Real-world effectiveness of COVID-19 vaccines: a literature review and meta-analysis.

作者
Caifang Zheng,Weihao Shao,Xiaorui Chen,Bowen Zhang,Gaili Wang,Weidong Zhang
出处
期刊:International Journal of Infectious Diseases [Elsevier]
被引量:3
标识
DOI:10.1016/j.ijid.2021.11.009
摘要

Abstract Objectives To estimate the COVID-19 vaccine effectiveness (VE) against concerned outcomes in real-world settings. Methods We included studies reported the COVID-19 VE from August 6, 2020, to October 6, 2021. We estimated the summary VE with 95% confidence intervals (95% CIs) against disease related to COVID-19. The results were presented in forest plots. Predefined subgroup analysis and sensitivity analysis was also performed. Results 51 records were included in this meta-analysis. In the full vaccination, the VE against SARS-CoV-2 infection, COVID-19 related hospitalization, admission to ICU, and death were 89.1% (95% CI, 85.6 to 92.6), 97.2% (95% CI, 96.1 to 98.3), 97.4% (95% CI, 96.0 to 98.8) and 99.0% (95% CI, 98.5 to 99.6), respectively. It showed that the VE against infection for general population aged 16 years or older, the elderly and health care workers (HCWs) were 86.1% (95% CI, 77.8 to 94.4), 83.8% (95% CI, 77.1 to 90.6) and 95.3% (95% CI, 92.0 to 98.6), respectively. For full vaccination against infection, 91.2% effectiveness of the Pfizer-BioNTech vaccine and the 98.1% effectiveness of Moderna vaccine were observed, while 65.7% effectiveness of the CoronaVac were reported. Conclusions The COVID-19 vaccines are highly protective against SARS-CoV-2 related diseases in the real-world settings.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
是事可可完成签到,获得积分10
3秒前
东方樱发布了新的文献求助10
3秒前
慕青应助FANYAO采纳,获得10
4秒前
典雅雨寒完成签到,获得积分10
4秒前
zw发布了新的文献求助10
6秒前
小Q啊啾发布了新的文献求助10
6秒前
111完成签到,获得积分10
6秒前
6秒前
8秒前
9秒前
Yunus发布了新的文献求助20
9秒前
9秒前
10秒前
Purlunatic完成签到,获得积分10
11秒前
su关闭了su文献求助
11秒前
Lllllllll发布了新的文献求助10
12秒前
lzl完成签到,获得积分10
13秒前
13秒前
在水一方应助cy采纳,获得10
14秒前
彭于彦祖应助kingwhitewing采纳,获得50
15秒前
15秒前
Yangzx完成签到,获得积分10
16秒前
16秒前
17秒前
温朋涛完成签到 ,获得积分10
17秒前
丘比特应助Dr.Sun采纳,获得10
18秒前
JMao发布了新的文献求助20
18秒前
18秒前
绪方发布了新的文献求助10
18秒前
SciGPT应助西江月大团子采纳,获得10
18秒前
ziytang完成签到,获得积分10
19秒前
19秒前
精明匪完成签到 ,获得积分20
19秒前
20秒前
oywc应助狂野书易采纳,获得10
20秒前
简单大叔发布了新的文献求助10
21秒前
21秒前
熊xiong发布了新的文献求助10
21秒前
21秒前
高分求助中
Evolution 10000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 600
Distribution Dependent Stochastic Differential Equations 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3157139
求助须知:如何正确求助?哪些是违规求助? 2808445
关于积分的说明 7877659
捐赠科研通 2466978
什么是DOI,文献DOI怎么找? 1313089
科研通“疑难数据库(出版商)”最低求助积分说明 630364
版权声明 601919