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Amazon Cyber Monday deals include $100 Acer Chromebook, $999 Apple MacBook

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Some of Amazon’s Cyber Monday laptop deals.

As the biggest online retailer in the known universe, no one is more equipped to handle Cyber Monday than Amazon. Among all of the deals it will be touting today, including sales on its own Fire tablets, the shopping Goliath has a number of specials for those looking to buy a new computer.

Front and center in its deals of the day, Amazon is discounting a quartet of Chromebooks, including the Acer CB3-131-CESZ with Intel Celeron processor, 2GB of RAM, 16GB of storage, and 11.6-inch display for just $99.99. You can double the RAM with the CB3-131-C8SZ for $30 more, or upgrade to one of two convertible Chromebooks: The Acer Chromebook R 13 runs on a MediaTek processor, and includes 4GB of RAM, 32GB of storage, and 13.3-inch full HD touchscreen for $289.99, while the Asus Flip C302 features an Intel Core m3 CPU, 4 gigs of RAM, 64GB of storage, and 12.5-inch touchscreen for $386.99.

Those looking for a deal on Apple’s MacBook will also find savings at Amazon today. Like Best Buy, the retailer is chopping the price of MacBook Pro laptops, in this case a significant discount on a 13-inch configuration with 3.3GHz Core i5 processor, 16GB of RAM, and 512GB solid-state drive for $1,984, or $315 less than Apple’s own price. Another deal of the day is on a previous generation 12-inch MacBook; if you can live with an older Intel Core m5-6Y54 CPU, you still get 8GB of RAM and 512GB SSD for $999.99, compared to $1,209 from the refurbished section of Apple’s online store.

In addition to continued savings on many of its Black Friday deals, Amazon has other Windows PCs on sale for Cyber Monday. If you act quickly, you can grab a choice of Dell Inspiron notebook — either the 15 3000 2-in-1 with eighth-generation Core i7-8550U, 8GB of RAM, 1TB hard drive, and 13.3-inch touchscreen for $629.99, or a gaming configuration with Core i7- 7700HQ, 8 gigs of RAM, terabyte hard drive and 128GB SSD, Nvidia GeForce GTX 1050 graphics, and 15.6-inch full HD display for $699.99.

Also on the clock as a limited-supply deal is the Asus ZenBook 3 for $999, which packages a Core i7-7500U CPU, 16GB of memory, and 512GB SSD into a 2-pound chassis with 12.5-inch display. Another Asus special is the Gaming G11CD-DB52 desktop with Core i5-6400, 8GB of RAM, terabyte hard drive, and GeForce GTX 950 graphics for $649, $150 off.

Amazon has two different Lenovo Flex 2-in-1 laptops on sale, depending on what you value more. For $599.99, the Flex 5 has a bigger screen (15.6-inch vs. 14-inch), but for $699 you can get a Flex 4 with a more powerful processor (Core i7 vs. Core i5), along with AMD Radeon R5 M430 graphics. Finally, gamers might appreciate the deal on the MSI GL62M gaming laptop, which offers i7-7700HQ, 8GB of RAM, 1TB hard drive and 128GB SSD, GeForce GTX 1050Ti, and 15.6-inch full HD display for $899.99, or almost $200 off.

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AstraZeneca’s best COVID vaccine result was a fluke. Experts have questions

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Enlarge / Vials in front of the AstraZeneca British biopharmaceutical company logo are seen in this creative photo taken on 18 November 2020.

Pharmaceutical giant AstraZeneca and the University of Oxford made an exciting announcement Monday: the COVID-19 vaccine they developed together appeared up to 90 percent effective at preventing disease. But in the days since, that exciting news melted into a pool of confusion after it became clear that the 90 percent figure came about from a complete accident. Now, experts are scratching their heads over what actually happened in the trial and what it means for the vaccine’s future.

The questions all swirl around the vaccine’s dosage regimen. In initial press releases, AstraZeneca and Oxford explained that researchers had used two different dosage regimens to test their experimental vaccine, AZD1222. In one regimen, trial participants received two “full” vaccine doses, 28 days apart. In the other, participants received a half dose of vaccine followed by a full dose 28 days later.

Pooling results from trials in the United Kingdom and another in Brazil, the researchers found the two-full-dose regimen was 62 percent effective at preventing COVID-19—a good, but not great result. The half-dose/full-dose regimen, on the other hand, appeared 90 percent effective—a rather impressive result.

The trouble is, there was never supposed to be a half-dose-full-dose regimen in any of the trials.

Serendipity?

“The reason we had the half-dose is serendipity,” Mene Pangalos, AstraZeneca’s head of non-oncology research and development, told Reuters in an interview Monday.

Pangalos explained that when the UK trial first began, Oxford researchers were giving patients their first round of shots and noticed that the vaccine’s side-effects—fatigue, headache, arm aches—were milder than expected.

“So, we went back and checked … and we found out that they had underpredicted the dose of the vaccine by half,” Pangalos said. The researchers then decided to continue on with the trial and give the relatively small number of incorrectly dosed patients the proper dose for their second shot.

In the pooled trial analysis, 2,741 participants were recruited while the incorrect half-dose/full-dose regimen was used and 8,895 participants were involved in the analysis of the two-full-dose regimen.

AstraZeneca and Oxford have been mum about how that error occurred exactly. Meanwhile, outside experts have raised doubt about whether the 90 percent efficacy with the half-dose/full-dose is even real, given the smaller number of participants.

Another wrinkle is that the dosing error occurred early in the trial when researchers were only recruiting people between the ages of 18 and 55—excluding older people more vulnerable to disease. The analysis with the two-full doses, on the other hand, did include older age groups.

Lingering questions

“There are a number of variables that we need to understand and what has been the role of each one of them in achieving the difference in efficacy,” Moncef Slaoui, chief scientist of the US government’s Operation Warp Speed, said in a press briefing Tuesday.

Operation Warp Speed has invested in AZD1222 and is supporting an ongoing trial of the vaccine in the US. Slaoui noted in the press conference that they knew about the dosing error at the time it happened. “When they realized that there was an error—or a change in the approach, the technique used—they corrected it,” he said.

Now that the results have come out, Slaoui says it’s important to dig into what was going on between the two regimens. For one thing, researchers should look to see if there are  different immune responses induced by the different dosages schemes. Some researchers have speculated that ramping up the vaccine dosage between the first and second shot could have helped build up better immune responses against the pandemic coronavirus, SARS-CoV-2.

Others have speculated that starting with a strong dose—as in the two-full-dose regimen— may have foiled efficacy because of the way AZD1222 is designed. The vaccine uses a weakened adenovirus as packaging to deliver to the immune system the genetic code for the SARS-CoV-2 spike protein. But starting out with a strong first dose may prime the immune system to focus on attacking the adenovirus, rather than the packaged coronavirus component, some think.

Once researchers have a better understanding of what was going on, then they can make decisions about altering the ongoing trials, Slaoui said. In the US, about 11,000 of a planned 40,000 participants have been recruited for a Phase III trial of AZD1222. So, it could still be altered to include the half-dose regimen if new information comes in. However, Salaoui noted that such information would have to come quickly, given the rate the pandemic is progressing in the US.

On a final note, Slaoui reemphasized that the difference in efficacy and the dosage error as whole could be meaningless in the end: “The 90 percent efficacy group and the 62 percent efficacy group are overlapping statistically, so it is still possible that that difference is a random difference,” he said. “It’s unlikely but it’s still possible it’s a random difference.”

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What we can learn from contact tracing an entire province

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Enlarge / Students have their temperature measured at Daowu middle school in China’s Hunan Province, part of the measures adopted to limit the spread of the coronavirus.

Early on in the COVID-19 pandemic, there were a lot of big questions about the basic properties of SARS-CoV-2: how quickly did it spread, could it spread from asymptomatic people, what was the typical mortality rate, and so on. We quickly started getting answers on some of these, but they were all imperfect in various ways. We could trace all the cases in controlled environments, like a cruise ship or aircraft carrier, but these probably wouldn’t reflect the virus’s spread in more typical communities. Or, we could trace things in real-world communities, but that approach would be far less certain to capture all the cases.

Over time, we’ve gotten lots of imperfect records, but we’ve started to build a consensus out of them. The latest example of this—a paper that describes contact tracing all cases that originated in Hunan, China—provides yet another set of measures of the virus’s behavior and our attempts to control infection. Papers like this have helped build the consensus on some of the key features of things like asymptomatic spread and the impact of contact tracing, so we thought it was a good chance to step back and look at this latest release.

Trace all the cases

The new work, done by an international team of researchers, focuses on the spread of SARS-CoV-2 in Hunan Province during the first outbreak after its origins in nearby Hubei. During the period of study, health authorities started by identifying cases largely by symptoms, and they then switched to a massive contact tracing effort and aggressive isolation policies. These efforts shut the outbreak down by early March. And, thanks to them, we have very detailed information on viral cases: 1,178 infected individuals, another 15,648 people they came in contact with, and a total of nearly 20,000 potential exposure events.

(A few additional cases occurred in Hunan during this time due to people who were infected elsewhere and then traveled into the province, but these aren’t considered in the analysis.)

One bit of good news: the researchers found that exposure in the context of health care was very low risk. This indicates that, as long as sufficient protective equipment is available, we can put procedures in place that minimize the spread of virus to healthcare workers.

The highest risk was, not surprisingly, among those sharing a household, followed by extended family members. The risk here actually went up as social distancing and isolation orders were put in place, as this forced people to spend more time in enclosed spaces with infected people. This heightened risk occurred despite the fact that China adopted a policy where people known to be infected were brought to dedicated isolation hospitals. Social and community contacts were intermediate-level risks.

The ability to quickly trace and isolate cases also altered other aspects of the virus’s spread. In the absence of any public health interventions, the peak of infectivity—the average point after being infected at which someone was most likely to pass the virus on—was about 5.3 days. This is roughly the same time as symptoms first become apparent. (Both these numbers are consistent with lots of additional studies elsewhere.)

But once efficient contact tracing was adopted, infected people typically went into isolation sooner. As a result most people passed on infections earlier, before they ended up isolated. (So there was a change in infection patterns even though nothing about the virus changed.) So, while they found that nearly two-thirds of people transmitted the virus prior to the onset of symptoms, some of that is a product of the public health measures taken.

Who infected whom?

It was clear that not all individuals were equally infective, something that had been seen previously. The authors estimate that 80 percent of the infections could be traced back to just 15 percent of the individuals, although again that number would be influenced by Hunan’s contact tracing and isolation, which would have prevented infections from many of those infected in the later stages of the outbreak. This study sheds no light on whether that’s because some people’s infections are more likely to spread for biological reasons, or because some individuals took part in “superspreader” events where environmental conditions enabled high levels of infection.

One thing that the researchers noted was that those under 12 years old were just as likely to pass the virus on as young adults were. But they’d seen that fewer of the children in that age group became infected in the first place. The role of children in driving outbreaks has been the subject of some controversy. It’s clear that young children are less likely to experience symptoms, but it has been less clear whether this was partly explained by them being less likely to pick up the virus in the first place. Obviously, this is something we’ll look for more certainty on, since it will help set educational policy.

Finally, the researchers looked at one of the basic measures of infectivity, the viral reproduction number (called R-naught), which measures how many infections on average arise from each infected individual. They came up with a similar baseline number as has been seen in other cases: 2.19. Anything above one means that the pandemic will grow, so a number that high is why SARS-CoV-2 has been so dangerous.

All of China’s interventions dropped this value, with the onset of contact tracing bringing it down to 1.5, and the aggressive contact tracing and isolation bringing it down to 1.01. While that last figure represents a case where the size of the outbreak is barely growing, it’s still not sufficient to completely end the virus’s circulation. “In practice, epidemic control is unrealistic if case isolation and quarantine of close contacts are the only measures in place,” the authors conclude.

Fortunately, they’re not the only tools we have; they cite policies like increased telework, reduced operation of restaurants and other service businesses, and higher face mask use as options that would add to the effect of contact tracing and isolation. And, since the margins are so close to start with, we wouldn’t even need high levels of adoption to make a sufficient difference.

Of course, all that happened in a country where the government could ensure any policy decisions were adopted, and cases were low enough that contact tracing could be effective. That’s certainly not the case in the US, so it’s likely that multiple efforts will be needed in parallel before extensive contact tracing can even be effective.

Overall, however, it’s critical to not place too much emphasis on the results of one paper; the strength of this one is that it largely supports data obtained from a variety of other sources. As the consensus built from these results gets stronger, we’ll be in a better position to tailor public health policies to the properties of the virus.

Science, 2020. DOI: 10.1126/science.abe2424  (About DOIs).

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We don’t have a COVID vaccine yet, but distribution is already messy

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Enlarge / A sign on the entrance to a pharmacy reads “Covid-19 Vaccine Not Yet Available”, November 23, 2020 in Burbank, California.

Individual states will ultimately decide who will get the first 6.4 million doses of COVID-19 vaccine, which will be distributed based on each state’s population rather than the levels of disease spread or number of high-risk people.

The approach, announced in a press briefing Tuesday, is a departure from earlier plans and reflects the frenzied effort to vaccinate a country of nearly 330 million as quickly as possible.

Top officials for Operation Warp Speed—the federal government’s program to swiftly develop and deliver COVID-19 vaccines and therapies—said at the briefing that the current approach is intended to “keep this simple.” However, the potential for state-by-state variation in early access to vaccines could easily become complicated—and time is ticking for states to get their distribution plans clarified. There’s just a matter of weeks before the Food and Drug Administration may grant an emergency authorization for a vaccine by Pfizer and BioNTech.

Last week, Pfizer and BioNTech announced that their mRNA vaccine was 95 percent effective at preventing symptomatic COVID-19 in their 43,000-participant clinical trial—and on Friday the companies submitted a request to the FDA for an Emergency Use Authorization (EUA). The FDA is reviewing the request now and will hold a public meeting with their Vaccines and Related Biological Products Advisory Committee on December 10 to discuss the potential authorization.

Federal and state officials, the companies, and private partners are all working under the expectation that the FDA will grant that authorization. If it does, the federal government plans to begin distribution of the vaccine within 24 hours of the EUA call. The challenge now is to figure out how to dole out that initial supply—among and within states.

Distribution recommendations

There are numerous bodies of experts who have released recommendations and guidance for distributing COVID-19 vaccines, including expert panels for the National Academies of Medicine and the World Health Organization. But the panel that has traditionally been tasked with this role—and the one that has made vaccine policy recommendations for decades—is the Advisory Committee on Immunization Practices (ACIP), a panel based from the Centers for Disease Control and Prevention.

In broad strokes, all the expert panels recommend vaccine distribution start with the highest-risk groups, including frontline healthcare workers, the elderly, and nursing home residents. But the initial batch of 6.4 million vaccine doses—if the Pfizer/BioNTech vaccine gets an EUA—won’t be enough to cover even those select high-risk groups, creating the need for more detailed prioritization plans.

ACIP has broadly suggested that allocation to states be based on the high-risk groups within them. In a meeting Monday, the panel laid out the framework of principals that will guide their specific prioritization recommendations for high-risk groups. However, ACIP isn’t planning to finalize those recommendations until after the FDA actually grants the EUA.

Operation Warp Speed officials had previously suggested they would wait for the ACIP recommendations before making the call on state allocations and prioritization recommendations. But that apparently changed late last Friday night.

“We hit the button at 11:35pm,” Gen. Gustave Perna, head of logistics for Operation Warp Speed, said at the press briefing Tuesday. “I finally made the decision Friday night—late Friday night—to snap the chalk line so states could prioritize based on [the] amount” of vaccine that has been allocated to them, which was based on population size.

State of things

Once those per-capita-bases allotments arrive, states will have to decide on their own how to divvy up the initial doses among people in the highest-priority groups.

It’s up to the federal government to set recommendations for prioritization, Secretary of Health and Human Services Alex Azar said at the briefing, but “it will be our nation’s governors in implementing the distribution plans to tell us… where to ship [vaccine doses] and they will decide whom the vaccine is given to. We hope that our recommendations will carry weight with them, but at the end of the day, they will make that decision.”

Azar went on to note that Operation Warp Speed is not waiting for the finalized ACIP prioritization recommendations to make their own guidance for states. They’re taking in recommendations from all the panels and the ACIP’s initial recommendations, he said.

“We are working expeditiously to formulate our recommended prioritization for vaccine distribution based on where we can secure the maximum effect under whatever the current epidemiological circumstances are in the United States at that time,” Azar said.

Though some states have already signaled that they will distribute vaccines according to the ACIP’s final guidance, Azar noted that vaccine allotments for each state will continue to be on a per capita basis, rather than risk. He stressed that this was intended to keep things simple and consistent.

Apart from the question of who will get vaccinated, Pfizer is busing working out the question of how. The company has been conducting “dry runs” of vaccine delivery and rehearsing with vaccine distributors how to unpack, store, and handle the vaccine doses once they arrive. In first practices, distributors have shown some “initial hesitation,” Perna said, but they have grown more comfortable with the protocols and helped Pfizer refine training methods.

The Pfizer/BioNTech vaccine’s distribution has been a point of concern given that it requires ultra-cold storage conditions of -70 degrees Celsius. But, Pfizer has worked to alleviate concern, emphasizing its cold-chain infrastructure already in place and its shipping containers that have GPS-enabled thermal sensor to track the location and temperature. Currently, the dry-runs for vaccine distribution have not included the dry ice needed to maintain the extreme storage temperature during shipping. But, according to the Washington Post, Pfizer will begin test-shipments that include dry ice in the coming weeks.

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