ArticleHuman vaccines & immunotherapeutics2022
Effectiveness of CoronaVac in preventing COVID-19 in healthcare workers.
Article in Human vaccines & immunotherapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Real-world effectiveness and factors associated with effectiveness of inactivated SARS-CoV-2 vaccines: a systematic review and meta-regression analysis.BMC medicine · 2023Pooled it
- Epidemiological and clinical characteristics of vaccinated COVID-19 patients: A meta-analysis and systematic review.International journal of immunopathology and pharmacologyPooled it
- Article
- COVID-19 inactivated and non-replicating viral vector vaccines induce regulatory training phenotype in human monocytes under epigenetic control.Frontiers in cellular and infection microbiology · 2023Article
- Fear of COVID-19 Impact on Professional Quality of Life among Mental Health Workers.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The CoronaVac vaccine was found to be effective against symptomatic COVID-19 and protective against severe disease in phase 3 studies. However, there are little data about its effectiveness in real-world conditions. The aim of the current study was to investigate the protective effect of the CoronaVac vaccine in health-care workers (HCWs) in Turkey, a country where CoronaVac is widely used. The questionnaire was sent to all employees in the form of a survey link by using a telephone application. In the survey, HCWs were asked about demographic characteristics; CoronaVac vaccination status, history of a COVID-19 infection, whether COVID-19 infection was before or after the CoronaVac vaccination; the time between being vaccinated and the COVID-19 infection; the clinical pictures of COVID-19 infection. Those who experienced COVID-19 before vaccination were compared with the breakthrough cases in terms of demographic and clinical features. A total of 628 HCW agreed to participate in the study. A total of 536 (85.3%) volunteers had been vaccinated and 92 (14.6%) had not been vaccinated against COVID-19 with CoronaVac. There was a history of COVID-19 infection in 234 (37.2%) subjects and 188 (35%) had been vaccinated and 46 (50%) not vaccinated. The rate experiencing COVID-19 disease was significantly lower in the vaccinated than the unvaccinated volunteers. The rate of breakthrough cases after CoronaVac was found to be 7%. The hospitalization rate was similar in the breakthrough cases and those who had COVID-19 before CoronaVac vaccination. The results of our study indicate that CoronaVac provides protection against COVID-19.
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Identifiers
What OpenQuestion holds
Registered trials
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.