How We Can Return to Normal Life in the COVID-19 Era
I was asked recently when life might return to normal. The question is simple but the answer is complex, with many knowns, lots of known unknowns, and some unknown unknowns. But I'll give it my best shot.
To get the fatality rate down to flu-like levels would require that we cut Covid-19 fatalities down by a factor of 5.
Since I'm human (and thus want my life back), I might be biased toward optimism.
Here's one way to think about it: Is there another infection that causes sickness and death at levels that we tolerate? The answer, of course, is 'yes': influenza.
According to the Centers for Disease Control, from 2010 to 2019, an average of 30 million Americans had the flu each year, leading to an annual average of 37,000 deaths. This works out to an infection-fatality rate, or IFR, of 0.12 percent. We've tolerated that level of illness death from influenza for a century.
Before going on, let's get one thing out of the way: Back in March, Covid-19 wasn't, as some maintained, "like the flu," and it still isn't. Since then, the U.S. has had 3.9 million confirmed Covid-19 cases and 140,000 deaths, for an IFR of 3.6 percent. Taking all the cases — including asymptomatic patients and those with minimal symptoms who were never tested for Covid-19 — into account, the real IFR is probably 0.6 percent, or roughly 5 times that of the flu.
Nonetheless, even a partly effective vaccine, combined with moderately effective medications, could bring Covid-19 numbers down to a tolerable, flu-like, threshold. It's a goal that seems within our reach.
Chronic mask-wearing and physical distancing are not my idea of normal, nor, I would venture to guess, would most other Americans consider these desirable states in which to live. We need both now to achieve some semblance of normalcy, but they're decidedly not normal life. My notion of normal: daily life with no or minimal mask wearing, open restaurants and bars, ballparks with fans, and theaters with audiences.
My projection for when we might get there: perhaps a year from now.
To get the fatality rate down to flu-like levels would require that we cut Covid-19 fatalities down by a factor of 5, via some combination of fewer symptomatic cases and a lower chance that a symptomatic patient will go on to die. How might that happen?
First, we have to make some impact on young people – getting them to follow the public health directives at higher rates than they are currently. The main reason we need to push younger people to stay safe is that they can spread Covid-19 to vulnerable people (those who are older, with underlying health problems). But, once the most vulnerable are protected (through the deployment of some combination of effective medications and a vaccine), the fact that some young people aren't acting safely – or maybe won't take a vaccine themselves – wouldn't cause so much concern. The key is whether the people at highest risk for bad outcomes are protected.
Then there's the vaccine. The first principle: We don't need a 100 percent-effective vaccine injected into 320 million deltoid muscles (in the U.S. alone). Thank God, since it's fanciful to believe that we can have a vaccine that's 100 percent effective, universally available by next summer, and that each and every American agrees to be vaccinated.
How are we doing in our vaccine journey? We've been having some banner days lately, with recent optimistic reports from several of the vaccine companies. In one report, the leading candidate vaccine, the one effort being led by Oxford University, led to both antibodies and a cellular immune response, a very helpful belt-and-suspenders approach that increases the probability of long-lasting immunity. This good news comes on the heels of the positive news regarding the American vaccine being made by Moderna earlier in July.
While every article about vaccines sounds the obligatory cautionary notes, to date we've checked every box on the path to a safe and effective vaccine. We might not get there, but most experts are now predicting an FDA-approvable vaccine (more than 50 percent effective with no show-stopping side effects) by early 2021.
It is true that we don't know how long immunity will last, but that can be a problem to solve later. In this area, time is our friend. If we can get to an effective vaccine that lasts for a year or two, over time we should be able to discover strategies (more vaccine boosters, new and better medications) to address the possibility of waning immunity.
All things considered, I'm going to put my nickel down on the following optimistic scenario: we'll have one, and likely several, vaccines that have been proven to be more than 50 percent effective and safe by January, 2021.
If only that were the finish line.
Once we vaccinate a large fraction of high-risk patients, having a moderate number of unvaccinated people running around won't pose as much threat.
The investments in manufacturing and distribution should pay off, but it's still inconceivable that we'll be able to get vaccines to 300 million people in three to six months. For the 2009 Swine Flu, we managed to vaccinate about 1 in 4 Americans over six months.
So we'll need to prioritize. First in line will likely be the 55 million Americans over 65, and the six to eight million patient-facing healthcare workers. (How to sort priorities among people under 65 with "chronic diseases" will be a toughie.) Vaccinating 80-100 million vulnerable people, plus clinicians, might be achievable by mid-21.
If we can protect vulnerable people with an effective vaccine (with the less vulnerable waiting their turn over a subsequent 6-12 month period), that may be enough to do the trick. (Of course, vulnerable people may also be least likely to develop immunity in response to a vaccine. That could be an Achilles' heel – time will tell.)
Why might that be enough? Once we vaccinate a large fraction of high-risk patients, having a moderate number of unvaccinated people running around won't pose as much threat. Since they're at lower risk, they have a lower chance of getting sick and dying than those who received the vaccine first.
We're likely to have better meds by then, too. Since March, we've discovered two moderately effective medications for Covid-19 — remdesivir and dexamethasone. It seems likely that we'll find others by next summer, perhaps even a treatment that prevents patients from getting ill in the first place. There are many such therapies, ranging from zinc to convalescent plasma, currently being studied.
Moreover, we know that hospitals that are not overrun with Covid-19 have lower mortality rates. If we've gotten a fairly effective vaccine into most high-risk people, the hospitals are unlikely to be overwhelmed – another factor that may help lower the mortality rate to flu-like levels.
All of these factors – vaccination of most vulnerable people, one or two additional effective medications, hospitals and ICU's that aren't overwhelmed – could easily combine to bring the toll of Covid-19 down to something that resembles that of the flu. Then, we should be able to return to normal life.
Whatever the reason, if enough people refuse the vaccine, all bets are off.
What do I worry about? There's the growing anti-vaxxer movement, for one. On top of that, it seems that many Americans worry that a vaccine discovered in record speed won't be safe, or that the FDA approval process will have been corrupted by political influences. Whatever the reason, if enough people refuse the vaccine, all bets are off.
Assuming only high-risk people do get vaccinated, there will still be cases of Covid-19, maybe even mini-outbreaks, well into 2021 and likely 2022. Obviously, that's not ideal, and we should hope for a vaccine that results in the complete eradication of Covid-19. But the point is that, even with flu-like levels of illness and death, we should still be able to achieve "normal."
Hope is not a strategy, as the saying goes. But it is hope, which is more than we've had for a while.
In the 1966 movie "Fantastic Voyage," actress Raquel Welch and her submarine were shrunk to the size of a cell in order to eliminate a blood clot in a scientist's brain. Now, 55 years later, the scenario is becoming closer to reality.
California-based startup Bionaut Labs has developed a nanobot about the size of a grain of rice that's designed to transport medication to the exact location in the body where it's needed. If you think about it, the conventional way to deliver medicine makes little sense: A painkiller affects the entire body instead of just the arm that's hurting, and chemotherapy is flushed through all the veins instead of precisely targeting the tumor.
"Chemotherapy is delivered systemically," Bionaut-founder and CEO Michael Shpigelmacher says. "Often only a small percentage arrives at the location where it is actually needed."
But what if it was possible to send a tiny robot through the body to attack a tumor or deliver a drug at exactly the right location?
Several startups and academic institutes worldwide are working to develop such a solution but Bionaut Labs seems the furthest along in advancing its invention. "You can think of the Bionaut as a tiny screw that moves through the veins as if steered by an invisible screwdriver until it arrives at the tumor," Shpigelmacher explains. Via Zoom, he shares the screen of an X-ray machine in his Culver City lab to demonstrate how the half-transparent, yellowish device winds its way along the spine in the body. The nanobot contains a tiny but powerful magnet. The "invisible screwdriver" is an external magnetic field that rotates that magnet inside the device and gets it to move and change directions.
The current model has a diameter of less than a millimeter. Shpigelmacher's engineers could build the miniature vehicle even smaller but the current size has the advantage of being big enough to see with bare eyes. It can also deliver more medicine than a tinier version. In the Zoom demonstration, the micorobot is injected into the spine, not unlike an epidural, and pulled along the spine through an outside magnet until the Bionaut reaches the brainstem. Depending which organ it needs to reach, it could be inserted elsewhere, for instance through a catheter.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu.
Imagine moving a screw through a steak with a magnet — that's essentially how the device works. But of course, the Bionaut is considerably different from an ordinary screw: "At the right location, we give a magnetic signal, and it unloads its medicine package," Shpigelmacher says.
To start, Bionaut Labs wants to use its device to treat Parkinson's disease and brain stem gliomas, a type of cancer that largely affects children and teenagers. About 300 to 400 young people a year are diagnosed with this type of tumor. Radiation and brain surgery risk damaging sensitive brain tissue, and chemotherapy often doesn't work. Most children with these tumors live less than 18 months. A nanobot delivering targeted chemotherapy could be a gamechanger. "These patients really don't have any other hope," Shpigelmacher says.
Of course, the main challenge of the developing such a device is guaranteeing that it's safe. Because tissue is so sensitive, any mistake could risk disastrous results. In recent years, Bionaut has tested its technology in dozens of healthy sheep and pigs with no major adverse effects. Sheep make a good stand-in for humans because their brains and spines are similar to ours.
The Bionaut device is about the size of a grain of rice.
Bionaut Labs
"As the Bionaut moves through brain tissue, it creates a transient track that heals within a few weeks," Shpigelmacher says. The company is hoping to be the first to test a nanobot in humans. In December 2022, it announced that a recent round of funding drew $43.2 million, for a total of 63.2 million, enabling more research and, if all goes smoothly, human clinical trials by early next year.
Once the technique has been perfected, further applications could include addressing other kinds of brain disorders that are considered incurable now, such as Alzheimer's or Huntington's disease. "Microrobots could serve as a bridgehead, opening the gateway to the brain and facilitating precise access of deep brain structure – either to deliver medication, take cell samples or stimulate specific brain regions," Shpigelmacher says.
Robot-assisted hybrid surgery with artificial intelligence is already used in state-of-the-art surgery centers, and many medical experts believe that nanorobotics will be the instrument of the future. In 2016, three scientists were awarded the Nobel Prize in Chemistry for their development of "the world's smallest machines," nano "elevators" and minuscule motors. Since then, the scientific experiments have progressed to the point where applicable devices are moving closer to actually being implemented.
Bionaut's technology was initially developed by a research team lead by Peer Fischer, head of the independent Micro Nano and Molecular Systems Lab at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Fischer is considered a pioneer in the research of nano systems, which he began at Harvard University more than a decade ago. He and his team are advising Bionaut Labs and have licensed their technology to the company.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu, who leads the cooperation with Bionaut Labs. He agrees with Shpigelmacher that the Bionaut's size is perfect for transporting medication loads and is researching potential applications for even smaller nanorobots, especially in the eye, where the tissue is extremely sensitive. "Nanorobots can sneak through very fine tissue without causing damage."
In "Fantastic Voyage," Raquel Welch's adventures inside the body of a dissident scientist let her swim through his veins into his brain, but her shrunken miniature submarine is attacked by antibodies; she has to flee through the nerves into the scientist's eye where she escapes into freedom on a tear drop. In reality, the exit in the lab is much more mundane. The Bionaut simply leaves the body through the same port where it entered. But apart from the dramatization, the "Fantastic Voyage" was almost prophetic, or, as Shpigelmacher says, "Science fiction becomes science reality."
This article was first published by Leaps.org on April 12, 2021.
How the Human Brain Project Built a Mind of its Own
In 2009, neuroscientist Henry Markram gave an ambitious TED talk. “Our mission is to build a detailed, realistic computer model of the human brain,” he said, naming three reasons for this unmatched feat of engineering. One was because understanding the human brain was essential to get along in society. Another was because experimenting on animal brains could only get scientists so far in understanding the human ones. Third, medicines for mental disorders weren’t good enough. “There are two billion people on the planet that are affected by mental disorders, and the drugs that are used today are largely empirical,” Markram said. “I think that we can come up with very concrete solutions on how to treat disorders.”
Markram's arguments were very persuasive. In 2013, the European Commission launched the Human Brain Project, or HBP, as part of its Future and Emerging Technologies program. Viewed as Europe’s chance to try to win the “brain race” between the U.S., China, Japan, and other countries, the project received about a billion euros in funding with the goal to simulate the entire human brain on a supercomputer, or in silico, by 2023.
Now, after 10 years of dedicated neuroscience research, the HBP is coming to an end. As its many critics warned, it did not manage to build an entire human brain in silico. Instead, it achieved a multifaceted array of different goals, some of them unexpected.
Scholars have found that the project did help advance neuroscience more than some detractors initially expected, specifically in the area of brain simulations and virtual models. Using an interdisciplinary approach of combining technology, such as AI and digital simulations, with neuroscience, the HBP worked to gain a deeper understanding of the human brain’s complicated structure and functions, which in some cases led to novel treatments for brain disorders. Lastly, through online platforms, the HBP spearheaded a previously unmatched level of global neuroscience collaborations.
Simulating a human brain stirs up controversy
Right from the start, the project was plagued with controversy and condemnation. One of its prominent critics was Yves Fregnac, a professor in cognitive science at the Polytechnic Institute of Paris and research director at the French National Centre for Scientific Research. Fregnac argued in numerous articles that the HBP was overfunded based on proposals with unrealistic goals. “This new way of over-selling scientific targets, deeply aligned with what modern society expects from mega-sciences in the broad sense (big investment, big return), has been observed on several occasions in different scientific sub-fields,” he wrote in one of his articles, “before invading the field of brain sciences and neuromarketing.”
"A human brain model can simulate an experiment a million times for many different conditions, but the actual human experiment can be performed only once or a few times," said Viktor Jirsa, a professor at Aix-Marseille University.
Responding to such critiques, the HBP worked to restructure the effort in its early days with new leadership, organization, and goals that were more flexible and attainable. “The HBP got a more versatile, pluralistic approach,” said Viktor Jirsa, a professor at Aix-Marseille University and one of the HBP lead scientists. He believes that these changes fixed at least some of HBP’s issues. “The project has been on a very productive and scientifically fruitful course since then.”
After restructuring, the HBP became a European hub on brain research, with hundreds of scientists joining its growing network. The HBP created projects focused on various brain topics, from consciousness to neurodegenerative diseases. HBP scientists worked on complex subjects, such as mapping out the brain, combining neuroscience and robotics, and experimenting with neuromorphic computing, a computational technique inspired by the human brain structure and function—to name just a few.
Simulations advance knowledge and treatment options
In 2013, it seemed that bringing neuroscience into a digital age would be farfetched, but research within the HBP has made this achievable. The virtual maps and simulations various HBP teams create through brain imaging data make it easier for neuroscientists to understand brain developments and functions. The teams publish these models on the HBP’s EBRAINS online platform—one of the first to offer access to such data to neuroscientists worldwide via an open-source online site. “This digital infrastructure is backed by high-performance computers, with large datasets and various computational tools,” said Lucy Xiaolu Wang, an assistant professor in the Resource Economics Department at the University of Massachusetts Amherst, who studies the economics of the HBP. That means it can be used in place of many different types of human experimentation.
Jirsa’s team is one of many within the project that works on virtual brain models and brain simulations. Compiling patient data, Jirsa and his team can create digital simulations of different brain activities—and repeat these experiments many times, which isn’t often possible in surgeries on real brains. “A human brain model can simulate an experiment a million times for many different conditions,” Jirsa explained, “but the actual human experiment can be performed only once or a few times.” Using simulations also saves scientists and doctors time and money when looking at ways to diagnose and treat patients with brain disorders.
Compiling patient data, scientists can create digital simulations of different brain activities—and repeat these experiments many times.
The Human Brain Project
Simulations can help scientists get a full picture that otherwise is unattainable. “Another benefit is data completion,” added Jirsa, “in which incomplete data can be complemented by the model. In clinical settings, we can often measure only certain brain areas, but when linked to the brain model, we can enlarge the range of accessible brain regions and make better diagnostic predictions.”
With time, Jirsa’s team was able to move into patient-specific simulations. “We advanced from generic brain models to the ability to use a specific patient’s brain data, from measurements like MRI and others, to create individualized predictive models and simulations,” Jirsa explained. He and his team are working on this personalization technique to treat patients with epilepsy. According to the World Health Organization, about 50 million people worldwide suffer from epilepsy, a disorder that causes recurring seizures. While some epilepsy causes are known others remain an enigma, and many are hard to treat. For some patients whose epilepsy doesn’t respond to medications, removing part of the brain where seizures occur may be the only option. Understanding where in the patients’ brains seizures arise can give scientists a better idea of how to treat them and whether to use surgery versus medications.
“We apply such personalized models…to precisely identify where in a patient’s brain seizures emerge,” Jirsa explained. “This guides individual surgery decisions for patients for which surgery is the only treatment option.” He credits the HBP for the opportunity to develop this novel approach. “The personalization of our epilepsy models was only made possible by the Human Brain Project, in which all the necessary tools have been developed. Without the HBP, the technology would not be in clinical trials today.”
Personalized simulations can significantly advance treatments, predict the outcome of specific medical procedures and optimize them before actually treating patients. Jirsa is watching this happen firsthand in his ongoing research. “Our technology for creating personalized brain models is now used in a large clinical trial for epilepsy, funded by the French state, where we collaborate with clinicians in hospitals,” he explained. “We have also founded a spinoff company called VB Tech (Virtual Brain Technologies) to commercialize our personalized brain model technology and make it available to all patients.”
The Human Brain Project created a level of interconnectedness within the neuroscience research community that never existed before—a network not unlike the brain’s own.
Other experts believe it’s too soon to tell whether brain simulations could change epilepsy treatments. “The life cycle of developing treatments applicable to patients often runs over a decade,” Wang stated. “It is still too early to draw a clear link between HBP’s various project areas with patient care.” However, she admits that some studies built on the HBP-collected knowledge are already showing promise. “Researchers have used neuroscientific atlases and computational tools to develop activity-specific stimulation programs that enabled paraplegic patients to move again in a small-size clinical trial,” Wang said. Another intriguing study looked at simulations of Alzheimer’s in the brain to understand how it evolves over time.
Some challenges remain hard to overcome even with computer simulations. “The major challenge has always been the parameter explosion, which means that many different model parameters can lead to the same result,” Jirsa explained. An example of this parameter explosion could be two different types of neurodegenerative conditions, such as Parkinson’s and Huntington’s diseases. Both afflict the same area of the brain, the basal ganglia, which can affect movement, but are caused by two different underlying mechanisms. “We face the same situation in the living brain, in which a large range of diverse mechanisms can produce the same behavior,” Jirsa said. The simulations still have to overcome the same challenge.
Understanding where in the patients’ brains seizures arise can give scientists a better idea of how to treat them and whether to use surgery versus medications.
The Human Brain Project
A network not unlike the brain’s own
Though the HBP will be closing this year, its legacy continues in various studies, spin-off companies, and its online platform, EBRAINS. “The HBP is one of the earliest brain initiatives in the world, and the 10-year long-term goal has united many researchers to collaborate on brain sciences with advanced computational tools,” Wang said. “Beyond the many research articles and projects collaborated on during the HBP, the online neuroscience research infrastructure EBRAINS will be left as a legacy even after the project ends.”
Those who worked within the HBP see the end of this project as the next step in neuroscience research. “Neuroscience has come closer to very meaningful applications through the systematic link with new digital technologies and collaborative work,” Jirsa stated. “In that way, the project really had a pioneering role.” It also created a level of interconnectedness within the neuroscience research community that never existed before—a network not unlike the brain’s own. “Interconnectedness is an important advance and prerequisite for progress,” Jirsa said. “The neuroscience community has in the past been rather fragmented and this has dramatically changed in recent years thanks to the Human Brain Project.”
According to its website, by 2023 HBP’s network counted over 500 scientists from over 123 institutions and 16 different countries, creating one of the largest multi-national research groups in the world. Even though the project hasn’t produced the in-silico brain as Markram envisioned it, the HBP created a communal mind with immense potential. “It has challenged us to think beyond the boundaries of our own laboratories,” Jirsa said, “and enabled us to go much further together than we could have ever conceived going by ourselves.”