• K: The Overlooked Variable That’s Driving the Pandemic - The Atlantic
    https://www.theatlantic.com/health/archive/2020/09/k-overlooked-variable-driving-pandemic/616548

    There’s something strange about this #coronavirus #pandemic. Even after months of extensive research by the global scientific community, many questions remain open.

    Why, for instance, was there such an enormous death toll in northern Italy, but not the rest of the country? Just three contiguous regions in northern Italy have 25,000 of the country’s nearly 36,000 total deaths; just one region, Lombardy, has about 17,000 deaths. Almost all of these were concentrated in the first few months of the outbreak. What happened in Guayaquil, Ecuador, in April, when so many died so quickly that bodies were abandoned in the sidewalks and streets?* Why, in the spring of 2020, did so few cities account for a substantial portion of global deaths, while many others with similar density, weather, age distribution, and travel patterns were spared? What can we really learn from Sweden, hailed as a great success by some because of its low case counts and deaths as the rest of Europe experiences a second wave, and as a big failure by others because it did not lock down and suffered excessive death rates earlier in the pandemic? Why did widespread predictions of catastrophe in Japan not bear out? The baffling examples go on.

    I’ve heard many explanations for these widely differing trajectories over the past nine months—weather, elderly populations, vitamin D, prior immunity, herd immunity—but none of them explains the timing or the scale of these drastic variations. But there is a potential, overlooked way of understanding this pandemic that would help answer these questions, reshuffle many of the current heated arguments, and, crucially, help us get the spread of COVID-19 under control.

    By now many people have heard about R0—the basic reproductive number of a pathogen, a measure of its contagiousness on average. But unless you’ve been reading scientific journals, you’re less likely to have encountered k, the measure of its dispersion. The definition of k is a mouthful, but it’s simply a way of asking whether a virus spreads in a steady manner or in big bursts, whereby one person infects many, all at once. After nine months of collecting epidemiological data, we know that this is an overdispersed pathogen, meaning that it tends to spread in clusters, but this knowledge has not yet fully entered our way of thinking about the pandemic—or our preventive practices.

    The now-famed R0 (pronounced as “r-naught”) is an average measure of a pathogen’s contagiousness, or the mean number of susceptible people expected to become infected after being exposed to a person with the disease. If one ill person infects three others on average, the R0 is three. This parameter has been widely touted as a key factor in understanding how the pandemic operates. News media have produced multiple explainers and visualizations for it. Movies praised for their scientific accuracy on pandemics are lauded for having characters explain the “all-important” R0. Dashboards track its real-time evolution, often referred to as R or Rt, in response to our interventions. (If people are masking and isolating or immunity is rising, a disease can’t spread the same way anymore, hence the difference between R0 and R.)

    Unfortunately, averages aren’t always useful for understanding the distribution of a phenomenon, especially if it has widely varying behavior. If Amazon’s CEO, Jeff Bezos, walks into a bar with 100 regular people in it, the average wealth in that bar suddenly exceeds $1 billion. If I also walk into that bar, not much will change. Clearly, the average is not that useful a number to understand the distribution of wealth in that bar, or how to change it. Sometimes, the mean is not the message. Meanwhile, if the bar has a person infected with COVID-19, and if it is also poorly ventilated and loud, causing people to speak loudly at close range, almost everyone in the room could potentially be infected—a pattern that’s been observed many times since the pandemic begin, and that is similarly not captured by R. That’s where the dispersion comes in.

    There are COVID-19 incidents in which a single person likely infected 80 percent or more of the people in the room in just a few hours. But, at other times, COVID-19 can be surprisingly much less contagious. Overdispersion and super-spreading of this virus are found in research across the globe. A growing number of studies estimate that a majority of infected people may not infect a single other person. A recent paper found that in Hong Kong, which had extensive testing and contact tracing, about 19 percent of cases were responsible for 80 percent of transmission, while 69 percent of cases did not infect another person. This finding is not rare: Multiple studies from the beginning have suggested that as few as 10 to 20 percent of infected people may be responsible for as much as 80 to 90 percent of transmission, and that many people barely transmit it.

    This highly skewed, imbalanced distribution means that an early run of bad luck with a few super-spreading events, or clusters, can produce dramatically different outcomes even for otherwise similar countries. Scientists looked globally at known early-introduction events, in which an infected person comes into a country, and found that in some places, such imported cases led to no deaths or known infections, while in others, they sparked sizable outbreaks. Using genomic analysis, researchers in New Zealand looked at more than half the confirmed cases in the country and found a staggering 277 separate introductions in the early months, but also that only 19 percent of introductions led to more than one additional case. A recent review shows that this may even be true in congregate living spaces, such as nursing homes, and that multiple introductions may be necessary before an outbreak takes off. Meanwhile, in Daegu, South Korea, just one woman, dubbed Patient 31, generated more than 5,000 known cases in a megachurch cluster.

    Unsurprisingly, SARS-CoV, the previous incarnation of SARS-CoV-2 that caused the 2003 SARS outbreak, was also overdispersed in this way: The majority of infected people did not transmit it, but a few super-spreading events caused most of the outbreaks. MERS, another coronavirus cousin of SARS, also appears overdispersed, but luckily, it does not—yet—transmit well among humans.

    This kind of behavior, alternating between being super infectious and fairly noninfectious, is exactly what k captures, and what focusing solely on R hides. Samuel Scarpino, an assistant professor of epidemiology and complex systems at Northeastern, told me that this has been a huge challenge, especially for health authorities in Western societies, where the pandemic playbook was geared toward the flu—and not without reason, because pandemic flu is a genuine threat. However, influenza does not have the same level of clustering behavior.

    We can think of disease patterns as leaning deterministic or stochastic: In the former, an outbreak’s distribution is more linear and predictable; in the latter, randomness plays a much larger role and predictions are hard, if not impossible, to make. In deterministic trajectories, we expect what happened yesterday to give us a good sense of what to expect tomorrow. Stochastic phenomena, however, don’t operate like that—the same inputs don’t always produce the same outputs, and things can tip over quickly from one state to the other. As Scarpino told me, “Diseases like the flu are pretty nearly deterministic and R0 (while flawed) paints about the right picture (nearly impossible to stop until there’s a vaccine).” That’s not necessarily the case with super-spreading diseases.

    Nature and society are replete with such imbalanced phenomena, some of which are said to work according to the Pareto principle, named after the sociologist Vilfredo Pareto. Pareto’s insight is sometimes called the 80/20 principle—80 percent of outcomes of interest are caused by 20 percent of inputs—though the numbers don’t have to be that strict. Rather, the Pareto principle means that a small number of events or people are responsible for the majority of consequences. This will come as no surprise to anyone who has worked in the service sector, for example, where a small group of problem customers can create almost all the extra work. In cases like those, booting just those customers from the business or giving them a hefty discount may solve the problem, but if the complaints are evenly distributed, different strategies will be necessary. Similarly, focusing on the R alone, or using a flu-pandemic playbook, won’t necessarily work well for an overdispersed pandemic.

    Hitoshi Oshitani, a member of the National COVID-19 Cluster Taskforce at Japan’s Ministry of Health, Labour and Welfare and a professor at Tohoku University who told me that Japan focused on the overdispersion impact from early on, likens his country’s approach to looking at a forest and trying to find the clusters, not the trees. Meanwhile, he believes, the Western world was getting distracted by the trees, and got lost among them. To fight a super-spreading disease effectively, policy makers need to figure out why super-spreading happens, and they need to understand how it affects everything, including our contact-tracing methods and our testing regimes.

    There may be many different reasons a pathogen super-spreads. Yellow fever spreads mainly via the mosquito Aedes aegypti, but until the insect’s role was discovered, its transmission pattern bedeviled many scientists. Tuberculosis was thought to be spread by close-range droplets until an ingenious set of experiments proved that it was airborne. Much is still unknown about the super-spreading of SARS-CoV-2. It might be that some people are super-emitters of the virus, in that they spread it a lot more than other people. Like other diseases, contact patterns surely play a part: A politician on the campaign trail or a student in a college dorm is very different in how many people they could potentially expose compared with, say, an elderly person living in a small household. However, looking at nine months of epidemiological data, we have important clues to some of the factors.

    In study after study, we see that super-spreading clusters of COVID-19 almost overwhelmingly occur in poorly ventilated, indoor environments where many people congregate over time—weddings, churches, choirs, gyms, funerals, restaurants, and such—especially when there is loud talking or singing without masks. For super-spreading events to occur, multiple things have to be happening at the same time, and the risk is not equal in every setting and activity, Muge Cevik, a clinical lecturer in infectious diseases and medical virology at the University of St. Andrews and a co-author of a recent extensive review of transmission conditions for COVID-19, told me.

    Cevik identifies “prolonged contact, poor ventilation, [a] highly infectious person, [and] crowding” as the key elements for a super-spreader event. Super-spreading can also occur indoors beyond the six-feet guideline, because SARS-CoV-2, the pathogen causing COVID-19, can travel through the air and accumulate, especially if ventilation is poor. Given that some people infect others before they show symptoms, or when they have very mild or even no symptoms, it’s not always possible to know if we are highly infectious ourselves. We don’t even know if there are more factors yet to be discovered that influence super-spreading. But we don’t need to know all the sufficient factors that go into a super-spreading event to avoid what seems to be a necessary condition most of the time: many people, especially in a poorly ventilated indoor setting, and especially not wearing masks. As Natalie Dean, a biostatistician at the University of Florida, told me, given the huge numbers associated with these clusters, targeting them would be very effective in getting our transmission numbers down.

    Overdispersion should also inform our contact-tracing efforts. In fact, we may need to turn them upside down. Right now, many states and nations engage in what is called forward or prospective contact tracing. Once an infected person is identified, we try to find out with whom they interacted afterward so that we can warn, test, isolate, and quarantine these potential exposures. But that’s not the only way to trace contacts. And, because of overdispersion, it’s not necessarily where the most bang for the buck lies. Instead, in many cases, we should try to work backwards to see who first infected the subject.

    Because of overdispersion, most people will have been infected by someone who also infected other people, because only a small percentage of people infect many at a time, whereas most infect zero or maybe one person. As Adam Kucharski, an epidemiologist and the author of the book The Rules of Contagion, explained to me, if we can use retrospective contact tracing to find the person who infected our patient, and then trace the forward contacts of the infecting person, we are generally going to find a lot more cases compared with forward-tracing contacts of the infected patient, which will merely identify potential exposures, many of which will not happen anyway, because most transmission chains die out on their own.

    The reason for backward tracing’s importance is similar to what the sociologist Scott L. Feld called the friendship paradox: Your friends are, on average, going to have more friends than you. (Sorry!) It’s straightforward once you take the network-level view. Friendships are not distributed equally; some people have a lot of friends, and your friend circle is more likely to include those social butterflies, because how could it not? They friended you and others. And those social butterflies will drive up the average number of friends that your friends have compared with you, a regular person. (Of course, this will not hold for the social butterflies themselves, but overdispersion means that there are much fewer of them.) Similarly, the infectious person who is transmitting the disease is like the pandemic social butterfly: The average number of people they infect will be much higher than most of the population, who will transmit the disease much less frequently. Indeed, as Kucharski and his co-authors show mathematically, overdispersion means that “forward tracing alone can, on average, identify at most the mean number of secondary infections (i.e. R)”; in contrast, “backward tracing increases this maximum number of traceable individuals by a factor of 2-3, as index cases are more likely to come from clusters than a case is to generate a cluster.”

    Even in an overdispersed pandemic, it’s not pointless to do forward tracing to be able to warn and test people, if there are extra resources and testing capacity. But it doesn’t make sense to do forward tracing while not devoting enough resources to backward tracing and finding clusters, which cause so much damage.

    Another significant consequence of overdispersion is that it highlights the importance of certain kinds of rapid, cheap tests. Consider the current dominant model of test and trace. In many places, health authorities try to trace and find forward contacts of an infected person: everyone they were in touch with since getting infected. They then try to test all of them with expensive, slow, but highly accurate PCR (polymerase chain reaction) tests. But that’s not necessarily the best way when clusters are so important in spreading the disease.

    PCR tests identify RNA segments of the coronavirus in samples from nasal swabs—like looking for its signature. Such diagnostic tests are measured on two different dimensions: Are they good at identifying people who are not infected (specificity), and are they good at identifying people who are infected (sensitivity)? PCR tests are highly accurate for both dimensions. However, PCR tests are also slow and expensive, and they require a long, uncomfortable swab up the nose at a medical facility. The slow processing times means that people don’t get timely information when they need it. Worse, PCR tests are so responsive that they can find tiny remnants of coronavirus signatures long after someone has stopped being contagious, which can cause unnecessary quarantines.

    Meanwhile, researchers have shown that rapid tests that are very accurate for identifying people who do not have the disease, but not as good at identifying infected individuals, can help us contain this pandemic. As Dylan Morris, a doctoral candidate in ecology and evolutionary biology at Princeton, told me, cheap, low-sensitivity tests can help mitigate a pandemic even if it is not overdispersed, but they are particularly valuable for cluster identification during an overdispersed one. This is especially helpful because some of these tests can be administered via saliva and other less-invasive methods, and be distributed outside medical facilities.

    In an overdispersed regime, identifying transmission events (someone infected someone else) is more important than identifying infected individuals. Consider an infected person and their 20 forward contacts—people they met since they got infected. Let’s say we test 10 of them with a cheap, rapid test and get our results back in an hour or two. This isn’t a great way to determine exactly who is sick out of that 10, because our test will miss some positives, but that’s fine for our purposes. If everyone is negative, we can act as if nobody is infected, because the test is pretty good at finding negatives. However, the moment we find a few transmissions, we know we may have a super-spreader event, and we can tell all 20 people to assume they are positive and to self-isolate—if there are one or two transmissions, there are likely more, exactly because of the clustering behavior. Depending on age and other factors, we can test those people individually using PCR tests, which can pinpoint who is infected, or ask them all to wait it out.

    Scarpino told me that overdispersion also enhances the utility of other aggregate methods, such as wastewater testing, especially in congregate settings like dorms or nursing homes, allowing us to detect clusters without testing everyone. Wastewater testing also has low sensitivity; it may miss positives if too few people are infected, but that’s fine for population-screening purposes. If the wastewater testing is signaling that there are likely no infections, we do not need to test everyone to find every last potential case. However, the moment we see signs of a cluster, we can rapidly isolate everyone, again while awaiting further individualized testing via PCR tests, depending on the situation.

    Unfortunately, until recently, many such cheap tests had been held up by regulatory agencies in the United States, partly because they were concerned with their relative lack of accuracy in identifying positive cases compared with PCR tests—a worry that missed their population-level usefulness for this particular overdispersed pathogen.

    To return to the mysteries of this pandemic, what did happen early on to cause such drastically different trajectories in otherwise similar places? Why haven’t our usual analytic tools—case studies, multi-country comparisons—given us better answers? It’s not intellectually satisfying, but because of the overdispersion and its stochasticity, there may not be an explanation beyond that the worst-hit regions, at least initially, simply had a few unlucky early super-spreading events. It wasn’t just pure luck: Dense populations, older citizens, and congregate living, for example, made cities around the world more susceptible to outbreaks compared with rural, less dense places and those with younger populations, less mass transit, or healthier citizenry. But why Daegu in February and not Seoul, despite the two cities being in the same country, under the same government, people, weather, and more? As frustrating at it may be, sometimes, the answer is merely where Patient 31 and the megachurch she attended happened to be.

    Overdispersion makes it harder for us to absorb lessons from the world, because it interferes with how we ordinarily think about cause and effect. For example, it means that events that result in spreading and non-spreading of the virus are asymmetric in their ability to inform us. Take the highly publicized case in Springfield, Missouri, in which two infected hairstylists, both of whom wore masks, continued to work with clients while symptomatic. It turns out that no apparent infections were found among the 139 exposed clients (67 were directly tested; the rest did not report getting sick). While there is a lot of evidence that masks are crucial in dampening transmission, that event alone wouldn’t tell us if masks work. In contrast, studying transmission, the rarer event, can be quite informative. Had those two hairstylists transmitted the virus to large numbers of people despite everyone wearing masks, it would be important evidence that, perhaps, masks aren’t useful in preventing super-spreading.

    Comparisons, too, give us less information compared with phenomena for which input and output are more tightly coupled. When that’s the case, we can check for the presence of a factor (say, sunshine or Vitamin D) and see if it correlates with a consequence (infection rate). But that’s much harder when the consequence can vary widely depending on a few strokes of luck, the way that the wrong person was in the wrong place sometime in mid-February in South Korea. That’s one reason multi-country comparisons have struggled to identify dynamics that sufficiently explain the trajectories of different places.

    Once we recognize super-spreading as a key lever, countries that look as if they were too relaxed in some aspects appear very different, and our usual polarized debates about the pandemic are scrambled, too. Take Sweden, an alleged example of the great success or the terrible failure of herd immunity without lockdowns, depending on whom you ask. In reality, although Sweden joins many other countries in failing to protect elderly populations in congregate-living facilities, its measures that target super-spreading have been stricter than many other European countries. Although it did not have a complete lockdown, as Kucharski pointed out to me, Sweden imposed a 50-person limit on indoor gatherings in March, and did not remove the cap even as many other European countries eased such restrictions after beating back the first wave. (Many are once again restricting gathering sizes after seeing a resurgence.) Plus, the country has a small household size and fewer multigenerational households compared with most of Europe, which further limits transmission and cluster possibilities. It kept schools fully open without distancing or masks, but only for children under 16, who are unlikely to be super-spreaders of this disease. Both transmission and illness risks go up with age, and Sweden went all online for higher-risk high-school and university students—the opposite of what we did in the United States. It also encouraged social-distancing, and closed down indoor places that failed to observe the rules. From an overdispersion and super-spreading point of view, Sweden would not necessarily be classified as among the most lax countries, but nor is it the most strict. It simply doesn’t deserve this oversize place in our debates assessing different strategies.

    Although overdispersion makes some usual methods of studying causal connections harder, we can study failures to understand which conditions turn bad luck into catastrophes. We can also study sustained success, because bad luck will eventually hit everyone, and the response matters.

    The most informative case studies may well be those who had terrible luck initially, like South Korea, and yet managed to bring about significant suppression. In contrast, Europe was widely praised for its opening early on, but that was premature; many countries there are now experiencing widespread rises in cases and look similar to the United States in some measures. In fact, Europe’s achieving a measure of success this summer and relaxing, including opening up indoor events with larger numbers, is instructive in another important aspect of managing an overdispersed pathogen: Compared with a steadier regime, success in a stochastic scenario can be more fragile than it looks.

    Once a country has too many outbreaks, it’s almost as if the pandemic switches into “flu mode,” as Scarpino put it, meaning high, sustained levels of community spread even though a majority of infected people may not be transmitting onward. Scarpino explained that barring truly drastic measures, once in that widespread and elevated mode, COVID-19 can keep spreading because of the sheer number of chains already out there. Plus, the overwhelming numbers may eventually spark more clusters, further worsening the situation.

    As Kucharski put it, a relatively quiet period can hide how quickly things can tip over into large outbreaks and how a few chained amplification events can rapidly turn a seemingly under-control situation into a disaster. We’re often told that if Rt, the real-time measure of the average spread, is above one, the pandemic is growing, and that below one, it’s dying out. That may be true for an epidemic that is not overdispersed, and while an Rt below one is certainly good, it’s misleading to take too much comfort from a low Rt when just a few events can reignite massive numbers. No country should forget South Korea’s Patient 31.

    That said, overdispersion is also a cause for hope, as South Korea’s aggressive and successful response to that outbreak—with a massive testing, tracing, and isolating regime—shows. Since then, South Korea has also been practicing sustained vigilance, and has demonstrated the importance of backward tracing. When a series of clusters linked to nightclubs broke out in Seoul recently, health authorities aggressively traced and tested tens of thousands of people linked to the venues, regardless of their interactions with the index case, six feet apart or not—a sensible response, given that we know the pathogen is airborne.

    Perhaps one of the most interesting cases has been Japan, a country with middling luck that got hit early on and followed what appeared to be an unconventional model, not deploying mass testing and never fully shutting down. By the end of March, influential economists were publishing reports with dire warnings, predicting overloads in the hospital system and huge spikes in deaths. The predicted catastrophe never came to be, however, and although the country faced some future waves, there was never a large spike in deaths despite its aging population, uninterrupted use of mass transportation, dense cities, and lack of a formal lockdown.

    It’s not that Japan was better situated than the United States in the beginning. Similar to the U.S. and Europe, Oshitani told me, Japan did not initially have the PCR capacity to do widespread testing. Nor could it impose a full lockdown or strict stay-at-home orders; even if that had been desirable, it would not have been legally possible in Japan.

    Oshitani told me that in Japan, they had noticed the overdispersion characteristics of COVID-19 as early as February, and thus created a strategy focusing mostly on cluster-busting, which tries to prevent one cluster from igniting another. Oshitani said he believes that “the chain of transmission cannot be sustained without a chain of clusters or a megacluster.” Japan thus carried out a cluster-busting approach, including undertaking aggressive backward tracing to uncover clusters. Japan also focused on ventilation, counseling its population to avoid places where the three C’s come together—crowds in closed spaces in close contact, especially if there’s talking or singing—bringing together the science of overdispersion with the recognition of airborne aerosol transmission, as well as presymptomatic and asymptomatic transmission.

    Oshitani contrasts the Japanese strategy, nailing almost every important feature of the pandemic early on, with the Western response, trying to eliminate the disease “one by one” when that’s not necessarily the main way it spreads. Indeed, Japan got its cases down, but kept up its vigilance: When the government started noticing an uptick in community cases, it initiated a state of emergency in April and tried hard to incentivize the kinds of businesses that could lead to super-spreading events, such as theaters, music venues, and sports stadiums, to close down temporarily. Now schools are back in session in person, and even stadiums are open—but without chanting.

    It’s not always the restrictiveness of the rules, but whether they target the right dangers. As Morris put it, “Japan’s commitment to ‘cluster-busting’ allowed it to achieve impressive mitigation with judiciously chosen restrictions. Countries that have ignored super-spreading have risked getting the worst of both worlds: burdensome restrictions that fail to achieve substantial mitigation. The U.K.’s recent decision to limit outdoor gatherings to six people while allowing pubs and bars to remain open is just one of many such examples.”

    Could we get back to a much more normal life by focusing on limiting the conditions for super-spreading events, aggressively engaging in cluster-busting, and deploying cheap, rapid mass tests—that is, once we get our case numbers down to low enough numbers to carry out such a strategy? (Many places with low community transmission could start immediately.) Once we look for and see the forest, it becomes easier to find our way out.

  • Turkey finally releases epidemic figures: coronavirus epicenter in Istanbul-Al monitor
    “Another 79 people died in the last 24 hours, bringing the death toll to 356 people, Health Minister Fahrettin Koca said. Another 2,456 people tested positive and the country now has 18,135 confirmed cases, he said.”
    #Covid-19#Turquie#Pandemic#Economy#migrant

    https://www.al-monitor.com/pulse/originals/2020/04/turkey-historic-catastrophe-erdogan-coronavirus.html

  • Turkish Medical Association: Covid-19 Spread All Around Turkey due to Government’s Mistakes-
    “As the coronavirus has spread all around Turkey because of the government’s mistakes in containing the disease, it has now lost the opportunity to implement a country-wide quarantine, according to the Turkish Medical Association”
    #Covid-19#Turquie#Erdogan#Pandemic#migrant

    http://m.bianet.org/english/health/222197-turkish-medical-association-covid-19-spread-all-around-turkey-due-t

  • #Coronavirus_Capitalism” : Naomi Klein’s Case for Transformative Change Amid Coronavirus Pandemic

    Author, activist and journalist Naomi Klein says the coronavirus crisis, like earlier ones, could be a catalyst to shower aid on the wealthiest interests in society, including those most responsible for our current vulnerabilities, while offering next to nothing to most workers and small businesses. In 2007, Klein wrote “The Shock Doctrine: The Rise of Disaster Capitalism.” Now she argues President Trump’s plan is a pandemic shock doctrine. In a new video for The Intercept, where she is a senior correspondent, Klein argues it’s vital for people to fight for the kind of transformative change that can not only curb the worst effects of the current crisis but also set society on a more just path.

    AMY GOODMAN: Today we spend much of the hour looking at the economic impact of the coronavirus pandemic, what some are calling coronavirus capitalism. Soon we’ll be joined by Nobel Prize-winning economist Joseph Stiglitz, whose new book is People, Power and Profits: Progressive Capitalism for an Age of Discontent. But first we begin with a new video by author and activist Naomi Klein, produced by The Intercept. In 2007, Klein wrote The Shock Doctrine: The Rise of Disaster Capitalism. Now she argues Trump’s plan is a pandemic shock doctrine, but it’s not the only way forward. The video opens with this quote from economist Milton Friedman, who says, “Only a crisis — actual or perceived — produces real change. When that crisis occurs, the actions that are taken depend on the ideas that are lying around.”

    NAOMI KLEIN: “Ideas that are lying around.” Friedman, one of history’s most extreme free market economists, was wrong about a whole lot, but he was right about that. In times of crisis, seemingly impossible ideas suddenly become possible. But whose ideas? Sensible, fair ones, designed to keep as many people as possible safe, secure and healthy? Or predatory ideas, designed to further enrich the already unimaginably wealthy while leaving the most vulnerable further exposed? The world economy is seizing up in the face of cascading shocks.

    TEDROS ADHANOM GHEBREYESUS: COVID-19 can be characterized as a pandemic.

    GEORGE STEPHANOPOULOS: In the wake of the coronavirus crisis, stocks have stopped trading on Wall Street after a 7% drop.

    KRISTINA PARTSINEVELOS: This is a historical day, the biggest drop we’ve seen since that crash in 1987.

    ELAINE QUIJANO: The drop was spurred by a growing oil price war as the market was already weakened by coronavirus fears.

    PRESIDENT DONALD TRUMP: Yeah, no, I don’t take responsibility at all.

    NAOMI KLEIN: In the midst of this widespread panic, corporate lobbyists of all stripes are of course dusting off all the ideas they had lying around. Trump is pushing a suspension of the payroll tax, which could bankrupt Social Security, providing the excuse to cut it or privatize it completely — an idea that has been lying around for very long time.

    PRESIDENT GEORGE W. BUSH: A worker, at his or her option, ought to be allowed to put some of their own money in a — you know, in a private savings account.

    NAOMI KLEIN: Lying around on both sides of the aisle.

    SEN. JOE BIDEN: When I argued if we should freeze federal spending, I meant Social Security, as well. I meant Medicare and Medicaid.

    NAOMI KLEIN: And then, there are the ideas being floated to bail out some of the wealthiest and most polluting sectors in our economy.

    PRESIDENT DONALD TRUMP: We are working very closely with the cruise line industry, likewise with the airline industry. They’re two great industries, and we’ll be helping them through this patch.

    NAOMI KLEIN: Bailouts for fracking companies, not to mention cruise ships, airlines and hotels, handouts which Trump could benefit from personally. Which is a big problem because the virus isn’t the only crisis we face. There’s also climate disruption, and these industries that are getting rescued with our money are the ones driving it. Trump has also been meeting with the private health insurers.

    PRESIDENT DONALD TRUMP: We’re meeting with the top executives of the health insurance companies.

    NAOMI KLEIN: The very ones who have made sure that so many Americans can’t afford the care they need. And what are the chances they don’t have their hands out? It seems like the whole pandemic is getting outsourced.

    BRIAN CORNELL: Well, Mr. President, thank you for inviting us here today, along with our colleagues from Walmart and Walgreens and our partners at CVS. Normally you’d view us as competitors, but today we’re focused on a common competitor. And that’s defeating the spread of the coronavirus.

    NAOMI KLEIN: The Fed’s first move was to pump $1.5 trillion into the financial markets, with more undoubtedly on the way. But if you’re a worker, especially a gig worker, there’s a very good chance you’re out of luck. If you do need to see a doctor for care, there’s a good chance no one’s going to help you pay if you aren’t covered. And if you want to heed the public health warnings to stay home from work, there’s also a chance that you won’t get paid. Of course, you still need to pay your rent and all of your debts — medical, student, credit card, mortgage. The results are predictable. Too many sick people have no choice but to go to work, which means more people contracting and spreading the virus. And without comprehensive bailouts for workers, we can expect more bankruptcies and more homelessness down the road.

    Look, we know this script. In 2008, the last time we had a global financial meltdown, the same kinds of bad ideas for no-strings-attached corporate bailouts carried the day, and regular people around the world paid the price. And even that was entirely predictable. Thirteen years ago, I wrote a book called The Shock Doctrine: The Rise of Disaster Capitalism, described a brutal and recurring tactic by right-wing governments. After a shocking event — a war, coup, terrorist attack, market crash or natural disaster — they exploit the public’s disorientation, suspend democracy, push through radical free market policies that enrich the 1% at the expense of the poor and middle class.

    But here is what my research has taught me. Shocks and crises don’t always go the shock doctrine path. In fact, it’s possible for crisis to catalyze a kind of evolutionary leap. Think of the 1930s, when the Great Depression led to the New Deal.

    PRESIDENT FRANKLIN ROOSEVELT: The only thing we have to fear is fear itself.

    NAOMI KLEIN: In the United States and elsewhere, governments began to weave a social safety net, so that the next time there was a crash, there would be programs like Social Security to catch people.

    PRESIDENT FRANKLIN ROOSEVELT: The right of every family to a decent home, the right to adequate medical care and the opportunity to achieve and enjoy good health.

    NAOMI KLEIN: Look, we know what Trump’s plan is: a pandemic shock doctrine, featuring all the most dangerous ideas lying around, from privatizing Social Security to locking down borders to caging even more migrants. Hell, he might even try canceling elections. But the end of this story hasn’t been written yet. It is an election year. And social movements and insurgent politicians are already mobilized. And like in the 1930s, we have a whole bunch of other ideas lying around.

    SEN. BERNIE SANDERS: Do we believe that everybody should be entitled, as a right, to healthcare?

    SANDERS SUPPORTERS: Yes!

    DOMINIQUE WALKER: We will not stop organizing and fighting until all unhoused folks who want shelter have shelter.

    REP. ILHAN OMAR: Canceling student debt.

    REP. RO KHANNA: It makes so much sense that if you’re sick, that you should not be penalized where you don’t have an income.

    NAOMI KLEIN: Many of these ideas were dismissed as too radical just a week ago. Now they’re starting to seem like the only reasonable path to get out of this crisis and prevent future ones.

    ELIZABETH COHEN: Now, here’s something that helps explain the difference between the testing situation in South Korea and the U.S. The South Korea, like European countries and Canada, has universal single-payer insurance. And that means that it’s easier to mobilize, and also people know what to do. There is pretty much one answer for how to get testing. The U.S. is a patchwork of countless different systems, and so you can’t say, “Here’s exactly the steps that every American should take in order to get tested.”

    NAOMI KLEIN: And with Washington suddenly in the giant stimulus business, this is precisely the time for the stimulus that many of us have been talking about for years.

    REP. ALEXANDRIA OCASIO-CORTEZ: Today is the day that we truly embark on a comprehensive agenda of economic, social and racial justice in the United States of America.

    NAOMI KLEIN: It’s called the Green New Deal. Instead of rescuing the dirty industries of the last century, we should be boosting the clean ones that will lead us into safety in the coming century. If there is one thing history teaches us, it’s that moments of shock are profoundly volatile. We either lose a whole lot of ground, get fleeced by elites and pay the price for decades, or we win progressive victories that seemed impossible just a few weeks earlier. This is no time to lose our nerve. The future will be determined by whoever is willing to fight harder for the ideas they have lying around.

    AMY GOODMAN: That’s author and activist Naomi Klein of The Intercept. The video ends with Milton Friedman’s quote: “Only a crisis — actual or perceived — produces real change. When that crisis occurs, the actions that are taken depend on ideas that are lying around. That, I believe, is our basic function: to develop alternatives to existing policies, to keep them alive and available until the politically impossible becomes politically inevitable.”

    This is Democracy Now!, democracynow.org, The War and Peace Report. When we come back, Nobel Prize-winning economist Joe Stiglitz. Stay with us.

    [break]

    AMY GOODMAN: That’s Spanish pianist Alberto Gestoso, performing the Titanic theme song, “My Heart Will Go On,” for his quarantined neighbors in Barcelona. He was on his balcony. Spain has had more than 3,400 cases of the coronavirus in the last 24 hours. Now at least 17,000 people are infected, and that’s only what is known without widespread testing.

    https://www.democracynow.org/2020/3/19/naomi_klein_coronavirus_capitalism
    #Naomi_Klein #stratégie_du_choc #pandémie #coronavirus #covid-19 #épidémie #capitalisme #pandemic_shock_doctrine

  • What happens to freedom of movement during a pandemic ?

    Restrictions are particularly problematic for those who need to move in order to find safety, but whose elementary freedom to move had been curtailed long before the Covid-19 outbreak.

    The severe consequences of the Covid-19 pandemic dominate headlines around the globe and have drawn the public’s attention unlike any other issue or event. All over the world, societies struggle to respond and adapt to rapidly changing scenarios and levels of threat. Emergency measures have come to disrupt everyday life, international travel has largely been suspended, and many state borders have been closed. State leaders liken the fight against the virus to engaging in warfare – although it is clear that the parallel is misleading and that those involved in the “war” are not soldiers but simply citizens. The situation is grim, and it would be a serious mistake to underestimate the obvious danger of infection, loss of life, the collapse of health services and the economy. Nonetheless, there is a need to stress that this phase of uncertainty entails also the risk of normalising ‘exceptional’ policies that restrict freedoms and rights in the name of crisis and public safety - and not only in the short term.

    “Of all the specific liberties which may come into mind when we hear the word “freedom””, philosopher Hannah Arendt once wrote, the “freedom of movement is historically the oldest and also the most elementary.” However, in times of a pandemic, human movements turn increasingly into a problem. The elementary freedom to move is said to be curtailed for the greater good, particularly for the elderly and others in high-risk groups. (Self-)confinement appears key – “inessential” movements and contact with others are to be avoided. In China, Italy and elsewhere, hard measures have been introduced and their violation can entail severe penalties. Movements from A to B need (state) authorisation and unsanctioned movements can be punished. There are good reasons for that, no doubt. Nevertheless, there is a need to take stock of the wider implications of our current predicament.

    In this general picture, current restrictions on movement are problematic for people who do not have a home and for whom self-quarantine is hardly an option, for people with disability who remain without care, and for people, mostly women, whose home is not a safe haven but the site of insecurity and domestic abuse. Restrictions are also particularly problematic for those whose elementary freedom to move had been curtailed long before the Covid-19 outbreak but who need to move in order to find safety. Migrants embody in the harshest way the contradictions and tensions surrounding the freedom of movement and its denial today. It is not surprising that in the current climate, they tend to become one of the first targets of the most restrictive measures.
    Migrant populations who moved, or still seek to move, across borders without authorisation in order to escape danger are subjected to confinement and deterrence measures that are legitimized by often spurious references to public safety and global health. Discriminatory practices that segregate in the name of safety turn those at risk into a risk. “We are fighting a two-front war”, Hungary’s Prime Minister Viktor Orban declared, “one front is called migration, and the other one belongs to the coronavirus, there is a logical connection between the two, as both spread with movement.” The danger of conflating the declared war on the pandemic with a war on migration is great, and the human costs are high. Restrictive border measures endanger the lives of vulnerable populations for whom movement is a means of survival.

    About two weeks ago, it was documented that the Greek coastguard opened fire on migrants trying to escape via the Aegean Sea and the land border between Turkey and Greece. Some people died while many were injured in a hyperbolic deployment of border violence. The European reaction, as embodied in the person of European Commission president Ursula von der Leyen, was to refer to Greece as Europe’s “shield”. About a week ago, it was uncovered that a migrant boat with 49 people on board which had already reached a European search and rescue zone was returned to Libya through coordinated measures taken by the EU border agency Frontex, the Armed Forces of Malta, and Libyan authorities. In breach of international law and of the principle of non-refoulement, the people were returned to horrid migrant camps in Libya, a country still at war. With no NGO rescuers currently active in the Mediterranean due to the effects of the Coronavirus, more than 400 people were intercepted at sea and forcibly returned to Libya over the past weekend alone, over 2,500 this year.

    Such drastic migration deterrence and containment measures endanger the lives of those ‘on the move’ and exacerbate the risk of spreading the virus. In Libyan camps, in conditions that German diplomats once referred to as “concentration-camp-like”, those imprisoned often have extremely weakened immune systems, often suffering from illnesses like tuberculosis. A Coronavirus outbreak here would be devastating. Doctors without Borders have called for the immediate evacuation of the hotspot camps on the Greek Islands, highlighting that the cramped and unhygienic conditions there would “provide the perfect storm for a COVID-19 outbreak”. This is a more general situation in detention camps for migrants throughout Europe and elsewhere, as it is in ‘regular’ prisons worldwide.

    Together with the virus, a politics of fear spreads across the world and prompts ever-more restrictive measures. Besides the detrimental consequences of curtailing the freedom to move already experienced by the most vulnerable, the worry is that many of these measures will continue to undermine rights and freedoms even long after the pandemic has been halted. And yet, while, as Naomi Klein notes, “a pandemic shock doctrine” may allow for the enactment of “all the most dangerous ideas lying around, from privatizing Social Security to locking down borders to caging even more migrants”, we agree with her that “the end of this story hasn’t been written yet.”

    The situation is volatile – how it ends depends also on us and how we collectively mobilize against the now rampant authoritarian tendencies. All around us, we see other reactions to the current predicament with new forms of solidarity emerging and creative ways of taking care of “the common”. The arguments are on our side. The pandemic shows that a global health crisis cannot be solved through nationalistic measures but only through international solidarity and cooperation – the virus does not respect borders.

    Its devastating effects strengthen the call to universal health care and the value of care work, which continues to be disproportionately women’s work. The pandemic gives impetus to those who demand the right to shelter and affordable housing for all and provides ammunition to those who have long struggled against migrant detention camps and mass accommodations, as well as against migrant deportations. It exposes the ways that the predatory capitalist model, often portrayed as commonsensical and without alternatives, provides no answers to a global health crisis while socialist models do. It shows that resources can be mobilized if the political will exists and that ambitious policies such the Green New Deal are far from being ‘unrealistic’. And, the Coronavirus highlights how important the elementary freedom of movement continues to be.
    The freedom of movement, of course, also means having the freedom not to move. And, at times, even having the freedom to self-confine. For many, often the most vulnerable and disenfranchised, this elementary freedom is not given. This means that even during a pandemic, we need to stand in solidarity with those who take this freedom to move, who can no longer remain in inhumane camps within Europe or at its external borders and who try to escape to find safety. Safety from war and persecution, safety from poverty and hunger, safety from the virus. In this period in which borders multiply, the struggle around the elementary freedom of movement will continue to be both a crucial stake and a tool in the fight against global injustice, even, or particularly, during a global health crisis.


    https://www.opendemocracy.net/en/can-europe-make-it/what-happens-freedom-movement-during-pandemic

    #liberté_de_circulation #liberté_de_mouvement #coronavirus #épidémie #pandémie #frontières #virus #mobilité #mobilité_humaine #migrations #confinement #autorisation #restrictions_de_mouvement #guerre #guerre_aux_migrants #guerre_au_virus #danger #fermeture_des_frontières #pandemic_shock_doctrine #stratégie_du_choc #autoritarisme #solidarité #solidarité_internationale #soins_de_santé_universels #universalisme #nationalisme #capitalisme #socialisme #Green_New_Deal #immobilité #vulnérabilité #justice #Sandro_Mezzadra #Maurice_Stierl

    via @isskein
    ping @karine4

  • Regular soap is extremely effective at deactivating viruses.
    https://diasp.eu/p/10602983

    Regular soap is extremely effective at deactivating viruses.

    #coronavirus #COVID19 #information #pandemic

    The hydrophobic tails of the soap molecules disrupt the structure of the lipid casing and destroy it.

    https://www.nytimes.com/2020/03/13/health/soap-coronavirus-handwashing-germs.html

    https://www.theguardian.com/commentisfree/2020/mar/12/science-soap-kills-coronavirus-alcohol-based-disinfectants