Conditioners of the infectious diseases dynamics

Costa, Ana Luiza Fontes de Azevedo; Neto, Orlando Alves Rodrigues; Silva-Júnior, Antonio Carlos Souza

doi:10.18468/estcien.2018v8n3.p09-23

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…2020;6:10816 acquired immunity and behavioral changes, that contribute to the end of an epidemic. 9 However, in the evolutive course of a virus during an epidemic in a large population such as the Brazilian population, considering the competition of the emerging viral pathogen with other endemic viruses, it is also expected the possibility of the emergence of viral quasiespecies that can find new hosts in populations of wild or domestic animals, and thus initiate events of reemergence of disease. 33…”

Section: Molecular Evidence Of the Zika Virus Biological Evolutionmentioning

confidence: 99%

What to Expect From a Viral Emerging Epidemics: The Brazilian Experience With the Zika Virus

Costa

Sousa

2020

Rev. Infec. e Saude

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Introduction:The transformations that the world population has been going through as a result of the processes of globalization and urbanization have also changed the dynamics of transmission of many infectious diseases, as well as their epidemiological profiles. In this context, this work proposes a reflection on the evolutionary aspects of emerging viral pathogens and factors that can contribute to reemergence events. Outline: This article brings reflections from the authors about the scientific literature, addressing ecological and evolutionary factors that may occur in cases of viral emerging pathogens according to the experience acquired after the Zika epidemic in Brazil. Results: The evolutionary mechanism by which viral agents evolve and acquire new structural and pathological properties also contributes to the decline in the number of cases in conjunction with preventive measures; and the biological diversity of vectors and possible candidates for intermediate hosts represents a factor that can contribute to the occurrence of epidemic events of reemergence. Implications: Analyzes focusing on the evolutionary aspects of viral agents can contribute to the early recognition of new symptoms, and identification of possible candidates for reservoir hosts, consequently, contributing to the prevention of reemergence events.

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Section: Molecular Evidence Of the Zika Virus Biological Evolutionmentioning

confidence: 99%

What to Expect From a Viral Emerging Epidemics: The Brazilian Experience With the Zika Virus

Costa

Sousa

2020

Rev. Infec. e Saude

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“…An ecologically imbalanced interaction between a microbial infectious agent and a host leads to infectious illnesses. As a result [2] provides information on the population's exposure and environmental impact. In this regard, it is crucial to comprehend how the aforementioned components interact in order to foster the creation of efficient management, health aid, and policy measures [3].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2023

Progr. Fract. Differ. Appl.

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Both mathematics and science are important for one another and have a close relationship. It is impossible to dispute the significance of mathematics in a number of scientific disciplines, including electrical engineering, physics, biology, and medicine. Due to a number of applications of mathematical biology in the twenty-first century, researchers have taken a special interest in this field. Due to the complexity of the underlying connections, both deterministic and stochastic epidemiological models are founded on an inadequate understanding of the infectious network. Over the past several years, the use of different fractional operators to model the problem has grown, and it is now a common way to study how epidemics spread. New fractional operators, the infectious disease model has been studied in this paper. By using different numerical techniques and the time fractional parameters, the mechanical characteristics of the fractional order model are identified. The uniqueness and existence have been established. The model's local and global stability analysis has been found. In order to justify the theoretical results, numerical simulations are carried out for the presented method in the range of fractional order to show the implications of fractional and fractal orders. We applied very effective numerical technique to obtain the solutions of the model and simulations. Also, we present conditions of existence for a solution to the purposed epidemic model and to calculate the reproduction number in certain state conditions of the analyzed dynamic system. Infectious disease fractional order model is offered for analysis with simulations in order to determine the possible efficacy of disease transmission in the Community. The Fractal fractional operator is employed to study the dynamical transmission of diseases effect on society which is helpful for analysis, decision making, and disease control. Are treated with the Banach contraction principle. Microorganisms, interactions between individuals or groups, and environmental, social, economic, and demographic factors on a broader scale are all examples. Finally, numerical simulations that demonstrate the impact of fractional parameters on our found solutions are built to study the impact of the system parameter on the disease's spread. In conclusion, fractional operators in mathematical models can help decision-makers make better choices regarding the course of action to take in an epidemic situation. Further, we suggested some future work directions with the help of the new hybrid fractional operator. Fractional Calculus is a prominent topic for research within the discipline of Applied Mathematics due to its usefulness in solving problems in many different branches of science, engineering, and medicine. Recent researchers have identified the importance of mathematical tools in various disease models as being very useful to study the dynamics with the help of fractional and integer calculus modeling.

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“…Infectious diseases are the result of a disharmonious ecological interaction between a microbial infectious agent (bacteria, fungi, parasites, or viruses, except for prions that are infectious proteins) and a host, where the dynamics in this interaction is subjected to the modulatory influence of several factors, such as the environment, the biological properties of the pathogens and the host susceptibilities to disease, as well as the influence of behavioral, cultural, and social patterns that can enhance or mitigate the host's exposure to the disease sources and consequently its transmission in the population [1].…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling of the Infectious Diseases: Key Concepts and Applications

da¹,

Amanajas²,

Lima³

et al. 2021

J Infect Dis Epidemiol

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Background:The transmission dynamics of infectious diseases is susceptible to changes governed by several factors, whose recognition is critical for the rational development of strategies for prevention and control, as well as for developing health policies. In this context, mathematical modeling can provide useful insights concerning transmission patterns and detection of parameters to mitigate disease in the population.Objectives: To didactically present the mathematical modeling of infectious diseases for health students and professionals as a tool in epidemiology.Methods: A comprehensive literature review was conducted with articles obtained from PubMed, Web of Science, and Google Scholar databases with the term infectious diseases mathematical modeling.Results: There are two main types of models built with a basis on fixed or probabilistic rates that describe individuals' movement in compartments that designate stages in the natural history of the disease. In this sense, deterministic models are non-probabilistic and stochastic models are probabilistic, the first one helps in developing a prospection of possible scenarios in epidemiology, while the second is more applicable in the study of the influence of variables in the transmission dynamics. Conclusion:The infectious agents are in a constant process of biological evolution, as well as the environment and human conceptions, culture, and behavior, implying a constant transformation in the epidemiological profile of infectious diseases, in which the mathematical modeling can provide support to the decision-making processes concerning epidemiology and public health.

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Conditioners of the infectious diseases dynamics

Cited by 5 publications

References 30 publications

What to Expect From a Viral Emerging Epidemics: The Brazilian Experience With the Zika Virus

What to Expect From a Viral Emerging Epidemics: The Brazilian Experience With the Zika Virus

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Mathematical Modeling of the Infectious Diseases: Key Concepts and Applications

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