How Much Will The Models Cost?

I have written before that there has never been a time in the history of mankind where more has been wagered on the output of a model than we are seeing right now.

Large sums of money, and the lives of many people, have been put on the line many times throughout history. Most of those instances involved going to war with an enemy that was known and a threat that was real and very well understood.

There is no question that Covid-19 is a threat. However, there is so much we don't know and understand about the disease. Even today we still don't understand the real nature of the threat. We don't know enough about its transmission. We don't know how many people have actually been infected. As a result, we don't really know how lethal it is.

For example, research in the last few days is starting to suggest that the use of ventilators may actually be doing more harm to Covid-19 patients than good.

In the last 3–5 days, a mountain of anecdotal evidence has come out of NYC, Italy, Spain, etc. about COVID-19 and characteristics of patients who get seriously ill. It’s not only piling up but now leading to a general field-level consensus backed up by a few previously little-known studies that we’ve had it all wrong the whole time.

There is no ‘pneumonia’ nor ARDS. At least not the ARDS with established treatment protocols and procedures we’re familiar with. Ventilators are not only the wrong solution, but high pressure intubation can actually wind up causing more damage than without, not to mention complications from tracheal scarring and ulcers given the duration of intubation often required… They may still have a use in the immediate future for patients too far to bring back with this newfound knowledge, but moving forward a new treatment protocol needs to be established so we stop treating patients for the wrong disease.

The past 48 hours or so have seen a huge revelation: COVID-19 causes prolonged and progressive hypoxia (starving your body of oxygen) by binding to the heme groups in hemoglobin in your red blood cells.

People are simply desaturating (losing o2 in their blood), and that’s what eventually leads to organ failures that kill them, not any form of ARDS or pneumonia. 

If true, that is quite a revelation in that all of the models have used ventilators as one of the key resource restraints we would have to have to treat the disease.

It is also where tremendous sums of money have been spent by hospitals, state governments and the federal government to make sure we have enough ventilators that cost from $25,000-$50,000 each.

In fact, the federal government currently has contracts with various manufacturers for the production of tens of thousands of additional ventilators.

Let's look at what the models were telling us a week ago and compare it to where we are today.

The IHME model seems to have had the most influence on government policy makers.

This is what that model predicted exactly one week ago as to the hospital resources that would be required today (April 9) in New York.

76,130 hospital beds needed.

11,782 ICU beds required.

9,427 ventilators would be necessary.

Keep in mind that this was not a model from one month ago. It was a model that was projected needs one week ago on April 2.

What are the actual numbers reported today by New York State?

18,279 Hospital beds in use. (24% of what the model projected)

4,925 ICU beds in use. (42% of the model)

Ventilators being used. (No numbers released but ICU is only about half of what ventilator projection was for this date)

What about my home state of Ohio?

This is the projection of hospital resource utilization in Ohio in the IHME model for today from one week ago.

4,892 hospital beds needed.

878 ICU beds.

703 ventilators.

What are the actual numbers reported on April 9?

1,612 Hospitalizations (33% of actual)

 497 in ICU (57% of actual)

No numbers provided on ventilators being used. However, the numbers in ICU are just over 2/3 of the number of ventilators that were projected to be required.

If you want to get an idea of how faulty the models and the logic that surrounds the reaction to the virus in Ohio is, consider this slide that Governor Mike Dewine recently used to show the success of the stay at home order and other mitigation efforts. (Hat tip to @AlexBerenson for pointing this out.)

Notice how this model shows a peak of 62,000 new cases if no mitigation efforts were undertaken.

However, also notice that the model shows a peak date of March 22.

When did the stay-at-home order in Ohio become effective? March 23. That is one day after the supposed peak according to the model.

Granted, Dewine closed the schools, bars and restaurants effective March 16. However, the fact is that it generally takes 5-7 days from the time someone is infected until symptoms manifest. Most cases showing up on March 22-23 would have resulted from people picking up the virus before most mitigation efforts had been implemented.

It should be noted that Dewine also banned any mass gatherings of 100+ on March 12. That could be responsible for the drop in cases from the original model. Do these numbers also suggest that this mitigation approach might have the greatest benefit at the least cost? It is worth considering. Was it really necessary to do everything else that was done?

How many confirmed cases were there in Ohio on March 23?

2,023 TOTAL CASES. That is not a daily count as shown in the graph. Those are all the cases.

The actual daily count of new cases on that date was 146.

That is the count the Ohio Department of Health is using today (April 9, 2020).

On March 23, this is what they were reporting at the time the stay-at-home order went into effect. The numbers have been revised upwards since that time.

Credit: https://www.wyso.org/post/coronavirus-ohio-live-coverage

Let's recap.

The model that Ohio used to justify the stay-at-home order projected 62,000 new cases on March 22 the day before the stay-at-home order was implemented.

The actual number of new cases on that day were 146 and almost all of those new cases involved infections that had to be received before any mitigation efforts went into effect.

146 out of 62,000 is .24%.

That means the model was off by 99.76% compared to actual results.

Below is Governor Dewine on Twitter extolling the great success of the mitigation efforts in Ohio compared to the original model.

For additional context, it was just over 10 days ago that Ohio's model was suggesting that we would see 10,000 new cases per day at the peak of the crisis in mid-May with full mitigation efforts in place. It was at that point I lost all confidence in the models Ohio or anyone else was using. I wrote in detail about my skepticism about the models being used in Ohio and elsewhere on March 29. I predicted that they would be proven wrong.

In other words, Dewine is taking credit for mitigation efforts for reducing cases in which a model had predicted would occur before almost anything was actually done!

That is quite a feat.

Let's be clear. I am not suggesting that the mitigation efforts have not been effective. They clearly have been. As stated, the ban on mass gatherings might be proven in the end to have produced the greatest bang for the buck. There is no doubt that fewer cases and fewer deaths have resulted from all of this social distancing.

If you doubt that take a look at this chart from HealthWeather.US which tracks readings from smart thermometers around the country and allows for the surveillance of fever-based seasonal illnesses such as influenza and Covid-19 in the United States.

This chart shows these illnesses were following a typical seasonal path until the beginning of March when we began to see atypical experience. That is when Covid-19  started to take hold in the country. The variance reached a peak on March 16 with about 5.1% of the population showing signs of illness compared to an expected 4.2%. Interestingly, this is also the exact time that many states started social distancing rules.

Credit; HealthWeather.US

You can see what happened next. Fever-related illnesses went into free fall. At this point, we have succeeded in almost completely wiping out all fever-based illnesses in the country. We are currently at 0.42% compared to an expected 2.66%!

However, the question in all of this is what are we supposed to compare these models to?

You can readily see that the model Ohio was relying on was flawed.

You can see the the IHME model was flawed.

We have seen success but at what cost?

Do the benefits outweigh the costs?

We are likely to see many more politicians and public heath experts bringing out the models and showing us what a great job they did as the Covid-19 crisis winds down.

Will those results be justified by the economic costs that have been incurred?

That question is likely to be with us for a very, very long time.

It practically begs for someone to create another model to help us determine the answer. 😀

Blinded By Their Bias

One of the more interesting things that I have observed during the Covid-19 crisis is how much it has revealed the true tendencies of the liberal left and mainstream media.

A common narrative from both is that Donald J.Trump is a fascist, authoritarian, autocratic leader who does not care about individual rights or civil liberties. They say he believes he is above the law and is only interested in consolidating and extending his power over the nation.

Here is a headline from an article that follows this theme.

However, what are we seeing with our own eyes during the Covid-19 crisis?

President Trump is governing with guidelines, recommendations and working to facilitate public/private sector solutions to the crisis. He has closely followed the guidance has has received from public health experts. There have been no orders, directives or a declaration of martial law for Trump to wield authoritarian power.

Trump has deferred to the nation's Governors to fashion customized responses to individual state needs and has supported them with national resources when needed. He has been very judicious in using the Defense Production Act that would make private businesses an arm of the federal government.

Of course, the same people who have been calling Trump an authoritarian, power-hungry fascist are now questioning Trump as to why he has not ordered all Governors to shut down their states and why he is not using the Defense Production Act to force all industries to do his bidding.

The fact that Trump is following the Constitution in all that he is doing seems to be lost on these people. As President, he is being very careful to not trample on state's rights or individual liberties to the greatest extent possible in this crisis. It is the exact opposite of what a power hungry authoritarian would do.

It should also be noted that we find the most authoritarian and autocratic responses to the crisis in cities and states governed by liberal Democrats. To be fair, we have also seen this behavior by Republican governors in blue states as well.

For example, Los Angeles Mayor Eric Garcetti is encouraging people to report businesses and others who are violating his stay-at-home order. He is even offering a reward for those who do so.

“You know the old expression about snitches—well, in this cases, snitches get rewards,” he said. “we want to thank you for turning folks in and making sure we are all safe.”

Garcetti also threatened to cut off the power and water to any non-essential business that continued to operate in violation of his order.

A lone paddleboarder was arrested in California for violating Governor Gavin Newsome's statewide stay-at-home order. The man faces a jail term of six months or $1,000 fine, or both, if convicted of the charge.

In Vermont, Republican Governor Phil Scott has ordered that all big box stores like Walmart, Target and Costco must stop the sale of nonessential items in the store even if they are allowed to be open to sell "essential" items.

These stores are supposed to take nonessential items off of the shelves or block customers from the aisles that have these items even as the store is open.

One of the nonessential categories is home and garden items. Therefore, you can go into the store to buy lettuce or carrots but you would not be able to buy the seeds to plant your own garden this spring. You also would be prohibited from buying a fishing rod at Walmart if you wanted to fish for your dinner rather than make another trip to the grocery store. How much sense does this make?

Trump is a "full-on authoritarian"? Compare his actions to some of the examples above.

How often do we also hear those on the liberal left decry economic injustice and privilege?

Who is being hurt the most from what we are going through?

I can assure you it is not the political class, public sector employees or limousine liberals.

Those being hurt the most are those that liberal Democrats claim are the people they want to help the most.

The people that are most vulnerable to what is going on with Covid-19 are lower and middle class workers who don't have the luxury of being able to work from home. They are in the front lines at work or have lost their jobs. They most assuredly are not "sheltered at home" in any shape or form.

The coronavirus is spreading a dangerous strain of inequality. Better-off Americans are still getting paid and are free to work from home, while the poor are either forced to risk going out to work or lose their jobs.

This chart shows how large the impact is on those as you go down the income ladder.

Credit: https://www.axios.com/axios-ipsos-coronavirus-index-rich-sheltered-poor-shafted-9e592100-b8e6-4dcd-aee0-a6516892874b.html?utm_source=newsletter&utm_medium=email&utm_campaign=newsletter_axiosam&stream=top

Who is the one who talks most about getting America back to work?

Why is President Trump castigated and ridiculed by the Left and mainstream media for wanting to get Americans back to work?

And considering the reality of the numbers in that chart, why did the Governors in Virginia and Maryland institute stay-at-home orders until June 10 hours after President Trump extended his guidelines until April 30?

This is nothing compared to what former Obama health advisor Zeke Emanuel said on MSNBC. By the way, Emanuel is also said to be Biden's top health advisor on his campaign.

12-18 months? Will there be a United States of America left by then if this was the policy put into place?

Below is another interesting chart I came across recently on Twitter. It was prepared by The New York Times and it uses cellphone data to assess which counties across the nation had the most travel last week compared to normal.

Credit: https://twitter.com/WLNSAlexSims/status/1246479343087497217

I thought it was an encouraging chart in that it showed just how effective social distancing and the stay-at-home orders have been. This is readily apparent in looking at the northeast part of the country and states like Ohio, Michigan, Illinois, Indiana and Wisconsin. It shows almost no travel is going on.

However, this was not how some of the liberals on Twitter saw it. They see everything as an  opportunity to demean and belittle anyone who doesn't breathe the rarefied air of their enclaves of privilege and pomposity.

A few examples in the responses to this chart that were on Twitter.

Do you notice a common theme? It doesn't matter the circumstances. There is a constant refrain from many liberals to denigrate and demean anyone who doesn't share their world view. Multiply it ten-fold if it has anything to do with Donald J. Trump or his supporters.

What seems to be lost on these people is that those areas in red on the map are mostly in rural areas with very low population density. They don't have a Whole Foods or Trader Joe's up the street they can walk to. They might have to drive 20 miles to get to an IGA. There is no corner drug store.

In fact, a lot of those people are still doing their jobs in growing crops and delivering essential items to the local stores of these self-righteous nincompoops in their mega metro areas.

In addition, if those people who were so quick to comment on Twitter had been willing to take the time to look a little closer at the map, they would have seen that there was no difference in the behaviors of those in the large metro areas in the red states than what is going on in the metro areas of the blue states.

I have highlighted the low travel in metro areas such as Raleigh-Durham, Charlotte, Miami, Atlanta, New Orleans, Nashville, Kansas City, St. Louis, Dallas-Ft. Worth and Houston. There is no "red" there.

The Covid-19 has been a massive wake-up call to our nation. It should cause every American to take a step back and reconsider a number of questions.

Should we rely on China and others for critical medical supplies and drugs?

Should we rely on China and others for a number of other strategic materials and goods?

How reliant should we allow ourselves to be on any other country in our supply chain of other goods?

How much can we trust Communist China to be transparent and open about issues that could have worldwide effects?

Seeing the risk of disease coming across the border so easily, should we be implementing much stronger measures at border control?

Can anyone still believe that an open border policy really serves the American people?

How much should we trust models to determine the expenditure of trillions of dollars? If the models in this case can vary 80-90% in a couple of weeks, how much trust should we put in climate models that are forecasting events a decade or more in advance?

There are many more.

One thing that has been answered unequivocally is that much of what comes out of the mouths of the mainstream media and Democrats about the fascist, authoritarian Donald Trump could not be further from reality.

It is in full view every day.

Unfortunately, too many people are blinded by their bias to see what is right in front of them.

Will We See The Peak This Week?

Will we see the peak this week on Covid-19?

That is a big question on everyone's mind.

Of course, a lot depends on what you define as the peak.

When you are dealing with an infectious disease the first thing you want to see is the point at which the exponential increase in cases slows. This indicates that some progress is being made in stopping the virus from spreading.

I shared this graph in an earlier post in which I tracked the 3-day rolling growth rate of confirmed cases in New York. The peak on that measure was reached on March 20. That number had trended down to 1.36x as of yesterday.

The peak you really want to see is when the number of new confirmed cases drops day over day.

New York still has not reached the point where that number is decreasing consistently on a daily
basis.

I have been watching the Hospitalization number involving Covid-19 most closely in that it is an indicator for two important factors in all of this. First, how large is the strain on our hospital system going to be. Second, it should gives us an idea of where the death rate is going to go. As more patients need to be hospitalized it follows that deaths will increase as well.

It seems to be the general rule in all of this that an increase in confirmed cases will lead to an increase in hospitalizations a week later and increased hospitalizations leads to increased deaths in another two weeks.

Notice that the peak growth rate on hospitalizations in New York was reached on March 28. That was 8 days after the the peak in the growth rate in confirmed cases was reached.

The good news in looking at the data is that the increase in the 3-day rolling growth rate for deaths also peaked around the same time rather than lagging the hospitalization rate. This might suggest that doctors have been finding better ways to treat Covid-10 patients and preventing the expected accelerated number of deaths consistent with growing confirmed cases (lagged by two weeks).

The peak most people are looking for is when the number of hospitalizations begins to decline as well as the daily count of deaths.

We are still not there on hospitalizations but, as shown above, it is slowing.

New York reported yesterday that the state had 15,905 people currently hospitalized which was an increase of 1,095 compared to the day before.

Credit: State of New York, 4/420

However, compare that hospitalization number with the IHME model that federal and state public health officials seem to have been following in making policy decisions.

That model suggested that 65,434 hospital beds would be needed for Covid-19 patients on April 4. That number would include 12,011 ICU beds.

Right now only 24% of the hospital beds and 34% of the ICU beds that were projected to be needed are being utilized.

That is clearly good news but consider the mobilization effort that has been required (hospital ship, field hospitals, thousands of extra ventilators) because of the reliance on this model?

A lot of time, money and effort has been expended based on that model.

These are the numbers New York released on Sunday, April 5.

Credit: New York State, 4/5/20

Here is another way to look at the trend on hospitalizations that was put together by Charlie Bilello.

In addition, deaths were +594 compared to +630 yesterday. All numbers were better than the day before including the number of patients discharged from hospitals.

The IHME model projects that maximum hospital peak resources is going to be reached in New York this week on April 9 and the strain on the system will thereafter diminish.

Based on what I am seeing right now, it does not look like we are going to be short 63,000 hospital beds and 9,400 ventilators in New York as the model projects.

My view seems to also be supported by the trend in ER visits to NYC hospitals for influenza-like and pneumonia conditions in the chart below. This would indicate that the peak in hospitalizations is approaching. ER visits have been declining among all age groups in the last week

Source: https://www1.nyc.gov/assets/doh/downloads/pdf/imm/covid-19-syndromic-surveillance-04052020-1.pdf

The IHME model also projects that the daily death total in New York will peak this week on April 10 with 855 deaths. There were 594 deaths in New York yesterday.

Based on the 3-day rolling growth rates I have calculated, I think the expected the number of deaths on April 10 could be higher than 855. I hope I am wrong. If it stays below that number I think we have definitely turned the corner in New York.

New Jersey also saw a large reduction in deaths over the last day. Is this an aberration or an indication that things are getting better? This week should give us an answer.

Credit: @JamieDupree

The IHME model is projecting that the peak in use of hospital resources will not be reached until April 15 nationally. It is also projects that April 16 will be the day that peak deaths for the nation are reached.

New York might reach a peak this week but it looks like it may be another week until we make the turn for the nation at large.

This is the reason why President Trump said this last week.

Credit; NationalPost.com

As I have written earlier, the only thing that has seen greater exponential growth than the virus is the negative effects it has had on the economy.

Another couple of examples from last week. Unfortunately, these are deep valleys rather than peaks.

Year over year change in traffic in retail stores.

How close can you get to losing 100% of your business in the course of a few weeks?

Hotel occupancy.

I am actually surprised this is not worse.

I am all for reversing what is going on.

Let's turn the virus peaks into large valleys and the economic valleys into peaks that become high plateaus.

The sooner the better.

Another interesting sight I saw today that says a lot about where we are right now.

This is a picture of the drive-thru at the nearest Starbucks to my house (the Starbucks is on the other side of the small strip center from the Panera you see in the foreground). There was a long line of cars wrapped around the building. I counted 18 cars in line at 300pm in afternoon. This is during a stay-at-home order. I guess coffee in the middle of the afternoon is an essential item.

This is the picture of the drive-thru at the closest Covid-19 testing center to my house at 1000am on Thursday. Not one car in sight.

Based on the news reports, you would think the lines at these drive-thrus would be reversed wouldn't you?

Looking At The Covid-19 Landscape

The landscape around us is changing as if an 8.0 magnitude has altered everything around us.

A few observations as I look across the landscape.

Unemployment 

10 million have filed for unemployment benefits in just two weeks time.

3.3 million last week. 6.6 million this week.

That pushes the total unemployment rate to over 9%

The Federal Reserve Bank of St. Louis suggests the unemployment rate could reach 32% before the end of June. In the Great Depression of the 1930's the highest unemployment rate reached was 25%.


Air Travel

Air Travel is down 94% from this time last year.

136,023 flew by air on April 1, 2020. 2,280,522 flew exactly one month ago on March 1.

If you need further proof, this is the TSA area at the Denver airport at 530pm CDT on April 2 which would normally be packed.

Credit: @Cernovich

Restaurants

Restaurants are closed throughout the United States except for take-out and delivery. The same is true for other countries as well. This graph shows the % change in diners from the end of February to the end of March. It is not easy to lose 100% of your business in two weeks no matter where you are in the world.

If you think it is tough in the United States what do you think it is going to be like in the other 150 countries in the world impacted by this?

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Asset Class Returns

Here is a chart of various asset class returns in March, since the market high on 2/19 and YTD. If you were an investor, there were plenty of way to lose money. These charts are all from Bespoke Investment Group.

US-related Equities

Global Equities

Bonds

Commodities

Changing Google Search Trends

Who ever thought that we would be searching "toilet paper delivery"?

Which States Are Showing The Worst ( and Best) Test Results

Michigan looks like the next big hot spot. Are there any flights still going to Hawaii?

A Sight On The Landscape We Would Like To See More Of

This is the drive-thru test site closest to my home. Not a car in line or in sight at 10am this morning. Workers standing ready but no business. This is one thing we want to see out of business SOON.

Trying To Find It In The Numbers

The public health scientists advising President Trump finally decided to unveil their models to the American people yesterday in a sober data-driven presentation.

If their objective was to shock the public with the numbers, their mission was clearly achieved.

The model is projecting 100,000-240,000 deaths over the next two months and that assumes that all of the current social distancing, school and business closures are continued for those two months.

The peak in deaths is currently projected to occur two weeks from now on April 15.

This is a graphic view of the model showing projected deaths as shown at the briefing.

Source: White House Coronavirus Task Force

We are to expect a very steep increase over the next two weeks following by a slow, descending decrease in deaths that would generally end around July 1.

Even at the low end, 100,000 deaths is a very big number. For that to occur in a two-month period is beyond sobering.

President Trump has compared this to fighting a war. If you compare this to combat deaths in U.S. wars this number would only be exceeded by deaths in World War II and the Civil War. Total deaths in World War I were higher (116,708) but many of the non-combat deaths were due to, ironically, the Spanish flu epidemic. Of course, those wars were each fought over about 4 years. We are talking about this number of death over the course of two months.

Combat Deaths in Various U.S. Wars
Credit: Wikipedia

Framed this way it is not difficult to see why President Trump has taken the actions he has.

However, it is important to remember that all of these projections are from a model. A model that uses inputs that are based on a set of assumptions.

The New York Times has its own interactive model in which anyone can input different variable assumptions and it will give a projection of expected cases, hospitalizations and deaths.

The variables include the intervention level, length of intervention, the date the intervention started, the impact of warm weather, how infectious the virus is, the hospitalization rate and the assumed death rate.

The first image is what the model looked like assuming that absolutely no interventions were initiated, an assumed moderate impact for warm weather, hospital rate of 11%, infection rate of 2.5% and death rate of 1%.

The infection rate assumption assumes that Covid-19 (2.5R0) is 67% more contagious than the seasonal flu (1.5R0) and results in 10x more hospitalizations and deaths. At this point that is considered the best guess on these variables by scientists but the fact is that none of these factors are known for sure. More research and study is needed.

This is how the New York Times model looked at the end of the initial 15-day social distancing measures that President Trump put in place assuming everything else was the same. The model suggests some benefit but it would not drastically alter the final outcomes.

This is what the model looks like with an additional 30 days of social distancing as we are doing now. You can see it has a significant effect.

However, I was interested in playing with a range of  variables to see what would have the largest impact. I only found one that had a gigantic effect.

What if the infection rate of Covid-19 is not 67% more infectious than the flu but only 33% more infectious?

If that is the assumption I made after considering the first 15 days of social distancing, and leave everything else the same, what does the graph look like? (Compare below graph to 2nd graph from the top).

You hardly can see any effect from virus. That shows you how sensitive these models are to the assumptions.

That is massive. That entire reduction comes from assuming a 2.5 R0 infection rate compared to 2.0 R0. Again, seasonal flu has a 1.5 R0.

Let's get some additional perspective on the issue of deaths by comparing the projected numbers we are hearing compared to what we might see in more "normal" times.

The CDC collects detailed records on influenza and pneumonia deaths each year during flu season. That data is also compared to total deaths to provide better perspective on how bad the flu season has been in creating excess mortality.

Here is the graph of national pneumonia and influenza (P&I) deaths over the last five years thru March 14, 2020. This is the most current data as it usually is reported with a two week lag.

Source: CDC

Notice that P&I deaths normally make up about 7-8% of deaths nationally in the winter months. In 2017-18 those deaths spiked to close to 11%. CDC data on total deaths in 2017-18 shows that there were around 250,000 deaths in each of the winter months. That means P&I deaths were around 100,000 during that winter and it has not been unusual to see 60,000 deaths in a normal year.

This is the graph for New York state for the period thru March 14. It indicates that seasonal flu deaths in New York were actually running below normal in the state until two weeks ago.

Source: CDC

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New York had 180 P&I deaths in the week ended March 14.

It had 44 reported deaths for Covid-19 for the week ended March 21.

It had 684 deaths for the week ended March 28.

In four days this week New York has had 1,213 deaths already.

Assuming that on average there are about 3,000 deaths per week in New York for all causes, there is little question we are seeing a lot of excess mortality from Covid-19 than from seasonal flu.

However, what about other states?

Here is the 5-year chart for Ohio thru March 14. You have to disregard the last couple of data points in this graph because the information is not complete. However, you should notice that Ohio typically peaks at about 7% deaths compared to New York's 10% in the winter months. Population density has to be a big reason for that among other factors

Source; CDC

Ohio typically averages about 2,500 overall deaths per week.

Ohio had an estimated 115 deaths from P&I in the week ended March 14.

It had 3 reported deaths from Covid-19 for the week ended March 21.

It had 25 deaths for the week ended March 28.

That would only be 1% of all deaths in the state. This probably would not even be noticed but for the intense scrutiny around Covid-19

As you can  from all of this, the numbers surrounding this entire issue are incredibly difficult to assess and evaluate.

Is this aggressive action taken in response to Covid-19 in the New York City metro area appropriate?

The models and the reality both say YES. There is little question that they are in the middle of a full blown health crisis.

Can the same be said for other parts of the country that don't have the same population density and have the same exposure to international travelers?

Dr. Birx says that the models they are relying on assume the same trajectory for the virus for the rest of the country as we are seeing in the New York numbers.

Using NYC experience and extrapolating it to the rest of the country seems like flawed logic to me. The fact that many other states were more proactive on mitigation efforts also should be a positive.

As I have written before, New York was at least two weeks late in its preparations. We are seeing the cost of that delay now.

I also often say that context is everything when assessing everything.

The problem with Covid-19 is that there are both too many assumptions and too much context to make sense of most everything to do with the numbers that are in play.

There may come a day when it might be possible to make sense of the numbers. That analysis will also undoubtedly have to factor in the economic impact of the decisions that have been made.

For now, I don't think there is one person on earth that can state with true conviction whether we have made the right decisions or not.

You just can't find it in the numbers.