Within-host mathematical modeling on crucial inflammatory mediators and drug interventions in COVID-19 identifies combination therapy to be most effective and optimal

Chhetri, Bishal; Bhagat, Vijay Manohar; Vamsi, D. K. K.; Ananth, V.S.; D, Bhanu Prakash; Mandale, Roshan; Muthusamy, Swapna; Sanjeevi, Carani B.

doi:10.1016/j.aej.2020.12.011

Cited by 28 publications

(47 citation statements)

References 35 publications

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“…The simulation is done using matlab software and ode solver ode45 is used to solve the system of equations. The parameter values of the within-host sub-model used in simulation is taken from [9]. These within-host parameter values are used in calculating the area under the viral load curve N h .…”

Section: Numerical Illustrations Of the Stability Of Equilibrium Pointsmentioning

confidence: 99%

“…Some of the important mathematical modelling studies that deal with transmission and spread of COVID-19 at between-host level can be found in [7,23,25,39,32,28,40,24,38,10,41,4,33]. Within-host mathematical modelling studies that deal with the interplay between the viral dynamics and immune response of COVID-19 disease can be found in [8,36].…”

Section: Introductionmentioning

confidence: 99%

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A Nested Multi-Scale Model for COVID-19 Viral Infection

Chhetri,

Vamsi,

Sanjeevi

2021

Preprint

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In this study, we develop and analyze a nested multi-scale model for COVID -19 disease that integrates within-host scale and between-host scale sub-models. First, the well-posedness of the multi-scale model is discussed, followed by the stability analysis of the equilibrium points. The disease-free equilibrium point is shown to be globally asymptotically stable for R0 < 1. When R0 exceeds unity, a unique infected equilibrium exists, and the system is found to undergo a forward (trans-critical) bifurcation at R0 = 1. Two parameter heat plots are also done to find the parameter combinations for which the equilibrium points are stable. The parameters β, π and Λ are found to be most sensitive to R0. The influence of within-host sub-model parameter on the between-host sub-model variables is numerically illustrated. The spread of infection in a community is shown to be influenced by within-host level sub-model parameters, such as the production of viral particles by infected cells (α), the clearance rate of infected cells by the immune system (x), and the clearance rate of viral particles by the immune system (y). The comparative effectiveness of the three health interventions (antiviral drugs, immunomodulators, and generalized social distancing) for COVID-19 infection was examined using the effective reproductive number RE as an indicator of the effectiveness of the interventions. The results suggest that a combined strategy of antiviral drugs, immunomodulators and generalized social distancing would be the best strategy to implement to contain the spread of infection in the community. We believe that the results presented in this study will help physicians, medical professionals, and researchers to make informed decisions about COVID -19 disease prevention and treatment interventions.

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Section: Numerical Illustrations Of the Stability Of Equilibrium Pointsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Nested Multi-Scale Model for COVID-19 Viral Infection

Chhetri,

Vamsi,

Sanjeevi

2021

Preprint

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“…Most of these studies ignore the intercellular delay by assuming that the infectious process is instantaneous, which may not be biologically true [21]. A detailed study of the SIV model developed on the basis of pathogenesis dealing with COVID -19 is carried out by the authors in [9]. In the present work, a model is developed and studied that takes into account the intercellular time delay.…”

Section: Model Without Interventionsmentioning

confidence: 99%

“…In the article [10], the authors have done an extensive study on the role of antiviral drugs such as Arbidol, Remdesivir, Lopinavir and Ritonavir and immunomodulators such as INF, and Zinc in COVID-19 infection. In this work initially, we extend the work done in [9] by incorporating inter-cellular time delay and do the stability analysis of the equilibrium points admitted by the model. Secondly, an optimal control problem is framed with antiviral agents and second-line drugs as control measures incorporating the adverse events caused by antiviral drugs and their roles in reducing the infected cell count and the viral load is studied.…”

Section: Introductionmentioning

confidence: 99%

Time Optimal Control Studies on COVID-19 Incorporating Adverse Events of the Antiviral Drugs

Chhetri¹,

Bhagat²,

Muthusamy³

et al. 2021

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The COVID -19 pandemic has resulted in more than 166 million infections and 3.4 million deaths worldwide. Several drug interventions targeting multiple stages of the pathogenesis of COVID -19 can significantly reduce induced infection and thus mortality. In this study, we first develop SIV model by incorporating the intercellular time delay and analyze the stability of the equilibrium points. The model dynamics admits disease-free equilibrium and the infected equilibrium with their stability, based on the value of basic reproduction number R0. We then frame an optimal control problem with antiviral drugs and second-line drugs as control measures and study their roles in reducing the infected cell count and the viral load. The comparative study done in the optimal control problem suggests that when the first line antiviral drugs shows adverse events, considering these drugs in reduced quantity along with the second line drug would be highly effective in reducing the infected cell and viral load in a COVID infected patients. Later, we formulate a time-optimal control problem with the objective to drive the system from any given initial state to the desired infection-free equilibrium state in minimal time. Using Pontryagin's Minimum Principle the optimal control strategy is shown to be of bang-bang type with possibility of switches between two extreme values of the optimal controls. Numerically, it is shown that the desired infection-free state is achieved in less time when the higher values of both the optimal controls are chosen. The results obtained from this study can be very helpful to researchers, epidemiologists, clinicians, and doctors who are working in this field.

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“…Cehhetri et al. [12] developed a mathematical within-host model and found that the combination of therapies including antiviral and immunomodulating drugs were optimal and most effective. Also, within-host models can help us to differentiate groups of patients with high mortality, Néant et al.…”

Section: Introductionmentioning

confidence: 99%

Computational simulations to dissect the cell immune response dynamics for severe and critical cases of SARS-CoV-2 infection

Blanco-Rodríguez

Hernández-Vargas

2021

Computer Methods and Programs in Biomedicine

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Background: COVID-19 is a global pandemic leading high death tolls worldwide day by day. Clinical evidence suggests that COVID-19 patients can be classified as non-severe, severe and critical cases. In particular, studies have highlighted the relationship between the lymphopenia and the severity of the illness, where CD8 T cells have the lowest levels in critical cases. However, quantitative understanding of the immune responses in COVID-19 patients is still missing. Objectives: In this work, we aim to elucidate the key parameters that define the course of the disease deviating from severe to critical cases. Dynamics of different immune cells are taken into account in mechanistic models to elucidate those that contribute to the worsening of the disease. Methods: Several mathematical models based on ordinary differential equations are proposed to represent data sets of different immune response cells dynamics such as CD8 T cells, NK cells, and also CD4 T cells in patients with SARS-CoV-2 infection. Parameter fitting is performed using the differential evolution algorithm. Non-parametric bootstrap approach is introduced to abstract the stochastic environment of the infection. Results: The mathematical model that represents the data more appropriately is considering CD8 T cell dynamics. This model had a good fit to reported experimental data, and in accordance with values found in the literature. The NK cells and CD4 T cells did not contribute enough to explain the dynamics of the immune responses. Conclusions: Our computational results highlight that a low viral clearance rate by CD8 T cells could lead to the severity of the disease. This deregulated clearance suggests that it is necessary immunomodulatory strategies during the course of the infection to avoid critical states in COVID-19 patients.

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Within-host mathematical modeling on crucial inflammatory mediators and drug interventions in COVID-19 identifies combination therapy to be most effective and optimal

Cited by 28 publications

References 35 publications

A Nested Multi-Scale Model for COVID-19 Viral Infection

A Nested Multi-Scale Model for COVID-19 Viral Infection

Time Optimal Control Studies on COVID-19 Incorporating Adverse Events of the Antiviral Drugs

Computational simulations to dissect the cell immune response dynamics for severe and critical cases of SARS-CoV-2 infection

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