Covid Exit Strategy

Here is an excellent web site:

Covid Exit Strategy

It lets you track each state’s progress towards a new normal. It is update frequently.

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Highly misleading. All the red states are well below the national average in infections and deaths so at worst are catching up. NY, NJ lead the entire world in per capita infections and deaths, of course they’re coming down. CT not far behind.

I’ve discussed this in some detail here. Contrary evidence is welcome.

Covid Strikes Back?

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For one thing, perhaps you didn’t read the title:

Tracking Our COVID-19 Response

Each state’s progress towards a new normal
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Nebraska is heading back up.

Click on the circle with arrow icon in the upper right corner to expand a frame. The one I’m citing is the bar graph, bottom left:

https://experience.arcgis.com/experience/ece0db09da4d4ca68252c3967aa1e9dd

You can click on individual county icons in the map, too.

This is notable… look at the age groups with the highest proportions (not having realized that they’re mortal yet and thus maybe more careless and more likely to be infected):

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Steve,
Thanks for the link to a thought-provoking article.

It does appear young people will test positive, and the chance that young people will have any serious harm or death is far, far lower than old people.

1 out of 6 people 80+ might die,
Fewer than 1-2 out of a thousand might die of those 30 and below

I wonder what an up to date graph would look like, and with more countries.

‘Not yet as bad as NY but catching up fast’ is a pretty low bar.

There are a number of issues with what you wrote there, some of which I’ll address.

That’s wrong. ‘The curve’ represents the infection rate that would have occurred without any efforts to control the outbreak. According to the CDC, seroprevalence in the NYC metro area is 6.9%, several times lower than even the most optimistic limit needed for herd immunity. Since in an uncontrolled outbreak, the infection rate will exceed the herd immunity level (‘epidemic overshoot’), they actually flattened the curve by more than that factor.

The original purpose of flattening the curve was to prevent epidemic overshoot. It’s something you want to do in any serious pandemic, regardless of other considerations, and an established idea in public health before this pandemic. With this pandemic, there were always multiple reasons for trying to reduce transmission: avoid overshoot, avoid overwhelming health care systems, delay most infections until more is known about treatment, and until therapies and (ideally) a vaccine are available.

No, eliminating SARS-CoV-2 is not possible. But plenty of countries have demonstrated that it can be controlled at a low enough level for the society and economy to be restored to a functional level while still protecting most of the population from infection. This doesn’t have to go on forever: we’ve already learned that one treatment can substantially reduce mortality, monoclonal antibodies will be available in reasonably large amounts within a few months, and a vaccine may well we deployable in roughly a year. Every developed country has shown that they can control the virus on the time scales needed – every developed country except the US. Our trajectory represents a public health failure of horrific proportions.

As you note subsequently, that’s not actually a confirmed number. Most estimates have been in the range of 0.5% to 1.0%. Hopefully, with improved treatment it’s now below 0.5% for most populations. More importantly, you’re comparing apples and oranges here – you’re comparing the estimated infection fatality rate for covid-19 with the case fatality rate for flu. The IFR for flu is much lower than 0.1% (see here for details). (You might also note that citing Ioannidis immediately causes you to lose a lot of credibility with anyone in this field – his work on covid-19 has been really bad.)

The Swedes disagree. In reality, their death rate has been much higher than their neighbors and the economic cost has been almost as high. (Which isn’t to say their approach was irrational – everyone was making it up as they went.)

In your discussion of herd immunity…

This clearly cannot be the result of herd immunity, since in most of the region infection rates were far lower than in places like Lombardy and NYC. The fact you cite here is in fact excellent evidence that the outbreak can be controlled for extended periods at quite low levels.

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What I heard repeated over and over was that the goal of flattening the curve was to keep the need for medical care below the capacity of the health care system.

Typically this was described with a flat line on a graph marked “health care capacity” or something similar and two curves — one soaring above the flat line and the other curve longer and flatter below the flat line.

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The US data look the same.

If I happen to find it again, I will post it.

This disease is dangerous to old people with health issues. Little kids do well with rare exceptions.

Edit:
Here is one picture of the data from the CDC:

The gray line shows the typical number of deaths in the country. The red lime shows this year.

Note there is no discernible increase in deaths for college age and below. For the very old, there is an increase. Alternatively, you could see Covid as hastening the death of those old people with underlying health conditions.

That was the simple motivation most often given to the public, yes. But the goal of avoiding overshoot existed even before this outbreak – it’s one of the conclusions from studying the 1918 flu epidemic.

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Avoiding overshoot of what?

If by ‘very old’ you mean older than 25, yes.

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I should have written for the very old there is a significant increase or significant advancement.

If the teachers can be protected, it looks like from these data that schools should restart, subject to temporary closes such as those common in flu and measles outbreaks.

Infections. See What is the best control strategy for multiple infectious disease outbreaks? - PMC, for example.

Depends on what you mean by significant. One thing I neglected to mention above is the much higher morbidity of covid-19 than things like the flu. Many of people even with ‘mild’ disease get very sick, and the fraction with long-term, possibly permanent, disability is alarmingly high.

True, provided the kids don’t live with other people.

I saw a news report yesterday that stated four times as many young children have died from the flu in the US this spring as have died from Covid.

For young children, the flu may have higher mortality.

Quite true. I was talking about the morbidity for adults. Even for young adults there’s a surprising amount.

You added the “fast”. That significantly alters the meaning of what I said, and is also incorrect.

It’s right. A simple look at the curve - rapid upslope, pointed peak, highest per capita infection and death rate in the world, three times that of Sweden (later superseded by NJ) tells me all I need. In my first draft I had written “totally failed” instead of “mostly failed” - but that wouldn’t have been fair. Only in a parallel universe where NY did nothing would we have known whether things might have been worse.

You’re picking one hypothetical benefit (a legitimate one, I concur) and incorrectly implying that was the basis for public policy decisions. The justification provided by all government authorities and health organizations was as I stated. Epidemic overshoot is not even mentioned in the Science paper from Harvard Epidemiology.

Really don’t care what prejudices people may have against Ioannidis. He’s widely respected in the medical field, despite the fact he got famous by criticizing it. He also ended up being right about the IFR back in mid-March - one of the very few.

Can’t imagine a worse measure of success than public polling. But given that the government betrayed the elderly, like NY and NJ, if I were a Swede I’d probably disapprove too. You don’t account for the fact that their case count and fatalities have dropped to extraordinarily low levels, without locking down.

Or may never happen. Staking the global economy and millions of people’s lives on a roll of the dice is not a sound strategy

The effectiveness of serology testing has not lived up to the hopes. It probably understates immunity because 1) mild infections don’t produce a strong enough AB response, 2) AB levels decline after a matter of weeks or months, 3) they can’t assess acquired T-cell immunity, 4) they can’t test for cross-immunity. For instance,
COVID-19 antibodies may fade in as little as 2 months, study says