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…
So let's have a look at the Gangelt paper. In general, this is a well done study investigating an early outbreak of #SARSCoV2 in a small community of 12,597 people. They estimate an infection attack rate of 15.5% corresponding to 1,956 people. (4/n)
Then, they estimate the IFR based on 7 deaths (7/1956 = 0.36%). You might say: Wait, what? How can you estimate an IFR based on 7 deaths only? Doesn't chance come into play here? You're right. With such a small number of deaths, you can't get precise estimates of the IFR. (5/n)
Assuming binomial sampling, one obtains a 95% CI of 0.14%-0.74%. While the authors report such a CI in the main text, they hide it for the numbers in the abstract. What is the rationale of presenting numbers with a precision that does not exist? This is somewhat concerning (6/n)
But there is more. According to this article from @hfeldwisch, they did not include all deaths that stem from infections up until the end of the study period. Instead of 7, there were probably 13 deaths. (7/n) medwatch.de/2020/11/26/die…
This would result in an IFR of 13/1956 = 0.66% (95% CI: 0.35%-1.13%). That's interesting, because this estimate is in good agreement with the results from our statistical modeling study and the seroprevalence study from Munich. (8/n)
While that's an interesting turn of events, I still would not put too much trust into an IFR from such a small community and with such a small number of deaths. Especially when there are much bigger studies around that are based on hundreds or thousands of deaths. (9/n)
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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)
The @SwissScience_TF proposes to halve confirmed #SARSCoV2 cases every two weeks to reach less than 500 cases in January. What does this mean regarding the reproduction number? A thread about doubling times and half-lifes of #SARSCoV. (1/n)
The figure (in German) shows the relationship between the reproduction number and the time in which the number of new #SARSCoV infections double (red) and reduce by 50% (green). (2/n)
In early March 2020, the virus spread uncontrolled in Switzerland with a reproduction number of 2.8 which corresponds to a doubling time of 3 days. (3/n)
Die @SwissScience_TF schlägt vor, dass wir die Fallzahlen alle zwei Wochen halbieren, um im Januar wieder auf unter 500 täglich bestätigte Fällen zu gelangen. Was bedeutet das bezüglich der Reproduktionszahl? Ein Thread zu Verdoppelungs- und Halbwertszeiten bei #SARSCoV2. (1/n)
Die Grafik zeigt den Zusammenhang zwischen der Reproduktionszahl und der Zeit in welcher sich die Anzahl Neuinfektionen von #SARSCoV2 verdoppeln (rot) bzw. halbieren (grün). (2/n)
Anfang März 2020 konnte sich das Virus in der Schweiz unkontrolliert ausbreiten, was einer Reproduktionszahl von 2,8 und einer Verdoppelungszeit von 3 Tagen entsprach. (3/n)
Reichen die seit 29. Oktober geltenden Massnahmen um eine Überlastung des Gesundheitswesens zu verhindern und die Anzahl Neuinfektionen mit #SARSCoV2 wieder auf ein überschaubares Niveau zu bringen? Thread über die zentrale Rolle einer frühzeitigen Einführung von Massnahmen. 1/n
Der Bericht wies darauf hin, dass die Testpositivität über die letzen sieben Tage bereits 7% betrug, was über dem von der @WHO empfohlenen Grenzwert von 5% lag. 3/n
Mir fällt auf, dass nach wie vor Schwierigkeiten bestehen, die täglich gemeldeten Zahlen des @BAG_OFSP_UFSP zu #COVID19 richtig zu interpretieren. Ein Thread. (1/n)
Laborbestätigte Fälle: Die täglich gemeldeten Fälle beziehen sich meist auf Tests welche während den letzten drei Tagen durchgeführt wurden (orange Balken in den Grafiken des @BAG_OFSP_UFSP). (2/n)
Das bedeutet, dass wir die tatsächliche Anzahl laborbestätigter Fälle der letzten 2-3 Tage noch nicht kennen, und daraus keinen Trend ableiten können. (3/n)