Novel Coronavirus Updates: How Healthcare System, Tests Work; More

0:00:07 Hi everyone, welcome to the A6NZ podcast, I’m Sonal.
0:00:12 We’ve been covering the novel coronavirus and COVID-19 disease on our other show, 16
0:00:16 Minutes, which you can find in a separate feed if you haven’t subscribed already, but
0:00:22 given that the topic of health system preparedness is top of mind right now and that the latest
0:00:28 CDC briefing touched on issues with test kits, the patient perspective of how the U.S. health
0:00:32 care system works, with clinicians calling the health department and so on, we’re running
0:00:38 last week’s episode of 16 Minutes in this feed because in it we covered how these tests
0:00:44 work, how the U.S. health care system works today when it comes to epidemics and preparedness
0:00:46 and where we might go in the future.
0:00:54 As a reminder, you can visit cdc.gov and who.int for more information, but as of now, the World
0:00:58 Health Organization reported on February 25th that for the first time since the onset of
0:01:04 symptoms of the first identified case of COVID-19, there have been more new cases reported from
0:01:09 countries outside of China than from China, and the CDC reported on February 26th that
0:01:15 there’s news about community spread, which means that cases of COVID-19 are appearing
0:01:18 without a known source of exposure.
0:01:23 And those communities currently include Hong Kong, Italy, Iran, Singapore, South Korea,
0:01:25 Taiwan, and Thailand.
0:01:29 So that’s the latest updates, now onto last week’s episode.
0:01:34 Hi everyone, welcome to the 23rd episode of 16 Minutes, our show where we cover the headlines
0:01:38 and what’s in the news, what’s happening, and tease apart what’s hype, what’s real
0:01:39 from our vantage point in tech.
0:01:41 I’m Sonal.
0:01:44 Today we’re doing another update on the topic of coronavirus.
0:01:48 We did a deeper dive in episode 21, which you can find in this feed or on our website
0:01:51 at a6nz.com/16minutes.
0:01:55 Much of that background is still relevant today, but in this episode we’re going to
0:01:56 cover two segments.
0:02:00 First, we’ll do a high-level overview of some of the practical implications for the U.S.
0:02:05 healthcare system with a6nz.bio general partner Julie Yu, and then the second segment is a
0:02:09 quick situation update from our previous episode with Judy Svitskaya.
0:02:12 As a reminder, all the sources and reports cited in this episode will be included in
0:02:16 the show notes, and we are not covering the clinical infectious disease specifics as we
0:02:20 will bring on our other experts for that in an upcoming episode.
0:02:21 So that’s a context.
0:02:25 Now before we chat, let me quickly share the latest updates, which are that the day after
0:02:30 we dropped our last episode, the World Health Organization declared on January 30th that
0:02:34 the coronavirus outbreak is a, quote, “public health emergency of international concern.”
0:02:37 And then the day after that, the Health and Human Services Secretary of the United States
0:02:41 declared a public health emergency to aid the nation’s healthcare community in responding
0:02:45 to the novel coronavirus, which, by the way, was officially named last week.
0:02:48 It is now known as COVID-19.
0:02:52 And to be clear, that’s the name of the disease, not the virus, which, as mentioned in our
0:02:58 last episode, was known as 2019 NCOV, but is now known as SARS-CoV-2.
0:03:03 And then also, as of last week, a lot happened in a week, the CMS, the U.S. Centers for
0:03:08 Medicare and Medicaid Services, developed a new billing code for providers and laboratories
0:03:12 to test patients for this virus that causes COVID-19.
0:03:16 And we’ll share details about how that test works in the second half of this episode, as
0:03:18 well as the latest global numbers.
0:03:22 But first, now let’s cover the U.S. care delivery aspects.
0:03:28 According to the CDC, as of February 17th, there are a total of 467 persons under investigation
0:03:34 for this in the United States, identified across 42 states, with 15 confirmed positive
0:03:36 for it and 60 pending.
0:03:40 So Julie, practically speaking, what’s actually happening here in our health care system as
0:03:41 it works today?
0:03:43 What happens when someone walks into a hospital?
0:03:47 So it depends a lot on where you’re walking into.
0:03:53 Most of the time, because our health care system is characterized by such access constraints,
0:03:56 you may see a lot of these patients actually showing up in the emergency room.
0:04:01 What happens is that they will check in with a registrar, essentially, and be asked, “What
0:04:02 is your reason for being here?”
0:04:05 Typically, they’ll also be collecting your insurance information.
0:04:07 You will do a physical visual assessment.
0:04:09 They might ask some very generic questions.
0:04:14 One of the training motions that’s happening in hospitals is that people are trying to
0:04:18 train those frontline staff to ask questions like, “Have you traveled to China in the last
0:04:19 two weeks?”
0:04:20 Et cetera.
0:04:24 And so you have to deploy field resource to make sure that even those frontline questions
0:04:25 are being asked.
0:04:26 Right.
0:04:27 I get it.
0:04:30 Sort of the difference between a generalist triage model and a more specialist triage
0:04:31 model.
0:04:32 Exactly.
0:04:33 Because that’s the biggest blind spot right now.
0:04:36 One of the big risks of this particular virus is that the pre-syntomatic period while you
0:04:39 are still contagious is fairly lengthy.
0:04:42 And so that’s one of the big sort of gaps right now is, you know, how do we just identify
0:04:43 those people?
0:04:46 So after they go through the ER and then what happens?
0:04:51 So assuming that people are being appropriately assessed and there is a determination that
0:04:56 there’s a potential risk that you are a coronavirus patient, you administer the test, again, assuming
0:05:00 that the test kits are in supply and based on those results.
0:05:05 If the patient is quarantined and assuming, again, that they are in an acute care facility
0:05:10 that has infrastructure to actually perform an appropriate quarantine, typically those
0:05:14 quarantine rooms are what are called negative pressure rooms, which basically means the
0:05:18 air in that room is sort of minimal seepage externally.
0:05:21 You’re essentially isolating the potential germs and contagion.
0:05:26 But again, that sort of begs again the point of, “Are you showing up at an ED of a facility
0:05:28 that actually has all this infrastructure?”
0:05:32 Many of these patients might just be walking into an urgent care clinic or a primary care
0:05:33 clinic.
0:05:37 And so oftentimes it might be the case that the patient could get sent home or referred
0:05:41 into one of these facilities with further delay, further exposure points, et cetera.
0:05:46 So basically there’s a potential for a lot of chaos on the front lines because we don’t
0:05:49 clearly understand where the risk points are.
0:05:53 And we’re sort of waiting for the patients to essentially show up versus being able to
0:05:54 be proactive.
0:05:55 Right.
0:05:56 And how about on the treatment side?
0:05:57 So there currently is no treatment for this.
0:06:02 My partner Jorge and I, and Jorge being an expert in genomics, oftentimes talk about the
0:06:07 areas of medicine and healthcare where clearly there’s an application for technology that
0:06:11 makes complete sense, but oftentimes it’s the business model component of it that holds
0:06:12 things back.
0:06:13 What do you guys mean by that?
0:06:19 So we have the capabilities to rapidly sequence bugs and other viral forms.
0:06:25 And there’s in theory a capability that says if you are able to quickly identify and rapidly
0:06:30 identify in the field, what type of bug you’re dealing with, that you could also synthesize
0:06:36 a vaccine on demand based on the fact that we can increasingly print genomic tools and
0:06:37 genomic content.
0:06:38 That’s technically possible right now?
0:06:39 The technology exists.
0:06:41 It’s not yet been deployed into practice.
0:06:45 There’s still a great degree of validation and testing.
0:06:49 Obviously we have a very rigorous system through which these types of technology are brought
0:06:53 to market with regards to clinical trials and regulation and whatnot.
0:06:58 The other piece is historically vaccines and other types of treatments like this have not
0:07:03 been a lucrative area for businesses to go into for a number of reasons.
0:07:08 And that’s another area that’s TBD is can you actually find the reimbursement path for
0:07:09 getting these products to market?
0:07:10 Okay.
0:07:13 So where we are right now, it seems like the focus is on what I’m calling the 3Gs, gowns,
0:07:14 goggles, and gloves.
0:07:19 I’m also very interested at a broader level because the World Health Organization did their
0:07:22 first annual report on global preparedness for health emergencies.
0:07:25 They basically wrote in their report, just came out last year, and they have targets
0:07:30 to September 2020 for progress towards that, that countries, donors, and multilateral institutions
0:07:35 must be prepared for the worst, quote, “A rapidly spreading pandemic due to a lethal
0:07:40 respiratory pathogen, whether naturally emergent or accidentally or deliberately released,
0:07:44 poses additional preparedness requirements, and that we must ensure adequate investment
0:07:48 in developing innovative vaccines and therapeutics as you talked about, surge manufacturing capacity,
0:07:51 appropriate non-pharmaceutical interventions, et cetera, et cetera.”
0:07:53 I guess I have two questions for you here.
0:07:58 One, where are we as a country from a systemic point on that readiness?
0:08:01 And then two, what does it say about where we should be?
0:08:05 So this to me is one of the biggest cases to be made for this concept of the unbundling
0:08:06 of the hospital.
0:08:12 When you look back at the history of how the facility side of healthcare has evolved, hospitals
0:08:16 were something that were born in the last century or so on the premise that if you were
0:08:21 to centralize the scarce resources, the doctors, the clinicians in a central location that
0:08:22 you could get efficiencies.
0:08:27 And by the way, also have the infrastructure, like the op-ex and cap-ex required to do big
0:08:30 labs and centralize the facilities and high-end procedures.
0:08:31 Right.
0:08:32 Exactly.
0:08:33 Not just the people.
0:08:34 Exactly.
0:08:37 And so the unfortunate consequence of that is that, yes, you can have these now very
0:08:41 high-end facilities that perform very advanced procedures, but where, again, we are forcing
0:08:45 the patients to travel outside of their homes, but also get exposed to others who have other
0:08:46 illnesses.
0:08:51 In fact, hospital-acquired infections are one of the major contributors to comorbidities
0:08:53 for patients who come to these acute care facilities.
0:08:56 We are in the middle of flu season, remember?
0:08:57 Yes.
0:09:01 So you’re already having rooms full of patients who suspect that they have some kind of illness.
0:09:05 That’s kind of like an iconic motion within our healthcare system is that we force patients
0:09:11 to come to these central monolithic facilities to get any kind of care versus going to them,
0:09:12 making it convenient to them.
0:09:16 And actually, it’s interesting that when you look back in the early 1900s, nearly half
0:09:19 of healthcare was actually delivered in the home.
0:09:22 Less than 1% of healthcare is now delivered in the home, even for the most senior and
0:09:24 frail patients in America.
0:09:25 Right.
0:09:28 And it’s also an access issue, because it means that people who can’t afford or live
0:09:33 in big hubs where you can afford these types of high, varying quality.
0:09:38 What that’s predicated on, though, it requires productization of the types of technologies
0:09:42 that you see in these hospital settings in such a way that can be decentralized.
0:09:47 A great basic but kind of elegant example of this is you see companies, one in particular
0:09:50 comes to mind that is doing a connected thermometer.
0:09:53 It’s marketed towards parents as something that they can use for their kids.
0:09:58 And when you look at the back end of their business, it’s basically a data company that
0:10:03 is acting as a sentinel to collect information about temperatures in communities and essentially
0:10:07 predict when there will be a flu outbreak or a cold outbreak, et cetera.
0:10:12 And they actually notify not only the end users, but they have connectivity into schools,
0:10:14 churches, other institutions.
0:10:19 And you can imagine that a system like that at scale for various types of diseases could
0:10:22 actually enable this sort of truly decentralized model.
0:10:27 But the only way that this can happen is if you have interoperable data systems that can
0:10:32 not only collect data from the clinical setting and make it readily available on an ad hoc
0:10:37 basis and across facilities across the country, but also take into account non-traditional
0:10:41 data sources like these smart devices that are connected in the communities to augment
0:10:44 your visibility across patient populations.
0:10:45 Okay.
0:10:47 So that’s sort of the unbundling of the hospital.
0:10:51 In that context, it all comes together like connects the dots.
0:10:56 This is how interoperability and data liquidity and data from unconventional sources and all
0:10:58 this stuff comes together.
0:11:01 That’s on the future of where we could go and what the ideal state could be.
0:11:04 What are some of the things that can happen now inside the hospital?
0:11:07 There’s, I would say, the human elements, the operational elements, and then the technology
0:11:08 elements.
0:11:14 So on the human side, this is what these organizations are sort of designed to do is deploy large
0:11:19 swaths of human labor in such a way that can sort of react to healthcare needs.
0:11:24 Operationally speaking, we mentioned earlier the logistics of how a patient flows through
0:11:25 the hospital.
0:11:28 You need to anticipate all the potential entry points that patients are coming in.
0:11:32 The hospital these days are health systems, really, and they need to have connectivity
0:11:37 into their primary care clinics, their urgent care clinics, et cetera, to really understand
0:11:40 systematically what’s going on across the network.
0:11:41 And now the tech part.
0:11:42 That’s what I’m most interested in given your vantage point.
0:11:43 Yeah.
0:11:44 Here’s what I’m going to say.
0:11:48 One nice thing about EHRs now, they are literally the primary tool that frontline clinicians
0:11:50 are using.
0:11:56 You’ve seen this now, hospitals literally interjecting very basic questions into the medical record
0:12:01 to prompt them to ask the things that could qualify whether or not a patient might potentially
0:12:03 be at risk for coronavirus.
0:12:08 So that’s where the fact that we now have this broad infrastructure layer laid down can
0:12:12 actually provide tremendous value in that you can make one change that does get propagated
0:12:15 to all of the endpoints in the care delivery system.
0:12:17 So doing things at scale through technology, basically.
0:12:22 So bottom line for me, Julie, how should we think about this in terms of the tech and
0:12:26 the delivery side and preparedness for the epidemic at that level?
0:12:31 I think this is shedding light on the fact that we as a healthcare system have many nodes
0:12:37 of potential failure when it comes to widespread epidemics and pandemics, but the direction
0:12:42 and everything that we’ve talked about around the notion of decentralization, of unbundling
0:12:48 of hospital, of using technology and distributed data streams to be able to be more responsive
0:12:51 and nimble is coming to light.
0:12:54 And so we will take learnings from this and apply it towards what the future of healthcare
0:12:55 needs to look like.
0:12:56 Thank you for joining this segment.
0:12:57 All right.
0:12:58 Thank you so much.
0:13:01 Now let me introduce Judy Savitskaya on the A6NZ Bio team.
0:13:02 Welcome, Judy.
0:13:03 Thanks, Donald.
0:13:04 Okay.
0:13:07 So let me just give a quick update on the stats of the disease.
0:13:11 This is Situation Report Number 25 from the World Health Organization.
0:13:13 We just came out February 14th.
0:13:16 Here’s the high-level summary of the numbers.
0:13:21 So globally, there are now 49,053 laboratory-confirmed cases.
0:13:26 In China, there are 48,548 laboratory-confirmed ones.
0:13:31 And then outside of China, there are 505 across 24 countries with two deaths outside of China.
0:13:35 The other thing, though, is there was a huge spike in the numbers.
0:13:39 And that was because they will include the number of clinically diagnosed cases into
0:13:43 the number of confirmed cases so that patients could receive timely treatment.
0:13:46 And previously, patients could only be diagnosed by test kits.
0:13:47 What does this mean scientifically?
0:13:48 Yeah.
0:13:53 So these cases have in the past been basically labeled as coronavirus cases, whether they
0:13:56 have the right nucleic acid sequence that belongs to that virus.
0:14:01 What they’re saying now is that they’re also going to count anybody who is symptomatic
0:14:05 in all the same ways that the virus has been presenting itself in other patients and has
0:14:06 the CT scan evidence.
0:14:11 So the former FDA commissioner, Scott Gottlieb, noted that this is happening because it’s
0:14:14 in the absence of a PCR test, which we briefly talked about last time.
0:14:18 There’s an open question about why these are not yet available at scale.
0:14:21 But can you give us a little bit more detail about what is the PCR test scientifically?
0:14:22 Yeah.
0:14:27 So PCR test stands for polymerase chain reaction, basically with amplifying a piece of DNA or
0:14:31 RNA nucleic acid by copying it over and over and over again.
0:14:35 What you’re doing in this test is basically you’re taking a sample from the patient.
0:14:37 There’s some nucleic acids in there.
0:14:41 The sequence is very long, but you take a small sequence of DNA, RNA, whatever you’re
0:14:43 trying to amplify.
0:14:44 This is an RNA virus.
0:14:49 So you’re trying to bind it with a sequence that you know belongs to that virus.
0:14:52 You attach it, it’s about 20 bases in length.
0:14:56 You use the polymerase chain reaction to extend out that 20 base primer to cover the entire
0:15:00 sequence or whatever like piece of the sequence that you’re trying to amplify.
0:15:02 And then you get many, many copies this way.
0:15:04 What does that give you having the many, many copies?
0:15:05 Surveillance or absence, right?
0:15:08 So, and amounts, it’s called real time PCR.
0:15:09 I actually don’t love the name.
0:15:14 I think QPCR is a better name for this quantitative PCR because it’s telling you how many pieces
0:15:18 of essentially like what is the viral load in the bloodstream or the load of whatever
0:15:20 pathogen you’re looking for.
0:15:24 So Keith Robison, who’s currently principal scientist at Ginkgo wrote about, you know,
0:15:25 how some of these tests work.
0:15:30 And he basically agrees with you that it should be called QPCR because as you note, what you’re
0:15:31 basically describing as it’s quantitative.
0:15:32 Yeah.
0:15:33 And real time doesn’t really mean much.
0:15:38 But there’s another critical reason why people don’t like RT-PCR is because there’s a completely
0:15:41 different concept that is called reverse transcriptase PCR.
0:15:44 That’s why it’s kind of hard to talk about this with this virus because it’s an RNA virus.
0:15:45 Right.
0:15:48 In fact, he also talks about the fact that PCR works with DNA.
0:15:52 But yet you’re telling me coronavirus is RNA, so can you help explain that distinction?
0:15:53 Absolutely.
0:15:58 So in this reaction, what you’re doing is using a polymerase that is used to binding either
0:16:00 DNA or RNA and then extending it.
0:16:04 So in the case of the RNA viruses, you need the reverse transcriptase.
0:16:10 So this is a weirdo polymerase that binds RNA templates and then extends and produces
0:16:11 DNA.
0:16:13 And the reason that you want DNA is that it’s really stable.
0:16:15 We have a ton of ways to measure it.
0:16:17 RNA is a little bit more fickle.
0:16:23 So if you can turn this RNA signature, this RNA message into a DNA output that actually
0:16:26 substantially simplifies downstream processing.
0:16:30 So this reverse transcriptase piece is what is doing the RNA to DNA translation.
0:16:31 Okay.
0:16:33 So we’ve talked about what’s going on in the test.
0:16:36 Let’s quickly talk about some of the differences from what we last talked about.
0:16:41 We talked about R0 last time, which is really practically how many people, a newly infected
0:16:46 person is likely to pass a virus on to and you explained what variables go into it.
0:16:48 What is your take on where we are with the R0?
0:16:49 Yeah.
0:16:52 We just talked about the spike, the definition of what this disease is.
0:16:55 Is it the viral load or is it like these symptoms?
0:16:56 That’s changing as well.
0:16:59 So I still think it’s too early to calculate an R0.
0:17:04 There’s still a ton of cases out there that are not showing symptoms, so we can’t really
0:17:06 calculate the number of people who have gotten infected.
0:17:11 I think we have technically approached the point where it is a pandemic, although the
0:17:13 definition for pandemic is quite loose.
0:17:17 The World Health Organization defines it as a worldwide spread of a new disease.
0:17:21 The Centers for Disease Control and Prevention, the CDC and the U.S. have a bit looser of
0:17:25 a definition describing as a disease that spreads across regions.
0:17:29 And quote from the CDC website is the fact that this virus has caused illness, including
0:17:35 illness resulting in death and sustained person-to-person spread in China is concerning.
0:17:39 These factors meet two of the criteria of a pandemic.
0:17:41 And by the way, people want to read an excellent piece.
0:17:45 Helen Branswell, and I mentioned her in our last episode, has a great piece in stat news
0:17:49 with the headline quote, “Undershining Pandemics, What They Mean, Don’t Mean, and What Comes
0:17:51 Next with the Coronavirus.”
0:17:53 From your take, why is it so freaking confusing?
0:17:58 The term pandemic is not particularly useful in this case because it only tells you about
0:17:59 the geographical spread.
0:18:02 It’s not actually telling you about the danger of the disease.
0:18:07 Like flu is a global pandemic annually, but the term doesn’t necessarily mean, you know,
0:18:09 very fatal or spreads very fast.
0:18:13 It just means it’s been into more than two geographies outside of its original origin.
0:18:20 So if a flu is a pandemic, that’s also endemic in that it is in our population and circulates.
0:18:22 Can you actually explain endemic?
0:18:25 Because my understanding of the word comes from like understanding evolution and Darwin
0:18:28 and knowing about endemic species and the Galapagos.
0:18:29 Yeah.
0:18:30 What does that mean?
0:18:32 So endemic is a more useful term than pandemic.
0:18:37 It’s something that is going to live in a latent way in the population or in the environment.
0:18:41 We should see a returning flu as the quintessential example of this.
0:18:45 It’s still an open question as to whether this coronavirus is going to become endemic.
0:18:46 Okay.
0:18:49 So that’s the difference between pandemics, endemic, and add one more name to the list,
0:18:50 which is misinfodemic.
0:18:56 I’ve read a lot of people describing this potentially as an infodemic because of the
0:19:00 spread of some fantastic rapid science, which you talked about last time, but there’s also
0:19:03 a spread of misinformation as well.
0:19:05 And so the two of these things are going hand in hand.
0:19:08 There’s a group that has already published an epidemiological model of what they expect
0:19:09 the spread to be.
0:19:15 Again, if any of the data that’s going into there is either intentionally falsified or
0:19:17 it is just too early.
0:19:18 Incomplete.
0:19:19 We don’t have good enough data.
0:19:21 Or like the measurements have changed, right?
0:19:26 So in the middle of last week, the way that Chinese hospitals were measuring cases changed.
0:19:29 So that’s going to mess up the data pretty substantially.
0:19:33 So I think that these models are going to suffer if garbage in, garbage out.
0:19:35 If this infodemic issue continues.
0:19:36 Okay.
0:19:40 So beyond the numbers and the definition, let’s quickly talk about some of the weightings.
0:19:44 According to the World Health Organization, some of the data from China last before this
0:19:50 big spike suggested that 82% of confirmed cases have only mild infection.
0:19:56 About 15% are severe enough to require hospital care and about 3% need intensive care.
0:19:59 And then preliminary data suggested that roughly 2% of the people who tested positive for the
0:20:00 virus have died.
0:20:05 And that’s important because last time we reported the CFR, the case fatality rates,
0:20:07 which for SARS was at 10%.
0:20:14 And for MERS, it was actually 37% in Saudi Arabia, but 34% outside of that region.
0:20:18 So last time you talked about the paradox between deadliness and the R0.
0:20:20 What’s your updates, if any, on that?
0:20:25 So the reason for that is that you can’t really have a high fatality rate and a fast
0:20:26 spreading virus.
0:20:30 Basically, dead people can’t spread the disease and people who are, you know, confined to
0:20:32 their beds also can’t spread the disease as fast.
0:20:35 But there’s another variable, which is incubation time.
0:20:41 So this is the length of time that it takes for the infection to demonstrate some symptoms.
0:20:44 And there’s a different period of time that’s called the latent period, which is the time
0:20:49 between getting infected and becoming infectious.
0:20:50 So these are two different variables.
0:20:52 And these interplay in a really interesting way.
0:20:56 If the latent time is really short, so you are infectious almost as soon as you’ve been
0:21:00 infected, but the incubation time is long, you have no idea that you’re infected.
0:21:02 You have no symptoms.
0:21:05 You feel completely normal, but it turns out that you’re actually spreading the virus.
0:21:10 So in that case, this sort of paradox between the case fatality and the spread rate is going
0:21:14 to break because you can start spreading without actually having symptoms.
0:21:18 It’s also probably too early to tell what the exact incubation period is going to be.
0:21:22 Most estimates I’ve seen have topped out at about 14 days, but that’s still pretty long.
0:21:25 So it’s something to definitely take into consideration.
0:21:26 Okay.
0:21:30 So bottom line it for me, where are we now in the situation update from the news and
0:21:31 your perspective?
0:21:35 So the bottom line is it’s still too early to put hard numbers on any of these facts.
0:21:40 It’s important to keep track of where the cases are coming up, where they’re being reported,
0:21:44 and don’t jump to any conclusions about case fatality rates, about R knots, because it’s
0:21:46 just too early.
0:21:49 Other than that, the same precautions apply.
0:21:50 Thank you for joining the segment.