Department of Infectious Disease Epidemiology, Statens Serum Institut, Copenhagen, Denmark.
Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Influenza Other Respir Viruses. 2022 Jul;16(4):707-716. doi: 10.1111/irv.12966. Epub 2022 Feb 23.
Seasonal influenza-associated excess mortality estimates can be timely and provide useful information on the severity of an epidemic. This methodology can be leveraged during an emergency response or pandemic.
For Denmark, Spain, and the United States, we estimated age-stratified excess mortality for (i) all-cause, (ii) respiratory and circulatory, (iii) circulatory, (iv) respiratory, and (v) pneumonia, and influenza causes of death for the 2015/2016 and 2016/2017 influenza seasons. We quantified differences between the countries and seasonal excess mortality estimates and the death categories. We used a time-series linear regression model accounting for time and seasonal trends using mortality data from 2010 through 2017.
The respective periods of weekly excess mortality for all-cause and cause-specific deaths were similar in their chronological patterns. Seasonal all-cause excess mortality rates for the 2015/2016 and 2016/2017 influenza seasons were 4.7 (3.3-6.1) and 14.3 (13.0-15.6) per 100,000 population, for the United States; 20.3 (15.8-25.0) and 24.0 (19.3-28.7) per 100,000 population for Denmark; and 22.9 (18.9-26.9) and 52.9 (49.1-56.8) per 100,000 population for Spain. Seasonal respiratory and circulatory excess mortality estimates were two to three times lower than the all-cause estimates.
We observed fewer influenza-associated deaths when we examined cause-specific death categories compared with all-cause deaths and observed the same trends in peaks in deaths with all death causes. Because all-cause deaths are more available, these models can be used to monitor virus activity in near real time. This approach may contribute to the development of timely mortality monitoring systems during public health emergencies.
季节性流感相关超额死亡率的估计可以及时提供有关疫情严重程度的有用信息。这种方法可以在应急响应或大流行期间利用。
对于丹麦、西班牙和美国,我们针对(i)所有原因、(ii)呼吸和循环系统、(iii)循环系统、(iv)呼吸和(v)肺炎和流感死亡原因,对 2015/2016 和 2016/2017 流感季节进行了年龄分层的超额死亡率估计。我们量化了国家之间的差异以及季节性超额死亡率估计和死亡类别。我们使用时间序列线性回归模型,根据 2010 年至 2017 年的死亡率数据,考虑时间和季节性趋势。
所有原因和特定原因死亡的每周超额死亡人数在时间顺序上的模式相似。2015/2016 和 2016/2017 流感季节的全因季节性超额死亡率在美国分别为每 10 万人 4.7(3.3-6.1)和 14.3(13.0-15.6),在丹麦分别为 20.3(15.8-25.0)和 24.0(19.3-28.7),在西班牙分别为 22.9(18.9-26.9)和 52.9(49.1-56.8)。季节性呼吸和循环系统超额死亡率估计比全因估计低两到三倍。
与全因死亡相比,当我们检查特定原因的死亡类别时,观察到的流感相关死亡人数较少,并且观察到所有死亡原因的死亡高峰趋势相同。由于全因死亡数据更易获取,因此这些模型可用于实时监测病毒活动。这种方法可能有助于在公共卫生紧急情况下开发及时的死亡率监测系统。