As discussed at #EPIDEMICS8 breakout session, @saCOVID19mc have started characterizing the #SARSCoV2 variant #Omicron; working estimates for this new variant are critical so the globe can plan with the best information possible: drive.google.com/file/d/1hA6Mec…

#NotYetPeerReviewed Based on S-Gene Target Failure (SGTF), we estimated #Omicron growth rate across RSA provinces. Gauteng has the clearest signal, and indicates growth of 0.21 (0.14, 0.27)/day, corresponding to a doubling time of 3.3 (2.5, 4.6) days.

#NotYetPeerReviewed

Now peered reviewed at @IntJEpidemiol: challenges (& a solution) for the test-negative study design when data are gathered during public health response in a population with clustered vaccine uptake (work w/ @TJHladish, W. John Edmunds, & @rozeggo)

academic.oup.com/ije/advance-ar… Briefly, this design is biased when mixing different testing data streams-e.g. tests for sick people & tests for *contacts* of sick people. That bias is exacerbated when vaccine coverage is homophilous-i.e. if you're vaccinated, likely your contacts are too & vice versa.

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NB: NOT PEER REVIEWED cmmid.github.io/topics/covid19… We calibrated a model used in a lot of @cmmid_lshtm COVID-19 work to the South African outbreak & interventions.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NB: NOT PEER REVIEWED

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NB: NOT PEER REVIEWED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NB: NOT PEER REVIEWED

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.