Excess deaths in the US and the UK are far from the worst, but my point is that countries at a similar level of development have done far better, and so have much less well-resourced countries. Had the US done as well as the model's estimate for China (38 vs. 250) about 702,000 more Americans would be alive today.Below the fold, I look at how Omicron has changed the picture.
The Economist now estimates around 350 per 100K, so in 5 months another roughly 334K have died, or about 2.2K/day. Using the Dept. of Transportation value of a life, these deaths have cost the economy $32B.
In the earlier post I made this comparison:
It isn't as though Australia's pandemic response has been exemplary, as Ian M McKay illustrates with savage irony in Thank goodness we did all the work , but through most of the pandemic their excess death rate was negative. Omicron has changed things, so their estimated daily excess death rate is now around 1.2 per 100K. The US estimated daily excess death rate is about 1.6 per 100K, so if the US was doing as well as Australia over 1,300 fewer Americans would be dying each day.
This graph compares the US and Australia. Had the US handled the pandemic as well as Australia (-17 vs. 250 per 100K), about 885,000 more Americans would be alive today.
U.S. Has Far Higher Covid Death Rate Than Other Wealthy Countries by Benjamin Mueller and Eleanor Lutz for the New York Times looks only at the officially reported deaths caused by COVID-19. In the US these are known to be an underestimate, coroners in red states are under pressure not to ascribe COVID-19 as the cause of death.
Since Dec. 1, when health officials announced the first Omicron case in the United States, the share of Americans who have been killed by the coronavirus is at least 63 percent higher than in any of these other large, wealthy nations, according to a New York Times analysis of mortality figures.Like the US, Australia has a right-wing government and media dominated by Rupert Murdoch. Despite that, cumulative deaths during Omicron in Australia are around 7 per 100K, whereas in the US they are around 4 times higher.
Although the presentation of the data in the NYT is excellent, the analysis of the reasons for the US' failure is mealy-mouthed. Mark Sumner critiques it in The U.S. is seeing a higher rate of deaths from omicron. It's important to know why:
In the article, the Times quotes an expert from Scotland who notes: “Death rates are so high in the States—eye-wateringly high.” But that quote breaks off without providing any explanation for how things got into this state.Sumner points out that it is only 23 paragraphs into the story that the NYT explains:
More Americans have also come to express distrust — of the government, and of each other — in recent decades, making them less inclined to follow public health precautions like getting vaccinated or reducing their contacts during surges, said Thomas Bollyky, director of the global health program at the Council on Foreign Relations.Sumner asks:
But … how did that happen? How is it that Americans have plenty of vaccine available, but won’t get vaccinated? How did it happen that Americans have become so distrustful?
Apparently this was a spontaneous phenomenon, perhaps related to … amber waves, or purple mountains. Certainly no one reading the article would get the impression that one political party has conducted a years-long campaign to generate that distrust. The fact that Republican Party officials have opposed vaccine mandates, demanded that businesses and schools remain open no matter how threatening the conditions, and worked to reduce levels of testing doesn’t get mentioned. Neither does the idea that that party—along with an entire television network—has pushed false cures like hydroxychloroquine and ivermectin on their supporters.
Covid has exacted a horrific death toll on red America: In counties where Donald Trump received at least 70 percent of the vote, the virus has killed about 47 out of every 100,000 people since the end of June, according to Charles Gaba, a health care analyst. In counties where Trump won less than 32 percent of the vote, the number is about 10 out of 100,000.
R2 is a statistic that will give some information about the goodness of fit of a model. In regression, the R2 coefficient of determination is a statistical measure of how well the regression predictions approximate the real data points. An R2 of 1 indicates that the regression predictions perfectly fit the data.
He now includes a graph of booster rates against the percentage vote for Trump. The strong partisan correlation is still present, but weaker at an R2 if 0.32. Alas, the levels of booster shots are depressingly low, showing the lack of a strong "get boosted" message from the administration. Note that only one point on the graph matches the UK's national average 55.7% booster rate.