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Kou Z, Li X, Liu T, Fan B, An W, An W, Dang M, Zhang K, Tang J, Zhu N, Pan R. A post-marketing study to evaluate the safety and immunogenicity of a quadrivalent influenza split-virion vaccine in elderly people aged 60 years and older. Trop Dis Travel Med Vaccines 2024; 10:18. [PMID: 39277739 PMCID: PMC11402193 DOI: 10.1186/s40794-024-00228-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 06/20/2024] [Indexed: 09/17/2024] Open
Abstract
BACKGROUND Influenza remains a global public health concern. Understanding the vaccination-induced response in an aging population, which is susceptible and at high risk, is essential for disease prevention and control. Here, we report findings on the safety and immunogenicity of a quadrivalent influenza split-virion vaccine (15 µg/subtype/0.5 ml/dose) (hereinafter referred to as the "quadrivalent influenza vaccine") in a population aged ≥ 60 years. METHODS This open-label, pragmatic post-marketing trial enrolled 1399 older adults to receive one dose of an approved commercially available quadrivalent influenza vaccine manufactured by Hualan Biological Bacterin Inc. (hereinafter referred to as "Hualan Bio"). Participants with contraindications for the vaccine were excluded, while poor health condition was acceptable. All vaccinated subjects experienced adverse events collection within 30 days and serious adverse events within 180 days post-vaccination. 25% subjects, selected randomly, underwent venous blood sampling pre-vaccination and 30 days after post-vaccination, for detecting antibody titers against each subtype of influenza virus by hemagglutination inhibition assay. The incidences of adverse events and antibody titers against each subtype of influenza virus were statistically analyzed using SAS 9.4. RESULTS No grade 3 adverse reactions occurred within 30 days post-vaccination. The incidences of overall adverse reactions, local adverse reactions and systemic adverse reactions were 3.79%, 2.86% and 1.00%, respectively. No serious adverse reactions occurred within 180 days post-vaccination. There were 350 subjects who completed venous blood sampling pre-vaccination, among whom 348 subjects completed venous blood sampling at 30 days post-vaccination for immunogenicity assessment. With respect to hemagglutination inhibition antibodies against influenza viruses H1N1, H3N2, BV and BY subtypes, at 30 days post-vaccination, the seroconversion rates were 87.64%, 75.57%, 73.28% and 78.74%, respectively; the seropositive rates were 93.97%, 98.56%, 79.31% and 95.40%, respectively; and the geometric mean increase (GMI) in post-immunization/pre-immunization antibodies was 24.80, 7.26, 10.39 and 7.39, respectively. CONCLUSION One 15 µg/subtype dose of the vaccine had a good safety profile and elicited favorable immunogenicity among subjects aged ≥ 60 years. The results of this study indicate that Hualan Bio quadrivalent influenza vaccine strike balance between safety and immunogenicity, supporting unnecessity to increase dosage or inoculation frequency for further enhancing immunogenicity. TRIAL REGISTRATION Registered on ClinicalTrials.gov. REGISTRATION NUMBER NCT06334510. Registered on 28/03/2024 (retrospectively registered).
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Affiliation(s)
- Zengqiang Kou
- Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Xiaoyu Li
- National Institutes for Food and Drug Control, Beijing, 102600, China
| | - Ti Liu
- Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Bei Fan
- Hualan Biological Engineering Inc, Xinxiang, 453003, China
| | - Wenqi An
- Hualan Biological Engineering Inc, Xinxiang, 453003, China
| | - Wenjue An
- Hualan Biological Bacterin Inc, No. 1-1, Hualan Avenue, Xinxiang City, Henan Province, 453003, China
| | - Mingan Dang
- Henan Center for Drug Evaluation and Inspection, Zhengzhou, 450008, China
| | - Ke Zhang
- Hualan Biological Bacterin Inc, No. 1-1, Hualan Avenue, Xinxiang City, Henan Province, 453003, China
| | - Jingning Tang
- Hualan Biological Bacterin Inc, No. 1-1, Hualan Avenue, Xinxiang City, Henan Province, 453003, China
| | - Nan Zhu
- Hualan Biological Bacterin Inc, No. 1-1, Hualan Avenue, Xinxiang City, Henan Province, 453003, China
| | - Ruowen Pan
- Hualan Biological Bacterin Inc, No. 1-1, Hualan Avenue, Xinxiang City, Henan Province, 453003, China.
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Yin TL, Chen N, Zhang JY, Yang S, Li WM, Gao XH, Shi HL, Hu HP. Excess multi-cause mortality linked to influenza virus infection in China, 2012-2021: a population-based study. Front Public Health 2024; 12:1399672. [PMID: 38887242 PMCID: PMC11182332 DOI: 10.3389/fpubh.2024.1399672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/15/2024] [Indexed: 06/20/2024] Open
Abstract
Objectives The aim of this study is to estimate the excess mortality burden of influenza virus infection in China from 2012 to 2021, with a concurrent analysis of its associated disease manifestations. Methods Laboratory surveillance data on influenza, relevant population demographics, and mortality records, including cause of death data in China, spanning the years 2012 to 2021, were incorporated into a comprehensive analysis. A negative binomial regression model was utilized to calculate the excess mortality rate associated with influenza, taking into consideration factors such as year, subtype, and cause of death. Results There was no evidence to indicate a correlation between malignant neoplasms and any subtype of influenza, despite the examination of the effect of influenza on the mortality burden of eight diseases. A total of 327,520 samples testing positive for influenza virus were isolated between 2012 and 2021, with a significant decrease in the positivity rate observed during the periods of 2012-2013 and 2019-2020. China experienced an average annual influenza-associated excess deaths of 201721.78 and an average annual excess mortality rate of 14.53 per 100,000 people during the research period. Among the causes of mortality that were examined, respiratory and circulatory diseases (R&C) accounted for the most significant proportion (58.50%). Fatalities attributed to respiratory and circulatory diseases exhibited discernible temporal patterns, whereas deaths attributable to other causes were dispersed over the course of the year. Conclusion Theoretically, the contribution of these disease types to excess influenza-related fatalities can serve as a foundation for early warning and targeted influenza surveillance. Additionally, it is possible to assess the costs of prevention and control measures and the public health repercussions of epidemics with greater precision.
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Affiliation(s)
- Tian-Lu Yin
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ning Chen
- School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jin-Yao Zhang
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shuang Yang
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wei-Min Li
- Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Beijing, China
| | - Xiao-Huan Gao
- Medical College, Hebei Engineering University, Hebei, China
| | - Hao-Lin Shi
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hong-Pu Hu
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 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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Geospatial epidemiology of hospitalized patients with a positive influenza assay: A nationwide study in Iran, 2016-2018. PLoS One 2022; 17:e0278900. [PMID: 36512615 PMCID: PMC9747007 DOI: 10.1371/journal.pone.0278900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 11/24/2022] [Indexed: 12/15/2022] Open
Abstract
INTRODUCTION Seasonal influenza is a significant public health challenge worldwide. This study aimed to investigate the epidemiological characteristics and spatial patterns of severe hospitalized influenza cases confirmed by polymerase chain reaction (PCR) in Iran. METHODS Data were obtained from Iran's Ministry of Health and Medical Education and included all hospitalized lab-confirmed influenza cases from January 1, 2016, to December 30, 2018 (n = 9146). The Getis-Ord Gi* and Local Moran's I statistics were used to explore the hotspot areas and spatial cluster/outlier patterns of influenza. We also built a multivariable logistic regression model to identify covariates associated with patients' mortality. RESULTS Cumulative incidence and mortality rate were estimated at 11.44 and 0.49 (per 100,000), respectively, and case fatality rate was estimated at 4.35%. The patients' median age was 40 (interquartile range: 22-63), and 55.5% (n = 5073) were female. The hotspot and cluster analyses revealed high-risk areas in northern parts of Iran, especially in cold, humid, and densely populated areas. Moreover, influenza hotspots were more common during the colder months of the year, especially in high-elevated regions. Mortality was significantly associated with older age (adjusted odds ratio [aOR]: 1.01, 95% confidence interval [CI]: 1.01-1.02), infection with virus type-A (aOR: 1.64, 95% CI: 1.27-2.15), male sex (aOR: 1.77, 95% CI: 1.44-2.18), cardiovascular disease (aOR: 1.71, 95% CI: 1.33-2.20), chronic obstructive pulmonary disease (aOR: 1.82, 95% CI: 1.40-2.34), malignancy (aOR: 4.77, 95% CI: 2.87-7.62), and grade-II obesity (aOR: 2.11, 95% CI: 1.09-3.74). CONCLUSIONS We characterized the spatial and epidemiological heterogeneities of severe hospitalized influenza cases confirmed by PCR in Iran. Detecting influenza hotspot clusters could inform prioritization and geographic specificity of influenza prevention, testing, and mitigation resource management, including vaccination planning in Iran.
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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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Jiang M, Yao X, Li P, Fang Y, Feng L, Hayat K, Shi X, Gong Y, Peng J, Atif N. Impact of video-led educational intervention on uptake of influenza vaccine among the elderly in western China: a community-based randomized controlled trial. BMC Public Health 2022; 22:1128. [PMID: 35668438 PMCID: PMC9169441 DOI: 10.1186/s12889-022-13536-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 05/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Influenza vaccination coverage rate among the elderly is low in China. We aimed to evaluate the impact of video-led educational intervention on influenza vaccine uptake among the Chinese elderly. METHODS A randomized controlled trial was conducted in 8 communities of Xi'an, a representative city in western China. Elderly aged over 60 years were randomized to the control group and intervention group (12-minute video education on influenza and its vaccination). Participants' knowledge, attitudes, and practices (KAP) of influenza was assessed by using a questionnaire survey before and after the intervention. The primary outcomes were participants' willingness to get influenza vaccinated and their actual uptake rates in the 2020-21 flu season. Secondary outcomes were the variations of pre- and post-intervention KAP scores. Intention-to-treat analysis was performed to analyze the data, and sensitivity analyses were conducted to examine the robustness of the results. RESULTS A total of 350 people were enrolled, with 175 individuals for each group. Participants in the intervention group were more willing to receive influenza vaccination than those in the control group (64.6% vs. 51.4%, p<0.05). The influenza vaccination uptake rate occurred in 10.3% of participants in the intervention group and 3.4% in the control group (odds ratio, 3.23; 95% CI 1.25-8.32, p<0.001). The post-intervention KAP scores in the intervention group were significantly higher compared to those in the control group (p<0.001). CONCLUSION Video-led education was an effective and feasible approach to improve old people's willingness and uptake of influenza vaccination in western China.
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Affiliation(s)
- Minghuan Jiang
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China. .,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China. .,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China. .,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China.
| | - Xuelin Yao
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
| | - Pengchao Li
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
| | - Yu Fang
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
| | - Liuxin Feng
- Department of Pharmacy, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710004, China
| | - Khezar Hayat
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
| | - Xinke Shi
- Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, China
| | - Yilin Gong
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
| | - Jin Peng
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
| | - Naveel Atif
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Center for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, Western China Science & Technology Innovation Harbor, Xi'an, 712000, China
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Wei Z, Sun X, Yang Y, Zhan S, Fu C. Seasonal influenza vaccine hesitancy profiles and determinants among Chinese children's guardians and the elderly. Expert Rev Vaccines 2021; 20:601-610. [PMID: 33792476 DOI: 10.1080/14760584.2021.1908134] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
OBJECTIVES Seasonal influenza vaccine coverage remains low in China due to possible influenza vaccine hesitancy (IVH) and practical issues. We sought to investigate IVH and its determinants among children's guardians and the elderly for a better understanding of the situation and for future intervention. METHODS We performed two cross-sectional studies to identify the profiles and determinants of IVH using stratified cluster random sampling in an eastern China province in 2019. RESULTS Of the 1564 guardians and 522 elders, 43.2% (95%CI: 40.4-46.0%) of guardians and 33.5% of elders (95%CI: 29.5-37.6%) had IVH. 'From rural area' (odds ratio: 1.36), 'don't know government recommendation for flu vaccination' (1.39), 'don't know flu vaccine is vaccinated annually' (1.93), and 'family members (0.22), friends and neighbors had positive attitude toward flu vaccine' (0.58) were related factors of the guardians' IVH. 'Aged 70-79 years' (0.46), 'had flu before' (0.35) and 'once had been vaccinated' (0.42) were related to the elderly's IVH. CONCLUSION Poor awareness of influenza and vaccination, relatives' negative/positive attitude, lack of government recommendations, anxiety about vaccine quality, and practical issues such as short supply are related to IVH in China. Precision education aimed at hesitancy in wider groups is anticipated to increase vaccine confidence and coverage in influenza-vulnerable groups.
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Affiliation(s)
- Zheng Wei
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiu Sun
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yingying Yang
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Siyi Zhan
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Chuanxi Fu
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
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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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Li P, Hayat K, Jiang M, Pu Z, Yao X, Zou Y, Lambojon K, Huang Y, Hua J, Xiao H, Du F, Shi L, Zhai P, Ji W, Feng Z, Gong Y, Fang Y. Impact of video-led educational intervention on the uptake of influenza vaccine among adults aged 60 years and above in China: a study protocol for a randomized controlled trial. BMC Public Health 2021; 21:222. [PMID: 33499830 PMCID: PMC7839176 DOI: 10.1186/s12889-021-10220-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Accepted: 01/12/2021] [Indexed: 11/15/2022] Open
Abstract
Background Influenza is a global health threat to older adults, and the influenza vaccine is the most effective approach to prevent influenza infection. However, influenza vaccination coverage among Chinese older adults is far less than in developed countries such as the United States (4.0% vs. 64.9%). This study aims to increase influenza vaccination coverage in Chinese adults ≥60 years using a video-led educational intervention conducted by medical students. Methods A cluster randomized controlled trial will be conducted in 4 districts of Xi’an city, Shaanxi Province, China, using a stratified sampling approach. Adults aged ≥60 years will be recruited from 8 community hospitals. A self-administered questionnaire of knowledge, attitudes, and practices (KAP) will be employed to record the KAP score. During the 6-month interventional period, participants in the intervention group will receive educational videos focused on influenza and influenza vaccination, coupled with a group discussion conducted by the medical students. For those in the control group, no intervention will be provided. The outcomes measured in both groups will be the influenza vaccination coverage and the KAP scores of all participants. Discussion Medical students are more likely to educate older adults about scientific knowledge of influenza and its vaccine compared to clinical practitioners, who, most of the time, remain over-occupied due to the extensive workload. Video-led counseling and education could be a useful option to optimize older adults’ understanding of influenza and influenza vaccination. This eventually could improve the uptake of influenza vaccine among Chinese older adults. Trial registration Chinese Clinical Trial Registry; ChiCTR2000034330; Registered 3rd July 2019. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-021-10220-1.
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Affiliation(s)
- Pengchao Li
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Khezar Hayat
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China.,Institute of Pharmaceutical Sciences, University of Veterinary and Animal Sciences, Lahore, 54000, Pakistan
| | - Minghuan Jiang
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Zhaojing Pu
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Xuelin Yao
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Yamin Zou
- Department of Pharmacy, the Hospital of Xi'an Jiaotong University, Xi'an, 710049, China
| | - Krizzia Lambojon
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Yifan Huang
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Jinghua Hua
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Hanri Xiao
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Fulei Du
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Li Shi
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Panpan Zhai
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Wenjing Ji
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Zhitong Feng
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Yilin Gong
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China.,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China.,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China.,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China
| | - Yu Fang
- Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmacy, Xi'an Jiaotong University, Xi'an, 710061, China. .,Center for Drug Safety and Policy Research, Xi'an Jiaotong University, Xi'an, 710061, China. .,Shaanxi Centre for Health Reform and Development Research, Xi'an, 710061, China. .,Research Institute for Drug Safety and Monitoring, Institute of Pharmaceutical Science and Technology, China's Western Technological Innovation Harbor, Xi'an, 710061, China.
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10
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Narayan VV, Iuliano AD, Roguski K, Bhardwaj R, Chadha M, Saha S, Haldar P, Kumar R, Sreenivas V, Kant S, Bresee J, Jain S, Krishnan A. Burden of influenza-associated respiratory and circulatory mortality in India, 2010-2013. J Glob Health 2020; 10:010402. [PMID: 32373326 PMCID: PMC7182391 DOI: 10.7189/jogh.10.010402] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background Influenza causes substantial morbidity and mortality worldwide, however, reliable burden estimates from developing countries are limited, including India. We aimed to quantify influenza-associated mortality for India utilizing 2010-2013 nationally representative data sources for influenza virus circulation and deaths. Methods Virological data were obtained from the influenza surveillance network of 10 laboratories led by National Institute of Virology, Pune covering eight states from 2010-2013. Death data were obtained from the nationally representative Sample Registration System for the same time period. Generalized linear regression with negative binomial distribution was used to model weekly respiratory and circulatory deaths by age group and proportion of specimens positive for influenza by subtype; excess deaths above the seasonal baseline were taken as an estimate of influenza-associated mortality counts and rates. Annual excess death rates and the 2011 India Census data were used to estimate national influenza-associated deaths. Results Estimated annual influenza-associated respiratory mortality rates were highest for those ≥65 years (51.1, 95% confidence interval (CI) = 9.2-93.0 deaths/100 000 population) followed by those <5 years (9.8, 95% CI = 0-21.8/100 000). Influenza-associated circulatory death rates were also higher among those ≥65 years (71.8, 95% CI = 7.9-135.8/100 000) as compared to those aged <65 years (1.9, 95% CI = 0-4.6/100 000). Across all age groups, a mean of 127 092 (95% CI = 64 046-190,139) annual influenza-associated respiratory and circulatory deaths may occur in India. Conclusions Estimated influenza-associated mortality in India was high among children <5 years and adults ≥65 years. These estimates may inform strategies for influenza prevention and control in India, such as possible vaccine introduction.
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Affiliation(s)
| | - A Danielle Iuliano
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Katherine Roguski
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Rohit Bhardwaj
- SRS division, Office of Registrar General of India, New Delhi, India
| | | | - Siddhartha Saha
- Influenza Division, Centers for Disease Control and Prevention, New Delhi, India
| | - Partha Haldar
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi
| | - Rajeev Kumar
- SRS division, Office of Registrar General of India, New Delhi, India
| | | | - Shashi Kant
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi
| | - Joseph Bresee
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Seema Jain
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Anand Krishnan
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi
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11
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Jin S, Li J, Cai R, Wang X, Gu Z, Yu H, Fang B, Chen L, Wang C. Age- and sex-specific excess mortality associated with influenza in Shanghai, China, 2010–2015. Int J Infect Dis 2020; 98:382-389. [DOI: 10.1016/j.ijid.2020.07.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/03/2020] [Accepted: 07/09/2020] [Indexed: 02/01/2023] Open
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12
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Cheng KJG, Rivera AS, Lam HY, Ulitin AR, Nealon J, Dizon R, Wu DBC. Influenza-associated excess mortality in the Philippines, 2006-2015. PLoS One 2020; 15:e0234715. [PMID: 32555618 PMCID: PMC7299398 DOI: 10.1371/journal.pone.0234715] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 06/01/2020] [Indexed: 01/22/2023] Open
Abstract
Influenza-associated mortality has not been quantified in the Philippines. Here, we constructed multiple negative binomial regression models to estimate the overall and age-specific excess mortality rates (EMRs) associated with influenza in the Philippines from 2006 to 2015. The regression analyses used all-cause mortality as the dependent variable and meteorological controls, time, influenza A and B positivity rates (lagged for up to two time periods), and annual and semiannual cyclical seasonality controls as independent variables. The regression models closely matched observed all-cause mortality. Influenza was estimated to account for a mean of 5,347 excess deaths per year (1.1% of annual all-cause deaths) in the Philippines, most of which (67.1%) occurred in adults aged ≥60 years. Influenza A accounted for 85.7% of all estimated excess influenza deaths. The annual estimated influenza-attributable EMR was 5.09 (95% CI: 2.20–5.09) per 100,000 individuals. The EMR was highest for individuals aged ≥60 years (44.63 [95% CI: 4.51–44.69] per 100,000), second highest for children aged less than 5 years (2.14 [95% CI: 0.44–2.19] per 100,000), and lowest for individuals aged 10 to 19 years (0.48 [95% CI: 0.10–0.50] per 100,000). Estimated numbers of excess influenza-associated deaths were considerably higher than the numbers of influenza deaths registered nationally. Our results suggest that influenza causes considerable mortality in the Philippines–to an extent far greater than observed from national statistics–especially among older adults and young children.
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Affiliation(s)
- Kent Jason Go Cheng
- Social Science Department, Maxwell School of Citizenship and Public Affairs, Syracuse University, Syracuse, NY, United States of America
- * E-mail:
| | - Adovich Sarmiento Rivera
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Hilton Yu Lam
- Institute of Health Policy and Development Studies, National Institutes of Health, University of the Philippines Manila, Manila, Philippines
| | - Allan Rodriguez Ulitin
- Institute of Health Policy and Development Studies, National Institutes of Health, University of the Philippines Manila, Manila, Philippines
| | - Joshua Nealon
- Vaccines Epidemiology and Modeling, Sanofi Pasteur, Singapore, Singapore
| | - Ruby Dizon
- Medical Affairs, Sanofi Pasteur, Taguig City, Metropolitan Manila, Philippines
| | - David Bin-Chia Wu
- Faculty of Pharmacy and Pharmaceutical Sciences, Monash University Malaysia, Selangor, Malaysia
- Asian Centre for Evidence Synthesis in Population, Implementation and Clinical Outcomes, Health and Well-Being Cluster, Global Asia in the 21st Century Platform, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia
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13
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Qi L, Li Q, Ding XB, Gao Y, Ling H, Liu T, Xiong Y, Su K, Tang WG, Feng LZ, Liu QY. Mortality burden from seasonal influenza in Chongqing, China, 2012-2018. Hum Vaccin Immunother 2020; 16:1668-1674. [PMID: 32343618 PMCID: PMC7482776 DOI: 10.1080/21645515.2019.1693721] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Purpose To estimate influenza-associated excess mortality rates (EMRs) in Chongqing from 2012 to 2018. Methods We obtained weekly mortality data for all-cause and four underlying causes of death (circulatory and respiratory disease (CRD), pneumonia and influenza (P&I), chronic obstructive pulmonary disease (COPD) and ischemic heart disease (IDH)), and influenza surveillance data, from 2012 to 2018. A negative-binomial regression model was used to estimate influenza-associated EMRs in two age groups (<65 years and ≥65 years). Results It was estimated that an annual average of 10025 influenza-associated deaths occurred in Chongqing, corresponding to 5.2% of all deaths. The average EMR for all-cause death associated with influenza was 33.5 (95% confidence interval (CI): 31.5–35.6) per 100 000 persons, and in separate cause-specific models we attributed 24.7 (95% CI: 23.3–26.0), 0.8 (95% CI: 0.7–0.8), 8.5 (95% CI: 8.1–9.0) and 5.0 (95% CI: 4.7–5.3) per 100 000 persons EMRs to CRD, P&I, COPD and IDH, respectively. The estimated EMR for influenza B virus was 20.6 (95% CI: 20.3–21.0), which was significantly higher than the rates of 5.3 (95% CI: 4.5–6.1) and 7.5 (95% CI: 6.7–8.3) for A(H3N2) and A(H1N1) pdm09 virus, respectively. The estimated EMR was 152.3 (95% CI: 136.1–168.4) for people aged ≥65 years, which was significantly higher than the rate for those aged <65 years (6.8, 95% CI: 6.3–7.2). Conclusions Influenza was associated with substantial EMRs in Chongqing, especially among elderly people. Influenza B virus caused a relatively higher excess mortality impact compared with A(H1N1)pdm09 and A(H3N2). It is advisable to optimize future seasonal influenza vaccine reimbursement policy in Chongqing to curb disease burden.
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Affiliation(s)
- Li Qi
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China.,Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Qin Li
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Xian-Bin Ding
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Yuan Gao
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China
| | - Hua Ling
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Tian Liu
- Infectious Disease Control and Prevention Department, Jingzhou Center for Disease Control and Prevention , Jingzhou City, Hubei Province, China
| | - Yu Xiong
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Kun Su
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Wen-Ge Tang
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Lu-Zhao Feng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention , Beijing, China
| | - Qi-Yong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China
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14
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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: 131] [Impact Index Per Article: 26.2] [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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15
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Hong K, Sohn S, Chun BC. Estimating Influenza-associated Mortality in Korea: The 2009-2016 Seasons. J Prev Med Public Health 2019; 52:308-315. [PMID: 31588700 PMCID: PMC6780294 DOI: 10.3961/jpmph.19.156] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 08/13/2019] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES Estimating influenza-associated mortality is important since seasonal influenza affects persons of all ages, causing severe illness or death. This study aimed to estimate influenza-associated mortality, considering both periodic changes and age-specific mortality by influenza subtypes. METHODS Using the Microdata Integrated Service from Statistics Korea, we collected weekly mortality data including cause of death. Laboratory surveillance data of respiratory viruses from 2009 to 2016 were obtained from the Korea Centers for Disease Control and Prevention. After adjusting for the annual age-specific population size, we used a negative binomial regression model by age group and influenza subtype. RESULTS Overall, 1 859 890 deaths were observed and the average rate of influenza virus positivity was 14.7% (standard deviation [SD], 5.8), with the following subtype distribution: A(H1N1), 5.0% (SD, 5.8); A(H3N2), 4.4% (SD, 3.4); and B, 5.3% (SD, 3.7). As a result, among individuals under 65 years old, 6774 (0.51%) all-cause deaths, 2521 (3.05%) respiratory or circulatory deaths, and 1048 (18.23%) influenza or pneumonia deaths were estimated. Among those 65 years of age or older, 30 414 (2.27%) all-cause deaths, 16 411 (3.42%) respiratory or circulatory deaths, and 4906 (6.87%) influenza or pneumonia deaths were estimated. Influenza A(H3N2) virus was the major contributor to influenza-associated all-cause and respiratory or circulatory deaths in both age groups. However, influenza A(H1N1) virus-associated influenza or pneumonia deaths were more common in those under 65 years old. CONCLUSIONS Influenza-associated mortality was substantial during this period, especially in the elderly. By subtype, influenza A(H3N2) virus made the largest contribution to influenza-associated mortality.
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Affiliation(s)
- Kwan Hong
- Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
| | - Sangho Sohn
- Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
| | - Byung Chul Chun
- Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
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Lei N, Wang HB, Zhang YS, Zhao JH, Zhong Y, Wang YJ, Huang LY, Ma JX, Sun Q, Yang L, Shu YL, Li SM, Sun LL. Molecular evolution of influenza B virus during 2011-2017 in Chaoyang, Beijing, suggesting the free influenza vaccine policy. Sci Rep 2019; 9:2432. [PMID: 30792414 PMCID: PMC6384887 DOI: 10.1038/s41598-018-38105-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 12/10/2018] [Indexed: 11/15/2022] Open
Abstract
Two influenza B virus lineages, B/Victoria and B/Yamagata, are co-circulating in human population. While the two lineages are serologically distinct and TIV only contain one lineage. It is important to investigate the epidemiological and evolutionary dynamics of two influenza B virus lineages in Beijing after the free influenza vaccine policy from 2007. Here, we collected the nasopharyngeal swabs of 12657 outpatients of influenza-like illness and subtyped by real-time RT-PCR during 2011–2017. The HA and NA genes of influenza B were fully sequenced. The prevalence is the highest in the 6–17 years old group among people infected with influenza B. Yamagata-lineage virus evolved to two inter-clade from 2011–2014 to 2014–2017. The amino acids substitutions of HA1 region were R279K in strains of 2011–2014 and L173Q, M252V in strains of 2014–2017. Substitutions L58P, I146V were observed in HA1 region of Victoria-lineage virus in 2011–2012 and I117V, N129D were showed in 2015–2017. Phylogenetic analysis of NA showed Yamagata-Victoria inter-lineage reassortant occurred in 2013–2014. Influenza B mainly infect the school-aged children in Beijing and the free influenza vaccine inoculation does not seem to block school-age children from infection with influenza B. The antigen characteristics of circulating influenza B were different to the recommended vaccine strains. We concluded that the Victoria-lineage vaccine strain should been changed and the free influenza vaccine should be revalued.
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Affiliation(s)
- Na Lei
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China.,National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Prevention and Control, Beijing, 102206, China
| | - Hai-Bin Wang
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Yu-Song Zhang
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Jian-Hong Zhao
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Yi Zhong
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Yuan-Jie Wang
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Li-Yong Huang
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Jian-Xin Ma
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China
| | - Qiang Sun
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Prevention and Control, Beijing, 102206, China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangdong, 510275, China
| | - Lei Yang
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Prevention and Control, Beijing, 102206, China
| | - Yue-Long Shu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Prevention and Control, Beijing, 102206, China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangdong, 510275, China
| | - Shu-Ming Li
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China.
| | - Ling-Li Sun
- Chaoyang District Center for Disease Prevention and Control, Beijing, 100021, China.
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Amaya Santiago HJ, Barbosa J, Saavedra Trujillo CH. Descripción de características demográficas y clínicas de una cohorte pacientes fallecidos por infección respiratoria aguda en Colombia durante los años 2009 a 2013. INFECTIO 2019. [DOI: 10.22354/in.v23i2.771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Objetivo: Describir las características clínicas, demográficas, aislamientos virales y hallazgos de histopatología de individuos que fallecieron por Infección Respiratoria Aguda (IRA) y que fueron notificados al Instituto Nacional de Salud (INS) entre los años 2009 y 2013.Métodos: Estudio observacional, descriptivo, retrospectivo, basado en la revisión de fichas epidemiológicas y reportes de estudios de virología e histopatología de muestras respiratorias de individuos fallecidos con diagnóstico de IRAResultados: De 1604 personas fallecidas se encontró que, 55% fueron hombres, 46,5% de los individuos tenía entre 20 y 59 años. La RT-PCR fue positiva en 18,3% de los casos, los virus más frecuentes fueron: influenza A(H1N1)pdm09 13,9%, A(H3N3) 1,9% e influenza B 0,5%. La letalidad de IRA fue mayor en los individuos que recibieron antiviral o antibiótico OR 2,80 (IC 95% 2,29 - 3,43) y 3,19 (IC 95% 2,63 – 3,86), respectivamente.Conclusión: El virus influenza A(H1N1) pdm09 fue el principal agente identificado en los casos fatales de IRA confirmada por laboratorio durante los años 2009 a 2013, con mayor letalidad en individuos entre 20 y 59 años; 64,7% de los casos fatales presentaron neumonitis. Se debe aclarar si el inicio de antivirales afecta el pronóstico en los casos graves de IRA.
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FORTUNATO F, IANNELLI G, COZZA A, DEL PRETE M, POLLIDORO F, COCCIARDI S, DI TRANI M, MARTINELLI D, PRATO R. Local deprivation status and seasonal influenza vaccination coverage in adults ≥ 65 years residing in the Foggia municipality, Italy, 2009-2016. JOURNAL OF PREVENTIVE MEDICINE AND HYGIENE 2018; 59:E51-E64. [PMID: 31016268 PMCID: PMC6419308 DOI: 10.15167/2421-4248/jpmh2018.59.4s2.1167] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Accepted: 12/20/2018] [Indexed: 11/16/2022]
Abstract
Introduction In Italy, vaccination against seasonal influenza has been recommended for the elderly since 1980, but coverage is still far below the WHO minimum target level of 75%. Effective interventions to improve influenza vaccination should take into account socioeconomic determinants of inequalities in vaccine uptake. This study aimed to assess differences in vaccination coverage, by socioeconomic status, among people ≥ 65 years of age residing in the Foggia municipality, Italy. Methods A Socio-Economic-Health Deprivation Index (SEHDI) was constructed by using a multivariate analysis model. The resident population, for census block, was classified in 5 deprivation groups. Differences in demographic and socioeconomic indicators, the standardized mortality ratios (SMRs), and the average vaccination coverage among deprivation groups were evaluated with the linear F-test. The association between census variables and influenza vaccination coverage, in each deprivation group, was assessed using the Pearson bivariate correlation. Results The SEHDI allowed to identify factors related to ageing, housing, household size and composition, and education. Forty percent of people residing in the Foggia municipality lived in conditions of socioeconomic and health deprivation. Belonging to families with 3 or 4 members was associated with increased coverage rates. In the most deprived group, vaccination uptake was positively associated with the dependency ratio. Conclusions The results of this study have shown that there is still large room for improving influenza vaccination coverage among subjects belonging to the most deprived areas. Surveillance of trends in influenza vaccine uptake by socioeconomic groups is a feasible contribution to implementing effective, tailored to the frail older persons, vaccine utilization programs.
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Affiliation(s)
| | | | | | | | | | | | | | | | - R. PRATO
- Rosa Prato, Department of Medical and Surgical Sciences, University of Foggia, viale Luigi Pinto, 71122 Foggia, Italy - Tel. +39 0881 588036 - Fax +39 0881 588047 - E-mail:
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Zhang L, Pan Y, Hackert V, van der Hoek W, Meijer A, Krafft T, Yang P, Wang Q. The 2015-2016 influenza epidemic in Beijing, China: Unlike elsewhere, circulation of influenza A(H3N2) with moderate vaccine effectiveness. Vaccine 2018; 36:4993-5001. [PMID: 30017144 DOI: 10.1016/j.vaccine.2018.07.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 07/05/2018] [Accepted: 07/10/2018] [Indexed: 01/31/2023]
Abstract
BACKGROUND While the 2015-2016 influenza season in the northern hemisphere was dominated by A(H1N1)pdm09 and B/Victoria viruses, in Beijing, China, there was also significant circulation of influenza A(H3N2) virus. In this report we estimate vaccine effectiveness (VE) against influenza A(H3N2) and other circulating viruses, and describe further characteristics of the 2015-2016 influenza season in Beijing. METHODS We estimated VE of the 2015-2016 trivalent inactivated vaccine (TIV) against laboratory-confirmed influenza virus infection using the test-negative study design. The effect of prior vaccination on current VE was also examined. RESULTS Of 11,000 eligible patients included in the study, 2969 (27.0%) were influenza positive. Vaccination coverage was 4.2% in both cases and controls. Adjusted VE against all influenza was 8% (95% CI: -16% to 27%): 18% (95% CI: -38% to 52%) for influenza A(H1N1)pdm09, 54% (95% CI: 16% to 74%) for influenza A(H3N2), and -8% (95% CI: -40% to 18%) for influenza B/Victoria. The overall VE for receipt of 2015-2016 vaccination only, 2014-2015 vaccination only, and vaccinations in both seasons was -15% (95% CI: -63% to 19%), -25% (95% CI: -78% to 13%), and 18% (95% CI: -11% to 40%), respectively. CONCLUSIONS Overall the 2015-2016 TIV was protective against influenza infection in Beijing, with higher VE against the A(H3N2) viruses compared to A(H1N1)pdm09 and B viruses.
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Affiliation(s)
- Li Zhang
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Yang Pan
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China
| | - Volker Hackert
- Public Health Service South Limburg, Department of Sexual Health, Infectious Diseases, and Environmental Health, Sittard-Geleen, The Netherlands
| | - Wim van der Hoek
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Adam Meijer
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Thomas Krafft
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Peng Yang
- Beijing Center for Disease Prevention and Control, Beijing, China; Beijing Research Center for Preventive Medicine, Beijing, China; School of Public Health, Capital Medical University, 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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20
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Jennings L, Huang QS, Barr I, Lee PI, Kim WJ, Buchy P, Sanicas M, Mungall BA, Chen J. Literature review of the epidemiology of influenza B disease in 15 countries in the Asia-Pacific region. Influenza Other Respir Viruses 2018; 12:383-411. [PMID: 29127742 PMCID: PMC5907823 DOI: 10.1111/irv.12522] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/26/2017] [Indexed: 01/06/2023] Open
Abstract
Influenza control strategies focus on the use of trivalent influenza vaccines containing two influenza A virus subtypes and one of the two circulating influenza type B lineages (Yamagata or Victoria). Mismatches between the vaccine B lineage and the circulating lineage have been regularly documented in many countries, including those in the Asia‐Pacific region. We conducted a literature review with the aim of understanding the relative circulation of influenza B viruses in Asia‐Pacific countries. PubMed and Western Pacific Region Index Medicus were searched for relevant articles on influenza type B published since 1990 in English language for 15 Asia‐Pacific countries. Gray literature was also accessed. From 4834 articles identified, 121 full‐text articles were analyzed. Influenza was reported as an important cause of morbidity in the Asia‐Pacific region, affecting all age groups. In all 15 countries, influenza B was identified and associated with between 0% and 92% of laboratory‐confirmed influenza cases in any one season/year. Influenza type B appeared to cause more illness in children aged between 1 and 10 years than in other age groups. Epidemiological data for the two circulating influenza type B lineages remain limited in several countries in the Asia‐Pacific, although the co‐circulation of both lineages was seen in countries where strain surveillance data were available. Mismatches between circulating B lineages and vaccine strains were observed in all countries with available data. The data suggest that a shift from trivalent to quadrivalent seasonal influenza vaccines could provide additional benefits by providing broader protection.
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Affiliation(s)
- Lance Jennings
- Canterbury District Health Board, Christchurch, New Zealand
| | - Qiu Sue Huang
- WHO National Influenza Centre, Institute of Environmental Science and Research, Porirua, New Zealand
| | - Ian Barr
- WHO Collaborating Centre for Reference and Research on Influenza, Melbourne, VIC, Australia
| | - Ping-Ing Lee
- Department of Pediatrics, National Taiwan University Children's Hospital, Taipei, Taiwan
| | - Woo Joo Kim
- Department of Internal Medicine, Korea University Guro Hospital, Seoul, Korea
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21
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Narayan VV, Iuliano AD, Roguski K, Haldar P, Saha S, Sreenivas V, Kant S, Zodpey S, Pandav CS, Jain S, Krishnan A. Evaluation of data sources and approaches for estimation of influenza-associated mortality in India. Influenza Other Respir Viruses 2018; 12:72-80. [PMID: 29197173 PMCID: PMC5818338 DOI: 10.1111/irv.12493] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/19/2017] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND No estimates of influenza-associated mortality exist for India. OBJECTIVE To evaluate national mortality and viral surveillance data from India for assessing their appropriateness in estimating influenza-associated mortality using varied analytic approaches. METHODS We reviewed influenza virus surveillance data from a national influenza surveillance network. We also reviewed national mortality data from Civil Registration System (CRS), Medical Certification of Cause of Death (MCCD) and the Sample Registration System (SRS). We compared and scored the different sources of mortality data using specific criteria, including the process of cause of death assignment, sample size, proportion of ill-defined deaths, representativeness and availability of time series data. Each of these 5 parameters was scored on a scale from 1 to 5. To evaluate how to generate an influenza-associated mortality estimate for India, we also reviewed 4 methodologic approaches to assess the appropriateness of their assumptions and requirements for these data sets. RESULTS The influenza virus surveillance data included year-round sample testing for influenza virus and was found to be suitable for influenza mortality estimation modelling. Based on scoring for the 5 mortality data criteria, the SRS data had the highest score with 20 of 25 possible score, whereas MCCD and CRS scored 16 and 12, respectively. The SRS which used verbal autopsy survey methods was determined to be nationally representative and thus adequate for estimating influenza-associated mortality. Evaluation of the modelling methods demonstrated that Poisson regression, risk difference and mortality multiplier methods could be applied to the Indian setting. CONCLUSION Despite significant challenges, it is possible to estimate influenza-associated mortality in India.
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Affiliation(s)
| | | | | | - Partha Haldar
- Centre for Community MedicineAll India Institute of Medical SciencesNew DelhiIndia
| | | | | | - Shashi Kant
- Centre for Community MedicineAll India Institute of Medical SciencesNew DelhiIndia
| | | | | | - Seema Jain
- Centers for Disease Control and PreventionNew DelhiIndia
| | - Anand Krishnan
- Centre for Community MedicineAll India Institute of Medical SciencesNew DelhiIndia
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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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Liu XX, Li Y, Zhu Y, Zhang J, Li X, Zhang J, Zhao K, Hu M, Qin G, Wang XL. Seasonal pattern of influenza activity in a subtropical city, China, 2010-2015. Sci Rep 2017; 7:17534. [PMID: 29235535 PMCID: PMC5727502 DOI: 10.1038/s41598-017-17806-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 12/01/2017] [Indexed: 11/13/2022] Open
Abstract
Influenza seasonality study is critical for policy-makers to choose an optimal time for influenza vaccination campaign, especially for subtropical regions where influenza seasonality and periodicity are unclear. In this study, we explored the seasonality and periodicity of influenza in Hefei, China during 2010 to 2015 using five proxies originated from three data sources of clinical surveillance of influenza-like illness (ILI), laboratory surveillance of influenza and death registration of pneumonia and influenza. We combined both wavelets analysis and de-linear-trend regression with Fourier harmonic terms to estimate seasonal characteristics of epidemic phase, peak time, amplitude, ratio of dominant seasonality. We found both annual cycle of influenza epidemics peaking in December-February and semi-annual cycle peaking in December-February and June-July in subtropical city Hefei, China. Compared to proxies developed by ILI and death registration data separately, influenza proxies incorporated laboratory surveillance data performed better seasonality and periodicity, especially in semi-annual periodicity in Hefei. Proxy of ILI consultation rate showed more timeliness peak than other proxies, and could be useful in developing the early warning model for influenza epidemics. Our study suggests to integrate clinical and laboratory surveillance of influenza for future influenza seasonality studies in subtropical regions.
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Affiliation(s)
- Xu-Xiang Liu
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Yahong Li
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China
| | - Yibing Zhu
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Juanjuan Zhang
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China
| | - Xiaoru Li
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Junqing Zhang
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Kefu Zhao
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Mingxia Hu
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Guoyou Qin
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China.
| | - Xi-Ling Wang
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China.
- Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
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Epidemiological and Virological Characteristics of Influenza in Chongqing, China, 2011-2015. PLoS One 2016; 11:e0167866. [PMID: 27936139 PMCID: PMC5148009 DOI: 10.1371/journal.pone.0167866] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Accepted: 11/21/2016] [Indexed: 11/21/2022] Open
Abstract
Background Chongqing is the largest municipality and located in Southwestern of China, with over 30 million registered inhabitants. There are few reports regarding the epidemiology of influenza in Chongqing. The objective of the paper is to explore the epidemiology of influenza in Chongqing, in order to provide scientific basis for prevention and control of influenza. Methodology /Principal Findings From 2011 to 2015, we collected information on influenza-like illness (ILI) patients fulfilling the case definition, and took nasalpharyngeal or throat swabs specimens from ILI cases per week at the 7 sentinel hospitals. Specimens were tested by reverse transcription-polymerase chain reaction(RT-PCR) for influenza. Descriptive epidemiology was applied to analyze the epidemiology and etiology of influenza. A total of 9,696,212 cases were enrolled, of which 111,589 were ILI. Of those 24,868 samples from ILI cases, 13.3% (3,314/24,868) tested positive for influenza virus (65.7% influenza A, 34.1% influenza B, and 0.2% influenza A and B co-infection). Among the influenza A viruses, 71.3% were seasonal influenza A(H3N2) and 28.7% were influenza A(H1N1)pdm09. No cases of seasonal A(H1N1) were detected. The isolation rate was highest in children aged 5–14 years old. Influenza activity consistently peaked during January-March in 2011–2015, and June-July in 2012, 2014 and 2015. Conclusions Influenza is an important public health problem among ILI patients in Chongqing, especially among school-aged children. It might be beneficial to prioritize influenza vaccination for school-aged children and implement the school-based intervention to prevent and mitigating influenza outbreaks in Chongqing, particularly during the seasonal peaks.
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Peng F, He J, Loo JFC, Yao J, Shi L, Liu C, Zhao C, Xie W, Shao Y, Kong SK, Gu D. Identification of microRNAs in Throat Swab as the Biomarkers for Diagnosis of Influenza. Int J Med Sci 2016; 13:77-84. [PMID: 26917988 PMCID: PMC4747873 DOI: 10.7150/ijms.13301] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2015] [Accepted: 12/15/2015] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Influenza is a serious worldwide disease that captures global attention in the past few years after outbreaks. The recent discoveries of microRNA (miRNA) and its unique expression profile in influenza patients have offered a new method for early influenza diagnosis. The aim of this study was to examine the utility of miRNAs for the diagnosis of influenza. METHODS Thirteen selected miRNAs were investigated with the hosts' throat swabs (25 H1N1, 20 H3N2, 20 influenza B and 21 healthy controls) by real-time quantitative polymerase chain reaction (RT-qPCR) using U6 snRNA as endogenous control for normalization, and receiver operating characteristic (ROC) curve/Area under curve (AUC) for analysis. RESULTS miR-29a-3p, miR-30c-5p, miR-34c-3p and miR-181a-5p are useful biomarkers for influenza A detection; and miR-30c-5p, miR-34b-5p, miR-205-5p and miR-449b-5p for influenza B detection. Also, use of both miR-30c-5p and miR-34c-3p (AUC=0.879); and miR-30c-5p and miR-449b-5p (AUC=0.901) are better than using one miRNA to confirm influenza A and influenza B infection, respectively. CONCLUSIONS Given its simplicity, non-invasiveness and specificity, we found that the throat swab-derived miRNAs miR-29a-3p, miR-30c-5p, miR-34b-5p, miR-34c-3p, miR-181a-5p, miR-205-5p and miR-449b-5p are a useful tool for influenza diagnosis on influenza A and B.
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Affiliation(s)
- Fang Peng
- 1. Department of Health Inspection and Quarantine, School of Public Health, Sun Yat-sen University, Guangzhou, China; 2. Shenzhen Entry-exit Inspection and Quarantine Bureau, Shenzhen, China
| | - Jianan He
- 2. Shenzhen Entry-exit Inspection and Quarantine Bureau, Shenzhen, China
| | - Jacky Fong Chuen Loo
- 3. Biochemistry Programme, School of Life Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Jingyu Yao
- 4. Guangdong Medical University, Zhanjiang, China
| | - Lei Shi
- 2. Shenzhen Entry-exit Inspection and Quarantine Bureau, Shenzhen, China
| | - Chunxiao Liu
- 2. Shenzhen Entry-exit Inspection and Quarantine Bureau, Shenzhen, China
| | - Chunzhong Zhao
- 2. Shenzhen Entry-exit Inspection and Quarantine Bureau, Shenzhen, China
| | - Weidong Xie
- 5. Shenzhen Key Lab of Health Science and Technology, Division of Life Sciences & Health, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China
| | - Yonghong Shao
- 6. College of Optoelectronics Engineering, Key Laboratory of Optoelectronic Devices and Systems, Ministry of Education and Guangdong Province, Shenzhen Key Laboratory of Sensor Technology, Shenzhen University, Shenzhen, China
| | - Siu Kai Kong
- 3. Biochemistry Programme, School of Life Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Dayong Gu
- 1. Department of Health Inspection and Quarantine, School of Public Health, Sun Yat-sen University, Guangzhou, China; 2. Shenzhen Entry-exit Inspection and Quarantine Bureau, Shenzhen, China
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26
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Pan Y, Zhang Y, Yang P, Qian H, Shi W, Wu S, Cui S, Zhang D, Wang Q. Epidemiological and Phylogenetic Characteristics of Influenza B Infection in Severe Acute Respiratory Infection Cases in Beijing, 2014 to 2015. Medicine (Baltimore) 2015; 94:e2399. [PMID: 26717393 PMCID: PMC5291634 DOI: 10.1097/md.0000000000002399] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Influenza B viral infection is of great importance, but the epidemiological and phylogenetic characteristics of influenza B infection in severe acute respiratory infection (SARI) cases are still unclear.The clinical information of 2816 SARI cases and 467,737 influenza-like illness (ILI) cases in Beijing area from September 2014 to April 2015 were collected and analyzed. Among them, 91 influenza B viruses isolated from SARI cases were sequenced.The overall yield rate of influenza A/B infection was 14.21% and 27.77% in sampled SARI and ILI cases, respectively. Compared with influenza A infection, the frequency of influenza B infection in SARI cases was higher in younger patients. Phylogenetic analysis suggested that most tested hemagglutination genes belonged to Yamagata lineage Clade 3, which were similar with current circulating viruses but different with 2014 to 2015 influenza season vaccine strain (Clade 2). Importantly, HA-Y3/NA-V4 intralineage reassorting was identified in Beijing area for the first time, which can act as a possible risk factor of SARIs.The influenza activity and virus types/subtypes/lineages among SARI patients were well correlated with that of ILI cases. Furthermore, the potential risk of reassorted influenza B virus infection should not be overlooked.
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Affiliation(s)
- Yang Pan
- From the Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control (CDC), Beijing, China
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27
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Zhao B, Qin S, Teng Z, Chen J, Yu X, Gao Y, Shen J, Cui X, Zeng M, Zhang X. Epidemiological study of influenza B in Shanghai during the 2009-2014 seasons: implications for influenza vaccination strategy. Clin Microbiol Infect 2015; 21:694-700. [PMID: 25882368 DOI: 10.1016/j.cmi.2015.03.009] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2014] [Revised: 02/13/2015] [Accepted: 03/21/2015] [Indexed: 11/29/2022]
Abstract
A new quadrivalent influenza vaccine has been available for influenza B, which can pose a significant global health burden. Shanghai has the highest GDP and largest metropolitan population in China. To understand the impact of influenza B in Shanghai in terms of age-related incidence and relative prevalence compared with other subtypes, we conducted this retrospective epidemiological study of influenza B in the 2009-2014 seasons. A total of 71 354 outpatients with influenza-like illness were included, and both lineages of influenza B and subtypes of influenza A were identified using real-time RT-PCR. The antigenic characteristics of influenza B isolates were analysed by sequencing and reciprocal haemagglutinin inhibition assay. On average, 33.45% of influenza strains were influenza B, and 40.20% of strains isolated from children were influenza B. The incidence of influenza B was highest (12.52 per 100 people with influenza-like illness) in children ages 6-17 years and usually peaked in this age group at the early stage of an influenza B epidemic. Overall, both matched and mismatched influenza B strains co-circulated in Shanghai annually, and 44.57% of the circulating influenza B belonged to the opposite lineage of the vaccine strains. We concluded that influenza B has caused a substantial impact in Shanghai and that school-aged children play a key role in the transmission of influenza B. Hence, it may be beneficial to prioritize influenza vaccination for school-aged children to mitigate the outbreaks of influenza B.
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Affiliation(s)
- B Zhao
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China; Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - S Qin
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Z Teng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - J Chen
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - X Yu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Y Gao
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - J Shen
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - X Cui
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - M Zeng
- Department of Infectious Diseases, Children's Hospital of Fudan University, Shanghai, China.
| | - X Zhang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
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28
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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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29
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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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30
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Hung IFN, Zhang AJ, To KKW, Chan JFW, Li C, Zhu HS, Li P, Li C, Chan TC, Cheng VCC, Chan KH, Yuen KY. Immunogenicity of intradermal trivalent influenza vaccine with topical imiquimod: a double blind randomized controlled trial. Clin Infect Dis 2014; 59:1246-55. [PMID: 25048848 DOI: 10.1093/cid/ciu582] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Imiquimod, a synthetic Toll-like receptor 7 agonist enhanced immunogenicity of influenza vaccine in a mouse model. We hypothesized that topical imiquimod before intradermal influenza vaccination (TIV) would produce similar effect in human. METHODS We performed a prospective 1-year follow-up, double-blind, randomized, controlled trial with adults with comorbidities. Participants were randomized to 1 of the following 3 vaccinations: topical 5% 250 mg imiquimod ointment followed by intradermal TIV, topical aqueous-cream followed by intradermal TIV, or topical aqueous-cream followed by intramuscular TIV. Patients and investigators were blinded to the type of topical treatment applied. Hemagglutination inhibition (HI) and microneutralization antibody titers were measured. The primary outcome was the day 7 seroconversion rate. RESULTS Ninety-one recruited participants completed the study. The median age was 73 years. On day 7, 27/30 (90%) patients who received imiquimod and intradermal TIV achieved seroconversion against the H1N1 strain by HI, compared with 4/30 (13.3%) who received aqueous-cream and intramuscular TIV (P < .001), and 12/31 (38.7%) who received aqueous-cream and intradermal TIV (P < .001). The seroconversion, seroprotection, and geometric mean titer-fold increase were met in all 3 strains in the imiquimod and intradermal TIV group 2 weeks earlier, and the better seroconversion rate was sustained from day 7 to year 1 (P ≤ .001). The better immunogenicity was associated with fewer hospitalizations for influenza or pneumonia (P < .05). All adverse reactions were self-limited. CONCLUSIONS Pretreatment with topical imiquimod significantly expedited, augmented, and prolonged the immunogenicity of influenza vaccination. This strategy for influenza immunization should be considered for the elderly population.
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Affiliation(s)
- Ivan F N Hung
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Anna J Zhang
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Kelvin K W To
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Jasper F W Chan
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Can Li
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Hou-Shun Zhu
- Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Patrick Li
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Clara Li
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Tuen-Ching Chan
- Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Vincent C C Cheng
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Kwok-Hung Chan
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
| | - Kwok-Yung Yuen
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu's Centre for Infection and Division of Infectious Diseases
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