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Luo H, Cui Y, Yu W, Li G, Zhao Q, Geng M, Wang H, Ma W. The impact of urbanization in China on influenza incidence across neighboring cities. J Infect 2025; 90:106370. [PMID: 39615844 DOI: 10.1016/j.jinf.2024.106370] [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: 08/28/2024] [Revised: 11/13/2024] [Accepted: 11/26/2024] [Indexed: 12/12/2024]
Abstract
OBJECTIVES Although the relationship between urbanization and influenza has received increasing attention, previous studies have often examined this relationship based on single indicators, neglecting the multi-dimensions of urban development and their integrated impact on influenza incidence in neighboring cities. METHODS A multidimensional urbanization evaluation framework was developed based on social, economic, and ecological dimensions to comprehensively assess urbanization. Then, we analyzed the impact of urbanization development on influenza incidence within and across cities using Bayesian spatiotemporal models and spatial Durbin models. Regional heterogeneity analysis was performed to investigate the impact of urbanization on influenza incidence within cities. RESULTS From 2014 to 2019, there were 5,062,254 influenza cases in 283 prefecture-level cities in China. Each standard deviation increment in comprehensive, social, and economic indexes of urbanization was associated with a 14.9% (95% CI: 6.1%, 24.3%), 9.9% (95% CI: 3.5%, 16.3%), and 13.4% (95% CI: 4.5%, 23.7%) increase in influenza incidence, respectively. The effects of urban development on influenza incidence varied significantly across regions, with the greatest impact found in southern China. Additionally, a significant positive spatial spillover effect of urbanization was observed on influenza incidence in surrounding cities. CONCLUSIONS Urbanization and its various dimensions were linked to increased risk of local influenza incidence, which also showed substantial positive spatial spillover effect to surrounding areas. During the rapid urbanization process in China, local governments should prioritize equity and accessibility in healthcare services and strengthen the coordinated prevention and control of influenza epidemics across cities.
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Affiliation(s)
- Hao Luo
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Climate Change and Health Centre, Shandong University, Jinan, China
| | - Yongbiao Cui
- Dezhou Center for Disease Control and Prevention, Dezhou, China
| | - Wenhao Yu
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Climate Change and Health Centre, Shandong University, Jinan, China
| | - Guoao Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Climate Change and Health Centre, Shandong University, Jinan, China
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Climate Change and Health Centre, Shandong University, Jinan, China
| | - Mengjie Geng
- Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Haitao Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Climate Change and Health Centre, Shandong University, Jinan, China.
| | - Wei Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Climate Change and Health Centre, Shandong University, Jinan, China.
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Deng P, Xue C, Yang T, Zheng B, Liu W, Yang L, Fei Y. Epidemiological analysis of influenza vaccination coverage in Pudong New Area, Shanghai (2013-2023): Implications for influenza vaccination strategies. Hum Vaccin Immunother 2024; 20:2412887. [PMID: 39387339 PMCID: PMC11469416 DOI: 10.1080/21645515.2024.2412887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Revised: 09/19/2024] [Accepted: 10/02/2024] [Indexed: 10/15/2024] Open
Abstract
Seasonal influenza remains a significant public health concern globally, with annual vaccinations as the most effectively preventive measure. This study examines influenza vaccination coverage rates across different age groups in Pudong New Area, Shanghai, China, from 2013 to 2023. This study extracted influenza vaccination data from the Shanghai Immunization Planning Information System (SIPIS) of the Center for Disease Control and Prevention Shanghai's Pudong New Area from 2013 to 2023. The analysis utilized weighted linear regression to compare vaccination rates over the study period. From 2013 to 2023, a cumulative total of 1,421,295 influenza vaccinations were administered in Pudong New Area, with the quadrivalent inactivated influenza vaccines (IIV4) and trivalent inactivated influenza vaccines (IIV3) comprising 56.8% and 42.9%, respectively. The overall average influenza vaccine coverage rate was 2.27% (95% CI: 2.26, 2.28). The 0-4 years group exhibited the highest average annual coverage rate of 22.52% (95% CI: 22.47, 22.57) among different age groups, in stark contrast to that of the 20-24 years age group, which had the lowest at 0.32% (95% CI: 0.31, 0.33). In terms of repeat vaccinations, a significant majority (86.87%) of recipients received only 1-2 doses, while just 13.13% received 3 or more doses. Although influenza vaccination coverage among preschool children in Pudong New Area is relatively high, it falls significantly short of WHO recommendations. Enhance the level of awareness of influenza vaccine among adults and provide a free influenza vaccination strategy for specific groups such as doctors, which is helpful to increase influenza vaccination rates among populations.
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Affiliation(s)
- Pengfei Deng
- Department of Immunology, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Caoyi Xue
- Department of Immunology, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Tian Yang
- Department of Immunology, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Bo Zheng
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
| | - Wenmin Liu
- Department of Immunology, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Laibao Yang
- Department of Immunology, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Yi Fei
- Department of Immunology, Shanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, China
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He Y, Luo K, Ni H, Kuang W, Fu L, Yi S, Lv Y, Zha W. Quantitative assessment of Public Health and Social Measures implementation and relaxation on influenza transmission during COVID-19 in China: SEIABR and GBDT models. J Glob Health 2024; 14:05038. [PMID: 39727104 DOI: 10.7189/jogh.14.05038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2024] Open
Abstract
Background Since 2019, China has implemented Public Health and Social Measures (PHSMs) to manage the coronavirus disease 2019 (COVID-19) outbreak. As the threat from SARS-CoV-2 diminished, these measures were relaxed, leading to increased respiratory infections and strained health care resources by mid-2023. Methods The study utilised WHO's FluNet and Oxford's COVID-19 Government Response Tracker to assess how policy shifts have affected influenza. It examined changes in influenza incidence, subtype prevalence, and epidemic cycles over three periods: pre-COVID-19 and pre-PHSMs, during COVID-19 and PHSMs, and post-COVID-19 and post-PHSMs. The SEIABR model estimated the transmission probability () and real-time reproduction number () across these periods, while a gradient boosting decision tree (GBDT) analysed the effects of PHSM indicators on influenza transmission. Results Results indicate that before PHSMs, the average incidence was 4.87 per 100 000, with a β-value of (7.95 ± 1.27) × 10-10 and Rt-value of 1.21 ± 0.16. During PHSMs, incidence dropped to 2.55 per 100 000, and β decreased to (3.17 ± 0.75) × 10-10 (Rt-value of 0.86 ± 0.20). Post-PHSMs, the incidence surged to 17.00 per 100 000, with β rising to 8.36 × 10-10 (Rt-value of 2.25). The GBDT model identified testing policies, public information campaigns, and workplace closures as the most impactful PHSM indicators. Conclusions PHSMs effectively mitigated the spread of influenza, providing a foundation for future policy development to prevent respiratory diseases.
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Affiliation(s)
- Yuxi He
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
| | - Kaiwei Luo
- Hunan Provincial Center for Disease Control and Prevention (Hunan Academy of Preventive Medicine), Changsha, Hu Nan, China
- Hunan Workstation for Emerging infectious Disease Control and Prevention, Changsha, Hu Nan, China
| | - Han Ni
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
| | - Wentao Kuang
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
| | - Liuyi Fu
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
| | - Shanghui Yi
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
| | - Yuan Lv
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
| | - Wenting Zha
- Hunan Key Laboratory of Molecular Epidemiology, School of Medicine, Hunan Normal University, Changsha, Hu Nan, China
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Wu K, Fan W, Wei J, Lu J, Ma X, Yuan Z, Huang Z, Zhong Q, Huang Y, Zou F, Wu X. Effects of fine particulate matter and its chemical constituents on influenza-like illness in Guangzhou, China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 290:117540. [PMID: 39689457 DOI: 10.1016/j.ecoenv.2024.117540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Revised: 12/10/2024] [Accepted: 12/10/2024] [Indexed: 12/19/2024]
Abstract
BACKGROUND Although the link between fine particulate matter (PM2.5) and influenza-like illness (ILI) is well established, the effect of the chemical constituents of PM2.5 on ILI remains unclear. This study aims to explore this effect in Guangzhou, China. METHODS Daily data on ILI cases, PM2.5 levels, and specific PM2.5 constituents (black carbon [BC], chlorine [Cl-], ammonia [NH4+], nitrate [NO3-], and sulfate [SO42-]) in Guangzhou, China, were collected for the period of 2014-2019. Additionally, data on gaseous pollutants and meteorological conditions were obtained. By using quasi-Poisson regression models, the association between exposure to PM2.5 and its constituents and ILI risk was estimated. Stratified subgroup analyses were performed by gender, age, and season to explore in depth the effects of these factors on disease risk. RESULTS Single-pollutant modeling results showed that an increase of one interquartile range (IQR) in Cl-, SO42-, PM2.5, NH4+, BC, and NO3- corresponded to relative risks of ILI of 1.046 (95 % CI: 1.004, 1.090) (lag03), 1.098 (95 % CI: 1.058, 1.139) (lag01), 1.091 (95 % CI: 1.054, 1.130) (lag02), 1.093 (95 % CI: 1.049, 1.138) (lag02), 1.111 (95 % CI: 1.074, 1.150) (lag03), and 1.103 (95 % CI: 1.061, 1.146) (lag03), respectively. Notably, the association between ILI and BC remained significant even after adjusting for PM2.5 mass. Subgroup analyses indicated that individuals aged 5-14 and 15-24 years may exhibit higher sensitivity to BC and Cl- exposure than other individuals. Furthermore, stronger associations were observed during the cold season than during the warm season. CONCLUSIONS Results showed that the mass and constituents of PM2.5 were significantly correlated with ILI. Specifically, the carbonaceous fractions of PM2.5 were found to have a pronounced effect on ILI. These findings underscore the importance of implementing effective measures to reduce the emission of specific sources of PM2.5 constituents to mitigate the risk of ILI. Nevertheless, limitations such as potential exposure misclassification and regional constraints should be considered.
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Affiliation(s)
- Keyi Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Weidong Fan
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
| | - Jianyun Lu
- Guangzhou Baiyun Center for Disease Control and Prevention, Guangzhou City, Guangdong 510440, China
| | - Xiaowei Ma
- Guangzhou Center for Disease Control and Prevention, Guangzhou City, Guangdong 510440, China
| | - Zelin Yuan
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Zhiwei Huang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Qi Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Yining Huang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China
| | - Fei Zou
- Department of Occupational Health and Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China.
| | - Xianbo Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), No.1023-1063, Shatai South Road, Baiyun District, Guangzhou 510515, China.
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Jia M, Li T, Jiang M, Dai P, Tang W, Xu Y, Wang Q, Li Q, Duan Y, Xiong Y, Han X, Li Z, Qian J, Feng L, Qi L, Yang W. Estimated number and incidence of influenza-associated acute respiratory infection cases in winter 2021/22 in Wanzhou District, China. Public Health 2024; 237:141-146. [PMID: 39388733 DOI: 10.1016/j.puhe.2024.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/22/2024] [Accepted: 09/12/2024] [Indexed: 10/12/2024]
Abstract
OBJECTIVES Understanding the burden of influenza-associated acute respiratory infection (ARI) and severe ARI (SARI) is crucial for public health decision-making. A population-based study with multiple data sources was conducted to estimate the burden of influenza-associated ARI in Wanzhou District, Chongqing, southern China. STUDY DESIGN Population-based surveillance study. METHODS Active surveillance of ARI was conducted in different levels of health facilities in the Wanzhou District between October 2021 and March 2022. Nasal or throat swabs were collected and tested for influenza viruses in hospital-based surveillance. A health utilisation survey was used to estimate health-seeking behaviour, and all electronic medical records were collected. An epidemiological model was used to estimate the disease burden. RESULTS There were an estimated 52,960 influenza-associated ARI (95 % confidence interval [CI]: 39,213-84,891), including 2,529 SARI cases (95 % CI: 1,385-21,712) during winter 2021/22 in the Wanzhou District. The incidence rate for all influenza-associated ARI and SARI was 3,385/100,000 and 162/100,000, respectively. A higher incidence rate of influenza-associated ARI was observed among individuals aged <50 years, while a higher influenza-associated SARI rate was observed in those aged ≥50 years. CONCLUSIONS Using an epidemiological model with data from multiple sources, this study documented a substantial burden of influenza-associated ARI in the Wanzhou District, highlighting the need for influenza vaccination and providing a possible foundation for public health decision-making.
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Affiliation(s)
- Mengmeng Jia
- National Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102629, China
| | - Tingting Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400016, China
| | - Mingyue Jiang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Peixi Dai
- Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400016, China
| | - Yunshao Xu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Qing Wang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Qing Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400016, China
| | - Yuping Duan
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Yu Xiong
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400016, China
| | - Xuan Han
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Zhuorong Li
- School of Public Health, Chongqing Medical University, Chongqing, 400016, China
| | - Jie Qian
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400016, China.
| | - Weizhong Yang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
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Yang M, Yi L, Jia F, Zeng X, Liu Z. Characteristics and outcome of influenza-associated encephalopathy/encephalitis among children in China. Clinics (Sao Paulo) 2024; 79:100475. [PMID: 39096859 PMCID: PMC11345302 DOI: 10.1016/j.clinsp.2024.100475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 05/30/2024] [Accepted: 07/21/2024] [Indexed: 08/05/2024] Open
Abstract
BACKGROUND Influenza-Associated Encephalopathy/Encephalitis (IAE) is characterized by high incidence and poor prognosis. The aim of this study is to describe the clinical features and outcomes of IAE in pediatric patients. METHODS We performed a retrospective review of hospitalized cases of laboratory-confirmed influenza infection between January 2018 and December 2021. Demographic, clinical, imaging, treatment and outcome data were collected. Statistical analysis was performed using SPSS software. RESULTS Of 446 children hospitalized with influenza, 71 cases were identified with a diagnosis of IAE. The median age was 3 years and 46 (64.8 %) were younger than 5 years. Only one patient was vaccinated for seasonal influenza. 46 (64.8 %) patients had abnormal electroencephalogram examination and 47 (66.2 %) had abnormal brain MRI or CT findings. 68 (95.8 %) patients were treated with oseltamivir/peramivir. 12 (16.9 %) patients suffered mortality. Non-survivors were more likely to have lower Glasgow coma score (median 7), longer duration of fever (median 3 days), with underlying medical conditions (P = 0.006), and complications including sepsis (P = 0.003), shock (P < 0.001), respiratory failure (P = 0.006), acute renal failure (P = 0.001), myocardial damage (P < 0.001), coagulation disorders (P = 0.03), electrolyte disturbance (P = 0.001) and hyperlactacidemia (P = 0.003). Non-survivors had higher percentages of corticosteroids (P = 0.003) and immunoglobulin (P = 0.003) treatments compared to survivors. CONCLUSIONS Children with IAE have a high mortality rate. Lower Glasgow coma score, longer duration of fever, with underlying medical conditions and complications pose a great risk to poor prognosis. Influenza vaccination is recommended to all eligible children.
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Affiliation(s)
- Min Yang
- Department of Pediatric Intensive Care Unit, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan, China
| | - Ling Yi
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan, China; Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fenglin Jia
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan, China; Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiaobin Zeng
- Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan, China; Medical Equipment Department, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhongqiang Liu
- Department of Pediatric Intensive Care Unit, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, Sichuan, China.
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Yin Y, Lai M, Lu K, Jiang X, Chen Z, Li T, Wang L, Zhang Y, Peng Z. Association between ambient temperature and influenza prevalence: A nationwide time-series analysis in 201 Chinese cities from 2013 to 2018. ENVIRONMENT INTERNATIONAL 2024; 189:108783. [PMID: 38823156 DOI: 10.1016/j.envint.2024.108783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 05/20/2024] [Accepted: 05/27/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Temperature affects influenza transmission; however, currently, limited evidence exists about its effect in China at the national and city levels as well as how temperature can be integrated into influenza interventions. METHODS Meteorological, pollutant, and influenza data from 201 cities in mainland China between 2013 and 2018 were analyzed at both the city and national levels to investigate the relationship between temperature and influenza prevalence. We examined the impact of temperature on the time-varying reproduction number (Rt) using generalized additive quasi-Poisson regression models combined with the distributed lag nonlinear model. Threshold temperatures were determined for seven regions based on the early warning threshold of serious influenza outbreaks, set at Rt = 1.2. A multivariate random-effects meta-analysis was employed to assess region-specific associations. The excess risk (ER) index was defined to investigate the correlation between Rt and temperature, modified based on seasonal and regional characteristics. RESULTS At the national level and in the central, northern, northwestern, and southern regions, temperature was found to be negatively correlated with relative risk, whereas the shapes of the data curves for the eastern, southwestern, and northeastern regions were not well defined. Low temperatures had an observable effect on influenza prevalence; however, the effects of high temperatures were not obvious. At an Rt of 1.2, the threshold temperatures for reaching a warning for serious influenza outbreaks were - 24.3 °C in the northeastern region, 16.6 °C in the northwestern region, and between 1℃ and 10 °C in other regions. CONCLUSION The study findings revealed that temperature had a varying effect on influenza transmission trends (Rt) across different regions in China. By identifying region-specific temperature thresholds at Rt = 1.2, more effective early warning systems for influenza outbreaks could be tailored. These findings emphasize the significance of the region-specific adaptation of influenza prevention and control measures.
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Affiliation(s)
- Yi Yin
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Miao Lai
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Kailai Lu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xin Jiang
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ziying Chen
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liping Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanping Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhihang Peng
- School of Public Health, Nanjing Medical University, Nanjing 211166, China; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
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Chen H, Xiao M. Seasonality of influenza-like illness and short-term forecasting model in Chongqing from 2010 to 2022. BMC Infect Dis 2024; 24:432. [PMID: 38654199 PMCID: PMC11036656 DOI: 10.1186/s12879-024-09301-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/07/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Influenza-like illness (ILI) imposes a significant burden on patients, employers and society. However, there is no analysis and prediction at the hospital level in Chongqing. We aimed to characterize the seasonality of ILI, examine age heterogeneity in visits, and predict ILI peaks and assess whether they affect hospital operations. METHODS The multiplicative decomposition model was employed to decompose the trend and seasonality of ILI, and the Seasonal Auto-Regressive Integrated Moving Average with exogenous factors (SARIMAX) model was used for the trend and short-term prediction of ILI. We used Grid Search and Akaike information criterion (AIC) to calibrate and verify the optimal hyperparameters, and verified the residuals of the multiplicative decomposition and SARIMAX model, which are both white noise. RESULTS During the 12-year study period, ILI showed a continuous upward trend, peaking in winter (Dec. - Jan.) and a small spike in May-June in the 2-4-year-old high-risk group for severe disease. The mean length of stay (LOS) in ILI peaked around summer (about Aug.), and the LOS in the 0-1 and ≥ 65 years old severely high-risk group was more irregular than the others. We found some anomalies in the predictive analysis of the test set, which were basically consistent with the dynamic zero-COVID policy at the time. CONCLUSION The ILI patient visits showed a clear cyclical and seasonal pattern. ILI prevention and control activities can be conducted seasonally on an annual basis, and age heterogeneity should be considered in the health resource planning. Targeted immunization policies are essential to mitigate potential pandemic threats. The SARIMAX model has good short-term forecasting ability and accuracy. It can help explore the epidemiological characteristics of ILI and provide an early warning and decision-making basis for the allocation of medical resources related to ILI visits.
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Affiliation(s)
- Huayong Chen
- School of Public Health, Research Center for Medical and Social Development, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, 400016, Chongqing, P. R. China
| | - Mimi Xiao
- School of Public Health, Research Center for Medical and Social Development, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, 400016, Chongqing, P. R. China.
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Zhang X, Shen P, Liu J, Ji X, Su K, Hu R, Chen C, Fang H, Jin X, Lin H, Sun Y, Yan LL. Evaluating the effectiveness and cost-effectiveness of free influenza vaccination policy for older adults in Yinzhou, China: Study protocol of a real-world analyses. Vaccine 2023:S0264-410X(23)00790-9. [PMID: 37419850 DOI: 10.1016/j.vaccine.2023.06.087] [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: 04/05/2023] [Revised: 06/28/2023] [Accepted: 06/29/2023] [Indexed: 07/09/2023]
Abstract
BACKGROUND Influenza causes excessive morbidity and mortality among older adults. While influenza vaccine provides protection against its infection, the vaccination coverage in China among older adults has been very low. Previous evidence on the cost-effectiveness of government-sponsored free influenza vaccination programs in China was primarily based on literature data, which might not always reflect real-world patient populations. The Yinzhou Health Information System (YHIS) is a regional database that captures electronic health records, insurance claims data, etc. for all residents in Yinzhou district, Zhejiang province, China. We will use YHIS to study the effectiveness, influenza-related direct medical cost and cost-effectiveness analysis (CEA) of the free influenza vaccination program for older adults. In this paper, we describe the study design and innovations in detail. METHODS We will establish a retrospective cohort of permanent older residents aged 65 and over, using YHIS between 2016 and 2021. We will estimate the vaccine coverage rate, influenza incidence rate and influenza-related direct medical cost from 2016 to 2021. Regression discontinuity will be used to estimate vaccine effectiveness for the 2020/2021 season. We will build a decision tree model to compare the cost-effectiveness of three influenza vaccination options (free trivalent influenza vaccine, free quadrivalent influenza vaccine, and no policy) from both societal and health system perspectives. Parameter inputs will be gathered from both YHIS and published literature. We will calculate the incremental cost-effectiveness ratio with cost and quality-adjusted life years (QALYs) discounted at 5 % annually. DISCUSSION Our CEA solidifies multiple sources including regional real-world data and literature for a rigorous evaluation of the government-sponsored free influenza vaccination program. The results will provide real-world evidence from real-world data on the cost-effectiveness of a real-world policy. Our findings are expected to support evidence-based policy making and to promote health for older adults.
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Affiliation(s)
- Xian Zhang
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China; MindRank Ltd., Hangzhou, China
| | - Peng Shen
- Yinzhou District Disease Prevention and Control Center, Ningbo, Zhejiang, China
| | | | - Xinyue Ji
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Kehan Su
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Rundong Hu
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Chen Chen
- School of Public Health, Wuhan University, Wuhan, Hubei, China
| | - Hai Fang
- China Center for Health Development Studies, Peking University, Beijing, China
| | | | - Hongbo Lin
- Yinzhou District Disease Prevention and Control Center, Ningbo, Zhejiang, China
| | - Yexiang Sun
- Yinzhou District Disease Prevention and Control Center, Ningbo, Zhejiang, China
| | - Lijing L Yan
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China; School of Public Health, Wuhan University, Wuhan, Hubei, China; PKU Institute for Global Health and Development, Peking University, Beijing, China; Ningbo Eye Hospital, Wenzhou Medical University, Ningbo, Zhejiang, China.
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10
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Li L, Liu T, Wang Q, Ding Y, Jiang Y, Wu Z, Wang X, Dou H, Jia Y, Jiao B. Genetic characterization and whole-genome sequencing-based genetic analysis of influenza virus in Jining City during 2021-2022. Front Microbiol 2023; 14:1196451. [PMID: 37426015 PMCID: PMC10324579 DOI: 10.3389/fmicb.2023.1196451] [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: 03/29/2023] [Accepted: 05/02/2023] [Indexed: 07/11/2023] Open
Abstract
Background The influenza virus poses a significant threat to global public health due to its high mutation rate. Continuous surveillance, development of new vaccines, and public health measures are crucial in managing and mitigating the impact of influenza outbreaks. Methods Nasal swabs were collected from individuals with influenza-like symptoms in Jining City during 2021-2022. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect influenza A viruses, followed by isolation using MDCK cells. Additionally, nucleic acid detection was performed to identify influenza A H1N1, seasonal H3N2, B/Victoria, and B/Yamagata strains. Whole-genome sequencing was conducted on 24 influenza virus strains, and subsequent analyses included characterization, phylogenetic construction, mutation analysis, and assessment of nucleotide diversity. Results A total of 1,543 throat swab samples were collected. The study revealed the dominance of the B/Victoria influenza virus in Jining during 2021-2022. Whole-genome sequencing showed co-prevalence of B/Victoria influenza viruses in the branches of Victoria clade 1A.3a.1 and Victoria clade 1A.3a.2, with a higher incidence observed in winter and spring. Comparative analysis demonstrated lower similarity in the HA, MP, and PB2 gene segments of the 24 sequenced influenza virus strains compared to the Northern Hemisphere vaccine strain B/Washington/02/2019. Mutations were identified in all antigenic epitopes of the HA protein at R133G, N150K, and N197D, and the 17-sequence antigenic epitopes exhibited more than 4 amino acid variation sites, resulting in antigenic drift. Moreover, one sequence had a D197N mutation in the NA protein, while seven sequences had a K338R mutation in the PA protein. Conclusion This study highlights the predominant presence of B/Victoria influenza strain in Jining from 2021 to 2022. The analysis also identified amino acid site variations in the antigenic epitopes, contributing to antigenic drift.
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Affiliation(s)
- Libo Li
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Tiantian Liu
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Qingchuan Wang
- Department of Medicine, Jining Municipal Government Hospital, Jining, China
| | - Yi Ding
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Yajuan Jiang
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Zengding Wu
- Department of AI and Bioinformatics, Nanjing Chengshi BioTech (TheraRNA) Co., Ltd., Nanjing, China
| | - Xiaoyu Wang
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Huixin Dou
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Yongjian Jia
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
| | - Boyan Jiao
- Department of Laboratory, Jining Center for Disease Control and Prevention, Jining, China
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11
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Deng X, Chen Z, Zhao Z, Chen J, Li M, Yang J, Yu H. Regional characteristics of influenza seasonality patterns in mainland China, 2005-2017: a statistical modeling study. Int J Infect Dis 2023; 128:91-97. [PMID: 36581188 DOI: 10.1016/j.ijid.2022.12.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 12/06/2022] [Accepted: 12/21/2022] [Indexed: 12/27/2022] Open
Abstract
OBJECTIVES To quantify the seasonal and antigenic characteristics of influenza to help understand influenza activity and inform vaccine recommendations. METHODS We employed a generalized linear model with harmonic terms to quantify the seasonal pattern of influenza in China from 2005-2017, including amplitude (circulatory intensity), semiannual periodicity (given two peaks a year), annual peak time, and epidemic duration. The antigenic differences were distinguished as antigenic similarity between 2009 and 2020. We categorized regions above 33° N, between 27° N and 33° N, and below 27° N as the north, central, and south regions, respectively. RESULTS We estimated that the amplitude in the north region (median: 0.019, 95% CI: 0.018-0.021) was significantly higher than that in the central region (median: 0.011, 95% CI: 0.01-0.012, P <0.001) and south region (median: 0.008, 95% CI: 0.007-0.008, P <0.001) for influenza A virus subtype H3N2 (A/H3N2). The A/H3N2 in the central region had a semiannual periodicity (median: 0.548, 95% CI: 0.517-0.577), while no semiannual pattern was found in other regions or subtypes/lineages. The antigenic similarity was low (below 50% in the 2009-2010, 2014-2015, 2016-2018, and 2019-2020 seasons) for A/H3N2. CONCLUSION Our study depicted the seasonal pattern differences and antigenic differences of influenza in China, which provides information for vaccination strategies.
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Affiliation(s)
- Xiaowei Deng
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Zhiyuan Chen
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Zeyao Zhao
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Junbo Chen
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Mei Li
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Juan Yang
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Hongjie Yu
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China; National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
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12
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Lian XY, Xi L, Zhang ZS, Yang LL, Du J, Cui Y, Li HJ, Zhang WX, Wang C, Liu B, Yang YN, Cui F, Lu QB. Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China. J Med Virol 2023; 95:e28514. [PMID: 36661040 DOI: 10.1002/jmv.28514] [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: 10/10/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 01/21/2023]
Abstract
This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM2.5 ), particulate matter 10 (PM10 ), sulphur dioxide (SO2 ), nitrogen dioxide (NO2 ), and carbon monoxide (CO), and a low concentration of ozone (O3 ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM10 , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.
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Affiliation(s)
- Xin Yao Lian
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China
| | - Lu Xi
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Zhong Song Zhang
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China
| | - Li Li Yang
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Juan Du
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Yan Cui
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Hong Jun Li
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Wan Xue Zhang
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Chao Wang
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Bei Liu
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Yan Na Yang
- Center for Disease Control and Prevention of Beijing Economic and Technological Development Area, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Fuqiang Cui
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China.,Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Qing Bin Lu
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China.,Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
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13
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Zhang ZS, Xi L, Yang LL, Lian XY, Du J, Cui Y, Li HJ, Zhang WX, Wang C, Liu B, Yang YN, Cui F, Lu QB. Impact of air pollutants on influenza-like illness outpatient visits under urbanization process in the sub-center of Beijing, China. Int J Hyg Environ Health 2023; 247:114076. [PMID: 36427387 DOI: 10.1016/j.ijheh.2022.114076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 11/01/2022] [Accepted: 11/15/2022] [Indexed: 11/23/2022]
Abstract
Air pollutants can cause serious harm to human health and a variety of respiratory diseases. This study aimed to explore the associations between air pollutants and outpatient visits for influenza-like illness (ILI) under urbanization process in the sub-center of Beijing. The data of ILI in sub-center of Beijing from April 1, 2014 to December 31, 2020 were obtained from Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and holidays. A total of 322,559 patients with ILI were included. The results showed that in the early urbanization period, the effects of PM2.5, PM10, SO2, O3, and CO on lag0 day, and PM2.5, PM10, O3, and CO on lag1 day were not significant. In the later urbanization period, AQI and the concentrations of PM2.5, PM10, SO2, NO2 and CO on lag1 day were all significantly associated with an increased risk of outpatient visits for ILI, which increased by 0.34% (95%CI 0.23%, 0.45%), 0.42% (95%CI 0.29%, 0.56%), 0.44% (95%CI 0.33%, 0.55%), 0.36% (95%CI 0.24%, 0.49%), 0.91% (95%CI 0.62%, 1.21%) and 0.38% (95%CI 0.26%, 0.49%). The concentration of O3 on lag1 day was significantly associated with a decreased risk of outpatient visits for ILI, which decreased by 0.21% (95%CI 0.04%, 0.39%). We found that the urbanization process had significantly aggravated the impact of air pollutants on ILI outpatient visits. These findings expand the current knowledge of ILI outpatient visits correlated with air pollutants under urbanization process.
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Affiliation(s)
- Zhong-Song Zhang
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, 100191, PR China
| | - Lu Xi
- Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Tongzhou Center for Diseases Prevention and Control, Beijing, 101100, PR China
| | - Li-Li Yang
- Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Tongzhou Center for Diseases Prevention and Control, Beijing, 101100, PR China
| | - Xin-Yao Lian
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, 100191, PR China
| | - Juan Du
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, 100191, PR China
| | - Yan Cui
- Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Tongzhou Center for Diseases Prevention and Control, Beijing, 101100, PR China
| | - Hong-Jun Li
- Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Tongzhou Center for Diseases Prevention and Control, Beijing, 101100, PR China
| | - Wan-Xue Zhang
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, 100191, PR China
| | - Chao Wang
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, 100191, PR China
| | - Bei Liu
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, 100191, PR China
| | - Yan-Na Yang
- Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Tongzhou Center for Diseases Prevention and Control, Beijing, 101100, PR China
| | - Fuqiang Cui
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, 100191, PR China; Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, 100191, PR China.
| | - Qing-Bin Lu
- Department of Laboratorial Science and Technology & Vaccine Research Center, School of Public Health, Peking University, Beijing, 100191, PR China; Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, 100191, PR China.
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14
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Li J, Zhang Y, Zhang X, Liu L. Influenza and Universal Vaccine Research in China. Viruses 2022; 15:116. [PMID: 36680158 PMCID: PMC9861666 DOI: 10.3390/v15010116] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/23/2022] [Accepted: 12/27/2022] [Indexed: 01/03/2023] Open
Abstract
Influenza viruses usually cause seasonal influenza epidemics and influenza pandemics, resulting in acute respiratory illness and, in severe cases, multiple organ complications and even death, posing a serious global and human health burden. Compared with other countries, China has a large population base and a large number of influenza cases and deaths. Currently, influenza vaccination remains the most cost-effective and efficient way to prevent and control influenza, which can significantly reduce the risk of influenza virus infection and serious complications. The antigenicity of the influenza vaccine exhibits good protective efficacy when matched to the seasonal epidemic strain. However, when influenza viruses undergo rapid and sustained antigenic drift resulting in a mismatch between the vaccine strain and the epidemic strain, the protective effect is greatly reduced. As a result, the flu vaccine must be reformulated and readministered annually, causing a significant drain on human and financial resources. Therefore, the development of a universal influenza vaccine is necessary for the complete fight against the influenza virus. By statistically analyzing cases related to influenza virus infection and death in China in recent years, this paper describes the existing marketed vaccines, vaccine distribution and vaccination in China and summarizes the candidate immunogens designed based on the structure of influenza virus, hoping to provide ideas for the design and development of new influenza vaccines in the future.
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Affiliation(s)
| | | | | | - Longding Liu
- Key Laboratory of Systemic Innovative Research on Virus Vaccine, Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming 650118, China
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15
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Yang J, Yang Z, Qi L, Li M, Liu D, Liu X, Tong S, Sun Q, Feng L, Ou CQ, Liu Q. Influence of air pollution on influenza-like illness in China: a nationwide time-series analysis. EBioMedicine 2022; 87:104421. [PMID: 36563486 PMCID: PMC9800295 DOI: 10.1016/j.ebiom.2022.104421] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 11/21/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Evidence concerning effects of air pollution on influenza-like illness (ILI) from multi-center is limited and little is known about how regional factors might modify this relationship. METHODS In this ecological study, ILI cases defined as outpatients with temperature ≥38 °C, accompanied by cough or sore throat, were collected from National Influenza Surveillance Network in China. We adopted generalized additive model with quasi-Poisson to estimate province-specific association between air pollution and ILI in 30 Chinese provinces during 2015-2019, after adjusting for time trend and meteorological factors. We then pooled province-specific association by using random-effect meta-analysis. Potential effect modifications of season and regional characteristics were explored. FINDINGS A total of 26, 004, 853 ILI cases and 777, 223, 877 hospital outpatients were collected. In general, effects of air pollutants were acute. An inter-quartile range increase of PM2.5, SO2, PM10, NO2 and CO at lag0, and O3 at lag0-2 was associated with 3.08% (95% CI: 1.91%, 4.27%), 3.00% (1.86%, 4.16%), 6.46% (4.71%, 8.25%), 7.21% (5.73%, 8.71%), 4.37% (3.05%, 5.70%), and -9.26% (-11.32%, -7.14%) change of ILI at national level, respectively. Associations between air pollutants and ILI varied by season and regions, with higher effect estimates in cold season, eastern and central regions and provinces with more humid condition and larger population. INTERPRETATION This study indicated that most air pollutants increased the risk of ILI in China. Our findings might provide implications for the development of policies to protect public health from air pollution and influenza. FUNDING National Natural Science Foundation of China and Chongqing Health Commission Program.
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Affiliation(s)
- Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China,Corresponding author.
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Mengmeng Li
- Department of Cancer Prevention, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Di Liu
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China
| | - Xiaobo 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, 102206, China
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Qinghua Sun
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China,Corresponding author.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Qiyong 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, 102206, China,Corresponding author.
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16
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Zhang R, Peng Z, Meng Y, Song H, Wang S, Bi P, Li D, Zhao X, Yao X, Li Y. Temperature and influenza transmission: Risk assessment and attributable burden estimation among 30 cities in China. ENVIRONMENTAL RESEARCH 2022; 215:114343. [PMID: 36115415 DOI: 10.1016/j.envres.2022.114343] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/19/2022] [Accepted: 09/11/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Many studies have explored the epidemiological characteristics of influenza. However, most previous studies were conducted in a specific region without a national picture which is important to develop targeted strategies and measures on influenza control and prevention. OBJECTIVES To explore the association between ambient temperature and incidence of influenza, to estimate the attributable risk from temperature in 30 Chinese cities with different climatic characteristics for a national picture, and to identify the vulnerable populations for national preventative policy development. METHODS Daily meteorological and influenza incidence data from the 30 Chinese cities over the period 2016-19 were collected. We estimated the city-specific association between daily mean temperature and influenza incidence using a distributed lag non-linear model and evaluated the pooled effects using multivariate meta-analysis. The attributable fractions compared with reference temperature were calculated. Stratified analyses were performed by region, sex and age. RESULTS Overall, an N-shape relationship between temperature and influenza incidence was found in China. The cumulative relative risk of the peak risk temperature (5.1 °C) was 2.13 (95%CI: 1.41, 3.22). And 60% (95%eCI: 54.3%, 64.3%) of influenza incidence was attributed to ambient temperature during the days with sensitive temperatures (1.6°C-14.4 °C). The ranges of sensitive temperatures and the attributable disease burden due to temperatures varied for different populations and regions. The residents in South China and the children aged ≤5 and 6-17 years had higher fractions attributable to sensitive temperatures. CONCLUSIONS Tailored preventions targeting on most vulnerable populations and regions should be developed to reduce influenza burden from sensitive temperatures.
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Affiliation(s)
- Rui Zhang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhibin Peng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yujie Meng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hejia Song
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Songwang Wang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Bi
- School of Public Health, The University of Adelaide, South Australia, Australia
| | - Dan Li
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiang Zhao
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaoyuan Yao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yonghong Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
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17
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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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Xu MM, Kang JY, Ji S, Wei YY, Wei SL, Ye JJ, Wang YG, Shen JL, Wu HM, Fei GH. Melatonin Suppresses Macrophage M1 Polarization and ROS-Mediated Pyroptosis via Activating ApoE/LDLR Pathway in Influenza A-Induced Acute Lung Injury. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:2520348. [PMID: 36425057 PMCID: PMC9681554 DOI: 10.1155/2022/2520348] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/07/2022] [Indexed: 11/17/2023]
Abstract
Influenza virus infection is one of the strongest pathogenic factors for the development of acute lung injury (ALI)/ acute respiratory distress syndrome (ARDS). However, the underlying cellular and molecular mechanisms have not been clarified. In this study, we aim to investigate whether melatonin modulates macrophage polarization, oxidative stress, and pyroptosis via activating Apolipoprotein E/low-density lipoprotein receptor (ApoE/LDLR) pathway in influenza A-induced ALI. Here, wild-type (WT) and ApoE-/- mice were instilled intratracheally with influenza A (H3N2) and injected intraperitoneally with melatonin for 7 consecutive days. In vitro, WT and ApoE-/- murine bone marrow-derived macrophages (BMDMs) were pretreated with melatonin before H3N2 stimulation. The results showed that melatonin administration significantly attenuated H3N2-induced pulmonary damage, leukocyte infiltration, and edema; decreased the expression of proinflammatory M1 markers; enhanced anti-inflammatory M2 markers; and switched the polarization of alveolar macrophages (AMs) from M1 to M2 phenotype. Additionally, melatonin inhibited reactive oxygen species- (ROS-) mediated pyroptosis shown by downregulation of malonaldehyde (MDA) and ROS levels as well as inhibition of the NLRP3/GSDMD pathway and lactate dehydrogenase (LDH) release. Strikingly, the ApoE/LDLR pathway was activated when melatonin was applied in H3N2-infected macrophages and mice. ApoE knockout mostly abrogated the protective impacts of melatonin on H3N2-induced ALI and its regulatory ability on macrophage polarization, oxidative stress, and pyroptosis. Furthermore, recombinant ApoE3 (re-ApoE3) inhibited H3N2-induced M1 polarization of BMDMs with upregulation of MT1 and MT2 expression, but re-ApoE2 and re-ApoE4 failed to do this. Melatonin combined with re-ApoE3 played more beneficial protective effects on modulating macrophage polarization, oxidative stress, and pyroptosis in H3N2-infected ApoE-/- BMDMs. Our study indicated that melatonin attenuated influenza A- (H3N2-) induced ALI by inhibiting the M1 polarization of pulmonary macrophages and ROS-mediated pyroptosis via activating the ApoE/LDLR pathway. This study suggested that melatonin-ApoE/LDLR axis may serve as a novel therapeutic strategy for influenza virus-induced ALI.
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Affiliation(s)
- Meng-Meng Xu
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Jia-Ying Kang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Shuang Ji
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Yuan-Yuan Wei
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Si-Liang Wei
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Jing-Jing Ye
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Yue-Guo Wang
- Department of Emergency Critical Care Medicine, First Affiliated Hospital of Anhui Provincial Hospital, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, 230001 Anhui, China
| | - Ji-Long Shen
- Provincial Laboratory of Microbiology and Parasitology of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Hui-Mei Wu
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Anhui Geriatric Institute, Department of Geriatric Respiratory Critical and Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
| | - Guang-He Fei
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
- Key Laboratory of Respiratory Disease Research and Medical Transformation of Anhui Province, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui, China
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Zhang J, Nian X, Li X, Huang S, Duan K, Li X, Yang X. The Epidemiology of Influenza and the Associated Vaccines Development in China: A Review. Vaccines (Basel) 2022; 10:1873. [PMID: 36366381 PMCID: PMC9692979 DOI: 10.3390/vaccines10111873] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/28/2022] [Accepted: 11/03/2022] [Indexed: 12/28/2023] Open
Abstract
Influenza prevention and control has been one of the biggest challenges encountered in the public health domain. The vaccination against influenza plays a pivotal role in the prevention of influenza, particularly for the elderly and small children. According to the epidemiology of influenza in China, the nation is under a heavy burden of this disease. Therefore, as a contribution to the prevention and control of influenza in China through the provision of relevant information, the present report discusses the production and batch issuance of the influenza vaccine, analysis of the vaccination status and vaccination rate of the influenza vaccine, and the development trend of the influenza vaccine in China.
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Affiliation(s)
- Jiayou Zhang
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
| | - Xuanxuan Nian
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
| | - Xuedan Li
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
| | - Shihe Huang
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
| | - Kai Duan
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
| | - Xinguo Li
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
| | - Xiaoming Yang
- National Engineering Technology Research Center for Combined Vaccines, Wuhan 430207, China
- Wuhan Institute of Biological Products Co., Ltd., Wuhan 430207, China
- China National Biotech Group Company Ltd., Beijing 100029, China
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20
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Yuan G, Wang H, Zhao Y, Mao E, Li M, Wang R, Zhou F, Jin S, Zhang Z, Xu K, Xu J, Liang S, Li X, Jiang L, Zhang L, Song J, Yang T, Guo J, Zhang H, Zhou Y, Wang S, Qiu C, Jiang N, Ai J, Wu J, Zhang W. Early identification and severity prediction of acute respiratory infection (ESAR): a study protocol for a randomized controlled trial. BMC Infect Dis 2022; 22:632. [PMID: 35858876 PMCID: PMC9296892 DOI: 10.1186/s12879-022-07552-7] [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: 05/05/2022] [Accepted: 06/17/2022] [Indexed: 11/21/2022] Open
Abstract
Background The outbreak of SARS-CoV-2 at the end of 2019 sounded the alarm for early inspection on acute respiratory infection (ARI). However, diagnosis pathway of ARI has still not reached a consensus and its impact on prognosis needs to be further explored. Methods ESAR is a multicenter, open-label, randomized controlled, non-inferiority clinical trial on evaluating the diagnosis performance and its impact on prognosis of ARI between mNGS and multiplex PCR. Enrolled patients will be divided into two groups with a ratio of 1:1. Group I will be directly tested by mNGS. Group II will firstly receive multiplex PCR, then mNGS in patients with severe infection if multiplex PCR is negative or inconsistent with clinical manifestations. All patients will be followed up every 7 days for 28 days. The primary endpoint is time to initiate targeted treatment. Secondary endpoints include incidence of significant events (oxygen inhalation, mechanical ventilation, etc.), clinical remission rate, and hospitalization length. A total of 440 participants will be enrolled in both groups. Discussion ESAR compares the efficacy of different diagnostic strategies and their impact on treatment outcomes in ARI, which is of great significance to make precise diagnosis, balance clinical resources and demands, and ultimately optimize clinical diagnosis pathways and treatment strategies. Trial registration Clinicaltrial.gov, NCT04955756, Registered on July 9th 2021.
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Affiliation(s)
- Guanmin Yuan
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Hongyu Wang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Yuanhan Zhao
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Enqiang Mao
- Departments of Emergency, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Mengjiao Li
- Departments of Emergency, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Ruilan Wang
- Department of Critical Care Medicine, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Fangqing Zhou
- Department of Critical Care Medicine, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Shanshan Jin
- Department of Critical Care Medicine, Shanghai General Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Ziqiang Zhang
- Department of Infectious Disease, Tongji Hospital, School of Medicine of Tongji University, Shanghai, China.,Department of Respiratory and Critical Care Medicine, Tongji Hospital, School of Medicine of Tongji University, Shanghai, China
| | - Ke Xu
- Department of Infectious Disease, Tongji Hospital, School of Medicine of Tongji University, Shanghai, China.,Department of Respiratory and Critical Care Medicine, Tongji Hospital, School of Medicine of Tongji University, Shanghai, China
| | - Jinfu Xu
- Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Shuo Liang
- Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xiang Li
- Department of Critical Care Medicine, Minhang Hospital, Fudan University, Shanghai, 201199, China
| | - Lijing Jiang
- Department of Critical Care Medicine, Minhang Hospital, Fudan University, Shanghai, 201199, China
| | - Lu Zhang
- Department of Critical Care Medicine, Minhang Hospital, Fudan University, Shanghai, 201199, China
| | - Jieyu Song
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Tao Yang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Jinxin Guo
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Haocheng Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Yang Zhou
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Sen Wang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Chao Qiu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Ning Jiang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China
| | - Jingwen Ai
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China.
| | - Jing Wu
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China.
| | - Wenhong Zhang
- Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, No. 12 Middle Urumqi Road, Jing'an, Shanghai, 200040, China. .,National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China. .,Key Laboratory of Medical Molecular Virology (MOE/MOH), Shanghai Medical College, Fudan University, Shanghai, China.
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21
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Qi L, Liu T, Gao Y, Li Q, Tang W, Tian D, Su K, Xiong Y, Yang J, Feng L, Liu Q. Effect of absolute humidity on influenza activity across different climate regions in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:49373-49384. [PMID: 35218485 DOI: 10.1007/s11356-022-19279-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
Until now, we have no thorough understanding the role of absolute humidity on influenza activity, especially in tropical and subtropical areas. In this study, we investigated the relationship between absolute humidity and influenza activity in seven municipalities/provinces covering different climatic zones in China. Weekly meteorological data and influenza surveillance data in seven provinces/municipalities in China were collected from January 2012 to December 2019. A distributed lag nonlinear model was adopted to investigate the association between absolute humidity (AH) and influenza activity in each study site. Then, seven study sites were grouped into three regions: northern, intermediate, and southernmost regions. A multivariate meta-analysis was applied to estimate the exposure-lag-response associations in three regions. The province-specific or municipality-specific curves appeared to be nonlinear, and the association between influenza activity and AH varied across regions. In Beijing and Tianjin, located in northern China, the cumulative relative risks (RRs) increased as weekly average AHmean fell below 3.41 g/m3 and 6.62 g/m3. In Guangdong and Hainan, located in southernmost China, the risk of influenza activity increased with rising average AHmean with 16.74 g/m3 and 20.18 g/m3 as the break points. In Shanghai, Zhejiang, and Chongqing, the relationship between weekly average AHmean and influenza could be described as U-shaped curves, with the lowest RRs when weekly average AHmean was 11.95 g/m3, 11.94 g/m3, and 15.96 g/m3, respectively. Meta-analysis results showed the cumulative RRs significantly increased as weekly average AHmean fell below 3.86 g/m3 in the northern region, whereas significantly increased as weekly average AHmean rose above 18.46 g/m3 and 15.22 g/m3 in intermediate and southernmost regions, respectively. Both low and high AH might increase influenza risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.
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Affiliation(s)
- Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
- 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, 102206, China
| | - Tian Liu
- Jingzhou Center for Disease Control and Prevention, Hubei, 434000, China
| | - Yuan Gao
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, 518107, China
| | - Kun Su
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Yu Xiong
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China.
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
| | - Qiyong 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, 102206, China.
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22
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Wu L, Guo X, Liu J, Ma X, Huang Z, Sun X. Evaluation of influenza vaccination coverage in Shanghai city during the 2016/17 to 2020/21 influenza seasons. Hum Vaccin Immunother 2022; 18:2075211. [PMID: 35621293 PMCID: PMC9481150 DOI: 10.1080/21645515.2022.2075211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Influenza is a common infectious disease resulting in substantial morbidity and mortality globally. The most effective strategy for preventing influenza is annual vaccination; however, the coverage rate of the influenza vaccine in Shanghai has not been well explored or reported. Therefore, this study aimed to determine coverage with the influenza vaccine and access trends in Shanghai city; data from Shanghai immunization information system was analyzed to estimate vaccination coverage during 2016–2017 through 2020–2021 influenza seasons. Vaccination coverage by age groups, immigration status, and districts was accessed. The influenza vaccination coverage (at least one dose) for 2016/2017 to 2020/2021 influenza seasons was 10.8‰ (95‰ CI: 10.7–10.8), 12.3‰ (95‰ CI: 12.3–12.4), 10.1‰ (95‰ CI: 10.0–10.1), 20.1‰ (95‰ CI: 20.0–20.2) and 50.8‰ (95‰ CI: 50.7–50.8) respectively. Although we found significantly higher vaccination coverage in females, children from 6 months to 17 years, and residents, it is still low in all subgroups of the population in Shanghai. Therefore, taking effective steps to promote influenza vaccination in Shanghai is recommended.
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Affiliation(s)
- Linlin Wu
- Department of Immunization Program, Shanghai Municipal Centers for Disease Prevention and Control, Shanghai, China
| | - Xiang Guo
- Department of Immunization Program, Shanghai Municipal Centers for Disease Prevention and Control, Shanghai, China
| | - Jiechen Liu
- Department of Immunization Program, Shanghai Municipal Centers for Disease Prevention and Control, Shanghai, China
| | - Xiaoying Ma
- Department of Immunization Program, Shanghai Municipal Centers for Disease Prevention and Control, Shanghai, China
| | - Zhuoying Huang
- Department of Immunization Program, Shanghai Municipal Centers for Disease Prevention and Control, Shanghai, China
| | - Xiaodong Sun
- Department of Immunization Program, Shanghai Municipal Centers for Disease Prevention and Control, Shanghai, China
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23
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Assessment of potential factors associated with the sensitivity and specificity of Sofia Influenza A+B Fluorescent Immunoassay in an ambulatory care setting. PLoS One 2022; 17:e0268279. [PMID: 35536787 PMCID: PMC9089855 DOI: 10.1371/journal.pone.0268279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 04/26/2022] [Indexed: 11/22/2022] Open
Abstract
Background Seasonal influenza leads to an increase in outpatient clinic visits. Timely, accurate, and affordable testing could facilitate improved treatment outcomes. Rapid influenza diagnostic tests (RIDTs) provide results in as little as 15 minutes and are relatively inexpensive, but have reduced sensitivity when compared to RT-PCR. The contributions of multiple factors related to test performance are not well defined for ambulatory care settings. We assessed clinical and laboratory factors that may affect the sensitivity and specificity of Sofia Influenza A+B Fluorescence Immunoassay. Study design We performed a post-hoc assessment of surveillance data amassed over seven years from five primary care clinics. We analyzed 4,475 paired RIDT and RT-PCR results from specimens collected from patients presenting with respiratory symptoms and examined eleven potential factors with additional sub-categories that could affect RIDT sensitivity. Results In an unadjusted analysis, greater sensitivity was associated with the presence of an influenza-like illness (ILI), no other virus detected, no seasonal influenza vaccination, younger age, lower cycle threshold value, fewer days since illness onset, nasal discharge, stuffy nose, and fever. After adjustment, presence of an ILI, younger age, fewer days from onset, no co-detection, and presence of a nasal discharge maintained significance. Conclusion Clinical and laboratory factors may affect RIDT sensitivity. Identifying potential factors during point-of-care testing could aid clinicians in appropriately interpreting negative influenza RIDT results.
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Wu B, Yu Y, Feng X. The Impacts of Gradually Terminating Nonpharmaceutical Interventions for SARS-CoV-2: A Mathematical Modelling Analysis. FUNDAMENTAL RESEARCH 2022. [PMCID: PMC9110308 DOI: 10.1016/j.fmre.2022.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
With the expansion of vaccination programs, the policy of terminating nonpharmaceutical interventions for preventing the SARS-CoV-2 pandemic should become more flexible. The current study investigated the clinical and economic outcomes of intervention policies combining nonpharmaceutical interventions and vaccination programs for dealing with the SARS-CoV-2 pandemic. An agent-based transmission model was adopted that describes how a SARS-CoV-2 virus spreads in the populations of China. The model inputs were derived from the literature and expert opinion. The following intervention policies were simulated: no intervention, strict nonpharmaceutical interventions, and nonpharmaceutical interventions for workplace, community, school and home gradually terminated by combining vaccination programs for specified age groups (vaccination age in years: 20–60, 20–70, 20–80, ≥20, ≥10 and whole population). Cumulative infections and deaths in one calendar year, costs and quality-adjusted life years (QALYs) were measured. When the vaccination program was taken up in at least the ≥20 years age group in all populations, nonpharmaceutical interventions for workplace and community settings could be gradually terminated because the cumulative number of infections was < 100 per 100,000 persons. Further ending nonpharmaceutical interventions in school and home settings could not meet the target even when the vaccination program had been taken up in all populations. When cumulative deaths were used as the endpoint, nonpharmaceutical interventions in workplace, community and school settings could be gradually terminated. Vaccine efficacy and coverage have substantial impacts. Terminating nonpharmaceutical interventions in workplace settings could produce the lowest cost when vaccination programs are taken up at least in the ≥10 years age group; this method dominates most intervention strategies due to its lower costs and higher QALYs. According to our findings, nonpharmaceutical interventions might be gradually terminated in Chinese settings.
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Ali ST, Cowling BJ, Wong JY, Chen D, Shan S, Lau EHY, He D, Tian L, Li Z, Wu P. Influenza seasonality and its environmental driving factors in mainland China and Hong Kong. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 818:151724. [PMID: 34800462 DOI: 10.1016/j.scitotenv.2021.151724] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/20/2021] [Accepted: 11/12/2021] [Indexed: 05/27/2023]
Abstract
BACKGROUND Influenza epidemics occur during winter in temperate zones, but have less regular seasonality in the subtropics and tropics. Here we quantified the role of environmental drivers of influenza seasonality in temperate and subtropical China. METHODS We used weekly surveillance data on influenza virus activity in mainland China and Hong Kong from 2005 through 2016. We estimated the transmissibility via the instantaneous reproduction number (Rt), a real-time measure of transmissibility, and examined its relationship with different climactic drivers and allowed for the timing of school holidays and the decline in susceptibility in the population as an epidemic progressed. We developed a multivariable regression model for Rt to quantify the contribution of various potential environmental drivers of transmission. FINDINGS We found that absolute humidity is a potential driver of influenza seasonality and had a U-shaped association with transmissibility and hence can predict the pattern of influenza virus transmission across different climate zones. Absolute humidity was able to explain up to 15% of the variance in Rt, and was a stronger predictor of Rt across the latitudes. Other climatic drivers including mean daily temperature explained up to 13% of variance in Rt and limited to the locations where the indoor measures of these factors have better indicators of outdoor measures. The non-climatic driver, holiday-related school closures could explain up to 7% of variance in Rt. INTERPRETATION A U-shaped association of absolute humidity with influenza transmissibility was able to predict seasonal patterns of influenza virus epidemics in temperate and subtropical locations.
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Affiliation(s)
- Sheikh Taslim Ali
- 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; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - 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; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region.
| | - Jessica Y 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
| | - Dongxuan Chen
- 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; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - Songwei Shan
- 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; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - 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; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
| | - Daihai He
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong Special Administrative Region
| | - Linwei Tian
- 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
| | - Zhongjie Li
- 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; Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region
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Parental Preferences of Influenza Vaccination for Children in China: A National Survey with a Discrete Choice Experiment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19042145. [PMID: 35206343 PMCID: PMC8871809 DOI: 10.3390/ijerph19042145] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 01/30/2022] [Accepted: 02/10/2022] [Indexed: 12/22/2022]
Abstract
The influenza vaccination coverage among children is low in China. We aimed to conduct a nationwide survey to quantify parental preferences and willingness to pay (WTP) for influenza vaccination for their children. Parents with children aged six months to 18 years from six provinces in China were investigated by a discrete choice experiment regarding six influenza vaccination attributes. Mixed logit models were used to estimate the relative importance of vaccine attributes and parents’ WTP. Interaction analysis and subgroup analysis were conducted to explore preference heterogeneity. A total of 1206 parents were included in the analysis. Parents reported vaccine effectiveness as the most important vaccine attribute. The mode of vaccine administration had no significant impact on parents’ preferences. Parents aged over 30 years with higher education or income levels were more likely to prefer no influenza vaccination for their children. The largest marginal WTP (CNY 802.57) for vaccination and the largest increase in vaccine uptake (41.85%) occurred with improved vaccine effectiveness from 30% to 80%. Parents from central regions or mid-latitude areas had a relatively lower WTP than those from other regions. No significant difference in the relative importance of vaccine attributes were observed among parents from various regions of China.
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Diamond C, Gong H, Sun FY, Liu Y, Quilty BJ, Jit M, Yang J, Yu H, Edmunds WJ, Baguelin M. Regional-based within-year seasonal variations in influenza-related health outcomes across mainland China: a systematic review and spatio-temporal analysis. BMC Med 2022; 20:58. [PMID: 35139857 PMCID: PMC8830135 DOI: 10.1186/s12916-022-02269-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/19/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND China experiences large variations in influenza seasonal activity. We aim to update and improve the current understanding of regional-based within-year variations of influenza activity across mainland China to provide evidence for the planning and optimisation of healthcare strategies. METHODS We conducted a systematic review and spatio-temporal meta-analysis to assess regional-based within-year variations of ILI outpatient consultation rates, influenza test positivity rates amongst both ILI outpatients and SARI inpatients, and influenza-associated excess mortality rates. We searched English and Chinese databases for articles reporting time-series data on the four influenza-related outcomes at the sub-national and sub-annual level. After synthesising the data, we reported on the mean monthly rate, epidemic onset, duration, peak and intensity. RESULTS We included 247 (7.7%) eligible studies in the analysis. We found within-year influenza patterns to vary across mainland China in relation to latitude and geographic location. High-latitude provinces were characterised by having short and intense annual winter epidemics, whilst most mid-latitude and low-latitude provinces experience semi-annual epidemics or year-round activity. Subtype activity varied across the country, with A/H1N1pdm09 and influenza B occurring predominantly in the winter, whereas A/H3N2 activity exhibited a latitudinal divide with high-latitude regions experiencing a winter peak, whilst mid and low-latitude regions experienced a summer epidemic. Epidemic onsets and peaks also varied, occurring first in the north and later in the southeast. We found positive associations between all influenza health outcomes. In addition, seasonal patterns at the prefecture and county-level broadly resembled their wider province. CONCLUSIONS This is the first systematic review to simultaneously examine the seasonal variation of multiple influenza-related health outcomes at multiple spatial scales across mainland China. The seasonality information provided here has important implications for the planning and optimisation of immunisation programmes and healthcare provision, supporting the need for regional-based approaches to address variations in local epidemiology.
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Affiliation(s)
- Charlie Diamond
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
| | - Hui Gong
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Fiona Yueqian Sun
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Yang Liu
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Billy J Quilty
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Mark Jit
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - W John Edmunds
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Marc Baguelin
- Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.,MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
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Kang M, Zanin M, Wong SS. Subtype H3N2 Influenza A Viruses: An Unmet Challenge in the Western Pacific. Vaccines (Basel) 2022; 10:vaccines10010112. [PMID: 35062773 PMCID: PMC8778411 DOI: 10.3390/vaccines10010112] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/07/2022] [Accepted: 01/07/2022] [Indexed: 02/04/2023] Open
Abstract
Subtype H3N2 influenza A viruses (A(H3N2)) have been the dominant strain in some countries in the Western Pacific region since the 2009 influenza A(H1N1) pandemic. Vaccination is the most effective way to prevent influenza; however, low vaccine effectiveness has been reported in some influenza seasons, especially for A(H3N2). Antigenic mismatch introduced by egg-adaptation during vaccine production between the vaccine and circulating viral stains is one of the reasons for low vaccine effectiveness. Here we review the extent of this phenomenon, the underlying molecular mechanisms and discuss recent strategies to ameliorate this, including new vaccine platforms that may provide better protection and should be considered to reduce the impact of A(H3N2) in the Western Pacific region.
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Affiliation(s)
- Min Kang
- School of Public Health, Southern Medical University, Guangzhou 510515, China;
- Guangdong Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Mark Zanin
- State Key Laboratory for Respiratory Diseases and National Clinical Research Centre for Respiratory Disease, Guangzhou Medical University, 195 Dongfengxi Road, Guangzhou 511436, China;
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China
| | - Sook-San Wong
- State Key Laboratory for Respiratory Diseases and National Clinical Research Centre for Respiratory Disease, Guangzhou Medical University, 195 Dongfengxi Road, Guangzhou 511436, China;
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China
- Correspondence: ; Tel.: +86-178-2584-6078
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Liu T, Wang P, Meng F, Ding G, Wu J, Song S, Sun L, Zhang S, Li Z, Xing W, Wang X. Incidence, circulation, and spatiotemporal analysis of seasonal influenza in Shandong, China, 2008-2019: A retrospective study. Influenza Other Respir Viruses 2022; 16:594-603. [PMID: 35014171 PMCID: PMC8983897 DOI: 10.1111/irv.12959] [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: 11/27/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Understanding the influenza-like illness (ILI) incidence, circulation pattern of virus strains and spatiotemporal pattern of influenza transmission are important for designing control interventions. Based on the 10 years' surveillance data, we aimed to provide a baseline characterization and the epidemiology and dynamics of influenza virus in Shandong. METHODS We extracted surveillance and laboratory testing data. We estimated the ILI incidence and analyzed the predominant virus. A wavelet power analysis was used to illustrate the periodicity. In addition, we applied a linear regression model to characterize the correlation of influenza seasonality with longitude. RESULTS The average ILI incidence was estimated to be 3744.79 per 1 million (95% confidence interval [CI]: 2558.09-4931.45) during 2009-2018. Influenza A/H1N1 and A/H3N2 strains predominated in the most influenza seasons in Shandong. The annual amplitude of influenza epidemics decreased with longitude (P < 0.05). In contrast, the epidemic peak of influenza emerged earlier in the western region and increased with longitude in influenza A (P < 0.05). The annual peak of the influenza B epidemic lagged a median of 4.2 weeks compared with that of influenza A. CONCLUSIONS The development or modification of seasonal influenza vaccination strategies requires the recognition that the incidence is higher in preschool- and school-aged children. Although seasonal influenza circulates annually in Shandong, the predominant virus strain circulation pattern is extremely unpredictable and strengthening surveillance for the predominant virus strain is necessary. Lower longitude inland regions need to take nonpharmaceutical or pharmaceutical interventions in advance during influenza high-occurrence seasons.
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Affiliation(s)
- Ti Liu
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Ping Wang
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China
| | - Fanyu Meng
- Statistical Analysis Center, Linyi Central Hospital, Linyi, China
| | - Guoyong Ding
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China
| | - Julong Wu
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Shaoxia Song
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Lin Sun
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Shengyang Zhang
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Zhong Li
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Weijia Xing
- School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China
| | - Xianjun Wang
- Shandong Provincial Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
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Xu C, Lao X, Li H, Dong L, Zou S, Chen Y, Gu Y, Zhu Y, Xuan P, Huang W, Wang D, Yi B. Incidence of medically attended influenza and influenza virus infections confirmed by serology in Ningbo City from 2017-2018 to 2019-2020. Influenza Other Respir Viruses 2022; 16:552-561. [PMID: 34989139 PMCID: PMC8983918 DOI: 10.1111/irv.12935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 10/17/2021] [Indexed: 11/27/2022] Open
Abstract
Objectives In mainland China, the disease burden of influenza is not yet fully understood. Based on population‐based data, we aimed to estimate incidence rates of medically attended influenza and influenza virus infections in Ningbo City. Methods We used data for outpatient acute respiratory illness (OARI) from a platform covering all health and medical institutes in Yingzhou District, Ningbo City. We applied generalized additive regression models to estimate influenza‐associated excess incidence rate of OARI by age. We recruited local residents aged ≥60 years in the autumn of 2019 and conducted follow‐up nearly 9 months later. Every survey, the sera were collected for testing hemagglutination inhibition antibody. Results From 2017–2018 to 2019–2020, the annual average of influenza‐associated incidence rate of OARI in all ages was 10.9%. The influenza‐associated incidence rate of OARI was the highest in 2017–2018 (16.9%) and the lowest in 2019–2020 (4.8%). Regularly, influenza‐associated incidence rates of OARI were the highest in children aged 5–14 years (range: 44.1–77.6%) and 0–4 years (range: 8.3–46.6%). The annual average of excess OARI incidence rate in all ages was the highest for influenza B/Yamagata (3.9%). The overall incidence rate of influenza infections indicated by serology in elderly people was 21% during the winter season of 2019–2020. Conclusions We identified substantial outpatient influenza burden in all ages in Ningbo. Our cohort study limited in elderly people found that this age group had a high risk of seasonal influenza infections. Our study informs the importance of increasing influenza vaccine coverage in high‐risk population including elderly people.
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Affiliation(s)
- Cuiling Xu
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing, P.R. China
| | - Xuying Lao
- Ningbo Municipal Center for Disease Prevention and Control, Ningbo, P.R. China
| | - Hongyu Li
- Laboratory of Microbiology, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, P.R. China
| | - Libo Dong
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing, P.R. China
| | - Shumei Zou
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing, P.R. China
| | - Yi Chen
- Ningbo Municipal Center for Disease Prevention and Control, Ningbo, P.R. China
| | - Yongquan Gu
- Yuyao Municipal Center for Disease Prevention and Control, Ningbo, P.R. China
| | - Yueqin Zhu
- Lanjiang Street Community Health Service Center, Ningbo, P.R. China
| | - Pingfeng Xuan
- Yangming Street Community Health Service Center, Ningbo, P.R. China
| | - Weijuan Huang
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing, P.R. China
| | - Dayan Wang
- Chinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health Commission, Beijing, P.R. China
| | - Bo Yi
- Ningbo Municipal Center for Disease Prevention and Control, Ningbo, P.R. China
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Yu X, Xu C, Huang W, Xu X, Xie W, Long X. The incidence of influenza in children was decreased in the first flu season after COVID-19 pandemic in Wuhan. J Infect Public Health 2021; 14:1279-1281. [PMID: 34500253 PMCID: PMC8393498 DOI: 10.1016/j.jiph.2021.08.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 07/07/2021] [Accepted: 08/22/2021] [Indexed: 11/25/2022] Open
Abstract
Wuhan, China was the first city to discover COVID-19. With the government's macro-control and the active cooperation of the public, the spread of COVID-19 has been effectively controlled. In order to understand the additional impact of these measures on the prevalence of common influenza, we have collected flu test data from the Pediatric Clinic of Zhongnan Hospital of Wuhan University from September to December 2020, and compared them with the same period in 2018 and 2019. It is found that compared with the same period in 2018 and 2019, the rate of children's influenza activity in 2020 has significantly decreased, which indicates that the protective measures against COVID-19 have effectively reduced the level of influenza activity.
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Affiliation(s)
- Xiaosi Yu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China; Department of Pediatric Surgery, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China
| | - Chen Xu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Wenjie Huang
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xianqun Xu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
| | - Wen Xie
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
| | - Xinghua Long
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
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Li J, Wang C, Ruan L, Jin S, Ye C, Yu H, Zhu W, Wang X. Development of influenza-associated disease burden pyramid in Shanghai, China, 2010-2017: a Bayesian modelling study. BMJ Open 2021; 11:e047526. [PMID: 34497077 PMCID: PMC8438833 DOI: 10.1136/bmjopen-2020-047526] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVES Negative estimates can be produced when statistical modelling techniques are applied to estimate morbidity and mortality attributable to influenza. Based on the prior knowledge that influenza viruses are hazardous pathogens and have adverse health outcomes of respiratory and circulatory disease (R&C), we developed an improved model incorporating Bayes' theorem to estimate the disease burden of influenza in Shanghai, China, from 2010 to 2017. DESIGN A modelling study using aggregated data from administrative systems on weekly R&C mortality and hospitalisation, influenza surveillance and meteorological data. We constrained the regression coefficients for influenza activity to be positive by truncating the prior distributions at zero. SETTING Shanghai, China. PARTICIPANTS People registered with R&C deaths (450 298) and hospitalisations (2621 787, from 1 July 2013), and with influenza-like illness (ILI) outpatient visits (342 149) between 4 January 2010 and 31 December 2017. PRIMARY OUTCOME MEASURES Influenza-associated disease burden (mortality, hospitalisation and outpatient visit rates) and clinical severity (outpatient-mortality, outpatient-hospitalisation and hospitalisation-mortality risks). RESULTS Influenza was associated with an annual average of 15.49 (95% credibility interval (CrI) 9.06-22.06) excess R&C deaths, 100.65 (95% CrI 48.79-156.78) excess R&C hospitalisations and 914.95 (95% CrI 798.51-1023.66) excess ILI outpatient visits per 100 000 population in Shanghai. 97.23% and 80.24% excess R&C deaths and hospitalisations occurred in people aged ≥65 years. More than half of excess morbidity and mortality were associated with influenza A(H3N2) virus, and its severities were 1.65-fold to 3.54-fold and 1.47-fold to 2.16-fold higher than that for influenza A(H1N1) and B viruses, respectively. CONCLUSIONS The proposed Bayesian approach with reasonable prior information improved estimates of influenza-associated disease burden. Influenza A(H3N2) virus was generally associated with higher morbidity and mortality, and was relatively more severe compared with influenza A(H1N1) and B viruses. Targeted influenza prevention and control strategies for the elderly in Shanghai may substantially reduce the disease burden.
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Affiliation(s)
- Jing Li
- School of Public Health, Fudan University, Shanghai, Shanghai, China
- Renal Division, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Clinical Research Academy, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Chunfang Wang
- Department of Vital Statistics, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Luanqi Ruan
- Research Base of Key Laboratory of Surveillance and Early Warning on Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Shan Jin
- Department of Vital Statistics, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Chuchu Ye
- Research Base of Key Laboratory of Surveillance and Early Warning on Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Huiting Yu
- Department of Vital Statistics, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Weiping Zhu
- Research Base of Key Laboratory of Surveillance and Early Warning on Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Xiling Wang
- School of Public Health, Fudan University, Shanghai, Shanghai, China
- Shanghai Key Laboratory of Meteorology and Health, Shanghai, China
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Chen J, Wang J, Zhang J, Ly H. Advances in Development and Application of Influenza Vaccines. Front Immunol 2021; 12:711997. [PMID: 34326849 PMCID: PMC8313855 DOI: 10.3389/fimmu.2021.711997] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 06/24/2021] [Indexed: 12/24/2022] Open
Abstract
Influenza A virus is one of the most important zoonotic pathogens that can cause severe symptoms and has the potential to cause high number of deaths and great economic loss. Vaccination is still the best option to prevent influenza virus infection. Different types of influenza vaccines, including live attenuated virus vaccines, inactivated whole virus vaccines, virosome vaccines, split-virion vaccines and subunit vaccines have been developed. However, they have several limitations, such as the relatively high manufacturing cost and long production time, moderate efficacy of some of the vaccines in certain populations, and lack of cross-reactivity. These are some of the problems that need to be solved. Here, we summarized recent advances in the development and application of different types of influenza vaccines, including the recent development of viral vectored influenza vaccines. We also described the construction of other vaccines that are based on recombinant influenza viruses as viral vectors. Information provided in this review article might lead to the development of safe and highly effective novel influenza vaccines.
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Affiliation(s)
- Jidang Chen
- School of Life Science and Engineering, Foshan University, Foshan, China
| | - Jiehuang Wang
- School of Life Science and Engineering, Foshan University, Foshan, China
| | - Jipei Zhang
- School of Life Science and Engineering, Foshan University, Foshan, China
| | - Hinh Ly
- Department of Veterinary & Biomedical Sciences, University of Minnesota, Twin Cities, MN, United States
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Yi H, Yang Y, Zhang L, Zhang M, Wang Q, Zhang T, Zhang Y, Qin Y, Peng Z, Leng Z, Yang W, Zheng J, Liang X, Feng L. Improved influenza vaccination coverage among health-care workers: evidence from a web-based survey in China, 2019/2020 season. Hum Vaccin Immunother 2021; 17:2185-2189. [PMID: 33497309 PMCID: PMC8189132 DOI: 10.1080/21645515.2020.1859317] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/10/2020] [Accepted: 11/25/2020] [Indexed: 12/17/2022] Open
Abstract
To understand influenza vaccination and its correlates among health-careworkers (HCWs) during the 2019/2020 season in China, we used a self-administeredelectronic questionnaire to collect information on demographics, occupational characteristics, influenza vaccination status and access to free vaccination on the "Breath Circles", a Chinese media platform for respiratory medical professionals. The reported influenza vaccine coverage among HCWs during this season was 67%, with more HCWs in a workplace with free vaccination than those with no free vaccination (79% vs.34%,p < .001). The influenza vaccine coverage among HCWs who were required or encouraged to get vaccinated by the workplace was significantly higher than that without any intervention measures (80% & 70 vs.39%,p < .001). The vaccine coverage in the workplaces with free and required vaccination simultaneously was highest compared to that with neither free vaccination nor any intervention measures (OR = 14.86, 95% CI: 10.93-20.20). The influenza vaccination coverage of HCWs in high-riskdepartments was significantly higher than that of other departments (70% vs.58%,p =.023). HCWs' vaccine coverage was related to personal opinions and attitudes toward influenza or influenza vaccines, as well as other constraints such as availability of influenza vaccines, workplace regulations, and access to free vaccines.
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Affiliation(s)
- Heya Yi
- Department of International Affairs,Chinese Preventive Medicine Association,Beijing,China
| | - Yuan Yang
- Division of Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing,China
| | - Li Zhang
- Editorial Department, BREATH-CIRCLES, Beijing, China
| | - Muli Zhang
- Division of Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing,China
| | - Qing Wang
- Division of Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing,China
| | - Ting Zhang
- School of Population Medicine and Public Health,Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing, China
| | - Yuyuan Zhang
- Department of International Affairs,Chinese Preventive Medicine Association,Beijing,China
| | - Ying Qin
- Division of Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing,China
| | - Zhibin Peng
- Division of Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing,China
| | - Zhiwei Leng
- School of Population Medicine and Public Health,Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing, China
| | - Weizhong Yang
- School of Population Medicine and Public Health,Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing, China
| | - Jiandong Zheng
- Division of Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing,China
| | - Xiaofeng Liang
- Department of International Affairs,Chinese Preventive Medicine Association,Beijing,China
| | - Luzhao Feng
- School of Population Medicine and Public Health,Chinese Academy of Medical Sciences & Peking Union Medical College,Beijing, China
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35
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Liu WJ, Xiao H, Dai L, Liu D, Chen J, Qi X, Bi Y, Shi Y, Gao GF, Liu Y. Avian influenza A (H7N9) virus: from low pathogenic to highly pathogenic. Front Med 2021; 15:507-527. [PMID: 33860875 PMCID: PMC8190734 DOI: 10.1007/s11684-020-0814-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Accepted: 07/08/2020] [Indexed: 12/13/2022]
Abstract
The avian influenza A (H7N9) virus is a zoonotic virus that is closely associated with live poultry markets. It has caused infections in humans in China since 2013. Five waves of the H7N9 influenza epidemic occurred in China between March 2013 and September 2017. H7N9 with low-pathogenicity dominated in the first four waves, whereas highly pathogenic H7N9 influenza emerged in poultry and spread to humans during the fifth wave, causing wide concern. Specialists and officials from China and other countries responded quickly, controlled the epidemic well thus far, and characterized the virus by using new technologies and surveillance tools that were made possible by their preparedness efforts. Here, we review the characteristics of the H7N9 viruses that were identified while controlling the spread of the disease. It was summarized and discussed from the perspectives of molecular epidemiology, clinical features, virulence and pathogenesis, receptor binding, T-cell responses, monoclonal antibody development, vaccine development, and disease burden. These data provide tools for minimizing the future threat of H7N9 and other emerging and re-emerging viruses, such as SARS-CoV-2.
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Affiliation(s)
- William J Liu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China.
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Haixia Xiao
- Laboratory of Protein Engineering and Vaccines, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences (CAS), Tianjin, 300308, China
| | - Lianpan Dai
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Di Liu
- CAS Key Laboratory of Special Pathogens and Biosafety, Chinese Academy of Sciences, Wuhan, 430071, China
- National Virus Resource Center, Chinese Academy of Sciences, Wuhan, 430071, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jianjun Chen
- CAS Key Laboratory of Special Pathogens and Biosafety, Chinese Academy of Sciences, Wuhan, 430071, China
- National Virus Resource Center, Chinese Academy of Sciences, Wuhan, 430071, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xiaopeng Qi
- Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yuhai Bi
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yi Shi
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - George F Gao
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
- Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yingxia Liu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China.
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Cumulative Effects of Particulate Matter Pollution and Meteorological Variables on the Risk of Influenza-Like Illness. Viruses 2021; 13:v13040556. [PMID: 33810283 PMCID: PMC8065612 DOI: 10.3390/v13040556] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/18/2021] [Accepted: 03/23/2021] [Indexed: 11/24/2022] Open
Abstract
The cold season is usually accompanied by an increased incidence of respiratory infections and increased air pollution from combustion sources. As we are facing growing numbers of COVID-19 cases caused by the novel SARS-CoV-2 coronavirus, an understanding of the impact of air pollutants and meteorological variables on the incidence of respiratory infections is crucial. The incidence of influenza-like illness (ILI) can be used as a close proxy for the circulation of influenza viruses. Recently, SARS-CoV-2 has also been detected in patients with ILI. Using distributed lag nonlinear models, we analyzed the association between ILI, meteorological variables and particulate matter concentration in Bialystok, Poland, from 2013–2019. We found an exponential relationship between cumulative PM2.5 pollution and the incidence of ILI, which remained significant after adjusting for air temperatures and a long-term trend. Pollution had the greatest effect during the same week, but the risk of ILI was increased for the four following weeks. The risk of ILI was also increased by low air temperatures, low absolute humidity, and high wind speed. Altogether, our results show that all measures implemented to decrease PM2.5 concentrations would be beneficial to reduce the transmission of SARS-CoV-2 and other respiratory infections.
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Shuai W, Chen X, Shan Y, Li W, Ma W, Lu Q, Li D. Clinical Characteristics and CT Findings in 148 Non-COVID-19 Influenza-Like Illness Cases: A Retrospective Control Study. Front Public Health 2021; 9:616963. [PMID: 33634067 PMCID: PMC7900189 DOI: 10.3389/fpubh.2021.616963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
Background: This study was to collect clinical features and computed tomography (CT) findings of Influenza-Like Illness (ILI) cases, and to evaluate the correlation between clinical data and the abnormal chest CT in patients with the Influenza-Like Illness symptoms. Methods: Patients with the Influenza-Like Illness symptoms who attended the emergency department of The Six Medical Center of The PLA General Hospital from February 10 to April 1, 2020 were enrolled. Clinical and imaging data of the enrolled patients were collected and analyzed. The association between clinical characteristics and abnormal chest CT was also analyzed. Results: A total of 148 cases were enrolled in this study. Abnormalities on chest CT were detected in 61/148 (41.2%) patients. The most common abnormal CT features were as follows: patchy consolidation 22/61(36.1%), ground-glass opacities 21/61(34.4%), multifocal consolidations 17/61(27.9%). The advanced age and underlying diseases were significantly associated with abnormal chest CT. Conclusions: Abnormal chest CT is a common condition in Influenza-Like Illness cases. The presence of advanced age and concurrent underlying diseases is significantly associated with abnormal chest CT findings in patients with ILI symptoms. The chest CT characteristic of ILI is different from the manifestation of COVID-19 infection, which is helpful for differential diagnosis.
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Affiliation(s)
- Weizheng Shuai
- Department of Critical Care Medicine, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xuxin Chen
- Department of Respiratory and Critical Care Medicine, The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yi Shan
- Department of Emergency Medicine, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wenping Li
- Radiology Department, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wei Ma
- Basic Medical Research Center, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qiaohui Lu
- Radiology Department, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Dawei Li
- Department of Critical Care Medicine, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
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38
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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: 4.5] [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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Tao YY, Li JX, Hu YM, Hu YS, Zeng G, Zhu FC. Quadrivalent influenza vaccine (Sinovac Biotech) for seasonal influenza prophylaxis. Expert Rev Vaccines 2021; 20:1-11. [PMID: 33434084 DOI: 10.1080/14760584.2021.1875823] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
INTRODUCTION Quadrivalent Influenza Vaccine (Sinovac Biotech) is a quadrivalent split-virion-inactivated influenza vaccine approved in China in June 2020 for individuals ≥3 years of age. It contains 15 µg hemagglutinin per strain including A/H1N1, A/H3N2, B/Victoria, and B/Yamagata, which could potentially improve protection against influenza B viruses. AREAS COVERED In this review, we summarize the development of quadrivalent influenza vaccines in China and foreign countries, and assess the immunogenicity and safety from the phase I and III clinical trials of Quadrivalent Influenza Vaccine in individuals ≥3 years of age. We also discuss the potential application of Quadrivalent Influenza Vaccine in young children 6-35 months of age according to the results of the phase III trial. EXPERT COMMENTARY The immunogenicity and safety profiles of Quadrivalent Influenza Vaccine containing two A and two B strains were comparable to the trivalent vaccines for the shared strains. The addition of a second B strain to the trivalent vaccine could induce superior immune responses for the alternate B strain. Since the two B strains co-circulated worldwide, the introduction of quadrivalent influenza vaccines has been expected to be a cost-effective strategy.
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Affiliation(s)
- Yan-Yang Tao
- School of Public Health, Southeast University; Nanjing, China
| | - Jing-Xin Li
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yue-Mei Hu
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yuan-Sheng Hu
- Clinical Research Department, Sinovac Biotech Co., LTD., Beijing, China
| | - Gang Zeng
- Clinical Research Department, Sinovac Biotech Co., LTD., Beijing, China
| | - Feng-Cai Zhu
- School of Public Health, Southeast University; Nanjing, China.,NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China.,Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
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40
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Yang J, Chen X, Deng X, Chen Z, Gong H, Yan H, Wu Q, Shi H, Lai S, Ajelli M, Viboud C, Yu PH. Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China. Nat Commun 2020; 11:5411. [PMID: 33110070 PMCID: PMC7591855 DOI: 10.1038/s41467-020-19238-2] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Accepted: 09/28/2020] [Indexed: 12/15/2022] Open
Abstract
The novel coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China, where the initial wave of intense community transmissions was cut short by interventions. Using multiple data sources, here we estimate the disease burden and clinical severity by age of COVID-19 in Wuhan from December 1, 2019 to March 31, 2020. Our estimates account for the sensitivity of the laboratory assays, prospective community screenings, and healthcare seeking behaviors. Rates of symptomatic cases, medical consultations, hospitalizations and deaths were estimated at 796 (95% CI: 703-977), 489 (472-509), 370 (358-384), and 36.2 (35.0-37.3) per 100,000 persons, respectively. The COVID-19 outbreak in Wuhan had a higher burden than the 2009 influenza pandemic or seasonal influenza in terms of hospitalization and mortality rates, and clinical severity was similar to that of the 1918 influenza pandemic. Our comparison puts the COVID-19 pandemic into context and could be helpful to guide intervention strategies and preparedness for the potential resurgence of COVID-19.
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Affiliation(s)
- Juan Yang
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Xinhua Chen
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Xiaowei Deng
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Zhiyuan Chen
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Hui Gong
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Han Yan
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Qianhui Wu
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Huilin Shi
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
| | - Shengjie Lai
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China
- WorldPop, Department of Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ, UK
| | - Marco Ajelli
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, 47405, USA
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, 02115, USA
| | - Cecile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Prof Hongjie Yu
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, 200030, Shanghai, China.
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41
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Liu Y, Gong W, Clifford S, Sundaram ME, Jit M, Flasche S, Klepac P. Designing a multi-layered surveillance approach to detecting SARS-CoV-2: A modelling study. Wellcome Open Res 2020. [DOI: 10.12688/wellcomeopenres.16256.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Countries achieving control of COVID-19 after an initial outbreak will continue to face the risk of SARS-CoV-2 resurgence. This study explores surveillance strategies for COVID-19 containment based on polymerase chain reaction tests. Methods: Using a dynamic SEIR-type model to simulate the initial dynamics of a COVID-19 introduction, we investigate COVID-19 surveillance strategies among healthcare workers, hospital patients, and community members. We estimate surveillance sensitivity as the probability of COVID-19 detection using a hypergeometric sampling process. We identify test allocation strategies that maximise the probability of COVID-19 detection across different testing capacities. We use Beijing, China as a case study. Results: Surveillance subgroups are more sensitive in detecting COVID-19 transmission when they are defined by more COVID-19-specific symptoms. In this study, fever clinics have the highest surveillance sensitivity, followed by respiratory departments. With a daily testing rate of 0.07/1000 residents, via exclusively testing at fever clinic and respiratory departments, there would have been 598 [95% eCI: 35, 2154] and 1373 [95% eCI: 47, 5230] cases in the population by the time of first case detection, respectively. Outbreak detection can occur earlier by including non-syndromic subgroups, such as younger adults in the community, as more testing capacity becomes available. Conclusions: A multi-layer approach that considers both the surveillance sensitivity and administrative constraints can help identify the optimal allocation of testing resources and thus inform COVID-19 surveillance strategies.
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42
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Yang J, Chen X, Deng X, Chen Z, Gong H, Yan H, Wu Q, Shi H, Lai S, Ajelli M, Viboud C, Yu H. Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.08.27.20183228. [PMID: 32909016 PMCID: PMC7480068 DOI: 10.1101/2020.08.27.20183228] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The pandemic of novel coronavirus disease 2019 (COVID-19) began in Wuhan, China, where a first wave of intense community transmission was cut short by interventions. Using multiple data source, we estimated the disease burden and clinical severity of COVID-19 by age in Wuhan from December 1, 2019 to March 31, 2020. We adjusted estimates for sensitivity of laboratory assays and accounted for prospective community screenings and healthcare seeking behaviors. Rates of symptomatic cases, medical consultations, hospitalizations and deaths were estimated at 796 (95%CI: 703-977), 489 (472-509), 370 (358-384), and 36.2 (35.0-37.3) per 100,000 persons, respectively. The COVID-19 outbreak in Wuhan had higher burden than the 2009 influenza pandemic or seasonal influenza, and that clinical severity was similar to that of the 1918 influenza pandemic. Our comparison puts the COVID-19 pandemic into context and could be helpful to guide intervention strategies and preparedness for the potential resurgence of COVID-19.
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Affiliation(s)
- Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Xinhua Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Xiaowei Deng
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Zhiyuan Chen
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Hui Gong
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Han Yan
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Qianhui Wu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Huilin Shi
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Shengjie Lai
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
- WorldPop, Department of Geography and Environment, University of Southampton, University Road, Southampton, SO17 1BJ, UK
| | - Marco Ajelli
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | - Cecile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
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43
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Silverman JD, Hupert N, Washburne AD. Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States. Sci Transl Med 2020; 12:scitranslmed.abc1126. [PMID: 32571980 PMCID: PMC7319260 DOI: 10.1126/scitranslmed.abc1126] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 06/18/2020] [Indexed: 12/17/2022]
Abstract
Detection of SARS-CoV-2 infections to date has relied heavily on RT-PCR testing. However, limited test availability, high false-negative rates, and the existence of asymptomatic or sub-clinical infections have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how influenza-like illness (ILI) outpatient surveillance data can be used to estimate the prevalence of SARS-CoV-2. We found a surge of non-influenza ILI above the seasonal average in March 2020 and showed that this surge correlated with COVID-19 case counts across states. If 1/3 of patients infected with SARS-CoV-2 in the US sought care, this ILI surge would have corresponded to more than 8.7 million new SARS-CoV-2 infections across the US during the three-week period from March 8 to March 28, 2020. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to have been doubling slower than every 4 days. Together these results suggest a conceptual model for the COVID-19 epidemic in the US characterized by rapid spread across the US with over 80% infected patients remaining undetected. We emphasize the importance of testing these findings with seroprevalence data and discuss the broader potential to use syndromic surveillance for early detection and understanding of emerging infectious diseases.
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Affiliation(s)
- Justin D Silverman
- College of Information Science and Technology, Penn State University, University Park, PA 16802, USA. .,Department of Medicine, Penn State University, Hershey, PA 17033, USA
| | - Nathaniel Hupert
- Weill Cornell Medicine, Cornell University, New York, NY 10065, USA.,New York-Presbyterian Hospital, New York, NY 10065, USA
| | - Alex D Washburne
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA.
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44
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Feng L, Feng S, Chen T, Yang J, Lau YC, Peng Z, Li L, Wang X, Wong JYT, Qin Y, Bond HS, Zhang J, Fang VJ, Zheng J, Yang J, Wu P, Jiang H, He Y, Cowling BJ, Yu H, Shu Y, Lau EHY. Burden of influenza-associated outpatient influenza-like illness consultations in China, 2006-2015: A population-based study. Influenza Other Respir Viruses 2020; 14:162-172. [PMID: 31872547 PMCID: PMC7040965 DOI: 10.1111/irv.12711] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 12/04/2019] [Accepted: 12/08/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Human influenza virus infections cause a considerable burden of morbidity and mortality worldwide each year. Understanding regional influenza-associated outpatient burden is crucial for formulating control strategies against influenza viruses. METHODS We extracted the national sentinel surveillance data on outpatient visits due to influenza-like-illness (ILI) and virological confirmation of sentinel specimens from 30 provinces of China from 2006 to 2015. Generalized additive regression models were fitted to estimate influenza-associated excess ILI outpatient burden for each individual province, accounting for seasonal baselines and meteorological factors. RESULTS Influenza was associated with an average of 2.5 excess ILI consultations per 1000 person-years (py) in 30 provinces of China each year from 2006 to 2015. Influenza A(H1N1)pdm09 led to a higher number of influenza-associated ILI consultations in 2009 across all provinces compared with other years. The excess ILI burden was 4.5 per 1000 py among children aged below 15 years old, substantially higher than that in adults. CONCLUSIONS Human influenza viruses caused considerable impact on population morbidity, with a consequent healthcare and economic burden. This study provided the evidence for planning of vaccination programs in China and a framework to estimate burden of influenza-associated outpatient consultations.
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Affiliation(s)
- Luzhao Feng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Shuo Feng
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Tao Chen
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
| | - Juan Yang
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Yiu Chung Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Zhibin Peng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Li Li
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Xiling Wang
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Jessica Y. T. Wong
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Ying Qin
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Helen S. Bond
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Juanjuan Zhang
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Vicky J. Fang
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Jiandong Zheng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Jing Yang
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Hui Jiang
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Yangni He
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Hongjie Yu
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Yuelong Shu
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
- School of Public Health (Shenzhen)Sun Yat‐sen UniversityShenzhenChina
| | - Eric H. Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
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