CDC WONDER : FROM DATABASE TO HIGH IMPACT FACTOR JOURNAL

Name: CDC WONDER : FROM DATABASE TO HIGH IMPACT FACTOR JOURNAL
Rating: 5.0 (2 reviews)

A Step-by-Step Mentored Approach to Converting Public Health Data to Impact Factor Publication

Created bySumia Fatima

Last updated 9/2025

English

What you'll learn

Understand and navigate the CDC WONDER interface to efficiently locate and access various public health datasets
Formulate and execute basic and advanced queries within CDC WONDER to extract specific health-related data.
Interpret and critically analyze the results generated from CDC WONDER queries, identifying key trends, patterns, and disparities in public health data.
Communicate findings effectively by summarizing and presenting CDC WONDER data analysis in high impact factor journals

Course content

6 sections • 15 lectures • 2h 22m total length

Introduction14:56
Explore the CDC Wonder analysis database to analyze mortality data, identify underlying, contributing, and multiple causes of death, and apply age-adjusted rates and ICD-10 codes for robust public health insights.
Exploring the CDC Wonder Analysis Database9:28
Explore the CDC Wonder analysis database to analyze mortality data using multiple and underlying causes, and learn data extraction across variables for topics such as atrial fibrillation and cardiac arrest.

Data Extraction (Overall, Gender. Age Groups and Places of Death)16:24
Learn to extract and clean CDC Wonder data for overall mortality, gender, age groups, and places of death (1999 to 2020), including provisional data, and export results to Excel.
Data Extraction (Race/Ethnicity and Geographical Locations)14:26
Extract and clean race and ethnicity mortality data from CDC WONDER, handling five racial groups, Hispanic origin, states, regions, and urban-rural classifications across 2021–2023 and provisional 2023 data.

Analysis Using Join Point Part 111:06
Analyze gender‑based age‑adjusted mortality trends from 1999 to 2020 using joinpoint, identifying significant changes via annual percentage changes. Prepare clean data, generate graphs, and export trend tables for reporting.
Analysis Using Join Point Part 27:18
Analyze percentile concepts and calculations for state-level age-adjusted mortality rates, identify 90th and 10th percentile states using a percentile calculator, and learn CDC Wonder result reporting.

Graphs12:54
Learn to build figures from CDC Wonder data, focusing on gender and age-adjusted mortality across years. Create line and pie charts, refine titles, and export figures for publication.
Central Illustration3:58
Learn how central illustrations capture gender data, age group, racial, metro and state data using templates, Canva figures, and uploaded visuals to boost publication potential.
Tables7:09
Learn to build tables from supplied templates, paste age-adjusted mortality rates data with upper and lower confidence intervals, and create separate figures for 1999–2020 and 2021–2023, following journal standards.

Methadology7:19
Explore the CDC wonder based methodology for descriptive death certificate analyses of heart failure from 1999 to 2020, detailing ICD codes, ethics, references, and joint point statistics.
Introduction and Discussion6:52
Explore how to write CDC Wonder analysis introductions and discussions, focusing on US and global trends, linking diseases, and presenting rationale, data, and limitations for high-impact journals.
Introduction and Discussion - Hands On9:32
Explore crafting a comprehensive abstract and introduction for public health articles, analyze aging and heart failure mortality in the US, and design a rigorous discussion to elevate journal impact.
Journal Selection11:48
Discover strategies to select journals by category and indexing, avoid predatory outlets, and target PubMed or Scopus indexed journals with suitable impact factors.
Submission into Journal6:32
Learn how to submit a manuscript to a medical journal, including pre-submission checks, selecting article type and reviewers, uploading title page and highlights, managing disclosures, ethical approvals, and ORCID IDs.

Requirements

No previous research experience required. You will learn everything you need to know

Description

Are you a public health professional, student, or researcher who wants to use real-world data to drive your work, but feels overwhelmed by the CDC WONDER database? Do you need to conduct a public health analysis for a paper, project, or presentation, but don't know where to start?

This course is your roadmap.

Welcome to the CDC Wonder Analysis Mentorship Course, a unique program designed to transform you from a beginner into a confident public health data analyst. This isn't a simple tutorial; it's a mentorship experience that will provide you with the practical skills and personal guidance to navigate the powerful CDC WONDER system and turn raw data into actionable insights.

What You'll Learn: A Practical, Mentored Approach

Over the course of this program, you will gain hands-on expertise in using the CDC WONDER platform. We will move beyond the basic tutorials and show you how to:

Navigate the CDC WONDER Database: Learn to efficiently select and use the right datasets (e.g., mortality, natality, cancer incidence) for your specific research questions.
Build & Refine Queries: Master the art of building complex queries to extract the exact data you need, filtering by age, race, gender, location, and time period.
Perform In-Depth Data Analysis: Discover how to calculate key epidemiological measures like crude and age-adjusted death rates, and confidently interpret your results.
Visualize and Present Your Findings: Turn your data into clear and compelling charts, tables, and maps that effectively communicate your research to any audience.

Why a Mentorship Program?

The CDC WONDER database can be complex. This course is designed as a mentorship program to provide you with the structure and support to overcome common challenges. You'll work through guided exercises, learn from real-world examples, and receive expert insights that will build your confidence and make you a more effective researcher.

Who is this course for?

This program is perfect for:

Public Health Students: Those working on capstone projects, theses, or research papers who need to use a robust public health database.
Epidemiology and Biostatistics Students: Anyone needing to apply theoretical knowledge to real-world data analysis.
Healthcare Professionals: Clinicians, hospital administrators, or public health practitioners who want to use data to inform decision-making and improve health outcomes.
Aspiring Researchers: Anyone who wants to build their research skills and create a portfolio of data analysis projects.

Ready to unlock the power of public health data?

Join me today and start your journey to becoming a skilled and confident data analyst using CDC WONDER.

Who this course is for:

Healthcare Professionals (Doctors, Nurses, Pharmacists, Allied Health Professionals)
Junior and Mid-Career Clinicians
Quality Improvement Leads and Managers
Trainees and Students

CDC WONDER : FROM DATABASE TO HIGH IMPACT FACTOR JOURNAL

What you'll learn

Explore related topics

Course content

Introduction2 lectures • 24min

Data Extraction2 lectures • 31min

Data Analysis2 lectures • 18min

Graphs, Tables and Central Illustration3 lectures • 24min

Manuscript Writing5 lectures • 42min

Special Lecture1 lecture • 2min

Requirements

Description

Who this course is for: