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A longitudinal mixed effects model for assessing mortality trends during vaccine rollout

Authors :
Shao, Qin
Polavarapu, Mounika
Small, Lafleur
Singh, Shipra
Nguyen, Quoc
Shao, Kevin
Source :
Healthcare Analytics; December 2024, Vol. 6 Issue: 1
Publication Year :
2024

Abstract

The rapid spread of coronavirus disease 2019 (COVID-19) initially presented unprecedented challenges for clinicians, policymakers, and healthcare systems, as there was limited evidence on the efficacy of various control measures. This study endeavors to provide a detailed and comprehensive overview of the global progression of the COVID-19 mortality in the context of vaccine rollout, utilizing public surveillance data from 145 countries sourced from the World Health Organization and the World Bank. The primary focus is to analyze shifts in the trend of new COVID-19 mortality worldwide before and after the introduction of COVID-19 vaccines. To achieve this, we propose a longitudinal mixed effects model aimed at elucidating the relationship between mortality trend and vaccination rollout, alongside other pertinent covariates. Our modeling approach seeks to accommodate variations in the timing of COVID-19 vaccine rollout among countries, as well as the correlation of observations from within the same country. Our findings highlight the significant impact of new cases, cardiovascular death rate, senior population, stringency index, and reproduction rate on mortality. However, we find that the impact of vaccination is not statistically significant, as evidenced by a relatively large p-value. Furthermore, the study reveals substantial disparities in mortality rates among countries across four income groups.

Details

Language :
English
ISSN :
27724425
Volume :
6
Issue :
1
Database :
Supplemental Index
Journal :
Healthcare Analytics
Publication Type :
Periodical
Accession number :
ejs66631404
Full Text :
https://doi.org/10.1016/j.health.2024.100347