Project One: Sars-CoV-2 Pandemic
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We’ve Lost the Struggle Against Covid-19.
It could have been under control months ago, if Trump had been willing to admit his mistake and started doing things the right way. As the pandemic has gone on (and on), it became more and more clear in my data that quite a few nations were succeeding in their efforts to bring their Covid-19 epidemic under control, where “control” is defined arbitrarily as averaging less than two new cases and/or one death per 100,000 population, over a seven day span. Of the seventeen advanced democracies I was tracking, fourteen were able to meet this definition in no more than 75 days after hitting their peak number of daily new cases and getting to work on prevention. Italy took 75, Germany ___, Australia, Japan, New Zealand, Taiwan and South Korea all less than __. All fourteen successful nations followed the guidelines provided by science. The three that did not succeed (the U.S., Britain, and Sweden) did not follow scientific recommendations and still have not reached the target definitions. Britain is getting close, but the U.S is moving in the other direction, with rapidly increasing numbers of cases and deaths. Lesson #1: Following the advice of science worked every time it was tried. Covid-19 can be reduced to low levels, and this can be done in two months or less. Once control was achieved the successful nations began relaxing their top-down measures, implementing a good tracking and testing program to identify and quarantine remaining infections, and essentially eliminate Sars-Cov-2 as a threat. All four nations now have death rates below .5 per million. Nine have had zero deaths in the past month except when stomping out new cases entering from abroad. But in order for tracking and testing to work effectively the incidence of infection in the population must be low, which means that rates of new cases are under control. Social scientists who have used tracking in social network research know that it is a difficult and labor intensive job. Above a certain point there are just too many people to track, because the number of persons potentially infected by each new case increases exponentially. When the number of persons possibly infected is limited, tracking can catch possible infections quickly and testing can identify new cases before the virus spreads to others. Hence: |
Links to Related Materials
Tracking data for 17 nationsTracking data for the 50 states plus D.C.Methodological issuesUPDATES AND NEW ITEMS:
McKinsey & Company conclude from their global analysis that nations achieve an economic rebound only when their public health response goes "well beyond a simple transient lockdown." Stringent controls are necessary to restore confidence and create the conditions for growth, but what matters is not stringency alone but the will of the nation to sustain the effort until the virus spread is reduced to near zero. Nations that united behind this effort brought the virus under control in two to three months. These nations, and only these nations, are now showing economic recovery in the visible indicators that McKinsey analyzes. This supports the conclusion I reach in example #4 below. Also re: Lying About Covid, Example 4: - Pew Research finds Americans more unhappy about how we handled Covid, and more aware of being divided opposing camps, than any other advanced democracy. [see Pew] - Q2 GDP for Australia revised to -7%. - The Economist"s Global Business Barometer predicts U.S. Q3 GDP will be -24%, compared with -17% global average. |
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Lesson #2: Easing up on a program of controls and replacing it with tracking and testing only works when the level of control has reached safe standards.
Lesson #3 is important for countering arguments that there is a tradeoff between effective action to control the disease and keeping the economy healthy. That myth has been pretty well disposed of by the fact (reality) that although the Swedish government has not even tried to take effective top-down action, their economy has suffered just as much as it has for other rich nations. According to Focus Economics panel of experts, Sweden is right in the middle. Based on current data, its GDP is predicted to decline by 4.7% in the months ahead. Japan is also at -4.7%, Australia at -3.8%, and Taiwan at 0.5%. The U.S comes in at -5.6%, Germany at -6.1%, and France at -9.3%. The implication is that a healthy national economy depends on a healthy population of workers and a healthy world economy. The third is: Lesson #3: The best way to keep an economy going during a pandemic is to bring the virus under control as quickly as possible. Other nations have also found better ways to support workers and small businesses during the crisis, but that is another topic. From what I can tell (and I have looked into it as carefully as I can), and from what I hear from other people who have arrived at the same position, this is the exact truth about how nations can succeed in controlling Covid-19 and the pandemic. What bothers me about other things I read is that journalists seem to have a professional inability to say that something is the truth and all the truth. Truth is so often qualified as “some people feel” or “there are suggestions that.” To imply that truth is fuzzy is, essentially, to not tell the truth about what is true. The problem here is that it weakens the argument and makes it less likely that real action will be taken. Hopefully the winds of synchronicity sweeping over us are bringing everyone to the same conclusion. Which get us to #4: Lesson #4: The situation of the United States right now is a disaster and causes enormous suffering of all kinds. The reason we are in this situation is entirely the fault of Donld J. Trump. We had the same choices as other nations, and the President is charged with making that decision. Everyone makes mistakes, so that is not the worst part of his failure. But real men admit their mistakes when they become irrevocably obvious, and a real president would then try to lead us in a better direction. Trump has done neither except lie, cover up, try to blame others. That is the purest truth, and we should not say or write anything that tries to water it down. He should be confronted with the truth at every moment. As if charging him with crimes against humanity. Parable of virus and humans. A virus epidemic is a competitive struggle between a population of humans and a population of viruses, so to understand epidemics we should look at them from the perspective of the virus. Viruses are complex chemical structures, not living organisms, but they possess a capacity to replicate themselves when the right proteins and other materials are available. Some cells in the human body provide an excellent source of these proteins, and Sars-CoV-2 has evolved ways of entering those cells once they come in contact with them. An epidemic occurs when humans fail to prevent viruses from entering their cells. When we succeed in keeping them out the virus is unable to replicate, its population disintegrates, and the epidemic is under control. Which side is winning the struggle depends entirely on whether viruses succeed in entering enough human bodies to replenish or expand their numbers. Individual humans therefore need to protect themselves, and our whole population needs to work as a team to prevent viruses from infecting anyone – friends and strangers as well as self. For viruses an epidemic is not a struggle. They have no intelligence, no capacity to initiate action. They just bump around following the laws of physics. We humans have a proudly proclaimed capacity for intelligence, so struggling with a virus might seem awfully one-sided. But human intelligence operates by orienting to the world in terms of both physical reality and social reality. These are often in opposition. Our minds construct physical reality comes from our perceptual senses while social reality is composed of ideas. We do things because when our minds process sensory information we try as much as possible to make that information fit with our ideas. Many ideas are very useful for getting around in the world, anticipating future events in time to prepare for them, etc. But we also invent fantasy worlds that seem totally real but may or may not fit well with physical reality. We can live in some fantasy worlds for a long time, but eventually reality will hit us in the face. If we live in a fantasy world that causes more bad results than good ones, that is a negative use of intelligence. The question therefore is, which side wins in a struggle between viruses with zero intelligence and humans operating with negative intelligence? Humans developed science as a disciplined effort to keep the social reality we construct with ideas getting too far out of whack with the physical world we perceive with our senses. As long as we have had written records we find evidence of some people trying to think in the way we call science, but modern science really began to develop during the past six centuries. Science is now our central force in struggles against virus pandemics, so it is fascinating to note that the origins of science in the 14th Century can be traced directly to the terrible epidemics that swept through Europe, including more than one wave of the bubonic plague. The argument is that everything the medical ideas of the time had to say about epidemics was exposed as false by the physical reality that was happening. So thinking about viruses made a fresh start. Social reality ran headlong into physical reality, and modern science began. Six centuries later, of course, we still find science-denial alive and doing its best to obstruct the application of scientific thinking to virus pandemics. It seems that science denial and anti-intellectualism will always be among us. Science denial is right at the core of side of the culture divide that wants to keep America the way they think it was, and that must always be kept in mind when thinking about Covid-19. Controlling Covid: Top-Down and Bottom-Up Approaches. Governments can decree top-down controls that close all sorts of events that gather people together, from movie theaters to businesses to bars, and they can impose lockdowns requiring people to stay at home except under specified circumstances. These are effective, although some are easier to enforce than others. Top-down controls can be unpopular so their purpose needs to be explained well and the length of time they are in effect needs to be kept to a minimum by building an effective program that brings the rate of new infections down as quickly as possible. [Particularly when a top-down measure is difficult to enforce, voluntary support by individual citizens is crucial. and this is where I think our public health & information programs have been lacking – critique. Teamwork. Trust. Taiwan and Finland etc. But this means changes in the whole society, not just public health. We have been weak on voluntary, but it is key to success. Protecting against an epidemic is like protecting against a forest fire. If some people keep throwing cigarette butts out their windows, the danger affects everyone. If some people refuse to wear facemasks, a few of them will without knowing it be infectious, putting the people around them in danger. If some people decide that they will take their chances on infection because they are young and healthy and at low risk of anything serious, quite a few of them will get infected, given the present levels of contagion. The virus will feed on them, probably without harming them much, and produce enormous numbers of new virus. Those will go out into the world looking for new bodies to enter, feed on, and multiply. So anyone who does not make the recommended behavior changes is making more than an individual decision. They are deciding to not be concerned about endangering other people. Struggling against the virus is a team sport, and teams rely on working together. Acknowledgements: The Nations data come from Our World in Data’s Coronavirus Pandemic Data Explorer. The States data come from GitHub’s NYTime/Covid-19 database. |
LYING ABOUT COVID WITH
STATISTICS 101 FOUR EGREGIOUS EXAMPLES Here is a preview of the four examples. Full discussion of each follows. Prevention program success or failure. The mother of all lies about Covid-19 is that our president has done the best he can to control Covid and has succeeded better than most other countries. Data for 17 advanced democracies show without exception that the most effective way for a nation to safeguard its economy is to react quickly to the first signs of a new virus epidemic, immediately institute a science-based prevention program, wait until the incidence of infections is brought down to about 1.0 per 100K population, and then begin relaxing controls. Of the 17 democracies I tracked, 14 followed this path and all 14 successfully controlled Covid, quickly or within a couple of months. The United States did not do this and now has by far the worst track record. [Update: Spain has now blown it and their pandemic now seems to be out of control.] Confirmed cases – up or down? The primary reason for the increasing numbers of confirmed cases of coronavirus in the U.S is not more testing, as Trump and 62% of Republicans polled by Pew Research say. The more important reason, as proper statistical analysis shows, is that many more of the people who were tested were positive. This lie was a cover-up for the totally unnecessary surge of coronavirus cases resulting from Trump's incompetence. The lie was believed by many people, but in this case only 19% of Democrats. Deaths. Trump argued in an interview that because the ratio of deaths to cases (deaths/cases) had been declining slightly, his efforts to control Covid were working. Actually, that only gives you the mortality rate, the rate at which people who contracted Covid during that period died. We do pretty well on that statistic, thanks to dedicated health workers, but it has almost nothing do thing to do with the total number of people dying of Covid. The number of cases increased dramatically during June and July, but deaths usually come 3-5 weeks after infection. Hence, an increase in the death rate does not show up for almost another month. By putting two lies together, Trump has been able to convince many people that he was doing a great job. The economy. Weakening preventive measures intended to control the spread of Covid-19 does not improve the economy, as Republicans state with no evidence as though it is a truism. Rather, nations with good Covid control programs reported better second quarter GDP's overall than nations like the U.S. or Sweden whose governments did nothing. Now one at a time, in more detail:
Lying about Covid with statistics 1 Jonathan Swan’s interview with Trump on August 4 attracted a lot of attention – excerpts seemed to be on television wherever I looked. I mostly watched Chris Cuomo’s hour on CNN. He and his health expert guest did a great job, except that they didn’t seem to really understand what was going on in that interview. It drove me crazy. Such simple matters were causing so much confusion. So here is my attempt to straighten things out. The biggest issue concerned Trump claiming that we had the lowest incidence of deaths from Covid-19 in the world. Swan pointed out that we actually have the highest, certainly among advanced democracies, and asked Trump where he got those figures. Trump handed him the sheets of paper he was reading from. Swan looked at them and immediately said, “Oh you’re taking deaths as a percentage of cases, not as a percentage of population.” Let’s stop right here and look at what is involved, because this is the part that Cuomo and his experts never seemed to really understand. People who get infected with the coronavirus usually become Confirmed Cases, the “cases” statistic. Some of these eventually die and become the “deaths” statistic. You get the percentage of deaths to cases by dividing: #deaths/#cases. That’s the ratio of deaths to cases, and it has been coming down for several reasons: Our wonderful, dedicated health professionals have learned how to keep more patients from dying, so the numerator has been gradually getting smaller. We have gradually been doing more and more testing, which discovers people who didn’t know they had it and may stay asymptomatic. This makes the denominator larger, and the deaths/cases ratio smaller. More of the people who test positive are young; young people are less likely to die, so the denominator increases with little change to the numerator. As a result, the mortality rate among confirmed cases came down from about eight percent to less than five, probably less than four percent now. However, the total number of deaths ultimately depends on how many cases you have. Number of cases is usually expressed as cases per 100,000 population, so that you can compare large nations with small nations or New Mexico with California. We presently have a pandemic raging through America, and our cases per 100K is now more than twenty times larger than other rich democracies. A larger number of cases means that more people are going to die, typically in three to five weeks. The fact that the deaths/cases ratio has been reduced means that half as many people who are known to have caught Covid will die as would have four months ago. But because twenty times as many Americans are becoming Cases as in other countries, we have ten times as many people dying. So that is the confusion – we do great with people once they catch Covid, but we have doomed the entire country to be much more likely to catch it. I find it easier to look at graphs than to read the information as text, so here is how I prepare the data. Each graph shows the number of new cases per 100,000 population each day from March 1 to August 3. – 151 days. The height of each graph is adjusted so the scale of new cases is about the same for all graphs. Hence the first graph is very squat. Nations that responded immediately and kept their initial surge low brought case rates down to zero or near zero within thirty days after their peak. They are still vulnerable to new infections, mostly coming in from other countries. Australia is a good example. But note that Australia is still below two cases per 100K, so they have time to tamp down their controls. 
Nations that responded early enough to keep their peaks moderate brought their infection rate down to below one new case per 100K within about fifty days. They had enough time before Covid-19 hit to see what was happening in Italy and get serious about controls. Germany is particularly important because geographically it belongs with France, Italy, etc. but it responded more like the Scandinavian countries - quickly and thoroughly.
Italy, as we all know, got hit early and hard, but was able to limit its peak to nine new cases per 100K. Spain didn’t peak until reaching 17 new cases per 100K. All were able to bring their rates down to below one per 100K within 75 days. They have had trouble keeping them there, but all have remained below two per 100K except Spain. But even here, Spain is currently at about five per 100K, which means that the number of potentially infectious people walking around in Spain is still low enough to be controlled with renewed effort. France and Canada had patterns similar to but more moderate than Italy.
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The moral of the story so far is that the U.S. has been doing a terrible job of responding to the Covid-19 pandemic, with the result that our new cases per day are incredibly high. New cases drive everything else, so we are stuck in prolonged suffering for no good reason at all – it is completely clear that if a nation does the right things it can stop Covid cold, in a month. The real issue is not only statistical confusion but everything that keeps us from changing what we do to pursue a rational course of action.
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Lying about Covid with statistics 2
Recent polling by Pew Research asked whether the “primary reason there are increasing numbers of confirmed cases of coronavirus in the U.S.” was:
a) “More people are being tested than in previous months,” or
b) “There are more new infections, not just more tests.”
Overall, 39 percent chose (a) and 60 percent chose (b). However, among Republicans 62% chose (a) and 36% chose (b), while among Democrats 19% chose (a) and 80% chose (b). That is a big difference. It means that members of each political party hold not only different opinions, but different beliefs about what is true. Believing that something is true when it is not true leads to political decisions that are likely to have bad results. So it is important to look at this carefully.
The relation between confirmed cases, number of tests given, and the percentage of tests that are positive is given by a simple equation:
#Cases = #Tests * %Positive.
If you multiply the number of tests given each day by the percent that were positive, you have the number of confirmed cases. This is a tautology, but it is useful - we can decompose #Cases into #Tests (for which there is data) and %Positive (for which there is also data). This allows us to look at #Tests and %Positive separately and estimate of the relative effect each had on #Cases during a given period of time, thus answering with data the question of whether (a) or (b) is correct.
The chart below shows #Cases, #Tests, and %Positive each day from April 10 to August 13. We want to look at how they change over time, so we can see what happens when #Tests goes up or down and when %Positive goes up or down. There were three different patterns, each for a different time period, because the background situation kept changing.
Recent polling by Pew Research asked whether the “primary reason there are increasing numbers of confirmed cases of coronavirus in the U.S.” was:
a) “More people are being tested than in previous months,” or
b) “There are more new infections, not just more tests.”
Overall, 39 percent chose (a) and 60 percent chose (b). However, among Republicans 62% chose (a) and 36% chose (b), while among Democrats 19% chose (a) and 80% chose (b). That is a big difference. It means that members of each political party hold not only different opinions, but different beliefs about what is true. Believing that something is true when it is not true leads to political decisions that are likely to have bad results. So it is important to look at this carefully.
The relation between confirmed cases, number of tests given, and the percentage of tests that are positive is given by a simple equation:
#Cases = #Tests * %Positive.
If you multiply the number of tests given each day by the percent that were positive, you have the number of confirmed cases. This is a tautology, but it is useful - we can decompose #Cases into #Tests (for which there is data) and %Positive (for which there is also data). This allows us to look at #Tests and %Positive separately and estimate of the relative effect each had on #Cases during a given period of time, thus answering with data the question of whether (a) or (b) is correct.
The chart below shows #Cases, #Tests, and %Positive each day from April 10 to August 13. We want to look at how they change over time, so we can see what happens when #Tests goes up or down and when %Positive goes up or down. There were three different patterns, each for a different time period, because the background situation kept changing.
Through two months after the initial peak, until about day 90, #Tests increased but %Positive dropped even faster, with the result that the number of new cases each day declined slightly. So the correct explanation during this time period is (b) - the decline in positives caused the rate of new cases to also decline. New York and neighboring states were bringing Covid under control in a way similar to Italy and Spain – very high initial peaks, declining in about two months to the 1.0 standard of control. During this time Covid was still fairly quiet in the rest of the country.
Then %Positives began going back up, slightly faster than the rate at which it had been coming down. Meanwhile testing continued to increase at the same rate as before. Between day 92 and day 130 (June 9 to July 9) #Tests increased by 57 percent or approximately 1.9% per day. %Positives rose by 79 percent or approximately 2.6% per day. With the two acting together, #Cases shot up dramatically. Therefore, both increased testing and higher percentages of infection both played a role, but the rapid spread of infections through southern states and across to Arizona had even more impact. The correct explanation for what happened during this time period is therefore (b).
On day 139 testing peaked and began to decline, dropping from 24.7 to 20.8 tests per 10,000 or 16 percent. Tests that were positive decreased only slightly during that period, from 8.3% to 7.7%, a seven percent drop. So the decline in cases was primarily caused by the decrease in testing, not by reducing the incidence of infection in the population, and this time the correct answer is (a). Trump had actually said that he wanted to reduce support for the testing program so he would look better because fewer confirmed cases would be identified.
Finally, from day 152 to 164 #Tests ceased dropping while %Positive went down 19 percent. Number of new cases went down at the same rate, 19 percent, as the equation predicts, so the correct answer is again (b). Credit must be given to the re-institution of control programs by state governments.
This part of the story is still under way. But overall it is clear that both the size of testing programs and the incidence of coronavirus infection can impact the number of cases. Most people, however, would agree that responsible governments should try to keep their testing programs running effectively and not cut them back for political purposes.
Late Breaking News (August 25): The CDC has decided that tests will not be given to people without symptoms. More than 90 percent of people now tested are negative, so excluding most of them would save a little money. It will also exclude people who are asymptomatic or were infected in the last two days but have not developed symptoms. This procedure will identify fewer cases, but the positives it fails to identify will nevertheless be able to pass the virus on to other people. As a consequence we will have a large group of people free to spread coronavirus to the population at large. What is the logic behind this, other than making Trump look better by temporarily lowering the official number of confirmed cases?
Then %Positives began going back up, slightly faster than the rate at which it had been coming down. Meanwhile testing continued to increase at the same rate as before. Between day 92 and day 130 (June 9 to July 9) #Tests increased by 57 percent or approximately 1.9% per day. %Positives rose by 79 percent or approximately 2.6% per day. With the two acting together, #Cases shot up dramatically. Therefore, both increased testing and higher percentages of infection both played a role, but the rapid spread of infections through southern states and across to Arizona had even more impact. The correct explanation for what happened during this time period is therefore (b).
On day 139 testing peaked and began to decline, dropping from 24.7 to 20.8 tests per 10,000 or 16 percent. Tests that were positive decreased only slightly during that period, from 8.3% to 7.7%, a seven percent drop. So the decline in cases was primarily caused by the decrease in testing, not by reducing the incidence of infection in the population, and this time the correct answer is (a). Trump had actually said that he wanted to reduce support for the testing program so he would look better because fewer confirmed cases would be identified.
Finally, from day 152 to 164 #Tests ceased dropping while %Positive went down 19 percent. Number of new cases went down at the same rate, 19 percent, as the equation predicts, so the correct answer is again (b). Credit must be given to the re-institution of control programs by state governments.
This part of the story is still under way. But overall it is clear that both the size of testing programs and the incidence of coronavirus infection can impact the number of cases. Most people, however, would agree that responsible governments should try to keep their testing programs running effectively and not cut them back for political purposes.
Late Breaking News (August 25): The CDC has decided that tests will not be given to people without symptoms. More than 90 percent of people now tested are negative, so excluding most of them would save a little money. It will also exclude people who are asymptomatic or were infected in the last two days but have not developed symptoms. This procedure will identify fewer cases, but the positives it fails to identify will nevertheless be able to pass the virus on to other people. As a consequence we will have a large group of people free to spread coronavirus to the population at large. What is the logic behind this, other than making Trump look better by temporarily lowering the official number of confirmed cases?
Lying about Covid with statistics 4
It is often stated, as if it was obviously true and needed no supporting evidence, that the Covid prevention programs recommended by science cause a nation’s economy to decline. This is may be true to some extent, but it is also possible that the sickness called Covid-19 by itself causes reductions in economic activity. People who are sick, even if they don’t stay home or become hospitalized, are probably not working at their best. Another consideration is that a nation’s economy is intimately dependent on its trading partners. If economies are depressed through the world, all are going to suffer together no matter what their control program involves. So what is really going on?
Gross Domestic Product second quarter reports are now out, so it is possible to examine the relationship between Covid prevention programs and GDP. This is shown in the table below. Almost all of the 17 nations I track reported negative GDP growth (Australia stayed barely afloat at 0.3). The potential impact of prevention programs is measured by the height at which each nation’s New Cases curve peaked. These peaks usually happened early, as the novel coronavirus took people by surprise and spread rapidly. Most countries then put in place serious prevention programs. The effects of the control programs on economies starts at the time of the peak and continues until the program has been effective in bringing the incidence of new cases down to less than 1.0 per 100,000 population per day. At this point controls can be safely relaxed and remaining infectious sources for spreading coronavirus can be controlled through tracking and testing programs rather than closely down sections of the economy.
As the table below indicates, nations that started their programs early were able to keep their peaks low, and suffered less from economic decline. Similarly, many nations reduced their new case rates to 1.0 quite quickly, often in less than one month, and these nations’ economies also suffered less. The correlation between peak number of new cases and GDP is -.70. For the number of days it took to bring the new cases curve from it peak to 1.0, r = -57. The r's are negative because for both variables better control is measured by shorter recovery periods. Nations that reacted quickly to the dangers of Covid kept their peaks lower, which also made it easier to bring their new case curve down to 1.0. Conclusion: the best was to keep an economy healthy during a virus pandemic is to start a good prevention program as quickly as possible. The opposite of what the United States has done. More evidence for that is emerging. Still more evidence: The Economist's Global Business Barometer predicts U.S. Q3 GDP will be -24%, compared with -17% global average.
Updates: Australia's Q2 GDP revised to -7%]
McKinsey & Company conclude from their global analysis that nations achieve an economic rebound only when their public health response goes "well beyond a simple transient lockdown." Stringent controls are necessary to restore confidence and create the conditions for growth, but what matters is not stringency alone but the will of the nation to sustain the effort until the virus spread is reduced to near zero. Nations that united behind this effort brought the virus under control in two to three months. These nations, and only these nations, are now showing economic recovery in the visible indicators that McKinsey analyzes. This supports the conclusion I reach in example #4 below.
Also re: Lying About Covid, Example 4:
- Pew Research finds Americans more unhappy about how we handled Covid, and more aware of being divided opposing camps, than any other advanced democracy. [see Pew]
- The Economist"s Global Business Barometer predicts U.S. Q3 GDP will be -24%, compared with -17% global average.
It is often stated, as if it was obviously true and needed no supporting evidence, that the Covid prevention programs recommended by science cause a nation’s economy to decline. This is may be true to some extent, but it is also possible that the sickness called Covid-19 by itself causes reductions in economic activity. People who are sick, even if they don’t stay home or become hospitalized, are probably not working at their best. Another consideration is that a nation’s economy is intimately dependent on its trading partners. If economies are depressed through the world, all are going to suffer together no matter what their control program involves. So what is really going on?
Gross Domestic Product second quarter reports are now out, so it is possible to examine the relationship between Covid prevention programs and GDP. This is shown in the table below. Almost all of the 17 nations I track reported negative GDP growth (Australia stayed barely afloat at 0.3). The potential impact of prevention programs is measured by the height at which each nation’s New Cases curve peaked. These peaks usually happened early, as the novel coronavirus took people by surprise and spread rapidly. Most countries then put in place serious prevention programs. The effects of the control programs on economies starts at the time of the peak and continues until the program has been effective in bringing the incidence of new cases down to less than 1.0 per 100,000 population per day. At this point controls can be safely relaxed and remaining infectious sources for spreading coronavirus can be controlled through tracking and testing programs rather than closely down sections of the economy.
As the table below indicates, nations that started their programs early were able to keep their peaks low, and suffered less from economic decline. Similarly, many nations reduced their new case rates to 1.0 quite quickly, often in less than one month, and these nations’ economies also suffered less. The correlation between peak number of new cases and GDP is -.70. For the number of days it took to bring the new cases curve from it peak to 1.0, r = -57. The r's are negative because for both variables better control is measured by shorter recovery periods. Nations that reacted quickly to the dangers of Covid kept their peaks lower, which also made it easier to bring their new case curve down to 1.0. Conclusion: the best was to keep an economy healthy during a virus pandemic is to start a good prevention program as quickly as possible. The opposite of what the United States has done. More evidence for that is emerging. Still more evidence: The Economist's Global Business Barometer predicts U.S. Q3 GDP will be -24%, compared with -17% global average.
Updates: Australia's Q2 GDP revised to -7%]
McKinsey & Company conclude from their global analysis that nations achieve an economic rebound only when their public health response goes "well beyond a simple transient lockdown." Stringent controls are necessary to restore confidence and create the conditions for growth, but what matters is not stringency alone but the will of the nation to sustain the effort until the virus spread is reduced to near zero. Nations that united behind this effort brought the virus under control in two to three months. These nations, and only these nations, are now showing economic recovery in the visible indicators that McKinsey analyzes. This supports the conclusion I reach in example #4 below.
Also re: Lying About Covid, Example 4:
- Pew Research finds Americans more unhappy about how we handled Covid, and more aware of being divided opposing camps, than any other advanced democracy. [see Pew]
- The Economist"s Global Business Barometer predicts U.S. Q3 GDP will be -24%, compared with -17% global average.
BASEBALL ALERT
U.S. fans were cardboard.
U.S. fans were cardboard.
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The Taiwanese people were able to control Covid-19 early and began relaxing their prevention measures months ago. Their baseball stands filled up again.
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U.S. fans remained cardboard. |
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Background:
Understanding the general human-virus context within which these statistical lies take place.
First I need to briefly describe my understanding of virus epidemics. Viruses are not living organisms. They are complex chemical structures that can reproduce themselves, maybe halfway between crystals and bacteria. When viruses come in contact with certain human cells they enter them and replicate themselves in huge numbers. These new coronaviruses leave the cell and are ready for circumstances to bring them into contact with fresh bodies. Viruses win an epidemic by multiplying faster than they disintegrate (which can happen in one minute or several weeks). Humans win an epidemic by not allowing viruses to enter human bodies, theirs or someone else’s. Science has gradually worked out good ways for humans to prevent viruses from entering. Nations that have been successful in getting all or almost all of their population to behave according to these guidelines, whether by laws and law enforcement, by closing businesses and public institutions, or by securing the voluntary cooperation of the public, have eliminated the virus from their territory except for the occasional hidden pocket or new invasions from outside. Tracking and testing works well when there are not too many cases to track effectively. It’s like bailing water from a boat you are sailing. If it’s a small leak you can control it, hopefully get all the water out. If the water is coming in over the gunnels or from a big crack in the hull, bailing is quickly going to become futile. Better try to fix the boat first.
The big question then is whether a nation responds to Covid with action known to be effective, or does something else. And in order for a program to be effective, the people of that nation, led by their chief executive, must muster the will and unity of spirit to cooperate fully in following its guidelines. Since our leader, Donald Trump, does not sympathize with science-based programs and has decided to delegate responsibility for Covid to the states and their governors, we have had divisiveness rather than unity, a strong will in some states but opposition in others, and cooperation only between the governors of states trying to implement science-based programs. Equally important, within every state we have opposition between rival factions of a culture war America has never, for 230 years, been able to resolve. Rather than encourage voluntary cooperation, Trump has been busy politicizing even those mindless little viruses. Viruses couldn’t care less about the politics, but dividing a nation of humans against itself has allowed them to win.
Now for the first fascinating event of Swan’s interview with Trump. After Swan told Trump that we actually have one of the highest death rates from Covid, Trump said, “No it’s all right here” and handed Swan some print-outs. Swan looked at them and said, “Oh, you’ve taken deaths relative to cases, when you should take them relative to population.” Trump then said, essentially, “No, that can’t be. It says right here that dividing deaths by cases shows that we have the lowest death rate in the world.” Clearly Trump did not understand what was going on at all, but put his faith in the fact that these pages were given to him, in writing, by the staff of “experts” who concoct his statistical lies. (Who are they?) The belief that truth comes from authority rather than analysis is typical of authoritarian leaders and their followers.
I submit therefore, as theory to carry forward from this analysis, that someone who uses only spontaneous, intuitive thinking, as Trump proudly proclaims that he does, has lost the capability of holding complex representations in his mind while examining them. Intuitive thinking lives only in the present. It can’t stop to reflect or use rational analysis for evaluating truth because that is no longer the present. One must surge ahead without any of that kind of thinking. If you look at Trump from this perspective, the things he says are not so much lies as part of a flow of consciousness that just accepts whatever words feel right at the moment. To think about whether a statement is a lie or not a lie requires comparing it with alternative statements and referring to a standard that allows judging between them. Trump has no time for any of those things.
Living in the present is very enjoyable. As a longtime meditator I’ve worked hard to be able to enjoy that experience. But to go through life without ever pausing to reflect or analyze would create a very strange kind of human being. Trump seems to have mastered intuitive thinking and combined it with narcissism and a touch of psychopathy in a way that few humans achieve. We have a chance to examine a world-class con man up close and personal. Although unfortunately he is also our president.
The second fascinating event in the interview occurred when Swan was arguing that if America undertook a good science-based antivirus program, we still have time to bring Covid under control. As a key part of this argument he pointed out that Trump has millions of devoted followers who will do anything he says. Why, he asked, did Trump not urge his followers to join with other millions of Americans and cooperate in voluntarily following science’s guidelines? It would be a success and he would be celebrated as a great man. Voluntary cooperation is the very heart of a successful antiCovid program, and, theoretically of course, that suggestion could work.
Trump makes us ask what kind of insanity we are living in. Thousands of people dying unnecessarily, the economy crashing, millions of people suffering from hunger and the other suddenly imposed torments of joblessness and being without insurance. And few people, although more and more every day, pointing out that the only reason for it is Trump. As Nancy Pelosi pointe out in this morning’s news, he is so skillful at diversionary tactics, somehow getting us to believe that lies and truths are all relative, that we lose track of what he is really doing. Trump told us in Times Square that he can do whatever he wants and get away with it. He is now limping toward the elections with that flag still flying.
Understanding the general human-virus context within which these statistical lies take place.
First I need to briefly describe my understanding of virus epidemics. Viruses are not living organisms. They are complex chemical structures that can reproduce themselves, maybe halfway between crystals and bacteria. When viruses come in contact with certain human cells they enter them and replicate themselves in huge numbers. These new coronaviruses leave the cell and are ready for circumstances to bring them into contact with fresh bodies. Viruses win an epidemic by multiplying faster than they disintegrate (which can happen in one minute or several weeks). Humans win an epidemic by not allowing viruses to enter human bodies, theirs or someone else’s. Science has gradually worked out good ways for humans to prevent viruses from entering. Nations that have been successful in getting all or almost all of their population to behave according to these guidelines, whether by laws and law enforcement, by closing businesses and public institutions, or by securing the voluntary cooperation of the public, have eliminated the virus from their territory except for the occasional hidden pocket or new invasions from outside. Tracking and testing works well when there are not too many cases to track effectively. It’s like bailing water from a boat you are sailing. If it’s a small leak you can control it, hopefully get all the water out. If the water is coming in over the gunnels or from a big crack in the hull, bailing is quickly going to become futile. Better try to fix the boat first.
The big question then is whether a nation responds to Covid with action known to be effective, or does something else. And in order for a program to be effective, the people of that nation, led by their chief executive, must muster the will and unity of spirit to cooperate fully in following its guidelines. Since our leader, Donald Trump, does not sympathize with science-based programs and has decided to delegate responsibility for Covid to the states and their governors, we have had divisiveness rather than unity, a strong will in some states but opposition in others, and cooperation only between the governors of states trying to implement science-based programs. Equally important, within every state we have opposition between rival factions of a culture war America has never, for 230 years, been able to resolve. Rather than encourage voluntary cooperation, Trump has been busy politicizing even those mindless little viruses. Viruses couldn’t care less about the politics, but dividing a nation of humans against itself has allowed them to win.
Now for the first fascinating event of Swan’s interview with Trump. After Swan told Trump that we actually have one of the highest death rates from Covid, Trump said, “No it’s all right here” and handed Swan some print-outs. Swan looked at them and said, “Oh, you’ve taken deaths relative to cases, when you should take them relative to population.” Trump then said, essentially, “No, that can’t be. It says right here that dividing deaths by cases shows that we have the lowest death rate in the world.” Clearly Trump did not understand what was going on at all, but put his faith in the fact that these pages were given to him, in writing, by the staff of “experts” who concoct his statistical lies. (Who are they?) The belief that truth comes from authority rather than analysis is typical of authoritarian leaders and their followers.
I submit therefore, as theory to carry forward from this analysis, that someone who uses only spontaneous, intuitive thinking, as Trump proudly proclaims that he does, has lost the capability of holding complex representations in his mind while examining them. Intuitive thinking lives only in the present. It can’t stop to reflect or use rational analysis for evaluating truth because that is no longer the present. One must surge ahead without any of that kind of thinking. If you look at Trump from this perspective, the things he says are not so much lies as part of a flow of consciousness that just accepts whatever words feel right at the moment. To think about whether a statement is a lie or not a lie requires comparing it with alternative statements and referring to a standard that allows judging between them. Trump has no time for any of those things.
Living in the present is very enjoyable. As a longtime meditator I’ve worked hard to be able to enjoy that experience. But to go through life without ever pausing to reflect or analyze would create a very strange kind of human being. Trump seems to have mastered intuitive thinking and combined it with narcissism and a touch of psychopathy in a way that few humans achieve. We have a chance to examine a world-class con man up close and personal. Although unfortunately he is also our president.
The second fascinating event in the interview occurred when Swan was arguing that if America undertook a good science-based antivirus program, we still have time to bring Covid under control. As a key part of this argument he pointed out that Trump has millions of devoted followers who will do anything he says. Why, he asked, did Trump not urge his followers to join with other millions of Americans and cooperate in voluntarily following science’s guidelines? It would be a success and he would be celebrated as a great man. Voluntary cooperation is the very heart of a successful antiCovid program, and, theoretically of course, that suggestion could work.
Trump makes us ask what kind of insanity we are living in. Thousands of people dying unnecessarily, the economy crashing, millions of people suffering from hunger and the other suddenly imposed torments of joblessness and being without insurance. And few people, although more and more every day, pointing out that the only reason for it is Trump. As Nancy Pelosi pointe out in this morning’s news, he is so skillful at diversionary tactics, somehow getting us to believe that lies and truths are all relative, that we lose track of what he is really doing. Trump told us in Times Square that he can do whatever he wants and get away with it. He is now limping toward the elections with that flag still flying.
CONCLUSIONS
There is only one simple, clear, obvious conclusion. In all my years of analyzing data I have seldom seen a conclusion so close to 100 percent certain. Scientists are cautious about these things, but the data speak for themselves at better than .00001 confidence level. We are in a terrible mess solely because we did the wrong things. Many wrong things. The choice between doing something right or doing it wrong was always Donald Trump’s. We could still change, but Trump seems to be pathologically unable to admit he has ever done anything wrong, so we will continue to suffer and endure until at least November 3, and more likely January 20. What we can do, and what it would be ridiculous and almost immoral not to do, is focus passionately on that conclusion. This applies especially to the media, but also to everyone of us whenever we find ourselves in conversations about Covid. People are awakening to this all over America. The Swan interview got a lot of attention because he at least tried to call out Trump on where he got his absurd statistics. A more forceful statement since then was Nancy Pelosi’s response during an Andrea Mitchell interview.
The most important fact, once you get the statistics straight, is that we are still doing the same wrong things to control Covid. The most important question is why we are still doing them, since their failure was clear at least by early June. The obvious answer is that Trump started out doing the wrong things, has never changed anything, and will not admit any error. He has been able to get away with all this while keeping his core happy and somehow keeping his opposition immobilized. We are learning about how he does this. Driven by his powerful drive to dominate he has been able to lie, dodge and divert most efforts to hold him accountable. Most of us can only watch his performances over television or internet. The chosen few who get to interact with him one-on-one carry the responsibility to represent all those of us not in his core. They have found interviewing or questioning him frustrating, and we who watch have found it agonizing to see him neutralize efforts to uncover the truth and neuterize the people trying.
That has been changing. There have been some semi-successful efforts recently and pushing hard to get to the source of the statistics he is lying with has been shown to help. But this is hit or miss. What we really need to do now (and by “we” I mean the people who have a chance to confront him in person and their organizations) is apply sabermetric statistical analysis as done in sports to events where people go head to head with Donald Trump. Nancy Pelosi is clearly the virtuoso all star here. Go over footage of her in action frame by frame. How does she do it? What are the weaknesses she senses and how does she respond? Clearly summoning a tremendous aura of power in an attempt to match Trump’s display is only one possible strategy. Jiu jitsu may be in order, or just throwing him off balance, using selected bait and switch moves. We have to know what we’re doing. There isn’t much time before the October debates, and our print and television journalists have a lot of training camp work to do.
There is only one simple, clear, obvious conclusion. In all my years of analyzing data I have seldom seen a conclusion so close to 100 percent certain. Scientists are cautious about these things, but the data speak for themselves at better than .00001 confidence level. We are in a terrible mess solely because we did the wrong things. Many wrong things. The choice between doing something right or doing it wrong was always Donald Trump’s. We could still change, but Trump seems to be pathologically unable to admit he has ever done anything wrong, so we will continue to suffer and endure until at least November 3, and more likely January 20. What we can do, and what it would be ridiculous and almost immoral not to do, is focus passionately on that conclusion. This applies especially to the media, but also to everyone of us whenever we find ourselves in conversations about Covid. People are awakening to this all over America. The Swan interview got a lot of attention because he at least tried to call out Trump on where he got his absurd statistics. A more forceful statement since then was Nancy Pelosi’s response during an Andrea Mitchell interview.
The most important fact, once you get the statistics straight, is that we are still doing the same wrong things to control Covid. The most important question is why we are still doing them, since their failure was clear at least by early June. The obvious answer is that Trump started out doing the wrong things, has never changed anything, and will not admit any error. He has been able to get away with all this while keeping his core happy and somehow keeping his opposition immobilized. We are learning about how he does this. Driven by his powerful drive to dominate he has been able to lie, dodge and divert most efforts to hold him accountable. Most of us can only watch his performances over television or internet. The chosen few who get to interact with him one-on-one carry the responsibility to represent all those of us not in his core. They have found interviewing or questioning him frustrating, and we who watch have found it agonizing to see him neutralize efforts to uncover the truth and neuterize the people trying.
That has been changing. There have been some semi-successful efforts recently and pushing hard to get to the source of the statistics he is lying with has been shown to help. But this is hit or miss. What we really need to do now (and by “we” I mean the people who have a chance to confront him in person and their organizations) is apply sabermetric statistical analysis as done in sports to events where people go head to head with Donald Trump. Nancy Pelosi is clearly the virtuoso all star here. Go over footage of her in action frame by frame. How does she do it? What are the weaknesses she senses and how does she respond? Clearly summoning a tremendous aura of power in an attempt to match Trump’s display is only one possible strategy. Jiu jitsu may be in order, or just throwing him off balance, using selected bait and switch moves. We have to know what we’re doing. There isn’t much time before the October debates, and our print and television journalists have a lot of training camp work to do.
