Your browser doesn't support javascript.
loading
Multilayer factors associated with excess all-cause mortality during the omicron and non-omicron waves of the COVID-19 pandemic: time series analysis in 29 countries.
Zou, Fengjuan; Xiao, Jianpeng; Jin, Yingying; Jian, Ronghua; Hu, Yijun; Liang, Xiaofeng; Ma, Wenjun; Zhu, Sui.
Afiliación
  • Zou F; Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
  • Xiao J; Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, 511430, China.
  • Jin Y; Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
  • Jian R; Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
  • Hu Y; Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
  • Liang X; Disease Control and Prevention Institute, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China.
  • Ma W; Chinese Preventive Medicine Association, Beijing, 100062, China.
  • Zhu S; Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, Guangdong, 510632, China. mawj@gdiph.org.cn.
BMC Public Health ; 24(1): 350, 2024 02 02.
Article en En | MEDLINE | ID: mdl-38308279
ABSTRACT

BACKGROUND:

The COVID-19 pandemic has resulted in significant excess mortality globally. However, the differences in excess mortality between the Omicron and non-Omicron waves, as well as the contribution of local epidemiological characteristics, population immunity, and social factors to excess mortality, remain poorly understood. This study aims to solve the above problems.

METHODS:

Weekly all-cause death data and covariates from 29 countries for the period 2015-2022 were collected and used. The Bayesian Structured Time Series Model predicted expected weekly deaths, stratified by gender and age groups for the period 2020-2022. The quantile-based g-computation approach accounted for the effects of factors on the excess all-cause mortality rate. Sensitivity analyses were conducted using alternative Omicron proportion thresholds.

RESULTS:

From the first week of 2021 to the 30th week of 2022, the estimated cumulative number of excess deaths due to COVID-19 globally was nearly 1.39 million. The estimated weekly excess all-cause mortality rate in the 29 countries was approximately 2.17 per 100,000 (95% CI 1.47 to 2.86). Weekly all-cause excess mortality rates were significantly higher in both male and female groups and all age groups during the non-Omicron wave, except for those younger than 15 years (P < 0.001). Sensitivity analysis confirmed the stability of the results. Positive associations with all-cause excess mortality were found for the constituent ratio of non-Omicron in all variants, new cases per million, positive rate, cardiovascular death rate, people fully vaccinated per hundred, extreme poverty, hospital patients per million humans, people vaccinated per hundred, and stringency index. Conversely, other factors demonstrated negative associations with all-cause excess mortality from the first week of 2021 to the 30th week of 2022.

CONCLUSION:

Our findings indicate that the COVID-19 Omicron wave was associated with lower excess mortality compared to the non-Omicron wave. This study's analysis of the factors influencing excess deaths suggests that effective strategies to mitigate all-cause mortality include improving economic conditions, promoting widespread vaccination, and enhancing overall population health. Implementing these measures could significantly reduce the burden of COVID-19, facilitate coexistence with the virus, and potentially contribute to its elimination.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adolescent / Female / Humans / Male Idioma: En Revista: BMC Public Health Asunto de la revista: SAUDE PUBLICA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adolescent / Female / Humans / Male Idioma: En Revista: BMC Public Health Asunto de la revista: SAUDE PUBLICA Año: 2024 Tipo del documento: Article País de afiliación: China