Why don’t you just dry them inside-out?
They dry fast and it takes no more time than clipping them onto your clips.
Tobias H
Karma: 299
Hm, all I can find are these small bumps in the end of January. [But I can’t figure out how to attach screenshots here.] I also can’t really see a plateau effect afterwards. An actual reaction, from a cursory view, only seems to happen on the 20. February. I’m not capable of saying whether these bumps show a market reaction or if it’s largely noise. Looking at the time before, it doesn’t seem like an unusual behaviour. [But I’m really not good at properly reading such charts, so I’d be interested in how you came to your conclusions.]
I think one key question, when talking about the EMH, is what we mean for an information to be available.
It’s plausible, that for the public it only became clear around 27. February that Covid19 would be huge.
But it seems some experts knew much earlier. Just a quick browse on epidemiological twitter, for example, and you can find quite some instances of people expecting this not to be contained in the beginning of February. There’s also the case of a swiss epidemiologist who was one of the first to warn swiss national media about Covid19 and claims to have sold all his stocks on January 21 in order to avoid losses from the outbreak.
One reason why you might not regard this information as available, is because it’s costly. In order to profit from it, you need to spend time and effort in order to receive and understand the information. I don’t think that is super plausible, given large banks and corporations with substantial research budgets.
Maybe these researchers were just lucky, there were certainly other researchers at this time who were far less concerned. But given that the information existed with at least some authority and was quite available, I would have expected the markets to at least somewhat react before mid-january.
I wasn’t sure whether it was the right place to post, as I myself didn’t feel able to judge how useful it really is. Thus I didn’t feel comfortable having it as a shortform post.
Here’s a tool to estimate how badly hospitals will be overfilled in your community.
http://scratch.neherlab.org/
It’s by Richard Neher and colleagues and an early stage tool. Might nevertheless be interesting to play around with.
Here’s the source and some explanations about the underlying model:
https://twitter.com/richardneher/status/1236980631789359104
Richard Neher and others created a tool to explore scenarios for hospital demand in your community:
http://scratch.neherlab.org/
It’s still in early stages. Source: https://twitter.com/richardneher/status/1236980631789359104
Just as a small piece of evidence:
I’ve read an interview of a patient released from a swiss hospital. She isn’t allowed to leave her appartment but can spend time in her garden and is allowed to recieve deliveries (there was no specification about how deliveries are done). This points towards the doctors not being very concerned about aerosolized infections.
1. Iran isn’t especially warm at this time of year. Temperatures were between −2°C and 12°C this february.
3. There’s loads of ‘liberal’ measures that governments can take to change the distribution of cases over time. Many of the estimates epidemiologists give are explicitly for scenarios without countermeasures. (For example, the estimate that 10% of the population will be infected at the peak of the epidemic.)
Maybe you’ve already done this:
Write a list of the names of everyone that attended. This way if any attendee turns out to have been infected you have a better chance of containing it within some section of your community.
This advice may be individually rational but seems generally quite bad from a social point of view. Don’t stockpile a medicine because you think the public health system will run out of it. Same goes for stockpiling a large number of surgical masks. I’ve heard that hospitals and institutions in Italy already fear running out of them, and masks are crucial in these places.
The case might be different for people with high age or a preexisting condition that puts them in danger.