Dengue disease, basic reproduction number and control

Dengue is one of the major international public health concerns. Although progress is underway, developing a vaccine against the disease is challenging. Thus, the main approach to fight the disease is vector control. A model for the transmission of Dengue disease is presented. It consists of eight mutually exclusive compartments representing the human and vector dynamics. It also includes a control parameter (insecticide) in order to fight the mosquito. The model presents three possible equilibria: two disease-free equilibria (DFE) and another endemic equilibrium. It has been proved that a DFE is locally asymptotically stable, whenever a certain epidemiological threshold, known as the basic reproduction number, is less than one. We show that if we apply a minimum level of insecticide, it is possible to maintain the basic reproduction number below unity. A case study, using data of the outbreak that occurred in 2009 in Cape Verde, is presented.Comment: This is a preprint of a paper whose final and definitive form has appeared in International Journal of Computer Mathematics (2011), DOI: 10.1080/00207160.2011.55454

Multipoint efficient iterative methods and the dynamics of Ostrowski's method

This is an Author's Accepted Manuscript of an article published in José L. Hueso, Eulalia Martínez & Carles Teruel (2019) Multipoint efficient iterative methods and the dynamics of Ostrowski's method, International Journal of Computer Mathematics, 96:9, 1687-1701, DOI: 10.1080/00207160.2015.1080354 in the International Journal of Computer Mathematics, SEP 2 2019 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/00207160.2015.1080354[EN] In this work, we introduce a modification into the technique, presented in A. Cordero, J.L. Hueso, E. Martinez, and J.R. Torregrosa [Increasing the convergence order of an iterative method for nonlinear systems, Appl. Math. Lett. 25 (2012), pp. 2369-2374], that increases by two units the convergence order of an iterative method. The main idea is to compose a given iterative method of order p with a modification of Newton's method that introduces just one evaluation of the function, obtaining a new method of order p+2, avoiding the need to compute more than one derivative, so we improve the efficiency index in the scalar case. This procedure can be repeated n times, with the same approximation to the derivative, obtaining new iterative methods of order p+2n. We perform different numerical tests that confirm the theoretical results. By applying this procedure to Newton's method one obtains the well known fourth order Ostrowski's method. We finally analyse its dynamical behaviour on second and third degree real polynomials.This research was supported by Ministerio de Economia y Competitividad under grant PGC2018-095896-B-C22 and by the project of Generalitat Valenciana Prometeo/2016/089.Hueso, JL.; Martínez Molada, E.; Teruel-Ferragud, C. (2019). Multipoint efficient iterative methods and the dynamics of Ostrowski's method. International Journal of Computer Mathematics. 96(9):1687-1701. https://doi.org/10.1080/00207160.2015.1080354S16871701969Amat, S., Busquier, S., & Plaza, S. (2010). Chaotic dynamics of a third-order Newton-type method. Journal of Mathematical Analysis and Applications, 366(1), 24-32. doi:10.1016/j.jmaa.2010.01.047Cordero, A., & Torregrosa, J. R. (2007). Variants of Newton’s Method using fifth-order quadrature formulas. Applied Mathematics and Computation, 190(1), 686-698. doi:10.1016/j.amc.2007.01.062Cordero, A., Martínez, E., & Torregrosa, J. R. (2009). Iterative methods of order four and five for systems of nonlinear equations. Journal of Computational and Applied Mathematics, 231(2), 541-551. doi:10.1016/j.cam.2009.04.015Cordero, A., Hueso, J. L., Martínez, E., & Torregrosa, J. R. (2012). Increasing the convergence order of an iterative method for nonlinear systems. Applied Mathematics Letters, 25(12), 2369-2374. doi:10.1016/j.aml.2012.07.005Jarratt, P. (1966). Some fourth order multipoint iterative methods for solving equations. Mathematics of Computation, 20(95), 434-434. doi:10.1090/s0025-5718-66-99924-