Delta变异出现期间人口密集发达国家COVID-19病死率的预测因素

G. Benisti, Avi Magid
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摘要

截至2021年9月,新冠肺炎疫情在全球造成2.2819亿确诊病例和470万人死亡。死亡率指标经常用于估计大流行的严重程度。其中包括病死率(CFR)。开发了一些数学模型来估计特定因素对疾病死亡率的影响。这些模型是在接种COVID-19疫苗之前建立的,因此没有考虑疫苗对COVID-19病死率的影响。此外,与COVID-19死亡率相关的其他一些因素,如糖尿病和心血管死亡率,未包括在这些模型中。本研究提供了一个数学模型,其中包含了Delta变异引起的第四波大流行期间COVID-19 CFR的一些潜在预测因子。为了评估这些预测因素,从一个实时可用的网站检索了10个人口稠密的发达国家的人口统计和临床信息。人口统计数据包括人口密度、65岁以上人口比例、人均GDP和吸烟率。临床数据包括糖尿病患病率、心血管死亡率、完全接种人群的百分比和CFR。进行单线性回归来评估每个潜在预测因子与CFR的关联。进行反向多元线性回归,以确定本研究预测CFR的自变量的最简洁组合。本研究建立的模型表明,65岁以上人口的百分比和心血管死亡率对CFR有积极影响,即它们与第四波COVID-19死亡率增加有关。此外,人均GDP对病死率有负面影响,即在第四波COVID-19期间,较高的人均GDP与较低的死亡率相关。此外,单线性回归显示,每个国家充分接种疫苗的人口百分比与CFR之间存在强烈的负相关。该模型揭示了几个潜在的人口统计学和临床因素,这些因素可以预测Delta变异出现期间人口密集的发达国家的CFR。建议按照建议接种疫苗,以降低COVID-19死亡率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictors of COVID-19 Case Fatality Rate in Highly Populated Developed Countries During the Emergence of the Delta Variant
By September 2021 the outbreak of the COVID-19 caused 228.19 million confirmed cases and 4.7 million deaths globally. Mortality measures are frequently used to estimate the severity of a pandemic. Among them is the Case Fatality Rate (CFR). Some mathematical models were developed to estimate the impact of specific factors on the disease’s mortality. These models were developed before the COVID-19 vaccines were administrated, and therefore did not consider the vaccines influence on COVID-19 fatality. Moreover, some other factors associated with COVID-19 mortality such as diabetes and cardiovascular mortality were not included in these models. This study offers a mathematical model with some potential predictors of COVID-19 CFR during the fourth pandemic wave caused by the Delta variant. To evaluate these predictors, demographic and clinical information for 10 highly populated developed countries was retrieved from a real-time available website. Demographic data included population density, percent of population above age 65, GDP per capita, and percent of smoking. Clinical data included diabetes prevalence, cardiovascular death rate, percent of fully vaccinated population, and CFR. Single linear regressions were conducted to assess the association of each potential predictor with CFR. A backward multiple linear regression was conducted to identify the most parsimonious combination of the independent variables of this study predicting CFR. The model developed in this study suggests that percent of population above age 65, and cardiovascular death rate have a positive effect on CFR, i.e., they are associated with increased COVID-19 fatality rate during the fourth wave. In addition, GDP per capita has a negative effect on CFR, i.e. – higher GDP per capita is associated with lower fatality rate during COVID-19 fourth wave. Moreover, single linear regressions show a strong negative association between percent of fully vaccinated people in each country and CFR. This model sheds light on several potential demographic and clinical factors which may predict CFR in highly populated developed countries during the emergence of the Delta variant. Vaccination in accordance with the recommendations is recommended to reduce COVID-19 mortality.
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