COVID-19 Ch 11: Modeling


this is exactly rain so when the word came down that audience venues were being shut down for the foreseeable future that was a real blower a big part of my job as an operatic soprano or at least that part of it that I actually get paid for is crowds both the audience and on stage with my colleagues but now a year that looked at least eventful is suddenly joust empty. Ironically wiped clean by this tiny organism contracts full through and that's obviously really stressful financially but also performing as big pot of how I define myself so it's not being mentally either. What has extra stress to this. Is that in any aunt? Foam that requires your body. It is by its very nature time bound. I will never sound exactly like I do right now ever again and usually that is fine because it just is what it is that's just aging but this is an unspecified period of time of not being able to do what. I've trained to twenty years now than not knowing when I get to do that. Again is a really big pot of how stressful that Spain. It's a really scary concept that when you tell time bounty you really can't afford to waste a year but putting all of that aside. Let's take a look basic essentials here in Australia L. Opera companies and concerts gently move to a festival schedule. That is to say we don't really have any set groups of autos soap operas. We don't hire to a regular SCHEMA. There's no operas guaranteed to see staged. We run off individual contracts and the flavor of the season. What is boils down to in practicality is a system where you have heaps a variety for the audience but no real stability for the artists who will hide specifically for each opera one year. You might be exactly the sound everyone wants and you get so much work that you barely go a month without learning any like something you and the next year they a completely different sound and you get nothing and it's not like you can change voice to fit with a one. It's your voice. It's is literally part of your body. Which side night is terrifying in the face of a virus especially a respiratory virus? Because we don't have a clear idea of what he g holds. We don't have a steady report on earnings. And that means we don't qualify for any income protection that government affords us through our welfare system. It really does feel like the government just straight up. Does Not Care about us at this point and while we as Ozzie. Artists are kind of used to that. It doesn't make hurt any less but there is a silver lining And that is ons community. A we are incredibly resilient and where usually pretty positive we pull together and what friendships. We have of really forged in the fire of adrenaline. I'm actually part of a group of artists that's dedicated to upskilling while we're out of work we figure we may as well use the time that we have Each day one of US teaches the rest of the skill that we found useful interesting from different crafts to kind of channel. Those creative needs to mental health strategies for dealing with this weird turmoil that we've been thrust into its really helps to take the edge off the stress that comes with keeping practice without knowing what do keeping in practice fool or if there's even anything to keep in practice full and keeping in touch with people who are in the same boat really does help reassure you that there is a shore somewhere that the end of all this. The final We just keep ourselves. We help our communities whenever we can And you know maybe we post some every now and then two shy people that we all still have the capacity fool and then we just told on. I'm a social worker in a large county in Ohio working in child welfare assessments or commonly known as child protective services. I am the one that goes out to investigate. Allegations of abuse and or neglect. I've been doing this job for about a year and a half. I'm originally from Mexico City and ironically enough. I lived through the H. N. One outbreak during my senior year of high school. Three weeks of vacation later life went on unlike our current situation. We are technically working from home now. Which means I do all my paperwork at home but I still have fieldwork. My days are unpredictable. We never know what kind of cases we're going to get ahead of time and we either respond to cases face to face within twenty four hours seventy two hours the same day or in emergencies in one hour as you can imagine. People are not typically happy to see me knock on their door and tell them they have a case open with our agency and that there is alleged maltreatment add to that already stressful situation of stranger showing up at their door asking to come into their home during a pandemic. A lot of these homes are in areas of subsidized housing. Where space is limited making social distancing extremely difficult. It's very rare. I am actually able to maintain six feet of distance between people. I have to get a full tour of the home especially when there are allegations of hazardous home conditions so interviewing people on the front porch isn't always an option in the worst case scenario where I have to remove a child from a home that child and whatever belongings. They have come in my car. Sometimes I respond to hospitals and I am interviewing people in hospital rooms where it's also hard to maintain six feet of distance especially if there are providers in the room as well. I'm supposed to ask every family before I go into their home if anyone has experienced a fever a cough or has been exposed to Kobe. Nineteen however even if they say yes. I cannot leave a child in a home until I have fully assessed the family and the home and determined that the child is safe. I've had families tell me that their friend or neighbor tested positive and I have to continue my assessment and just hope for the best. I wear mass have hand sanitizer and wash my hands as much as I can. But that's difficult when you're driving from house to house and don't have anywhere to stop the scariest part. Is that the number of reports of child. Abuse or neglect have significantly decreased. Children are not interacting with mandated reporters and disclosing. What is going on at home? A lot of these children do not have access to technology and cannot check in with their providers even over the phone or on the Internet for children that are in the custody of the county visitations with their parents is held over video conferencing available to both the parents and foster parents. This is less than ideal. But it's the best we can do while following stay at home. Orders and social distancing guidelines court dates have been postponed over and over again and the only hearings being held. Are Those where we have requested. Emergency custody of a child who is an imminent risk of harm? This means that the cases that are already open and trying to go through all court proceedings to either reunify with their child or terminate. Parental rights are at a standstill. These cases will remain open much longer than usual on a personal level. I've always had helpings. -IETY in generalized anxiety. Which are at peak level since this outbreak. I have to try to set it aside while I do my job but it has become increasingly difficult. We aren't hiring more people because they have not figured out how to train people from afar as shadowing is a huge part of training as you can imagine. This job has an extremely high turnover rate and we always need more people to make matters worse. My husband has severe asthma and I'm constantly afraid I'll bring the virus home to him. My coworkers and I have all accepted that we are likely going to come in contact with the virus in get sick. It's just a matter of when my name is Dr Morgan Lenzi. I'm a small animal veterinarian. Marion in Houston Texas. The clinic I currently work as a high volume general practice. Meaning we see anything firm routine. Wellness care to emergencies. In early February. We were pretty concerned about our ability to get personal protective equipment. Or P P. A general practitioners. We do quite a bit of surgery and we use gloves masks. Couns etcetera The veterinarians and some of the veterinary nurses at our job began to order cloth masks in anticipation of not being able to get disposable ones and then when Cova nineteen hit the US pretty hard veterinarians were called to donate as much of our disposable PP as we could to the human doctors on the front lines. Of course this was something we were happy and willing to do. But that meant we had to be very conscious about how we were using our PB. One other way veterinarians were asked to help was to donate are ventilators. So our clinic. is a general practice. We don't have a ventilator but a lot of the specialty care facilities in certain States Colorado New York. I think even Michigan Have donated their ventilators human hospitals for their use so we were called as a profession to try and delay elect to procedures if we were able to and that included vaccinating pets. But I think one of the biggest debates that I've seen in our profession is what we consider elective so many of the vaccines dogs and cats receive in my mind are considered a central dogs and cats are required to be vaccinated for rabies by law. And they're required to keep this vaccine up to date The other thought was you know dogs and Texas. Her highly recommended to get the leptospirosis vaccine every year as well. If we stopped vaccinating for this we see more cases of Leptospirosis and people. Veterinarians are definitely at the front lines. When it comes to keeping people safe from zoonotic diseases and I really can't imagine what would happen if we had another outbreak like rabies. Lepto on top of this current pandemic. The biggest change for US started in the middle of March. At that time we moved to curbside service. Only this meant that. The veterinarian says would collect history for the pet over the phone from the owner got to the parking lot retrieve the pet from the car and then once the pets inside. I do my physical exam and then call the owner with my treatment plan to address any questions they may have I. This was really nice. I mean most veterinarians are introverts and engaging in small talk with clients. All Day was exhausting. Being able to get on the phone and get to the point quickly was sort of. Nice however almost six weeks into this thing. I'm realizing that the small talk really helped me to break up some of the hard conversations I had to have throughout the day. Additionally it's hard to know if the owner is understanding what I'm diagnosing their pet or the treatment plan for their pet over the phone. I rely so much on body language to understand my clients and I'm sorely missing that right now. One of the most difficult parts of all this has been euthanasia's when an owner brings in their pet for euthanasia. I can't hug them or comfort them. In the ways that I usually would We stand six feet away from the owner saying goodbye to their pet and deliver the drugs through a very long extension set which makes this process much more clinical than it used to be the thing I worry about. The most is the human doctors on our frontlines. That have been hit the hardest as a veterinarian. I'm accustomed to making just tough decisions that could potentially lead to a pet stuff It's hard enough to lose a patient when you've done everything in your power to save them. Though in your resources are low. You're overwhelmed and you have to make difficult decisions about who gets a hospital bed and who needs to go home. That takes a huge toll to all the doctors out there. Just no veterans are rooting for you. And if you need a shoulder to cry on. We're here for you at first. It seemed so far away. Something we just heard about but that couldn't touch us. The first confirmed death was in Everett. Not far from where our funeral home is. I remember the day in January when we heard of this case as a funeral director myself and my co workers are very cautious of emerging disease as we deal directly with the dead and in facilities or homes of those people where their loved ones or staff may also be infected. It still didn't seem real or plausible that our daily lives would change. The situation has blown up in day. As you all know as of today May I twenty twenty Washington has had eight hundred one deaths from cove it every day we receive notification of new deaths and as we are one of the largest firms in Seattle we have received several hundred of these cases. I have completely lost count of the Cova cases. That are now under my purview. One of the most heartbreaking things I've witnessed is not only the death toll but the families directly impacted in many ways by this when impact comes from the risk of exposure to the disease itself to people living with or around the person who died when I call families who have had a loss to set up the next steps for them. They're often grieving but now they can't even come to meet with us. They themselves are often on quarantine and must stay alone for two weeks before they can even begin to process their grief. People need hugs and shoulders to cry on when they have a loss and no one can offer that right now. We were the ones that did that. And now out of fear for our own safety neither can we. The second impact on these families came when the governor issued the stay at home order the original order that came. Mid-march brought out funerals or gatherings. Completely families were devastated. We began to panic. Not just because of the loss of the healing capacity that a funeral can bring a lot of people but the religious aspect and belief systems that some cultures have some cultures have certain traditions or ceremonies. That must happen. For a person's soul to pass into the next realm. It was within a week that the governor revised this restriction the massive implications on People's mental health were petitioned by people in funeral homes churches and the general public and the mandate was quickly repealed. It was finally settled upon by the end of March that we would be allowed to hold a gathering was attended by immediate family. Only the definition of immediate family was left up to the families themselves. Some are small. Some are very large. Some relationships extend beyond blood and that was not something we were able to determine ourselves. Things look so very different. It's not just the Cova deaths. People are still dying from suicide murder. Drug overdoses and accidents. Those families that have been thrown into a tragic loss. Also have to navigate this new system of grieving without a hug. And it's awful to watch. We are out of P E. We are considered second level in need for P. P. so trying to get masks and gloves is a challenge. We ordered them. They are on back order. They never arrive. We have to clean the whole facility. After a funeral the scarcity of disinfectants was rough. It's gotten better but for a time. It did not feel safe last week. Seattle area funeral homes ran out of the specialty bodybags we use for Cova cases. They're known as disaster pouches and there extra protective leak proof and impermeable to pathogen and molecular travel. This seems to be the very basic level. If P p. e. that we are no longer able to accommodate. We use now three regular bags and do the best we can never in my career. Did I think I would see the FEMA refrigerated body trailers? I remember the day about two weeks ago when I saw my first. We have to now and they are full at about forty bodies each not to mention our internal cooler which holds several hundred bodies. I live in a home with children and immuno-compromised people every day I am terrified at what might bring home the time it takes to clean and sanitize daily is unreal the consistent stress of trying to do my job be a mother and wife and keep myself protected is immense. I cry or nearly cry every day. Either on my way to work or on the way home I cannot express in words how exhausted and emotionally drained my co workers and I am I know we all love what we do and helping people navigate the worst day of someone's life but we all need this to be over as soon as possible. I love helping families making a grieving widow smile facilitating chance to say goodbye. I feel essential. People need me. I stand in the back at funeral services for immediate family. Were families take off their masks to hug and cry on each other's shoulders. That's what people do at funerals. Little Comfort is found from gays from a masked face at six feet away. No no no no no no no no no no no no no no no no no no no no no no no no no no Wow Wow those firsthand accounts like wow just so so phenomenal. Thank you every one for sending those in. We really appreciate everyone of you. That has taken the time to fill out the form and to send us your stories there. It's incredible to get to hear stories from so many different people right now. Yeah it really is thank you thank you. We very much appreciate it. Hi I'm Aaron Welsh and I'm Aaron Almond Updike and this is this podcast will kill you. Welcome to the Eleventh Episode Eleven. I can't believe it I'm shocked. I'd I don't know how we've done this quite honestly I don't know it's all a blur aired all a blur. This is our enemy of a pandemic series on Cova nineteen this week. We're diving into a topic that has generated a ton of headlines and has influenced decisions that have impacted billions of people around the world. That is math modeling of infectious disease. Let's hear it for math. Clap Clap. Clap format this. Might be the one episode. I convinced my brother. Listen to. How long will this pandemic go on? I don't know how bad is it going to get great question. How can we slow it down? Would love to know that. And how can we even begin to address those questions? Let me guess the answer at least for that question is math math. Surprise the rise in this episode we want to lay a groundwork for understanding what mathematical models of infectious disease. Actually look like where they get the data that they use what current models of covert nineteen are being used for and most importantly how we can actually evaluate these headline making models. That is very important. Yeah it's I'm very excited and to walk us through. The wonderful world of math models is Mike lowry senior research scientist at the Institute for Disease Modeling. He did such a fantastic job of breaking down these complex topics and were so very excited to share his interview with you but before we do that. It's quarantined time. Oh yeah anytime baby. What are we drinking today? Erin Oh you know quarantine eleven correspondingly worse vic sense in but what's in quarantine eleven? That's what we really want to know the key question it's basically a Manhattan. I approve. I mean listen to its quarantine times. Okay we're not going to get too fancy. Na Na NA It's delicious it's simple. We will post the full recipe for this quarantine and are Non Alcoholic Placebo Rita on our website and over social media channels. So you can figure out how we make a Manhattan Non Alcoholic if you follow US okay. Now that that's out of the way we do still have a few more pieces of business to tend to. We received some feedback from our last episode in this series which was on education and that episode primarily focused on the impact that cove in nineteen has had on schools in the US and we want to share a few of these responses with you. The first email excerpt comes from someone who wanted to clarify a point of discussion in the education episode where we talked about equity in schools particularly highlighting the long history of racism and disparity in Education for native Americans in this country. So I'll read you part of that email near the beginning of the interview the substantial and historically entrenched disparities in public education in our country were casually dismissed as a native American whose mothers struggled with boarding school abuse and the traumatic scars of Education Racism for most of her life. This was distressing to hear alarming structural disparities exist at all levels of Public School Education for Poor Black. Latin X and native American students in both urban and rural context. Furthermore data about these disparities have been collected and widely reported on for more than one hundred twenty years since W. E. B. Dubois began publishing his sociological work at the turn of the twentieth century. Yes Yep great excellent points thank you for sending setting aside email And then the second email comes from a Finnish journalist who wanted to provide a more nuanced picture of the impact of this pandemic on Finnish schools. The social security net is undoubtedly more advanced than the American. But the fact is that also in the Finnish. Society Corona Pandemic has brought societies inequalities to light in a very uncomfortable way when talking about the schools and children particularly this highlights both differences in income and wealth as well as problems with domestic violence substance abuse and mental health issues since the schools closed in mid March. Both teachers and Child Welfare services have expressed concern of those who for example have a very toxic environment and for whom the school is normally a sanctuary with safe adults and a warm meal every day. Many families have lost income and many are struggling with the extra expenses brought on by having the whole family at home all of the time. Not everyone has an Internet connection at home and in for example low income families with multiple children. They might not have enough computers for all of them to attend school schools. Also report difficulty in getting hold of some children and families and the means to protect. These children have worsened now that they don't meet the children regularly children with special needs and needed. Extra support might have lost that. In Finland School lunches are normally free of charge to all pupils during the state of emergency when the schools have closed their doors. The government still recommend that municipalities. Who are responsible for. The education provide lunch for those who need it not all municipalities to and between those. Who Do it's done in many different ways in some cities you can pick up lunch every day and others weekly and some offer money instead for many kids. The school lunch might be the only meal they eat during the day so for those children and families for their municipality does not offer lunch. The situation is very difficult again. Thank you for sending that. Yes yes thank you so much. It's bad everywhere has without means for sure. Sure and the last thing that we wanted to share was a correction about the twenty percent reduction in pay to public school teachers in Hawaii that was mentioned during the interview. This reduction which would also include other public employees. Not just teachers has not actually happened yet. As of May first so these pay cuts have been proposed but have not been finalized yet and may not be finalized depending on how things are decided so another important correction. Yeah thank you so much for sharing those insights and corrections with us. We love hearing from our listeners and we wish that we could respond to each and every one of you if only there were more hours in the day constant refrain reframe okay. Are we ready to talk about Matt? Let's do it. We'll take a quick break and then we'll get down to business. Hey I'm curt brown older and I'm Scott Landes. We're too silly due to love the absurd and we got a brand new podcast called bananas. You should listen. Every Tuesday we discuss absolutely bonkers news stories from around the world. Things like man. Walking oddly found to have twenty one live pigeons in pants missing. Parrot TURNS UP MINUS BRITISH ACCENT fultz speaking Spanish NASA prep for alien communication with LSD Dolphin. Sex EXPERIMENT WHO? And we've got great guests like Norbert Star Kristin Shaw so for all you. Tv or movie starring Actors Producers. I can take out my teeth. So that's one more. If you WANNA real weird look we can give it to you so give us a listen if you enjoy the nutty shocking and the Downright Bananas Bananas every Tuesday on exactly right. Subscribe now on Stitcher Apple Podcast spotify or wherever. You like to listen Hi. I'm Dr Mike. Familiarity and I'm a principal research scientist that Institute for Disease Motley. Ibm is super disease. Modeling is a research institute. That's a collaboration. Between Intellectual Ventures and Bill and Melinda Gates it focuses on issues around disease control elimination and ideally eradication on and until recently had a heavy focus on developing world applications including Malaria Elimination Control Polio eradication HIV control regulus typhoid vaccination policy. Things like that in the starting in January we started to pay more and more attention to this thing that has now covert nineteen recognizing its pandemic potential and have increasingly pivoted. A bunch of efforts towards trying to understand what's happening with covert and trying to understand what we can do about it too besides staying home for the next infinite once or let it rip and see what happens great. Thank you so very much for joining us today. We're very excited to chat with you about some math modeling. Thank you for having me. It's one of my favorite topics. Of course okay. So before we get into the cove in nineteen specific stuff. We would love to just lay a groundwork for what math models are and what they're used for in infectious disease and so could you just start us off by answering. What is a math model? And what are some of the goals of mathematical modeling? Yeah it's a it's an excellent question and I think it's way bigger than just infectious disease but certainly infectious diseases. Having its moment right now like maybe never before so the key idea with mathematical modeling. In general is you're trying to make a simplified synthetic version of the real world in some way that has really explicit rules. That's the mathematics part and then with those rules of how your synthetic you know. Representations of the world actually interacts you. Try to learn about the different possibilities of how the real world could interact and you also often try to work backwards and say I've seen these things in the real world. I think I can map them. Onto my representation. I sorta say my model kind of looks like the real world and some specific way and then I can often ask questions of the model. I can't ask the real world like you know. How did the transmission actually happened? I didn't measure how virus got from one long to one now but statistically speaking what might have happened there what might happen there on average across a large population and the other thing we can do with models and why we care about models especially in infectious disease research is that we only get one real world but we can often computer. We can run many different scenarios many different variations on how we think. The simplified world works and that helps us do two things that are really important. One is again. Try to understand stuff that we can't see directly but how it probably works and into it allows us to explore different future scenarios based on what we've seen so far may depend on different kinds of decisions or different actions are also different scientific. Learnings if you haven't yet resolved on will affect how that plays out. Yes creating a world of parallel universes. That's literally how it works on. The computers have ten ten thousand computers on a on a cloud. Cluster of doing the same thing in parallel each one trying out a little different pathway. Exactly how it works. It's amazing it's amazing so talking specifically now about infectious disease models. Can you walk us through? What the basic components are of an infectious disease model like an SI our model perfect. Yeah the the most common starting model like the front of the textbooks is often what's called an SI armato the S. I n are referred a states that a person in your model can have s means. They're susceptible to the disease. I means they're currently infected with the disease and are usually means they've recovered from the disease and in the simplest models. We assume when you've recovered you have immunity for the rest of your life. That's one of those first. Assumptions is often not true and then with those people have these simple states of either susceptible infected recovered. We put them together in transmission model and we let them interact in some very simplified way. The simplest version is literally sort of like everybody's GonNa Conference Center. Everybody shaking everybody's hand. Everyone's talking to everybody. It's all completely well-mixed. Everybody gets along and in that context then we can introduce an infected person at the beginning of the epidemic. Democ in our model they're interacting with all these susceptible people in so they can pretty easily transmit the infection. How easily is a property? Both of the pathogen itself and exactly how much mixing those people are doing. And how closer talking to each other and all that and then it goes from one infected to a few infected to a lot more effective as time goes on if you keep everybody in this little conference room for as long as it takes. Some of those infected people start to recover. Now they're no longer susceptible transmission continues. But it's getting harder to transmit because there's fewer people around that aren't already recovered and eventually the whole thing plays itself out and you've had your epidemic come and go excellent. Yeah and so you know the data that you used to estimate these parameters so that the population or the size of each of the states that you mentioned the S. and I and our and then also the transmission rate. You know how fast one person moves from the susceptible state to the infected State and then also maybe a recovery rate. Where do the data usually come from to estimate those different numbers or parameters yet another great question and thinking about where the data comes from? We'll help you really understand that comment I made earlier about what parts of modeling is about looking backwards to see things. You can't measure and what parts are about understanding what's compatible with the data you have so if we focus on the individual part for a second like how long is someone infected for which is another way of saying how fast they go from the infected environment the I. Compartment so the R recovered compartment that we can often in a best case scenario measure from people who shop at a hospital or Metro from people who participate in study We literally measured the virus when they start expressing it this shedding viruses. We usually say and we can measure when they stop. And so. That's something that in principle you can measure pretty directly. Individual Properties are often like that immunity is something similar. You can measure people's anybody change and in certain circumstances where if you've measured the right way you can even measure how protective antibodies about getting infected again. So those kind of stuff. The best data come from actually measuring people individually the thing that we very rarely get to measure individual Directly from people because it's it's the experiments are more difficult more invasive. They take a lot more. Logistics is the transmission part itself is used to characterize on average how many people infected person transmits to the way we usually figure that out is not by measuring directly but by looking at the development of infections over time that we measure in a population like we measure at the hospital. And so you sort of say. Well I think there's this many people I think they're infections kind of look like this and then I've seen two people infected yesterday. Four people today. Eight people sixteen and so on and I back calculate that. Oh if that's what the data pattern looks like it. Looks like each inactive person. Maybe causes to more new infections on average. And that's how I figure it out. It's an inference. It's not. It's very rarely a direct natural gotcha and so you know with these models with the basic modeling of of a hypothetical or even real life epidemic or outbreak. They seem to tend to follow what we call this epidemic curve. You we talked about this a bit in terms of the Conference Center mixing and how eventually that population is going to run out of susceptible individuals and so are those the basic patterns that you see for the curve. And what are some of the other things that determine the shape of that curve again really relevant to? What's going on right now. With covert the simple as assumption that leads to occur the common one you see in the front of the textbook and the one that we think of when we think about diseases where we're not trying specifically to control them in any way but we're just sort of letting them play out is that the curve is driven by immunity. Which in the language of sl our model is driven by the interaction between susceptible becoming eventually recovered an being no longer eligible to infected again. So we go back to the conference center picture. You know. Be more specific with like concepts of are not thrown into the thing you know if the first infected person shows up in that conference center and they're sick. The first thing that could actually happen. Is they go wash their hands. And they don't actually transmit anybody we don't hear about but what can also happen. Probabilistically on is. Let's say the person didn't do that or they did it and we still got unlucky because they seized on this ramp then transmit to a few people and now you've had one person turned into a few infections and a few infections turned into more as long as this are not number is above one. Each infection makes more than one infection. And so that's the process that leads to exponential growth early on if I started with one thing and I get more than one thing at grows and grows and grows browse. But then we're the curve comes in as as we said in the room. There's only a finite number of people. There's not infinite people with intimate handshakes and so eventually the there'll be an infected person who starts the virus wants to transmit but they're actually their contact is not susceptible anymore and so their ability to transmit is reduced on average they'll transmit less often this effective reproductive number. That is now lower than the original basic reproduction number. Because there's some people you can't transmit to and eventually you'll naturally get to a point where the effective reproductive number has become a low one or which is to say. Each new infection can only transmit to less than one new person. And you do that. A bunch of times eventually dies out. If nothing else happens that process of exponential growth early followed by exponential decay later works itself out as the curve that we typically see. What's really important to think about that? In the context of Kovic is there are lots of other ways to produce curves that aren't just driven by immunity in a closed population. What's happening right now? All over the world is generating hers by changing our behavior and so instead of by generating unity and letting it run. Its course we're actually changing how we interact with each other and manipulating the probability of transmission in the first place manipulating the zero not just letting the effective reproductive number playout uncontained and so in situation. If you in the end manipulate contact enough so that the transmission rate goes from exponential growth. You know slowly decaying that look like an EPI curve but the difference between this and the immunity story is we haven't consumed the resource of the many susceptible people and so if we were to see if we if when we changed behavior. There's the possibility that the contacts will ramp up again and transmission will ramp up again and we'll get something that looks very different than a classical curve multiple humps that could go up and down and much of the future of the world dealing with covert is going to be figuring out how to mitigate the potential for rebounds as we changed behavior so we can keep the curve shape that we're okay was given all the consequences that has the society both the disease and what we're doing about That was really well. Put how much behavior plays a role in shaping. These curves is hugely important. I think to keep in mind. It's not just a predetermined thing. So can you talk us through some of the assumptions that you have to make when you're constructing one of these models and how that kind of relates to the uncertainty inherent within models and how that might infect sort of interpretation so just sort of more generally speaking about assumptions and uncertainty in mathematical modeling okay. Yes so. There's a lot. A lot of choices can be made for many different purposes one purpose of which being? How quickly do you need an answer? That's better than the seat of your pants on. But also what is your scientific objective. What aspect of the disease is most important to the question? You're asking so many levels of complexity? Many different kinds of assumptions if your objective is to estimate something like the effective reproductive number on average and not to look at the details of how asymmetric people do this and symptomatic people do that young people. Do those people do that in all those kinds of details. If you don't care about that you just want to get the average to characterize what's happening in a large population of all you can make often pretty simple assumptions. That are not particularly different than the model. We've been discussing with the case of covert you have to add. A behavioral component the allows the parameters to change over time. Even if you're not sure why and so- models like that are useful if you want to sort of provide situational awareness on. This is one of the things that we work on idea where we sort of used a simple model to look at the recent past. Try to understand how to transmission led to the recent past and maybe do what we call a now cast which is to say not a long-term forecasts but like the data. Were you telling us about what happened a week and a half ago? And so can we. Further estimate was probably happening right now in the very near future based on a continuing the trends. We've seen before those kind of models don't have that many parts they don't have that many parameters but what they're good at his answering one type of question descriptively. What's happened recently? And what might happen soon at a different level complexity and something else we work on. It is for example all this conversation now about testing tracing isolation quarantine how using information using better testing is hopefully going to become an option increasingly across the world that helps us get out of the current situation with code while being able to return some increased level of social and economic. That makes us all happier. People and that kind of thing requires a lot of details. You have to understand more about how many people live in a house and how many people go to different kinds of offices and it matters if you're trying to test people to tell them to stay home before they continue to transmit you have to figure out or make assumptions about is. Most of the transmission happened at the beginning of the infection while people don't really know that they're sick yet or does it happen route and then you have to think more about how they interact because when a contactor picks the phone they're going to have to call somebody is that somebody mostly GonNa be household members or classroom numbers or people. You work with or is that you have no idea how to track down. Who was on the subway next to you and those different assumptions matter and often when you're asking that kind of really detailed question where the individual details matter. You have to make a lot more assumptions. You can also use a lot more data to help you understand some of those assumptions and in those kind of things. You're often your focus is going to be less on. Let me predict exactly what's going to happen because you can't really know exactly what's going to happen. You can never know that but it's especially hard in these complex models but your questions might be more like am I pretty sure for lots of ranges opens things. I don't know lots of uncertainty option. A IS BETTER THAN OPTION B. Am I pretty sure that if we try option a we can measure? How well it does work. I can't predict how well it's GonNa work but we can figure out afterwards. How well it was working in a justice on that so models have the sort of more detailed in justic sure can be a lot more assumption rich but then correspondingly are going to be weaker at your really making sure. They've gotten everything right and you use them in a difficult I you try to use them to understand ranked preferences. What's better than what else I'm in less. Try to use them for long term forecast at least that sort of approach that I tend to take in my own work okay. Interesting so more simple models are used to kind of understand what's going on and what might happen in the future more complex models more about decision making in terms of not what is going to happen. But what are the different outcomes? That could happen if X IF WE CHOOSE. Xyz? Yeah that's a great rule of thumb because those are where they excel as you look across the many models being used in not just right now but through like the history of epidemiological modelling. The boundaries are blurrier than I just made it sound. And so that's one thing to pay attention to is if you're seeing a very simple model being used for a complex prediction the hair on the back of your neck. Stand up and go I wonder and then conversely if you're seeing a very complex model being used for fairly simple prediction there's a question about how sure am I that they've explored that simple prediction could be because the universe of their model seems potentially a lot bigger than what I'm seeing in the output and so that's another What do I think is actually going on there? Certainly questioned professional model is ask each other all the time when review each other for. That's really that's really interesting. And so then. These different models might be used at different stages within a pandemic. Let's say for example to guide different public health measures. And so can you talk a little bit about how we might use a model differently or use a different model. Even early on in pandemic versus during the middle of one versus at the end of a pandemic. Yes this is very much what we're seeing. Play out around the world in modeling right now including within idea my own organization early on you often start simple for two reasons one is. You don't know that much and so you want to use fewer more flexible assumptions. That capture what you do know and not try to say too much about what you don't and characterize all the uncertainties usually easier to characterize because you like there's not that much. I can only tell us this. Good okay that's what it is but then also especially early in this pandemic and this is a continual tension ideal with my professional work as my colleagues is a decent answer soon is better than a great answer a year from now because decisions have to be made that affect what happens and we want to be able to help inform on those decisions with our expertise certainly not drive them but are able to provide a different way of looking at the same data to public health audiences like the government and that has a useful frame to what they're already understand in there already have as their deep expertise so as we start with simple models we learn more and also the questions change like a month ago or month and a half ago. Now in the question was okay. When should we start doing some physical distancing and how well will it work and then the question was well? How well did it work? And we're starting to find a lot of places all over the world. It's took exponentially going catastrophe and has slowed down to close to something to sort of sustain indefinitely with the selective reproductive number equals one knowing the reproductive number changed is a slightly more complex than in the first question. Still fairly simple and you can estimate lots of different ways in lots of different groups. Are doing this. Where the questions are going now. And where the models are going now is how do we better understand why the effect of reproductive number changed the way this not just that it changed but what specifically of the many things everyone around the world just changed in the last six weeks what specifically had the biggest contributions to the change what specifically was no big deal and we can just let it go back to close normal and it will probably be fine than okay if we want to start doing newer strategy strategies? That are going to be more specific. How do they place you know if you have better information you don't have to? You have changed their behavior to the same extent you might be able to have less or more and be able to respond to the virus itself and so that again is another level of complexity. Because it's not just modeling what the viruses doing. But it's then modeling Howard. We societally likely to respond to what the virus doing. What are its consequences and so the complexity goes up as the questions? Go Up and as the time moves on the questions are getting more complex and and also we're learning more scientifically often. We learn about a disease over many years. Most science moves over the timescale of years. In here where trying to learn over weeks and so we're trying to ask these complicated questions build complicated models understand the limitations of our simple models that we haven't ever confronted before at the same time as every was trying to make everything better and change what's happening and so that that leads to a whole `nother cloud of of of uncertainty and challenge. That's just inherent to where we are at all time. Typically and as a community dealing with this thing yeah and so you know talking now shifting more specifically into Kovic nineteen models and predictions and forecasts. Can you just kind of walk us? Through what a basic model of cove nineteen might look like for instance like would follow the same model that you described earlier yes. The simplest models often follow the same sl. Our framework with one very important exception. Which is there's nowhere on earth to our knowledge except for maybe some small villages here or there that have had really severe epidemics early on where immunity is the dominant reason that the transmission rate is changing. So we can't just rely on the sort of chapter one of the textbook. Immunity produces a bell shape. We have to incorporate some concept of behavior and that can be as simple as the transmission rate changes over time in ways that estimate but not really understand why models like that have been useful for covert for understanding. You know what is changing models. That are that simple have been also useful for sort of understanding in the next few weeks. What is likely to happen if trends? Continue as they have. That was very useful for hospital. Utilization predictions you know. How worried should we be about overwhelming healthcare system and many of the early predictions going back to February? Were in the focus of okay. We have no idea what's going to happen. But what if we do nothing? A simple model even or complex model in that moment is an exponential growth model. And that's that and it's going to say you know if we do nothing with Cova really dire outcomes that we haven't seen in the century are from an infectious disease are going to happen and so from there. We sort of say okay. That's one of useful prediction. But then unlike weather prediction models actually change what happens which is an important thing understand ready. Miala when modeling and data together. Clearly tell a story. It's on us as a learning issues than act in response to that story so that the worst doesn't happen in one of the things. That's been super gratifying for me. Just as a person forget about US professional with covert is watching like so much of the world actually make major changes to save lots of lives that have completely changed with those early. Outcome could have been to where they are right now. Models that can adapt to that continuous process or going to do better in the future than models that were more rigid about what we thought we understood early on and are just trying to keep shoving forward. You brought up a very good point about models telling a story that is sort of a choose your own adventure like a snake tail in its mouth sort of at a story there. Yeah and and that's one of the things that I you know. I certainly want us to be really careful about. I try my best and they're probably don't always succeed. is to be really mindful of of the difference between like a prediction and a scenario. And what I think. The the differences right is often like again using weather as the modeling system. That almost everybody's familiar with that's a prediction system. Where we have an enormous amount of understanding of the physics. We have a lot of measurements happening all over the world and on the scale of weather days not centuries or at least years. We don't do anything that changes the weather and so we can get better and better at predicting it and it will play out as we get better predicting it it'll play out like we said it was going to happen and modeling is in that context really prediction tool in something like Cova. I think of it more for the future as a scenario exploration tool because the would depend entirely on the future behavior of the community that the covert is transmitting courts. At least until far in the future where the stronger effects of hopefully some significant immunity which is itself still uncertain. As to what that's GONNA look like will kick in and make some of these stories simpler and so certainly in our science communication. We try to emphasize. Like here's what could happen in the next few weeks if everything stays the same? And here's what could happen if things change to make transmission a little less or they change to make transmission a little more and so. That's why getting emphasis on scenarios is to help. Visualize how choices of some change could lead to different outcomes And that's different than prediction in my mind. Because in the end it's the choices will affect the scenario. That happens and we don't know that. Yeah that's that's such a good point and I think you know I've seen a little bit here and there are people saying. Oh well why do we have to just severe lockdown if cases are so low and it's like well let's that's the cases are so low because we had a severe lockdown like it's it goes hand-in-hand. Yeah I wish I remember where I saw this on twitter. I is that that's why you take your medicine like you start feeling sick. And then you take medicine to make you not get really sick and potentially die. A physical distancing is the medicine for a community transmittable disease at this point in time one for which we don't have other good options so yet we took the medicine. Things are getting better and like not taking your full course of antibiotics. If we stop taking the medicine to get worse again exactly great. It's definitely definitely true. So what are the questions I have is is a little bit specific as regards to sort of building these covert nineteen models and I was just wondering know whether whether some models use just lab confirmed cases so like people who have tested positive Or have been tested and tested positive or whether there are any models that are also extrapolating based on the number of asymptomatic individuals or The people who seemed to be clinically diagnosed positive just based on symptoms alone whether these models are using just lab diagnose cases or also clinically diagnosed cases of cove. Nineteen as well yet. Another really important question. The answer is there are models that are using jus- clinically confirmed cases lab confirmed cases. There are models using multiple case definitions their models using not just tastes finishes but also you know we learned this thing from a paper and send Jen and we think it's probably the same in such and such city so let's just copy that art over in use it until we learned something better about the city that we're looking at the moment. Lots of different data sources. I think the way to think about this is again. What is the objective of the model and also where? What kind of data is most reliable? 'cause that's also super important right now. With covert we make assumptions about how those different data streams represent a sample of the total population models can be more or less complex and how they handle those assumptions and they can all feed together to tell sort of one story about what's happening underneath with the population prevalence and one of the exciting things through those also starting to be more data more projects that really set out to learn about the parts of the population that don't just show up. In clinical case reporter lab confirm his reporting and that kind of data becomes more available these surveys of Sierra logical surveys that look for immunity history also shedding surveys look for actively shutting virus in people who didn't show up at the hospital are giving us yet another type of data stream that again held a story about the population and depending on the model is objective. What data they have access to. You have more or less complex pieces that you put together to tell a coherent story about the whole population. Yeah looking back on these earlier models of cove in nineteen. So let's say like a month ago. What can we take away from the performance of a model like if evaluate a model a month or two months after it was first created and we evaluate? How well it actually measured up to what we saw. What does that tell us? What does that? What does that mean to us to evaluate a model prediction or a model even a model result of any kind from a few months ago or a couple of months ago the most important thing from viewing it as a modeling scientists. Viewing by professional ends is. What was the objective that model set out to do? And then how do we judge did against that objective so one example? We talked about earlier models that in early February predicted. Millions of that. Salt WITH UNMITIGATED outcome. Well so far. That hasn't happened. Because we didn't have an unmitigated world but we might be able to judge that prediction on. How did it capture? What was known at the time How did it influence decision making in a direction that epidemiologist collectively think is the right direction or not Was the presenter of the model is sort of humble about what they were trying to do in clear about what they were trying to do or did they overreach based on like. I started here and actually what what I try to talk about was three other things that not really what. I focused on that sort of a scientific integrity component then their models that look that what. What if you make this change or that change or the other and then something we can? Judge is working backwards. Both which scenario seems to be played out that's useful because it helps us anchor what we've seen what we were what we were expecting in the past but then we can also further into the model if the model has the details and say did it get the right answer for the right reasons based on new science that we've learned or get lucky. This is how I view it as a professional. I think if I was just feeling like when I watched the news at night or on my phone. There's more of a sense of. Can I see how the the narrative that's being spun around this model connects to what the figure the graph actually looks like? And if it does I feel better about the coherence between the two. Even if the prediction doesn't necessarily play out correctly because then the next thing I'm looking for is if the prediction was incorrect. How did that model or that model or address that discrepancy? And did we learn something from that discrepancy? Or not if we do if you know communicated in a learning way and and we can point to like. Oh this was this assumption. That didn't play out the same way. We thought that's what the outcome was different. And I think that's a really successful effort but it's a it's different than the communication question. Everybody wants to know what's going to happen and I come back to. I don't think that's quite the right way to think about what these models are capable of doing. At least maybe a few weeks. You can guess the things. Don't change that fast. And it'll be predictive but beyond that again it comes down to the choices we're making a society and that's GonNa make it hard to really use. Prediction is the right lens. Yeah so I won't ask you then to predict what's going to happen but I will ask Whether there is any agreement among models as to what policies might be the best for the ideal scenario which is the least number of cases as possible and the fewest deaths and ideally with with some sort of relatively tolerable. Societal cost which often an additional layer of complication. Here so us. Like is there a consensus of from of different things from the models and I would actually put it as I think. There's more of a consensus among model irks And the differences that aspect of how fast. Everything's moving of you often. Those of us who've made a career out of thinking about it became electrical. Modeling can sink through things that we've not yet had time or a colleagues have not yet had time to actually turn into real math. You can run that multi-diverse on your computer cluster. And really play out and so you'll see pieces of stories that are out there now and over the next few months it will continue to be more and more and I think the consensus at the moment is something like the following. At least I should say more carefully. I'm not sure if this is the consensus. It's the campaign I fall into. That is probably the more safe way to say so. We do expect that to keep. That's under control and to keep hospitals from being overwhelmed that there will be some physical distancing for a very long time. I have very long time. Could be months could be more than a year it could. It will depend on the availability of an effective scene but to meet the goal is not letting covert and hit. Everybody that's GonNa hit We're likely to still need some physical distancing overtime but added to that there's a lot of interest in interventions that are more specifics to control the transmission. The popular talk of the moment is test traced isolate and quarantine those kind of interventions contact tracing interventions. They look for people who have the disease and then try to get ahead of where. The disease is transmitted by interviewing them about their social network and connecting to the people that they were likely to have transmitted to and ask those people to change their behavior to stay home if they might be sick to get test find out if they are and otherwise. Make it so that it's harder for those people to continue to transmit on and that will prune transmission trains and keep things under control to do that as a really resource intensive thing and so most countries although not all are in a position where we need we weren't we weren't sitting on a squad that was ready to do this for everywhere on Earth a global pandemic and so there's a resource question about how feasible that will be and in the modeling one of the at very active areas of research is. How do you trade off the blanket physical distancing which is required when you don't know where the disease is and the contact tracing based interventions? That will be more effective as you have better information about. Who's getting sick and missing fewer and fewer people with that information. I think and I think a lot of my colleagues thing that like the path forward is going to be the most realistic to be determined based on resources and coordination holiday and behavior. Of how does that trade off play out with the ideal that we get to better and better information on that makes less and less physical distancing necessary but one caveat I want to add that's Intrinsic? Dacoven that we think we've learned in the last few months is there's definitely some Cova transmission that happens before people are showing symptoms. And there's definitely some people who show negligible or really no symptoms and so there's likely to be a fundamental limit on even if you had infinite resources being able to track down every infection and stop it from transmitting just because they'll be transmission events for which there's nothing you can observe and so that feedback is why we think it's it's not likely to literally go back to normal plus contact tracing if we want to control the transmission to the levels that we've you know are hoping to do it now. I think it's something like that. Is the short term consensus a really important uncertainty as to? How does this play out? You know two years from now or three years from now is is how durable is the immunity that covert nineteen generates and people who get infected. And we don't know where covert business space and and it's it's reasonable that it could be on sort of towards either extreme because on one hand it's a corona virus like the common cold ones for which communities not that durable but on the other hand it's causes a much more severe infection a lot of people so the immune response may be quite different. So maybe it'll be more durable than typical common cold grown avars those all matter because it really matters to like does this. This cove in nineteen disappeared from Earth. Once we have a vaccine or or does it become a thing that if you're vaccinated you're probably safe but you need to get vaccinated every year to how does that play out in the future. Exactly those parts. The interactions of immunity transmission is stuff that like really clouds. What could happen to three or four years from now Yeah I'd like to ask you when I see a headline that says Oh this model is just has. Just come out and predicts this many things. It can be really difficult to evaluate whether that model is reliable or what I should take away from that model and so do you have any suggestions for how we should think about these models and how we should evaluate them Or COMPARE THEM. Yeah a couple come to mind the first one. It's one that's frustrating and it's frustrating to me again as a person who's afraid of covert is that Be Very wary of absolute predictions for the many reasons we've discussed about how they're not of physics in this situation their behavior dependent and we can choose that and so that would be one rule of thumb is. If I'm hearing a modeling resolve it says like with high confidence. Something is going to happen. You know in August and that's that I am very wary of it. An immediately asked myself under what assumptions about the future. Is that likely to be true. And so. That's one rule of thumb. Now I'll soften that and say if it says here's what's likely to happen in the next two weeks. I get much less critical. Because that's your society changes that fast most of the time. And so that's a that's a more reliable thing to predict. Maybe another rule of thumb. Is You know again one? That might be frustrating and one that I probably done a lot in this interview. At least I hope hot and this interview is the communication around the model. Keep Heggie what it says in if it does. That's a good thing. The hedging verbally is a challenge of translating mathematics into the conversation. So when we talk about uncertainty in our models there's a very precise way to sort of define uncertainty and we can make a graph that shows a range of estimates and has some principal reason. It happens but then when you translate it to the written your written media that's not technical or or conversation trying to communicate like here's what I think I know confidently versus years where I'm not. So sure is something that if people can to near ear to that that will help them understand what they can and can't believe about what they're hearing and conversely if they don't hear that again they should be wearing those certainly how. I think of it as a as a member of the community when I watch a model on the news or read a tweet not a paper that sort of how. I approach Yeah those are great great tips for sure so I have one final question for you and it's more on a personal note. Is there any positive change? You hope to see come out of this pandemic whether it relates to just sort of view as a member of the community or you as a as a model or in your professional life anything that you just a little silver lining. Maybe hope for the future. Oh yeah absolutely. Covert IS REVEALING. Something we all should know. We are all together. It affects us. Disease makes that clear. Because you're there is no individual decision that doesn't have consequences but we're all in together and something. That's been mostly gratifying. Something I've been really you know continually like can tear up if I let myself think about. It is how much from the middle of February forward to now all over the world. People have made dramatic changes to how they live. Inconvenient changes the personally damaging in many cases. Because they're trying to say save themselves but also save the lives of their neighbor Or their grandmother that they accidentally transmit tune and that to me is is remarkable and and also you know moving to a professional scale one of the things. That's also been I think really promising and really GonNa just gratifying. I was prior to this three months ago. Most of my work was on. Polio transmission with applications largely towards developing world. I didn't have close relationships for the most part with public health officials. And you know I had a peer group of different models but we often would talk more to each other and you know and if I had relationships they were in place as far away that I wasn't intellectually was trying to help wouldn't feel close to and I've watched you know the fact that I'm here right now because so many people from so many different organizations with so many different backgrounds are like all just bent towards good. And we'll like let's work together. I don't care how we used to do. It will is something of value here. Let's figure out how to make it work like we're in it together and figuring out how to make it work has just been awesome. It makes me sad that it takes something like this to really make that crystal clear but boy. I hope we remember it. A One cove is under control or hopefully on. Thank you again so much to Dr Mike. Familiarity for giving us the low down on math models. It was great. We covered so much ground in that interview to another. Phanom Interview Erin. Loved it a lot getting to listen to it? Really truly thank you thank you. I mean he did. He did such an awesome job. Though I thought of explaining I mean this is such a complex topic and so to break it down in this really accessible way like. That's not an easy thing to do. So we appreciate it. We really do. I think a lot of people get very scared when they hear about math and I feel like that made math not so scary. Yeah absolutely okay so Aaron. What did we learn? We've learned so so very much. Okay what are the top five things we learn to how five things okay number one math models of infectious disease can help us? Ask and answer all kinds of questions. And they come in all different shapes and sizes but in general they're used for two basic purposes number one models can allow us to imagine a multi verse of possible outcomes and this can help us make decisions about which course of action to take or which policy to put into place. Aaron. I think you said it's like an endgame possible. I'm sorry infinity war. It's like when doctor strange is like what are all the possibilities. Let me just go through the six billion of them. Wow I just got called out hard thing the wrong movie. Sorry get your marvel movies right here. Okay the second thing that models can do is help us to understand what happened retrospectively which is really useful since somethings we can't measure directly and there's also this inherent trade off between making models more complex or keeping them very simple complex models allow us to ask complex questions but you often will sacrifice accuracy for that because of all of the assumptions that you have to make in those models you end up using these more complex models to make decisions about which option is better whereas simpler models might be used to actually forecast what might happen at least in the short term. Yes definitely very cool. Yeah number two. The modeling that most of us are probably familiar with is weather forecasting. This blew my mind. I mean I think it's a really good. It's a really good way to put it. It's a really good way to think about it. These comparisons yeah and so in weather forecasting. Of course you get these predictions for what's going to happen later today or tomorrow or this week or next week. But there are several big differences between modeling the weather and modeling. An epidemic or pandemic. The first is that we have a wealth of incredibly detailed and long term data on weather patterns whereas something like Kobe Nineteen. We're still very much learning as we go. Another huge difference is that unlike whether prediction these models of infectious disease can actually change. What happens in the future so we really shouldn't think of infectious disease modeling as making predictions? But it's more about imagining a bunch of different scenarios that could happen depending on the choices we make now and I think this is particularly important to remember as we revisit some of the earlier models of cove in nineteen. Under what circumstances were they predicting this or that amount of deaths? Many of those models may have been estimating the intensity of the pandemic if we did nothing to control it so the fact that the case numbers or deaths are below right now what was predicted in those scenarios does not mean that the physical distancing or the shutdowns that these measures that we've taken it doesn't mean that they are too extreme but rather it's more that their evidence that they are working to actually slow the pandemic and prevent those worst case scenario from happening. Right yeah I feel like that's such an important point because it's really easy to look at it and say. Oh well what's happening now doesn't match those models. But that's not really the point of those models number three as we've talked about before on this podcast epidemics tend to follow a curve where we have a steep increase in cases peak followed by sharp decline. Often that decline in cases happens because you run out of susceptible people to infect however with Cova nineteen. We still have an enormous amount of susceptible people that we need to protect from infection. So we can't necessarily expect to see that sharp decline. Our collective behavior will be the thing that determines the shape of the curve not just the transmission dynamics of the virus by practicing distancing. We're manipulating that are not remember. And we're driving it down as much as we possibly can. If we lift these measures the effective are not could climb back up and we could end up creating an epidemic curve. That looks more like eight. Kimmel with multiple humps. We don't want a camel curve no offense to camel no offense to Campbell's very cool yeah number four. It seems that physical distancing might have to continue for a very long time in order to keep that effective reproductive rate very low. But we're still learning so much about Kovic. Nineteen that could change the exact nature of these physical distancing measures and one of the areas that models are looking at is teasing apart which measures seem to be most effective and which may not be that effective and exactly what kinds of resources we would need to control the spread of infection once a case is detected so a ramped up test trace isolate quarantine strategy and based on what we learn. There might be adjustments to the current. Everybody physical distance strategy to only having certain people or certain places do physical distancing but because of what we've learned so far about asymmetric and pre-symptomatic individuals and their ability to transmit the virus contact. Tracing alone is probably not going to be enough. So some physical distancing seems like it's going to remain for at least a good amount of time in the future. Yeah like we're in this for the long haul. It seems yeah or at least a long haul who knows what on call number five in general if you are looking and thinking about whether to trust a model or not. There are a couple of rules of them number. One be wary of absolute predictions especially if they are long-term ones and if someone says they're almost certainly going to be x number of cases in September maybe take that prediction with a grain of salt because apparently there from the nineteen twenties. Exactly who trust that kind of a voice you know number? Two listen to how the model is described and weather. Uncertainty is acknowledged if a person describes or acknowledges the uncertainty in the model. That's actually a good thing if someone says well. This is one possible outcome based on X. Y. Z. But we don't know how much of a role ABC plays. That's good knowing and discussing. The limits of a model is a matter of scientific integrity and we should be wary of someone overstating. What their model can do. I think that's good general practice as good as say it's a pretty good like life role. Someone says I'm an expert. I know everything. Don't question my knowledge authority like Lou. Well see I know everything about everything. That's the kind of voice you know what I mean Erin sure okay. Well Yeah I mean. Those are the top five things but there's definitely so often were That you can pick out of that interview incredible. Hopefully you learned that math is Kinda fun because I think it. I think it's fun. It is so powerful. What you can do. It's amazing. Yeah I love it. Yeah and if you want to learn more about math or maybe get a little bit deeper of a dive into infectious disease and how it's modeled and by math. I watched an amazing lecture by Robyn Thompson at Oxford Mathematics and this is on Youtube. It's titled How do Mathematicians Model Infectious Disease Outbreaks? And he did such a great job of again sort of like taking you through. You know what a model is all of these different aspects and there's also a visual component. Which really might help you to see some of these different numbers and figures that we talked about like on your actual computer screen so we will post a link to that on our website and if there are any modeling books like for the lay person that anyone wants to suggest or send our way. Please please do so. We will share them most definitely another thing that I wanted to call out not necessarily a resource but just a fun. Little thing that I found is a book that we got an advanced reader's copy of called the down days by AILSA Hugo. And I really liked it. So it's a it's a fiction book and the timing of this could not be like spookier because it first of all it. Do you remember the Lake Tanganyika laughter epidemic that we talked about in the dancing plague? I remember you talking about it. Okay well it's sort of like a fictionalized account of that but in the future like current times and but it's like goes on for a long time. Everyone's wearing masks all over the place. Everyone wears gloves everywhere. There's like full-on quarantine. All the time in one of the the wild things to that happened was that like people were like drinking bleach because someone told them it was going to clean insides. Yeah Win. Fiction is so close to real life that you're like why it's it's spooky but I really enjoyed the book and it comes out like in in early. May or early June. I can't remember we're going to put it on our bookshop and are good reads list But yeah if you want to kind of like even dive deeper into the world of like fictional into the world of pandemics. Here's a fictional one. You can try out and then one final thing that I wanNA shout out. Is that our lovely lovely heard. The heard on read started a silver linings thread. So if you want to add your silver lining Go on Reddit and check out the sub reddit. Teepee W K Y and add your silver lining. It's really wonderful and really like it makes my heart. Happy to see all those. If if you need just like a little a little mood booster you could just go on and read everyone else's silver linings. Because you're happy it's excellent. Yeah well that was a really fun episode. Thank you again so much Dr Lori for spending the time to chat with us and all of our listeners. We really appreciate it. Yes we do and thank you to blood mobile for providing the music for this episode and all of our episodes and thank you to you listeners. For listening and sticking along. We hope that you enjoyed this map. Heavy Episode Yeah. Let us know. Yeah and also yes. Thank you okay until next time. Wash your hands. Filthy Animals

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