Gro-Tsen Profile picture
10 Nov, 4 tweets, 1 min read
It turns out there's a whole genre of “what <language X> sounds like to non-<X> speakers” videos on YouTube, where someone (presumably a polyglot) utters phonetically/phonotactically plausible, but meaningless sounds, of various languages X. I find them really fun to listen to!
For example this one, which went viral some time ago:
The first one I encountered was, I think, this one (for some reason it's gone from YouTube, but miraculously preserved by the Internet Archive):
And the most recent one I came across is this one:

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More from @gro_tsen

10 Nov
On dirait que le covid s'amuse à nous donner des données qui sont délicates ou ambiguës à analyser (stratégie pour nous diviser? 😅). Case in point: les courbes d'incidence dans les métropoles françaises — l'inflection est-elle l'effet du couvre-feu + confinement? immunité?
(Les graphes en question sont tirés de… à qui je fais confiance pour reprendre les données diffusées par les pouvoirs publics.)
Sous l'effet du couvre-feu et confinement, je m'attendrais à voir:
⁃ une baisse soudaine de la pente (logarithmique) dans les quelques jours suivant le 17 octobre pour les courbes de gauche (couvre-feu), et une nouvelle qqs jours après le 30 octobre pour toutes (confinement),
Read 7 tweets
5 Nov
✽ An important clarification which I feel I have to make concerning “herd immunity”, its value and more importantly, its definition. The point is, the basic reproduction number R₀ describes a population that is immunologically AND sociologically “naïve”. •1/32
In other words, R₀ describes (the number of individuals who will be infected, on average, by one infected individual inside) a population which has never come in contact with the virus, but doesn't even know about it, care about it, or take any kind of precaution. •2/32
Consequently, if we apply the formula 1 − 1/R (which itself has many caveats and limitations, but it's not the point I'm trying to make here) to this number R₀, we are computing a herd immunity threshold for a naïve population as described in the previous tweet: … •3/32
Read 32 tweets
26 Oct
Bon, je me suis enfin sorti les doigts du c😶l pour faire un calcul d'espérance de vie perdue par les morts covid en France à ce jour:
⁃ âge moyen des décès hospitaliers: 80.5 ans,
⁃ espérance de vie moyenne¹ des décédés: 11.4 ans.

1. Sans tenir compte des comorbidités.
OK, «espérance de vie des décédés», c'est ridicule. Vous me comprenez: celle qu'ils avaient a priori à leur âge+sexe.

Fine print: j'ai procédé en supposant la fonction morts(âge) continue affine par morceaux pour obtenir les totaux par dizaine d'années publiée sur Géodes.
J'ai intégré ça contre l'espérance de vie publiée sur… et… pour les âges élevés, elle aussi rendue affine par morceaux.
Read 8 tweets
26 Oct
Catalogue de mesures envisagées (élargir le couvre-feu, obliger au télétravail, interdire les longs déplacements, fermer les écoles, fermer d'autres lieux publics…), mais comme d'habitude, rien comme «réquisitionner des chambres d'hôtel pour permettre aux fragiles de s'isoler».
(Sans parler de l'option «ne rien faire de plus», qui devrait au moins être sur la table avant toutes les mesures répressives qui n'ont fait preuve que de leur coût et pas de leur efficacité.)
«Mais ouin! Si on laisse le virus passer, on ne peut pas protéger parfaitement les personnes âgées et vulnérables.» Oui, alors parce qu'on ne peut pas les protéger parfaitement, on n'essaie même pas un tout petit peu …
Read 4 tweets
25 Oct
Perhaps the most frustrating thing in this whole pandemic is how impossible it is to find reliable and readable information about public health measures taken in various places (lockdowns, school and business closures, curfews, mask mandates, etc.). •1/8
That we have unreliable and often contradictory data concerning the virus itself is understandable. But concerning our OWN public actions in response to it, information ought to be near-perfect! Instead, documentation is disastrous. •2/8
I live in France and I can't even keep track of the rules which apply here. They change twice a week and from place to place in a mad, incoherent mess. There isn't even a government Web site recapitulating them all (we're all supposed to read the law, I guess). •3/8
Read 9 tweets
25 Oct
There's something really fishy going on with “effective reproduction numbers” in various analyses of this pandemic. And I'm not talking about predicting the future, I'm talking about analysing the past. Here we see a claim of R~3 for Belgium. •1/21
On the other hand, researchers at the Centre for Mathematical Modelling of Infectious Diseases have a web site computing R(t) for many countries, and their estimates for Belgium never went above 1.5 in the computed time frame:… •2/21
Now briefly speaking, computing R(t) depends on two things: the exponential rate of growth r (=logarithmic slope, =logarithmic derivative) of the number of new cases, and temporal data on infections, notably the “serial interval” and its distribution. •3/21
Read 23 tweets

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