Measuring influencing factors affecting mortality rates during the COVID-19 pandemic
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 a...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Global Health Action |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/16549716.2024.2428067 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832096700881174528 |
|---|---|
| author | Jih-Shong Wu Kuo-Kuang Huang |
| author_facet | Jih-Shong Wu Kuo-Kuang Huang |
| author_sort | Jih-Shong Wu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c10cec5cb10346a48eda4bb22d276855 |
| institution | Kabale University |
| issn | 1654-9880 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Global Health Action |
| spelling | doaj-art-c10cec5cb10346a48eda4bb22d2768552025-02-05T12:46:14ZengTaylor & Francis GroupGlobal Health Action1654-98802024-12-0117110.1080/16549716.2024.24280672428067Measuring influencing factors affecting mortality rates during the COVID-19 pandemicJih-Shong Wu0Kuo-Kuang Huang1Chihlee University of TechnologyDepartment of International TradeBackground 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.http://dx.doi.org/10.1080/16549716.2024.2428067covid-19infectionmortalityinefficiencystochastic frontier analysis |
| spellingShingle | Jih-Shong Wu Kuo-Kuang Huang Measuring influencing factors affecting mortality rates during the COVID-19 pandemic Global Health Action covid-19 infection mortality inefficiency stochastic frontier analysis |
| title | Measuring influencing factors affecting mortality rates during the COVID-19 pandemic |
| title_full | Measuring influencing factors affecting mortality rates during the COVID-19 pandemic |
| title_fullStr | Measuring influencing factors affecting mortality rates during the COVID-19 pandemic |
| title_full_unstemmed | Measuring influencing factors affecting mortality rates during the COVID-19 pandemic |
| title_short | Measuring influencing factors affecting mortality rates during the COVID-19 pandemic |
| title_sort | measuring influencing factors affecting mortality rates during the covid 19 pandemic |
| topic | covid-19 infection mortality inefficiency stochastic frontier analysis |
| url | http://dx.doi.org/10.1080/16549716.2024.2428067 |
| work_keys_str_mv | AT jihshongwu measuringinfluencingfactorsaffectingmortalityratesduringthecovid19pandemic AT kuokuanghuang measuringinfluencingfactorsaffectingmortalityratesduringthecovid19pandemic |