Trevor Bedford Profile picture
19 Dec, 18 tweets, 8 min read
With #COVID19 vaccine efficacy of ~95%, I'm looking forward to vaccine distribution in 2021 bringing the pandemic under control. However, I'm concerned that we'll see antigenic drift of SARS-CoV-2 and may need to update the strain used in the vaccine with some regularity. 1/18
First, some background. RNA viruses all evolve extremely rapidly, but some like influenza are able to accept mutations to their surface proteins in such a way that they can partially escape human immunity. This process is known as "antigenic drift". 2/18
For influenza, this necessitates regular vaccine updates to keep up with an evolving virus population. Other RNA viruses like measles mutate quickly but are unable to change protein structure to escape from immunity and so these vaccines don't need updating. 3/18
There has been an open question to the degree to which SARS-CoV-2 will behave like influenza and require vaccine updates. However, emerging evidence suggests that antigenic drift is likely. 4/18
First off, we have new studies on antigenic drift in seasonal coronaviruses. Katie Kistler and I have shown abundant adaptive evolution in the spike proteins of viruses OC43 and 229E consistent with antigenic drift (bedford.io/papers/kistler…). 5/18
We also now have direct serological evidence of antigenic drift in 229E from @eguia_rachel, @jbloom_lab et al, suggesting that reinfection by seasonal coronaviruses that occurs every ~3 years is in part due to evolution of the virus. 6/18
For SARS-CoV-2, we only expect antigenic variants to spread once enough people have been infected to give these variants a transmission advantage gained by the ability to reinfect some portion of individuals immune to the original variant. 7/18
At this point, many countries have had perhaps 10% to 20% of their population infected (medrxiv.org/content/10.110…), and so we expect some weak evolutionary pressure for antigenic drift. 8/18
We've now seen the emergence and spread of several variants that may have some antigenic impact. These variants are generally labeled based on the mutation to the SARS-CoV-2 spike protein. For example N439K has a change from asparagine (N) to lysine (K) at site 439 in spike. 9/18
This variant N439K is now present in ~5% of recent viruses from Europe (nextstrain.org/ncov/europe?c=…) and shows evidence of escape from some monoclonal antibodies and decreased reactivity to some convalescent sera (@emcat1, @robertson_lab et al biorxiv.org/content/10.110…). 10/18
Recent announcements have focused on spread of N501Y in the UK () and independent emergence and spread of N501Y in South Africa (). 11/18
The UK variant in particular has several mutations that are of biological interest and deserves close attention (@arambaut, @pathogenomenick et al virological.org/t/preliminary-…). 12/18
Independent emergence and spread of variants is suggestive of natural selection where in addition to N501Y we see for example S477N emerging independently in Europe (nextstrain.org/ncov/europe?c=…) and in Australia (nextstrain.org/ncov/oceania?c…). 13/18
@firefoxx66 is maintaining a list of mutations of interest with associated @nextstrain views and relevant publications at github.com/emmahodcroft/c…. 14/18
All this said, I'm not concerned that these variants will significantly reduce vaccine efficacy in the 2021 rollout. Most circulating SARS-CoV-2 viruses do not have any mutations in the spike receptor binding domain (nextstrain.org/ncov/global?c=…). 15/18
Additionally, single mutations will generally have small impacts on polyclonal immune responses and the strong immune response to the mRNA vaccines would suggest that a large antigenic change would be needed to significantly reduce efficacy. 16/18
However, we may see modest reductions in vaccine efficacy due to antigenic drift and will likely need a process in the coming years by which we update the spike variant used in the vaccine to best match circulating viruses. 17/18
Going forward, I suggest:
1. Emerging variants should be assayed against sera from recovered and vaccinated individuals to test for antigenic effects
2. Immunization records should be connected to genomic surveillance to identify variants involved in breakthrough infections
18/18

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More from @trvrb

17 Dec
There has been a significant question about the degree to which Thanksgiving holiday and associated travel and social gatherings may have contributed to transmission of #COVID19. Here I try to briefly address this question. 1/8
Based on known incubation periods (nejm.org/doi/full/10.10…), we expect, on one end, some infections arising on Nov 26 to become symptomatic on Nov 30 and on the other end, for some infections arising on Nov 30 to become symptomatic on Dec 6. 2/8
This brackets the window where we expect most of the increased case load to be. However, most states only list cases based on date of report rather than date the case became symptomatic. This causes jitter that's hard to deal with when looking for a Thanksgiving effect. 3/8
Read 8 tweets
12 Dec
Although the US is continuing to hit records for daily #COVID19 cases reported, the rate of exponential growth has slowed. Mortality is still catching up to increased case loads and I expect daily deaths reported to further increase. 1/8
This plot summarizes the overall picture. Bubble size is proportional to daily cases per capita from @COVID19Tracking and bubble color shows Rt from rt.live. Timepoints are shown up to two weeks ago due to delay in reliable estimates of Rt. 2/8
The Midwest and Mountain West had rapid growth during October resulting in large epidemics in November, but they're now starting to plateau or decline in incidence. Although current incidence is lower, the epidemic is still growing in much of the East Coast. 3/8
Read 8 tweets
10 Dec
The US reported over 3000 deaths from #COVID19 today and the 7-day average of deaths has hit a record with today's average of 2276. Here, I dig into these grim mortality numbers and look at deaths across ages and across weeks in the epidemic. 1/14
I'm using data from @CDCgov (cdc.gov/nchs/nvss/vsrr…) that records weekly deaths involving COVID-19 as well as deaths from all causes. These data use actual date of death but there is a reporting lag. 2/14
CDC reports 261k deaths involving COVID-19 in this dataset. Over half of these deaths are in individuals 75 or older and over three quarters are in individuals 65 or older. 3/14
Read 14 tweets
4 Dec
The US is reporting over 2000 deaths per day from Dec 1 and I believe will do so consistently throughout December based on daily case loads above 120k starting early November. 1/4
A drop in reporting over Thanksgiving weekend has made for some difficulty in directly comparing 7-day averaged deaths, but the trend is clear. Red bars are daily reported deaths from @COVID19Tracking and black line is 7-day sliding average. 2/4
The simple projection of 1.7% of reported cases into deaths 22 days later has remained largely accurate, although drop of reporting during Thanksgiving weekend is quite clear. We'll know soon whether 7-day average returns back to projection. 3/4
Read 4 tweets
1 Dec
I don't think that this study by Basavaraju et al from @CDCgov can be taken as evidence that #COVID19 was circulating in the US in December 2019. 1/10
academic.oup.com/cid/advance-ar…
The authors do a careful serological investigation, but it necessarily suffers from testing a large number of samples with an assay that is not perfectly specific. 2/10
The ELISA used by the authors has a stated specificity of 99.3% and the authors tested 519 "true negative" blood samples collected from 2016 to 2019 from healthy adults and suspected hanta virus patients and observed 3 false positives (0.6%) matching this specificity. 3/10
Read 12 tweets
26 Nov
Another update on #COVID19 circulation in the US. With today's report we're seeing an average of ~172k daily cases reported compared to ~157k a week ago, and we're seeing ~1650 daily deaths reported compared to ~1200 a week ago. 1/10
Although this is still a staggering amount of cases and growing daily, the rate of growth at the US level appears to be (at least temporarily) slowing. Here, I've plotted data from @COVID19Tracking, showing daily cases in the US on a log scale alongside 7-day moving average. 2/10
Throughout October we saw steady exponential growth of the US epidemic (indicated by linear-on-a-log-scale dynamics and shown in the graph as the dashed straight line). Early November outpaced this steady growth but has recently slowed. 3/10
Read 10 tweets

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