Research Nexus

CDC WONDER & GBD Workshop

Master Public Health Data Analysis with CDC WONDER & Institute for Health Metrics and Evaluation GBD Tools.

Why Choose CDC WONDER & GBD Workshop?

At Research Nexus, we offer a diverse range of programs designed to empower your research journey and align with your goals.

This course provides a practical introduction to public health data systems, focusing on CDC WONDER and the Global Burden of Disease (GBD) Study. Participants will learn how to extract, analyze, visualize, and interpret health data using modern research tools and basic R programming. The course also covers research development, scientific publication, and collaborative project work to help learners apply data-driven approaches in public health research and decision-making.

Module 1: Foundations of Public Health Data Systems

Introduction to Public Health Data Sources

  • Overview of CDC WONDER and GBD
  • Understanding their purpose, mission, and role in evidence-based decision-making

The Global Health Landscape

  • Key epidemiological measures:
    • Mortality
    • Morbidity
    • DALYs
    • YLLs
    • YLDs
  • How GBD and CDC WONDER complement each other for comprehensive analysis

Module 2: Navigating CDC WONDER

System Overview and Interface

  • Navigating the CDC WONDER platform
  • Understanding databases:
    • Mortality
    • Natality
    • Cancer incidence
    • Other public health datasets

Building and Refining Queries

  • Creating basic and advanced queries
  • Applying filters:
    • Age
    • Race
    • Gender
    • Location
    • Time period
  • Understanding and applying age-adjusted rates

Data Export and Management

  • Downloading datasets
  • Formatting data for:
    • Spreadsheets
    • Statistical software
    • Research analysis

Module 3: Understanding the Global Burden of Disease (GBD) Study

Introduction to the GBD Consortium

  • What is GBD?
  • Overview of the international research network
  • Understanding the collaborative framework
  • Introduction to the GBD modeling flowchart and methodology

GBD Metrics and Interpretation

  • Deep dive into:
    • DALYs
    • YLLs
    • YLDs
    • Risk factors
  • Analyzing:
    • Patterns
    • Disparities
    • Population trends
    • Sex-based and time-based comparisons

Becoming a GBD Collaborator

  • Registration and access to GBD resources
  • Understanding training requirements
  • Collaboration model and participation process

Module 4: Data Analysis & Visualization Tools

GBD Data Exploration

  • Hands-on training with the GBD Compare Tool
  • Using the GBD Results Tool for data extraction

CDC WONDER Visualization

  • Creating:
    • Charts
    • Tables
    • Maps
  • Best practices for public health data presentation

Introduction to R Programming for Health Data

  • Using R for CDC WONDER and GBD data analysis
  • Basic data manipulation
  • Data visualization and plotting in R

Module 5: From Analysis to Publication

Structuring Research Questions

  • Developing research questions using CDC WONDER and GBD datasets
  • Selecting meaningful and publishable topics

Targeting High-Impact Journals

  • Converting analyses into research manuscripts
  • Understanding journal requirements for database studies

Data Use Policies and Ethics

  • Citation requirements for public health databases
  • Ethical use of health data
  • Addressing data quality concerns and limitations

Module 6: Advanced Workshop & Team Project

Collaborative Research Project

  • Team-based research development
  • Extracting and analyzing data using CDC WONDER and GBD tools

Scheduling and Team Management

  • Task distribution among team members
  • Developing a work plan for timely manuscript submission

Presentation of Findings

  • Presenting results using data visualizations
  • Peer review and feedback sessions

Module 6: Advanced Workshop & Team Project

Collaborative Research Project

  • Team-based research development
  • Extracting and analyzing data using CDC WONDER and GBD tools

Scheduling and Team Management

  • Task distribution among team members
  • Developing a work plan for timely manuscript submission

Presentation of Findings

  • Presenting results using data visualizations
  • Peer review and feedback sessions