R Tools for Rapid Outbreak Analytics

Online Lab Meeting Times:

• Thursday July 10, 1:00 - 2:30 PM ET and 3:00 - 4:30 PM ET
• Friday July 11, 1:00 - 2:30 PM ET and 3:00 - 4:30 PM ET

Classroom: Virtual

Module Summary:

Applied analyses for use during disease outbreak have different requirements than research-driven analyses.  This module provides an introduction to tools and workflows for producing rapid analyses and reports in the early stages of disease outbreak response.  We will use a case-study approach to familiarize learners with the set of tools and practices available for rapid analyses, drawing primarily on the R packages developed by the Epiverse initiative and the R Epidemics Consortium.  Topics will include: producing and handling line-list data, making estimates of disease  incidence, reproduction numbers, and other actionable parameters,  nowcasting and short-term forecasting.  We will discuss of best practices for producing reports in policy-relevant situations and under resource and time pressure.  

Prerequisites:

Participants are expected to have a basic understanding of R, including basic tidyverse workflows, how to open and write R scripts, read in data, and use basic functions and syntax in RStudio.  Participants are also expected to have prior knowledge of basic descriptive statistics and epidemiological modeling concepts.

Module Content:

• Overview of the toolbox for rapid outbreak analytics
• Selecting the right tool for purpose
• Common tasks, data types,  and workflows in outbreak response
• Generating, aggregating, cleaning line-list data 
• Working with missing data and reporting delays
• Rapid incidence and reproduction estimates: methods, purpose, and implementation
• Short-term forecasting and nowcasting: methods, purpose, and implementation
• Setting up an environment for rapid, reproducible workflows and reporting
• Best practices for useful and impactful reporting
• Linking to communities of practice