Day 1 (January 4, 2022)
- Introductions and course overview
- Lecture: The art of modeling
- Lecture: Modeling pragmatics and practicalities
Day 2 (January 11, 2022)
- Lecture: Deterministic compartmental models
- Exercise: Numerical solution of deterministic epidemiological models
Day 3 (January 18, 2022)
Assigned reading: Drake, J.M. et al. 2021. Five approaches to the suppression of SARS-CoV-2 without intensive social distancing. Proceedings of the Royal Society, Series B 288:20203074. Supplement (please read at least the first three pages of the supplement).
Day 4 (February 1, 2022)
- Lecture: Stochastic compartmental models
- Exercise: Numerical solution of stochastic epidemiological models
Day 5 (February 8, 2022)
Day 6 (February 15, 2022)
Day 7 (February 22, 2022)
- Lecture: Model calibration II: estimation by maximum likelihood
- Exercise: Likelihood estimation
Day 8 (March 3, 2022)
Day 9 (March 10, 2022)
Day 10 (March 17, 2022)
Suggested readings (case studies)
- Anonymous. 1978. Influenza in a boarding school. British Medical Journal 1:587.
- Blower, S.M., H. B. Gershengorn, R.M. 2000. A tale of two futures: HIV and antiretroviral therapy in San Francisco. Science 287:650-654.
- Grais, R.F., M.J. Ferrari, C. Dubray, O.N. Bjornstad, B.T. Grenfell, A. Djibo, F. Fermon, P.J. Guerin. 2006. Estimating transmission intensity for a measles epidemic in Niamey, Niger: Lessons for intervention. Transactions of the Royal Society of Tropical Medicine and Hygiene 100:867-873.
- Legrand, J., R.F. Grais, P.Y. Boelle, A.J. Valleron, & A. Flahault. 2007. Understanding the dynamics of Ebola epidemics. Epidemiology & Infection 135:610-621.
- McCabe, R. et al. 2021. Communicating uncertainty in epidemic models. Epidemics 37:100520.
- Park, A.W., J.M. Daly, N.S. Lewis, D.J. Smith, J.L.N. Wood, B.T. Grenfell. 2009. Quantifying the impact of immune escape on transmission dynamics of influenza. Science 326:726-728.
- Pitzer, V.E. et al. 2012. Direct and indirect effects of rotavirus vaccination: Comparing predictions from transmission dynamic models. PLOS One 7(8): e42320.
- Read, J., Lessler, J., Riley, S., Wang, S., Tan, L.J., Kwok, K.O., et al. 2014. Social mixing patterns in rural and urban areas of southern China. Proceedings of the Royal Society B: Biological Sciences 281:20140268.
- Rohani, P., Zhong, X., & King, A. A. 2010. Contact network structure explains the changing epidemiology of pertussis. Science 330:982–985.
- Schenzle, D. 1984. An age-structured model of pre- and post-vaccination measles transmissiont. IMA Journal of Mathematics Applied in Medicine and Biology 1:169–191.
Suggested readings (modeling)
- Keeling, M.J. & P. Rohani. 2007. Modeling infectious diseases in humans and animals. Princeton University Press.
- Vynnyky, E., & R. White. 2010. An introduction to infectious disease modelling. Oxford University Press.
- Heesterbeek, J. A. P., & Roberts, M. G. 2007. The type-reproduction number T in models for infectious disease control. Mathematical Biosciences 206(1):3–10.
- Diekmann, O., Heesterbeek, J. A. P., & Roberts, M. G. 2009. The construction of next-generation matrices for compartmental epidemic models. Journal of the Royal Society Interface 7:873–885.
- Heffernan, J.M., R.J. Smith & L. Wahl. 2005. Perspectives on the basic reproductive ratio. Journal of the Royal Society Interface 2:281-293.
- van den Driessche, P. & J. Watmough. 2002. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical Biosciences 180:29-48.
Suggested readings (R programming)
- Crawley, M.J. 2007. The R book. Wiley.
- Matloff, N. 2011. The Art of R Programming. No Starch Press.
- Venables, W.N., & B.D Ripley. 2002. Modern Applied Statistics with S. 4th edition. Springer.
- Jones, O., R. Maillardet, & A. Robinson. 2014. Introduction to scientific programming and simulation with R. Second edition. Chapman & Hall.
- Wickham, H. & G. Grolemund. 2016. R for Data Science. O’Reilly.