Measuring influencing factors affecting mortality rates during the COVID-19 pandemic

Abstract

Background The COVID-19 pandemic has revealed clear deficiencies in global public health policies and healthcare systems when confronted with the emergence of a novel and deadly infectious disease. Objectives With 4 years elapsed since the onset of the pandemic, ample data now exist to analyse the associations between the implementation of diverse public health policies, sociodemographic factors and COVID-19 mortality rates. Methods This study utilised the dataset compiled by ‘Our World in Data’ spanning the period of the COVID-19 pandemic from 2020 to 2022. Stochastic frontier analysis was employed to assess the influencing factors and their relationship with mortality rates resulting from COVID-19 infections across 156 countries or regions. Results This study yielded several key findings: (1) There remains a 33% margin for improvement in the global mortality rate concerning the COVID-19 pandemic; (2) During the initial stage of the pandemic, when an effective vaccine was not yet available, implementing public health control policies could reduce both the infection and mortality rates; (3) Areas characterised by higher population densities, a greater proportion of individuals aged 65 and over, and elevated prevalence rates of diabetes demonstrated higher mortality rates; and (4) Increasing vaccination coverage emerged as an effective strategy for reducing mortality rates. Conclusions As our understanding of the COVID-19 virus improves, global economies and social interactions have gradually returned to normality. It is anticipated that the findings of this study can serve as a valuable reference in combating potential future pandemics caused by unknown viruses.

Keywords

• covid-19
• infection
• mortality
• inefficiency
• stochastic frontier analysis