16
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Wang X, Jiang H, Wu P, Uyeki TM, Feng L, Lai S, Wang L, Huo X, Xu K, Chen E, Wang X, He J, Kang M, Zhang R, Zhang J, Wu J, Hu S, Zhang H, Liu X, Fu W, Ou J, Wu S, Qin Y, Zhang Z, Shi Y, Zhang J, Artois J, Fang VJ, Zhu H, Guan Y, Gilbert M, Horby PW, Leung GM, Gao GF, Cowling BJ, Yu H. Epidemiology of avian influenza A H7N9 virus in human beings across five epidemics in mainland China, 2013-17: an epidemiological study of laboratory-confirmed case series. THE LANCET. INFECTIOUS DISEASES 2017; 17:822-832. [PMID: 28583578 DOI: 10.1016/s1473-3099(17)30323-7] [Citation(s) in RCA: 215] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 04/25/2017] [Accepted: 05/03/2017] [Indexed: 12/31/2022]
Abstract
BACKGROUND The avian influenza A H7N9 virus has caused infections in human beings in China since 2013. A large epidemic in 2016-17 prompted concerns that the epidemiology of the virus might have changed, increasing the threat of a pandemic. We aimed to describe the epidemiological characteristics, clinical severity, and time-to-event distributions of patients infected with A H7N9 in the 2016-17 epidemic compared with previous epidemics. METHODS In this epidemiological study, we obtained information about all laboratory-confirmed human cases of A H7N9 virus infection reported in mainland China as of Feb 23, 2017, from an integrated electronic database managed by the China Center for Disease Control and Prevention (CDC) and provincial CDCs. Every identified human case of A H7N9 virus infection was required to be reported to China CDC within 24 h via a national surveillance system for notifiable infectious diseases. We described the epidemiological characteristics across epidemics, and estimated the risk of death, mechanical ventilation, and admission to the intensive care unit for patients admitted to hospital for routine clinical practice rather than for isolation purpose. We estimated the incubation periods, and time delays from illness onset to hospital admission, illness onset to initiation of antiviral treatment, and hospital admission to death or discharge using survival analysis techniques. FINDINGS Between Feb 19, 2013, and Feb 23, 2017, 1220 laboratory-confirmed human infections with A H7N9 virus were reported in mainland China, with 134 cases reported in the spring of 2013, 306 in 2013-14, 219 in 2014-15, 114 in 2015-16, and 447 in 2016-17. The 2016-17 A H7N9 epidemic began earlier, spread to more districts and counties in affected provinces, and had more confirmed cases than previous epidemics. The proportion of cases in middle-aged adults increased steadily from 41% (55 of 134) to 57% (254 of 447) from the first epidemic to the 2016-17 epidemic. Proportions of cases in semi-urban and rural residents in the 2015-16 and 2016-17 epidemics (63% [72 of 114] and 61% [274 of 447], respectively) were higher than those in the first three epidemics (39% [52 of 134], 55% [169 of 306], and 56% [122 of 219], respectively). The clinical severity of individuals admitted to hospital in the 2016-17 epidemic was similar to that in the previous epidemics. INTERPRETATION Age distribution and case sources have changed gradually across epidemics since 2013, while clinical severity has not changed substantially. Continued vigilance and sustained intensive control efforts are needed to minimise the risk of human infection with A H7N9 virus. FUNDING The National Science Fund for Distinguished Young Scholars.
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Affiliation(s)
- Xiling Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Hui Jiang
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Luzhao Feng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shengjie Lai
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lili Wang
- Institute Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai, China
| | - Xiang Huo
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Ke Xu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Enfu Chen
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xiaoxiao Wang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Jianfeng He
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Renli Zhang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jin Zhang
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China
| | - Jiabing Wu
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China
| | - Shixiong Hu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Hengjiao Zhang
- Hunan Provincial Center for Disease Control and Prevention, Changsha, China
| | - Xiaoqing Liu
- Jiangxi Provincial Center for Disease Control and Prevention, Nanchang, China
| | - Weijie Fu
- Jiangxi Provincial Center for Disease Control and Prevention, Nanchang, China
| | - Jianming Ou
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Shenggen Wu
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Ying Qin
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhijie Zhang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yujing Shi
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Juanjuan Zhang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jean Artois
- Spatial Epidemiology Lab. (SpELL), 'Université Libre de Bruxelles', Brussels, Belgium
| | - Vicky J Fang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Huachen Zhu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; Centre of Influenza Research and State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Emerging Infectious Diseases (The University of Hong Kong-Shenzhen Branch), Shenzhen Third People's Hospital, Shenzhen, China; Shantou University-The University of Hong Kong Joint Institute of Virology, Shantou University, Shantou, China
| | - Yi Guan
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China; Centre of Influenza Research and State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China; State Key Laboratory of Emerging Infectious Diseases (The University of Hong Kong-Shenzhen Branch), Shenzhen Third People's Hospital, Shenzhen, China; Shantou University-The University of Hong Kong Joint Institute of Virology, Shantou University, Shantou, China
| | - Marius Gilbert
- Spatial Epidemiology Lab. (SpELL), 'Université Libre de Bruxelles', Brussels, Belgium; Fonds National de la Recherche Scientifique, Brussels, Belgium
| | - Peter W Horby
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Gabriel M Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - George F Gao
- Chinese Center for Disease Control and Prevention, Beijing, China; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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17
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Xiang N, Iuliano AD, Zhang Y, Ren R, Geng X, Ye B, Tu W, Li CA, Lv Y, Yang M, Zhao J, Wang Y, Yang F, Zhou L, Liu B, Shu Y, Ni D, Feng Z, Li Q. Comparison of the first three waves of avian influenza A(H7N9) virus circulation in the mainland of the People's Republic of China. BMC Infect Dis 2016; 16:734. [PMID: 27919225 PMCID: PMC5139097 DOI: 10.1186/s12879-016-2049-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 11/21/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND H7N9 human cases were first detected in mainland China in March 2013. Circulation of this virus has continued each year shifting to typical winter months. We compared the clinical and epidemiologic characteristics for the first three waves of virus circulation. METHODS The first wave was defined as reported cases with onset dates between March 31-September 30, 2013, the second wave was defined as October 1, 2013-September 30, 2014 and the third wave was defined as October 1, 2014-September 30, 2015. We used simple descriptive statistics to compare characteristics of the three distinct waves of virus circulation. RESULTS In mainland China, 134 cases, 306 cases and 219 cases were detected and reported in first three waves, respectively. The median age of cases was statistically significantly older in the first wave (61 years vs. 56 years, 56 years, p < 0.001) compared to the following two waves. Most reported cases were among men in all three waves. There was no statistically significant difference between case fatality proportions (33, 42 and 45%, respectively, p = 0.08). There were no significant statistical differences for time from illness onset to first seeking healthcare, hospitalization, lab confirmation, initiation antiviral treatment and death between the three waves. A similar percentage of cases in all waves reported exposure to poultry or live poultry markets (87%, 88%, 90%, respectively). There was no statistically significant difference in the occurrence of severe disease between the each of the first three waves of virus circulation. Twenty-one clusters were reported during these three waves (4, 11 and 6 clusters, respectively), of which, 14 were considered to be possible human-to-human transmission. CONCLUSION Though our case investigation for the first three waves found few differences between the epidemiologic and clinical characteristics, there is continued international concern about the pandemic potential of this virus. Since the virus continues to circulate, causes more severe disease, has the ability to mutate and become transmissible from human-to-human, and there is limited natural protection from infection in communities, it is critical that surveillance systems in China and elsewhere are alert to the influenza H7N9 virus.
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Affiliation(s)
- Nijuan Xiang
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | | | - Yanping Zhang
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Ruiqi Ren
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Xingyi Geng
- Jinan Prefecture Center for Disease Control and Prevention, Shandong, China
| | - Bili Ye
- Shenzhen Prefecture Center for Disease Control and Prevention, Guangdong, China
| | - Wenxiao Tu
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Ch Ao Li
- Tianjin Municipal Center for Disease Control and Prevention, Tianjin, China
| | - Yong Lv
- Luan Prefecture Center for Disease Control and Prevention, Anhui, China
| | - Ming Yang
- Xuancheng Prefecture Center for Disease Control and Prevention, Anhui, China
| | - Jian Zhao
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Yali Wang
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Fuqiang Yang
- Jiangxi Provincial Center for Disease Control and Prevention, Jiangxi, China
| | - Lei Zhou
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Bo Liu
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Yuelong Shu
- Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Daxin Ni
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Zijian Feng
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China
| | - Qun Li
- Chinese Center for Disease Control and Prevention, No. 155 Changbai Road, Changping District, Beijing, China.
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18
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Lin YP, Yang ZF, Liang Y, Li ZT, Bond HS, Chua H, Luo YS, Chen Y, Chen TT, Guan WD, Lai JCC, Siu YL, Pan SH, Peiris JSM, Cowling BJ, Mok CKP. Population seroprevalence of antibody to influenza A(H7N9) virus, Guangzhou, China. BMC Infect Dis 2016; 16:632. [PMID: 27814756 PMCID: PMC5097368 DOI: 10.1186/s12879-016-1983-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2016] [Accepted: 10/27/2016] [Indexed: 12/02/2022] Open
Abstract
Background Since the identification in early 2013 of severe disease caused by influenza A(H7N9) virus infection, there have been few attempts to characterize the full severity profile of human infections. Our objective was to estimate the number and severity of H7N9 infections in Guangzhou, using a serological study. Methods We collected residual sera from patients of all ages admitted to a hospital in the city of Guangzhou in southern China in 2013 and 2014. We screened the sera using a haemagglutination inhibition assay against a pseudovirus containing the H7 and N9 of A/Anhui/1/2013(H7N9), and samples with a screening titer ≥10 were further tested by standard hemagglutination-inhibition and virus neutralization assays for influenza A(H7N9). We used a statistical model to interpret the information on antibody titers in the residual sera, assuming that the residual sera provided a representative picture of A(H7N9) infections in the general population, accounting for potential cross-reactions. Results We collected a total of 5360 residual sera from December 2013 to April 2014 and from October 2014 to December 2014, and found two specimens that tested positive for H7N9 antibody at haemagglutination inhibition titer ≥40 and a neutralization titer ≥40. Based on this, we estimated that 64,000 (95 % credibility interval: 7300, 190,000) human infections with influenza A(H7N9) virus occurred in Guangzhou in early 2014, with an infection-fatality risk of 3.6 deaths (95 % credibility interval: 0.47, 15) per 10,000 infections. Conclusions Our study suggested that the number of influenza A(H7N9) virus infections in Guangzhou substantially exceeded the number of laboratory-confirmed cases there, albeit with considerable imprecision. Our study was limited by the small number of positive specimens identified, and larger serologic studies would be valuable. Our analytic framework would be useful if larger serologic studies are done. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1983-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yong Ping Lin
- Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangdong, China.,Research Centre of Translational Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Zi Feng Yang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Ying Liang
- Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Zheng Tu Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Helen S Bond
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Huiying Chua
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ya Sha Luo
- Department of Laboratory Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong, China
| | - Yuan Chen
- Department of Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Ting Ting Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Wen Da Guan
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - Jimmy Chun Cheong Lai
- Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yu Lam Siu
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Si Hua Pan
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangdong, China
| | - J S Malik Peiris
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.,HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.,Centre of Influenza Research, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China. .,School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Pokfulam, Hong Kong, China.
| | - Chris Ka Pun Mok
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China. .,Centre of Influenza Research, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
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19
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Abstract
In response to the severe acute respiratory syndrome (SARS) pandemic of 2003 and the influenza pandemic of 2009, many countries instituted border measures as a means of stopping or slowing the spread of disease. The measures, usually consisting of a combination of border entry/exit screening, quarantine, isolation, and communications, were resource intensive, and modeling and observational studies indicate that border screening is not effective at detecting infectious persons. Moreover, border screening has high opportunity costs, financially and in terms of the use of scarce public health staff resources during a time of high need. We discuss the border-screening experiences with SARS and influenza and propose an approach to decision-making for future pandemics. We conclude that outbreak-associated communications for travelers at border entry points, together with effective communication with clinicians and more effective disease control measures in the community, may be a more effective approach to the international control of communicable diseases.
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20
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Abstract
In March 2013 the first cases of human avian influenza A(H7N9) were reported to the World Health Organization. Since that time, over 650 cases have been reported. Infections are associated with considerable morbidity and mortality, particularly within certain demographic groups. This rapid increase in cases over a brief time period is alarming and has raised concerns about the pandemic potential of the H7N9 virus. Three major factors influence the pandemic potential of an influenza virus: (1) its ability to cause human disease, (2) the immunity of the population to the virus, and (3) the transmission potential of the virus. This paper reviews what is currently known about each of these factors with respect to avian influenza A(H7N9). Currently, sustained human-to-human transmission of H7N9 has not been reported; however, population immunity to the virus is considered very low, and the virus has significant ability to cause human disease. Several statistical and geographical modelling studies have estimated and predicted the spread of the H7N9 virus in humans and avian species, and some have identified potential risk factors associated with disease transmission. Additionally, assessment tools have been developed to evaluate the pandemic potential of H7N9 and other influenza viruses. These tools could also hypothetically be used to monitor changes in the pandemic potential of a particular virus over time.
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Daidoji T, Watanabe Y, Ibrahim MS, Yasugi M, Maruyama H, Masuda T, Arai F, Ohba T, Honda A, Ikuta K, Nakaya T. Avian Influenza Virus Infection of Immortalized Human Respiratory Epithelial Cells Depends upon a Delicate Balance between Hemagglutinin Acid Stability and Endosomal pH. J Biol Chem 2015; 290:10627-42. [PMID: 25673693 DOI: 10.1074/jbc.m114.611327] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Indexed: 12/13/2022] Open
Abstract
The highly pathogenic avian influenza (AI) virus, H5N1, is a serious threat to public health worldwide. Both the currently circulating H5N1 and previously circulating AI viruses recognize avian-type receptors; however, only the H5N1 is highly infectious and virulent in humans. The mechanism(s) underlying this difference in infectivity remains unclear. The aim of this study was to clarify the mechanisms responsible for the difference in infectivity between the current and previously circulating strains. Primary human small airway epithelial cells (SAECs) were transformed with the SV40 large T-antigen to establish a series of clones (SAEC-Ts). These clones were then used to test the infectivity of AI strains. Human SAEC-Ts could be broadly categorized into two different types based on their susceptibility (high or low) to the viruses. SAEC-T clones were poorly susceptible to previously circulating AI but were completely susceptible to the currently circulating H5N1. The hemagglutinin (HA) of the current H5N1 virus showed greater membrane fusion activity at higher pH levels than that of previous AI viruses, resulting in broader cell tropism. Moreover, the endosomal pH was lower in high susceptibility SAEC-T clones than that in low susceptibility SAEC-T clones. Taken together, the results of this study suggest that the infectivity of AI viruses, including H5N1, depends upon a delicate balance between the acid sensitivity of the viral HA and the pH within the endosomes of the target cell. Thus, one of the mechanisms underlying H5N1 pathogenesis in humans relies on its ability to fuse efficiently with the endosomes in human airway epithelial cells.
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Affiliation(s)
- Tomo Daidoji
- From the Department of Infectious Diseases, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan
| | - Yohei Watanabe
- the Department of Virology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan
| | - Madiha S Ibrahim
- the Department of Virology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan, the Department of Microbiology, Faculty of Veterinary Medicine, Damanhour University, Damanhour 22111, Egypt
| | - Mayo Yasugi
- the Department of Virology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan, the Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Izumisano, Osaka, 598-8531, Japan
| | - Hisataka Maruyama
- the Department of Micro-Nano Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan, and
| | - Taisuke Masuda
- the Department of Micro-Nano Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan, and
| | - Fumihito Arai
- the Department of Micro-Nano Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan, and
| | - Tomoyuki Ohba
- the Department of Frontier Bioscience, Hosei University, Koganei, Tokyo 184-8584, Japan
| | - Ayae Honda
- the Department of Frontier Bioscience, Hosei University, Koganei, Tokyo 184-8584, Japan
| | - Kazuyoshi Ikuta
- the Department of Virology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan
| | - Takaaki Nakaya
- From the Department of Infectious Diseases, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto 602-8566, Japan,
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22
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Zhang Y, Shen Z, Ma C, Jiang C, Feng C, Shankar N, Yang P, Sun W, Wang Q. Cluster of human infections with avian influenza A (H7N9) cases: a temporal and spatial analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2015; 12:816-28. [PMID: 25599373 PMCID: PMC4306894 DOI: 10.3390/ijerph120100816] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 01/07/2015] [Indexed: 12/03/2022]
Abstract
Objectives: This study aims to describe the spatial and temporal characteristics of human infections with H7N9 virus in China using data from February 2013 to March 2014 from the websites of every province’s Population and Family Planning Commission. Methods: A human infection with H7N9 virus dataset was summarized by county to analyze its spatial clustering, and by date of illness onset to analyze its space-time clustering using the ESRI® Geographic Information System (GIS) software ArcMap™ 10.1 and SatScan. Results: Based on active surveillance data, the distribution map of H7N9 cases shows that compared to the rest of China, the areas from near the Yangtze River delta (YRD) to farther south around the Pearl River delta (PRD) had the highest densities of H7N9 cases. The case data shows a strong space-time clustering in the areas on and near the YRD from 26 March to 18 April 2013 and a weak space-time clustering only in the areas on and near the PRD between 3 and 4 February 2014. However, for the rest of the study period, H7N9 cases were spatial-temporally randomly distributed. Conclusions: Our results suggested that the spatial-temporal clustering of H7N9 in China between 2013 and 2014 is fundamentally different.
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Affiliation(s)
- Yi Zhang
- Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
| | - Zhixiong Shen
- Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA 70118, USA.
| | - Chunna Ma
- Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
| | - Chengsheng Jiang
- Maryland Institute for Applied Environmental Health, School of Public Health in University of Maryland, College Park, MD 20742, USA.
| | - Cindy Feng
- School of Public Health & The Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada.
| | - Nivedita Shankar
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
| | - Peng Yang
- Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
| | - Wenjie Sun
- School of Food Science, Guangdong Pharmaceutical University, Zhongshan 528458, China.
| | - Quanyi Wang
- Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
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Viral lung infections: epidemiology, virology, clinical features, and management of avian influenza A(H7N9). Curr Opin Pulm Med 2015; 20:225-32. [PMID: 24637225 DOI: 10.1097/mcp.0000000000000047] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
PURPOSE OF REVIEW The avian influenza A(H7N9) virus has jumped species barrier and caused severe human infections. Here, we present the virological features relevant to clinical practice, and summarize the epidemiology, clinical findings, diagnosis, treatment, and preventive strategies of A(H7N9) infection. RECENT FINDINGS As of 18 February 2014, A(H7N9) virus has caused 354 infections in mainland China, Taiwan, and Hong Kong with a case-fatality rate of 32%. Elderly men were most affected. Most patients acquired the infection from direct contact with poultry or from a contaminated environment, although person-to-person transmission has likely occurred. A(H7N9) infection has usually presented with severe pneumonia, often complicated by acute respiratory distress syndrome and multiorgan failure. Mild infections have been reported in children and young adults. Nasopharyngeal aspirate and sputum samples should be collected for diagnosis, preferably using reverse transcriptase-PCR. Early treatment with neuraminidase inhibitors improved survival, but the efficacy of antivirals was hampered by resistant mutants. The closure of live poultry markets in affected areas has significantly contributed to the decline in the incidence of human cases. SUMMARY The emergence of A(H7N9) virus represents a significant health threat. High vigilance is necessary so that appropriate treatment can be instituted for the patient and preventive measures can be implemented.
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Feng L, Wu JT, Liu X, Yang P, Tsang TK, Jiang H, Wu P, Yang J, Fang VJ, Qin Y, Lau EH, Li M, Zheng J, Peng Z, Xie Y, Wang Q, Li Z, Leung GM, Gao GF, Yu H, Cowling BJ. Clinical severity of human infections with avian influenza A(H7N9) virus, China, 2013/14. ACTA ACUST UNITED AC 2014; 19. [PMID: 25523971 DOI: 10.2807/1560-7917.es2014.19.49.20984] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Assessing the severity of emerging infections is challenging because of potential biases in case ascertainment. The first human case of infection with influenza A(H7N9) virus was identified in China in March 2013; since then, the virus has caused two epidemic waves in the country. There were 134 laboratory-confirmed cases detected in the first epidemic wave from January to September 2013. In the second epidemic wave of human infections with avian influenza A(H7N9) virus in China from October 2013 to October 2014, we estimated that the risk of death among hospitalised cases of infection with influenza A(H7N9) virus was 48% (95% credibility interval: 42-54%), slightly higher than the corresponding risk in the first wave. Age-specific risks of death among hospitalised cases were also significantly higher in the second wave. Using data on symptomatic cases identified through national sentinel influenza-like illness surveillance, we estimated that the risk of death among symptomatic cases of infection with influenza A(H7N9) virus was 0.10% (95% credibility interval: 0.029-3.6%), which was similar to previous estimates for the first epidemic wave of human infections with influenza A(H7N9) virus in 2013. An increase in the risk of death among hospitalised cases in the second wave could be real because of changes in the virus, because of seasonal changes in host susceptibility to severe infection, or because of variation in treatment practices between hospitals, while the increase could be artefactual because of changes in ascertainment of cases in different areas at different times.
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Affiliation(s)
- L Feng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
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25
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Abstract
In the years prior to 2013, avian influenza A H7 viruses were a cause of significant poultry mortality; however, human illness was generally mild. In March 2013, a novel influenza A(H7N9) virus emerged in China as an unexpected cause of severe human illness with 36% mortality. Chinese and other public health officials responded quickly, characterizing the virus and identifying more than 400 cases through use of new technologies and surveillance tools made possible by past preparedness and response efforts. Genetic sequencing, glycan-array receptor-binding assays, and ferret studies reveal the H7N9 virus to have increased binding to mammalian respiratory cells and to have mutations associated with higher virus replication rates and illness severity. New risk-assessment tools indicate H7N9 has the potential for further mammalian adaptation with possible human-to-human transmission. Vigilant virologic and epidemiologic surveillance is needed to monitor H7N9 and detect other unexpected novel influenza viruses that may emerge.
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Affiliation(s)
- Daniel B Jernigan
- Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, Georgia 30329; ,
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26
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Xiang N, Havers F, Chen T, Song Y, Tu W, Li L, Cao Y, Liu B, Zhou L, Meng L, Hong Z, Wang R, Niu Y, Yao J, Liao K, Jin L, Zhang Y, Li Q, Widdowson MA, Feng Z. Use of national pneumonia surveillance to describe influenza A(H7N9) virus epidemiology, China, 2004-2013. Emerg Infect Dis 2014; 19:1784-90. [PMID: 24206646 PMCID: PMC3837642 DOI: 10.3201/eid1911.130865] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
In mainland China, most avian influenza A(H7N9) cases in the spring of 2013 were reported through the pneumonia of unknown etiology (PUE) surveillance system. To understand the role of possible underreporting and surveillance bias in assessing the epidemiology of subtype H7N9 cases and the effect of live-poultry market closures, we examined all PUE cases reported from 2004 through May 3, 2013. Historically, the PUE system was underused, reporting was inconsistent, and PUE reporting was biased toward A(H7N9)-affected provinces, with sparse data from unaffected provinces; however, we found no evidence that the older ages of persons with A(H7N9) resulted from surveillance bias. The absolute number and the proportion of PUE cases confirmed to be A(H7N9) declined after live-poultry market closures (p<0.001), indicating that market closures might have positively affected outbreak control. In China, PUE surveillance needs to be improved.
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27
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Thomas RE. Is influenza-like illness a useful concept and an appropriate test of influenza vaccine effectiveness? Vaccine 2014; 32:2143-9. [PMID: 24582634 PMCID: PMC7127078 DOI: 10.1016/j.vaccine.2014.02.059] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2013] [Revised: 02/07/2014] [Accepted: 02/12/2014] [Indexed: 11/23/2022]
Abstract
PURPOSE To assess the utility of "influenza-like illness" (ILI) and whether it appropriately tests influenza vaccine effectiveness. PRINCIPAL RESULTS The WHO and CDC definitions of "influenza-like illness" are similar. However many studies use other definitions, some not specifying a temperature and requiring specific respiratory and/or systemic symptoms, making many samples non-comparable. Most ILI studies find less than 25% of cases are RT-PCR-positive, those which test for other viruses and bacteria usually find multiple other pathogens, and most identify no pathogen in about 50% of cases. ILI symptom and symptom combinations do not have high sensitivity or specificity in identifying PCR-positive influenza cases. Rapid influenza diagnostic tests are increasingly used to screen ILI cases and they have low sensitivity and high specificity when compared to RT-PCR in identifying influenza. MAIN CONCLUSIONS The working diagnosis of ILI presumes influenza may be involved until proven otherwise. Health care workers would benefit by renaming the WHO and CDC ILI symptoms and signs as "acute respiratory illness" and also using the WHO acute severe respiratory illness definition if the illness is severe and meets this criterion. This renaming would shift attention to identify the viral and bacterial pathogens in cases and epidemics, identify new pathogens, implement vaccination plans appropriate to the identified pathogens, and estimate workload during the viral season. Randomised controlled trials testing the effectiveness of influenza vaccine require all participants to be assessed by a gold standard (RT-PCR). ILI has no role in measuring influenza vaccine effectiveness. ILI is well established in the literature and in the operational definition of many surveillance databases and its imprecise definition may be inhibiting progress in research and treatment. The current ILI definition could with benefit be renamed "acute respiratory illness," with additional definitions for "severe acute respiratory illness" (SARI) with RT-PCR testing for pathogens to facilitate prevention and treatment.
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Affiliation(s)
- Roger E Thomas
- Department of Family Medicine, Faculty of Medicine, University of Calgary, G012, Health Sciences Centre, 3330 Hospital Drive NW, Calgary, Alberta, Canada T2N 4N1.
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28
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Fuller T, Havers F, Xu C, Fang LQ, Cao WC, Shu Y, Widdowson MA, Smith TB. Identifying areas with a high risk of human infection with the avian influenza A (H7N9) virus in East Asia. J Infect 2014; 69:174-81. [PMID: 24642206 DOI: 10.1016/j.jinf.2014.03.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Revised: 03/04/2014] [Accepted: 03/07/2014] [Indexed: 10/25/2022]
Abstract
OBJECTIVES The rapid emergence, spread, and disease severity of avian influenza A (H7N9) in China has prompted concerns about a possible pandemic and regional spread in the coming months. The objective of this study was to predict the risk of future human infections with H7N9 in China and neighboring countries by assessing the association between H7N9 cases at sentinel hospitals and putative agricultural, climatic, and demographic risk factors. METHODS This cross-sectional study used the locations of H7N9 cases and negative cases from China's influenza-like illness surveillance network. After identifying H7N9 risk factors with logistic regression, we used Geographic Information Systems (GIS) to construct predictive maps of H7N9 risk across Asia. RESULTS Live bird market density was associated with human H7N9 infections reported in China from March-May 2013. Based on these cases, our model accurately predicted the virus' spread into Guangxi autonomous region in February 2014. Outside China, we find there is a high risk that the virus will spread to northern Vietnam, due to the import of poultry from China. CONCLUSIONS Our risk map can focus efforts to improve surveillance in poultry and humans, which may facilitate early identification and treatment of human cases.
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Affiliation(s)
- Trevon Fuller
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, 619 Charles E. Young Dr. East, Los Angeles, CA 90095, USA.
| | - Fiona Havers
- Epidemic Intelligence Service assigned to Influenza Division, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, MS-A04, Atlanta, GA 30333, USA
| | - Cuiling Xu
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, China Center for Disease Control and Prevention, 155 Changbai Rd, Changping District, Beijing 102206, People's Republic of China
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, No. 20, Dongda Street, Fengtai District, Beijing 100071, People's Republic of China
| | - Wu-Chun Cao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, No. 20, Dongda Street, Fengtai District, Beijing 100071, People's Republic of China
| | - Yuelong Shu
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, China Center for Disease Control and Prevention, 155 Changbai Rd, Changping District, Beijing 102206, People's Republic of China
| | - Marc-Alain Widdowson
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, MS-A04, Atlanta, GA 30333, USA
| | - Thomas B Smith
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, 619 Charles E. Young Dr. East, Los Angeles, CA 90095, USA; Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 621 Charles E. Young Dr. East, Los Angeles, CA 90095, USA
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Li Q, Zhou L, Zhou M, Chen Z, Li F, Wu H, Xiang N, Chen E, Tang F, Wang D, Meng L, Hong Z, Tu W, Cao Y, Li L, Ding F, Liu B, Wang M, Xie R, Gao R, Li X, Bai T, Zou S, He J, Hu J, Xu Y, Chai C, Wang S, Gao Y, Jin L, Zhang Y, Luo H, Yu H, He J, Li Q, Wang X, Gao L, Pang X, Liu G, Yan Y, Yuan H, Shu Y, Yang W, Wang Y, Wu F, Uyeki TM, Feng Z. Epidemiology of human infections with avian influenza A(H7N9) virus in China. N Engl J Med 2014; 370:520-32. [PMID: 23614499 PMCID: PMC6652192 DOI: 10.1056/nejmoa1304617] [Citation(s) in RCA: 506] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND The first identified cases of avian influenza A(H7N9) virus infection in humans occurred in China during February and March 2013. We analyzed data obtained from field investigations to describe the epidemiologic characteristics of H7N9 cases in China identified as of December 1, 2013. METHODS Field investigations were conducted for each confirmed case of H7N9 virus infection. A patient was considered to have a confirmed case if the presence of the H7N9 virus was verified by means of real-time reverse-transcriptase-polymerase-chain-reaction assay (RT-PCR), viral isolation, or serologic testing. Information on demographic characteristics, exposure history, and illness timelines was obtained from patients with confirmed cases. Close contacts were monitored for 7 days for symptoms of illness. Throat swabs were obtained from contacts in whom symptoms developed and were tested for the presence of the H7N9 virus by means of real-time RT-PCR. RESULTS Among 139 persons with confirmed H7N9 virus infection, the median age was 61 years (range, 2 to 91), 71% were male, and 73% were urban residents. Confirmed cases occurred in 12 areas of China. Nine persons were poultry workers, and of 131 persons with available data, 82% had a history of exposure to live animals, including chickens (82%). A total of 137 persons (99%) were hospitalized, 125 (90%) had pneumonia or respiratory failure, and 65 of 103 with available data (63%) were admitted to an intensive care unit. A total of 47 persons (34%) died in the hospital after a median duration of illness of 21 days, 88 were discharged from the hospital, and 2 remain hospitalized in critical condition; 2 patients were not admitted to a hospital. In four family clusters, human-to-human transmission of H7N9 virus could not be ruled out. Excluding secondary cases in clusters, 2675 close contacts of case patients completed the monitoring period; respiratory symptoms developed in 28 of them (1%); all tested negative for H7N9 virus. CONCLUSIONS Most persons with confirmed H7N9 virus infection had severe lower respiratory tract illness, were epidemiologically unrelated, and had a history of recent exposure to poultry. However, limited, nonsustained human-to-human H7N9 virus transmission could not be ruled out in four families.
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Affiliation(s)
- Qun Li
- The authors' affiliations are listed in the Appendix
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30
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Qiu C, Yuan S, Tian D, Yang Y, Zhang A, Chen Q, Wan Y, Song Z, He J, Li L, Sun J, Zhou M, Qiu C, Zhang Z, Lu S, Zhang X, Hu Y, Xu J. Epidemiologic report and serologic findings for household contacts of three cases of influenza A (H7N9) virus infection. J Clin Virol 2014; 59:129-31. [PMID: 24388209 PMCID: PMC7106538 DOI: 10.1016/j.jcv.2013.12.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Revised: 11/23/2013] [Accepted: 12/04/2013] [Indexed: 11/27/2022]
Abstract
BACKGROUND AND OBJECTIVE We conducted epidemiologic investigations and serologic assays on household contacts that were extensively exposed to three influenza A (H7N9) virus infected case-patients before infection-control practices were implemented. STUDY DESIGN Data on the early clinical course of each patient and the exposure history for each patient's household contacts were obtained by interviewing household members and by reviewing medical records. Viral RNA in patient samples was tested using real-time reverse transcriptase polymerase chain reaction assay. Antibodies against H7N9 virus in serum samples were tested using hemagglutination inhibition and pseudovirus based neutralization assays. RESULTS All household contacts were extensively exposed to the case-patients without the use of measures to protect against infection. Viral RNA was detected in the specimens from case-patients for approximately 7-11 days after confirmation of infection. However, the results of the analyses of serum specimens taken from the household contacts 15-26 days post exposure revealed no evidence of transmission of H7N9 virus from the case-patients to the contacts. CONCLUSION Despite ample unprotected exposures to case-patients during the virus shedding period, household members in this report were not infected by the H7N9 virus.
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MESH Headings
- Adult
- Aged
- Aged, 80 and over
- Antibodies, Viral/blood
- Contact Tracing
- Family Characteristics
- Female
- Hemagglutination Inhibition Tests
- Humans
- Influenza A Virus, H7N9 Subtype/genetics
- Influenza A Virus, H7N9 Subtype/immunology
- Influenza A Virus, H7N9 Subtype/isolation & purification
- Influenza, Human/epidemiology
- Influenza, Human/transmission
- Influenza, Human/virology
- Male
- Middle Aged
- Neutralization Tests
- RNA, Viral/blood
- RNA, Viral/genetics
- Real-Time Polymerase Chain Reaction
- Reverse Transcriptase Polymerase Chain Reaction
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Affiliation(s)
- Chao Qiu
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Songhua Yuan
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Di Tian
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu Yang
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Anli Zhang
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qingguo Chen
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yanmin Wan
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhigang Song
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jing He
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liangzhu Li
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jun Sun
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Mingzhe Zhou
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chenli Qiu
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhiyong Zhang
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shuihua Lu
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaoyan Zhang
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China; State Key Laboratory for Infectious Disease Prevention and Control, China CDC, Beijing, China.
| | - Yunwen Hu
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Jianqing Xu
- Shanghai Public Health Clinical Center & Institutes of Biomedical Sciences, Key Laboratory of Medical Molecular Virology of Ministry of Education/Health, Shanghai Medical College, Fudan University, Shanghai, China; State Key Laboratory for Infectious Disease Prevention and Control, China CDC, Beijing, China.
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Yang P, Pang X, Deng Y, Ma C, Zhang D, Sun Y, Shi W, Lu G, Zhao J, Liu Y, Peng X, Tian Y, Qian H, Chen L, Wang Q. Surveillance for avian influenza A(H7N9), Beijing, China, 2013. Emerg Infect Dis 2013; 19:2041-3. [PMID: 24274700 PMCID: PMC3840857 DOI: 10.3201/eid1912.130983] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
During surveillance for pneumonia of unknown etiology and sentinel hospital-based surveillance in Beijing, China, we detected avian influenza A(H7N9) virus infection in 4 persons who had pneumonia, influenza-like illness, or asymptomatic infections. Samples from poultry workers, associated poultry environments, and wild birds suggest that this virus might not be present in Beijing.
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Peng Y, Xie ZX, Liu JB, Pang YS, Deng XW, Xie ZQ, Xie LJ, Fan Q, Luo SS. Epidemiological surveillance of low pathogenic avian influenza virus (LPAIV) from poultry in Guangxi Province, Southern China. PLoS One 2013; 8:e77132. [PMID: 24204754 PMCID: PMC3813733 DOI: 10.1371/journal.pone.0077132] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2013] [Accepted: 08/29/2013] [Indexed: 02/02/2023] Open
Abstract
Low pathogenic avian influenza virus (LPAIV) usually causes mild disease or asymptomatic infection in poultry. However, some LPAIV strains can be transmitted to humans and cause severe infection. Genetic rearrangement and recombination of even low pathogenic influenza may generate a novel virus with increased virulence, posing a substantial risk to public health. Southern China is regarded as the world “influenza epicenter”, due to a rash of outbreaks of influenza in recent years. In this study, we conducted an epidemiological survey of LPAIV at different live bird markets (LBMs) in Guangxi province, Southern China. From January 2009 to December 2011, we collected 3,121 cotton swab samples of larynx, trachea and cloaca from the poultry at LBMs in Guangxi. Virus isolation, hemagglutination inhibition (HI) assay, and RT-PCR were used to detect and subtype LPAIV in the collected samples. Of the 3,121 samples, 336 samples (10.8%) were LPAIV positive, including 54 (1.7%) in chicken and 282 (9.1%) in duck. The identified LPAIV were H3N1, H3N2, H6N1, H6N2, H6N5, H6N6, H6N8, and H9N2, which are combinations of seven HA subtypes (H1, H3, H4, H6, H9, H10 and H11) and five NA subtypes (N1, N2, N5, N6 and N8). The H3 and H9 subtypes are predominant in the identified LPAIVs. Among the 336 cases, 29 types of mixed infection of different HA subtypes were identified in 87 of the cases (25.9%). The mixed infections may provide opportunities for genetic recombination. Our results suggest that the LPAIV epidemiology in poultry in the Guangxi province in southern China is complicated and highlights the need for further epidemiological and genetic studies of LPAIV in this area.
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Affiliation(s)
- Yi Peng
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Zhi-xun Xie
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
- * E-mail:
| | - Jia-bo Liu
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Yao-shan Pang
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Xian-wen Deng
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Zhi-qin Xie
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Li-ji Xie
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Qing Fan
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
| | - Si-si Luo
- Guangxi Key Laboratory of Animal Vaccines and Diagnostics, Guangxi Veterinary Research Institute, Nanning, Guangxi Province, China
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To KKW, Chan JFW, Chen H, Li L, Yuen KY. The emergence of influenza A H7N9 in human beings 16 years after influenza A H5N1: a tale of two cities. THE LANCET. INFECTIOUS DISEASES 2013; 13:809-21. [PMID: 23969217 PMCID: PMC7158959 DOI: 10.1016/s1473-3099(13)70167-1] [Citation(s) in RCA: 116] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Infection with either influenza A H5N1 virus in 1997 or avian influenza A H7N9 virus in 2013 caused severe pneumonia that did not respond to typical or atypical antimicrobial treatment, and resulted in high mortality. Both viruses are reassortants with internal genes derived from avian influenza A H9N2 viruses that circulate in Asian poultry. Both viruses have genetic markers of mammalian adaptation in their haemagglutinin and polymerase PB2 subunits, which enhanced binding to human-type receptors and improved replication in mammals, respectively. Hong Kong (affected by H5N1 in 1997) and Shanghai (affected by H7N9 in 2013) are two rapidly flourishing cosmopolitan megacities that were increasing in human population and poultry consumption before the outbreaks. Both cities are located along the avian migratory route at the Pearl River delta and Yangtze River delta. Whether the widespread use of the H5N1 vaccine in east Asia-with suboptimum biosecurity measures in live poultry markets and farms-predisposed to the emergence of H7N9 or other virus subtypes needs further investigation. Why H7N9 seems to be more readily transmitted from poultry to people than H5N1 is still unclear.
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Affiliation(s)
- Kelvin KW To
- State Key Laboratory for Emerging Infectious Diseases, Research Centre of Infection and Immunology, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jasper FW Chan
- State Key Laboratory for Emerging Infectious Diseases, Research Centre of Infection and Immunology, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Honglin Chen
- State Key Laboratory for Emerging Infectious Diseases, Research Centre of Infection and Immunology, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Kwok-Yung Yuen
- State Key Laboratory for Emerging Infectious Diseases, Research Centre of Infection and Immunology, Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
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Yu L, Wang Z, Chen Y, Ding W, Jia H, Chan JFW, To KKW, Chen H, Yang Y, Liang W, Zheng S, Yao H, Yang S, Cao H, Dai X, Zhao H, Li J, Bao Q, Chen P, Hou X, Li L, Yuen KY. Clinical, virological, and histopathological manifestations of fatal human infections by avian influenza A(H7N9) virus. Clin Infect Dis 2013; 57:1449-57. [PMID: 23943822 DOI: 10.1093/cid/cit541] [Citation(s) in RCA: 90] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Systematic analysis of histopathological and serial virological changes of fatal influenza A(H7N9) cases is lacking. METHODS Patients with A(H7N9) infection admitted to our intensive care unit during 10-23 April 2013 were included. Viral loads in the respiratory tract, as inferred from the cycle threshold (Ct) value of reverse transcription polymerase chain reaction (RT-PCR), and the serum hemagglutination inhibition (HAI) antibody titer, were analyzed. Postmortem biopsies of the lung, liver, kidney, spleen, bone marrow, and heart were examined. RESULTS Twelve patients (6 deaths, 6 survivors) were included. Median viral load was higher in sputa than the nasopharyngeal swabs for fatal cases (median Ct, 23 vs 30.5; P = .08). RT-PCR for A(H7N9) was positive in stool samples (4/6 [67%]) of fatal cases and (2/6 [33%]) of survivors, but was negative in the cerebrospinal fluid, urine, or blood of all patients. Nosocomial bacterial infections were more common in patients who died than in survivors (83% vs 50%). HAI titers increased by ≥4-fold in those with convalescent sera. Postmortem biopsy for 3 patients showed acute diffuse alveolar damage. Patient 1, who died 8 days after symptom onset, had intra-alveolar hemorrhage. Patients 2 and 3, who died 11 days after symptom onset, had pulmonary fibroproliferative changes. Reactive hemophagocytosis in the bone marrow and lymphoid atrophy in splenic tissues were compatible with laboratory findings of leukopenia, lymphopenia, and thrombocytopenia. Hypoxic and fatty changes of kidney and liver tissues are compatible with impaired renal or liver function. CONCLUSIONS Fatal A(H7N9) infection was characterized by viral and secondary bacterial pneumonia with 67% having positive RT-PCR in stool.
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Affiliation(s)
- Liang Yu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases
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Yang S, Chen Y, Cui D, Yao H, Lou J, Huo Z, Xie G, Yu F, Zheng S, Yang Y, Zhu Y, Lu X, Liu X, Lau SY, Chan JFW, To KKW, Yuen KY, Chen H, Li L. Avian-Origin Influenza A(H7N9) Infection in Influenza A(H7N9)–Affected Areas of China: A Serological Study. J Infect Dis 2013; 209:265-9. [DOI: 10.1093/infdis/jit430] [Citation(s) in RCA: 88] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Cowling BJ, Jin L, Lau EHY, Liao Q, Wu P, Jiang H, Tsang TK, Zheng J, Fang VJ, Chang Z, Ni MY, Zhang Q, Ip DKM, Yu J, Li Y, Wang L, Tu W, Meng L, Wu JT, Luo H, Li Q, Shu Y, Li Z, Feng Z, Yang W, Wang Y, Leung GM, Yu H. Comparative epidemiology of human infections with avian influenza A H7N9 and H5N1 viruses in China: a population-based study of laboratory-confirmed cases. Lancet 2013; 382:129-37. [PMID: 23803488 PMCID: PMC3777567 DOI: 10.1016/s0140-6736(13)61171-x] [Citation(s) in RCA: 234] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The novel influenza A H7N9 virus emerged recently in mainland China, whereas the influenza A H5N1 virus has infected people in China since 2003. Both infections are thought to be mainly zoonotic. We aimed to compare the epidemiological characteristics of the complete series of laboratory-confirmed cases of both viruses in mainland China so far. METHODS An integrated database was constructed with information about demographic, epidemiological, and clinical variables of laboratory-confirmed cases of H7N9 (130 patients) and H5N1 (43 patients) that were reported to the Chinese Centre for Disease Control and Prevention until May 24, 2013. We described disease occurrence by age, sex, and geography, and estimated key epidemiological variables. We used survival analysis techniques to estimate the following distributions: infection to onset, onset to admission, onset to laboratory confirmation, admission to death, and admission to discharge. FINDINGS The median age of the 130 individuals with confirmed infection with H7N9 was 62 years and of the 43 with H5N1 was 26 years. In urban areas, 74% of cases of both viruses were in men, whereas in rural areas the proportions of the viruses in men were 62% for H7N9 and 33% for H5N1. 75% of patients infected with H7N9 and 71% of those with H5N1 reported recent exposure to poultry. The mean incubation period of H7N9 was 3·1 days and of H5N1 was 3·3 days. On average, 21 contacts were traced for each case of H7N9 in urban areas and 18 in rural areas, compared with 90 and 63 for H5N1. The fatality risk on admission to hospital was 36% (95% CI 26-45) for H7N9 and 70% (56-83%) for H5N1. INTERPRETATION The sex ratios in urban compared with rural cases are consistent with exposure to poultry driving the risk of infection--a higher risk in men was only recorded in urban areas but not in rural areas, and the increased risk for men was of a similar magnitude for H7N9 and H5N1. However, the difference in susceptibility to serious illness with the two different viruses remains unexplained, since most cases of H7N9 were in older adults whereas most cases of H5N1 were in younger people. A limitation of our study is that we compared laboratory-confirmed cases of H7N9 and H5N1 infection, and some infections might not have been ascertained. FUNDING Ministry of Science and Technology, China; Research Fund for the Control of Infectious Disease and University Grants Committee, Hong Kong Special Administrative Region, China; and the US National Institutes of Health.
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Affiliation(s)
- Benjamin J. Cowling
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Lianmei Jin
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Eric H. Y. Lau
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Qiaohong Liao
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Wu
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Hui Jiang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tim K. Tsang
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jiandong Zheng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Vicky J. Fang
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Zhaorui Chang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Michael Y. Ni
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Qian Zhang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dennis K. M. Ip
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jianxing Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liping Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenxiao Tu
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ling Meng
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Joseph T. Wu
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Huiming Luo
- National Immunization Program, Chinese Center for Disease Control and Prevention Beijing, China
| | - Qun Li
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuelong Shu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission
| | - Zhongjie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zijian Feng
- Public Health Emergency Center, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weizhong Yang
- Office of the Director, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Wang
- Office of the Director, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Gabriel M. Leung
- Infectious Disease Epidemiology Group, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Hongjie Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
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