Department of Radiation Oncology, Leopoldina Hospital, Schweinfurt, Germany.
Next Society Institute, Kazimieras Simonavicius University, Vilnius, Lithuania.
Front Public Health. 2022 Jul 28;10:922230. doi: 10.3389/fpubh.2022.922230. eCollection 2022.
To clarify the high variability in COVID-19-related deaths during the first wave of the pandemic, we conducted a modeling study using publicly available data.
We used 13 population- and country-specific variables to predict the number of population-standardized COVID-19-related deaths in 43 European countries using generalized linear models: the test-standardized number of SARS-CoV-2-cases, population density, life expectancy, severity of governmental responses, influenza-vaccination coverage in the elderly, vitamin D status, smoking and diabetes prevalence, cardiovascular disease death rate, number of hospital beds, gross domestic product, human development index and percentage of people older than 65 years.
We found that test-standardized number of SARS-CoV-2-cases and flu vaccination coverage in the elderly were the most important predictors, together with vitamin D status, gross domestic product, population density and government response severity explaining roughly two-thirds of the variation in COVID-19 related deaths. The latter variable was positively, but only weakly associated with the outcome, i.e., deaths were higher in countries with more severe government response. Higher flu vaccination coverage and low vitamin D status were associated with more COVID-19 related deaths. Most other predictors appeared to be negligible.
Adequate vitamin D levels are important, while flu-vaccination in the elderly and stronger government response were putative aggravating factors of COVID-19 related deaths. These results may inform protection strategies against future infectious disease outbreaks.
为了阐明大流行第一波期间与 COVID-19 相关的死亡人数的高度变异性,我们使用公开可用的数据进行了建模研究。
我们使用了 13 个人口和国家特定的变量,使用广义线性模型预测 43 个欧洲国家的人口标准化 COVID-19 相关死亡人数:SARS-CoV-2 病例的检测标准化数量、人口密度、预期寿命、政府反应的严重程度、老年人流感疫苗接种覆盖率、维生素 D 状况、吸烟和糖尿病患病率、心血管疾病死亡率、医院床位数量、国内生产总值、人类发展指数以及 65 岁以上人口的百分比。
我们发现,检测标准化的 SARS-CoV-2 病例数量和老年人流感疫苗接种覆盖率是最重要的预测因素,其次是维生素 D 状况、国内生产总值、人口密度和政府反应严重程度,这些因素共同解释了 COVID-19 相关死亡人数变化的大约三分之二。后一个变量与结果呈正相关,但相关性较弱,即政府反应越严厉的国家死亡人数越高。较高的流感疫苗接种覆盖率和较低的维生素 D 水平与更多的 COVID-19 相关死亡有关。其他大多数预测因素似乎可以忽略不计。
适当的维生素 D 水平很重要,而老年人的流感疫苗接种和更强有力的政府反应可能是 COVID-19 相关死亡的加重因素。这些结果可能为未来传染病爆发的保护策略提供信息。