Lockdown has been lasting for a long time, and myths have filled the internet all over the place. Today I want to try and dispel a few of those myths, but also point out some things that are happening, but also very weird when you start thinking about them.

What is wrong

1. Trump's Covid-19 medicine (hydroxychloroquine) helps... and if it doesn't help it doesn't hurt.

I'm sorry everyone, but the results are in, and disprove this completely. Trump's medicine increases the chance of dying by a third on average, and also causes heart arrhythmia as a major complication in many patients. Many of Trump's statements are open for multiple interpretations, but in this case there is no ambiguity. He is taking the medication himself, and is a fool for doing so.

2. Most of us have been infected already

We can now also safely say that this one is wrong. Many groups have now tested for anti-bodies, and even in hard-hit states like France and Spain only 5% of people appear to have been infected: https://twitter.com/EricTopol/status/1260666412164542465

In *very* hard hit cities like New York, the percentage may be as high as 20%, but even that is only a small minority of the population.

A rough and incomplete overview of various tests can be found here: https://docs.google.com/spreadsheets/d/17Tf1Ln9VuE5ovpnhLRBJH-33L5KRaiB3NhvaiF3hWC0/edit#gid=0

3. We are accurately tracking the Covid-19 pandemic

Various websites like Worldometers and Ourworldindata give exact numbers on how many cases have been confirmed and how many deaths are confirmed. Meanwhile, the Financial Times is tracking how many more people are dying than normally around this time of year. Now, first of all all three of these sources are reporting very different numbers, with the Financial Times often reporting the highest numbers.

But the sad thing is that even the Financial Times is underestimating the deaths. For instance, let's look at the graph in that article today, on May 23rd:

The numbers look pretty dramatic here. For instance, the FT reports 8,900 excess deaths in the Netherlands, while Worldometers reports about 5,800 deaths from Covid-19.

But if you look even more closely, you'll find that the little excess death graph from the FT ends on... April 26th, almost a month ago.

Likewise, for the US it reports 52,300 deaths on April 18th, and on that same day Worldometers reported about 40,000 deaths. Today, worldometers is reporting about 98,000 deaths in the US, but given the previous discrepancy with the FT data, I would argue that 130,000 is probably a more realistic estimate.

To further compound this incredible mess, there are almost certainly countries out there that deliberately underreport their deaths.

4. Smoking reduces the risk of Covid-19

Yes, I fell for this one as well. But it doesn't stand up to serious scrutiny really.

What is weird

Having dispelled some myths, I now would like to cover a few things that are just plain weird; things we should be reconsidering.

1. Schools are closed, but after-school activities are continuing in full steam online

For two months now, my daughter is doing online zoom classes about ballet, singing, acting, and she even got offers to do online karate. Yet, when it comes to actual school, there are no such online streaming sessions, and pretty much the whole of the UK has to do with weekly homeschooling workload e-mails.

I understand that afterschool clubs provide online classes simply because they might go out of business otherwise (and schools do not), but isn't this whole situation getting a little bit ridiculous?

2. The obsession with the reproductive rate R appears ever lasting

As a reminder, the reproduction rate R is the average number of people that a given patient will infect on average. A number less than 1 indicates that, on average, an epidemic fizzles out, and a number greater than 1 indicates that it is growing.

I am not fundamentally against measuring epidemics in this way, but it is painful to see how R gets completely misused by just about everyone. Allow me to indulge on listing the sins.

1. Politicians are telling us that an R lower than one means we're doing well. There is a very simple counterpoint to make here: the easiest way to get a low R on the short term is to do far too little testing. And that is exactly what happened during this pandemic.

2. Modellers are putting R as an input parameters in their model, but also reporting R as an output. The Kucinskas code is just one example of it, but modellers are doing it just about anywhere. This can be dangerous, because it means that any error in your initial estimation of R immediately passes on as errors in your model outputs. Also, there is just something fundamentally weird about putting a measure as input and then producing it as an output, it feels a bit like second-serving food in a restaurant...

3. The community has cheerfully abandoned much simpler measures in favor of “R”

At the start of the pandemic, people still spoke about doubling times, or the percentage growth per day or week of the number of affected cases or deaths. All these measures are simpler and more intuitive than this R number. But some I suppose the magical “R” number makes for more appealing article titles?

3. The stock market just pretends nothing has happened

The S&P 500 is actually at a higher point than it was a year ago, even though 38 million people (and counting...) have been laid off:

S&P 500 index over the last year. From Google Search.

I cannot begin to fathom what warped logic drives this perception of the future business potential in the US.

Credits

Header image courtesy of Marco Verch.

Oh, and a last thing popped up for the subscribers: