ArticlemBio2022
Great Expectations of COVID-19 Herd Immunity.
Article in mBio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Autopsy findings in cases of fatal COVID-19 vaccine-induced myocarditis.ESC heart failure · 2025Pooled it
- COVID-19 vaccination intention among nursing, medical, and dental students: A systematic review and meta-regression analysis.Human vaccines & immunotherapeutics · 2023Pooled it
- COVID-19 vaccine uptake at six months post vaccine availability in Central Texas: an observational study disentangling the moveable middle.Frontiers in health services · 2025Article
- Knowledge and training of Italian students in Healthcare Settings on COVID-19 vaccines and vaccination strategies, one year after the immunization campaign.Journal of preventive medicine and hygiene · 2023Article
- Understanding the challenges to COVID-19 vaccines and treatment options, herd immunity and probability of reinfection.Journal of Taibah University Medical Sciences · 2023Review
- Review
- Inframarginal externalities: COVID-19, vaccines, and universal mandates.Public choice · 2023Article
- Anaphylaxis and allergic reactions to COVID-19 vaccines: A narrative review of characteristics and potential obstacles on achieving herd immunity.Health science reports · 2022Article
- Recapping the Features of SARS-CoV-2 and Its Main Variants: Status and Future Paths.Journal of personalized medicine · 2022Review
- From Pandemicity to Endemicity: The Journey of SARS-CoV-2.Journal of epidemiology and global 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
There is a common preconception that reaching an estimated herd immunity threshold through vaccination will end the COVID-19 pandemic. However, the mathematical models underpinning this estimate make numerous assumptions that may not be met in the real world. The protection afforded by vaccines is imperfect, particularly against asymptomatic infection, which can still result in transmission and propagate pandemic viral spread. Immune responses wane and SARS-COV-2 has the capacity to mutate over time to become more infectious and resistant to vaccine elicited immunity. Human behavior and public health restrictions also vary over time and among different populations, impacting the transmissibility of infection. These ever-changing factors modify the number of secondary cases produced by an infected individual, thereby necessitating constant revision of the herd immunity threshold. Even so, vaccination remains a powerful strategy to slow down the pandemic, save lives, and alleviate the burden on limited health care resources.
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.