Group items tagged

The military was also given positions of responsibility in the Wuhan institute, according to a US Senate report. A book published in 2015 by the military academy discusses how Sars viruses represent a “new era of genetic weapons” that can be “artificially manipulated into an emerging human disease virus, then weaponised and unleashed”.

The authors are PLA researchers, and one of the book’s editors has collaborated on numerous scientific papers with Wuhan scientists. They discuss how Sars can be weaponised by fusing it with other viruses and “serial passaging” the resulting mutant to make it more dangerous.

The investigators believe the Chinese military had taken an interest in developing a vaccine for the viruses so they could be used as potential bioweapons. If a country could inoculate its population against its own secret virus, it might have a weapon to shift the balance of world power.

The PLA had its own vaccine specialist, Zhou Yusen, a decorated military scientist at the academy, who had collaborated with the Wuhan scientists on a study of the Mers coronavirus and was working with them at the time of the outbreak.

Suspicion fell on him after the pandemic because he produced a patent for a Covid vaccine with remarkable speed in February 2020, little more than a month after the outbreak of the virus had first been admitted to the world by China.

A report published in April, co-authored by Dr Robert Kadlec, who was responsible for the US’s vaccine development programme, concluded that Zhou’s team must have been working on a vaccine no later than November 2019 — just as the pandemic began. One of the US investigators said testimony from scientists connected to the Wuhan institute’s collaborators suggested Covid-19 vaccine work was going on at the laboratory before the outbreak.

However, there was a no-go area: the Moijang mine. Seven of Hughes’s team headed to the mine in June 2020, including Camping Huang, the PhD student who had investigated the miners’ mystery illness soon after they died.

One of the investigator sources said the secret military-funded experiments on the mine virus, RaTG13, began in 2016. At around that time, the Wuhan institute became even less open about its work and mostly stopped revealing any new coronaviruses it discovered. In the lead-up to the pandemic, the Wuhan institute frequently experimented on coronaviruses alongside the Academy of Military Medical Sciences, a research arm of the People’s Liberation Army (PLA). In published papers, military scientists are listed as working for the Beijing Institute of Microbiology and Epidemiology, which is the military academy’s base.

An investigator said: “We were rock-solid confident that this was likely Covid-19 because they were working on advanced coronavirus research in the laboratory of Dr Shi. They’re trained biologists in their thirties and forties. Thirty-five-year-old scientists don’t get very sick with influenza.”

On November 19, the safety director of the Chinese Academy of Sciences made a visit, according to the institute’s website. He addressed a meeting of the institute’s leadership with important “oral and written” instructions from China’s president, Xi Jinping, regarding “a complex and grave situation”.

A later study by academics at Wuhan University located the hotspots in Wuhan where people were reporting on social media that they needed treatment for Covid. At the time, the authorities were eager to play down the suggestion that the city’s Huanan seafood market was the source of the outbreak; the study was used to show that the initial hotspots in December and January were several miles away.

When the study was first published, the Wuhan institute was not marked on the map it provided. So a report by the US Senate did just that — and found the institute right next to the biggest hotspot in the month before the province was locked down on January 23. The first case in Britain was recorded a week later.

Even before the West was told a mysterious virus was killing people in Wuhan, the Chinese authorities were beginning an information clampdown.

In the first months of the pandemic, there was a strong desire among Chinese scientists to head off to the bat caves in Yunnan to see whether they could find a place where Covid may have originated.

The investigators also saw communications intercepts that allegedly show three Wuhan institute researchers working at its level 3 laboratory on coronavirus gain-of-function work had fallen sick with coronavirus symptoms in the second week of November 2019, when many experts believe the pandemic began. One of the researchers’ family members later died.

When they arrived, they were told the Moijang mine was closed, so they sampled bats in another abandoned copper mine nearby. On the first day of their work, police arrived, seized the samples and took them to their station, where they were interrogated and detained for 48 hours.

Officers also went to their hotel and seized the samples they had collected from elsewhere. Even though the team had approval to test in the area, they were ordered to leave. “We did provide documentation to show we were there legally,” said Hughes. “But there was just too much fear and so they didn’t release those samples.”

Most coronavirus experts in China, she said, were too fearful of the consequences to examine Covid’s origins. “They haven’t touched it because of the risks associated with working on it.

The key issue is not “human-competitive” intelligence (as the open letter puts it); it’s what happens after AI gets to smarter-than-human intelligence. Key thresholds there may not be obvious, we definitely can’t calculate in advance what happens when, and it currently seems imaginable that a research lab would cross critical lines without noticing.

Many researchers steeped in these issues, including myself, expect that the most likely result of building a superhumanly smart AI, under anything remotely like the current circumstances, is that literally everyone on Earth will die. Not as in “maybe possibly some remote chance,” but as in “that is the obvious thing that would happen.”

It’s not that you can’t, in principle, survive creating something much smarter than you; it’s that it would require precision and preparation and new scientific insights, and probably not having AI systems composed of giant inscrutable arrays of fractional numbers.

Absent that caring, we get “the AI does not love you, nor does it hate you, and you are made of atoms it can use for something else.”

he rule that most people aware of these issues would have endorsed 50 years earlier, was that if an AI system can speak fluently and says it’s self-aware and demands human rights, that ought to be a hard stop on people just casually owning that AI and using it past that point. We already blew past that old line in the sand. And that was probably correct; I agree that current AIs are probably just imitating talk of self-awareness from their training data. But I mark that, with how little insight we have into these systems’ internals, we do not actually know.

The likely result of humanity facing down an opposed superhuman intelligence is a total loss

To visualize a hostile superhuman AI, don’t imagine a lifeless book-smart thinker dwelling inside the internet and sending ill-intentioned emails. Visualize an entire alien civilization, thinking at millions of times human speeds, initially confined to computers—in a world of creatures that are, from its perspective, very stupid and very slow. A sufficiently intelligent AI won’t stay confined to computers for long. In today’s world you can email DNA strings to laboratories that will produce proteins on demand, allowing an AI initially confined to the internet to build artificial life forms or bootstrap straight to postbiological molecular manufacturing.

There’s no proposed plan for how we could do any such thing and survive. OpenAI’s openly declared intention is to make some future AI do our AI alignment homework. Just hearing that this is the plan ought to be enough to get any sensible person to panic. The other leading AI lab, DeepMind, has no plan at all.

An aside: None of this danger depends on whether or not AIs are or can be conscious; it’s intrinsic to the notion of powerful cognitive systems that optimize hard and calculate outputs that meet sufficiently complicated outcome criteria.

I didn’t also mention that we have no idea how to determine whether AI systems are aware of themselves—since we have no idea how to decode anything that goes on in the giant inscrutable arrays—and therefore we may at some point inadvertently create digital minds which are truly conscious and ought to have rights and shouldn’t be owned.

I refrained from signing because I think the letter is understating the seriousness of the situation and asking for too little to solve it.

the thing about trying this with superhuman intelligence is that if you get that wrong on the first try, you do not get to learn from your mistakes, because you are dead. Humanity does not learn from the mistake and dust itself off and try again, as in other challenges we’ve overcome in our history, because we are all gone.

If we held anything in the nascent field of Artificial General Intelligence to the lesser standards of engineering rigor that apply to a bridge meant to carry a couple of thousand cars, the entire field would be shut down tomorrow.

We are not on course to be prepared in any reasonable time window. There is no plan. Progress in AI capabilities is running vastly, vastly ahead of progress in AI alignment or even progress in understanding what the hell is going on inside those systems

Many researchers working on these systems think that we’re plunging toward a catastrophe, with more of them daring to say it in private than in public; but they think that they can’t unilaterally stop the forward plunge, that others will go on even if they personally quit their jobs.

This is a stupid state of affairs, and an undignified way for Earth to die, and the rest of humanity ought to step in at this point and help the industry solve its collective action problem.

When the insider conversation is about the grief of seeing your daughter lose her first tooth, and thinking she’s not going to get a chance to grow up, I believe we are past the point of playing political chess about a six-month moratorium.

The moratorium on new large training runs needs to be indefinite and worldwide. There can be no exceptions, including for governments or militaries. If the policy starts with the U.S., then China needs to see that the U.S. is not seeking an advantage but rather trying to prevent a horrifically dangerous technology which can have no true owner and which will kill everyone in the U.S. and in China and on Earth

Here’s what would actually need to be done:

Shut down all the large GPU clusters (the large computer farms where the most powerful AIs are refined). Shut down all the large training runs

Put a ceiling on how much computing power anyone is allowed to use in training an AI system, and move it downward over the coming years to compensate for more efficient training algorithm

Track all GPUs sold. If intelligence says that a country outside the agreement is building a GPU cluster, be less scared of a shooting conflict between nations than of the moratorium being violated; be willing to destroy a rogue datacenter by airstrike.

Frame nothing as a conflict between national interests, have it clear that anyone talking of arms races is a fool

Make it explicit in international diplomacy that preventing AI extinction scenarios is considered a priority above preventing a full nuclear exchange, and that allied nuclear countries are willing to run some risk of nuclear exchange if that’s what it takes to reduce the risk of large AI training runs.

when your policy ask is that large, the only way it goes through is if policymakers realize that if they conduct business as usual, and do what’s politically easy, that means their own kids are going to die too.

The Tesla Inc. CEO tweeted in February that OpenAI had been founded as an open-source nonprofit “to serve as a counterweight to Google, but now it has become a closed source, maximum-profit company effectively controlled by Microsoft. Not what I intended at all.”

Backers say his brand of social-minded capitalism makes him the ideal person to lead OpenAI. Others, including some who’ve worked for him, say he’s too commercially minded and immersed in Silicon Valley thinking to lead a technological revolution that is already reshaping business and social life. 

In the long run, he said, he wants to set up a global governance structure that would oversee decisions about the future of AI and gradually reduce the power OpenAI’s executive team has over its technology. 

Mr. Altman said he doesn’t necessarily need to be first to develop artificial general intelligence, a world long imagined by researchers and science-fiction writers where software isn’t just good at one specific task like generating text or images but can understand and learn as well or better than a human can. He instead said OpenAI’s ultimate mission is to build AGI, as it’s called, safely.

In its founding charter, OpenAI pledged to abandon its research efforts if another project came close to building AGI before it did. The goal, the company said, was to avoid a race toward building dangerous AI systems fueled by competition and instead prioritize the safety of humanity.

While running Y Combinator, Mr. Altman began to nurse a growing fear that large research labs like DeepMind, purchased by Google in 2014, were creating potentially dangerous AI technologies outside the public eye. Mr. Musk has voiced similar concerns of a dystopian world controlled by powerful AI machines. 

Messrs. Altman and Musk decided it was time to start their own lab. Both were part of a group that pledged $1 billion to the nonprofit, OpenAI Inc. 

OpenAI researchers soon concluded that the most promising path to achieve artificial general intelligence rested in large language models, or computer programs that mimic the way humans read and write. Such models were trained on large volumes of text and required a massive amount of computing power that OpenAI wasn’t equipped to fund as a nonprofit, according to Mr. Altman. 

“We didn’t have a visceral sense of just how expensive this project was going to be,” he said. “We still don’t.”

Tensions also grew with Mr. Musk, who became frustrated with the slow progress and pushed for more control over the organization, people familiar with the matter said. 

OpenAI executives ended up reviving an unusual idea that had been floated earlier in the company’s history: creating a for-profit arm, OpenAI LP, that would report to the nonprofit parent. 

Reid Hoffman, a LinkedIn co-founder who advised OpenAI at the time and later served on the board, said the idea was to attract investors eager to make money from the commercial release of some OpenAI technology, accelerating OpenAI’s progress

“You want to be there first and you want to be setting the norms,” he said. “That’s part of the reason why speed is a moral and ethical thing here.”

The decision further alienated Mr. Musk, the people familiar with the matter said. He parted ways with OpenAI in February 2018. 

Mr. Musk announced his departure in a company all-hands, former employees who attended the meeting said. Mr. Musk explained that he thought he had a better chance at creating artificial general intelligence through Tesla, where he had access to greater resources, they said.

A young researcher questioned whether Mr. Musk had thought through the safety implications, the former employees said. Mr. Musk grew visibly frustrated and called the intern a “jackass,” leaving employees stunned, they said. It was the last time many of them would see Mr. Musk in person.  

Mr. Musk’s departure marked a turning point. Later that year, OpenAI leaders told employees that Mr. Altman was set to lead the company. He formally became CEO and helped complete the creation of the for-profit subsidiary in early 2019.

OpenAI said that it received about $130 million in contributions from the initial $1 billion pledge, but that further donations were no longer needed after the for-profit’s creation. Mr. Musk has tweeted that he donated around $100 million to OpenAI. 

In the meantime, Mr. Altman began hunting for investors. His break came at Allen & Co.’s annual conference in Sun Valley, Idaho in the summer of 2018, where he bumped into Satya Nadella, the Microsoft CEO, on a stairwell and pitched him on OpenAI. Mr. Nadella said he was intrigued. The conversations picked up that winter.

“I remember coming back to the team after and I was like, this is the only partner,” Mr. Altman said. “They get the safety stuff, they get artificial general intelligence. They have the capital, they have the ability to run the compute.”   

Mr. Altman shared the contract with employees as it was being negotiated, hosting all-hands and office hours to allay concerns that the partnership contradicted OpenAI’s initial pledge to develop artificial intelligence outside the corporate world, the former employees said. 

Some employees still saw the deal as a Faustian bargain. 

OpenAI’s lead safety researcher, Dario Amodei, and his lieutenants feared the deal would allow Microsoft to sell products using powerful OpenAI technology before it was put through enough safety testing,

They felt that OpenAI’s technology was far from ready for a large release—let alone with one of the world’s largest software companies—worrying it could malfunction or be misused for harm in ways they couldn’t predict.  

Mr. Amodei also worried the deal would tether OpenAI’s ship to just one company—Microsoft—making it more difficult for OpenAI to stay true to its founding charter’s commitment to assist another project if it got to AGI first, the former employees said.

Microsoft initially invested $1 billion in OpenAI. While the deal gave OpenAI its needed money, it came with a hitch: exclusivity. OpenAI agreed to only use Microsoft’s giant computer servers, via its Azure cloud service, to train its AI models, and to give the tech giant the sole right to license OpenAI’s technology for future products.

In a recent investment deck, Anthropic said it was “committed to large-scale commercialization” to achieve the creation of safe AGI, and that it “fully committed” to a commercial approach in September. The company was founded as an AI safety and research company and said at the time that it might look to create commercial value from its products. 

Mr. Altman “has presided over a 180-degree pivot that seems to me to be only giving lip service to concern for humanity,” he said. 

“The deal completely undermines those tenets to which they secured nonprofit status,” said Gary Marcus, an emeritus professor of psychology and neural science at New York University who co-founded a machine-learning company

The cash turbocharged OpenAI’s progress, giving researchers access to the computing power needed to improve large language models, which were trained on billions of pages of publicly available text. OpenAI soon developed a more powerful language model called GPT-3 and then sold developers access to the technology in June 2020 through packaged lines of code known as application program interfaces, or APIs. 

Mr. Altman and Mr. Amodei clashed again over the release of the API, former employees said. Mr. Amodei wanted a more limited and staged release of the product to help reduce publicity and allow the safety team to conduct more testing on a smaller group of users, former employees said. 

Mr. Amodei left the company a few months later along with several others to found a rival AI lab called Anthropic. “They had a different opinion about how to best get to safe AGI than we did,” Mr. Altman said.

Anthropic has since received more than $300 million from Google this year and released its own AI chatbot called Claude in March, which is also available to developers through an API. 

Mr. Altman disagreed. “The unusual thing about Microsoft as a partner is that it let us keep all the tenets that we think are important to our mission,” he said, including profit caps and the commitment to assist another project if it got to AGI first. 

In the three years after the initial deal, Microsoft invested a total of $3 billion in OpenAI, according to investor documents. 

More than one million users signed up for ChatGPT within five days of its November release, a speed that surprised even Mr. Altman. It followed the company’s introduction of DALL-E 2, which can generate sophisticated images from text prompts.

By February, it had reached 100 million users, according to analysts at UBS, the fastest pace by a consumer app in history to reach that mark.

n’s close associates praise his ability to balance OpenAI’s priorities. No one better navigates between the “Scylla of misplaced idealism” and the “Charybdis of myopic ambition,” Mr. Thiel said. 

Mr. Altman said he delayed the release of the latest version of its model, GPT-4, from last year to March to run additional safety tests. Users had reported some disturbing experiences with the model, integrated into Bing, where the software hallucinated—meaning it made up answers to questions it didn’t know. It issued ominous warnings and made threats. 

“The way to get it right is to have people engage with it, explore these systems, study them, to learn how to make them safe,” Mr. Altman said.

After Microsoft’s initial investment is paid back, it would capture 49% of OpenAI’s profits until the profit cap, up from 21% under prior arrangements, the documents show. OpenAI Inc., the nonprofit parent, would get the rest.

He has put almost all his liquid wealth in recent years in two companies. He has put $375 million into Helion Energy, which is seeking to create carbon-free energy from nuclear fusion and is close to creating “legitimate net-gain energy in a real demo,” Mr. Altman said.

He has also put $180 million into Retro, which aims to add 10 years to the human lifespan through “cellular reprogramming, plasma-inspired therapeutics and autophagy,” or the reuse of old and damaged cell parts, according to the company. 

He noted how much easier these problems are, morally, than AI. “If you’re making nuclear fusion, it’s all upside. It’s just good,” he said. “If you’re making AI, it is potentially very good, potentially very terrible.” 

So 1 kilogram of AMB-FUBINACA could be portioned out over 15,625 doses, with a typical street price of $35. That means the dealer stands to make close to $500,000.

As soon as the drug shows up on the radar of authorities, the makers move on to the next compound.

And if the dangers of synthetic cannabinoids have researchers concerned, the risks of designer opioids are perhaps even greater.

Just last month, the federal Drug Enforcement Administration issued an alert for a new designer drug called Pink, which had been responsible for 46 deaths, including 31 in New York and 10 in North Carolina.

“Pink belongs to a family of deadly synthetic opioids far more potent than morphine,” according to the agency. “It is usually imported to the United States, mainly from illicit labs in China.”

while it is not in the interest of dealers to kill their clients, as these synthetic compounds become increasingly potent, the risks will continue to grow.

“No compound that has been made yet has the potential to kill thousands of people,” he said. “But that is a scenario that is becoming more and more close to reality.”

“It is in my mind one of the great, unreported ironies of the first Obama administration.”

“People are asking us, how do they protect their privacy?” Mr. Meinrath said.

Radio Free Asia, a United States government-financed nonprofit, has given $1 million to explore multiple overseas deployments. The countries involved have not been revealed, Mr. Meinrath said, adding, “I can’t talk about specific locations because lives could be at risk.”

The mesh software, called Commotion, is a major redesign of systems that have been run for years by experts across Europe, said Mr. Meinrath, who is now director of the New America Foundation’s X-Lab. The idea, he said, was to take the technology out of what he calls “the geekosphere” and make it accessible to the public. (Commotion is available to download free from the project’s website.)

Resilience could become the prime argument for mesh networks, with privacy as a bonus, said Jonathan Zittrain, a professor of law and computer science at Harvard and co-founder of the Berkman Center for Internet and Society. That is similar to the original Internet, before it was controlled by corporate hands and scoured by government spies, he said.“It makes mesh more like the Internet than the Internet,” he said.

“We want to serve every person in the world” with high-speed Internet signals, said Yael Maguire, head of Facebook’s Connectivity Lab. The dream — assuming regulators around the planet go along with it — is a fleet as big as 1,000 drones connecting people to the Internet. And where it is too remote even for the drones, satellites would do the trick.

Facebook’s effort in artificial intelligence is called deep learning, for the number of levels at which it critically analyzes information. By figuring out context, Facebook better knows why people anywhere are looking at something, and what else it can do to keep them engaged.

For the long term, Mr. Zuckerberg hopes Facebook’s A.I. will translate languages on the fly, know strangers you might meet and, of course, bring you the highest-value ads

Because, in the end, it’s still about getting you to look at more ads.“The fundamental thing about advertising is people paying to get a message in front of you,” Mr. Schroepfer said. “That won’t go away in my life, though the form may change.”

But gene drive technology is so powerful that leading researchers have urged scientists in the field to be cautious. A warning published in August in the prestigious journal Science, by teams in the UK, US, Australia and Japan, said that while gene drives have the potential to save lives and bring other benefits, the accidental release of modified organisms “could have unpredictable ecological consequences.”

They call on scientists to ensure that experimental organisms cannot escape from their labs, be released on purpose, or even find their way out accidentally in the event of a natural disaster. Researchers should also be open about the precautions they take to prevent an unintended release, they said.

In the latest study, mosquitoes were engineered to carry genes for antibodies that target the human malaria parasite, Plasmodium falciparum. When released into the wild, researchers believe the modified insects will breed with normal mosquitoes and pass the anti-malarial genes on to their young, making an ever-increasing proportion of future generations resistant to the malaria parasite.

In lab tests, the modified mosquitoes passed on their anti-malarial genes to 99.5% of their offspring, suggesting that the procedure was incredibly effective and efficient. To track which insects inherited the antibody genes, the scientists added a tracer gene that gave carriers red fluorescent eyes.

Dr Hörst is hopeful that her team's work will be helpful in ruling out erroneous organic signatures, yet she notes that the results do show exoplanets may be capable of creating the building blocks for life.

Public health laboratories in all 50 states and Washington, D.C. are now testing for the coronavirus and many more labs are completing testing verification procedures outlined by the Federal Drug Administration. But some states are actively discouraging testing for anyone who is not showing symptoms, and a request from a doctor is no guarantee of a test, Dr. LeRoy said.

The state labs are largely being used for patients identified by the Centers for Disease Control and Prevention as high priority. This includes hospitalized patients with symptoms compatible with the coronavirus; those over 65; those with chronic medical conditions or compromised immune systems; those who show symptoms within 14 days of being in contact with a confirmed coronavirus patient; and those with a history of travel to China, Italy, Iran or South Korea.

With over 8 million people, New York City is also the largest city in the country. So New York's high number of coronavirus cases is also just a reflection of its size. The state will likely lead the country in coronavirus cases even if its infection rate per person is not the highest, Sepkowitz said.

Another reason why New York has so many confirmed coronavirus cases is because it is looking for them.The US has lagged behind other countries in testing suspected cases, and people across the country have told CNN that they have been unable to get tested.New York, though, has made a dedicated push to ramp up testing at hospitals, labs and drive-through centers specifically set up in the most dense areas. With FDA approval, New York state authorized 28 public and private labs to begin testing for coronavirus on March 13, the first state to do so.

Cuomo said over 100,000 people have been tested for coronavirus in New York. He said Thursday that about 25% of all testing nationwide has been performed by New York.

Cuomo has earned rave reviews for his daily press conferences during the crisis. But both he and de Blasio were slow to aggressively shut schools, events and social gatherings in the early days of the outbreak.

New York City is a world-renowned tourist destination and the most visited destination in the US. As such, Cuomo said that contagious people from countries that had earlier coronavirus outbreaks traveled to the city and spread the virus.

Given all those reasons, New York City was always bound to be a hub of rapidly spreading cases. But it is far from the last.

what the administration should have been doing in January to prepare us for today.

She cites the delay on tests, without which “cases go undetected and people continue to circulate” as a leading issue along with other missed federal government responses—many of which are still not fully operational

The prescient recommendations from experts across disciplines in the period before COVID-19 reached American shores—about testing, equipment, and distancing—make clear that more than any single factor, it was Trump’s squandering of out lead-time which should have been used to prepare for the pandemic that has exacerbated this crisis.

What follows is an annotated timeline revealing the warning signs the administration received and showing how slow the administration was to act on these recommendations.

The Early Years: Warnings Ignored

2017: Trump administrations officials are briefed on an intelligence document titled “Playbook for Early Response to High-Consequence Emerging Infectious Disease Threats and Biological Incidents.” That’s right. The administration literally had an actual playbook for what to do in the early stages of a pandemic

February 2018: The Washington Post writes “CDC to cut by 80 percent efforts to prevent global disease outbreak.” The meat of the story is “Countries where the CDC is planning to scale back include some of the world’s hot spots for emerging infectious disease, such as China, Pakistan, Haiti, Rwanda and Congo.”

May 2018: At an event marking the 100 year anniversary of the 1918 pandemic, Borio says “pandemic flu” is the “number 1 health security issue” and that the U.S. is not ready to respond.

One day later her boss, Rear Adm. Timothy Ziemer is pushed out of the administration and the global health security team is disbanded

Beth Cameron, former senior director for global health security on the National Security Council adds: “It is unclear in his absence who at the White House would be in charge of a pandemic,” Cameron said, calling it “a situation that should be immediately rectified.” Note: It was not

January 2019: The director of National Intelligence issues the U.S. Intelligence Community’s assessment of threats to national security. Among its findings:

A novel strain of a virulent microbe that is easily transmissible between humans continues to be a major threat, with pathogens such as H5N1 and H7N9 influenza and Middle East Respiratory Syndrome Coronavirus having pandemic potential if they were to acquire efficient human-to-human transmissibility.”

Page 21: “We assess that the United States and the world will remain vulnerable to the next flu pandemic or large scale outbreak of a contagious disease that could lead to massive rates of death and disability, severely affect the world economy, strain international resources, and increase calls on the United States for support.”

September, 2019: The Trump Administration ended the pandemic early warning program, PREDICT, which trained scientists in China and other countries to identify viruses that had the potential to turn into pandemics. According to the Los Angeles Times, “field work ceased when funding ran out in September,” two months before COVID-19 emerged in Wuhan Province, China.

2020: COVID-19 Arrives

anuary 3, 2020: The CDC is first alerted to a public health event in Wuhan, China

January 6, 2020: The CDC issues a travel notice for Wuhan due to the spreading coronavirus

Note: The Trump campaign claims that this marks the beginning of the federal government disease control experts becoming aware of the virus. It was 10 weeks from this point until the week of March 16 when Trump began to change his tone on the threat.

January 10, 2020: Former Trump Homeland Security Advisor Tom Bossert warns that we shouldn’t “jerk around with ego politics” because “we face a global health threat…Coordinate!”

January 18, 2020: After two weeks of attempts, HHS Secretary Alex Azar finally gets the chance to speak to Trump about the virus. The president redirects the conversation to vaping, according to the Washington Post. 

January 21, 2020: Dr. Nancy Messonnier, the director of the National Center for Immunization and Respiratory Disease at the CDC tells reporters, “We do expect additional cases in the United States.”

January 27, 2020: Top White House aides meet with Chief of Staff Mick Mulvaney to encourage greater focus on the threat from the virus. Joe Grogan, head of the White House Domestic Policy Council warns that “dealing with the virus was likely to dominate life in the United States for many months.”

January 28, 2020: Two former Trump administration officials—Gottlieb and Borio—publish an op-ed in the Wall Street Journal imploring the president to “Act Now to Prevent an American Epidemic.” They advocate a 4-point plan to address the coming crisis:

(1) Expand testing to identify and isolate cases. Note: This did not happen for many weeks. The first time more than 2,000 tests were deployed in a single day was not until almost six weeks later, on March 11.

(3) Prepare hospital units for isolation with more gowns and masks. Note: There was no dramatic ramp-up in the production of critical supplies undertaken. As a result, many hospitals quickly experienced shortages of critical PPE materials. Federal agencies waited until Mid-March to begin bulk orders of N95 masks.

January 29, 2020: Trump trade advisor Peter Navarro circulates an internal memo warning that America is “defenseless” in the face of an outbreak which “elevates the risk of the coronavirus evolving into a full-blown pandemic, imperiling the lives of millions of Americans.”

January 30, 2020: Dr. James Hamblin publishes another warning about critical PPE materials in the Atlantic, titled “We Don’t Have Enough Masks.”

January 29, 2020: Republican Senator Tom Cotton reaches out to President Trump in private to encourage him to take the virus seriously.

Late January, 2020:  HHS sends a letter asking to use its transfer authority to shift $136 million of department funds into pools that could be tapped for combating the coronavirus. White House budget hawks argued that appropriating too much money at once when there were only a few U.S. cases would be viewed as alarmist.

Trump’s Chinese travel ban only banned “foreign nationals who had been in China in the last 14 days.” This wording did not—at all—stop people from arriving in America from China. In fact, for much of the crisis, flights from China landed in America almost daily filled with people who had been in China, but did not fit the category as Trump’s “travel ban” defined it.

January 31, 2020: On the same day Trump was enacting his fake travel ban, Foreign Policy reports that face masks and latex gloves are sold out on Amazon and at leading stores in New York City and suggests the surge in masks being sold to other countries needs “refereeing” in the face of the coming crisis.

February 4, 2020: Gottlieb and Borio take to the WSJ again, this time to warn the president that “a pandemic seems inevitable” and call on the administration to dramatically expand testing, expand the number of labs for reviewing tests, and change the rules to allow for tests of people even if they don’t have a clear known risk factor.

Note: Some of these recommendations were eventually implemented—25 days later.

February 5, 2020: HHS Secretary Alex Azar requests $2 billion to “buy respirator masks and other supplies for a depleted federal stockpile of emergency medical equipment.” He is rebuffed by Trump and the White House OMB who eventually send Congress a $500 million request weeks later.

February 4 or 5, 2020: Robert Kadlec, the assistant secretary for preparedness and response, and other intelligence officials brief the Senate Intelligence Committee that the virus poses a “serious” threat and that “Americans would need to take actions that could disrupt their daily lives.”

February 5, 2020: Senator Chris Murphy tweets: Just left the Administration briefing on Coronavirus. Bottom line: they aren't taking this seriously enough. Notably, no request for ANY emergency funding, which is a big mistake. Local health systems need supplies, training, screening staff etc. And they need it now.

February 9, 2020: The Washington Post reports that a group of governors participated in a jarring meeting with Dr. Anthony Fauci and Dr. Robert Redfield that was much more alarmist than what they were hearing from Trump. “The doctors and the scientists, they were telling us then exactly what they are saying now,” Maryland Gov. Larry Hogan (R) said.

the administration lifted CDC restrictions on tests. This is a factually true statement. But it elides that fact that they did so on March 3—two critical weeks after the third Borio/Gottlieb op-ed on the topic, during which time the window for intervention had shrunk to a pinhole.

February 20, 2020: Borio and Gottlieb write in the Wall Street Journal that tests must be ramped up immediately “while we can intervene to stop spread.”

February 23, 2020: Harvard School of Public Health professor issues warning on lack of test capability: “As of today, the US remains extremely limited in#COVID19 testing. Only 3 of ~100 public health labs haveCDC test kits working and CDC is not sharing what went wrong with the kits. How to know if COVID19 is spreading here if we are not looking for it.

February 24, 2020: The Trump administration sends a letter to Congress requesting a small dollar amount—between $1.8 billion and $2.5 billion—to help combat the spread of the coronavirus. This is, of course, a pittance

February 25, 2020: Messonier says she expects “community spread” of the virus in the United States and that “disruption to everyday life might be severe.” Trump is reportedly furious and Messonier’s warnings are curtailed in the ensuing weeks.

Trump mocks Congress in a White House briefing, saying “If Congress wants to give us the money so easy—it wasn’t very easy for the wall, but we got that one done. If they want to give us the money, we’ll take the money.”

February 26, 2020: Congress, recognizing the coming threat, offers to give the administration $6 billion more than Trump asked for in order to prepare for the virus.

February 27, 2020: In a leaked audio recording Sen. Richard Burr, chairman of the Intelligence Committee and author of the Pandemic and All-Hazards Preparedness Act (PAHPA) and the Pandemic and All-Hazards Preparedness and Advancing Innovation Act (reauthorization of PAHPA), was telling people that COVID-19 “is probably more akin to the 1918 pandemic.”

March 4, 2020: HHS says they only have 1 percent of respirator masks needed if the virus became a “full-blown pandemic.”

March 3, 2020: Vice President Pence is asked about legislation encouraging companies to produce more masks. He says the Trump administration is “looking at it.”

March 7, 2020: Fox News host Tucker Carlson, flies to Mar-a-Lago to implore Trump to take the virus seriously in private rather than embarrass him on TV. Even after the private meeting, Trump continued to downplay the crisis

March 9, 2020: Tom Bossert, Trump’s former Homeland Security adviser, publishes an op-ed saying it is “now or never” to act. He advocates for social distancing and school closures to slow the spread of the contagion.

Trump says that developments are “good for the consumer” and compares COVID-19 favorably to the common flu.

March 17, 2020: Facing continued shortages of the PPE equipment needed to prevent healthcare providers from succumbing to the virus, Oregon Senators Jeff Merkeley and Ron Wyden call on Trump to use the Defense Production Act to expand supply of medical equipment

March 18, 2020: Trump signs the executive order to activate the Defense Production Act, but declines to use it

At the White House briefing he is asked about Senator Chuck Schumer’s call to urgently produce medical supplies and ventilators. Trump responds: “Well we’re going to know whether or not it’s urgent.” Note: At this point 118 Americans had died from COVID-19.

March 20, 2020: At an April 2nd White House Press Conference, President Trump’s son-in-law Jared Kushner who was made ad hoc point man for the coronavirus response said that on this date he began working with Rear Admiral John Polowczyk to “build a team” that would handle the logistics and supply chain for providing medical supplies to the states. This suggestion was first made by former Trump Administration officials January 28th

March 22, 2020: Six days after calling for a 15-day period of distancing, Trump tweets that this approach “may be worse than the problem itself.”

March 24, 2020: Trump tells Fox News that he wants the country opened up by Easter Sunday (April 12)

As Trump was speaking to Fox, there were 52,145 confirmed cases in the United States and the doubling time for daily new cases was roughly four days.

Scientists call these two shapes the prefusion and postfusion forms of the spike. Antibodies against the prefusion shape work powerfully against the coronavirus, but postfusion antibodies don’t stop it.

they discovered a way to keep the protein locked in a tulip-like prefusion shape. All they had to do was change two of more than 1,000 building blocks in the protein into a compound called proline.

All three of the vaccines that have been authorized so far in the United States — from Johnson & Johnson, Moderna and Pfizer-BioNTech — use the 2P spike.

Other vaccine makers are using it as well. Novavax has had strong results with the 2P spike in clinical trials and is expected to apply to the Food and Drug Administration for emergency use authorization in the next few weeks. Sanofi is also testing a 2P spike vaccine and expects to finish clinical trials later this year.

Dr. McLellan’s ability to find lifesaving clues in the structure of proteins has earned him deep admiration in the vaccine world. “This guy is a genius,” said Harry Kleanthous, a senior program officer at the Bill & Melinda Gates Foundation. “He should be proud of this huge thing he’s done for humanity.”

The potency of the vaccine brought an extra benefit: The researchers needed fewer viruses for an effective dose. A single egg may yield five to 10 doses of NDV-HXP-S, compared to one or two doses of influenza vaccines.

once Dr. McLellan and his colleagues handed off the 2P spike to vaccine makers, he turned back to the protein for a closer look. If swapping just two prolines improved a vaccine, surely additional tweaks could improve it even more.

The winner contained the two prolines in the 2P spike, plus four additional prolines found elsewhere in the protein. Dr. McLellan called the new spike HexaPro, in honor of its total of six prolines.

The structure of HexaPro was even more stable than 2P, the team found. It was also resilient, better able to withstand heat and damaging chemicals. Dr. McLellan hoped that its rugged design would make it potent in a vaccine.

the University of Texas set up a licensing arrangement for HexaPro that allows companies and labs in 80 low- and middle-income countries to use the protein in their vaccines without paying royalties.

The first wave of authorized Covid-19 vaccines require specialized, costly ingredients to make. Moderna’s RNA-based vaccine, for instance, needs genetic building blocks called nucleotides, as well as a custom-made fatty acid to build a bubble around them. Those ingredients must be assembled into vaccines in purpose-built factories.

The way influenza vaccines are made is a study in contrast. Many countries have huge factories for making cheap flu shots, with influenza viruses injected into chicken eggs. The eggs produce an abundance of new copies of the viruses. Factory workers then extract the viruses, weaken or kill them and then put them into vaccines.

In March, he joined forces with two fellow University of Texas biologists, Ilya Finkelstein and Jennifer Maynard. Their three labs created 100 new spikes, each with an altered building block. With funding from the Gates Foundation, they tested each one and then combined the promising changes in new spikes. Eventually, they created a single protein that met their aspirations.

PATH then connected the Mount Sinai team with influenza vaccine makers. On March 15, Vietnam’s Institute of Vaccines and Medical Biologicals announced the start of a clinical trial of NDV-HXP-S. A week later, Thailand’s Government Pharmaceutical Organization followed suit. On March 26, Brazil’s Butantan Institute said it would ask for authorization to begin its own clinical trials of NDV-HXP-S.

n vaccine maker Avi-Mex as an intranasal spray. The company will start clinical trials to see if the vaccine is even more potent in that form.

Washington Post fact-checker Glenn Kessler similarly raised eyebrows for declaring that the theory is "suddenly credible." 

Mr. Vollmer’s 1936 textbook makes a similar suggestion, though more as an approach to reducing crime than Ms. Kaba’s goal of creating a cooperative society in which police are obsolete. Mr. Vollmer asserted that school, welfare, health, and recreation were more likely to prevent crime than jails.

To this point, Mr. Vollmer would perhaps respond that reforming the police doesn’t come cheap — and that public funds could be used to educate would-be officers. When he forced out his deputies, he rebuilt the department with extra money from the city for education, raises and lab equipment. The proposals of Ms. Kaba and other police abolitionists would put public funds toward educating a wide range of people in community support jobs: mental health experts, conflict de-escalation teams, addiction specialists and advocates who can help the unhoused find shelter.

A large test of the Novavax COVID-19 vaccine's effectiveness, conducted in tens of thousands of volunteers in the United States and Mexico, is about to wrap up. Dr. Gregory Glenn, president of research and development for Novavax, told an audience at a recent webinar hosted by the International Society for Vaccines that "we anticipate filing for authorization in the U.K., U.S. and Europe in the third quarter."

To make the virus protein, Novavax uses giant vats of cells grown in the lab. But there's another way to make the protein: Get plants in a greenhouse to do it.

"Especially in elderly individuals in that study, it was not as immunogenic as it should be," says Dr. Paul Goepfert at the University of Alabama at Birmingham, who was one of the researchers involved in those early studies. He says the issue turned out to be an incorrect calculation of the dose of vaccine being delivered."So instead of giving 10 micrograms of the dose, they were actually giving one microgram," Goepfert says.

Early studies suggest Medicago's candidate vaccine does just that, and the company is confident enough in those findings that it's already begun a large study in people that could involve as many as 30,000 volunteers in 11 countries.

Another latecomer that's coming is the pharmaceutical giant Sanofi. Its protein subunit vaccine against the coronavirus is also grown in cells in the lab.

Late last year the company was getting ready to mount a large study of the vaccine's effectiveness when the early results in a smaller group of people showed it did not seem to be inducing the immune response that would be protective.

The plants used are related to the tobacco plant, and have been modified to contain the genetic instructions to make the viral protein.The plants do something very valuable — they make a lipid shell that surrounds a bunch of the viral proteins, with the proteins sticking out.

Goepfert says it'll be a good thing if all these vaccines make it to consumers. But that alone isn't going to solve the problem of getting people vaccinated.Why? "Because the vaccines that we have now are just beyond our wildest dreams kind of effective," he says. "And I'm living in a state right now where it just frustrates me how slow our vaccine uptake is."

Several states in the Northeast also have among the country’s worst outbreaks now. Connecticut, New Jersey and Pennsylvania, among others, are all experiencing marked rises in case counts, and labs have identified both the B.1.1.7 variant and large shares of another variant, B.1.526.

The B.1.526 variant, which first appeared in New York City in samples from November, appears in two forms: one with a mutation that may help the virus evade antibodies and another that may help it bind more tightly to human cells.

The outbreak in the Northeast is currently much worse than it is in California, but California faces a variant of its own that makes up a large share of cases.

Studies have indicated the variant first discovered in California, B.1.427/B.1.429, may also be more transmissible than earlier forms of the virus, but it does not appear to spread as quickly as B.1.1.7.

Like the variant first discovered in New York City, the B.1.427/B.1.429 variant has also been seen in high levels in neighboring states, including Arizona, but does not yet make up a significant number of cases outside the region.

In Michigan, Covid-19 hospitalizations are already more than three times higher than they were a month ago. Other states with rising cases are also seeing significant increases in hospitalized Covid-19 patients.

The vaccine rollout continues to speed up, and recent studies confirm that vaccines are effective against the coronavirus in the real world, giving experts hope that an end may be in sight. But with increased transmission, they say, comes a renewed need for caution in the immediate term.

“I think we’ve got to hang on just a little bit longer, being conservative and getting more people vaccinated,” Dr. Martin said. “I’d hate to see us having another hospital surge when we’re getting so close to being done with this. I’m definitely worried about it.”

The problem echoes the country’s catastrophic stumbles early in the pandemic, when a lack of testing allowed the virus to spread widely. Currently, only a tiny fraction of all positive coronavirus tests in the United States are forwarded for further sequencing.

t if scientists don’t know what strains are moving through the population, the mutations that matter may pop up undetected.

For months, scientists have been sounding alarms and trying to ramp up genetic sequencing of test samples, but the effort has been plagued by a lack of funding, political will and federal coordination

Centers for Disease Control and Prevention Director Rochelle Walensky said Friday that the government is increasing the level of sequencing nationwide.“We have scaled up surveillance dramatically just in the last 10 days, in fact. But our plans for scaling up surveillance are even more than what we’ve done so far,”

Ultimately, the country needs real-time data — similar to the dashboards now used to track daily cases, hospitalizations and deaths — to track variants and their prevalence across the country

“None of that exists right now. We’re incredibly behind compared to other countries,”

The U.S. effort is so underdeveloped that it’s impossible to say exactly how many virus cases are sequenced daily.

The CDC has warned that the variant found in the United Kingdom — which British scientists said could be up to 70 percent more transmissible — could become dominant in the United States by March.

It also recently contracted with four private companies — Quest, Labcorp, Illumina and Helix — to conduct more sequencing. By mid-February, those contracts should hit full capacity, analyzing 6,000 samples per week, CDC officials said.

Illumina estimates that the country needs to sequence 5 percent of its coronavirus cases to detect a new variant when the variant represents about 0.1 percent to 1.0 percent of the country’s case

However, the United States so far has only sequenced about 0.32 percent of its total cases

the country ranks 38th out of 130 countries reporting whole-genome sequencing data.

The United States has sequenced 84,177 samples out of 25.7 million cases as of Friday, according to a Washington Post analysis. By comparison, the United Kingdom, in ninth place, has sequenced 214,000 genomes — almost 6 percent — of the country’s 3.7 million cases.

Unlike the United States, the U.K. invested in genetic sequencing early on in the pandemic, launching its genomics consortium in March with a $27 million investment and a multimillion-dollar boost late last year.

Even before the emergence of mutations such as the variants first discovered in South Africa and the United Kingdom, U.S. experts had been warning for months about the need for a national standard for genetic surveillance.

In May, the CDC launched a surveillance program for the coronavirus called SPHERES (SARS-CoV-2 Sequencing for Public Health Emergency Response, Epidemiology, and Surveillance). But, in practice, the program relied on a haphazard patchwork of academic labs contributing genetic sequencing on a volunteer basis.

A July report by the National Academies of Science said that “poor funding, coordination, and capacity” had led to a “patchy, typically passive, and reactive” U.S. sequencing effort.