Near real-time tracking the spread of N501Y (B.1.1.7, B.1.351) in Geneva, Switzerland. We project that N501Y will reach a frequency of 82% (95%CI: 53%-95%) by 1 March 2021. @EpiPose 1/4 ispmbern.github.io/covid-19/varia…
We estimate a 33% (95% CI: 15%-56%) and 47% (95% CI: 21%-78%) increased transmissibility of N501Y variants, assuming a generation time of 5 and 7 days, respectively. 2/4
While these estimates are somewhat lower than earlier findings for B.1.1.7 in the UK, the increased transmissibility underlines the necessity of strict control measures in order to prevent an increase in SARS-CoV-2 incidence in Geneva and the rest of Switzerland. 3/4
There is lots of talk about #COVID19-related excess mortality. How does the situation look like in Switzerland? 🧵1/5
2020 started with a mild influenza season and Switzerland was on its way to a year with negative excess mortality. Then came the pandemic and a relatively early ‘lockdown' limited the number of #COVID19-related death to around 2,000 during spring. 2/5
Until autumn, Switzerland still had hardly any excess mortality. Then came the second wave in October and hesitancy to introduce control measures resulted in an excess mortality of 5,527 by week 50. 3/5
There is great concern about the potential spread of the new #SARSCoV2 variant (B.1.1.7) outside the UK. How many cases do we have to expect in Switzerland and will they spread further? Let's do some back-of-the-envelope calculations. 1/n ecdc.europa.eu/en/publication…
Around 10,000 British visitors have arrived in Switzerland since December 14. Many of them are visiting Switzerland for their ski holidays. 2/n tagesanzeiger.ch/auf-der-suche-…
The Real-time Assessment of Community Transmission (REACT) programme estimated #SARSCoV2 RT-PCR swab-positivity (prevalence) in the UK during early December at around 1%. That would correspond to around 100 positive cases among the British visitors. 3/n imperial.ac.uk/medicine/resea…
The Swiss government issued an ordinance stating that restaurants can be kept open when R < 1, and must close when R > 1 at the cantonal level. Worth having some reflections about how R values should influence policy decisions. A thread. 1/n admin.ch/opc/de/classif…
In Switzerland, these policy decisions will be made based on point estimates of R that are provided with two (!) decimal places. For example, R is currently given as 0.98 in the canton of Valais. 2/n covid19.admin.ch/en/repro/val?t…
To be honest, the ordinance sounds a bit like a technocratic idiocy to me. But let’s have a look at how @GOVUK uses R as a guide during the pandemic response. 3/n gov.uk/guidance/the-r…
Letzten Freitag hat der Bundesrat eine Art "Ampelsystem" eingeführt. Macht dieses und die in den Medien diskutierten Anpassungen aus epidemiologischer Sicht Sinn? In meinen Augen lautet die Antwort ganz klar nein. Ein Thread. 1/n edi.admin.ch/edi/de/home/do…
Zuerst einmal: Wozu benötigt man ein Ampelsystem? Ein solches System erlaubt bei klar definierten Schwellenwerten verschiedene Massnahmenpakete schnell einzuleiten. 2/n
Dies erlaubt es der Bevölkerung auf anstehende Massnahmen vorbereitet zu sein, bietet deutlich mehr Planungssicherheit und kann im besten Fall einen raschen Anstieg der Epidemie verhindern oder zumindest abschwächen. 3/n
What is the overall infection fatality ratio (IFR) of #SARSCoV2 in Germany? The widely discussed Gangelt study now got published in @NatureComms. There are a number of issues with its estimate of the IFR. A thread. (1/n) nature.com/articles/s4146…
What do we already know about the IFR in Germany? At @ISPMBern, we published a modeling study that estimates the IFR at 0.8% (95% CI: 0.5%-1.1%) for Bavaria and 0.7% (95% CI: 0.5%-1.3%) for Baden-Württemberg based on 1,049 and 802 deaths. (2/n) journals.plos.org/plosmedicine/a…
The IFR can also be estimated from seroprevalence studies. A recently published report from Munich (Bavaria) found an IFR of 0.8% (0.6%-1.1%), confirming our earlier estimates. (3/n) klinikum.uni-muenchen.de/Abteilung-fuer…
In the current situation, it is critically important to follow the epidemic trends of #SARSCoV2 across age groups and cantons. Changes in the number of daily confirmed cases, hospitalizations, ICU occupancy and deaths can all provide meaningful insights. (2/n)
One can fit a negative binomial generalized linear model (glm.nb in R) to the data with reported numbers as a response variable and date and weekend as predictors. This allows to estimate the exponential increase or decrease of the different indicators of the epidemic. (3/n)