The capacity for pathogen genomics in public health expanded rapidly during the coronavirus disease 2019 (COVID-19) pandemic, but many public health laboratories did not have the infrastructure in place to handle the vast amount of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequence data generated. The California Department of Public Health, in partnership with Theiagen Genomics, was an early adopter of cloud-based resources for bioinformatics and genomic epidemiology, resulting in the creation of a SARS-CoV-2 genomic surveillance system that combined the efforts of more than 40 sequencing laboratories across government, academia and industry to form California COVIDNet, California’s SARS-CoV-2 Whole-Genome Sequencing Initiative. Open-source bioinformatics workflows, ongoing training sessions for the public health workforce, and automated data transfer to visualization tools all contributed to the success of California COVIDNet. While challenges remain for public health genomic surveillance worldwide, California COVIDNet serves as a framework for a scaled and successful bioinformatics infrastructure that has expanded beyond SARS-CoV-2 to other pathogens of public health importance,

This study was supported by the:
  • Centers for Disease Control and Prevention (Award Epidemiology and Laboratory Capacity for Infectious Diseases, Cooperative Agreement Number 5 NU50CK000539)
    • Principle Award Recipient: ApplicableNot
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.

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  1. Khare S, Gurry C, Freitas L, Schultz MB, Bach G et al. GISAID’s role in pandemic response. China CDC Wkly 2021; 3:1049–1051 [View Article] [PubMed]
    [Google Scholar]
  2. Wheeler DL, Barrett T, Benson DA, Bryant SH, Canese K et al. Database resources of the national center for biotechnology information. Nucleic Acids Research 2007; 36:D13–D21 [View Article]
    [Google Scholar]
  3. O’Toole Á, Scher E, Underwood A, Jackson B, Hill V et al. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evol 2021; 7:veab064 [View Article] [PubMed]
    [Google Scholar]
  4. Hadfield J, Megill C, Bell SM, Huddleston J, Potter B et al. Nextstrain: real-time tracking of pathogen evolution. Bioinformatics 2018; 34:4121–4123 [View Article] [PubMed]
    [Google Scholar]
  5. Turakhia Y, Thornlow B, Hinrichs AS, De Maio N, Gozashti L et al. Ultrafast Sample placement on Existing tRees (UShER) enables real-time phylogenetics for the SARS-CoV-2 pandemic. Nat Genet 2021; 53:809–816 [View Article] [PubMed]
    [Google Scholar]

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