Course Description
Computational and mathematical methods for building and analyzing models of infectious diseases. Population-level processes for a range of infectious diseases of humans, wildlife, and livestock will be studied incorporating a variety of transmission mechanisms. Within-host processes will also be addressed.
Athena Title
Modeling Infectious Diseases
Equivalent Courses
Not open to students with credit in EPID 8515E, ECOL 8515E, IDIS 8515E
Prerequisite
EPID 7010 or EPID 7010E or ECOL 4000/6000 or permission of department
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Course Objectives
Knowledge Students will be exposed to the major processes involved in a variety of infectious diseases. They will learn a broad range of basic mathematical and computational methodologies for modeling infectious diseases. They will be able to recognize key parameters in a variety of models and give their meaning. They will be able to derive some basic important results in the theory of infectious disease transmission. Comprehension Students will understand how key processes such as transmission, recovery and waning immunity operate. They will be able to articulate the steps required to formulate a mathematical model. They will interpret biological problems as simple mathematical and computational models. Application Students will develop ideas and concepts introduced in lectures to practical examples through instructional computer lab sessions. They will be able to modify basic models to add more realism or to apply it to a different biological problem. Analysis Students will learn to break down large-scale infectious disease observations into component processes and will understand how important concepts in infectious disease modeling are manifested in real situations. They will be able to correct basic computer programs so that they work as intended. They will be able to distinguish between infectious disease theory and inference from data. They will be able to interpret the results of models in a biological context. Synthesis Students will appreciate the progression of ideas that has led to the modern field of infectious disease modeling. They will be able to combine component processes, relevant to infectious diseases, into single models that can explain infectious disease progression in populations. Students will learn the value of considering several infectious diseases together to ask broader questions about why they affect populations differently. Evaluation Students will learn the usefulness and assumptions of different types of mathematical and computational models in infectious disease studies. They will also be able to critically read and evaluate mathematical modeling studies of infectious diseases that are published in primary research journals. Students will be able to discriminate between good and bad models and will be able to discern what type of data sets can best be used with models to answer research questions.
Topical Outline
1. Introduction to the topic 2. Introduction to R 3. Mathematical refresher 4. The basics: Simple compartmental models 5. Different forms of transmission (frequency-dependent & density-dependent) 6. The latent period; acquired & waning immunity 7. Stochastic models 8. Within-host models 9. Herd immunity & vaccination strategies 10. Parasite evolution I: transmission-virulence trade- offs; increase of virulence due to vaccines 11. Parasite evolution II: emergence of drug resistance and vaccine escape mutants 12. Critical community sizes & disease 'fade-outs' 13. Spatial models (the rescue effect, synchrony) 14. Network models applied to STDs 15. Regulation of wildlife by infectious diseases 16. Macro-parasite models 17. Vector-borne diseases 18. Fitting models to (and estimating parameters from) data 19. Uncertainty and sensitivity analysis 20. Multi-pathogen/multi-host systems