What about a 99.99% reduction in travel? Wuhan has 11 million and 1% of that is 100k, I'd imagine the quarantine is more successful than preventing 100k people from travelling.
As I said in a different comment, 5 million people leave Wuhan every year around this time, and the model that made this 99%/25% prediction is using data that already takes into account this mass-migration.
I think their point is that with such a high reproduction number, the impact of anyone slipping through is amplified so much that reduction in travel alone will not do much to stop the spread.
> reduction in travel alone will not do much to stop the spread.
This is exactly what you can't conclude from the analysis that was done, the numbers matter significantly.
If a 99% restriction locally gives a 25% reduction globally, that tells us very little about what happens with a 99.99% restriction, which is probably closer to what has been achieved.
It's not. The model used historical figures from Jan 2017 as its input data, so would also be taking into account these New Year's mass-migrations. Also, this year's stopped at a relative early stage.
Sure, if you want to get precise, you can model a 0% reduction in traffic for the first 10 days, then a subsequent reduction to 99.99%. The numbers will be completely different than modelling a reduction to 99% for the whole period.
Quoting numerical estimates without understanding how the underlying model compares to reality, is just stupid.
Are you replying to the wrong comment? The article I posted is about five million having left the city _before lockdown_, which completely invalidates any model.
I am replying to the correct comment. Like I said, the model uses input data from Jan 2017, which will contain exactly this same migration as what you're currently discussing. This lockdown is strictly an improvement on the modelled situation. Read the paper describing the model, then come back and reply.
Figure 4 in the images from this tweet[1] (taken from the same paper above, page 8) show the effect of a 99% reduction in travel, over 65% of people in cities across China will become infected.
> Dr. Eric Feigl-Ding (Eric Ding) is a health economist, epidemiologist, and nutrition scientist at the Harvard Chan School of Public Health, and an expert advisor to the World Health Organization.
I'm not usually one for relying heavily on authority, but this guy[1] is likely to know when the R0 number looks very, very bad.
Literally thousands of other people have the same qualifications as him and are also not freaking out over Twitter. I'd say the data leans more heavily in the other direction.
If 1% of all (medical) scientists is 500 then that means there are 50k (medical) scientists in the whole world. With some basic web searching, that would appear to be an underestimate; "thousands" would be a better estimate.
[1] https://www.scmp.com/news/china/society/article/3047720/chin...