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This current blog, the second one in this sequence on covid-related buzzwords, deals with the rampantly and uncritically used term "immunity, " often made more authoritative by the combination of "herd immunity". There are experts and pundits who would pontificate on TV that herd immunity is the only hope for humanity against the SARS-COV2 virus. It is of course a truism, eventually immunity will happen in some form, the question is how long that would take, how long such immunity will last, and what fraction of the population must develop immunity (and for how long) before the spread of the disease is under control. Most importantly, how many people will die from it in the process. We do not know the answer to any of these questions. No expert can answer any of these questions at any level of confidence.
Having simulated SARS-COV2 infection rates using toy lattice models searching for phase transitions to zero infection, I found that everything depends on the choice of parameters so sensitively that no mathematical statement independent of biology, demography, and sociology can be made. For example, in a completely isolated population, the disappearance may depend on such obvious parameters as the population density, the total population, the age distribution, the assumptions regarding fatality, or the temporal duration of the immunity among other parameters. But it also depends on more non-obvious parameters, such as human interactions and the community's health habits, which are rather difficult to parametrize in simulations (and in real life). Most importantly, of course, isolated communities are not relevant in today's world. Once the system is open to the outside world anything can happen depending on the mobility of people in and out of the system.
It is no different in this sense from trying to simulate an interactive physical system open to the environment. It simply cannot be done unless we make drastic assumptions about the environment, which are unlikely to apply to real life scenarios. Such assumptions about the environment while dealing with open systems are common in physics' simulations, they are often made uncritically based on the available computing resources. While in physics it is acceptable to do this, since nothing really is at stake (except perhaps what the reviewers in the journal would say about these assumptions), for covid-19, knowing the necessary boundary conditions are essential for making any reasonable mathematical statement about the threshold for herd immunity. I basically gave up after realizing that I can get any threshold I choose down to 50% by adjusting the environmental conditions. Other adjustments of parameters produce a threshold for herd immunity as high as almost 100%!
A particularly telling example in this context is what just happened in Croatia, a country that managed to bring its covid-19 infections down to zero in May, an impressive achievement in a country of 4 million people at the center of Europe. We could compare it with the state of Maryland in the US with a population of 6 million, where the covid-19 infection rate was roughly1000 per day in May, and is still around 600 per day, never going below 400 per day during the whole April-September period. After this astounding success of suppressing covid-19, Croatia decided to open up in June with a huge number of tourists coming in from the near-by European countries of Germany, Czech Republic, and Austria. What happened then as Croatia lifted lockdown and became an open system for all Europeans to visit its bars and beaches? Its number of covid-19 infections started growing right away, as some of the tourists brought covid-19 infections with them, and reached almost 300 per day on September 4, its highest covid infection number so far. Below I depict the covid-19 cases in Croatia (top) along with the tourist influx starting in July from three European countries (bottom). Note that the tourist influx in 2020 is only around 50% of that in 2019. This is not the end of the story. All the visitors to Croatia from other European countries eventually went back home after their Croatian vacations, taking the gift of covid with them. Immediately there were covid flare ups in Germany, Austria, and the Czech Republic, directly connected to people returning from Croatia! This is the problem of making any quantitative statement about the required level of immunity in a community to achieve the so-called "herd immunity". In any open society the herd is the whole world and one must consider global immunity, this is made more complicated as the whole world is so heterogeneous.
Herd immunity refers to a situation where a certain infection is under control in a community by virtue of the fact that a large fraction of the community is immune to it because they have already been infected. So, herd immunity is immunization without vaccination as it arises from direct exposure to the infection. Both vaccines and herd immunity work the same way, but vaccines work on single individuals and herd immunity works on a whole community ("the herd"). All the limitations of vaccines I discussed in my last blog apply to the herd immunity concept too, except now it impacts the whole community, not just single individuals. The most important questions are: (1) What is the minimum fraction of a community (this is the immunity "threshold") that must be immune for the whole community to be immune? (2) How long does this herd immunity last if individual immunity to the SARS-COV2 virus lasts only a month or two?
Both questions can be answered by simulations for an isolated community if we make assumptions about the duration of individual immunity and social interactions in the particular isolated community. For example, if 100% of the community has developed long-lasting immunity, the whole community is obviously safe from further infections! It is easy to see that the fraction does not need to be 100% for the infection to eventually disappear since the exponential infection growth occurs through random encounters between infected individuals and uninfected individuals. If a majority of the population is immune, most random encounters will not lead to an increasing infection rate. But answers to both questions depend so strongly on the assumptions of the model that they are of no use in public health decisions. They are only mathematical statements flowing logically from the underlying assumptions. The appropriate boundary conditions underlying covid-19 are unknown, and most likely completely non-universal. For example, the herd immunity threshold for New York City is likely to be very different from that in Wyoming. In both cases, if the individual immunity lasts for a short time, herd immunity itself becomes a meaningless construct.
In addition, herd immunity is only meaningful in isolated communities. Even an immune community could see infections growing if a sudden large influx of infected individuals takes place. The fact that we do not know the statistical distribution of the individual immunity to covid-19 indicates that it is premature to talk about herd immunity. If the typical individual immunity duration is only one month, herd immunity is no longer a meaningful concept as the disease will simply incubate through recovered patients who get re-infected randomly. In fact, talking about herd immunity threshold is sensible only when the individual immunity is long lasting. Otherwise, the disease will recur periodically and randomly no matter what fraction of the community may be immune at a particular instant in time.
For example, we do not develop any herd immunity to the seasonal flu, which recurs every year with varying intensity as it travels between northern and southern hemispheres, mutating occasionally leading to severe or mild symptoms, but never disappears. We do not develop any herd immunity to the common cold either, no matter how many people are infected in the cold season. A large number of people getting infected is only a necessary condition for developing the herd immunity, it is by no means sufficient.
It is instructive to examine the common cold when thinking about herd immunity. Societies typically do not develop herd immunity to the common cold, no matter how many individuals catch a cold in a season and/or how many times an individual may have been infected. People develop some temporary immunity, but how much and for how long varies enormously from person to person, and depends a great deal on environmental conditions (such as exposures to others with cold). Of course, the common cold and covid-19 are very different, although some cold viruses are also coronaviruses (the common cold is caused by several distinct viruses). This is only an example to emphasize that just because a virus-borne disease is highly prevalent does not guarantee that humans will develop herd immunity. Right now, we simply do not know enough about SARS-COV2 in order to make any educated guess on the prospects for herd immunity. After all, this virus made its zoonosis to humans only about 10 or so months ago.
It may be worthwhile in the context of covid-19 to think about the prevailing situation with the common cold in some depth. The common cold arises from human coronaviruses (15%), including types 229E, NL63, OC43, and HKU1 (but not novel coronaviruses as SARS-COV2 is called) and also from rhinoviruses (about 80%). No immunity or vaccine exists for the common cold. It is possible to catch a cold several times a year, and people typically catch it year to year. The same may very well apply to SARS-COV2. In fact, there are already documented cases of the same individual getting the covid-19 disease more than once, with the infection dates separated by only a few weeks. Of course, all this proves is that absolute and permanent immunity to SARS-COV2 is unlikely in all humans. The important question is how long such an immunity lasts on the average and what fraction of the exposed individuals develops at least a partial immunity. Until we know the answers to these questions, herd immunity to covid-19 remains a speculation, and we must assume that it is not very effective.
For the common influenza any immunity is also partial and temporary. We know of people who catch the flu often in flu seasons, and there are others who rarely catch it. The deadly 1918 "Spanish" flu suddenly vanished after killing 25-100 million people worldwide during 1918-19. No one precisely knows why it vanished. One speculation is immunity and the other is mutation. There is no doubt that partial immunity to SARS-COV2 could happen and is perhaps already happening, after all, every exposed person does not develop the disease. The question is how extensive such an immunity is and how long it lasts on the average. For developing herd immunity more than 80% of people must develop immunity for reasonably long periods of time, approximately 6 months. We have no medical/biological information on such an immunity development in any community yet. We cannot therefore count on the herd immunity coming to our rescue in the near future. Perhaps in 2024, but not now. Social distancing and mask wearing must continue indefinitely.
In fact, a preliminary clinical experiment on covid-19 herd immunity has already taken place in Sweden, where the government made a deliberate decision not to lock down or force stay in place at all, in sharp contrast to all other countries, in order to develop herd immunity throughout the whole society. This experiment has been a failure, although the Swedish authorities are somewhat reluctant to admit it directly, they equivocate. There has been no herd immunity in Sweden to SARS-COV2. Of course, a truly controlled experiment would have required two identical Swedens, one with a strict "stay in place" order and one without, and then compare the outcomes. This is the physics way of doing things, which cannot be done in real life with a pandemic. So, we do the next best thing and compare Sweden with other similar countries.
Fortunately, Sweden is not totally unique as a country like America, India, China, Russia, or Brazil. At least two other countries very similar to Sweden exist: Denmark and Norway. So, how does Sweden do when compared with Denmark and Norway? Or Germany, another large highly affluent and relatively homogeneous Northern European country? The statistics as of September 20 for covid-19 infections and fatalities in these 4 countries, given as a number out of 100,000 with the population density and total populations of each country in the parenthesis, is the following:
Sweden (10 million, 64 per sq. mi): Infections (88,237); Fatalities (5865)
Germany (83 million, 623 per sq. mi): Infections (274,997); Fatalities (9477)
Denmark (6 million, 354 per sq mi): Infections (23,323); Fatalities (644)
Norway ( 5.4 million, 38 per sq mi): Infections (12, 954); Fatalities (267)
These numbers compellingly establish that the Swedish experiment of developing herd immunity has been a colossal failure. It is a mystery why the head of public health in Sweden has not been fired yet for carrying out such a reckless experiment endangering the lives of many Swedish citizens.
With a population less than that of Denmark and Norway combined (and a lower overall population density of these two countries), Sweden managed to produce almost 3 times as many covid cases and an astonishing 20 times the fatality rate than Norway. Germany, with 10 times the population and population density of Sweden, has only three times the number of covid infections than Sweden and less than three times the fatalities. There are very few western countries which can justifiably be said as having done worse than the US in tackling the covid-19 crisis. Sweden may be the only advanced western nation to fall into this unenviable category. If normalized by the population, the number of Swedish covid-19 fatalities would translate to almost 300,000 deaths in the US today, 50% larger than even the astonishingly tragic number of 200,000 covid fatalities in America right now. Sweden has a fatality rate of almost 7% per infection, whereas even USA has a fatality rate of 2.9%. In fact, Sweden's fatality rate per infection is among the highest in the world, much higher than the average fatality of 1.3% in the whole world. So much for the herd immunity experiment!
For the sake of comparison, the corresponding US and global numbers for September 20 are:
USA (331 million, 93 per sq mi): Infections (6.8 million); Fatalities (199,633)
World (7.8 billion; 163 per sq mi): Infections (31.1 million); Fatalities (961, 638)
The failed (and tragic) Swedish experiment in herd immunity does not prove that we can never achieve herd immunity. It just proves that it cannot be done in the cheap quickly. It is possible that after covid-19 makes its rounds through the world several times, eventually some highly variable (both spatially and temporally) levels of herd immunity might develop and the number of fatalities will stabilize at some astonishingly large number. After all, cancer kills 10 million people worldwide every year, and even road accidents and diarrhea kill 4 million worldwide annually. I do not know what this number might be, but if I had to guess, I will say it is likely to be around 3-8 million a year worldwide and 400,000 a year in the US if we do not have a successful vaccine. Improvement in therapeutics and general medical treatment is sure to come as we learn more about the modus operandi of this virus. In the short term, which I define to be 1-3 years, therapeutics is the only hope, not vaccine or herd immunity.
This brings up the most important question: If neither a vaccine nor herd immunity is around the corner, what do we do? The answer is crystal clear. We wear masks as much as possible, avoid crowds, maintain social distancing everywhere, and keep on maintaining a flattened curve. If we do not vigorously maintain social distancing the curve will grow exponentially, as happened recently in Israel, Spain, and France. Below are the covid-19 infection graphs for Israel/France/Spain compared with the US (yes, right at this moment these three countries are doing worse than America on a per capita basis). The next time someone mentions "herd immunity" with respect to covid-19, ask them to look at Sweden (or to Israel/France/Spain in mid-September).
Among the most misunderstood terms being extensively used these days in the context of covid-19 pandemic reports are 'vaccine', 'immunity', and 'post-covid.' I order them by increasing degrees of obtuseness, with 'post-covid' being the most blatantly meaningless. I am not dignifying truly absurd statements, such as 'we have rounded the final turn' or 'this thing will miraculously go away,' in this blog. Such manifestly absurd claims appeal only to the truly ignorant. In fact, I would claim that the rather ominous-sounding statement made by Anthony Fauci during an interview with MSNBC on September 10 where he said that it could be 'well into 2021, maybe even toward the end of 2021' before we "get back to a degree of normality which resembles where we were prior to Covid" was based mostly on optimism. Nobody knows, not even Tony Fauci, when normalcy will return. It is possible, perhaps even likely, that it will be many years before normalcy, in the sense of a return to the pre-covid situation, happens.
The possibility that modern life has changed permanently in some fundamental manner because of covid-19 is real. It is entirely possible that 'before'/'after' will forever be distinguishable as a sharp first order phase transition.. On a much more limited scale, this happened after 9/11 to aviation when flying in commercial planes changed permanently. Sometimes things never go back to normal if normal is defined as the way of life before a particular event. Anyone who has ever encountered the death of a loved one, a child or a spouse, knows very well that there is no going back ever to 'normal'. I certainly know. The same is true for societies. There are transformative events which simply are not reversible and going back to normal may not happen. I do not know if covid-19 is such an event, but it is possible that it is. At least, we must take seriously the possibility that there could be permanent behavior changes caused by (or rather forced by) covid-19, and going back to normal (in the sense of the way we all lived in 2018) may not happen. In this blog and the next few, I will address each of these issues: vaccines, immunity, and life 'post-covid.' This current blog discusses the issue of a covid-19 vaccine.
Let us start with 'vaccine'. Where is the scientific evidence that we will have a successful vaccine against covid-19 infections? Nowhere to be found. What is the scientific evidence that we will have a successful vaccine quickly, possibly within the year? None. We do not have vaccines against the common cold. In fact, we do not have vaccines against any of the coronaviruses, not only the types causing the common cold, but not even for serious diseases such as MERS and SARS. One could argue that the covid-19 situation is radically different from other coronaviruses because of the huge commercial interest and the international government commitment across national borders. But if commercial interest and government funding could lead to successful vaccines and/or cures for all serious diseases, then cancer, which causes 10 million deaths worldwide each year, would have been eliminated.
The truth is that much of the medical advance against cancer has been in early detection and improved surgical techniques and not really in the therapeutics, despite the great deal of activity in immunotherapy, gene therapy, and vaccines. One's chances for surviving a non-resectable stage 4 cancer diagnosis has hardly changed over the last 30 years, in spite of tremendous commercial and government interest. Given that there is no successful vaccine against any respiratory disease (and none against any coronavirus), there is no obvious reason to believe that a successful vaccine against covid-19 is just around the corner. Even if a vaccine is developed, there are serious safety issues associated with a new vaccine to be used by hundreds of millions (possibly billions) of people. It is unclear that clinical trials could assure a reasonable level of safety for a new vaccine quickly. In fact, such trials for assuring safety may take a year or two even if a decent vaccine candidate is identified in the laboratory.
Another important aspect of a covid-19 vaccine is its effectiveness. What fraction of the vaccinated population would develop reasonable immunity? Unless it is 60-70%, the vaccine would not be particularly useful, particularly since it may create a false sense of security, leading to lax social distancing which could be deadly. In addition, there is the question of the time duration of the vaccine effectiveness. If a vaccine is effective only for a short time, but provides a false sense of security, the overall effect could be worse, again because people may stop social distancing once they are vaccinated. The truth is that the only thing known about covid-19 vaccines is that many companies big and small are trying to develop a vaccine, and so are many countries. We know nothing else, except that there is no effective vaccine against any coronavirus. The crucial question of how the vaccine's safety would be decided and how effectiveness (both the fraction of people developing vaccine immunity and the time duration of the immunity) is to be determined are unknown. The companies (and the countries) developing vaccines are not transparent at all in these questions, except once in a while when we find out about adverse safety effects in a clinical trial.
Then, there is the whole matter of non-medical issues strongly affecting the introduction of the vaccine, whether it is the political pressure associated with the coming November elections in the US or countries (e.g. Russia) jumping ahead with the introduction of a vaccine with no details on its efficacy or safety. A particularly sad example of the ineffectiveness of the whole covid-19 medical planning is the Eastman Kodak company. They received a large federal contract for developing covid-19 drugs, leading to a huge spike in its stock price, which precipitated an allegation of possible criminal insider trading. Eastman Kodak is a failed photographic film company with no expertise in drug development whatsoever. The fact that this company can secure a covid-19 federal contract says a lot about how disorganized and incompetent the whole process has been.
In the context of covid-19 vaccines, I'm including a quote from New York Times on September 11 (updated September 13), which provides excerpts from an interview with Dr. Fauci, who arguably, is the leading infectious disease expert in the US (most certainly the most well-known):
"Dr. Anthony Fauci says 'If we get a really good vaccine and just about everybody gets vaccinated… you’ll have a degree of immunity in the general community that I think you can walk into a theater without a mask and feel like it’s comfortable that you’re not going to be at risk.' He said that would most likely not be until mid- to late 2021."
I note the crucial use of 'If' in the sentence, which actually conveys NO information whatsoever. The first 'if' states that a vaccine may or may not be available in a year. The second 'if' says that everybody may or may not get vaccinated. Then, he concludes by saying 'I think'. I understand that Dr. Fauci is in a tough position as people expect him to know it all and somehow be clairvoyant about the future course of the pandemic. The truth is that he knows not an iota more than I do on this issue, but he is forced to make pronouncements and predictions. Unlike the politicians, he paraphrases what he says with 'if' and 'but' and 'I think', and puts all potential success against covid-19 at least a year and a half in the future, knowing full well that any prediction in the press that far into the future is pretty safe since nobody would remember at the end of 2021what he said in September 2020. He should, but perhaps cannot, tell the truth, which in this case would have been 'I have no idea, I do not know if we will have successful vaccine, I do not know how successful and safe it would be, I do not know when such a vaccine would come out and how long it would be before we know if the vaccine is working. What I do know is that we will know nothing for an indefinite future which I arbitrarily define to be the end of 2021.'
I see absolutely no reason for Dr. Fauci to mention the end of 2021 as a time line here except that it is far away enough without being too far in the future (and indeed, Dr. Fauci provides no scientific or logistical reason whatsoever in claiming the end of 2021 as a prospective timeline for a vaccine). All this interview shows is that Dr. Fauci is a veteran when it comes to press interviews and is capable of making profound-sounding pronouncements with no content whatsoever. The truth is that no one, not Dr. Fauci, not I, and not President Trump, has any idea when, and if ever, a 'successful' covid-19 vaccine will be available, and what its level of success would be.
If anybody understands how difficult it is to produce a vaccine against a new virus, Anthony Fauci is that person. Throughout the 1980s and beyond he spearheaded an effort to create a vaccine against the AIDS virus (HIV), and basically, it was a failure in spite of a 20-year effort. Medical success against AIDS came through therapeutics not vaccines, and it is conceivable that the same would happen for covid-19 (although the two virus types are very different, if anything covid-19, being a coronavirus, is likely to be a more difficult vaccine target than HIV).
In addition to the challenging decision of finding a vaccine that works and is also safe (both extremely difficult tasks likely to take years), there is the issue of producing enough vaccines to inoculate all of the USA (requiring at least 360 million doses) and the whole world (requiring 7 billion doses). How long would that take? Again, nobody knows. Suppose Dr. Fauci turns out to be clairvoyant in his prediction of the end of 2021 as the timeline for a successful vaccine, it still has to be produced in mass quantities and transported everywhere for the actual vaccination process. This is a task never before attempted in human history, so a reasonable guess is impossible. But, just today (September 14), the decisive authority on the vaccine production, the CEO of the Serum Institute, the world's largest (by far) vaccine producer, told us 'A vaccine won't be available for everyone before the end of 2024'. So, even if a successful vaccine is made in the laboratory today, its production to immunize everybody will take 4 years! It is very likely that each person will need this vaccination repeatedly (perhaps on a monthly basis) since it is quite impossible to imagine a scenario where a coronavirus vaccine remains effective longer than a few months. This implies that not only the actual development of a safe and effective vaccine is far in the future, its sufficient production to meet the global need is in the very distant future.
The real problem is that a not-very-effective (even if it is safe, and safety is a huge issue here since ensuring safety for a vaccine to be given to billions of people worldwide is not an easy task) vaccine could be counter-productive. Imagine a 'safe' covid-19 vaccine that immunizes only 50% of the people, and the immunity only lasts for a few months. Obviously, we have no way of knowing which 50% is effectively immunized, and how long the immunity lasts in each person. A simple simulation shows that such a vaccine could do more damage than no vaccine if everybody then relaxes all social distancing protocols and we go back to our pre-covid way of life. Unmasked crowded restaurants, planes, public transportation, schools, stadiums, bars and so on. One therefore must continue the strict social distancing protocol indefinitely even after a vaccine is introduced simply because it may take years for us to really know the level of effectiveness of the vaccine.
Going back to a pre-covid life right after a vaccine is introduced could be disastrous, particularly if the vaccine is introduced prematurely. The problem is that we do not quite know the definition of 'premature' here since we never faced anything like covid-19 before.
My own feeling is that eventually covid-19 will be brought under control by a combination of therapeutics, behavior changes, a vaccine, and immunity, perhaps in that order. We are unlikely to go back to the pre-covid life of unmasked crowds in the intermediate future. There will be vaccines, but their efficacy and safety will be uncertain, and their availability is likely to be limited. People must continue social distancing and mask wearing even after vaccines are available because we cannot be sure who is or is not immunized (and for how long) by the vaccine.
If the seriousness of the situation is not obvious, let me conclude this blog with some sobering facts, sticking to the current covid-19 statistics in USA:
(1) As of September 14, meetings in groups of more than six - inside or outside - are illegal in England, punishable by an on-the-spot fine. This is because there has been a spike in cases. The UK had 6 deaths on September 11. The US had 1,094 deaths on September 11, and President Trump held a crowded unmasked rally of 5000 in Nevada on September 12, saying 'I'm on a stage and it's very far away,' Trump said. 'And so I'm not at all concerned.' What about all the people in the crowd attending the rally?
(2) The number of reported covid-19 deaths in the US (population 330 million) on September 9 is 1209, to be contrasted with the total number of deaths on the same day being less than 100 in all the following 7 countries combined (total population ~ 500 millions): Spain, Germany, France, UK, Canada, Japan, Italy.
(3) You hear a lot about how the covid-19 situation is improving in the US—it is indeed a shame that the world's most powerful and the most scientifically advanced society is resigned to accepting an average of 35,000 new infections and 700 deaths per day as an improvement! Perhaps this is the future: In the US we accept roughly 300,000 covid-19 deaths per year as routine, and countries like Vietnam and Taiwan (total population around 125 millions) have virtually no covid-19 deaths at all! I append the latest on new cases from New York Times below for USA (population: 330 millions) and Germany (population: 81 millions) for a depressing comparison.
Aspects of the covid-19 crisis have changed in a completely unexpected way, certainly not anything I had anticipated in my earlier blogs during June 1-17. Actually, no one had.
First, the aspects I did predict reasonably correctly: (1) the pandemic will subside in the Northern Hemisphere starting in July—this has been more or less true with one big exception (see below); (2) the pandemic will ravage parts of the Southern Hemisphere starting in July; (3) the death rate growth will remain much lower than the infection rate growth.
All over Europe, the pandemic basically disappeared: Italy, Spain, France, UK all now have very low new infection rates; and the death rates from covid-19 are close to zero in most of Europe. Iran and China also have negligible new infections and deaths from covid-19. No doubt that most of the Northern Hemisphere is doing far better during June 15-July 31 than it did during February-June. By contrast, covid-19 has wreaked havoc in Brazil, Chile, Peru, South Africa during June 15-July 31, all countries in the Southern Hemisphere.
The country that has defied all logic is the US. The fact that the US is most certainly the most advanced nation in the world in terms of technology, science, medicine, logistics, and wealth makes the US’s astounding covid-19 failure a matter of historical significance, which would be studied by scholars for hundreds of years in the future. How could this happen? Why did this happen? I will speculate a bit, but first some numbers.
Right now, as of July 31, the 10 countries (ignoring city states like Andorra, San Marino, Luxembourg) with the highest per capita total covid-19 infections are: Panama (1562), Bahrain (2611), Brazil (1271), United States (1396), Oman (1639), Kuwait (1618), Peru (1274), Qatar (3979), Chile (1899), Armenia (1306). The numbers in the parenthesis provide the total reported covid-19 infections as of July 31 per 100,000 population in each country. For normalization, this number for the world is 235, and for some other representative countries are: Russia (580), India (121), China (7), UK (456), Germany (252), Italy (410), Canada (314). Yes, the "China virus" has vanished in China, and has taken over residence in the US! The most-infected countries in March-April were all Western European nations such as Belgium, Italy, France, Spain, Sweden, UK, Netherlands, Ireland and so on (with the US being number 9 behind these 8 Western European countries) because of their very high population densities.
I made the case at that time that covid-19 infections seem to be strictly following the classic proportionality to population density rule of a contagion with the most affected countries being the Western European densely populated nations and the Northeastern US states (New York, New Jersey, Connecticut, Massachusetts, Rhode Island). This is no longer true. Now, the countries occupying the unenviable top spots are mostly extremely hot and sparsely populated Arab countries in the middle-east, a few Southern Hemisphere countries, the outlier Armenia, and the great US of A. How did we go from being #9 behind crowded European countries to being #6 behind Qatar, Bahrain, Chile, Kuwait, Panama in three months? How did the highly-crowded European countries control their covid-19 spread while the US rate kept on increasing after plateauing for a few weeks in May? There is no easy single answer to this question other than saying we failed miserably as a nation. Clearly, the country had no plan whatsoever, and states/localities dealt with the crisis on a piecemeal basis according to the local political climate and whim.
The fact is that SARS-COV2 could not care less about our political beliefs, who is red versus who is blue, our state boundaries, or whether China lied about the virus in the beginning or not did not play any role in our decision making process regarding covid-19. While our obsession was on the nonessential trivialities, covid-19 kept on spreading and killing, first in the Northeast, and then in the South and the Sun Belt (Arizona, Texas, Florida).
How did this happen? How could USA belong to a list with Panama, Bahrain, Oman, Kuwait, Qatar, Armenia? These are not countries that ever come up in the American vocabulary, most Americans would not be able to point to any of these countries on a world map. Yet here we are lumped with them in the list of the most infected coronavirus nations in the world. How is it possible that the UK, with a population density of 725 per sq mi, which is 8 times higher than the US population density of 92 per sq mi, has a covid-19 infection rate of almost one-quarter of the US rate. When in April, the US and the UK had very comparable per capita infection rates? I certainly do not know the answer. Just saying that our government failed is a non-answer since it is basically a tautology. Of course, somebody failed, and it must be the government in a collective sense. But the US is not a dictatorship, our government, in principle, is a reflection of our collective self. So the question remains: how could such a colossal failure occur in a country which has NIH, CDC, FDA, and arguably the best medical-hospital-public health system in the world? I show below the evolution of covid-19 in USA (left) and UK (right) for a direct comparison, the current population of the two countries are: USA (328 million), UK (67 million).
One answer probably is that the basic anti-intellectual and anti-scientific individualism in a large fraction of the US population is in all likelihood an extremely subversive property when it comes to combating a highly contagious deadly virus which could not care less about how great America is and how we always defeat our enemies. The American exceptionalism hurt our cause in dealing with this crisis rather than helping us. When it comes to the virus SARS-COV2, we are no different from Qatar and Armenia. Nobody told the virus that we are very special and exceptional and are strong enough to face the virus without masks and social distancing, and stare it down and scare it to humble defeat just by the virtue of our great strength. This tactic was tried all over the American South, from Florida to Arizona, with spectacular failure.
If people do not wear masks and do not maintain social distancing, an increasing fraction of the population will get infected, until everybody is infected, this is the law of exponential growth that we discussed in our earlier blogs. People in the Northeastern US understood the simplicity of the situation after being badly hurt during March-April: wear masks everywhere and do not go closer than 6 feet to anybody. People in Florida and many other states decided that they are strong enough to face the virus without masks and social distancing. The situation most likely is also exacerbated by the extremely hot temperatures throughout the south during June-July, so people crowd indoors in air-conditioned comfort without masks, a perfect scenario for SARS-COV2 to jump from person to person going on its exponential growth. This is also consistent with a large number of the current infections happening among the relatively younger people. Young people feel they are immortals, particularly if their leaders mislead them into believing that masks are simply an elitist conspiracy to make strong Americans look wimpy.
A rather visual example of the US leadership failure was manifestly apparent in the theatre of the absurd that played out today, July 31, during a congressional hearing, where Dr. Fauci, the sage face of US coronavirus response, was grilled by the Republican congressman Jim Jordan of Ohio. All Mr. Jordan was interested in doing, and you must remember the somber seriousness of the occasion, the three senior officials of the US federal covid-19 response team (Fauci, Director of CDC Robert Redfield, and Admiral Brett Gioroir of HHS who is coordinating the national covid-19 testing efforts) were being questioned by the House Select Subcommittee on the Coronavirus Crisis.
After all Congress makes all the budgetary funding decisions in the US system. But, all Mr. Jordan was interested in is in making Dr. Fauci admit that the ongoing protests in the streets of America (Black Lives Matter and other related protests) are spreading covid-19 as much as, if not more than, the documented covid-19 spreading and super-spreading events in various churches all over the country. Representative Jordan had no other question or reflection, all he wanted to do is to make Dr. Fauci admit that protests are bad, and churches are good! Of course, Jordan was no match for Fauci, who is not only an intellectual giant, but also a very savvy bureaucrat who has been speaking in front of politicians in the Congress since the mid-1980s.
If you knew nothing about US politics, you would think that this must be a funny movie scene deliberately showing some truly absurd happenings, but this was no movie scene, Jordan had a singular purpose. He was trying to impress an audience of ONE, and he succeeded, his audience of one tweeted later in the day praising Jordan's absurd performance. The sad thing is that Representative Jordan’s behavior here is not an exception, although this was a bit extreme even for him, and this is really saying something. His behavior is just an example of the modus operandi of the whole US political leadership in facing coronavirus. Instead of dealing with it as an existential public health and medical crisis which may kill millions of Americans, much of the leadership is busy dealing with it as another serious political problem.
This congressional coronavirus hearing on July 31 is actually worth watching in order to partially understand the underlying causes of our failure: https://www.youtube.com/watch?v=IEcO69p--L4
Another rather unbelievable aspect of this July 31 congressional hearing was how lame and pathetic the covid-19 scientific leadership of Fauci-Redfield-Gioroir came across in this hearing. They had nothing substantive to say about controlling the crisis except hoping for the quick development of a vaccine. They expressed hope that there would be a successful vaccine, they answered questions with non-answers because they simply do not have any answers. In fact, all they said is what I am saying in this blog (and my full time job is doing theoretical physics, not fighting the covid-19 crisis, I am by no means a public health expert): Wear masks, avoid crowds, social distance, wash your hands, and pray for a vaccine coming up soon. Period. The only factual point that came out in this hearing is actually quite incredible, and very sobering. In answering a direct question, that Fauci deftly punted. I have noticed that Dr. Fauci rarely answers questions, perhaps he learned from his initial miscues in February when he asserted that the US is safe and then in March when he asserted that Americans do not need to wear masks. Admiral Gioroir just bluntly admitted that USA will not have a covid-19 test with results available within 48-72 hours any time soon! This was an astonishing admission, and my respect for the Admiral went up exponentially. Here is a man who is not afraid to tell the truth, even the most unpleasant truth. Perhaps his military training allows him to speak the truth, but what I heard in his honest answer provided another reason for our failure in tackling covid-19. If test results are taking 7-14 days to come back, there is no point in doing covid-19 testing since in 7-14 days the infected person would typically spread the virus copiously all over. So, the message is: do not get tested, it is useless right now, just stay home if you feel the slightest bit sick and/or are running a temperature.
The only 'good' thing is that the death rate, although high in the absolute sense (~155,000 deaths in USA and ~ 700,000 in the world), is not increasing (around 3.4% in USA and 3.7% in the world—these numbers are surely much exaggerated by virtue of the fact that the reported infection rates are surely much lower than the actual infection rates due to the lack of adequate testing—the real infection rate is likely to be 10 times, if not more, than the reported rate given the paucity of testing all over). But, if we do not have a vaccine and the whole world eventually gets infected by SARS-COV2, we may have between 20 million and 200 million dead in the world from covid-19 and between 1 million and 12 million dead in USA perhaps within the next 12-24 months. This is a truly unimaginable human tragedy. In addition, it is anybody’s guess what would happen to the economy if a disaster of this level actually comes to pass. So, no matter how bad things appear right now, it could get far worse.
Getting back to how the USA could fall so far behind all other advanced western nations in the covid-19 statistics. With less than 5% of the world's population, America now accounts for close to 25% of covid-19 infections and fatalities. My only guess is that it is a combination of many factors: total failure at the federal level, a complete inability to anticipate the scale of the problem at the highest level of our public health system in the beginning of the pandemic (the fact that I, as the Director, closed down our theory center CMTC two weeks before any state or locality in the USA started its lockdown, and I am no public health expert, clearly shows how bad the initial collective US response was), and the anti-elite, anti-intellectual, anti-scientific American 'can-do' gung-ho spirit where the motto is that masks are for the weak. This was greatly exacerbated by a large number of political leaders saying complete nonsense, many of whom now want the schools to open in the fall with no restrictions (who even were stupid enough to encourage large crowded gatherings without masks in June-July).
It may help to think of an imaginary scenario in understanding the failure of US response to covid-19. Imagine that a secret group of all-powerful terrorists have descended into the US in disguise and are all over the country. We do not know where they are from, we do not know what their ideology is. The only thing we know is that they want to kill Americans and are very good in doing it. They are killing on the average 1000 or more Americans every day, and they have killed more than 155,000 Americans in the 5-month period of March-July. Plus, they have sent another million or more Americans to the hospital with grave injuries. How would the nation react? Well, we have some examples: Pearl Harbor on December 7, 1941 which killed 2401 Americans and September 11, 2001 which killed 2977 Americans. How did we react? The country mobilized and went into wars right away. The leaders did not sit around asking about church versus protest. There was immediate concerted military action. Covid-19 is no different (in fact, it is a much more dangerous enemy than any collection of terrorists) except now the US homeland has been invaded by a ruthless virus whose only goal is to kill, and so far, our response has been pathetic. Our response has been the way Panama or Qatar or Armenia would respond to a foreign military invasion!
It will take many years of intense research to figure out how the US fared so spectacularly poorly in its handling of the covid-19 crisis. I think that this is the kind of historical question which will never be resolved by a unique neat answer. Saying it is all Trump is a cliche, which cannot explain the total abject failure, the US system is an elected federal republic where the governing responsibility is distributed at every level: country, state, county, city, locality. But the important point is that it is by no means too late yet. Covid-19 has been devastating so far, but the official reported infection number in USA is still a manageable 4.5 million (roughly 1.5% of the population). We must stop the exponential growth right now, flattening the curve everywhere. The way to do it is simple (and you do not need vaccines to flatten the curve); everybody must always wear masks and keep social distance from others, and no crowd should be allowed to gather anywhere. This is a simple change of behavior. If the alternative is death, most of us would probably be happy to modify our behavior. This is what is at stake right now.
We must remember that the virus has not vanished anywhere, it is everywhere among us, and the only way to keep it under control, until a successful vaccine appears (over which we as individuals have no control), is to avoid getting infected and to avoid infecting others. The rules for accomplishing this is simple: Avoid crowds, wear masks, maintain strict social distancing, wash your hands repeatedly. This is what the countries in the Western Europe did. This is what China and Japan and Taiwan and Australia and Canada did. This is what we must ALL do too. There is no need to listen to the politicians or even to Dr. Fauci, they know nothing more than we all do. There is no great technical secret lurking underneath the crisis here. We all know what to do, now we must just do it.
My colleague Maissam Barkeshli pointed out a wonderful 2-year old article by Robert Dijkgraaf in the Quanta Magazine (June 4, 2018).
The article in Quanta is provocatively titled "There are no laws of physics: There's only the landscape" (Quanta Magazine Online June 4, 2018). In this blog, I will take a break from the scientifically frustrating topic of covid-19, the subject of my first 6 blogs, and venture into the intellectually depressing topic of there being no laws of physics, Einstein is turning in his grave, and so is Dirac, who apparently said that all of chemistry can be derived just from his equation. Looking back, I am sure that this story is apocryphal; Dirac was far too smart and far too reticent to make such a remark.
I agree wholeheartedly with Robert, who is as good an expositor of science as there can be. I literally believe that there are no ultimate laws of nature to be discovered, not by string theorists, not by condensed matter physicists (such as myself), and not by anybody. The human brain is finite, although it has a huge capacity, and the universe in some sense is infinite, as it apparently keeps on expanding faster and faster. There is no chance of our figuring out the ultimate laws of nature that control the universe using our finite brains, so we might as well accept that the universe does not follow, in the strictest sense, any ultimate laws. The more we learn about the universe, more new laws should emerge as has happened continuously during the last 400 years since Newton/Kepler/Galileo. Before that, we made little systematic progress in understanding the physical world, and scientific knowledge in the modern sense did not really exist. What is amazing is the fact that we can make sense of some aspects of this infinite universe through our laws of physics. It may have been Feynman (another great scientist who was also a great expositor) who first said it; the issue is not how clever we humans are in figuring out how nature works, it is how clever nature is in following our laws!
What we call laws of physics, whether they are Newton's laws of mechanics and gravitation, Maxwell's equations for electricity and magnetism, Einstein's theory of special and general relativity, Schrodinger's and Dirac's equations in quantum physics, or even the string theory, are all effective descriptions of nature at various levels. They are all internally consistent mathematically and (hopefully) eventually consistent with human experience as observed in laboratory experiments. This is all they are, nothing more. Nature is infinite, and as our experience matures, our laws must evolve as there is no ultimate law waiting to be discovered in the end. Just an increasingly complex effective description that works (in a precise sense) to allow us to describe nature at a reasonable level and helps us improve human life by contributing to technology. It is like the peeling of an infinite onion, the more we peel, the more there is to peel.
It is interesting to note that even a hundred years ago the physical laws were many and were all directly connected with the successful description of some concrete aspects of the natural world. Some examples are Planck's law, Hooke's law, Stoke's law, Faraday's law, Lenz's law, Boyle's law, Dulong-Petit law, Wiedemann-Franz law, and so on. Laws of physics as an all-encompassing ultimate theory using fundamental forces and reductionist building blocks is a powerful intellectual bias that developed only over the last 100 or so years. Einstein contributed mightily to physics becoming a subject focused on investigating the ultimate quasi-religious question of whether God had any choice in designing the universe! No wonder Einstein, as great as he was, spent the last 30 years of his life wasting away on the futile search for an impossible unified field theory as the ultimate theory of everything.
Laws of nature, in the strictest ultimate sense, do not exist. We have only internal mathematical consistency and explanations of facts. In very good theories, this consistency is very tight, not allowing a huge number of tuning parameters. String theory is a very successful theory in terms of its consistency and mathematical tightness; it is indeed rather magical the way gravity and quantum mechanics exist equivalently within it. However, string theory has so far been ineffective in predicting facts, particularly new facts that can be tested in laboratories.
For example, a great worthy early goal of the string theory in providing explanations for the many tuning parameters of the standard model still remains elusive. I am unimpressed by its claim of having 'predicted gravity', which was an acceptable claim in 1984, but no longer in 2020. String theory so far has remained like a proverbial highly promising brilliant assistant professor whose promise is always in the future. I am not criticizing string theory, I am a big fan of its mathematical tightness and I agree that someday it may turn out to be the next great thing in explaining facts. But 40 years is a very long time to wait for 'someday'. Now, with supersymmetry itself in doubt as a fact, I am not sure that conclusions based on the string theory should be aggressively discussed. String theories have led to some remarkable insights, e.g., a deep unexpected connection between gravity and conformal field theories, the so-called AdS/CFT duality. These are extraordinarily powerful concepts, although it is unclear right now if this by itself leads to any new physical laws.
My focus is the so-called 'landscape' problem in string theories, where literally zillions of universes (~ 10^500, the number is so large that it seems obscene) are acceptable solutions of the theory. If true, one can declare victory as one of those zillions of universes must be our universe, and all one needs to do is to somehow find that particular solution to figure out our existence. Of course, this is an impossible task because of the exceptionally large number of possible universes existing in the landscape, and all with their own distinct laws. This scenario is often called the multiverse.
The other way of looking at it is that all possible laws, conceivable and inconceivable, are allowed in some possible universe, and laws of physics are no longer meaningful or unique from a fundamental sense, since they depend entirely on where in the multiverse landscape one is looking. It is ironic that the theory of everything turned out to imply an 'everything' (i.e. the landscape), which is exponentially larger than any 'everything' anybody could have imagined before. The search to predict the fundamental constants like the fine structure constant ('alpha') starting from a parameter-free ultimate theory is ending up showing that essentially all values of fundamental constants are allowed in different universes in the vast landscape. This landscape/multiverse scenario is perhaps philosophically similar to invoking God, as homo sapiens have been doing for a very long time, claiming that everything is the way it is because this is what God wishes, God works in a mysterious way. Instead of God, we appeal to a landscape. Both make predictions impossible, and the concept of fundamental natural laws becomes moot.
It is possible that progress will come in the future as deep patterns are discovered in the landscape, some large parts of the landscape may turn out to be useless swamps, and other parts may turn out to be connected with each other in subtle ways not discernable today. Perhaps someday far in the future, the landscape will start making sense. If so, string theory will then be a true theory of everything.
One possible conclusion, therefore, is that the conventional reductionist approach of particle physics, where natural laws are increasingly focused on smaller and smaller building blocks (molecules/atoms/nuclei/quarks/electrons/neutrinos, etc..) and fundamental forces (gravity, electromagnetism, nuclear weak and strong forces) acting between the building blocks, is no longer a fruitful objective way of looking at the physical world. There are no fundamental building blocks and no fundamental forces, and as such there are no laws. The only thing we are left with is the landscape, where the 'laws' depend on the specific universe one is dealing with. This is so mind-bogglingly complex that the whole idea of natural laws must be modified. An apparently strange end to a worthy journey which started with atoms as hypothetical indivisible constituents of matter 2500 years ago and witnessed a great recent triumph in the experimental discovery of the Higgs particle in 2012.
In the end, our physical laws are only 'boundary conditions', and not intrinsic at all, depending entirely on where in the landscape we happen to be! Einstein's lofty quest to find out if God had any choice ends in a rather crafty God who made every possible choice and designed an unimaginably complex landscape with all possible universes.
As a theoretical condensed matter physicist I do not find the 'landscape' scenario discouraging at all. The fact that there are essentially infinite number of possible laws only makes doing science more exhilarating because exploring the landscape will remain an active and creative activity forever, theoretical physics can never end because the landscape is simply too vast. I already know from my 40 years of experience in working on real-life laboratory physical phenomena, such as superconductivity, magnetism, metal-insulator transition, phase transition, quantum Hall effects, superfluidity, etc., that the whole idea of an ultimate law based on an equation using just the 'building blocks' and 'fundamental forces' is unworkable and essentially a fantasy. It may work in some limiting cases (one example is QED, which I discuss separately below), but in general the problems one wants to solve are just too complex to be solved by starting with a fundamental reductionist equation from first principles. Predictions based on a fundamental equation are impossible because of the great complexity of the possible solutions. We might as well then invoke a God to explain things, which will be a perfect explanation (the ultimate Theory of Everything) with no predictive power.
In condensed matter physics we actually have such a single 'fundamental' equation, an ultimate law, which leads to ALL the complex phenomena and phases of matter that we find in the natural world around us. This equation is simply the Hamiltonian (i.e. the energy functional) of the system in terms of the underlying electrons and nuclei (which are the building blocks for condensed matter) with the fundamental force being the electrical Coulomb interaction between the building blocks. That is it. That simple. Of course, the complexity comes from the fact that a cubic centimeter of matter will typically have 10^23 of these building blocks, and we cannot solve this equation from first principles at all. If we could, we would find every possible phenomenon and every possible phase of matter, those already seen and those yet to be discovered.
Suppose we find a way to exactly solve the fundamental equation of condensed matter physics for a macroscopic piece of matter containing 10^23 or more atoms. This will not help in our understanding at all since this 'solution' would be a set of at least 10^23 complex numbers at every instant of time giving us the quantum mechanical wave function of the system. Looking through 10^23 complex numbers at each instant of time is obviously an impossible task unless we know exactly where to look so that we can discern the patterns in the system to figure out what is going on. This will necessitate our knowing precisely what to look for so that we simply do not get lost in a 'solution' with no meaningful information. Or rather so much information that we have no idea how to do anything with it.
This is why in condensed matter physics we must first have some idea of what we are looking for using effective descriptions of the physical system. Unless we have some ideas about the patterns we are looking for, even having an 'ultimate solution' (i.e. the complete wave function of the system as a function of time) of the fundamental equation takes us nowhere. Thus, progress in condensed matter physics comes always from knowing where in the vast condensed matter landscape one is interested in, and then building effective descriptions focusing on the phenomena and patterns in that specific part of the landscape. No good would come out of a complete solution of the fundamental equation since it would simply have hopelessly detailed and mostly useless information about the whole landscape which is simply too complex for us to handle.
This is our condensed matter 'phase and phenomena' landscape. This landscape has in principle every possible arrangement of these 10^23 atoms and electrons, leading to all possible phenomena. We could just declare victory and stop doing condensed matter physics even if we cannot solve our fundamental equation to derive the results. The beauty of condensed matter physics is to build simple effective models which capture some low energy approximate descriptions of this extraordinarily complex landscape of phenomena and phases, leading to useful predictions and explanations. The famous BCS theory underlying superconductivity is an effective theory where almost everything about this ultimate equation is discarded except for a tiny piece involving an effective interaction between a fraction of the electrons around the Fermi surface and the thermally excited background lattice (called 'phonons') of the nuclei. This was so exquisite and subtle an effective theory that it took almost 50 years between the laboratory discovery of superconductivity in 1911 and its eventual approximate BCS theoretical description in 1957.
All attempts to understand superconductivity during 1911-1957 using the first principles approach to the fundamental equation failed until the BCS theory came along to show us which part of the hugely complicated fundamental Hamiltonian is relevant for explaining superconductivity. BCS theory acted as a detailed map guiding us directly to the part of the condensed matter landscape where superconductivity resides, the full fundamental equation did not allow that possibility because of its complexity.
In condensed matter physics, we do not have the choice of giving up simply because our fundamental reductionist equation has too many possible solutions, as it most certainly does. That would be akin to throwing away the proverbial baby with the bath water. For us, condensed matter physicists, the entire physics is to explore the nook and crannies of the landscape, because those are the phenomena that must be understood. The appeal of condensed matter theory is the chance to embrace and explore the details of the landscape using the flashlights and maps of effective field theories, not reductionist microscopic equations using building blocks and Coulomb forces as our tools.
Sometimes the word 'emergence' is used to emphasize the fact that collective many-body properties of many particles interacting with each other are very difficult to predict based on the reductionist approach using building blocks and fundamental forces, they must be guessed using a variety of effective theories using coarse-grained approximate descriptions. This requires a great deal of careful creative thinking in order to obtain the appropriate emergent properties, a brute force reductionist approach almost never works. The BCS theory is a great example of such an effective theory.
Another example is the existence of liquids in nature, it is easy to guess the existence of solids (at low temperatures) and gases (at high temperatures) based on the fundamental equation, but liquids existing at intermediate temperatures are an emergent collective phase that are difficult to guess theoretically. Another amazing collective emergent property, not predicted theoretically, is the quantum Hall effect with its perfectly quantized electrical resistance in a tiny transistor, which turns out to be a very subtle topological phenomenon lurking in a non-obvious manner in the condensed matter landscape.
It is instructive to expand on the idea of liquids as an emergent property. Suppose we have 10 molecules interacting through some force (e.g. Lennard-Jones potential) in an isolated closed off box. We will take molecules as the building blocks and the effective inter-molecular force as the fundamental interaction for this example. If we cool this box down to very low temperatures, the molecules will stop moving around randomly (temperature is nothing other than the measure of the average speed of the molecular motion in a system) and create a solid with a well-defined volume and shape. If we heat the box up to very high temperatures, the random fast chaotic molecular motion, with the molecules colliding repeatedly with each other and with the walls of the box, will lead to a gas, which has neither a fixed volume nor a fixed shape—it just fills up the container. These two limiting phases are obvious: low temperature solid and high temperature gas. We know that most materials also have an intermediate liquid phase in between the solid and the gas, but it is not so easy to define exactly when that happens. A liquid has a well-defined volume (or density, to be precise), so it is more like a solid in that sense, but it has no well-defined shape, it simply takes the shape of the container you put it in, so in that sense it is like a gas.
At what stage does a system become a liquid? Clearly, with very few molecules, the concept of a liquid phase is not meaningful, we only have a gas and a solid at high and low temperatures. As we increase the number of molecules, eventually the liquid phase is an emergent collective property of macroscopic materials, but exactly when such an intermediate phase between a gas and a solid emerges is not so easy to define in a precise manner. Clearly, 10 water molecules will not form liquid water that we are all familiar with at room temperatures, but 10^25 water molecules will fill a glass as a liquid, which we can drink. If liquids did not exist at all in a hypothetical world, it would have been very difficult, if not impossible, to predict them just from a microscopic reductionist ultimate law. This is the enigma of emergence at the heart of condensed matter physics. Strange and unexpected phases and phenomena exist in the vast condensed matter landscape, which are almost impossible to envision or predict based on a fundamental ultimate law. There are ideas that space-time itself may be an emergent behavior somehow, but this is pure speculation with no concrete theories supporting it. Human consciousness is also thought to be an emergent collective behavior of the whole brain; we have no idea exactly how and why.
There are some parallels between the string multiverse landscape and the condensed matter phenomena and phase landscape. Both provide essentially impossible technical challenges to theorists. Only very small regions of the landscape can be explored using weak-coupling perturbation theories, the standard tool of theoretical physics. In most condensed matter systems, the electrical Coulomb interaction between electrons is not parametrically small in any sense, and therefore, perturbation theory is inapplicable except in asymptotic regimes of little physical interest. Almost none of the important emergent interacting collective phases and phenomena in condensed matter physics was theoretically predicted, most of them are essentially experimental discoveries of serendipity. This includes, among others, high-temperature superconductivity, as well as integer and fractional quantum Hall effects.
It may be worthwhile to emphasize that, in spite of many similarities, there is a key difference between the string theory multiverse landscape and the condensed matter phase/phenomena landscape. In the string multiverse, we are forever confined to our specific universe by accidental boundary conditions beyond our control. This particular universe, one out of apparently ~ 10^500 possible universes in the landscape (all with their own individual fundamental laws), has the standard model with its hadrons and leptons, it has the Higgs particle (as well as W and Z particles), it has QED with alpha~ 1/137 defining the electromagnetic interaction, and so on. This is the only universe experimentally accessible to us no matter how high in energy our accelerators take us to. We can never learn anything experimental about the other 10^500 universes, we are stuck to just one specific universe where we happen to be in the landscape purely accidentally. This seems to be a somewhat depressing situation as we are simply prisoners of the boundary conditions we did not get to choose.
By contrast, the condensed matter phase/phenomena landscape is, in principle, experimentally accessible to us in its totality. Perhaps we need much lower temperatures, much higher magnetic fields, much higher pressures and so on than what is technologically possible today, but there is no limit to our exploration of the condensed matter landscape, it is just out there with its almost infinite possible phases and phenomena waiting to be discovered. New discoveries in the condensed matter landscape are guaranteed forever because technological improvements will allow us to explore the landscape in greater and greater details, but the landscape being essentially infinite, we will never run out of new phenomena and phases.
We are by no means stuck to just the phenomena already discovered and already imagined or predicted. The future of condensed matter physics is never-ending since our landscape, while being complex and vast, is forever accessible. Sometimes we may have to wait for a long time for exploring parts of the landscape. One example is the Bose-Einstein condensation (BEC), a highly coherent quantum phase of matter akin to a laser beam made of atoms rather than light, which was predicted in the 1920s, but was discovered in the laboratories only in the mid-1990s (a 70-year waiting period, much longer than the Higgs particle, which took 50 years for its discovery) when experimental techniques to cool atomic gases to temperatures as low as nanokelvins were eventually developed. Another example is the existence of non-Abelian quasiparticles, which are neither fermions nor bosons (the two types of fundamental particles defining the standard model), which have been predicted to exist in certain low-dimensional condensed matter systems. They have not been directly experimentally discovered yet in spite of rather intense search over the last 10-15 years. I am convinced, however, that they exist and will be found in the laboratories although I do not know how long it will take, I certainly hope that it is not 70 years. When found, these non-Abelian quasiparticles would enable a particular kind of fault-tolerant quantum computation, called 'topological quantum computation', which would not require extensive error correction protocols for its operation.
An obvious fact is that the condensed matter landscape is independent of the existence or not of the string theory multiverse landscape. The condensed matter landscape would be unaffected if the string theory landscape disappears tomorrow because of some spectacular new theoretical breakthrough, and the condensed matter landscape of phenomena and phases was here long before string theorists started discussing the multiverse landscape. The fundamental equation of condensed matter involves electrons, nuclei, and electromagnetic interactions, which are completely unaffected even by discoveries within the standard model, let alone developments in string theories. The discovery of quarks, W and Z particles, and the Higgs particle did not in any way affect condensed matter physics since all of these are involved with very high-energy intra-nuclear physics, which is not relevant for condensed matter phases and phenomena. One of the basic pillars of theoretical physics is that physics at one energy or length scale is typically not affected by physics at very different length and energy scales. For example, we do not need to apply quantum mechanics to do weather forecasting, and the complex civil engineering of building skyscrapers does not require any information about the arrangement of quarks inside the nuclei. This independence of the condensed matter landscape from the ultimate laws of particle physics makes condensed matter physics both particularly rich and particularly subtle. The existence or not of super-symmetry, important as it is in understanding the hierarchy problem in the standard model of particle physics, will have no direct bearing on condensed matter physics. Indeed, the experimental discovery of the Higgs particle in 2012 was an earth-shattering event in particle physics (just imagine what would have happened if the Higgs did not show up in the LHC experiments), but had no direct effect whatsoever in condensed matter physics.
One of the most important and theoretically mysterious aspects of the condensed matter phase/phenomena landscape is the emergence of biological life, and perhaps even more significantly, conscious intelligent life (such as ourselves) somewhere in that landscape. A part of this landscape, human beings, likely to be a set of measure zero in the landscape filled with lifeless phenomena and phases, gets to think about the landscape itself! What we humans refer to as 'consciousness' may very well be the ultimate emergent collective behavior (in the brain), which most likely will forever remain inaccessible to reductionist 'ultimate' laws of physics. This seems miraculous and probably explains why religion has been so central to such a large number of humans for a very long time. It is much easier to just give up and think of a supreme being ordaining everything than to actually accept that the landscape is exponentially large, allowing many unpredictably complex possibilities, even conscious life itself. Apparently, there are close to 10 million known species of life on the earth, and this is a very small fraction of the actual number of species, a recent publication speculates that it may take 1000 years just to identify all the species!
All of these biological species are controlled by precisely the same fundamental reductionist condensed matter equation involving electrons, nuclei, and Coulomb interactions as inanimate objects such as metals and magnets are. In that sense, from the viewpoint of theoretical physics, life, even conscious intelligent human life capable of blogging and idly speculating on the nature of physical laws, is just an emergent collective property of the fundamental equation, residing somewhere within our vast landscape of phenomena and phases exactly the same way as superconductors, magnets, liquids, crystals, glasses, and all other materials that condensed matter physicists study in the laboratory. It is humbling to realize that the basic law underlying humans is the same as that controlling a magnet.
However, this knowledge is also manifestly useless because every human knows that human beings are qualitatively different from magnets. This, in a nutshell, is the problem of insisting on a fundamental ultimate law. It is unclear that the enigma of consciousness, which we all feel, but is hard to describe, will ever be quantitatively explained by an ultimate law using building blocks of electrons and nuclei (let alone, leptons and hadrons) interacting through fundamental forces. We may discover in the end that such a law is irrelevant for answering some of the most important questions one may have. Such an ultimate law would tell us nothing about how to cure stage-4 terminal cancer or how to eliminate the covid-19 pandemic. It most certainly will not tell us how to eliminate poverty in the world, cure all the childhood diseases, end violence, or improve human tolerance for each other.
Finally, I will comment on QED, undoubtedly the most successful fundamental theory homo sapiens have ever created. Experiment and theory agree to better than 10 decimal place in QED, this is an astonishing achievement of human intellect. The great success of QED is, however, purely accidental and dependent entirely on the basic QED interaction strength alpha~ 1/137 being small. This enables one to expand the fundamental equation in powers of alpha, and keep only the first few powers in a systematic manner. Why is alpha small? We have no idea, it is an experimental fact that alpha is small. Actually, alpha is not a constant at all, it changes with energy (slowly), and it happens to be small only at our usual energy scales. If you go to very (unimaginably) high, but still finite, energy scales, alpha actually diverges, making the premise of the whole QED theory questionable. This problem has the historical name of Landau pole or Moscow zero. The spectacular success of QED is based only on the accidental fact that alpha at ordinary energy scales happens to be very small (~ 1/137) in our universe. We have no way of predicting alpha from any deeper fundamental theory, all we can say is that it just so happens that we are accidentally in that universe in the landscape where alpha~1/137.
Another strange aspect of QED is that the perturbation series in powers of alpha is actually only asymptotic, and diverges logarithmically when the series is extended to high powers of alpha. Because of the very small value of alpha (~1/137), this does not pose any problem to the theoretical physicists in our universe, but you should feel sorry for the universe where alpha~ 1 since the perturbation series then would fail already at the first order in alpha (more on this point below). Thus, the spectacular agreement between theory and experiment in QED, which is based entirely on a systematic perturbative expansion in alpha, is a pure matter of luck since alpha is not ordained to be 1/137 because of any fundamental reasons, it just happens to be 1/137 in our universe. The deep sounding question of why alpha is 1/137 allowing QED to be the most successful theory ever is moot because it is simply a boundary condition defining our universe.
It may be intellectually unsatisfactory that our laws (e.g. the precise value of the fine structure constant) are simple accidents (or boundary conditions) of where our universe happens to be in the landscape, but we must live with it. There cannot be any reductionist fundamental explanation for it any more than for why I suddenly chose to write a blog on the topic of the existence or not of physical laws today! Even our most successful reductionist theory (QED) is suspect and not quite internally consistent on its own. This is not just a matter of academic interest. Condensed matter physics has systems (e.g. graphene) whose underlying theory is very similar to QED except that the effective alpha can easily be larger than one (and in some experimental situations, it can be much larger than one). What happens then? The great success of QED goes out of the window because a weak-coupling perturbation theory as in regular QED fails, and we are suddenly in a universe within the landscape where alpha being 1 or even 20 becomes possible. (How one does theoretical physics in a situation where alpha is much larger than one is a highly technical subject beyond the scope of the current blog, but obviously, a perturbation-theoretic approach is not the appropriate starting point.) Such is the complexity/richness of condensed matter physics where the landscape itself, with all its incredible details, is the interesting physics, not the end of physics. I spend much of my time exploring the landscape figuring out which parts of it are manifesting themselves in the current laboratory experiments, and which parts should be observable in future experiments. Phenomena and phases, once thought impossible (or totally unknown), reside in the landscape, and sometimes in our imagination, but most often, sheer serendipity lead to their discoveries. Exploring the phase/phenomena landscape is what condensed matter physics is all about.
Returning to the theme of the ultimate laws of physics, one may argue that quantum mechanics itself is such a law since it has been hugely successful for close to 100 years with no experimental violations. Quantum mechanics is actually more like a set of rules (or a grammar) that we physicists use to express our laws rather than being an ultimate law itself. In addition, in quantum mechanics (or, more generally, in quantum field theories), space and time are variables which are put in by hand and are not emergent. Presumably, space and time should come out naturally from an ultimate law of physics, and not put in by hand as independent variables. It is difficult to imagine that a thousand years from now, physicists will still use quantum mechanics as the fundamental description of nature as we do today; something else should replace quantum mechanics by that time just as quantum mechanics itself replaced Newtonian mechanics. Of course, I have no idea what that something else might be, but I see no particular reason that our description of how the physical universe seems to work should reach the pinnacle suddenly in the beginning of the 21st century, and become stuck forever at quantum mechanics. Note that my firm belief that quantum mechanics, as we know now (1925-2020), cannot be the ultimate law has nothing to do with all the pseudo-philosophical hand-wringing associated with Schrodinger's cat or Wigner's friend and so on, I am neither concerned about the wave function collapse nor about entanglement here. I simply find it difficult to believe that suddenly physics has discovered the final law during my lifetime, and physicists 10,000 years from now would still be using anything remotely similar to the quantum mechanics of today to make sense of the physical world around them. This is simply too depressing a thought to me, just imagine if I were trying to figure out non-Abelian Majorana zero modes and topological superconductivity using the arguments of Aristotle (or even Newton)! Newton's laws were extraordinarily successful for three hundred years, but we had to go beyond them as we learned more about the universe, and the same should happen with quantum laws some day in the future. Of course, any such unknown new theory of the future must build on and incorporate the physics of quantum mechanics, just as quantum mechanics built on and incorporated classical mechanics (for example, quantum mechanics uses the same variables such as space, time, momentum, angular momentum, energy, etc. as classical mechanics does, but with reinterpreted meaning and completely different dynamical laws). Our understanding of the physical world must continue indefinitely unimpeded by any temporally fixed discovery of an ultimate law. Search for a unique ultimate law for the physical world is a fantasy.
This 6th covid-19 blog deals with the closely related issues of 'flattening the curve' and covid-19 fatalities and speculates on the uncertain future course of the pandemic. In contrast to my first 5 blogs on covid-19, this current blog deals less with facts and data, focusing more on matters of principle and theory. As a practicing theoretical physicist, such speculations come naturally to me even if covid-19 is orders of magnitude more complex an experimental problem than anything I have come across in physics. In the end, as a professional theoretical physicist, I must at some point theorize and generalize. I cannot help it.
'Flattening the curve' is likely to be among the first jargons a lay person came across in the context of the current pandemic, right after the terms coronavirus, covid-19, and SARS-COV2. It is rather surprising that the Wikipedia page on 'Flattening the curve' was created only on April 7, 2020 more than two months after the first covid-19 case was reported in the USA. This is more than 3 months after SARS-COV2 wreaked havoc in Wuhan, more than 2 months after WHO declared covid-19 to be a public health emergency, and almost 3 weeks after WHO announced covid-19 to be a global pandemic. The first covid-19 case was officially announced in USA in late January and the first death in February. (It is very likely that the actual first SARS-COV2 infection occurred in USA much earlier, perhaps in late December.) New York Times already mentioned flattening the curve on March 12, and by late-March most Americans were familiar with the terminology as social distancing was imposed by the authorities across the country in most localities, ostensibly to 'flatten the curve'. The expression is now used every day in every newspaper and TV news report in discussing covid-19. But what exactly is it? And why is it important?
There are widespread misconceptions about 'flattening the curve'. In epidemiology, flattening the curve refers to using mitigation mechanisms (e.g. social distancing, shelter at home, quarantine) often imposed by the government or local authorities to suppress the sharp exponential initial rise of the number of infections as a function of time so that the public health system has time to respond. Imagine an epidemic starting with just one infected person in a community (e.g. a city, a county, a state, a country) where each infected person infects three other persons on the average per day. This would be referred to as r=3, where 'r', the so-called reproduction number, is the number of new infections per day for every infected person, it is the effective number of persons each infected person infects every day. After n days (we ignore all recovery and fatality for simplicity, assuming that the recovery and fatality times are rather long, which is a valid assumption), there will be roughly r^n new infected people: on Day 1, 3; on Day 2, 9; on Day 3, 27; on Day 4, 81; and so on for r=3. This is called exponential growth since the number of new infections is growing very fast as a power law in the number of days. Now, suppose that each infected person infects only two other persons per day on the average because of social distancing (r decreases from 3 to 2 because of reduced person-to-person contact), so that now the number of new infections per day increases as 2, 4, 8, 16 and so on day by day with new infections now growing as 2^n. Then after n days, the number of new infections per day has decreased by a huge factor of (3/2)^n. After 10 days, this amounts to an almost a factor of 58 decrease in the daily new infection rates. We have 'flattened the curve' because the daily infection rate went down in n days from 3^n to 2^n. The number is still increasing at an alarming rate, but the rate is much lower than that without any social distancing. What happens if we can bring down effective r to unity by very strict social distancing so that each infected individual on the average infects just one person per day, then the infection rate hardly goes up at all, the curve has been maximally flattened. Of course r=0 is still better, but then we have no epidemic to talk about.
So, the goal of social distancing is to flatten the curve or equivalently to reduce the effective reproduction number r. It all sounds very straightforward with little scope for misunderstanding. The problem (and any consequent misunderstanding) arises from asking how this flattening eventually ends without the intervention of a drug (or vaccine) to eliminate the disease. The truth is that flattening the curve is not equivalent to the elimination of the contagion. No matter how low the infection rate induced by the flattening, everybody in the community will eventually, given enough time, get infected even if the infection rate is very low because the virus has not vanished from the community (again, I am ignoring immunity and recovery from consideration here for simplicity). If we assume an r=1 so that each infected person infects on the average only one new person per day, the number of infected persons would still increase as 1+2+3+4...+n= n(n+1)/2 ~n^2/2 after n days. So, after 10 days there will be roughly 50 infected persons, which is a factor of 40 lower than the total number of infected persons (~2000) if each infected person is infecting 2 others per day but is not zero. Without the intervention of vaccine/drug, social distancing by itself would not eliminate the disease, all it would do is to slow down the rate of increase of infection as long as social distancing continues, thus buying us time to find an effective vaccine or treatment.
Flattening the curve helps reduce the rate of increase in infection enormously, thus increasing the time period over which the disease progresses slowly. Flattening the curve without a medical solution does not eliminate the disease, but helps the community buy time to find a solution. Also, social distancing must continue indefinitely in some form for the curve to remain flattened until the virus actually vanishes on its own or some effective treatment/vaccine is introduced.
Let us dig a bit deeper into flattening the curve. Suppose the community is New York City with a population of 10 million, and initially r=3, with no social distancing. So the number of daily new infections goes as 3^n on the nth day, and the 10 million people in NYC are all infected just in 12 days. For example, on the 13th day, 3^13= 1,594,323 people would have been infected for r=3 even starting with just one infected person in the beginning. So, the absolute total infection peak in this no-mitigation (r=3) scenario is reached only in 12 days with the whole population of the city infected (again assuming no immunity and no recovery for simplicity). If social distancing brings down the value of r to 2, i.e. each person infects only 2 persons per day instead of 3, then it will take 19 days for the whole population of 10 million to be infected. The curve being sharply peaked in 12 days with all 10 million inhabitants infected for r=3 is now peaked in 19 days for r=2 – To a flattening in time by more than 50%. For r=1.5, when each infected person infects one and a half persons on the average per day (which means half the people infect one and the other half infect two per day on the average), it takes 31 days for 10 million people to get infected. What would happen if social distancing brings down r to just 1 so that the total infection is now increasing only as n^2 in contrast to the daily infection increasing at the exponential rate of 2^n or 3^n. It will now take 4472 days, which is more than 10 years, to infect all 10 million people. The curve has been flattened in time by a factor of 373 by suppressing r from 3 to 1—this is the power of flattening the curve, but only if r has been reduced to one or below by social distancing.
Going from r=3 to r=1.5 only flattens the curve by a factor of 31/12, which is less than 3, but going from r=1.5 to r=1 flattens the curve by the huge factor of 4472/31=144. For r>1, the infection growth is exponential, and the curve has not been substantially flattened even if it decreases (e.g. from r=3 to r=2 or r=1.5). Only when stringent social distancing brings down the effective infection rate to r=1 (or below), the curve has been effectively flattened, and it may seem that the problem is completely solved. Untrue. This is because the assumption underlying all these estimates is that the social distancing continues indefinitely even after r is brought down to one or below. Otherwise, if social distancing stops right after reaching r=1, the infection rate may start increasing exponentially again, and we may return to the disastrous 'unflattened' situation with r>1.
It is therefore not enough to flatten the curve and stop social distancing, because then the infection may start growing exponentially again with r increasing above one, infecting all 10 million people in just a few days. So, all flattening the curve does is buy time, in fact, a lot of time if r can be brought down to unity (and only a little time if r remains above one). But to maintain the advantage of flattening the curve, the social distancing must continue indefinitely at some level so that r remains at or below one, otherwise the advantage of flattening will disappear in a matter of days (as is most likely happening right now all over the southern US with the infection rate increasing like crazy in Arizona, Florida, South Carolina, and Texas, where lax social distancing has been amply documented by the press). Until a vaccine or an effective therapy comes along (or if the virus suddenly disappears mysteriously because of some random mutation or some other reason), social distancing by itself only buys time, and does not cure the disease.
Social distancing to flatten the curve must continue indefinitely for the pandemic to remain under control in the absence of a vaccine or effective treatment. This is not universally recognized, even after the authorities lift the strict enforcement of social distancing through phased relaxations, as is happening all over the country (New York City and Washington DC just entering their Phase 3 relaxation), people must continue social distancing voluntarily as much as possible through wearing face masks, avoiding crowded places, and staying home if sick! If not, exponential growth with r>1 is bound to return, and complete lockdowns by the authorities will again be necessary.
The real importance of social distancing arises in the context of hospitalization logistics. If the infection rate is increasing too quickly, as it would if r is larger than one, hospitals and all medical facilities are quickly overrun by the infected patients, creating complete chaos and likely leading to many deaths because of the lack of any medical care for most patients since all the hospitals are full. Therefore, early and sustained social distancing could save a lot of lives simply through its secondary effect of keeping the medical system viable without overwhelming it with too many patients too quickly. Flattening the curve leads to a much slower rate of growth of the disease (lasting over a much longer period of time) even if equal number of patients are infected over a long period of time (many months or a year) anyway, thus enabling the public health system to cope with the patient load at any particular moment in time.
After all, a situation with 10 million covid-19 patients coming to hospitals over a 10-year period is very different from a situation where 10 million patients are brought to the same hospitals in 15 days. This is the most important reason to enforce a strict and early social distancing protocol. In fact, any delay is deadly, if exactly the same social distancing (suppressing r from 3 to 1) starts on the 2nd day versus the 5th day (from the very first infection), the difference in the number of new patients just on the 7th day would be 12 patients versus 1200 patients, a factor of 100! These numbers demonstrate the great importance of early mitigation, a delay of even a few days in enforcing social distancing could lead to a total disaster. This is what happened in Wuhan originally, and then in Italy, and also in New York City. By contrast, Taiwan, Hong Kong, Vietnam, Germany, Japan, Singapore acted early in their social distancing protocols, thus doing a more effective flattening of their curves. Ending the social distancing early (e.g. before r reaches well below one) could also be deadly (unless a treatment and/or a vaccine has come along meanwhile) because going back to the 'normal' could mean that the r-value might creep back from being below 1 to above 1 in a short time, and therefore, any complete relaxation of social distancing could bring back an exponential growth in the infection rate almost instantaneously.
The good news is that social distancing most certainly helps keep the disease under control, the bad news is that without the disease actually suppressed medically (a vaccine, a therapy, a mutation, perhaps external conditions such as weather) the artificially induced flattening the curve through social distancing only helps as long as it continues, it cannot be a permanent solution by itself.
The above discussion clearly shows the importance of face masks, avoiding crowds, not allowing too many people in a room, quarantine of the infected people, etc. even after strict social distancing and lockdown have brought the infection spread under control (which means that r has decreased to one or below, and the daily infection growth rate is no longer exponential). Everything must be done to maintain r below one, otherwise we are back to square one, and the infection will start growing exponentially again (Alabama, Arizona, Florida, South Carolina, Texas, etc.), with the necessity of strict government-induced lockdown happening again. The lockdown imposed by the authorities, if enforced stringently, can indeed suppress the infection growth from being exponential (i.e. r>1 with the daily growth going as r^n) to a slow power law growth (i.e. r=1 or <1 with the total infection increasing as n^2 or slower), but eventually, all societies must come back to some semblance of normalcy, so the stringent lockdown must be relaxed once the curve has been flattened with r being less than unity. This is what is going on all over the Northern Hemisphere, and particularly in USA, where phased relaxations of social distancing are occurring everywhere so that life (and the economy) can return to some kind of normal, which would be impossible with a complete lockdown.
The inherent problem with such relaxation is that if people do not voluntarily maintain reasonable social distancing on their own, r will surely rise, passing unity, and the exponential growth will simply come back with a vengeance. This may have already happened in Arizona, parts of India and Russia, and possibly in Florida and Texas. This may also be happening in many of the US southern states, where the lockdown started late and ended early. Most likely, in many of these states the lockdown ended when r was barely below unity, and once the authorities relaxed the forced lockdown, people simply ignored social distancing, and within a week, the infection growth became exponential again. Unfortunately, lockdown and social distancing do not eliminate the disease, only vaccines, effective treatments, and the eventual development of 'herd immunity' (which is very far in the future for covid-19 since it is a brand new virus for humans) can eliminate the disease. Social distancing done correctly gives us time (possibly, a lot of time) to develop treatments and vaccines, but without social distancing, the exponential growth is bound to return with the consequent disaster of an overwhelmed public health system and many fatalities.
The importance of vigorous continued voluntary social distancing once the lockdown has been lifted is an absolutely essential public health necessity in keeping the covid-19 under control at this stage when a vaccine is not within sight. All one has to do is to look at the countries/regions like Taiwan, Hong Kong, and South Korea which have been extraordinarily successful in controlling covid-19 in spite of being extremely vulnerable to SARS-COV2 because of their geographic locations and population densities. The people in those places have maintained strict voluntary social distancing to keep covid-19 under control for more than 6 months now. This can be done, but everybody must wear face masks, avoid crowds as much as possible, and stay away at home if any sickness of any kind develops. This is our life in the foreseeable future. The alternative is an exponential growth in the infection rate, no matter how flattened the curve has been in the past. Just ask the people in Arizona!
It may be sobering to briefly discuss the best estimated current r values for different parts of the US and compare them with the past r values to infer about the course of the pandemic in USA. A word of caution in this context is that r estimates are always very approximate and prone to large errors since they change day to day and depend on many local factors such as the rate of testing. Nevertheless, the comparison of r among different states at the same time and for the same state at different times gives us a qualitative idea about the pandemic trend. Right now, June 15-21, 25 states in the USA have r exceeding unity (ranging between r=1.02 and 1.60), and two months ago, in mid-April, only 6 states had r exceeding unity (ranging between r=1.02 and 1 .11). Interestingly, only one state (Kentucky) has had its r-value above unity throughout the last two months, but fortunately, its r hovered around 1.02 throughout, which is not great, since r>1, but is not disastrously dangerous either. It is manifestly obvious that the covid-19 pandemic has worsened in mid-June in the USA from the viewpoint of increasing infection rates. Texas (r=1.16 now versus 0.86 in mid-April), South Carolina (r=1.20 now versus 0.79 in mid-April), Arizona (r=1.28 now versus 0.91 in mid-April), and Florida (r=1.39 now versus 0.81 in mid-April) are rather representative of the states in the south with serious exponential growth problem (only a part of this increase could be attributed to enhanced testing). The fact that all of these states initially did manage to flatten their curves (in the sense that they all had r<1 in mid-April) through social distancing is telling. This means that the lifting of the original lockdown has led to people simply relaxing social distancing to a dangerous degree, increasing r back above unity.
By contrast, the originally hard-hit and densely populated northeastern states such as New York (r=0.83), New Jersey (r=0.75), Massachusetts (r=0.69), and Connecticut (r= 0.72) have flattened the curve and then maintained the flattening very effectively through strict social distancing (and through intelligent voluntary measures) even after the phased relaxation of the lockdown. The difference between and r=1.39 (Florida) and r=0.83 (New York) is huge. For r=1.39, there will be a total of 68 infected persons after 10 days starting with just one infected person spreading the virus whereas for r=0.83, there will be only 6 infected persons after 10 days, a factor of 11 difference in the number of infections already during the first 10 days, and of course the difference keeps on growing exponentially in time. Everything should be done to re-flatten the curve in the southern US states by bringing back stringent government-imposed lockdowns if necessary. Otherwise, it will be a matter of days before covid-19 infections start growing exponentially all over US since people do move around from state to state taking their virus with them.
It is also clear why extensive testing is crucial in this context. Only infected people, whether they are sick or asymptomatic, can infect others. Imagine a scenario, where we automatically know every infected person in the community each morning by 'some magic'. Then, we do not need across-the-board social distancing or lockdown of the whole community, all we need is to quarantine those who are infected so that they cannot infect anyone else. It is that simple. This magic of course is easily conjured by having extensive and intelligent testing of the community, which is obviously much less constraining than locking down the whole community. If we can locate the infected people and also the people whom the infected people came into contact with (the so-called 'contact tracing'), we can completely suppress the growth of infection simply by isolating the infected people until they are no longer infected. We do not need to flatten the curve by isolating everybody at home, we only need to isolate the infected ones if we can find them—there will be no curve to flatten in such a scenario of extensive testing.
This is what Taiwan, Hong Kong, South Korea, Singapore (for a while at least), Vietnam, Germany have done well (and China did eventually very effectively after ignoring the initial crisis in Wuhan for a while). The US public health officials and US Governments (both federal and local) have failed miserably in this respect, and the fact that US has both by far the highest numbers of infections and fatalities from covid-19 can be directly correlated with our pathetic failure in testing and contact tracing, and consequently, in accomplishing any effective isolation of the virus-spreaders. We have so far tested only about 6% of the population, which is simply too low a number in a country where 0.6% already test positive for the virus.
A real concern in this context is the somewhat uncontrolled and unwise social distancing relaxation going on right now all over the southern US states, which may lead to a total disaster with the exponential covid-19 growth (i.e. r exceeding unity) coming back all over the country, necessitating a total lockdown (and the associated economic breakdown) again all over USA. It is clear that a national policy on testing, contact tracing, and social distancing is badly needed to avoid a nation-wide huge disaster in the near future. The unavoidable truth is that the US public health system has so far failed miserably in controlling covid-19, no matter how one looks at the situation. With only 4% of the global population, USA has 30% of the reported global infections and 25% of the reported global covid-19 fatalities. This is an astonishing failure for the world's leading economic, scientific, and technological power. Other countries which were hit hard by covid-19, such as China, Italy, Spain, France, UK, all managed to control their covid-19 crisis much more effectively than US has done. Imagine a scenario where the US is in an actual military conflict with a hostile enemy invading the homeland, and 120,000 Americans die during the first 4 months of the war, which is a much higher rate of fatalities than in any war US has ever been involved with including the two world wars and even the civil war. How would the nation react then? What would have our government done in such a dire situation?
Finally, I will comment on covid-19 fatalities. As described above, the effect of flattening the curve on covid-19 fatalities is indirect. Flattening the curve suppresses the exponential growth of infection, thus avoiding the invariable overwhelming of the medical system in the community which is bound to happen in a very short time (just a few days!) if the exponential growth continues. If the medical system is overwhelmed and all the hospitals are overflowing with patients (this happened in Hubei province in China in mid-January 2020 and the Lombardi region of Italy in March 2020), then obviously many more people are likely to die from covid-19 simply because of a complete lack of even rudimentary medical attention. So by flattening the curve, we not only suppress the exponential growth of the infection itself, we also reduce the number of fatalities as an important secondary effect. Unfortunately, the situation does not improve permanently unless a vaccine comes or some herd immunity develops, and it is possible that lockdown and relaxation will have to continue periodically for the indefinite future as the curve flattens during the lockdown, and then unflattens going back to exponential again as people ignore social distancing and face masks when the lockdown is lifted by the authorities. Of course, the virus could mutate and just vanish, but we cannot count on miracles to help us here.
So what does the future hold? I can only guess, but my guess is as good as anybody else's at this point of ignorance/uncertainty about covid-19.
First, I am not optimistic about an effective vaccine magically appearing in the market in less than two years. The fastest vaccine development ever (for mumps) took four years. In addition, no coronavirus, in fact no respiratory infection, has any effective vaccine. Of course, developing a vaccine for common cold does not probably provide a terrific profit incentive. By contrast, any company developing a successful SARS-COV2 vaccine may become a trillion dollar enterprise with a potential 7 billion worldwide customer base. So capitalism may help the cause of a rapid vaccine development. I certainly hope that my guess is completely wrong, and an effective vaccine is developed quickly. Then, what? The Phase 3 trial for this vaccine must involve millions of people to ensure that any harmful side effect is less than 0.1% or so. Even for a very small 0.1% adverse side effect, millions of people may be affected since billions will be vaccinated, so the logistics of ensuring the efficacy as well as the safety of such a vaccine would be a real challenge. Such a clinical trial by itself may take years.
What about herd immunity, which in this context means that so many people are already infected by the SARS-COV2 virus that it can no longer spread because most people are immune to it as they have been already exposed. There is a hypothesis, never proven clinically, that the reason behind the 1918-19 Spanish Flu not killing a large number of older people above 65 in age (a large fraction of the 100 million or so fatalities in the 19818-19 flu occurred in the 20-30 age group in sharp contrast to covid-19 where more than 80% of the fatalities are in the above-65 age group) is because these older people were unknowingly exposed to very small doses of the virus a long time ago, perhaps in their childhood, without showing symptoms but achieving immunity. How long would it be before 70-80% of the world is infected by SARS-COV2 in order to develop herd immunity? A very long time, of course, although how long is very difficult to calculate as it depends on far too many unknown details. Right now, even in New York City, the estimated infection rate is only about 20% of the population of the city, for the whole USA, the number is less than 1% obviously, there are 360 million people in US, and we have 2 million reported infections. Even including the possibility of a large undercounting of the infection rate, reaching an 80% infection rate in the whole world would take a long time.
Thus, both vaccine and herd immunity are in the far (and unknown) future, certainly more than a year away, perhaps several years away. One irony here is that flattening the curve, so essential for the control of the disease, works strongly against the development of herd immunity since the infection rate is being kept low deliberately through flattening. If we allow the natural exponential infection rate without any external mitigation (and therefore no flattening), herd immunity will come in a matter of months , if not weeks, but the problem is that so will come millions of death from covid-19. In my hypothetical example of r=3 in a community of 10 million people, everybody gets infected in two weeks without any social distancing or flattening, thus providing very quick herd immunity, but at a fatality rate of 5% (which seems to be the current best fatality estimate in the USA based on the reported infections of 2.2 million with almost 120,000 fatalities as well as a world infection number of 8.5 million with a reported fatality of 457,000, the fact that these numbers are likely inaccurate does not in any way change the point of principle I am making here) will then lead to 500,000 fatalities from covid-19 just in New York City, the equivalent number for the whole USA will be 18 million dead, but the rest of the population perhaps enjoying herd immunity. For the whole world, the number of fatalities if everybody gets infected, thus guaranteeing herd immunity, will be 350 million dead, assuming the same 5% fatality rate It is certainly possible that this (i.e. world herd immunity) is how the Spanish Flu of 1918-19 seemingly disappeared after killing 100 million people, and leaving the rest immune to the virus. We cannot rule out the possibility that in the end, covid-19 will do the same.
Scientifically, it is possible for such a nightmare to occur, if we cannot develop a vaccine or a treatment. It therefore does not seem like a reasonable proposition to let the virus grow unchecked in order to provide mass herd immunity quickly! I note that 100 million dead in 1918-19 is approximately a similar fraction of the world population (around 1.8 billion in 1918-19) at that time as 350 million dead would be compared with the current population (approximately 7.8 billion). Let us hope that this does not happen, but hope, by itself, will achieve nothing unless we adopt voluntary social distancing as an essential part of our future life style just as we put on jackets in the winter to stay warm and obey traffic lights at intersections in order to avoid accidents. Voluntary and habitual social distancing and wearing face masks must become an essential part of our future lifestyle until covid-19 has truly disappeared.
The other problem with the herd immunity scenario is that we simply do not know how good the immunity to SARS-COV2 would be. Is it possible to get infected repeatedly? We do not know. Is it possible that subsequent infections, even if they happen, are no longer life-threatening? We do not know. What if any immunity lasts for a very short time and is not very effective? We do not know. After all, people can catch bad colds several times in one season, it does not appear that humans develop effective immunity to the cold coronavirus. So, herd immunity is not guaranteed by any means for SARS-COV2 even if the infection goes through the whole community.
I am, however, reasonably optimistic about the development of some kind of (at least partially) effective drug therapy treatment for covid-19. After all, the disease kills through pneumonia or other respiratory problems or through a direct immune reaction. These are treatable conditions, e.g. pneumonia has many effective treatments and anti-inflammatory drugs should be effective in curing some aspects of the covid-19 illness. My hope, therefore, is that covid-19 eventually will become similar to a serious flu, very dangerous if one catches it, but effective treatments should eventually be available. Meanwhile, we must maintain vigorous social distancing, avoid crowded places as much as possible, and wear face masks in all public places.
An absolutely key issue to remember is that we live in a closely physically interconnected world where even national boundaries, let alone state or county or city boundaries, mean little as people travel (in the absence of a total lockdown/quarantine) back and forth everywhere. Our global economy is based on the premise of global connections and international trades, and within the US we believe that we can travel where ever we want whenever we wish. Thus, lifting lockdowns immediately leads to the whole world becoming a single habitat for the SARS-COV2 virus! Thus, flattening the curve bringing r all the way to zero in one region or locality means little if the virus is growing exponentially elsewhere. We are truly in it all together because of the total geographic interdependence of modern economy and modern life. The curves must be flattened everywhere, otherwise in some sense it is not flattened anywhere because of our intrinsic interconnectedness.
If covid-19 is growing exponentially in Florida, New York City and Washington DC are no longer safe even if these cities brought down their effective r-values well below one by strictly enforced social distancing, all it would take is just for one infected person to move from one region to another for the exponential growth to start all over again unless we are all vigilant in voluntary social distancing round the clock independent of how low the current local infection rate might be. Just look at what happened in Beijing last week with the sudden appearance of a large covid-19 cluster (and the consequent complete lockdown immediately enforced by the authorities) seemingly from nowhere in spite of the authorities being sanguine that SARS-COV2 has been vanquished in China. Nothing can be taken for granted for the foreseeable future independent of how benign a particular time and place may appear.
There is no question that, whether we like it or not, covid-19 will impose permanent changes in our lifestyles in many fundamental ways. The virus does not care how we feel, it has found a very effective vector, humans who love being socially crowded together, to multiply, and it will do so as much and as long as it can. We cannot stop its march just by wishing so. Going back to the normal, if 'normal' is defined by the way life was a year ago in June 2019, will take a very long time, at least several years. A highly infectious air-borne virus with a high mortality rate and a relatively long latency period is a formidable enemy.
Now that the 2020 summer is almost officially here (June 20-September 22, 2020), I expect covid-19 to subside in the US, and this blog in this series will address the specific issue of sporadic recent outbreaks of covid-19 with increasing infection rates (as of this week, June 7-14) in several US states, and several parts of the world.
What do they imply? Is the disease roaring back? Is the much discussed second wave here? Is sheltering at home going to be re-imposed just as most states are relaxing their lockdowns and starting phased reopening? Is the pandemic increasing/decreasing worldwide
First, a word of caution. I have no special insight here, this is not the physics of Majorana zero modes in nanowires, where I can pass expert judgments based on my specialized knowledge. I know little about covid-19, but so does everybody else it seems. Seeing the ambivalence of the leading health experts on the topic, whether they are from CDC or WHO or NIH, that it 'may be this or perhaps that', and reading as many technical epidemiological covid-19 publications as I can find, I have concluded that nobody out there knows more than I do. This is of course not good because I know little, but this is not unexpected. This is a very hard problem, and we do not have any past experience dealing with a pandemic of this magnitude affecting the whole world. So, people are making their best guesses.
Most technical simulations of the problem are rather trivial from a physicist's perspective. They involve either plotting all the data for infections/fatalities on a daily basis, and then smooth numerical extrapolations or numerical solutions of a set of simple differential equations (the so-called SEIR model: susceptible/exposed/infected/recovered) using a large set of unknown parameters (with many more parameters than dynamical variables) with unknown initial conditions. Predicting where covid-19 is going is essentially as difficult as predicting the weather or the stock market. One may have some limited success over a very short time period by recognizing and then extrapolating some hidden patterns in the existing data, or by integrating a set of nonlinear equations over a short time period, but long-term predictions are essentially impossible. Indeed, even after the fact, post-diction (let alone before-the-fact prediction) is difficult for pandemics. There is no universally accepted mechanism for the apparent disappearance of the 1918-19 Spanish flu after killing around 100 million people. One should therefore take with a grain of salt various recent publications claiming that covid-19 infections would have reached 60 million people if various social distancing measures were not put in. These claims are unverifiable in a scientific sense, and if you look at the actual model predictions as a function of time, you find that all models are consistently under-predicting the number of infections and deaths even over short time periods.
Predictions are necessary of course to give us some baselines, but to the zeroth order nobody knows anything in regard to what we refer to as 'knowledge' or 'prediction' in physics. Gravity waves were really predicted in 1917 and the Higgs boson was really predicted in 1964, although they took 100 and 50 years respectively to be realized in the laboratory to become facts. No such hard prediction is possible for pandemics (or stock markets). I would challenge any public health expert to predict the infection rate and fatality rate of covid-19 in November 2020 in USA. I am willing to bet a 100-point Napa Cabernet Sauvignon that I have in my basement if someone can predict the actual future covid-19 numbers six months from now within a 10% accuracy!
Well, first the good news. The pandemic is most definitely decreasing in the Northern Hemisphere right now (see my blogs 2 and 3) with the fatality rates going down essentially in all countries with the impending summer. This is simply a statement of fact, which applies to the US and the whole world, with the current exceptions being a few Southern Hemisphere countries (e.g. Brazil). By contrast, however, the infection rate is going up slightly (for the last couple of weeks) in the overall world statistics (see blog 2). How long this decrease in the fatality rate will continue and what is causing it are unknown, but the decrease itself is a fact.
It is, however, indeed true that many southern US states are showing increased covid-19 infection rates right now, and in some cases substantial hospitalization have increased also. Among the hardest hit states right now are California, Arizona, Texas, Florida, and North Carolina. See some examples below taken from NY Times of June 13. What is going on? Why is the infection rate going up in 23 states while decreasing (or remaining the same) in 29 states/regions? Is this the second wave? Are we doomed? Do we need to lock down again?
The key to answering these questions lies in quantitatively comparing the covid-19 fatality rates per capita in the states where the infection rate is increasing versus where it is decreasing. The infection itself could increase for a number of reasons, for example (and most importantly), more testing. The infection rate is a poor indicator of the covid-19 intensity compared with the fatality rate (see blog 2) because the infection rate statistics are highly inaccurate and increases/decreases almost randomly with the rate of testing. The fatality rate is a better measure simply because deaths are reported accurately in most localities. The covid-19 death rate per 100,000 in the states with an increase in reported covid-19 infections ranges from 1 in Hawaii to 16 in Arizona, with the median rate of around 10 per 10,000. By contrast, the covid-19 death rates in the northeastern US (New York, New Jersey, etc.) with decreasing infections range from 40 to 157 per 100,000 with a median death rate more than 5 times that of the states with the increasing rate.
What does this mean? It means that the states with increasing infection rates are simply at the beginning of their first wave, perhaps because of less vigorous early testing and less stringent social distancing. However, while the infection rates are seemingly increasing in the south, they are much lower than the truly hard-hit northeastern states, so the situation is not dire yet.
States like Arizona and Alabama had little overall covid-19 infections so far, and therefore, the rate is growing more quickly in these states. Going from 1 infection to 2 is a 100% increase, whereas going from 100,000 to 110,000 is only a 10% increase! It is simple arithmetic which is driving the increase in these sates right now, and the situation may turn around soon with overall infection rates decreasing everywhere by July 1.
The dramatic increase in the recent infection rates in a large number of southern states most likely arises from a combination of reasons, each set of reasons varying in details for each state, and only a careful quantitative analysis could figure out the cause. My guess is that it is a combination of the following factors: enhanced testing, very slow (and often tepid) response to the initial infection, a general reluctance to adhere to social distancing and wearing masks (often encouraged by local politicians, who are remarkably ignorant and irresponsible), and a late start of the first wave of covid-19 which has been exacerbated by the extremely unwise early relaxation of lockdown. In spite of all of these factors contributing to the increased infection rate, I point out that states like Florida (8th in population density and 28th in covid-19 per capita infection rate), Texas (26th and 36th), Arizona (33rd and 23rd), Alabama (27th and 26th) still have rather low covid-19 infection rates (and even lower fatality rates) compared to the northeastern US states where covid-19 is decreasing at a rapid rate.
It may be useful to dig a little deeper into the covid-19 numbers in some of these states that are currently experiencing increasing numbers of infection. It is a challenge to find granular covid-19 data for individual states, but I have managed to find the detailed data for Arizona, California, and Florida, which are among the three warmest US states. All three states have reported (see the graphics) recent increases in the daily covid-19 infection rates, with Arizona showing the steepest increase. Arizona is also by far the hottest state with Phoenix temperature going above 100 degrees essentially every day in the May-August period. I cannot think of any reasons besides enhanced testing causing the sudden jump of Arizona's covid-19 infection rate on June 1. It is very unlikely, if not impossible, for the real infection rate to suddenly jump from ~ 700 daily on May 30 to ~ 1400 daily on June 5 except for greatly enhanced testing. I conclude therefore that this is an apparent infection rate increase and not a real rate increase. It is possible that the real rate increased somewhat too because of early social distancing relaxation, but this is likely to be a smaller effect than the apparent increase caused by enhanced testing.
Very similar sudden jumps in the reported daily infection rates in many other states (e.g. Hawaii, Alabama, Texas, South and North Carolinas) are also likely to be apparent rate increases due to enhanced testing. Looking at the daily fatality rates should give us a better perspective on the course of the disease. I emphasize that the reported fatality rate is a much better figure to understand the scope of the disease than the reported infection rate, if for no other reason than the fact that the reported fatality rate is likely to be much more accurate. In Arizona, the fatality rate hardly budged during the May 7-June 15 period, although the apparent infection rate went up. In fact, although not statistically significant because of large fluctuations in the day to day numbers of covid-19 fatalities, one can argue that the covid-19 fatality rate in Arizona has actually decreased between May 7 (26 deaths) and June 10 (7 deaths). A similar decrease is also apparent between May 23 (22 deaths) and June 12 (2 deaths), and so on. It is therefore untrue that Arizona is undergoing a severe increase in its covid-19 affliction, perhaps the only increase is an apparent increase in the infection rate because of more testing.
A very similar story emerges also in California and Florida, where reported infection rates have also gone up over the last 2-3 weeks. In California, the death rate was 105 on May 15 and 27 on June 14, a factor of 4 decrease in the daily death rate. In Florida, the number of deaths on May 14 and June 13 were the same (47), and the overall daily death rate has decreased from a peak of 83 on April 28. In both California and Florida the reported infection rate has increased (see graphics), though not as dramatically as in Arizona. An important statistical fact in this context is that the total death rates in all these states, with increasing infection rates, have remained linear or slightly sub-linear in time, implying that the disease is most certainly not increasing in any manner right now during the summer season. After all, if SARS-COV2 becomes an innocuous virus, like common cold, which infects a huge number of people, but kills very few, it will become an annoyance, not a deadly pandemic. We should not obsess too much with infection rates, but focus on the fatalities. We do not lock down societies because of an extensive cold infection everywhere.
In this context it might be useful to emphasize the dichotomy that I coined 'the rate anomaly' in my second blog. The fact that the covid-19 fatality rate is going down much faster than the infection rate is still as true now as it was 2-3 weeks ago. Below are the current (June 13 NYT) figures for the daily US infection rate (top) versus daily US fatality rate (bottom), and it is obvious that the death rate continues deceasing much faster than the infection rate, and more important, although there is an apparent plateauing of the daily infection rate over the last 7 days, due to the increasing rates in 23 states as discussed above, the fatality rate marches downward at the same rate as before! There could be some slowing down of the fatality rate over the next couple of weeks, but I predict that it will continue decreasing throughout the summer until the second wave hits. What we are seeing is a fluctuation associated with local inhomogeneity which would not affect the overall covid-19 fatality rate because the first wave has already passed the most vulnerable dense population centers of the Northeastern United States. Arizona and Alabama matter little in the overall statistics, no matter how important they are to the people living in those states. In any case, I suspect that given the impending summer season, the infection rates will go down in both states reasonably soon (see blog 3).
In this context, I may mention some of the massive misunderstanding of statistics I see regularly on TV (less so in the reputable print press). For example, a health expert being interviewed on cable TV said the other day with a straight face that obviously temperature has no effect on covid-19 because it is 115 degrees in Phoenix and people are getting infected! This statement is as dumb as saying that obviously driving speed has no effect on traffic fatalities because there are fatal accidents even when driving at 25 miles per hour! This is not an absolute 'yes' or 'no' issue, it is a matter of a probability distribution, and seasonal temperatures can at best decrease the probability of infection or fatality, it can never eliminate it. Higher temperatures do not absolutely kill the virus, it simply suppresses its efficacy in a probabilistic manner, one could still catch a cold in a very hot summer! Perhaps weather can decrease the overall 'r-factor' (the hypothetical average number of persons each average infected person infects) by 30-40%, decreasing it from 2 to 1.2 or from 1.2 to 0.9. Importantly though, it cannot push it down to zero. One could drive on the beltway at 100 mph without getting involved in an accident and one could get involved in a bad accident at 50 mph, but the fact that lower speed decreases the accident probability is obvious. Temperature is likely playing a similar role in covid-19 pandemic as I argued in my third blog, nothing else easily explains the relative low infection/fatality rate in India compared with the US, and the current rapid increase in the infection/fatality rate in Brazil.
Another expert, apparently a well-known infectious disease epidemiologist who is often on cable TV, actually said in mid-May (I was watching with complete incredulity, bordering on shock) that face masks are just cosmetic, they do not help at all. His triumphant logic, asserted with an all-knowing grin on TV, is that people in Hubei province in China were already wearing masks for 'cultural reasons' and 'it didn't do anything to stop it'. First, the logic that masks are useless since they do not completely stop the disease is so ridiculous that all I can say is that I hope this person is not driving around at 150 mph on the highway; after all slow speed does not stop all accidents. Second, the claim that masks did not help in Hubei because the disease killed many people shows such a basic misunderstanding of scientific experiments that I felt embarrassed for this distinguished expert. The only way to conclude anything here is to do two parallel experiments, one where people wear masks in Hubei and one where they do not, keeping all other conditions the same, and then to check if the spread of disease and the number of fatalities are the same or different in the two situations. In any case, the claim that masks do not help at all is of course ludicrous, masks most certainly lower ones chances of either spreading the disease unknowingly and of getting the virus easily. Masks do not provide 100% protection, nothing does. I hope that this expert was making the ridiculous claim of masks being only cosmetic only because he wanted to be outrageous so that the cable channel brings him back. I most certainly hope, particularly since he looks like of an elderly age where covid-19 could be a serious disease for him, that he regularly wears a mask himself when he goes out even if he tells everybody that he is doing it only for cosmetic reasons. I realized that just because one is a public health expert does not guarantee that the person understands probability and statistics at all, which is indeed a sobering thought. Everybody should be wearing a mask for the indefinite future, independent of the crazy things regularly asserted on TV. It should be as regular as wearing winter coats in Minnesota in January.
I have noticed a similar ignorance (perhaps even more so) in a cable channel well known for its extreme conservative views. One commentator here was screaming that clearly social distancing is over-hyped because many states with late social distancing (and early opening), e.g. Georgia and Florida, have relatively low covid-19 infections and deaths. This of course would be hilarious (because it is so stupid) if it was not such a dangerous claim. It again shows complete ignorance about probability and statistics—of course, this is not surprising because the same commentator most likely also claims that owning guns by private citizens saves lives (because of one or two anecdotal episodes) in spite of absolutely overwhelming evidence that just by owning guns a private individual substantially enhances his/her chances of dying by gun violence (or having a close family member getting killed by gun violence).
Rampant disregard and misunderstanding of statistics and probability by both experts and pseudo-experts is an unintended minor consequence of the covid-19 pandemic.
To emphasize the seasonality of coronavirus, I show below the plots for the seasonality of all known coronaviruses, but not SARS-COV2 for which no such data exist as yet, in the Northeast US (very similar plots exist for the other US regions) taken from CDC. As one can see coronaviruses peak strongly in the cold months, almost, but not completely, disappearing in the summer months. Note that the virus does not vanish with hotter weather, but decreases substantially, which is my prediction for covid-19 too. Of course, it is possible, but not probable, that SARS-COV2, while being a coronavirus, would behave differently, but there is no strong reason to believe so. I therefore contend that the current covid-19 infection increase in many (mostly southern) US states is simply a reflection of their early social distancing protocols being less rigorous (as well as more testing), leading to the first wave of covid-19 finally catching up in these regions as it already did in the Northeast a month to two ago. This is the only logical possible inference here.
Before concluding this blog, my fifth in this series, let me emphasize what I am not claiming so that there is no misunderstanding on where I stand. I am not saying that the covid-19 pandemic is over, and we can declare victory. That would be a ridiculous thing to say, and I most certainly am not saying anything of that nature. All I am saying is that if one digs a little deep in the available data, there is very good reason to believe that covid-19 is decreasing in its strength in the US overall, and even in most states for the time being (i.e. as of June 15, 2020). I am also saying that I myself expect this decrease to continue through the end of August and perhaps even the end of September. This last statement is not based only on the existing data, of course, since the existing data tell us about the past and not the future. My inference on a continued decrease of covid-19 in the US for the next three months is based on the educated guess that the summer months, with their higher seasonal temperature and humidity, would suppress covid-19 just as all known coronavirus spread is suppressed during the summer months.
I emphasize that suppression is not elimination, the virus is here to stay, but its virulence will be weak in June-September in the US and most countries in the Northern Hemisphere. This is of course an average macro statement. There can be, and will be, huge local fluctuations. If huge rallies are held with people jam-packed in close quarters for hours with nobody wearing masks, there could be huge covid-19 outbreaks initiated by such stupid events. If a basketball stadium is filled with 15,000 unmasked spectators watching a game for three hours, there is likely to be a huge outbreak, and so on. There will be local fluctuations depending on the level of voluntary social distancing people engage in even during the summer months. People must still err on the side of caution as SARS-COV2 will not vanish in the summer, it will simply be much less effective.
As for myself, I will continue wearing masks when I go out. I will only go to stores when I must. I will certainly avoid any gathering of people including seminars and meetings unless each individual has at least 100 sq ft of exclusive space and everybody is wearing a mask. I will not fly. The only exception I may make, and probably it is unwise to do so, is to start going back to Michelin-starred restaurants in Washington DC and New York City when they eventually reopen, but only a couple of times a week. We are all allowed our own reckless adventures so that life still maintains some meaning beyond just mere living.
We have received many comments on the blog, and it is probably useful to quote from some of these comments and provide a response where appropriate. As such, this 4th installment in the covid-19 series is exclusively dedicated to the comments/responses from earlier blog articles. As always, we invite further comments to be possibly featured in future blogs. A dialoge should clarify various aspects of this complex and deadly pandemic.
The following discussion is not in any particular order, and the italicized parts below each comment are responses from the author, Sankar Das Sarma.
Very interesting analysis. I like the optimism that it may engender. I find your analysis more useful than most of what I read on a daily basis. Most of what I read simply boils down to "we really don't know much". Thanks for sharing your blog. I'm going to continue to follow it.
Sankar Das Sarma (SDS): Thank you, Jeff, the whole point of this covid-19 blog is to find some patterns in the pandemic which go beyond the 'we really don't know much' statement although this statement remains remarkably true. Biology, virology, and pandemics are simply so much more complex than physics.
I enjoyed reading your inaugural blog. It's full of interesting ideas and thoughts – perhaps too many. One of the challenges bloggers face is sustainability. Repeatedly coming up with something original that people will want to read is difficult. When I blogged once a week as PT's online editor, I kept myself to one main idea per blog. I don't think it's accurate to say that "physics is as far from covid-19 as anything can be." In Physics Today's current issue, David Kramer reports on physicists who are modeling the pandemic. In the May issue he reported on the use of x rays, electrons and neutrons to decipher and disable the virus's molecular machinery. For the July issue, Toni Feder will report on what other physicists are doing to defeat the virus (designing and building PPE for example).
Just had the chance to read your fascinating second installment. I wondered about the same question. My hunch is that the severity of the disease depends on the intensity of the initial infection, that is, how many viral particles are introduced into the body. If the number is small, it's conceivable that the immune system can repel the disease. If the number is large, the immune system is overwhelmed. Social distancing could be reducing the intensity of infections and, with it, the fatality rate. Some years ago I learned from my doctor that my blood carries the antibodies for mumps and chickenpox, two diseases I've never suffered. One of my childhood neighbors had mumps. My sister had chickenpox. They likely infected me.
SDS: You make some good points, Charles. Our current understanding of immune system is really primitive, perhaps similar to mechanics before Newton and electricity well before Maxwell and Faraday (to give some examples from physics). In fact, the hope that herd immunity will eventually triumph over SARS-COV2 virus is only a hope. Exactly why the 1918-19 Spanish flu disappeared suddenly is still not understood, and the possibility of herd immunity playing a role in its disappearance as a deadly disease remains only a plausible hypothesis. Clearly, immunity is imperfect for the most well-known coronavirus causing common cold. One could get sick with cold many times, even more than once in the same season, so any antibodies against the cold coronavirus is at best only partially effective. We know nothing about immunity against SARS-COV2 except that a large number of people catching the virus does not become sick. This is no different from saying that a large number of people smoking regularly does not develop lung cancer, good for those people, but we still do not know what the key factors are. On your other point, perhaps I was a bit too harsh on the physics community, but my expectation is high from physics.
I am not in denial that leadership (in the main) and for a long time was not as aware as it could or perhaps should have been of the potential danger of the then approaching pandemic. So I recognize that. By mid-February a small number of us in APS leadership positions were already extremely concerned. We had not been successful in
convincing our colleagues. That ONLY happened that night of 29 Feb on a dramatic 1.5 hour Zoom-session with the complete team of the executive line, the CEO and her staff, and the meeting organizers. That is my only point.
SDS: Thank you, Jim, for your clarification. These are obviously difficult, but important, decisions. The good thing is that APS finally did cancel the 2020 March Meeting, which, we all agree, turned out to be a wise decision. I urge particular caution on the part of APS for future in-person meetings for example, an early decision on the 2021 March Meeting will be highly appreciated by the condensed matter physics community. APS should be proactive and make a decision on the 2021 March Meeting (with its expected 15,000 attendance) long before March to avoid the trouble faced by many prospective attendees (e.g. loss of nonrefundable ticket/hotel cost) in addition to the difficulties of those who already showed up in Denver for the 2020 March Meeting.
Hi Sankar, that's a very nice piece. I look forward to reading on your further perspectives. What worries me most in the covid19 case is the future of international air travel and difficulties with border crossing. My lifestyle of a lab PI used to be such that I would spend at least 3-4 month outside US. I don't exactly see myself as a homeowner in Laurel with a lawnmower!
SDS: Thank you Vlad, yes, as I emphasize in my blog, not having to travel and interact directly with physicists all over the world because of lockdown and social distancing would be a disaster for physics. On the other hand, unless the virus disappears, I do not see an easy solution. I am pessimistic about a vaccine or effective anti-viral therapy.
1. I think you might be underestimating how physicists like Michelle Girvan and others in the statistical and complexity physics world are getting involved. I actually wrote a short note about CFR (case fatality rates) with Sagdeev and his former student who is in Moscow and we submitted it to Nature and Lancet correspondence. It didn't get published, they are inundated, but it was not a bad paper, analyzing CFR and how it might be tweaked to make better estimates. Also Michelle organized some seminars on the SIR model and she and her colleagues did tutorials over zoom. Anyway, you're right that we maybe don't do enough, but it might be that we are doing somethings. And people are trying.
2. I think your theme that if physicists were so smart they should have seen this coming is a humbling thing. And there's nothing as valuable as humility. Thanks for doing that. As to what you might comment on next....it is my opinion that being a physicist is like being a priest in a strange religion. Physicists know things about nature that totally transcend what's necessary to navigate the world. And so the last person has no clue how a physicist can know anything, how deeply we dive into a topic, how complex nature is, and how difficult it is to say we know anything at all about nature. For instance, the average person might be suspicious about evolution because they really cannot fathom how something as complex as life could arise out of nothing, but as physicists we understand that life is an unbelievably complex thermodynamic process that takes in energy and evolves, interacting with the environment. If you agree with this, I'd love to hear your thoughts on how we could be better at articulating nature. Like how we could do a computer simulation of statistical mechanics on a network and be able to say anything about the pandemic. This is consistent with that wonderful title of the article Eugene Wigner wrote in 1960, 'The Unreasonable Effectiveness of Mathematics in the Natural Sciences'.
SDS: Thank you, Drew, for your insightful comments. It is good to know that physicists are getting involved in simulating the pandemic. In fact, I myself have some interesting simulation results which would be presented in future blogs.
Thanks for a really interesting and well written article. I just thought I would comment that some lucky experimentalists are still collecting data. Inour case our HAWC experiment in the high mountains of Mexico pretty much runs completely remotely. We have workers who live in Atzizintla, the town just down the hill from the HAWC site who are allowed to go up there in small groups once a week or when there is a crisis and who are generally able to deal with any issues that arise. Our biggest issue is dealing with the volume of data. HAWC produces ~2 TB of data a day. The data is stored at the site and transferred via fiber to portable disk arrays to Atzizintla. Nominally the data is hand carried from there to UNAM in Mexico City about once a week or brought to Puebla and shipped by DHL. From there it is transferred to permanent storage at UNAM and transferred via internet to Maryland where a second copy is kept. Then the data at the site is deleted. For about the last 6 weeks we have not been able to move data. Since portable data array holds 29TB (or about two weeks of data each). We have of ~6 of these (12 weeks worth) and about 4-6 week's worth of storage on site. So, if we can't move data we can continue to store redundant data (on site and in Atzizintla) until probably mid to late August. We are hoping that someone can make a data transfer run in the next few weeks and that will give us more cushion and a chance to get the data we haven't moved. In the mean time everyone is working on new analyses and algorithms on the nearly 6PB of data we do have.
As for getting work done, this week we are having a virtual collaboration meeting via zoom. Because people are located from China to Europe we have to settle on 10am - ~2 pm EDT Monday - Friday. Four hours is about as much zoom as can productively be handled anyway. (I had 7.5 hours straight a few weeks back when we had our faculty meeting after an entire day of Astro 2020 meetings and I was a complete vegetable by the time it was done). On the other hand, I find I have more time to work on papers without commuting (something I don't miss) and spending time talking to my colleagues at work (something I do miss). Anyway, I did enjoy reading your article - anything to avoid reading/watching the news and being outraged. I (like most us) make my daily plots of covid cases in Montgomery and PG counties looking for a positive trend. Maybe in the last few days but with reopening it may be short-lived.
SDS: Thank you Jordan, it is interesting to know how you and your collaborators are managing to continue your experimental research in spite of being sheltered at home. It seems that Montgomery and Prince Georges Counties are finally planning to enter Phase II reopening this week.
I am writing to make a pedantic and somewhat frivolous comment about the thoughtful piece that you wrote. You ascribed the saying 'Predictions are difficult, especially about the future' to Groucho Marx. However, in my misspent youth I was a serious student of Marx–Groucho (and siblings) much more than Karl. Although it is possible that Groucho did say this at some point, I am pretty sure that he has no association with this saying. I point this out not as an issue of scholarly attribution, but rather because there is an amusing physics connection with the expression, it was one of Bohr's. In these times of pandemic and unrest, anything amusing, particularly connected to physics, should be welcome.
I have always liked this expression and frequently have used it in colloquia, pointing out the Bohr connection. One interesting thing is that the saying is often misattributed to the baseball catcher and part-time linguistic philosopher, Yogi Berra. This is largely because it sounds very much like one of Yogi's utterances. But, as Yogi himself pointed out 'I really didn’t say everything I said.' I always thought that any saying that could be plausibly attributed to Neils Bohr, Yogi Berra, and now Groucho, is something special. While Bohr did use this saying, he did not coin it. As far as I can tell from cursory research on the internet (caveat emptor), it was apparently something of a Danish proverb. I hope this small digression does not distract from the important serious matters about which you wrote.
SDS: Thanks, Tom, this is an important point. I knew about the attribution of this quote to Yogi Berra, but chose Groucho instead. It is good to know the actual origin.
I thank you immensely your including me on the initial text of your
blog. I do not have as involved a vision of what is happening now. Your vision of us physicists reminds me of the Petry dish note I sent you, we somehow have not found a boundary to grab and that shows as you comment. You well know that there is no boundary. The combination of the pandemic with the economic breakdown and the social unrest is going to make for a unique experiment. They are coupled in some complicated ways. Right now I am starting to think of another text, similar in size to the one I sent you and we discussed. I will send it to you once I have it written.
I have had some interesting interactions with former students. TRIUMF at Vancouver is beginning to open so I will be able to help the students in the laboratory using some video, as it will be a long time before the laboratory will be open to people from outside British Columbia. I believe right now they are operating at the 30% level of people on site, but it is open. They never closed it completely as this is the main source for some medical isotopes for the whole continent.
SDS: Thank you Luis, I look forward to your piece.
I hope you've been doing well in the midst of this pandemic. It was nice to read your thoughts on the matter last night, especially since I've been pondering many of the same things over the past few months. First of all, I must say that despite being an experimentalist (or at least, an aspiring one), I have probably benefitted from this shut-down: it turns out the summer before graduate school is not such a bad time to be locked at home with plentiful time to catch up on reading.
On the other hand, starting in a new lab in the fall with at the very least stringent occupancy restrictions, and at worst another shut-down, is a definite cause for concern. Finding a way to stay productive with limited or no lab access is something I've been contemplating for the past few weeks, and that I'd like to talk with you in more detail about sometime. I think that the one aspect of things that we have control over, especially senior scientists such as yourself, is maintaining regular seminars and running conferences online. Even though they can't replicate the in-person interactions and organic collaboration you mentioned in your post, I think they still help maintain some semblance of community.
As you may already be aware, there are some successful efforts at organizing online conferences: in particular, this seminar series https://virtualscienceforum.org/#/long_range_colloquium has been rather well "attended" (200+ people for all of the talks I've tuned into). They seem to be interested in having other people organize online conferences using their platform, and I would imagine that someone such as yourself could put together something very interesting and draw more attention to their organization. Also, have you considered running CMTC seminars over zoom?
SDS: Thank you, Nick, yes, the shutdown does enable some to focus on their work better, no question about it, but overall it surely affects physics (and everything else) adversely. I agree that I should organize talks/conferences online, I simply lack the energy at this point of my life.
I read your blog article and appreciate your perspective. When I was a graduate student in philosophy at Maryland, I spent a bit of time working with Fred Suppe who was a philosopher of science. Fred did some research with Jim Yorke and a doctoral student, Brandy Rapatski, on HIV transmission in the late 1990s and early 2000s. I do not know Brandy personally, but I thought you might find her research interesting since she applies mathematical modeling to epidemics.http://www.killi.com/brandy/.
SDS: Thank you, Tom, for pointing out the interesting simulation.
Thanks for sharing us with this very insightful article. May I share a few of my idea with you? Can I translate this article to Chinese for the non-commercial usage? I want to re-post it to a Chinese social media, Wechat, to let more people in China know. I will definitely cite properly and put the original link referring to CMTC blog website.
SDS: Thank you Haining, and yes, most certainly you can translate it if you so desire!
Thank you for sharing your thoughts with the community through a blog post. I liked the historical perspective and the descriptive challenges for experimentalists and theorists. I agree that it is important for physicists to lend a voice and write about this historic crisis. I also agree that condensed matter physicists have models that might address the crisis. However, I also think that physicists could explain the use of objectivity in warning systems that might apply for viruses, maybe like earthquake alerts that (in fact) automatically provide some early warnings. Warning systems for improbable events should be something that physicists understand due to models like avalanche theories. It is probably important to remove human subjectivity from some early warning systems. Humans are not good at estimating both probability and uncertainty during most news conferences, and it appears that this includes Fauci, who clearly was especially mistaken at the beginning. Also, perhaps Fauci had pressure from within his organization to protect the CDC that a tenured professor would not. I look forward to reading the next post.
SDS: Thank you, Kevin, for your comments, and we agree that physicists getting involved in studying the covid-19 pandemic could be useful.
Thanks for sharing your blog with me. It is difficult to find well researched work on the pandemic. I have read several articles that speak to warm temperatures as a factor in Covid spread but your blog provide some interesting underlying data.
SDS: Thank you Fran, and indeed, the main reason for my writing this blog is that I could not find answers to very simple (and to me, rather obvious) questions I had about the pandemic. As I figured out the answers to my questions, I realized that others may have the same questions, so I should describe my findings in some manner.
My impression is that covid cases and deaths are likely both severely underreported outside first world countries. In Italy it was found that if you assume the deviation from average death rate was entirely due to covid, then the actual covid deaths are 4-5x higher than reported. It would be interesting to simply look at the overall death rates in India, Bangladesh, etc, and compare that to the official covid death count.
It certainly does seem like weather plays a huge role. Why else would the death rate in the US have gotten cut by half compared to a month ago while quarantine rules have been lifted?
I wonder if people are simply healthier in those countries by some measure. US has high levels of obesity, diabetes, etc. On the other hand, western Europe got hit hard as well, and they do not have the obesity problems of the US. Perhaps the obsession of the West with "cleanliness," anti-bacterial soap, and sterilizing everything has dramatically weakened the population's immune system? So being a "first world" country is actually a disadvantage when it comes to having a strong immune system?
On that note, it's strange that Japan's population is aging, but they have extremely low covid death rate.
SDS: Thank you, Maissam, for your many thoughtful comments, only a few of which I am quoting here. There could very easily be other factors in play causing the covid-19 fatality rate in India to be much lower than in USA and Western European countries. One possibility is inherent better immunity as you mention. Another possibility is that India has a remarkably young population compared with USA and Western Europe, which obviously would suppress covid-19 fatalities. The possibility that India has a huge (under-counted) covid-19 infection rate and relatively low fatality rate is most likely arising from several different mechanisms, but I am reasonably persuaded that the weather is playing a role. I do not think that there is much under-reporting of Indian covid-19 fatalities since most deaths are concentrated in big cities such as Delhi and Mumbai, where a vigorous free press would ensure that the number of officially reported deaths is consistent with the reality. Reasons why huge pandemics rise and fall are very poorly understood in general, for example, the precise cause for the sudden disappearance of the 1918-19 Spanish flu after killing roughly 100 million people worldwide is still debated.
I had been wondering about how much heat and population density has been having an effect, but didn't have a chance to look carefully. Covid going away in July sounds hopeful for me at a personal level.
But as far as November goes your analysis leads to the product of a small number of infections in July that will likely be amplified by some near exponential growth over early fall from lax social distancing leading to an unpredictable November.
I was looking through your blog post again and remembered one possible caveat for optimism over the summer that I had heard somewhere over the radio. One difference between the slums of Mumbai and developed countries like the US is air-conditioning indoors. The indoor temperature and humidity conditions in the US are much more favorable for virus spread. If most people spend time interacting indoors from opening up from the lockdown as it is happening now, is it clear that the summer will be as much of a slow time for Covid infection rates? It is possible that high indoor humidity still helps.
SDS: Thanks, Jay Deep, I wish I could tell you what would happen in November, but I simply do not know. Nobody knows. If social distancing remains effective, it is certainly possible for the second wave next fall to be weak, but we simply do not know right now.You make a good point about the possible effect of AC and in general indoor versus outdoor. It has become clear that outdoor infections are rather rare (except possibly in big gatherings), and the fact that poor people in hot/humid countries spend much of their time outdoors may very well be playing s role here. Also, weather includes both temperature/humidity--- more humid it is, less viral infection typically, just as hotter it is less virus is around. I emphasize so that there is no misunderstanding SARS-COV2 will not disappear in the summer, but its virulence and infectiousness should decrease considerably. This is what happens with all known coronavirus, and it is therefore reasonable to expect the same for this novel coronavirus too.
I've enjoyed your writings; thank you for your careful explanations. I am very much hopeful that the weather will have protected everyone participating in the civil rights demonstrations.
SDS: Thank you, Anne, I am reasonably convinced that young people staying outside in the hot weather with masks are pretty safe from SARS-COV2 infection, of course, there is no 100% safety.
In my last blog, Covid-19 II, I discussed the 'rate anomaly', associated with the large discrepancy between the day-to-day changes in covid-19 infection and fatality rates (with the fatality rate being substantially lower, by factors of 3-5, than the infection rate) over the last 8 weeks and its possible implications and cause. In this blog, my third article, I discuss the 'population anomaly', and I analyze the relative statistical dependence of covid-19 on the geographic population densities of the affected areas.
Before getting to the main thrust of this article, where I focus on the per capita covid-19 induced fatality statistics in various localities compared with the local population densities to point out some significant anomalies, I wish to comment on my critical approach in this covid-19 blog. It is manifestly not a reductionist approach that we, theoretical physicists, adore so much. I do not start, at least not in these first few articles, from a microscopic physical approach on how the virus spreads (or not) to conclude or predict some outcome. I do hope to present in future blogs the results of my cellular automata type dynamical microscopic simulations on the covid-19 spread (and how to contain it, at least as a matter of principle), but the input 'experimental' parameters for such a microscopic model are hopelessly unknown in reality, making the use of such a reductionist approach of dubious practical utility.
The subject of this blog is the role of population density in the covid-19 pandemic. At first, it may seem a bit trivial. After all it is obvious that all other things being equal, the higher the population density, the higher the covid-19 infection rate. However, unlike physics, in real life other things are never equal, and controlled experiments are of limited usefulness in understanding raging pandemics. For example, one of the first badly affected states in the US was Louisiana, which ranks exactly in the middle in population density among the states. Obviously, other things were unequal here. It is, however, not unreasonable to assume that in the 'steady state', when initial fluctuations are damped out, population density should perhaps be the most important criterion for the covid-19 pandemic. Is this true empirically? For the initial discussion below I am assuming similar social distancing regulations everywhere, I will discuss deviations from this assumption later. This is the classic theoretical physics approach, where one typically starts with an ideal model.
It is well-known that the US (with 110,000 deaths on June 6) has the most covid-19 fatalities in the world. The per capita covid-19 fatality in the US is 34 per 100,000, which ranks 9th in the world. This is while the US ranks 145th in population density among the world's countries with a population density of 34 per square mile. In fact, the US population density is well below the world average. The 8 countries above the US in covid-19 fatality rates are all countries in Western Europe: Belgium, UK, Spain, Italy, Sweden, France, Netherlands, Ireland. The country with the 10th highest per capita fatality rate just below the US is Canada, with 21 fatalities per 100,000. I am ignoring countries with very small populations such as Andorra, San Marino, and so on. This is an astonishing list as these are among the most advanced first world western nations with excellent public health service. One would have expected India (population density 412 per square mile), Bangladesh (1172 per square mile), Hong Kong (6800), Vietnam (300), or Singapore (8000) to have much higher covid-19 per capita infection rates than the US if population density is indeed the absolute determining factor. Indeed, most of these countries got their first known covid-19 infection around the same time as the US. However, the reverse is true. These highly populous, and often relatively poor, countries have much lower covid-19 infection and fatality rates than the affluent Western European countries and USA. What gives?
In fact, I was in India when the first covid-19 infection was reported on January 30—it was the front-page news in the Indian press across the board. The US also had its first reported case in January. In spite of having similar initial conditions, the covid-19 infection and fatality rates in India are orders of magnitude smaller than in US, ~ 7000 compared with 110,00 in the US. This is despite the fact that India has a much higher (and poorer) population density and a substantially weaker public health system. The parts of India most affected by covid-19 are the big slums in Mumbai and Delhi, places with the highest (and the poorest) population densities in the world (often with 10 or more people sleeping packed on the floors of 100 square feet rooms). So, a simple explanation for the huge difference between the covid-19 impact between the two countries is hard to come by. It is certainly possible, even likely, that the covid-19 infection rate is substantially undercounted in India, but it is hard to see a serious undercounting of covid-19 fatalities in large Indian cities such as Mumbai and Delhi. The low fatality rate in India, compared with North America and Western Europe seems to be a real effect.
A similar covid-19 population density anomaly exists among the US states as well. The highest covid-19 per capita fatality rates in the US are, as expected, in the densest populous states/regions: New Jersey, Washington DC, Connecticut, Rhode Island, New York, Massachusetts, Maryland, Pennsylvania, Illinois, Delaware. Another hard-hit state, Michigan, has the 17th highest population density. The only state showing a high covid-19 per capita fatality rate that is not highly populated is Louisiana, with the 25th highest population density. So far, so good, the expected correlation between population density and the covid-19 pandemic seems to manifest itself except for Louisiana. Here, the exception could perhaps be explained by the Mardi Gras festival with its huge crowd descending in New Orleans at the end of February just as the SARS-COV2 virus was spreading through the US.
The problem arises when we look at a few states/regions, which do not show up in the list of states with high covid-19 deaths/infections, in spite of having very high population densities. Puerto Rico (#3 in population density) has among the lowest covid-19 fatality rates of any place in the US (4 per 100,000). Hawaii (#13 in population density) has only 1 covid-19 fatality per 100,000, the lowest in all of USA. Less spectacular, but still anomalous, Florida (#8 in population density) and California (#11 in population density) have rather low covid-19 fatality rates of 12 per 100,000. This puts these two highly populous states in the lowest quartile among the states in covid-19 fatality rates! Why are California, Florida, Hawaii, Puerto Rico so anomalous in terms of covid-19 fatalities, not correlating with their high population densities?
It is apparent that population density, while being a key indicator underlying the covid-19 pandemic, cannot be the whole story. There are glaring exceptions such as India, Bangladesh, Singapore, and Vietnam where there are very low covid-19 fatalities compared with very high population densities. This 'population anomaly' also applies to several US states/territories: Hawaii, Puerto Rico, Florida, and California.
What is the underlying cause/mechanism for this population anomaly?
I suspect that it is the weather. Other things being equal, warmer places are relatively immune to the covid-19 pandemic. Higher temperature does not eliminate the virus of course, but it appears to suppress its virulence and infectiousness. No other single hypothesis seems to be consistent with India being affected much less by covid-19 than the US, and Puerto Rico being much less affected than New Jersey. This is also consistent with the common cold, which is the commonest known coronavirus, being much more virulent in colder weather (in spring and winter rather than in summer). I am not suggesting that higher temperatures would drive covid-19 to zero, it will not, but I believe that it will suppress the spread of covid-19.
I predict a much reduced covid-19 virulence during the June-August summer months in the US overall, although there will be strong spatial and temporal fluctuation effects depending on boundary conditions. One can catch a bad cold in the summer, but the chances of being sick with a bad cold are much higher in the winter! I anticipate a similar scenario for the SARS-COV 2 virus virulence also, much stronger in cold weather than in warm weather. This experiment is going on all over the world right now, with the Northern (Southern) hemisphere entering summer (winter), and if the hypothesis is valid, the covid-19 pandemic will worsen in Brazil and improve in the US over the next 3-4 months.
The important question is what happens in October-November 2020 once the warm weather gives in to colder temperatures in the US. Does covid-19 come roaring back in a second wave (like what happened with the deadly 1918-19 Spanish Flu)? Or does it remain suppressed as social distancing produces a permanent dent on the contagion?
Unfortunately, there is no way anyone can answer this question. We know so little about this 'novel' virus which homo sapiens have never been exposed to before.
In this second blog on the covid-19 pandemic, I want to focus on the mysteries and questions surrounding the pandemic which I have found puzzling. Specifically, I will examine where the analytical-quantitative statistical methods used extensively in physics could be of potential usefulness in understanding aspects of this pandemic.
I emphasize that many of the most important questions surrounding covid-19 are biological, clinical, and virological, where physics in the traditional sense could make little contribution. For example, developing vaccines or finding suitable anti-viral therapies are necessarily well outside the scope of physics. Why the US, with only 4% of the world's population, has one third of the current world covid-19 fatalities is also outside the scope of physics. Except for the tautologically obvious answer that the US response to the pandemic has been woefully ineffective. There are, however, more narrow factual questions about the covid-19 pandemic where physics-based models, simulations, and analysis could provide useful insights. These are the questions I will focus on in the next few blogs starting with the current one.
These questions I raise are by no means exhaustive. These are representative questions where, I believe, thoughtful quantitative modeling could be of considerable help. In each blog, starting with this one, I will focus on one question/mystery and discuss its implications. Subsequent blogs will raise more questions.
First, I wish to focus on the mysterious dichotomy between the fatality rate and the infection rate of covid-19. I discuss here the US statistics (although the same appears to be true for the world covid-19 statistics too, as well as just for New York City and possibly for many countries). This dichotomy is the large difference in the decrease in the fatality rate versus the decrease in the infection rate after the initial increase in infections and deaths were flattened by social distancing. Both began to drop starting in mid-April, but the rates by which they decreased have differed by a large factor over the whole 6-week period, from mid-April to late-May. I append below the most current plots showing the daily infection rate in the top figure and the daily death rate in the bottom figure, both for the US. These two figures are taken from the Washington Post of May 30. Specifically, the number of daily deaths has decreased by 55% (from 2103 per day to 961 per day) in the 36-day period between April 25 and May 30. By contrast, the number of new daily infections has decreased only by 11% (from 26,600 to 23,600) in the same period. This factor of 5 difference between the daily infection rate and the fatality rate has huge public health implications and must be understood in quantitative and qualitative details.
Physicists can contribute to the understanding of the underlying causes for this dichotomy by using quantitative modeling and simulations. The fact that the daily death rate is going down much faster than the rate of decrease in the daily new infection rate is obvious just by looking at the two figures, but it is useful to point out some salient features. The dichotomy is independent of whether one focuses on the average rate (e.g. 7-day rolling averages defined by the solid curves) or on the local maxima/minima of the individual daily rates (as reflected in the temporal variations in the histograms). For example, comparing just the peaks (or the troughs) in the daily infection rates versus the daily fatality rates between April and May again shows a much larger decrease in the fatalities per day than in the number of new cases per day. For example, the fatality peak on April 14 records 2820 deaths, decreasing to 1408 deaths on May 27, a decrease of more than a factor of 2 over a 44-day period. By contrast, the infection rate peak on April 9 of 33792 decreases only to 24409 on May 29, only a 28% decrease over a 51-day period. The same huge difference in the two rates applies also to the local minima in the rates. The daily death rate at the local minima decreases by 68% between April 13 and May 25 whereas the daily infection rate decreases by 35% during the longer period spanning April 5 to May 26.
No matter how one looks at it, there are differences of more than a factor of 2 between the decrease in the daily infection rate and the daily death rate as both rates start decreasing. This is well outside any statistical fluctuations. In sharp contrast, there is no such difference in the initial rising part of the two curves, between the third week of March and mid-April both rates increased by more than a factor of 10 before turning over in mid-April and starting to decrease as social distancing flattened the curve. As an aside, I mention that the apparent periodic wavy temporal pattern (with a clear 7-day period) in the two rates with crests and troughs is simply a human artifact of the reporting going down each weekend, obviously not because fewer people are getting infected or dying on weekends (SARS-COV2 virus does not care about weekends), but because fewer employees are working on weekends tabulating statistics.
The fact that the fatality rate is substantially lower than the infection rate in the decreasing parts of the covid-19 curves obviously raises questions and has various important implications. It should, however, be emphasized that this dichotomy appears to be qualitatively scale-invariant as long as fairly large numbers (of both infections and deaths) are involved. It applies to the global statistics as well as to the New York City statistics (and most likely to Spain and Italy and other countries badly affected by covid-19, although I have not checked this explicitly). This scale invariance indicates that the dichotomy is arising from something fundamental about the spread of SARS-COV2 in human communities. In fact, the dichotomy is more dramatic in the world covid-19 statistics (curves not shown here). The daily world infection rate is still increasing although at a lower rate than it did in the beginning months of the pandemic. However, the world death rate is steadily decreasing since April. For example, the daily infection rate has increased from 72,000 on April 5 to 134,000 on May 30 whereas the daily death rate has decreased from 8500 on April 16 to 4000 on May 30! This is truly remarkable. In New York City, the daily infection rate decreased from 6000 on April 11 to 700 on May 30 whereas the death rate decreased from 800 to around 40 in the same time period, a factor of 20 decrease in the death rate compared with a factor of 8.5 for the infection rate.
The most important question is actually not the origin of this dichotomy (i.e. why?) although in physics we are often focused singularly on 'why'. The most important question is what will happen to this difference. The future of these differences will have profound consequences in the reopening of the locked-down communities and future mitigation of the virus. If the fatality rate is flattening at a much faster pace than the infection rate, it could only mean that fewer people are dying in the decreasing tail of covid-19. In fact, taking into account the well-accepted fact that the infection rate is probably under-reported, the actual difference between the two rates may be much larger than the estimates I give above. If it is indeed true that the death rate is suppressed substantially as local distancing and nationwide lockdowns lead to a flattening of the curve, the implications for restarting society are enormous. After all, humans suffer from all kinds of coronavirus, appearing most frequently in the form of the common cold, which is an all-encompassing coronavirus that we accept with no fear because death from the common cold is not that common. Imagine if SARS-COV2 transforms to something like an ordinary 'cousin' of the common cold virus after its initial onslaught. Then, we would have much less to worry about than compared to a situation where the death rate keeps constant pace with the infection rate. I do not know that this is what is going on. We need more experimental data in the sense that we need to make sure that the death rate does not start to increase in the future eliminating the dichotomy. The facts existing right now give us considerable reason for optimism about the future because, after all, a viral infection is a minor irritation as long as it does not kill people.
There is one other question which all physicists would ask right away when they notice the experimental result of the dichotomy: Why? Why is the fatality rate so far below the infection rate when they are both decreasing (and in fact, for the global pandemic, the infection rate is still increasing while the fatality rate is decreasing steadily)? One obvious common-sense answer is that all the vulnerable people (or at least most of them) have already died in the rising part of the disease, and that by the time a decrease in the daily infection rate begins, people who are getting infected are much less vulnerable and consequently recover more quickly. So, perhaps as the disease tracks downwards it comes to resemble much more the coronavirus-induced common cold, apparently 20% of common colds are caused by the coronavirus in the early spring. However, in the beginning where we see an exponential growth of the virus, it is much more like the deadly SARS or MERS, which has a very large fatality rate. I do not know that this is what is going on, but this is a working hypothesis which explains the existing facts. I have developed theories for condensed matter phenomena based on less empirical support. If indeed, the decreasing part of the covid-19 curves represent something closer to the behavior of common cold, we have many public health options for mitigation.
Some additional empirical support for the suppressed deadliness of covid-19 in the deceasing April 20 - May 30 part of the curves comes from the fact (not shown here) that the hospitalization and ICU admission rates of covid-19 patients have also gone down much faster than the decreasing rate of the infection. Most of the new covid-19 patients are not only not dying at a higher rate (equal to the infection rate), they are not even getting very sick at a higher rate. If this continues (and we simply do not know and must await future data), then a day may come soon when the covid-19 fatality rate vanishes in spite of having a finite daily infection rate. If so, then covid-19 has become like a common cold virus, it is contagious, perhaps very contagious, but it is no longer deadly.
The dichotomy in the fatality versus infection rates demands attention from physicists far more competent than me to figure out its cause and implications.
I have been following covid-19 like almost everybody else while sheltering at home these past few months. I probably have had a little bit more time to reflect on the crisis than most people. My two sons are grown up and working in Chicago and New York City, so I have had little distracting me from my physics research and from contemplating our current strange and isolated covid-19 life. There is only so much theoretical physics one can do day after day in isolation, there are 168 hours each week after all. I cannot help but bring the perspective of a physicist while following the crisis, and I keep on wondering how pathetically absent we physicist are in the discussion and mitigation of perhaps the most significant crisis facing America since the Civil War.
One in four Americans are out of work (>40 million), and more than 100,000 are dead in just two and a half months. But, we physicists are not playing any active or passive role in trying to solve the biggest existential crisis facing the country in more than 100 years. World War II killed more than 250,000 Americans over a 4-year period, but the American homeland was never invaded. The Great Depression led to widespread unemployment, reaching perhaps a maximum of 24% at its peak. Covid-19 arguably is our greatest crisis since the Civil War, and no end is in sight. On a less serious level, the 2020 Boston Marathon was canceled, the very first cancellation in its 125-year history! Although less substantive than the millions of unemployed and hundreds of thousands of death, the cancellation of Boston Marathon, NCAA Basketball Tournament, and even the 2020 Summer Olympics are of great symbolic significance in defining the covid-19 crisis. During these 125 years, many historical events of great import happened: World War I and II, the Spanish flu pandemic of 1918-19, the Great Depression, the Korean and Vietnam wars, Cuban missile crisis, the civil rights and antiwar upheavals of the 60s, 9/11, two Iraq wars, an almost 20-year long war in Afghanistan, the Cold War, and many recessions. None of them killed 100,000 Americans in less than three months or led to 40 million unemployed Americans. This is the covid-19 perspective of a theoretical physicist, which will continue on a semi-regular basis. I cannot help but look at the covid-19 crisis as a scientific-technological problem. The spread of the virus through humans in the end is a highly nonlinear dynamical problem in physical kinetics, the eventual disappearance of the problem is some kind of a (natural or induced) percolation phase transition in all likelihood. We physicists should have a lot to say about this topic.
The SARS-COV2 virus, which causes covid-19, has of course had a huge impact on the physics community, just as it has had huge impact on every human being. All physics conferences, seminars, colloquia, workshops, as well as most physics lecture courses in universities have been canceled everywhere since the beginning of March. While this is true for all subjects/communities, the community of physics has showed no particular foresight or brilliance in anticipating the calamity of covid-19.
For example, the American Physical Society cancelled its annual 2020 March Meeting in Denver (scheduled March 1st-7th, 2020) literally at the absolute last moment, on the evening of Saturday, February 29th. I was supposed to take a flight at 5am on Sunday morning from Washington IAD to Denver, and I received a phone call from the APS President Jim Gates around 10pm on Saturday night telling me about the cancellation. In case you are wondering why Jim, a very busy man, would call me to inform me about the last-minute cancellation of the March Meeting with an anticipated attendance of close to 15,000 physicists, there is a short story behind it. The week before (around February 20th or so) I actually sent a message to APS, expressing concern and suggesting a possible cancellation, and I got a prompt response saying
the answer is that we are proceeding as planned, but are monitoring the CDC website constantly as well as that of the WHO. This was on February 27th, basically the same day that President Trump assured us that the virus would disappear magically. Fortunately, APS changed its mind at the very last moment (I wish President Trump did so too, but that would be a different blog). This is all despite the fact that a large number of attendees, including many foreign participants, were already in Denver by the time the meeting was cancelled. However, it is still a great relief that the meeting was cancelled. Otherwise, given the extremely crowded lecture rooms in typical March Meetings, I shudder to think how many physicists all over the world would be sick with covid-19 and how many others we would have infected!
Why did the leading physics organization in the world wait literally until the last moment to cancel a meeting, which would have been an unmitigated disaster if it took place? Since that time covid-19 has killed 100,000 Americans (at least) in less than three months and has infected close to 5 million people (at least) worldwide. Yet we, the physicists in the US, could not see this dark future at all even on February 28th. This unfortunately reflects poorly on us and shows that we are at best only marginally better than the politicians in predicting the future. This is in spite of the fact that predictions, particularly falsifiable predictions, are a central premise of physics. In the end, when the most crucial existential crisis of the last 100 years hit the US, we turned out to be no better than others, reinforcing the Groucho Marx truism that all predictions are difficult, particularly about the future. I should mention in the passing that some other organizations were in fact more prescient in their evaluation of covid-19 Facebook cancelled two huge conferences scheduled for March and May already in mid-February.
Starting with the cancellation of the APS March Meeting in Denver on March 1st, the physics community was proactive, and a vast majority of, if not all, physics conferences/meetings were indeed cancelled all over the world. In fact, these cancellations continue. I just received the cancellation notice for a conference scheduled to be held in August in Germany. So far, 10 of the 12 conferences/workshops I was supposed to be attending all over the world in 2020 have been cancelled, and only 2, both scheduled in October 2020 (one in Beijing, China and one in Dresden, Germany) have not yet been cancelled. I will be surprised if these two are not cancelled eventually. I simply do not see 100 attendees packing into a lecture room to listen to in-person lectures happening in 2020. In mid-May we ourselves canceled a conference scheduled to be held at the University of Maryland on November 6-8th. The other direct effect of covid-19 has been the cancellation of in-person physics seminars, which started in the US around March 15th as the various states started locking down. It is a bit astonishing on hindsight, but most physics departments in the US, including our own Condensed Matter Theory Center (CMTC) at the University of Maryland, were holding regular seminars/colloquia even up to the middle of March. It is clear that the community of physics did no better than others (including politicians) in its anticipation of the impending calamity. This is despite the fact that the covid-19 crisis was already crystal clear in China and Italy by the end of February. So, physicists after all are no smarter than others in spite of the secret belief of many physicists (certainly, many theoretical physicists)!
In our condensed matter theory group at the University of Maryland , about 25 physicists (students/postdocs/faculty) were supposed to be attending the 2020 March Meeting, only 2 cancelled out of the meeting (around February 24th) a week before the APS announcement of the cancellation because they were apprehensive about flying/attending a large meeting. Both, not coincidentally, are from Taiwan—so their wisdom is most likely grounded in the memory of SARS. No wonder Taiwan, in spite of having close ties to Wuhan province, has had only 7 covid-19 related deaths in a country of 25 million people whereas the US has had 102,000 deaths already in a country of 330 million people—a per capita fatality ratio of 1100 in favor of Taiwan. All the scientific-technological advantages of the US mean little because we (including the physics community) failed to anticipate the scope of the crisis.
Why was the whole physics community (as well as individual physicists) completely oblivious to the ominous pandemic possibility of covid-19 until it was too late? Why did we underestimate the SARS-COV2 virus? We are scientists with great analytical skills, who are focused on the mysteries of the universe. We really want to know how nature works. I cannot imagine a more relevant scenario than covid-19 in terms of nature’s mysterious workings. An unknown virus makes a zoonosis somewhere in the Hubei province of China (although the patient zero has never been found, and the infamous Wuhan ‘meat market’ is apparently not the place for this first human infection) and starts killing a large number of people in Wuhan, China, and then in Lombardi, Italy. The American press reports these findings in depth, and we physicists keep on doing what we have been doing as if nothing has happened: We keep on writing papers on topics of little relevance to the universe around us (mostly things which could possibly happen at astronomically high energies or astronomically low temperatures or at astronomically far distances from the earth). If there ever was a scientific problem demanding the attention of all scientists, it is the covid-19 crisis. This is a disease which may transform our modern life as much as any other event since 1900. The Spanish flu of 1918-19 killed 100 million people globally after originating in Kansas (around half a million Americans), but once it vanished in 1920, its effect on life was minimal, as the world was much less connected and most people travelled little. There were no physics conferences or seminars in 1920! The only global calamities affecting the US, surpassing CVOID-19 in scope during the last 100 years, are perhaps the two world wars. Although 9/11 was a great national trauma, its permanent effect on our everyday life turned out to be the need to arrive at airports an hour or two ahead of the flight time instead of arriving a few minutes before the flight.
But covid-19 is not over yet. We do not know where it is going just as we did not know on March 1st that all of us would be locked down in our homes for more than two months, or that we would be wearing masks and washing our hands constantly. We did not know that purchasing simple things like milk, water, eggs, soap, bath tissues, etc. in supermarkets would become impossible. We did not know that close to 40 million Americans would become jobless and there would be mile-long lines at food banks. We did not know that all the restaurants would simply close down as would all the recreational and entertainment facilities: theatres, movies, museums, and casinos. We did not know that schools would simply close down, sending all students home indefinitely. We did not know that nobody would fly anymore. We did not know that more than 100,000 Americans would die in two months from a disease whose existence nobody knew of even in December of 2019.
Perhaps the lack of appreciation of the covid-19 dangers among physicists is understandable in the context of the general failure of all experts (even the experts in infectious disease and public health) in anticipating the crisis. Even Antony Fauci, the revered covid-19 sage of Washington DC, said in late February that he does not believe that SARS-COV2 poses any particular danger to Americans. Yes, he really did. He felt that one cannot shut out the rest of the world, but the truth is one can and one should when facing an impending pandemic. I have noticed that even Dr. Fauci, a great expert that he is, has vacillated on several key points about the progression of the disease. At first, he was sure that the disease would most definitely return in the fall (the so-called
second wave), now he says that the second wave is not inevitable. In the beginning he was adamant that a vaccine could not happen in less than 18 to 24 months, now he is saying that a vaccine is possible by the end of 2020. Perhaps given the ambivalence and equivocation even by the revered Dr. Fauci, it is understandable that we physicists did not have a clue about covid-19 and did not appreciate the dangers of SARS-COV2 at all. I wish I could claim that I knew all along how dangerous this virus is, after all I contacted APS on my own expressing concerns about the March Meeting already in February. The truth is I vastly underestimated the danger. I was going to different restaurants in Washington, DC almost every night for dinner until March 20th. Washington, DC and Maryland closed down on March 30th and 23rd, respectively. So, my wisdom is at best only a few days ahead of the politicians'. When I look back at my 2-3 hour long dinners at some of the most crowded DC restaurants during March 1st-20th, the word
carefulness is not what I would use now to characterize my behavior. I was basically as ignorant as anybody else in terms of my anticipation of the covid-19 calamity.
Although I can claim no special foresight or wisdom in anticipating the vast scope of the covid-19 crisis in USA, I did take the initiative in closing down CMTC on March 18th, forbidding anyone from coming to the center. This is not by any means something I can brag about, but it is still earlier than any US states (California locked down on March 19th!), and almost two weeks before the state of Maryland locked down. Here is the message I sent out on March 18th to all 33 members of CMTC:
CMTC is closing down as of tonight March 18th. This means that CMTC members cannot come to CMTC until further notice.
I made this decision taking everything into account including the latest modelling of the virus impact. The next 2 weeks are crucial in determining if the curve has been flattened sufficiently or not. In addition, having no janitorial and maintenance services in CMTC implies that we cannot use CMTC since there is a genuine possibility of filth piling up or some huge plumbing problem developing suddenly with no repairs. Feel free to contact me if you need clarifications, but CMTC IS CLOSED FOR EVERYBODY UNTIL FURTHER NOTICE. Everybody must work from home doing the usual 'teleworking'. This is being done for everybody's safety. (I will show up randomly to ensure that the lockdown is working and people are not using their CMTC offices.)
If I was really wise, I probably would have closed it down on March 1st, but fortunately, no one at CMTC has developed covid-19.
Getting back to the theme of the interplay between covid-19 and the physics community, it is relatively easy right now, somewhat after the fact, to state the profound impact of the pandemic on physicists. All experimental physics research has come to a screeching halt since all laboratories are under strict lockdown. I polled my most trusted experimental colleagues and found an almost unequivocal response across the board that their experimental research in the labs has stopped. A few younger experimentalists, extremely tech-savvy, are managing to run some limited measurements through the internet, but even they emphasize that this is not a sustainable mode of operation. Theorists are somewhat luckier since we are not dependent on physical labs for our research. At least one excellent theorist pronounced covid-19 as a blessing in disguise for theorists because apparently we can now do physics round the clock from home without being bothered by the mundane. Another excellent theorist pronounced that the lockdown has been an unmitigated disaster for his research, since he can only focus on his research for no more than 2 hours per day from home. I do not know either personally well, but my guess would be that the differences in their pronouncements on the impact of covid-19 is probably directly related to one having no children at home and the other having small children at home.
There is no question, however, that theorists can still work from home reasonably effectively, children or no children. How effectively a theorist may be able to work from home depends entirely on their personal circumstances and personalities, but all theorists, unlike any experimentalist, are better off in terms of their research during the pandemic lockdown. For example, I posted 9 papers on arXiv with 13 different co-authors during the March through May 3-month period. This is certainly much more than my average productivity. So, in some sense, I am probably in the camp of the physicist who triumphantly pronounced the covid-19 lockdown as a positive development for theoretical physics research! My situation as a theoretical physicist is, however, quite unique. First, I live alone and basically have nothing to do except for physics and dining in good restaurants, which I can no longer do. So, I certainly am doing physics for a greater number of hours per day on the average during the covid-19 lockdown than before. Second, I have a large number of collaborators, right now I am working with 24 different physicists (16 in Maryland and 8 in other institutions all over the world), and theoretical collaborations are possible at some level during the lockdown through emails/dropbox/zoom/skype, etc. The question, however, still remains whether it is possible to sustain this style of collaboration through internet for an indefinite period of time. The answer, in my experience, is most definitely 'no'.
Starting totally new projects on brand new ideas is very difficult, if not impossible, to do over the internet, no matter how clear and fast the zoom connection might be. I have started working on three completely new problems with my students during the lockdown, and all of them are very slow going. Without the active give-and-take of face-to-face discussions, it seems almost impossible to make progress on collaborative theoretical projects where defining the problem is the main challenge. Once the problem is defined, the calculations can mostly be done at home, but even then, comparing results and discussing follow-ups over the internet is a very cumbersome and inefficient process.
What about solo research? After all, the great ones (Newton, Maxwell, Einstein, Schrodinger, Dirac, Schwinger) rarely wrote collaborative papers, at least not for their groundbreaking work. Can high-quality one-person theoretical research continue indefinitely under lockdown? I cannot answer this question with certainty since I last wrote solo papers regularly only during 1980-86 and realized then that I am much more effective in a collaborative environment, as I enjoy solving many problems rather than focusing on one grand problem of the day. Perhaps solo theoretical research does benefit from a lockdown. This is an interesting question, which I will not try to answer because it is completely irrelevant in my field of physics (
quantum condensed matter physics). To zeroth order, non-collaborative solo research is nonexistent in the theoretical condensed matter physics of today. A cursory look at the most-cited papers in the Physical Review B (
Condensed Matter Physics) since 2010 shows no single-author paper in the top-100 list and very few in the top-1000 list. Theoretical condensed matter physics is essentially a collaborative enterprise with most notable papers having 2-4 coauthors. I therefore believe that the lack of direct face-to-face discussions will affect theoretical research in a profoundly negative way if this continues for many months.
Somewhat less important, but still not insignificant, is the role of conferences/seminars/workshops in fostering good theoretical research. Physics in the end is what physicists do, and if physicists do not interact directly face-to-face at events, listening to each other to come up with new ideas, I think that theoretical physics will atrophy. There is a reason that institutions such as KITP in Santa Barbara and ACP in Aspen and ICTP in Trieste play very important roles in all of theoretical physics. They allow theorists to interact directly with each other, leading to progress which most definitely would be impossible otherwise. The lack of face to face collaborative discussions and the absence of seminars/workshops/conferences are bound to have a profound negative effect on theoretical physics if this lockdown continues. Perhaps in some distant future we will get used to zoom/skype discussions just as we got used to air travel under rigorous security constraints eventually (after 9/11), but I have serious doubts.
Physicists (as well as other professional scientists) are very fortunate that none of us is (as yet) unemployed because of covid-19. But, if the crisis continues into the indefinite future (six months or more), our lives are bound to be affected more directly. For example, it is likely that foreign PhD students and postdoctoral fellows will no longer get visas and that this will strongly affect research in theoretical physics, where more than 50% of the younger US researchers are foreigners. In our center, only 5 of the 25 non-faculty researchers (students/postdocs) are US citizens, the rest hold temporary US visas. Given that university budgets are likely to be drastically cut because of covid-19 induced financial losses, new faculty hiring will disappear for the next couple of years. If labs do not reopen soon, all of physics research will suffer because pure theory without any experiments would require a rather small number of researchers. The future is uncertain to say the least.
In my next blog, I will address the issue of how physicists can play a role in the covid-19 crisis. Right now, physics is as far from the covid-19 landscape as anything can be. This is unfortunate since in the end the covid-19 crisis is a scientific-technological crisis, and physics should play a role here. Physics and physicists have played important roles over the years in arms-control, climate issues, finance and economics, engineering, and biology. The relative silence of the physics community in perhaps the most important crisis facing the country for more than 100 years is therefore somewhat surprising. Physicists have considerable expertise in statistical and analytical techniques, simulations and modeling, complexity theory, physical kinetics, network theories, and dynamical systems of many interacting degrees of freedom. All of these tools could be put to good use in developing both abstract and practical tools for understanding and perhaps even controlling the spread of SARS-COV2 virus.