The world has been faced with many health issues from the beginning. Mathematical and statistical modeling has been an efficient method for the control of these issues. Modeling in this area is improving rapidly due to their significant effect and results. The importance of modeling is that it allows researchers to apply their mathematical and statistical theories to real-life problems.

Infectious diseases caused by viruses and cancer are the leading causes of the increase in mortality rates every year. People all around the world encounter crucial challenges because of these health issues. In recent years, researchers have been developing new methods for the analysis of these issues with the basis of Ordinary Differential Equations (ODE), Partial Differential Equations (PDE), Fractional Differential Equations (FDE), Stochastic Differential Equations (SDE), etc. Mathematical and statistical modeling of the evolution of diseases enables the researchers to find out the underlying reason(s) of the progress of health problems. As a result, models demonstrate the reasons so that they can improve the diagnosis, control, and treatment of diseases. Furthermore, because of the huge range of the field and health problems, many questions are still open and need to be discussed and analyzed.

This Special Issue focuses on demonstrating cutting-edge mathematical and statistical modeling in health sciences, as well as epidemiology and methods of analyzing them. We invite authors to contribute interdisciplinary papers in mathematical and statistical modeling. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• ODE (Ordinary Differential Equations) modeling of infectious diseases
• ODE (Ordinary Differential Equations) modeling of cancer
• FDE (Fractional Differential Equations) modeling of infectious diseases
• FDE (Fractional Differential Equations) modeling of cancer
• PDE (Partial Differential Equations) modeling of infectious diseases
• PDE (Partial Differential Equations) modeling of cancer
• Statistical modeling of infectious diseases
• Statistical modeling of cancer
• Statistical analysis
• Numerical simulations
• Statistical data analysis in health sciences
• Statistical analysis of generic problems arising when considering the scarcity of data/high variability/great diversity of the modeled variables