Dynamic systems and pandemics. A relationship to think better
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Puche Navarro, R. ., & González, Ángela. (2021). Dynamic systems and pandemics. A relationship to think better. Revista Guillermo De Ockham, 19(1), 3–6. https://doi.org/10.21500/22563202.5389 (Original work published May 31, 2021)
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References
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Barry, J. (2004). The great Influenza: The Story of the Deadliest Pandemic in History. Penguin Books UK.
Espinoza, M. (2003). El triste destino del azar. Límite, (10). 1-23.
Kermack, W. O & McKendirck, A. G. (1927). A Contribution to the Mathematical Theory of Epidemics. Proceedings of the Royal Society A. 115, 700-721. https://doi.org/10.1098/rspa.1927.0118
Kwuimy, C.A.K., Nazari, F., Jiao, X., Rohani, P., Nataraj, C. (2020). Nonlinear dynamic analysis of an epidemiological model for COVID-19 including public behavior and government action. Nonlinear Dynamics, 101, 1545-1559. https://doi.org/10.1007/s11071-020-05815-z
Mandelbrot, B. (2002). Fractals, Graphics, and Mathematics Education. En Michael Frame y Benoit Mandelbrot (Eds.). 21-38. Fractals, Graphics, and Mathematics Education. Cambridge University Press.
Morin, E. (2009). Introducción al pensamiento complejo. Gedisa: Madrid
Munné, F. (2013). Perfecto e imperfecto: completo. Estudios sobre la complejidad. California-edit : Bogotá
Ossa, J. C. (2011). Un intextricable juego de pérdidas y ganancias. Acta Colombiana de Psicologia. (14)2. 45-55
Prigogyne, I. (1993). Les lois du chaos. Flammarion: Paris
Puche-Navarro, R. (2009). ¿Es La mente no lineal? Programa Editorial Universidad del Valle: Cali
Shoabib, M., Asif Zahoor Raja, M., Touseef Sabir, M., Hussain Bukhari, A., Alrabaiah, H., Sha, Z., Kuman, P., Islam, S., (2021). A stochastic numerical analysis based on hybrid NAR-RBFs networks nonlinear SITR model for novel COVID-19 dynamics. Computer Methods and Programs in Biomedicine. 202, 1-17. https://doi.org/10.1016/j.cmpb.2021.105973
Young, P. C., & Chen, F. (2021). Monitoring and forecasting the COVID-19 epidemic in the UK. Annual Reviews in Control. https://doi.org/https://doi.org/10.1016/j.arcontrol.2021.01.004.
Barry, J. (2004). The great Influenza: The Story of the Deadliest Pandemic in History. Penguin Books UK.
Espinoza, M. (2003). El triste destino del azar. Límite, (10). 1-23.
Kermack, W. O & McKendirck, A. G. (1927). A Contribution to the Mathematical Theory of Epidemics. Proceedings of the Royal Society A. 115, 700-721. https://doi.org/10.1098/rspa.1927.0118
Kwuimy, C.A.K., Nazari, F., Jiao, X., Rohani, P., Nataraj, C. (2020). Nonlinear dynamic analysis of an epidemiological model for COVID-19 including public behavior and government action. Nonlinear Dynamics, 101, 1545-1559. https://doi.org/10.1007/s11071-020-05815-z
Mandelbrot, B. (2002). Fractals, Graphics, and Mathematics Education. En Michael Frame y Benoit Mandelbrot (Eds.). 21-38. Fractals, Graphics, and Mathematics Education. Cambridge University Press.
Morin, E. (2009). Introducción al pensamiento complejo. Gedisa: Madrid
Munné, F. (2013). Perfecto e imperfecto: completo. Estudios sobre la complejidad. California-edit : Bogotá
Ossa, J. C. (2011). Un intextricable juego de pérdidas y ganancias. Acta Colombiana de Psicologia. (14)2. 45-55
Prigogyne, I. (1993). Les lois du chaos. Flammarion: Paris
Puche-Navarro, R. (2009). ¿Es La mente no lineal? Programa Editorial Universidad del Valle: Cali
Shoabib, M., Asif Zahoor Raja, M., Touseef Sabir, M., Hussain Bukhari, A., Alrabaiah, H., Sha, Z., Kuman, P., Islam, S., (2021). A stochastic numerical analysis based on hybrid NAR-RBFs networks nonlinear SITR model for novel COVID-19 dynamics. Computer Methods and Programs in Biomedicine. 202, 1-17. https://doi.org/10.1016/j.cmpb.2021.105973
Young, P. C., & Chen, F. (2021). Monitoring and forecasting the COVID-19 epidemic in the UK. Annual Reviews in Control. https://doi.org/https://doi.org/10.1016/j.arcontrol.2021.01.004.
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