
An international comparison of the second derivative of Covid-19 deaths [pdf] - hdivider
https://www.medrxiv.org/content/10.1101/2020.03.25.20041475v1.full.pdf
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avs733
it is notable that this work is done by an electrical engineer and a
cardiologist, not epidemiologists. More than anything, the arm chair
epidemiology is the our current second biggest danger. Epidemiology is hard.
incredibly hard. It isn't viral marketing. It isn't electrical engineering.
Data isn't pure or assumed to be correct. There data source was basically
websites.

~~~
thu2111
Based on what we've seen so far, electrical engineering and cardiology are
significantly more rigorous than epidemiology, which appears to be more like
economics or social psychology in terms of the robustness of its methods and
quality of its work.

~~~
avs733
Define rigor.

In context I suspect you mean something like "treat data as objective." I can
go to France and pickup and hold the literal kilogram. U can't do that, yet,
with people's brains to the level needed for psych measurement.

Personally, I prefer social sciences and epi methods (get economics out of
here...) Because they are more transparent about the role of the researcher
and the limitations of their data. They don't bluntly trust it...the engineers
I work with largely do. They assume data represents truth and is largely
without meaningful error.

~~~
thu2111
I've elaborated here on what I mean here:
[https://news.ycombinator.com/item?id=22737948](https://news.ycombinator.com/item?id=22737948)

It's not just how much data is trusted (though note: Professor Ferguson at
Imperial appears to trust the data coming out of Italy almost completely).
It's the whole set of problems.

~~~
avs733
Trusting data and data being objective

>Right now I absolutely want to see papers written by physicists studying
COVID-19. Why - because physics is a significantly more rigorous field than
epidemiology. I trust the average physicist to have at least slightly higher
standards, for instance I trust them to at least pretend to care about
statistical uncertainty, and I suspect many of them will upload their source
code. I don't expect any of them to email their paper straight to known-
friendly newspapers. (from your other post)

Is a really...bad idea. Let's not presume knowledge transfers from one
discipline to another, that standards look the same, or that Alan Sokal was
anything other than an egomaniac.

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hdivider
Full title (not possible to put as title because of HN limits):

An international comparison of the second derivative of COVID deaths after
implementation of social distancing measures

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lonelappde
Better comparison:

[http://91-divoc.com/pages/covid-
visualization/](http://91-divoc.com/pages/covid-visualization/)

~~~
xiphias2
This visualization doesn't show the lockdown effects that the paper estimates

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twoslide
I tried fitting a third order polynomial for JHU Covid data, just as a way to
kill time. For all countries, the 95% confidence interval of the second
derivatice overlapped zero (i.e. it can't be estimated very well). We only
have about three weeks of data from the 10th death, for most countries, you
can't fit a very good curve with that.

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bigpumpkin
Can't expect China-like second derivative when countries are not doing these
counter measures:

Isolation of suspected cases and close contacts

Universal masking

Restrictions on travel inside country

Sending doctors from the rest of the country to epidemic centers.

~~~
kspacewalk2
This presumes all of these measures are highly effective, which is far from
certain or obvious.

~~~
vkou
Not taking any of these measures is highly effective at failing to control the
virus. We're currently seeing it play out across Europe and the US.

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chipperyman573
It's been a long time since I took calc. What does the second derivative show
us?

~~~
lsb
Acceleration.

The rate of change of the rate of change of deaths.

The word exponential only occurs once in the paper, and the rate of change of
an exponential is an exponential, so take as many derivatives as you want and
it's still going up. Why they don't take the log of deaths over time isn't
explained.

~~~
dpwm
I've seen very little coverage that really uses the term exponential in a way
that suggests those reporting know the implications of that. I've seen one
plot with a logarithmic y-axis, and that was in the Guardian some time ago.
From it, it appeared a crude heuristic could be drawn that from the point that
lockdown is implemented, the cumulative deaths appear to grow between two and
three orders of magnitude.

I've been grabbing the data put out by Johns Hopkins [0] for the last few days
to update some plots in a very hacky Jupyter notebook.

Crucially, the plots are normalized to (estimated) populations and the y-scale
is logarithmic. I've put them on github in case anyone else is interested [1].

[0]
[https://github.com/CSSEGISandData/COVID-19](https://github.com/CSSEGISandData/COVID-19)

[1]
[https://github.com/dpwm/covid19-analysis/blob/master/Coronav...](https://github.com/dpwm/covid19-analysis/blob/master/Coronavirus%20Deaths.ipynb)

edit: Clarified that though exponential growth is widely used, the
implications of that are not followed up. It's past my bedtime!

~~~
grandmczeb
> I've seen one plot with a logarithmic y-axis, and that was in the Guardian
> some time ago.

You mean like the widely cited NYT Coronavirus death tracker[1]?

[1]
[https://www.nytimes.com/interactive/2020/03/21/upshot/corona...](https://www.nytimes.com/interactive/2020/03/21/upshot/coronavirus-
deaths-by-country.html)

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X6S1x6Okd1st
The methodology don't really explain how they aligned the second derivative
curve to China or why that's reasonable.

I wouldn't put much faith in their predictions.

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squidproquo
If anyone has a forecast for the United States, this website is aggregating
forecasts:

[https://www.unitarity.com/app/challenges/us-coronavirus-
outb...](https://www.unitarity.com/app/challenges/us-coronavirus-
outbreak/events/mar-20)

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daxfohl
I have a hard time believing Spain will have a higher peak than USA.

~~~
fermienrico
You can't look at Spain and USA without considering the total population.

As someone in this thread pointed out: [http://91-divoc.com/pages/covid-
visualization/](http://91-divoc.com/pages/covid-visualization/)

Take a look at the charts of cases/1M people. It is obvious that US will have
more cases simply because of the population.

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bernardv
Very little details on the methodology

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dboreham
How so? They said they computed the second derivative. What more is there to
say?

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willis936
You can’t compute the second derivative of data from May 2020 when it is
currently March 2020. Where did the data come from?

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9wzYQbTYsAIc
China data time shifted to match the country of interest.

~~~
softwaredoug
That seems to make a pretty big assumption western countries can achieve that?
My understanding even a small amount of non compliance has big consequences...

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stefan_
This looks like one of those P versus NP papers.

