All about the Coronavirus

0:00:04 Hi, everyone. Welcome to this week’s episode of 16 Minutes, where we cover what’s going
0:00:08 on, what’s in the news from our vantage point in tech. In this episode, we’re going to
0:00:13 go deep on one topic, which is the coronavirus, and it’s a very fast-developing news cycle,
0:00:17 so we’re going to take a snapshot for where we are right now. And since this show is all
0:00:21 about teasing apart what’s hype, what’s real, given all the buzz and headlines out there,
0:00:24 we’re going to try to focus on what we know and what we don’t know. I’ve tried drawing
0:00:30 wherever possible from primary sources, so CDC reports, World Health Organization reports,
0:00:35 etc., instead of only looking at news headlines and derivative reports. And our ASICs and
0:00:38 the expert, who I’ll introduce in a moment, will be bringing in the vantage point coming
0:00:41 from bioengineering and that aspect as well.
0:00:45 So first of all, let me quickly summarize the news. People are referring to this outbreak
0:00:50 as the coronavirus, but it’s actually a new type of coronavirus because coronavirus is
0:00:55 actually the general term for a more common category of viruses. And this current strain
0:01:03 is called 2019-NCOV for 2019-N novel coronavirus. It’s a rapidly developing situation, but
0:01:10 as of January 26, according to the situation update on the World Health Organization website,
0:01:16 there’s a total of 2014 confirmed cases that have been reported globally. Of these, 98%
0:01:24 were reported from China, including Hong Kong, Macau, and Taipei. 324 of 1,975 cases have
0:01:30 been reported as severely ill, with 56 deaths reported to that date. Finally, 29 confirmed
0:01:35 cases have been reported out of China in 10 countries, and in the table that the World
0:01:40 Health Organization provided, there’s two cases listed in the US, but there’s more.
0:01:43 Again, this is from the Six Situations Report, which comes out every few days, and this one
0:01:47 came out on Sunday, January 26. That’s a very high-level summary. Now, let me welcome Judy
0:01:52 Sovitzkaya on the A6nz BioDeal team. First of all, really quickly, what is it? What is
0:01:53 the coronavirus?
0:02:00 Yeah, so let’s discuss what even is a virus. So a virus is basically a bunch of DNA or
0:02:05 RNA, some sort of nucleic acid, surrounded by a protein shell called the capsid of the
0:02:09 virus. That is the entire organism. And a lot of people actually don’t even call this
0:02:13 an organism because it’s not quite alive and it’s not quite dead. It’s something in
0:02:14 between.
0:02:17 There’s kind of a debate in the scientific community and the philosophical community
0:02:22 about what is a living thing. And the place where most people have come down is that you
0:02:27 need two conditions to be alive. You need to metabolize, which means you’re taking some
0:02:31 chemicals, transforming them into other chemicals, and pulling out energy in the process and
0:02:37 using that energy for something. And the second requirement for a living thing is to multiply,
0:02:43 to reproduce. So viruses really only satisfy the second condition. They don’t do anything
0:02:47 on their own. They don’t… Outside of a human host, they are non-living.
0:02:52 So that’s why there’s such a debate. The bottom line is that they don’t metabolize, but they
0:02:53 do multiply.
0:02:54 Exactly.
0:02:58 So tell me now more about the coronavirus category.
0:03:04 So the reason it’s called coronavirus is because on electron microscopy images, it actually
0:03:09 looks like there’s a little crown around the virus. The capsid for the coronavirus has
0:03:14 these proteins on it that are spikes. And a lot of the ways that we’re developing vaccines
0:03:17 against this virus and a lot of the ways that we’re identifying different types of these
0:03:21 viruses is by characterizing those spike proteins.
0:03:26 And as with most things in biology, we use Greek symbols to denote different versions
0:03:30 of the coronavirus. So there’s the alpha, the beta, the delta, and the gamma, which
0:03:36 are kind of four of the main categories of coronavirus. A lot of the common viruses are
0:03:39 either alpha or beta types, but SARS and MERS, they’re all betas.
0:03:43 Okay. So that’s kind of scientifically what it is. Now let’s practically break down the
0:03:48 symptoms. According to the CDC, the symptoms can include fever, cough, shortness of breath,
0:03:53 or other respiratory symptoms. And they believe that at this time, that symptoms of this virus
0:04:00 may appear in as few as two days or as long as 14 days after exposure. And this is actually
0:04:04 similar to what’s been seen with the previous incubation period of MERS viruses. And I’ll
0:04:08 get to what that is in a minute. But unlike those viruses, this particular one rarely
0:04:13 produces obvious like runny noses or intestinal symptoms necessarily, just according to one
0:04:18 report and that was recently published in Lancet. So I guess the question is that all
0:04:21 of these things are on a continuum. It’s not very discreet. Like this is all symptoms that
0:04:24 can describe frankly, any common cold, right? It’s the WebMD problem.
0:04:28 Right. Basically, you can Google it and find, associate yourself with anything. So the question
0:04:34 I have is, how does this stack up against MERS and SARS? And just really quickly to
0:04:39 summarize, SARS was the acronym for severe acute respiratory syndrome. There’s a big
0:04:44 outbreak of it in the early 2000s. And then MERS is Middle East respiratory syndrome.
0:04:49 And that is new as of 2012. So coronaviruses cause about 10 to 30% of colds, just your
0:04:54 common colds. And those are not nearly as serious as this disease. And some of the differences
0:05:00 between these epidemic causing coronaviruses versus your common cold is just the severity
0:05:04 of the infection, the likelihood that you are to die or to have really serious complications
0:05:10 from the infection. And in all of these cases, SARS, MERS, and this current coronavirus,
0:05:15 it’s because the coronavirus is infecting the lower part of the respiratory tract versus
0:05:17 just staying around your upper respiratory tract area.
0:05:21 Right. So not just your mouth, nose and sinuses, but by going into your lungs. So just like
0:05:26 a quick summary of where the fatality rates are, SARS apparently claimed about 10% of
0:05:32 people and MERS was much worse, claiming 30% of the people it infected. It’s also interesting
0:05:35 because I’ve been reading a lot of papers, but none of them are peer reviewed. In fact,
0:05:40 one of the papers between Friday and today was already updated with V2, but the authors
0:05:44 of the local institutes of virology, Chinese Academy of Sciences, local hospitals and the
0:05:50 provincial CDCs in China within this area supposedly analyze full length genome sequences
0:05:54 from five patients at the early stage of the outbreak. And they found that almost all of
0:05:59 those were identical to each other. So it’s the same virus and B, that about 79.5%. And
0:06:05 again, this is the current paper still being updated, identify to SARS coronavirus.
0:06:08 So that’s actually the most interesting thing from a bioengineering perspective about this
0:06:14 particular epidemic is how incredibly quickly we have sequenced this virus for past epidemics.
0:06:19 It’s taken time for us to really understand the genome and the molecular nature of a given
0:06:23 virus that’s causing an epidemic. In this case, within two weeks, people had already
0:06:29 published draft versions of the genome sequence for this virus. And the science is happening
0:06:34 in the sort of really live way that doesn’t happen very often where people are commenting
0:06:36 literally in the GenBank on the GenBank website.
0:06:40 The CDC uploaded the entire genome of the virus from the first reported case in the
0:06:44 United States to GenBank. And it’s also interesting because in the age of social media, which
0:06:50 cuts both ways virally, it’s also spreading information much faster. Coronavirus was first
0:06:54 detected in Wuhan city in the Hubei province in China, beginning with 44 patients who had
0:07:00 quote, pneumonia of unknown etiology or unknown cause between New Year’s Eve and the first
0:07:05 couple of days of 2020. And then was identified as a new type of virus isolated by Chinese
0:07:10 authorities on January 7. And then on January 11 and 12, the World Health Organization received
0:07:14 detailed information from the National Health Commission in China that the outbreak is associated
0:07:21 with exposures in one seafood market in Wuhan city. And basically it’s showing the spread
0:07:26 of information. Whereas with the SARS crisis, journalist Helen Branswell at Stat News was
0:07:31 commenting because she had covered the SARS crisis in 2003, that one might be tempted
0:07:35 to say SARS start was worse, it spread faster, not sure that’s true. SARS was well underway
0:07:40 for at least 4.5 months before the world knew there was a new virus spreading. This current
0:07:44 coronavirus seems to have been spotted much, much sooner after its emergence. But what’s
0:07:47 really interesting is not just that it’s been spotted sooner, but that the genetic
0:07:53 information we have is moving much faster. So can you talk to me about what that tells
0:07:54 us and why that matters?
0:07:58 So there’s a couple of areas where you get benefits from having all this genetic information
0:08:03 so quickly. The first is just diagnosis. So if tomorrow somebody in San Francisco was
0:08:07 to go into an urgent care clinic and say that they have a cold, we could really quickly
0:08:12 identify whether or not that actually belongs to this epidemic.
0:08:16 Another advantage we have once we have the genome sequence is that in this age of genomic
0:08:20 medicine that we’re entering, where we’re actually creating vaccines that are based
0:08:26 on genome sequences. The third implication is for figuring out treatments and also predicting
0:08:30 some of the features of the epidemic. So we know in this example that this coronavirus
0:08:35 looks really similar to SARS. So we can look back at the SARS epidemic, understand how
0:08:39 quickly it’s spread, in which populations. And from the genomic information, you can
0:08:44 actually see, for example, the spikes on the corona, which are involved in getting into
0:08:49 cells, do those look similar to what the SARS spikes look like? And maybe the treatments
0:08:51 that work in this case as well.
0:08:54 So the high level summary is that having the genomic information, which we didn’t have
0:08:59 then when we do have now, by then I mean the SARS outbreak, which happened about 2002 to
0:09:05 2004, the peak was 2003, is that you can classify things much more easily, figure out where
0:09:10 it belongs, it doesn’t belong, kind of isolate that, that you can develop things faster based
0:09:14 on it, although there isn’t a vaccine yet, and that you can figure out treatment protocols
0:09:17 based on the similarities and differences.
0:09:21 Was there anything else on the connection between mayors and SARS from a genomics perspective?
0:09:26 Yeah. So because the science is happening live, you’re seeing a lot of pretty quick modifications
0:09:31 to what people have already said. So the first paper analyzing the genome of this virus that
0:09:38 I saw at least, described that the spike proteins that are used to enter into lung cells are
0:09:42 different enough between SARS and this new coronavirus, that they thought it wouldn’t
0:09:47 be as bad as SARS. And then within like literally two days, I think I saw a paper that corrected
0:09:51 that and said that actually the protein is quite similar at the protein level.
0:09:54 Are there any bioengineering implications of that? This goes to me that the eternal
0:09:58 question of how DNA expresses itself practically in the complexity of disease.
0:10:02 That’s a really good question. This mirrors everything in genomics where we thought that
0:10:05 once we have the sequence, we’ll know all the answers. And that’s definitely not the
0:10:09 case. We can know from the DNA what the difference is going to be in the protein. That’s one
0:10:13 to one, there’s no guessing there. But once we know what’s different about the protein,
0:10:18 we don’t yet know quite what that means for how it will behave. So we don’t know if that
0:10:23 difference means it’s stronger or it’s weaker or if it will infect different cells or what
0:10:24 that’s going to mean.
0:10:28 So now let’s move on to more of the details of how it spreads and the measurements of
0:10:33 that spread. So first note is that generally the coronavirus has spread through air. They’re
0:10:39 known as zoonotic in that they originate in animals and only sometimes leap to humans.
0:10:43 And there’s been some speculation that this one seemed to originate in bats, but it’s
0:10:48 usually indirect mechanisms. So in mayors, it went from bats to camels before going to
0:10:52 humans. And a couple of papers have commented on the similarity of this new virus to bat
0:10:58 DNA. Like one found that it’s 96% identical. Another journal of medical virology also
0:11:02 observed similar components, but suggested snakes and many other people are skeptical
0:11:06 of that. The long story short is no one really knows, despite having some genomic information
0:11:07 around it.
0:11:11 But it’s interesting to note that important epidemics come from animal sources and some
0:11:15 speculation about the reason for that is that the viruses have time to evolve in their animal
0:11:19 hosts and they’re evolving away from what human hosts have seen before and what their
0:11:21 immune system has been able to recognize before.
0:11:27 So then let’s talk about the spread. A lot of the articles are talking about R0 or R0.
0:11:28 What does it measure?
0:11:33 So R0 is essentially the number of people that you would expect to get infected from
0:11:34 any single case of infection.
0:11:37 So if the R0 is say five, what does that mean?
0:11:41 That means that you should expect that on average, five people will get sick from one
0:11:45 single person that they come into contact with. So for every person that has the disease,
0:11:47 five additional people get the disease.
0:11:52 And interestingly, these are reported as ranges. So like measles has an R0 of 12 to 18.
0:11:57 Yeah. So measles is super infectious. It’s known as sort of the highest or one of the
0:12:01 highest infectiousness variables, which is why it was so important to have vaccines and
0:12:03 herd immunity for measles specifically.
0:12:08 And the reason that it’s reported as ranges is because they depend on the particular population
0:12:10 and the particular moment in time.
0:12:15 So then let’s just talk about some of the facts of the spread. So the 29 exported cases reported
0:12:21 by the World Health Organization, 26 had a travel history from Wuhan city in China.
0:12:24 And then for two of the three cases that were identified in countries outside of China,
0:12:29 one in Australia had direct contact with the confirmed case from Wuhan while in China.
0:12:33 And one in Vietnam had no travel history, but was in contact with the confirmed case.
0:12:35 His father had a travel history to Wuhan.
0:12:39 So what we do know is that human to human transmission is occurring. The preliminary
0:12:42 are not estimate that was presented at the International Health Regulations Emergency
0:12:49 Committee was a range of 1.4 to 2.5, which relatively to the measles example is not as
0:12:54 crazy bad. SARS had an R not between two to five. So that kind of puts that those numbers
0:12:55 in perspective.
0:12:59 It might be a little premature to set these numbers just because the number of cases is
0:13:04 still been relatively low and they haven’t had time to play themselves out. So we don’t
0:13:08 know if there’s many, many cases out there who have not presented symptoms and therefore
0:13:12 we don’t have clear stats on those people.
0:13:17 The big question here is how bad is this epidemic? That’s the question with every epidemic. And
0:13:20 it’s actually so much more complicated than that because there’s a number of different
0:13:24 variables that go into determining how bad something is going to be. It’s very tempting
0:13:29 to put sort of a single number on how bad on a scale of one to 10, for example, but it
0:13:33 doesn’t really take into account all of the nuance in each particular epidemic.
0:13:38 So our not is calculated from the data is actually an aggregate measure. There’s a lot
0:13:41 of different variables that go into our not. So to break them all down into their individual
0:13:44 components and then we can build them back up into our not.
0:13:48 There’s a lot of variables that are going to matter here. One is how well does the virus
0:13:53 transmit itself? So if it’s airborne, it’s able to multiply or transmit itself substantially
0:13:54 more easily.
0:13:59 Right. Versus like exchanging bodily fluids and which requires a lot of specific contact.
0:14:03 Exactly. Another piece is how is it actually getting into the cells? Is it good at infecting
0:14:09 cells? Is it good at its job essentially? Another question is what is the population that it’s
0:14:15 occurring inside of? Is that population moving a lot? Are people coming into very close contact
0:14:20 with each other? So that’s also going to factor in particularly interesting feature of this
0:14:24 is that it happened during Chinese New Year, which is a period of time when a lot of people
0:14:26 in China travel.
0:14:29 So what I think is really interesting to this and having worked at the Gates Foundation and
0:14:35 seen how we think about epidemics on a global scale is that there’s different, there’s two
0:14:39 orthogonal ways to think about an epidemic, which is how much does it spread and then
0:14:41 how bad is it once you get it.
0:14:44 And you’re saying it’s orthogonal or contradictory or why?
0:14:49 So there’s a notion of case fatality, which is for each infection with what likelihood
0:14:53 will the person die from that infection or have like very serious complications. And that’s
0:14:57 actually completely orthogonal to all of the other variables that we talked about before.
0:15:03 One is that if the virus is actually not that deadly or if it expresses itself in a person
0:15:07 after a substantial incubation sign, it might end up creating a bigger epidemic because
0:15:13 that additional time will allow the patient to infect additional individuals. The are
0:15:19 not for that particular virus might be substantially higher, even though its fatality rate is lower.
0:15:23 So it’s an interesting paradox that you could actually have a virus that is less bad once
0:15:26 you get it, but is more bad on the population scale.
0:15:30 So you have to define the metric by which you’re saying whether or not an epidemic is
0:15:34 bad. Is it the number of people who die? Is it the number of people who are infected?
0:15:38 Is it the extent of the spread geographically? There’s a lot of different ways to think about
0:15:40 how bad an epidemic is.
0:15:44 Now let’s just talk about treatments and concrete things that are happening right now.
0:15:48 So just to quickly summarize what’s happening. The CDC is conducting entry skinnings at five
0:15:55 major airports Atlanta, Chicago, Los Angeles, LAX, New York City, JFK and San Francisco.
0:15:58 Doctors are treating symptoms. There’s no vaccine yet. The CDC has developed a real-time
0:16:06 reverse transcription polymerase chain reaction or RRT-PCR test that can diagnose this virus
0:16:08 in respiratory and serum samples.
0:16:15 So what that is is basically a way of seeing if the nucleic acids, if the patient sample
0:16:19 contains the same sequence as the sequence that we know to be involved with the virus
0:16:23 that we know as a part of the virus. So you don’t have to sequence every single patient.
0:16:28 Okay, and then on January 24th, just a few days ago, the CDC publicly posted the assay
0:16:32 protocol for this test and the quote they said, “Currently testing for this virus must
0:16:36 take place at the CDC, but in the coming days and weeks, they will share these tests with
0:16:40 domestic and international partners. And they’re also growing the virus and cell culture, which
0:16:44 is necessary for further studies, including for additional characterization.”
0:16:49 So concretely now from a practical technology point of view, because obviously this is the
0:16:53 serious crisis. There’s a lot to be done and a lot of different players. Where do you sort
0:16:56 of seeing some of the things that might happen that where tech can help?
0:17:01 What’s really interesting about this moment is that because we have this increase in genomic
0:17:08 medicine, just this past weekend, the Coalition for Epidemic Preparedness Innovations, CEPI,
0:17:13 gave out grants to three different pharmaceutical companies of a total of $12.5 million, and
0:17:17 they’re currently engaged in a race. These companies are targeting dates for releasing
0:17:22 their vaccine of between four to 16 weeks from now, which is just totally unheard of.
0:17:27 For a company to spin up a vaccine for the SARS epidemic in 2003 would have taken months
0:17:32 to years for them to develop the new drug and actually get it approved. In this case,
0:17:36 two of these companies made these types of vaccines for other sequences. They’re able
0:17:40 to take what they’ve already built in-house for their other programs, and they can just
0:17:44 very quickly adapt it to this particular virus. All they have to do is create a drop-in replacement
0:17:49 of the sequence that they’ve already worked on with the sequence of this new coronavirus.
0:17:55 Is it fair to say that it’s not dissimilar to engineering in terms of semiconductor and
0:17:58 manufacturing lines? When you say drop-in sequence, does that mean that it’s basically
0:18:03 a matter of using existing scaling methods and you’re just changing the actual code,
0:18:04 quite literally the biological code?
0:18:09 I think that’s actually a really good way of describing it. It’s changing the code,
0:18:12 but you already have the manufacturing line set up. You already know exactly how you’re
0:18:17 going to make this thing. There may be differences, but they will be minimal compared to the differences
0:18:20 that would have existed with a completely different medicine.
0:18:22 Having to bespoke or custom-make it yourself.
0:18:23 Yeah, exactly.
0:18:28 Bottom-line it for me, Judy. How should we think about this news about the coronavirus
0:18:35 still developing? Just to be very clear. Specifically, this is for NCOV 2019. We’ve
0:18:39 covered the high level of what we know and what we don’t know. What would your bottom-line
0:18:42 be from the perspective of a bioengineer?
0:18:46 The bottom-line is that we really need to think about how we are interacting with people,
0:18:51 how we’re traveling, and how we are protecting ourselves from the virus. From my perspective
0:18:57 as a bioengineer, we’ve been talking about how sequencing and synthesis of DNA is becoming
0:19:02 faster and cheaper every single day. This is an example of that in action. This is not
0:19:06 something that would have been possible even a couple of years ago. I think that what we’re
0:19:10 seeing is the beginning of how quickly and how efficiently we’re going to be able to
0:19:16 get to vaccines in the future as we continue to decrease the cost of sequencing and synthesis.
0:19:20 This is a really interesting time because we’re able to figure out the diagnostics piece,
0:19:25 the vaccine piece, and the treatment piece. It’s still in progress, but we have a huge
0:19:26 head start.
0:19:33 Thank you, Judy. For those of you who would like more information, please visit www.cdc.gov/coronavirus.
0:19:38 I’ve also included the link sources for this episode in the show notes, which you can find
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