Assessing the impact of vaccination in a COVID-19 compartmental model

Esteban, E. P.; Almodovar-Abreu, Lusmeralis

doi:10.1016/j.imu.2021.100795

Cited by 9 publications

(10 citation statements)

References 18 publications

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“…Antonini et al [12] used a mean duration of vaccinal and infection immunity of 240 days to predict short-term outcomes in Italy. For the first wave of COVID-19, Esteban & Almodovar-Abreu [14] used a sevencompartment vaccination model, which assumed no waning of efficacy, to forecast and compare deaths at 180 days into the first wave for assumed unvaccinated and vaccinated populations under an assumed 95% vaccine efficacy. Steyn et al [15] developed a vaccination model for New Zealand, assuming no waning of efficacy, with an assumed basic reproduction number of 6 for the delta variant.…”

Section: Vaccine Models Reviewedmentioning

confidence: 99%

Sensitivity of endemic behaviour of COVID-19 under a multi-dose vaccination regime, to various biological parameters and control variables

Dagpunar

2023

R. Soc. open sci.

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For an infectious disease such as COVID-19, we present a new four-stage vaccination model (unvaccinated, dose 1 + 2, booster, repeated boosters), which examines the impact of vaccination coverage, vaccination rate, generation interval, control reproduction number, vaccine efficacies and rates of waning immunity upon the dynamics of infection. We derive a single equation that allows computation of equilibrium prevalence and incidence of infection, given knowledge about these parameters and variable values. Based upon a 20-compartment model, we develop a numerical simulation of the associated differential equations. The model is not a forecasting or even predictive one, given the uncertainty about several biological parameter values. Rather, it is intended to aid a qualitative understanding of how equilibrium levels of infection may be impacted upon, by the parameters of the system. We examine one-at-a-time sensitivity analysis around a base case scenario. The key finding which should be of interest to policymakers is that while factors such as improved vaccine efficacy, increased vaccination rates, lower waning rates and more stringent non-pharmaceutical interventions might be thought to improve equilibrium levels of infection, this might only be done to good effect if vaccination coverage on a recurrent basis is sufficiently high.

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Section: Vaccine Models Reviewedmentioning

confidence: 99%

Sensitivity of endemic behaviour of COVID-19 under a multi-dose vaccination regime, to various biological parameters and control variables

Dagpunar

2023

R. Soc. open sci.

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“…Antonini, Calandrini, and Bianconi, 2021 use a mean duration of vaccinal and infection immunity of 240 days to predict short-term outcomes in Italy. For the first wave of Covid-19, Esteban and Almodovar-Abreu, 2021 use a 7 compartment vaccination model, which assumes no waning of efficacy, to forecast and compare deaths at 180 days into the first wave for assumed un-vaccinated and vaccinated populations under an assumed 95% vaccine efficacy. Steyn et al, 2022 develop a vaccination model for New Zealand, assuming no waning of efficacy, with an assumed basic reproduction number of 6 for the delta variant.…”

Section: Vaccine Models Reviewedmentioning

confidence: 99%

Sensitivity of endemic behaviour of Covid-19 under a multi-dose vaccination regime, to various biological parameters and control variables

Dagpunar

2022

Preprint

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For an infectious disease such as Covid-19, we present a new four-stage vaccination model (un-vaccinated, dose 1+2, booster, repeated boosters), which examines the impact of vaccination coverage, vaccination rate, generation interval, control reproduction number, vaccine efficacies, and rates of waning immunity, upon the dynamics of infection. We derive a single equation that allows computation of equilibrium prevalence and incidence of infection, given knowledge about these parameter and variable values. Based upon a 20 compartment model, we develop a numerical simulation of the associated differential equations. The model is not a forecasting or even predictive one, given the uncertainty about several biological parameter values. Rather, it is intended to aid qualitative understanding of how equilibrium levels of infection may be impacted upon, by the parameters of the system. We examine one at a time sensitivity analysis around a base case scenario. The key finding which should be of interest to policy makers, is that while factors such as improved vaccine efficacy, increased vaccination rates, lower waning rates, and more stringent non- pharmaceutical interventions might be thought to improve equilibrium levels of infection, this might only be done to good effect, if vaccination coverage on a recurrent basis, is sufficiently high.

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“…Recently, Kanj et al ( 20 ), Hasan and Saeed ( 21 ), and Jeta et al ( 22 ) reviewed nineteen diseases, of which nine employed compartments compartmental (deterministic) models to analyze the transmission dynamics of the Mpox virus in populations comprising both humans and non-humans. These studies explored variations of the classical SIR (Susceptible-Infected-Recovered) vector-borne models ( 23 – 25 ) within the context of human and non-human interaction and utilized them to study Mpox disease transmission. Incorporating vaccination classes ( 26 ) is essential for the disease’s accurate representation of progression and incubation.…”

Section: Introductionmentioning

confidence: 99%

Exploring the dynamics of monkeypox transmission with data-driven methods and a deterministic model

Das

2024

Front. Epidemiol.

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IntroductionMpox (formerly monkeypox) is an infectious disease that spreads mostly through direct contact with infected animals or people's blood, bodily fluids, or cutaneous or mucosal lesions. In light of the global outbreak that occurred in 2022–2023, in this paper, we analyzed global Mpox univariate time series data and provided a comprehensive analysis of disease outbreaks across the world, including the USA with Brazil and three continents: North America, South America, and Europe. The novelty of this study is that it delved into the Mpox time series data by implementing the data-driven methods and a mathematical model concurrently—an aspect not typically addressed in the existing literature. The study is also important because implementing these models concurrently improved our predictions' reliability for infectious diseases.MethodsWe proposed a traditional compartmental model and also implemented deep learning models (1D- convolutional neural network (CNN), long-short term memory (LSTM), bidirectional LSTM (BiLSTM), hybrid CNN-LSTM, and CNN-BiLSTM) as well as statistical time series models: autoregressive integrated moving average (ARIMA) and exponential smoothing on the Mpox data. We also employed the least squares method fitting to estimate the essential epidemiological parameters in the proposed deterministic model.ResultsThe primary finding of the deterministic model is that vaccination rates can flatten the curve of infected dynamics and influence the basic reproduction number. Through the numerical simulations, we determined that increased vaccination among the susceptible human population is crucial to control disease transmission. Moreover, in case of an outbreak, our model showed the potential for epidemic control by adjusting the key epidemiological parameters, namely the baseline contact rate and the proportion of contacts within the human population. Next, we analyzed data-driven models that contribute to a comprehensive understanding of disease dynamics in different locations. Additionally, we trained models to provide short-term (eight-week) predictions across various geographical locations, and all eight models produced reliable results.ConclusionThis study utilized a comprehensive framework to investigate univariate time series data to understand the dynamics of Mpox transmission. The prediction showed that Mpox is in its die-out situation as of July 29, 2023. Moreover, the deterministic model showed the importance of the Mpox vaccination in mitigating the Mpox transmission and highlighted the significance of effectively adjusting key epidemiological parameters during outbreaks, particularly the contact rate in high-risk groups.

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Assessing the impact of vaccination in a COVID-19 compartmental model

Cited by 9 publications

References 18 publications

Sensitivity of endemic behaviour of COVID-19 under a multi-dose vaccination regime, to various biological parameters and control variables

Sensitivity of endemic behaviour of COVID-19 under a multi-dose vaccination regime, to various biological parameters and control variables

Sensitivity of endemic behaviour of Covid-19 under a multi-dose vaccination regime, to various biological parameters and control variables

Exploring the dynamics of monkeypox transmission with data-driven methods and a deterministic model

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