āVariants Are a Normal Part of Viruses
Viruses change through mutations that create new strains of virus over time. This is a normal process that happens with most viruses. We call these strains variants.
Some variants grow and persist in the community while many variants simply fizzle out. Most variants do not have a meaningful impact on things like hospitalization rates, severity, or infectivity.
Why Are We Trackingā Variants?
Scientists and public health officials are studying variants to learn more about how to control their spread. They want to understand whether the variants:
- Change the effectiveness of COVID-19 vaccines
- Cause milder or more severe disease in people
- Spread more easily from person-to-person
- Are detected by currently available viral tests
- Respond to medicines currently being used to treat people for COVID-19
Variants We Are Tracking
Variants of Concern
Variants of concern are likely to have one or more of the following features:
- More contagious
- Likely to cause more severe symptoms
- Resistant to treatment
- More resistant to vaccines
Variant |
Known differences |
Delta
|
- 200% increased transmission compared to other variants
- Reduced antibody treatment effectiveness
|
Omicron |
- At least 2 to 4 times more transmissible than the Delta variant
- Reduced effectiveness of certain antibody treatments
|
The Omicron variant (Pango Lineage B.1.1.529) has been classified into the following sublineages: BA.1, BA.2, BA.3, BA.4, BA.5, and XBB. Each sublineage is further classified into several distinct sublineages due to accumulation of additional mutations. Mutations are very commonly found in the Spike protein, which facilitates the virus entering the cell. The Spike protein is also the target of many vaccines, and mutations in this protein are associated with increased immune evasion.
Genomic Surveillance
The State of California alongside various public and private partners select positive COVID-19 tests for
whole genome sequencing to understand what variants are circulating in the community. Sequencing allows scientists to look at the unique genetic code of a virus which can be used to compare similarities and differences between samples.
Current Variant Proportions and Modeling Estimates
Percent prevalence of variants circulating in California are listed in the table below. Of total cases sequenced in July 2024, 37.3% were KP.3 (JN.1.11.1.3), 21.5% were KP.2 (JN.1.11.1.2), and 15.2% were LB.1 (JN.1.9.2).
Lineage |
JN.1 |
LB.1 |
JN.1.11.1 |
KP.1.1 |
KP.2 |
KP.2.3 |
KP.3 |
KP.3.1.1 |
JN.1.16 |
Parent |
BA.2.86 |
JN.1.9.2 |
JN.1 |
JN.1.11.1 |
JN.1.11.1 |
JN.1.11.1 |
JN.1.11.1 |
JN.1.11.1 |
JN.1 |
May 2024 |
23.3% |
3.3% |
7.0% |
8.8% |
15.8% |
-
|
9.2% |
- |
14.1% |
June 2024 |
18.5% |
8.7% |
2.2% |
5.6% |
23.6% |
- |
33.3% |
- |
5.1% |
July 2024 |
9.6% |
15.2% |
3.0% |
7.6% |
11.2% |
10.3% |
28.6% |
8.7% |
3.3%ā
|
ā
Since there is a known delay in the availability of sequencing results, CDPH
CalCAT model provides estimates of variant proportions for the most recent weeks. Models are updated biweekly on Fridays. Based on
CDPH model estimates, KP.3.1.1, a sublineage of KP.3, is predicted to be the variant with the highest proportion and fastest growing proportion. ā
Clinical Decision-Making
Providers should prioritize use of nirmatrelvir/ritonavir (Paxlovid) and remdesivir for treatment of mild to moderate COVID-19 in outpatients at risk for disease progression as these drugs continue to be effective against all Omicron sublineages. If neither of these are clinically appropriate, please see the NIH COVID-19 Treatment Guidelines for additional, effective options.
Please note that monoclonal antibodies are not currently authorized for pre-exposure prophylaxis or treatment of COVID-19 in any region of the United States due to increasing prevalence of sublineages that have been associated with resistance to these agents.