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

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.

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 § https://www.cdc.gov/coronavirus/2019-ncov/variants/spheres.html ¶ https://www.aphl.org/programs/preparedness/Crisis-Management/COVID-19-Response/Pages/Sequence-Based-Surveillance-Submission.aspx ** Sequence tagging allows for sequencing partners to tag or label randomly sampled SARS-CoV-2 sequences submitted via GISAID EpiCov and NCBI GenBank to be used in CDC genomic surveillance estimates. https://www. aphl.org/programs/preparedness/Crisis-Management/Documents/Technical-Assistance-for-Categorizing-Baseline-Surveillance-Update-Oct2021.pdf † † A consensus sequence is produced by aligning SARS-CoV-2 nucleotide sequences produced through sequencing a sample and then determining the most common nucleotide at each position. It is an interoperable genomic surveillance unit that can be combined from laboratory sources. § § https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/variantsurveillance/variant-info.html 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 ¶ ¶ https://github.com/CDCgov/SARS-CoV-2_Genomic_Surveillance *** Flagged estimates are presented with a note indicating they might be less reliable. https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf 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 † † † CIs show uncertainty around an estimate describing observed data; prediction intervals show uncertainty around predictions of unobserved data, such as the nowcast variant proportions.

Discussion
This report summarizes CDC's weekly surveillance of variant proportions, which are used to drive public health action. The proportional distribution of SARS-CoV-2 variants circulating in the United States changed considerably during 2021. In spring 2021, Alpha co-circulated nationally with several other variants (e.g., Gamma, Delta, Eta, and Iota), but Delta became the predominant variant nationally in late June. Delta remained the only SARS-CoV-2 variant circulating at a high proportion from August-November but was rapidly overtaken by Omicron in late December. The rises of the Delta and Omicron variants were associated with major surges in COVID-19 cases during July-September 2021 and December 2021-January 2022, respectively. § § § § The Omicron-driven wave that started in December 2021 is declining. These variant dynamics illustrate how SARS-CoV-2 has continued to evolve, with different variants defining different phases of the COVID-19 pandemic.
Variant emergence and growth are likely influenced by a combination of viral and host population factors. Factors contributing to Delta's rise in prevalence include increased transmissibility and a subtle increase in immune escape relative to previous variants (5,6). Omicron's rise in prevalence was likely driven by increased transmissibility (7) that might be due primarily to immune escape ¶ ¶ ¶ ¶ (8), which also decreases the effectiveness of vaccines and monoclonal antibodies (9). However, early studies suggest that the relative severity of disease attributed to Omicron infections is lower than that resulting from infections with other SARS-CoV-2 variants.***** , † † † † † A variant's ability to spread and cause disease is affected by population susceptibility (duration of variant-specific immunity, cross-protection from previous infections, and vaccine-induced immunity). Transmission is also influenced by human behavior, particularly through prevention strategies.
relatively small numbers of available sequences, especially at the jurisdictional and regional levels. Third, current variant estimation analyses might differ from past analyses because of changes in PANGO lineage definitions over time. Finally, the presented dates correspond to clinical testing, and noted variants were likely present before these periods; for example, wastewater surveillance indicates that Omicron was circulating in the United States >1 week before the first reported case (10). CDC's national SARS-CoV-2 genomic surveillance program has expanded data sources and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes have enhanced the robustness and representativeness of variant proportion estimates. Nowcast modeling at multiple geographic levels has enabled more timely estimation and demonstrated an ability to monitor emerging variants, even those circulating at low levels. SARS-CoV-2 variants are expected to continue emerging; a future variant might challenge the predominance of Omicron and exhibit different characteristics that affect public health and clinical interventions. Consequently, it is important to maintain SARS-CoV-2 genomic surveillance to ensure emerging variants are monitored and to promptly inform public health planning and practice.