An Evolutionary Perspective of Virus Propagation

Machado, J. A. Tenreiro

doi:10.3390/math8050779

Cited by 5 publications

(4 citation statements)

References 55 publications

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“…Also, concerning evolutionary and game of life algorithms [50,51], predefined parameters and initial inputs are crucial for the machine learning analysis. However, beyond biological features as described in the last paragraph, unpredictable scale of infected individuals are found worldwide without vaccination or social isolation.…”

Section: Discussionmentioning

confidence: 99%

SARS-COV-2: SIR Model Limitations and Predictive Constraints

Telles¹,

Lopes

Franco

2021

Symmetry

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Background: The main purpose of this research is to describe the mathematical asymmetric patterns of susceptible, infectious, or recovered (SIR) model equation application in the light of coronavirus disease 2019 (COVID-19) skewness patterns worldwide. Methods: The research modeled severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) spreading and dissemination patterns sensitivity by redesigning time series data extraction of daily new cases in terms of deviation consistency concerning variables that sustain COVID-19 transmission. The approach opened a new scenario where seasonality forcing behavior was introduced to understand SARS-COV-2 non-linear dynamics due to heterogeneity and confounding epidemics scenarios. Results: The main research results are the elucidation of three birth- and death-forced seasonality persistence phases that can explain COVID-19 skew patterns worldwide. They are presented in the following order: (1) the environmental variables (Earth seasons and atmospheric conditions); (2) health policies and adult learning education (HPALE) interventions; (3) urban spaces (local indoor and outdoor spaces for transit and social-cultural interactions, public or private, with natural physical features (river, lake, terrain). Conclusions: Three forced seasonality phases (positive to negative skew) phases were pointed out as a theoretical framework to explain uncertainty found in the predictive SIR model equations that might diverge in outcomes expected to express the disease’s behaviour.

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Section: Discussionmentioning

confidence: 99%

SARS-COV-2: SIR Model Limitations and Predictive Constraints

Telles¹,

Lopes

Franco

2021

Symmetry

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“…As shown in [16], mathematical models are a key tool for guiding public health measures in order to make decisions regarding potential economic and health interventions and when deciding how to intervene. To obtain models, a possible approach are evolutionary epidemic diffusion models [17] using suitable data, or more traditionally, compartmental models similar to the classic SEIR model, an overview of which can be found in [18]. An interesting paper is [19], where an SEIR model for COVID-19 dynamics incorporating the environment and social distancing is considered.…”

Section: Literature Reviewmentioning

confidence: 99%

Extension of SEIR Compartmental Models for Constructive Lyapunov Control of COVID-19 and Analysis in Terms of Practical Stability

2021

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Due to the worldwide outbreak of COVID-19, many strategies and models have been put forward by researchers who intend to control the current situation with the given means. In particular, compartmental models are being used to model and analyze the COVID-19 dynamics of different considered populations as Susceptible, Exposed, Infected and Recovered compartments (SEIR). This study derives control-oriented compartmental models of the pandemic, together with constructive control laws based on the Lyapunov theory. The paper presents the derivation of new vaccination and quarantining strategies, found using compartmental models and design methods from the field of Lyapunov theory. The Lyapunov theory offers the possibility to track desired trajectories, guaranteeing the stability of the controlled system. Computer simulations aid to demonstrate the efficacy of the results. Stabilizing control laws are obtained and analyzed for multiple variants of the model. The stability, constructivity, and feasibility are proven for each Lyapunov-like function. Obtaining the proof of practical stability for the controlled system, several interesting system properties such as herd immunity are shown. On the basis of a generalized SEIR model and an extended variant with additional Protected and Quarantined compartments, control strategies are conceived by using two fundamental system inputs, vaccination and quarantine, whose influence on the system is a crucial part of the model. Simulation results prove that Lyapunov-based approaches yield effective control of the disease transmission.

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“…In particular, Mowshowitz [5] interpreted the topological information content of a graph, such as its entropy measure. Since then, various graph entropy measures have been defined to investigate the structural properties of graphs [6][7][8] as well as [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%