Modelos baseados em indivíduos e redes complexas no controle da brucelose bovina
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Data
2021-02-25
Autores
Araujo, Roniel Antonio de
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Universidade Estadual Paulista (Unesp)
Resumo
As doenças infecciosas são responsáveis pelo maior número de mortes na população humana e animal. A brucelose, por exemplo, é a doença zoonótica mais comum em todo o mundo, dificultando gravemente a produtividade do gado e a saúde humana. Pelo seu grande potencial de perda econômica, a brucelose é especialmente preocupante em locais com importantes atividades agropecuárias. Diante desse cenário, métodos que possam auxiliar na prevenção e evitar a propagação da brucelose em bovinos, tornam-se cada vez mais necessários. Os modelos matemáticos vêm mostrando ser uma ferramenta muito útil na busca de estratégias de controle para essa doença infecciosa. Estratégias de modelagem, como Modelos Baseados em Indivíduos (MBI’s) e estudos em Redes Complexas, têm sido crescentemente empregados na modelagem de processos infecciosos. Desse modo, esse trabalho buscou associar essas duas ferramentas matemáticas, MBI e Redes Complexas, de tal forma que no MBI proposto, fossem incorporados modelos de redes de contato mais realísticos para entender como ocorre a evolução da brucelose em bovinos, visto que no MBI, as interações entre os indivíduos eram representadas por grafos completos, ou seja, todos estavam conectados entre si, situação que não ocorre na natureza. Dessa forma, foi implementado um MBI com os modelos de Redes Complexas e foram feitas simulações, a fim de comparação entre as soluções produzidas pelos modelos de redes e o MBI, onde observou-se que tais modelos tinham comportamentos semelhantes ao MBI, e que ainda, a evolução da Brucelose é, de certa forma, sensível à topologia de rede utilizada.
Infectious diseases are responsible for the highest number of deaths in the human and animal population. Brucellosis, for example, is the most common zoonotic disease worldwide, severely hindering livestock productivity and human health. Due to its great potential for economic loss, brucellosis is especially worrying in places with important agricultural activities. In view of this scenario, methods that can help prevent and avoid the spread of brucellosis in cattle are becoming increasingly necessary. The mathematical models have been shown to be a very useful tool in the search for control strategies for this infectious disease. Modeling strategies such as Individual-Based Models (IBM’s) and Complex Network studies have been increasingly employed in modeling infectious processes. Thus, this work sought to associate these two mathematical tools, IBM and Complex Networks, in such a way that in the proposed IBM, more realistic network models were incorporated to understand how the evolution of brucellosis in cattle occurs, since the IBM, the interactions between individuals were represented by complete graphs, that is, all were connected to each other, a situation that did not occur in nature. Thus, an IBM was implemented with the Complex Network models and simulations were performed to compare the solutions produced by the network models with the IBM, where it was observed that such models had similar behaviors to the IBM, and that still, the evolution of Brucellosis is, in a way, sensitive to the network topology used.
Infectious diseases are responsible for the highest number of deaths in the human and animal population. Brucellosis, for example, is the most common zoonotic disease worldwide, severely hindering livestock productivity and human health. Due to its great potential for economic loss, brucellosis is especially worrying in places with important agricultural activities. In view of this scenario, methods that can help prevent and avoid the spread of brucellosis in cattle are becoming increasingly necessary. The mathematical models have been shown to be a very useful tool in the search for control strategies for this infectious disease. Modeling strategies such as Individual-Based Models (IBM’s) and Complex Network studies have been increasingly employed in modeling infectious processes. Thus, this work sought to associate these two mathematical tools, IBM and Complex Networks, in such a way that in the proposed IBM, more realistic network models were incorporated to understand how the evolution of brucellosis in cattle occurs, since the IBM, the interactions between individuals were represented by complete graphs, that is, all were connected to each other, a situation that did not occur in nature. Thus, an IBM was implemented with the Complex Network models and simulations were performed to compare the solutions produced by the network models with the IBM, where it was observed that such models had similar behaviors to the IBM, and that still, the evolution of Brucellosis is, in a way, sensitive to the network topology used.
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Palavras-chave
Modelo Baseado em Indivíduos, Redes complexas, Brucelose bovina, Individual-based models, Complex networks, Bovine brucellosis