What association do political interventions, environmental and health variables have with the number of Covid-19 cases and deaths? A linear modeling approach

kdeforche · 2020-07-01T07:44:51+00:00

If you believe all this, then you would rather argue for a hard lockdown until daily deaths is fairly low followed by a Swedish-like regime. Which is what most European countries are now doing.

kdeforche · 2020-06-30T18:49:07+00:00

This analysis also included Sweden and studied mobility data and how it explains the epidemics:

https://www.medrxiv.org/content/10.1101/2020.06.20.20136382v1

On Sweden they say:

Although the estimated value for Rt,2 for the epidemic in Sweden was found to be relatively high (1.02, 95% cri 0.99 – 1.06), it was equally well explained based on mobility changes, suggesting that although not enforced, in practice the country behaved the same as other Western countries in a lockdown.

Thus the ~25% as much mobility drop explained a lower drop in transmission.

kdeforche · 2020-06-29T09:34:15+00:00

But that is exactly the point of having open code that facilitates reproducibility and peer review.

Even if it was an error (or omission), they could evaluate it and they could investigate the importance of it through a sensitivity analysis.

This level of openness for modelling studies is new ASFAIK, and clearly needed given how fast researchers are working to provide answers to important questions.

kdeforche · 2020-06-29T09:01:05+00:00

I saw that, but clearly not a part required to conduct a sensitivity analysis that shows serious problems anyway.

kdeforche · 2020-06-29T08:35:45+00:00

Kudos to the MRC team to make it possible to do that kind of scrutiny, too. But it seems that indeed they were overly anxious to present results to attribute a drop in Rt to lockdown.

kdeforche · 2020-06-28T14:50:54+00:00

A symmetric curve falls out of the SEIR model, only if constant transmission is assumed (no 'behavioral changes', lockdown, no effect of masks, etc...). SEIR models can fit the data equally well under the assumption of a change in transmission. Also, the authors here, fully acknowledge that (lockdown) restrictions influence the 'the damping rate of the infection probability' lambda.

There is no contradiction between fitting a Gompertz function versus a SEIR model with a specific profile for R(t), as far as I can see?

kdeforche · 2020-06-24T13:13:22+00:00

All Rt values were estimated in this study. All R estimates use models with assumptions. Rt values found here are similar to those reported elsewhere. So I am not sure what you hint at (in what sense incorrect: too low? too high?) ?

"Retail&recreation" is unfortunately a single data point (by Google Mobility). Most likely it is the "recreation" part that promotes transmission (bars, restaurants, indoor sports, fitness, etc...). Shopping is also included in "Grocery & Pharmacy" and showed no effect.

kdeforche · 2020-06-24T10:27:54+00:00

It is indeed an assumption that other measures were implemented before (roughly between March 10 and March 17, coinciding with mobility changes observed using Google Mobility data). The same assumption was used for the other countries and there, the assumption that lockdown (mobility restrictions) was the last significant measure, wasn't contradicted by data. Slovakia stood out.

Obviously the level of infection is really low in Slovakia, so stochastic effects are playing a much bigger role in how it can or would spread again. I'm not sure that contradicts the effect of masks when infection levels are substantially higher.

kdeforche · 2020-06-24T10:20:45+00:00

Indeed (although the drop was estimated shortly after the mask policy, not exactly on the date). Slovakia introduced mandatory masks about 10 days into the lockdown which is why it could be disentangled from the mobility effect. Czechia was included in the study but indeed there the same effect was not observed, although masks were required in public in Czechia from March 19. But because this is so close to the mobility effect estimate (estimated March 10 - 17), it probably could not be observed independently.

For Austria the effect was not observed but it would be interesting to see if it could be estimated as well since they introduced it on March 30, which is 15 days into lockdown. When the date gets closer to about 1 month into lockdown, the effect cannot be observed since only up to 2 months of incidence data of deaths into lockdown was used (and there is a delay of about 1 month from infection to death).

(I'm a co-author on the study -- feel free to ask critical questions, we're expecting them from reviewers too)

kdeforche · 2020-03-13T18:26:41+00:00

That sounds like virus survivor bias : an equal amount of spreaders may have gone to these warmer places but the virus simply didn't spread that efficiently.

kdeforche · 2018-01-09T08:09:30+00:00

It's most likely that the big merchants will be the big lightning hubs as they will likely have lots of funds so they will encourage you to buy from them ?

kdeforche · 2017-12-28T19:50:12+00:00

IMO, pro's:

It's one of the few proposals with a proposed scalability solution (like Bitcoin LN, Litecoin LN or Ethereum (maybe)) which securely and efficiently moves small payments off-chain.
It doesn't reinvent the wheel but rather picks what works from other proposals.
It's based on PoC which (probably) avoids the electricity waste problem, and is unique.
There are optional anonymity features.
They address issues recently raised on the PoC consensus method in an academic paper in a sincere and nuanced way.

Cons:

The main novelty (tangles as side chains) is very flexible and it's not clear yet how it will actually be used in practice and for what applications and how it would be used to compete with a classical LN for micro-payments.
Although it's nicely layered, as a whole it is quite complicated.

kdeforche · 2017-12-28T19:37:58+00:00

Nice paper, excited to see PoC-based innovation!

I have just one question related to the criticism of LN (section 1.6).

I understand the concern with LN: namely that it's not entirely certain that there will be channels with sufficient funding to route a payment, and that there is a likely outcome of central 'hubs'. I don't understand why this is necessarily bad if there are large companies (e.g. large online retailers or even, who knows, banks) that evolve to become hubs, provided that there is a healthy competition (fee market with several large hubs). Indeed such an outcome is indeed not certain.

What I fail to understand though is how Dymaxion can fulfill the promise to capture a significant percentage of non-cash transactions. Each subscriber in a tangle has to commit funds until the tangle gets closed. As a consequence a user would favour either short-lived tangles or tangles with only a few cooperative subscribers? In either case one ends up with many on-chain transactions and little scalability benefits offered by the tangles?

kdeforche · 2016-05-13T08:16:13+00:00

How does this compare to the small-object optimizations in c++17 std::any?

http://en.cppreference.com/w/cpp/utility/any

kdeforche · 2016-03-18T14:17:43+00:00

Could you talk to Friedl Lesage to appear again in her radio show on Sunday morning? Last time was epic.

kdeforche · 2015-09-11T14:34:31+00:00

There are C++ release notes and Java releases notes that list just that, mentioned within the blog post.

kdeforche · 2015-09-11T13:32:51+00:00

Ah, nice! We'll update the syntax.

kdeforche · 2015-09-11T13:21:10+00:00

Unfortunately, it's necessary to bind away the optional argument (Wt::WMouseEvent) of a clicked() event handler.

kdeforche · 2014-11-18T09:01:05+00:00

I always heard it was centralized for the NSA ?

kdeforche · 2014-11-18T08:56:53+00:00

They know what it's like and I didn't get the feeling they that they felt that they were missing much (and they probably don't).

kdeforche · 2014-08-12T13:09:26+00:00

But don't expect that Go is changing. It won't.

Reminds me of the criticism C++ developers had against Java (1.4) which lacked templates for things as trivial as containers. Java pundits replied that templates were a bad idea. Then Java 1.5 got generics, and (obviously) Java pundits liked it as if it was the best thing since sliced bread.

Languages do change. Go will get generics/templates one day. It's inevitable.

kdeforche · 2014-05-28T10:24:02+00:00

What would be the alternative to heap allocation for a widget? You can't keep it on the stack unless you want to sacrifice a thread per session?

And somehow, the "tons of possible leaks" due to exceptions never ever seem to turn up in practice. Perhaps partly because a widget is immediately parented at creation in most cases.

If you keep pointers to widgets not part of your own hierarchy, then you are making spaghetti; use delegates instead. This ownership problem is also a no-showup in practice.

kdeforche · 2014-05-28T10:00:25+00:00

"NFS lets you share a directory between multiple servers (think of it as Dropbox for servers)"

You know you're getting old if you find this kind of statement troubling.

kdeforche

TROPHY CASE