In 2023 our Covid-19 infection problems are being caused by XBB recombinant variants. The Omicron BA.5 bivalent vaccine has had no effect on the immune evading BQ variants or XBB recombinant variants. In December the first highly infectious recombinant variant, XBB, began spreading around the world. Since then the XBB variant XBB.1.5, has rapidly spread across the country and the world. XBB variants are rapidly increasing with XBB.1.9.1, XBB.1.9.2, and XBB.1.16 of particular concern.
On January 13, the World Health Organization (WHO) updated its recommendations on mask wearing to specify that, given the global spread of COVID-19, masks should be worn “irrespective of the local epidemiological situation,” meaning that masks are now recommended for everyone, not just people in areas with high levels of transmission.
XBB.1.5 Variant Continues to Dominate in the United States
During the week ending in 4/21/23, the CDC estimates that based on genomic surveillance, XBB.1.5 accounted for 73.6% of infections, XBB.1.16 at 9.6% of infections, XBB.1.9.1 at 7.9% of infections, XBB.1.9.2 at 2.9% of infections, XBB .1.5.1 at 2.2% of infections and new isolate FD.2 at 1.6% of isolates rounding out the top six SARS-CoV-2 variants. Variant XBB.1.9.1, unlike all other variants tested in March 10th UK Technical Bulletin 51, had a 15% growth advantage over XBB.1.5. XBB.1.16 was not tested at that time but based on rapid spread worldwide appears to also have a significant growth advantage. In the UK Technical Bulletin 52 from April 21, XBB.1.9.2 and XBB.1.16 have a growth advantage over XBB.1.5.
What happens next? History shows us that the variants with the most significant growth rate advantage will be the next dominant variant. Our current guess is as always a moving target with the current leading candidates being XBB.1.9.1, XBB.1.9.2, XBB.1.16 and XBB.1.5 variants. Due to increased air travel between countries with no masking required in airports other isolates from China or India might become predominant in the next three months.
The following is a quote from a recent paper by Madison Stoddard et al.: “At its heart, the problem is one of risk management-plausible risks do not need to be inevitable in order to warrant mitigation. In his book “The Black Swan”, a classic in the risk-management community, author Nassim Nicholas Talib describes a type of event known as a Grey Swan – a rare and highly consequential event that, unlike absolutely unforeseen Black Swan events, can be expected. Our work here shows that ahistorical and potentially destabilizing mortality events as a result of the COVID-19 pandemic are Grey Swans, very much within the realm of the possible. In this paper, we describe one mechanism by which this can occur-antigenic shift (a sudden jump in immune evasion) leading to a reversion to a higher death rate. Such an event, if it were to happen, would not only have been predictable, but can occur repeatedly in the absence of further corrective measures.”
We’re asking people to take those corrective measures; be respiratorily safe by wearing an N95 mask, avoiding in-person gatherings, and improving ventilation. This is the only way to prevent a possible Gray Swan event.
This paper is also notable because it challenges the widely-held belief that “hybrid immunity” to SARS-CoV-2 is advantageous.
U.S. COVID Data
Here are our 14-day moving average determinations for SARS-CoV-2 for the United States. We use the WORLDOMETERS aggregators data set to make any projections since it includes data from the Department of Veterans Affairs, the U.S. Military, federal prisons and the Navajo Nation.



On 4/21/23, the United States had 4,172 documented new infections. There were also 35 deaths. Forty-one states and the District of Columbia did not report their infections, and 43 states and the District of Columbia didn’t report their deaths.
In the United States on 4/20/23 the number of hospitalized patients (4,778) had decreased (-13% compared to the previous 14 days). On 4/21/23 1,473 patients were seriously or critically ill. Patients are still dying each day (average 152/day, the last 14 days).
As of 4/21/23, we have had 1,159,003 deaths and 106,540,840 SARS-CoV-2 infections in the United States. We have had at least 177,414 new infections in the last 14 days. We are adding an average of 88,707 new infections every seven days. For the pandemic in the United States we are averaging one death for every 91.92 infections or over 10,878 deaths for each one million infections. As of 4/21/23, thirty-nine states have had greater than 500,000 total infections, and 39 states and Puerto Rico have had greater than 5,000 total deaths. Forty-seven states and Puerto Rico have had greater than 2,000 deaths. Only Vermont has had less than a thousand deaths (929 deaths). As of 4/21/23, 14 states have over 4,000 deaths per million population: Arizona (4,585, Mississippi (4,512), West Virginia (4,488, unchanged in 2 weeks), New Mexico (4,376), Arkansas (4,328, unchanged in 4 weeks), Alabama (4,310, unchanged in 2 weeks), Tennessee (4,294, unchanged in 2 weeks), Michigan (4,272), Kentucky (4,131), New Jersey (4,065), Florida (4,057, unchanged in 4 weeks), Louisiana (4,064), Georgia (4,023) and Oklahoma (4,052). Eighteen states (Alabama, Virginia, Missouri, North Carolina, Indiana, Tennessee, Massachusetts, Ohio, Michigan, Georgia, Illinois, New Jersey, Pennsylvania, Florida, Texas, New York, Arizona and California) have had greater than 20,000 deaths. Nine states have had greater than 40,000 deaths: Florida (87,141 deaths, unchanged in 4 weeks), Texas (94,260 deaths), New York (77,513 deaths), Pennsylvania (50,860 deaths), Georgia (42,717 deaths), Ohio (42,126 deaths), Illinois (41,866 deaths), Michigan (42,667), and California (102,096 deaths, 20th most deaths in the world).
On 11/20/20, there were 260,331 (cumulative) deaths in the US from SARS-CoV-2. Since 11/20/20 (29 months), there were 891,892 new deaths from SARS-CoV-2. For 25 of those months, vaccines have been available to all adults. During these 25 months, 586,804 people have died of SARS-CoV-2 infections. Clearly, a vaccine-only approach is not working anywhere, especially not in the United States. In addition to getting more people vaccinated, most of the hospitalizations and deaths could have been prevented by proper masking (N95 or better), social distancing, and treatment with oral antiviral agents like Paxlovid. We recommend all of these precautions and treatments to every patient in our clinic, and we have only lost one patient to COVID-19 in 3 years.
As of 4/21/23, California was ranked 31st in the USA in infection percentage at 30.84%. In California, 26.87% of the people were infected in the last 24 months. As of 4/21/23, 33 states have had greater than 30% of their population infected. Fifty states, the District of Columbia and Puerto Rico have greater than 20% of their population infected.
Watching World Data
Over the next few months, we’ll be paying close attention to correlations between the SARS-CoV-2 data, the number of isolates identified in various countries and states, and the non-pharmaceutical interventions (like mask mandates and lockdowns) put in place by state and national governments. Data on infections, deaths, and percent of population infected was compiled from Worldometers. Data for this table for SARS-CoV-2 Isolates Currently Known in Location was compiled from GISAID and the CDC. It’s worth noting that GISAID provided more data than the CDC.
Location | Total Infections as of 4/21/23 | New Infections on 4/21/23 | Total Deaths | New Deaths on 4/21/23 | % of Pop.Infected | SARS-CoV-2 Isolates Currently Known in Location | National/ State Mask Mandate | Currently in Lockdown |
World | 686,333,011(1,457,824 new infections in the last 14 days with an average of 104,130 infections per day). | 60,230 | 6,859,230(21,719 new deaths in the last 14 days with an average of 1,551 deaths per day.) | 413 | 8.80% | B2 lineageAlpha/B.1.1.7 (UK)Eta/B.1.525 (Nigeria/UK)Iota/B.1.526 (USA-NYC)Beta/B.1.351 (SA)Epsilon/B.1.427 + B.1.429 (USA)*Gamma/P.1 (Brazil)Zeta/P.2 (Brazil)A lineage isolateV01.V2 (Tanzania)APTK India VOC 32421Delta/B.1.617.2 (India)BV-1 (Texas, USA)Kappa/B.1.617.1 (India)Lambda/C.37 (Peru)Theta/P.3 (Philippines) Mu/B.1.621 (Colombia)C.1.2 (South Africa 2% of isolates in July 2021)R1 (Japan)Omicron/B.1.1.529 + BA.1 + BA.2 + BA.3 (South Africa November 2021)B.1.640.1 (Congo/France)B.1.640.2 (Cameroon/France)Four new recombinants 12/31 to 3/22)BA.2.12.1 (USA)BA.4 (South Africa)BA.5 (South Africa)BA.2.75 (India 7/22)BA.4.6 (USA 7/22)BF.7BJ.1XBB (new recombinant India)BQ.1BQ.1.1BS.1BN.1XBB.1XBB.1.5CH.1.1XBB.1.9.1XBB.1.5.1XBB.1.16FD.2 | No | No |
USA | 106,540,840(ranked #1) 177,414 new infections in the last 14 days with an average of 12,672 infections/day | 4,172(ranked #6) 41 states and D.C. failed to report infections on 4/21/23. | 1,159,003(ranked #1) 2,107 new deaths reported in the last 14 days or an average of 151 deaths/ day. | 35 43 states and D.C.failed to report deaths on 4/21/23. | 31.82% | B2 lineageAlpha/B.1.1.7 (UK)Eta/B.1.525 (Nigeria/UK)Iota/B.1.526 (USA-NYC)Beta/B.1.351 (SA)Epsilon/B.1.427 + B.1.429 (USA)*Gamma/P.1 (Brazil)Zeta/P.2 (Brazil)Delta/B.1.617.2 (India)BV-1 (Texas, USA)Theta/P.3 (Philippines) Theta/P.3 (Philippines) Kappa/B.1.617.1 (India)Lambda/C.37 (Peru)Mu/B.1.621 (Colombia)R1(Japan) Omicron/B.1.1.529 + BA.1 + BA.2 (South Africa November 2021)B.1.640.1 (Congo/France)Recombinant Delta AY.119.2- Omicron BA.1.1 (Tennessee, USA 12/31/21)\BA.2BA.2.12.1 (United States)BA.4 (South Africa 11/21)BA.5 (South Africa 11/21)BA.2.75 (India 7/22)BA.4.6 (USA 7/22)BA.4.6 (USA 7/22)BF.7BJ.1XBB (new recombinant India)BQ.1BQ.1.1BN.1XBB.1XBB.1.5XBB.1.5.1CH.1.1XBB.1.9.1XBBB.1.9.2XBB.1.16FD.2 | No | No |
Brazil | 37,407,232(ranked #5) 87,978 new infections in the last 14 days. | – | 701,215(ranked #2; 659 new deaths in the last 14 days) | – | 17.37% | No | No | |
India | 44,869,684(ranked #2)124,580 new infections in the last 14 days. | – | 531,258(ranked #3) 324 new deaths in the last 14 days) | – | 319% | No | No | |
United Kingdom | 24,555,629(ranked #9) 106,900 new infections reported in the last 42 days. | – | 221,943 (ranked #6) 12,547 new deaths reported in the last 42 days. | – | 35.85% | B2 lineageAlpha/B.1.1.7 (UK)Eta/B.1.525 (Nigeria/UK)Beta/B.1.351 (SA)Epsilon/B.1.427 + B.1.429 (USA)*Gamma/P.1 (Brazil)Delta/B.1.617.2 (India)Theta/P.3 (Philippines) Kappa/B.1.617.1 (India)Lambda/C.37 (Peru)Mu/B.1.621 (Colombia)C.1.2 (South Africa)Omicron/B.1.1.529 + BA.1 (South Africa November 2021)B.1.640.1 (Congo/France)XD (AY.4/BA.1) recombinantXF (Delta/BA.1) recombinantXE (BA.1/BA.2) recombinantBA.2BA.2.12.1 (United States)BA.4 (South Africa 11/21)BA.5 (South Africa 11/21)BA.2.75 (India 7/22)XBBXBB.1XBB.1.5XBB.1.5.1CH.1.1XBB.1.9.1 | No | No |
California, USA | 12,186,221(ranked #13 in the world; 2,709 new infections in the last 14 days). | – | 102,096 (ranked #20 in world; 53 new deaths in the last 14 days | – | 30.84% | B2 lineageAlpha/B.1.1.7 (UK)Eta/B.1.525 (Nigeria/UK)Beta/B.1.351 (SA)Gamma/P.1 (Brazil)Epsilon/B.1.427 + B.1.429 (USA)*Zeta/P.2 (Brazil)Delta/B.1.617.2 (India)Theta/P.3 (Philippines) Kappa/B.1.617.1 (India)Lambda/C.37 (Peru) Mu/B.1.621 (Colombia) Omicron/ B.1.1.529 + BA.1 (South Africa November 2021)BA.2BA.2.12.1 (United States)BA.4 (South Africa 11/21)BA.5 (South Africa 11/21)BA.2.75 (India 7/22)BQ.1BQ.1.1BN.1XBBXBB.1XBB.1.5CH.1.1XBB.1. 5.1XBB.1.9.1XBB.1.9.2XBB.1.16 | No | No |
Mexico | 7,572,705(ranked #19) 19,979 new infections in 14 days). | 1,949(rank #8) | 333,732,(ranked #5) 143 new deaths in the last 14 days) | 14 | 5.75% | No | No | |
South Africa | 4,076,463(ranked #38; 1,362 new infections in the last 14 days). | – | 102,595 (ranked #18) no new deaths reported in the last 84 days). | – | 6.70% | B2 lineageAlpha/B.1.1.7 (UK)Beta/B.1.351 (SA)Delta/B.1.617.2 (India)Kappa/B.1.617.1 (India) C.1.2 (South Africa, July 2021)Omicron/B.1.1.529 + BA.1 (South Africa November 2021)B.1.640.1 (Congo/France)BA.2BA.4 (South Africa 11/21)BA.5 (South Africa 11/21) | No | No |
Canada | 4,641,301(ranked #33) 7,624 new infections in 14 days). | – | 52,247(ranked #24) 126 new deaths in the last 14 days. | – | 12.09% | No | No | |
Russia | 22,796,845(ranked #10), 98,820 new infections in 14 days). | 7,116 (ranked #4) | 398,007(ranked #4)510 new deaths in 14 days | 33 | 15.63%0.07% increase in 14 days. | No | No | |
Peru | 4,499,355(ranked #35, 4,984 new infections in 14 days).. | – | 220,073(ranked #7) 124 new deaths in the last 14 days. | – | 13.35% | No | No | |
Spain | 13,825,052(ranked #12; 26,305 new infections in 14 days). | 1,604 (ranked#10) | 120,715 (ranked #15) 289 new deaths in 14 days. | 13 | 29.59% | No | No | |
France | 39,938,443 (ranked #3) 102,626 new infections in 14 days). | 7,400 (ranked #3) | 166,289 (ranked #10) 432 new deaths in 14 days. | 125 | 60.89% a 0.15% increase in 14 days. | No | No | |
Germany | 38,393,992(ranked #4; 25,101 new infections in 14 days.) | 1,626 (ranked #9) | 172,536 (ranked #9)1,125 new deaths in 14 days. | 108 | 45.77%0.07% increase in 14 days | No | No | |
South Korea | 31,053,459 (ranked #7; 158,800 new infections in 14 days). | 13,596(ranked #1) | 34,408 (ranked #32) 90 new deaths in 14 days. | 7 | 60.49%0.30% increase in 14 days | No | No | |
Japan | 33,628,545(ranked #6)120,165 new infections in the last 14 days | 10,074(ranked #2) | 74,388(ranked #20)278 new deaths in the last 14 days for an average of 27 deaths per day. | 24 | 26.77%0.09% of the population infected in the last 14 days. | No | No | |
Hong Kong | 2,887,756(ranked# 41) 2,330 new infections in the last 14 days. | 234 | 13,500 (ranked #60)17 new deaths in the last 14 days. | 3 | 37.97%0.03% increase in the last 14 days.` | No | No | |
China | 503,302 | – | – | – | – | – | – | – |
What Our Team Is Reading This Week
- Live-attenuated vaccine sCPD9 elicits superior mucosal and systemic immunity to SARS-CoV-2 variants in hamsters https://www.nature.com/articles/s41564-023-01352-8
- SARS-CoV-2 variants resistant to monoclonal antibodies in immunocompromised patients constitute a public health concern https://doi.org/10.1172/JCI168603
- “Super-Spreaders” and Person-to-Person Transmission of Andes Virus in Argentina https://www.nejm.org/doi/full/10.1056/NEJMoa2009040
- The gray swan: model-based assessment of the risk of sudden failure of hybrid immunity to SARS-CoV-2 https://doi.org/10.1101/2023.02.26.23286471
- The Black Swan by Nassim Nicholas Talib https://bookshop.org/p/books/the-black-swan-second-edition-the-impact-of-the-highly-improbable-with-a-new-section-on-robustness-and-fragility-nassim-nicholas-taleb/7841914?ean=9780812973815
- SARS-CoV-2 variants of concern and variants under investigation in England Technical briefing 51, 10 March 2023 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1141754/variant-technical-briefing-51-10-march-2023.pdf
- SARS-CoV-2 variants of concern and variants under investigation in England Technical briefing 50, 10 February 2023 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1135877/variant-technical-briefing-50-10-february-2023.pdf
- Identification of a molnupiravir-associated mutational signature in SARS-CoV-2 sequencing databases (Preprint) https://doi.org/10.1101/2023.01.26.23284998
- COVID drug drives viral mutations — and now some want to halt its use https://www.nature.com/articles/d41586-023-00347-z#ref-CR1
- SARS-CoV-2 variants of concern and variants under investigation in England Technical briefing 49, 11 January 2023 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1128554/variant-technical-briefing-49-11-january-2023.pdf
- Long COVID: major findings, mechanisms and recommendations (Nature) https://www.nature.com/articles/s41579-022-00846-2
- Enhanced fusogenicity and pathogenicity of SARS-CoV-2 Delta P681R mutation (Nature) https://doi.org/10.1038/s41586-021-04266-9
- Virological characteristics of the SARS-CoV-2 XBB variant derived from recombination of two Omicron subvariants (Preprint) https://doi.org/10.1101/2022.12.27.521986
- SARS-CoV-2 infection and persistence in the human body and brain at autopsy (Nature) https://doi.org/10.1038/s41586-022-05542-y
- Lifting Universal Masking in Schools — Covid-19 Incidence among Students and Staff (NEJM) https://www.nejm.org/doi/full/10.1056/NEJMoa2211029
You must be logged in to post a comment.