Pathogen Genomics for Epidemiology: Interpretation
- Continuing Education
Start Today Register and begin immediately.
Learn how to interpret pathogen genomic data to meaningfully inform epidemiological investigations and public health action.
- Online; Self-Paced
This course is offered on demand and participants progress through the materials at their own pace.
Free
Continuing Education
This course does not offer CME Credits.
1 Hour
On This Page
Overview
Pathogen Genomics for Epidemiology: Interpretation focuses on making sense of genomic data for public health decision‑making, including pathogen characterization, surveillance, and outbreak investigations.
The first section introduces common genomic representations of genomic data—including database comparisons, time‑series plots, distance matrices, network diagrams, and phylogenetic trees—clarifying what each represents, how it is used in epidemiologic investigations, and key considerations for use and interpretation.
The second section examines factors that shape patterns observed in genomic data. You will consider how pathogen biology, mutation rate, and replication opportunity influence expected genomic differences, and how sampling frameworks, sequence quality, and the choice of contextual sequences affect the signals you see. Through realistic outbreak and surveillance scenarios, you will practice integrating genomic findings with epidemiologic and other contextual information, moving beyond fixed cutoffs toward more nuanced, question-driven interpretations.
Key concepts are presented in brief, accessible video segments, with knowledge checks throughout to help you test your understanding and apply your learning. Emphasizing core principles over rigid rules, this course prepares epidemiologists to interpret pathogen genomic data thoughtfully and to integrate genomic evidence into public health practice.
Learning Objectives
- Describe how pathogen genomic data are used in public health and how they help identify features like antimicrobial resistance and mutation patterns, whilst also recognizing key limitations of these data.
- Explain how common genomic outputs (such as time-series plots, genome maps, distance matrices, networks, and phylogenetic trees) are used in surveillance and outbreak investigations, and interpret what they can reveal about transmission.
- Recognize how factors like sampling approach, sequence quality, and available epidemiologic and clinical data affect the interpretation of genomic findings and the strength of conclusions that can be drawn.
- Apply an integrated understanding of pathogen biology, genomic data, and epidemiologic context to interpret genomic results in a variety of public health investigation scenarios.
Who Should Participate?
Pathogen Genomics for Epidemiology: Interpretation is recommended for anyone who uses or interprets pathogen genomic data for public health applications.
Completion of Foundations I: Conceptual Foundations of Pathogen Genomics and Foundations II: Technical Introduction to Pathogen Genomic Epidemiology: Mutations, Transmission, and Phylogenetics is recommended before taking this course and subsequent courses in this program.
Learners seeking to complete the “Pathogen Genomics for Epidemiology” track should complete several courses prior to this one: Foundations I, Foundations II, and Sequencing Strategies for Pathogen Genomics.
Course topics
Course Introduction
- Beyond the Outbreak: Using Pathogen Genomics for Starbacter Surveillance in Robinwood
Common Genomic Outputs in Epidemiological Investigations
- Section Introduction: Common Genomic Outputs
- Pathogen Characterization: Database Matching, Gene Presence or Absence, and Genome Maps
- Genomic Surveillance: Time-Series Plots and Population-Level Genome Maps
- Outbreak Investigation: Distance Matrices and Network Diagrams
- Outbreak Investigation: Phylogenetic Trees
Factors Shaping Genomic Data Interpretation
- Section Introduction: Factors Shaping Genomic Data Interpretation
- How Pathogen Biology Shapes Genomic Divergence
- How Dataset Composition Influences Observed Patterns
- Weighing Genomic and Epidemiological Evidence Together
Acknowledgments
These courses were developed under the U.S. Pathogen Genomics Centers of Excellence (PGCoE), and supported by the Office of Advanced Molecular Detection, U.S. Centers for Disease Control and Prevention (CDC) through Cooperative Agreement Number CK22-2204. Contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention. View Full Acknowledgments
Course Directors
- Molecular Epidemiologist, Central Region Genomic Epidemiology Training Lead Bureau of Epidemiology and Public Health Informatics, Kansas Department of Health and Environment
Bronwyn MacInnis
PhD
- Director, Pathogen Genomic Surveillance Institute Scientist, Broad Institute of MIT and Harvard
This course is non-accredited.
Note: Physicians may be able to self-claim AMA PRA Category 2 Credit™ for participation in activities not certified for AMA PRA Category 1 Credit™. AMA Category 2 Credit™ is self-designated by physicians for learning that meets the AMA definition of CME and ethical standards, and is relevant and worthwhile to their practice. Examples of activities that may qualify include teaching, peer discussions, reading medical literature, research, writing, and quality improvement work. Physicians must decide for themselves whether this course qualifies for AMA PRA Category 2 Credit™. Additional information from the AMA regarding AMA PRA Category 2 Credit™ can be found here: What to know about the other kind of CME credit.