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卫生系统参数对 COVID-19 死亡率的预测因素:跨越 203 个国家的生态研究。

The predictors of COVID-19 mortality among health systems parameters: an ecological study across 203 countries.

机构信息

International Institute of Health Management Research (IIHMR), Plot 3, Sector 18A, Dwarka, New Delhi, 110 075, India.

Department of Biostatistics, All India Institute of Medical Science (A.I.I.M.S), New Delhi, India.

出版信息

Health Res Policy Syst. 2022 Jun 27;20(1):75. doi: 10.1186/s12961-022-00878-3.

Abstract

BACKGROUND

Health systems responsiveness is the key to addressing infectious disease threats such as pandemics. The paper outlines an assessment of health systems resilience by exploring the association of health systems and Global Health Security (GHS) parameters with case load and mortality resulting from COVID-19 across 203 countries using an ecological design.

METHODOLOGY

Correlation analysis was performed to assess the relationship of each of the indicators with COVID 19 cases and deaths per million population. Stepwise multiple regression models were developed to determine the predictors of COVID-19 cumulative cases and deaths per million population separately.

RESULTS

Global health security indicators seemed to have a strong association when analyzed individually but those did not necessarily translate into less burden of cases or deaths in the multivariable analysis. The predictors of cumulative deaths per million population included general government expenditure on health as a proportion of general government expenditure, responsiveness of the system to prevent the emergence and release of pathogens and governance related voice and accountability.

CONCLUSION

To conclude, health financing parameters and preventive activities with regard to emergence of pathogens were better predictors of cumulative COVID-19 cases and deaths per million population compared to other health systems and global health security indicators.

摘要

背景

卫生系统的反应能力是应对传染病威胁(如大流行)的关键。本文通过生态设计,利用各国卫生系统和全球卫生安全(GHS)参数与 203 个国家/地区每百万人的 COVID-19 病例和死亡率之间的关系,评估卫生系统的恢复力。

方法

相关性分析用于评估每个指标与 COVID-19 病例和每百万人死亡数的关系。分别建立逐步多元回归模型,以确定 COVID-19 累计病例和每百万人死亡数的预测因素。

结果

全球卫生安全指标在单独分析时似乎具有很强的关联性,但在多变量分析中,这些指标并不一定转化为病例或死亡负担的减轻。每百万人累计死亡人数的预测因素包括卫生总支出占政府总支出的比例、系统预防病原体出现和释放的反应能力以及与治理有关的发言权和问责制。

结论

总之,与其他卫生系统和全球卫生安全指标相比,卫生筹资参数和病原体出现方面的预防措施是 COVID-19 累计病例和每百万人死亡数的更好预测因素。

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