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Deng X, Chen Z, Zhao Z, Chen J, Li M, Yang J, Yu H. Regional characteristics of influenza seasonality patterns in mainland China, 2005-2017: a statistical modeling study. Int J Infect Dis 2023; 128:91-97. [PMID: 36581188 DOI: 10.1016/j.ijid.2022.12.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 12/06/2022] [Accepted: 12/21/2022] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVES To quantify the seasonal and antigenic characteristics of influenza to help understand influenza activity and inform vaccine recommendations. METHODS We employed a generalized linear model with harmonic terms to quantify the seasonal pattern of influenza in China from 2005-2017, including amplitude (circulatory intensity), semiannual periodicity (given two peaks a year), annual peak time, and epidemic duration. The antigenic differences were distinguished as antigenic similarity between 2009 and 2020. We categorized regions above 33° N, between 27° N and 33° N, and below 27° N as the north, central, and south regions, respectively. RESULTS We estimated that the amplitude in the north region (median: 0.019, 95% CI: 0.018-0.021) was significantly higher than that in the central region (median: 0.011, 95% CI: 0.01-0.012, P <0.001) and south region (median: 0.008, 95% CI: 0.007-0.008, P <0.001) for influenza A virus subtype H3N2 (A/H3N2). The A/H3N2 in the central region had a semiannual periodicity (median: 0.548, 95% CI: 0.517-0.577), while no semiannual pattern was found in other regions or subtypes/lineages. The antigenic similarity was low (below 50% in the 2009-2010, 2014-2015, 2016-2018, and 2019-2020 seasons) for A/H3N2. CONCLUSION Our study depicted the seasonal pattern differences and antigenic differences of influenza in China, which provides information for vaccination strategies.
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Affiliation(s)
- Xiaowei Deng
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Zhiyuan Chen
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Zeyao Zhao
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Junbo Chen
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Mei Li
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Juan Yang
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Hongjie Yu
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China; National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
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Mavragani A, Yan ZL, Luo L, Liu W, Yang Z, Shi C, Ming BW, Yang J, Cao P, Ou CQ. Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model. JMIR Public Health Surveill 2023; 9:e42530. [PMID: 36630176 PMCID: PMC9878364 DOI: 10.2196/42530] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/14/2022] [Accepted: 11/25/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Accurate estimation of the influenza death burden is of great significance for influenza prevention and control. However, few studies have considered the short-term harvesting effects of influenza on mortality when estimating influenza-associated excess deaths by cause of death, age, sex, and subtype/lineage. OBJECTIVE This study aimed to estimate the cause-, age-, and sex-specific excess mortality associated with influenza and its subtypes and lineages in Guangzhou from 2015 to 2018. METHODS Distributed-lag nonlinear models were fitted to estimate the excess mortality related to influenza subtypes or lineages for different causes of death, age groups, and sex based on daily time-series data for mortality, influenza, and meteorological factors. RESULTS A total of 199,777 death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical CI [eCI] 19.85-30.16) per 100,000 persons; 7142 of 8791 (81.2%) deaths were due to respiratory or cardiovascular mortality (EMR 20.36, 95% eCI 16.75-23.74). Excess respiratory and cardiovascular deaths in people aged 60 to 79 years and those aged ≥80 years accounted for 32.9% (2346/7142) and 63.7% (4549/7142) of deaths, respectively. The male to female ratio (MFR) of excess death from respiratory diseases was 1.34 (95% CI 1.17-1.54), while the MFR for excess death from cardiovascular disease was 0.72 (95% CI 0.63-0.82). The average annual excess respiratory and cardiovascular mortality rates attributed to influenza A (H3N2), B/Yamagata, B/Victoria, and A (H1N1) were 8.47 (95% eCI 6.60-10.30), 5.81 (95% eCI 3.35-8.25), 3.68 (95% eCI 0.81-6.49), and 2.83 (95% eCI -1.26 to 6.71), respectively. Among these influenza subtypes/lineages, A (H3N2) had the highest excess respiratory and cardiovascular mortality rates for people aged 60 to 79 years (20.22, 95% eCI 14.56-25.63) and ≥80 years (180.15, 95% eCI 130.75-227.38), while younger people were more affected by A (H1N1), with an EMR of 1.29 (95% eCI 0.07-2.32). The mortality displacement of influenza A (H1N1), A (H3N2), and B/Yamagata was 2 to 5 days, but 5 to 13 days for B/Victoria. CONCLUSIONS Influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly, even after considering mortality displacement. The mortality burden of influenza B, particularly B/Yamagata, cannot be ignored. Contrasting sex differences were found in influenza-associated excess mortality from respiratory diseases and from cardiovascular diseases; the underlying mechanisms need to be investigated in future studies. Our findings can help us better understand the magnitude and time-course of the effect of influenza on mortality and inform targeted interventions for mitigating the influenza mortality burden, such as immunizations with quadrivalent vaccines (especially for older people), behavioral campaigns, and treatment strategies.
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Affiliation(s)
| | - Ze-Lin Yan
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Wenhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chen Shi
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Bo-Wen Ming
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jun Yang
- School of Public Health, Guanghzou Medical University, Guangzhou, China
| | - Peihua Cao
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.,Clinical Research Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
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3
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Dong K, Gong H, Zhong G, Deng X, Tian Y, Wang M, Yu H, Yang J. Estimating mortality associated with seasonal influenza among adults aged 65 years and above in China from 2011 to 2016: A systematic review and model analysis. Influenza Other Respir Viruses 2022; 17:e13067. [PMID: 36394198 PMCID: PMC9835403 DOI: 10.1111/irv.13067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 10/25/2022] [Accepted: 10/26/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Estimation of influenza disease burden is crucial for optimizing intervention strategies against seasonal influenza. This study aimed to estimate influenza-associated excess respiratory and circulatory (R&C) and all-cause (AC) mortality among older adults aged 65 years and above in mainland China from 2011 to 2016. METHODS Through a systematic review, we collected influenza-associated excess R&C and AC mortality data of older adults aged 65 years and above for specific cities/provinces in mainland China. Generalized linear models were fitted to estimate the corresponding excess mortality for older adults by province and nationwide, accounting for the potential variables of influenza virus activity, demography, economics, meteorology, and health service. All statistical analyses were conducted using R software. RESULTS A total of 9154 studies were identified in English and Chinese databases, and 11 (0.1%) were included in the quantitative synthesis after excluding duplicates and screening the title, abstract, and full text. Using a generalized linear model, the estimates of annual national average influenza-associated excess R&C and AC mortality among older adults aged 65 years and above were 111.8 (95% CI: 92.8-141.1) and 151.6 (95% CI: 127.6-179.3) per 100,000 persons, respectively. Large variations in influenza-associated excess R&C and AC mortality among older adults were observed among 30 provinces. CONCLUSIONS Influenza was associated with substantial excess R&C and AC mortality among older adults aged 65 years and above in China from 2011 to 2016. This analysis provides valuable evidence for the introduction of the influenza vaccine into the National Immunization Program for the elderly in China.
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Affiliation(s)
- Kaige Dong
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Hui Gong
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Guangjie Zhong
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Xiaowei Deng
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Yuyang Tian
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Minghan Wang
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Hongjie Yu
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
| | - Juan Yang
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public HealthFudan UniversityShanghaiChina,School of Public Health, Fudan University, Key Laboratory of Public Health SafetyMinistry of EducationShanghaiChina
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Li J, Chen Y, Wang X, Yu H. Influenza-associated disease burden in mainland China: a systematic review and meta-analysis. Sci Rep 2021; 11:2886. [PMID: 33536462 PMCID: PMC7859194 DOI: 10.1038/s41598-021-82161-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 01/18/2021] [Indexed: 11/22/2022] Open
Abstract
Influenza causes substantial morbidity and mortality. Many original studies have been carried out to estimate disease burden of influenza in mainland China, while the full disease burden has not yet been systematically reviewed. We did a systematic review and meta-analysis to assess the burden of influenza-associated mortality, hospitalization, and outpatient visit in mainland China. We searched 3 English and 4 Chinese databases with studies published from 2005 to 2019. Studies reporting population-based rates of mortality, hospitalization, or outpatient visit attributed to seasonal influenza were included in the analysis. Fixed-effects or random-effects model was used to calculate pooled estimates of influenza-associated mortality depending on the degree of heterogeneity. Meta-regression was applied to explore the sources of heterogeneity. Publication bias was assessed by funnel plots and Egger’s test. We identified 30 studies eligible for inclusion with 17, 8, 5 studies reporting mortality, hospitalization, and outpatient visit associated with influenza, respectively. The pooled influenza-associated all-cause mortality rates were 14.33 and 122.79 per 100,000 persons for all ages and ≥ 65 years age groups, respectively. Studies were highly heterogeneous in aspects of age group, cause of death, statistical model, geographic location, and study period, and these factors could explain 60.14% of the heterogeneity in influenza-associated mortality. No significant publication bias existed in estimates of influenza-associated all-cause mortality. Children aged < 5 years were observed with the highest rates of influenza-associated hospitalizations and ILI outpatient visits. People aged ≥ 65 years and < 5 years contribute mostly to mortality and morbidity burden due to influenza, which calls for targeted vaccination policy for older adults and younger children in mainland China.
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Affiliation(s)
- Jing Li
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China
| | - Yinzi Chen
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China
| | - Xiling Wang
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China. .,Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
| | - Hongjie Yu
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China
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Influenza-attributable years of life lost in older adults in a subtropical city in China, 2012-2017: A modeling study based on a competing risks approach. Int J Infect Dis 2020; 97:354-359. [PMID: 32562848 DOI: 10.1016/j.ijid.2020.06.041] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/09/2020] [Accepted: 06/11/2020] [Indexed: 11/21/2022] Open
Abstract
OBJECTIVE The aim of this study was to estimate influenza-attributable years of life lost (YLL) in older adults in subtropical Hefei, China during the years 2012-2017, based on a competing risks approach. METHODS The quasi-Poisson model was fitted to weekly numbers of all-cause deaths by 5-year age groups for older adults ≥60 years of age. The product of the weekly influenza-like illness consultation rate and the proportion of specimens that tested positive for influenza was taken as the measurement of influenza activity, which was incorporated into the model as an exploratory variable. Excess deaths associated with influenza were calculated by subtracting baseline deaths (setting influenza activity to zero) from fitted deaths. Influenza-attributable YLL accounting for competing risks was estimated using restricted mean lifetime survival analysis. RESULTS The annual influenza-attributable YLL was highest in the 75-79 years age group (565 per 100,000 persons, 95% confidence interval 550-580), followed by the 80-84, 70-74, 85-89, 65-69, and 60-64 years age groups. Influenza A(H3N2) virus was associated with higher YLL than A(H1N1) and B viruses. Influenza-attributable YLL accounted for 1.03-1.53% of total YLL, and the proportion would be overestimated to 2.91-7.34% if the traditional Kaplan-Meier method ignoring competing risks was used. CONCLUSIONS Although influenza-associated mortality increased with age, influenza-attributable YLL was found to be highest in the 75-79 years age group.
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Rumisha SF, George J, Bwana VM, Mboera LEG. Years of potential life lost and productivity costs due to premature mortality from six priority diseases in Tanzania, 2006-2015. PLoS One 2020; 15:e0234300. [PMID: 32516340 PMCID: PMC7282655 DOI: 10.1371/journal.pone.0234300] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 05/22/2020] [Indexed: 01/14/2023] Open
Abstract
Background Mortality statistics are traditionally used to quantify the burden of disease and to determine the relative importance of the various causes of death. Some of the most frequently used indices to quantify the burden of disease are the years of potential life lost (YPLL) and years of potential productive life lost (YPPLL). These two measures reflect the mortality trends in younger age groups and they provide a more accurate picture of premature mortality. This study was carried out to determine YPLL, YPPLL and cost of productivity lost (CPL) due to premature mortality caused by selected causes of deaths in Tanzania. Methods and findings Malaria, respiratory diseases, HIV/AIDS, tuberculosis, cancers and injuries were selected for this analysis. The number of deaths by sex and age groups were obtained from hospital death registers and ICD-10 reporting forms in 39 public hospitals in Tanzania, covering a period of 2006–2015. The life expectancy method and human capital approach were used to estimate the YPLL, YPPLL and CPL due to premature mortality. During 2006–2015, malaria, HIV/AIDS, tuberculosis, respiratory diseases, HIV+tuberculosis, cancer and injury were responsible for a total of 96,834 hospital deaths, of which 46.4% (n = 57,508) were among individuals in the productive age groups (15–64 years). The reported deaths contributed to 2,850,928 YPLL (female = 1,326,724; male = 1,524,205) with an average of 29 years per death. The average YPLL among females (32) was higher than among males (28). Malaria (YPLL = 38 per death) accounted for over one-third (35%) of the total YPLL. There was a significant increase in YPLL due to the selected underlying causes of death over the 10-year period. Deaths from the selected causes resulted into 1,207,499 YPPLL (average = 21 per death). Overall, HIV/AIDS contributed to the highest YPPLL (323,704), followed by malaria (243,490) and injuries (196,505). While there was a general decrease in YPPLL due to malaria, there was an increase of YPPLL due to HIV/AIDS, respiratory diseases, cancer and injuries during the 10-year period. The total CPL due to the six diseases was US$ 148,430,009 for 10 years. The overall CPL was higher among males than females by 29.1%. Over half (58%) of the losses were due to deaths among males. HIV/AIDS accounted for the largest (29.2%) CPL followed by malaria (17.8%) and respiratory diseases (14.6%). The CPL increased from US$11.4 million in 2006 to US$17.9 million in 2016. Conclusions The YPLL, YPPLL and CPL due to premature death associated with the six diseases in Tanzania are substantially high. While malaria accounted for highest YPLL, HIV/AIDS accounted for highest YPPLL and CPL. The overall CPL was higher among males than among females. Setting resource allocation priorities to malaria, HIV/AIDS and respiratory diseases that are responsible for the majority of premature deaths could potentially reduce the costs of productivity loss in Tanzania.
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Affiliation(s)
- Susan F. Rumisha
- National Institute for Medical Research, Dar es Salaam, Tanzania
| | - Janeth George
- SACIDS Foundation for One Health, Sokoine University of Agriculture, Morogoro, Tanzania
| | - Veneranda M. Bwana
- National Institute for Medical Research, Amani Research Centre, Muheza, Tanzania
| | - Leonard E. G. Mboera
- National Institute for Medical Research, Dar es Salaam, Tanzania
- SACIDS Foundation for One Health, Sokoine University of Agriculture, Morogoro, Tanzania
- * E-mail:
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Yan Y, Ou J, Zhao S, Ma K, Lan W, Guan W, Wu X, Zhang J, Zhang B, Zhao W, Wan C, Shi W, Wu J, Seto D, Yu Z, Zhang Q. Characterization of Influenza A and B Viruses Circulating in Southern China During the 2017-2018 Season. Front Microbiol 2020; 11:1079. [PMID: 32547518 PMCID: PMC7272714 DOI: 10.3389/fmicb.2020.01079] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 04/30/2020] [Indexed: 01/03/2023] Open
Abstract
The trivalent seasonal influenza vaccine was the only approved and available vaccine during the 2016–2018 influenza seasons. It did not include the B/Yamagata strain. In this study, we report an acute respiratory disease outbreak associated with influenza B/Yamagata infections in Guangzhou, Southern China (January through March, 2018). Among the 9914 patients, 2241 (22.6%) were positive for the influenza B virus, with only 312 (3.1%) positive for the influenza A virus. The influenza B/Yamagata lineage dominated during this period in Southern China. The highest incidence of influenza A virus infection occurred in the children aged 5–14 years. In contrast, populations across all age groups were susceptible to the influenza B virus. Phylogenetic, mutations, and 3D structure analyses of hemagglutinin (HA) genes were performed to assess the vaccine-virus relatedness. The recommended A/H1N1 vaccine strain (A/Michigan/45/2015) during both 2017–2018 and 2018–2019 was antigen-specific for these circulating isolates (clade 6B.1) in Spring 2018. An outbreak of influenza B/Yamagata (clade 3) infections in 2018 occurred during the absence of the corresponding vaccine during 2016–2018. The recommended influenza B/Yamagata vaccine strain (B/Phuket/3073/2013) for the following season (2018–2019) was antigen-specific. Although there were only a few influenza B/Victoria infections in Spring 2018, five amino acid mutations were identified in the HA antigenic sites of the 19 B/Victoria isolates (clade 1A), when compared with the 2016–2018 B/Victoria vaccine strain. The number was larger than expected and suggested that the influenza B HA gene may be more variable than previously thought. One of the mutations (K180N) was noted to likely alter the epitope and to potentially affect the viral antigenicity. Seven mutations were also identified in the HA antigenic sites of 2018–2020 B/Victoria vaccine strain, of which some or all may reduce immunogenicity and the protective efficacy of the vaccine, perhaps leading to more outbreaks in subsequent seasons. The combined epidemiological, phylogenetic, mutations, and 3D structural analyses of the HA genes of influenza strains reported here contribute to the understanding and evaluation of how HA mutations affect vaccine efficacy, as well as to providing important data for screening and selecting more specific, appropriate, and effective influenza vaccine candidate strains.
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Affiliation(s)
- Yuqian Yan
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Junxian Ou
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Shan Zhao
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Kui Ma
- Guangdong Provincial Key Laboratory of Virology, Institute of Medical Microbiology, Jinan University, Guangzhou, China
| | - Wendong Lan
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Wenyi Guan
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xiaowei Wu
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jing Zhang
- Guangdong Provincial Key Laboratory of Virology, Institute of Medical Microbiology, Jinan University, Guangzhou, China
| | - Bao Zhang
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Wei Zhao
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chengsong Wan
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Weifeng Shi
- Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Jianguo Wu
- Guangdong Provincial Key Laboratory of Virology, Institute of Medical Microbiology, Jinan University, Guangzhou, China
| | - Donald Seto
- Bioinformatics and Computational Biology Program, School of Systems Biology, George Mason University, Manassas, VA, United States
| | - Zhiwu Yu
- Division of Laboratory Science, The Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China
| | - Qiwei Zhang
- Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Virology, Institute of Medical Microbiology, Jinan University, Guangzhou, China
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8
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Yang J, Atkins KE, Feng L, Baguelin M, Wu P, Yan H, Lau EHY, Wu JT, Liu Y, Cowling BJ, Jit M, Yu H. Cost-effectiveness of introducing national seasonal influenza vaccination for adults aged 60 years and above in mainland China: a modelling analysis. BMC Med 2020; 18:90. [PMID: 32284056 PMCID: PMC7155276 DOI: 10.1186/s12916-020-01545-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 03/03/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND China has an aging population with an increasing number of adults aged ≥ 60 years. Influenza causes a heavy disease burden in older adults, but can be alleviated by vaccination. We assessed the cost-effectiveness of a potential government-funded seasonal influenza vaccination program in older adults in China. METHODS We characterized the health and economic impact of a fully funded influenza vaccination program for older adults using China-specific influenza disease burden, and related cost data, etc. Using a decision tree model, we calculated the incremental costs per quality-adjusted life year (QALY) gained of vaccination from the societal perspective, at a willingness-to-pay threshold equivalent to GDP per capita (US$8840). Moreover, we estimated the threshold vaccination costs, under which the fully funded vaccination program is cost-effective using GDP per capita as the willingness-to-pay threshold. RESULTS Compared to current self-paid vaccination, a fully funded vaccination program is expected to prevent 19,812 (95% uncertainty interval, 7150-35,783) influenza-like-illness outpatient consultations per year, 9418 (3386-17,068) severe acute respiratory infection hospitalizations per year, and 8800 (5300-11,667) respiratory excess deaths due to influenza per year, and gain 70,212 (42,106-93,635) QALYs per year. Nationally, the incremental costs per QALY gained of the vaccination program is US$4832 (3460-8307), with a 98% probability of being cost-effective. The threshold vaccination cost is US$10.19 (6.08-13.65). However, variations exist between geographical regions, with Northeast and Central China having lower probabilities of cost-effectiveness. CONCLUSIONS Our results support the implementation of a government fully funded older adult vaccination program in China. The regional analysis provides results across settings that may be relevant to other countries with similar disease burden and economic status, especially for low- and middle-income countries where such analysis is limited.
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Affiliation(s)
- Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Katherine E Atkins
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
| | - 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
| | - Marc Baguelin
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - 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
| | - Han Yan
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Eric H Y Lau
- 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
| | - Joseph T 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
| | - Yang Liu
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - 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
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- 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
- Modelling and Economics Unit, Public Health England, London, UK
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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9
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Feng L, Feng S, Chen T, Yang J, Lau YC, Peng Z, Li L, Wang X, Wong JYT, Qin Y, Bond HS, Zhang J, Fang VJ, Zheng J, Yang J, Wu P, Jiang H, He Y, Cowling BJ, Yu H, Shu Y, Lau EHY. Burden of influenza-associated outpatient influenza-like illness consultations in China, 2006-2015: A population-based study. Influenza Other Respir Viruses 2020; 14:162-172. [PMID: 31872547 PMCID: PMC7040965 DOI: 10.1111/irv.12711] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 12/04/2019] [Accepted: 12/08/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Human influenza virus infections cause a considerable burden of morbidity and mortality worldwide each year. Understanding regional influenza-associated outpatient burden is crucial for formulating control strategies against influenza viruses. METHODS We extracted the national sentinel surveillance data on outpatient visits due to influenza-like-illness (ILI) and virological confirmation of sentinel specimens from 30 provinces of China from 2006 to 2015. Generalized additive regression models were fitted to estimate influenza-associated excess ILI outpatient burden for each individual province, accounting for seasonal baselines and meteorological factors. RESULTS Influenza was associated with an average of 2.5 excess ILI consultations per 1000 person-years (py) in 30 provinces of China each year from 2006 to 2015. Influenza A(H1N1)pdm09 led to a higher number of influenza-associated ILI consultations in 2009 across all provinces compared with other years. The excess ILI burden was 4.5 per 1000 py among children aged below 15 years old, substantially higher than that in adults. CONCLUSIONS Human influenza viruses caused considerable impact on population morbidity, with a consequent healthcare and economic burden. This study provided the evidence for planning of vaccination programs in China and a framework to estimate burden of influenza-associated outpatient consultations.
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Affiliation(s)
- Luzhao Feng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Shuo Feng
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Tao Chen
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
| | - Juan Yang
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Yiu Chung Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Zhibin Peng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Li Li
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Xiling Wang
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Jessica Y. T. Wong
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Ying Qin
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Helen S. Bond
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Juanjuan Zhang
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Vicky J. Fang
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Jiandong Zheng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Jing Yang
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Hui Jiang
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Yangni He
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Hongjie Yu
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Yuelong Shu
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
- School of Public Health (Shenzhen)Sun Yat‐sen UniversityShenzhenChina
| | - Eric H. Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
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10
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One Hundred Years of Influenza Since the 1918 Pandemic - Is China Prepared Today? China CDC Wkly 2019; 1:56-61. [PMID: 34594605 PMCID: PMC8422199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 11/22/2019] [Indexed: 11/23/2022] Open
Abstract
Almost 100 years after the 1918 influenza pandemic, China experienced its largest, most widespread epidemic of human infections with avian influenza A (H7N9), the influenza virus with the greatest pandemic potential of all influenza viruses assessed to date by the United States Centers for Disease Control and Prevention's Influenza Risk Assessment Tool. This historical review describes how China was affected by the 1918, 1958, 1968, and 2009 influenza pandemics, records milestones in China's capacity to detect and respond to influenza threats, and identifies remaining challenges for pandemic preparedness. This review suggests that past influenza pandemics have improved China's national capabilities such that China has become a global leader in influenza detection and response. Further enhancing China's pandemic preparedness to address remaining challenges requires government commitment and increased investment in China's public health and healthcare systems.
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11
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Liu Y, Zhang Y, Zhao W, Liu X, Hu F, Dong B. Pharmacotherapy of Lower Respiratory Tract Infections in Elderly-Focused on Antibiotics. Front Pharmacol 2019; 10:1237. [PMID: 31736751 PMCID: PMC6836807 DOI: 10.3389/fphar.2019.01237] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 09/27/2019] [Indexed: 02/05/2023] Open
Abstract
Lower respiratory tract infections (LRTIs) refer to the inflammation of the trachea, bronchi, bronchioles, and lung tissue. Old people have an increased risk of developing LRTIs compared to young adults. The prevalence of LRTIs in the elderly population is not only related to underlying diseases and aging itself, but also to a variety of clinical issues, such as history of hospitalization, previous antibacterial therapy, mechanical ventilation, antibiotic resistance. These factors mentioned above have led to an increase in the prevalence and mortality of LRTIs in the elderly, and new medical strategies targeting LRTIs in this population are urgently needed. After a systematic review of the current randomized controlled trials and related studies, we recommend novel pharmacotherapies that demonstrate advantages for the management of LRTIs in people over the age of 65. We also briefly reviewed current medications for respiratory communicable diseases in the elderly. Various sources of information were used to ensure all relevant studies were included. We searched Pubmed, MEDLINE (OvidSP), EMBASE (OvidSP), and ClinicalTrials.gov. Strengths and limitations of these drugs were evaluated based on whether they have novelty of mechanism, favorable pharmacokinetic/pharmacodynamic profiles, avoidance of interactions and intolerance, simplicity of dosing, and their ability to cope with challenges which was mainly evaluated by the primary and secondary endpoints. The purpose of this review is to recommend the most promising antibiotics for treatment of LRTIs in the elderly (both in hospital and in the outpatient setting) based on the existing results of clinical studies with the novel antibiotics, and to briefly review current medications for respiratory communicable diseases in the elderly, aiming to a better management of LRTIs in clinical practice.
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Affiliation(s)
- Yang Liu
- The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Geriatric Health Care and Medical Research Center, Sichuan University, Chengdu, China
| | - Yan Zhang
- The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Geriatric Health Care and Medical Research Center, Sichuan University, Chengdu, China
| | - Wanyu Zhao
- The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Geriatric Health Care and Medical Research Center, Sichuan University, Chengdu, China
| | - Xiaolei Liu
- The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Geriatric Health Care and Medical Research Center, Sichuan University, Chengdu, China
| | - Fengjuan Hu
- The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Geriatric Health Care and Medical Research Center, Sichuan University, Chengdu, China
| | - Birong Dong
- The Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
- Geriatric Health Care and Medical Research Center, Sichuan University, Chengdu, China
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12
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Li L, Liu Y, Wu P, Peng Z, Wang X, Chen T, Wong JYT, Yang J, Bond HS, Wang L, Lau YC, Zheng J, Feng S, Qin Y, Fang VJ, Jiang H, Lau EHY, Liu S, Qi J, Zhang J, Yang J, He Y, Zhou M, Cowling BJ, Feng L, Yu H. Influenza-associated excess respiratory mortality in China, 2010-15: a population-based study. Lancet Public Health 2019; 4:e473-e481. [PMID: 31493844 PMCID: PMC8736690 DOI: 10.1016/s2468-2667(19)30163-x] [Citation(s) in RCA: 138] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 07/24/2019] [Accepted: 07/30/2019] [Indexed: 01/03/2023]
Abstract
BACKGROUND The estimation of influenza-associated excess mortality in countries can help to improve estimates of the global mortality burden attributable to influenza virus infections. We did a study to estimate the influenza-associated excess respiratory mortality in mainland China for the 2010-11 through 2014-15 seasons. METHODS We obtained provincial weekly influenza surveillance data and population mortality data for 161 disease surveillance points in 31 provinces in mainland China from the Chinese Center for Disease Control and Prevention for the years 2005-15. Disease surveillance points with an annual average mortality rate of less than 0·4% between 2005 and 2015 or an annual mortality rate of less than 0·3% in any given years were excluded. We extracted data for respiratory deaths based on codes J00-J99 under the tenth edition of the International Classification of Diseases. Data on respiratory mortality and population were stratified by age group (age <60 years and ≥60 years) and aggregated by province. The overall annual population data of each province and national annual respiratory mortality data were compiled from the China Statistical Yearbook. Influenza surveillance data on weekly proportion of samples testing positive for influenza virus by type or subtype for 31 provinces were extracted from the National Sentinel Hospital-based Influenza Surveillance Network. We estimated influenza-associated excess respiratory mortality rates between the 2010-11 and 2014-15 seasons for 22 provinces with valid data in the country using linear regression models. Extrapolation of excess respiratory mortality rates was done using random-effect meta-regression models for nine provinces without valid data for a direct estimation of the rates. FINDINGS We fitted the linear regression model with the data from 22 of 31 provinces in mainland China, representing 83·0% of the total population. We estimated that an annual mean of 88 100 (95% CI 84 200-92 000) influenza-associated excess respiratory deaths occurred in China in the 5 years studied, corresponding to 8·2% (95% CI 7·9-8·6) of respiratory deaths. The mean excess respiratory mortality rates per 100 000 person-seasons for influenza A(H1N1)pdm09, A(H3N2), and B viruses were 1·6 (95% CI 1·5-1·7), 2·6 (2·4-2·8), and 2·3 (2·1-2·5), respectively. Estimated excess respiratory mortality rates per 100 000 person-seasons were 1·5 (95% CI 1·1-1·9) for individuals younger than 60 years and 38·5 (36·8-40·2) for individuals aged 60 years or older. Approximately 71 000 (95% CI 67 800-74 100) influenza-associated excess respiratory deaths occurred in individuals aged 60 years or older, corresponding to 80% of such deaths. INTERPRETATION Influenza was associated with substantial excess respiratory mortality in China between 2010-11 and 2014-15 seasons, especially in older adults aged at least 60 years. Continuous and high-quality surveillance data across China are needed to improve the estimation of the disease burden attributable to influenza and the best public health interventions are needed to curb this burden. FUNDING National Science Fund for Distinguished Young Scholars, National Science and Technology Major Project of China, National Institute of Health Research, the Harvard Center for Communicable Disease Dynamics from the National Institute of General Medical Sciences, and the China-US Collaborative Program on Emerging and Re-emerging Infectious Disease.
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Affiliation(s)
- Li Li
- 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
| | - Yunning Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, 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
| | - Zhibin Peng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiling Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Tao Chen
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese CDC, Beijing, China
| | - Jessica Y T Wong
- 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
| | - Juan Yang
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 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
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiu Chung Lau
- 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
| | - Jiandong Zheng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shuo Feng
- 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
| | - Ying Qin
- 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
| | - 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
| | - 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
| | - Eric H Y Lau
- 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
| | - Shiwei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jinlei Qi
- National Center for Chronic and Noncommunicable Disease Control and Prevention, 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
| | - Jing Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese CDC, Beijing, China
| | - Yangni He
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 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
| | - 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.
| | - Hongjie Yu
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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13
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Hu Y, Chu K, Lavis N, Li X, Liang B, Liu S, Shao M, Shu JD, Tabar C, Samson S. Immunogenicity and safety of a trivalent inactivated influenza vaccine produced in Shenzhen, China versus a comparator influenza vaccine: a phase IV randomized study. Hum Vaccin Immunother 2019; 15:1066-1069. [PMID: 30779689 PMCID: PMC6605815 DOI: 10.1080/21645515.2019.1581541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 01/18/2019] [Accepted: 02/01/2019] [Indexed: 11/03/2022] Open
Abstract
Seasonal influenza causes substantial morbidity and mortality in China, which largely results from limited vaccine accessibility and poor vaccination coverage. Since 2013, Sanofi Pasteur's facilities in Shenzhen, China have produced a trivalent inactivated influenza vaccine (Shz-IIV3) for each influenza season according to Chinese pharmacopeia requirements. However, the immunogenicity of Shz-IIV3 has not been compared to existing Chinese trivalent inactivated influenza vaccines (IIV3s). Here, we describe the results of a phase IV, observer-blind, randomized study to evaluate whether the immunogenicity of Shz-IIV3 was non-inferior to a comparator IIV3 (Hualan Biological Engineering Inc) also manufactured and licensed in China. Healthy adults aged 18-59 years were randomly assigned in a 1:1 ratio to receive a single 0.5-mL intramuscular injection of the 2017-2018 Northern Hemisphere formulation of Shz-IIV3 (n = 800) or the comparator IIV3 (n = 799). Between baseline and day 28 after vaccination, hemagglutination inhibition titers for the three vaccine strains increased by at least 4-fold and were of similar magnitude in Shz-IIV3 and comparator IIV3 recipients. The rate of seroconversion or significant increase in titers was 62% to 92% in Shz-IIV3 recipients, and 63% to 91% in comparator IIV3 recipients. Post-vaccination hemagglutination inhibition titers and seroconversion rates for Shz-IIV3 were statistically non-inferior to the comparator IIV3 for all three influenza vaccine strains. Rates of solicited and unsolicited vaccine-related adverse events were similar between the two vaccine groups. These results demonstrated that Shz-IIV3 was as immunogenic and safe in adults as a comparator Chinese IIV3, and support the continued use of Shz-IIV3 in China.
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Affiliation(s)
- Yuemei Hu
- Vaccine Clinical Evaluation Department, Jiangsu Center for Disease Prevention and Control, Nanjing, China
| | - Kai Chu
- Vaccine Clinical Evaluation Department, Jiangsu Center for Disease Prevention and Control, Nanjing, China
| | | | - Xiaoling Li
- Medical Operations, Sanofi Pasteur, Beijing, China
| | - Bill Liang
- Medical Department, Sanofi Pasteur, Beijing, China
| | - Shuzhen Liu
- Division of Respiratory Virus Vaccines, National Institutes for Food and Drug Control, Beijing, China
| | - Ming Shao
- Division of Respiratory Virus Vaccines, National Institutes for Food and Drug Control, Beijing, China
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14
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Abstract
Pandemic influenza remains the single greatest threat to global heath security. Efforts to increase our preparedness, by improving predictions of viral emergence, spread and disease severity, by targeting reduced transmission and improved vaccination and by mitigating health impacts in low- and middle-income countries, should receive renewed urgency.
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Affiliation(s)
- Peter Horby
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK.
- International Severe Acute Respiratory and Emerging Infections Consortium, Oxford, UK.
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15
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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: 2.0] [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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16
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Li L, Wong JY, Wu P, Bond HS, Lau EHY, Sullivan SG, Cowling BJ. Heterogeneity in Estimates of the Impact of Influenza on Population Mortality: A Systematic Review. Am J Epidemiol 2018; 187:378-388. [PMID: 28679157 PMCID: PMC5860627 DOI: 10.1093/aje/kwx270] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 06/22/2017] [Accepted: 06/27/2017] [Indexed: 12/15/2022] Open
Abstract
Influenza viruses are associated with a substantial global burden of morbidity and mortality every year. Estimates of influenza-associated mortality often vary between studies due to differences in study settings, methods, and measurement of outcomes. We reviewed 103 published articles assessing population-based influenza-associated mortality through searches of PubMed and Embase, and we identified considerable variation in the statistical methods used across studies. Studies using regression models with an influenza activity proxy applied 4 approaches to estimate influenza-associated mortality. The estimates increased with age and ranged widely, from -0.3-1.3 and 0.6-8.3 respiratory deaths per 100,000 population for children and adults, respectively, to 4-119 respiratory deaths per 100,000 population for older adults. Meta-regression analysis identified that study design features were associated with the observed variation in estimates. The estimates increased with broader cause-of-death classification and were higher for older adults than for children. The multiplier methods tended to produce lower estimates, while Serfling-type models were associated with higher estimates than other methods. No "average" estimate of excess mortality could reliably be made due to the substantial variability of the estimates, partially attributable to methodological differences in the studies. Standardization of methodology in estimation of influenza-associated mortality would permit improved comparisons in the future.
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Affiliation(s)
- Li Li
- WHO Collaborating Center 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
- WHO Collaborating Center for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Jessica Y Wong
- WHO Collaborating Center 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
| | - Peng Wu
- WHO Collaborating Center 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
| | - Helen S Bond
- WHO Collaborating Center 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
| | - Eric H Y Lau
- WHO Collaborating Center 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
| | - Sheena G Sullivan
- WHO Collaborating Center for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
| | - Benjamin J Cowling
- WHO Collaborating Center 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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17
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Wu S, Wei Z, Greene CM, Yang P, Su J, Song Y, Iuliano AD, Wang Q. Mortality burden from seasonal influenza and 2009 H1N1 pandemic influenza in Beijing, China, 2007-2013. Influenza Other Respir Viruses 2018; 12:88-97. [PMID: 29054110 PMCID: PMC5818349 DOI: 10.1111/irv.12515] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2017] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Data about influenza mortality burden in northern China are limited. This study estimated mortality burden in Beijing associated with seasonal influenza from 2007 to 2013 and the 2009 H1N1 pandemic. METHODS We estimated influenza-associated excess mortality by fitting a negative binomial model using weekly mortality data as the outcome of interest with the percent of influenza-positive samples by type/subtype as predictor variables. RESULTS From 2007 to 2013, an average of 2375 (CI 1002-8688) deaths was attributed to influenza per season, accounting for 3% of all deaths. Overall, 81% of the deaths attributed to influenza occurred in adults aged ≥65 years, and the influenza-associated mortality rate in this age group was higher than the rate among those aged <65 years (113.6 [CI 49.5-397.4] versus 4.4 [CI 1.7-18.6] per 100 000, P < .05). The mortality rate associated with the 2009 H1N1 pandemic in 2009/2010 was comparable to that of seasonal influenza during the seasonal years (19.9 [CI 10.4-33.1] vs 17.2 [CI 7.2-67.5] per 100 000). People aged <65 years represented a greater proportion of all deaths during the influenza A(H1N1)pdm09 pandemic period than during the seasonal epidemics (27.0% vs 17.7%, P < .05). CONCLUSIONS Influenza is an important contributor to mortality in Beijing, especially among those aged ≥65 years. These results support current policies to give priority to older adults for seasonal influenza vaccination and help to define the populations at highest risk for death that could be targeted for pandemic influenza vaccination.
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Affiliation(s)
- Shuangsheng Wu
- Beijing Center for Disease Prevention and ControlBeijingChina
- Beijing Research Center for Preventive MedicineBeijingChina
| | - Zaihua Wei
- Beijing Center for Disease Prevention and ControlBeijingChina
- Beijing Research Center for Preventive MedicineBeijingChina
| | - Carolyn M. Greene
- United States Centers for Disease Control and PreventionAtlantaGeorgia
| | - Peng Yang
- Beijing Center for Disease Prevention and ControlBeijingChina
- Beijing Research Center for Preventive MedicineBeijingChina
| | - Jianting Su
- Beijing Center for Disease Prevention and ControlBeijingChina
- Beijing Research Center for Preventive MedicineBeijingChina
| | - Ying Song
- United States Centers for Disease Control and PreventionAtlantaGeorgia
| | - Angela D. Iuliano
- United States Centers for Disease Control and PreventionAtlantaGeorgia
| | - Quanyi Wang
- Beijing Center for Disease Prevention and ControlBeijingChina
- Beijing Research Center for Preventive MedicineBeijingChina
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The impact of influenza on the health related quality of life in China: an EQ-5D survey. BMC Infect Dis 2017; 17:686. [PMID: 29037172 PMCID: PMC5644056 DOI: 10.1186/s12879-017-2801-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 10/04/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Influenza causes considerable morbidity and mortality in China, but its impact on the health-related quality of life (HRQoL) has not been previously measured. METHODS We conducted a retrospective telephone survey to assess the impact of influenza on the HRQoL among outpatients and inpatients using the EuroQoL EQ-5D-3 L instrument. Participants were individuals with laboratory-confirmed influenza infection registered by the National Influenza-like-illness Surveillance Network in 2013. RESULTS We interviewed 839 of 11,098 eligible influenza patients. After excluding those who were unable to complete the HRQoL for the registered influenza episode, 778 patients were included in the analysis. Both outpatients (n = 529) and inpatients (n = 249) most commonly reported problems with pain/discomfort (71.8% of outpatients and 71.9% of inpatients) and anxiety/depression (62.0% of outpatients and 75.1% of inpatients). For individual influenza outpatients, the mean health utility was 0.6142 (SD 0.2006), and the average quality adjusted life days (QALD) loss was 1.62 (SD 1.84) days. The HRQoL of influenza inpatients was worse (mean health utility 0.5851, SD 0.2197; mean QALD loss 3.51 days, SD 4.25) than that of outpatients (p < 0.05). The presence of underlying medical conditions lowered the HRQoL for both outpatients and inpatients (p < 0.05). CONCLUSIONS Influenza illness had a substantial impact on HRQoL. QALD loss due to an acute influenza episode in younger children was comparable to that due to enterovirus A71-associated hand, foot and mouth disease. Our findings are key inputs into disease burden estimates and cost-effectiveness evaluations of influenza-related interventions in China.
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Guo P, Zhang J, Wang L, Yang S, Luo G, Deng C, Wen Y, Zhang Q. Monitoring seasonal influenza epidemics by using internet search data with an ensemble penalized regression model. Sci Rep 2017; 7:46469. [PMID: 28422149 PMCID: PMC5396076 DOI: 10.1038/srep46469] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 03/20/2017] [Indexed: 02/05/2023] Open
Abstract
Seasonal influenza epidemics cause serious public health problems in China. Search queries-based surveillance was recently proposed to complement traditional monitoring approaches of influenza epidemics. However, developing robust techniques of search query selection and enhancing predictability for influenza epidemics remains a challenge. This study aimed to develop a novel ensemble framework to improve penalized regression models for detecting influenza epidemics by using Baidu search engine query data from China. The ensemble framework applied a combination of bootstrap aggregating (bagging) and rank aggregation method to optimize penalized regression models. Different algorithms including lasso, ridge, elastic net and the algorithms in the proposed ensemble framework were compared by using Baidu search engine queries. Most of the selected search terms captured the peaks and troughs of the time series curves of influenza cases. The predictability of the conventional penalized regression models were improved by the proposed ensemble framework. The elastic net regression model outperformed the compared models, with the minimum prediction errors. We established a Baidu search engine queries-based surveillance model for monitoring influenza epidemics, and the proposed model provides a useful tool to support the public health response to influenza and other infectious diseases.
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Affiliation(s)
- Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Jianjun Zhang
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Li Wang
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Shaoyi Yang
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Ganfeng Luo
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Changyu Deng
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Ye Wen
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou, Guangdong, 515041, People’s Republic of China
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Liu XX, Qin G, Li X, Zhang J, Zhao K, Hu M, Wang XL. Excess mortality associated with influenza after the 2009 H1N1 pandemic in a subtropical city in China, 2010–2015. Int J Infect Dis 2017; 57:54-60. [DOI: 10.1016/j.ijid.2017.01.039] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Revised: 01/25/2017] [Accepted: 01/27/2017] [Indexed: 11/17/2022] Open
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Mo Z, Nong Y, Liu S, Shao M, Liao X, Go K, Lavis N. Immunogenicity and safety of a trivalent inactivated influenza vaccine produced in Shenzhen, China. Hum Vaccin Immunother 2017; 13:1-7. [PMID: 28301266 PMCID: PMC5489275 DOI: 10.1080/21645515.2017.1285475] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
A split-virion trivalent inactivated influenza vaccine produced according to the Chinese pharmacopeia (Shz-IIV3) has been commercially available in China since 2014. Here, we describe the results of a phase IV open-label trial to describe the immunogenicity and safety of the 2014–2015 Northern Hemisphere formulation of Shz-IIV3 in individuals ≥ 6 months of age. Subjects 6–35 months of age received 2 half-doses of Shz-IIV3 (0.25 ml) 28 d apart, and subjects ≥ 3 y of age received a single full dose (0.5 ml). The study included 602 subjects. Except for the A (H3N2) strain in subjects 3–17 years, geometric mean hemagglutination inhibition titer ratios were ≥ 10 and rates of seroconversion/significant increase in titer were ≥ 78% in all age groups. For the H3N2 strain in subjects 3–17 years, the geometric mean titer ratio was 3.8 and the rate of seroconversion/significant increase was 56%. Post-vaccination seroprotection rates were ≥ 88% for all strains in all age groups. The most common solicited reactions were injection-site pain/tenderness and fever, most of which were grade 1 and resolved within 3 d. Vaccine-related unsolicited adverse events were reported only by subjects 6–23 months, most of which were mild abnormal crying and irritability. No vaccine-related serious adverse events and no deaths were reported. No new safety signals or unexpected safety events occurred, although an immediate anaphylactic skin reaction occurred in one subject. This study confirmed that the 2014–2015 Northern Hemisphere formulation of Shz-IIV3 was well tolerated and highly immunogenic in subjects ≥ 6 months of age.
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Affiliation(s)
- Zhaojun Mo
- a Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control , Guangxi , China
| | - Yi Nong
- a Guangxi Zhuang Autonomous Region Center for Disease Prevention and Control , Guangxi , China
| | - Shuzhen Liu
- b National Institutes for Food and Drug Control , Beijing , China
| | - Ming Shao
- b National Institutes for Food and Drug Control , Beijing , China
| | | | - Kerry Go
- d Sanofi Pasteur , Swiftwater , PA , US
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Lv J, Ren ZY, Zhang YY, Liu YE, Gao J, Yao K, Feng D, Li ZY, Feng X, Liu YX, Jia N. Study on age-dependent pre-existing 2009 pandemic influenza virus T and B cell responses from Chinese population. BMC Infect Dis 2017; 17:136. [PMID: 28187750 PMCID: PMC5301333 DOI: 10.1186/s12879-017-2215-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 01/20/2017] [Indexed: 03/07/2023] Open
Abstract
BACKGROUND The outbreak of the 2009 H1N1 influenza pandemic (H1N1pdm) affected thousands of people in Mexico and the United States, and spread rapidly throughout the world from April 2009 to July 2010. To explore the age-specific prevalence of seroprotection against H1N1pdm infection, we estimated pre-existing humoral and cellular immunities of residents in Northern China against H1N1pdm and seasonal H1N1 virus in an age-dependent manner. METHODS Anonymous serum samples were collected from 1425 to 1434 adult healthy individuals before and after the pandemic outbreak, and then grouped by birth year 1913-1990. The antibody titers of H1N1pdm and seasonal H1N1 were determined using microneutralization (MN) assays, and the proportion of seropositive was estimated based on the year of birth. Separately, another 63 blood samples were collected in 2006 and prepared for analysis of virus specific memory B and IFN-γ+ T cells using the ELISpot assays. RESULTS The prevalence of pre-existing H1N1pdm-specific sero-antibodies in the elderly population (>60 years old) was 7.8%. The younger group, aged 19 to 60 years, exhibited a significant increase in seropositivity for H1N1pdm after the pandemic (4.9% before pandemic and 18.9% after pandemic, p < 0.05). The prevalence of H1N1pdm specific MBCs before the pandemic in the elderly (>60 years) and younger populations (<60 years) was 38% (8/21) and 48% (20/42), respectively (p = 0.6). The IFN-γ+ T cell responses to the pandemic and seasonal viruses were significantly lower in the elder group than those in the younger group (<60 years) (p < 0.05). CONCLUSIONS Pre-existing serum antibodies and memory B cells against H1N1pdm were low in all age group, whereas diminished memory T cell responses to this virus were observed in the elderly population both before and after the pandemic.
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Affiliation(s)
- Jin Lv
- The General Hospital of PLA Rocket Force, 16 Xin Jie Kou Wai Street, Hai-Dian District, Beijing, 100088, People's Republic of China
| | - Zhen-Yong Ren
- Beijing Center for Disease Prevention and Control, Beijing, 100013, People's Republic of China
| | - Ying-Ying Zhang
- The General Hospital of PLA Rocket Force, 16 Xin Jie Kou Wai Street, Hai-Dian District, Beijing, 100088, People's Republic of China
| | - Yun-E Liu
- The General Hospital of PLA Rocket Force, 16 Xin Jie Kou Wai Street, Hai-Dian District, Beijing, 100088, People's Republic of China
| | - Jun Gao
- The General Hospital of PLA Rocket Force, 16 Xin Jie Kou Wai Street, Hai-Dian District, Beijing, 100088, People's Republic of China
| | - Kun Yao
- National Development and Reform Commission Hospital, Beijing, People's Republic of China
| | - Dan Feng
- Chinese PLA General Hospital, 28 Fu-Xing Road, Hai-Dian District, Beijing, 10853, People's Republic of China
| | - Zhen-Yuan Li
- The General Hospital of PLA Rocket Force, 16 Xin Jie Kou Wai Street, Hai-Dian District, Beijing, 100088, People's Republic of China
| | - Xin Feng
- The General Hospital of PLA Rocket Force, 16 Xin Jie Kou Wai Street, Hai-Dian District, Beijing, 100088, People's Republic of China.
| | - Yun-Xi Liu
- Chinese PLA General Hospital, 28 Fu-Xing Road, Hai-Dian District, Beijing, 10853, People's Republic of China.
| | - Na Jia
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
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Yang J, Atkins KE, Feng L, Pang M, Zheng Y, Liu X, Cowling BJ, Yu H. Seasonal influenza vaccination in China: Landscape of diverse regional reimbursement policy, and budget impact analysis. Vaccine 2016; 34:5724-5735. [DOI: 10.1016/j.vaccine.2016.10.013] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Revised: 10/02/2016] [Accepted: 10/04/2016] [Indexed: 01/19/2023]
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Caini S, Huang QS, Ciblak MA, Kusznierz G, Owen R, Wangchuk S, Henriques CMP, Njouom R, Fasce RA, Yu H, Feng L, Zambon M, Clara AW, Kosasih H, Puzelli S, Kadjo HA, Emukule G, Heraud JM, Ang LW, Venter M, Mironenko A, Brammer L, Mai LTQ, Schellevis F, Plotkin S, Paget J. Epidemiological and virological characteristics of influenza B: results of the Global Influenza B Study. Influenza Other Respir Viruses 2016; 9 Suppl 1:3-12. [PMID: 26256290 PMCID: PMC4549097 DOI: 10.1111/irv.12319] [Citation(s) in RCA: 146] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
INTRODUCTION Literature on influenza focuses on influenza A, despite influenza B having a large public health impact. The Global Influenza B Study aims to collect information on global epidemiology and burden of disease of influenza B since 2000. METHODS Twenty-six countries in the Southern (n = 5) and Northern (n = 7) hemispheres and intertropical belt (n = 14) provided virological and epidemiological data. We calculated the proportion of influenza cases due to type B and Victoria and Yamagata lineages in each country and season; tested the correlation between proportion of influenza B and maximum weekly influenza-like illness (ILI) rate during the same season; determined the frequency of vaccine mismatches; and described the age distribution of cases by virus type. RESULTS The database included 935 673 influenza cases (2000-2013). Overall median proportion of influenza B was 22·6%, with no statistically significant differences across seasons. During seasons where influenza B was dominant or co-circulated (>20% of total detections), Victoria and Yamagata lineages predominated during 64% and 36% of seasons, respectively, and a vaccine mismatch was observed in ≈25% of seasons. Proportion of influenza B was inversely correlated with maximum ILI rate in the same season in the Northern and (with borderline significance) Southern hemispheres. Patients infected with influenza B were usually younger (5-17 years) than patients infected with influenza A. CONCLUSION Influenza B is a common disease with some epidemiological differences from influenza A. This should be considered when optimizing control/prevention strategies in different regions and reducing the global burden of disease due to influenza.
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Affiliation(s)
- Saverio Caini
- Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands
| | - Q Sue Huang
- Institute of Environmental Science and Research, Wellington, New Zealand
| | | | - Gabriela Kusznierz
- Instituto Nacional de Enfermedades Respiratorias Dr. Emilio Coni, Santa Fe, Argentina
| | - Rhonda Owen
- Department of Health and Ageing, Influenza Surveillance Section, Surveillance Branch, Office of Health Protection, Woden, ACT, Australia
| | - Sonam Wangchuk
- Public Health Laboratory, Department of Public Health, Ministry of Health, Thimphu, Bhutan
| | | | - Richard Njouom
- Service de Virologie, Centre Pasteur du Cameroun, Yaounde, Cameroon
| | - Rodrigo A Fasce
- Sección de Virus Respiratorios y Exantemáticos, Instituto de Salud Pública de Chile, Santiago de Chile, Chile
| | - 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
| | - Luzhao Feng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Maria Zambon
- Respiratory Virus Unit, Public Health England, Colindale, UK
| | - Alexey W Clara
- US Centers for Disease Control, Central American Region, Guatemala City, Guatemala
| | - Herman Kosasih
- US Naval Medical Research Unit No. 2, Jakarta, Indonesia
| | - Simona Puzelli
- National Influenza Center, Istituto Superiore Sanità, Rome, Italy
| | - Herve A Kadjo
- Respiratory Viruses Unit, Pasteur Institute of Côte d'Ivoire, Abidjan, Côte d'Ivoire
| | - Gideon Emukule
- US Centers for Disease Control and Prevention, Nairobi, Kenya
| | - Jean-Michel Heraud
- National Influenza Center, Virology Unit, Institut Pasteur of Madagascar, Antananarivo, Madagascar
| | - Li Wei Ang
- Epidemiology and Disease Control Division, Ministry of Health, Singapore, Singapore
| | - Marietjie Venter
- Global Disease Detection, US-CDC, Pretoria, South Africa.,Zoonoses Research Unit, Department of Medical Virology, University of Pretoria, Pretoria, South Africa
| | - Alla Mironenko
- L.V.Gromashevsky Institute of Epidemiology and Infectious Diseases National Academy of Medical Science of Ukraine, Kiev, Ukraine
| | - Lynnette Brammer
- Epidemiology and Prevention Branch, Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - François Schellevis
- Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands
| | | | - John Paget
- Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands
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Temporal Patterns of Influenza A and B in Tropical and Temperate Countries: What Are the Lessons for Influenza Vaccination? PLoS One 2016; 11:e0152310. [PMID: 27031105 PMCID: PMC4816507 DOI: 10.1371/journal.pone.0152310] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 03/11/2016] [Indexed: 12/28/2022] Open
Abstract
Introduction Determining the optimal time to vaccinate is important for influenza vaccination programmes. Here, we assessed the temporal characteristics of influenza epidemics in the Northern and Southern hemispheres and in the tropics, and discuss their implications for vaccination programmes. Methods This was a retrospective analysis of surveillance data between 2000 and 2014 from the Global Influenza B Study database. The seasonal peak of influenza was defined as the week with the most reported cases (overall, A, and B) in the season. The duration of seasonal activity was assessed using the maximum proportion of influenza cases during three consecutive months and the minimum number of months with ≥80% of cases in the season. We also assessed whether co-circulation of A and B virus types affected the duration of influenza epidemics. Results 212 influenza seasons and 571,907 cases were included from 30 countries. In tropical countries, the seasonal influenza activity lasted longer and the peaks of influenza A and B coincided less frequently than in temperate countries. Temporal characteristics of influenza epidemics were heterogeneous in the tropics, with distinct seasonal epidemics observed only in some countries. Seasons with co-circulation of influenza A and B were longer than influenza A seasons, especially in the tropics. Discussion Our findings show that influenza seasonality is less well defined in the tropics than in temperate regions. This has important implications for vaccination programmes in these countries. High-quality influenza surveillance systems are needed in the tropics to enable decisions about when to vaccinate.
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Sex and Age Differences in Mortality in Southern China, 2004-2010. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2015; 12:7886-98. [PMID: 26184261 PMCID: PMC4515697 DOI: 10.3390/ijerph120707886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Revised: 06/17/2015] [Accepted: 06/17/2015] [Indexed: 11/16/2022]
Abstract
The purpose of this study was to describe the mortality patterns in the southern provinces of China, and to provide epidemiologic data on sex and age differences of death outcomes. Reliable mortality and population data from January 2004 to December 2010 were obtained from 12 Disease Surveillance Point (DSP) sites in four provinces of China. Death data from all causes and respiratory disease, chronic obstructive pulmonary disease (COPD), pneumonia and influenza, circulatory disease, and ischemic heart disease, were stratified by year, month of death occurrence and sex, seven age groups, and summarized by descriptive statistics. The mean annual mortality rates of the selected 12 DSP sites in the southernmost provinces of China were 543.9 (range: 423.9-593.6) deaths per 100,000 population. The death rates show that noted sex differences were higher in the male population for all-cause, COPD and circulatory diseases. Pneumonia and influenza death rates present a different sex- and age-related distribution, with higher rates in male aged 65-74 years; whereas the death rates were opposite in elderly aged ≥75 years, and relatively higher in young children. This study had practical implications for recommending target groups for public health interventions.
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Feng L, Yang P, Zhang T, Yang J, Fu C, Qin Y, Zhang Y, Ma C, Liu Z, Wang Q, Zhao G, Yu H. Technical guidelines for the application of seasonal influenza vaccine in China (2014-2015). Hum Vaccin Immunother 2015; 11:2077-101. [PMID: 26042462 PMCID: PMC4635867 DOI: 10.1080/21645515.2015.1027470] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 03/05/2015] [Indexed: 10/23/2022] Open
Abstract
Influenza, caused by the influenza virus, is a respiratory infectious disease that can severely affect human health. Influenza viruses undergo frequent antigenic changes, thus could spread quickly. Influenza causes seasonal epidemics and outbreaks in public gatherings such as schools, kindergartens, and nursing homes. Certain populations are at risk for severe illness from influenza, including pregnant women, young children, the elderly, and people in any ages with certain chronic diseases.
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Affiliation(s)
- 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
| | - Peng Yang
- Beijing Center for Disease Control and Prevention; Beijing, China
| | - Tao Zhang
- School of Public Health; Fudan University; Shanghai, China
| | - Juan Yang
- Key Laboratory of Surveillance and Early-warning on Infectious Disease; Division of Infectious Disease; Chinese Center for Disease Control and Prevention; Beijing, China
| | - Chuanxi Fu
- Guangzhou Center for Disease Control and Prevention; Guangzhou, 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
| | - Yi Zhang
- Beijing Center for Disease Control and Prevention; Beijing, China
| | - Chunna Ma
- Beijing Center for Disease Control and Prevention; Beijing, China
| | - Zhaoqiu Liu
- Hua Xin Hospital; First Hospital of Tsinghua University; Beijing, China
| | - Quanyi Wang
- Beijing Center for Disease Control and Prevention; Beijing, China
| | - Genming Zhao
- School of Public Health; Fudan University; Shanghai, China
| | - Hongjie Yu
- Key Laboratory of Surveillance and Early-warning on Infectious Disease; Division of Infectious Disease; Chinese Center for Disease Control and Prevention; Beijing, China
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Tang D, Wang C, Nie J, Chen R, Niu Q, Kan H, Chen B, Perera F. Health benefits of improving air quality in Taiyuan, China. ENVIRONMENT INTERNATIONAL 2014; 73:235-242. [PMID: 25168129 DOI: 10.1016/j.envint.2014.07.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2014] [Revised: 07/21/2014] [Accepted: 07/22/2014] [Indexed: 06/03/2023]
Abstract
Since 2000, the government in Shanxi province has mounted several initiatives and mandated factory shutdowns with the goal of reducing coal burning emissions and the environmental impacts of industrialization. We estimated the health benefits associated with air quality improvement from 2001 to 2010 in Taiyuan, Shanxi Province, using disability-adjusted life years (DALYs) and monetized the health benefits using value of statistical life (VOSL). Data were collected on annual average concentrations of particulate matter less than 10 μm in aerodynamic diameter (PM10) and relevant health outcomes in Taiyuan from 2001 to 2010. Selected exposure-response functions were used to calculate the cases of death or disease attributable to PM10 annually over a 10-year period. These were summed to calculate the DALYs lost and their monetary value associated with PM10 each year between 2001 and 2010. Air quality improvement from 2001 to 2010 was estimated to have prevented 2810 premature deaths, 951 new cases of chronic bronchitis, 141,457 cases of outpatient visits, 969 cases of emergency-room visits and 31,810 cases of hospital admissions. The DALYs (VOSL) decreased by 56.92% (52.68%) from 52,937 (7274 million Yuan) in 2001 to 22,807 (3442 million Yuan) in 2010. Premature deaths accounted for almost 95% of the total DALYs. Our analysis demonstrates that air pollution abatement during the last decade in Taiyuan has generated substantial health benefits.
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Affiliation(s)
- Deliang Tang
- Shanxi Medical University, PR China; Columbia Center for Children's Environmental Health, United States.
| | - Cuicui Wang
- Fudan University School of Public Health, PR China
| | | | - Renjie Chen
- Fudan University School of Public Health, PR China
| | - Qiao Niu
- Shanxi Medical University, PR China
| | - Haidong Kan
- Fudan University School of Public Health, PR China.
| | | | - Frederica Perera
- Columbia Center for Children's Environmental Health, United States
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Yang P, Thompson MG, Ma C, Shi W, Wu S, Zhang D, Wang Q. Influenza vaccine effectiveness against medically-attended influenza illness during the 2012-2013 season in Beijing, China. Vaccine 2014; 32:5285-9. [PMID: 25092635 DOI: 10.1016/j.vaccine.2014.07.083] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2014] [Revised: 07/08/2014] [Accepted: 07/22/2014] [Indexed: 12/23/2022]
Abstract
BACKGROUND Influenza vaccine coverage remains low in China, and there is limited information on the preventive value of local vaccination programs. METHODS As part of influenza virological surveillance in Beijing, China during the 2012-2013 influenza season, we assessed the vaccine effectiveness (VE) of one or more doses of trivalent inactivated influenza vaccine (IIV3) in preventing medically-attended influenza-like-illness (ILI) associated with laboratory-confirmed influenza virus infection using a test-negative case-control design. Influenza vaccination was determined based on self-report by adult patients or the parents of child patients. RESULTS Of 1998 patients with ILI, 695 (35%) tested positive for influenza viruses, including 292 (42%) A(H3N2), 398 (57%) A(H1N1)pdm09, and 5 (1%) not (sub)typed influenza viruses. The rate of influenza vaccination among all patients was 4% (71/1998). Among influenza positive patients, 2% (57/1303) were vaccinated compared to 4% (14/695) among influenza negative patients, resulting in VE for one or more doses of vaccine (adjusted for age, sex, week, and days since illness onset) against all circulating influenza viruses of 52% (95% CI=12-74%). A significant adjusted VE for one or more doses of vaccine for all ages against A(H1N1)pdm09 of 59% (95% CI, 8-82%) was observed; however, the VE against A(H3N2) was 43% (95% CI, -30% to 75%). The point estimate of VE was 59% (95% CI, 19-79%) for those aged <60 years, but a negative VE point estimate without statistical significance was observed among those aged ≥60 years. CONCLUSIONS IIV3 conferred moderate protection against medically-attended influenza in Beijing, China during the 2012-2013 season, especially against the A(H1N1)pdm09 strain and among those aged <60 years old.
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Affiliation(s)
- Peng Yang
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Mark G Thompson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Chunna Ma
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Weixian Shi
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Shuangsheng Wu
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Daitao Zhang
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Quanyi Wang
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China.
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Feng L, Li Z, Zhao S, Nair H, Lai S, Xu W, Li M, Wu J, Ren L, Liu W, Yuan Z, Chen Y, Wang X, Zhao Z, Zhang H, Li F, Ye X, Li S, Feikin D, Yu H, Yang W. Viral etiologies of hospitalized acute lower respiratory infection patients in China, 2009-2013. PLoS One 2014; 9:e99419. [PMID: 24945280 PMCID: PMC4063718 DOI: 10.1371/journal.pone.0099419] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2014] [Accepted: 05/14/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Acute lower respiratory infections (ALRIs) are an important cause of acute illnesses and mortality worldwide and in China. However, a large-scale study on the prevalence of viral infections across multiple provinces and seasons has not been previously reported from China. Here, we aimed to identify the viral etiologies associated with ALRIs from 22 Chinese provinces. METHODS AND FINDINGS Active surveillance for hospitalized ALRI patients in 108 sentinel hospitals in 24 provinces of China was conducted from January 2009-September 2013. We enrolled hospitalized all-age patients with ALRI, and collected respiratory specimens, blood or serum collected for diagnostic testing for respiratory syncytial virus (RSV), human influenza virus, adenoviruses (ADV), human parainfluenza virus (PIV), human metapneumovirus (hMPV), human coronavirus (hCoV) and human bocavirus (hBoV). We included 28,369 ALRI patients from 81 (of the 108) sentinel hospitals in 22 (of the 24) provinces, and 10,387 (36.6%) were positive for at least one etiology. The most frequently detected virus was RSV (9.9%), followed by influenza (6.6%), PIV (4.8%), ADV (3.4%), hBoV (1.9), hMPV (1.5%) and hCoV (1.4%). Co-detections were found in 7.2% of patients. RSV was the most common etiology (17.0%) in young children aged <2 years. Influenza viruses were the main cause of the ALRIs in adults and elderly. PIV, hBoV, hMPV and ADV infections were more frequent in children, while hCoV infection was distributed evenly in all-age. There were clear seasonal peaks for RSV, influenza, PIV, hBoV and hMPV infections. CONCLUSIONS Our findings could serve as robust evidence for public health authorities in drawing up further plans to prevent and control ALRIs associated with viral pathogens. RSV is common in young children and prevention measures could have large public health impact. Influenza was most common in adults and influenza vaccination should be implemented on a wider scale in China.
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Affiliation(s)
- Luzhao Feng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Zhongjie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Shiwen Zhao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
| | - Harish Nair
- Centre for Population Health Sciences, Global Health Academy, The University of Edinburgh, Edinburgh, United Kingdom
- Public Health Foundation of India, New Delhi, India
| | - Shengjie Lai
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Wenbo Xu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mengfeng Li
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-Sen University, Guangzhou, China
| | - Jianguo Wu
- State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China
| | - Lili Ren
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wei Liu
- Beijing Institute of Microbiology and Epidemiology, State Key Laboratory of Pathogen and Biosecurity, Beijing, China
| | | | - Yu Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xinhua Wang
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Zhuo Zhao
- Liaoning Provincial Center for Disease Control and Prevention, Shenyang, China
| | - Honglong Zhang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Fu Li
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-Sen University, Guangzhou, China
| | - Xianfei Ye
- Shanghai Public Health Clinical Center, Shanghai, China
| | - Sa Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Daniel Feikin
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Hongjie Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (HY)
| | - Weizhong Yang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
- * E-mail: (WY); (HY)
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31
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Green HK, Andrews N, Fleming D, Zambon M, Pebody R. Mortality attributable to influenza in England and Wales prior to, during and after the 2009 pandemic. PLoS One 2013; 8:e79360. [PMID: 24348993 PMCID: PMC3859479 DOI: 10.1371/journal.pone.0079360] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2013] [Accepted: 09/30/2013] [Indexed: 11/19/2022] Open
Abstract
Very different influenza seasons have been observed from 2008/09-2011/12 in England and Wales, with the reported burden varying overall and by age group. The objective of this study was to estimate the impact of influenza on all-cause and cause-specific mortality during this period. Age-specific generalised linear regression models fitted with an identity link were developed, modelling weekly influenza activity through multiplying clinical influenza-like illness consultation rates with proportion of samples positive for influenza A or B. To adjust for confounding factors, a similar activity indicator was calculated for Respiratory Syncytial Virus. Extreme temperature and seasonal trend were controlled for. Following a severe influenza season in 2008/09 in 65+yr olds (estimated excess of 13,058 influenza A all-cause deaths), attributed all-cause mortality was not significant during the 2009 pandemic in this age group and comparatively low levels of influenza A mortality were seen in post-pandemic seasons. The age shift of the burden of seasonal influenza from the elderly to young adults during the pandemic continued into 2010/11; a comparatively larger impact was seen with the same circulating A(H1N1)pdm09 strain, with the burden of influenza A all-cause excess mortality in 15-64 yr olds the largest reported during 2008/09-2011/12 (436 deaths in 15-44 yr olds and 1,274 in 45-64 yr olds). On average, 76% of seasonal influenza A all-age attributable deaths had a cardiovascular or respiratory cause recorded (average of 5,849 influenza A deaths per season), with nearly a quarter reported for other causes (average of 1,770 influenza A deaths per season), highlighting the importance of all-cause as well as cause-specific estimates. No significant influenza B attributable mortality was detected by season, cause or age group. This analysis forms part of the preparatory work to establish a routine mortality monitoring system ahead of introduction of the UK universal childhood seasonal influenza vaccination programme in 2013/14.
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Affiliation(s)
- Helen K. Green
- Respiratory Diseases Department, Centre for Infectious Disease Surveillance and Control, Public Health England, London, United Kingdom
| | - Nick Andrews
- Statistics Department, Centre for Infectious Disease Surveillance and Control, Public Health England, London, United Kingdom
| | - Douglas Fleming
- Birmingham Research Unit, Royal College of General Practitioners, Birmingham, United Kingdom
| | - Maria Zambon
- Respiratory Virus Unit, Virus Reference Department, Microbiology Services, Public Health England, London, United Kingdom
| | - Richard Pebody
- Respiratory Diseases Department, Centre for Infectious Disease Surveillance and Control, Public Health England, London, United Kingdom
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Abstract
Background Poisson regression modelling has been widely used to estimate the disease burden attributable to influenza, though not without concerns that some of the excess burden could be due to other causes. This study aims to provide annual estimates of the mortality and hospitalization burden attributable to both seasonal influenza and the 2009 A/H1N1 pandemic influenza for Canada, and to discuss issues related to the reliability of these estimates. Methods Weekly time-series for all-cause mortality and regression models were used to estimate the number of deaths in Canada attributable to influenza from September 1992 to December 2009. To assess their robustness, the annual estimates derived from different parameterizations of the regression model for all-cause mortality were compared. In addition, the association between the annual estimates for mortality and hospitalization by age group, underlying cause of death or primary reason for admission and discharge status is discussed. Results The crude influenza-attributed mortality rate based on all-cause mortality and averaged over 17 influenza seasons prior to the 2009 A/H1N1 pandemic was 11.3 (95%CI, 10.5 - 12.1) deaths per 100 000 population per year, or an average of 3,500 (95%CI, 3,200 - 3,700) deaths per year attributable to seasonal influenza. The estimated annual rates ranged from undetectable at the ecological level to more than 6000 deaths per year over the three A/Sydney seasons. In comparison, we attributed an estimated 740 deaths (95%CI, 350–1500) to A(H1N1)pdm09. Annual estimates from different model parameterizations were strongly correlated, as were estimates for mortality and morbidity; the higher A(H1N1)pdm09 burden in younger age groups was the most notable exception. Interpretation With the exception of some of the Serfling models, differences in the ecological estimates of the disease burden attributable to influenza were small in comparison to the variation in disease burden from one season to another.
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Yu H, Alonso WJ, Feng L, Tan Y, Shu Y, Yang W, Viboud C. Characterization of regional influenza seasonality patterns in China and implications for vaccination strategies: spatio-temporal modeling of surveillance data. PLoS Med 2013; 10:e1001552. [PMID: 24348203 PMCID: PMC3864611 DOI: 10.1371/journal.pmed.1001552] [Citation(s) in RCA: 194] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2013] [Accepted: 10/10/2013] [Indexed: 10/29/2022] Open
Abstract
BACKGROUND The complexity of influenza seasonal patterns in the inter-tropical zone impedes the establishment of effective routine immunization programs. China is a climatologically and economically diverse country, which has yet to establish a national influenza vaccination program. Here we characterize the diversity of influenza seasonality in China and make recommendations to guide future vaccination programs. METHODS AND FINDINGS We compiled weekly reports of laboratory-confirmed influenza A and B infections from sentinel hospitals in cities representing 30 Chinese provinces, 2005-2011, and data on population demographics, mobility patterns, socio-economic, and climate factors. We applied linear regression models with harmonic terms to estimate influenza seasonal characteristics, including the amplitude of annual and semi-annual periodicities, their ratio, and peak timing. Hierarchical Bayesian modeling and hierarchical clustering were used to identify predictors of influenza seasonal characteristics and define epidemiologically-relevant regions. The annual periodicity of influenza A epidemics increased with latitude (mean amplitude of annual cycle standardized by mean incidence, 140% [95% CI 128%-151%] in the north versus 37% [95% CI 27%-47%] in the south, p<0.0001). Epidemics peaked in January-February in Northern China (latitude ≥33°N) and April-June in southernmost regions (latitude <27°N). Provinces at intermediate latitudes experienced dominant semi-annual influenza A periodicity with peaks in January-February and June-August (periodicity ratio >0.6 in provinces located within 27.4°N-31.3°N, slope of latitudinal gradient with latitude -0.016 [95% CI -0.025 to -0.008], p<0.001). In contrast, influenza B activity predominated in colder months throughout most of China. Climate factors were the strongest predictors of influenza seasonality, including minimum temperature, hours of sunshine, and maximum rainfall. Our main study limitations include a short surveillance period and sparse influenza sampling in some of the southern provinces. CONCLUSIONS Regional-specific influenza vaccination strategies would be optimal in China; in particular, annual campaigns should be initiated 4-6 months apart in Northern and Southern China. Influenza surveillance should be strengthened in mid-latitude provinces, given the complexity of seasonal patterns in this region. More broadly, our findings are consistent with the role of climatic factors on influenza transmission dynamics. Please see later in the article for the Editors' Summary.
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Affiliation(s)
- Hongjie Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Wladimir J. Alonso
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Luzhao Feng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Yi Tan
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Yuelong Shu
- National Institute for Viral Disease Control and Prevention, China CDC, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, China
| | - Weizhong Yang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Centre for Disease Control and Prevention, Beijing, China
- * E-mail: (CV); (WY)
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (CV); (WY)
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Simonsen L, Spreeuwenberg P, Lustig R, Taylor RJ, Fleming DM, Kroneman M, Van Kerkhove MD, Mounts AW, Paget WJ. Global mortality estimates for the 2009 Influenza Pandemic from the GLaMOR project: a modeling study. PLoS Med 2013; 10:e1001558. [PMID: 24302890 PMCID: PMC3841239 DOI: 10.1371/journal.pmed.1001558] [Citation(s) in RCA: 305] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2013] [Accepted: 10/15/2013] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries. METHODS AND FINDINGS We obtained weekly virology and underlying cause-of-death mortality time series for 2005-2009 for 20 countries covering ∼35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%-85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000-249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons <65 y. Limitations include lack of representation of low-income countries among single-country estimates and an inability to study subsequent pandemic waves (2010-2012). CONCLUSIONS We estimate that 2009 global pandemic respiratory mortality was ∼10-fold higher than the World Health Organization's laboratory-confirmed mortality count. Although the pandemic mortality estimate was similar in magnitude to that of seasonal influenza, a marked shift toward mortality among persons <65 y of age occurred, so that many more life-years were lost. The burden varied greatly among countries, corroborating early reports of far greater pandemic severity in the Americas than in Australia, New Zealand, and Europe. A collaborative network to collect and analyze mortality and hospitalization surveillance data is needed to rapidly establish the severity of future pandemics. Please see later in the article for the Editors' Summary.
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Affiliation(s)
- Lone Simonsen
- Department of Global Health, George Washington University School of Public Health and Health Services, Washington, District of Columbia, United States of America
- Sage Analytica, Bethesda, Maryland, United States of America
- * E-mail:
| | | | - Roger Lustig
- Sage Analytica, Bethesda, Maryland, United States of America
| | | | | | - Madelon Kroneman
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Maria D. Van Kerkhove
- Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College, London, United Kingdom
- Global Influenza Programme, World Health Organization, Geneva, Switzerland
| | - Anthony W. Mounts
- Global Influenza Programme, World Health Organization, Geneva, Switzerland
| | - W. John Paget
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
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Grefenstette JJ, Brown ST, Rosenfeld R, DePasse J, Stone NTB, Cooley PC, Wheaton WD, Fyshe A, Galloway DD, Sriram A, Guclu H, Abraham T, Burke DS. FRED (a Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC Public Health 2013; 13:940. [PMID: 24103508 PMCID: PMC3852955 DOI: 10.1186/1471-2458-13-940] [Citation(s) in RCA: 96] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2013] [Accepted: 09/25/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mathematical and computational models provide valuable tools that help public health planners to evaluate competing health interventions, especially for novel circumstances that cannot be examined through observational or controlled studies, such as pandemic influenza. The spread of diseases like influenza depends on the mixing patterns within the population, and these mixing patterns depend in part on local factors including the spatial distribution and age structure of the population, the distribution of size and composition of households, employment status and commuting patterns of adults, and the size and age structure of schools. Finally, public health planners must take into account the health behavior patterns of the population, patterns that often vary according to socioeconomic factors such as race, household income, and education levels. RESULTS FRED (a Framework for Reconstructing Epidemic Dynamics) is a freely available open-source agent-based modeling system based closely on models used in previously published studies of pandemic influenza. This version of FRED uses open-access census-based synthetic populations that capture the demographic and geographic heterogeneities of the population, including realistic household, school, and workplace social networks. FRED epidemic models are currently available for every state and county in the United States, and for selected international locations. CONCLUSIONS State and county public health planners can use FRED to explore the effects of possible influenza epidemics in specific geographic regions of interest and to help evaluate the effect of interventions such as vaccination programs and school closure policies. FRED is available under a free open source license in order to contribute to the development of better modeling tools and to encourage open discussion of modeling tools being used to evaluate public health policies. We also welcome participation by other researchers in the further development of FRED.
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Affiliation(s)
- John J Grefenstette
- Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
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Yu H, Feng L, Viboud CG, Shay DK, Jiang Y, Zhou H, Zhou M, Xu Z, Hu N, Yang W, Nie S. Regional variation in mortality impact of the 2009 A(H1N1) influenza pandemic in China. Influenza Other Respir Viruses 2013; 7:1350-60. [PMID: 23668477 PMCID: PMC4634298 DOI: 10.1111/irv.12121] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/15/2013] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Laboratory-confirmed deaths grossly underestimate influenza mortality burden, so that reliable burden estimates are derived from indirect statistical studies, which are scarce in low- and middle-income settings. OBJECTIVES Here, we used statistical excess mortality models to estimate the burden of seasonal and pandemic influenza in China. METHODS We modeled data from a nationally representative population-based death registration system, combined with influenza virological surveillance data, to estimate influenza-associated excess mortality for the 2004-2005 through 2009-2010 seasons, by age and region. RESULTS The A(H1N1) pandemic was associated with 11·4-12·1 excess respiratory and circulatory (R&C) deaths per 100,000 population in rural sites of northern and southern China during 2009-2010; these rates were 2·2-2·8 times higher than those of urban sites (P<0·01). Influenza B accounted for a larger proportion of deaths than pandemic A(H1N1) in 2009-2010 in some regions. Nationally, we attribute 126,200 (95% CI, 61,000-248,400) excess R&C deaths (rate of 9·4/100,000) and 2,323,000 (1,166,000-4,533,000) years of life lost (YLL) to the first year of A(H1N1)pdm circulation. CONCLUSIONS The A(H1N1) pandemic posed a mortality and YLL burden comparable to that of interpandemic influenza in China. Our high burden estimates in rural areas highlight the need to enhance epidemiological surveillance and healthcare services, in underdeveloped and remote areas.
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Affiliation(s)
- Hongjie Yu
- Department of Epidemiology and Statistics, Public Health School, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
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