Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
Infection. 2021 Jun;49(3):463-473. doi: 10.1007/s15010-020-01566-6. Epub 2021 Jan 25.
The coronavirus disease 2019 (COVID-19) pandemic has spread to all countries in the world, and different countries have been impacted differently. The study aims to understand what factors contribute to different COVID-19 impacts at the country level.
Multivariate statistical analyses were used to evaluate COVID-19 deaths and cases relative to nine other demographic and socioeconomic factors in all countries and regions of the world using data as of August 1, 2020. The factors analyzed in the study include a country's total COVID-19 deaths and cases per million population, per capita gross domestic product (GDP), population density, virus tests per million population, median age, government response stringency index, hospital beds availability per thousand population, extreme poverty rate, Bacille Calmette-Guérin (BCG) vaccination rate, and diphtheria-tetanus-pertussis (DTP3) immunization rate.
The study reveals that COVID-19 deaths per million population in a country most significantly correlates, inversely, with the country's BCG vaccination rate (r = - 0.50, p = 5.3e-5), and also significantly correlates a country's per capita GDP (r = 0.39, p = 7.4e-3) and median age (r = 0.30, p = 0.042), while COVID-19 cases per million population significantly correlate with per capita GDP and tests per thousand population. To control for possible confounding effects of age, the correlation was assessed in countries propensity score matched for age. The inverse correlation between BCG vaccination rates and COVID-19 case (r = - 0.30, p = 0.02) and death (r = - 0.42, p = 0.0007) remained significant among the top 61 countries with the highest median age.
This study contributes to a growing body of evidence supporting the notion that BCG vaccination may be protective against COVID-19 mortality.
2019 年冠状病毒病(COVID-19)大流行已蔓延至世界所有国家,不同国家受其影响程度不同。本研究旨在了解哪些因素导致国家层面 COVID-19 影响的差异。
使用多变量统计分析方法,评估截至 2020 年 8 月 1 日全球所有国家和地区 COVID-19 死亡人数和病例数与其他 9 个人口统计学和社会经济因素的关系。研究分析的因素包括一个国家每百万人口的 COVID-19 总死亡人数和病例数、人均国内生产总值(GDP)、人口密度、每百万人口的病毒检测数、中位年龄、政府反应严格程度指数、每千人口的医院床位数、赤贫率、卡介苗(BCG)接种率和白喉-破伤风-百日咳(DTP3)免疫接种率。
本研究表明,一个国家 COVID-19 每百万人口的死亡人数与该国的 BCG 接种率呈显著负相关(r=−0.50,p=5.3e-5),与人均 GDP(r=0.39,p=7.4e-3)和中位年龄(r=0.30,p=0.042)呈显著正相关,而 COVID-19 每百万人口的病例数与人均 GDP 和每千人的检测数呈显著正相关。为了控制年龄可能造成的混杂影响,在按年龄进行倾向评分匹配的国家中评估了相关性。在中位年龄最高的前 61 个国家中,BCG 接种率与 COVID-19 病例(r=−0.30,p=0.02)和死亡(r=−0.42,p=0.0007)之间的负相关仍然显著。
本研究为越来越多的证据支持卡介苗接种可能对 COVID-19 死亡率具有保护作用的观点做出了贡献。