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Carl A. B. Pearson

12 Jan, 5 tweets, 3 min read

@timwrussell

Analysis of novel SARS-CoV-2 variant in South Africa. Like the variant in the UK, 501Y.V2 is associated with a resurgence of the COVID-19 pandemic.

work w/ @timwrussell @_nickdavies @AdamJKucharski John Edmunds & @rozeggo

NB: NOT PEER REVIEWED cmmid.github.io/topics/covid19…

@cmmid_lshtm

We calibrated a model used in a lot of @cmmid_lshtm COVID-19 work to the South African outbreak & interventions. In this model, to explain the increasing epidemic, 501Y.V2 needs to be either more transmissible or evading cross-protection.

NB: NOT PEER REVIEWED

If there is cross-protection against 501Y.V2, it's roughly 50% more transmissible. If it has the same transmissibility, then prior infection only confers 80% protection against 501Y.V2.

Both of these are big public health problems!

NB: NOT PEER REVIEWED

We also saw indications of increased severity, but many potential explanations there.

Both increased transmissibility and severity call for urgency in vaccination and continued vigilance in other measures, and continuing analysis of new variants.

#COVID19

NB: NOT PEER REVIEWED

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More from @cap1024

Carl A. B. Pearson

@cap1024

25 Dec 20

@rozeggo

Submitted (finally) revisions to this analysis of using the test-negative study design in the presence of public health measures. Some new thoughts, in light of pandemic!
Work w/ @rozeggo, @TJHladish, & John Edmunds.

NB: NOT PEER REVIEWED
medrxiv.org/content/10.110…

When criteria for testing vary systematically, the design can be biased. In outbreak & pandemic response, testing happens passively (e.g. you're sick => seek care => get tested) & actively (e.g. co-worker is test+ => contact-tracing => you get tested).

NB: NOT PEER REVIEWED

These represent diff risks and thus differ in thresholds for testing. e.g. in passive route, generic risk => testing conditional on symptoms, but for active scenario => high exposure risk => unconditional testing (e.g. COVID19 TTI protocols).

NB: NOT PEER REVIEWED

Read 8 tweets

Carl A. B. Pearson

@cap1024

7 May 20

@cmmid_lshtm

Thanks to the folks at @cmmid_lshtm and @SacemaQuarterly, and particularly @carivs, @kathmoreilly, Anna Foss, and @SACEMAdirector. This work is now peer reviewed at: eurosurveillance.org/content/10.280…

I want to use this opportunity to talk about "wrong" forecasts.

https://twitter.com/cap1024/status/1243514619618045959

We forecast dates that African countries would *report* 1K and 10K cases. We used very sparse data (first 25 or fewer cases prior to 23 March), w/ deliberately low-detail method (branching processes), assuming global epi estimates & discounting any potential interventions.

That very simple approach worked well for countries that couldn't (or didn't) respond to early warnings like ours. My previous tweets about this report are from 27 March; since then 12 countries have reported >1K cases: who.int/docs/default-s…

Read 9 tweets

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Carl A. B. Pearson

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