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Yin TL, Chen N, Zhang JY, Yang S, Li WM, Gao XH, Shi HL, Hu HP. Excess multi-cause mortality linked to influenza virus infection in China, 2012-2021: a population-based study. Front Public Health 2024; 12:1399672. [PMID: 38887242 PMCID: PMC11182332 DOI: 10.3389/fpubh.2024.1399672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/15/2024] [Indexed: 06/20/2024] Open
Abstract
Objectives The aim of this study is to estimate the excess mortality burden of influenza virus infection in China from 2012 to 2021, with a concurrent analysis of its associated disease manifestations. Methods Laboratory surveillance data on influenza, relevant population demographics, and mortality records, including cause of death data in China, spanning the years 2012 to 2021, were incorporated into a comprehensive analysis. A negative binomial regression model was utilized to calculate the excess mortality rate associated with influenza, taking into consideration factors such as year, subtype, and cause of death. Results There was no evidence to indicate a correlation between malignant neoplasms and any subtype of influenza, despite the examination of the effect of influenza on the mortality burden of eight diseases. A total of 327,520 samples testing positive for influenza virus were isolated between 2012 and 2021, with a significant decrease in the positivity rate observed during the periods of 2012-2013 and 2019-2020. China experienced an average annual influenza-associated excess deaths of 201721.78 and an average annual excess mortality rate of 14.53 per 100,000 people during the research period. Among the causes of mortality that were examined, respiratory and circulatory diseases (R&C) accounted for the most significant proportion (58.50%). Fatalities attributed to respiratory and circulatory diseases exhibited discernible temporal patterns, whereas deaths attributable to other causes were dispersed over the course of the year. Conclusion Theoretically, the contribution of these disease types to excess influenza-related fatalities can serve as a foundation for early warning and targeted influenza surveillance. Additionally, it is possible to assess the costs of prevention and control measures and the public health repercussions of epidemics with greater precision.
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Affiliation(s)
- Tian-Lu Yin
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ning Chen
- School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jin-Yao Zhang
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Shuang Yang
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wei-Min Li
- Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Beijing, China
| | - Xiao-Huan Gao
- Medical College, Hebei Engineering University, Hebei, China
| | - Hao-Lin Shi
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hong-Pu Hu
- Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Mavragani A, Yan ZL, Luo L, Liu W, Yang Z, Shi C, Ming BW, Yang J, Cao P, Ou CQ. Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model. JMIR Public Health Surveill 2023; 9:e42530. [PMID: 36630176 PMCID: PMC9878364 DOI: 10.2196/42530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/14/2022] [Accepted: 11/25/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Accurate estimation of the influenza death burden is of great significance for influenza prevention and control. However, few studies have considered the short-term harvesting effects of influenza on mortality when estimating influenza-associated excess deaths by cause of death, age, sex, and subtype/lineage. OBJECTIVE This study aimed to estimate the cause-, age-, and sex-specific excess mortality associated with influenza and its subtypes and lineages in Guangzhou from 2015 to 2018. METHODS Distributed-lag nonlinear models were fitted to estimate the excess mortality related to influenza subtypes or lineages for different causes of death, age groups, and sex based on daily time-series data for mortality, influenza, and meteorological factors. RESULTS A total of 199,777 death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical CI [eCI] 19.85-30.16) per 100,000 persons; 7142 of 8791 (81.2%) deaths were due to respiratory or cardiovascular mortality (EMR 20.36, 95% eCI 16.75-23.74). Excess respiratory and cardiovascular deaths in people aged 60 to 79 years and those aged ≥80 years accounted for 32.9% (2346/7142) and 63.7% (4549/7142) of deaths, respectively. The male to female ratio (MFR) of excess death from respiratory diseases was 1.34 (95% CI 1.17-1.54), while the MFR for excess death from cardiovascular disease was 0.72 (95% CI 0.63-0.82). The average annual excess respiratory and cardiovascular mortality rates attributed to influenza A (H3N2), B/Yamagata, B/Victoria, and A (H1N1) were 8.47 (95% eCI 6.60-10.30), 5.81 (95% eCI 3.35-8.25), 3.68 (95% eCI 0.81-6.49), and 2.83 (95% eCI -1.26 to 6.71), respectively. Among these influenza subtypes/lineages, A (H3N2) had the highest excess respiratory and cardiovascular mortality rates for people aged 60 to 79 years (20.22, 95% eCI 14.56-25.63) and ≥80 years (180.15, 95% eCI 130.75-227.38), while younger people were more affected by A (H1N1), with an EMR of 1.29 (95% eCI 0.07-2.32). The mortality displacement of influenza A (H1N1), A (H3N2), and B/Yamagata was 2 to 5 days, but 5 to 13 days for B/Victoria. CONCLUSIONS Influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly, even after considering mortality displacement. The mortality burden of influenza B, particularly B/Yamagata, cannot be ignored. Contrasting sex differences were found in influenza-associated excess mortality from respiratory diseases and from cardiovascular diseases; the underlying mechanisms need to be investigated in future studies. Our findings can help us better understand the magnitude and time-course of the effect of influenza on mortality and inform targeted interventions for mitigating the influenza mortality burden, such as immunizations with quadrivalent vaccines (especially for older people), behavioral campaigns, and treatment strategies.
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Affiliation(s)
| | - Ze-Lin Yan
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Wenhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chen Shi
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Bo-Wen Ming
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jun Yang
- School of Public Health, Guanghzou Medical University, Guangzhou, China
| | - Peihua Cao
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China.,Clinical Research Center, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
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Rizzi S, Strozza C, Zarulli V. Sex-differences in excess death risk during the COVID-19 pandemic: an analysis of the first wave across Italian regions. What have we learned? GENUS 2022; 78:24. [PMID: 35966179 PMCID: PMC9362380 DOI: 10.1186/s41118-022-00172-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 07/17/2022] [Indexed: 11/23/2022] Open
Abstract
In this commentary, we bring together knowledge on sex-differences in excess death during the first wave of the COVID-19 pandemic in Italy, one of the most hit European countries. We zoom into Italian regions to account for the spatial gradient of the spread of the virus. Analyses of excess death by sex during the COVID-19 pandemic have been possible thanks to weekly mortality data released by national statistical offices, mainly in developed countries. The general finding is that males up to 75 years old have been suffering more excess death compared to females. However, the picture is less clear-cut at older ages. During previous epidemics, such as SARS, Swine Flu, and MERS, studies are limited and produce scattered, non-conclusive evidence. Knowledge of the sex-pattern of susceptibility to mortality from virulent respiratory diseases and its interplay with age could improve crisis management during future epidemics and pandemics. National statistical offices should provide weekly mortality data with spatial granularity, disaggregated by sex and age groups, to allow for such analyses.
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Liu YL, Xie TA, Lin GL, Deng W, Lin QR, Pan ZY, Fan SJ, Li ZX, Ouyang S, Zhu GD, Ji TX, Wu LJ, Xia Y, Guo XG. Diagnostic accuracy of Xpert Xpress Flu/RSV for detection of Influenza and Respiratory syncytial virus. Jpn J Infect Dis 2021; 75:183-191. [PMID: 34053954 DOI: 10.7883/yoken.jjid.2020.987] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Xpert Xpress Flu/RSV is a fast and automated real-time nucleic acid amplification tool for detecting influenza virus and respiratory syncytial virus (RSV). The aim of this study was to verify the accuracy of Xpert Xpress Flu/RSV in detecting influenza virus and RSV. PubMed, EMBASE, Cochrane Library, and Web of Science were searched up to October 2020. The quality of original research was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 guidelines. Meta-DiSc 1.4 software was used to analyze the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and Summary receiver operating characteristic curve. Deek's funnel plot asymmetry test was used to evaluate the publication bias by Stata 12.0. Ten studies with 25 fourfold tables were included in this analysis. The sensitivity of Xpert Xpress Flu/RSV in detecting influenza A, influenza B, and RSV was 0.97, 0.98, 0.96, respectively, and the specificity was 0.97, 1.00, 1.00, respectively. Compared with other common clinical real-time reverse transcriptase PCR (RT-PCR), Xpert Xpress Flu/RSV is a valuable tool for diagnosing influenza virus and RSV with high sensitivity and specificity.
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Affiliation(s)
- Ye-Ling Liu
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Tian-Ao Xie
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Geng-Ling Lin
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Wei Deng
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Qin-Rong Lin
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Zhi-Yong Pan
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Shu-Jin Fan
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China
| | - Zhen-Xing Li
- Department of Respiratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China
| | - Shi Ouyang
- Department of Infectious Disease, The Fifth Affiliated Hospital of Guangzhou Medical University, China
| | - Guo-Dong Zhu
- Department of Geriatrics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, China
| | - Tian-Xing Ji
- Department of Clinical Medicine, The Second Affiliated Hospital of Guangzhou Medical University, China
| | - Li-Juan Wu
- Baoan Maternal and Child Health Hospital of Jinan University, China
| | - Yong Xia
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China.,Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, China.,Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, China
| | - Xu-Guang Guo
- Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, China.,Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, China.,Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, China.,Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, China
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Liu X, Peng X, Lin Z. Evodiamine Enhanced the Anti-Inflammation Effect of Clindamycin in the BEAS-2B Cells Infected with H5N1 and Pneumoniae D39 Through CREB-C/EBPβ Signaling Pathway. Viral Immunol 2021; 34:410-415. [PMID: 33945347 DOI: 10.1089/vim.2020.0319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Pneumonia is a pulmonary disease among children. Evodiamine, a traditional Chinese medicine, is known for anti-inflammatory effect. This study aimed to investigate the impact of evodiamine on severe pneumonia-like cells and the underlying mechanism involved. H5N1 and pneumoniae D39 was used to induce severe pneumonia-like conditions in BEAS-2B cells. The cell viability in BEAS-2B cells after treatments with 0, 20, 40, 60, 80, and 100 μM evodiamine was examined using MTT assays. The protein concentrations of inflammatory cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-6 and IL-1β, and Toll-like receptors (TLRs) were measured by enzyme-linked immunosorbent assay methods and the protein and mRNA changes in C/EBPβ/CREB were measured using Real Time-quantitative polymerase chain reaction and Western blot methods. Our results revealed that Evodiamine significantly decreased TNF-α, IL-6, and IL-1β in BEAS-2B cells. Moreover, evodiamine markedly reduced TLR2,3,4 protein expression and the phosphorylated protein of C/EBPβ and CREB. Besides, evodiamine combined with clindamycin exerted more significant effects than clindamycin alone. Taken together, our results demonstrated that evodiamine enhanced the anti-inflammation effect of clindamycin in the BEAS-2B cells infected with H5N1 and pneumoniae D39 through CREB-C/EBPβ signaling pathway.
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Affiliation(s)
- Xiaqing Liu
- Children's Respiratory Department, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Xiaofang Peng
- Cell and Molecular Diagnosis Center, Sun Yat Sen Memorial Hospital, Sun Yat Sen University, Guangzhou, China
| | - Zhengfang Lin
- Center Laboratory, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
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Clinical Characteristics and Predictors of Mortality in Critically Ill Adult Patients with Influenza Infection. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18073682. [PMID: 33916073 PMCID: PMC8037506 DOI: 10.3390/ijerph18073682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 03/28/2021] [Accepted: 03/31/2021] [Indexed: 11/16/2022]
Abstract
Patients with influenza infection may develop acute respiratory distress syndrome (ARDS), which is associated with high mortality. Some patients with ARDS receiving extracorporeal membrane oxygenation (ECMO) support die of infectious complications. We aimed to investigate the risk factors affecting the clinical outcomes in critically ill patients with influenza. We retrospectively reviewed the medical records of influenza patients between January 2006 and May 2016 at the Kaohsiung Veterans General Hospital in Taiwan. Patients aged below 20 years or without laboratory-confirmed influenza were excluded. Critically ill patients who presented with ARDS (P = 0.004, odds ratio (OR): 8.054, 95% confidence interval (CI): 1.975–32.855), a higher Acute Physiology and Chronic Health Evaluation (APACHE) II score (P = 0.008, OR: 1.102, 95% CI: 1.025–1.184), or higher positive end-expiratory pressure (P = 0.008, OR: 1.259, 95% CI: 1.061–1.493) may have a higher risk of receiving ECMO. Influenza A (P = 0.037, OR: 0.105, 95% CI: 0.013–0.876) and multiple organ failure (P = 0.007, OR: 0.056, 95% CI: 0.007–0.457) were significantly associated with higher mortality rates. In conclusion, our study showed critically ill influenza patients with ARDS, higher APACHE II scores, and higher positive end-expiratory pressure have a higher risk of receiving ECMO support. Influenza A and multiple organ failure are predictors of mortality.
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Lau K, Dorigatti I, Miraldo M, Hauck K. SARIMA-modelled greater severity and mortality during the 2010/11 post-pandemic influenza season compared to the 2009 H1N1 pandemic in English hospitals. Int J Infect Dis 2021; 105:161-171. [PMID: 33548552 DOI: 10.1016/j.ijid.2021.01.070] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/26/2021] [Accepted: 01/29/2021] [Indexed: 10/22/2022] Open
Abstract
OBJECTIVE The COVID-19 pandemic demonstrates the need for understanding pathways to healthcare demand, morbidity, and mortality of pandemic patients. We estimate H1N1 (1) hospitalization rates, (2) severity rates (length of stay, ventilation, pneumonia, and death) of those hospitalized, (3) mortality rates, and (4) time lags between infections and hospitalizations during the pandemic (June 2009 to March 2010) and post-pandemic influenza season (November 2010 to February 2011) in England. METHODS Estimates of H1N1 infections from a dynamic transmission model are combined with hospitalizations and severity using time series econometric analyses of administrative patient-level hospital data. RESULTS Hospitalization rates were 34% higher and severity rates of those hospitalized were 20%-90% higher in the post-pandemic period than the pandemic. Adults (45-64-years-old) had the highest ventilation and pneumonia hospitalization rates. Hospitalizations did not lag infection during the pandemic for the young (<24-years-old) but lagged by one or more weeks for all ages in the post-pandemic period. DISCUSSION The post-pandemic flu season exhibited heightened H1N1 severity, long after the pandemic was declared over. Policymakers should remain vigilant even after pandemics seem to have subsided. Analysis of administrative hospital data and epidemiological modelling estimates can provide valuable insights to inform responses to COVID-19 and future influenza and other disease pandemics.
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Affiliation(s)
- Krystal Lau
- Imperial College Business School: Department of Economics & Public Policy; Centre for Health Economics & Policy Innovation, London, United Kingdom SW7 2AZ.
| | - Ilaria Dorigatti
- Imperial College London: MRC Centre for Global Infectious Disease Analysis (MRC GIDA), Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, London, United Kingdom W2 1PG
| | - Marisa Miraldo
- Imperial College Business School: Department of Economics & Public Policy; Centre for Health Economics & Policy Innovation, London, United Kingdom SW7 2AZ
| | - Katharina Hauck
- Imperial College London: MRC Centre for Global Infectious Disease Analysis (MRC GIDA), Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, London, United Kingdom W2 1PG
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Anzai T, Fukui K, Ito T, Ito Y, Takahashi K. Excess Mortality From Suicide During the Early COVID-19 Pandemic Period in Japan: A Time-Series Modeling Before the Pandemic. J Epidemiol 2021; 31:152-156. [PMID: 33310986 PMCID: PMC7813773 DOI: 10.2188/jea.je20200443] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 11/29/2020] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Suicide amidst the coronavirus disease (COVID-19) pandemic is an important issue. In Japan, the number of suicides in April 2020 decreased by nearly 20% from that in 2019. To assess the impact of an infectious disease pandemic, excess mortality is often discussed. Our main purpose was evaluating excess mortality from suicide in Japan during the early pandemic period. METHODS We used data on suicides collected by the National Police Agency of Japan until June 2020. We estimated excess mortality during the early pandemic period (March-June 2020) using a time-series model of the number of suicides before the pandemic. A quasi-Poisson model was employed for the estimation. We evaluated excess mortalities by the categories of age and sex, and by prefecture. RESULTS No significant excess mortality was observed throughout the early pandemic; instead, a downward trend in the number of suicides for both sexes was noted. For males, negative values of excess mortalities below the lower bound of the 95% prediction interval were observed in April and May. All numbers of females during the period were included in the interval, and the excess mortalities in June were positive and higher than those in April and May. In Tokyo, the number of suicides was below the lower bound throughout the period. CONCLUSION Our results suggest that various changes, such as communication, and social conditions amid the early COVID-19 pandemic induced a decrease in suicides in Japan. However, continuous monitoring is needed to evaluate the long-term effects of the pandemic on suicides.
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Affiliation(s)
- Tatsuhiko Anzai
- Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Keisuke Fukui
- Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan
- Department of Medical Statistics, Research & Development Center, Osaka Medical College, Osaka, Japan
| | - Tsubasa Ito
- Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yuri Ito
- Department of Medical Statistics, Research & Development Center, Osaka Medical College, Osaka, Japan
| | - Kunihiko Takahashi
- Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
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Li J, Chen Y, Wang X, Yu H. Influenza-associated disease burden in mainland China: a systematic review and meta-analysis. Sci Rep 2021; 11:2886. [PMID: 33536462 PMCID: PMC7859194 DOI: 10.1038/s41598-021-82161-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 01/18/2021] [Indexed: 11/22/2022] Open
Abstract
Influenza causes substantial morbidity and mortality. Many original studies have been carried out to estimate disease burden of influenza in mainland China, while the full disease burden has not yet been systematically reviewed. We did a systematic review and meta-analysis to assess the burden of influenza-associated mortality, hospitalization, and outpatient visit in mainland China. We searched 3 English and 4 Chinese databases with studies published from 2005 to 2019. Studies reporting population-based rates of mortality, hospitalization, or outpatient visit attributed to seasonal influenza were included in the analysis. Fixed-effects or random-effects model was used to calculate pooled estimates of influenza-associated mortality depending on the degree of heterogeneity. Meta-regression was applied to explore the sources of heterogeneity. Publication bias was assessed by funnel plots and Egger’s test. We identified 30 studies eligible for inclusion with 17, 8, 5 studies reporting mortality, hospitalization, and outpatient visit associated with influenza, respectively. The pooled influenza-associated all-cause mortality rates were 14.33 and 122.79 per 100,000 persons for all ages and ≥ 65 years age groups, respectively. Studies were highly heterogeneous in aspects of age group, cause of death, statistical model, geographic location, and study period, and these factors could explain 60.14% of the heterogeneity in influenza-associated mortality. No significant publication bias existed in estimates of influenza-associated all-cause mortality. Children aged < 5 years were observed with the highest rates of influenza-associated hospitalizations and ILI outpatient visits. People aged ≥ 65 years and < 5 years contribute mostly to mortality and morbidity burden due to influenza, which calls for targeted vaccination policy for older adults and younger children in mainland China.
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Affiliation(s)
- Jing Li
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China
| | - Yinzi Chen
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China
| | - Xiling Wang
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China. .,Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
| | - Hongjie Yu
- School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Xuhui District, Shanghai, 200231, China
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10
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Liu R, Liu X, Yang P, Du X, He L, Chen T, Li X, Xie G, Wu S, Su J, Xia S, Jiang C, Huffman MD, MacIntyre CR, Wei Z, Wang Q, Dong J, Anderson C. Influenza-associated cardiovascular mortality in older adults in Beijing, China: a population-based time-series study. BMJ Open 2020; 10:e042487. [PMID: 33444216 PMCID: PMC7678395 DOI: 10.1136/bmjopen-2020-042487] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
OBJECTIVE This study comprehensively estimated the excess cardiovascular disease (CVD) mortality attributable to influenza in an older (age ≥65 years) population. DESIGN Ecological study. SETTING Aggregated data from administrative systems on CVD mortality, influenza surveillance and meteorological data in Beijing, China. MAIN OUTCOME MEASURE Excess overall CVD, and separately for ischaemic heart disease (IHD), ischaemic stroke, haemorrhagic stroke mortality attributable to influenza, adjusting for influenza activity, time trend, seasonality and ambient temperature. RESULTS CVD (risk ratio (RR) 1.02, 95% CI 1.01, 1.02), IHD (RR 1.01, 95% CI 1.01, 1.02), ischaemic stroke (RR=1.03, 95% CI 1.02, 1.04), but not haemorrhagic stroke (RR=1.00, 95% CI 0.99, 1.01) mortality, were significantly associated with every 10% increase in influenza activity. An increase in circulating A(H1N1)09pdm, A(H3N2) and B type virus were all significantly associated with CVD and ischaemic stroke mortality, but only A(H3N2) and B type virus with IHD mortality. The strongest increase in disease mortality was in the same week as the increase in influenza activity. Annual excess CVD mortality rate attributable to influenza ranged from 54 to 96 per 100 000 population. The 3%-6% CVD mortality attributable to influenza activity was related to an annual excess of 916-1640 CVD deaths in Beijing, China. CONCLUSIONS Influenza activity has moderate to strong associations with CVD, IHD and ischaemic stroke mortality in older adults in China. Promoting influenza vaccination could have major health benefit in this population. BACKGROUND Influenza may trigger serious CVD events. An estimation of excess CVD mortality attributable to influenza has particular relevance in China where vaccination is low and CVD burden is high. METHODS This study analysed data at the population level (age ≥65 years) using linked aggregated data from administrative systems on CVD mortality, influenza surveillance and meteorological data during 2011 to 2018. Quasi-Poisson regression models were used to estimate the excess overall CVD, and separately for IHD, ischaemic stroke, haemorrhagic stroke mortality attributable to influenza, adjusting for influenza activity, time trend, seasonality and ambient temperature. Analyses were also undertaken for influenza subtypes (A(H1N1)09pdm, A(H3N2) and B viruses), and mortality risk with time lags of 1-5 weeks following influenza activity in the current week.
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Affiliation(s)
- Rong Liu
- Heart Health Research Center, Beijing, China
| | | | - Peng Yang
- Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China
| | - Xin Du
- Heart Health Research Center, Beijing, China
- Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing, China
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Liu He
- Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing, China
| | - Tiange Chen
- Ping An Healthcare Technology, Beijing, China
| | - Xiang Li
- Ping An Healthcare Technology, Beijing, China
| | - Guotong Xie
- Ping An Healthcare Technology, Beijing, China
- Ping An Health Cloud Company Limited, Beijing, China
- Ping An International Smart City Technology Co., Ltd, Beijing, China
| | - Shuangsheng Wu
- Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China
| | - Jianting Su
- Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China
| | - Shijun Xia
- Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing, China
| | - Chao Jiang
- Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing, China
| | - Mark D Huffman
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Chandini Raina MacIntyre
- Biosecurity Research Program, Kirby Institute, The University of New South Wales, Sudney, New South Wales, Australia
| | - Zaihua Wei
- Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China
| | - Quanyi Wang
- Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine, Beijing, China
| | - Jianzeng Dong
- Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing, China
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Craig Anderson
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- The George Institute China at Peking University Health Science Center, Beijing, China
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Dihydrodibenzothiepine: Promising hydrophobic pharmacophore in the influenza cap-dependent endonuclease inhibitor. Bioorg Med Chem Lett 2020; 30:127547. [DOI: 10.1016/j.bmcl.2020.127547] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/27/2020] [Accepted: 09/06/2020] [Indexed: 11/21/2022]
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12
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Jin S, Li J, Cai R, Wang X, Gu Z, Yu H, Fang B, Chen L, Wang C. Age- and sex-specific excess mortality associated with influenza in Shanghai, China, 2010–2015. Int J Infect Dis 2020; 98:382-389. [DOI: 10.1016/j.ijid.2020.07.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/03/2020] [Accepted: 07/09/2020] [Indexed: 02/01/2023] Open
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Mohammad KN, Chan EYY, Wong MCS, Goggins WB, Chong KC. Ambient temperature, seasonal influenza and risk of cardiovascular disease in a subtropical area in Southern China. ENVIRONMENTAL RESEARCH 2020; 186:109546. [PMID: 32334173 DOI: 10.1016/j.envres.2020.109546] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Given the regular winter recurrence of influenza epidemics and the biologically plausible association between seasonal influenza and cardiovascular events, researchers assumed a valid and reliable influenza forecast could envision the timing and burden of winter surge in cardiovascular (CVD) hospitalizations. This, however, is well justified only in temperate regions. In this study, we aim to investigate the temporal association between ambient temperature, seasonal influenza and risk of cardiovascular events in a subtropical city. METHODS Generalized additive model was used in conjunction with distributed-lag non-linear model of quasi-Poisson family to estimate the association of interest with daily CVD admissions as outcome and daily influenza admissions as predictor, while controlling for meteorological factors (i.e. temperature, relative humidity, wind speed and total rainfall) and respiratory pollutants (i.e. nitrogen dioxide, sulphur dioxide, ozone and PM10). Results were expressed in the form of relative risk (RR). RESULTS Using median as the reference value, a U-shaped association was observed between CVD admissions and temperature. A slight decrease in RR was detected mainly towards the lower end of the temperature scale after adjusting for influenza admissions. Risk of CVD admission was found to be positively associated with the number of influenza hospitalization cases; this association remained consistent and statistically significant across subgroups of age except for those aged 5-49 years. CONCLUSION The slight reduction in CVD admission risk towards the lower end of the temperature scale after controlling for influenza activity might be attributed to the winter peaks of influenza, meaning that the effect of low temperature on CVD admissions might be partly mediated by influenza infection. In summary, this study reassures us that ambient temperature is independently associated with CVD hospital admissions and offers support for a positive association between seasonal influenza activity and cardiovascular events in Hong Kong.
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Affiliation(s)
- Kirran N Mohammad
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Emily Ying Yang Chan
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Martin Chi Sang Wong
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - William Bernard Goggins
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Ka Chun Chong
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, China; Centre for Health System and Policy Research, The Chinese University of Hong Kong, Hong Kong, China.
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Influenza-attributable years of life lost in older adults in a subtropical city in China, 2012-2017: A modeling study based on a competing risks approach. Int J Infect Dis 2020; 97:354-359. [PMID: 32562848 DOI: 10.1016/j.ijid.2020.06.041] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/09/2020] [Accepted: 06/11/2020] [Indexed: 11/21/2022] Open
Abstract
OBJECTIVE The aim of this study was to estimate influenza-attributable years of life lost (YLL) in older adults in subtropical Hefei, China during the years 2012-2017, based on a competing risks approach. METHODS The quasi-Poisson model was fitted to weekly numbers of all-cause deaths by 5-year age groups for older adults ≥60 years of age. The product of the weekly influenza-like illness consultation rate and the proportion of specimens that tested positive for influenza was taken as the measurement of influenza activity, which was incorporated into the model as an exploratory variable. Excess deaths associated with influenza were calculated by subtracting baseline deaths (setting influenza activity to zero) from fitted deaths. Influenza-attributable YLL accounting for competing risks was estimated using restricted mean lifetime survival analysis. RESULTS The annual influenza-attributable YLL was highest in the 75-79 years age group (565 per 100,000 persons, 95% confidence interval 550-580), followed by the 80-84, 70-74, 85-89, 65-69, and 60-64 years age groups. Influenza A(H3N2) virus was associated with higher YLL than A(H1N1) and B viruses. Influenza-attributable YLL accounted for 1.03-1.53% of total YLL, and the proportion would be overestimated to 2.91-7.34% if the traditional Kaplan-Meier method ignoring competing risks was used. CONCLUSIONS Although influenza-associated mortality increased with age, influenza-attributable YLL was found to be highest in the 75-79 years age group.
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Qi L, Li Q, Ding XB, Gao Y, Ling H, Liu T, Xiong Y, Su K, Tang WG, Feng LZ, Liu QY. Mortality burden from seasonal influenza in Chongqing, China, 2012-2018. Hum Vaccin Immunother 2020; 16:1668-1674. [PMID: 32343618 PMCID: PMC7482776 DOI: 10.1080/21645515.2019.1693721] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Purpose To estimate influenza-associated excess mortality rates (EMRs) in Chongqing from 2012 to 2018. Methods We obtained weekly mortality data for all-cause and four underlying causes of death (circulatory and respiratory disease (CRD), pneumonia and influenza (P&I), chronic obstructive pulmonary disease (COPD) and ischemic heart disease (IDH)), and influenza surveillance data, from 2012 to 2018. A negative-binomial regression model was used to estimate influenza-associated EMRs in two age groups (<65 years and ≥65 years). Results It was estimated that an annual average of 10025 influenza-associated deaths occurred in Chongqing, corresponding to 5.2% of all deaths. The average EMR for all-cause death associated with influenza was 33.5 (95% confidence interval (CI): 31.5–35.6) per 100 000 persons, and in separate cause-specific models we attributed 24.7 (95% CI: 23.3–26.0), 0.8 (95% CI: 0.7–0.8), 8.5 (95% CI: 8.1–9.0) and 5.0 (95% CI: 4.7–5.3) per 100 000 persons EMRs to CRD, P&I, COPD and IDH, respectively. The estimated EMR for influenza B virus was 20.6 (95% CI: 20.3–21.0), which was significantly higher than the rates of 5.3 (95% CI: 4.5–6.1) and 7.5 (95% CI: 6.7–8.3) for A(H3N2) and A(H1N1) pdm09 virus, respectively. The estimated EMR was 152.3 (95% CI: 136.1–168.4) for people aged ≥65 years, which was significantly higher than the rate for those aged <65 years (6.8, 95% CI: 6.3–7.2). Conclusions Influenza was associated with substantial EMRs in Chongqing, especially among elderly people. Influenza B virus caused a relatively higher excess mortality impact compared with A(H1N1)pdm09 and A(H3N2). It is advisable to optimize future seasonal influenza vaccine reimbursement policy in Chongqing to curb disease burden.
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Affiliation(s)
- Li Qi
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China.,Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Qin Li
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Xian-Bin Ding
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Yuan Gao
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China
| | - Hua Ling
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Tian Liu
- Infectious Disease Control and Prevention Department, Jingzhou Center for Disease Control and Prevention , Jingzhou City, Hubei Province, China
| | - Yu Xiong
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Kun Su
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Wen-Ge Tang
- Infectious Disease Control and Prevention Department, Chongqing Municipal Center for Disease Control and Prevention , Chongqing, China
| | - Lu-Zhao Feng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention , Beijing, China
| | - Qi-Yong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention , Beijing, China
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16
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Epidemiological features and time-series analysis of influenza incidence in urban and rural areas of Shenyang, China, 2010-2018. Epidemiol Infect 2020; 148:e29. [PMID: 32054544 PMCID: PMC7026897 DOI: 10.1017/s0950268820000151] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
In recent years, there have been a significant influenza activity and emerging influenza strains in China, resulting in an increasing number of influenza virus infections and leading to public health concerns. The aims of this study were to identify the epidemiological and aetiological characteristics of influenza and establish seasonal autoregressive integrated moving average (SARIMA) models for forecasting the percentage of visits for influenza-like illness (ILI%) in urban and rural areas of Shenyang. Influenza surveillance data were obtained for ILI cases and influenza virus positivity from 18 sentinel hospitals. The SARIMA models were constructed to predict ILI% for January–December 2019. During 2010–2018, the influenza activity was higher in urban than in rural areas. The age distribution of ILI cases showed the highest rate in young children aged 0–4 years. Seasonal A/H3N2, influenza B virus and pandemic A/H1N1 continuously co-circulated in winter and spring seasons. In addition, the SARIMA (0, 1, 0) (0, 1, 2)12 model for the urban area and the SARIMA (1, 1, 1) (1, 1, 0)12 model for the rural area were appropriate for predicting influenza incidence. Our findings suggested that there were regional and seasonal distinctions of ILI activity in Shenyang. A co-epidemic pattern of influenza strains was evident in terms of seasonal influenza activity. Young children were more susceptible to influenza virus infection than adults. These results provide a reference for future influenza prevention and control strategies in the study area.
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Li L, Liu Y, Wu P, Peng Z, Wang X, Chen T, Wong JYT, Yang J, Bond HS, Wang L, Lau YC, Zheng J, Feng S, Qin Y, Fang VJ, Jiang H, Lau EHY, Liu S, Qi J, Zhang J, Yang J, He Y, Zhou M, Cowling BJ, Feng L, Yu H. Influenza-associated excess respiratory mortality in China, 2010-15: a population-based study. Lancet Public Health 2019; 4:e473-e481. [PMID: 31493844 PMCID: PMC8736690 DOI: 10.1016/s2468-2667(19)30163-x] [Citation(s) in RCA: 131] [Impact Index Per Article: 26.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 07/24/2019] [Accepted: 07/30/2019] [Indexed: 01/03/2023]
Abstract
BACKGROUND The estimation of influenza-associated excess mortality in countries can help to improve estimates of the global mortality burden attributable to influenza virus infections. We did a study to estimate the influenza-associated excess respiratory mortality in mainland China for the 2010-11 through 2014-15 seasons. METHODS We obtained provincial weekly influenza surveillance data and population mortality data for 161 disease surveillance points in 31 provinces in mainland China from the Chinese Center for Disease Control and Prevention for the years 2005-15. Disease surveillance points with an annual average mortality rate of less than 0·4% between 2005 and 2015 or an annual mortality rate of less than 0·3% in any given years were excluded. We extracted data for respiratory deaths based on codes J00-J99 under the tenth edition of the International Classification of Diseases. Data on respiratory mortality and population were stratified by age group (age <60 years and ≥60 years) and aggregated by province. The overall annual population data of each province and national annual respiratory mortality data were compiled from the China Statistical Yearbook. Influenza surveillance data on weekly proportion of samples testing positive for influenza virus by type or subtype for 31 provinces were extracted from the National Sentinel Hospital-based Influenza Surveillance Network. We estimated influenza-associated excess respiratory mortality rates between the 2010-11 and 2014-15 seasons for 22 provinces with valid data in the country using linear regression models. Extrapolation of excess respiratory mortality rates was done using random-effect meta-regression models for nine provinces without valid data for a direct estimation of the rates. FINDINGS We fitted the linear regression model with the data from 22 of 31 provinces in mainland China, representing 83·0% of the total population. We estimated that an annual mean of 88 100 (95% CI 84 200-92 000) influenza-associated excess respiratory deaths occurred in China in the 5 years studied, corresponding to 8·2% (95% CI 7·9-8·6) of respiratory deaths. The mean excess respiratory mortality rates per 100 000 person-seasons for influenza A(H1N1)pdm09, A(H3N2), and B viruses were 1·6 (95% CI 1·5-1·7), 2·6 (2·4-2·8), and 2·3 (2·1-2·5), respectively. Estimated excess respiratory mortality rates per 100 000 person-seasons were 1·5 (95% CI 1·1-1·9) for individuals younger than 60 years and 38·5 (36·8-40·2) for individuals aged 60 years or older. Approximately 71 000 (95% CI 67 800-74 100) influenza-associated excess respiratory deaths occurred in individuals aged 60 years or older, corresponding to 80% of such deaths. INTERPRETATION Influenza was associated with substantial excess respiratory mortality in China between 2010-11 and 2014-15 seasons, especially in older adults aged at least 60 years. Continuous and high-quality surveillance data across China are needed to improve the estimation of the disease burden attributable to influenza and the best public health interventions are needed to curb this burden. FUNDING National Science Fund for Distinguished Young Scholars, National Science and Technology Major Project of China, National Institute of Health Research, the Harvard Center for Communicable Disease Dynamics from the National Institute of General Medical Sciences, and the China-US Collaborative Program on Emerging and Re-emerging Infectious Disease.
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Affiliation(s)
- Li Li
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yunning Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Zhibin Peng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiling Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Tao Chen
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese CDC, Beijing, China
| | - Jessica Y T Wong
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Juan Yang
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Helen S Bond
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiu Chung Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jiandong Zheng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shuo Feng
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ying Qin
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Vicky J Fang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Hui Jiang
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Eric H Y Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Shiwei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jinlei Qi
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Juanjuan Zhang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jing Yang
- National Institute for Viral Disease Control and Prevention, Collaboration Innovation Center for Diagnosis and Treatment of Infectious Diseases, Chinese CDC, Beijing, China
| | - Yangni He
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Luzhao Feng
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Hongjie Yu
- Key Laboratory of Surveillance and Early-warning on Infectious Disease, Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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Salto-Quintana JN, Rivera-Alfaro G, Sánchez-Ramos EL, Gómez-Gómez A, Noyola DE. Post-pandemic influenza-associated mortality in Mexico. Pathog Glob Health 2019; 113:67-74. [PMID: 30895882 PMCID: PMC6493299 DOI: 10.1080/20477724.2019.1589211] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
Abstract
Influenza is a leading cause of respiratory tract infections worldwide and there is limited information on the impact of the influenza A(H1N1)pdm virus on mortality after the 2009 pandemic. Using national mortality register data through 1998-2015 in Mexico, influenza-associated mortality was estimated for respiratory, cardiovascular, and all-cause events. The proportion of influenza-associated respiratory and cardiovascular deaths among different age groups were compared. There were 8,853,986 death registries included for the 1998-2015 winter seasons, average influenza-associated respiratory, cardiovascular, and all-cause mortality rates were 5.2, 6.3, and 19.6 deaths/100,000 population, respectively. The largest number of respiratory influenza-associated deaths occurred in adults 60 years of age and older, followed by children <5 years of age; during the 2009 pandemic, 2011-2012, and 2013-2014 winter seasons there was a larger number of deaths in the 20-59 years old group. Influenza-associated mortality rates showed a continuous reduction in children <5 years of age. After the 2009 pandemic, influenza A(H1N1)pdm09 virus-associated mortality in Mexico showed a persistent change in the demographic pattern of the most severely affected population, particularly during the 2013-2014 season. Influenza associated-mortality has decreased in children <5 years of age and continue to be elevated in adults >60 years of age.
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Affiliation(s)
- Jack N. Salto-Quintana
- Microbiology Department, Facultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
- Internal Medicine Division, Hospital Central “Dr. Ignacio Morones Prieto”, San Luis Potosí, México
| | - Gerardo Rivera-Alfaro
- Microbiology Department, Facultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
| | - Evelyn L. Sánchez-Ramos
- Childhood and Adolescence Health Care Department, Servicios de Salud de San Luis Potosí, San Luis Potosí, México
| | - Alejandro Gómez-Gómez
- Internal Medicine Division, Hospital Central “Dr. Ignacio Morones Prieto”, San Luis Potosí, México
| | - Daniel E. Noyola
- Microbiology Department, Facultad de Medicina, Universidad Autónoma de San Luis Potosí, San Luis Potosí, México
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Ye C, Zhu W, Yu J, Li Z, Zhang Y, Wang Y, Gu H, Zou W, Hao L, Hu W. Understanding the complex seasonality of seasonal influenza A and B virus transmission: Evidence from six years of surveillance data in Shanghai, China. Int J Infect Dis 2019; 81:57-65. [PMID: 30684745 DOI: 10.1016/j.ijid.2019.01.027] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 01/06/2019] [Accepted: 01/17/2019] [Indexed: 10/27/2022] Open
Abstract
OBJECTIVES Understanding the complexity of influenza subtype seasonality is critical to promoting a suitable vaccination program. The aim of this study was to identify and compare the seasonality and epidemiological features of seasonal influenza subtypes after the 2009 A/H1N1 pandemic and to lay a foundation for further investigation into the social and environmental factors affecting seasonal influenza virus transmission. METHODS Influenza-like illness (ILI) case surveillance was conducted in two sentinel hospitals in Pudong New Area, Shanghai between 2012 and 2018. Weekly data on ILI cases were analyzed. A time-series seasonal decomposition analysis was used to reveal the seasonality of influenza and epidemiological features among different subtypes. RESULTS In total, 10977 ILI patients were enrolled of whom 2385 (21.7%) had laboratory-confirmed influenza. Compared to influenza A (16.3%), influenza B (5.4%) was less frequently detected among the ILI patients (p<0.001). Semiannual epidemic peaks were identified in four of the years during the 6-year study period, while only one annual epidemic peak was found in the other two years. An epidemic peak occurred in each winter season, and a secondary peak also occasionally occurred in summer or spring. A/H3N2 predominated in both summer and winter, while A/H1N1, B/Yamagata, and B/Victoria circulated almost exclusively in winter or spring. Two lineages of influenza B seemed to predominate in alternating years. CONCLUSIONS This study highlights the complexity of seasonal influenza virus activity in a subtropical region of China, presenting both semiannual and annual epidemic peaks in different years. The results of this study may provide further insight into possible improvements in the timing of influenza vaccination in Shanghai, China.
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Affiliation(s)
- Chuchu Ye
- Research Base of Key Laboratory of Surveillance and Early Warning of Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Shanghai, China; School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Weiping Zhu
- Research Base of Key Laboratory of Surveillance and Early Warning of Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Shanghai, China
| | - Jianxing Yu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhongjie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuzhou Zhang
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Yuanping Wang
- Research Base of Key Laboratory of Surveillance and Early Warning of Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Shanghai, China
| | - Huozheng Gu
- Research Base of Key Laboratory of Surveillance and Early Warning of Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Shanghai, China
| | - Wenwei Zou
- Research Base of Key Laboratory of Surveillance and Early Warning of Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Shanghai, China
| | - Lipeng Hao
- Research Base of Key Laboratory of Surveillance and Early Warning of Infectious Disease, Pudong New Area Center for Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Shanghai, China.
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
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Li H, Chen X, Zhou SJ. Dauricine combined with clindamycin inhibits severe pneumonia co-infected by influenza virus H5N1 and Streptococcus pneumoniae in vitro and in vivo through NF-κB signaling pathway. J Pharmacol Sci 2018; 137:12-19. [PMID: 29769163 DOI: 10.1016/j.jphs.2018.01.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 01/14/2018] [Accepted: 01/18/2018] [Indexed: 11/29/2022] Open
Abstract
Dauricine, isolated from Menispermum dauricum, has been widely used for treatment of various diseases, including cardiac ischemia and inflammation-related diseases. However, little is known regarding to the effect of dauricine on severe pneumonia. Therefore, the aim was to investigate the effect of dauricine on severe pneumonia and its mechanism during progress. Herein, H5N1 and Streptococcus pneumoniae (D39) were conducted to induce severe pneumonia in both BEAS-2B cells and mice. In vitro, dauricine reversed the protein and mRNA expressions of TNF-α, IL-6 and IL-1β, examined by ELISA and qRT-PCR assay, respectively. In addition, the nuclear translocation of NF-κB/p65 and the phosphorylation expressions of IκBα and IKKα/β, examined by western blotting, were dose-dependently dropped by dauricine. However, dauricine had no significant effect on MAPKs, including JNK, ERK and p38. In vivo, dauricine significantly decreased MPO activity, the lung wet/dry weight ratio, the protein and mRNA expression of TNF-α, IL-6 and IL-1β, the expressions of NF-κB/p65, and attenuated the lung histological alterations. Besides, compared to dauricine alone, combined with clindamycin had more remarkably effects on severe pneumonia in vitro. Overall, the results suggested that dauricine, a relatively drug that targets NF-κB, in combination with clindamycin, maybe a novel therapeutic strategy for severe pneumonia.
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Affiliation(s)
- Hui Li
- Department of Critical Care Medicine, The Third Affiliated Hospital of Soochow University, The First People's Hospital of Changzhou, No. 185 Juqian Street, Changzhou 213003, Jiangsu, People's Republic of China
| | - Xin Chen
- Emergency Department, The Third Affiliated Hospital of Soochow University, The First People's Hospital of Changzhou, No. 185 Juqian Street, Changzhou 213003, Jiangsu, People's Republic of China
| | - Shu-Jun Zhou
- Department of Critical Care Medicine, The Third Affiliated Hospital of Soochow University, The First People's Hospital of Changzhou, No. 185 Juqian Street, Changzhou 213003, Jiangsu, People's Republic of China.
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21
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Liu XX, Li Y, Zhu Y, Zhang J, Li X, Zhang J, Zhao K, Hu M, Qin G, Wang XL. Seasonal pattern of influenza activity in a subtropical city, China, 2010-2015. Sci Rep 2017; 7:17534. [PMID: 29235535 PMCID: PMC5727502 DOI: 10.1038/s41598-017-17806-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 12/01/2017] [Indexed: 11/13/2022] Open
Abstract
Influenza seasonality study is critical for policy-makers to choose an optimal time for influenza vaccination campaign, especially for subtropical regions where influenza seasonality and periodicity are unclear. In this study, we explored the seasonality and periodicity of influenza in Hefei, China during 2010 to 2015 using five proxies originated from three data sources of clinical surveillance of influenza-like illness (ILI), laboratory surveillance of influenza and death registration of pneumonia and influenza. We combined both wavelets analysis and de-linear-trend regression with Fourier harmonic terms to estimate seasonal characteristics of epidemic phase, peak time, amplitude, ratio of dominant seasonality. We found both annual cycle of influenza epidemics peaking in December-February and semi-annual cycle peaking in December-February and June-July in subtropical city Hefei, China. Compared to proxies developed by ILI and death registration data separately, influenza proxies incorporated laboratory surveillance data performed better seasonality and periodicity, especially in semi-annual periodicity in Hefei. Proxy of ILI consultation rate showed more timeliness peak than other proxies, and could be useful in developing the early warning model for influenza epidemics. Our study suggests to integrate clinical and laboratory surveillance of influenza for future influenza seasonality studies in subtropical regions.
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Affiliation(s)
- Xu-Xiang Liu
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Yahong Li
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China
| | - Yibing Zhu
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Juanjuan Zhang
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China
| | - Xiaoru Li
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Junqing Zhang
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Kefu Zhao
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Mingxia Hu
- Hefei Center for Disease Control and Prevention, Anhui, China
| | - Guoyou Qin
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China.
| | - Xi-Ling Wang
- Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China.
- Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
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22
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Yu X, Wang C, Chen T, Zhang W, Yu H, Shu Y, Hu W, Wang X. Excess pneumonia and influenza mortality attributable to seasonal influenza in subtropical Shanghai, China. BMC Infect Dis 2017; 17:756. [PMID: 29212467 PMCID: PMC5719671 DOI: 10.1186/s12879-017-2863-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 11/27/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Disease burden attributable to influenza is substantial in subtropical regions. Our study aims to estimate excess pneumonia and influenza (P&I) mortality associated with influenza by subtypes/lineages in Shanghai, China, 2010-2015. METHODS Quasi-Poisson regression models were fitted to weekly numbers of deaths from causes coded as P&I for Shanghai general and registered population. Three proxies for influenza activity were respectively used as an explanatory variable. Long-term trend, seasonal trend and absolute humidity were adjusted for as confounding factors. The outcome measurements of excess P&I mortality associated with influenza subtypes/lineages were derived by subtracting the baseline mortality from fitted mortality. RESULTS Excess P&I mortality associated with influenza were 0.22, 0.30, and 0.23 per 100,000 population for three different proxies in Shanghai general population, lower than those in registered population (0.34, 0.48, and 0.36 per 100,000 population). Influenza B (Victoria) lineage did not contribute to excess P&I mortality (P = 0.206) while influenza B (Yamagata) lineage did (P = 0.044). Influenza-associated P&I mortality was high in the elderly population. CONCLUSIONS Seasonal influenza A virus had a higher P&I mortality than influenza B virus, while B (Yamagata) lineage is the dominant lineage attributable to P&I mortality.
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Affiliation(s)
- Xinchun Yu
- Department of Biostatistics, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, 200231 Xuhui District, Shanghai, China
| | - Chunfang Wang
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Tao Chen
- National Institute for Viral Disease Control and Prevention, China Centers for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, China
| | - Wenyi Zhang
- Institute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, China
| | - Huiting Yu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Yuelong Shu
- National Institute for Viral Disease Control and Prevention, China Centers for Disease Control and Prevention, Key Laboratory for Medical Virology, National Health and Family Planning Commission, Beijing, China.,School of Public Health, Sun Yat-sen University, Shenzhen, China
| | - Wenbiao Hu
- School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, Brisbane, QLD, 4059, Australia. .,Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Brisbane, QLD, 4059, Australia.
| | - Xiling Wang
- Department of Biostatistics, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, 200231 Xuhui District, Shanghai, China. .,Shanghai Key Laboratory of Meteorology and Health, Shanghai, China.
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