ArticleChaos, solitons, and fractals2022
Modeling the effect of the vaccination campaign on the COVID-19 pandemic.
Article in Chaos, solitons, and fractals, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- Optimal strategies for fair vaccine allocation: integrating non-pharmaceutical interventions, regional quarantine, and social challenges in epidemic control.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- A Scoping Review of Machine Learning Applications Across Epidemiological Stages of Zoonotic Disease.Transboundary and emerging diseases · 2026Article
- Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.Nature communications · 2025Article
- Design, Synthesis and Biological Exploration of NovelInternational journal of molecular sciences · 2024Article
- Reconstruction of incidence reporting rate for SARS-CoV-2 Delta variant of COVID-19 pandemic in the US.Infectious Disease Modelling · 2024Article
- Bayesian modeling of dynamic behavioral change during an epidemic.Infectious Disease Modelling · 2023Article
- Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19.European journal of operational research · 2023Article
- The language of vaccination campaigns during COVID-19.Medical humanities · 2023Article
- Optimal vaccination in a SIRS epidemic model.Economic theory · 2022Article
- Attention based parameter estimation and states forecasting of COVID-19 pandemic using modified SIQRD Model.Chaos, solitons, and fractals · 2022Article
- How many asymptomatic cases were unconfirmed in the US COVID-19 pandemic? The evidence from a serological survey.Chaos, solitons, and fractals · 2022Article
- Susceptibility to Resurgent COVID-19 Outbreaks Following Vaccine Rollouts: A Modeling Study.Viruses · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Population-wide vaccination is critical for containing the SARS-CoV-2 (COVID-19) pandemic when combined with restrictive and prevention measures. In this study we introduce SAIVR, a mathematical model able to forecast the COVID-19 epidemic evolution during the vaccination campaign. SAIVR extends the widely used Susceptible-Infectious-Removed (SIR) model by considering the Asymptomatic (A) and Vaccinated (V) compartments. The model contains several parameters and initial conditions that are estimated by employing a semi-supervised machine learning procedure. After training an unsupervised neural network to solve the SAIVR differential equations, a supervised framework then estimates the optimal conditions and parameters that best fit recent infectious curves of 27 countries. Instructed by these results, we performed an extensive study on the temporal evolution of the pandemic under varying values of roll-out daily rates, vaccine efficacy, and a broad range of societal vaccine hesitancy/denial levels. The concept of herd immunity is questioned by studying future scenarios which involve different vaccination efforts and more infectious COVID-19 variants.
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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.