a16z Podcast - Novel Coronavirus Updates: How Healthcare System, Tests Work; More

Episode Date: February 27, 2020

This episode covers the following -- since our previous deep-dive on the novel coronavirus outbreak -- including:practical implications for the U.S. healthcare system given how it works today, and where we might go in the future — with a16z general partner Julie Yoo, given our vantage point in tech; andhow the rt-PCR test works — with a16z bio partner Judy Savitskaya;…in conversation with Sonal Chokshi.Sources for updates at top:CDC's latest briefing February 26, 2020, transcriptWHO situation report #27  February 25, 2020 [we covered #6 and #25 on previous episodes]Sources for last week's episode:latest numbers: cases in the U.S. (CDC, as of February 17, 2020); global cases (WHO situation report #25, February 14, 2020); spike in diagnosing cases as reported in China (SCMP, Scott Gottlieb)situation & policy statements/reports: CDC summary (as of February 14, 2020); “Annual report on global preparedness for health emergencies”, WHO (Global Preparedness Monitoring Board, 2019)on definitions (of pandemics, endemics), other terms, and various naming conventions: “Understanding pandemics: What they mean, what they don’t mean, and what comes next with the coronavirus”, Helen Branswell, StatNews (February 12, 2020); on disease occurrence and levels (CDC); “misinfodemic“; best practices on naming new human infectious diseases (WHO); qPCR (Keith Robison)image: CDC test kit for COVID-19/ Wikimedia Commons 

Hi, everyone. Welcome to the A6 and Z podcast. I'm Sonal. We've been covering the novel coronavirus and COVID-19 disease on our other show, 16 minutes, which you can find in a separate feed if you haven't subscribed already. But given that the topic of health system preparedness is top of mind right now, and that the latest CDC briefing touched on issues with test kits, the patient perspective of how the U.S. health care system works, with clinicians, calling the Health Department and so on, we're running last week's episode of 16 minutes in this feed because in it we covered how these tests work, how the U.S. healthcare system works today when it comes to epidemics and preparedness and where we might go in the future. As a reminder, you can visit cdc.gov and who.h.o.int for more information,

but as of now, the World Health Organization reported on February 25th that for the first time, since the onset of symptoms of the first identification, case of COVID-19, there have been more new cases reported from countries outside of China than from China, and the CDC reported on February 26th that there's news about community spread, which means that cases of COVID-19 are appearing without and known source of exposure, and those communities currently include Hong Kong, Italy, Iran, Singapore, South Korea, Taiwan, and Thailand. So that's the latest updates. Now onto last week's episode. Hi everyone, welcome to the 23rd episode of 16 Minutes, our show where we cover the headlines

and what's in the news, what's happening, and tease apart what's hype, what's real from our vantage point in tech. I'm Sonal. Today we're doing another update on the topic of coronavirus. We did a deeper dive in episode 21, which you can find in this feed or on our website at a6.c.com slash 16 minutes. Much of that background is still relevant today. But in this episode, we're going to cover two segments. First, we'll do a high-level overview of some of the practical implications for the U.S. healthcare system with A6 and Z Bio-General partner Julie U. And then the second segment is a quick situation update from our previous episode with Judy Savitskaya. As a reminder, all the sources and reports cited in this episode will be included in the show notes. And we are not covering the clinical

infectious disease specifics as we will bring on our other experts for that in an upcoming episode. So that's a context. Now, before we chat, let me quickly share the latest updates, which are that the day after we dropped our last episode, the World Health Organization declared on January 30th that the coronavirus outbreak is a, quote, public health emergency of international concern. And then the day after that, the Health and Human Services Secretary of the United States declared a public health emergency to aid the nation's health care community in responding to the novel coronavirus, which, by the way, was officially named last week. It is now known as COVID-19. And to be clear, that's the name of the disease, not the virus, which as mentioned in our last episode

was known as 2019 NCOV, but is now known as SARS-C-OV-2. And then also, as of last week, a lot happened in a week. The CMS, the U.S. Centers for Medicare and Medicaid Services, developed a new billing code for providers and laboratories to test patients for this virus that causes COVID-19. And we'll share details about how that test works in the second half of this episode, as well as the latest global numbers. But first, now let's cover the U.S. care delivery aspects.

according to the CDC as of February 17th, there are a total of 467 persons under investigation for this in the United States identified across 42 states with 15 confirmed positive for it and 60 pending. So Julie, practically speaking, what's actually happening here in our healthcare system as it works today? What happens when someone walks into a hospital? So it depends a lot on where you're walking into. Most of the time, because our health care system is characterized by such access constraints, you may see a lot of these patients actually showing up in the emergency room. What happens is that they will check in with a registrar essentially and be asked, you know, what is your reason for being here? Typically, they'll also be collecting like your

insurance information. We'll do sort of a physical visual assessment. They might ask some very generic questions. One of the training motions that's happening in hospitals is that people are trying to train those frontline staff to ask questions like, have you traveled to China in the last two weeks, et cetera. And so you have to sort of deploy, you know, field resource to make sure that even though those frontline questions are being asked. Right. I get it. Sort of the difference between a generalist triage model and a more specialist triage model. Exactly. Because that's the biggest blind spot right now. One of the characteristics of this particular virus is that the pre-systimatic period, while you are so contagious, is fairly lengthy. And so that's one of the big sort of gaps right now

is, you know, how do we just identify those people? So after they go through the ER and then what happens? So assuming that people are being appropriately assessed and there is a determination that there's a potential risk that you are a coronavirus patient, you administer the test, again, assuming that the test kits are in supply and based on those results, if the patient is quarantined, and assuming again that they are in an acute care facility that has infrastructure to actually perform an appropriate quarantine, typically those quarantine rooms are what are called negative pressure rooms, which basically means the air in that room is sort of minimal. seepage externally. You're essentially isolating the potential germs and contagion. But again, that sort of begs again the point of, are you showing up at an ED of a facility that actually has all this infrastructure? Many of these patients might just be walking into an urgent care clinic or a primary care clinic. And so oftentimes it might be the case that the patient could get sent home or referred into one of these facilities with further delay, further exposure points, etc. So basically there's a potential for a lot of chaos on the front lines because we don't

clearly understand where the risk points are. And we're sort of waiting for the patients to essentially show up versus being able to be proactive. Right. And how about on the treatment side? So there currently is no treatment for this. My partner Jorge and I, and Jorge being an expert in genomics, oftentimes talk about the areas of medicine and health care where clearly there's an application for technology that makes complete sense, but oftentimes it's the business model component of it that holds things back. What do you guys mean by that? So we have the capabilities to rapidly sequence bugs and other viral forms. And there's, you know, in theory, a capability that says if you are able to quickly identify and rapidly identify in the field, what type of bug you're

dealing with, that you could also synthesize a vaccine on demand based on the fact that we can increasingly print genomic tools and genomic content. That's technically possible right now? The technology exists. It's not yet been deployed into practice. There's still a great degree of validation and testing. Obviously, we have a very rigorous, you know, system through which these types of technology are brought to market with regards to clinical trials and regulation and whatnot. The other piece is historically, vaccines and other types of treatments like this have not been a lucrative area for businesses to go into for a number of reasons. And that's another area that's TBD is, you know, can you actually find the reimbursement path for getting

these products to market? Okay. So where we are right now, it seems like the focus is on what I'm calling the three Gs, gowns, goggles, and gloves. I'm also very interested at a broader level because the World Health Organization did their first annual report on global preparedness for health emergencies. And they basically wrote in their report, just came out last year, and they have targets to September 2020 for progress towards that, that countries, donors, and multilateral institutions must be prepared for the worst. Quote, a rapidly spreading pandemic due to a lethal respiratory pathogen, whether naturally

emergent or accidentally or deliberately released, poses additional preparedness requirements. and that we must ensure adequate investment in developing innovative vaccines and therapeutics, as you talked about, surge manufacturing capacity, an appropriate non-pharmaceutical interventions, et cetera, et cetera. I guess I have two questions for you here. One, where are we as a country from a systemic point on that readiness? And then two, what does it say about where we should be? So this to me is one of the biggest cases to be made for this concept of the unbundling of the hospital. When you look back at the history of how the facility side of healthcare has evolved, hospitals were something that were born in the last, you know, century or so on the premise that if you were to

centralize the scarce resource, the doctors, the clinicians in a central location, that you could get efficiencies. And by the way, also have the infrastructure, like the app, the up-exam required to do like big labs and centralized facilities and high-end procedures and whatnot, not just the people. Exactly. And so, you know, the unfortunate consequence of that is that, yes, you can have these now very high-end facilities that perform very advanced procedures. But where, again, we are forcing the patients to travel outside of their homes, but also get exposed to others who have other illnesses. In fact, hospital-acquired infections are, you know, one of the major contributors to comorbidities for patients who come to these acute care facilities. We are in the middle of flu season,

remember? So you're already having rooms full of patients who suspect that they have some kind of illness. That's kind of like an iconic motion within our healthcare system is that we force patients to come to these central monolithic facilities to get any kind of care versus going to them, making it convenient to them. And actually, it's interesting that when you look back, you know, in the early 1900s, nearly half of health care was actually delivered in the home. Less than 1% of health care is now delivered in the home, even for the most senior and frail patients in America.

Right. And it's also an access issue because it means that people who can't afford or live in big hubs where you can afford these types of high, you know, varying quality. What that's predicated on, though, it requires productization of the types of technologies that you see in these hospital settings in such a way. way that can be decentralized. A great basic but kind of elegant example of this is you see companies, one in particular comes to mind that is doing a connected thermometer. It's marketed towards parents as something that they can use for their kids. And when you look at the back end

of their business, it's basically a data company that is acting as a sentinel to collect information about temperatures in communities and essentially predict when there will be a flu outbreak or a cold outbreak, et cetera. And they actually notified not only the end users, but they have connectivity into schools, churches, other institutions. And you know, you can imagine that a system like that at scale for various types of diseases could actually enable this sort of truly decentralized model. But, you know, that the only way that this can happen is if you have interoperable data systems that can not only collect data from the clinical setting and make it readily available on an ad hoc basis across facilities across the country, but also taken to

to account non-traditional data sources, like these smart devices that are connected in the communities, to augment your visibility across patient populations. Okay, so that's sort of the unbundling of the hospital. In that context, it all comes together, like connects the dots. This is how interoperability and data liquidity and data from unconventional sources and all this stuff comes together. Exactly. That's on the future of where we could go and what the ideal state could be.

What are some of the things that can happen now inside the hospital? There's, I would say, the human elements, the operational elements, and then the technology elements. So on the human side, this is what these organizations are sort of designed to do, is deploy large swaths of human labor in such a way that can sort of react to health care needs. Operationally speaking, we mentioned earlier the logistics of how a patient flows through the hospital. You need to anticipate all the potential entry points that patients are coming in. Hospital these days are health systems, really, and they need to have connectivity into their personal. primary care clinics, their urgent care clinics, et cetera, to really understand systematically what's going on across the network. And now the tech part. That's what I'm most interested in giving

your vantage point. Yeah. Here's what I'm going to, I'm going to say one nice thing about EHRs now. They are literally the primary tool that frontline clinicians are using. You've seen this. Now, hospitals literally interjecting very basic questions into the medical record to prompt them to ask the things that could qualify whether or not a patient might potentially be at risk for coronavirus. So that's where the fact that we now have this broad infrastructure layer laid down can actually provide tremendous value in that you can make one change that does get propagated to all of the endpoints in the care delivery system. So doing things that scale through technology, basically. So bottom line it for me, Julie, how should we think about this in terms of the tech and the

delivery side and preparedness for the epidemic at that level? I think this is shedding light on the fact that we as a healthcare system have many nodes of potential failure when it comes to widespread epidemics and pandemics, but the direction and everything that we've talked about around the notion of decentralization, of unbundling of hospital, of using technology and distributed data streams to be able to be more responsive and nimble is coming to light. And so we will take learning from this and apply towards what the future of healthcare needs to look like. Thank you for joining this segment.

All right. Thank you so much. Now let me introduce Judy Savitskaya on the A6 and Z bio team. Welcome, Judy. Thanks, Sonnell. Okay. So let me just give a quick update on the stats of the disease. This is Piduation Report number 25 from the World Health Organization. We just came out February 14th. Here's the high level summary of the numbers. So globally, there are now 49,053 laboratory confirmed cases. In China, there are 48,548 laboratory confirmed ones. And then outside of China, there are 505 across 24 countries with two debts outside of China. The other thing, though, is there was a huge spike in the numbers, and that was because they will include the number of clinically diagnosed cases into the number of confirmed cases so that patients could receive timely treatment and previously patients could only be diagnosed by test kits. What does this mean scientifically?

Yeah, so these cases have in the past been basically labeled as coronavirus cases, whether they have the right nucleic acid sequence that belongs to that virus. What they're saying now is that they're also going to count anybody who is symptoms. in all the same ways that the virus has been presenting itself in other patients and has the CT scan evidence. So the former FDA Commissioner Scott Gottlieb noted that this is happening because it's in the absence of a PCR test, which we briefly talked about last time. There's an open question about why these are not yet available at scale. But can you give us a little bit more detail about what is the PCR test scientifically? Yeah. So PCR test stands for polymerase chain reaction, basically a way of amplifying a piece of DNA or RNA and nucleic acid by copying it over and over and over

again. What you're doing in this test is basically you're taking a sample from the patient. There's some nucleic acids in there. The sequence is very long, but you take a small sequence of DNA, RNA, whatever you're trying to amplify. This is an RNA virus. So you're trying to bind it with a sequence that you know belongs to that virus. You attach it. It's about 20 bases in length. You use the polymerase chain reaction to extend out that 20 base primer to cover the entire sequence or whatever like piece of the sequence that you're trying to amplify. And then you get many, many copies this way. What does that give you having the many, many copies? Presence or absence, right? So, and amounts. It's called real-time PCR. I actually don't love the name. I think QPCR is a better name for this, quantitative

PCR, because it's telling you how many pieces of, essentially, like, what is the viral load in the bloodstream, or the load of whatever pathogen you're looking for. So Keith Robeson, who's currently principal scientist at Ginkgo, wrote about, you know, how some of these tests work. And he basically agrees with you that it should be called QPCR because as you note, what you're basically describing is it's quantitative. Yeah. And real time doesn't really mean much. There's another critical reason why people don't like RT PCR is because there's a completely different concept that is called reverse transcriptase PCR. That's why it's kind of hard to talk about this with this virus because it's an RNA virus. Right. In fact, he also talks about the fact that

PCR works with DNA, but yet you're telling me coronavirus is RNA. So can you help explain that distinction? Absolutely. So in this reaction, what you're doing is using a polymerase that is used to binding either DNA or RNA and then extending it. So in the case of the RNA viruses, you need the reverse transcriptase. So this is a weirdo polymerase that binds RNA templates and then extends and produces DNA. And the reason that you want DNA is that it's really stable. We have a ton of ways to measure it. RNA is a little bit more fickle.

So if you can turn this RNA signature, this RNA message into a DNA output that actually substantially simplifies downstream processing. So this reverse transcriptase piece is what is doing the RNA to DNA translation. Okay. So we've talked about what's going on in the test. Let's quickly talk about some of the differences from what we last talked about. We talked about R not last time, which is really practically how many people, a newly infected person is likely to pass the virus onto.

And you explained what variables go into it. What is your take on where we are with the R not? Yeah. We just talked about the spike, the definition of what this disease is. Like, is it the viral load or is it like these symptoms? that's changing as well. So I still think it's too early to calculate an R-Not. There's still a ton of cases out there that are not showing symptoms, so we can't really calculate the number of people who have gotten infected. I think we have technically approached the point where it is a pandemic,

although the definition for pandemic is quite loose. The World Health Organization defines it as a worldwide spread of a new disease. The Centers for Disease Control and Prevention, the CDC and the U.S. have a bit looser of a definition describing as a disease that spreads across regions, and quote from the CDC website is the fact that this virus has caused illness, including illness resulting in death and sustained person-to-person spread in China is concerning. These factors meet two of the criteria of a pandemic. And by the way, people want to read an excellent piece. Helen Branswell, and I mentioned her in our last episode, has a great piece in stat news with the headline, quote, understanding pandemics,

what they mean, don't mean, and what comes next with the coronavirus? From your take, why is it so freaking confusing. The term pandemic is not particularly useful in this case because it only tells you about the geographical spread. It's not actually telling you about the danger of the disease. Like flu is a global pandemic annually. But the term doesn't necessarily mean, you know, very fatal or spreads very fast. It just means it's been into more than two geographies outside of its original origin. So if a flu is a pandemic, that's also endemic in that it is in our population and circulates. Can you actually explain endemic because my understanding of the word comes from like understanding evolution and Darwin and knowing about endemic species in the Galapagos. Yeah. What does that mean?

So endemic is a more useful term than pandemic. It's something that is going to live in a latent way in the in the population or in the environment. We should see it returning flu as the quintessential example of this. It's still an open question as to whether this coronavirus is going to become endemic. Okay. So that's the difference between pandemics, endemic, and add one more name to the list, which is mis-infodemic. I've heard a lot of people describing this potentially as an infodemic because of the spread of some fantastic rapid science, which you talked about last time,

but there's also a spread of misinformation as well. And so the two of these things are going hand in hand. There's a group that has already published an epidemiological model of what they expect the spread to be. Again, if any of the data that's going into there is either intentionally falsified or it is just too early, we don't have good enough data. It's incomplete.

Or like the measurements have changed, right? So in the middle of this, of last week, the way that Chinese hospitals were measuring cases changed. So that's going to mess up the data pretty substantially. So I think that these models are going to suffer if garbage in, garbage out, if this infodemic issue continues. Okay. So beyond the numbers and the definition, let's quickly talk about some of the weightings. According to the World Health Organization, some of the data from China last before this big spike suggested that 82% of confirmed cases have only mild infection. About 15% are severe enough to require hospital care and about 3% need intensive care.

And the preliminary data suggested that roughly 2% of the people who tested positive for the virus have died. And that's important because last time we reported the CFR or the case fatality rates, which for SARS was at 10% and for Mares, it was actually 37% in Saudi Arabia, but 34% outside of that region. So last time you talked about the paradox between deadliness and the R-Not, what's your updates? if any on that. So the reason for that is that you can't really have a high fatality rate and a fast-spreading virus. Basically, dead people can't spread the disease and people who are, you know, confined to their beds also can't spread the disease as fast. But there's another variable, which is incubation time. So this is the length of time that it takes for the infection to demonstrate some symptoms. And then

there's a different period of time that's called the latent period, which is the time between getting infected and becoming infectious. So these are two different variables. And these interplay in a really interesting way. If the latent time is really short, so you are infectious almost as soon as you've been infected, but the incubation time is long, you have no idea that you're infected. You have no symptoms. You feel completely normal, but it turns out that you're actually spreading the virus. So in that case, this sort of paradox between the case fatality and the spread rate is going to break because you can start spreading without actually having symptoms. It's also probably too early to tell what the exact incubation period is going to be. Most estimates I've seen

have topped out at about 14 days, but that's still pretty long. So it's something to definitely take into consideration. Okay, so bottom line it for me. Where are we now in the situation update from the news and your perspective? So the bottom line is it's still too early to put hard numbers on any of these facts. It's important to keep track of where the cases are coming up, where they're being reported, but don't dump any conclusions about case fatality rates, about are nots, because it's just too early. Other than that, the same precautions apply. Thank you for joining the segment. Thanks so much, Sennell.