Dengue Transmission Dynamics Analysis and Simulation in Minas Gerais - Brazil
Keywords:
Control Strategies, Mosquito Dynamics, Ross-Macdonald Model, SIR ModelAbstract
Dengue control is a challenging task due to the complexity of the factors that involve its spread. The use of mathematical models to investigate the spread of dengue allows us to understand its behavior and provide information for its eradication. In this work, the analysis and simulation of the dynamics of dengue transmission to the State of Minas Gerais-Brazil- was proposed. Mathematical models were simulated using free software Scilab®. In order to assess the impact on the epidemiological curve of the disease, the main methods of mosquito population control (insecticide, larvicide and mechanical control) were analyzed. The results obtained showed that mechanical control was the most efficient method, with 9.3% reduction of cases, as it acts directly in the breeding sites. It is noteworthy that insecticide and larvicide control also had a positive impact on the epidemiological curve, with a decrease of 7.9% and 6.3% of cases, respectively. This justifies the use of these techniques concurrently with mechanical control. The use of projections obtained by mathematical models can guide decision making regarding the adoption of public policies to reduce dengue cases.
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References
E. M. S. Costa, E. A. Costa, R. V. da Cunha, “Desafios da prevenção e controle da dengue na fronteira Brasil/Bolívia: representações sociais de gestores e profissionais da saúde,” Physis: Revista de Saúde Coletiva, vol. 28, no. 1, pp. 1–21, Out. 2018. DOI: 10.1590/S0103-73312018280415
Fiocruz, “Estudo investiga ressurgimento da dengue após epidemia de zika,” 2021. [Online]. Available: https://portal.fiocruz.br/noticia/estudo-investiga-ressurgimento-da-dengue-apos-epidemia-de-zika. Acessado em: Out. 2021.
J. D. Murray “Mathematical biology. I. An introduction”, 3ed, vol. 17. Springer, 2002, pp.315-394.
Fiocruz, “Pesquisa mostra os efeitos da resistência a inseticidas no mosquito da dengue,” 2012. [Online]. Available: https://portal.fiocruz.br/noticia/pesquisa-mostra-os-efeitos-da-resistencia-inseticidas-no-mosquito-da-dengue. Acessado em: Out. 2021.
T. Silva, J. Montalvão, “Inversion of the SIR-SI System for Estimation of Human-Vector Contact Rate and Prediction of Dengue Cases,” IEEE Latin America Transactions, vol. 17, no. 9, pp. 1482-1490, Set. 2019
W. J. Mcbride, H. Biefeldt-Ohmann, "Dengue viral infections; pathogenesis and epidemiology," Microbes Infect, vol. 2, pp. 1041–50, Ago. 2000.
R. S. Barbosa, A. S. S. Soares, D. A. Coelho, D. A. Santos, "Software de simulações dos modelos Sir e Seir como ferramenta de gerenciamento ambiental de doenças epidemiológicas," Scientia Cum Industria, vol. 4, no. 2, pp. 114–118, 2016. DOI: 10.18226/23185279.v4iss2p114
E. Iboi, O.O. Sharomi, C. Ngonghala, A. B. Gumel, "Mathematical Modeling and Analysis of COVID-19 pandemic in Nigeria," Mathematical Biosciences and Engineering, vol.7, no.6 pp. 7192–7220, Jul. 2020.
S. Kim, J. Lee, E. Jung, "Mathematical model of transmission dynamics and optimal control strategies for 2009 A/H1N1 influenza in the Republic of Korea," Journal of Theoretical Biology, vol. 412, no. 7, pp. 74–85, Jan. 2017. DOI: 10.1016/j.jtbi.2016.09.025
H. M. Yang, C. P. Ferreira, "Assessing the effects of vector control on dengue transmission," Applied Mathematics and Computation, vol. 198, pp. 401–413, 2008.
A. Goyal, L. E. Liao, A. S. Perelson, "Within-host mathematical models of hepatitis B virus infection: Past, present, and future," Current Opinion in Systems Biology, vol. 18, pp. 27–35, 2019. DOI: 10.1016/j.coisb.2019.10.003
N. G. Sousa, A. O. Cardoso, R. F. Cardoso, A. G. Utsumi, "Análise da dinâmica de transmissão da COVID-19 em Minas Gerais: Modelagem e Simulação," Research, Society and Development, vol. 9, no. 8, pp. 1–17, 2020.
A. O. Cardoso, N. G. Sousa, R. F. Cardoso, A. G. Utsumi, "Análises de estratégias de isolamento social para o enfrentamento da pandemia COVID-19 em Minas Gerais/Brasil," Holos, vol. 5, pp. 1–19, 2020.
IBGE. População. Disponível em: https://cidades.ibge.gov.br/brasil/mg/panorama. Acesso em 28 jan.2021.
A. Pandey, A. Mubayi, J. Medlock, "Comparing vector–host and SIR models for dengue transmission," Mathematical Biosciences, vol. 246, pp. 252–259, 2013.
S. E. Eikenberry, M. Mancuso, E. Iboi, T. Phan, K. Eikenberry, Y. Kuang, E. Kostelich, A. B. Gumel, "To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic," Infectious Disease Modelling, vol. 5, pp. 293–308, Abr. 2020. DOI: 10.1016/j.idm.2020.04.001
SES, Secretaria de Estado de Saúde de Minas Gerais, " Boletim Epidemiológico de Monitoramento dos casos de Dengue, Chikungunya e Zika," 2020. [Online]. Available: http://www.saude.mg.gov.br. Acessado em: Out. 2021.
UFPel, Universidade Federal de Pelotas, "Gestor, veja aqui o passo a passo para combater o Aedes Aegypti," 2017. [Online]. Available: https://dms.ufpel.edu.br/aedes/. Acessado em: Jan.2021.
I. A. Braga, D. Valle, "Aedes aegypti: inseticidas, mecanismos de ação e resistência," Epidemiologia e Serviços de Saúde, vol. 16, no. 4, pp. 279-293, Dez. 2007.
T.C. Correia, V. O. Flausino, L. L. Figueiredo, T. V. S. Ferreira, T. V. Rabelo, T. D. F. Coelho, A. C. Castro e Abreu, K. A. Prince, "Prevalência de dengue clássica e dengue hemorrágica no Brasil, entre 2011 e 2015," Revista Eletrônica Acervo Saúde, vol. 22, pp.1-8, Abr. 2019.
I. Ghosh, P. K. Tiwarib, J. Chattopadhyay, "Effect of active case finding on dengue control: Implications from a mathematical model," Journal of Theoretical Biology, vol. 464, no. 7, pp. 50-62, Mar. 2019.
