## Mathematical Aspects of Epidemiology

#### Call for Papers

Epidemiology is the study of the patterns, causes, and effects of health and disease conditions in defined populations. The use of computational tools such as mathematical modeling and computational simulation, as well as statistical analysis, is applied in this field for prediction of future behaviour of the problem under investigation.

Since then researchers have been making dynamical systems one of their primary examination tools in exploring epidemiological problems. By applying dynamical systems and using differential equations, epidemiologists show that malaria, gonorrhea, measles, and other contagious diseases could be controlled under some specific strategies.

A noncommunicable disease is a health condition or disease, which is by definition noninfectious and nontransmissible among people. Noninfectious diseases may be chronic diseases of long duration and slow development, or they may give rise to more rapid death such as some types of sudden stroke. They include autoimmune diseases, heart disease, stroke, many cancers, asthma, diabetes, chronic kidney disease, osteoporosis, Alzheimer's disease, and cataracts. Though occasionally (erroneously) mentioned as synonymous with chronic diseases, noninfectious diseases are differentiated only by their noninfectious cause, not necessarily by their duration.

In this special issue, we aim at inviting authors working on both infectious and noninfectious diseases to submit original research and review articles that seek to report and present the latest results in the theoretical and practical analyses of dynamical systems and articles that employ dynamical systems through mathematical modelling to describe and resolve medical/biological issues.

Potential topics include, but are not limited to:

• Modelling epidemiological problem with differential equations
• Modelling epidemiological problems with fractional differential equations
• Modelling neurological diseases from cellular and/or epidemiological perspectives
• Impact study of environmental changes on the transmission of vector-borne diseases
• Stability and bifurcation analyses on biological models of dynamical systems
• Computational methods (numerical simulation, parameter identification, and data fitting and optimization) in biological models of dynamical systems
• Stochastic methods in epidemiology
• Modeling noninfectious diseases with both integer and noninteger differential equations
 Manuscript Due Friday, 31 October 2014 First Round of Reviews Friday, 23 January 2015 Publication Date Friday, 20 March 2015

#### Lead Guest Editor

• Abdon Atangana, University of the Free State, Bloemfontein, South Africa