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12 febrero, 2022

Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants — United States, June 2021–January 2022

What is already known about this topic?

CDC conducts genomic surveillance to track SARS-CoV-2 variants in the United States.

What is added by this report?

CDC’s SARS-CoV-2 genomic surveillance has been expanded to incorporate sequence data from public repositories and to produce weighted estimates of variant proportions at the jurisdiction level. The Delta (B.1.617.2 and AY sublineages) variant rose to predominance in late June 2021, followed by the rapid rise of Omicron (B.1.1.529 and BA sublineages) in December 2021.

What are the implications for public health practice?

The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021–January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC’s COVID Data Tracker website to enable timely public health action. The SARS-CoV-2 Delta (B.1.617.2 and AY sublineages) variant rose from 1% to >50% of viral lineages circulating nationally during 8 weeks, from May 1–June 26, 2021. Delta-associated infections remained predominant until being rapidly overtaken by infections associated with the Omicron (B.1.1.529 and BA sublineages) variant in December 2021, when Omicron increased from 1% to >50% of circulating viral lineages during a 2-week period. As of the week ending January 22, 2022, Omicron was estimated to account for 99.2% (95% CI = 99.0%–99.5%) of SARS-CoV-2 infections nationwide, and Delta for 0.7% (95% CI = 0.5%–1.0%). The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.

In November 2020, CDC expanded its genomic surveillance program to track SARS-CoV-2 lineages at the national and U.S. Department of Health and Human Services (HHS) regional levels (1,2). CDC also initiated SARS-CoV-2 Sequencing for Public Health Emergency Response, Epidemiology, and Surveillance§ (SPHERES), a national SARS-CoV-2 genomic surveillance consortium. Currently, the national genomic surveillance program integrates three principal sources of SARS-CoV-2 sequence data: 1) the National SARS-CoV-2 Strain Surveillance (NS3) program; 2) CDC-contracted commercial sequencing data; and 3) sequences from public health, academic, and clinical laboratories that are tagged** as baseline surveillance in public genomic data repositories, such as Global Initiative on Sharing All Influenza Data (GISAID) and National Center for Biotechnology Information (NCBI) GenBank. Inclusion of tagged SARS-CoV-2 sequence data was instituted in October 2021 to enhance the geographic representativeness and precision of variant proportion estimates and to enhance the surveillance program’s sustainability.

SARS-CoV-2 consensus sequences†† submitted or tagged for national genomic surveillance were combined, assessed for quality, deduplicated, and analyzed for weekly estimation of variant proportions at the national, HHS regional, and jurisdictional levels. SARS-CoV-2 variant proportions (with 95% CIs) were estimated weekly for variants of concern, variants of interest, variants being monitored,§§ and any other lineages accounting for >1% of sequences nationwide during the preceding 12 weeks. Proportion estimation methods used a complex survey design with statistical weights to correct potential biases because samples selected for sequencing might not be representative of all SARS-CoV-2 infections (Box).¶¶ Each submitting laboratory source was considered a primary sampling unit, and the geographic level (i.e., jurisdictional, HHS regional, or national) and week of sample collection for each sequence, a stratum. Weights account for the probability that a sample from an infection is sequenced and are trimmed to the 99th percentile. Variant proportion estimates that did not meet the National Center for Health Statistics’ data presentation standards for proportions were flagged.*** During June 2021–January 2022, the median interval from SARS-CoV-2 sample collection to availability of consensus sequences was 15 days. Therefore, to estimate variant proportions during the most recent 2 weeks, multinomial regression models were fit for national and regional estimates to nowcast (2) variant proportions with corresponding 95% projection intervals††† using the most recent 21 weeks of data for prediction. To compare the speeds of initial variant transmission, the doubling time of each variant was calculated using the “time” covariate in nowcast models. All analyses used PANGO SARS-CoV-2 lineage nomenclature and sublineages were aggregated under the parent lineage (3). This activity was reviewed by CDC and conducted consistent with applicable federal law and CDC policy.§§§

https://www.cdc.gov/mmwr/volumes/71/wr/mm7106a4.htm?s_cid=mm7106a4_w&fbclid=IwAR2eNCC86H9Wl9OmVgI4MoyKiTPu236bG8ZN5bDW9vzuf7CwbYkVpwbk440


Créditos: Comité científico Covid

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