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@robert_dyrdak Thank you Robert! I wouldn't have written it up without your encouragement, & it's a better paper thanks to your proofreading! Will buy you a drink next time we meet!

The default scenario is for a medium-size city in Switzerland with a fairly slow-spreading outbreak and strong infection control measures. You can adjust all parameters (sometimes a little fiddly, we are working on it). The population parameters can be adjusted in this panel:

The basic epidemiological parameters can be adjusted in this panel. You can set the annual average R0, the delay from infection to transmission, and the typical infectious period. These add up to a serial interval of 8 days in our defaults.

In addition, to estimate hospital bed demand, you can select the average length of a hospital stay. This applies to both regular and ICU beds additively. Presumed seasonal variation can also be adjusted.

To explore the effect of infection control measures, you can modify the graph in this panel. The value modulates the baseline parameters set above. Moving dots down implies more control: 1 corresponds to no control, 0 to avoiding all infections.

Our assumptions on severity are summarized in this table informed by data from China CDC. Most columns are editable and allow you to specify what fraction of cases show up in statistics, how many of those are severe, critical, and fatal (in a nested fashion).

The main outputs are graphs of cases, severe cases, critical cases, and cumulative fatalities. (show/hide lines by clicking on the legend). OECD average *total* hospital capacity (scaled to population) is indicated as a horizontal line.

We hope this is useful, we welcome suggestions, and want to stress that these are scenarios of simplistic models. The actual outcome depends above all on what we do to prevent the spread of #COVID19.

After seeing a tweet on the many pages of obituaries in Bergamo's newspaper, I went and counted them in issues in Jan, Feb, and March. Death counts are at >7-fold above baseline corresponding to 7 weeks of excess deaths -- possibly attributable to #COVID19.

So proud of Richard Neher, Ivan Aksamentov, & Nicholas Noll for working SO hard on this amazing model which helps people understand #COVID19 #SARSCoV2 model predictions & hospital bed demand. Developed also with @robert_dyrdak & Jan Albert These are amazing people!!

Happy to have been given the opportunity to talk about #covid19 at karolinska

We have completed our first experiments on neutralization of Omicron by Pfizer BNT162b2 vaccination elicited immunity Manuscript available at sigallab.net and should be available on medRxiv in the coming days

This is our first set of data and is not corrected for values going below the lowest dilution used - we present the raw fold change, which is likely to be adjusted as we do more experiments.

Thank you Sandile for leading, Khadija Khan, Farina Karim, Laurelle Jackson for making it possible, and our terrific collaborators Penny Moore, Tulio de Oliveira, Richard Lessells, Houriiyah Tegally, PhD 🇲🇺. There are many more key people to thank, but I need to get some sleep first

Omicron antibody neutralization thread, with preliminary results, and substantial caveats. Most credit to Daniel Sheward. We’ve been racing to generate neutralization data as fast as possible, and our first results were read this afternoon (1/n).

Key to all of this was the early sharing of data from South Africa (driven by Tulio de Oliveira), and the identification of S-gene target failures as a means of screening for Omicron samples, which is now used globally (12/n)

On our side, Daniel Sheward has been exceptional in all this, as have key collaborators Karlsson Hedestam Lab Alec Pankow, and especially Jan Albert and his team for rapidly identifying and sharing a set of anonymised samples from suspected Omicron cases (13/n)

Another Omicron neutralization thread, this time about monoclonal antibodies. Once again, massive cred to Daniel Sheward, and everyone else from the previous data release. This time, we also need to especially thank LSSI Reddy (1/n)

A brief draft with numbers and some technical details can be downloaded here: tinyurl.com/bdh3snmf - but please expect this to change. Once again, thanks to Daniel Sheward LSSI Reddy and everyone else involved (14/n)

Our paper on the discovery of a new variant of HIV with heightened transmissibility and virulence is out today in Science science.org/doi/10.1126/sc… Teamwork from two consortia, and analysis led by Chris Wymant @chriswymant.bsky.social 1/n