Something very, very bad is happening today in Florida with the Holland America Zaandam cruise ship. Many terrible things are happening around us now. But here I am talking about a sort of willful malice or abandonment that is a deliberate decision, something that I think may haunt the decision-makers even if the loss of life is only a tiny fraction of what is unfolding across the country.
The Zaandam is approaching Florida and appears to be in the midst of another ship-wide outbreak like ships that came to port in Japan and Oakland, California. The current report is that 190 guests and crew have flu-like symptoms; eight have tested positive for COVID-19; four guests have died since the ship left Buenos Aires on March 7th.
In response to that data out of Italy suggesting the official COVID-19 death toll may dramatically understate the loss of life in the country, we’ve begun looking at the same data in the US. One challenge is that this data is collected much more rapidly in Europe than in the United States. I picked that up in my reporting. And what Josh Kovensky has found has confirmed that. A lot of this data won’t be available for a while. In some cases the people you would need to ask to pull data from earlier years are currently swamped dealing with the new data. In this first report we just published, Josh talks to some experts in the field and looks at the how this work will eventually be done. The studies out of Puerto Rico after Hurricane Maria will be a guide. Check out this piece. Very important part of the story.
Most of you reading this probably rightly think that Donald Trump and his top advisors catastrophically mismanaged the country’s COVID-19 response. But we also know that the disease has had a shattering impact on countries around the world. So how do we measure the real world impact of the failure to do early testing or start planning to deploy medical resources in January or February? One potential comparison is Germany – another wealthy, industrialized democracy with a world-class capacity in the sciences. Germany got moving early on testing and they have a lot of ICU beds. They also moved rapidly toward aggressive social distancing, at least compared to countries like Italy. You can read more details about it here.
I wanted to add a bit more about that IHME study – some more perspective on what it is and isn’t telling us. Before I do, a quick point. Last night an exasperated TPM Reader FT wrote in saying in so many words all the debate about models is morbid. What are we accomplishing by debating technicalities about why a horrid number of Americans are going to die versus twice a horrid number? And if we’re saying it’s so bad in advance what incentive does anyone have to social distance?
First, this is all overwhelming stuff. I’m sitting here this morning with the news that the number of people who die in this calamity is likely to be counted in the hundreds of thousands. I’m simultaneously numbed and overwhelmed by it. We all have to pace ourselves. And we all have to be gentle with ourselves and others around us. One of those things is taking some breaks from the news when we need to.
As I explained to TPM Reader JG, who wrote the email below, when I’m writing about or describing something where my knowledge is very limited I try to keep it vague and refer people to the source. I’m sharing JG’s follow up on the “rosy scenarios” post because he gets into a, probably the key element about why these models have a major uncertainty contained in them.
A comment on your “Rosy Scenarios” post. I read Carl Berstrom’s Twitter threads about the IHME study and think you’re understating just how rosy the estimates from that study are. Outside of the assumptions on the biological side – that there is “Wuhan-style” social distancing for the duration of the epidemic – the main problem is that the study is an exercise in mathematical curve fitting, not biology.
Yesterday I shared with you that modeling site from the Institute for Health Metrics and Evaluation, which is based at the University of Washington School of Medicine. This is the one that models the course and intensity of the COVID-19 pandemic both nationwide and in individual states. It’s clearly getting a lot of attention. Apparently it’s now being cited by the White House and just moments ago I was watching a CNN interview with Dr. Chris Murray, one of the researchers behind the modeling.
Yesterday I corresponded with a TPM Reader who referenced the theory that the cataclysmic economic data we are now seeing predicted on quarterly GDP, unemployment and more are categorically different because they are being created deliberately to accomplish a specific purpose. We don’t have a bad economy. We deliberately shut the economy down to save lives and prevent a specific sort of economic and societal chaos caused by mass mortality. There are significant ways in which this is true. But I wanted to explain key ways it is not.
We have intentionally placed what amounts to a pause on broad portions of the national economy. It’s not a mystery why we’re heading into a period of mass unemployment. We specifically told tens of millions of people not to go to work. But this is something like placing a pause on blood flow through your body. When the blood stops flowing it’s not just a matter of starting it up again. When the blood stops flowing a lot of things start to break and they don’t unbreak when the flow resumes. The analogy between the physical body and economic life is a strong one.
A new estimate from economists at the St. Louis Fed project total COVID-19 Crisis employment reductions at 47 million people. That would translate into a 32.1% unemployment rate. To give some perspective that is significantly higher than the peak unemployment during the Great Depression (24.9%) and wildly higher than anything seen during the Great Recession (10%).
Here is an interesting data source projecting the scope and duration of the epidemic across the United States and within each individual state. I cannot speak to the accuracy or methodology. I am pointing it out to you because it’s the work of the Institute for Health Metrics and Evaluation, a research center attached to the University of Washington School of Medicine. In other words, these are credentialed, serious people. Whether they’re correct I cannot say. And I pass it on on that basis.