Fitting Epidemic Models to Data: A Tutorial in Memory of Fred Brauer.

Area of Science:

• Mathematical epidemiology
• Dynamical systems theory
• Computational statistics

Background:

• Fred Brauer, a mathematician, contributed to dynamical systems and mathematical epidemiology.
• He recognized the need for fitting models to data in infectious disease transmission but avoided data analysis.
• This led to the development of the fitode R package to address this gap.

Purpose of the Study:

• To introduce the user-friendly R package, fitode.
• To provide a tutorial on fitting compartmental epidemic models to observed time series data.
• To assist readers with a background in dynamical systems but limited statistical experience.

Main Methods:

• Development of the fitode R package for fitting ordinary differential equations to time series.
• Application of the package to demonstrate fitting compartmental epidemic models.
• Utilizing a user-friendly interface for data analysis.

Main Results:

• The fitode package successfully facilitates the fitting of dynamical models to time series data.
• The tutorial demonstrates a practical approach to applying epidemic models.
• The package simplifies complex data analysis tasks for users with a mathematical background.

Conclusions:

• The fitode R package is a valuable tool for fitting dynamical models, particularly in mathematical epidemiology.
• It bridges the gap between theoretical dynamical systems and practical data analysis in public health.
• The package empowers researchers to apply infectious disease models to real-world data more effectively.