In Episode 12, Quinn and Brian ask: Can algorithms predict the next major pandemic? Pretty please? Joining us: Dr. Sam Scarpino, Assistant Professor of Marine & Environmental Sciences and Physics and a core faculty member in the Network Science Institute at Northeastern University. We discuss whether, and if so, how advanced algorithms and data science can help predict and prevent the next major pandemic. Also, the importance of a liberal arts education, bad wifi in 2018, and my wife’s iPhone. Want to send us feedback? Tweet us, email us, or leave us a voice message! Links: Dr. Sam Scarpino on Twitter Sam’s book selection: On Immunity: An Inoculation Dharma.ai Quinn Emmett on Twitter Brian Colbert Kennedy on Twitter Intro/outro by Tim Blane Subscribe to our newsletter at ImportantNotImportant.com! Like and share us on Facebook! Check us on Instagram! Follow us on Twitter! Pin us on Pinterest! Tumble us or whatever the hell you do on Tumblr! Ok that’s enough good lord
Quinn: Welcome to Important, Not Important. My name is Quinn Emmett.
Brian: And I'm Brian Colbert Kennedy.
Quinn: And our guest today is Dr. Sam Scarpino, a data scientist and Assistant Professor of Marine and Environmental Sciences and Physics, and a core faculty member in the Network Science Institute at Northeastern University. Sam works in infectious diseases, forecasting and predictive modeling, disease genomics, and transcriptomics, outbreak surveillance, network science, and decision making under uncertainty, which is basically just parenting.
Brian: Yeah, yeah, yeah. He does it all. You just named a thousand things.
Quinn: Right. And our question today, for episode 12 is whether and if so, how, advanced algorithms in data science can help prevent the next major pandemic.
Brian: Sam seems to think that the answer to that is yes.
Brian: It really was an awesome conversation. Sam's not going to say it, so we'll say it. Basically, you're welcome everyone. Here's another guest that's basically keeping you alive, even if you didn't realize it.
Quinn: Right. Which was one of our intentions, right? With this thing. One of the themes was to highlight these people on the ground doing the hard work that can talk about a specific topic that's affecting you. These people that aren't in the headlines.
Brian: Yeah. A lot of people that you might not know are super important, actually.
Quinn: Right? And speaking of headlines, you probably missed the most important one, so make sure you go to importantnotimportant.com, and subscribe to your, to our ... not yours.
Brian: It's ours.
Quinn: I guess it's everybody's, free weekly newsletter. Right now. So go ahead.
Brian: We'll wait.
Quinn: We'll do that right now. Listen folks, climate change is here. It's still here. It's going to be here for a while.
Brian: Long time.
Quinn: It's getting warmer in LA again.
Brian: Yep. It's 80 degrees. 80 degrees this week.
Quinn: Yep. And Brian swears that none of those things is why he shaved his beard, and now looks like a gross toddler.
Brian: No I don't look like a gross toddler, I look like a-
Quinn: You do.
Brian: ... an adorable young man.
Quinn: No, it's not okay. Uncanny is not the right word. It's a toddler on a motorcycle. With tattoos. What kind of parent lets their toddler get tattoos? Hopefully no parent.
Brian: You're describing something that is not what sits before you, okay? I just look a little bit different. I look fine.
Quinn: Look, I don't judge people because they look different, but it's very strange.
Brian: It's very strange, I'll agree to that. I've told you before and I'll tell you again, it was not up to me. I was shaved. I have been shaved. So it's going to grow back and everything's going to be fine. And shut up.
Quinn: So you're slathered in tattoos, there's a new one every six months? Or year?
Brian: Oh, let's go year.
Quinn: Okay. Let's say you're allowed to have a child one day.
Brian: Right. "Let's say you're allowed to have a child one day," he says to me. Okay, got it.
Quinn: By both whoever your significant other is, that poor unfortunate soul-
Brian: Oh, you're so sweet.
Quinn: ... and by society. When are they allowed to get a tattoo?
Brian: They're allowed to get a tattoo when they're legally allowed to get a tattoo. They certainly-
Brian: ... can't do it when they live with me. And I will try to impress upon them the importance of holding off for as long as possible until they truly think that this is a thing that they want to be on their body forever.
Quinn: What was your first tattoo and how old were you?
Brian: I was 18 years old. My very good friend, my best-
Quinn: Like 18th birthday?
Brian: It was in the summer after. So I turned 18 in October, went to Florida, in the summer.
Quinn: That was your first mistake. Sorry.
Brian: Sorry Florida. My best friend and I got [crosstalk 00:03:49]-
Quinn: Your first tier friend.
Brian: My first? No. There are many friends in the first tier, you included. Not many. There are some. You're included.
Quinn: Either way, it hasn't worked out great for me. Keep going.
Brian: We went down to Florida for a trip, and we got matching tattoos. At that time in Illinois you had to be 21, so we couldn't-
Quinn: That's adorable.
Brian: ... do it at home.
Quinn: Wait. Is he the one with the iron?
Brian: Yes, that is the same friend. That's not our matching tattoo, though. That's his.
Quinn: It fucking is now. Why don't you tell everybody about that one?
Brian: Well, in Florida we got the matching tattoos of a Chinese symbol that we were told by-
Quinn: It's not.
Brian: It's definitely not.
Quinn: Whatever it is it's not.
Brian: I'm pretty sure our tattoo artist's name was Nighthawk.
Brian: Pretty sure. And we went in there, we had an appointment. We were there on time, and when the appointment was supposed to start, he came out and he was like, "I'm gonna finish this sandwich first."
Quinn: Sure. Yeah. [crosstalk 00:04:41]. Whatever you need, Nighthawk.
Brian: So Nighthawk finished his sandwich, he tattooed some shit on us that probably doesn't mean anything that we think it is, but they're matching, and it's adorable and he's my best bud. And yeah, then-
Quinn: What's amazing is he stayed your best bud considering-
Brian: The next story.
Quinn: Mm-hmm (affirmative). Please.
Brian: I have on my arm a tattoo of an iron burn.
Quinn: An iron? What kind of iron?
Brian: Just like your average clothing iron for when you need to get wrinkles out of your button-up.
Quinn: Why do you have that tattoo, Brian?
Brian: What had happened was I mistakenly thought that the iron in front of me was warm, not hot, and I thought it would be funny to sneak up behind my best friend and give him a little spook with a warm iron.
Quinn: That's what people do to their best friend.
Brian: I think everybody probably has that thought at some point.
Quinn: And how did that go for him?
Brian: Super bad. Really, really bad. It was so hot, and it stuck to his arm and I pulled it away, and skin had so quickly melted and stretched.
Quinn: As skin does.
Brian: It was the dumbest thing maybe I've ever done.
Quinn: Well ... And as penance, you did what?
Brian: Yes, as penance, I think I was either visiting him or that's when I lived back home? But anyway, I moved back to LA or I was back in LA, decided to apologize by having the exact iron burn marks from that iron. I had him take a picture of it and send it to me. I brought that to the tattoo shop. I said, "I need this iron tattooed on me, but as if it had burned me." And then he did it. It really looks wonderful. It looks like a burn. People think it's a burn all the time. And then actually a couple days after I got this tattoo, the tattoo artist was fired for tattooing drunk. So another fun part of the story. A lot of fun.
Quinn: Tattoos hurt.
Brian: Oh, yeah.
Quinn: But not as bad as a hot iron.
Brian: I think he got the short end of the stick on that one.
Quinn: Both in the surprise of being burnt by his theoretical best friend, with a hot iron.
Brian: Mm-hmm (affirmative). For no reason. As a joke. It was dumb. But now everything's fine. He was just here in town visiting. We were friendlier than ever. Now all is good. And plus he got a tattoo over his burn. You can't even see his burn anymore. I actually, in that regard, I got the short end. Plus I had to pay for mine. He got his for free.
Quinn: You're a monster.
Brian: Yeah, basically.
Quinn: So listen, great conversation today. Thanks to everybody for tuning in. We're excited about this one. Let's go talk to Dr. Sam Scarpino, shall we?
Brian: Let us.
Quinn: Awesome. Our guest today is Dr. Sam Scarpino, and together we're going to ask whether advanced algorithms and data science can help prevent future major outbreaks of disease. Dr. Scarpino, welcome.
Sam Scarpino: Hi, thanks for having me.
Brian: Absolutely. Thanks for being here. Sam, tell us who you are and what you do.
Sam Scarpino: I'm a professor in the Network Science Institute at Northeastern University in Boston. What I spend most of my time doing is trying to understand why certain diseases spread and others don't. Why certain diseases spread further, faster, stronger in some populations, in some countries, at some times of the year and not others. And then to translate those improved understandings into improved public health practice, improved clinical decision making and improved response to disease outbreaks.
Brian: Seems important.
Quinn: Seems important. And you do all of this through just gut intuition, correct?
Sam Scarpino: Unfortunately, not.
Quinn: You're a witch doctor. Right.
Sam Scarpino: I was going to make a joke about politicians and gut intuitions, but maybe I'll leave it.
Quinn: No, no, no. All of those things are welcome here.
Brian: Yeah, please.
Quinn: We can always take them out later if you're horrified by what's coming out of your mouth. Awesome man.
Brian: So let's set up our conversation for today. Our listeners have heard this a million times, but we're big believers in questions. But questions that don't provoke action are basically just philosophy, and these times call for action, and that's what we're trying to do here, where we're trying to go.
Quinn: Right. So what we're going to do is we're going to set everybody up with some context for discussion, specifically around the subject matter and the history of it, where we are today, and then dig in a little bit how you apply, and then progress to our question of the day. And then finally, most importantly, some actionable steps our wonderful listeners can take. Because everybody is on the action bandwagon these days. Does that sound good, Sam?
Sam Scarpino: Sounds great.
Brian: I haven't heard "action bandwagon" before. I like that phrase. That was good.
Quinn: Okay. Leave it alone.
Brian: All right. So get ready for this one, Sammy. We always start with one question to really get to the heart of why our guests are here, why you're here today.
Quinn: Here existentially, and also on the podcast.
Sam Scarpino: Right.
Brian: Yes. The big here. So instead of saying, "Tell us your life story," or whatever, we like to ask why are you vital to the survival of the species? Don't hold back.
Quinn: Be honest.
Sam Scarpino: Wow. Wow, that's a hard question to answer with-
Brian: We thought about giving you a little warning, and then we said, "Nah."
Sam Scarpino: Well, I think the biggest part of me wants to say that there isn't anything that I'm doing that is vital for the survival of the human race or the planet, because I actually believe very strongly in the sort of ethos of call to collective action, that as a group, we can accomplish things that any one individual could never hope to accomplish.
Sam Scarpino: Maybe to provide a slightly better answer in terms of maybe the motivation for the question, which is learning something about me, one of my big roles as a professor is to mentor and train the next generation of scientists, and to interact with the public and with public health policy makers regarding the science and practice of disease forecasting, disease modeling.
Sam Scarpino: And so I think those two roles, mentoring-teaching being one, and interfacing with the public/public health policy and decision makers, are the things that I do that I believe are having the biggest impact.
Brian: Yeah. I mean I think that's a pretty great answer.
Quinn: Pretty damn good answer.
Brian: Pretty vital.
Quinn: Pretty damn good answer.
Brian: Although you're-
Quinn: You guys, it's so funny. We've really gone back and forth on whether to give people advance. And we started asking this about halfway through our run so far. Obviously we're still relatively early days, but it's always tempting to give people advance notice, but I don't want a stock answer. I kind of want people to be like, "Oh my god. What the hell? What do I say here? How do I toot my own horn without sounding like-"
Brian: Yeah, and the responses have been so wonderful. I wonder how it would be if we went the other way and gave the warning? I think we're doing it right.
Quinn: Maybe somebody else besides Sam will give them that opportunity.
Quinn: Because he didn't get it. All right. With that, let's dig into some context for today's topic question, which is not too dissimilar from our previous conversation with the amazing Dr. Nahid Bhadelia earlier this month.
Quinn: Which is where we're talking about big nasty diseases and the people who are trying to stop them, and you guys do it in very different ways. We're going to talk about a little bit here the sort of history of disease and trying to figure out where they come from and why. And then where we are today, and how you're sort of working on it, and then talk about the future.
Quinn: So people always say, "History's written by the winners." Well, if you really look at this stuff, history has basically been written by at least up to penicillin or so, the lucky folks who survived some truly fucked up diseases over the past thousand plus years.
Quinn: History has a long list of these brutal diseases and pandemics that cut through mostly densely populated areas. For a variety of reason.
Brian: Typhoid, bubonic plague, black death, cholera, influenza, AIDs.
Quinn: AIDs for sure. And there's a lot of reasons why they rage so hard.
Brian: Yeah. Some reasons are even identified and fixed already. Clean water, for example in some places. Certainly not-
Quinn: Not all of them.
Brian: ... everywhere. And yeah, we'll probably talk about that shortly. Or specific symptoms or combinations of symptoms, better reporting, ending stigma.
Quinn: Ending stigma around disease has been really helpful.
Brian: Some reasons we've identified and either can't do anything about or we're building on actually. Like city density, reverse urban sprawl, vaccinations, antibiotics.
Quinn: Right. And there's always going to be outliers, like Typhoid Mary, right? Quickest version ever, and Sammy, correct me if I'm way off base here. She was asymptomatic. She was a family cook, which worst profession ever for somebody with typhoid. And she kept basically going job to job and accidentally killing people. And they figured her out, finally. Not her fault. They isolated her on an island, like Napoleon. She didn't love that. She broke out and started cooking again. Which again, not great. But at that point, blood's on her hands a little bit. So asymptomatic, hard to pin down. But there's always going to be issues like, that, and that's why we have the centers where a friend of the pod, Dr. Bhadelia, come in and save all of our collective asses.
Quinn: And then, modern day we haven't fixed sanitation or clean water in very large parts of the world. And as climate change keeps getting worse, we're going to continue to have major disasters where even in developed places that goes away. Otherwise in Yemen's cholera issues should be an international crises. Right? Pakistan's depending on India, of all people, for vaccinations. India itself is one of the least available countries for drinking water. Look at Nigeria, places like that.
Brian: There's I think 844 million people don't have clean water? And that's certainly not going to get better with climate change and immigration.
Quinn: Right. So let's talk about the future. We've got across all these different disciplines, whether it's traffic or disease or whatever, the ability now with computers to sort through massive sets of existing data, the stuff that's been sitting around forever, a large part of it now, as you look at health records, is transcribing and making things readable and standardized. But also live incoming data where it's prepared correctly. And I think I have to imagine that's where our guest spends most of his time today.
Quinn: So we've gone from being completely unable to understand where and how a disease starts or what it looks like, to modeling where it's coming from, where it's likely to go. And in some cases, how we can stop it from starting all together. Or at least the most high risk area.
Quinn: So that's the history of fucking disease. Sam, correct me if I'm wrong on any of that stuff?
Sam Scarpino: I think from a high level perspective, you've gotten everything totally correct. I'm sure there are some details in there that some of us aren't aware of from the Typhoid Mary story, there's almost always a caveat or ...
Quinn: Oh sure.
Sam Scarpino: I think from the perspective of understanding the history of infectious diseases in about 37 seconds, that's pretty accurate.
Quinn: Yeah. You're welcome. All right. Well, listen. That's enough from me. With that for some context, let's focus on our question. Can advanced algorithms and data science help prevent future major outbreaks of disease? Sam, go.
Sam Scarpino: The short answer is yes. The longer answer is that many of the problems currently facing data-driven decision making, machine learning, artificial intelligence, data science at large are also problems when trying to apply these methods to infectious disease response. So maybe I'll give two examples. The first one will provide some color to why I think that these data-driven computational mathematical approaches can have a real impact. The second, maybe why we should pause a bit and be very careful about how we proceed.
Sam Scarpino: So the good news could be if we think about the Ebola outbreak, that started in 2014, in West Africa. One of the reasons that it ended up growing so large is that it took a while for individuals on the ground to understand that it was Ebola causing these illnesses, and not something else. And for the international community to wake up and deploy resources.
Sam Scarpino: The types of methods that the field that I'm in works on, and that sort of data science uses more broadly, would be very applicable to this kind of situation. Basically asking the question, "Is this thing that we're seeing like other things we've seen before, or is it completely different or a little bit different or different enough that we should be concerned?"
Sam Scarpino: And I think every indication is that had we been applying some of these methods to data coming out of West Africa, we might have been able to pick up the outbreak earlier.
Brian: It seems wild that we weren't doing that.
Sam Scarpino: Well one of the issues is actually what I think is the primary reason that the outbreak grew so large. It's actually related to the second point that I was going to make, and I also think it's in general one of the biggest explanatory factors in terms of disease prevalence. And that's poverty and lack of infrastructure.
Sam Scarpino: So these countries in West Africa had just emerged from decades of civil war. They had almost no functioning healthcare system, so something like five physicians per 100,000, eight nurses or community healthcare workers per 100,000, and eight hospital beds per 100,000. Prior to the outbreak.
Brian: Holy shit.
Sam Scarpino: Yeah. And so part of the reason there wasn't any data is because there weren't any real healthcare facilities that were available to most of the individuals that were there.
Sam Scarpino: Just to try to put this in really stark perspective, I did a back of the envelope calculation for a blog article for Nautilus magazine. Just kind of asking if we took some neighboring countries, like Nigeria, Central African Republic, Democratic Republic of Congo, that have stopped Ebola outbreaks, and just said, "Well what if we needed to increase the infrastructure associated with public health in Sierra Leone, Liberia, and Guinea, up to the level of these other African countries that have stopped Ebola outbreaks, how much would it cost?" And the number was something like 50 to 200 million dollars. Which is about what we spent on television advertising for the midterm elections. The last time we had them. So it pales in comparison the billions of dollars in actual cost and economic cost that were associated with Ebola this past cycle.
Quinn: Right. And this is preventative money. To make sure this shit doesn't get a lot worse.
Sam Scarpino: That's right. Although preventative is something that's very hard to fund. Through nearly any organization, there are a handful of organizations that will fund preventative work for infectious diseases, but the vast majority is all around response. And then part of that is because the organizations that are involved in the response are overwhelmed as it is, and so they don't have the bandwidth to sort of work on preventative [crosstalk 00:20:43].
Quinn: So the entire American health system is built on reactive as opposed to preventative. Not exactly a model for success.
Brian: Could we switch that up?
Sam Scarpino: Oh yeah. Absolutely. As a part of the same analysis, I have those data on health care infrastructure, as well as healthcare spending for every country on earth. And has been reported many, many times, we pay more per capita than anyone else, and we have a healthcare system that is-
Quinn: Not great.
Sam Scarpino: No, not great is generous. That is worse than countries that are spending 10, 50, 100 times less money per person than we are on healthcare.
Quinn: All right. So-
Sam Scarpino: We're digressing.
Quinn: No, no, no. We love to digress. It's our favorite thing. It's a shock that any of these things actually get done. So talk to me a little bit and pick your example here, because I imagine there's a few different versions. Again, we've got some nerdy listeners, but we want to help them really get an understanding. Explain to us how you build a model or a case from soup to nuts. When do you get started? How do you get started? Do you do any of these things sort of preemptively, or is it a, "Whup. Ebola's starting." Talk us through it. How does your job work, basically?
Sam Scarpino: It works in two different ways. The first is that we will have sustained and ongoing research programs focused on particular diseases, or particular mechanisms that might cut across disease, so poverty being one of them. And so in the background, when there are no health emergencies related to infectious diseases that are ongoing, we're working on scientific research associated with past outbreaks. What this usually looks like is improving our understanding of different mechanisms related to disease transmission.
Sam Scarpino: An example would be some work we did a couple of years ago on how replacing six school teachers if done imprecisely can actually accelerate the spread of influenza. The easiest way to understand this is the teacher almost certainly got sick because of their students. School children are the primary drivers of influenza transmission.
Quinn: They're disgusting.
Sam Scarpino: To put a fine point on it, yes.
Quinn: I've got some pretty disgusting kids.
Sam Scarpino: You take this sick teacher and replace them with a substitute teacher who is not sick, and you're almost certainly moving them from an environment where there are not a lot of sick schoolchildren into a place where we know there are sick schoolchildren because the teacher just had to get replaced. And then that individual is at elevated risk of becoming infected themselves.
Sam Scarpino: And so what we did to show this, is to construct a mathematical model that describes in an abstract way, what a classroom looks like in terms of social contacts, what a population looks like in terms of social contacts, and then how we might expect a disease to move through that population if we either are or are not replacing teachers as they get sick.
Sam Scarpino: One of the reasons that I think it's so important to use these kinds of models is that it provides a mechanism for structured reasoning through what are otherwise very complicated problems. But when the paper came out, one of the initial interpretations is that we were advocating against sick leaves. And categorically that's the opposite of what we're advocating for.
Sam Scarpino: So it turns out when you look at what's actually going on, if you replace the teacher very, very quickly, then there's no risk for increased spread. It's only if the teacher stays at work for a couple of days and then has to go home because they get sicker that you end up with this accelerating spread. And so what we're really advocating for is a more flexible sick leave policy so that people don't do what I think is very common in the US, which is you have limited sick days, you go in, you try to push through.
Brian: You still go to work when you're sick.
Sam Scarpino: You're sick for a couple of days at work and then you get worse, and then you go home. And that's about the worst thing that you can do from a population perspective in terms of transmission.
Quinn: It makes sense, but it's fascinating.
Brian: But yeah. That's absolutely what people do. You just try to-
Sam Scarpino: That's right.
Brian: ... get going. You got this.
Quinn: Right. It's [crosstalk 00:25:29] the whole British thing during the war, and now has been abused and every tchotchke store in the world is, "Keep calm and carry on." It's like, "No, well ... but don't, actually." Maybe do that in the comfort of your own home where you're not poisoning other people.
Brian: Yep. Wow.
Sam Scarpino: So the answer to the second kind of part of your question is, if there is an outbreak, like Ebola, like Zika virus, like the influenza pandemic in 2009, then a lot of us will deploy our resources to respond to that particular outbreak. So during Ebola, there were weekly calls with a large number of infectious disease modeling groups at universities and relevant parties in the US government around what we were doing, what we were seeing, what the models were saying. What they were seeing at the health agencies in the US and how that was fitting into the broader response.
Sam Scarpino: An example would be from Ebola, trying to use the genome sequencing data of Ebola viruses collected in Sierra Leone, to estimate the number of cases that we were seeing in hospitals, versus the number of cases that were being completely missed by the healthcare system because people weren't going to the hospitals. Maybe they were dying at home.
Quinn: If I can interrupt real quick, so curious questions, when something like that, like Ebola happens in that situation, and like you said, calls start weekly, do you guys, and "you guys" I mean your Justice League of disease modeling friends, have to fight to say, "Hey, make sure this info is getting to us, or has it started to become part of standard protocol that we need to get that sort of data to you folks to help prevent it from getting worse? Where are we in the threshold of your profession and your skills being a standard part of the response?
Sam Scarpino: Well I think there's kind of maybe two questions that I'll try to answer there.
Quinn: Yeah, I'm sorry.
Sam Scarpino: No, that's okay. I'll answer the easier one first, which is to what extent are individuals with skills like mine being integrated into the response? What we're seeing is a really rapid increase, just like we are kind of across all sectors in the use of people with data science and modeling skills as a part of decision making. Right? So I think that the ability to visualize, analyze, communicate large and complex data sets is valuable. And that value is being realized in a variety of sectors, including infectious disease response.
Sam Scarpino: The harder question is on the data availability and the data sharing. And that one we're seeing improvements. Each outbreak, it seems to get a little bit easier to share data to coordinate, but it's still very complicated for a variety of reasons. One of those reasons is that we're often dealing with highly sensitive, personally identifiable information associated with health. Which means that it has to be protected and safeguarded and used responsibly, used ethically. And so even just negotiating what that looks like, what is the ethical use of data during an Ebola outbreak? It takes time. It takes time to coordinate across everyone. It takes time to decide what that actually means in the context of an outbreak.
Quinn: And theoretically, you're working with very limited time.
Sam Scarpino: That's right. The second is that there's also a lot of interest on the parts of countries, regions within countries, not to share data because they don't want, for example, tourists, to stop visiting. We saw this in Florida during the Zika virus outbreak. Florida wasn't sharing detailed information on where Zika virus cases were occurring, in large part because of their fears around tourism dollars. Which of course were also very real fears, because tourism did take a hit during the Zika virus outbreak. So there's that aspect of it.
Sam Scarpino: And then there's also a very unfortunate aspect, which is that scientists are often competing with each other for funding, for publications. They're often competing with public health agencies for funding and publications, which means that the interests aren't always as aligned as they should be.
Sam Scarpino: And that third piece is something that many of us have been working very, very hard to solve. Because that's actually something that we have more control over than the other two pieces.
Brian: Fascinating. So much stuff that the average person doesn't think about.
Quinn: That's why we're here today, Brian.
Brian: Yeah, yeah. Really wild.
Sam Scarpino: Well related to that, and maybe I'll very quickly mention the second thing which is the note of caution about these data-driven methods, in part because as you mentioned, some of your nerdy listeners are going to be going crazy because I promised two stories and I didn't give the second one.
Brian: They're just going to lose their minds, Sam.
Sam Scarpino: Maybe like you can see the parentheses being left open in my code.
Sam Scarpino: Like nails on a chalkboard probably to some people right now. We finished some work with the state of Texas on predicting inpatient hospitalization demand for influenza, and influenza is one of the leading causes of mortality every year in the US and globally. It's usually in the top 10 both in the US and globally.
Quinn: And then you have a year like this year.
Sam Scarpino: That's right. And so there's a huge amount of interest from the perspective of hospitals in preparing for the flu outbreak. They want to know how many beds they need, how many ventilators, how many nurses, physicians, et cetera.
Brian: More than eight beds per 100,000 people, please.
Sam Scarpino: So they want to know how many individuals with influenza they should expect, and so they're interested in forecasts. They're interested in forecasts from public health agencies, from academic researchers, but the data from hospitals doesn't show up in most of the health agencies until well after the flu outbreak is over. It's usually three or four months before the hospitalization data are available. That's because it takes a long time to coordinate, aggregate the data, get it disseminated to everyone, et cetera.
Sam Scarpino: What they want to do, is use more real time data to make forecasts. So the real time data that we have are emergency department visits, how many people walk through the door of the emergency department last week with flu-like symptoms? Data from primary healthcare providers, so family doctors, on how many of their patients had flu-like symptoms. And then data from things like Google, which is how many people are searching for cough, sore throat, or-
Quinn: Google "flu". Right.
Sam Scarpino: That's right. Google flu trends. And so what we did is we built a model to forecast inpatient hospitalization demand using those kinds of data, and we can show that for individuals who live in neighborhoods in the upper three-fourths of the income distribution, we can highly, with high degree of accuracy, forecast hospitalization demand. And that's not surprising because those same individuals who are going to the hospital, they almost certainly went to the emergency room, they almost certainly went to their primary healthcare provider. They almost certainly, or someone in their family almost certainly Googled for their symptoms.
Sam Scarpino: However, for individuals in the lowest income quartile, not only do they have three times the rate, so three times per capita hospitalizations, as the other groups of the population, we have almost no ability to accurately forecast the hospitalization demand. In large part because those individuals are sicker because they don't have access to primary healthcare providers. They don't really even have access to emergency departments. And so they're invisible to the public health agencies, the state and local governments, and to the hospitals.
Quinn: And I have to imagine in some way, they're probably the most susceptible to these type of diseases or outbreaks, that swatch of humanity.
Sam Scarpino: Well, certainly poverty is amongst if not the biggest explanatory variable in terms of why some groups, some parts of a city, some parts of a country, some countries have a higher health burden than others.
Sam Scarpino: It is still very much an open question exactly why that. Some of it has to do with the issues you were discussing in the beginning, sanitation, access to good drinking water. For influenza, one of the big drivers of hospitalization in children, is exacerbated asthma symptoms. So if you live in an area with low environmental quality in terms of the air, or if you don't have access to inhalers, or your prescriptions aren't filled, then you're at higher risk for hospitalization.
Sam Scarpino: That's another way in which you could have a higher health burden in lower socioeconomic populations. Maybe they have lower air quality in the neighborhoods or in the households or in the schools, where they don't have access to primary healthcare to make sure that their prescriptions for inhalers are filled.
Quinn: Right. And they probably don't have healthcare because America's a nightmare wasteland.
Quinn: All right. So you did a project like that with Texas. Is your proactive work done more on a sort of a geography basis, or a disease hotspot basis? I imagine there's plenty of overlap. I'm just picturing a super cool headquarters with flat screens and something flashing red, and you yelling at some intern, like, "Get me on that plane."
Brian: Oh my god. Tell me that happened.
Sam Scarpino: I'm usually the person being yelled at to get on the airplane.
Quinn: Oh, shh. We don't have to tell people that. That's fine.
Sam Scarpino: No, I know. When I did my PhD at the University of Texas at Austin, we did have a giant bank of flat screen TVs where there would be maps of different outbreaks going on.
Quinn: That's wild.
Sam Scarpino: And my PhD advisor would be asking me very politely to get on airplanes and-
Quinn: Right. I also imagine, though, that that bank of TV screens, for like a normal person, it's just showing live outbreaks around the world, that's kind of something you can't un-see. You know? But at the same time, when we talk about climate change and shit like that on the podcast, or amongst each other, so much of it's happening to the air and the water. Which are things you can't necessarily see. So people conveniently either they just don't see them, or they put their head in the sand about it. And all of the sudden, the ocean currents have changed and we're fucked.
Quinn: So maybe people need to see those big flashing screens and Sam being told very politely to get on a plane and, "Save those people."
Sam Scarpino: I can imagine a counter argument, which is people being desensitized as a result of so many warnings. And I think that's actually one of the things that we wrestle with the most in terms of how we operationalize the tools that we're developing, which is that you want people to be sufficiently scared/motivated to act appropriately, decisively and quickly, but you also don't want them to become desensitized to the signals such that they stop paying attention. The boy who cries wolf scenario.
Quinn: Totally. And I get it. You can only ask people so many times, make them stand arms. But on the other hand, you have shit like what happened and continues to happen like in California a couple of years ago where because these stupid, rich white people said, "Oh, well nobody has polio anymore. Why do we need to get vaccinated? I'm not gonna vaccinate my kids and let me get the school voucher." And then all of the sudden, everybody at Disneyland has measles. There's got to be some sort of balance. Right?
Sam Scarpino: I think in the context of vaccination, the balance is that people need to get their kids vaccinated.
Brian: Get vaccinations. Right.
Sam Scarpino: Vaccines are safe. There's no question about that. And so the only reason that you wouldn't be getting your child vaccinated, is a selfish one, because what you're doing is putting other people's kids at risk. And there's no other way really to describe that aside from selfishness.
Quinn: Yep. Yeah, we feel more or less the same way.
Quinn: My daughter got whooping cough even though she was vaccinated. And it's just pretty frustrating.
Sam Scarpino: Well I'm sorry to hear that. One of the things that I work on is whooping cough, and that disease is very challenging from a public health perspective, in part because of a scenario that's similar to the Typhoid Mary one, which is that it's relatively common for adults to be infected with whooping cough and not know it.
Quinn: Oh really?
Sam Scarpino: But be able to infect children who will go on to develop symptoms.
Sam Scarpino: I'm actually finishing up a edited volume on pertussis, and one of the things about this disease is that basically since we've been paying attention to pertussis, it's been one of the leading killers of infants. And even after the advent of vaccination, you had lots of countries with low vaccination rates where pertussis remained a major cause of infant mortality. And now in the United States, we've seen this incredible resurgence. It's a terrifying resurgence in whooping cough. Part of it being driven by people not getting vaccinated, but part of it possibly being driven to other issues related to asymptomatic adults.
Quinn: Interesting. Let's talk about the innovation/scientific/medical, et cetera. What innovations are sort of societal progress in the past few years have either helped or hindered your work in how you apply your work every day?
Sam Scarpino: I think there have been a couple of really major innovations. One of which is the increase in computing power, especially tied to Cloud computing environments that allow us to analyze large data sets and quickly disseminate the results around the globe. So even in the course of my still relatively short career, the types of questions we've been able to ask and answer with computational methods has changed dramatically.
Quinn: Mm-hmm (affirmative). Can you give some specific examples of where you've benefited from that?
Sam Scarpino: Right. So some specific examples would be the director of the institute where I work is Professor Alessandro Vespignani, is able to run large scale individual level simulations of outbreaks spreading throughout the United States, spreading throughout the globe. To better understand what might happen with certain interventions, to better understand what the effect or lack of effect might be of things like border closure. And that means simulating the individual action of hundreds of millions or billions of people, hundreds of thousands of times, to get a sense of the statistical uncertainty fast enough that it can be acted upon during outbreak.
Quinn: I don't know why you're acting like this is a difficult thing to do.
Sam Scarpino: In some sense, it's not actually that difficult. It just takes giant computers to do it. Each individual thing that's happening is not very complicated, it's the aggregation of those things that becomes so complicated and so unwieldy.
Quinn: So what do you work on? You got like a 2016 MacBook Pro, you go with the touch bar?
Brian: Me too man.
Sam Scarpino: I've got a touch bar computer, yeah. And actually that's one of the things that is very relevant and makes these really hard problems to work on, is that oftentimes whatever we're going to implement has to run on someone's laptop in 15 minutes. Or 10 minutes, or five seconds.
Quinn: Sure. Sure. Especially when you have to go mobile and somebody yells at you to get on a plane. You can't exactly take your super computer with you.
Sam Scarpino: Right. But that's also one of the things that Cloud computing has helped with, right?
Sam Scarpino: Is that I might have my 2014 MacBook Air, but I can log into my Google Cloud or Amazon Web Services account and get access to more computers than have ever existed on earth.
Quinn: Sure. It's amazing, because that MacBook Air isn't doing anything on its own. I love it, but ... Fits in an envelope, but it's not processing much.
Sam Scarpino: No. It's not known for its computational heft, that's for sure. The second thing, and this is related to what I alluded to regarding the Ebola outbreak and the reporting of cases, is our ability to rapidly and cost effectively sequence the genomes of pathogens during an outbreak, and make those data available for modeling analysis and public health decision making. That's not something that existed in any meaningful way when I started my PhD about 10 years ago, and it's something that's now a regular part of the recent outbreaks of Ebola and Zika that have happened.
Brian: All right. Well, those sound great. Can you tell us what is still missing? What do you need realistically to make this even more efficient?
Quinn: To make it more efficient, to make it more practical, to make it more either impactful in preventing these things, which as you said, prevention is really tough to define. It's like Obama, "Save nine million jobs." A lot of people say, "What does that mean?"
Brian: And they're terrible people.
Quinn: But on the other hand, similarly, efficient and speedy in the case. What technologically wise, what's out there?
Brian: Faster MacBook Airs, of course. We've covered that. But what else?
Sam Scarpino: That's right. So faster MacBook Airs, high on the list of priorities. I think one of the things is the ability to collect and share data rapidly that does not increase the burden on individuals involved on the ground in a response. Right? So if you're caring for patients in the Ebola hot zone, high on your list of priorities is not filling out paperwork so that PhDs in other countries can build mathematical models and share them with public health agencies.
Sam Scarpino: Even if those models were having a measurable improvement on the probability of survival or on the efficiency that you can deliver care, et cetera, it's still not as high on the priority as maximizing the amount of time and effort you can put towards saving lives. And so that's something that technology can help us with. Technology can, if built and designed well, make it easier to gather large rich data sets that can be readily shared during an outbreak.
Sam Scarpino: I think the second piece would be preparedness ahead of time regarding data, and that's actually something that I've been working on with a working group at the World Economic Forum, and with a startup company that I'm involved with called Dharma.ai, is to develop data resources that can be rapidly deployed during an outbreak that have already been vetted and approved from an ethical perspective, from a patient privacy perspective. All of the things that are deeply important, and very hard to get right quickly during an outbreak, we can prepare ahead of time to have those things in place.
Quinn: Is that like standardized protocols that ... Every situation's different, but the ones that seem to apply everywhere, is that intake? What are those things?
Sam Scarpino: Yeah, I think it's all of the above, right? There are going to be differences for every outbreak, but there are going to be a lot of things that are very similar. The kinds of data that you might gather on a person that is fighting an Ebola infection are going to be by and large very similar to the kinds of data you would gather on anyone in any hospital all over the world. Vital signs, et cetera. The kinds of information that you might gather in a refuge camp about access to clean water, about bed nets if it's a malaria or mosquito borne disease risk area, et cetera. All of those things are similar enough that they can be standardized.
Sam Scarpino: Again, because this is an international response, the international community can decide what they think the privacy and ethical standards are, and then ensure that those are being met by whatever mechanism is being used to collect the data. So are they being stored in a secure way? Are they being collected in a secure way? If it involves Doctors Without Borders, does the technology meet the new European Union privacy standards encodified by what's called GDPR, so that we'll be able to collect the data once it starts streaming in.
Sam Scarpino: A very simple example would be that one of the European Union regulations around data privacy is that the data has to be stored in a country that has the same privacy standards as the European Union, which almost invariably means that you have to store the data in Europe. Most companies that store data, are here, or either won't or can't tell you were the data are being stored. So Dropbox, for example won't guarantee where your data are being stored.
Quinn: That's not helpful.
Sam Scarpino: No. But even solving relatively simple things like that, are things that we can do ahead of time so that we're not bogged down in legal proceedings to make sure that the data are being stored in Belgium when we're trying to roll out an Ebola response.
Brian: Yeah. In the midst of the outbreak.
Sam Scarpino: That's right.
Quinn: It's like when my wife comes and tells me, she shows me her iPhone, and she says, "This message pops up every day, and I hit 'dismiss' and it drives me crazy." And I'm just like, "If one time you didn't hit 'dismiss' and you just dealt with the problem, you would never have this problem-"
Brian: Never get it again.
Quinn: ... again." So it's like that?
Sam Scarpino: I'm going to avoid weighing in on that as a good or bad analogy.
Sam Scarpino: However, I will say that the spirit of it, I agree with. Which is that it is often far easier, cheaper, and more efficient to prepare rather than to react.
Brian: Yeah. Sure. Sam, you've talked in the past about the benefits of working a cross-disciplinary environment. Talk us through that. How much does your unique cross-disciplinary approach benefit your work? And is that an example that could be emulated elsewhere for other problems?
Sam Scarpino: Well first of all, I'll certainly say that I am not alone in either my appreciation or attempt at inter-disciplinary research. It's something that has become a buzzword, and even despite that there are still a large number of individuals in academia, the private sector, the public sector, that really strongly believe in and live by inter-disciplinary approaches to problems.
Sam Scarpino: I think from my perspective, one of the most actionable benefits is that it exposes you to lots of different ways of thinking about problems, and lots of different ways of solving problems. And we know from many different kinds of studies that have been done, that diversity measured in many different ways, is important for problem solving, and can be very important for high functioning teams.
Sam Scarpino: From an academic perspective, within the research group that I lead at Northeastern, we have physicists, biologists, computer scientists, and one of the rules is that you're not really allowed to say something unless you can explain it to everyone in the room.
Quinn: Mm. I like that.
Brian: That's awesome.
Sam Scarpino: It's serving two purposes, which is one, being able to explain things to people is incredibly important. It's probably one of the hardest skills to learn, but it's one of the most important ones to have. And I'm also a very firm believer that there's almost nothing that can't be explained to someone who's willing to and interested in learning about it. So I don't think it's this issue of we don't have the right training or they're not intelligent enough. I think if you're a good enough communicator, you can explain something to anyone who's willing and interested in listening.
Quinn: Sorry. It's funny, I read this book recently, which it has influenced and continues to influence this podcast, it's called A More Beautiful Question.
Brian: Oh yeah.
Quinn: And it talks about, again, practical questions and solving problems and critical thinking and things like that. But one of them is, and again I've got a fleet of toddlers in my house. But the five why's, which is if you're asking someone to explain something and you ask why five times for each answer they give, it both should dial it down to its most fundamental parts so that everyone can understand it, but hopefully helps that person clarify it a little bit for themselves as well. Both from a problem solving standpoint, but also just practically so they can explain it to someone again. And I do think that really matters, like you said. It needs to be able to translate to everyone.
Sam Scarpino: Yeah, I couldn't agree more. And actually that was going to be precisely the second point about why I think it's so important for us to be asked to explain ourselves.
Quinn: You're welcome.
Sam Scarpino: I often get accused by students of playing this game called Read My Mind, which is I ask a question, and then I tell everyone that that's not the answer I was looking for. But in this case, you read my mind perfectly, which is that when we're in our own discipline, when we're in the area that we've been trained in the most, I suspect that's also the situation where we become the most complacent and the most sort of desensitized to questioning. So it's probably the easiest area for me to make a mistake in, is in something that I think I know really well because I'm not being as careful.
Sam Scarpino: And so if someone's asking me those five why's, really driving all the way down to the bottom, maybe you wouldn't be surprised that in those areas where you're most comfortable are the times where it's the hardest for you to get all the way to the bottom. And then it becomes very insightful when you realize you've misunderstood something or there's a better or faster or more appropriate or fair, more ethically appropriate way of addressing a problem.
Quinn: Sure, and it even gets to a topical thing these days, which is I'm a big tech nerd and love all this science and do everything, but I went to a liberal arts school, and so I stand up for the humanities because they do matter. Again, philosophy can sometimes be not practical. But you look at a situation like Facebook's current nightmare, and go, "Boy, if you'd had some humanities folks in the room ..." Again, coming back to being proactive, somebody might have said, "Should we do this? Is it the right thing to do? What are the anthropological ramifications of this?"
Quinn: It matters. It matters for everybody to understand what we're trying to do or what we're doing or what we've done in a situation, however digital or practical on the ground.
Sam Scarpino: I'll admit that I'm hopelessly biased, because my mother's an artist, my father's a history professor, and my wife is an English professor.
Quinn: Yeah, you're surrounded.
Sam Scarpino: Yeah. I think that a liberal arts education is incredibly important. One of the most interesting things that I've seen working with the startup I mentioned is-
Quinn: The Dharma Initiative?
Sam Scarpino: And in fact, the CTO of Dharma, one of the things that is the biggest differentiator for him, is how people communicate in the written form, because we spend a lot of time talking to each other in Slack, we have to describe what we're doing in our code, and if you can't communicate clearly and succinctly, then you're not going to be a high functioning software engineer, even if you're one of the best programmers around.
Quinn: Sure. So I guess that provides me with a really great segue, so thank you. What does a young person, one of our listeners, preferably a female person of color, need to do or to qualify in to be the next Sam Scarpino?
Sam Scarpino: I would be remiss if this didn't start with a caveat, which is things are changing so quickly in terms of what is required to be a data scientist, what is required to become an academic, that the lessons that I've learned are very rapidly becoming obsolete. And maybe that's actually my first piece of advice, which is that it's very hard for anyone to give concrete advice because things are changing so quickly.
Sam Scarpino: I think liberal arts education, humanities, are incredibly important. Learning how to solve problems for yourself, and how to ask the right kinds of questions, equally important. And those to me feel like generalized research skills. So how do you go to the library? How do you go onto the internet and find the answer that you're looking for quickly and efficiently?
Sam Scarpino: And then I think beyond that, finding a network of people who you can learn from, be mentored by, receive support from, is equally important. I know that my friends and colleagues and collaborators are a big part of the reason that I'm so excited to come to work every day. And these are the people that are going to be shepherding you through the ups and downs all the way through the process of training and finding jobs and working in high stress environments.
Sam Scarpino: One of the, probably the most succinct ways that I've heard this put, was by one of my mentors, which is there are too many nice, smart people to work with assholes.
Quinn: Oh, man. That applies in my industry a thousand times over. Totally agree.
Sam Scarpino: Yeah. And I think aside from those things, the other side of the coin is to be aware of the fact that as humans, especially as people that live in the US, one of the things that we're the worst at, is understanding why some people are succeeding and other people are not. Almost always, the reason is because of where they came from financially, connections their parents had, because they got lucky.
Sam Scarpino: And so that's another thing to remember, is that if you're the kind of person like I am who's always looking for an explanation for something, sometimes the answer is that it was just random. Or it was just the way things started out. That that person started with a headstart because of the family that they grew up in, and you're never going to be as successful as they are unless you get incredibly lucky.
Sam Scarpino: And that maybe sounds a little bit depressing, and I don't mean it to be. What I mean it to be is that we're naturally always comparing ourselves to other people, and it's and easy way to end up either intimidated or feeling down about yourself and your accomplishments. And largely that's because we're putting it in the wrong context in terms of the kinds of things we've been able to achieve.
Quinn: Mm-hmm (affirmative). All right. So you're a super nerd with a fancy computer who loves Melville. Most of us aren't those people. And even the ones who are going to grow up to try to become Sam 3.0, it's a finite, it's a specific number of people who can succeed at all of those things. But how can the rest of our listeners, which are basically nerdy Pod Save America listeners, basically. How can they act with both of their hands, and also with their vote to advance what you do? To make the world a healthier place using skills like these and platforms like yours?
Sam Scarpino: Great question. The first would be to get vaccinated. But more importantly, to take someone with you to get vaccinated. So one of the things that we work on are social networks, and one of the things that's largely true of social networks is that your friends have more friends than you do. So one of the easiest ways to find people with lots of friends is to say, "Sam, I don't care about you. I care about who your friend is, because that person is almost certainly gonna be very popular if a lot of people are naming them." So get yourself vaccinated and then take your most popular friend to go get vaccinated.
Quinn: I like that.
Sam Scarpino: The second thing would be, and this is from a voting perspective, is science funding. And in particular, basic science research. Right? So we just saw with the latest budget that came out that Rand Paul went on a rant about how the NSF funds fruit fly research or whatever thing he was picking up on.
Sam Scarpino: The thing about basic science research is that in many cases, it's often very difficult to figure out ahead of time, which of the things that we learn are only going to do the lovely thing of increasing our understanding about ourselves, our universe, our society, et cetera, as compared to the things that are going to end up saving hundreds of millions of lives. Or hundreds of millions of dollars.
Sam Scarpino: A good example of that is actually the Ebola outbreak. We spend very, very little money on Ebola research prior to the outbreak. But one of the things that we learned as a result of basic science funding for a neglected tropical disease, that was a relatively low risk to the United States, is that individuals are not infectious. They cannot transmit Ebola virus until well after they've started showing symptoms.
Sam Scarpino: What that meant, is that when the individual who flew from Liberia to Dallas was on that airplane, they were not able to transmit. If we hadn't known that, I don't think the collapse of the global airline industry would have been an unreasonable outcome of that event.
Quinn: Oh, that's good news. And yeah, right. By the way, when we find that moment and that person, and shit is starting to go wrong, we can't really go back and fund basic science research at that moment. Like you said, we don't know what's going to come of it, but, I don't know, it's probably going to be helpful. The answer is it's going to be applicable, and it's probably going to be helpful.
Quinn: So what are the specific things our voters should be saying to their representatives about funding basic science research? We try to, again, make things as actionable for people as possible. What specifically should they literally say? What are they fighting for?
Sam Scarpino: They're fighting for increased funding for the National Science Foundation, increased funding for the National Institutes of Health. They're fighting for decreased government oversight in how the National Science Foundation and National Institutes of Health decide to fund research. And not that there isn't oversight, but the way that it's traditionally been funded is that scientists sit on panels and those panels decide what gets funded. And one of the things that many Republicans in Congress would like to do is that the congressmen and women get to pick what gets funded, and that doesn't sound like a very good situation to me.
Sam Scarpino: Both increasing budgets in the entities that are involved in funding basic science research, the National Science Foundation in particular, the defense of scientific freedom. I would also say that at the state level, increased funding support for our publicly held universities, because their financial solvency is going to be directly tied to the amount of research that's done at our US institutions, which is what provides so much benefit back to the taxpayer and to our country.
Sam Scarpino: Right? So if you think about it, one of the crown jewels in the history of our country is the system of higher education that we've built, that we're largely now either throwing away or mortgaging as a result of complete lack of investment in higher education across the board.
Quinn: Right. We're making it completely unattainable for most folks.
Sam Scarpino: Making it completely unattainable for most folks, and then the cherry on top is making it so that individuals are not interested in coming to the United States to go to school. Right?
Sam Scarpino: We've seen international applications dropping, and so what we're basically doing is no longer bringing the best and brightest into our country, no longer bringing in external dollars in terms of tuition to support the education and research of people in the United States. We're not providing support through tax money. We're basically completely pulling the rug out from under higher education.
Quinn: Right. Making it impossible for those exact diverse thinkers that you mentioned earlier to actually attend university, and then further bring that perspective to occupations such as yours. It's good. It's going well.
Sam Scarpino: I'm optimistic.
Quinn: I am too.
Brian: By the way, we do have to stay that way, otherwise we're fucked.
Quinn: No, it's all fixable. And it might look completely different in 20 years, in which case my 529's are going to be in some trouble. But there's an argument, and I've talked about this before, about how do we pivot higher education to focus less on sort of siloed concentrations, or majors as we call it in the US, to more critically well-rounded problems or issues, such as drinking water or clean air, or disease.
Quinn: If you're on track for a religion major, like I was for really no reason, there's not a lot of technical training going in there, or influence in the concentration at all. But if you build around these more applicable, practical things, you're going to bring in a more diverse set of voices and perspectives and talents and skills that should ultimately build for the future.
Sam Scarpino: I couldn't agree more. I actually disagree slightly with the comment about philosophy. I think I know a lot of philosophers who it's hard to get actionable information from. I think in terms of the approach to reasoning and to structuring our thoughts around ethics, especially as it pertains to big data, philosophy as a field probably has a whole lot more that it could be offering. Just as one example-
Quinn: Totally agree. Again, I love it. Again, I was an nerdy religion major. I took plenty of philosophy. It's just how do we just, not pivot it, but how do we apply it? We want to make sure we're just ... especially right now in what some say is the most important year of our lives. How do we just make sure we're taking a step back from problems to ask bigger philosophical questions, but also taking when we're just sitting here asking bigger philosophical questions, saying like, "Okay. Can we apply this?" Again that goes back to the book A More Beautiful Question. How do we make this a little more actionable? If it's a closed ended question, how do we open it up or vice versa, to make sure that it's something that we can move on?
Sam Scarpino: Oh, I think that's great general advice, right? Which is we should always be asking ourselves capital W, Why are we doing something? And lowercase W, why are we doing something? So what is the big philosophical reason, or medium sized philosophical reason that we're doing something, and are we doing something that's actually going to move the needle in the direction that we want to move it? And continued reflection on both of those is going to help ensure that we don't get too deep in the weeds such that we miss the forest for the trees, and also ensure that when we're down in the weeds that we're in the right part. The metaphor is breaking down here, but we're in the [crosstalk 01:09:47].
Quinn: No, no, no. Stick with it, man.
Brian: Keep it going, baby.
Quinn: Keep going.
Sam Scarpino: We're in the right part of the path or something, or maybe that we find the weeds instead of the flowers or something.
Quinn: Yeah, no. It's good. It's good. People get it. People got it.
Sam Scarpino: I'll end on a high note, make it really sound like I know what I'm talking about.
Quinn: Yeah, yeah, yeah. Good work. Way to flame out there at the end.
Brian: We have some more fun stuff coming up here. It's going to end great. We always like to ask a few questions, sort of a lightning round if you're ready to spout some quick answers.
Sam Scarpino: I'm ready.
Quinn: All right. Again, this is a little bit like the first one, but when was the first time in your life Sam, you really realized you had the power of change, or the power to do something meaningful?
Sam Scarpino: That's a hard question. I guess that's the point. That's probably why you asked it?
Quinn: Yep. Yeah. Exactly.
Brian: Next up is what's your favorite color.
Sam Scarpino: Yeah, my favorite color is blue, I like mint chocolate chip ice cream.
Quinn: Good, good.
Sam Scarpino: I would say maybe a time that is among the first is in college I went to do some work in Kenya, and one of the things that I did was to conduct a large-scale survey of access to drinking water, access to toilet facilities, for a bunch of families that were caring for orphans in a rural area.
Sam Scarpino: The reason I was conducting the survey is that I was a part of this agency, but I felt like I didn't really have any skills. I said, "I don't really know. I mean, I'm not a physician, I'm a college student that doesn't really know how to do much besides wake up and go to class." And I said, "Well, what I guess I could do, is I could go do a survey. I could gather some data, and then I could use the results of those data to try and obtain funding." And that's what we did.
Sam Scarpino: We ended up getting funding to dig new toilets for 12 single parent families that were caring for orphans. And I think that that had a measurable effect on those families. So that to me was one of the first concrete examples of both seeing that data, the simple act of enumerating things, can change lives.
Sam Scarpino: But also that people with a very diverse set of skills can all have a role to play, that you don't have to be a physician. You don't have to be a community healthcare worker to save lives, to improve lives. That there are lots of ways in which we can leverage our own individual skills in order to have a big impact.
Quinn: Can I ask, what did that do to you? Knowing that you had that impact both then and I guess now. It seems to have obviously stuck with you.
Sam Scarpino: I think at the time, I didn't really understand what kind of impact it was having. I felt very good at the time because I could see that I was doing something that mattered and that I was able to use the skills that I'd learned out in the real world, outside of the university. So I think that, at the time, was what I was mostly focused on.
Sam Scarpino: Now, when I look back, what I take away from that experience is again, how incredibly important it is for even simple things like conducting a census, that once someone has been counted, it's much harder to ignore them. Right? So even going into a refugee camp and finding out how many people are there, how many women are going to be giving birth in the next two months, how many people have access to clean drinking water, makes it much harder for the international, national, local, communities to ignore those problems. Right? If you haven't been counted, if you haven't been enumerated, then you can be much more easily ignored.
Sam Scarpino: And the second thing would be the importance of not just trying to make decisions from afar, but engaging with all of the relevant stakeholders, including the people who you're actually going to be working for. So in this case, spending four months, which is not very much time, but spending four months with these families to really work with them to understand what the problems are instead of from afar, from United States, from behind my computer, trying to understand what the problems are in a community or what the needs are in a community.
Brian: Yeah. Beautiful.
Quinn: All right. Number two. How do you consume the news?
Sam Scarpino: I consume the news in a few different ways. The first is I try to have a technology blackout in the morning, even if it's just for five minutes, and read something that's been printed on a piece of paper and have a cup of coffee and eat some cereal. And so I-
Quinn: Wait. What's your cereal?
Sam Scarpino: My aunt makes granola, and she regularly sends us like a 50 pound box of granola.
Brian: We'll give you our office address.
Sam Scarpino: Okay. Yeah. I will send you guys some. This stuff is super delicious.
Quinn: That's awesome.
Sam Scarpino: That's one of the ways I consume news. The other would be all over the map. Things that I run across on Twitter, things that get recommended to me by Google, New York Times, Washington Post. I would say though, maybe, and this might be an actionable item, is if it's something that is new to me, that I've not been exposed to before, I'll try to read about it on three or four different platforms before I really start to formulate some opinions in my head. And also try to make sure that it's not just an AP news-wire that's been reposted on three or four different places, that it's actually-
Quinn: Right. Different reporting.
Sam Scarpino: ... different news entities or different podcasts or blogs that are distilling the information and putting it into context for me.
Brian: Yeah, that's pretty great.
Quinn: That's incredibly balanced. But everybody does that. Right?
Brian: All right. Question number three.
Quinn: Last one.
Brian: We love this one. If you could Amazon Prime one book to Donald Trump, what would it be?
Sam Scarpino: Do we know if he knows how to read?
Quinn: No, listen, that's come up a couple times.
Brian: We do not.
Quinn: All right? Look, it's the thought that matters.
Brian: Somebody will translate it into photos for him.
Quinn: Go with your heart and think, "You know what? This is the one. He's gonna read this one. Or someone's gonna read it to him at night." I don't know. The point is he's going to consume it in some way. You have to believe in that.
Sam Scarpino: I read a book. It's actually a short essay called On Immunity, by Eula Biss, and I think it's a really lovely exploration of her own fears around vaccinating her child, and then doing research into the history of the anti-vaccine movement. And then ultimately deciding to vaccinate her child. I think that it's an incredibly important and accessible narrative/essay about the reason we need to vaccinate our children, why it's safe, and the history of all the fear surrounding it.
Sam Scarpino: I'd send it to President Trump because I think everybody should probably read this book, but I don't know that he's said as much about vaccines, which might mean that he can still be influenced.
Quinn: Yeah, right.
Sam Scarpino: I don't know. I also heard that he just says whatever the last thing it was that he heard, and so I care a lot about people getting vaccinated and so maybe I'll send him the book and he'll read it, and that'll be the last thing he hears.
Brian: And he'll tweet it out.
Quinn: I love it man. Dude, this has been so awesome. We really appreciate it.
Brian: Very much.
Quinn: Where can our listeners find you online, man?
Sam Scarpino: Well first I want to say it's been a lot of fun. I really appreciate you both reaching out. I've enjoyed listening to your podcast.
Quinn: Thanks, dude.
Sam Scarpino: And I'm really excited that I get to be a part of it.
Quinn: Us too.
Sam Scarpino: In terms of finding me, I'm on Twitter, sbscarpino. I also have a website, it's scarpino.gethub.io. There aren't that many Scarpinos, so if you just Google "Scarpino" you'll probably find me.
Quinn: All righty.
Sam Scarpino: There are some more famous Scarpinos, but there aren't that many of them so you can dig through and find me.
Quinn: Awesome, awesome. Well, we really appreciate it man, both you taking the time today and everything you do out there in the world. It's either making people healthier or keeping us healthy, or making sure we don't get sick. And it's the proverbial "we", because you operate around the world and the world appreciates that. So thank you so much for your time, man, and for everything you do. You gotta keep kicking ass out there, all right?
Sam Scarpino: You guys too. Please keep informing everyone and calling everyone to action, because as we all know, that's what's really going to make a change both over the next year, during the next election, but then over the coming decades with all these important things like climate change, disease, et cetera.
Brian: Hell yeah.
Quinn: All right Sam. Well we will talk to you soon, man.
Brian: Thank you very much.
Sam Scarpino: All right. Thanks so much, I appreciate it. Have a good night.
Quinn: Yeah, you too.
Sam Scarpino: All right.
Quinn: Thanks to our incredible guest today, and thanks to all of you for tuning in. We hope this episode has made your commute or awesome workout or dishwashing or fucking dogwalking late at night, that much more pleasant. As a reminder, please subscribe to our free email newsletter at importantnotimportant.com. It is all the news most vital to our survival as a species.
Brian: And you can follow us all over the internet, and you can find us on Twitter at importantnotimp.
Quinn: That's just so weird.
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Brian: And you can find the show notes from today right in your little podcast player, and at our website, importantnotimportant.com.
Quinn: Thanks to the very awesome Tim Blane for our jamming music, to all of you for listening, and finally, most importantly, to our moms for making us. Have a great day.
Brian: Thanks guys.