It is so helpful to have multiple estimates that can be used for triangulation, and very encouraging when they agree! Thank you all!
The results from @MRC_Outbreak about the reduction in #COVID19 transmission in Switzerland are now very similar to our estimates from @ISPMBern at @unibern https://imperialcollegelondon.github.io/covid19estimates/#/details/Switzerland …pic.twitter.com/V5hj6xdcsv
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Add the work of @tanja819 and her team to that as well:https://bsse.ethz.ch/cevo/research/sars-cov-2/real-time-monitoring-in-switzerland.html …
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Infections declining faster than in Germany (stringency only 70/100) Question: Which of the swiss measures (that are not also implemented in Germany) supress R most effectively ? I thought the measures in both countries similar, but Switzerland more successful in reducing R<1pic.twitter.com/SDPfZIo8fD
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I noticed that the R0 started much higher in Germany than in Switzerland.
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Very interesting and great work. My brain struggles how the observed R can (is being) related to R0 (in my understanding: the biological reproduction number in unprotected population). And would R0 vary with age? True R0 would be important for policy decisions.
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contrary to common misconception, "R0" is not an intrinsic property of the pathogen. It also depends on population mobility and other things. Think of it as the "R" without any containment measures. (Also often overlooked "serial interval" just as important than R)
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Concratulating Sitzerland for *crushing* the curve (R<1-x
) not only flatten (R=1+x)
Germany, unfortunately, just fails to reduce R<1. What do they do different than Switzerland ?pic.twitter.com/I73qDtKxAj
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Nothing really stands out to me. Life in my little town is almost indistinguishable from before. They are limiting entrance into supermarkets and most shops are closed but everyone is walking around as usual without masks. Perhaps just early messaging and low density living.
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Hmmm... is R_t as discontinuous as this plot suggests? If so, would an earlier complete lockdown not always be the answer to get R<1? And would an earlier complete lockdown also not have pushed Rt lower than its eventual value?
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Epidemiologically, the solution is simple: Implement lockdown at maximum intensity (R -> 0.5). but for relatively short time, i.e. 6 weeks after which daily new infections decrease to near zero. THEN relax lockdown and control beginning re-outbreaks by testing/tracking
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Wydaje się, że ładowanie zajmuje dużo czasu.
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