Welcome!
Welcome to our project on modeling pneumococcal disease, a leading cause of death in children under 5 worldwide. Public health is an interdisciplinary field that measures and tracks disease trends and promotes health through policy and treatment interventions. We will investigate the impact of pneumococcal vaccines and the phenomenon of serotype replacement, where uncommon serotypes variations not targeted by the therapy flourish and take over as the predominant causes of disease after vaccination. Using data from infectious disease surveillance systems and statistical methods such as time series analysis, hierarchical modeling, and serotype clustering and association, we aim to understand serotype replacement and its implications. Our analyses will be conducted in R.
Our objectives for this course will be to:
- Characterize and contextualize pneumococcal serotype replacement in several global populations.
- Explore the implications of different vaccine programs on the serotype distribution of invasive pneumococcal disease.
- Discuss biological, epidemiological, and policy choices that can contribute to our understanding of serotype replacement and pneumococcal evolution.
We will accomplish these objectives using data from national and multinational infectious disease surveillance systems, and the following statistical methods:
- Time series analysis
- Hierarchical modeling
- Sequence clustering with the Global Pneumococcal Sequencing (GPS) project analysis pipeline
- Association detection Market Basket
Purpose of This Site
Sharing code-based materials poses a challenging technical problem that Canvas is not well suited to handle. Therefore, we have created an instructor GitHub webpage where we can effectively create, communicate, and distribute course materials. This platform provides students with the most current information in an easily accessible format and allows us, the instructors, to distribute materials more efficiently.
On this site, you will find:
- A schedule of important project goals and assignment dates.
- Webpages with full weekly hands-on demonstrations of concepts.
- Weekly codebases for students to apply in their own projects, reflecting that week’s concepts.
- Links to the subgroup dataset zip files, the associated paper, and brief descriptions of them.
- Links to other course materials, including blank slide decks, poster layouts, slides, and more.
About the Instructors
Stephanie Perniciaro, PhD, MPH
Associate Research Scientist in Epidemiology (Microbial Diseases)
The surveillance and epidemiology of vaccine-preventable respiratory diseases, especially pneumococcal disease, is my passion. I want to determine how to efficiently and effectively protect populations from pneumococcal disease, both invasive (bacteremia, meningitis) and non-invasive (otitis media, non-bacteremic pneumonia). I'm interested in respiratory disease surveillance, serotype replacement, antibiotic resistance, vulnerable populations, vaccine schedules, vaccine advocacy, and overcoming vaccine hesitancy.
Shelby Golden, MS
Data Scientist I
With my work I aim to contribute to impactful projects that advance scientific understanding by utilizing strong analytical skills and a deep commitment to reliable data-driven decision-making.
My background is in computational mathematics, molecular biology, and biochemistry. I hold a Master of Science in Applied Computational Mathematics from Johns Hopkins University and dual Bachelor of Science degrees in Molecular, Cellular, Developmental Biology and Biochemistry, alongside a minor in Engineering in Applied Mathematics from the University of Colorado at Boulder.