There is an (older) Financial Times article that did an excellent analysis on this (free to read): https://www.ft.com/content/a26fbf7e-48f8-11ea-aeb3-955839e06...
But, this article (also free to read) came out today from the Financial Times and is way better. The UK is doing far worse than the US interestingly: https://www.ft.com/content/6b4c784e-c259-4ca4-9a82-648ffde71...
Countries like France, Spain, and Italy (Mediterranean countries) in particular rank badly (besides having an uncontrollable infection problem) for the calculation of total excess deaths (compared to previous years) because they have some of the highest average lifespans in the world, largest percentages of elderly populations, and have extremely high quality universal healthcare (for example, the third leading cause of death in the US is actually preventable medical errors, so we really do not have phenomenal healthcare, even if you have “great insurance” and “can pay for it”).
Every death is a tragedy, but we didn't do half-lockdowns for the flu before. Why are we doing a full lockdown for something that is 2x the flu.
Antibody testing largely supports a 0.4% death rates conclusion, I've tracked this data in a spreadsheet I made [2]. 0.4% is close to the mean and median of the studies I recorded.
Edit: I know it's gauche to complain about downvotes, but this post is just citing data to make a point. Even if you are worried about Covid, it seems dishonest to downvote data.
[1] https://www.wcnc.com/article/news/health/coronavirus/data-cd...
[2] https://docs.google.com/spreadsheets/d/16onEUBWIV5IqN1RCvTla...
If you are a programmer how much would you appreciate a medical doctor with no training or experience in software development questioning your technical decisions about what to use when building a software service?
I’m not sure what the basis is if your criticism. If a medical doctor wants to submit a PR I would review it based on merits.
But broadly, the studies I've cited largely back up the CDC's estimate of 0.4% IFR. Some of them have methodology in the papers themselves which give similar numbers, and I encourage you to read the raw data.
But an IFR close to the flu is not at all surprising. Covid is a respiratory infection. It kills the same way the flu kills (eg. pneumonia), so you'd naively expect them to have similar fatality rates and outcomes, and they do.
If I wanted to reduce the risk of acquiring or transmitting an airborne infection back in February, I would wear a mask and avoid enclosed spaces without waiting for CDC's permission. Indeed, I would ignore their advice to the contrary, which stood until April (!)
It would be really nice if we could defer to competent technocratic experts, but they earn their trust by having credible track records, not by collecting credentials.
The train to technocratic ditatorship is paved with... the great glucose poisioning epidemic, loss of free speech, loss of self defense. Todays conventional wisdom is often not looked on favorably in the future.
http://www.youtube.com/watch?v=TRnB9El_V5g
Are we going to wear masks for the rest of our lives (outside FFS)? Pandemics are an authortarian dream. The ability to engineer pandemics will only expand.
A bit of scale: Consider how many children go missing in the US each year.
COVID-19 mortality rates, however, are almost always reported according to narrower inclusion criteria (either positive COVID-19 dx or "presumptive COVID-19"), so there is a risk of an apples-to-oranges comparison here. One ought either count death certificates or estimate the total mortality burden, but not both.
There are two parts of flu/covid IFR: fatalities and infections.
For flu fatalities, the CDC does indeed upward adjust the count. They do this by looking at how many people died of pneumonia, and multiplying that by a number. The number is the estimated percent of pneumonia deaths that are from the flu, which they base on historical data.
For flu infections, it's a bit more obtuse. The best I was able to find was this paper from the CDC [1], which says they use a Monte Carlo model to estimate the number of infections.
For Covid, the deaths are based on diagnoses, not necessarily tests. Diagnoses are from symptoms, so it is not completely accurate. Some flu cases could be misdiagnosed as covid cases if you don't do a test. For infections, the numbers are typically based on the results from antibody tests (not Monte Carlo models).
I agree that it's definitely not apples-to-apples comparison, but it's hard to say if the comparison is in favor of flu being more deadly, or covid being more deadly, because there are confounding factors in both directions.