Covid cases have dropped 77% in six weeks. Experts should level with the public about the good news.
www.wsj.com
Edit: some good stuff in the comments section, but I really don't understand the science and will let other reply.
The best sciency one I could find.....
If 2/3 of the country had been infected, on top of the 15% that have already had at least one vaccine dose, you would notice. Case rates would be dropping so fast it would make your head spin. While the last five weeks have been encouraging, positive news, we are still getting ~500,000 confirmed cases a week, which is not consistent with an R0 just above 1.0 and a population at large that is less than 1/3 susceptible.
I agree the proportion that's been infected is probably much larger than the ~10% that's confirmed with tests, but there's a lot of room between 10% and 67%.
This strikes me as the latest iteration of shell game that goes something like this: "Let's concoct a very high estimate of the number of people who have already been infected because no one really knows for sure and our number cannot be disproven, and our estimate implies that the infection fatality rate is low, and it also implies we're close to herd immunity so there's really no problem!" In this case the author rearranges the steps a little, but it's the same basic game.
From the WSJ opinion piece: "The Covid-19 infection fatality rate is about 0.23%. These numbers indicate that roughly two-thirds of the U.S. population has had the infection."
A google search reveals that , low and behold, this is the exact number Ioannidis came up with: "The median infection fatality rate across all 51 locations was 0.27% (corrected 0.23%)."(link below). Ioannidis is always a good source of estimates if one want to play this game. In March of 2020 Ioannidis estimated there might be a total of 10,000 COVID deaths in the U.S.: "If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3% in the general population — a mid-range guess from my Diamond Princess analysis — and that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths." (2nd link below)(granted, he used this as an example, but why use an example if you think it's completely ridiculous?)
With reference to the Imperial College of London article (third link below), the infection fatality rate tends to much higher in high income countries with older populations:
"Using these age-specific estimates, we estimate the overall IFR in a typical low-income country, with a population structure skewed towards younger individuals, to be 0.23% (0.14-0.42 95% prediction interval range). In contrast, in a typical high income country, with a greater concentration of elderly individuals,
we estimate the overall IFR to be 1.15% (0.78-1.79 95% prediction interval range)."
In other words, the author is probably off by a factor of about 5 with regards to the infection fatality rate in the U.S., meaning he is also off by a factor of 5 with regards to the percentage of the U.S. population that has already been infected (using his methodology). This means that only about 1/5 of 2/3 of the U.S. population (i.e. 13%) has already been infected (again, using his methodology). The latest number for total reported cases in the U.S. is about 28 million (fourth link below), which is about 8.4% of the population. There's no doubt that the number of infections is more than this, but it provides a starting point to look at the number of infections.
I suspect that more than 13% of the U.S. population has already been infected, but this is probably a better estimate if one wants to use the author's IFR approach. Given the uncertainty in IFR estimates, the author's approach to estimating the total number of infections strikes me as being highly speculative.
The CDC estimated 83 million total infections (about 25%) through the end of last year (fourth link below). I suspect this involves a large SWAG factor as well, but it seems plausible. Even if 30-35% of the population has immunity from prior infections or vaccines, it's well short of herd immunity.
I suppose it's possible that there will be a huge surge in cases that will lead to herd immunity by April, but that's clearly not what the author is predicting.
I'd concede that predictions are difficult, especially when they involve the future.
article published in January 2021
www.who.int
A fiasco in the making? As the #coronavirus pandemic takes hold, we are making decisions without reliable data.
www.statnews.com
Report 34 - COVID-19 Infection Fatality Ratio: Estimates from Seroprevalence
www.imperial.ac.uk
A detailed county map shows the extent of the coronavirus outbreak, with tables of the number of cases by county.
www.nytimes.com
Cases, data, and surveillance to track and analyze COVID-19.
www.cdc.gov
