Course Information

  • Instructor: Andreas Handel
  • Office Location: 124 B.S. Miller Hall, Health Sciences Campus
  • Email:
  • Office Hours: by appointment/online
  • Course Meeting Time and Location: online, see Schedule document for details

Course Material

All materials used in this course are freely available online. You will be able to access all materials from this website.

Course Description

This course provides an introduction to infectious disease epidemiology using a model-based approach. We will use simulation models to understand the dynamics of transmission and spread of infectious diseases. You do not have to (but could) build models or write computer code as part of this course.

Course Learning Objectives

The specific learning objectives that I hope you will achieve by going through this course are:

  • Explain and compute important epidemiological measures, such as reproductive number and level of herd immunity

  • Appraise the fundamentally causal nature of mechanistic infectious disease (ID) computer models and master the use of such models to address important ID epidemiology research questions

  • Interpret the meaning of specific dynamic patterns seen in ID incidence and prevalence

  • Choose optimal ID intervention strategies based on features of specific IDs

  • Predict the impact of different ID intervention strategies

  • Critically evaluate the ID epidemiology literature

  • Compare and assess the strengths and weaknesses of different ID data collection and analysis approaches

  • Formulate meaningful ID epidemiology research questions of public health importance

  • Select the appropriate data collection and analysis approach for a specific ID research question

  • Explain the importance of system dynamical thinking for the study and control of ID


Please see the Course Introduction document for details regarding grading.

Class Attendance, Make-up Policy

This class is online. There are no synchronous events you are required to attend. You are expected to submit all assignments by their due dates. Excused misses of due dates are only provided by prior agreement with the instructor or for special reasons (e.g. medical emergency).


This is a quantitative course. We will not go deep into the mathematical details of infectious disease models, you will not need to build models or write computer code. However some statistical background and being comfortable with quantitative thinking are useful. Formal requirement for the course is BIOS 7010. If you didn’t take this course, please contact me to get permission to enroll.

Getting Help

If you have questions about any aspect of the course, please do not hesitate to ask for help. The course materials describe in detail the ways you can ask for help. See the Communication section for more details.

University Honor Code and Academic Honesty Policy

All academic work must meet the standards contained in A Culture of Honesty. All students are responsible to inform themselves about those standards before performing any academic work. More detailed information about academic honesty can be found at:

Discussions with your classmates and the instructor are encouraged. However, the final work should be your own.

Students with Disabilities

Students with disabilities who require reasonable accommodations in order to participate in course activities or meet course requirements should contact the instructor.

General Disclaimers

This syllabus is a general plan, deviations announced to the class by the instructor may be necessary.

Course Outline

For an outline of the course, please see the Schedule document.

More Details

The introductory unit of this course contains all the logistic details you need to know.

COVID-19 information

Since this is an online course, the hope is that COVID-19 will not affect things too much. I consider any COVID-19 related issues that might prevent you from submitting your work by the indicated deadlines to be the same as any other possible medical emergency. Just let me know and we’ll work things out.

In general, you are expected to follow all UGA rules regarding COVID-19. See UGA’s COVID-19 resource page for all relevant information: