Its not a significant amount of testing if we're only testing those with severe symptoms
Here in SF at least there are scores of people I know who all were sick with a "weird flu" at some point from February to now who would all kill for a test to show that they have COVID immunity. These are people who could potentially go back into society and do more work / enjoy their lives instead of being shuttered inside with anxiety
It is currently _IMPOSSIBLE_ to get any kind of test to prove that
Like how does it work? Would love to go do that
it’s free and they do it for everybody
Do we know this for sure? I've read that we're seeing re-infections of people who previously had it, but it wasn't clear exactly what was happening.
the hardest thing about this is finding real information and then accepting it.
Is a pretty hard line to take when all the facts are evolving and we’re learning more every day
> These are people who could potentially go back into society
Nobody knows if they could go back or not but the statement that they might is somehow the most dangerous form of misinformation.
Drawing the line at ~5M inhabitants, the following countries/territories have conducted more tests per million population than the US: The UAE, Norway, Switzerland, Germany, Portugal, Italy, Ireland, Austria, Hong Kong, Australia, Spain, New Zealand, Israel, Czechia, Singapore, Canada, Belgium, South Korea, and Russia.
There's the old adage "nine women can't make a baby in a month". Sometimes there are real-world limits to scaling, and the U.S. does have an incredible amount of tests to create.
And it's not like Portugal, Italy, Spain, or the Czech Republic are particularly small or particularly wealthy.
https://ourworldindata.org/grapher/full-list-cumulative-tota...
(I'm using cumulative because the daily numbers are missing for Germany, France, and the Netherlands)
I ask because the data I have shows the US solidly in the middle for the big EU countries over the past month (Germany and France don't show up on the daily graphs)
- Italy started earliest, but the daily per-capita tests have been higher every day except Apr 4: https://ourworldindata.org/grapher/full-list-daily-covid-19-...
- Austria, Czechia, and Portugal have been higher than the US more often than not: https://ourworldindata.org/grapher/full-list-daily-covid-19-...
- Belgium is on par; the UK & the Netherlands are definitely worse: https://ourworldindata.org/grapher/full-list-daily-covid-19-...
https://www.worldometers.info/coronavirus/country/south-kore...
Since they have coronavirus relatively under control and have been doing extensive testing and contact tracing for months, it's plausible that they've caught most cases. It's wishful thinking to believe the infection fatality rate is an order of magnitude lower.
Here's the result of randomized testing in Iceland, which also has the virus under control and has done even more testing per capita (https://www.nejm.org/doi/full/10.1056/NEJMoa2006100?query=fe...)
Randomized testing was still finding 0.6% of the population (outside those otherwise quarantined already) actively infected. This means even in Iceland, less than half of infections were being caught.
Iceland's CFR right now is 0.74% using deaths/recovered (or if you use an ultimate 20% hospitalization fatality rate, around 0.87%). If they missed half of infections, you get an IFR down to under 0.5%, though I'll admit they are doing better by keeping their most vulnerable population from being infected. (note the low infection rate for people 70+ at https://www.covid.is/data).
So no, not an order of magnitude lower, but 3x lower (0.7%) is looking pretty reasonable. Imperial College's latest estimate is 0.66% for China (https://www.medrxiv.org/content/10.1101/2020.03.09.20033357v...).
I'd just like to point out that this is still a far cry from the wishful thinking a lot of people are putting forth, claiming an IFR of < 0.1%, that 30% of the population have already had the disease and that herd immunity is both imminent and feasible.
These interpretations seem less likely to be true today than they did two weeks ago, and even then they were making assumptions on the optimistic side.
An IFR of 0.5% and a hospitalization rate in the high single digits is still a big frickin problem for society, when the disease has a reproduction number greater than 2 (and in the absence of countermeasures, more likely in the region 2-5).
South Korea had 5 deaths per day on both 2/29 and 4/13 that’s a horrible sign.
Looking at the raw data, I don't think Korea ever had below 3% using deaths/recoveries. Iceland is at 0.75% right now. Two weeks after peak, Korea was at a crude CFR (deaths/total confirmed) at 1.1%
Also, deaths/recoveries is the least useful metric to compare countries as people with minimal symptoms recover first, again look at the South Korea or China graphs of the number of infected over time.
and meanwhile germany's data points toward a similar conclusion as the south korean data
singapore also has a 1.5% deaths/recovered... and it's been higher in the past if you've been following closely (as high as 2%... question is where have all the new cases been coming from?)
icelands data could easily be skewed if they avoided a nursing home getting infected, given their low number of cases, and even there 1% fatality seems plausible.
Germany and Singapore are also missing many infections. A recent serological study in Germany actually argued for 0.4%.
You are correct that IFR is skewed by who the population is and what interventions are done. But then again, so is the often cited flu benchmark (where we have targeted vaccinations of at-risk groups).
(And age is a huge thing to be aware of skewing the data. e.g. the pediatric IFR from covid is on the order of seasonal flu)
And taiwan is at 1.5% CFR as well?
And still 60 or so unresolved diamond princess cases with ~7 in critical condition?
Every country is missing large numbers of cases, so CFR doesn't mean much - randomized testing is what is needed.
Imperial College's paper (linked above which gives a 0.7% population IFR) uses Diamond Princess as an input. The relative risk ratio they give for someone age 70 (mean age on Diamond Princess) is something like 4.5x (IFR ~3%), so you'd natively guess about 80 deaths from the 2,666 passengers.
The CDC is currently estimating an R0 of 5.7, which has likely been repressed by shelter in place orders. But even if it was only 4 before any interventions, there's still a chance there there are closer to 20M cases in the US rather than the 660,000 now.
My point is just that there's still a lot we don't know, and small changes in our understanding could implicate massive changes in the reality on the ground.
This would dovetail with the fact that places like sub-Saharan Africa and India haven't been hit very hard yet; they also happen to be _very_ young compared to Western countries.
If that's the case, it'd explain why developed countries are bearing the brunt of the pandemic. A very interesting example of similarly developed countries with comparable (but not equal) populations and population density, but different vaccination regimes are Portugal and Spain. Looking at their [2]respective [3]charts, the differences are stark. A similar difference can be seen between Ecuador and Argentina, even though the Greater Buenos Aires area is very population dense.
If this pans out, following the trends and [4] this map would validate that hypothesis.
[1]https://nypost.com/2020/04/14/coronavirus-death-rates-lower-...
[2]https://www.worldometers.info/coronavirus/country/portugal/
As someone else pointed out, the BCG needs a booster. While growing up I was given the initial one and two boosters. Most countries stopped doing that, which could also explain the effect. There's also the matter of which strain was used to create the vaccine: apparently some strains were better at fighting tuberculosis than others, so the same might apply (if the BCG vaccine actually made a difference) to COVID-19.
Anyway, my objective wasn't to start a conspiracy theory. We already have enough of those going around.
Obvious to me, perhaps dumb, question - if countries that were slower to change vaccination regimes have some advantage, then wouldn't we see older people in the countries that did change also at an advantage? Yet all reporting seems to be that older people are harder hit.
Based on other available data the severity of the Covid symptoms are dependent on both the length of exposure and total exposure to the virus. A cruise ship with recirculated air likely means prolonged exposure to high concentrations of the virus that won't fit most other patients exposure.
May be about double that. Per wiki article, I noticed this a few days ago (https://en.wikipedia.org/wiki/2019%E2%80%9320_outbreak_of_no...)
"Initial estimates of the basic reproduction number (R0) for COVID-19 in January were between 1.4 and 2.5,[381] but a subsequent statistical analysis has concluded that it may be much higher.[382]"
From that link wiki provided (https://wwwnc.cdc.gov/eid/article/26/7/20-0282_article) (edit: and note this is published on the CDC website)
"...we calculated a median R0 value of 5.7 (95% CI 3.8–8.9)"
So this sucks harder then.
Source: https://www.contagionlive.com/news/asymptomatic-influenza-in...
> Study results revealed an overall pooled prevalence for asymptomatic carriers of 19.1% for any type of influenza, 21.0% for influenza A, and 22.7% for influenza A(H1N1). For subclinical carriers, the overall pooled prevalence of was found to be 43.4% for any type of influenza, 42.8% for influenza A, and 39.8% for influenza A(H1N1).
> Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet
This sounds like circular logic - how we know it indeed started in January and not before? How do we know how many had it asymptomatically if we didn't test 99% of the population? We're making assumption based on knowledge gathered by select sample of 1% chosen by severity of symptoms - how can we make conclusion about how it works in the rest of the population and what's the dynamics there?
[1] https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx
Indeed, without serological testing, we're necessarily making some assumptions. But there's other evidence that points this way, too.
Genetic analysis based on samples from around China and the world point to a single index patient in Hubei Province around late November. China's case tracing has not gotten to an index patient, but it appears to be pretty close, and also points to an initial case around the same time.
If there was a single case in late November, then we'd expect a few hundred cases by January. Some number of these will have traveled, but many would not.
While the US clearly had major blind spots in testing, we were explicitly looking for symptomatic cases from China. The first detected case was Jan 21. There may have been a few earlier, but genetic analysis of cases in Washington point to an index patient in the Seattle area around that time.
The BPR is estimated from the known cases, so it cannot tell you anything about a hypothetical large number of unknown cases.
Antibody tests in a recent German study of households gave 15% infection rate.
However, if we apply the estimated mortality rate (0.37%) based on that to 11500 deaths in hot-spot New York, it would amount to over 3 million cases, again roughly 15% of the population.
Now perhaps Germans are so much healthier and their healthcare is so much better, making their real mortality rate so much lower. It's all speculation at this point, either way.
Also, the particular antibody tests they used appears to have a much higher FP rate than they claimed. Another study found 4% FPs rather than <1% like the press release for the Gangelt testing claimed.
If COVID-19 can spread to 15% of that particular population within that timeframe, and the estimate of a basic reproduction number of 2-3 predicts that this is not possible, then the estimate must be wrong.
> Also, the particular antibody tests they used appears to have a much higher FP rate than they claimed. Another study found 4% FPs rather than <1% like the press release for the Gangelt testing claimed.
Perhaps, but that doesn't put much of a dent into the results.
A FP rate that high will make a very significant difference in the results. (How large a difference depends on whether the 15% is a raw number or if it's been adjusted based on the expected test specificity and sensitivity. One would hope nobody would just report the raw numbers. But since all we've gotten from this study is basically a press release, expecting scientific rigor seems ill advised.)
Longer term follow-up found ~25% of infections were asymptomatic.
In the US, we're now doing significant amounts of testing, but we're still primarily testing only those with severe symptoms. Even limiting our sample to people presenting with severe matching symptoms of COVID-19, we're finding ~20% PCR-positive for SARS-CoV-2.
Beyond that, we also have good evidence that the Basic Reproduction Number is somewhere between 2-3. Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet.