Morales Kathleen F, Paget John, Spreeuwenberg Peter
Sage Analytica, Portland, Maine, USA.
Netherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands.
BMC Infect Dis. 2017 Sep 25;17(1):642. doi: 10.1186/s12879-017-2730-0.
A global pandemic mortality study found prominent regional mortality variations in 2009 for Influenza A(H1N1)pdm09. Our study attempts to identify factors that explain why the pandemic mortality burden was high in some countries and low in others.
As a starting point, we identified possible risk factors worth investigating for Influenza A(H1N1)pdm09 mortality through a targeted literature search. We then used a modeling procedure (data simulations and regression models) to identify factors that could explain differences in respiratory mortality due to Influenza A(H1N1)pdm09. We ran sixteen models to produce robust results and draw conclusions. In order to assess the role of each factor in explaining differences in excess pandemic mortality, we calculated the reduction in between country variance, which can be viewed as an effect-size for each factor.
The literature search identified 124 publications and 48 possible risk factors, of which we were able to identify 27 factors with appropriate global datasets. The modelling procedure indicated that age structure (explaining 40% of the mean between country variance), latitude (8%), influenza A and B viruses circulating during the pandemic (3-8%), influenza A and B viruses circulating during the preceding influenza season (2-6%), air pollution (pm10; 4%) and the prevalence of other infections (HIV and TB) (4-6%) were factors that explained differences in mortality around the world. Healthcare expenditure, levels of obesity, the distribution of antivirals, and air travel did not explain global pandemic mortality differences.
Our study found that countries with a large proportion of young persons had higher pandemic mortality rates in 2009. The co-circulation of influenza viruses during the pandemic and the circulation of influenza viruses during the preceding season were also associated with pandemic mortality rates. We found that real time assessments of 2009 pandemic mortality risk factors (e.g. obesity) probably led to a number of false positive findings.
一项全球大流行死亡率研究发现,2009年甲型H1N1流感大流行存在显著的地区死亡率差异。我们的研究旨在确定一些因素,以解释为何在一些国家大流行死亡率负担高,而在另一些国家则低。
首先,我们通过有针对性的文献检索,确定了值得研究的甲型H1N1流感大流行死亡率的可能风险因素。然后,我们使用一种建模程序(数据模拟和回归模型)来确定能够解释甲型H1N1流感大流行导致的呼吸道死亡率差异的因素。我们运行了16个模型以得出可靠结果并得出结论。为了评估每个因素在解释大流行超额死亡率差异中的作用,我们计算了国家间方差的减少量,这可被视为每个因素的效应量。
文献检索确定了124篇出版物和48个可能的风险因素,其中我们能够利用合适的全球数据集确定27个因素。建模程序表明,年龄结构(解释了国家间平均方差的40%)、纬度(8%)、大流行期间甲型和乙型流感病毒的传播(3 - 8%)、前一个流感季节甲型和乙型流感病毒的传播(2 - 6%)、空气污染(PM10;4%)以及其他感染(艾滋病毒和结核病)的流行率(4 - 6%)是解释全球死亡率差异的因素。医疗保健支出、肥胖水平、抗病毒药物的分发以及航空旅行并不能解释全球大流行死亡率的差异。
我们的研究发现,2009年年轻人比例较大的国家大流行死亡率较高。大流行期间流感病毒的共同传播以及前一个季节流感病毒的传播也与大流行死亡率相关。我们发现,对2009年大流行死亡率风险因素(如肥胖)的实时评估可能导致了一些假阳性结果。