COVID-19: Some Empirical Observations and Reasons for Optimism

April 14, 2020

Welcome back to a new post! I hope you all had a happy and safe Easter Weekend! Last week I published a post wondering about how the stock market can be down “only” about 20% in the first quarter when we’re facing a deadly virus, a wide-ranging shutdown of the economy and no clear idea when we can reopen again. We are expecting a deep recession and macro data significantly worse than during the Global Financial Crisis.

If you listen to the media talking heads it’s all doom and gloom, so why is the stock market holding up so well? Why isn’t the stock market down 55% as in 2009 or even 80% as in 1932? Does the stock market “know” something that even your trusted news anchor doesn’t realize yet?

I updated some of the charts I posted a few weeks ago and gathered some additional data as well. And it all looks much better than the breathless and scary headlines in the media. Maybe that’s why the stock market looks relatively solid – under the circumstances, at least.

Let’s take a look…

1: The fatality rate will likely be much lower than the early estimates

Early estimates of the fatality rate looked quite scary: 3.4%. Even now, if you look at the deaths vs. confirmed cases, the fatality rate is even higher than 3.4% in most countries, e.g., 4% in the U.S.!. But all those numbers are garbage estimates from people who don’t know statistics. When we divide the number of deaths by the number of confirmed cases, we could potentially vastly undercount the denominator because there are likely many more infected people that are asymptomatic. There are some indications that the current simple case fatality estimates wildly overestimate the lethality of the virus:

  • German scientists performed a large study in one of the very first German COVID-19 clusters, a small town in Nordrhein-Westfalen (my former home state, by the way). They found that in addition to the 2% of the population already confirmed, there were an additional 14% infected that had no idea they had the CCP critter. Therefore, the death rate was 0.37%. Even that death rate might be too high to extrapolate to the larger German population because we’re now much better prepared to deal with COVID-19 patients than back in February when the virus hit an unsuspecting 12,000-resident town unprepared for the onslaught of a global pandemic. More testing needs to be done but these early results definitely look much better than 3.4%! (Side note for the math/stats geeks: Some critics of the study have pointed out that the 16% estimate is too high due to the less than 100% specificity of the test. But that issue is quantitatively not relevant as this paper points out.)
  • Iceland has been aggressive with testing (easy to do in a country of 300,000): more than 10% of the entire population has been tested so far (compared to 0.5%-2.0% in most of the large developed countries). The fatality rate so far: Just under 0.5% (8 deaths out of 1,700 confirmed cases). Even that death rate might be too high if you consider that in the remaining 90% of the population not tested yet there will be many more asymptomatic people. Source: worldometers.info
  • Updated 4/14/2020 8:30pm PDT: At two NYC hospitals (New York Presbyterian Allen Hospital and Columbia University Irving Medical Center), 215 pregnant women who came in for delivery were routine-tested upon admission. 33 of them tested positive for COVID-19. Most of them asymptomatic. That’s 15.3%, almost exactly the same figure as in the German study above and much higher than the 1% confirmed infection rate. It would also lower the current New York fatality rate from 5+% to 0.36% if we extrapolate the infection rate of 15.3% to the entire population. Link: NEJM
  • As pointed out in the excellent Wall Street Journal op-ed piece by two Stanford Medical School professors, 0.9% of the people evacuated from Wuhan on January 31 eventually tested positive for COVID-19. If you extrapolate that 0.9% prevalence to the entire Wuhan metro area you had a 30-times higher infection rate than reported and confirmed at that time. And thus a much lower death rate! Of course, there could be self-selection, and thus, the result is not as robust as the German scientific study involving a large group of randomly sampled subjects.
  • Updated 4/17/2020: A sample of 3,300 subjects in Santa Clara County California found that the true infection is 50-85 times larger than the confirmed cases. That means that the true fatality rate is only between 1/85 and 1/50 of the current naive case fatality rate: between 0.12% and 0.20%. About in line with the seasonal flu. Vie WSJ: “New Data Suggest the Coronavirus Isn’t as Deadly as We Thought

So, the lesson here is: without trying to minimize how scary and deadly the disease is, the death rates floating around in the media are complete junk. Of course, journalists not only get away with exaggerating the lethality, but they are even incentivized to do so: “if it bleeds it leads!” In contrast, when people put their money where their mouth is, i.e., the stock market, cooler heads prevail. I think the stock market holding steady foreshadows large downward revisions of the fatality rates in the future.

2: The age distribution of cases and deaths is heavily tilted toward old people

Just to be sure, a 0.37% death rate is still substantial. If I faced a 25% chance of catching the virus and then a 0.37% conditional probability of dying from it, that’s still about a one-in-one-thousand probability of dying over the next few weeks and months. I could certainly rationalize staying at home then! Why take a chance, right?

Well, that 0.37% number is still complete junk science if we were to apply it to the whole population equally. Let’s look at the following completely unrelated example to drive home this principle: In the U.S., more than 5,000 motorcyclists die every year. Does that mean I have a 0.0016% probability (5,000/320,000,000) of dying in a motorcycle accident this year? No, I have a 0% chance because I don’t ride a motorcycle. On the other hand, an average motorcyclist has a 0.059% fatality rate, much higher than the average American!

The same principle is at work with COVID-19. The fatality rates differ wildly by age. Unfortunately, it’s not that easy to get your hands on high-quality data. I found data on the Swiss Health Ministry site that details the number of cases, hospitalizations and deaths by age group. Here’s what I found when I processed the data:

  • Out of 884 deaths up to April 13, there were 860 in the 60+ age group and only 24 in the 0-59 age group.
  • Thus, unconditionally, Swiss residents age 80+ have a COVID-19 fatality rate 366 times higher(!!!) than those aged 0-59: 1,352 per million vs. 3.7 per million residents.
  • Swiss residents aged 0-59 have only 1/27.9 the death rate per million residents of the overall population: 3.7 vs. 103
  • On April 13, the (naive) case fatality rate (deaths divided by confirmed cases) among all Swiss residents was 3.47%, coincidentally close to the early Wuhan figure (and likely far overestimated for the reasons laid out above). But notice that for people aged 0-59, the case fatality rate is 0.15%, only 1/23.9 of the overall rate.
  • And conditional on being a confirmed COVID-19 patient, people aged 80+ have a 129.2-times higher death rate to 0-59-year-olds: 18.78% vs. 0.15%.
  • If you assume that, just like in Germany, the true infection prevalence is 8-times higher than confirmed, then the death rate for people aged 0-59, conditional on being infected is not even 0.15% but under 0.02%.
Swiss Fatality Data 2020-04-13
Fatality rates in Switzerland as of 4/13/2020. Source: Bundesamt für Gesundheit

And just to be sure: I’d never argue that old people’s lives count less. Quite the opposite, we should likely be much more stringent in quarantining and protecting older citizens. But we can also be a lot more lenient in opening businesses again and letting younger folks out of their homes and go back to work (but please wear a face mask!!!).

By the way, I tried to find comparable data in the U.S., but the CDC publishes very incomplete data that covers only a fraction of the fatalities (less than one-third). Qualitatively, you had similar patterns though quantitatively not quite as stark as in Switzerland. But then again, there could be a selection bias in the data set if it covers only a small fraction of the total fatalities.

Update 5/5/2020: On the CDC page, there’s no more data on the age distribution anymore. I wonder why…

Summary so far

The 3.4% fatality rate that was floating around initially and is still probably stuck in people’s heads is far too high. Once we make two adjustments 1) account for the bias due to testing only people with bad enough symptoms and 2) accounting for the age distribution of fatalities, then the fatality rate looks a lot less menacing, see the chart below. If you apply the German fatality rate of 0.37% and then assume that young people have only 1/23 of the overall fatality rate we’re down to 0.016% for people aged 0-59. The actual figure might be higher or lower depending on what kind of age distribution you have in the under-counting of asymptomatic people. For example, if you assume that the asymptomatic patients are primarily young and healthy people their true fatality rate might be even much lower than 0.016%.

Fatality Rates Media v Reality

This is all great news for the restart of the economy. It debunks that insane narrative that nobody will even want to go back to work or go out to the shopping malls because you will die with a probability of 3.4%. Nonsense! Be careful and wear a facemask and minimize the chance of even contracting the virus and then even if you get the virus there’s a minuscule 0.016% chance of dying from it. All that sounds much better than the media’s narrative of “3.4% of the people who catch it will die”

In fact, if you take your motorcycle to work or to the mall then you should be 3.5-times more scared of dying in a traffic accident (0.059%) than COVID-19 (0.016%)!

3: Most countries were able to “bend the curve” already

A while ago, I shared some thoughts on the state of the world, including some charts. Well, we now have more data on cases and fatalities and I thought I’ll post an update on some of the charts. Because I added more countries and I like to automate the process I switched from Excel to Octave (a free version of Matlab). So I updated the charts from a while ago and also added a few additional countries, 26 total:

  • North America: Canada, USA
  • South America: Brazil
  • Europe: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland, UK
  • Asia-Pacific (incl. Middle East): Australia, Israel, South Korea, Taiwan

Notably absent: China and Iran because I don’t trust their data.

Since I can post only a small selection of charts here, I’ve set up a Google Drive folder if you want to check the other charts not displayed here:

Google Drive Shared Folder: “Big ERN’s COVID-19 Charts”

All charts are copyrighted but, of course, just like everything I publish here they are totally legal to use and reuse for free as long as the source is properly acknowledged.

Let’s start with the U.S. up to April 13:

  • In the top panel, we notice how the growth rate has already slowed down. In the chart with a log-scale on the y-axis, you see that as a flattening of the curve.
  • In the middle and bottom panels, I also plot the daily new cases and deaths (this time on a linear scale, not in logs) and I also include a Hodrick-Prescott-filtered series (lambda=10) to smooth out some of the daily noise and potentially weekly seasonality apparent in some of the places. Both new cases and new deaths have certainly slowed down over the weekend.
C19_Summary_USA
Total cumulative cases and deaths (top), new cases (middle) and deaths (bottom) for the USA. Notice, the top chart has a log-y-scale, the other two are linear scales. Source: www.worldometers.info/coronavirus/

Other countries are already ahead of the U.S. For example, Germany seems to be over the hump. New cases peaked in late March already and have since trended down from close to 6,000 to under 3,000. Deaths are lagging behind a bit (as expected) but even they are probably at or even beyond the peak.

C19_Summary_GER
Total cumulative cases and deaths (top), new cases (middle) and deaths (bottom) for Germany. Notice, the top chart has a log-y-scale, the other two are linear scales. Source: www.worldometers.info/coronavirus/

Germany’s small neighbor to the South, Austria, is in even better shape. New confirmed cases have been plummeting since the March 26 peak. Austria has also just opened schools and small shops again and plans to open more businesses, including shopping malls in May.

C19_Summary_AUT
Total cumulative cases and deaths (top), new cases (middle) and deaths (bottom) for Austria. Notice, the top chart has a log-y-scale, the other two are linear scales. Source: www.worldometers.info/coronavirus/

I have a lot more charts but can’t display them all. See the charts I posted on my Google Drive with the name “C19_Summary_XYZ”” where XYZ is the 3-letter country code.

From just eyeballing the country charts I would put the 26 countries in the following bins:

  • Significantly past the hump: Australia, Iceland, South Korea, Spain, Taiwan, Italy
  • New cases definitely declining, deaths still near a peak: Austria, Switzerland, Czechia, Denmark, Finland, Germany, Luxembourg, Norway
  • New cases near the top, maybe slightly declining: Canada, France, Israel, Poland, Portugal, Sweden (hard to tell – too much daily volatility, potentially even weekly seasonality), USA
  • New cases still rising (though no longer exponentially): Belgium, Brazil, Ireland, Netherlands, UK
  • I tried to be conservative; I could have put some of them in a higher category…

4: Even countries with no draconian shutdown measures bent their curves!

OK, critics may argue that as soon as we loosen the shutdown restrictions, the cases and deaths will revert back to geometric growth and the situation will get out of control again. Overcrowded hospitals, dead people lying in the streets, you name it. We shall see how it works out in Austria and Denmark. But I doubt we even have to wait that long because there are at least two countries without a full-scale shutdown to watch carefully:

Sweden opted to just let the virus do its thing while keeping businesses mostly open. Apart from prohibiting gatherings with more than 50 people, the government only gives recommendations to residents. So far at least that has not had any outrageously negative effects on cases and/or deaths. Sweden’s curve has certainly flattened and daily new cases and deaths look like they are at or even slightly past the peak. Sweden’s government has so far resisted calls to shut down the economy. A lot of doubter’s arguments, e.g. in Forbes’ “Sweden Continues With Controversial Coronavirus Strategy: Is It A Big Mistake?” sound less like a well-reasoned argument and more like an appeal “hey, we shot ourselves in the foot with our complete economic shutdown, so it would be nice if Sweden could do the same – shared misery is half the misery, you know?!”

C19_Summary_SWE
Total cumulative cases and deaths (top), new cases (middle) and deaths (bottom) for Sweden. Notice, the top chart has a log-y-scale, the other two are linear scales. Source: www.worldometers.info/coronavirus/

Update (4/14/2020, 4pm PDT):

As some people pointed out, Sweden may not exactly be over the hump (yet). There’s certainly a weekly seasonality pattern here. Cases and deaths usually jump Tuesdays to Thursdays. I updated the chart and included a 7-day rolling average in the chart for Sweden, see below. New cases are only flattening if you look at the 7-day rolling average. Deaths are bending down just slightly. It’s too early to call that a victory, but the situation is certainly not getting out of control in Sweden either. I will monitor this carefully!

C19_Summary_SWE2

Update 4/28/2020: The brain behind the Swedish policy, Prof. Johan Giesecke:

 

Iceland is another country without too much of heavyhanded government response. As mentioned above, it has one of the highest numbers of confirmed cases as a percentage of the population (the second-highest in my 26-country sample, after Luxembourg). But that’s due to testing people at a rate 5-10 times higher than in other countries. But new cases and deaths have slowed down significantly. Iceland is open for business, even welcoming tourists – if you can get there. And to the shutdown-fetishists’ chagrin, people are not dying in the streets: 8 fatalities so far. Out of 1,700+ total confirmed cases, 993 have recovered and out of the 770 remaining active cases, 10 are critical (Source: www.worldometers.info/coronavirus, accessed on 4/13). So, the hospitals are not exactly overflowing either. It’s a great success story and it should be celebrated. Wouldn’t that deserve at least a 1-hour special on CNN?

C19_Summary_ICL
Total cumulative cases and deaths (top), new cases (middle) and deaths (bottom) for Iceland. Notice, the top chart has a log-y-scale, the other two are linear scales. Source: www.worldometers.info/coronavirus/

So, both Iceland and Sweden were able to flatten the curve without flattening (killing?) the economy.  If and when we loosen our shutdown measures there is a good chance that the situation will not get completely out of control from there if we follow some of the same less-restrictive prescriptions from those two Scandinavian pioneers: be reasonable, keep your distance, but go about your business as usual in every other way. If the rest of the world can get off their butt and acknowledge that Sweden and Iceland probably succeeded then there’s hope for a quick recovery!

By the way, as I was writing this I found this very nice 60 Minutes Australia episode on YouTube talking about some of the issues that are on my mind. It was the best and most rational reporting I’ve seen so far. Why don’t we have journalists like that in the U.S.?

  • At the 5.45 mark: Prof. Bjorn Lomborg about the difficult tradeoffs: “Going too hard on lockdown is a strategy that will come back to bite us in the long-run”
  • At the 8:35 mark: The Swedish experience. Looks a lot nicer than the Australian “police state” right now.
  • At the 13:36 mark: Infectious disease modeler Prof. Emma McBride on the benefit of letting the disease spread in “low-risk” demographic groups. They must have looked at the same data as I did here!

Update 4/15/2020: I should mention that I never intend to create the impression that Sweden and Iceland will go through this episode completely unscathed. Quite the opposite, they will likely also experience a recession, just like the rest of the world. But it will likely be a lot less severe than in the countries that completely shut down for an extended time.

5: U.S. States Data

I can also apply the same analysis to the 50 U.S. States plus D.C. The data come from the New York Times GitHub page.

Again, I can’t post all 51 charts here so I keep the state-level data in my Google Drive folder for your enjoyment. But here are a few observations: Within the U.S., we have just as much, probably even more variation than across countries in my 26-country sample. On the one hand, you have NY and NJ with more cases per population than even Iceland and Luxembourg. On the other hand, you have dozens of states with lower infection rates than even some of the less-impacted countries. (though no U.S. state can beat Taiwan).

 

C19_CountriesVsStates_Cases

The same format, but this time I plot the fatalities per 1 million residents, see the chart below. Again, NY State tops even Spain and Italy (though I doubt that NY will top the Lombardy region of Italy). But there are plenty of states with even lower fatality rates than some of the less-impacted countries. That’s really good news!

C19_CountriesVsStates_Deaths

Critics will certainly argue that all the states with lower infection rates are just waiting to become the next New York State. But I doubt that! Here are some time series charts of cases per 1 million residents. I can’t fit them all in one chart, so I bunched them together by groups of 10 to 11 states. Here are the 31 states with the highest case rates so far, see the three charts below. All states are bending their curves already. I doubt that any other state will reach the NY state 10,000 cases per million residents anytime soon! (well, South Dakota is still in exponential growth but from a very low level right now, so let’s monitor that!!!).

C19_TS_CasesPC.1
Part 1: Cases per 1m residents. The 11 highest-ranking states.
C19_TS_CasesPC.2
Part 2: Cases per 1m residents. States ranked 12th the 21st.

Also, notice how the nation’s largest state by population, California, is only ranked 31st among the 51 in cases per capita. And the curve there is bending really nicely:

C19_TS_CasesPC.3
Part 3: Cases per 1m residents. States ranked 22nd to 31st.

Some of the states that were floated as “The Next New York” such as Michigan, Louisiana and Florida also don’t look like they are going down the tubes. Here’s Michigan: new cases peaked in early April, deaths are probably near the peak or even declining.

C19_Summary_MI
Michigan: new cases reached a peak in early April. Deaths might have peaked or are close to peaking.

Here’s Florida: daily new cases seemed to have peaked:

C19_Summary_FL
Florida: new cases started a slight downward trend. Deaths might also be close to the peak.

And here’s Louisiana:  daily new cases have plummeted, deaths are also probably past their peak already:

C19_Summary_LA
Louisiana: it looks like cases peaked in early April. Deaths could be at or even beyond the peak.

So, to the doom and gloom fetishists’ great disappointment, MI, FL and LA will not be another New York State and certainly not a New York City. Thank God for that!

Also, back to California: new cases have already started to bend down. Deaths are probably near their peak:

C19_Summary_CA
New cases in California peaked in early April. New deaths look like they might be leveling off.

And finally, here’s my home state of Washington, the state with the first confirmed case and first confirmed fatality: No more out of control exponential growth (see top panel), cases have slowed down and even deaths seem to be on a downward trajectory:

C19_Summary_WA
Washington State: new cases are now declining. Deaths have also dropped.

Summary

So, overall, these are hopeful developments from the COVID-19 front! No wonder the stock market is holding up better than during the Great Depression. COVID-19 will not wipe out civilization, that was clear from the beginning. But investors have become hopeful that it will not wipe out the economy either!

Update 4/27/2020: The academic blessing of opening up again also came from one of the most impressive researchers in the field, Dr. John Ioannidis from Stanford University:

And this here is the full interview (more than 1 hour, but worth every second!!!)

 

A caveat…

Of course, here’s a scenario that could completely derail the stock market’s optimistic outlook: politicians and unelected officials are unwilling/unable to admit that we might have somewhat overreacted during the whole shutdown. Nobody should feel ashamed because back in March we had no idea how bad the virus will turn out. The shutdown was 100% defensible back then and I certainly had my worries about Sweden and Iceland (and thus kudos to them for serving as the guinea-pigs for the rest of us).

But if people are not willing to admit that it’s about time to relax the economic shutdown soon, out of some misguided bureaucratic pi$$ing contest – excuse my language – we’re in for a lot of trouble. Expect the stock market to completely tank to 2009 levels (-55%) and maybe even to 1932 levels (-80%) in that case. 

Sorry for ranting!

Update 4/28/2020: I’ve decided to close the comments for this post, the first time I ever had to do that. Nice discussion, but I realize that some people disagree with me and there’s not going to be common ground, ever. Let’s just move on to different topics…

Title Picture Credit: Pixabay.com

 

211 thoughts on “COVID-19: Some Empirical Observations and Reasons for Optimism

  1. Thank you Karsten for your thoughtful and detailed analysis.There is a significant psychological/emotional component that is lost though (OBVIOUS BIAS POINT: I’m an acute care psychiatrist). This is a situation where the overreaction was the only way to get ANY reaction. It’s not much different than the base point of someone who wants to know the weather. If there is a prediction for rain, a person may bring their umbrella. If there is a prediction of a heavy storm, a person has to consider the factors of their personal situation. If there is a prediction of a hurricane, then there will likely be a coordinated effort on the part of local…perhaps state…perhaps federal level to address possible concerns.
    The actual result of the preparation is not nearly as important as the preparation itself. NY/NJ residents laughed at how we “wasted our time” worrying about hurricane Irene. I still have to deal with patients who will “never get over how stupid we were ignoring” the threat of Sandy. I have spirited debates over the “worse than coin-flip” odds of the efficacy of a seasonal flu vaccine, but now those debates have shifted to how “people are stupid” to not social distance (a tactic that has never been employed until now in my professional career). To put it in another perspective, you have pointed out that the Javits center is an overreaction because it wasn’t used in hindsight. That’s a wonderful point, because the Javits center is not meant to be a hospital to begin with. The idea that anyone would have to be that forward thinking is scary in and of itself.
    I’m not used to talking to colleagues who have had to make the phone calls to families multiple times a day, every day about their loved one dying in the ICU. That was a once a week or less occurrence at some of our hospitals (most people leave the hospital alive on a regular basis; with Covid, not as much). This is wearing down nurses, APNs, techs, EMTs. It’s startling to “know” that at age 38, I’m not at high risk, but then have someone near my age in the medical field die anyway (I apologize for anecdotal evidence. I know it ultimately means very little in the discussion). I have no clue if this type of response is happening anywhere else.
    I fully admit my limited scope of knowledge, and ignorance from an epidemiological standpoint, because my focus demands that I deal with personal cases. But I do know that, from that perspective, discussing the economy on a larger scale will fall on deaf ears. I sincerely hope that the data so far, as limited as it is in scope, is accurate. The lack of full scale testing is the greatest limitation.

    1. Thanks for sharing that story. And thanks for your service in the medical community.
      I agree that in order for people to move their butts you have to scare them a little bit. Mission accomplished. But since the whole thing has worked out relatively well and deaths are well below the initial estimates it’s time to stop the scare tactics.

      Also, I never viewed the Javits Center as an overreaction. It was the right thing to do at that time, as an insurance policy. But when we find out that hospital capacity is not being overwhelmed it’s time to reopen the economy (slowly) as it was initially planned. I sense a bait-and-switch because now people want to shut down the economy until we find a vaccine. Which was never on the table initially. The shutdown was to give the hospitals breathing room. Now they have the room and we shut reverse parts of the shutdown.

  2. I think what may make the US worse though is our obesity problem. You rightfully pointed out that fatality is geared toward the old, however the caveat is that ICU and fatalities in under 65 yr olds appear to be worse in those with BMI>30, which I’m going to guess the US is amongst the leader in it. Even if the death rate is similar, I’d suspect our ICU admissions for younger people will be higher. Any data you could find on that?

    1. Excellent point! I’m worried about that too! In the Swiss data you notice that there is a huge difference in lethality between old and young. In the U.S. there is a large spread but quite as large. One explanation could be that we have more obese folks.
      It would also explain the difference between NYC and Santa Clara fatalities.
      No data on this available, though. The epidemiologists SHOULD be collecting and studying this, but I guess they are too busy feeling important and giving interviews on CNN right now.

  3. https://www.cnbc.com/2020/04/15/watch-now-healthy-returns-the-path-forward-with-cidraps-dr-michael-osterholm.html

    This is an excellent interview for his epidemiological viewpoints on Covid-19…including what we need to do differently going forward while trying to control Covid-19. He acknowledges that we need to make some difficult decisions, because we also need to provide for ourselves as we follow a rational course not just as individuals, but as a country, and as a world to do this as well as possible.

    He is one of the most informed experts on the planet in public health, and in new viral epidemics, and has written extensively on that topic. He is also a very capable communicator, and is well accepted in his field of expertise.

    His background: https://directory.sph.umn.edu/bio/sph-a-z/michael-osterholm

    1. I have to shake my head about him. (even though he’s at the U of M, my alma mater!)
      No discussion about the vast differences in lethality across different demographic groups (old vs. young, working vs. retired, healthy vs. pre-existing conditions, overweight vs. normal weight, etc.) and what that means for the pros and cons of reopening.
      No discussion about the negative impacts on the health and life-expectancy of 30 million unemployed people.
      I learned absolutely nothing from that interview. What does he propse we ACTUALLY do for the next 20 months? Does he propose we keep the economy shut down for 20 months until we find a vaccine? For something with 2 to 5-times the lethality of the flu?

      I very much liked the interview with Jay Bhattacharya from Stanford Medical School. He is an MD and an Econ PhD (!) and he understands the statistical challenges and economic tradeoffs much better.

      The first half is about the Sabta Clara study and the second half is about the cost-benefit analysis, something that ordinary epidemiologists probably don’t fully grasp.

        1. I would discard some of the twitter/buzzfeed lynchmob.

          NYC’s worse results can be accounted for by
          Bill DeBlasio claiming “nothing to worry about” until mid-March
          NYC getting a more dangerous strain of COVID
          Younger population in CA
          Healthier population in CA
          Colder climate, more pre-existing cold/flu cases
          Getting bigger virus loads on you while people are coughing and sneezing on you in damp cold subway cars
          So, I’m not troubled by a 6x difference in the death rate when you look at the worst impacted area vs. least impacted area.

          About the sampling: true there has been oversampling of certain demographic groups. But the researchers adjusted for that. Also, in isolation I could have agreed with the criticism. But everywhere in the world you get confirming results:
          a) Gangelt/Germany 15% positive tests. With probably one of the most robust and soundest statistical sampling techniques applied there.
          b) the pregnant women in the 2 NYC hospitals also 15%. Also less endogeneity problem because the women showed up on their own without having to respond to an ad or email.

          1. Well, the twitter “lynchmob” I linked to is a public health professor. And many more of similar stature are saying the same.

            The NYC OB study again comes up with fatality rate of more like 0.8%+.

            NYC is also similar to the U.S. as a whole in terms of age >65 (and more likely healthier in general than U.S. as a whole – e.g. obesity distribution in U.S. https://www.cdc.gov/obesity/data/prevalence-maps.html), so fatality rate there seems pretty relevant to the country as a whole.

            1. Watch this expert: https://www.youtube.com/watch?v=cwPqmLoZA4s
              NYC’s higher death rates are explained by nosocomial infections, i.e., hospital-acquired infections. NYC hospitals went through the same disaster as in Lobardy. You have the same crazy variations in death rates in Europe as CA vs. NYC. I would not be worried about a 6x difference in the IFR.
              (discussion about the hospital situation starts at around the 7:15 mark)

              1. Higher death rates from admitted Covid patients is very likely highly associated with hospitals being overwhelmed by the numbers and severe condition of the patients being admitted… and yes, that will cause an increase in the nosocomial infections and a host of other things that make patient care and safety less effective.

                1. Hospitals were probably overwhelmed with too many patients with moderate and mild patients and they spread the virus there in the hospital. That’s what Ioannides seems to say.
                  Now we have learned the lesson to admit only the most severe cases and let the people with moderate symptoms cure themselves at home. But the early clusters (Lombardy and NYC) didn’t know how to properly. At least that’s the way I interpret his comments.

  4. Don’t forget that the masks only inhibit droplets from your mouth and nose from entering the “public space”. Don’t think that the mask keeps you from getting infected!!

    1. Uhm, you’re about 4 weeks late. That was the false story the so-called experts floated early on. Their story has now changed: simple face masks can reduce the risk of catching it. Not eliminate but REDUCE.
      But you’re right, unless you wear a level-4-lab biohazard suit you can never feel 100% protected.

  5. Big ERN for the win. Couldn’t agree more!!

    As a physician this has been a huge overreaction. We need to wisely move back into normalcy. A phased approach is appropriate at this time.

    The media is largely to blame. They don’t have to compete with anything at this time as sports have stopped and people can’t socialize. It is a feeding frenzy for them.

    If mortality had been in the 5-7% range or if we had seen a significant number of deaths in the younger age groups I would understand the fear. As pandemics go this is a very mild pandemic. (Compared to 1918 and bubonic plague). My hope is that out of this we are better prepared for the next pandemic which could be much, much worse.

    Keep up the good work.

    1. Also a physician (that has taken care of COVID patients), and disagree that there has been an overreaction. Wisely opening up in a phased approach, sure – but with much better testing and contact tracing than we have now, and when cases have consistently slowed.

      If spread in Italy or NYC had continued unabated, mortality would have risen once you exceed the capacity of health system. From a colleague in NYC (a Cardiologist who was recruited to act as an Intensivist because they didn’t have enough Intensivists to see the units full of COVID): “SICU, MICU, CCU, CT-ICU, Stepdown Units, operating rooms, all vented COVID.” For the non-medical people, that means that every ICU in the hospital (as well as parts of the hospital that do not normally function as ICUs) were full of COVID patients on ventilators, with 80% mortality once vented. Once you exceed the number of ventilators (which even if NYC has 20% prevalence now, multiply by 4x to get to herd immunity and you’ll easily overwhelm hospitals), all of those patients that would have needed ventilators will die. And keep in mind that other cities and states have not reached that point BECAUSE we shut down. It’s reminiscent of anti-vaxxers saying they don’t need their MMR because nobody gets measles anymore.

      Even IF the infection fatality rate ends up being 0.1% (which I don’t believe will be the case), it was certainly not an overreaction to shut down when we had no idea what the IFR actually was and we were seeing health systems in wealthy countries on the verge of being overwhelmed. Nothing to do with the media.

      1. We, as a country, did not over react… we under reacted and reacted too late. Even if too late, a coordinated national effort did not happen… but if it had, we would likely be in a much better situation over all right now. S. Korea and New Zealand did things well, and in a very rational fashion… nationally we have basically cluster-ducked making the right decisions. A lack of national leadership, and yes, citizen cooperation has made things much worse than they need to be.

        1. We shall see who’s coming out of this better Sweden or NZ. NZ has shut down and they’re stuck now. If they reopen, the virus spreads and kills just as many people as in Sweden. If they stay shut down until we have a vaccine, they’ll ruin their economy. Worst of all worlds.
          So, to you and Korea and Singapore and NZ and lot of others I respond: don’t declare victory until this is all over. Don’t smile at the crocodile until you’re crossed the river! 🙂

      2. Strawman argument. Never argued that the initial sutdown was an overreaction. But now that we’ve found out that we have ample capacity even in NYC, it’s time to open up again, slowly. Certainly in the rest of the country, probably also in NYC.

    2. Thanks, Dr.!
      I hope that we take the lessons from this heart and be better prepared for the next event like this. But I’m also concerned that lots of people will deduce all the wrong lessons from this. See the politicians, the media and even a lot of commenters here.

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