Social Determinants of Health Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Department of Biostatistics and Epidemiology, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
J Prev Med Hyg. 2021 Jul 30;62(2):E261-E269. doi: 10.15167/2421-4248/jpmh2021.62.2.1569. eCollection 2021 Jun.
The COVID-19-related deaths are growing rapidly around the world, especially in Europe and the United States.
In this study we attempt to measure the association of these variables with case fatality rate (CFR) and recovery rate (RR) using up-to-date data from around the world.
Data were collected from eight global databases. According to the raw data of countries, the CFR and RR and their relationship with different predictors was compared for countries with 1,000 or more cases of COVID-19 confirmed cases.
There were no significant correlation between the CFR and number of hospital beds per 1,000 people, proportion of population aged 65 and older ages, and the number of computed tomography per one million inhabitants. Furthermore, based on the continents-based subgroup univariate regression analysis, the population (R = 0.37, P = 0.047), GPD (R = 0.80, P < 0.001), number of ICU Beds per 100,000 people (R = 0.93, P = 0.04), and number of CT per one million inhabitants (R = 0.78, P = 0.04) were significantly correlated with CFR in America. Moreover, the income-based subgroups analysis showed that the gross domestic product (R = 0.30, P = 0.001), number of ICU Beds per 100,000 people (R = 0.23, P = 0.008), and the number of ventilator (R = 0.46, P = 0.01) had significant correlation with CFR in high-income countries.
The level of country's preparedness, testing capacity, and health care system capacities also are among the important predictors of both COVID-19 associated mortality and recovery. Thus, providing up-to-date information on the main predictors of COVID-19 associated mortality and recovery will hopefully improve various countries hospital resource allocation, testing capacities, and level of preparedness.
全球范围内 COVID-19 相关死亡人数迅速增加,尤其是在欧洲和美国。
本研究旨在利用全球最新数据,评估这些变量与病死率(CFR)和康复率(RR)的相关性。
数据来自全球 8 个数据库。根据各国的原始数据,比较了 COVID-19 确诊病例超过 1000 例的国家的 CFR 和 RR 及其与不同预测因素的关系。
在考虑到各国人口数量后,病死率与每千人口的医院床位数量、65 岁及以上人口比例和每百万人 CT 数量之间没有显著相关性。此外,基于大洲的单变量回归分析,人口(R = 0.37,P = 0.047)、人均国内生产总值(R = 0.80,P < 0.001)、每 10 万人口的 ICU 床位数量(R = 0.93,P = 0.04)和每百万人 CT 数量(R = 0.78,P = 0.04)与美国的病死率显著相关。此外,基于收入的亚组分析表明,国内生产总值(R = 0.30,P = 0.001)、每 10 万人口的 ICU 床位数量(R = 0.23,P = 0.008)和呼吸机数量(R = 0.46,P = 0.01)与高收入国家的病死率显著相关。
国家的准备程度、检测能力和医疗保健系统能力也是 COVID-19 相关死亡率和康复率的重要预测因素。因此,提供 COVID-19 相关死亡率和康复率的主要预测因素的最新信息有望改善各国医院资源配置、检测能力和准备水平。