Dominic Suciu - COVID-19, Epidemiology and Informatics

I'm Dominic Succi I am a machine learning and bioinformatics researcher in Seattle I've spent the last twenty years half in biotech half in half in machine learning Big Data things like that and I my talk is gonna be on the epidemiology and informatics but specifically in the context of the Cova 19 outbreak what I'm trying to show is how a quote-unquote digitally transformed world would what this what this pandemic and how any pandemic would look like in a digitally transformed world so how do I get the mouse to work if you guys can click the do I have control of the mouse ah here we go yes so what I'm gonna be talking to you guys about as we watched this very alarming video go by what I'm gonna be my talk is I'm gonna tell you about what we should have been doing the past ten years and what we should be doing in the future and what we can do once that what we're have to do now that we're in the middle of a pandemic so as you this ends it goes up to around 28 remember this ended about a month ago and it goes to about 40,000 that's that's back at the beginning of February we're at eighty thousand cases and Counting and 3,000 deaths but this kind of shows you a little bit I found this on the web there's a reference for it if you guys want to look for it but this kind of shows you how coronavirus is compared to other ones now watch what happens at this point so our old friend influenza comes up and we can see that despite the fact that SARS is really bad swine flu is still the biggest one and that's because it has such a huge reservoir in the not just it really a lot of that has to do with the the animals that it lives in that pass it on the most this is Spanish flu just for a little perspective okay we can go back to the main slide so maybe I should have brought a sickle [Laughter] so it's not that bad one of the issues with so one thing I should say about influenza is that let me go back because I don't want you guys to see this yet so one of the issues with influenza is the receptor that it uses to make entry into the cell the the receptor for both the really dangerous form of influenza and then not so dangerous form of influenza are in the lungs the one in corona virus isn't a mouse so you have it on your tongue you have it on the roof of your mouth in the mucosa that's why it's so important to wash your hands not get stuff in your mouth you don't have to breathe it in with seasonal influenza if you breathe it really deeply that's where the receptors are in the human body with the really the pandemic form of influenza if you breathe it in your upper respiratory tract that's where the receptors are the DAP strain recognizes it's all about how it gets into you it's what affects your walking into a room in which there's a viral particle what the efficiency of those actually entering your body so Corona while it's very bad if influenza had that same receptor we'd be in a lot more trouble just because if it's where it is so let's go to the next slide so I want to give you a little bit of perspective so I'm going to start with a little history of viruses and I mean like virus like life forms have been around for billions of years I mean they were here before us in fact the correct way of thinking about it is that it's we are the actual invader not the other way around like cellular life forms came into a world in which they were viruses and there has been a constant battle between us and them ever since if you want to see what that battle really looked like especially early on you can look at bacteria and the viral pathogens of bacteria called phages and a very good place to look for that is in the therm of on the hot water pools in Yellowstone there's a group at Montana University that studies them and what they do is they look they basically monitor the water and what they see is every month or so there's this big bacterial bloom and then everything dies they look in the illness in the in the pool and they find phage sequence and then what they started to find was that phage sequin would show up inside the genome of the bacteria and they realized that there was a mechanism and if you think about it it's kind of like an immune memory for bacteria a really ancient memory system for bacteria and they realized that there was a mechanism that would take that sequence go through the cell find the copies of it and kill it and it was the cells anti antiviral mechanism so echoes of this battle appear throughout the tree of life from restriction enzymes which are used for genetic engineering to mRNA in humans mRNA in humans is a form of the CRISPR system and even the nucleus itself there still are a lot of viruses that I mean the development of the nucleus if you think about it and evolution was really done to protect the cells from from virus so right now if we look in the in GenBank there's around 1700 sequence viral genomes that you could look at but if you look at the actual sequences there's millions just in the viral space so when you go into a doctor claiming that you have flu-like symptoms you usually get diagnosed with the common cold but the reality the common cold can be one of six families of different diseases the two up top are the nastiest of the two or thermomix virus which is the influenza and if you look at the number of sequences that have been isolated that have been isolated for them you kind of get an idea of what the genbank and what the CDC and what the health community thinks is important so the the issue is that because it doesn't affect how you get treated by your doctor there isn't really good monitoring so you can go in to your doctor and no one really knows exactly what you have all these things are circulating in the population but no one really understands exactly how much of each one there is and we really need better monitoring than that I used to work with a guy named Rob Lance EOD from the CDC and he was the world expert on West Nile virus his daughter one day got sick and he went and tested her and surprise surprise I mean he had one of the few tests for that strain of West Nile in the world because he was developing it and his daughter actually came out positive I thought I don't think it was the it was the one that was epidemic but it was a strain of the West Nile virus so what he taught me years ago is that these things there's a lot these things are these rare pathogens are actually a lot more common they're all over the place if we had good monitoring of them we would be able to respond to pandemics a lot better so Co vid this is what we do with sequence data and I'm going to give you kind of a quick view of you know why sequencing data is important how we help we can get actionable information from it so the graph this is the viral particle there's different parts of the viral particle the important ones the MNS are in the right-hand section in this little this guy the important parts are right there and you can see that some of it is conserved there's a big dip these are previous forms of corona virus this paper came out like a week ago okay the hundred percent line is Koh vyd 19 the one that's infecting everybody right now the blue line is the bat virus that was isolated about six months ago in China by Chinese researchers that were looking for it and they were studying it because other corona viruses that come out of those same areas back in 2003 when the first stars the important thing was this once they had a sample within a few days they had the whole sequence all 39,000 genomes in 2003 you didn't have that ability your sequencing rate we know we had this talk earlier today about how you know there was a big peak in sequencing that was next-gen sequencing but in 2003 you didn't have the ability you have to actually subclone each fragment and that took a long time you there had to grow it up and get enough that could pull it down or other methods in 2003 to reseated this brilliant experiment there's a professor from UCSF he did a brilliant experiment in which he was looking for the SARS virus and what he did was he took every known sequence of virus took the most in common ones put them on a chip labeled one sample in green and another one in red took one from a patient I took one from a normal patient put them on the chip and looked for differences and the difference is one of those differences when he scraped it off with a microscope turned out to be the SARS the first isolation of SARS at this point we don't need to do crazy things like that and then come up with ink you know I mean this is a really there's a really hard experiment to do we don't have to do that anymore we have next-gen sequencing that have the ability to sequence millions one two you know 25 to 5 million reads in a single run so you don't have to know what you're looking for you just put it in the Machine and do it now what would we do with the sequencing data during a pandemic we would develop we would be developing we use the sequencing data to develop vaccines and drugs during normal times what we would be doing is hopefully predicting these things from coming so right now new strains of of kovat are being sequenced constantly and the reason why they're doing it I mean you may have heard in the press people say oh it's mutating it absolutely naturally mutates but the mutations are not really significant what the mutations are being used for is to trace the lineage so what you can do is you can look at a city and sequence the sequences that are coming and none of the mutations are going to make it worse if anything they're gonna make it less worse they're gonna make they're gonna attenuate this particular virus it's not gonna make it any any any worse than it is now but if you look at the sequencing rate and if you look at this the the patients and what sequence they have you can create a kind of a who got at first who came in first if you for example even in Washington they found that wha two is a direct descendant of if you see a completely different sequence showing up in Washington you'll know that it may have come from somewhere else if you have sequencing data around the world you'll probably even know where it came from you'll be able to figure out where what the wood the chain of transmission was so that's what it's used for now what can you do so what about when there isn't a pandemic what can you do with sequencing data and there's a great paper that came out in 2005 I actually contacted the author last year last night because I was curious if she was did more work in this space and what they noticed what people have noticed for years is that there's this strange periodicity to the influenza virus every five years or so so this new strain comes out and it's really nasty and it takes over the entire population and it kills a lot of people and the researchers in the study we're trying to answer that question and what they found is this first of all the sequence between between pandemics are very different from each other how does that sequence happen how does it change because you really can't change a lot of sequences at once and what they found was during non pandemic years the sequence has this kind of a set of they do these neutral mutations that don't really affect the function but it diversifies the sequence space it allows it to cast a very wide net to look for new forms to to to emerge as a new strain lift so it uses those years those passive years those years that it's living in the animal population and animal reservoir to create to create the diversity necessary to create entirely new forms that become really to become the next pandemic and everyone is worried about these and it's very hard to monitor that space and the important thing is - while it's there so the next slide shows you the different virus of different human viruses and there's there's two big classes of human viruses the arthropod viruses the ones that are hosted by by insects and the the the the usually the respiratory viruses that are hosted by mammals and those viruses live in a almost like a they live normally that they don't always kill their hosts it's especially true with bats where bats absolutely can live perfectly fine but if you wanted to know what was happening what the evolution what state but the state of the evolution was during this during the the the intervening years between pandemics you have to be sampling those population of animals that are the reservoirs and that is exactly what the Chinese were doing in Wuhan and that was exactly the right thing to do this is what you're supposed to do when you don't have a pandemic they're getting in a lot a lot of people are complaining I mean I don't really yes but but didn't you say that these things during that period the dormancy period if you will they're not dormant but yeah well I don't have a better word for sure non pathogenic or whatever none yeah whatever they're evolving during that period of time so what can we do what did the Chinese do to battle that during that that period of time I'll get to that I'll get to that because there is that that's my solution you're jumping right so building on that right down front on your right yes earlier you had said a mutation wouldn't have a negative effect it would be you know if I had a second mutation we more than likely you know kill the virus and yet this is mutations going on here if I understand your chart there's so let me go back here so during that during that time in which it's kind of incubating it explores the space by there's different kinds of mutations you can do it to a protein some mutations don't have any effect at all they they take one amino acid and convert it into a suitable that could work just as well you can have an you know the protein off on an elbow and you can change the sequences and then it doesn't affect the real structure of the protein but if you make enough of those all of a sudden you create brand-new structures that might become relevant to the new thing and that's why you see big changes in sequence new structures that you didn't see before from if you look just from one pandemic to another and most importantly they they they jump and take over the entire population so you don't for five years there's a kind of a pandemic a mini pandemic that sequence is kind of dominant for a while but the reservoir has the sequence of the next pandemic and it's evolving it over time so I'm not the first person to think of this other people have had thought of it one of them is a guy named Eric Schadt who's one of the he used to be from Seattle and New York stole him he's now at Mount Sinai so we need to be doing monitoring what we should have been doing is we should have been doing monitoring and that monitoring needs to be passive it needs to be anonymized and it needs to be continual you do not know what you're looking for you want to collect samples at a certain regular basis and you want to do that over time and hopefully you will get kind of like a chain of of you know a chain over time you you're supposed to see how this evolution is taking place the best place is to take samples our hospitals because sick people tend to go to hospitals and it would be a great place to go the problem is that because of HIPAA laws and I mean really silly HIPAA laws you should not need consent to take a patient's sample that he gave to the clinic anyway and use it for whatever you want I mean I think the the benefit that could come from taking that as long as it's anonymized as long as it's pooled all those things that you can do that would not break the privacy of the individual patient but yet you'd still be able to get users very meaningful and for information from that you should be able to have kind of like a disgusting sample from a hospital like this is everyone's like snot for a week you should be able to sequence that and to kind of see what that population is seeing I used to work for a company called combi matrix I'll talk a little bit about it later but one of the projects I did was it's creepy but it was really cool we had these devices we was to build with an SBIR grant and we built these devices and what they did was they would kind of pull in mosquitos and cities and from the blood that you'd get from the mosquitos you'd kind of see what kind of blood-borne pathogens were in the population yes it's the issue the cost of the sequencing because it's still not pennies or is it really just the inability to anonymize the patient information which one could think could be done I think it's a common it's a couple of car it's a couple of things one is I don't think the cost is that bad if you get what's important it's actionable information I don't think people believe that there is enough actionable information the the the the patient sample is definitely a problem I don't think you're allowed to just go in and do that you should be but but but you're but I don't think especially when you're involved in a hospital so what did Eric Schadt - he went to the toilet so he went and sampled sewage and he looked at the sewage and he was able to see all the viruses all these enterovirus --is that were coming out I guess there's no consent when you flush a toilet so so so this is a terrible slide if anyone ever shows you a slide like this I mean I I don't really know what's going on here I think there's like planes and satellites that are flying into some buildings but I think they could be computers there's like cars and bags of money that are flying into the computer and then you get this predictive model of disease and then you come up with therapies so I stole this slide from somewhere else I was using it as a stub I never would have seriously presented it but my slide is not as pretty so this is what you can actually do with the data so if you could see the evolution of these pathogens as they take place we may be able to predict when we're about to have a new outbreak and here's oh and there's a couple of things you could do but what this would let you do is it would lets you get a head of vaccine development if you started seeing new forms of for example to spike protein the first thing you could do is develop Diagnostics for them all of a sudden you'd have Diagnostics that are already developed for a spike protein that is in the population but it may not have emerged yet but if it doesn't merge you know right away that you've already got our stays develop they're not that expensive to make for vaccine development it's certainly more expensive but I don't think it would be so bad to have a kind of a diverse a diverse set of antigens that the vaccines could go after it doesn't mean that everyone has to get you in that you have to you have to shoot everyone with it but it does mean that it would be really helpful to have that this would be what a global response to pandemic would be like yes what would you focus on I'm wondering and presumably there's tons of viruses that maybe you don't do anything and so are you looking for specific evolutions of the strains we know are bad or is it so cheap to create vaccines if you anticipate we could we get to the point where creating a vaccine is very inexpensive mmm yes and no so I would focus on two viruses there's vaccines for all those of our all what except for the top two we kind of have to develop it over time there's vaccines for all the all the other repertory viruses I showed you okay this gets you to have relevant viruses that will actually be effective when a new when a new form comes out that's what this is about and this is what this information would get you there it doesn't get you there all the way but what gives me hope for the ability to do that because having the sequence is not enough it's also important to kind of understand what the structure is but and right now to determine protein structure is it's one of the great quote-unquote unsolved problems in biology if you were to do it you'd have to do a crystal structure there's all this stuff you have to do it's very complicated but because there's been so much data connecting sequences to structure deep neural network models have been increasingly giving you very good predictions as to the structure so in the next few years I suspect that these will get better especially when you constrain them to a set of known genomes or known proteins and you're going to get to a point in which these will be part of the loop so you look at the randoms the sequence that comes out of those other out of the art of the reservoir you can compute structures you can see how that changes once you see something that looks relevant you can say oh we have something but the sis the state were in now is that every once in a while someone wants to write a paper they run into a cave somewhere get some bat droppings and in sequence it and then they and then they do that they do it they don't do it in a continual manner and we should be doing it in a continual manner we should be looking into these animal reservoirs pigs you should be sequencing all the time this is where the worst is the next killers is in pigs forget coronavirus so there's questions right relative to vaccines could you comment a little bit on generally a lot of the vaccines are done based upon polar on the backs of chicken eggs there's a myth or I think there yeah I think you think I'm not sure how they're grown but but growing up a vaccine is hard I have I have some promising technologies in two slides but I just want to talk about one more thing so I rewrote this slide because I think it's really important the reality is that our greatest need is still cheap assays cheap diagnostics the future of global health does not cost three hundred dollars for an assay for a few no or $50 for an assay okay the future of global health costs five cents an assay and developing like extremely cheap assays like that requires an enormous amount of technology ok you need something that I like to call a high-tech low-tech approach a lot of times the technology you need is throwaways from the semiconductor industry things that have can be repurposed to do things that you never would have designed it in the first place okay and I mean I'm not talking in any kind of a Fantasyland I mean this this has actually happened I know someone who was one of the managing directors at app Mel and he told me something very interesting he said you know if they add know if you don't know makes the chip that's inside your glucose monitoring stick and his big fight with whatever the companies I think it was Roche was whether each chip should be four point three cents or four point seven cents okay those are the kind of assays and technologies we should be developing but they require a big vision and the reason why is because the real frontlines of global health are not at the hospital's down the street the real frontlines for global health are in the third world ok one of the projects I worked on looked at antibiotic resistance and I worked I remember I talked to the doctor there was a kid that from Seattle and he went to India got run over by train lost his leg god it's the hospital system got infected by some of the worst antibiotic resistant strains of bacteria that there were and he barely survived and barely was brought back to life here they had to keep him in a whole quarantine I met his doctor and what his doctor told me that was really interesting was this the antibiotic there's like a highway from the third-world to us of antibiotic-resistant strains and the reason is because we give out of compassion we give all these drugs to the third-world not to blame them or anything but we give them out of compassion and I do not control how they give them out they usually do not follow the guidelines and a lot of times they simply don't have the testing framework to decide whether you should give a patient one antibiotic versus another that is where your fight is now the trick is you don't have to build really expensive machines and make them the real technology that will actually be useful that will actually make a difference is a cheap technology that can be made easily with existing infrastructure but that has a really high-tech but cheap component not if anything from my talk it would be this idea if I can plant this idea of how important that is next slide here sorry so what we should and mostly are doing is as I said rapid diagnostic and sequencing and I've been asked because about the you know like what kind of what kind of things are I mean this is just a very brief and superficial survey of what of what the promising tree of treatments are out there that I think are here and I think the the Gilead trial I think is really important there's also the possibility of repurposing existing antivirals and using them as cocktails these might work and finally normal vaccine development takes about 18 months the problem is not just so I mean I don't know how many of you guys understand immunology if you guys want a quick him you know I have nine minutes I can teach you immunology in nine minutes it's you thought I was going to have a slide about washing your hand so I don't have a slide for it so I'm gonna just explain it to you it's shocking how few people know and understand immunology ASP like the anti-vaxxer is my number one question to them is do you have you ever taken forget taken cracked open and Immunology book and and like I've never found a single person that actually has it's amazing huh I mean II mean ologists are weird they have all these weird like even even among biochemists they're kind of like the weird group because they have all this terminology that baffles everybody but let me give you the quick the the skinny the way the immune system works is this when you ingest something or you know you get an infection there are these cells called antigen presentation cells and what they do is and there's two forms okay so the first form it just kind of grabs what's in this what's in what what it's in the medium pulls it in sticks it into this lysosomal compartment that has a lot of acids and that chops up whatever it's found it floating around there are these proteins called the MHC that mat that needs to go into an acidic compartment in order to ever fold in to show up they go into this place and in there there is this matching between the little pieces of protein that were chopped up and not MHC component they those MHC eventually go and present themselves on the surface so it's an MHC that is based on a particular person but it's inherited when you want to give a transplant you have to match the MHC so you don't have a response and then it presents this the T cells are part of your immune system and there are them the frontline of this and what they do is they they start in your they start in your bone marrow and then they end up in your thymus and in your thymus they're challenged by self anti by self antigen the normal things that you expect to see if they react very strongly they get killed they're never allowed outside of the cell but when if they get outside they each of them I should mention that each of them has a kind of a random shape on its recognition arm so when they're allowed each cell that comes out is completely different from another one only if they recognize something will they then expand and they do and they clonally expand and you get enough of a response and that becomes your immune memory that's actually what your immune memory really is there's a company in Seattle called adaptive that actually sequences t-cell populations and you get an idea of what your immune memory looks like so the second half of antigen presentation is the cell monitoring itself and this is so the first one goes after bacteria or agents that show up in your blood the second one looks inside the cell it's introspective so what happens is these cells and all cells actually do this as they produce proteins they take a little sample out of what they're making stick it in a lysosomal compartment and then they present that to the outer world and when they would they're not to present it if that's recognized by a t cell called a t cytotoxic cell that T cell will then respond and kill the cell that is in fact and that's how your immune system kills infection the reason why vaccine development is so difficult and it's so hard to predict is because you don't know which piece of DNA or which piece of protein from your viral protein is presented you don't know which molecule of dozens in each individual and each individual has a different combination of them will be doing the presenting which would help you predict which sequence is there and you also don't know the shape of the T cell molecule that shows up and whether it's going to actually recognize anything and if there wasn't anything that maybe turned it off so it's not something that you can just turn a switch on and get it to work it's still a really difficult process okay now there is one company and I'm not pushing it I don't know anything about it but and I do know some I know that it's clever it kind of hops the process by instead of producing the protein it kind of feeds the messenger RNA directly into the patient the patient's cells produce the protein and that might give you an idea of what elicits a response in a more natural way because normally the way vaccines work is you put them in something called adjuvant and no one really understands why or how adjuvant really works despite what they say and adjuvant is like this big mess and it just makes the I don't know it's like it's it's a it's a big mess that that gets the whole immune system to to to attack it yes why can't we use copied large-scale computational simulation to help us do this stuff of genomic large-scale copy of genomic simulation in particular what an excellent question you should read my blog I've opposed exactly talking about that so first is the scale so if you look at the the T cell receptor space the repertoire of not just an individual but a whole population its vast that the car the combinatorial space is to the ninth or to the tenth of possible sequences you could have and and there's a company in Seattle adaptive is sequencing all that and even in that space they're trying to put all that together and yes there was a great path of saying well if I had this t-cell receptor that had this shape and maybe we can feature eyes it with not just the sequence but the actual shape of that t-cell receptor and then we'd be able to guess at what it was actually presenting but you still have the problem of not knowing which piece from the antigen is getting presented and in presenting the system so other words you could say oh that looks like a great sequence let's just make it but when the virus is expressed that sequence may never show up when they never be presented that's why it's still an empirical trial and Charlie that still takes time why moderno is actually interesting is they kind of skip one of the steps it's not it's not perfect it's it's still issue the ideal solution would allow you to understand the structure on both sides and predict what the T cell receptor would be like and you could just amplify that up you just come in with it for example that would be a real solution that would solve that room but we're still stuck with with with that the other problem and this is a problem for everybody and this is you guys and the people that work for it or that you work for you guys are business leaders you guys work for government you guys have a very hard job because there's a balancing act that's really difficult that you have to do you have to stop the pandemic and you have to find measures to do that you need to keep the economy going and you can't swamp the hospital system so just for reference this is the number of hospital beds for 1,000 people in the population and in we're one of the hosts I don't know how that happened but I guess we're very efficient at getting people out of hospitals quickly so we keep that I guess our high rates do that also do no harm this one of the most important charts first of all whatever I tell you about is cannot be trumped by anything but those two links on the left say but it's important to keep in mind who are the real vulnerable population in this outbreak and and you you need to protect those and and I mean and in this in this phase if you have any influence caution is not a bad thing to be using at this point so a summary I think I don't need a summary but thank you oh you want I wanted I wanted the test log picture it's what I said before like you need a kind of a if we had been monitoring we would have been responding a lot better to this pandemic monitoring whereas if you would ask me 10 years ago what the actionable items for monitoring would be I wouldn't have had very much but now because of deep learning and because of trends I see in that space I think monitoring actually can be have truly actionable results and thank you so much if you guys have any questions left here yeah just your last comment when you say monitoring I just want are you kind of talking more on the global perspective or more just at the US because if earlier saying China was doing the right things with the observations of the you know in the host animals for it does this morning if you want to clarify more yes I wanted right so I the the easiest monitoring we can do is put a next-gen sequencing machine in a hospital that collects all the nasty samples especially the upper respiratory ones you know just makes a soup every week out of it an RLC buffer which is this great buffer that kills everything makes a soup out of it and just gives you sequencing data you would see who the people coming into your hospital are you don't need to have it in every hospital but it would be nice to have it in in community hospitals places like that it's not impossible to do it would give you a view of what's actually flowing through the population over time backwards okay this isn't something you have to annotate or anything you just throw it out there any blast against it that's totally doable right now I believe by a merrier is is doing something like that for anti antibiotic resistance in France but it should be global the coolest project would be to go like with a pith helmet and bat caves and get samples but I think you can do that in an automated way in which you don't like put yourself at risk when you go in there but I'm sure there's ways I'd be like a feeder I kind of like a bat feeder that would let you sample a little saliva when they come and eat and then you just are pulling samples out all the time so one of the that guy from the CDC that I knew I met his boss who was in his like 80s or whatever and this guy in even in the 80s or 70s he would like put nets in bridges in Texas capture bats and and go and see what they had in there what's alive or they had and it was I was like I want this job I mean these are the people that are on the frontline of a lot of these pandemics and they are I mean they're their heroes I think they they're amazing so I think we should give them the tools they need but if you guys really want to change global health for the better the biggest need in every way and everything I feel the one thing that would solve everything would be really cheap diagnostics and it's totally doable I used to work for a company called combi matrix and we synthesized with rays of allah goes so we actually were you know we use 20 year old semiconductor technology that we repurposed to do DNA synthesis on an array and and we you know this is a while ago but the point is that it was you know the this factory that we were getting our chips made from wasn't doing anything else was actually going out of business but they were making our chips because there was all this technology to do it the the means are there the will is not there i think people want to I think too many people are looking to see how much money they can make per a say when they don't realize that the real money and it's huge is the volume if you see volume and you see it at the global scale the money is much bigger than some stupid $30 or on a say I don't think enough people see that but you guys do right thank you thank you did you stay oh just a reminder of everybody we had a talk 2016 in Austin Barbara Han told us about her algorithms that would determine the most likely places that these viruses would be created whether it was a cave in China or in South America and it would that kind of dovetails nicely with this you don't have to go to every bad cave if you know the right bat games we do have a couple more quote you got some more questions yeah there's other any more questions yes I'm just curious yesterday we had a question a poll question of one we thought this would become a pandemic what's your problem prognostication on whatever this is going I in a month it doubled so what from from February 2 to now it doubled the biggest problem I've seen and this is you guys probably read more on this than I have cuz I was really focused on certain things but the biggest issue is in the scariest issue wing is when you have like one or two cases in the country if you're building your exponential curve out of oh there's two cases in Spain like expect a lot more in Spain they come in clusters and I don't think all the shoes have fallen and the problem the other problem is that we're late in the game we're heading into our spring and all of a sudden the southern hemisphere might start carrying a load and that's gonna be really nasty you may have a second phase on this one yeah so that's a related question the 1918 flu was really the 1918 - 1999 flu it backed off in the summer and then came back right three more seasons oh do you think that could happen here I think so it may not it may simply not I mean these things go away in the summer though they're all see there they have a seasonality to them I mean that's hard to tell I wouldn't speculate how that was but I mean one way that really makes sense now and not a 1918 is that is that is the southern hemisphere and remember the birds the birds are evil and you gotta shoot them all we uh we sent one of our guys to Alaska and they were like you know grabbing ducks and sequencing them and stuff things like we shouldn't let these guys go we don't all come the reason why it's so bad is because it comes in the in the bird population they poop they do anything and it's all over the place all of a sudden so that that's a real issue Wow more stuff to be scared thank you very much thank you and you're with us for lunch right yeah [Applause]

Channel: TTI/Vanguard

Views: 2,631

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Keywords: covid-19, epidemiology, informatics, coronavirus, artificial intelligence, ai

Id: gTejXbNES4g

Length: 43min 37sec (2617 seconds)

Published: Tue Mar 10 2020