Data Science in Infectious Disease Modeling using R

Online Lab Meeting Times:

• Monday, July 7, 1:00 - 2:30 PM ET and 3:00 - 4:30 PM ET
• Tuesday July 8, 1:00 - 2:30 PM ET and 3:00 - 4:30 PM ET

Classroom: Virtual

Module Summary:

This course will foster a problem solving mindset while exploring more advanced concepts in R and is ideal for someone who has some familiarity with R (base and Tidyverse). There are multiple approaches to coding an analysis; contents covered in this course will serve as a guide to help you decide which approach is best for your particular situation.  

The course will draw concepts from R for Data Science, Advanced R, and R for Epidemiology books along with the instructors’ experiences with infectious disease modeling.  We will work in both base R and the tidyverse to wrangle messy data and build analytic workflows.  

Prerequisites:

Familiarity with R base and Tidyverse, including:

• R Studio/Post Studio
• R Markdown
• Pipes

Module Content:

This course will consist of 3 themes:

1. Foundations in data science that are not often covered in an Intro R programming course.
2. Advanced data wrangling tailored to different types of public health data.
3. Special considerations for SISMID and public health data.

Asynchronous content: 

1. Foundation Theme

2. Problem solving using advanced data wrangling

3. Advanced Coding Methods

4. Special considerations 

Synchronous content:

1. Foundations

2. Working with public health survey data

3. Working with simulation/time series data

4. Working with line list/PII data