China Has Completely Failed To Defeat Income Inequality The descendants of the pre-revolution economic elite are significantly better off today than the descendants of the pre-revolution poor. by James Pethokoukis

A lot has happened in Italy over the past six centuries or so. There were many, many wars. Lots of popes, too. Also the Renaissance. Plus the films of Federico Fellini. And Totti.

But through it all, the surnames of the successful haven’t changed so much. At least that was the main finding in the 2016 paper, “Intergenerational Mobility in the Very Long Run: Florence 1427-2011” by Italian economists Guglielmo Barone and Sauro Mocetti. The researchers looked at tax records from Florence in 1427 — including surnames, occupations, earnings, and wealth — and matched them to city tax records from 2011. The top-earning surnames today “were already at the top of the socioeconomic ladder six centuries ago – they were lawyers or members of the wool, silk, and shoemaker guilds; their earnings and wealth were always above the median.”

One event not experienced by Italians was a brutal communist revolution followed by decades of totalitarian rule. Had that happened, maybe the researchers wouldn’t have found such a persistence of socioeconomic status. Inequality would have been forever beaten out of society.

Take China, for instance. The second half of the 20th century saw that country experience two major revolutions: the Communist Revolution in the 1950s and the Cultural Revolution from 1966 to 1976. As described in the new working paper “Persistence through Revolutions” by Alberto Alesina, Marlon Seror, David Yang, Yang You, and Weihong Zeng, those tumultuous events represented “two of the most extreme attempts in human history to eliminate the advantages of the elite, to eradicate inequality in wealth and education, to close down formal channels of intergenerational transmission such as inheritance and schooling, and to erase cultural differences in the population, especially between the rich and the poor.”

The expropriation and redistribution of land, as well as the closure of secondary schools and universities, were particularly effective in achieving the “homogenization of the population.” But only over the short run. When China opened up, the old inequality returned. From the paper:

However, three decades after the introduction of economic reforms in the 1980s, the descendants of the former elites earn a 17% higher annual income than those of the former non-elites, such as poor peasants. The grandchildren of pre-revolution elites systematically bounced back, despite the cards being stacked against them and their parents. They could not inherit land and other assets from their grandparents, their parents could not attend secondary school or university due to the Cultural Revolution; their parents were unwilling to express previously stigmatized pro-market attitudes in surveys; and they reside in counties that have become more equal and more hostile toward inequality today.

One channel we emphasize is the cultural transmission of values from one generation to the other. The grandchildren of the former landlords are more likely to express pro-market and individualistic values, such as approving of competition as an economic driving force, and willing to exert more effort at work and valuing education as an input into success. In fact, the vertical transmission of cultural values (“informal human capital”) is extremely resilient: even stigmatizing public expression of values may not be sufficient, since the transmission in the private environment could occur regardless. The cultural transmission within the family seems to have survived extraordinarily broad and deep institutional and political changes, with an extraordinary resilience.

And here is the example of the persistence of advantage in the family history of Guangyu Huang:

Guangyu was born in 1969. His grandfather was a rich landlord in Guangdong, who lost most of his land and assets during the Communist Revolution. Guangyu’s father, Changyi Huang, grew up in the midst of the Communist and Cultural Revolutions, and as a result received no inheritance, no formal education, and eked out living by extracting persimmon oil. Guangyu grew up after the revolutions, but lived by collecting trash with his siblings during his early childhood. Eventually, Guangyu graduated from Renmin University, one of China’s most prestigious colleges. Guangyu’s fate changed in 1987 when he seized the opportunity of the first wave of private enterprise boom during the reform era of China, and founded GOME Electronics. GOME became a huge success, making Guangyu the richest man in mainland China between 2004 and 2018, with a net worth of RMB 36 billion (approximately US$ 5 billion). While this is certainly an extreme example, we show in the paper that Huang’s family story represents a more general pattern across China. Despite extraordinary repression, the descendants of the pre-revolution economic elite are significantly better off today than the descendants of the pre-revolution poor.

 One thing that popped into my head while reading this was the possible role of innate or biological traits. The researchers do address this issue. Because they did not have direct measures of personalities or intelligence, they could not “rule in or rule out the possibility that these characteristics contribute to the persistence.” That aside, the paper does provide a valuable lesson in a) just what it takes to stomp out inequality — and how if you ease up on those draconian measures it just comes roaring back — and in b) how foreign such radical equality is to the successful human experience.

Is Coronavirus a 'Black Swan' Event? Spoiler alert: it isn’t. by Glenn McGillivray

Since the “black swan” metaphor was coined in the 2007 book of the same name it has become fashionable to label virtually all low probability/high impact events black swans. 

But the danger of making an occurrence like the COVID-19 outbreak appear to be astronomically rare is that we will treat it as such and fail to prepare for the next pandemic. What’s more, those accountable for this preparation will dismiss their blatant failures because of the perceived exceptional nature of the event.

As managing director of the oldest university-based disaster risk reduction research institute in Canada, and with almost 30 years of researching and writing about disaster risk management, I know this all too well. When you make an event seem exceptional when it really isn’t, it will be used as a crutch by those who failed to prepare in the face of the known risk.

What is a black swan?

In The Black Swan, written by professor, statistician and former options trader Nassim Taleb, the author explains how an event can come to be named a black swan:

“First, it is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it carries an extreme ‘impact.’ Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable.”

So, by their very nature, black swan events are quite exclusive. They must be, because if next to everything is a black swan, then nothing is.

But this still leaves the question: Can COVID-19 be considered a black swan?

Let’s look at some of the facts and place them against the three attributes set out by Taleb.

Attribute one: Is the COVID pandemic an outlier?

History shows that infectious diseases, epidemics and pandemics, have been the number 1 mass killers of people, outperforming even natural disasters and wars (indeed, more people died from the 1918 flu outbreak than died in the First World War).

That pandemics break out from time to time is well known and well documented.

So, too, are warnings about the “next” outbreak. Says journalist Ed Yong in The Atlantic:

“In recent years, hundreds of health experts have written books, white papers and op-eds warning of the possibility. Bill Gates has been telling anyone who would listen, including the 18 million viewers of his TED Talk. In 2018, I wrote a story for The Atlantic arguing that America was not ready for the pandemic that would eventually come.”

Both George W. Bush (in November 2005) and Barack Obama (in December 2014) warned of the next pandemic in speeches at the National Institutes of Health.

Along with the historical record and the many articles, papers and other sources that warn of the next pandemic, governments themselves often conduct exercises, including table-top simulations and other planning, in an attempt to determine how to get ahead of the next pandemic.

Seven days before Donald Trump took office on January 20, 2017, his aides and out-going Obama administration officials were briefed on a table-top exercise that played through a fictitious outbreak of H9N2 — an influenza virus — with effects not unlike what we have seen with SARS-CoV-2.

Similarly, in 2019, the Trump administration’s own Department of Health and Human Services carried out a pandemic simulation tagged as “Crimson Contagion,” which played out a viral outbreak originating in China that could kill close to 600,000 people in the United States alone.

So, can we say in all fairness and honesty that no one saw the possibility of COVID-19 coming?

Attribute two: Does COVID-19 carry an extreme impact?

Taleb’s second requirement is that the event must have a major impact.

At writing, attempting to provide an accurate quantitative impact of COVID-19 would be akin to snapping a picture of an odometer as the car is racing down the Autobahn.

However, while COVID-19 is not anticipated to have an impact even remotely close to that of the 1918 flu outbreak (at least 50 million deaths), there can be no question that the current pandemic has had — and will continue to have — an extreme impact, both on people and on national economies.

Attribute three: Is it, or will it be, normalized after the fact?

The concept of “normalizing” a large event — by rendering it explainable or predictable in hindsight — completes the three criteria and makes it a black swan. However, this element seems quite arbitrary, raising several questions:

Who is qualified to normalize an event in this manner, whereby the initial shock of the event is then casually dismissed?

How can we know if an event is normalized unjustly or if the normalization is legitimate?

Can important comments by journalists like Bryan Walsh (“COVID-19, could not have been more predictable” and “COVID-19 marks the return of a very old — and familiar — enemy”) and Yong (“A global pandemic of this scale was inevitable”) be effectively neutralized by dismissing them as mere attempts to normalize or brush off the current crisis? The danger in doing so is that rejecting the inevitability of a pandemic like COVID-19 also enables us to reject the likelihood of future pandemics, and the need to be better prepared.

And, since the propensity to normalize can be attributed to a blind spot in human cognition (that is, people are hardwired to normalize), should it even be an attribute of a black swan in the first place?

Since we are still in the midst of the current pandemic crisis, we do not yet know whether the COVID-19 pandemic will be normalized.

So COVID-19, a black swan or no?

In the study of natural hazards, the chances of a flood or an earthquake or a hurricane happening in any given period in a given place is expressed in terms of time and probability. For example, the probability of one in 100 years for a flood means that there is a one per cent chance of a flood affecting a given area in any one year. This means that there is a 99 per cent chance that a given place will not be flooded — pretty good odds.

However, if you carry that same probability over a longer time frame — say over the life of a mortgage or the time residents plan to stay in a home (let’s say it’s 30 years) — the probability of a one in 100 flood hitting that house goes from one per cent per year to 26 per cent over the course of the mortgage — greater than one in four odds.

In a 2018 research study, investigators made the assumption that the probability of a pandemic of a certain level occurring is one in 100, or one per cent in any given year. So, just as with a flood, when calculated for a 30-year period, there is greater than a one in four chance of a pandemic occurring. Carrying the odds over 50 years means there is almost a 40 per cent chance of a global outbreak.

The subtitle of Taleb’s book is “The impact of the highly improbable.” But an event like COVID-19 is not all that rare. Indeed, history is replete with such events, there have been numerous warnings from many sources, and the mathematical odds of an occurrence are not all that remote. With pandemics, it is not really a question of if, but usually when.

Indeed, Taleb recently weighed in on the question of whether COVID-19 is or isn’t a black swan.

Spoiler alert: it isn’t.

What Is Our 'Plan B' If The Coronavirus Vaccine Never Comes? The federal government’s response to the coronavirus pandemic could turn out to be a policy mistake of epic proportions. by Paul H. Kupiec

The federal government’s response to the coronavirus pandemic could turn out to be a policy mistake of epic proportions. The success of the current response depends on the development of an effective vaccine in record time which allows the country to quickly return to its pre-virus economic boom. Should reality fall short, Congress will have created a massive amount of new federal debt with no plan B.

Policies that provide temporary support to shuttered businesses keeping their non-working employees on the payroll are tremendously expensive. They will only work if the public-private initiatives underway can engineer a quick reduction in the virus spread that allows the nation to return to business as usual, which is why the success of the government’s response hinges on the rapid development of an effective vaccine.

History suggests that expectations of a quick vaccine are heavily optimistic. After almost 40 years of research, there is no vaccine for the HIV. Similarly, there are no vaccines for SARS, MERS, or the common cold. It took 10 years to develop a vaccine for the Avian H5N1 virus. Moreover, vaccines do not offer complete protection. According to the CDC, the current seasonal flu vaccine is estimated to be only 45 percent effective.

The probability of death after contracting COVID-19 is unknown but not insubstantial. In Connecticut, 7.6 percent of all confirmed COVID-19 patients have died. Death rates are similarly high in Massachusetts (5.3 percent), Louisiana (6.2 percent), and Minnesota (7.5 percent). Once asymptomatic cases are accounted for, experts expect the average mortality rate to be much lower, perhaps under 1 percent. Still, without an effective vaccine, the overall risks of the coronavirus are material because a person with the coronavirus likely infects on average between two and 2.5 other people. Without an effective vaccine, informed consumers are likely to demand social distancing mitigation once businesses reopen — with or without a government social-distance mandate.

If social distancing remains the only practical mitigant for the foreseeable future, then many businesses will be forced to adapt to remain viable. It is hard to imagine that airlines, cruise ships, mass transit, eat-in restaurants, sporting events, and all other types of activities that rely on large concentrated gatherings of people will be able to resume pre-crisis operations profitably in this new environment. Taxpayers cannot afford to continue to support these businesses payrolls indefinitely. If the probability of survival of these types of businesses is remote in a COVID-19 world, it is shortsighted for Congress to be mortgaging America’s future on programs that freeze these potentially obsolete businesses in time, betting on the unlikely possibility that they can quickly and profitably be revived. Congress’s failure to devote at least some of these resources to developing a plan B — a plan that does not rely on the timely development of a successful vaccine — could end up being an expensive policy mistake.

It is not surprising that funding for programs that maintain the businesses and lifestyles of voters harmed by the virus through no fault of their own garner unanimous political support. Politicians of all stripes favor programs that grease their own reelection chances, especially when the inevitable spending constraints imposed by shortsighted bailout programs are realized in the future.

However, while there is no doubt the economic transitions catalyzed by the COVID-19 pandemic will be painful for many, they are also unlikely to be avoidable. Congress and the executive branch need to rise above narrow self-interest and focus more attention on formulating a plan B with programs designed to transition the economy so it can continue grow and prosper should the world fail to develop an effective coronavirus vaccine.

Could Any of These 47 Drugs Help Defeat the Coronavirus? Here's what the initial tests show. by Nevan Krogan

The more researchers know about how the coronavirus attaches, invades and hijacks human cells, the more effective the search for drugs to fight it. That was the idea my colleagues and I hoped to be true when we began building a map of the coronavirus two months ago. The map shows all of the coronavirus proteins and all of the proteins found in the human body that those viral proteins could interact with. 

In theory, any intersection on the map between viral and human proteins is a place where drugs could fight the coronavirus. But instead of trying to develop new drugs to work on these points of interaction, we turned to the more than 2,000 unique drugs already approved by the FDA for human use. We believed that somewhere on this long list would be a few drugs or compounds that interact with the very same human proteins as the coronavirus.

We were right.

Our multidisciplinary team of researchers at the University of California, San Francisco, called the QCRG, identified 69 existing drugs and compounds with potential to treat COVID-19. A month ago, we began shipping boxes of these drugs off to Institut Pasteur in Paris and Mount Sinai in New York to see if they do in fact fight the coronavirus.

In the last four weeks, we have tested 47 of these drugs and compounds in the lab against live coronavirus. I’m happy to report we’ve identified some strong treatment leads and identified two separate mechanisms for how these drugs affect SARS-CoV-2 infection. Our findings were published on April 30 in the journal Nature.

he more researchers know about how the coronavirus attaches, invades and hijacks human cells, the more effective the search for drugs to fight it. That was the idea my colleagues and I hoped to be true when we began building a map of the coronavirus two months ago. The map shows all of the coronavirus proteins and all of the proteins found in the human body that those viral proteins could interact with. 

In theory, any intersection on the map between viral and human proteins is a place where drugs could fight the coronavirus. But instead of trying to develop new drugs to work on these points of interaction, we turned to the more than 2,000 unique drugs already approved by the FDA for human use. We believed that somewhere on this long list would be a few drugs or compounds that interact with the very same human proteins as the coronavirus.

We were right.

Our multidisciplinary team of researchers at the University of California, San Francisco, called the QCRG, identified 69 existing drugs and compounds with potential to treat COVID-19. A month ago, we began shipping boxes of these drugs off to Institut Pasteur in Paris and Mount Sinai in New York to see if they do in fact fight the coronavirus.

In the last four weeks, we have tested 47 of these drugs and compounds in the lab against live coronavirus. I’m happy to report we’ve identified some strong treatment leads and identified two separate mechanisms for how these drugs affect SARS-CoV-2 infection. Our findings were published on April 30 in the journal Nature.

The testing process

The map we developed and the FDA drug catalog we screened it against showed that there were potential interactions between the virus, human cells and existing drugs or compounds. But we didn’t know whether the drugs we identified would make a person more resistant to the virus, more susceptible or do anything at all.

To find those answers we needed three things: the drugs, live virus and cells in which to test them. It would be optimal to test the drugs in infected human cells. However, scientists don’t yet know which human cells work best for studying the coronavirus in the laboratory. Instead we used African green monkey cells, which are frequently used in place of human cells to test antiviral drugs. They can be readily infected with the coronavirus and respond to drugs very closely to the way human cells do.

After infecting these monkey cells with live virus, our partners in Paris and New York added the drugs we identified to half and kept the other half as controls. They then measured the amount of virus in the samples and the number of cells that were alive. If the samples with drugs had a lower virus count and more cells alive compared to the control, that would suggest the drugs disrupt viral replication. The teams were also looking to see how toxic the drugs were to the cells.

After sorting through the results of hundreds of experiments using 47 of the predicted drugs, it seems our interaction predictions were correct. Some of the drugs do in fact work to fight the coronavirus, while others make cells more susceptible to infection.

It is incredibly important to remember that these are preliminary findings and have not been tested in people. No one should go out and buy these drugs.

But the results are interesting for two reasons. Not only did we find individual drugs that look promising to fight the coronavirus or may make people more susceptible to it; we know, at a cellular level, why this is happening.

We identified two groups of drugs that affect the virus and they do it two different ways, one of which has never been described.

Disrupting translation

At a basic level, viruses spread by entering a cell, hijacking some the cell’s machinery and using it to make more copies of the virus. These new viruses then go on to infect other cells. One step of this process involves the cell making new viral proteins out of viral RNA. This is called translation.

When going through the map, we noticed that several viral proteins interacted with human proteins involved in translation and a number of drugs interacted with these proteins. After testing them, we found two compounds that disrupt the translation of the virus.

The two compounds are called ternatin-4 and zotatifin. Both of these are currently used to treat multiple myeloma and seem to fight COVID-19 by binding to and inhibiting proteins in the cell that are needed for translation.

Plitidepsin is a similar molecule to ternatin-4 and is currently undergoing a clinical trial to treat COVID-19. The second drug, zotatifin, hits a different protein involved in translation. We are working with the CEO of the company that produces it to get it into clinical trials as soon as possible.

Sigma receptors

The second group of drugs we identified work in an entirely different way.

Cell receptors are found both inside of and on the surface of all cells. They act like specialized switches. When a specific molecule binds to a specific receptor, this tells a cell to do a specific task. Viruses often use receptors to infect cells.

Our original map identified two promising MV cell receptors for drug treatments, SigmaR1 and SigmaR2. Testing confirmed our suspicions.

We identified seven drugs or molecules that interact with these receptors. Two antipsychotics, haloperidol and melperone, which are used to treat schizophrenia, showed antiviral activity against SARS-CoV-2. Two potent antihistamines, clemastine and cloperastine, also displayed antiviral activity, as did the compound PB28 and the female hormone progesterone.

Remember, all these interactions have so far only been observed in monkey cells in petri dishes.

At this time we do not know exactly how the viral proteins manipulate the SigmaR1 and SigmaR2 receptors. We think the virus uses these receptors to help make copies of itself, so decreasing their activity likely inhibits replication and reduces infection.

Interestingly, a seventh compound – an ingredient commonly found in cough suppressants, called dextromethorphan – does the opposite: Its presence helps the virus. When our partners tested infected cells with this compound, the virus was able to replicate more easily, and more cells died.

This is potentially a very important finding, but, and I cannot stress this enough, more tests are needed to determine if cough syrup with this ingredient should be avoided by someone who has COVID-19.

All these findings, while exciting, need to undergo clinical trials before the FDA or anyone else should conclude whether to take or stop taking any of these drugs in response to COVID-19. Neither people nor policymakers nor media outlets should panic and jump to conclusions.

Another interesting thing to note is that hydroxychloroquine – the controversial drug that has shown mixed results in treating COVID-19 – also binds to the SigmaR1 and SigmaR2 receptors. But based on our experiments in both labs, we do not think hydroxychloroquine binds to them efficiently.

Researchers have long known that hydroxychloroquine easily binds to receptors in the heart and can cause damage. Because of these differences in binding tendencies, we don’t think hydroxychloroquine is a reliable treatment. Ongoing clinical trials should soon clarify these unknowns.

Treatment sooner rather than later

Our idea was that by better understanding how the coronavirus and human bodies interact, we could find treatments among the thousands of drugs and compounds that already exist.

Our idea worked. We not only found multiple drugs that might fight SARS-CoV-2, we learned how and why.

But that is not the only thing to be excited about. These same proteins that SARS-CoV-2 uses to infect and replicate in human cells and that are targeted by these drugs are also hijacked by related coronaviruses SARS-1 and MERS. So if any of these drugs do work, they will likely be effective against COVID-22, COVID-24 or any future iterations of COVID that may emerge.

Are these promising leads going to have any effect?

The next step is to test these drugs in human trials. We have already started this process and through these trials researchers will examine important factors such as dosage, toxicity and potential beneficial or harmful interactions within the context of COVID-19.

A Russian Navy Aircraft Carrier Killer Submarine Went Down in 2000. Here's Why. Why attack the Kursk? by Kyle Mizokami

In the end, the sinking of the Kursk appears to have been caused by a simple, freak accident of chemistry. The tragedy only reinforces how dangerous life aboard a submarine really is, and how important safety is in the underwater realm. 

In 2000, a Russian submarine designed to sink aircraft carriers became a victim of its own arsenal. The cruise-missile submarine Kursk suffered a massive explosion and sank after an onboard torpedo accidentally detonated. The accident was the worst naval disaster suffered by post–Cold War Russia.

The Soviet Union’s greatest adversaries at sea were the aircraft carriers of the U.S. Navy. With their versatile air wings, American carriers could frustrate the Warsaw Pact’s plans wartime plans, doing everything from escorting convoys across the Atlantic to bombing Soviet Northern Fleet bases above the Arctic Circle. They also carried nuclear weapons, making them exceptionally dangerous to the Soviet coastline.

The Soviets’ solution was the construction of the Oscar-class submarines. Some of the largest submarines ever constructed, they displaced measure 506 feet long with a beam of nearly sixty feet—nearly twice that of the Soviet Union’s Alfa-class attack submarines. At 19,400 tons submerged, they were larger than the American Ohio-class ballistic-missile submarines.

They were large for a reason: each Oscar carried two dozen huge P-700 Granit missiles. The P-700 was a large missile designed to kill large ships. The P-700 was thirty-three feet long and nearly three feet wide. Each weighed 15,400 pounds each, most of which was fuel for the ramjet-powered engine which propelled the missile at speeds of Mach 1.6 to a range of 388 miles. The missile packed either a 1,653-pound conventional high explosive warhead, enough to damage an aircraft carrier, or a five-hundred-kiloton nuclear warhead, enough to vaporize a carrier. The missiles would be fed targeting data from the Legenda space surveillance system, which would hunt fast-moving carrier battle groups from orbit.

The missiles were concealed beneath the hull in two rows of twelve, in silos pointed upward at a seventy-degree angle. It was this arsenal that earned them the then-unusual SSGN designation in the West, with the G standing for “guided missile.”

If that weren’t enough, the Oscars had a large complement of torpedoes. Each submarine had four standard-diameter 533-millimeter torpedo tubes that could launch standard homing torpedoes, SS-N-15 “Starfish” antisubmarine missiles or SS-N-16 “Stallion” antiship missiles. It also had two oversized 650-millimeter torpedo tubes for launching Type 65-76A torpedoes against larger ship targets. Together the six tubes were armed with twenty-four torpedoes.

The Oscars needed to be fast to intercept American nuclear-powered aircraft carriers, and that meant they too needed nuclear propulsion. Each was powered by two OK-650 nuclear reactors that together provided 97,990 shipboard horsepower. This accelerated the submarines to up to fifteen knots on the surface and a speedy thirty-three knots underwater.

Twenty Oscar-class submarines were planned, but only thirteen were built before the end of the Cold War and the demise of the Soviet Union. K-141, also known as Kursk, was laid down in March 1992 and commissioned into the Russian Northern Fleet in December 1994.

On August 15, 2000, the Kursk was on exercise with major elements of the Russian Northern Fleet, including the aircraft carrier Admiral Kuznetsov and battlecruiser Pyotr Velikiy. Kursk, which was fully loaded with Granit missiles and torpedoes, was scheduled to make a simulated attack on an aircraft carrier. At 11:28 a.m., an underwater explosion was detected followed two minutes later by a second, larger explosion. One Russian account claims that the twenty-eight-thousand-ton battlecruiser Pyotr Velikiy shook from the first explosion, and a Norwegian seismic station recorded both explosions.

Kursk had suffered two massive explosions and sank in 354 feet of water at a twenty-degree vertical angle. An explosion had ripped through the front of the hull, tearing a terrible gash along the upper bow. Still, at least twenty-three of the 118 crew had survived the sinking, as a note penned by one of the ship’s senior officers, Lt. Capt. Dmitri Kolesnikov, indicated. The note was dated exactly two hours after the initial explosion. Rescue efforts by Russian—and later British and Norwegian—teams failed to rescue the survivors.

A Russian inquiry into the accident concluded that one of the Kursk’s Type 65-76A torpedoes had exploded. A faulty weld in a torpedo or damage to a torpedo during movement had caused it to leak hydrogen peroxide. Like many torpedoes, the Type 65 used hydrogen peroxide as an underwater fuel. Unfortunately, hydrogen peroxide becomes explosive when it comes into contact with a catalyst, such as organic compounds or fire. A similar accident is thought to have sank HMS Sidon, a Royal Navy submarine, in 1955.

Conspiracy theories regarding the sinking of the Kursk are rife on the Russian Internet. Many allege that nearby American attack submarines sank the Kursk with Mark 48 torpedoes. While technically possible (in absence of the evidence of an internal torpedo explosion) there is no remotely plausible motive for such an attack during a period of good U.S.-Russian relations. Why attack the Kursk? Why was only the Kursk sunk, and not the Kuznetsov and Pyotr Velikiy? Why would the Russian government cover up the attack?

In the end, the sinking of the Kursk appears to have been caused by a simple, freak accident of chemistry. The tragedy only reinforces how dangerous life aboard a submarine really is, and how important safety is in the underwater realm. Finally, the rush to conspiracy is a warning that, had this incident occurred during a genuine crisis, such an accident could cause a dangerous escalation that could lead to war.

Why It's Too Early to Tell If Remdesivir Cures Coronavirus We have only gotten results from the preliminary study. by Nial Wheate and Andrew Bartlett

The race is on to find a drug that is both effective and safe for treating COVID-19, which has spread to 3.1 million infections and caused 220,000 deaths worldwide. 

This week, the US National Institute of Allergy and Infectious Diseases released findings of a clinical trial of the experimental antiviral drug remdesivir. This showed COVID-19 patients recovered more quickly and had an improved survival rate when taking the drug, compared with those given a placebo and standard care.

But these are just the preliminary results of one study. Other human trials have not shown similar results. Further trials are under way and will more definitively show whether remdesivir is a suitable and effective treatment for COVID-19.

What is remdesivir?

Remdesivir is an experimental antiviral drug being developed by Gilead Sciences. Originally it was being developed as a treatment for Ebola, a viral infection that causes severe internal bleeding. But researchers are now interested in its potential to treat patients with COVID-19.

Remdesivir mimics a natural ingredient called adenosine of DNA and RNA, the latter being a molecule similar to DNA that is used to carry the genetic information of viruses. After the drug is activated in the body, it works by blocking a type of enzyme called a polymerase, which is needed to make DNA and RNA.

When you block the enzyme, the virus can’t make copies of itself, limiting the development of symptoms and spread of the disease.

It should be noted that no drug is perfectly safe, and remdesivir is no different. Studies undertaken so far suggest the drug may damage the liver and cause other short-term side effects such as nausea and vomiting.

These side effects need to be taken into consideration when treating COVID-19 patients who have other underlying conditions.

Clinical trials in US positive but only preliminary

This week the National Institute of Allergy and Infectious Diseases (NIAID) released the results of its trial using remdesivir for COVID-19 patients. They studied the effects of the drug on patients who were already infected with COVID-19 to see whether it helped them recover faster and improve their survival rate.

Adult patients hospitalised with COVID-19 were given daily injections of remdesivir. They were found to recover four days faster, an improvement of 31%, when compared with other patients who only received standard care and placebo.

The results also indicated that more patients survived the infection with remdesivir treatment, with the death rate dropping from 11.6% to 8%.

The results are significant enough that director of NIAID Anthony Fauci said it was an “ethical responsibility” for the remaining trial patients who were taking the placebo to be switched to the active drug.

But we need to treat the results of this trial with caution; for the moment they are only preliminary.

A data and safety panel has looked at the initial results, but they haven’t been peer-reviewed. During peer review, independent experts from the scientific community scrutinise the study design, methods, data produced, and the conclusions before the study is published in a medical journal.

How does it compare with other studies?

The results of other trials, such as one undertaken in China, have not shown the same promising results.

The Chinese study was published in the Lancet, considered one of the most influential medical journals in the world. This trial was a randomised, double-blind, placebo-controlled study which means that neither the researchers nor the patients knew if they’d been given the active drug or a placebo.

These types of studies can reduce some biases that can influence studies, but also help quantify the effectiveness of the drug.

But the study also had limitations that need to be recognised. The patients were not as seriously ill as those in the NIAID trial, and the study was terminated early because the outbreak in China was easing.

In the end, the study only collected data on 237 patients, compared with 1,063 patients in the NIAID trial. The authors acknowledge further study is needed in more seriously ill patients and with a larger sample size.

Currently there are more than a dozen other clinical trials of remdesivir and COVID-19 being undertaken throughout the world. We need to await the data to know for sure whether the drug is as effective as we need it to be.

How Can Your Phone Tell You If You've Been Exposed to the Coronavirus? Apple and Google have created an exposure notification system. by Johannes Becker and David Starobinski

On April 10, Apple and Google announced a coronavirus exposure notification system that will be built into their smartphone operating systems, iOS and Android. The system uses the ubiquitous Bluetooth short-range wireless communication technology. 

There are dozens of apps being developed around the world that alert people if they’ve been exposed to a person who has tested positive for COVID-19. Many of them also report the identities of the exposed people to public health authorities, which has raised privacy concerns. Several other exposure notification projects, including PACT, BlueTrace and the Covid Watch project, take a similar privacy-protecting approach to Apple’s and Google’s initiative.

So how will the Apple-Google exposure notification system work? As researchers who study security and privacy of wireless communication, we have examined the companies’ plan and have assessed its effectiveness and privacy implications.

Recently, a study found that contact tracing can be effective in containing diseases such as COVID-19, if large parts of the population participate. Exposure notification schemes like the Apple-Google system aren’t true contact tracing systems because they don’t allow public health authorities to identify people who have been exposed to infected individuals. But digital exposure notification systems have a big advantage: They can be used by millions of people and rapidly warn those who have been exposed to quarantine themselves.

Because Bluetooth is supported on billions of devices, it seems like an obvious choice of technology for these systems. The protocol used for this is Bluetooth Low Energy, or Bluetooth LE for short. This variant is optimized for energy-efficient communication between small devices, which makes it a popular protocol for smartphones and wearables such as smartwatches.

Bluetooth LE communicates in two main ways. Two devices can communicate over the data channel with each other, such as a smartwatch synchronizing with a phone. Devices can also broadcast useful information to nearby devices over the advertising channel. For example, some devices regularly announce their presence to facilitate automatic connection.

To build an exposure notification app using Bluetooth LE, developers could assign everyone a permanent ID and make every phone broadcast it on an advertising channel. Then, they could build an app that receives the IDs so every phone would be able to keep a record of close encounters with other phones. But that would be a clear violation of privacy. Broadcasting any personally identifiable information via Bluetooth LE is a bad idea, because messages can be read by anyone in range.

Anonymous exchanges

To get around this problem, every phone broadcasts a long random number, which is changed frequently. Other devices receive these numbers and store them if they were sent from close proximity. By using long, unique, random numbers, no personal information is sent via Bluetooth LE.

Apple and Google follow this principle in their specification, but add some cryptography. First, every phone generates a unique tracing key that is kept confidentially on the phone. Every day, the tracing key generates a new daily tracing key. Though the tracing key could be used to identify the phone, the daily tracing key can’t be used to figure out the phone’s permanent tracing key. Then, every 10 to 20 minutes, the daily tracing key generates a new rolling proximity identifier, which looks just like a long random number. This is what gets broadcast to other devices via the Bluetooth advertising channel.

When someone tests positive for COVID-19, they can disclose a list of their daily tracing keys, usually from the previous 14 days. Everyone else’s phones use the disclosed keys to recreate the infected person’s rolling proximity identifiers. The phones then compare the COVID-19-positive identifiers with their own records of the identifiers they received from nearby phones. A match reveals a potential exposure to the virus, but it doesn’t identify the patient.

Most of the competing proposals use a similar approach. The principal difference is that Apple’s and Google’s operating system updates reach far more phones automatically than a single app can. Additionally, by proposing a cross-platform standard, Apple and Google allow existing apps to piggyback and use a common, compatible communication approach that could work across many apps.

No plan is perfect

The Apple-Google exposure notification system is very secure, but it’s no guarantee of either accuracy or privacy. The system could produce a large number of false positives because being within Bluetooth range of an infected person doesn’t necessarily mean the virus has been transmitted. And even if an app records only very strong signals as a proxy for close contact, it cannot know whether there was a wall, a window or a floor between the phones.

However unlikely, there are ways governments or hackers could track or identify people using the system. Bluetooth LE devices use an advertising address when broadcasting on an advertising channel. Though these addresses can be randomized to protect the identity of the sender, we demonstrated last year that it is theoretically possible to track devices for extended periods of time if the advertising message and advertising address are not changed in sync. To Apple’s and Google’s credit, they call for these to be changed synchronously.

But even if the advertising address and a coronavirus app’s rolling identifier are changed in sync, it may still be possible to track someone’s phone. If there isn’t a sufficiently large number of other devices nearby that also change their advertising addresses and rolling identifiers in sync – a process known as mixing – someone could still track individual devices. For example, if there is a single phone in a room, someone could keep track of it because it’s the only phone that could be broadcasting the random identifiers.

Another potential attack involves logging additional information along with the rolling identifiers. Even though the protocol does not send personal information or location data, receiving apps could record when and where they received keys from other phones. If this was done on a large scale – such as an app that systematically collects this extra information – it could be used to identify and track individuals. For example, if a supermarket recorded the exact date and time of incoming rolling proximity identifiers at its checkout lanes and combined that data with credit card swipes, store staff would have a reasonable chance of identifying which customers were COVID-19 positive.

And because Bluetooth LE advertising beacons use plain-text messages, it’s possible to send faked messages. This could be used to troll others by repeating known COVID-19-positive rolling proximity identifiers to many people, resulting in deliberate false positives.

Nevertheless, the Apple-Google system could be the key to alerting thousands of people who have been exposed to the coronavirus while protecting their identities, unlike contact tracing apps that report identifying information to central government or corporate databases.