COVID-19 Genomic Epidemiology Toolkit

The Office of Advanced Molecular Detection presents this toolkit to address topics related to the application of genomics to epidemiologic investigations and public health response to SARS-CoV-2. The COVID-19 Genomic Epidemiology Toolkit is meant to further the use of genomics in responding to COVID-19 at the state and local level.

Each module includes a dedicated survey to inform future training development. We value your input.

Meet the Toolkit Developers
toolkit shape with words COVID-19 Genomic Epidemiology Toolkit
toolkit shape with words COVID-19 Genomic Epidemiology Toolkit

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More modules and materials will be added to this toolkit, so please check back for updates or subscribe to the mailing list.

Welcome and Overview

CDC’s Dr. Greg Armstrong gives an introduction to the COVID-19 Genomic Epidemiology Toolkit and describes the role for genome sequencing in public health.

Presenter: Gregory L. Armstrong, MD
Director, Advanced Molecular Detection Program,  CDC

ToolkitModule_0 pdf icon[PDF – 15 slides]

Part 1: Introduction
Module 1.1 - What is genomic epidemiology?

This module provides an introduction to genomic epidemiology, with specific reference to SARS-CoV-2 sequencing for epidemiologic investigations.

Presenter: Nancy Chow, PhD
Bioinformatics and Informatics Lead, CDC

ToolkitModule_1.1 pdf icon[PDF – 23 slides]

Take the Feedback Survey for Module 1.1

Further Reading

  1. Pathogen Genomics in Public Health. Armstrong et al. 2019 NEJM. www.ncbi.nlm.nih.gov/pmc/articles/PMC7008580/external icon
  2. Towards a genomics-informed, real-time, global pathogen surveillance systemGardy and Loman. 2017 Nat Rev Genomics. www.ncbi.nlm.nih.gov/pmc/articles/PMC7097748/external icon

Resources

  1. Scientists have a powerful new tool for controlling the coronavirus: Its own genetic code. Washington Post, 2020. www.washingtonpost.com/graphics/2020/health/coronavirus-genetic-code/external icon
Module 1.2 - The SARS-CoV-2 genome

This module describes the basics of microbial genomes, with specific refence to the SARS-CoV-2 genome.

Presenter: Shatavia S. Morrison, PhD​
Bioinformatics Unit Lead​, CDC

ToolkitModule_1.2 pdf icon[PDF – 15 slides]

Take the Feedback Survey for Module 1.2

Further Reading

  1. How Coronavirus Mutates and Spreads. New York Times, 2020. www.nytimes.com/interactive/2020/04/30/science/coronavirus-mutations.htmlexternal icon
  2. SARS-CoV-2 Sequencing Data: The Devil is in the Genomic Details. Hemarajata 2020 ASM.org asm.org/Articles/2020/October/SARS-CoV-2-Sequencing-Data-The-Devil-Is-in-the-Genexternal icon
  3. Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020. Alm et al. 2020 Euro Surveill. www.ncbi.nlm.nih.gov/pmc/articles/PMC7427299/external icon

Resources

  1. SARS-CoV-2 Sequencing ResourcesGithub.com/CDCgov. github.com/CDCgov/SARS-CoV-2_Sequencingexternal icon
Module 1.3 - How to read a phylogenetic tree

This module describes the anatomy of phylogenetic trees and how to interpret them in the context of transmission.

Presenter: Michael Weigand, PhD​
Bioinformatician, CDC

ToolkitModule_1.3 pdf icon[PDF – 28 slides]

Take the Feedback Survey for Module 1.3

Further Reading

  1. How to read a phylogenetic tree. ARTIC Network. artic.network/how-to-read-a-tree.htmlexternal icon
  2. Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California. Deng et al. 2020 Science. www.ncbi.nlm.nih.gov/pmc/articles/PMC7286545/external icon
  3. Rapid SARS-CoV-2 whole-genome sequencing and analysis for informed public health decision-making in the NetherlandsMunnink et al. 2020 Nature Medicine. www.nature.com/articles/s41591-020-0997-yexternal icon
  4. Cryptic transmission revealed by genomic epidemiology. Trevor Bedford 2020. bedford.io/blog/ncov-cryptic-transmission/external icon

Resources

  1. How to interpret phylogenetic trees. Nextstrain.org. nextstrain.org/narratives/trees-backgroundexternal icon 
  2. Genomic epidemiology playbook — a primer on uses and interpretation. Sidney Bell. Nextstrain.org. nextstrain.org/community/narratives/czbiohub/covidtracker/pawnee-interpretation-examplesexternal icon
Module 1.4 - Emerging variants of SARS-CoV-2

This module introduces basic concepts relevant to the emergence of new SARS-CoV-2 variants and the role of sequencing in their detection and definition.

Presenter: Michael Weigand, PhD​
Bioinformatician, CDC

ToolkitModule_1.4 pdf icon[PDF – 975 KB]

Take the Feedback Survey for Module 1.4

Further Reading

  1. The coronavirus is evolving before our eyes. The Atlantic, 2021. www.theatlantic.com/health/archive/2021/01/coronavirus-mutations-variants/617694/external icon
  2. Coronavirus variants and mutations. New York Times, 2021. www.nytimes.com/interactive/2021/health/coronavirus-variant-tracker.htmlexternal icon
  3. Emergence and spread of a SARS-CoV-2 variant through Europe in the summer of 2020. Hodcroft et al. 2020 MedRxiv. www.medrxiv.org/content/10.1101/2020.10.25.20219063v2external icon
  4. Tracking changes in SARS-CoV-2 spike: evidence that D614G increases infectivity of the COVID-19 virus. Korber et al. 2021 Cell. www.sciencedirect.com/science/article/pii/S0092867420308205external icon
  5. Preliminary genomic characterisation of an emergent SARS-CoV-2 lineage in the UK defined by a novel set of spike mutations. Rambaut et al. 2020 Virological. www.virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563external icon
  6. Genomic epidemiology identifies emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States. Washington et al. 2021 MedRxiv. www.medrxiv.org/content/10.1101/2021.02.06.21251159v1external icon
  7. Emergence of SARS-CoV-2 B.1.1.7 lineage — United States, December 29, 2020–January 12, 2021. Galloway et al. 2021 MMWR. www.cdc.gov/mmwr/volumes/70/wr/mm7003e2.htm

Resources

  1. About variants of the virus that causes COVID-19​​. www.cdc.gov/coronavirus/2019-ncov/transmission/variant.html
  2. Genomic surveillance for SARS-CoV-2 variants. www.cdc.gov/coronavirus/2019-ncov/cases-updates/variant-surveillance.html
  3. Why S-gene sequencing is key for SARS-CoV-2 surveillance. ThermoFisher. www.thermofisher.com/blog/behindthebench/why-s-gene-sequencing-is-key-for-sars-cov-2-surveillance/external icon
  4. PANGO lineage global reports. cov-lineages.org/global_report.htmlexternal icon
  5. CoVariants.org. covariants.orgexternal icon
  6. SARS-CoV-2 mutation situation reports. Scripps Research. outbreak.info/situation-reports/external icon
  7. Pangolin COVID-19 lineage assigner. pangolin.cog-uk.io/external icon
  8. Nextclade clade assignment, mutation calling. clades.nextstrain.org/external icon
Part 2: Case Studies
Module 2.1 - SARS-CoV-2 sequencing in Arizona

This module provides insight into how SARS-CoV-2 sequencing is used to describe the genomic epidemiology of a state and as an investigative tool in COVID-19 outbreak settings.

Presenter: Hayley Yaglom, MS, MPH​
Genomic Epidemiologist, Translational Genomics Research Institute

Arizona Covid-19 Presentation
[Full Version]external icon [Short Version]external icon

Take the Feedback Survey for Module 2.1

Further Reading

  1. An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona. Ladner et al. 2020 American Society for Microbiology. mbio.asm.org/content/11/5/e02107-20external icon

Resources

  1. AZ-Strain: Genomic Epidemiology of SARS-CoV-2 in Arizona nextstrain.org/community/narratives/tgennorth/arizona-covid-19/ external icon
Module 2.2 - Healthcare cluster transmission

This module provides insight into two separate outbreaks at long-term care settings, and how sequencing helped clarify the pattern of transmission in these settings.

Presenter: Nicholas Lehnertz, MD MPH MHS
Physician and Epidemiologist, Minnesota Department of Health​

ToolkitModule_2.2 pdf icon[PDF – 18 slides]

Take the Feedback Survey for Module 2.2

Further Reading

  1. Serial testing for SARS-CoV-2 and virus whole-genome sequencing. Taylor et al. 2020 MMWR. www.cdc.gov/mmwr/volumes/69/wr/mm6937a3.htm
Module 2.3 - Investigating workplace-community transmission

This module investigates an outbreak at a meat processing plant using sequencing to differentiate workplace and community transmission.

Presenter: Nicholas Lehnertz, MD MPH MHS​
Physician and Epidemiologist, Minnesota Department of Health

Toolkit Module 2.3 pdf icon[PDF – 14 slides]

Take the Feedback Survey for Module 2.3

Further Reading

  1. Utilization of whole genome sequencing to understand SARS-CoV-2 transmission dynamics in long-term care facilities, correctional facilities and meat processing plants in Minnesota, March – June 2020. Lehnertz et al. 2020 MedRxiv. https://www.medrxiv.org/content/10.1101/2020.12.30.20248277v1external icon
  2. COVID-19 among workers in meat and poultry processing facilities ― 19 states, April 2020. Dyal et al. 2020 https://www.cdc.gov/mmwr/volumes/69/wr/mm6918e3.htm
Module 2.4 - Superspreading event in a pre-symptomatic population

This module reviews how genomic epidemiology was used to investigate a COVID-19 superspreading event in a congregate care setting.

 

Presenter: Glen R. Gallagher, PhD
Division Director, Molecular Diagnostics and Virology
Massachusetts Department of Public Health

Toolkit Module 2.4 pdf icon[PDF – 16 pages]

Take the Feedback Survey for Module 2.4

Further Reading

  1. Phylogenetic analysis of SARS-CoV-2 in Boston highlights the impact of superspreading events. Lemieux et al. 2020. science.sciencemag.org/content/371/6529/eabe3261external icon
  2. Presymptomatic transmission of severe acute respiratory syndrome coronavirus 2 among residents and staff at a skilled nursing facility: Results of real-time polymerase chain reaction and serologic testing. Goldberg et al. 2020. academic.oup.com/cid/article/72/4/686/5871989external icon

Resources

  1. Nextstrain build: https://auspice.broadinstitute.org/sars-cov-2/boston/gisaid-0929?f_SNF_A_EXPOSURE=YESexternal icon

Further Reading for Case Studies

  1. Presymptomatic SARS-CoV-2 infections and transmission in a skilled nursing facility. Arons et al. 2020 NEJM. www.ncbi.nlm.nih.gov/pmc/articles/PMC7200056/external icon
  2. COVID-19 outbreak associated with a 10-day motorcycle rally in a neighboring state. Firestone et al. 2020 MMWR. www.cdc.gov/mmwr/volumes/69/wr/mm6947e1.htm?s_cid=mm6947e1_w
  3. The emergence of SARS-CoV-2 in Europe and North America. Worobey et al. 2020 Science. science.sciencemag.org/content/370/6516/564external icon
  4. Interregional SARS-CoV-2 spread from a single introduction outbreak in a meat-packing plant in northeast Iowa. Richmond et al. 2020 MedRxiv. www.medrxiv.org/content/10.1101/2020.06.08.20125534v1external icon
  5. SARS-CoV-2 sequencing reveals rapid transmission from college student clusters resulting in morbidity and deaths in vulnerable populations. Richmond et al. 2020 MedRxiv. www.medrxiv.org/content/10.1101/2020.10.12.20210294v1external icon
Part 3: Implementation
Module 3.1 - Getting started with Nextstrain

This module gives an introduction to Nextstrain, a powerful tool for interactive tree visualization.

Presenter: Michael Weigand, PhD​​
Bioinformatician​, CDC

ToolkitModule_3.1 pdf icon[PDF – 20 slides]

Take the Feedback Survey for Module 3.1

Further Reading

  1. Nextstrain: Real-time tracking of pathogen evolution. Hadfield et al. 2018. Bioinformatics. academic.oup.com/bioinformatics/article/34/23/4121/5001388 external icon

Resources

  1. Nextstrain documentation docs.nextstrain.orgexternal icon
  2. A Getting Started Guide to the Genomic Epidemiology of SARS-CoV-2 docs.nextstrain.org/en/latest/tutorials/SARS-CoV-2/steps/index.html#a-getting-started-guide-to-the-genomic-epidemiology-of-sars-cov-2external icon
  3. Interacting with auspice, the visualization web application neherlab.org/201901_krisp_auspice.htmlexternal icon
  4. SPHERES state builds nextstrain.org/groups/spheresexternal icon
Module 3.2 – Getting started with MicrobeTrace

This module introduces MicrobeTrace for transmission network analysis using SARS-CoV-2 sequencing and contact tracing data.

Presenter: Ellsworth Campbell, MS ​
Computational Biologist​, CDC

Toolkit Module 3.2 pdf icon[PDF – 28 slides]

Take the Feedback Survey for Module 3.2

Further Reading

  1. MicrobeTrace: Retooling Molecular Epidemiology for Rapid Public Health Response. Campbell et al. 2020 BioRxiv. https://www.biorxiv.org/content/10.1101/2020.07.22.216275v1external icon
  2. Participation in fraternity and sorority activities and the spread of COVID-19 among residential university communities — Arkansas, August 21–September 5, 2020. Vang et al. 2021 MMWR. https://www.cdc.gov/mmwr/volumes/70/wr/mm7001a5.htm

Resources​

  1. MicrobeTrace. https://microbetrace.cdc.gov ​
  2. MicrobeTrace documentation. https://github.com/CDCgov/MicrobeTrace/wikiexternal icon
  3. MicrobeTrace tutorial. https://youtu.be/O52eeyUbpIoexternal icon  ​

Hands-on

  1. Example node list. excel icon[CSV – 1KB]
  2. Example phylogenetic tree.txt icon
Module 3.3 – Real-time phylogenetics with UShER

This module provides an introduction to UShER and an easy to use web portal for fast phylogenetic tree calculation.

Presenter: Russ Corbett-Detig, PhD
Assistant Professor, Department of Biomolecular Engineering, University of California, Santa Cruz

Toolkit Module 3.3 pdf icon[PDF – 20 slides]

Take the Feedback Survey for Module 3.3

Further Reading

  1. Ultrafast Sample Placement on Existing Trees (UShER) Empowers Real-Time Phylogenetics for the SARS-CoV-2 Pandemic. Turakhia et al. 2020 BioRxiv. https://www.biorxiv.org/content/10.1101/2020.09.26.314971v1external icon

Resources​

  1. UShER web portal. https://genome.ucsc.edu/cgi-bin/hgPhyloPlaceexternal icon
  2. UShER source code.  https://github.com/yatisht/usherexternal icon

Hands-on​

  1. UShER example data. https://github.com/russcd/USHER_DEMOexternal icon
Module 3.4 – Walking through Nextstrain trees

This module demonstrates how to navigate through Nextstrain phylogenetic trees using various functionalities such as filtering, zooming, coloring and labeling to further analyze SARS-CoV-2 genomic epidemiological data.

Presenter: Krisandra Allen, MPH, MB(ASCP)CM
Molecular Epidemiologist
Washington State Department of Health

Toolkit Module 3.4 pdf icon[PDF – 18 slides]

Take the Feedback Survey for Module 3.4

Resources

  1. Nextstrain SARS-CoV-2 resourcesexternal icon

Hands-on​

  1. Module 3.4 Demo Meta Data excel icon[CSV – 1KB]
    Note: Please convert the ToolkitModule_3.4-demoData.csv file into a tsv file. This is needed for Nextstrain. Instructions on how to convert csv to tsv are here: https://docs.nextstrain.org/en/latest/tutorials/SARS-CoV-2/steps/data-prep.htmlexternal icon.
  2. Module 3.4 Demo Phylogenetic Tree: https://nextstrain.org/groups/blab/ncov/tutorialexternal icon
Module 3.5 – Public genome repositories for SARS-CoV-2

This module introduces two public repositories for sharing SARS-CoV-2 genome sequence data and basic tips for searching them.

Presenter: Michael Weigand, PhD​​
Bioinformatician​, CDC

Toolkit Module 3.5 pdf icon[PDF – 20 slides]

Take the Feedback Survey for Module 3.5

Resources

  1. Global Initiative on Sharing All Influenza Data (GISAID). www.gisaid.orgexternal icon
  2. National Center for Biotechnology Information (NCBI) SARS-CoV-2 resources. www.ncbi.nlm.nih.gov/sars-cov-2/external icon
  3. NCBI Virus SARS-CoV-2 data dashboard. www.ncbi.nlm.nih.gov/labs/virus/vssi/#/sars-cov-2external icon
  4. NCBI Umbrella BioProject of US sequencing efforts. www.ncbi.nlm.nih.gov/bioproject/PRJNA615625external icon
  5. NCBI GenBank submission. submit.ncbi.nlm.nih.gov/sarscov2/genbankexternal icon
  6. NCBI SRA submission. submit.ncbi.nlm.nih.gov/sarscov2/sraexternal icon
  7. SARS-CoV-2 GISAID submission protocol. www.protocols.io/view/sars-cov2-gisaid-submission-protocol-bh98j99wexternal icon
  8. SARS-CoV-2 GenBank submission protocol. www.protocols.io/view/sars-cov-2-ncbi-assembly-submission-protocol-genba-bg2tjyenexternal icon
  9. SARS-CoV-2 SRA submission protocol. www.protocols.io/view/sars-cov-2-ncbi-submission-protocol-sra-biosample-bf7bjrinexternal icon
  10. Public Health Alliance for Genomic Epidemiology (PHA4GE) resources. pha4ge.org/resources/external icon
  11. Public Health Alliance for Genomic Epidemiology (PHA4GE) protocols. www.protocols.io/workspaces/pha4ge/publicationsexternal icon
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Page last reviewed: April 19, 2021