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I do think this will become clear shortly as we observe what happens in countries like Denmark and Switzerland or states like Florida which are farther along on their B.1.1.7 trajectories relative to the US as a whole. 13/13
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Increased transmissibility of B.1.1.7 will certainly stretch out circulation of COVID-19 and make it harder to bring under control relative to the non-B.1.1.7 scenario, but I'm not sure at this point how much of a spring B.1.1.7 wave to expect. 12/13
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It's not clear to me at this point whether biological increase in transmissibility of B.1.1.7 will "win" against further improvements to seasonality and immunity in ~6 weeks time at the end of March. 11/13
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However, current prevalence differs across states and B.1.1.7 may become dominant in some areas of the US earlier than other areas. 10/13
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Recent work from
@genesareclever,@gkay92,@K_G_Andersen and colleagues looking at B.1.1.7 in the US (https://www.medrxiv.org/content/10.1101/2021.02.06.21251159v1 …) estimated a similar rate of frequency increase, which suggests B.1.1.7 will reach 50% frequency in the US by perhaps late March. 9/13pic.twitter.com/QbZZpxi0YB
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A similar rate of growth of B.1.1.7 is observed in Denmark and Switzerland with Denmark reaching ~20% B.1.1.7 frequency and Switzerland reaching nearly 20% B.1.1.7 frequency at the end of January. 8/13pic.twitter.com/pWPWPYZYD8
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However, the rapid take-off of B.1.1.7 will push against these gains. The trajectory of B.1.1.7 in the UK decently fits a simple logistic growth model with a growth rate r of 0.07 per day as assessed using SARS-CoV-2 genome data from
@GISAID. 7/13pic.twitter.com/WwrWEWS4Gi
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Solely based on continued improvements to seasonality and continued increase in population immunity due to natural infection and vaccination I'd expect this trend to largely continue and the US fall/winter surge to be brought further under control. 6/13
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This shows "inflation" in Nov and Dec followed by "deflation" starting mid-Jan. The Dakotas and surroundings show a similar trajectory to other states, but were ahead of the curve with an epidemic peak in Nov. 5/13pic.twitter.com/W6lV2ULjWI
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The US fall/winter epidemic is illustrated here as a series of twice monthly snapshots with bubble size representing per-capita case counts in a state and bubble color representing Rt, where red indicates growing epidemics and blue represents declining epidemics. 4/13pic.twitter.com/mSC0w42ckG
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Generally, Rt > 1 in Nov and Dec corresponding to rising cases and drops below 1 in Jan corresponding to falling cases. We've seen a steady decline in Rt from Nov to Feb. Thus, current decline is not a sudden shift in circumstance, but resulted from reaching Rt < 1. 3/13
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Working with case counts from
@COVID19Tracking and Rt estimates from https://epiforecasts.io , I'm showing US confirmed cases broken out by state alongside transmission rate as measured by Rt through time. 2/13pic.twitter.com/hhbbuQsLaa
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After a ~2 month plateau from mid-Nov to mid-Jan, the US
#COVID19 epidemic has undergone a steady week after week decline and is now back to daily case counts last seen in late October. A thread on what we might expect going forwards. 1/13pic.twitter.com/M7vrdECUX2
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Follow up #1: From March (https://twitter.com/trvrb/status/1242628564324761606 …) until December, my expectation was antigenic evolution like in seasonal CoVs which are roughly as fast as flu B (see https://bedford.io/papers/kistler-hcov-adaptive-evolution/ …). With VOCs, I now expect more like flu A, but this could be pace that's not sustained.
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Additionally, with new vaccine technologies (and particularly mRNA vaccines) we'll have the ability to more effectively chase the virus than we do with the seasonal influenza vaccine, which suffers from lower immunogenicity and longer lead times for strain updates. 18/18
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That said, the evolution that we've seen with the recent variants of concern may represent an unusual circumstance in which the virus has made a large evolutionary jump to a new "fitness peak" and that won't be seen year-after-year. 17/18
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Both simple rate of amino acid substitutions in spike S1 and titer drops in serological assays suggest that SARS-CoV-2 might be in the same ballpark as influenza A in terms of capacity for antigenic evolution. 16/18
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This titer reduction is very roughly what is seen in an average of 3 years of influenza H3N2 evolution, but yearly jumps of 8-fold titer reductions in H3N2 are historically not uncommon, with H3N2 showing a staccato pace to its antigenic evolution. 15/18
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The comparable datapoint for SARS-CoV-2 is work by Wibmer et al (https://www.biorxiv.org/content/10.1101/2021.01.18.427166v1 …) and Cele et al (https://www.medrxiv.org/content/10.1101/2021.01.26.21250224v1 …) showing an ~8-fold titer reduction in neutralization assays to the 501Y.V2 variant from South Africa. 14/18https://twitter.com/trvrb/status/1351785352793493505 …
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The rate of antigenic drift in influenza can be quantified by per-year fold-reduction in serological assays. For influenza H3N2, this rate averages ~1 two-fold titer reduction per-year. 13/18
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