Second wave. COVID-19

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Second wave. COVID-19

The World Health Organization (WHO) said: “The coronavirus pandemic is gaining momentum. The COVID-19 coronavirus pandemic in the world has been going on for six months, and so far the crisis is far from over. We all want this to end … But the harsh reality is that it’s not even close to the end. Despite the fact that many countries around the world have made some progress, in fact the global pandemic is gaining momentum.”
Earlier, experts and analysts at Alfa Resonance Capital expressed some opinions on issues related to COVID-19. You can get acquainted with these publications in the articles: “COVID-19 or everything is just beginning”, “Pandemic 2020 or the crisis of democracy?”, “Life after the crisis of 2020”. However, we propose to understand in more detail what exactly has changed since the pandemic began, what awaits the population of our planet in the future, and where will the business move on?

Why COVID-19 was not infected 80% of people, as scientists predicted? Was quarantine really needed? The second wave of the epidemic threatens the world? The World Health Organization reported that at the end of June, the coronavirus epidemic entered a “new dangerous phase”: for the first time in the world for the first time in all observations, more than 150 thousand new infections are recorded. Moreover, in all cities and regions of Europe, America and Asia, where the epidemic began in the spring, the peak of the first wave is obviously passed. All these cities and regions managed in 8-12 weeks – and regardless of whether they introduced strict quarantine measures or not; in all – no matter how many – no more than 10–20% of the population was ill. In the spring, few expected this epidemic to develop: most scientists made gloomy forecasts, promising that during the first wave more than half of the population would be ill, and overcrowding of hospitals and morgues could be avoided only with the help of strict quarantine.

The epidemic began six months ago. What do we know about her for sure? Scientists have found almost all the most important parameters of the epidemic:
  • The incubation period of the virus is quite accurately known: it is about five days from the moment of infection to the onset of the first symptoms.
  • It was found that the infected person becomes contagious a few days before the onset of symptoms. The study of real pairs of transmission of the virus showed that such “pre-asymptomatic” infected people are responsible for almost half of all subsequent infections. This creates enormous difficulties for the authorities – in order to track and isolate all contacts of the identified infected, they need to act quickly: the clock goes by until the new infected, who have not yet developed symptoms, have infected the next group of people. This has prompted authorities and companies from different countries to develop applications for mobile devices with which you can quickly track contacts of infected people.
  • We learned that in most countries (but not in all) the epidemic at first looks like an explosion – the virus spreads through the population very quickly. Sometimes it is possible to identify a “null patient” or patients who have infected many people, but more often the source of primary infection remains unknown.
  • Most of the countries after the first “explosion” of infections in one way or another copied the epidemic control model tested in China: strict quarantine measures were introduced, service enterprises, restaurants, bars, schools and many enterprises whose employees can work from home were closed. Following such lockdowns, an economic crisis of unprecedented strength and form inevitably came: at the same time, demand fell (citizens reduced spending) and supply (a significant part of enterprises did not work).
  • Scientists have found the true lethality of the virus: according to recent reviews of many studies, on average it makes up 0.64% of all (including asymptomatic) infected. In countries with a young population, mortality is slightly lower, in countries with an elderly population – slightly higher. In the oldest populations (for example, on the Diamond Princess liner, where the virus spread in a population of more than half of elderly passengers), mortality was 1.5%. Knowledge of mortality allows you to clarify the data on cases of infection in each country, region and city – they can be calculated from the number of deaths (and in countries where there is a systematic underestimation of coronavirus deaths – from statistics on excess mortality).
As the virus was studied and its effect on people’s lives, new questions arose.
  • We do not know exactly how really restrictive measures of different governments affected the epidemic. At first glance, quarantines can fully explain the decline in the spread of the virus. So, the researchers found a correlation between a decrease in population mobility and a decrease in the number of deaths from coronavirus. After mobility decreased by two thirds of the “pre-viral” level, mortality everywhere began to fall.
“However, there were exceptions to this rule: in Switzerland, Belarus, and Sweden, mobility was not even one day lower than two thirds of the “pre-virus” level, but the epidemic stopped at the same time as in other European countries. In some regions where restrictions were lifted long ago – for example, in Wuhan, the epicenter of the pandemic – this did not lead to a new surge in infections. At the same time, Wuhan, as well as any other large city in the world, as it seems, did not nearly reach the “group immunity” calculated by epidemiologists – that is, the share of patients who were ill with 60–80%, in which, according to popular epidemiological models, the epidemic itself had to end.
  • In the UK, the mobility of the population a few weeks ago exceeded the threshold beyond which the growth of infections and mortality was supposed to begin. However, the epidemic there, after a long plateau, on the contrary, began to slow down rapidly. A similar situation seems to have developed in Russia: the mobility of the population, calculated according to Apple, exceeded the threshold of 68% (two-thirds of the “pre-virus”) back in early May, after which it continued to grow. Thus, we can conclude that quarantine in the country was observed worse and worse. However, in June, when quarantine was finally lifted, all indicators of morbidity and mortality in Russia began to decline rapidly.
  • In the meantime, in the least affected Chinese provinces, as well as in states that particularly successfully and quickly stopped infection in the spring (from Israel to South Korea and Germany), the virus almost disappeared, and then reappeared – and now they fear that this is the beginning of the second waves of the epidemic.
  • We do not know exactly how each restrictive measure or sanitary norm affects the epidemic. Similar restrictions were introduced in most countries in a single package, and therefore it is very difficult to single out the contribution of each measure individually. Moreover, it is difficult to even evaluate their contribution theoretically, because we do not know exactly how the virus is transmitted (and how it is not transmitted). So, recent studies indicate that the main path to infection is long-term close communication in a closed room; all other methods – from fleeting contact on the street to infection through surfaces – no longer look so dangerous.
  • Another question concerns the impact of quarantine on the economy: economists do not agree, the crisis would have been less deep if there were no restrictions on movement and enterprises were closed. It is clear that the epidemic itself became the main cause of the crisis, which changed the behavior of the population and instilled uncertainty in investors. But the longer the restrictions remain, the greater the likelihood that enterprises and the population will not be able to adapt to the new viral reality; this threatens the economies of different countries with a protracted depression.
  • Thus, it is very difficult for economists to calculate the share of guilt in the crisis of the epidemic, centralized measures to combat it and the information (truthful and not so) that determines the behavior of the population. This complicates the search for a compromise between saving lives (we don’t know exactly how different quarantine measures preserve them) and preserving enterprises and jobs (we don’t know how they would be preserved if different restrictions were not introduced).
  • All this uncertainty and the strange spread of the virus in different countries again aggravated discussions about the quality of the models with which scientists are trying to predict the development of the epidemic. In the spring, proponents of tough measures convinced politicians in almost all countries of the world that they needed the toughest lockdowns (without which millions of deaths and crowded hospitals would have awaited the world). Now, in honor of the theory of “selective restrictions” and models that predict the possibility of less destructive for the economy and society control over the epidemic.

Recall what were these models? And what was wrong with them? The first models and forecasts based on them appeared in February. Almost all of them belonged to the class of SEIR models that were developed in the middle of the last century and have since been used to predict the spread of a wide variety of viruses. WHAT DOES SEIR MEAN? The main thing you need to know about these models:
  • The entire population (population) is simplistically considered homogeneous (i.e. uniformly mixed). With this simplification, everyone has an equal chance of contacting any other. The number of infections here is proportional to the product of the number of infected and the number of “vulnerable” and depends on the initial transmission rate of the infection (that is, on the properties of the virus itself) and the density of contacts between different groups.
  • The transmission rate is set through two parameters: the serial interval is the typical time that an infected person remains contagious, and R₀ is the reproduction rate (it can be understood as the average number of people that one infected manages to infect during the time until he recovers).
The R₀ coefficient can be different in different populations (this is easy to imagine if you mentally compare the transmission of the virus in a large city or a remote village). However, within large populations (cities or regions), most models consider the coefficient R коэффициент to be indivisible and homogeneous.
  • In addition, at different stages of the epidemic, the reproduction rate will change (at each point in time it is denoted as Rt). For example, Rt will fall due to measures taken to suppress the epidemic, which interrupt the transmission chain of the virus (various forms of quarantine, detection and isolation of infected people and monitoring their contacts).
  • The model behaves completely differently for different values ​​of R₀ (Rt). With Rt values ​​less than one (that is, when each infected person infects on average less than one “vulnerable”), the epidemic dies out. At Rt> 1, it spreads and covers a significant part of the population.
  • The epidemic will stop only when a significant proportion of the population becomes ill and gains immunity (the so-called group immunity), and the proportion of “vulnerable” decreases so that the virus no longer has enough “targets” for distribution (in this case, it’s the new coronavirus that’s being considered, to which, as it is believed, no one in the population initially has immunity).
  • Artificially group immunity can be obtained only with the help of vaccination, which is not yet available in the case of coronavirus.
  • Using the serial interval and R₀, it is just possible to calculate the “depth of damage” of the epidemic (attack rate) – the proportion of the population that will be infected until the virus spreads due to the lack of those who do not have immunity. The depth of the lesion is always slightly higher than the threshold of “group immunity”, because people continue to become infected for some time even after the epidemic has already subsided.
  • Most of the models in relation to the coronavirus predicted the “depth of damage” in 60-80% of the population of countries affected by the epidemic.

Quarantine introduced due to SEIR-models? Almost all measures against coronavirus were tested by the first victims: China and South Korea. In China, they developed a quarantine package, and in Korea, a system for mass testing and identifying infected contacts (China also used mobile applications for these purposes, but did not rely on tests). Most likely, the authorities of China and South Korea were guided not by models, but by recent experience in combating other deadly diseases caused by coronaviruses – SARS and MERS, respectively. All other countries (with rare exceptions) have adopted the Chinese or Korean experience (or a mixture of them).
But the signal for imposing restrictions in the West was nevertheless a model published on March 16 by Neil Ferguson’s group from Imperial College in London. It favorably differed from the crude SEIR models in that it did not consider the population as “uniformly mixed”, but was based on real contacts between the inhabitants of the UK and their distribution among the cities of the country (according to the census). The main parameter of “heterogeneity” was the difference in population density in different regions, as well as in the number of workers in offices, factories and students in classes and classrooms.
According to the model, more than 81% of people in the USA and Great Britain (as well as in other countries where the epidemic started at that time, but they were not considered in detail) should be ill with the coronavirus. If strict quarantine measures are not introduced, more than half a million people will die in the UK in a few weeks, and 2.2 million in the United States, scientists wrote.
After the release of this work, the authorities of Great Britain and many US states (until then did not believe in the danger of the virus) limited the movement of people, closed schools, restaurants and many enterprises. At the same time, almost all countries of Europe and the Middle East, where the virus came, entered quarantine. In Europe, only Sweden and Belarus refrained from quarantining.
Naturally, the Ferguson group, which had so clearly influenced the policies of the largest states, was immediately criticized. Mostly she was blamed for the too low assessment of the difference in the rate of transmission of the virus in different population groups.
The models that were used at the beginning of the epidemic were criticized in two ways:
  1. Methodology. Epidemiologists have long realized that SEIR models have a big flaw: they simplify reality too much, believing populations to be homogeneously mixed. In fact, populations of animals, and even more so people, have a complex network structure. In different “departments” of these networks, the infection spreads differently, and therefore the concept of a single and indivisible “reproduction rate” does not make sense.
  2. The philosophy of science. From the point of view of evidence-based medicine in healthcare, any interventions that are not confirmed by complex studies (and independent of the subjectivity of the researchers themselves) are possible only as a last resort.

Is it possible to introduce restrictions without evidence? They argue about this! Is there an alternative to old models? There is – but so far, alas, mostly theoretical. In the 1980-1990s, epidemiologists, realizing the incompleteness and inaccuracy of the old methods, developed a whole class of network models for the spread of infections. Their main differences from the old methods:
  • They do not consider the population as a homogeneous set of particles with equal chances of “contact”. On the contrary, these models tend to complicate the structure of contacts so as to bring them closer to reality. Separate groups within the population are modeled – up to each household and networks (professional, transport, and any others) connecting with other groups. An important part of network models is the age groups and the structure of their contacts, especially for diseases that have pronounced age differences in the incidence and severity of the disease (as is the case with coronavirus).
  • The speed and depth of infection in this case depends on the density of contacts. Obviously, for different infections and in different groups, the laws of distribution will be very different. So, for example, many infections do not depend on population density at all: say, for the speed of spread of malaria, the density of “agents”, infected mosquitoes, is important.
  • It is becoming more and more difficult with respiratory diseases, but in their case you can find many examples when it is not the crowded population but the social activity of group members that are important (there are studies that confirm that the dependence of epidemic parameters on population density is not very large). Probably all three diseases – SARS, MERS and COVID-19 – are just very sensitive to the social activity of each group in the population. By “socially active” it is not at all necessary to understand groups of people who go to bars and nightclubs to the last, attend crowded meetings or go on a visit in the midst of an epidemic. Particularly active include many professional groups: shift workers living in a dormitory at a distant drilling rig, or doctors in an infectious diseases hospital.
  • A consequence of the heterogeneity of the population – the models do not operate with the reproduction coefficient R₀ common for the population: it will be different for each group.
The last property can completely change the conclusions of the simulation: with the same observed R₀, radically different predictions of the “depth of damage”, group immunity and the spread of infection can turn out.
One study adapting network models to COVID-19 provides an “intuitive” example: suppose one coronavirus infected in a regular (non-infectious) hospital. In the hospital, there are six doctors in nine single rooms. The first carrier infected one doctor. He, forced to communicate closely with a large number of patients and colleagues, infected six patients and four doctors. On new infected patients lying in the wards, the chain of transmission of the virus was interrupted. But infected doctors each infected 10 people – also in the proportion of 60% of patients and 40% of colleagues. If after that all the doctors and patients are regularly tested in the hospital, the reproduction rate of 3 will be fixed; according to models with a homogeneous population, this means that two-thirds of the members should be infected in the entire population until “group immunity” is reached. However, if we take into account that there is a rather low percentage of doctors in the population, then only about 8.3% of the population (⅚ of all doctors) will be infected to stop the epidemic in hospitals.
In the case of deadly coronaviruses, nosocomial transmission is one of the most important ways the epidemic spreads. But not only it – all three viruses show a high (if not record) “heterogeneity” of infection: roughly speaking, a very small proportion of infected (the so-called superspreders) are responsible for most of the infections. These superspreders, most likely, are included in their groups of especially socially active ones (where the “classmates” infected by them also have every chance of becoming “super”). Members of less active groups infected by them are likely to be a “dead end path for the virus,” that is, they themselves infect on average less than one person.
In recent weeks, there has been a lot of work evaluating the role of superspreders in the spread of a new coronavirus (based on real proven cases of infection). It follows that about 10% of those infected are responsible for 80% of new infections. That is, most of the new infections occur within the most active groups, which become the main victims of the epidemic. Once they reach their own threshold of “group immunity”, the epidemic will come to naught. In general, for the population, this threshold will mean infection of about 10% of members, some scientists believe.

That is, quarantine was not needed? The restrictions imposed by the governments of different countries did exactly what they should: saved lives and saved hospitals from overload. At the beginning of the epidemic, SEIR models give exactly the same predictions as network models. And only after the peak has passed, the indicators begin to differ: in older models, after quarantine removal, a new wave of infections should immediately follow; in network models, the second wave may come with a delay or not come at all. It all depends on whether all the most active groups have been ill.

What to do with the economy? How to let her recover if the second wave threatens us? Economists have the hardest time: they are forced to make forecasts and give advice to the authorities in the face of uncertainty in all respects:
  • It is unclear how the epidemic will develop in the still inactive groups. It is not clear whether new restrictions will be required and how they will be respected by economic agents. It is known that in developing countries (a study in Mexico), where the authorities cannot spend trillions of dollars to support citizens and enterprises, quarantine is a difficult compromise between the population and itself: all the time you have to make a choice between the health of loved ones (and a decrease in social activity) and well-being (and increased activity). In developed countries, this “trade” is also present (especially among poor groups), but the problem is not so acute.
  • There is no full understanding of what the same compromise looks like – “public health versus the well-being of the country” – at the level of power and the whole society. There is a lot of information (from countries that did not introduce quarantine) that falling consumer demand and rising unemployment depend on public perceptions of the danger of infection, and not just on measures to combat the epidemic. According to South Korea, the fear caused by the epidemic destroyed jobs in the country without quarantines; Americans object that restrictions make it more effective – jobs during quarantine disappear for a long time, which threatens the economy and citizens with a long-term depression.
In these extremely uncertain conditions, economists are looking for ways to avoid the trade-off between health and well-being. If the creation of the vaccine is delayed, then it will be necessary to avoid new total restrictions, but not to allow the loss of lives.
The most popular option addressed by well-known economists is to isolate those whose lives are in the greatest danger, that is, older citizens (everyone else will gradually receive group immunity). The option resembles the Swedish strategy, which ended in failure: the virus entered many nursing homes in the country, which led to increased mortality. And the Swedish economy seems to suffer no less than the neighbors who were in quarantine.
Losses of those who quarantined too early and did not come up with a replacement for it may be the highest: such a policy increases the risk of new outbreaks. As the US Federal Reserve economists found out, during the Spanish city, those cities that hastened to lift restrictions after the first wave suffered more economically than those who showed patience.

Was there really a virus? Reliably and objectively, only one thing – there was a global release of information about a certain world-class danger, which is difficult to verify and which is difficult to refute. Certain statistics were provided that told us about the high mortality and infection rates. But from what diseases? From our screens disappeared statistics on mortality from heart attacks, on mortality by age, on mortality from pneumonia, AIDS and so on. However, information on the level of mortality and morbidity from the coronavirus began to prevail on all information platforms. Don’t you find this strange? In other words, we got information that was beneficial, and not which actually happened. Knowingly false information about the spread of the disease, which, in fact, does not pose a serious danger to humanity.

Why is it difficult to check? The pandemic, quarantine and isolation regime forced humanity to shut itself down inside its own homes. Information about the state of the outside world is obtained only through the media. Observing social distance does not allow groups to gather, exchange opinions and news. The obligatory wearing of medical masks erased our faces and our emotions, turning the world’s population into silent and faceless slaves, following the instructions of the powerful. We were forced to remain silent and meekly believe only in what television and radio dictate to us. We were deprived of the right to our own opinion, we were deprived of the opportunity to be at the epicenter of events and the right of personal presence in the places of unfolding events. Therefore, the ability to verify the accuracy of information is artificially minimized.
Meanwhile, it is reliably known that the information provided on overcrowded hospitals and morgues is false, and medical staff follow orders “from above”. In addition, many actors appeared in screens in medical gowns, posting photographs of their tormented faces. The goal is simple – to arouse pity, believe and meekly stay at home. In fact – the hospitals are empty – check for yourself!

The situation comes to the point of absurdity. In some countries of the world, representatives of hospitals and insurance companies offer cash rewards if you agree to subscribe to the diagnosis of COVID-19 or to subscribe to the fact that your relative died from coronavirus. Medical holdings receive huge subsidies from the state for showing high disease statistics from COVID-19. In pursuit of this money, all means are good. Therefore, doctors are not enough. For example, in the Russian Federation, oncologists or psychiatrists come to call an ambulance for heart pain. They do not provide assistance to the patient, but take a coronavirus test and issue a two-week quarantine order. Violated the quarantine – a fine, left the house – a fine.
As a result of all this: home-based “self-isolation”, information shortages of truthful news, uncertainties in work and business, lack of sufficient funds and so on, the population of our planet is under constant psychological stress, bordering on disruption and aggression. Also, there were cases when people without medical masks were subjected to physical violence from people wearing masks. They dressed us with muzzles and convinced that it was necessary!

What is all this for? In war, all means are good – it doesn’t matter if it’s economic war or physical warfare. Any war always and at all times begins with the economic weakening of its adversary. The history of our world and our present is the clearest confirmation of this. Obviously, a process of weakening the economy of a number of countries is currently underway. Can this speak of an economic war? Yes! Can this speak of the impending war (including the third world war)? Yes!

When to wait for the second wave of a pandemic? Obviously, the economic and social sanctions that have arisen under the auspices of the “pandemic” are not yet over, but will only be exacerbated and tightened. Analysts at Alfa Resonance Capital, analyzing the frequency, depth and order of information impacts on the population, predict the second wave of the pandemic from mid-August 2020 and its peak in October-November this year. A business should now be ready for these events and look for ways to protect its funds and entrepreneurial activities.

Business, who will survive, what to invest in and what to attract investment in? As the long-standing practice of doing business in the midst of global economic crises has shown, and also (and this is extremely important!) In the midst of the first wave of the COVID-19 pandemic, there are a number of segments that not only continue to feel comfortable in extreme conditions, but also demonstrate noticeable growth and scaling of their own activities. In the wake of general panic, uncertainty and fears, people are investing in products that will remain liquid at all times. Accordingly, the following business segments remain “on horseback”: construction and real estate operations, the jewelry business, the pawnshop business, the production of essential goods and products, transport and personal protective equipment and life safety.

How to save and increase? Any smart business is a flexible mechanism that can instantly adapt to existing and incoming changes in market conditions. Building strategies to survive and scale a business is not a “tomorrow” process, but a “yesterday” process. Accordingly, any strategy calculates scenarios for the development of the market or its fall, obviously over several years. The current realities are a great moment to confirm or refute the hypotheses expressed in the existing strategies of your business. However. this is not always possible based on purely personal experience. Alfa Resonance Capital offers a full range of consulting and financial services and tools that can really help in the development of your business. For all questions:




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