Modeling the emergence of vaccine-resistant variants with Gaussian convolution. COVID-19: Could the wrong strategy ruin vaccine efficiency?

Mapping Intimacies ◽

10.1101/2021.07.07.21259916 ◽

2021 ◽

Author(s):

Christian Bongiorno ◽

John Cagnol

Keyword(s):

Natural Selection ◽

Compartmental Model ◽

Substantial Portion ◽

Vaccination Strategies ◽

Gaussian Convolution

The SARS-CoV-2 virus, which is responsible for the COVID-19 pandemic, has been shown to mutate. In the absence of a vaccine, natural selection will favor variants with higher transmissibility rates. However, when a substantial portion of the population is vaccinated, natural selection will shift towards favoring variants that can resist the vaccine. These variants can therefore become dominant and even cancel out the benefit of the vaccine. This paper develops a compartmental model which simulates this phenomenon and shows how various vaccination strategies can lead to the emergence of vaccine-resistant variants.

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Modeling Chickenpox Dynamics with a Discrete Time Bayesian Stochastic Compartmental Model

Complexity ◽

10.1155/2018/3060368 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

A. Corberán-Vallet ◽

F. J. Santonja ◽

M. Jornet-Sanz ◽

R.-J. Villanueva

Keyword(s):

Discrete Time ◽

Compartmental Model ◽

Predictive Distribution ◽

Model Parameters ◽

Immunization Program ◽

Posterior Predictive Distribution ◽

Vaccination Strategies ◽

Proposed Model ◽

Routine Immunization Program ◽

The Impact

We present a Bayesian stochastic susceptible-exposed-infectious-recovered model in discrete time to understand chickenpox transmission in the Valencian Community, Spain. During the last decades, different strategies have been introduced in the routine immunization program in order to reduce the impact of this disease, which remains a public health’s great concern. Under this scenario, a model capable of explaining closely the dynamics of chickenpox under the different vaccination strategies is of utter importance to assess their effectiveness. The proposed model takes into account both heterogeneous mixing of individuals in the population and the inherent stochasticity in the transmission of the disease. As shown in a comparative study, these assumptions are fundamental to describe properly the evolution of the disease. The Bayesian analysis of the model allows us to calculate the posterior distribution of the model parameters and the posterior predictive distribution of chickenpox incidence, which facilitates the computation of point forecasts and prediction intervals.

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Evaluating COVID-19 booster vaccination strategies in a partially vaccinated population: a modeling study.

10.21203/rs.3.rs-1143391/v1 ◽

2021 ◽

Author(s):

Clément Massonnaud ◽

Jonathan Roux ◽

Vittoria Colizza ◽

Pascal Crépey

Keyword(s):

Compartmental Model ◽

Age Groups ◽

Booster Vaccination ◽

Primary Vaccination ◽

Effective Strategy ◽

Younger Adults ◽

Vaccination Strategies ◽

Admission Data ◽

Vaccination Campaigns ◽

The Impact

Abstract Background. Several countries are implementing COVID-19 booster vaccination campaigns. The objective of this study was to model the impact of different primary and booster vaccination strategies. Methods. We used a compartmental model fitted to hospital admission data in France to analyze the impact of primary and booster vaccination strategies on morbidity and mortality, assuming waning of immunity and various levels of virus transmissibility during winter. Results. Strategies prioritizing primary vaccinations were systematically more effective than strategies prioritizing boosters. Regarding booster strategies targeting different age groups, their effectiveness varied with immunity and virus transmissibility levels. If waining of immunity affects all adults, people aged 30 to 49 years should be boosted in priority, even for low transmissibility levels. Discussion. Increasing the primary vaccination coverage should remain a priority. If a plateau has been reached, boosting immunity of younger adults could be the most effective strategy, especially if SARS-CoV-2 transmissibility is high.

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Vaccination strategies in structured populations under partial immunity and reinfection

10.1101/2021.11.23.21266766 ◽

2021 ◽

Author(s):

Gabriel Rodriguez-Maroto ◽

Iker Atienza-Diez ◽

Saul Ares ◽

Susanna Manrubia

Keyword(s):

Socioeconomic Status ◽

Compartmental Model ◽

Demographic Data ◽

Vaccination Rate ◽

Structured Populations ◽

Demographic Structure ◽

Vaccine Administration ◽

Vaccination Strategies ◽

It Impacts ◽

Parameter Values

Optimal protocols of vaccine administration to minimize the effects of infectious diseases depend on a number of variables that admit different degrees of control. Examples include the characteristics of the disease and how it impacts on different groups of individuals as a function of sex, age or socioeconomic status, its transmission mode, or the demographic structure of the affected population. Here we introduce a compartmental model of infection propagation with vaccination and reinfection and analyse the effect that variations on the rates of these two processes have on the progression of the disease and on the number of fatalities. The population is split into two groups to highlight the overall effects on disease caused by different relationships between vaccine administration and various demographic structures. We show that optimal administration protocols depend on the vaccination rate, a variable severely conditioned by vaccine supply and acceptance. As a practical example, we study COVID-19 dynamics in various countries using real demographic data. The model can be easily applied to any other disease and demographic structure through a suitable estimation of parameter values. Simulations of the general model can be carried out at the interactive webpage https://mybinder.org/v2/gh/IkerAtienza/SIYRD/main?urlpath=\%2Fvoila\%2Frender\%2FSimulator.ipynb

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A game-theoretic model of Monkeypox to assess vaccination strategies

PeerJ ◽

10.7717/peerj.9272 ◽

2020 ◽

Vol 8 ◽

pp. e9272 ◽

Cited By ~ 4

Author(s):

Sri Vibhaav Bankuru ◽

Samuel Kossol ◽

William Hou ◽

Parsa Mahmoudi ◽

Jan Rychtář ◽

...

Keyword(s):

Compartmental Model ◽

West African ◽

Endemic Equilibrium ◽

Viral Fitness ◽

Theoretic Model ◽

African Countries ◽

Vaccination Strategies ◽

Game Theoretic ◽

Game Theoretic Model ◽

Disease Free

Monkeypox (MPX) is a zoonotic disease similar to smallpox. Its fatality rate is about 11% and it is endemic to the Central and West African countries. In this paper, we analyze a compartmental model of MPX dynamics. Our goal is to see whether MPX can be controlled and eradicated by voluntary vaccinations. We show that there are three equilibria—disease free, fully endemic and previously neglected semi-endemic (with disease existing only among humans). The existence of semi-endemic equilibrium has severe implications should the MPX virus mutate to increased viral fitness in humans. We find that MPX is controllable and can be eradicated in a semi-endemic equilibrium by vaccination. However, in a fully endemic equilibrium, MPX cannot be eradicated by vaccination alone.

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Modelling the interplay of SARS-CoV-2 variants in the United Kingdom.

10.1101/2021.11.26.21266485 ◽

2021 ◽

Author(s):

Nadia Barreiro ◽

Tzipe Govezensky ◽

Cecilia Ventura ◽

Matias Nunez ◽

Pablo Bolcatto ◽

...

Keyword(s):

Compartmental Model ◽

Population Distribution ◽

Severe Disease ◽

Model System ◽

Periodic Waves ◽

Global Features ◽

Vaccination Strategies ◽

The United Kingdom ◽

The Uk ◽

Vaccine Shortage

Most COVID-19 vaccines have proved to be effective to combat the pandemic and to prevent severe disease but their distribution proceeds in a context of global vaccine shortage Their uneven distribution favors the appearance of new variants of concern, as the highly transmissible Delta variant, affecting especially non-vaccinated people. We consider that devising reliable models to analyse the spread of the different variants is crucial. These models should include the effects of vaccination as well as non-pharmaceutical measures used to contain the pandemic by modifying social behaviour. In this work, we present a stochastic geographical model that fulfills these requirements. It consists of an extended compartmental model that includes various strains and vaccination strategies, allowing to study the emergence and dynamics of the new COVID-19 variants. The models conveniently separates the parameters related to the disease from the ones related to social behavior and mobility restrictions. The geographical spread of the virus is modeled taking into account the actual population distribution in any given country of interest. Here we choose the UK as model system, taking advantage of the reliable available data, in order to fit the recurrence of the currently prevalent variants. Our computer simulations allow to describe some global features observed in the daily number of cases, as the appearance of periodic waves and the features that determine the prevalence of certain variants. They also provide useful predictions aiming to help planning future vaccination boosters. We stress that the model could be applied to any other country of interest.

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