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Ten recommendations for supporting open pathogen genomic analysis in public health.
Black, Allison; MacCannell, Duncan R; Sibley, Thomas R; Bedford, Trevor.
  • Black A; Department of Epidemiology, University of Washington, Seattle, Washington, USA.
  • MacCannell DR; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
  • Sibley TR; Office of Advanced Molecular Detection, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. fms2@cdc.gov.
  • Bedford T; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Nat Med ; 26(6): 832-841, 2020 06.
Article in English | MEDLINE | ID: covidwho-594839
ABSTRACT
Increasingly, public-health agencies are using pathogen genomic sequence data to support surveillance and epidemiological investigations. As access to whole-genome sequencing has grown, greater amounts of molecular data have helped improve the ability to detect and track outbreaks of diseases such as COVID-19, investigate transmission chains and explore large-scale population dynamics, such as the spread of antibiotic resistance. However, the wide adoption of whole-genome sequencing also poses new challenges for public-health agencies that must adapt to support a new set of expertise, which means that the capacity to perform genomic data assembly and analysis has not expanded as widely as the adoption of sequencing itself. In this Perspective, we make recommendations for developing an accessible, unified informatic ecosystem to support pathogen genomic analysis in public-health agencies across income settings. We hope that the creation of this ecosystem will allow agencies to effectively and efficiently share data, workflows and analyses and thereby increase the reproducibility, accessibility and auditability of pathogen genomic analysis while also supporting agency autonomy.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Population Dynamics / Coronavirus Infections / Genomics Type of study: Observational study Limits: Humans Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2020 Document Type: Article Affiliation country: S41591-020-0935-z

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Population Dynamics / Coronavirus Infections / Genomics Type of study: Observational study Limits: Humans Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2020 Document Type: Article Affiliation country: S41591-020-0935-z