When: Wednesdays 4-5pm, Fall semester of each year Units: 1-2
This seminar will take the form of a weekly journal club, beginning with a review of some of the classic papers on infectious disease modeling – e.g. Daniel Bernoulli’s 1760 paper on the population-level benefits of universal smallpox inoculation – and moving on to some of the latest developments in the field – e.g. the role of genetic data in model development, and the use of individual-based models in informing disease control strategies. In light of the ongoing pandemic, a major focus will be on COVID-19 models. Additional examples will be drawn from HIV, Ebola, influenza, and mosquito-borne diseases such as malaria and Zika virus. The seminar will be discussion-based, and students with particular infectious diseases and methods of interest are encouraged to bring them to the instructor’s attention. The instructor will present the first two papers, after which class members will take turns leading the discussion.
Relation to other courses: This course is complementary to the activity-based PB HLTH 252B. This course surveys the literature in the field, providing context for the concepts raised in PB HLTH 252B, and extending these concepts by exploring the latest developments in the field.
Prerequisites: None Reading: A possible sequence of papers will be provided in the first week of class (see the course outline below for an example) and will be finalized in the second week of class depending on interests. Grading: 50% presentation of a paper, 50% participation in discussion
PB HLTH 252B: Modeling the dynamics of infectious disease processes
When: Mondays 2-5pm, Spring semester of each year Units: 3
The goal of this course is to lead students through the process of designing mathematical models of infectious diseases, fitting these models to data, and using them as public health tools to design effective control strategies. Examples are drawn from COVID-19, HIV, influenza, Ebola, and mosquito-borne diseases such as malaria and Zika virus. Each class consists of a lecture followed by a computer-based activity to apply the material. Students also work on a project in which they design their own model and use it to answer a specific research question. Deep mathematical knowledge is not required as the goal of the course is to teach modeling skills to epidemiologists; however, students should be able to write and interpret ordinary differential equations, and to manipulate code in R. A modeling program called Berkeley Madonna will also be used to code differential equations and will be taught in-class.
Prerequisites: Familiarity with ordinary differential equations and programming in R Textbook:An Introduction to Infectious Disease Modelling by Emilia Vynnycky & Richard White. Additional material will be uploaded to the course website weekly. Software:R, Berkeley Madonna, Excel Grading: 20% weekly activities, 30% midterm project presentation and report, 50% final project presentation and report