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Covid-19, your community, and you — a data science perspective

Written: 09 Mar 2020 by Jeremy Howard and Rachel Thomas

We are data scientists—that is, our job is to understand how to analyze and interpret data. When we analyze the data around covid-19, we are very concerned. The most vulnerable parts of society, the elderly and the poor, are most at risk, but controlling the spread and impact of the disease requires us all to change our behavior. Wash your hands thoroughly and regularly, avoid groups and crowds, cancel events, and don’t touch your face. In this post, we explain why we are concerned, and you should be too. For an excellent summary of the key information you need to know, read Corona in Brief by Ethan Alley (the president of a non-profit that develops technologies to reduce risks from pandemics).


Anyone is welcome to translate this article, to help their local communities understand these issues. Please link back to here with appropriate credit. Let us know on Twitter so we can add your translation to this list.


We need a working medical system

Just over 2 years ago one of us (Rachel) got a brain infection which kills around 1/4 of people who get it, and leaves 1/3 with permanent cognitive impairment. Many others end up with permanent vision and hearing damage. Rachel was delirious by the time she crawled across the hospital parking lot. She was lucky enough to receive prompt care, diagnosis, and treatment. Up until shortly before this event Rachel was in great health. Having prompt access to the emergency room almost certainly saved her life.

Now, let’s talk about covid-19, and what might happen to people in Rachel’s situation in the coming weeks and months. The number of people found to be infected with covid-19 doubles every 3 to 6 days. With a doubling rate of three days, that means the number of people found to be infected can increase 100 times in three weeks (it’s not actually quite this simple, but let’s not get distracted by technical details). One in 10 infected people requires hospitalization for many weeks, and most of these require oxygen. Although it is very early days for this virus, there are already regions where hospitals are entirely overrun, and people are no longer able to get the treatment that they require (not only for covid-19, but also for anything else, such as the life-saving care that Rachel needed). For instance, in Italy, where just a week ago officials were saying that everything was fine, now sixteen million people have been put on lock-down (update: 6 hours after posting this, Italy put the entire country on lock-down), and tents like this are being set up to help handle the influx of patients:

A medical tent used in Italy A medical tent used in Italy

Dr. Antonio Pesenti, head of the regional crisis response unit in a hard-hit area of Italy, said, “We’re now being forced to set up intensive care treatment in corridors, in operating theaters, in recovery rooms… One of the best health systems in the world, in Lombardy is a step away from collapse.”

This is not like the flu

The flu has a death rate of around 0.1% of infections. Marc Lipsitch, the director of the Center for Communicable Disease Dynamics at Harvard, estimates that for covid-19 it is 1-2%. The latest epedemiological modeling found a 1.6% rate in China in February, sixteen times higher than the flu1 (this might be quite a conservative number however, because rates go up a lot when the medical system can’t cope). Current best estimates expect that covid-19 will kill 10 times more people this year than the flu (and modeling by Elena Grewal, former director of data science at Airbnb, shows it could be 100 times more, in the worst case). This is before taking into consideration the huge impact on the medical system, such as that described above. It is understandable that some people are trying to convince themselves that this is nothing new, an illness much like the flu, because it is very uncomfortable to accept the reality that this is not familiar at all.

Trying to understand intuitively an exponentially increasing growth in the number of infected people is not something that our brains are designed to handle. So we have to analyze this as scientists, not using our intuition.

Where will this be in 2 weeks? 2 months? Where will this be in 2 weeks? 2 months?

For each person that has the flu, on average, they infect 1.3 other people. That’s called the “R0” for flu. If R0 is less than 1.0, then an infection stops spreading and dies out. If it’s over 1.0, it spreads. R0 currently is 2-3 for covid-19 outside China. The difference may sound small, but after 20 “generations” of infected people passing on their infection, an R0 of 1.3 would result in 146 infections, but an R0 of 2.5 would result in 36 million infections! (This is, of course, very hand-wavy and ignores many real-world impacts, but it’s a reasonable illustration of the relative difference between covid-19 and flu, all other things being equal).

Note that R0 is not some fundamental property of a disease. It depends greatly on the response, and it can change over time2. Most notably, in China R0 for covid-19 has come down greatly, and is now approaching 1.0! How, you ask? By putting in place measures at a scale that would be hard to imagine in a country such as the US—for instance, entirely locking down many giant cities, and developing a testing process that allows more than a million people a week to be tested.

One thing which comes up a lot on social media (including from highly-followed accounts such as Elon Musk) is a misunderstanding of the difference between logistic and exponential growth. “Logistic” growth refers to the “s-shaped” growth pattern of epidemic spread in practice. Obviously exponential growth can’t go on forever, since otherwise there would be more people infected than people in the world! Therefore, eventually, infection rates must always decreasing, resulting in an s-shaped (known as sigmoid) growth rate over time. However, the decreasing growth only occurs for a reason–it’s not magic. The main reasons are:

  • Massive and effective community response, or
  • Such a large percentage of people are infected that there’s fewer uninfected people to spread to.

Therefore, it makes no logical sense to rely on the logistic growth pattern as a way to “control” a pandemic.

Another thing which makes it hard to intuitively understand the impact of covid-19 in your local community is that there is a very significant delay between infection and hospitalization — generally around 11 days. This may not seem like a long time, but when you compare it to the number of people infected during that time, it means that by the time you notice that the hospital beds are full, community infection is already at a level that there will be 5-10 times more people to deal with.

Note that there are some early signs that the impact in your local area may be at least somewhat dependent on climate. The paper Temperature and latitude analysis to predict potential spread and seasonality for COVID-19 points out that the disease has so far been spreading in mild climates (unfortunately for us, the temperature range in San Francisco, where we live, is right in that range; it also covers the main population centers of Europe, including London.)

“Don’t panic. Keep calm.” is not helpful

One common response we’ve seen on social media to people that are pointing out the reasons to be concerned, is “don’t panic” or “keep calm”. This is, to say the least, not helpful. No-one is suggesting that panic is an appropriate response. For some reason, however, “keep calm” is a very popular reaction in certain circles (but not amongst any epidemiologists, whose job it is to track these things). Perhaps “keep calm” helps some people feel better about their own inaction, or makes them feel somehow superior to people who they imagine are running around like a headless chicken.

But “keep calm” can easily lead to a failure to prepare and respond. In China, tens of millions were put on lock-down and two new hospitals were built by the time they reached the statistics that the US has now. Italy waited too long, and just today (Sunday March 😎 they reported 1492 new cases and 133 new deaths, despite locking down 16 million people. Based on the best information we’re able to ascertain at this stage, just 2-3 weeks ago Italy was in the same position that the US and UK are in today (in terms of infection statistics).

Note that nearly everything about covid-19 at this stage is up in the air. We don’t really know it’s infection speed or mortality, we don’t know how long it remains active on surfaces, we don’t know whether it survives and spreads in warm conditions. Everything we have is current best guesses based on the best information people are able to put together. And remember, the vast majority of this information is in China, in Chinese. Currently, the best way to understand the Chinese experience so far is to read the excellent Report of the WHO-China Joint Mission on Coronavirus Disease 2019, based on a joint mission of 25 national and international experts from China, Germany, Japan, Korea, Nigeria, Russia, Singapore, the United States of America and the World Health Organization (WHO).

When there’s some uncertainty, that perhaps this won’t be a global pandemic, and perhaps everything just might pass by without the hospital system collapsing, that doesn’t mean that the right response is to do nothing. That would be enormously speculative and not an optimal response under any threat modeling scenario. It also seems extremely unlikely that countries like Italy and China would effectively shut down large parts of their economy for no good reason. It’s also not consistent with the actual impacts we’re seeing on the ground in infected areas, where the medical system is unable to cope (for instance, Italy is using 462 tents for “pre-triage”, and still has to move ICU patients from infected areas).

Instead, the thoughtful, reasonable response is to follow the steps that are recommended by experts to avoid spreading infections:

  • Avoid large groups and crowds
  • Cancel events
  • Work from home, if at all possible
  • Wash hands when coming and going from home, and frequently when out
  • Avoid touching your face, especially when outside your home (not easy!)
  • Disinfect surfaces and packages (it’s possible the virus may remain active for 9 days on surfaces, although this still isn’t known for sure either way).

It’s not just about you

If you are under 50, and do not have risk factors such as a compromised immune system, cardiovascular disease, a history of previous smoking, or other chronic illnesses, then you can have some comfort that covid-19 is unlikely to kill you. But how you respond still matters very much. You still have just as much chance of getting infected, and if you do, just as much chance of infecting others. On average, each infected person is infecting over two more people, and they become infectious before they show symptoms. If you have parents that you care about, or grandparents, and plan to spend time with them, and later discover that you are responsible for infecting them with covid-19, that would be a heavy burden to live with.

Even if you are not in contact with people over 50, it is likely that you have more coworkers and acquaintances with chronic illnesses than you realize. Research shows that few people disclose their health conditions in the workplace if they can avoid it, for fear of discrimination. Both of us are in high risk categories, but many people who we interact with regularly may not have known this.

And of course, it is not just about the people immediately around you. This is a highly significant ethical issue. Each person who does their best to contribute to controlling the spread of the virus is helping their whole community to slow down the rate of infection. As Zeynep Tufekci wrote in Scientific Amercian: “Preparing for the almost inevitable global spread of this virus… is one of the most pro-social, altruistic things you can do”. She continues:

We should prepare, not because we may feel personally at risk, but so that we can help lessen the risk for everyone. We should prepare not because we are facing a doomsday scenario out of our control, but because we can alter every aspect of this risk we face as a society. That’s right, you should prepare because your neighbors need you to prepare—especially your elderly neighbors, your neighbors who work at hospitals, your neighbors with chronic illnesses, and your neighbors who may not have the means or the time to prepare because of lack of resources or time.

This has impacted us personally. The biggest and most important course we’ve ever created at, which represents the culmination of years of work for us, was scheduled to start at the University of San Francisco in a week. Last Wednesday (March 4), we made the decision to move the whole thing online. We were one of the first large courses to move online. Why did we do it? Because we realized early last week that if we ran this course, we were implicitly encouraging hundreds of people to get together in an enclosed space, multiple times over a multi-week period. Bringing groups together in enclosed spaces is the single worst thing that can be done. We felt ethically obliged to ensure that, at least in this case, this didn’t happen. It was a heart-breaking decision. Our time spent working directly with our students has been one of the great pleasures and most productive periods every year. And we had students planning to fly in from all over the world, who we really didn’t want to let down3.

But we knew it was the right thing to do, because otherwise we’d be likely to be increasing the spread of the disease in our community4.

We need to flatten the curve

This is extremely important, because if we can slow down the rate of infection in a community, then we give hospitals in that community time to deal with both the infected patients, and with the regular patient load that they need to handle. This is described as “flattening the curve”, and is clearly shown in this illustrative chart:

Staying under that dotted line means everything Staying under that dotted line means everything

Farzad Mostashari, the former National Coordinator for Health IT, explained: “New cases are being identified every day that do not have a travel history or connection to a known case, and we know that these are just the tip of the iceberg because of the delays in testing. That means that in the next two weeks the number of diagnosed cases will explode… Trying to do containment when there is exponential community spread is like focusing on putting out sparks when the house is on fire. When that happens, we need to switch strategies to mitigation–taking protective measures to slow spread & reduce peak impact on healthcare.” If we can keep the spread of disease low enough that our hospitals can handle the load, then people can access treatment. But if the cases come too quickly, then those that need hospitalization won’t get it.

Here’s what the math might look like, according to Liz Specht:

The US has about 2.8 hospital beds per 1000 people. With a population of 330M, this is ~1M beds. At any given time, 65% of those beds are already occupied. That leaves about 330k beds available nationwide (perhaps a bit fewer this time of year with regular flu season, etc). Let’s trust Italy’s numbers and assume that about 10% of cases are serious enough to require hospitalization. (Keep in mind that for many patients, hospitalization lasts for weeks — in other words, turnover will be very slow as beds fill with COVID19 patients). By this estimate, by about May 8th, all open hospital beds in the US will be filled. (This says nothing, of course, about whether these beds are suitable for isolation of patients with a highly infectious virus.) If we’re wrong by a factor of two regarding the fraction of severe cases, that only changes the timeline of bed saturation by 6 days in either direction. If 20% of cases require hospitalization, we run out of beds by ~May 2nd If only 5% of cases require it, we can make it until ~May 14th. 2.5% gets us to May 20th. This, of course, assumes that there is no uptick in demand for beds from other (non-COVID19) causes, which seems like a dubious assumption. As healthcare system becomes increasingly burdened, Rx shortages, etc, people w/ chronic conditions that are normally well-managed may find themselves slipping into severe states of medical distress requiring intensive care & hospitalization.

A community’s reaction makes all the difference

As we’ve discussed, this math isn’t a certainty—China has already shown that it’s possible to reduce the spread by taking extreme steps. Another great example of a successful response is Vietnam, where, amongst other things, a nationwide advertising campaign (including a catchy song!) quickly mobilized community response and ensured that people adjusted their behavior appropriately.

This is not just a hypothetical situation — it was clearly displayed in the 1918 flu pandemic. In the United States two cities displayed very different reactions to the pandemic: Philadelphia went ahead with a giant parade of 200,000 people to help raise money for the war. But St Louis put in place carefully designed processes to minimize social contacts so as to decrease the spread of the virus, along with cancelling all large events. Here is what the number of deaths looked like in each city, as shown in the Proceedings of the National Academy of Sciences:

Impact of differing responses to the 1918 Flu pandemic Impact of differing responses to the 1918 Flu pandemic

The situation in Philadelphia became extremely dire, even getting to a point where there were not enough funeral caskets or morgues to handle the huge number of dead from the flu.

Richard Besser, who was acting director of the Centers for Disease Control and Prevention during the 2009 H1N1 pandemic, says that in the US “the risk of exposure and the ability to protect oneself and one’s family depends on income, access to health care, and immigration status, among other factors.” He points out that:

The elderly and disabled are at particular risk when their daily lives and support systems are disrupted. Those without easy access to health care, including rural and Native communities, might face daunting distances at times of need. People living in close quarters — whether in public housing, nursing homes, jails, shelters or even the homeless on the streets — might suffer in waves, as we have already seen in Washington state. And the vulnerabilities of the low-wage gig economy, with non-salaried workers and precarious work schedules, will be exposed for all to see during this crisis. Ask the 60 percent of the U.S. labor force that is paid hourly how easy it is to take time off in a moment of need.

The US Bureau of Labor Statistics shows that less than a third of those in the lowest income band have access to paid sick leave:

Most poor Americans do not have sick leave, so have to go to work. Most poor Americans do not have sick leave, so have to go to work.

We don’t have good information in the US

One of the big issues in the US is that very little testing is being done, and testing results aren’t being properly shared, which means we don’t know what’s actually happening. Scott Gottlieb, the previous FDA commissioner, explained that in Seattle there has been better testing, and we are seeing infection there: “The reason why we knew early about Seattle outbreak of covid-19 was because of sentinel surveillance work by independent scientists. Such surveillance never got totally underway in other cities. So other U.S. hot spots may not be fully detected yet.” According to The Atlantic, Vice President Mike Pence promised that “roughly 1.5 million tests” would be available this week, but less than 2,000 people have been tested throughout the US at this point. Drawing on work from The COVID Tracking Project, Robinson Meyer and Alexis Madrigal of The Atlantic, said:

The figures we gathered suggest that the American response to the covid-19 and the disease it causes, COVID-19, has been shockingly sluggish, especially compared with that of other developed countries. The CDC confirmed eight days ago that the virus was in community transmission in the United States—that it was infecting Americans who had neither traveled abroad nor were in contact with others who had. In South Korea, more than 66,650 people were tested within a week of its first case of community transmission, and it quickly became able to test 10,000 people a day.

Part of the problem is that this has become a political issue. In particular, President Donald Trump has made it clear that he wants to see “the numbers” (that as, the number of people infected in the US) kept low. This is an example of where optimizing metrics interferes with getting good results in practice. (For more on this issue, see the Ethics of Data Science paper The Problem with Metrics is a Fundamental Problem for AI). Google’s Head of AI Jeff Dean, tweeted his concern about the problems of politicized disinformation:

When I worked at WHO, I was part of the Global Programme on AIDS (now UNAIDS), created to help the world tackle the HIV/AIDS pandemic. The staff there were dedicated doctors and scientists intensely focused on helping address that crisis. In times of crisis, clear and accurate information is vital to helping everyone make proper and informed decisions about how to respond (country, state, and local governments, companies, NGOs, schools, families, and individuals). With the right information and policies in place for listening to the best medical and scientific experts, we will all come through challenges like the ones presented by HIV/AIDS or by COVID-19. With disinformation driven by political interests, there’s a real risk of making things way, way worse by not acting quickly and decisively in the face of a growing pandemic, and by actively encouraging behaviors that will actually spread the disease more quickly. This whole situation is incredibly painful to watch unfold.

It doesn’t look like there is the political will to turn things around, when it comes to transparency. Health and Human Services Secretary Alex Azar, according to Wired, “started talking about the tests health care workers use to determine if someone is infected with the new coronavirus. The lack of those kits has meant a dangerous lack of epidemiological information about the spread and severity of the disease in the US, exacerbated by opacity on the part of the government. Azar tried to say that more tests were on the way, pending quality control.” But, they continued:

Then Trump cut Azar off. “But I think, importantly, anybody, right now and yesterday, that needs a test gets a test. They’re there, they have the tests, and the tests are beautiful. Anybody that needs a test gets a test,” Trump said. This is untrue. Vice President Pence told reporters Thursday that the US didn’t have enough test kits to meet demand.

Other countries are reacting much more quickly and significantly than the US. Many countries in SE Asia are showing great results, including Taiwan, where R0 is down to 0.3 now, and Singapore, which is being proposed as The Model for COVID-19 Response. It’s not just in Asia though; in France, for instance, any gathering of >1000 people is forbidden, and schools are now closed in three districts.

In conclusion

Covid-19 is a significant societal issue, and we can, and should, all work to decrease the spread of the disease. This means:

  • Avoiding large groups and crowds
  • Canceling events
  • Working from home, if at all possible
  • Washing hands when coming and going from home, and frequently when out
  • Avoiding touching your face, especially when outside your home.

Note: due to the urgency of getting this out, we haven’t been as careful as we normally like to be about citing and crediting the work we’re relying on. Please let us know if we’ve missed anything.

Thanks to Sylvain Gugger and Alexis Gallagher for feedback and comments.


(Click ↩ on a footnote to go back to where you were.)

  1. Epidemiologists are people who study the spread of disease. It turns out that estimating things like mortality and R0 are actually pretty challenging, so there is a whole field that specializes in doing this well. Be wary of people who use simple ratios and statistics to tell you how covid-19 is behaving. Instead, look at modeling done by epidemiologists. 

  2. Well, not technically true. “R0” strictly speaking refers to the infection rate in the absence of response. But since that’s not really ever the thing that we care about, we’ll let ourselves be a bit sloppy on our definitions here. 

  3. Since that decision, we’ve worked hard to find a way to run a virtual course which we hope will be even better than the in-person version would have been. We’ve been able to open it up to anyone in the world, and will be running virtual study and project groups every day. 

  4. We’ve made many other smaller changes to our lifestyle too, including exercising at home instead of going to the gym, moving all our meetings to video-conference, and skipping night events that we’d been looking forward to. 


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I think the "Keep Calm" is far better than "Panic, fear for your lives"

Idaho has not had one case of active CV reported yet all the Costcos had a run on TP and water. Panic does not help those that need those supplies. When this hit there were people hauling out 10 cases at a time of TP. Costco put a limit of 2 the other day and people started bitching about it. My daughter works for them and was able to snag one for us. 

Like I said in another post, unless people start turning into goo or zombies I am not going to get wound up. Besides, I have a bunch of tread mills set up out side the house for the slow and fast zombies. 

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Posted (edited)

Click this link for charts....CL



Coronavirus: Why You Must Act Now

Politicians, Community Leaders and Business Leaders: What Should You Do and When?

Tomas Pueyo
Mar 10 · 26 min read

Updated on 3/13/2020. Now reflects an update on containment vs. mitigation strategies. 11 translations at the bottom. Send me more existing translation in private notes at the bottom. This article has received 17 million views in the last 48h.

With everything that’s happening about the Coronavirus, it might be very hard to make a decision of what to do today. Should you wait for more information? Do something today? What?

Here’s what I’m going to cover in this article, with lots of charts, data and models with plenty of sources:

  • How many cases of coronavirus will there be in your area?
  • What will happen when these cases materialize?
  • What should you do?
  • When?

When you’re done reading the article, this is what you’ll take away:


The coronavirus is coming to you.

It’s coming at an exponential speed: gradually, and then suddenly.

It’s a matter of days. Maybe a week or two.

When it does, your healthcare system will be overwhelmed.
Your fellow citizens will be treated in the hallways.

Exhausted healthcare workers will break down. Some will die.

They will have to decide which patient gets the oxygen and which one dies.

The only way to prevent this is social distancing today. Not tomorrow. Today.

That means keeping as many people home as possible, starting now.


As a politician, community leader or business leader, you have the power and the responsibility to prevent this.


You might have fears today: What if I overreact? Will people laugh at me? Will they be angry at me? Will I look stupid? Won’t it be better to wait for others to take steps first? Will I hurt the economy too much?


But in 2–4 weeks, when the entire world is in lockdown, when the few precious days of social distancing you will have enabled will have saved lives, people won’t criticize you anymore: They will thank you for making the right decision.


Ok, let’s do this.

1. How Many Cases of Coronavirus Will There Be in Your Area?

Country Growth


The total number of cases grew exponentially until China contained it. But then, it leaked outside, and now it’s a pandemic that nobody can stop.


As of today, this is mostly due to Italy, Iran and South Korea:


There are so many cases in South Korea, Italy and China that it’s hard to see the rest of the countries, but let’s zoom in on that corner at the bottom right.


There are dozens of countries with exponential growth rates. As of today, most of them are Western.


If you keep up with that type of growth rate for just a week, this is what you get:


If you want to understand what will happen, or how to prevent it, you need to look at the cases that have already gone through this: China, Eastern countries with SARS experience, and Italy.


Source: Tomas Pueyo analysis over chart from the Journal of the American Medical Association, based on raw case data from the Chinese Center for Disease Control and Prevention

This is one of the most important charts.

It shows in orange bars the daily official number of cases in the Hubei province: How many people were diagnosed that day.

The grey bars show the true daily coronavirus cases. The Chinese CDC found these by asking patients during the diagnostic when their symptoms started.

Crucially, these true cases weren’t known at the time. We can only figure them out looking backwards: The authorities don’t know that somebody just started having symptoms. They know when somebody goes to the doctor and gets diagnosed.

What this means is that the orange bars show you what authorities knew, and the grey ones what was really happening.

On January 21st, the number of new diagnosed cases (orange) is exploding: there are around 100 new cases. In reality, there were 1,500 new cases that day, growing exponentially. But the authorities didn’t know that. What they knew was that suddenly there were 100 new cases of this new illness.

Two days later, authorities shut down Wuhan. At that point, the number of diagnosed daily new cases was ~400. Note that number: they made a decision to close the city with just 400 new cases in a day. In reality, there were 2,500 new cases that day, but they didn’t know that.

The day after, another 15 cities in Hubei shut down.

Up until Jan 23rd, when Wuhan closes, you can look at the grey graph: it’s growing exponentially. True cases were exploding. As soon as Wuhan shuts down, cases slow down. On Jan 24th, when another 15 cities shut down, the number of true cases (again, grey) grinds to a halt. Two days later, the maximum number of true cases was reached, and it has gone down ever since.

Note that the orange (official) cases were still growing exponentially: For 12 more days, it looked like this thing was still exploding. But it wasn’t. It’s just that the cases were getting stronger symptoms and going to the doctor more, and the system to identify them was stronger.

This concept of official and true cases is important. Let’s keep it in mind for later.

The rest of regions in China were well coordinated by the central government, so they took immediate and drastic measures. This is the result:


Every flat line is a Chinese region with coronavirus cases. Each one had the potential to become exponential, but thanks to the measures happening just at the end of January, all of them stopped the virus before it could spread.

Meanwhile, South Korea, Italy and Iran had a full month to learn, but didn’t. They started the same exponential growth of Hubei and passed every other Chinese region before the end of February.

Eastern Countries

South Korea cases have exploded, but have you wondered why Japan, Taiwan, Singapore, Thailand or Hong Kong haven’t?

Taiwan didn’t even make it to this graph because it didn’t have the 50 cases threshold that I used.

All of them were hit by SARS in 2003, and all of them learned from it. They learned how viral and lethal it could be, so they knew to take it seriously. That’s why all of their graphs, despite starting to grow much earlier, still don’t look like exponentials.

So far, we have stories of coronavirus exploding, governments realizing the threat, and containing them. For the rest of the countries, however, it’s a completely different story.

Before I jump to them, a note about South Korea: The country is probably an outlier. The coronavirus was contained for the first 30 cases. Patient 31 was a super-spreader who passed it to thousands of other people. Because the virus spreads before people show symptoms, by the time the authorities realized the issue, the virus was out there. They’re now paying the consequences of that one instance. Their containment efforts show, however: Italy has already passed it in numbers of cases, and Iran will pass it tomorrow (3/10/2020).

Washington State

You’ve already seen the growth in Western countries, and how bad forecasts of just one week look like. Now imagine that containment doesn’t happen like in Wuhan or in other Eastern countries, and you get a colossal epidemic.

Let’s look at a few cases, such as Washington State, the San Francisco Bay Area, Paris and Madrid.


Washington State is the US’s Wuhan.The number of cases there is growing exponentially. It’s currently at 140.

But something interesting happened early on. The death rate was through the roof. At some point, the state had 3 cases and one death.

We know from other places that the death rate of the coronavirus is anything between 0.5% and 5% (more on that later). How could the death rate be 33%?

It turned out that the virus had been spreading undetected for weeks. It’s not like there were only 3 cases. It’s that authorities only knew about 3, and one of them was dead because the more serious the condition, the more likely somebody is to be tested.

This is a bit like the orange and grey bars in China: Here they only knew about the orange bars (official cases) and they looked good: just 3. But in reality, there were hundreds, maybe thousands of true cases.

This is an issue: You only know the official cases, not the true ones. But you need to know the true ones. How can you estimate the true ones? It turns out, there’s a couple of ways. And I have a model for both, so you can play with the numbers too (direct link to copy of the model).

First, through deaths. If you have deaths in your region, you can use that to guess the number of true current cases. We know approximately how long it takes for that person to go from catching the virus to dying on average (17.3 days). That means the person who died on 2/29 in Washington State probably got infected around 2/12.

Then, you know the mortality rate. For this scenario, I’m using 1% (we’ll discuss later the details). That means that, around 2/12, there were already around ~100 cases in the area (of which only one ended up in death 17.3 days later).

Now, use the average doubling time for the coronavirus (time it takes to double cases, on average). It’s 6.2. That means that, in the 17 days it took this person to die, the cases had to multiply by ~8 (=2^(17/6)). That means that, if you are not diagnosing all cases, one death today means 800 true cases today.

Washington state has today 22 deaths. With that quick calculation, you get ~16,000 true coronavirus cases today. As many as the official cases in Italy and Iran combined.

If we look into the detail, we realize that 19 of these deaths were from one cluster, which might not have spread the virus widely. So if we consider those 19 deaths as one, the total deaths in the state is four. Updating the model with that number, we still get ~3,000 cases today.

This approach from Trevor Bedford looks at the viruses themselves and their mutations to assess the current case count.

The conclusion is that there are likely ~1,100 cases in Washington state right now.

None of these approaches are perfect, but they all point to the same message: We don’t know the number of true cases, but it’s much higher than the official one. It’s not in the hundreds. It’s in the thousands, maybe more.

San Francisco Bay Area

Until 3/8, the Bay Area didn’t have any death. That made it hard to know how many true cases there were. Officially, there were 86 cases. But the US is vastly undertesting because it doesn’t have enough kits. The country decided to create their own test kit, which turned out not to work.

These were the number of tests carried out in different countries by March 3rd:

Sources for each number here

Turkey, with no cases of coronavirus, had 10 times the testing per inhabitant than the US. The situation is not much better today, with ~8,000 tests performed in the US, which means ~4,000 people have been tested.


Here, you can just use a share of official cases to true cases. How to decide which one? For the Bay Area, they were testing everybody who had traveled or was in contact with a traveler, which means that they knew most of the travel-related cases, but none of the community spread cases. By having a sense of community spread vs. travel spread, you can know how many true cases there are.

I looked at that ratio for South Korea, which has great data. By the time they had 86 cases, the % of them from community spread was 86% (86 and 86% are a coincidence).

With that number, you can calculate the number of true cases. If the Bay Area has 86 cases today, it is likely that the true number is ~600.

France and Paris

France claims 1,400 cases today and 30 deaths. Using the two methods above, you can have a range of cases: between 24,000 and 140,000.

The true number of coronavirus cases in France today is likely to be between 24,000 and 140,000.

Let me repeat that: the number of true cases in France is likely to be between one and two orders or magnitude higher than it is officially reported.

Don’t believe me? Let’s look at the Wuhan graph again.

Source: Tomas Pueyo analysis over chart and data from the Journal of the American Medical Association

If you stack up the orange bars until 1/22, you get 444 cases. Now add up all the grey bars. They add up to ~12,000 cases. So when Wuhan thought it had 444 cases, it had 27 times more. If France thinks it has 1,400 cases, it might well have tens of thousands

The same math applies to Paris. With ~30 cases inside the city, the true number of cases is likely to be in the hundreds, maybe thousands. With 300 cases in the Ile-de-France region, the total cases in the region might already exceed tens of thousands.

Spain and Madrid

Spain has very similar numbers as France (1,200 cases vs. 1,400, and both have 30 deaths). That means the same rules are valid: Spain has probably upwards of 20k true cases already.

In the Comunidad de Madrid region, with 600 official cases and 17 deaths, the true number of cases is likely between 10,000 and 60,000.

If you read these data and tell yourself: “Impossible, this can’t be true”, just think this: With this number of cases, Wuhan was already in lockdown.

With the number of cases we see today in countries like the US, Spain, France, Iran, Germany, Japan, Netherlands, Denmark, Sweden or Switzerland, Wuhan was already in lockdown.

And if you’re telling yourself: “Well, Hubei is just one region”, let me remind you that it has nearly 60 million people, bigger than Spain and about the size of France.

2. What Will Happen When These Coronavirus Cases Materialize?

So the coronavirus is already here. It’s hidden, and it’s growing exponentially.

What will happen in our countries when it hits? It’s easy to know, because we already have several places where it’s happening. The best examples are Hubei and Italy.

Fatality Rates

The World Health Organization (WHO) quotes 3.4% as the fatality rate (% people who contract the coronavirus and then die). This number is out of context so let me explain it.


It really depends on the country and the moment: between 0.6% in South Korea and 4.4% in Iran. So what is it? We can use a trick to figure it out.

The two ways you can calculate the fatality rate is Deaths/Total Cases and Death/Closed Cases. The first one is likely to be an underestimate, because lots of open cases can still end up in death. The second is an overestimate, because it’s likely that deaths are closed quicker than recoveries.

What I did was look at how both evolve over time. Both of these numbers will converge to the same result once all cases are closed, so if you project past trends to the future, you can make a guess on what the final fatality rate will be.

This is what you see in the data. China’s fatality rate is now between 3.6% and 6.1%. If you project that in the future, it looks like it converges towards ~3.8%-4%. This is double the current estimate, and 30 times worse than the flu.

It is made up of two completely different realities though: Hubei and the rest of China.


Hubei’s fatality rate will probably converge towards 4.8%. Meanwhile, for the rest of China, it will likely converge to ~0.9%:


I also charted the numbers for Iran, Italy and South Korea, the only countries with enough deaths to make this somewhat relevant.


Iran’s and Italy’s Deaths / Total Cases are both converging towards the 3%-4% range. My guess is their numbers will end up around that figure too.


South Korea is the most interesting example, because these 2 numbers are completely disconnected: deaths / total cases is only 0.6%, but deaths / closed cases is a whopping 48%. My take on it is that a few unique things are happening there. First, they’re testing everybody (with so many open cases, the death rate seems low), and leaving the cases open for longer (so they close cases quickly when the patient is dead). Second, they have a lot of hospital beds (see chart 17.b). There might also be other reasons we don’t know. What is relevant is that deaths/cases has hovered around 0.5% since the beginning, suggesting it will stay there, likely heavily influenced by the healthcare system and crisis management.

The last relevant example is the Diamond Princess cruise: with 706 cases, 6 deaths and 100 recoveries, the fatality rate will be between 1% and 6.5%.

Note that the age distribution in each country will also have an impact: Since mortality is much higher for older people, countries with an aging population like Japan will be harder hit on average than younger countries like Nigeria. There are also weather factors, especially humidity and temperature, but it’s still unclear how this will impact transmission and fatality rates.

This is what you can conclude:

  • Excluding these, countries that are prepared will see a fatality rate of ~0.5% (South Korea) to 0.9% (rest of China).
  • Countries that are overwhelmed will have a fatality rate between ~3%-5%

Put in another way: Countries that act fast can reduce the number of deaths by a factor of ten. And that’s just counting the fatality rate. Acting fast also drastically reduces the cases, making this even more of a no-brainer.

Countries that act fast reduce the number of deaths at least by 10x.

So what does a country need to be prepared?

What Will Be the Pressure on the System

Around 20% of cases require hospitalization, 5% of cases require the Intensive Care Unit (ICU), and around 2.5% require very intensive help, with items such as ventilators or ECMO (extra-corporeal oxygenation).


The problem is that items such as ventilators and ECMO can’t be produced or bought easily. A few years ago, the US had a total of 250 ECMO machines, for example.

So if you suddenly have 100,000 people infected, many of them will want to go get tested. Around 20,000 will require hospitalization, 5,000 will need the ICU, and 1,000 will need machines that we don’t have enough of today. And that’s just with 100,000 cases.

That is without taking into account issues such as masks. A country like the US has only 1% of the masks it needs to cover the needs of its healthcare workers (12M N95, 30M surgical vs. 3.5B needed). If a lot of cases appear at once, there will be masks for only 2 weeks.

Countries like Japan, South Korea, Hong Kong or Singapore, as well as Chinese regions outside of Hubei, have been prepared and given the care that patients need.

But the rest of Western countries are rather going in the direction of Hubei and Italy. So what is happening there?

What an Overwhelmed Healthcare System Looks Like

The stories that happened in Hubei and those in Italy are starting to become eerily similar. Hubei built two hospitals in ten days, but even then, it was completely overwhelmed.

Both complained that patients inundated their hospitals. They had to be taken care of anywhere: in hallways, in waiting rooms…

I heavily recommend this short Twitter thread. It paints a pretty stark picture of Italy today

Healthcare workers spend hours in a single piece of protective gear, because there’s not enough of them. As a result, they can’t leave the infected areas for hours. When they do, they crumble, dehydrated and exhausted. Shifts don’t exist anymore. People are driven back from retirement to cover needs. People who have no idea about nursing are trained overnight to fulfill critical roles. Everybody is on call, always.

Francesca Mangiatordi, an Italian nurse that crumbled in the middle of the war with the Coronavirus

That is, until they become sick. Which happens a lot, because they’re in constant exposure to the virus, without enough protective gear. When that happens, they need to be in quarantine for 14 days, during which they can’t help. Best case scenario, 2 weeks are lost. Worst case, they’re dead.

The worst is in the ICUs, when patients need to share ventilators or ECMOs. These are in fact impossible to share, so the healthcare workers must determine what patient will use it. That really means, which one lives and which one dies.

“After a few days, we have to choose. […] Not everyone can be intubated. We decide based on age and state of health.” —Christian Salaroli, Italian MD.

Medical workers wear protective suits to attend to people sickened by the novel coronavirus, in the intensive care unit of a designated hospital in Wuhan, China, on Feb. 6. (China Daily/Reuters), via Washington Post

All of this is what drives a system to have a fatality rate of ~4% instead of ~0.5%. If you want your city or your country to be part of the 4%, don’t do anything today.

Satellite images show Behesht Masoumeh cemetery in the Iranian city of Qom. Photograph: ©2020 Maxar Technologies. Via The Guardian and the The New York Times.

3. What Should You Do?

Flatten the Curve

This is a pandemic now. It can’t be eliminated. But what we can do is reduce its impact.

Some countries have been exemplary at this. The best one is Taiwan, which is extremely connected with China and yet still has as of today fewer than 50 cases. This recent paper explain all the measures they took early on, which were focused on containment.

They have been able to contain it, but most countries lacked this expertise and didn’t. Now, they’re playing a different game: mitigation. They need to make this virus as inoffensive as possible.

If we reduce the infections as much as possible, our healthcare system will be able to handle cases much better, driving the fatality rate down. And, if we spread this over time, we will reach a point where the rest of society can be vaccinated, eliminating the risk altogether. So our goal is not to eliminate coronavirus contagions. It’s to postpone them.


The more we postpone cases, the better the healthcare system can function, the lower the mortality rate, and the higher the share of the population that will be vaccinated before it gets infected.

How do we flatten the curve?

Social Distancing

There is one very simple thing that we can do and that works: social distancing.

If you go back to the Wuhan graph, you will remember that as soon as there was a lockdown, cases went down. That’s because people didn’t interact with each other, and the virus didn’t spread.

The current scientific consensus is that this virus can be spread within 2 meters (6 feet) if somebody coughs. Otherwise, the droplets fall to the ground and don’t infect you.

The worst infection then becomes through surfaces: The virus survives for up to 9 days on different surfaces such as metal, ceramics and plastics. That means things like doorknobs, tables, or elevator buttons can be terrible infection vectors.

The only way to truly reduce that is with social distancing: Keeping people home as much as possible, for as long as possible until this recedes.

This has already been proven in the past. Namely, in the 1918 flu pandemic.

Learnings from the 1918 Flu Pandemic


You can see how Philadelphia didn’t act quickly, and had a massive peak in death rates. Compare that with St Louis, which did.

Then look at Denver, which enacted measures and then loosened them. They had a double peak, with the 2nd one higher than the first.


If you generalize, this is what you find:


This chart shows, for the 1918 flu in the US, how many more deaths there were per city depending on how fast measures were taken. For example, a city like St Louis took measures 6 days before Pittsburgh, and had less than half the deaths per citizen. On average, taking measures 20 days earlier halved the death rate.

Italy has finally figured this out. They first locked down Lombardy on Sunday, and one day later, on Monday, they realized their mistake and decided they had to lock down the entire country.

Hopefully, we will see results in the coming days. However, it will take one to two weeks to see. Remember the Wuhan graph: there was a delay of 12 days between the moment when the lockdown was announced and the moment when official cases (orange) started going down.

How Can Politicians Contribute to Social Distancing?

The question politicians are asking themselves today is not whether they should do something, but rather what’s the appropriate action to take.

There are several stages to control an epidemic, starting with anticipation and ending with eradication. But it’s too late for most options today. With this level of cases, the two only options politicians have in front of them are containment and mitigation.


Containment is making sure all the cases are identified, controlled, and isolated. It’s what Singapore, Hong Kong, Japan or Taiwan are doing so well: They very quickly limit people coming in, identify the sick, immediately isolate them, use heavy protective gear to protect their health workers, track all their contacts, quarantine them… This works extremely well when you’re prepared and you do it early on, and don’t need to grind your economy to a halt to make it happen.

I’ve already touted Taiwan’s approach. But China’s is good too. The lengths at which it went to contain the virus are mind-boggling. For example, they had up to 1,800 teams of 5 people each tracking every infected person, everybody they got interacted with, then everybody those people interacted with, and isolating the bunch. That’s how they were able to contain the virus across a billion-people country.

This is not what Western countries have done. And now it’s too late. The recent US announcement that most travel from Europe was banned is a containment measure for a country that has, as of today, 3 times the cases that Hubei had when it shut down, growing exponentially. How can we know if it’s enough? It turns out, we can know by looking at the Wuhan travel ban.

This chart shows the impact that the Wuhan travel ban had delaying the epidemic. The bubble sizes show the number of daily cases. The top line shows the cases if nothing is done. The two other lines show the impact if 40% and 90% of travel is eliminated. This is a model created by epidemiologists, because we can’t know for sure.

If you don’t see much difference, you’re right. It’s very hard to see any change in the development of the epidemic.

Researchers estimate that, all in all, the Wuhan travel ban only delayed the spread in China by 3–5 days.

Now what did researchers think the impact of reducing transmission would be?


The top bloc is the same as the one you’ve seen before. The two other blocks show decreasing transmission rates. If the transmission rate goes down by 25% (through Social Distancing), it flattens the curve and delays the peak by a whole 14 weeks. Lower the transition rate by 50%, and you can’t see the epidemic even starting within a quarter.

The US administration’s ban on European travel is good: It has probably bought us a few hours, maybe a day or two. But not more. It is not enough. It’s containment when what’s needed is mitigation.

Once there are hundreds or thousands of cases growing in the population, preventing more from coming, tracking the existing ones and isolating their contacts isn’t enough anymore. The next level is mitigation.


Mitigation requires heavy social distancing. People need to stop hanging out to drop the transmission rate (R), from the R=~2–3 that the virus follows without measures, to below 1, so that it eventually dies out.

These measures require closing companies, shops, mass transit, schools, enforcing lockdowns… The worse your situation, the worse the social distancing. The earlier you impose heavy measures, the less time you need to keep them, the easier it is to identify brewing cases, and the fewer people get infected.

This is what Wuhan had to do. This is what Italy was forced to accept. Because when the virus is rampant, the only measure is to lock down all the infected areas to stop spreading it at once.

With thousands of official cases — and tens of thousands of true ones — this is what countries like Iran, France, Spain, Germany, Switzerland or the US need to do.

But they’re not doing it.

Some business are working from home, which is fantastic.
Some mass events are being stopped.
Some affected areas are in quarantining themselves.

All these measures will slow down the virus. They will lower the transmission rate from 2.5 to 2.2, maybe 2. But they aren’t enough to get us below 1 for a sustained period of time to stop the epidemic. And if we can’t do that, we need to get it as close to 1 for as long as possible, to flatten the curve.

So the question becomes: What are the tradeoffs we could be making to lower the R? This is the menu that Italy has put in front of all of us:

  • Nobody can enter or exit lockdown areas, unless there are proven family or work reasons.
  • Movement inside the areas is to be avoided, unless they are justified for urgent personal or work reasons and can’t be postponed.
  • People with symptoms (respiratory infection and fever) are “highly recommended” to remain home.
  • Standard time off for healthcare workers is suspended
  • Closure of all educational establishments (schools, universities…), gyms, museums, ski stations, cultural and social centers, swimming pools, and theaters.
  • Bars and restaurants have limited opening times from 6am to 6pm, with at least one meter (~3 feet) distance between people.
  • All pubs and clubs must close.
  • All commercial activity must keep a distance of one meter between customers. Those that can’t make it happen must close. Temples can remain open as long as they can guarantee this distance.
  • Family and friends hospital visits are limited
  • Work meetings must be postponed. Work from home must be encouraged.
  • All sports events and competitions, public or private, are canceled. Important events can be held under closed doors.

Then two days later, they added: No, in fact, you need to close all businesses that aren’t crucial. So now we’re closing all commercial activities, offices, cafes and shops. Only transportation, pharmacies, groceries will remain open.”

One approach is to gradually increase measures. Unfortunately, that gives precious time for the virus to spread. If you want to be safe, do it Wuhan style. People might complain now, but they’ll thank you later.

How Can Business Leaders Contribute to Social Distancing?

If you’re a business leader and you want to know what you should do, the best resource for you is Staying Home Club.

It is a list of social distancing policies that have been enacted by US tech companies—so far, 328.

They range from allowed to required Work From Home, and restricted visits, travel, or events.

There are more things that every company must determine, such as what to do with hourly workers, whether to keep the office open or not, how to conduct interviews, what to do with the cafeterias… If you want to know how my company, Course Hero, handled some of these, along with a model announcement to your employees, here is the one my company used (view only version here).

4. When?

It is very possible that so far you’ve agreed with everything I’ve said, and were just wondering since the beginning when to make each decision. Put in another way, what triggers should we have for each measure.

Risk-Based Model for Triggers

To solve this, I’ve created a model.

It enables you to assess the likely number of cases in your area, the probability that your employees are already infected, how that evolves over time, and how that should tell you whether to remain open.

It tells us things like:

  • If your company had 100 employees in the Washington state area, which had 11 coronavirus deaths on 3/8, there was a 25% chance at least one of your employees was infected, and you should have closed immediately.
  • If your company had 250 employees mostly in the South Bay (San Mateo and Santa Clara counties, which together had 22 official cases on 3/8 and the true number was probably at least 54), by 3/9 you would have had ~2% chances to have at least one employee infected, and you should have closed your office too.
  • [Updated as of 3/12] If your company is in Paris (intramuros), and it has 250 employees, today there’s a 95% chance that one of your employees has the coronavirus, and you should close your office by tomorrow.

The model uses labels such as “company” and “employee”, but the same model can be used for anything else: schools, mass transit… So if you have only 50 employees in Paris, but all of them are going to take the train, coming across thousands of other people, suddenly the likelihood that at least one of them will get infected is much higher and you should close your office immediately.

If you’re still hesitating because nobody is showing symptoms, just realize 26% of contagions happen before there are symptoms.

Are You Part of a Group of Leaders?

This math is selfish. It looks at every company’s risk individually, taking as much risk as we want until the inevitable hammer of the coronavirus closes our offices.

But if you’re part of a league of business leaders or politicians, your calculations are not for just one company, but for the whole. The math becomes: What’s the likelihood that any of our companies is infected? If you’re a group of 50 companies of 250 employees on average, in the SF Bay Area, there’s a 35% chance that at least one of the companies has an employee infected, and 97% chance that will be true next week. I added a tab in the model to play with that.

Conclusion: The Cost of Waiting

It might feel scary to make a decision today, but you shouldn’t think about it this way.


This theoretical model shows different communities: one doesn’t take social distancing measures, one takes them on Day n of an outbreak, the other one on Day n+1. All the numbers are completely fictitious (I chose them to resemble what happened in Hubei, with ~6k daily new cases at the worst). They’re just there to illustrate how important a single day can be in something that grows exponentially. You can see that the one-day delay peaks later and higher, but then daily cases converge to zero.

But what about cumulative cases?


In this theoretical model that resembles loosely Hubei, waiting one more day creates 40% more cases! So, maybe, if the Hubei authorities had declared the lockdown on 1/22 instead of 1/23, they might have reduced the number of cases by a staggering 20k.

And remember, these are just cases. Mortality would be much higher, because not only would there be directly 40% more deaths. There would also be a much higher collapse of the healthcare system, leading to a mortality rate up to 10x higher as we saw before. So a one-day difference in social distancing measures can end exploding the number of deaths in your community by multiplying more cases and higher fatality rate.

This is an exponential threat. Every day counts. When you’re delaying by a single day a decision, you’re not contributing to a few cases maybe. There are probably hundreds or thousands of cases in your community already. Every day that there isn’t social distancing, these cases grow exponentially.

Share the Word

This is probably the one time in the last decade that sharing an article might save lives. They need to understand this to avert a catastrophe. The moment to act is now.

I will start adding links to translations here. I can’t verify any except for Spanish, French and Italian, so if translations look bad, please let me know.



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Don't panic. Keep calm. Should have been stated earlier than Thursday as a shot was fired in a Wallie word parking lot in what is considered one of the safest cities around these parts. Lines at Kroger and other grocery stores were out of the stores. Telling people to keep calm is a voice of reason in this full blown psychosis affecting those with TDS.

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Mods.....perhaps this thread can be moved over to the health section.....just keep it easy on yourself....


The Italy model seems to be the one for the US to own opinion is soon all US borders will be closed.....some State borders....shelter in place will be required......"The Peefect Storm"

Below find a bit more on Italy.....I believe it's pretty accurate.....





The epicenter of the coronavirus outbreak has moved from China to Europe, and within Europe, Italy has been hit the hardest. It struck first in Lombardy, in the north, but the national government has now imposed stringent quarantine regulations on the entire country of 61 million. Augie Kymmel is an American who has lived in Italy for 30 years, and she has filed this report from Cerete, a village in the province of Bergamo, northeast of Milan, not far from the border with Switzerland.



CERETE, BERGAMO, ITALY — Today is Friday, March 13, not an unlucky day in Italy, where Friday the 17th is jinxed. I woke up feeling more upbeat.

A wide-body Airbus A350 landed last night at Rome Fiumicino with much-needed medical supplies, including precious ventilators and masks, courtesy of the Chinese Red Cross. This morning I found out that not only was it carrying 31 tons of equipment — enough for 30 ICU wards for COVID-19 patients, as reported by China Daily — but also nine expert doctors and nurses with experience in tackling the disease.


If China can provide Italy with urgent medical assistance, Italy will be able help other countries in dire need. In fact, it was widely reported that the Bergamo hospital already shared its emergency model during a video conference with doctors in the U.S. who had participated in the Harvard Medical School Surgical Leadership Program.



I had been looking for an explanation for the high death rate in the Bergamo suburbs: Was it a more virulent coronavirus or the older population? This morning, reading an interview in the Corriere della Sera, I finally found a potential answer that gave me hope that many fatal cases could be avoided with the help of family doctors and social workers. A nephrologist working at the Bergamo hospital believes this coronavirus strain has been mutating quickly, probably since last December, when doctors in the area first noted more serious cases of pneumonia than usual. What’s more, ill people are afraid to go to the hospital, and instead stay at home taking acetaminophen and antibiotics for as long as they can, until they can no longer breathe.

A man wearing a mask walks in Codogno, Italy. (Antonio Calanni/AP)

A man wearing a mask walks in Codogno, Italy. (Antonio Calanni/AP)

Although we’re just at the start of our lockdown, which will remain in effect until at least April 3, most residents in our area seem willing to go along with the new travel restrictions and stay home. There’s not much of a choice, since all cafés, restaurants and nonessential retail businesses have been closed since March 12; schools and other venues were shuttered previously. Essential businesses like factories are open as long as workers are separated by at least 1 meter. Personally, I haven’t heard any major complaints yet. I think most of us are pretty scared by the relentlessly climbing coronavirus positives. Families here are already used to eating home-cooked meals, but stopping by a café for an espresso and chatting with friends will soon be sorely missed. Up until this week, students were able to hang out with their classmates after finishing their live-streamed classes and/or online homework; now they have to rely fully on their cellphones to keep in touch. Taking a walk or running is allowed, if you maintain the required 1-meter distance. We’re in the countryside, so there is plenty of space, unlike in the cities where young people, in particular, have no place except parks to escape to. Police officers there have been checking self-declarations — required for any kind of travel, even on foot — and breaking up groups congregating in green areas. Some cities have already locked their gated parks. Last I heard, more than 2,000 tickets have been issued to Italians for unjustified travel not related to work, health or emergencies.

Cerete, Italy. (Ago76 via Wikicommons)

Cerete, Italy. (Ago76 via Wikicommons)

Masks and disinfectant have been out of stock all over northern Italy for weeks. People who are lucky enough to have a mask or two at home have begun wearing them. This morning I emailed an order to the Cerete pharmacy and was pleased to find out that they now have hand sanitizer. Still no FFP2 masks though.

In my village and others in the area, the town government has teamed up with local pharmacies, grocers and café owners to provide free delivery of food and medicine to residents over 65 and people with disabilities who are unable to leave their homes during the lockdown or fear they will be infected. Young volunteers are providing door-to-door service.

To rescue the overloaded Lombardy hospital system, military doctors and nurses have been brought in and retirees have returned to work. Doctors from other parts of the country who are willing to take on the risk are hired overnight. Universities in the region have arranged for as many as 250 nurses to graduate early this year to supplement the existing staff, not only to manage the ever-growing patient load but also to substitute for workers who are now in quarantine or intensive care.

A person suspected to have the coronavirus is helped into an ambulance by medical personnel n Nembro, Italy. (Fotogramma/Abaca via Zuma Press)

A person suspected to have the coronavirus is helped into an ambulance by medical personnel n Nembro, Italy. (Fotogramma/Abaca via Zuma Press) More

Another bit of potentially good news: The evening’s figures indicate that the number of new coronavirus positives may be decelerating.

The Ministry of Health reported 17,660 total cases in Italy, a rise of just under 17 percent (2,547) compared with a rate of 21 percent on March 12. Hospitalizations have dropped to 7,426, with 1,328 in intensive care. Total deaths are 1,266 and recoveries, 1,439.

In Lombardy, there are now 9,820 total cases. However, the rate of increase has greatly fallen off to 12.5 percent (1,095) compared with 20 percent on March 12.

One thing that can be learned from Italy is that everyone needs to take preventive measures before an area becomes a hotspot. An Italian study conducted by a group of scientists in Milan has shown that the first coronavirus to arrive in Lombardy could have originated in Germany and circulated undetected for more than a month before surfacing with a vengeance in Codogno, Italy, on Feb. 21. As early as mid-January, doctors in that area were aware of an unusually large number of pneumonia cases, which they now realize were mistakenly attributed to the flu or seasonal factors like the very dry weather. Back in February, many Italians waited too long before calling their family doctors, not only causing their condition to worsen, but also allowing them to infect many others.

A hospital employee tends to a patient at a temporary emergency structure set up outside the Brescia hospital in Lombardy, Italy. (Miguel Medina/AFP via Getty Images)

A hospital employee tends to a patient at a temporary emergency structure set up outside the Brescia hospital in Lombardy, Italy. (Miguel Medina/AFP via Getty Images) More

As is already known from the cases in Italy and the U.S., fragile senior citizens, especially those living in crowded nursing homes, are at risk during the COVID-19 epidemic and can be infected both by visitors and staff. In Lombardy, visitors have been banned from nursing homes, except for urgent needs, since the government decree of March 4.

But not only the elderly should stay isolated at home (or outdoors) to protect themselves and others from the coronavirus. ISS, the Italian National Institute of Health, has recently found that the age breakdown of COVID-19 positives is as follows: 1.4 percent under 20, 20.6 percent from 20 to 49, 35.3 percent from 50 to 69, and 42.8 percent 70 and over. The average age is 64, and 60.4 percent are men. Of total cases analyzed, 26 percent, including children, have been hospitalized: 21 percent with severe symptoms and 5 percent, critical. In general, recovery takes a long time and demands resources that are in short supply. Lombardy’s so-called patient No. 1, a 38-year-old previously healthy amateur athlete, has finally been moved out of intensive care to a less critical unit — after a 3-week stay hooked up to a ventilator.

My brother-in-law thinks the invincible younger generation finally woke up and started paying attention this week when the Italian football championship was canceled. Live-streamed closed-door matches didn’t work because the fans gathered together to watch them. So the government apparently made the right move!

Silvio Brusaferro, president of the ISS, says we will know if the epidemic is under control only at the beginning of April. That’s a long time to wait.

A woman walks in Codogno, Italy, in the Lombardy region. (Antonio Calanni/AP)

A woman walks in Codogno, Italy, in the Lombardy region. (Antonio Calanni/AP)

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Edited by coorslite21
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I tend to be contrarian in my views.

Here are some of my random thoughts/Qs.

Corona virus has been around for years, yes this is a new strain/GM/mutation, regardless of source the death rate is still remarkably low and in no way correlates to world wide panic currently being whipped up by the media.

Think of this, Wuhan has supposed resettled 5 million people. There is no info on this. What if all or most are dead?? If that holds true, then it would not be Corona virus it must be something catastrophic with a very high death rate. This must be a biological weapon that escaped or was used on the unsuspecting Guinea pig population. If this is true, stage actors in China would be now filling in for Chinese politicians as the true leaders will be hunkered down in biological secure facilities.

Not an encouraging thought process on my part.

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LOL let's hide this thread because this smacks us all in the face with the politicization of this so-called pandemic to hurt Trump's re-election but hasn't so we must hide the thread because we all know Orange man bad lalalala ... the real pandemic is the TDS that has gripped the world. More people have died from the 2019-2020 seasonal flu in the last six months than COVD-19. We don't hear of those deaths. 

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House sends coronavirus relief bill to Senate after delay by GOP congressman

Rebecca Shabad and Alex Moe
NBC NewsMarch 17, 2020

WASHINGTON — The House on Monday night passed a bill containing technical corrections to the coronavirus relief bill it passed over the weekend, sending it to the Senate to be considered for a vote at some point this week.

Around 8:10 p.m. ET, the House passed the corrections by unanimous consent during a pro forma session since the lower chamber is on recess this week.

Earlier in the day, Rep. Louie Gohmert, R-Texas, held up the process because he insisted on reading them, a Democratic leadership aide confirmed Monday. He spoke on the floor Monday night and said that the technical corrections make the bill better and he withdrew his objection to pass the measure by unanimous consent.

Senate GOP leaders have not yet specified an exact day for voting on the bill, but a number of senators want to act on it as soon as possible and want to get started on a third relief package.

Gohmert was able to hold it up because if one member stands in opposition, the House can't send the bill to the Senate without bringing the entire House back to Washington for a vote. The Senate is in session this week, but schedules have been fluid because of the coronavirus outbreak.


Gohmert was among 40 Republicans who voted against the original bill, which overwhelmingly passed the House and was endorsed by President Donald Trump. In a statement explaining his vote, Gohmert praised how Trump had negotiated the package but said, "This crucial bill was not even given the normal amount of time to debate it on the House floor."


Gohmert said that he had a number of questions he wanted answered before the vote but that there was no time. "We voted, and I truly had wanted to vote yes but could not for a bill that created so many concerns without time to examine whether some of our language did more harm than good."

"Unfortunately, now that it has passed the House, we will find out what this bill actually does," he said. "Hopefully, the Senate will take the time to clean up the damage our bill caused and not just rubber-stamp it, so I can vote for the bill that they send back to the House."

Senate Majority Leader Mitch McConnell, R-Ky., acknowledged in a statement Sunday that the ball is in the House's court. He said that he commends the work Treasury Secretary Steven Mnuchin did to strike the agreement and that senators from both parties are carefully reviewing the details and "are eager to act swiftly to help American workers, families and small businesses navigate this challenging time."

House Speaker Nancy Pelosi, D-Calif., who negotiated the legislation with Mnuchin, said the legislation includes free coronavirus testing, even for the uninsured, two weeks of paid sick leave and paid family and medical leave. To help people who lose their jobs amid the outbreak, Pelosi said the bill would strengthen unemployment insurance and boost food security initiatives like food stamps.

It also would increase federal funds "for Medicaid to support our local, state, tribal and territorial governments and health systems, so that they have the resources necessary to combat this crisis," she said.


GO RV, then BV

Edited by Shabibilicious
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7 hours ago, Theseus said:

More people have died from the 2019-2020 seasonal flu in the last six months than COVD-19. We don't hear of those deaths. 


They're called "percentages" should look into that, from reputable sources, of course.  ;)


GO RV, then BV

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On 3/17/2020 at 9:30 AM, Shabibilicious said:


They're called "percentages" should look into that, from reputable sources, of course.  ;)


GO RV, then BV

According to CDC, this year's flu season has led to at least 17 million medical visits and 370,000 hospitalizations. CDC found that the percentage of outpatient visits for influenza-like illness increased to 5.2% in the week ending on March 7, up from 5.1% the previous week. The national baseline for those visits is 2.4%.


CDC estimated that there have been at least 22,000 deaths related to the flu so far this season.


Yeah you should look before you leap, bucko. 


Just to compare:


Coronavirus Cases:





So there are only four thousand more cases of the coronavirus than deaths by the flu. CDC numbers not percentages!
Edited by Theseus
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      DESCRIPTION OF THE FIGURES FIG. 1—Growth kinetics of M41-R-6 and M41-R-12 compared to M41-CK (M41 EP4) on CK cells
      FIG. 2—Clinical signs, snicking and wheezing, associated with M41-R-6 and M41-R-12 compared to M41-CK (M41 EP4) and Beau-R (Bars show mock, Beau-R, M41-R 6, M41-R 12, M41-CK EP4 from left to right of each timepoint).
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      FIG. 4—Clinical signs, snicking, associated with M41R-nsp10rep and M41R-nsp14,15,16rep compared to M41-R-12 and M41-CK (M41 EP5) (Bars show mock, M41-R12; M41R-nsp10rep; M41R-nsp14,15,16rep and M41-CK EP5 from left to right of each timepoint).
      FIG. 5—Ciliary activity of M41R-nsp10rep and M41R-nsp14,15,16rep compared to M41-R-12 and M41-CK in tracheal rings isolated from tracheas taken from infected chicks (Bars show mock; M41-R12; M41R-nsp10rep; M41R-nsp14,15,16rep and M41-CK EP5 from left to right of each timepoint).
      FIG. 6—Clinical signs, snicking, associated with M41R-nsp10, 15rep, M41R-nsp10, 14, 15rep, M41R-nsp10, 14, 16rep, M41R-nsp10, 15, 16rep and M41-K compared to M41-CK (Bars show mock, M41R-nsp10,15rep1; M41R-nsp10,14,16rep4; M41R-nsp10,15,16rep8; M41R-nsp10,14,15rep10; M41-K6 and M41-CK EP4 from left to right of each timepoint).
      FIG. 7—Clinical signs, wheezing, associated with M41R-nsp10, 15rep, M41R-nsp10, 14, 15rep, M41R-nsp10, 14, 16rep, M41R-nsp10, 15, 16rep and M41-K compared to M41-CK (Bars show mock, M41R-nsp10,15rep1; M14R-nsp10,14,16rep4; M41R-nsp10,15,16rep8; M41R-nsp10,14,15rep10; M41-K6 and M41-CK EP4 from left to right of each timepoint).
      FIG. 8—Ciliary activity of M41R-nsp10, 15rep, M41R-nsp10, 14, 15rep, M41R-nsp10, 14, 16rep, M41R-nsp10, 15, 16rep and M41-K compared to M41-CK in tracheal rings isolated from tracheas taken from infected chicks (Bars show mock, M41R-nsp10,15rep1; M41R-nsp10,14,16rep4; M41R-nsp10,15,16rep8; M41R-nsp10,14,15rep10; M41-K6 and M41-CK EP4 from left to right of each timepoint).
      FIG. 9—Growth kinetics of rIBVs compared to M41-CK on CK cells. FIG. 9A shows the results for M41-R and M41-K. FIG. 9B shows the results for M41-nsp10 rep; M41R-nsp14, 15, 16 rep; M41R-nsp10, 15 rep; M41R-nsp10, 15, 16 rep; M41R-nsp10, 14, 15 rep; and M41R-nsp10, 14, 16.
      FIG. 10—Position of amino acid mutations in mutated nsp10, nsp14, nsp15 and nsp16 sequences.
      FIG. 11—A) Snicking; Respiratory symptoms (wheezing and rales combined) and C) Ciliary activity of rIBV M41R-nsp 10,14 rep and rIBV M41R-nsp 10,16 rep compared to M41-CK (Bars show mock, M41R-nsp10,14rep; M41R-nsp10,16rep and M41-K from left to right of each timepoint).
      DETAILED DESCRIPTION The present invention provides a coronavirus comprising a variant replicase gene which, when expressed in the coronavirus, causes the virus to have reduced pathogenicity compared to a corresponding coronavirus which comprises the wild-type replicase gene.
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      As used herein the term “derived from” means that the replicase gene comprises substantially the same nucleotide sequence as the wild-type replicase gene of the relevant coronavirus. For example, the variant replicase gene of the present invention may have up to 80%, 85%, 90%, 95%, 98% or 99% identity with the wild type replicase sequence. The variant coronavirus replicase gene encodes a protein comprising a mutation in one or more of non-structural protein (nsp)-10, nsp-14, nsp-15 or nsp-16 when compared to the wild-type sequence of the non-structural protein.
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      In broilers, coughing and rattling are common clinical signs, rapidly spreading in all the birds of the premises. Morbidity is 100% in non-vaccinated flocks. Mortality varies depending on age, virus strain, and secondary infections but may be up to 60% in non-vaccinated flocks.
      The first IBV serotype to be identified was Massachusetts, but in the United States several serotypes, including Arkansas and Delaware, are currently circulating, in addition to the originally identified Massachusetts type.
      The IBV strain Beaudette was derived following at least 150 passages in chick embryos. IBV Beaudette is no longer pathogenic for hatched chickens but rapidly kills embryos.
      H120 is a commercial live attenuated IBV Massachusetts serotype vaccine strain, attenuated by approximately 120 passages in embryonated chicken eggs. H52 is another Massachusetts vaccine, and represents an earlier and slightly more pathogenic passage virus (passage 52) during the development of H120. Vaccines based on H120 are commonly used.
      IB QX is a virulent field isolate of IBV. It is sometimes known as “Chinese QX” as it was originally isolated following outbreaks of disease in the Qingdao region in China in the mid 1990s. Since that time the virus has crept towards Europe. From 2004, severe egg production issues have been identified with a very similar virus in parts of Western Europe, predominantly in the Netherlands, but also reported from Germany, France, Belgium, Denmark and in the UK.
      The virus isolated from the Dutch cases was identified by the Dutch Research Institute at Deventer as a new strain that they called D388. The Chinese connection came from further tests which showed that the virus was 99% similar to the Chinese QX viruses. A live attenuated QX-like IBV vaccine strain has now been developed.
      IBV is an enveloped virus that replicates in the cell cytoplasm and contains an non-segmented, single-stranded, positive sense RNA genome. IBV has a 27.6 kb RNA genome and like all coronaviruses contains the four structural proteins; spike glycoprotein (S), small membrane protein (E), integral membrane protein (M) and nucleocapsid protein (N) which interacts with the genomic RNA.
      The genome is organised in the following manner: 5′UTR—polymerase (replicase) gene—structural protein genes (S-E-M-N)—UTR 3′; where the UTR are untranslated regions (each ˜500 nucleotides in IBV).
      The lipid envelope contains three membrane proteins: S, M and E. The IBV S protein is a type I glycoprotein which oligomerizes in the endoplasmic reticulum and is assembled into homotrimer inserted in the virion membrane via the transmembrane domain and is associated through non-covalent interactions with the M protein. Following incorporation into coronavirus particles, the S protein is responsible for binding to the target cell receptor and fusion of the viral and cellular membranes. The S glycoprotein consists of four domains: a signal sequence that is cleaved during synthesis; the ectodomain, which is present on the outside of the virion particle; the transmembrane region responsible for anchoring the S protein into the lipid bilayer of the virion particle; and the cytoplasmic tail.
      All coronaviruses also encode a set of accessory protein genes of unknown function that are not required for replication in vitro, but may play a role in pathogenesis. IBV encodes two accessory genes, genes 3 and 5, which both express two accessory proteins 3a, 3b and 5a, 5b, respectively.
      The variant replicase gene of the coronavirus of the present invention may be derived from an IBV. For example the IBV may be IBV Beaudette, H120, H52, IB QX, D388 or M41.
      The IBV may be IBV M41. M41 is a prototypic Massachusetts serotype that was isolated in the USA in 1941. It is an isolate used in many labs throughout the world as a pathogenic lab stain and can be obtained from ATCC (VR-21™). Attenuated variants are also used by several vaccine producers as IBV vaccines against Massachusetts serotypes causing problems in the field. The present inventors chose to use this strain as they had worked for many years on this virus, and because the sequence of the complete virus genome is available. The M41 isolate, M41-CK, used by the present inventors was adapted to grow in primary chick kidney (CK) cells and was therefore deemed amenable for recovery as an infectious virus from a cDNA of the complete genome. It is representative of a pathogenic IBV and therefore can be analysed for mutations that cause either loss or reduction in pathogenicity.

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