Quantifying rotavirus kinetics in the REH tumor cell line using in vitro data

González-Parra, Gilberto; Dobrovolny, Hana M.; Aranda, Diego; Chen-Charpentier, Benito M.; Rojas, Rafael Antonio Guerrero

doi:10.1016/j.virusres.2017.09.023

Cited by 20 publications

(12 citation statements)

References 71 publications

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“…Understanding the processes underlying viral loss of infectivity is also important for constructing accurate mathematical models of the infection process. Most viral kinetics models assume exponential decay of virus (Baccam et al 2006;Perelson et al 1996;González-Parra and Dobrovolny 2015;González-Parra et al 2018), but recent studies suggest that this might not be an accurate assumption for all viruses (Beauchemin et al 2019;Ailavadi et al 2019;Bozkurt et al 2015). Incorrect modeling of the mechanism of viral decay could lead to erroneous predictions of viral time courses, particularly when using models to estimate antiviral efficacy from viral decay rates (Palmer et al 2017;Cardozo et al 2020Cardozo et al , 2017.…”

Section: Introductionmentioning

confidence: 99%

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Energy Requirements for Loss of Viral Infectivity

Rowell

Dobrovolny

2020

Food Environ Virol

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Outside the host, viruses will eventually lose their ability to infect cells due to conformational changes that occur to proteins on the viral capsid. In order to undergo a conformational change, these proteins require energy to activate the chemical reaction that leads to the conformational change. In this study, data from the literature is used to calculate the energy required for viral inactivation for a variety of different viruses by means of the Arrhenius equation. We find that some viruses (rhinovirus, poliovirus, human immunodeficiency virus, Alkhumra hemorrhagic fever virus, and hepatitis A virus) have high inactivation energies, indicative of breaking of a chemical double bond. We also find that several viruses (respiratory syncytial virus, poliovirus, and norovirus) have nonlinear Arrhenius plots, suggesting that there is more than a single pathway for inactivation of these viruses.

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Section: Introductionmentioning

confidence: 99%

“… 1996 ; González-Parra and Dobrovolny 2015 ; González-Parra et al. 2018 ), but recent studies suggest that this might not be an accurate assumption for all viruses (Beauchemin et al. 2019 ; Ailavadi et al.…”

Section: Introductionmentioning

confidence: 99%

Energy Requirements for Loss of Viral Infectivity

Rowell

Dobrovolny

2020

Food Environ Virol

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“…Notably, other models have been presented to study the spread of Zika in human and mosquito populations. However, those mathematical models have more parameters, which may cause an identifiability problem when we need to estimate the model's parameter values using real data of infected cases [2,28,29].…”

Section: Mathematical Modelmentioning

confidence: 99%

Optimization of the Controls against the Spread of Zika Virus in Populations

2020

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In this paper, we study and explore two control strategies to decrease the spread of Zika virus in the human and mosquito populations. The control strategies that we consider in this study are awareness and spraying campaigns. We solve several optimal control problems relying on a mathematical epidemic model of Zika that considers both human and mosquito populations. The first control strategy is broad and includes using information campaigns, encouraging people to use bednetting, wear long-sleeve shirts, or similar protection actions. The second control is more specific and relies on spraying insecticides. The control system relies on a Zika mathematical model with control functions. To develop the optimal control problem, we use Pontryagins’ maximum principle, which is numerically solved as a boundary value problem. For the mathematical model of the Zika epidemic, we use parameter values extracted from real data from an outbreak in Colombia. We study the effect of the costs related to the controls and infected populations. These costs are important in real life since they can change the outcomes and recommendations for health authorities dramatically. Finally, we explore different options regarding which control measures are more cost-efficient for society.

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“…Recently, there have been a growing literature regarding mathematical models for virus infection within-host [9][10][11][12][13][14][15][16][17][18][19]. These mathematical models include a variety of characteristics related to the viral dynamics.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Analysis and Numerical Solution of a Model of HIV with a Discrete Time Delay

et al. 2021

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We propose a mathematical model based on a set of delay differential equations that describe intracellular HIV infection. The model includes three different subpopulations of cells and the HIV virus. The mathematical model is formulated in such a way that takes into account the time between viral entry into a target cell and the production of new virions. We study the local stability of the infection-free and endemic equilibrium states. Moreover, by using a suitable Lyapunov functional and the LaSalle invariant principle, it is proved that if the basic reproduction ratio is less than unity, the infection-free equilibrium is globally asymptotically stable. In addition, we designed a non-standard difference scheme that preserves some relevant properties of the continuous mathematical model.

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Quantifying rotavirus kinetics in the REH tumor cell line using in vitro data

Cited by 20 publications

References 71 publications

Energy Requirements for Loss of Viral Infectivity

Energy Requirements for Loss of Viral Infectivity

Optimization of the Controls against the Spread of Zika Virus in Populations

Mathematical Analysis and Numerical Solution of a Model of HIV with a Discrete Time Delay

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