Xu-Xiang Liu1, Guoyou Qin2, Xiaoru Li1, Junqing Zhang1, Kefu Zhao1, Mingxia Hu1, Xi-Ling Wang3. 1. Hefei Center for Disease Control and Prevention, Anhui, China. 2. Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China. 3. 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. Electronic address: erinwang@fudan.edu.cn.
Abstract
OBJECTIVES: The aim of this study was to use a quasi-Poisson regression model to estimate the mortality burden associated with influenza type/subtypes in a subtropical city in China, for the years 2010-2015. METHODS: Quasi-Poisson models were fitted separately to weekly numbers of deaths from various causes. The exploratory variables were products of weekly proportions of specimens positive for influenza type/subtypes and weekly influenza-like illness consultation rates to represent influenza activity. Adjustments were made for long-term and seasonal trends, absolute humidity, and population size as confounding factors in the models. Excess deaths associated with influenza were regarded as the measurement for disease burden of influenza. RESULTS: The excess mortality for all-cause death associated with influenza was 9.9 per 100000 population in Hefei, with influenza A(H3N2) virus having the highest excess mortality rate, followed by influenza A(H1N1) virus and influenza B virus. Following the 2009 H1N1 pandemic, the highest excess mortality rate associated with influenza for different causes was consistently found in the year 2014, with the excess mortality rate for all-cause death reaching 17.47 per 100000 population. The sex differences in influenza-associated mortality were not statistically significant (p>0.05). CONCLUSIONS: The mortality burden of influenza has been substantial in Hefei since the 2009 influenza pandemic, while the evidence on sex differences in mortality burden is limited. The severity profile of influenza type/subtypes in China needs to be assessed and confirmed in more cities in future studies.
OBJECTIVES: The aim of this study was to use a quasi-Poisson regression model to estimate the mortality burden associated with influenza type/subtypes in a subtropical city in China, for the years 2010-2015. METHODS: Quasi-Poisson models were fitted separately to weekly numbers of deaths from various causes. The exploratory variables were products of weekly proportions of specimens positive for influenza type/subtypes and weekly influenza-like illness consultation rates to represent influenza activity. Adjustments were made for long-term and seasonal trends, absolute humidity, and population size as confounding factors in the models. Excess deaths associated with influenza were regarded as the measurement for disease burden of influenza. RESULTS: The excess mortality for all-cause death associated with influenza was 9.9 per 100000 population in Hefei, with influenza A(H3N2) virus having the highest excess mortality rate, followed by influenza A(H1N1) virus and influenza B virus. Following the 2009 H1N1 pandemic, the highest excess mortality rate associated with influenza for different causes was consistently found in the year 2014, with the excess mortality rate for all-cause death reaching 17.47 per 100000 population. The sex differences in influenza-associated mortality were not statistically significant (p>0.05). CONCLUSIONS: The mortality burden of influenza has been substantial in Hefei since the 2009 influenza pandemic, while the evidence on sex differences in mortality burden is limited. The severity profile of influenza type/subtypes in China needs to be assessed and confirmed in more cities in future studies.
Authors: Jack N Salto-Quintana; Gerardo Rivera-Alfaro; Evelyn L Sánchez-Ramos; Alejandro Gómez-Gómez; Daniel E Noyola Journal: Pathog Glob Health Date: 2019-03-21 Impact factor: 2.894
Authors: Wei-Cheng Hong; Shu-Fen Sun; Chien-Wei Hsu; David-Lin Lee; Chao-Hsien Lee Journal: Int J Environ Res Public Health Date: 2021-04-01 Impact factor: 3.390