Evidence map›Paper›PMID 37368748›Full record

ArticleTropical medicine and infectious disease2023

Analysis of Factors Influencing the Clinical Severity of Omicron and Delta Variants.

Shanlu Zhao, Kaiwei Luo, Yichao Guo, Mingli Fang, Qianlai Sun, Zhihui Dai, Hao Yang, Zhifei Zhan, Shixiong Hu, Tianmu Chen and 1 more

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Shanlu ZhaoHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Kaiwei LuoHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Yichao GuoSchool of Public Health, Xiamen University, Xiamen 361102, China.
Mingli FangHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Qianlai SunHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Zhihui DaiHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Hao YangHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Zhifei ZhanHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Shixiong HuHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.
Tianmu ChenSchool of Public Health, Xiamen University, Xiamen 361102, China.ORCID 0000-0003-0710-5086
Xiaojun LiHunan Provincial Center for Disease Control and Prevention (Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences), Changsha 410005, China.

Funding

Chinese Academy of Medical Sciences Coronavirus Disease 2019 Science and Technology Research Project in 2020 2020HY320003Hunan Provincial Innovative Construction Special Fund 2022SK2121Hunan Provincial Innovative Construction Special Fund: Emergency response to the COVID-19 outbreak 2020SK3012Scientific Research Project of Hunan Provincial Health Committee A202312066016Scientific Research Project of Hunan Provincial Health Committee D202312058730
6 · The paper itself

Abstract

The Omicron variant is the dominant strain circulating globally, and studies have shown that Omicron cases have milder symptoms than Delta cases. This study aimed to analyze the factors that affect the clinical severity of Omicron and Delta variants, evaluate and compare the effectiveness of COVID-19 vaccines with different technological platforms, and assess the vaccine effectiveness against different variants. We retrospectively collected the basic information of all local COVID-19 cases reported by Hunan Province to the National Notifiable Infectious Disease Reporting System from January 2021 to February 2023, including gender, age, clinical severity, and COVID-19 vaccination history. From 1 January 2021 to 28 February 2023, Hunan Province reported a total of 60,668 local COVID-19 cases, of which, 134 were infected with the Delta variant and 60,534 were infected with the Omicron variant. The results showed that infection with the Omicron variant (adjusted OR (aOR): 0.21, 95% CI: 0.14-0.31), getting vaccinated (booster immunization vs. unvaccinated aOR: 0.30, 95% CI: 0.23-0.39) and being female (aOR: 0.82, 95% CI: 0.79-0.85) were protective factors for pneumonia, while old age (≥60 years vs. <3 years aOR: 4.58, 95% CI: 3.36-6.22) was a risk factor for pneumonia. Being vaccinated (booster immunization vs. unvaccinated aOR: 0.11, 95% CI: 0.09-0.15) and female (aOR: 0.54, 95% CI: 0.50-0.59) were protective factors for severe cases, while older age (≥60 years vs. < 3 years aOR: 4.95, 95% CI: 1.83-13.39) was a risk factor for severe cases. The three types of vaccines had protective effects on both pneumonia and severe cases, and the protective effect on severe cases was better than that on pneumonia. The recombinant subunit vaccine booster immunization had the best protective effect on pneumonia and severe cases, with ORs of 0.29 (95% CI: 0.2-0.44) and 0.06 (95% CI: 0.02-0.17), respectively. The risk of pneumonia from Omicron variant infection was lower than that from Delta. Chinese-produced vaccines had protective effects on both pneumonia and severe cases, with recombinant subunit vaccines having the best protective effect on pneumonia and severe pneumonia cases. Booster immunization should be advocated in COVID-19 pandemic-related control and prevention policies, especially for the elderly, and booster immunization should be accelerated.

Indexed as

clinical severityCOVID-19SARS-Cov-2vaccination

Identifiers

PMID37368748
PMCPMC10301725

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.