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Serfling回归模型在深圳市流感超额死亡估计中的应用
引用本文:黄智峰,刘晓剑,吴永胜,杨连朋,邹宇华,李烨,蔡云鹏.Serfling回归模型在深圳市流感超额死亡估计中的应用[J].中华疾病控制杂志,2017,21(11):1170-1174.
作者姓名:黄智峰  刘晓剑  吴永胜  杨连朋  邹宇华  李烨  蔡云鹏
作者单位:1. 广东药科大学公共卫生学院社会医学教研室, 广东 广州 510310;
基金项目:国家高技术研究发展计划
摘    要:目的 运用Serfling回归模型评估深圳市2013-2015年深圳市因流感引起的死亡负担,为了解深圳市流感的流行程度和制定疫苗接种策略提供参考依据。方法 收集深圳市2013-2015年根本死因为全死因(all-cause,AC)、呼吸和循环系统疾病(respiratory and circulatory disease,R&C)、流感和肺炎(pneumonia and influenza,P&I)三类死亡数据,并划分全年龄组、<65岁组和≥ 65岁组,分别拟合Serfling回归模型,估计深圳市2013-2015年的超额死亡数和超额死亡率。结果 2013-2015年用AC估计的深圳市年平均流感超额死亡数为652.80人,年均超额死亡率为6.11/10万。用R&C估计的深圳市年平均流感超额死亡数为449.78人,年均超额死亡率为4.21/10万。用P&I估计的深圳市年平均流感超额死亡数为44.94人,年均超额死亡率为0.42/10万。结论 Serfling回归模型显示老年人是流感超额死亡发生的高危人群,尤其是已患有呼吸和循环系统疾病的人群。

关 键 词:流行性感冒    流行病学方法    死亡率
收稿时间:2017-03-21

Application of Serfling cyclical regression model in the estimation of influenza-associated excess mortality in Shenzhen
HUANG Zhi-feng,LIU Xiao-jian,WU Yong-sheng,YANG Lian-peng,ZOU Yu-hua,LI Ye,CAI Yunpeng.Application of Serfling cyclical regression model in the estimation of influenza-associated excess mortality in Shenzhen[J].Chinese Journal of Disease Control & Prevention,2017,21(11):1170-1174.
Authors:HUANG Zhi-feng  LIU Xiao-jian  WU Yong-sheng  YANG Lian-peng  ZOU Yu-hua  LI Ye  CAI Yunpeng
Institution:1. Department of Social Medicine, School of Public Health, Guangdong Pharmaceutical University, Guangzhou 510310, China;2. Department of Information, Shenzhen Center for Disease Control and Prevention, Shenzhen 518000, China;3. Injury Prevention Research Center, Shantou University, Shantou 515000, China;4. Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China
Abstract:Objective To estimate the excess mortality caused by influenza in Shenzhen from 2013 to 2015,in order to provide scientific reference for understanding the epidemic characteristics of influenza and formulating the strategy of vaccination.Methods All reported influenza deaths in Shenzhen from 2013 to 2015 were collected and divided into three groups,including all-age,< 65years old and ≥65 years old groups.Based on the data of all cause deaths (AC),respiratory and circulatory deaths (R&C) and pneumonia and influenza deaths (P&I),age-specific Serfling cyclical regression model was established to estimate the influenza-associated excess mortality and death numbers for three groups.Results From 2013 to 2015,the AC-based estimates of the annually averaged excess death and mortality due to influenza were 652.80 and 6.11 per 100 000 person years respectively.The R&C-based estimates excess death and mortality due to influenza were 449.78 and 4.21 per 100 000 person years respectively.The P&I-based estimates excess death and mortality due to influenza were 44.94 and 0.42 per 100 000 person years respectively.Conclusions Serfling cyclical regression model shows that the elderly,especially those already suffer from respiratory and circulatory system diseases are the high-risk groups of excess death due to influenza.
Keywords:Grippe  Epidemiologic methods  Mortality
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