Stochastic Modeling of Dynamics of the Spread of COVID-19 Infection Taking Into Account the Heterogeneity of Population According To Immunological, Clinical and Epidemiological Criteria

Pertsev, N. V.; Loginov, K. K.; Lukashev, A.; Vakulenko, Yu.

doi:10.17537/2022.17.43

“…Finally, the model can be used to predict the intensity of airborne infection spreading by infected individuals, e.g., the amount of virus which is transmitted via droplets from a SARS-CoV-2 infected person, depending on the time of infection and the immune response parameters. This type of estimates provide a direct information that may be included in the epidemiological models of virus spreading in the human population [58,59]. We note that a probabilistic model was recently elaborated linking the viral load and the host infectiousness [21].…”

Section: Discussionmentioning

confidence: 99%

Predicting the Kinetic Coordination of Immune Response Dynamics in SARS-CoV-2 Infection: Implications for Disease Pathogenesis

Grebennikov

¹

,

Karsonova

²

,

Loguinova

³

et al. 2022

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A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter evaluation. The calibration of the mathematical model of SARS-CoV-2 infection is based on combining the parameter guesses from our earlier study of influenza A virus infection, some recent quantitative models of SARS-CoV-2 infection and clinical data-based parameter estimation of a subset of the model parameters. Hence, the calibrated mathematical model represents a theoretical exploration type of study, i.e., ‘in silico patient’ with mild-to-moderate severity phenotype, rather than a completely validated quantitative model of COVID-19 with respect to all its state-space variables. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the kinetics of immune responses with the clinical phenotypes of COVID-19. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to the pathogenesis of COVID-19, i.e., the sensitivity of the peak viral load to the parameters characterizing the antiviral specific response components, the kinetic coordination of the individual innate and adaptive immune responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e., the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds for variations of the innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination between them were identified.

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“…the amount of virus which is transmitted via droplets from a 160 SARS-CoV-2 infected person, depending on the time of infection and the immune response 161 parameters. This type of estimates provide a direct information that may be included 162 into the epidemiological models of virus spreading in the human population[49,53]. We 163 note that a probabilistic model was recently elaborated linking the viral load and the host 164 infectiousness[15].…”

mentioning

confidence: 99%

Predicting the Cross-Coordinated Immune Response Dynamics in Sars-Cov-2 Infection: Implications for Disease Pathogenesis

Grebennikov¹,

Karsonova²,

Логинова³

et al. 2022

Preprint

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A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter estimation. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the clinical phenotypes of COVID-19 with the kinetics of immune responses. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to pathogenesis of COVID-19, i.e. sensitivity of the peak viral load to parameters characterizing the specific response components, the kinetic coordination of the individual responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e. the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds in the relative unbalance between innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination were identified.

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Stochastic Modeling of Time- and Place-Local Contacts of Individuals in an Epidemic Process

Pertsev

¹

,

Topchii

²

,

Loginov

³

2023

J. Appl. Ind. Math.

0

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Stochastic Modeling of Dynamics of the Spread of COVID-19 Infection Taking Into Account the Heterogeneity of Population According To Immunological, Clinical and Epidemiological Criteria

Cited by 6 publications

References 21 publications

Predicting the Kinetic Coordination of Immune Response Dynamics in SARS-CoV-2 Infection: Implications for Disease Pathogenesis

Predicting the Kinetic Coordination of Immune Response Dynamics in SARS-CoV-2 Infection: Implications for Disease Pathogenesis

Predicting the Cross-Coordinated Immune Response Dynamics in Sars-Cov-2 Infection: Implications for Disease Pathogenesis

Stochastic Modeling of Time- and Place-Local Contacts of Individuals in an Epidemic Process

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