I am hearing reports of very long lines at "coffee shops" in the Netherlands, as they are about to be closed. Can anyone here confirm or otherwise (or are you standing in one now?? 
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Meanwhile, official numbers so cases outside China set to pass 100,000 in the next couple days, and still doubling every 4-5 days.
Guessing (conservatively imvho) that this under-represents the actual number of infected by an order of magnitude, there are probably a million people (at least) with this thing worldwide outside China.
And (conservatively again) rounding up to a five day doubling time, that gives a projection (not prediction) of about a billion infected outside China by about the beginning of May.
One way or the other, of course, it will be leveling off shortly thereafter.
https://www.worldometers.info/coronavirus/coronavirus-cases/#case-tot-outchina
Public Radio just now:
The governor of Illinois on Sunday ordered all bars and restaurants in his state to close amid the threat of the new coronavirus, and officials elsewhere in the country said they were considering similar restrictions after revelers ignored warnings against attending large gatherings
The unconstrained doubling time has often been as little as 1.5 days in the span from about 10 cases to about 100 cases. This comes from a daily growth of 1.60x/day. Wuhan continued at the high rate for somewhat longer.
From 100 to about 5,000 cases the daily growth often slows to about 1.33 - 1.35x/day. This has been repeated in country after country. This corresponds to a doubling time of 2.33 days (8x/week). Note: Dr. Fauci and many others have been citing a doubling time of one week. That is grossly in error. It is much much faster than that. And that has enormous impacts on decision making.
From about 5,000 cases to 10,000 cases the doubling time often slows. It finally seems to stabilize at 1.15 - 1.20x/day in many cases. That corresponds to a doubling time of ~4 - 5 days.
It might be possible to put some sort of relation to that. But the individual variation by location is no doubt important. And once massive quarantines are imposed the relationship falls apart - as it should.
The slow down from 1.33 - 1.35x/day seems to very much be associated with societal changes - distancing, hand washing, self-isolation and ultimately quarantines. I suspect that is precisely what it is. It may also be partly influenced by the statistics of human to human contact. This can occur as the infection moves from the most mobile and contacted part of the population into more isolated segments with less contact. At even higher infection counts, it can also happen with statistical reduction in the population pool available of those who have not yet been infected.
This latter effect is where herd immunity comes in. If the R0 is small enough (near 1), when a significant part of the population is infected the statistical chance of infected people infecting others drops taking the R0 under 1. At that point the infection chains peter out and die. The most you can expect from that is a ratio of 0.6. That means that when the R0 is greater than the inverse of this, i.e. > 1.66, that herd immunity will not stop the chains.
When the R0 is substantial this does not happen. The effective R0 still drops due to the reduced probability of finding uninfected people to infect. However, with a high R0, there are still enough people to keep the effective R0 above unity, so the chains continue.
With an extremely infective virus, herd immunity has much less importance. This is where Boris is making a huge mistake in Great Britain. He reportedly wants to rely on herd immunity to end the chains. I do not know this first, second or even third hand. So treat that as rumor until someone links a story. Whether true or not it provides backdrop for explaining why this will not work.
This virus has been reported to have a serial time (the average time it takes one person to infect another in a chain) of 5.9, 7.2, and 7.5 days. These are not significantly different evaluations. They are all long. Also, the virus seems to be contagious for at least several of the days before symptoms show at day 5-7 on average.
If we know or can estimate the serial time, and we know the slope of the growth curve of infections (plotted logarithmically), we can calculate the effective R0 = (growth rate/day)^(serial time in days). the growth rate itself is the exponential of the slope of the curve on the logarithmic plot (to the same base as the plot was made).
So for the typical growth rate of 1.35x/day and a serial time of 5.9 days we get an R0 of 5.87. With the same growth rate and a serial time of 7.5 days the R0 is 7.50.
These are in the same range as Chicken Pox. It is highly communicable!
During the early phase with growth at ~1.6x/day, the equivalent R0 is then 16 - 34 !!! That is Measles territory and worse.
This is what Edmountain was referring to. The major factors involved in this pandemic involve this infectivity, not the CFR. The CFR gets to consequences. It doesn't tell the whole story.
For disaster planning, both of these and the ratios for various morbidities are all important. For disaster management in an ER, the focus is on the specifics of the disease as it affects treatment and as it affects infection control.
The issues for decision makers and emergency managers is mostly about trying to stop the spread, and about logistics issues related to impacts on health care and societal functions. So long as those do not exceed the capacity of the emergency services, the details of what they have to deal with though important, are a second level concern. The first level concern is in minimizing the catastrophes growth so that they do not become overwhelmed. Then next, if they will be, figuring out any ways to reduce those impacts to levels that can be dealt with.
In China that meant doing the mass quarantines, ... as first level response; then rapidly building hospitals and moving in equipment and personnel (doctors and nurses, plus support equipment and supplies) to handle the surge as it occurred. Italy failed there. The hospitals were and remain overwhelmed. At that point, the hospital emergency staff are in triage mode. They are having to decide who lives and who dies. This will traumatize them for the rest of their lives.
Within the medical establishments the focus is different. There the focus is on infection control both for all of the patients AND for all of the doctors, nurses, and staff, while being able to rapidly assess and handle all of the casualties and their specific needs without exhausting everyone, or consuming all available supplies. Slightly lower in priority is efforts to find the most effective and expeditious treatments with the best outcomes. Those are all a delicate dance with conflicting priorities and resource needs.
Back to your specific question. Since the time to display symptoms is generally about 5-7 days, this means that under the expected conditions with a growth rate of 1.35x/day, The number infected is about 6 times the number exhibiting symptoms. And since it often takes a day or two for those to present, thats 1.8 times more yet. And if the systems require that they be "confirmed" through testing to be counted, and the tests take 2 days to return answers, that is yet another 1.8x multiplier. For that case, the number infected is something like 20 times the confirmed count (give or take - a lot).
If there are no test kits available (US case) and the policy is to not test unless certain very constrained conditions exist (again - the US case), then the true population infected count may be staggeringly higher than the confirmed case count. In that case, deaths from causes that look like COVID may be a better indicator. And those occur something like 17 days on average following confirmed infection - 23 days in total. So death count times 1,000 may be a crude estimate of the likely count of those infected. That presumes of course that all those dying of the disease get counted as that, even if they were never tested for it. Otherwise, the number is higher. Using these ratios for the United States this would suggest somewhere between 48,000 and 59,000 people infected a day ago. (Remember too that the data ia almost always a day late). That converts to 65-80,000 today.
Note also that as time passes, the counts smear together current and past counts, and these ratios break down. Do not rely on them other than as extremely crude thumb rules. Even then - do not rely on them.
If the controls began to go in place less than a week ago (true), then the growth is the same for the next few days at least. Remember that people are infected for almost a week before showing symptoms - so that week delay is baked into the problem.
If we use a growth rate of 1.25x/day for the next week (given how much people are beginning to do), then a week from today we should expect that there are 300-400 thousand people infected in the US.
BUT, if the numbers are suppressed due to under counting, these may dramatically underestimate the total infected at every stage.
Continue that same growth for one more week (i.e. no significant national actions for the next week, just haphazard State and individual actions that cause the rate of growth to remain at 1.25x/day for another week), then before anything changes, the number of infected people in the US reaches 1.4 - 1.8 million.
That is a likely minimum case BEFORE significant national controls take force. It only takes 24 more days (31 from now - one month) of inaction for those numbers to grow to involve every injectable person in the United States. And the first 6 of those are already baked in. Each passing moment dramatically lessens the effectiveness of any action taken.
That is the nature and problem with exponential growth. By the time you see you have a problem it has already eaten your lunch.
Sam
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