入射(几何)
中国
人口学
环境卫生
相对风险
分布滞后
流行病学
地理
可归因风险
中国上海
医学
传输(电信)
置信区间
风险评估
统计
人口
内科学
数学
计算机科学
电气工程
工程类
社会学
区域科学
计算机安全
考古
几何学
作者
Rui Zhang,Zhibin Peng,Yujie Meng,Hejia Song,Songwang Wang,Peng Bi,Dan Li,Xiang Zhao,Xiaoyuan Yao,Yonghong Li
标识
DOI:10.1016/j.envres.2022.114343
摘要
Many studies have explored the epidemiological characteristics of influenza. However, most previous studies were conducted in a specific region without a national picture which is important to develop targeted strategies and measures on influenza control and prevention.To explore the association between ambient temperature and incidence of influenza, to estimate the attributable risk from temperature in 30 Chinese cities with different climatic characteristics for a national picture, and to identify the vulnerable populations for national preventative policy development.Daily meteorological and influenza incidence data from the 30 Chinese cities over the period 2016-19 were collected. We estimated the city-specific association between daily mean temperature and influenza incidence using a distributed lag non-linear model and evaluated the pooled effects using multivariate meta-analysis. The attributable fractions compared with reference temperature were calculated. Stratified analyses were performed by region, sex and age.Overall, an N-shape relationship between temperature and influenza incidence was found in China. The cumulative relative risk of the peak risk temperature (5.1 °C) was 2.13 (95%CI: 1.41, 3.22). And 60% (95%eCI: 54.3%, 64.3%) of influenza incidence was attributed to ambient temperature during the days with sensitive temperatures (1.6°C-14.4 °C). The ranges of sensitive temperatures and the attributable disease burden due to temperatures varied for different populations and regions. The residents in South China and the children aged ≤5 and 6-17 years had higher fractions attributable to sensitive temperatures.Tailored preventions targeting on most vulnerable populations and regions should be developed to reduce influenza burden from sensitive temperatures.
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