ArticleChaos, solitons, and fractals2021
Uncertainty quantification of a mathematical model of COVID-19 transmission dynamics with mass vaccination strategy.
Article in Chaos, solitons, and fractals, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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
19 citing papers in PubMed.
- Bayesian uncertainty quantification to identify population level vaccine hesitancy behaviours.PloS one · 2026Article
- Decoding uncertainty for clinical decision-making.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions.Frontiers in immunology · 2025Review
- Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models.Infectious Disease Modelling · 2024Review
- Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models.medRxiv : the preprint server for health sciences · 2024Article
- An Epidemic Model with Infection Age and Vaccination Age Structure.Infectious disease reports · 2024Article
- Estimation and sensitivity analysis of a COVID-19 model considering the use of face mask and vaccination.Scientific reports · 2023Article
- Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa.PloS one · 2023Article
- The numerical solution of a mathematical model of the Covid-19 pandemic utilizing a meshless local discrete Galerkin method.Engineering with computers · 2022Article
- Dynamic of a two-strain COVID-19 model with vaccination.Results in physics · 2022Article
- Robust optimal control of compartmental models in epidemiology: Application to the COVID-19 pandemic.Communications in nonlinear science & numerical simulation · 2022Article
- Modeling of COVID-19 spread with self-isolation at home and hospitalized classes.Results in physics · 2022Article
- Projecting the Pandemic Trajectory through Modeling the Transmission Dynamics of COVID-19.International journal of environmental research and public health · 2022Article
- Optimizing COVID-19 vaccination programs during vaccine shortages.Infectious Disease Modelling · 2022Article
- Optimal control-based vaccination and testing strategies for COVID-19.Computer methods and programs in biomedicine · 2021Article
- Mathematical modeling of COVID-19 transmission dynamics between healthcare workers and community.Results in physics · 2021Article
- A COVID-19 Epidemic Model Predicting the Effectiveness of Vaccination in the US.Infectious disease reports · 2021Article
- Article
- A Mathematical Model of COVID-19 with Vaccination and Treatment.Computational and mathematical methods in medicine · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, the uncertainty quantification and sensitivity analysis of a mathematical model of the SARS-CoV-2 virus transmission dynamics with mass vaccination strategy has been carried out. More specifically, a compartmental epidemic model has been considered, in which vaccination, social distance measures, and testing of susceptible individuals have been included. Since the application of these mitigation measures entails a degree of uncertainty, the effects of the uncertainty about the application of social distance actions and testing of susceptible individuals on the disease transmission have been quantified, under the assumption of a mass vaccination program deployment. A spectral approach has been employed, which allows the uncertainty propagation through the epidemic model to be represented by means of the polynomial chaos expansion of the output random variables. In particular, a statistical moment-based polynomial chaos expansion has been implemented, which provides a surrogate model for the compartments of the epidemic model, and allows the statistics, the probability distributions of the interesting output variables of the model at a given time instant to be estimated and the sensitivity analysis to be conducted. The purpose of the sensitivity analysis is to understand which uncertain parameters have most influence on a given output random variable of the model at a given time instant. Several numerical experiments have been conducted whose results show that the proposed spectral approach to uncertainty quantification and sensitivity analysis of epidemic models provides a useful tool to control and mitigate the effects of the COVID-19 pandemic, when it comes to healthcare resource planning.
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.