Uma Simulação com Agentes para Estudar a Propagação da COVID-19 em Ibirama(SC)
Resumo
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.
Palavras-chave:
Simulações com agentes, COVID-19, propagação de doenças
Referências
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FECAM (2019). Federação Catarinense de Municı́pios: Relatório empresas Ibirama. [https://static.fecam.net.br/uploads/72/arquivos/1444231 Relatorio Empresas Ibirama.pdf]. Acesso em: Abr/2020.
IBGE (2010). Instituto Brasileiro de Geografia e Estatı́stica - Censo Demográfico 2010. [cidades.ibge.gov.br/brasil/sc/ibirama/pesquisa/23/27652]. Acesso em: Abr/2020.
Jacintho, L. F., Batista, A. F., Ruas, T. L., Marietto, M. G., and Silva, F. A. (2010). An agent-based model for the spread of the dengue fever: a swarm platform simulation approach. In Proceedings of the 2010 Spring Simulation Multiconference, pages 1–8.
Keeling, M. J. and Rohani, P. (2008). Modeling infectious diseases in humans and animals. Princeton University Press.
Klügl, F. and Bazzan, A. L. C. (2012). Agent-based modeling and simulation. AI Magzine, 33(3):29–40.
Lu, R., Niu, P., Zhao, L., Wang, H., Wang, W., and Tan, W. (2020). Sequencing the complete genome of COVID-19 virus from clinical samples using the sanger method. China CDC Weekly, 2:447.
Macal, C. and North, M. (2014). Introductory tutorial: Agent-based modeling and simulation. In Proceedings of the 2014 Winter Simulation Conference, WSC ’14, pages 6–20, Piscataway, NJ, USA. IEEE Press.
Matrajt, L. and Leung, T. (2020). Evaluating the effectiveness of social distancing interventions to delay or flatten the epidemic curve of coronavirus disease. Emerging Infectious Disease, 26(8).
Nakamura, K., Ide, S., Saito, S., et al. (2020). Covid-19 can suddenly become severe: a case series from Tokyo, Japan. Global Health & Medicine.
NCPERET (2020). The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team - the epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (covid-19). China CDC Weekly, 2(8):113–122.
SBI (2020). Informe da Sociedade Brasileira de Infectologia (SBI) sobre o novo coronavı́rus. [https://www.infectologia.org.br/admin/zcloud/principal/2020/03/InformativoCoV-12-03-2020.pdf]. Acesso em: Abr/2020.
SED SC (2020). SED - Secretaria de Estado da Educação - Educação de Jovens e Adultos - SC. [http://sed.sc.gov.br/servicos/etapas-e-modalidades-de-ensino/29-modalidadede-ensino/6617-educacao-de-jovens-e-adultos]. Acesso em: Abr/2020.
Thompson, J., McClure, R., Blakely, T., et al. (2020). Modelling the likelihood of eliminating the SARS-CoV-2 pandemic in australia and new zealand under current public health policy settings: An agent-based-seir modelling approach. [http://dx.doi.org/10.2139/ssrn.3588074 ]. Acesso em: Jun/2020.
World Health Organization (2020a). Coronavirus disease 2019 (covid-19) situation report–51. [www.who.int/docs/default-source/coronaviruse/situationreports/20200311-sitrep-51-covid-19.pdf]. Acesso em: Jun/2020.
World Health Organization (2020b). Q&A on coronaviruses (covid-19). [www.who.int/emergencies/diseases/novel-coronavirus-2019/question-and-answershub/q-a-detail/q-a-coronaviruses]. Acesso em: Jun/2020.
World Health Organization (2020c). WHO coronavirus disease (COVID-19) dashboard. [https:covid19.who.int]. Acesso em: Ago/2020.
BRASIL (2002). Decreto-lei 10.406, de 10 de janeiro de 2002. [www.planalto.gov.br/ccivil 03/leis/2002/l10406.htm]. Acesso em: Abr/2020.
Britton, T., Ball, F., and Trapman, P. (2020). A mathematical model reveals the influence of population heterogeneity on herd immunity to sars-cov-2. Science, 369(6505):846– 849.
ECDC (2020). European Centre for Disease Prevention and Control - Guidance for discharge and ending isolation in the context of widespread community transmission of COVID-19. [www.ecdc.europa.eu/sites/default/files/documents/covid-19-guidancedischarge-and-ending-isolation-first%20update.pdf]. Acesso em: Abril/2020.
Edmonds, B. (2001). The use of models-making MABS more informative. In International Workshop on Multi-Agent Systems and Agent-Based Simulation (MABS), pages 15–32, Boston, USA.
Eisinger, D. and Thulke, H.-H. (2008). Spatial pattern formation facilitates eradication of infectious diseases. Journal of Applied Ecology, 45(2):415–423.
FECAM (2019). Federação Catarinense de Municı́pios: Relatório empresas Ibirama. [https://static.fecam.net.br/uploads/72/arquivos/1444231 Relatorio Empresas Ibirama.pdf]. Acesso em: Abr/2020.
IBGE (2010). Instituto Brasileiro de Geografia e Estatı́stica - Censo Demográfico 2010. [cidades.ibge.gov.br/brasil/sc/ibirama/pesquisa/23/27652]. Acesso em: Abr/2020.
Jacintho, L. F., Batista, A. F., Ruas, T. L., Marietto, M. G., and Silva, F. A. (2010). An agent-based model for the spread of the dengue fever: a swarm platform simulation approach. In Proceedings of the 2010 Spring Simulation Multiconference, pages 1–8.
Keeling, M. J. and Rohani, P. (2008). Modeling infectious diseases in humans and animals. Princeton University Press.
Klügl, F. and Bazzan, A. L. C. (2012). Agent-based modeling and simulation. AI Magzine, 33(3):29–40.
Lu, R., Niu, P., Zhao, L., Wang, H., Wang, W., and Tan, W. (2020). Sequencing the complete genome of COVID-19 virus from clinical samples using the sanger method. China CDC Weekly, 2:447.
Macal, C. and North, M. (2014). Introductory tutorial: Agent-based modeling and simulation. In Proceedings of the 2014 Winter Simulation Conference, WSC ’14, pages 6–20, Piscataway, NJ, USA. IEEE Press.
Matrajt, L. and Leung, T. (2020). Evaluating the effectiveness of social distancing interventions to delay or flatten the epidemic curve of coronavirus disease. Emerging Infectious Disease, 26(8).
Nakamura, K., Ide, S., Saito, S., et al. (2020). Covid-19 can suddenly become severe: a case series from Tokyo, Japan. Global Health & Medicine.
NCPERET (2020). The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team - the epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (covid-19). China CDC Weekly, 2(8):113–122.
SBI (2020). Informe da Sociedade Brasileira de Infectologia (SBI) sobre o novo coronavı́rus. [https://www.infectologia.org.br/admin/zcloud/principal/2020/03/InformativoCoV-12-03-2020.pdf]. Acesso em: Abr/2020.
SED SC (2020). SED - Secretaria de Estado da Educação - Educação de Jovens e Adultos - SC. [http://sed.sc.gov.br/servicos/etapas-e-modalidades-de-ensino/29-modalidadede-ensino/6617-educacao-de-jovens-e-adultos]. Acesso em: Abr/2020.
Thompson, J., McClure, R., Blakely, T., et al. (2020). Modelling the likelihood of eliminating the SARS-CoV-2 pandemic in australia and new zealand under current public health policy settings: An agent-based-seir modelling approach. [http://dx.doi.org/10.2139/ssrn.3588074 ]. Acesso em: Jun/2020.
World Health Organization (2020a). Coronavirus disease 2019 (covid-19) situation report–51. [www.who.int/docs/default-source/coronaviruse/situationreports/20200311-sitrep-51-covid-19.pdf]. Acesso em: Jun/2020.
World Health Organization (2020b). Q&A on coronaviruses (covid-19). [www.who.int/emergencies/diseases/novel-coronavirus-2019/question-and-answershub/q-a-detail/q-a-coronaviruses]. Acesso em: Jun/2020.
World Health Organization (2020c). WHO coronavirus disease (COVID-19) dashboard. [https:covid19.who.int]. Acesso em: Ago/2020.
Publicado
20/10/2020
Como Citar
TEIXEIRA, Lucas; SANTOS, Fernando.
Uma Simulação com Agentes para Estudar a Propagação da COVID-19 em Ibirama(SC). In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 17. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 176-187.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2020.12127.
