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.
The Senate majority leader tried to give him an out.
It’s hardly surprising that Sen. Mitch McConnell (R-KY) would contort himself into a pretzel to offer President Trump some sort of excuse — especially one dripping in Trump’s favorite flavor of partisanship — for the administration’s botched handling of the coronavirus outbreak in the U.S. But the befuddling bit is Trump didn’t bite.
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.
For a variety of reasons, I pay close attention to the manufacturing sector. I think it’s partly because I grew up in Cleveland and still have a lot of friends who work in shops and factories — many who are already out of work. Although we’ve more or less transitioned to a services-based economy, making stuff is still a core aspect of the American identity. We all know the service sector is taking a massive blow. We can see the stores closed, we can’t go to our favorite bar. But the manufacturing economy is less visible — except to those in it. The rest of us will feel the impact down the road when this loss of productivity manifests in myriad ways.
This morning the Institute of Supply Management released its March manufacturing report. As expected, it was pretty bad: Reduced demand, a slowing supply chain, reduced employment. But I want to highlight a couple specific data points. Read More
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.
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.
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.
I’ve been working on collecting different bits of information pointing to dramatically higher COVID-19 mortality than is showing up in official statistics. (Josh Kovensky is beginning to report the story in the US.) We discussed the evidence out of Italy suggesting official COVID fatality numbers were only capturing a fraction of the “excess mortality” showing up in particular towns. (This involves comparing the average number of deaths from all causes in a specific town or region during a particular date range to the number of deaths in the same date range during the COVID pandemic.)
Now TPM Reader ND passed along to me this article from the Spanish daily El Pais, which reports a similar study in Spain. The numbers show a discrepancy very similar to those from northern Italy.
The national COVID-19 crisis is still dominated by events inside the state of New York. Until a couple days ago roughly comparable numbers of Americans were dying in New York each day as every other state in the country combined. Because of this, one way I find helpful to make sense of the situation is to look at New York state and compare it not to the national numbers but the numbers from the rest of the country outside New York state. This helps understand the dynamics in other parts of the country separate from the situation in New York and see how they compare.
Here are three graphs that give us that snapshot of the situation unfolding in the country.