An Optimistic Assessment of COVID-19

PIcture credit: Aleph Blog, and the same for all the graphs and charts in this post. All liability for mistakes here is mine.

This post is different than any other I have done at Aleph Blog. I will try to write this in a nice way even though it is a strong and out-of-consensus opinion on a topic that many are edgy about.

I realize I might be wrong here, but I will present to you what I think, along with what I think are the limitations of my analysis. Part of my reason for writing this is that I think that most of the reporting on COVID-19 is subject to a bias common in our culture among politicians, lawyers, bureaucrats, and the media: an extreme bias toward safety because the costs of being wrong on the optimistic side are high than the rewards for being right. (Example: NOAA overpredicts disasters, and so do most hurricane forecasters.)

This post will be structured like this:

• Summary of findings and recommendations
• Limitations of the analysis
• Breaking down the results by groups of countries
• A discussion of the “Second Wave,” with policy recommendations
• Closing comments
• Appendix for math nerds

Summary of findings and recommendations

• The First Wave of the crisis will pass more quickly than most expect. Most countries with a large number of COVID-19 cases will have 99% of their First Wave cases reported by mid-April.
• Of the 13 countries with the most cases of COVID-19, the least of them has reported 41% of their likely First Wave cases. Of those same nations, none are expected to have more than 0.3% infected with COVID-19.
• The real challenge will come in dealing with the Second Wave of the crisis. How do governments deal with a smallish number of new cases, and keep them from growing into a new epidemic?
• In the Second Wave, governments should selectively tell some to stay home, while telling most people to get about their normal work.
• Quarantine those who are sick with COVID-19 and those who have been with them, until they are tested and have a negative result. Continue to disallow international travel, or insist on a two week quarantine upon returning.
• Let healthy people return to their work. All businesses are necessary businesses.
• Avoid bizarre stimulus programs that are harmful in the long run. Tell the Fed that monetary policy can’t solve everything, and not to play favorites.

Limitations of the analysis

• I am not a public health specialist. I am a statistician with a background in econometrics, which has its similarities with biometrics.
• My analysis assumes that processes for finding new cases of COVID-19 are constant, or mostly so. That is not always true — an example is when China announced a large amount of new cases all at once.
• I use an inverse logistic curve for my analysis. All functional forms have their limitations, and for the nations analyzed as of this date, the minimum pseudo-R-squared is 79.4%, and the highest is 98.5%. That said, this is a common functional form for epidemics.
• The model assumes that there is one wave. That will not prove to be true, as can be seen from China and South Korea.
• All sorts of things can go wrong that are not in the data now — mutations, civil disobedience, large bureaucratic errors, large policy errors, etc.

Analysis By Group

Those that are though the First Wave

We have two in this group: South Korea and China. I don’t trust China’s data. In each case, though, you have the First Wave go through their nation and burn out, followed by an excess number of new cases where the public health authorities may not be catching up with what could be the Second Wave. I’ll talk more about the Second wave below.

The unusual case of Iran

Really, I don’t know what is going on in Iran on COVID-19 but it looks like the initial new cases started to slow down, and then they let up on restrictions too soon. New cases hit a new high yesterday, which doesn’t fit the paradigm of a consistent response the the crisis. COVID-19 seem to be out of control in Iran.

Those that are close to done

Italy and Germany are past the halfway mark in the epidemic, and are having lower new cases on average daily.

In general, the policy responses of a nation influence the amount of the population subject to infection, and the ability of the infected to interact with the broader society.

The rest

These are the nations that have not certainly passed the 50% mark as of today as I estimate the infection. As I have watched this develop over the last week, the most difficult aspect of estimation comes when you are near the halfway point. Small changes in actual new cases make a big difference in estimated new cases. An example is the United States, who has had significantly lower new cases than expected for a preponderance of the last week. The US got off to a slow start in its reaction to the crisis, but seemingly has caught up and then some.

WIth these countries, the odds of being wrong is the highest. Thus all conclusions with them must be considered tentative. But with so many of them following nearly the same pattern, despite very different responses to the crisis, gives more certainty to this analysis.

A discussion of the “Second Wave,” with policy recommendations

When you look at the data of CHina and South Korea, you see how the epidemic went through the s-curve, and then has persistently high new cases thereafter. I call this the “Second Wave.” Iran seems to be a case where their society inadequately stops transmission, and so instead of following an s-curve of an exponential, it seems to keep increasing in a way that is almost quadratic — slow but steady.

This will be the grand problem for most countries. How do you eradicate the virus after you have had large success in interrupting its transmission? Looking at the relative success of South Korea in the First Wave I would say that you do the following:

• Test and quarantine aggressively.
• Of those who test positive for COVID-19, quarantine all of their contacts, and test them. Continue quarantine for those who test positive, and quarantine/test their contacts as well. Repeat as needed.
• But don’t quarantine everyone. Let those who are healthy work. Encourage those who are old or have compromised immune systems to stay home for the duration of the crisis, and give some assistance to them.
• Don’t assist all of society because that is way too expensive and not needed — get them back to work. Don’t give into the idea of denying people work and then offering meager assistance. It is an inferior idea for those who are healthy.
• This applies to the actions of the Federal Reserve as well — don’t harm the value of capital by artificially creating more capital that has no earnings capacity.

Closing comments

This analysis shows the the slowest of the nations written about here is passing the middle of the crisis quite rapidly, and the practical end of the crisis is in mid-April, when 99% of all First Wave new cases will have been realized. The real challenge will come in dealing with the cases after that, which will be sporadic and localized. How do we keep that from becoming a semi-permanent bother to the world, because the cost of putting life on hold is high, as is the cost of losing lives.

Quarantining and testing aggressively is the best solution, together with letting the healthy work. This should be the guiding star for all policymakers, because we need to strike the right balance between breaking the social connections that lead to disease transmission, and allowing people to labor to support themselves. We are not trying to save the financial markets; we are trying to protect people who work.

Appendix for math nerds

The above was how I structured my analysis. It followed a logistic curve, which has the following benefit: infections begin exponentially, but get retarded by two factors: one is that even if people do almost nothing as in 1918, the uninfected population shrinks, which blunts further growth. Second, people act to blunt further growth. They separate themselves from each other, and particularly those who are infected. This is is akin to removing fuel from the fire.

The logistic curve has a number of advantages for estimation. It notices the slowing down of the percentage growth in total cases, while media and politicians continue to panic.

Remember that that the media and politicians selfishly like to maximize their influence, and try to create panics — it is good for them to maximize fear. The same is true for many in public health. Truly, we should spend more on public health, but it is one of those things that governments naturally neglect… because they are short-sighted, and will not spend money on something the lowers risk, but does not bring any present good. (Note to Christians: in the Old Testament public health was a function of their government via the priests. It should be a normal function of government to deal with contagion.)

Final note: I did not write this with Donald Trump in mind. I did not vote for him and will not vote for him. That said, he is on the right track when he says the cure should not be worse than the disease. Even a blind squirrel finds a nut every now and then.

It is foolish to warp monetary policy and fiscal policy when healthy people are perfectly capable of working. Don’t destroy ordinary incentives and rack up tons of debt by keeping people idle. Test, quarantine, test, quarantine, etc. , but leave the main body of society alone, particularly for a virus that does not harm the healthy working population much.

To that end, I ask that Republicans be real Republicans, and not expand the deficit further. I ask that the Federal Reserve stop trying to be God, and be content with merely having a currency with a consistent value.

Government is best when it is small. We are not facing the Black Death, nor the Spanish Flu. We will get through this, God willing. We don’t need to panic.