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Trump’s Incompetent Management of the Covid-19 Pandemic: The Consequences for Health

Trump and his administration have utterly mismanaged the Covid-19 pandemic.  The direct result of this ineptitude has been tens of thousands more Americans dying (already) than would have been the case had the US managed the pandemic as well as any of the developed countries of the Asia and Pacific region.  The difference is not small.  This is also not a calculation comparing what the US did to what theoretically might have been possible.  Rather, it is a comparison to what these seven countries actually achieved, facing the same virus as the US.

The chart above shows the cumulative number of deaths from Covid-19 for the US and for seven Asian/Pacific countries between March 1 and April 25, with the numbers all scaled, for comparability, to what they would have been at the US population level.  The data comes from that assembled on an on-going basis by Johns Hopkins University, where a description is available here, and the country data itself available here.  The country population figures to work out the rates per million are those reported by the UN.

US deaths from the virus totaled 53,755 as of April 25.  The figures for each of the seven Asian/Pacific countries are, at this scale, all scrunched up at the bottom of the chart and are almost indistinguishable.  Each and every one has done far better than the US.

Focusing on the figures for April 25 only, one has:

The highest number of deaths among the seven Asian/Pacific countries (when scaled to the US population) would have been South Korea at 1,562.  That is 97% less than the US had.  The levels at all the other countries would have been even lower.  The least would have been Taiwan, with just 83 deaths from the virus (99.8% less than the US), despite far closer links to China.  Not re-scaled for population, the number of deaths so far in South Korea have totaled 242.  In Taiwan, there have been only 6.

US fatalities from Covid-19 have also just passed another significant milestone.  As of April 25 they now exceed the total number of US deaths in combat during World War I:

The figures for combat deaths are all from the Department of Veteran Affairs.  The total number of deaths from Covid-19 surpassed the number of combat deaths during the entire period of the Vietnam War on April 22, and passed the number of combat deaths during the Korean War on April 16.  And Covid-19 deaths of course continue to rise.  Over the most recent week, the daily increase averaged 2,156.

Yet Trump continues to assert that he and his administration have done a superb job of managing this crisis.  If there are any issues, he has at various times asserted the blame is with China, the Chinese President Xi Jinping (whom he, at other times, lauded), the WHO, Obama, Hillary Clinton, Democratic mayors, Democratic governors, Democrats in Congress and the Senate, Democrats more generally, the news media, government civil servants (the “deep state”), and others.

But not himself.  What can he be faulted for?  David Frum (a longtime self-described “conservative Republican” who served as a speechwriter for George W. Bush, but who is now very much a critic of Trump) puts it well in an April 7 article in The Atlantic.  I will quote it at length:

“That the pandemic occurred is not Trump’s fault. The utter unpreparedness of the United States for a pandemic is Trump’s fault. The loss of stockpiled respirators to breakage because the federal government let maintenance contracts lapse in 2018 is Trump’s fault. The failure to store sufficient protective medical gear in the national arsenal is Trump’s fault. That states are bidding against other states for equipment, paying many multiples of the precrisis price for ventilators, is Trump’s fault. Air travelers summoned home and forced to stand for hours in dense airport crowds alongside infected people? That was Trump’s fault too. Ten weeks of insisting that the coronavirus is a harmless flu that would miraculously go away on its own? Trump’s fault again. The refusal of red-state governors to act promptly, the failure to close Florida and Gulf Coast beaches until late March? That fault is more widely shared, but again, responsibility rests with Trump: He could have stopped it, and he did not.

The lying about the coronavirus by hosts on Fox News and conservative talk radio is Trump’s fault: They did it to protect him. The false hope of instant cures and nonexistent vaccines is Trump’s fault, because he told those lies to cover up his failure to act in time. The severity of the economic crisis is Trump’s fault; things would have been less bad if he had acted faster instead of sending out his chief economic adviser and his son Eric to assure Americans that the first stock-market dips were buying opportunities. The firing of a Navy captain for speaking truthfully about the virus’s threat to his crew? Trump’s fault. The fact that so many key government jobs were either empty or filled by mediocrities? Trump’s fault. The insertion of Trump’s arrogant and incompetent son-in-law as commander in chief of the national medical supply chain? Trump’s fault.

For three years, Trump has blathered and bluffed and bullied his way through an office for which he is utterly inadequate. But sooner or later, every president must face a supreme test, a test that cannot be evaded by blather and bluff and bullying. That test has overwhelmed Trump.”

Since April 7 one could add much more to this list, most recently Trump’s comments at his April 23 press briefing on the possible curative effects of injecting disinfectants into the body.  Health professionals around the country scrambled to warn the public not to do this – it could be deadly – and Trump is responsible for this confusion.  Or the ousting in the last week of Dr. Rick Bright, a highly respected medical researcher with a career on vaccine development, who as the head of BARDA (the Biomedical Advanced Research and Development Authority) had a lead role in the urgent development of a vaccine for Covid-19.  The ousting of such an official in the middle of a pandemic is astonishing for any reason.  Dr. Bright, in a statement issued through his lawyers, said it was because he had resisted administration pressure to promote the anti-malarial drugs chloroquine and hydroxychloroquine that Trump had repeatedly touted, even though there was no good evidence of their efficacy.  Indeed, a recent study found that hydroxychloroquine significantly increased the number of deaths of Covid-19 patients compared to those given the usual care.

Trump, however, is unwilling to take responsibility for these repeated failures.  In a March 13 press briefing he famously said “I don’t take responsibility at all” (where this was with specific reference to the lack of adequate testing in the US for a critical two months).  Rather, it was someone else’s fault.

Leadership requires taking responsibility.  Successful presidents do.

Covid-19: Using Fatality Rates to Estimate the Degree of Undercounting and Undertesting

The United States terribly bungled the introduction of testing for the virus that causes Covid-19, with a delay of more than a month during a critical time.  Even now, the testing rate is still less than half that of a number of European countries (per unit of population).  As a result, public health officials as well as regional hospitals have been “flying blind” as they try to manage their way through this crisis.

It is widely acknowledged that with the continued limitations on testing, the US is severely undercounting the number of Covid-19 cases in the country.  But undercounting by how much?  One can arrive at a rough estimate using the measured case fatality rates (which are based on the number of cases that have been confirmed by lab tests), and estimates of what the fatality rate is among all those infected by the virus (which is formally called the “infection fatality rate”).  And the figures suggest that we may be undercounting the number of Covid-19 cases by a factor of perhaps six to nine.  That is, the true number of Covid-19 cases in the US as of the evening of April 15 was not 633,000, but rather between 3.8 and 5.7 million.  That is not a small difference, and provides an indication of how much better the US needs to get at testing if it is to be able to reopen the economy safely.

The method used here is based on aggregate numbers, which limits its precision.  Hence the broad range given of six to nine.  But only aggregate numbers are at this point publicly available.  I would also emphasize that I am an economist (and know a bit of math) and not an epidemiologist.  Estimates provided by epidemiologists using micro data sets that trace samples of individuals, will be far better than what can be provided here, and presumably such work is now underway.  But for the purpose here, which is to arrive at a rough estimate of what the true Covid-19 case count might be in the US, the method should suffice.

The “case fatality rate” is simply the number of deaths from some disease divided by the number of cases of those that had the disease.  Once an epidemic is over, with all cases known and resolved (either by the patients surviving, or not), this rate can be measured easily.  But it is far more difficult to arrive at a good estimate during an epidemic.  The number of cases may be rising exponentially, as are also the number of fatalities from the disease.  But the fatalities occur with a lag.  That is, as the disease runs its course over some period of time, the fatalities today will be linked to the number of those coming down with the disease some number of days earlier, not to the number of those who have been diagnosed with the disease as of today.  Secondly, and importantly, it can be difficult to know during the course of the epidemic whether the number of cases that have been confirmed by some diagnostic test matches well or not the number of actual cases.  No testing is universal, but there are different degrees of how adequate or inadequate it is.

To address the first issue, one can compare the number of fatalities today to what the number of confirmed cases were some number of days before.  While there will be some distribution of the number of days between when symptoms are first observed and the death of those who will die from the disease, if that distribution does not vary over time then one can use a simple average for the number of days for this period.  That distribution might start to lengthen once we have more effective therapies to treat those with Covid-19, but so far we do not.

The chart at the top of this post then shows what the observed ratios were in the aggregate numbers for the US, between deaths from Covid-19 and confirmed cases with time lags of 10 days, 7 days, 6 days, 5 days, and none.  These are all “case fatality rates”, where the no lag case (where the current total number of deaths is divided simply by the current total number of confirmed cases) is called the “naive case fatality rate”.  The data comes from the data set assembled by The New York Times, which it is making available through GitHub.

The figures cover the period from March 30 (when the total number of fatalities first passed 3,000, and the number of confirmed cases totaled 163,000) to April 15 (when fatalities were almost ten times higher at 28.3 thousand, and the number of confirmed cases totaled 630,000).  When there is no lag, with the number of total deaths as per some date divided by the total number of cases as of that same date, the curve (shown in black on the chart above) will be low in a situation where both cases and deaths are rising.  And it will be rising as the growth rate of each slows (as we will discuss below) because then the number of deaths will more closely “catch up” with the number of confirmed cases.

At the opposite extreme, the curve in red in the chart of the ratio with a lag of ten days will be high (as current total deaths are calculated as a ratio to the number of cases of many days before, when the cases were much smaller), and will decline over time as the underlying growth rates (of cases and deaths) slow and there is again a “catch up”.

In the middle, a lag of six days leads to a ratio which is very close to constant, at about 6.0%.  It fits well, but also suggests that since late March there has not been any working off of the backlog of untested cases.  If, as we will discuss below, the infection fatality rate were around 1.0% or less (which appears to be the general consensus among the experts at this point), then that curve should be falling from 6% down towards 1%.  It isn’t.  The only alternative explanation would be that the US is in fact testing most of those who have caught the virus, and that the fatality rate from the disease is therefore in fact 6%.  I do not believe that to be true (and it would be horrendous if it were), which implies not only that there has been substantial under-testing, but also that the margin of under-testing has not improved.

One might also question whether the six days for a lag that leads to a close fit in this data is too short given what is known about the disease.  But it is consistent with how a “confirmed case” is recorded in the statistics.  It is always based on a lab test for the virus that causes Covid-19, and these tests are only given to patients after they show symptoms (and for many, after possible other causes of those symptoms are ruled out).  But when someone comes down with symptoms, there will always be some lag, on the order of perhaps 2 to 4 days between when the symptoms start and when they seek a test.  There may then be a delay of another day or two before the test is taken.  There will then be another delay between when the test is taken and when the results are found.  Due to the bungled roll-out of testing in the US, these delays have been as long as 9 days (at least in the Washington, DC, area).  Finally, the case is only recorded as a confirmed case to be added to the national statistics on the day the test result is made available, not on the day the test was taken.  A death, when it occurs, is then on average some number of days after that.

A six-day lag found in the data between when cases are confirmed and death occurs (in those cases where it is fatal) is therefore consistent with an estimate (from an article published in The Lancet) that the mean time between when symptoms first appear and death was 17.8 days for those who died.

Another way to look at this relationship is in terms of the growth rates:

Here I have only included the curves for the rates (expressed in growth rates per day, but on a seven-day moving average ending on the date shown) for total confirmed cases, for total deaths, and for the confirmed cases lagged by six days.  They have all fallen substantially over this period, which is of course critically important to the nation – exponential growth at such rates would be disastrous if they did not fall and fall quickly.  And one sees that the daily growth in the number of deaths follows very closely to what the daily growth had been in total confirmed cases six days before.

This falling curves also indicate that social distancing has worked.  Social distancing measures were only put into force starting in mid-March, and were then often substantially strengthened over the next week or two as state and local officials saw the number of Covid-19 cases exploding.  By the last week of March the growth in the total number of confirmed cases had then begun to decline (the peak growth rate was 38% a day in the seven-day period ending March 23), with this then falling to 21% a day for the seven-day period ending March 30, and the rest then as shown in the chart.  The growth in the number of deaths then fell similarly, but with a six-day lag.

What does this then imply for the actual number of Covid-19 cases in the US?  As noted above, assuming a six-day lag between when a case is recorded as “confirmed” and when those who will die for the disease do die, leads to a ratio of 6.0% between the number of deaths and number of confirmed cases (six days before).  And also as noted before, the general consensus among epidemiologists, based on what is now known, is that the fatality rate for all those who come down with Covid-19 may be around 1.0% or less.  A good deal of work is underway to try to estimate this better, but it is still early.  One careful estimate, part of the same article published in The Lancet cited before, is that the rate is 0.66%.

Using the 1.0% and 0.66% estimates as a range for what the fatality rate might be for all those who come down with Covid-19, why does the data indicate a ratio of 6.0% in what is observed?  The answer has to be that testing is not capturing a high share of those with the infection.  And while it is not surprising that in the middle of a pandemic the number of cases is being underestimated, what is surprising and significant is the degree of that underestimation for the virus that causes Covid-19.  If the true fatality rate of all those who have the disease is 1.0%, the implication of the 6.0% ratio observed is that the true number of cases in the US is six times higher than what is currently estimated.  And if the true fatality rate is 0.66%, then the true number of cases is nine times higher.  With 633,000 cases as of April 15, that implies the true number of cases is between 3.8 and 5.7 million.

There is both good news and bad news in this.  The good news is that a high share of those infected with the virus may be suffering such mild symptoms (and possibly no symptoms at all) that they do not feel compelled to call a doctor and have a test.  However, with the continued limitations on testing availability there are also many not being tested who clearly should be.  The sum of these two groups together can be easily calculated from the figures.  Simple shares would indicate that those not being tested would be in the range of 83 to 89% of all those infected.  Most of these are probably in the category of those exhibiting mild or even no symptoms, but we will not know how large that share is until the US is testing all those with any symptoms.

The bad news, however, is that those with mild or even no symptoms appear able to pass on the virus to others.  And the person catching the virus from that individual may then suffer severe symptoms.  It all depends on the individual – their genes, age, health condition, and other such factors.

This means that carrying out the testing to identify infected individuals will be far more difficult than would be the case if symptoms were always clear.  But until vaccines are available or effective therapeutics have been developed, there really is no alternative to the traditional public health measures of identification of those infected, isolating those with the disease, tracing all the contacts of those thus identified, and then quarantining all those contacts until it is clear whether or not they have caught the virus.  This will be difficult when a substantial share of those with the disease do not manifest clear symptoms, but is not impossible.  Those who have caught the virus got it from someone, and good public health work can often find them.

This would have been far easier to do if action had been taken immediately, in January, when it was clear that what had happened in Wuhan was serious (one does not impose a full lockdown on a city of 11 million if is it not serious) and the WHO was issuing a series of increasingly urgent warnings (starting from January 5).  Trump, in contrast, famously asserted on January 22, in an interview while at the Davos meetings in Switzerland, that he was not concerned about the virus – that “We have it totally under control”.  He also boasted of having “a great relationship with President Xi” of China, with no problem in cooperation with China on the virus.  “The relationship is very good”, Trump said.

If action had been taken in January or even early February, the US would only have had to deal with on the order of dozens of cases a day.  Identification, isolation, tracing of contacts, and quarantining then would have been far easier than what will now be necessary, when confirmed new cases since April 2 have averaged 30,000 per day.

Social distancing has worked in bringing the growth rate in new cases down to single digits and, with a lag, to a similar slowdown in the growth in fatalities.  But it has been achieved only with an effective shutting down of the economy, with an unemployment rate that is probably now the highest it has been since the Great Depression (we will find out when the April figure is reported at the end of the month).  Trump’s refusal until mid-March to see Covid-19 as the serious threat that it is has come at a tremendous cost.

 

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Update:  April 18, 2020

After I put up this post yesterday, I came across two reports with figures that are broadly consistent with the findings of the analysis.

There are two components leading to undertesting.  One is that a substantial share of those with the symptoms of Covid-19 are not being tested in the US.  The second is that a substantial share of those carrying the virus are asymptomatic or only mildly symptomatic, and hence do not seek a test (or qualify for a test due to the current limits on testing).  However, those carrying the virus can still spread it to others, even if they are asymptomatic.

The two reports are of analyses where they could test 100% of an isolated population, and then see among all those testing positive what share were asymptomatic.  One report was on testing of the 4,800 sailors on the US Navy aircraft carrier Theodore Roosevelt.  Of the 600 sailors who tested positive, roughly 60% did not show symptoms of Covid-19.  If one assumes that those showing no symptoms would not have otherwise been tested, and that perhaps half of those exhibiting symptoms would not have been tested (in the US testing as it is being carried out now), then 80% of those with the virus would not be recorded in the US as a “confirmed case”.

The figure of one-half not seeking a test is, of course, a pure guess, but is not necessarily unreasonable.  If your symptoms are there but moderate (keep in mind that about 80% of the confirmed cases do not require hospitalization – they stay home instead where they self-monitor), it might well be rational for many individuals not to seek a test unless their condition worsens.  Not only do you have to find a testing location, but you will likely need to line up and wait, and stay relatively close to a large number of individuals who are there precisely because they think they have the disease.  There may also be insurance issues, even though the tests are in principle supposed now to be free to the individual.

The other report was on the testing of all 3,000 individuals in an isolated village in Northern Italy.  It found that 50 to 75% of those who tested positive were asymptomatic (why there is a range on this is not clear to me).  They then isolated those who tested positive (88 individuals), and the number of those sick in the village from Covid-19 fell to seven in less than 10 days.  Hence isolation works well if you can identify all those carrying the virus.  If the share asymptomatic was 50%, and one then assumes that only half of those with symptoms would be tested (under US conditions), then the share of confirmed cases would be just 25% of actual cases.  And if the share asymptomatic was 75%, with half of those with symptoms being tested, then the share of confirmed cases would be just 12.5% of actual cases.

There are limitations, of course, to these analyses.  The samples are not all that large, they are special populations (sailors who are mostly male and mostly aged between 20 and 50, or those living in an isolated village in Italy, where the share elderly may be high), plus the tests were all done at one point in time.  Those asymptomatic at the time of the test may have started to come down with obvious symptoms a few days later.  But while this might apply to some, it is also clear from this and other work that many of those with the disease, but who were tested for some reason (most likely as part of the process of tracing and testing the contacts of those who came down with the disease) never exhibit outward symptoms.

All this suggests that current testing in the US is only capturing a small share of those with the disease.

Trump’s Mismanagement of the Covid-19 Crisis: South Korea Shows What Would Have Been Possible

Source:  David Leonhardt, Newsletter of April 13, 2020, The New York Times

I normally only include charts I have developed myself in this blog, but the chart above, from David Leonhardt of the New York Times, is particularly striking.  It comes from his newsletter of April 13, and shows the daily number of deaths (on a seven-day moving average) per 10 million people, from February 19 to now in the US and in South Korea.

It shows what the US could have achieved had the Trump administration managed this crisis as well as South Korea has.  And one cannot argue that South Korea is a rich country with resources that the US does not have – GDP per capita in the US is double that of South Korea.  Nor is it because of travel bans.  Trump repeatedly asserts that the crisis would have been far greater in the US had he not had the singular wisdom to impose a ban on travel (by non-US citizens) from China on February 2 (and from Europe and other countries later).  But the only travel ban South Korea has imposed has been travel from Hubei Province in China.  And South Korea has far more contact with China, from both business and personal travel and trade in goods, than the US has.  Yet despite this, the deaths from Covid-19 have been far fewer in South Korea than in the US even after scaling for population.

And it is not only South Korea that has demonstrated competence in the management of the Covid-19 virus.  Death rates in other countries of East Asia, all similarly heavily exposed to China, have been even lower than that of South Korea.  In terms of the cumulative number of deaths from Covid-19 since the crisis began (as of April 13), there have been 4 deaths per million of population in South Korea, but just 2 per million in Singapore, 1 per million in Japan, 0.5 per million in Hong Kong, and 0.3 per million in Taiwan.  For the US, in contrast, the total is 71 per million.  (Reminder:  The chart above tracks deaths per day, not the cumulative total, and shows the figures per 10 million of population.)

This also shows that Trump’s repeated assertion that the deaths suffered in the US were inevitable – that nothing more could have been done – is simply nonsense.  Sadly, it is deadly nonsense.  South Korea shows what could have been done.  Travel bans were not important.  Rather, it was the basic public health measures of large-scale testing, identifying those with the virus or who may have been exposed to the virus, quarantining or isolating those exposed (including self-isolating, along with self-monitoring and regular reporting), and then treating in hospitals those who developed severe symptoms.

None of this is new to public health professionals.  And the US has excellent public health professionals.  What was different in the US was Trump, who refused to listen to them and indeed treated many of those in government as enemies to be attacked (as those with expertise were seen as members of the “deep state”).

The US had prepared plans on what to do should an infectious disease such as Covid-19 threaten.  There was, for example, a major effort to develop such plans in 2006/2007, towards the end of the Bush administration.  The work included running exercises similar to war-games of various scenarios (“table-top” exercises), to see how officials would respond and what the likely outcomes then would be.  These plans were further developed during Obama’s two terms in office.  But the Trump administration then ignored this previous preparation, and indeed took pride in dismantling important elements of it.

Dr. James Lawler, now an infectious disease doctor at the University of Nebraska but then serving in the Bush White House, participated in the 2006/2007 task force.  Over the weekend, the New York Times released a trove of over 80 pages of emails (obtained through a Freedom of Information Act request) of late-January to mid-March from Dr. Lawler and other experts, in and out of government, discussing how to address the crisis.  Particularly telling is a March 12 email from Dr. Lawler in which he said:

“We are making every misstep initially made in the table-tops at the outset of pandemic planning in 2006.  We had systematically addressed all of these and had a plan that would work – and has worked in Hong Kong/Singapore.  We have thrown 15 years of institutional learning out the window …”

Throwing those 15 years of institutional learning out the window has had deadly consequences.

The Rapid Growth in Deaths from Covid-19: The Role of Politics

Deaths from Covid-19 have been growing at an extremely rapid rate.  The chart above shows what those rates have been in the month of March, averaged over seven day periods to smooth out day-to-day fluctuations.  The figures are for the daily rate of growth over the seven day period ending on the date indicated.  The curves start in the first period when there were at least 10 cases, which was on March 3 for the US as a whole.  Hence the first growth rate shown is for the one week period of March 3 to 10.  As I will discuss below, the chart has not only the growth rates for the US as a whole but also for the set of states that Trump won in 2016 and for the set that Clinton won.  They show an obvious pattern.

The data come from the set assembled by The New York Times, based on a compilation of state and local reports.  The Times updates these figures daily, and has made them available through the GitHub site.  And it provides a summary report on these figures, with a map, at least daily.

I emphasize that the figures are of daily growth rates, even though they are calculated over one week periods.  And they are huge.  For the US as a whole, that rate was just over 28% a day for the seven day period ending March 30.  It is difficult to get one’s head around such a rapid rate of growth, but a few figures can be illustrative.  In the New York Times database, 3,066 Americans had died of Covid-19 as of March 30.  If the 28% rate of growth were maintained, then the entire population of the US (330 million) would be dead by May 16.  For many reasons, that will not happen.  The entire population would have been infected well before (if there was nothing to limit the spread) and it is fatal for perhaps 1% of those infected.  And the 99% infected who do not die develop an immunity, where once they recover they cannot spread the virus to others.  For this reason as well, 100% of those not previously exposed will not catch the virus.  Rather, it will be some lower share, as the spread becomes less and less likely as an increasing share of the population develops an immunity.  This is also the reason why mass vaccination programs are effective in stopping the spread of a virus (including to those not able to receive a vaccination, such as very young children or those with compromised immune systems).

So that 28% daily rate of growth has to come down, preferably by policy rather than by running out of people to infect.  And there has been a small reduction in the last two days (the seven day periods ending March 29 and March 30), with the rate falling modestly to 28% from a 30% rate that had ruled since the seven day period ending March 22.  But it has much farther to go to get to zero.

The recent modest dip might be an initial sign that the social distancing measures that began to be put in place around parts of the nation by March 16 are having a positive effect (and where many individuals, including myself, started social distancing some time before).  It is believed that it takes about 4 to 7 days after being infected before one shows any symptoms, and then, in those cases where the symptoms are severe and require hospitalization (about 20% of the total), another several days to two weeks before it becomes critical for those where it will prove fatal.  Hence one might be starting to see the impacts of the policies about now.

But the social distancing measures implemented varied widely across the US.  They were strict and early in some locales, and advisory only and relatively late in other locales.  Sadly, Trump injected a political element into this.  Trump belittled the seriousness of Covid-19 until well into March, even calling Covid-19 a “hoax” conjured up by the Democrats while insisting the virus soon would go away.  And even since mid-March Trump has been inconsistent, saying on some days that it needs to be taken seriously and on others that it was not a big deal.  Fox News and radio hosts of the extreme right such as Rush Limbaugh also belittled the seriousness of the virus.

It is therefore understandable that Trump supporters and those who follow such outlets for what they consider the news, have not shown as much of a willingness to implement the social distancing measures that are at this point the only way to reduce the spread of the virus.  And it shows in the death figures.  The red curve in the chart at the top of this post shows the daily growth rates of fatalities from this virus in those states that voted for Trump in the 2016 election.  While the spread of the virus in these states, many of which are relatively rural, started later than in the states that voted for Clinton, their fatalities from the virus have since grown at a substantially faster pace.

The pace of growth in the states that voted for Clinton has also been heavily influenced by the rapid spread of the virus in New York.  As of March 30, more than half (57%) of the fatalities in the Clinton states was due to the fatalities in New York alone.  And New York is a special case.  With its dense population in New York City, where a high proportion use a crowded subway system or buses to commute to work, with the work then often in tall office buildings requiring long rides in what are often crowded elevators, it should not be surprising that a virus that goes person to person could spread rapidly.

Excluding New York, the rate of increase in the other states that voted for Clinton (the curve in green in the chart above) is more modest.  The rates are also then even more substantially lower than those in the Trump-voting states.

But any of these growth rates are still incredibly high, and must be brought down to zero quickly.  That will require clear, sustained, and scientifically sound policy, from the top.  But Trump has not been providing this.

A Very Faint First Sign to be Hopeful on Covid-19: Except Not Yet for the US

Source:  New York Times, “Coronavirus Deaths by U.S. State and Country Over Time:  Daily Tracking”, downloaded March 25, 2020, with deaths reported as of 8:20am on March 25.

As in any epidemic where disease spreads person to person, the number of deaths from the Covid-19 coronavirus has exploded at exponential rates.  An important question is how long it will continue to grow like this.  It cannot continue forever, as one cannot infect more than 100% of the population, and most such diseases are turned around well before that.  But where it will turn around, with a leveling off in the cumulative number of cases, depends not only on the characteristics of the disease (how easily it spreads) but also on policy.  Since there is not yet a vaccine nor a treatment that will always work, the spread of the disease and the number of deaths from it depends on the effectiveness of social distancing measures, so there is less person to person contact and therefore less spread of the virus.  So far, this has been the only effective means to reduce the number of those catching the virus.

And there now appears to be some early evidence that such social distancing measures have helped.  The chart at the top of this post is an excellent graphic prepared by the New York Times, updated daily, which presents on a semi-log scale the cumulative number of deaths from Covid-19 by country, plotted against the number of days since that country’s 25th death.  The Financial Times also presents (and updates daily) a very similar chart, although it presents the results for each country in terms of the number of days since the 10th death.  Both of these news sources are making available this material, and all of their coronovirus coverage, free to anyone, including non-subscribers.  I very much encourage everyone to examine these postings, as there is a good deal of interesting further material (including charts on the number of deaths by national sub-regions, as well as the cumulative number of confirmed cases).  The New York Times charts are also interactive, where they present (for any individual country or region chosen) the rate of growth over the most recent 7 days, i.e. how fast it is growing now.

By presenting the numbers on a semi-log scale (where the vertical axis is logarithmic, while the horizontal axis is in regular linear terms), a path that is a straight line will indicate a constant rate of growth, and the slope of that line will indicate what that rate of growth is (where the steeper the line the higher the rate of growth).  [If you are not familiar with this, review your high school algebra textbook or read through a web post such as this one.]  The faint, gray, straight lines on the chart then show what the total number of deaths would be (for some number of days since the 25th death) if the number of deaths doubled each day, or doubled every 2 days, or doubled every 3 days, or every week, or every month.

There are several interesting findings one can draw from this:

a)  What I found most interesting, and the reason I titled this post as a “First Sign to be Hopeful”, is that for most of the countries (with the US a notable exception), the paths start out quite steep, with doubling times of between every day and every 2 days, but that they then begin to bend over to the right.  That is, they shift over time to a flatter slope, meaning a slowdown in the rate of growth in deaths.  Mainland China, which was hit first, is now (as I write this) at an almost completely flat slope, which means close to a zero rate of growth.  The curve for Italy has also bent over so that it now hits the gray line for doubling every 3 days.  But that does not mean deaths are doubling every 3 days in Italy right now.  Rather, cases were growing at a faster rate in Italy earlier (doubling at about every 2 days at first), and have decelerated to the point where the cumulative number of cases in Italy are now where they would be had they doubled every 3 days throughout.  But the slope now is a good deal less than what it was in the early days.  The New York Times interactive chart indicates that at the pace of the last 7 days, the number of deaths in Italy is now growing at a rate of doubling every 5 days.  And one sees that flattening out in a number of other cases as well, including hard-hit Iran and Spain.

b)  Japan and to a lesser degree South Korea are exceptions in that their recent rates of growth have not fallen.  But both are also exceptions in that their rates of growth, while steady (the path lines are close to straight), have also been a good deal less than that of other countries.  Their doubling times over the last 7 days (as I write this) are both low at 11 days for South Korea and 12 days for Japan.

c)  The US is also a notable exception.  The pace of growth was relatively low for the US for the first 10 days (from when the 25th death was recorded in the US).  Unlike any other country, the pace then accelerated in the US to a doubling time of every 3 days.  Or more precisely, the number of deaths in the US grew from 60 as of day 10 (from when the 25th death was recorded) to 728 deaths on day 19 (March 24).  That is a 32.0% rate of growth per day, or an increase of 2.3 times every 3 days.

Why was the pace of growth relatively modest in the US at first, and then picked up?  That is not clear from these aggregate figures, but might be because the US is a large country, where there have been several centers of outbreak and those centers are relatively distant from each other.  The earliest center was the State of Washington, and the second (and to a more limited degree at first) in California.  Then New York was hit, followed now by major centers in Michigan, Illinois, Florida, Louisiana, and Georgia.  Adding up these varied impacts by locale across the country as a whole (and where doubling times may also vary by locale, especially for New York) may explain the US curve that starts relatively slow, but then accelerates.

Furthermore, with the Trump administration unwilling or unable to provide direction and management at the national level, each state and locality has been left to enact measures on their own and at their own pace.  These have been primarily social distancing measures, but with major differences in how strict they have been structured.  And most of the measures have been enacted reactively, to local cases being confirmed, rather than preemptively.

What is perhaps most disturbing of all for those of us in the US is that there is no indication as yet of the aggregate US curve beginning to bend over to the right.  It has been close to a straight upward line for the last 9 days, growing at a rate of 32% a day.  The only encouraging sign is that the curve for Washington State alone (shown at the New York Times posting) does bend over to the right, similar to what is seen in other countries.  Washington was hit first with the virus, with the initial deaths there, and early on had a doubling time of every 3 days.  But it was then the first state to put in place relatively strict social distancing measures, and the pace of doubling has now dropped to every 9 days (based on deaths over the most recent week).

Overall, the US was late to enacting social distancing measures, with most only put in place over the last week to week and a half.  Their impact on the number of deaths from the virus will then only be seen two or three weeks later, due to the lag from when one catches the virus to when they start to show symptoms (about one week), to when their cases become serious and lead, for some, to death (a further week or two).

Watching whether the US curve starts to bend to the right soon, in the next week or two, will certainly be of interest.