ArticleInfectious disease reports2021
A COVID-19 Epidemic Model Predicting the Effectiveness of Vaccination in the US.
Article in Infectious disease reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.Systematic reviews · 2024Pooled it
- Influence of waning immunity on vaccination decision-making: A multi-strain epidemic model with an evolutionary approach analyzing cost and efficacy.Infectious Disease Modelling · 2024Article
- Assessing the dynamics and impact of COVID-19 vaccination on disease spread: A data-driven approach.Infectious Disease Modelling · 2024Article
- An Epidemic Model with Infection Age and Vaccination Age Structure.Infectious disease reports · 2024Article
- Spatio-Temporal Patterns of the SARS-CoV-2 Epidemic in Germany.Entropy (Basel, Switzerland) · 2023Article
- Article
- Effectiveness of COVID-19 vaccines and their challenges (Review).Experimental and therapeutic medicine · 2021Review
- Deep-Data-Driven Neural Networks for COVID-19 Vaccine Efficacy.Epidemiologia (Basel, Switzerland) · 2021Article
- A COVID-19 Epidemic Model Predicting the Effectiveness of Vaccination in the US.Infectious disease reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A model of a COVID-19 epidemic is used to predict the effectiveness of vaccination in the US. The model incorporates key features of COVID-19 epidemics: asymptomatic and symptomatic infectiousness, reported and unreported cases data, and social measures implemented to decrease infection transmission. The model analyzes the effectiveness of vaccination in terms of vaccination efficiency, vaccination scheduling, and relaxation of social measures that decrease disease transmission. The model demonstrates that the subsiding of the epidemic as vaccination is implemented depends critically on the scale of relaxation of social measures that reduce disease transmission.
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.