An agent-based model for the spread of the Dengue fever

Jacintho, Luis F.O.; Batista, André F. M.; Ruas, Terry; Marietto, Maria G. B.; Silva, Fábio A.

doi:10.1145/1878537.1878540

Cited by 17 publications

(7 citation statements)

References 11 publications

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“…Simulações com agentes têm sido aplicadas para estudar a propagação de doenças e avaliar maneiras mais eficientes de prevenção. [Jacintho et al 2010] estudaram a propagação da dengue no Brasil utilizando um modelo baseado em agentes que simula o processo de propagação da doença. São considerados aspectos como informação climática, estações do ano, alimentação e locais comágua para a reprodução dos mosquitos, maior probabilidade de morte do agente em caso de múltiplas infecções (dengue hemorrágica).…”

Section: Trabalhos Relacionadosunclassified

Uma Simulação com Agentes para Estudar a Propagação da COVID-19 em Ibirama(SC)

Teixeira

Santos

2020

Anais Do Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2020)

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A COVID-19 tem causado milhares de mortes mundialmente e prejuízos na economia dos países assolados pela pandemia. Neste artigo apresentamos uma simulação baseada em agentes para estudar a propagação da COVID-19 no município de Ibirama (SC). A simulação utiliza dados populacionais, educacionais e empresariais reais, e também o mapa real do município contendo as suas vias e localização das instituições de ensino e empresas. A simulação considera agentes estudantes e trabalhadores, que se movem pelo ambiente e interagem entre si. Diferentes cenários de isolamento social destes agentes foram simulados. Os resultados obtidos indicam que políticas de isolamento social são efetivas para reduzir a propagação do vírus.

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Section: Trabalhos Relacionadosunclassified

Uma Simulação com Agentes para Estudar a Propagação da COVID-19 em Ibirama(SC)

Teixeira

Santos

2020

Anais Do Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2020)

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“…However, the higher granularity and resolution of agent-based models comes with the cost of data availability and computational complexity. Fortunately, increasing computational power, data availability, and devel-opment of intelligent computational algorithms result in the increasing popularity of agent-based models in understanding the spread of epidemics [116][117][118][119][120][121][122][123].…”

Section: Agent-based Models Of Epidemicsmentioning

confidence: 99%

Mathematical and computational approaches to epidemic modeling: a comprehensive review

Duan

Fan

Zhang

et al. 2015

Front. Comput. Sci.

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Mathematical and computational approaches are important tools for understanding epidemic spread patterns and evaluating policies of disease control. In recent years, epidemiology has become increasingly integrated with mathematics, sociology, management science, complexity science, and computer science. The cross of multiple disciplines has caused rapid development of mathematical and computational approaches to epidemic modeling. In this article, we carry out a comprehensive review of epidemic models to provide an insight into the literature of epidemic modeling and simulation.We introduce major epidemic models in three directions, including mathematical models, complex network models, and agent-based models. We discuss the principles, applications, advantages, and limitations of these models. Meanwhile, we also propose some future research directions in epidemic modeling. Table 1 Classification of epidemic models Types Names Methods Mathematical models Compartmental models, Reed-Frost models Differential equations, stochastic process, Monte Carlo, Markov chains Complex network models System dynamics models in complex networks, numerical simulations of epidemics in complex networks, metapopulation models, weighted networks, adaptive networks Differential equations, stochastic processes Agent-based models

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“…What makes ABM unique for modeling complex adaptive systems is the way an ABM is typically designed. ABMs have been used in domains as diverse as Biological Sciences (Bailey, Lawrence, Shang, Katz, & Peirce, 2009;Siddiqa et al, 2009), disease spread models such as for Dengue (Jacintho, Batista, Ruas, Marietto, & Silva, 2010), Social Sciences (Dennard, Richardson, & Morçöl, 2008), Economics (Cartier, 2004) and Computer Sciences (Muaz Niazi & Hussain, 2010;M. A. Niazi & A. Hussain, 2011a).…”

Section: Agent-based Modelingmentioning

confidence: 99%

A Novel Formal Agent-Based Simulation Modeling Framework of an AIDS Complex Adaptive System

Siddiqa

Niazi

2013

International Journal of Agent Technologies and Systems

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HIV/AIDS spread depends upon complex patterns of interaction among various sub-sets emerging at population level. This added complexity makes it difficult to study and model AIDS and its dynamics. AIDS is therefore a natural candidate to be modeled using agent-based modeling, a paradigm well-known for modeling Complex Adaptive Systems (CAS). While agent-based models are also well-known to effectively model CAS, often times models can tend to be ambiguous and the use of purely textbased specifications (such as ODD) can make models difficult to be replicated.Previous work has shown how formal specification may be used in conjunction with agent-based modeling to develop models of various CAS. However, to the best of our knowledge, no such model has been developed in conjunction with AIDS. In this paper, we present a Formal Agent-Based Simulation modeling framework (FABS-AIDS) for an AIDS-based CAS. FABS-AIDS employs the use of a formal specification model in conjunction with an agent-based model to reduce ambiguity as well as improve clarity in the model definition. The proposed model demonstrates the effectiveness of using formal specification in conjunction with agent-based simulation for developing models of CAS in general and, social network-based agent-based models, in particular.

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An agent-based model for the spread of the Dengue fever

Cited by 17 publications

References 11 publications

Uma Simulação com Agentes para Estudar a Propagação da COVID-19 em Ibirama(SC)

Uma Simulação com Agentes para Estudar a Propagação da COVID-19 em Ibirama(SC)

Mathematical and computational approaches to epidemic modeling: a comprehensive review

A Novel Formal Agent-Based Simulation Modeling Framework of an AIDS Complex Adaptive System

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