SynthesisReviews in medical virology2021
How strong is the evidence that it is possible to get SARS-CoV-2 twice? A systematic review.
Synthesis in Reviews in medical virology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 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
8 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The Protection of Naturally Acquired Antibodies Against Subsequent SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis.Emerging microbes & infections · 2022Pooled it
- The prevalence of adaptive immunity to COVID-19 and reinfection after recovery - a comprehensive systematic review and meta-analysis.Pathogens and global health · 2022Pooled it
- How strong is the evidence that it is possible to get SARS-CoV-2 twice? A systematic review.Reviews in medical virology · 2021Pooled it
- Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.BMC infectious diseases · 2024Article
- Peripartum outcomes and immune responses after SARS-CoV-2 infection in the third trimester of pregnancy.BMC pregnancy and childbirth · 2024Article
- COVID-19: the possibility, ways, mechanisms, and interruptions of mother-to-child transmission.Archives of gynecology and obstetrics · 2023Review
- Confirmed reinfection with SARS-CoV-2 during a pregnancy: A case report.Clinical case reports · 2022Article
- Milder symptoms and shorter course in patients with re-positive COVID-19: A cohort of 180 patients from Northeast China.Frontiers in microbiology · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With a large number of coronavirus disease 2019 (Covid-19) patients being discharged from hospital with negative test results for SARS-CoV-2, it has been reported that several recovered cases tested positive after discharge (re-positive, RP). This finding has raised several important questions for this novel coronavirus and Covid-19 disease. In this review, we have discussed several important questions, including: (1) Can the virus re-infect recovered individuals? (2) What are the possible causes of the re-positive reverse transcriptase-polymerase chain reaction (RT-PCR) test in recovered patients? (3) What are the implications of these re-positive cases concerning the spread of the virus? Understanding how recovery from Covid-19 confers immunity to decrease the risk of re-infection is needed to inform current efforts to safely scale back population-based interventions, such as physical distancing. We have also described what is currently known about the immune response to Covid-19, highlighted key gaps in knowledge, and identified opportunities for future research. Overall, the quality of the evidence is poor and we describe the features that should be described for future cases.
Indexed as
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.