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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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Li H, Zeng Y, Gan L, Tuersun Y, Yang J, Liu J, Chen J. Urban-rural disparities in the healthy ageing trajectory in China: a population-based study. BMC Public Health 2022; 22:1406. [PMID: 35870914 PMCID: PMC9308310 DOI: 10.1186/s12889-022-13757-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 06/22/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Purpose
The aim of this study is to measure the trajectory of healthy ageing among Chinese middle-aged and older population, and explore the disparity of the trajectory, as well as contributing factors, between urban and rural areas in China.
Methods
A total of 9402 respondents aged 45 years and older interviewed in four waves (2011, 2013, 2015 and 2018) were selected from the China Health and Retirement Longitudinal Study. Healthy ageing score was calculated through item response theory. A latent growth mixture model (LGMM) was applied to distinguish the trajectory of healthy aging. A multinomial logistics regression model (MLRM) was used to explore the relationship between urban-rural areas and healthy aging trajectories, and further to explore associated factors in rural and urban areas separately.
Results
The healthy ageing score was lower in rural areas than urban areas in each survey wave. Five classes (“continuing-low”, “continuing-middle”, “continuing-middle-to-high”, “significantly-declining”, “continuing-high”) were grouped through LGMM. The MLRM results showed that urban living was significantly associated with a higher likelihood of being healthy (for [continuing-low/continuing-high]: β = − 1.17, RRR = 0.31, P < 0.001, 95% CI = 0.18–0.53; and for [continuing-middle/continuing-high]: β = − 0.53, RRR = 0.59, P < 0.001, 95% CI = 0.49–0.71).
Conclusion
Healthy ageing is a prominent objective in the development of a country, and rural-urban disparities are an essential obstacle to overcome, with the rural population more likely to develop a low level of healthy ageing trajectory. Prevention and standardized management of chronic diseases should be enhanced, and social participation should be encouraged to promote healthy ageing. The policy inclination and resource investment should be enhanced to reduce disparity in healthy ageing between urban and rural areas in China.
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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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Estimating excess septicaemia mortality and hospitalisation burden associated with influenza in Hong Kong, 1998 to 2019. Epidemiol Infect 2022; 150:e101. [PMID: 35606895 PMCID: PMC9128349 DOI: 10.1017/s0950268822000760] [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] [Indexed: 11/07/2022] Open
Abstract
Influenza virus infections can lead to a number of secondary complications, including sepsis. We applied linear regression models to mortality and hospital admission data coded for septicaemia from 1998 to 2019 in Hong Kong, and estimated that septicaemia was associated with an annual average excess mortality rate of 0.23 (95% CI 0.04–0.40) per 100 000 persons per year and an excess septicaemia hospitalisation rate of 1.73 (95% CI 0.94–2.50) per 100 000 persons per year. The highest excess morbidity and mortality was found in older adults and young children, and during influenza A(H3N2) epidemics.
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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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Feng L, Feng S, Chen T, Yang J, Lau YC, Peng Z, Li L, Wang X, Wong JYT, Qin Y, Bond HS, Zhang J, Fang VJ, Zheng J, Yang J, Wu P, Jiang H, He Y, Cowling BJ, Yu H, Shu Y, Lau EHY. Burden of influenza-associated outpatient influenza-like illness consultations in China, 2006-2015: A population-based study. Influenza Other Respir Viruses 2020; 14:162-172. [PMID: 31872547 PMCID: PMC7040965 DOI: 10.1111/irv.12711] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 12/04/2019] [Accepted: 12/08/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Human influenza virus infections cause a considerable burden of morbidity and mortality worldwide each year. Understanding regional influenza-associated outpatient burden is crucial for formulating control strategies against influenza viruses. METHODS We extracted the national sentinel surveillance data on outpatient visits due to influenza-like-illness (ILI) and virological confirmation of sentinel specimens from 30 provinces of China from 2006 to 2015. Generalized additive regression models were fitted to estimate influenza-associated excess ILI outpatient burden for each individual province, accounting for seasonal baselines and meteorological factors. RESULTS Influenza was associated with an average of 2.5 excess ILI consultations per 1000 person-years (py) in 30 provinces of China each year from 2006 to 2015. Influenza A(H1N1)pdm09 led to a higher number of influenza-associated ILI consultations in 2009 across all provinces compared with other years. The excess ILI burden was 4.5 per 1000 py among children aged below 15 years old, substantially higher than that in adults. CONCLUSIONS Human influenza viruses caused considerable impact on population morbidity, with a consequent healthcare and economic burden. This study provided the evidence for planning of vaccination programs in China and a framework to estimate burden of influenza-associated outpatient consultations.
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Affiliation(s)
- Luzhao Feng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Shuo Feng
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Tao Chen
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
| | - Juan Yang
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Yiu Chung Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Zhibin Peng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Li Li
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Xiling Wang
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Jessica Y. T. Wong
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Ying Qin
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Helen S. Bond
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Juanjuan Zhang
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Vicky J. Fang
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Jiandong Zheng
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Jing Yang
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Hui Jiang
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
| | - Yangni He
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
| | - Hongjie Yu
- Key Laboratory of Surveillance and Early‐warning on Infectious DiseaseDivision of Infectious DiseaseChinese Center for Disease Control and PreventionBeijingChina
- Key Laboratory of Public Health SafetyMinistry of EducationSchool of Public HealthFudan UniversityShanghaiChina
| | - Yuelong Shu
- National Institute for Viral Disease Control and PreventionCollaboration Innovation Center for Diagnosis and Treatment of Infectious DiseasesChinese Center for Disease Control and PreventionBeijingChina
- School of Public Health (Shenzhen)Sun Yat‐sen UniversityShenzhenChina
| | - Eric H. Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and ControlSchool of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina
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Ng Y, Chua LAV, Ma S, Jian Ming Lee V. Estimates of influenza-associated hospitalisations in tropical Singapore, 2010-2017: Higher burden estimated in more recent years. Influenza Other Respir Viruses 2019; 13:574-581. [PMID: 31433131 PMCID: PMC6800300 DOI: 10.1111/irv.12676] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 08/06/2019] [Accepted: 08/06/2019] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND We previously estimated Singapore's influenza-associated hospitalisation rate for pneumonia and influenza (P&I) in 2010-2012 to be 29.6 per 100 000 person-years, which corresponds to 11.2% of all P&I hospitalisations. OBJECTIVES This study aims to update Singapore's estimates of the influenza-associated pneumonia and influenza (P&I) hospitalisation burden using the latest data from 2010 to 2017. METHODS We estimated the number of P&I hospitalisations associated with influenza using generalised additive models. We specified the weekly number of admissions for P&I and the weekly influenza positivity in the models, along with potential confounders such as weekly respiratory syncytial virus (RSV) positivity and meteorological data. RESULTS In 2010-2017, 16.3% of all P&I hospitalisations in Singapore were estimated to be attributed to influenza, corresponding to an excess influenza-associated P&I hospitalisation rate of 50.1 per 100 000 person-years. Higher excess rates were estimated for children aged 0-4 years (186.8 per 100 000 person-years) and elderly aged ≥ 65 years (338.0 per 100 000 person-years). Higher influenza-associated hospitalisation rates were estimated for 2016 and 2017 (67.9 and 75.1 per 100 000 persons, respectively) years when the influenza A(H3N2) subtype was dominant. CONCLUSION Influenza burden in Singapore has increased since 2010. Influenza vaccination programmes should continue to be prioritised for the young and the elderly.
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Affiliation(s)
- Yixiang Ng
- Epidemiology and Disease Control DivisionMinistry of HealthSingapore CitySingapore
| | - Lily Ai Vee Chua
- Epidemiology and Disease Control DivisionMinistry of HealthSingapore CitySingapore
| | - Stefan Ma
- Epidemiology and Disease Control DivisionMinistry of HealthSingapore CitySingapore
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Preliminary results of official influenza and acute respiratory infection surveillance in two towns of Burkina Faso, 2013-2015. BMC Infect Dis 2018; 18:330. [PMID: 30012098 PMCID: PMC6048705 DOI: 10.1186/s12879-018-3241-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 07/05/2018] [Indexed: 11/10/2022] Open
Abstract
Background In 2010, influenza, influenza-like illness (ILI) and acute respiratory infection (ARI) surveillance was established by the government of Burkina Faso. We provide preliminary descriptive results from this surveillance activity. Methods The study period was 2013 through 2015. Two primary healthcare facilities in Bobo-Dioulasso district reported ILI in outpatients. Influenza virology, using reverse transcription-polymerase chain reaction (rRT-PCR), was available for a proportion of ILI patients. One hospital, in the capital Ouagadougou, reported ARI in both outpatients and inpatients (hospitalized). Inpatients admitted with ARI were considered severe ARI (SARI). We estimated the proportion of primary care outpatient visits that were ILI, and the proportion of those that were due to influenza, by age. We estimated the proportion of hospital outpatient visits that were ARI and the proportion of those that were SARI, by age. Results Among combined outpatient visits in the Bobo-Dioulasso facilities, 19.6% were for ILI. One half (49.9%) of outpatient visits in infants and 30.9% in 1–4 year-olds were ILI. Among ILI outpatient visits 14.8% were due to influenza virus and, of these, 58.5% were type A and 41.5% type B. At the Ouagadougou hospital, 6.7% of outpatient visits were ARI, and 22.3% of those were SARI. The highest proportions of ARI were among infants (19.8%) and 1–4 year-olds (16.0%). The proportion of ARI that was SARI was highest among ≥15 year-olds (31.5%) followed by 1–4 year-olds (22.4%). Overall, 4.1% of SARI patients died. Conclusions These preliminary data indicate the importance of respiratory infections among health care attendances in Burkina Faso, and influenza may be an important contributor to these.
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Infection prevention and control in outpatient settings in China-structure, resources, and basic practices. Am J Infect Control 2018; 46:802-807. [PMID: 29395504 DOI: 10.1016/j.ajic.2017.12.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2017] [Revised: 12/06/2017] [Accepted: 12/06/2017] [Indexed: 02/05/2023]
Abstract
BACKGROUND More than 7 billion visits are made by patients to ambulatory services every year in mainland China. Healthcare-associated infections are becoming a new source of illness for outpatients. Little is known about infection prevention, control structure, resources available, and basic practices in outpatient settings. METHODS In 2014, we conducted a multisite survey. Five provinces were invited to participate based on geographic dispersion. Self-assessment questionnaires regarding the structure, infrastructure, apparatus and materials, and basic activities of infection prevention and control were issued to 25 hospitals and 5 community health centers in each province. A weight was assigned to each question according to its importance. RESULTS Overall, 146 of 150 facilities (97.3%) participated in this study. The average survey score was 77.6 (95% confidence interval 75.7-79.5) and varied significantly between the different gross domestic product areas (P < .01), but scores were not significantly different between the 5 facility types (P = .07). The main lapse of infrastructure was in providing hand hygiene equipment (43.4%) and masks (38.7%) for patients in the waiting areas and main entrances. CONCLUSION In a sample of ambulatory facilities in 5 provinces in China, infection prevention and control was practiced consistently, although there were lapses in some areas.
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Stewart RJ, Ly S, Sar B, Ieng V, Heng S, Sim K, Machingaidze C, Roguski K, Dueger E, Moen A, Tsuyuoka R, Iuliano AD. Using a hospital admission survey to estimate the burden of influenza-associated severe acute respiratory infection in one province of Cambodia-methods used and lessons learned. Influenza Other Respir Viruses 2018; 12:104-112. [PMID: 29453796 PMCID: PMC5818350 DOI: 10.1111/irv.12489] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/09/2017] [Indexed: 01/15/2023] Open
Abstract
Background Understanding the burden of influenza‐associated severe acute respiratory infection (SARI) is important for setting national influenza surveillance and vaccine priorities. Estimating influenza‐associated SARI rates requires hospital‐based surveillance data and a population‐based denominator, which can be challenging to determine. Objectives We present an application of the World Health Organization's recently developed manual (WHO Manual) including hospital admission survey (HAS) methods for estimating the burden of influenza‐associated SARI, with lessons learned to help others calculate similar estimates. Methods Using an existing SARI surveillance platform in Cambodia, we counted influenza‐associated SARI cases during 2015 at one sentinel surveillance site in Svay Rieng Province. We applied WHO Manual‐derived methods to count respiratory hospitalizations at all hospitals within the catchment area, where 95% of the sentinel site case‐patients resided. We used HAS methods to adjust the district‐level population denominator for the sentinel site and calculated the incidence rate of influenza‐associated SARI by dividing the number of influenza‐positive SARI infections by the adjusted population denominator and multiplying by 100 000. We extrapolated the rate to the provincial population to derive a case count for 2015. We evaluated data sources, detailed steps of implementation, and identified lessons learned. Results We estimated an adjusted influenza‐associated 2015 SARI rate of 13.5/100 000 persons for the catchment area of Svay Rieng Hospital and 77 influenza‐associated SARI cases in Svay Rieng Province after extrapolation. Conclusions Methods detailed in the WHO Manual and operationalized successfully in Cambodia can be used in other settings to estimate rates of influenza‐associated SARI.
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Affiliation(s)
- Rebekah J Stewart
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA.,Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sovann Ly
- Communicable Disease Control Department, Ministry of Health, Phnom Penh, Cambodia
| | - Borann Sar
- Influenza Program, United States Centers for Disease Control and Prevention, Phnom Penh, Cambodia
| | - Vanra Ieng
- Emerging Disease Surveillance and Response, World Health Organization, Phnom Penh, Cambodia
| | - Seng Heng
- Communicable Disease Control Department, Ministry of Health, Phnom Penh, Cambodia
| | - Kheng Sim
- Communicable Disease Control Department, Ministry of Health, Phnom Penh, Cambodia
| | - Chiedza Machingaidze
- Emerging Disease Surveillance and Response, World Health Organization, Phnom Penh, Cambodia
| | - Katherine Roguski
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Erica Dueger
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA.,Emerging Disease Surveillance and Response, World Health Organization Regional Office for the Western Pacific, Manila, Philippines
| | - Ann Moen
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Reiko Tsuyuoka
- Emerging Disease Surveillance and Response, World Health Organization, Phnom Penh, Cambodia
| | - A Danielle Iuliano
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Emergency Department demand associated with seasonal influenza, 2010 through 2014, New South Wales, Australia. Western Pac Surveill Response J 2017; 8:11-20. [PMID: 29051837 PMCID: PMC5635331 DOI: 10.5365/wpsar.2017.8.2.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Introduction Influenza’s impact on health and health care is underestimated by influenza diagnoses recorded in health-care databases. We aimed to estimate total and non-admitted influenza-attributable hospital Emergency Department (ED) demand in New South Wales (NSW), Australia. Methods We used generalized additive time series models to estimate the association between weekly counts of laboratory-confirmed influenza infections and weekly rates of total and non-admitted respiratory, infection, cardiovascular and all-cause ED visits in NSW, Australia for the period 2010 through 2014. Visit categories were based on the coded ED diagnosis or the free-text presenting problem if no diagnosis was recorded. Results The estimated all-age, annual influenza-attributable respiratory, infection, cardiovascular and all-cause visit rates/100 000 population/year were, respectively, 120.6 (99.9% confidence interval [CI] 102.3 to 138.8), 79.7 (99.9% CI: 70.6 to 88.9), 14.0 (99.9% CI: 6.8 to 21.3) and 309.0 (99.9% CI: 208.0 to 410.1). Among respiratory visits, influenza-attributable rates were highest among < 5-year-olds and ≥ 85-year-olds. For infection and all-cause visits, rates were highest among children; cardiovascular rates did not vary significantly by age. Annual rates varied substantially by year and age group, and statistically significant associations were absent in several years or age groups. Of the respiratory visits, 73.4% did not require admission. The non-admitted proportion was higher for the other clinical categories. Around 1 in 100 total visits and more than 1 in 10 respiratory or infection visits were associated with influenza. Discussion Influenza is associated with a substantial and annually varying burden of hospital-attended illness in NSW.
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Allard MA, Baillié G, Castro-Benitez C, Faron M, Blandin F, Cherqui D, Castaing D, Cunha AS, Adam R, Vibert É. Prediction of the Total Liver Weight using anthropological clinical parameters: does complexity result in better accuracy? HPB (Oxford) 2017; 19:338-344. [PMID: 28043763 DOI: 10.1016/j.hpb.2016.11.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 10/07/2016] [Accepted: 11/30/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND The performance of linear models predicting Total Liver Weight (TLW) remains moderate. The use of more complex models such as Artificial Neural Network (ANN) and Generalized Additive Model (GAM) or including the variable "steatosis" may improve TLW prediction. This study aimed to assess the value of ANN and GAM and the influence of steatosis for predicting TLW. METHODS Basic clinical and morphological variables of 1560 cadaveric donors for liver transplantation were randomly split into a training (2/3) and validation set (1/3). Linear models, ANN and GAM were built by using the training cohort and evaluated with the validation cohort. RESULTS The TLW is subject to major variations among donors with similar morphological parameters. The performance of ANN and GAM were moderate and similar to that of linear models (concordance coefficient from 0.36 to 0.44). In 28-30% of cases, TLW cannot be predicted with a margin of error ≤20%. The addition of the variable "steatosis" to each model did not improve their performance. CONCLUSION TLW prediction based on anthropological parameters carry a significant risk of error despite the use of more complex models. Others determinants of TLW need to be identified and imaging-based volumetric measurements should be preferred when feasible.
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Affiliation(s)
- Marc-Antoine Allard
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France; INSERM, Unit UMRS776, Villejuif, F-94800, France.
| | - Gaëlle Baillié
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France
| | - Carlos Castro-Benitez
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France
| | - Matthieu Faron
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France
| | - Frédérique Blandin
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France
| | - Daniel Cherqui
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
| | - Denis Castaing
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
| | - Antonio Sa Cunha
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
| | - René Adam
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France; INSERM, Unit UMRS776, Villejuif, F-94800, France
| | - Éric Vibert
- Centre Hépato-Biliaire, Paul Brousse Hospital, AP-HP, Villejuif, F-94800, France; INSERM, Unit 1193, Villejuif, F-94800, France; University of Paris-Sud, Villejuif, F-94800, France
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