# Progress in nonlinear analysis research by Erik T. Hoffmann

By Erik T. Hoffmann

Non-linear research is a huge, interdisciplinary box characterized via a mix of research, topology, and purposes. Its suggestions and strategies give you the instruments for constructing extra reasonable and actual types for various phenomena encountered in fields starting from engineering and chemistry to economics and biology. This publication offers fresh and critical learn within the box.

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The first term of the right-hand side represents the decrease (per year) of the number of asymptomatically infected males, which is caused by the fact that asymptomatically infected males are cured by chance. By (6) we see that the last term of the right-hand side represents the number (per year) of males of j years old who become asymptomatically infected in a year i. ,43. ,43, (9) k= max{ j− F ,15} where af = af(i,j) is a nonnegative-valued function of i and j. From Assumption 2, we see that no person of 15 years old is infected asymptomatically.

Math. In: Progress in Nonlinear Analysis Research Editor: Erik T. Hoffmann, pp. 21-29 ISBN: 978-1-60456-359-7 © 2009 Nova Science Publishers, Inc. Chapter 2 A MATHEMATICAL-MODEL APPROACH TO CHLAMYDIAL INFECTION IN JAPAN Minoru Tabata1*, Toshitake Moriyama2, Satoru Motoyama2 and Nobuoki Eshima3 1 Department of Mathematical Sciences, Graduate School of Engineering / School of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, Japan 2 Department of Obstetrics and Gynecology, Kobe University, Graduate School of Medicine, Kobe 650-0017, Japan 3 Department of Statistics, Faculty of Medicine, Oita University, Oita 879-5593 Japan Abstract We construct an age-dependent mathematical epidemic model of chlamydial infection, which fits the demonstrative data accumulated by the STDs (sexually transmitted diseases) surveillance conducted by the Japanese Government.

We denote them by am = am(j) and af = af(j). ,44. The infection coefficients thus determined are described in Figs. 3-4, the initial data thus determined are described in Figs. 07. Applying these quantities to (8-12), we obtain Figs. ,2002 and Figs. 7-10. 28 Minoru Tabata, Toshitake Moriyama, Satoru Motoyama et al. Comparing Figs. 1-2 and Figs. , that the model fits the demonstrative data. Furthermore, from the numerical simulations of the model, we see that if the initial data, the infection coefficients, and the parameters leave the functions and the values that are obtained in Figs.