Coronavirus: Out of Many, One

What the US Federal Government and the States Should Do to Fight the Coronavirus

Tomas Pueyo
29 min readApr 1, 2020

My two previous articles, Coronavirus: Why You Must Act Now and The Hammer and the Dance, have gathered over 60 million views together and have been translated into over 30 languages each. This article focuses on the situation in the US as of March 31st 2020.

Following articles:

  1. Coronavirus: Learning How to Dance: How the best countries are fighting the epidemic
  2. Coronavirus: The Basic Dance Steps Everybody Can Follow

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Summary: It makes political and economic sense for the US to suppress the coronavirus. For that, states and the federal government each have their own roles that they need to adjust.

The US is now the country with most coronavirus cases in the world. It is likely to keep that title in the history books. Two key reasons are government decentralization and concerns about the economic impact of aggressive social distancing measures.

Here’s what we’re going to cover today, with a lot of data, charts and sources:

  1. What’s the situation in the US and its states
  2. Why the coronavirus should be a bipartisan issue
  3. The economics of controlling the virus
  4. Which decisions should be left to the federal government or to states

Here’s what you’ll take away:

The coronavirus is growing everywhere in the US.
Some states are on their way to controlling it.
Others have massive outbreaks that make China’s outbreak pale in comparison.
Many are unprepared, and will suffer some of the worst outbreaks.
All voters care about this, Democrats and Republicans.
Democrats were hit first.
But Republicans have more to lose.
They’re older and more likely to die.
Most hesitation comes from the perceived cost of suppressing the virus.
Fortunately, it’s cheaper to suppress it than to let it run loose.
We should do it.
But right now, states are left fending for themselves. It’s a mess.
They are competing against each other instead of collaborating.
They might be forced to seal their borders with each other.
There is a role for states and a role for the federal government. The federal government coordinates, the states execute.
If both step up, we will save lives and increase the GDP.

OK, let’s do this.

1. The Current Situation in US States

A few weeks ago, I shared this graph to alert people of what was to come in other countries.

This is an update four weeks later on all these countries that appeared so small above:

In the previous graph I showed countries with 50 cases or more. Now I’m showing countries with 1000 cases or more. There’s 181 countries with coronavirus cases, or over 90% of the total.

Note that now I’m adding China, which tells you how bad the situation is. The vertical axis has gone from a maximum of 6,000 to 200,000. A factor of 33x in four weeks. We quickly forget these orders of magnitude, but it’s worth remembering: three weeks ago, the US had fewer than 1,000 cases and there was still a debate of whether there would be an epidemic. This is what exponential growth looks like.

And you can see the trajectory.

It’s not good.

Let’s zoom in, looking at the state level.

New York used to dwarf everything else, but now New Jersey is joining it. Note that as of 3/31, only four countries have more cases than New York. And it’s still adding thousands of cases a day.

Remember how we zoomed in to the bottom right corner to see the emerging coronavirus countries? Let’s do that again, this time with states, taking New York and New Jersey out.

Oh, and just for context, this is the point at which Hubei shut down.

I use absolute numbers (total cases) instead of relative numbers (cases per capita) because here we’re trying to assess whether there’s an outbreak or not. Absolute numbers show if there’s a cluster and how big it is. Per capita doesn’t show this. Eg, if Liechtenstein had 5 cases, it would look like a national emergency in relative numbers, but it’s nothing. When assessing outbreaks, absolute numbers are more relevant. When assessing how bad the situation was a posteriori, relative numbers will be more relevant. The other reason is that relative numbers are much harder to process.

From now on, I’m going to use “Hubeis” as a measure, because everybody has a good sense of what happened there. A “Hubei” is a region that has more cases than Hubei when it was shut down. Hubei shut down with 444 confirmed cases, and ended up with close to 70,000 cases and 3,200 deaths. As a rule of thumb, a region that has more cases than Hubei but hasn’t taken the same measures as Hubei at least as early as them is very likely to end up with both more cases and more deaths than Hubei.

So now we have 33 states (34 including DC) with more cases than Hubei when it shut down (accounting for 92% of US GDP). I had to rebuild these charts 3 times in 5 days because they quickly became outdated. There were “only” 13 Hubeis in the US on Friday; now there are 33.

33 US States have more cases than Hubei when it shut down

Here’s a geographic visualization of all the counties where there are cases.

But that’s not real cases. It’s just official ones. How close are official cases from real cases? It depends on how much you test:

This chart shows the share of tests that are positive. In the case of Spain, with 50% of cases positive, it’s very likely that they are missing a lot of cases. As a result, it’s very likely that Spain has many more cases than the 100,000 it reports.

We can see that countries that are doing a good job at controlling the virus understand the situation because they identify most cases. Vietnam, Taiwan, Singapore, South Korea and Germany all have less than 4% positives. They are still probably undercounting, but probably not by much.

So what does this look like in the US?

If you’re looking for testing sites close to where you live in the US, here’s a good resource

There are a few states that have good enough testing to be close to the true number of cases: New Mexico, Hawaii, the Dakotas, and Minnesota have testing levels similar to South Korea’s. But all of them also have few cases. As soon as a state has an outbreak, it gets overwhelmed, can’t keep up with tests, and undercounts the true number of cases.

So how can states assess how many cases they truly have?

Assuming a fatality rate of 1% (one in 100 cases dies), you can back out one estimate of true cases:

This approximation would double the number of official cases, from ~200,000 officially today, to ~400,000. This is still likely to be an underestimate, because people take on average 3 weeks to die from the coronavirus.

This forgets time-to-death. If instead we use the back-of-the-envelope calculation from previous posts, where one death today means 100 cases three weeks ago (1% fatality rate, and it takes 3 weeks on average from contagion to death), and these double every week for three weeks, so they end up becoming 800 cases today, the situation becomes much more dire. Even if we assume cases doubled only two times in the last two weeks because of social distancing measures, this is what we see:

According to this, more than a million people are already infected in the US, and most states would have thousands of cases. Because I used two doublings instead of three, this is likely still an underestimate.

So let’s summarize so far: we are in a situation where the US has 33 states with more cases than Hubei, and probably many more, but it has no way to know for sure because it’s not testing enough.

2. The Bipartisan Case against the Coronavirus

You might have noted that, as a rule of thumb, the states that have more cases lean Democrat.

The Coronavirus Hit Urban Areas First

Big urban areas are usually more connected to the rest of the world via travel. That means they’ve imported more cases, faster.

They also have a higher urban density, which means a higher transmission rate of the virus. The more people are close by, the more you meet every day, and the faster the virus spreads.

Because the vote in urban areas tends to lean more Democrat, states controlled by Democratic governors today have been impacted by the virus earlier, so they have taken measures earlier. It’s not a coincidence that New York is Ground Zero for the coronavirus in the U.S., and that the San Francisco Bay Area was initially among the worst impacted. Maybe that’s why San Francisco ordered a shelter in place on 3/16, California on 3/19, and New York on 3/20 — well before other major cities and states.

The fact that democratic-leaning states have been hit earlier explains why Democrat voters have been worried about the coronavirus earlier. As more and more cases have appeared in different states, concerns about the virus have grown on both sides.

Source: Civiqs, via the New York Times

This chart was only updated two weeks ago. What does that polarization look like today?

Now, both parties are equally concerned. That’s important, because the virus is about to hit Republican states hard.

The Coronavirus Will Hit Republicans Too

This is the growth of Coronavirus cases in states that have a Republican governor today:

There are 16 Hubeis among Republican states (states with more cases than Hubei when it shut down). With the current growth rates, by next week there will be 22. As a reminder, Hubei ended up with over 70,000 cases and 3,000 deaths.

Not surprisingly, both Democrat-leaning and Republican-leaning voters strongly advocate for measures to curb the virus:

Link to article

It is notable that a majority of voters from both parties support every single one of the measures above. Voters want tough measures against the coronavirus.

So what measures are Republican-controlled states taking?

Coronavirus Measures in Republican-Controlled States

Details of measures per state can also be found at the Kaiser Family Foundation site. Updated as of 3/29/2020

In a thoughtful decision, all fifty states have at least issued a State Emergency Declaration, and many are much stricter. For example, Alaska, despite a very low population density, has mandated strong measures, such as a shelter-in-place, travel bans, and wide business closures. West Virginia established a shelter in place with just 40 cases.These measures make sense given the unique challenges of delivering healthcare across Alaska and the fact that West Virginia has been ranked 44th in overall health and 48th in clinical care.

But most are still very short of the measures they need to take. For example, Florida still has no ban for large gatherings, no business closures, and no stay-at-home orders beyond quarantines for travelers. Yet it leads all other Republican-controlled states in terms of cases. Even worse, Florida has just exported back across the United States countless spring breakers who hung out together in mass gatherings, especially on beaches the state refused to close.

Georgia, another leading state in terms of cases, has taken similar measures to Florida, except that bars and restaurants are still open with limited service, and high-risk groups are asked to stay home.

Meanwhile, Mississippi, with nearly 1,000 cases, requires a fever of 100.4 AND severe cough or chest pain to receive testing, and on March 24th, the governor reversed non-essential shutdowns applied by local jurisdictions.

Countries like South Korea or Singapore can get away with light social distancing measures because they have extensive testing, contact tracing, quarantines, isolations and travel bans: thanks to these measures, they can quickly identify cases and prevent them from infecting others.

That is not the case for many of these states. As we saw, most have poor testing. Contact tracing is worse: no state in the US has a good process as of today. That’s why most states need to apply The Hammer — a strategy of heavy social distancing for a few weeks — to control the virus and buy themselves time to set up these measures. But many states aren’t doing that either, especially when governed by Republican governors:

Chart updated as of 3/29/2020

Republican-controlled states have had a huge advantage: They have seen what has happened to their Democratic-controlled brethren, but because they are on average more rural, the coronavirus took time to reach them. But it will reach them. Some rural states, like Alaska or Idaho, have taken advantage of this delay. Others, like Oklahoma, Mississippi or Missouri, are not taking enough measures to contain the virus: It will continue spreading invisibly, infecting the people of these states.

Update: the states of Mississippi, Nevada, Georgia and Florida mandated statewide directives for citizens to stay home the same day as this article was published.

State lawmakers consider many things when deciding what measures to take, primarily health and the economy. Another factor that is surely in their mind, but isn’t discussed much, is political calculation.

The Coronavirus Kills Republican-Leaning Voters More

Most readers are acquainted with fatality rates per age group:

What I haven’t seen much is the overlap of this graph with partisanship:

The older you are, the more likely you are to both vote Republican and die from the coronavirus. Voters aged 80+ are 80 times more likely to die from the coronavirus than those under 40 (16% fatality rate vs. ~0.2%).

This effect is strong enough that people who voted for Trump in the 2016 election are around 30% more likely to die from the coronavirus than Democrats. In some swing states from the 2016 election, such as Pennsylvania, if the coronavirus were to run wild, this effect alone could have wiped out up to 30% of the gap between Republicans and Democrats in the 2016 election.

Infected Republicans are 30% more likely to die from the coronavirus than Democrats because of their age

This shows the loss of voters from coronavirus deaths. It doesn’t account for other effects, such as the votes of the family members of the deceased who might be angry at politicians for the avoidable death of their loved ones, or collateral damage of people who might die due to a collapsed healthcare system, or the family members of those people, or other secondary effects.

Many other factors will hurt rural voters more than urban ones. For example, the healthcare system has much less capacity in rural areas. The rural population tends to have worse health, so a higher likelihood of comorbidities that increase the fatality rate of coronavirus. On top of that, they don’t even get more spared by infections: the flu season tends to be delayed in rural areas compared to urban ones, but when it hits, it hits much harder.

This graph shows how flu epidemics impact 600 US cities based on their size. Bigger cities are more to the right and have bigger circles, so the small bubbles on the left show smaller cities. The vertical axis represents how concentrated the flu season is in particular weeks. We can see that big cities concentrate at the bottom right, which means their epidemics are spread over many weeks. Conversely, the smaller cities are, the more they tend to be at the top left, meaning their epidemics are concentrated in fewer weeks. This is believed to be caused partially by the fact that there is always some transmission, and hence ongoing herd immunity, in urban areas. This won’t be the case with the coronavirus, since there’s no herd immunity yet, but what this does illustrate is that smaller cities don’t get spared because they’re small. They do get hit, and when they do, the epidemic also hits hard.

To the extent Republican governors are hesitating to declare strict containment measures for political reasons, it will eventually become clear that they got the politics exactly backwards: instituting stricter measures early-on would have helped keep their most loyal voters alive.

3. Coronomics

The main hesitance of some American policymakers to take strong, early action against the coronavirus comes from economic tradeoffs between two very different approaches.

  1. Mitigation: Take some measures now but don’t be too aggressive. Just flatten the curve, go through the epidemic, build herd immunity, and go back to business as usual. This has the benefit of avoiding an economic shock early on because the economy doesn’t shut down for a few weeks or months. But during the epidemic, people will avoid going to work or consuming, for fear of getting infected. That ongoing panic can strain the economy for as long as people believe the epidemic is uncontrolled.
  2. Suppression (The Hammer and the Dance): Apply a “Hammer” early on and shut down the economy for a few weeks or months. That will bring infections to nearly zero while giving time to organize everything, from testing to contact tracing. Once testing data indicates it’s safe, move towards the “Dance,” a period during which social distancing measures are reduced, but some measures might still be needed nevertheless, depending on the situation.

Both approaches have ramifications and costs. For example, the heavy psychological toll of the fear of the virus or the loss of a job can depress consumers and their income, reducing their spending. The resulting demand shock could put companies out of business if they don’t have enough cash and banks don’t want to lend. If too many of these companies go out of business, the financial system itself could be imperiled. Consumers, particularly shocked by losses in their retirement accounts could significantly increase their savings rate — which means significantly reducing consumption for years.

So, on the balance, what’s the economic impact of each?

The Big Picture of Pandemics

Before we jump into the comparison, it’s useful to take a step back and put the entire pandemic thing into economic perspective: How bad is this going to be economically over the next few years? These are the potential scenarios:

There are 3 scenarios:

  • We can go back to normal. BCG and the Harvard Business Review call this “V-shape”.
  • We can go back to growing like we used to, but having lost enough GDP that we never gain that growth back, and take some years to go back to the same level of the economy. We can call this “U-shape”.
  • The slump is big and afterwards there’s some lingering issues in the economy and we don’t quite go back to the same level of GDP growth. We can call this “L-shape”.

These can impact the level of the GDP as well as its growth.

Which scenario each country will go through depends on how we react, but in the grand scheme of things, after a year of pain, it is likely that we will go back to normal. Let me explain.

A recent analysis showed that the 1918 pandemic reduced GDP per capita of the average country by 6%, and consumption by 8% for a year.

And yet, for most pandemics of the 20th century, the economy went back to normal afterwards.

Link to source

This is important because it puts the entire discussion into perspective: What we decide today will impact lives and the economy in the short term. There are also risks in the economy today that are different from the past. However, what history teaches us is that, usually, after a pandemic, the economy goes back to normal. The decisions we take will have a tremendous impact this year and next, but economically, in a few years it’s likely that the impact will be minimal.

So Which One Is Better, Mitigation or Suppression?

The complexity of mitigation and suppression economic outcomes is such that it’s very hard to model. If only there had been a real-life test where we could compare the different strategies…

It turns out, there is.

In the 1918 pandemic, different US cities had different approaches to the pandemic. Some took it easy, like Philadelphia, with measures that came too late and for a short period of time. Other cities, like St Louis, took measures quickly and for a longer period of time.

I’ve already talked about these cities in the past, but only about fatality rates. A crucial paper that came out on Thursday, March 26th, now also compares their measures with their economic outcomes.

Before showing their results, it’s important to ask ourselves: What should we expect to find?

It’s crucial to understand this graph. On the horizontal axis, we have mortality. On the vertical one, as a proxy for economic growth, we have the growth in employment. This graph illustrates the hypothesis, not actual data: Red dots are hypothetical cities that impose few social distancing measures, while green dots are cities that take stronger social distancing measures.

If indeed social distancing measures had been bad for the economy, what we should see is that cities with higher mortality rates (because they applied measures that were too little too late) had a bigger economic growth in the years after.

Is this what we actually found?

This is one of the more complex graphs in this entire article, so let’s explain it a bit. Red dots are cities that had weaker social distancing measures than the average city. Green dots are cities that had stronger social distancing measures than the average. The line shows the trend: more mortality meant less employment after the pandemic. The grey area shows the confidence interval: the true trend is likely to be within that area, meaning that it’s extremely likely that it was a downward trend. Because the virus hit the East Coast first, cities in the West had time to learn from cities in the East and take stronger, faster measures. That, however, generates a bias. There are more biases, such as that wealthier cities could manage the healthcare crisis better, but might be hit worse by the virus, or cities with more density could be hit more. So researchers controlled for factors such as density, wealth, population… Their controls were the 1910 agriculture employment share, 1910 manufacturing employment share, 1910 urban population share, 1910 income per capita, and log 1910 population.

Researchers found the opposite of the hypothesis. “Mitigation”, the strategy where the measures taken are weaker, was much worse for the economy than “suppression”, heavier social distancing measures.

As you can see, most green dots are at the top left (fewer deaths, more economic growth) and the red dots are at the bottom right (more deaths, less economic growth). Together, they form a trend: the more people died (because there were weaker social distancing measures), the weaker the economy was afterwards.

Not only that, but this was true for both how long measures were taken and how fast they were enacted. And it wasn’t just due to losing more workers: It remains true for other economic indicators, such as growth in manufacturing value and growth in national banking assets.

From the charts below, the quick takeaway is that more social distancing measures were better for the economy, no matter how you look at it.

Here are some quotes directly from the paper:

“Our findings suggest that pandemics can have substantial economic costs, and NPIs can have economic merits, beyond lowering mortality”

“Cities that intervened earlier and more aggressively experience a relative increase in real economic activity after the pandemic”

“More severely affected areas experience a relative decline in manufacturing employment, manufacturing output, bank assets, and consumer durables.”

“The declines in all outcomes are persistent, and more affected areas remain depressed relative to less exposed areas from 1919 through 1923.”

“Reacting 10 days earlier to the arrival of the pandemic in a given city increases manufacturing employment by around 5% in the post period. Likewise, implementing NPIs for an additional 50 days increases manufacturing employment by 6.5% after the pandemic.”

Obviously, there are differences between the 1918 flu pandemic and the 2020 coronavirus pandemic: This one affects older people, it has a lower fatality rate, the healthcare system is stronger, people can work from home more, we’re much more connected so the virus spreads more quickly everywhere… We don’t know what would be true for this pandemic. But… the only economic evidence we have of social distancing measures is that they helped, rather than hurt, the economy.

What other data points can we look at to assess how bad suppression could be for the economy? What about the markets?

How the Chinese Equity Market Valued the Hubei Lockdown

China is the only good example to understand how the markets value a massive outbreak, because it’s the only country that has had a huge one and that has (apparently) been able to control it.

When Hubei shut down, the markets panicked. But as soon as they were down, they started going back up again. By the beginning of March, they had gone back to nearly normal, their level before the lockdown, and a similar level as the year before. What that means is that investors believed a full shutdown of an area of 60 million people barely registered in the grand scheme of things.

Only when the coronavirus became a pandemic did investors start worrying again. But what matters here is how they valued the cost of the lockdown. The answer appears to be: Not much.

Incidentally, the day President Trump announced the National Emergency, markets went up.

This is not much information, but we need to realize that we’re making decisions that might cost millions of lives with very little data. Any information we have needs to be part of our analysis. And so far, all the evidence we have suggests a suppression strategy would not be more expensive than mitigation, but rather the opposite.

Ok, let’s take a step back. Now we have some evidence that:

  • 21st century pandemics have tended to have a short-term effect on the economy
  • Quicker and longer social distancing measures probably benefit the economy
  • A lockdown that can control an outbreak was enough to increase the confidence of investors to bring the Chinese stock market back to the levels before the lockdown.

Based on the little we know today, it looks like Suppression is economically better than Mitigation once you have an outbreak.

The Price of a Life

One of the core challenges lawmakers have when comparing Suppression and Mitigation is that tradeoffs between life and money are hard. The major benefit of Suppression, the lives saved, can’t be translated into money.

But it can.

The cost in deaths to the US would range between $750 billion and $15 trillion.

We do that all the time. In insurance, pharmacology or healthcare, for example, society has to decide how much a life is worth.

This is a painful reality in healthcare: We don’t have infinite resources. We can’t, unfortunately, treat everybody for everything. Otherwise, we would go bankrupt. As a society, we are forced to make decisions: How should we spend the limited resources we have? What measures are worth paying for, and which ones are too expensive?

The way we calculate this is by asking ourselves: How much are we willing to pay to extend our life? In healthcare in the US, that number turns out to be between $50,000 and $150,000 per year.

If we assume the average age of death for coronavirus is 78, these people have on average 10 more years to live, which means the average coronavirus patient would pay up to $1.5 million to avoid death (10 years * $150,000 per year).

We don’t live to make money. We make money to live.

In my previous post, I explained how direct deaths from a mitigation strategy in the US could range between 500,000 and over 10 million. As a quick back-of-the-envelope reminder, it’s the result of assuming the share of the US population that gets infected ranges between 40% and 75%, and the fatality rate ranges between 1% (currently 1.5% in South Korea, the country with some of the best testing and healthcare system) and 4% (Hubei region. Note the current fatality rate in Italy is ~10%, but they are probably undercounting cases). That does not account for collateral damage (other people who die because they don’t have access to urgent healthcare), which could greatly increase the death rate.

If we account for how much we value life, the cost of the coronavirus in deaths for the US would be between $750 billion and $15 trillion. For context, that’s between 4% and 75% of GDP. The cost in lives would be staggering.

Let’s summarize all this information

Notes: some people have asked me how it is possible that the value of some people’s lives is comparable to the size of GDP. GDP is broadly the value created in a year, not the total wealth we have. The total wealth we have in the US is approximately $1 million per person on average, which means the US’s wealth is ~$320 trillion. That does not account for the wealth in terms of life, but puts the cost of $15 trillion in lives into perspective. Also I haven’t talked about the costs to the economy of the Dance phase of the Suppression strategy, once heavy social distancing measures subside. That’s because, if done well, countries can “dance” with only a small subset of measures that don’t cost much: testing, contact tracing, quarantines, isolation, hygiene education, and travel bans. Note finally that a suppression strategy would cost all of society but would benefit older people more, as they are the ones most likely to be saved by these measures. As such, they are a transfer of wealth from all of society towards our seniors, who in the US tend to vote Republican.

Some societies are adopting a “survival of the fittest” approach, exposing their populations to the virus and letting the weak die. But it looks like that approach might weaken these societies more, making them, in turn, not be the fittest they could be in the face of this epidemic.

All these numbers, with the surprising conclusion that a Suppression strategy would likely be less costly than a Mitigation strategy. But these numbers obscure a larger truth:

We don’t live to make money. We make money to live.

And the best way to illustrate that is through war.

4. Out of Many, One

This is War

President Trump put it very clearly on March 18th: This is war.

He compared the sacrifices we will need to make to those of World War II. This is exactly how we should be looking at the problem.

Imagine we had foreign agents. They have infiltrated the US. They are invisible. They are spreading across the country: slowly, silently. And then, they strike: rapidly, randomly. People start falling left and right. Over a matter of days, the death toll of 9/11 is passed, and then dwarfed. At some point, it becomes clear that the death toll will be worse than Iraq. Worse than Vietnam. Worse than World War II. Worse than all of America’s wars combined.

If this was happening, the US would stop everything it’s doing and single-mindedly focus all of its attention and money to beat this enemy.

That’s why the US has the mightiest military in the world. That’s why it spent $2.4 trillion on the wars against Iraq and Afghanistan. That’s why, during World War II, two-thirds of the American economy had been integrated into the war effort: to beat the enemies that threaten America.

This is what should be happening now. The fact that our enemies are invisible viruses and not invisible agents doesn’t change much. If anything, it only makes it easier, because we’re smarter than them and we can beat them.

But only one entity can declare war and harness the resources we would need: the federal government.

Survival of the Fittest

China had a centralized response to the coronavirus. South Korea had a centralized response. Taiwan. Italy. Spain. France. UK. Poland. India. All centralized responses. Meanwhile, so far in the US, we have let states take the lead.

There are many situations where that approach is reasonable. But waging war against an exponentially growing threat that all countries face at the same time is not one of those situations.

We have a $2 trillion package to fight the coronavirus. It’s a war-like budget, but without war-like measures. The government has invoked the Defense Production Act, for example, but hasn’t actually used it yet. As a result, states and companies are struggling to face the challenge, but in some places, they’re drowning.

Trade War over Supplies

One of the best examples is the purchase of personal protective equipment (PPE), such as masks, goggles, gowns or gloves.

Traditional medical distributors such as Cardinal Health or McKesson are doing what they can to get PPEs from the manufacturing center of the world, China. Except that China has been closed for business for nearly a month. Just as the supply plummeted, demand exploded around the world, with orders of magnitude more requests from all countries in the world for more of everything. Even if China wanted, it couldn’t supply everything. That’s assuming that China wants to. In the middle of a trade war with the US, and with a grey market that is much more profitable than the official one, the traditional channels don’t work. Suppliers are selling to the highest bidder.

When there’s will, we can overcome these challenges, such as the recent airlifting of medical supplies spearheaded by the White House. But this is piecemeal right now, not a systematic approach.

Homegrown Mess for Protective Equipment

The country is mobilized. Everybody wants to help, from tech to education. In healthcare, hundreds of initiatives have sprung up to produce the PPEs our healthcare workers need. Manufacturing plants across the country are trying to change their production towards masks, face screens or any other PPE. But they don’t have the money, designs or logistics to start, and they don’t know where to sell. Dozens of organizations have sprung up to help, such as the PPE Coalition. But we need one master effort to immediately coordinate all manufacturers, financiers, designers, lawyers, logistics experts, and customers in one place.

If we had months, the private sector could figure it out. But we have days. When you need speed, you need a single actor coordinating everything, and the obvious one is the federal government.

But the response so far has been for states to figure it out by themselves. The federal government has told state governors to find ventilators by themselves. That is tragic.

Fratricide for Ventilators

First, states are not experts on this. They don’t have their own CDCs. They don’t deal with ventilator markets. They don’t know where the supply is. Every day counts, but instead of mandating what needs to happen, thousands of state employees are trying to become overnight experts in ventilator and PPE procurement.

But even if they were experts, they couldn’t do it. Because now every state is fighting for itself. Every state needs ventilators, either because they need them today, or because they will need them tomorrow. This is a matter of life and death, so they’re bidding against each other. Ventilator and PPE providers are looking at this and selling to the highest bidder. Survival of the fittest.

States are bidding against each other for ventilators and protective equipment. Survival of the fittest.

A coordinated federal response would eliminate all these problems: it would harness the experience of the best experts, it would determine the prices and quantities to be manufactured, and it would distribute assets based on needs, not on whoever is fast and rich enough to buy them first.

Unaffordable Testing Kits

Arguably, the single most important measure against the coronavirus is to test as many people as possible to identify all the infected, isolate them, trace their contacts, and quarantine them. This is the bread and butter of how all East Asia countries have controlled the virus. It’s how we’ll know how when, in a Suppression strategy, it’s time to switch from the Hammer (total lockdown) to the Dance (relaxed social distancing measures).

But in the US, not only do we have a very hard time testing. It’s unaffordable. If testing for the virus was as simple as getting a test covered by your insurance, that would be easy. But that’s not how it works.

People who are symptomatic and seek care may be billed for a visit with a doctor, an influenza test, a chest x-ray, and bacterial, viral, or blood culture tests. These costs can add up very quickly, particularly for people with no insurance or who have high-deductible health plans.Castlight Report

With all these, a simple coronavirus test can end up costing people over $4,000. That does not include the treatment. There is no way you can test everybody with that price tag.

Contact Tracing and Quarantine Enforcement

China had 1,800 teams of five people each figuring out every single person that a coronavirus patient might have infected while out and about. These techniques were extremely advanced, looking at mobile phone location or credit card data, cross-referencing with mass transport tickets, and using other tools to identify every single potential contagion.

Meanwhile, in the US, we’re leaving all of that to the states.

Quarantine enforcement is equally technologically-advanced and time-consuming. Some countries use apps, while others track the movement of your phone to know if you’re still at home and call you if they suspect you left your phone home.

None of this exists in the US. As we know, the NSA already has a lot of this data. The government is already using it, they’re just not using it for this yet, and 50 states can’t be expected to all figure it out on their own.

The government doesn’t need to do all of this, but it needs to coordinate it. We will go much faster if we develop a single app for all states and we tell everybody to use that same app. We will also need software for contact tracing workers to do their job. States can employ these workers, but with the time we have available, the fastest way to get this done is through a the federal government, even if it’s through a public-private partnership between with tech companies.

All of that can be done while maintaining privacy, like in Singapore. And if people don’t want to use the app, they can opt out like in Poland and just expect random visits from state enforcement workers.

The Weakest Link

All of this puts US states in a very tough situation. The richest ones might be able to organize all of this and develop the technology required. But many will not. These states will suffer outbreaks they can’t see or control. That will create difficult dynamics between them.

Imagine Alaska applies a costly Hammer and locks down the state for weeks. It manages to control the epidemic, and sets up great testing and contact tracing processes. Meanwhile, maybe Texas doesn’t want to do the same, and there’s an uncontrolled epidemic.

What will Alaska do? Will it let Texans come, at risk of seeding new outbreaks? No, it will want to ban them from traveling to Alaska. Clever Texans will just travel to another state and go from there to Alaska. So Alaska will be forced to seal its borders. And every state that takes the coronavirus seriously will have to seal its borders too. This is already happening.

If you think that’s impossible, legal experts disagree: states can close their borders to other states.

When the federal government treats every state like an independent country, the states require the same tools as those of independent countries. Even though Spain is part of the European Union, as an independent country, it sealed its borders.

Individual states are only as strong as the weakest link. Either the US mandates measures at the federal level, or states will be forced to behave like countries and eventually seal their borders.

What Should the States and the Federal Government Do?

The takeaway is that both states and the federal government have their own roles to fulfill. So far, states are taking the lead, and many are doing what’s needed. But some haven’t. And even the best ones still need coordination in some areas.

Based on all of this, here are some key measures the federal government should contemplate:

  • Healthcare Supplies: Centralize the purchase of critical supplies (ventilators, PPEs, test kits…) and allocate them to states, allowing them to distribute within the state. Provide supplier guarantees so that they don’t underproduce in fear of ending up with too much unsold inventory.
  • Homegrown Production: Support the homegrown production of critical supplies, including financing and supplier guarantees. Determine a clearinghouse so that supply, demand, and philanthropic help know where to meet. Either build one through a public-private partnership, or anoint one of the existing platforms to speed up market making (eg, Google for ventilators, PPE Coalition for PPEs).
  • Centralize Contact Tracing: Build with a public/private partnership the technology needed to trace contacts easily. Create a law that requires companies to hand over the data needed to make it work and allows its use by federal and state employees. Provides the tools for states to actually carry out the contact tracing. Create the tools in a way that privacy is optimized, and add an automatic expiration date to the law.
  • Either mandate country-wide social distancing measures, or provide very specific guidelines for states and clarify their ability to seal borders with each other. The application of social distancing measures should adapt to the reality on the ground: What works in infected cities with lots of work-from-home ability might not fit rural areas with low density, no coronavirus cases, and predominant farming activity. If a federal mandate is unworkable, use access to other resources and funding for compliance.
  • Speed up decision-making or get out of the way when states need agility. For example, testing kits could arguably be better off without the heavy oversight of the FDA, given all the international best practices and the speed of local laboratories. Use the FDA recommendations as guidance and best practices, rather than as a gate.
  • Lead an initiative to guarantee free coronavirus testing to citizens, all costs included.
  • Actively update travel bans: Right now, they are mostly from China, Iran and Europe, but that doesn’t reflect the reality on the ground anymore. There are as of today 23 countries outside of these places with more than 1,000 cases, and many more quickly growing.
  • Support states with advice and money to educate the population on the importance and best practices of social distancing and hygiene.

Conclusion: Join, or Die

The United States is the strongest country in the world. It has the most vibrant economy, the mightiest military. It has inspired democracies through history, and shines the values of freedom around the world.

All of this originated two and a half centuries ago, when a group of ragtag colonies, subservient to a remote king, decided to band together to overturn a tyranny.

That triumph emerged from the union of the original thirteen states. Independent, they couldn’t beat the mighty United Kingdom. Together, they did.

This is why the US is called the United States. It was the union that brought the force. It’s why the seal of the United States of America declares: E Pluribus Unum.

Out of many, one.

We are facing the biggest battle of our generation, and it all comes down to today. We have two options on our hands: Either we unite as a country, or we will crumble as individual states.

The margin of error is so small. A few days off, and thousands more die. Our healthcare workers are already dying on the lines. They’re willing to give their lives for all of us. Because that’s what living is about. We, too, need to fight for every life of our compatriots. Because we know, when we add up these lives, this will make the difference between winning and losing. Between living, or letting our loved ones die.

I want to be on the winning team. Do you?

If you believe this article, or any other similar article, can help your lawmakers make the right decisions, please share it. Millions have done it with the previous articles, and they might have saved countless lives.

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This has been a massive team effort with the help of dozens of people who have provided research, sources, arguments, feedback on wording, challenged my arguments and assumptions, and disagreed with me. Special thanks to Carl Juneau, John Hsu, Genevieve Gee, Matt Bell, Elena Baillie, Xianhang Zhang, Jorge Peñalva, Pierre Djian, Mike Kidd, Yasemin Denari, Eric Ries, Castlight, Berin Szoka, Andy Skrzypacz, Shishir Mehrotra, Dan Hess, Mudit Garg, David Walker, Max Henderson, Jonathan Kreiss-Tomkins, Misha David Chellam, Michael Ovadia, Peter Schwartz, Mick Costigan, Alex Whitehead, Mike LeVasseur, and many more. This would have been impossible without all of you.

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Tomas Pueyo
Tomas Pueyo

Written by Tomas Pueyo

2 MSc in Engineering. Stanford MBA. Ex-Consultant. Creator of applications with >20M users. Currently leading a billion-dollar business @ Course Hero

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