Sistema Multiagente para simulação de propagação viral no contexto da COVID-19 utilizando a ferramenta NetLogo
Resumo
A transmissão de doenças infecciosas, como o vírus causador da COVID-19, tem se tornado cada vez mais relevante, dada sua implicação direta na sociedade, impactando setores econômicos e sociais. No entanto, esses impactos não são distribuídos de forma uniforme entre a população, afetando mais intensamente pessoas que vivem em territórios vulnerabilizados – tanto pela maior exposição ao vírus quanto pelas dificuldades de acesso ao sistema de saúde. Deste modo, este trabalho propõe um sistema multiagente, desenvolvido na ferramenta NetLogo, para simulação da propagação do vírus da COVID-19. A principal contribuição da proposta é oferecer um modelo de simulação com sistemas multiagentes, incluindo aspectos sociais e clínicos da população.
Referências
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Gojo Cruz, J. I. N. and Clariño, M. A. A. D. (2022). An agent-based modeling and simulation tool for the exploration of the effects of masks and vaccines on covid-19 spread. In 2022 2nd International Conference in Information and Computing Research (iCORE), pages 60–65.
Karim, S. S. A. and Karim, Q. A. (2021). Omicron sars-cov-2 variant: a new chapter in the covid-19 pandemic. The Lancet, 398(10317):2126–2128.
Matta, G. C., Rego, S. P., and Souto, F., editors (2021). Os impactos sociais da Covid-19 no Brasil: populações vulnerabilizadas e respostas à pandemia. Fiocruz, Rio de Janeiro.
Ministério da Saúde (2025). Covid-19 no brasil. Disponível em: [link]. Acesso em: 7 jun. 2025.
Russell, S. and Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson Education, Hoboken, NJ, USA, 4th edition.
Sahneh, F. D., Scoglio, C., and Van Mieghem, P. (2012). Generalized epidemic mean-field model for spreading processes over multilayer complex networks. IEEE/ACM Transactions on Networking, 21(5):1609–1620.
Shanaa, M. and Abdallah, S. (2020). Agent-based simulation for covid-19 outbreak within a semi-closed environment. In 2020 First International Conference of Smart Systems and Emerging Technologies (SMARTTECH), pages 231–236.
Sheikh, A., McMenamin, J., Taylor, B., and Robertson, C. (2021). Sars-cov-2 delta voc in scotland: demographics, risk of hospital admission, and vaccine effectiveness. The Lancet, 397(10293):2461–2462.
Starr, J. and Kain, M. (2022). Agent-based simulation of social determinants of health for equitable covid-19 intervention. In 2022 7th International Conference on Intelligent Informatics and Biomedical Science (ICIIBMS), volume 7, pages 319–326.
Uriu, K., Okumura, K., Uwamino, Y., Chen, L., Tolentino, J. E., Asakura, H., Nagashima, M., Sadamasu, K., Yoshimura, K., Ito, J., et al. (2025). Virological characteristics of the sars-cov-2 nb. 1.8. 1 variant. The Lancet Infectious Diseases.
Volz, E., Mishra, S., Chand, M., et al. (2021). Assessing transmissibility of sars-cov-2 lineage b.1.1.7 in england. Nature, 593(7858):266–269.
Wilensky, U. (1999). NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University.
Wooldridge, M. (2009). An Introduction to MultiAgent Systems. Wiley, Chichester, West Sussex, England, 2nd edition.
Gkiolmas, A., Chalkidis, A., Papaconstantinou, M., Iqbal, Z., and Skordoulis, C. (2015). An alternative use of the netlogo modeling environment, where the student thinks and acts like an agent, in order to teach concepts of ecology. arXiv preprint arXiv:1501.05779.
Gojo Cruz, J. I. N. and Clariño, M. A. A. D. (2022). An agent-based modeling and simulation tool for the exploration of the effects of masks and vaccines on covid-19 spread. In 2022 2nd International Conference in Information and Computing Research (iCORE), pages 60–65.
Karim, S. S. A. and Karim, Q. A. (2021). Omicron sars-cov-2 variant: a new chapter in the covid-19 pandemic. The Lancet, 398(10317):2126–2128.
Matta, G. C., Rego, S. P., and Souto, F., editors (2021). Os impactos sociais da Covid-19 no Brasil: populações vulnerabilizadas e respostas à pandemia. Fiocruz, Rio de Janeiro.
Ministério da Saúde (2025). Covid-19 no brasil. Disponível em: [link]. Acesso em: 7 jun. 2025.
Russell, S. and Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson Education, Hoboken, NJ, USA, 4th edition.
Sahneh, F. D., Scoglio, C., and Van Mieghem, P. (2012). Generalized epidemic mean-field model for spreading processes over multilayer complex networks. IEEE/ACM Transactions on Networking, 21(5):1609–1620.
Shanaa, M. and Abdallah, S. (2020). Agent-based simulation for covid-19 outbreak within a semi-closed environment. In 2020 First International Conference of Smart Systems and Emerging Technologies (SMARTTECH), pages 231–236.
Sheikh, A., McMenamin, J., Taylor, B., and Robertson, C. (2021). Sars-cov-2 delta voc in scotland: demographics, risk of hospital admission, and vaccine effectiveness. The Lancet, 397(10293):2461–2462.
Starr, J. and Kain, M. (2022). Agent-based simulation of social determinants of health for equitable covid-19 intervention. In 2022 7th International Conference on Intelligent Informatics and Biomedical Science (ICIIBMS), volume 7, pages 319–326.
Uriu, K., Okumura, K., Uwamino, Y., Chen, L., Tolentino, J. E., Asakura, H., Nagashima, M., Sadamasu, K., Yoshimura, K., Ito, J., et al. (2025). Virological characteristics of the sars-cov-2 nb. 1.8. 1 variant. The Lancet Infectious Diseases.
Volz, E., Mishra, S., Chand, M., et al. (2021). Assessing transmissibility of sars-cov-2 lineage b.1.1.7 in england. Nature, 593(7858):266–269.
Wilensky, U. (1999). NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University.
Wooldridge, M. (2009). An Introduction to MultiAgent Systems. Wiley, Chichester, West Sussex, England, 2nd edition.
Publicado
29/09/2025
Como Citar
ALVES, Bruno C.; CALDAS, Letícia B.; F. JUNIOR, Ulisses G.; SANTOS, Agatha C. S.; GROSSMANN, Rodolfo B.; BORN, Míriam B.; AGUIAR, Marilton S. de.
Sistema Multiagente para simulação de propagação viral no contexto da COVID-19 utilizando a ferramenta NetLogo. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 19. , 2025, Fortaleza/CE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 324-331.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2025.37558.
