1 00:00:00,200 --> 00:00:02,440 Speaker 1: Guess what, mango, what's that? Well, do you remember a 2 00:00:02,480 --> 00:00:04,960 Speaker 1: few weeks ago when we talked to Daniel Pink about 3 00:00:04,960 --> 00:00:08,639 Speaker 1: the science of perfect timing? What if I said no, like, 4 00:00:08,640 --> 00:00:11,399 Speaker 1: would you be concerned about that? That? Maybe a little 5 00:00:11,400 --> 00:00:13,520 Speaker 1: bit concerned because this was just a few weeks ago, 6 00:00:13,560 --> 00:00:16,560 Speaker 1: but especially because it was a super interesting episode and 7 00:00:16,680 --> 00:00:20,079 Speaker 1: conversation and just all of that talk about how timing 8 00:00:20,160 --> 00:00:22,880 Speaker 1: matters in so many ways that we don't stop and 9 00:00:22,920 --> 00:00:25,200 Speaker 1: think about. You know, one of the things we talked 10 00:00:25,200 --> 00:00:27,040 Speaker 1: about was how much timing matters when it comes to 11 00:00:27,080 --> 00:00:30,160 Speaker 1: medical treatments, like when not to have a surgery or 12 00:00:30,440 --> 00:00:32,559 Speaker 1: when to go to the doctor. But you know, one 13 00:00:32,600 --> 00:00:35,000 Speaker 1: of the things we didn't talk about were the strange 14 00:00:35,080 --> 00:00:38,519 Speaker 1: findings around the time of day and getting vaccinations and 15 00:00:38,560 --> 00:00:41,479 Speaker 1: other specific medical treatments wait at the time of day 16 00:00:41,560 --> 00:00:44,559 Speaker 1: matters from vaccinations. Yeah, So there was this really interesting 17 00:00:44,560 --> 00:00:48,040 Speaker 1: story about this in Scientific American and everything from cancer 18 00:00:48,080 --> 00:00:51,720 Speaker 1: treatments to flu shots can trigger slightly different responses in 19 00:00:51,800 --> 00:00:54,280 Speaker 1: our bodies depending on the time of day that we 20 00:00:54,320 --> 00:00:56,920 Speaker 1: get them. So with flu shots, a few studies have 21 00:00:56,960 --> 00:00:59,800 Speaker 1: actually found that those who got flu shots before eleven 22 00:00:59,840 --> 00:01:02,840 Speaker 1: a m produced more antibodies than those who got them 23 00:01:02,920 --> 00:01:06,600 Speaker 1: later in the afternoon, which is so strange. It really is, 24 00:01:06,680 --> 00:01:09,039 Speaker 1: and it's yet another reminder of just how much we 25 00:01:09,080 --> 00:01:11,360 Speaker 1: have to learn about our body clocks and the way 26 00:01:11,400 --> 00:01:13,840 Speaker 1: they work. But back to the flu. I mean, we 27 00:01:13,880 --> 00:01:16,560 Speaker 1: wanted to focus today's episode on answering some of the 28 00:01:16,640 --> 00:01:20,400 Speaker 1: many questions people have, like why are some flu seasons 29 00:01:20,400 --> 00:01:23,440 Speaker 1: worse than others, how do scientists know when some seasons 30 00:01:23,440 --> 00:01:26,880 Speaker 1: will be particularly bad, and what goes into deciding what 31 00:01:27,000 --> 00:01:29,840 Speaker 1: this year's vaccine is going to look like. Those are 32 00:01:29,880 --> 00:01:32,160 Speaker 1: just a few of the questions we're answering today. So 33 00:01:32,240 --> 00:01:55,720 Speaker 1: let's dive in Y today their podcast listeners, Welcome to 34 00:01:55,720 --> 00:01:58,200 Speaker 1: Part Time Genius. I'm Will Pearson, and as always I'm 35 00:01:58,240 --> 00:02:00,600 Speaker 1: joined by my good friend man guest ticket and on 36 00:02:00,640 --> 00:02:04,280 Speaker 1: the other side of the soundproof glass offering complimentary flu shots. 37 00:02:04,320 --> 00:02:07,240 Speaker 1: I think, yeah, that's what the sign says to anybody 38 00:02:07,280 --> 00:02:09,240 Speaker 1: brave enough to take him on it. That's our friend 39 00:02:09,240 --> 00:02:12,720 Speaker 1: and producer Tristan McNeil. I mean, it is a nice gesture, 40 00:02:12,760 --> 00:02:16,080 Speaker 1: don't you think, Mango. Yeah, although probably an illegal one too, 41 00:02:16,120 --> 00:02:19,120 Speaker 1: I'm guessing. Well, either way, he's getting a lot of 42 00:02:19,160 --> 00:02:21,760 Speaker 1: side eye glances from people around the office today. But 43 00:02:22,320 --> 00:02:24,560 Speaker 1: I can't say I blame the guy for wanting to 44 00:02:24,600 --> 00:02:27,760 Speaker 1: take some precautions. I mean, you know, personally vaccinating all 45 00:02:27,760 --> 00:02:31,359 Speaker 1: your coworkers might be an extreme reaction. But yeah, there's 46 00:02:31,400 --> 00:02:34,200 Speaker 1: no denying that this year's flu season is a pretty 47 00:02:34,320 --> 00:02:36,720 Speaker 1: rough one. For example, I was looking at some of 48 00:02:36,760 --> 00:02:40,160 Speaker 1: the stats and the latest flu update from January nineteenth, 49 00:02:40,240 --> 00:02:43,440 Speaker 1: the CDC reports that thirty two states plus New York 50 00:02:43,480 --> 00:02:47,239 Speaker 1: City in Puerto Rico are currently experiencing what's considered high 51 00:02:47,280 --> 00:02:50,640 Speaker 1: flu activity, and things aren't much better in other states. 52 00:02:50,639 --> 00:02:53,200 Speaker 1: In fact, Hawaii is actually the only U. S state 53 00:02:53,240 --> 00:02:57,120 Speaker 1: that's not experiencing widespread flu activity. Yeah, but I mean, 54 00:02:57,240 --> 00:02:59,560 Speaker 1: it's all sad to deal with false alarms around missile strikes, 55 00:02:59,560 --> 00:03:02,440 Speaker 1: so it's it's a bit of a trade off. I guess. Yeah, 56 00:03:02,120 --> 00:03:04,760 Speaker 1: that's a fair point. But you know, as you might 57 00:03:04,800 --> 00:03:07,560 Speaker 1: have guessed, today's show is all about influenza or is 58 00:03:07,600 --> 00:03:10,519 Speaker 1: it's better known just the flu, And we're gonna talk 59 00:03:10,520 --> 00:03:12,880 Speaker 1: a little bit about what the illness is and how 60 00:03:12,919 --> 00:03:15,240 Speaker 1: it spreads, as well as some of the clever ways 61 00:03:15,280 --> 00:03:18,519 Speaker 1: analysts have found to track flu activity. But we also 62 00:03:18,560 --> 00:03:21,280 Speaker 1: want to debunk some of the popular misconceptions around the flu. 63 00:03:21,440 --> 00:03:23,560 Speaker 1: And you know, since I just brought up the severity 64 00:03:23,600 --> 00:03:25,880 Speaker 1: of this year's flu season, I do want to make 65 00:03:25,880 --> 00:03:28,359 Speaker 1: sure we put some of that hype in perspective. Yeah, 66 00:03:28,360 --> 00:03:29,680 Speaker 1: I mean, you don't want to give the flu a 67 00:03:29,680 --> 00:03:32,680 Speaker 1: bad name or anything, right, I mean, you know, people talk, 68 00:03:33,440 --> 00:03:35,520 Speaker 1: but seriously, you know, while there have been close to 69 00:03:35,680 --> 00:03:39,960 Speaker 1: nine thousand influence of related hospitalization since October of last year, 70 00:03:40,720 --> 00:03:43,640 Speaker 1: the overall hospitalization rate is actually down from the two 71 00:03:43,680 --> 00:03:47,160 Speaker 1: thousand fourteen two thousand fifteen season, which was considered a 72 00:03:47,280 --> 00:03:50,560 Speaker 1: very high severity season. So all, this year's flu season 73 00:03:50,680 --> 00:03:53,040 Speaker 1: is a bad one. It is an unprecedented and we've 74 00:03:53,080 --> 00:03:56,720 Speaker 1: actually dealt with worse in recent years. Yeah. It's also 75 00:03:56,720 --> 00:03:59,200 Speaker 1: worth keeping in mind that the CDC announced on January 76 00:03:59,200 --> 00:04:02,040 Speaker 1: twelve that flu activity has likely peaked for the season, 77 00:04:02,160 --> 00:04:04,680 Speaker 1: which is a good thing. Although even if the worst 78 00:04:04,760 --> 00:04:07,240 Speaker 1: is over, officials say there's still about three months to 79 00:04:07,240 --> 00:04:10,240 Speaker 1: go until the illness is gone for the season. Oh wow, 80 00:04:10,280 --> 00:04:12,080 Speaker 1: so it is still a good idea to get that 81 00:04:12,120 --> 00:04:16,200 Speaker 1: flu shot. Just I don't know, maybe not from TRISCA. Right. Well, 82 00:04:16,560 --> 00:04:18,400 Speaker 1: while we're setting to the record straight about the flu. 83 00:04:18,560 --> 00:04:20,920 Speaker 1: We should probably address one of the biggest myths about it, 84 00:04:21,120 --> 00:04:23,359 Speaker 1: which is that you can use antibiotics to treat it. 85 00:04:23,800 --> 00:04:25,920 Speaker 1: And this is something a lot of people swear by, 86 00:04:26,040 --> 00:04:29,000 Speaker 1: but the truth is that antibiotics only respond to illness 87 00:04:29,040 --> 00:04:31,920 Speaker 1: is caused by bacteria, and since the flu is born 88 00:04:32,000 --> 00:04:35,840 Speaker 1: from virus, not bacteria, antibiotics actually don't have any effect 89 00:04:35,839 --> 00:04:37,719 Speaker 1: on it. Yeah, you know, and this is something I 90 00:04:37,720 --> 00:04:40,240 Speaker 1: think many of our listeners probably already know. But it 91 00:04:40,360 --> 00:04:43,360 Speaker 1: is surprising when you read survey after survey of people 92 00:04:43,440 --> 00:04:45,839 Speaker 1: misunderstanding this. So so why do you think it trips 93 00:04:45,920 --> 00:04:47,880 Speaker 1: up so many people. Well, part of it is that 94 00:04:47,960 --> 00:04:51,360 Speaker 1: a viral infection of the nose thrown lungs can sometimes 95 00:04:51,400 --> 00:04:55,839 Speaker 1: lead to bacterial illnesses like bronchitis. Like antibiotics do have 96 00:04:55,880 --> 00:04:59,440 Speaker 1: an effect on this kind of secondary bacterial infection, so 97 00:04:59,680 --> 00:05:01,839 Speaker 1: sometimes as people credit them for helping with both kinds 98 00:05:01,839 --> 00:05:04,880 Speaker 1: of illness. And that kind of confusion was especially common 99 00:05:04,880 --> 00:05:07,680 Speaker 1: a few decades ago when it was really popular with 100 00:05:07,760 --> 00:05:11,520 Speaker 1: doctors to preemptively prescribe antibiotics to flu patients. This was 101 00:05:11,560 --> 00:05:14,000 Speaker 1: kind of a way to ward off the bacterial complications. 102 00:05:14,520 --> 00:05:16,640 Speaker 1: And you know, once the patients began to feel better, 103 00:05:16,680 --> 00:05:20,839 Speaker 1: they had mistakenly attribute the recovery to these trusty antibiotics. Yeah, 104 00:05:20,839 --> 00:05:23,120 Speaker 1: and I think the other confusion is around the stomach 105 00:05:23,160 --> 00:05:26,039 Speaker 1: flu though, too. I mean, I think antibotics typically do 106 00:05:26,279 --> 00:05:28,920 Speaker 1: help with that, right, Yeah they do. I mean that's 107 00:05:28,960 --> 00:05:31,920 Speaker 1: only because the stomach flu isn't a real thing, or 108 00:05:31,920 --> 00:05:35,480 Speaker 1: at least it's not actually influenza. So remember, the flu 109 00:05:35,600 --> 00:05:38,919 Speaker 1: is of respiratory illness caused by viruses. It has nothing 110 00:05:39,000 --> 00:05:42,520 Speaker 1: to do with the gastro intestinal system. But people associate 111 00:05:42,600 --> 00:05:45,120 Speaker 1: the general feeling of awfulness they get from stomach sickness 112 00:05:45,240 --> 00:05:47,479 Speaker 1: with that of having, you know, a nasty case of 113 00:05:47,480 --> 00:05:50,640 Speaker 1: the flu. So any kind of stomach bug or food 114 00:05:50,640 --> 00:05:53,520 Speaker 1: born illness just gets labeled the flu. Well, and you know, 115 00:05:53,560 --> 00:05:56,359 Speaker 1: since antibotics would actually help with the kind of bacteria 116 00:05:56,440 --> 00:05:59,080 Speaker 1: you deal with in food poisoning, that's I don't know, 117 00:05:59,160 --> 00:06:01,839 Speaker 1: maybe another reason for this whole myth about that helping 118 00:06:01,880 --> 00:06:04,479 Speaker 1: them with the flu. Yeah, that's right. I mean people 119 00:06:04,520 --> 00:06:07,240 Speaker 1: just hone in on the time antibiotics help them kick 120 00:06:07,279 --> 00:06:10,120 Speaker 1: the stomach flu. Yeah. Well, you know, another misconception about 121 00:06:10,160 --> 00:06:13,000 Speaker 1: the flu is how it's spread. You know, most people 122 00:06:13,040 --> 00:06:15,160 Speaker 1: know the illness can be spread by others through these 123 00:06:15,200 --> 00:06:17,839 Speaker 1: droplets of fluid that we expel when we cough or 124 00:06:17,880 --> 00:06:21,279 Speaker 1: sneeze or even just talk. And these droplets can be 125 00:06:21,320 --> 00:06:24,279 Speaker 1: launched as far as six feet, which makes it easy 126 00:06:24,320 --> 00:06:26,840 Speaker 1: for them to land in people's mouths or noses. It's 127 00:06:26,880 --> 00:06:28,920 Speaker 1: just nasty to think about it, but you know they're 128 00:06:28,960 --> 00:06:31,320 Speaker 1: inhaling them into their lungs as well, so it's it's 129 00:06:31,360 --> 00:06:35,480 Speaker 1: pretty easy to spread that. It's so gross to think about. Yeah, 130 00:06:35,520 --> 00:06:37,320 Speaker 1: but you know, the other way to spread the flu 131 00:06:37,480 --> 00:06:40,920 Speaker 1: is through contact with contaminated objects, and this is where 132 00:06:41,000 --> 00:06:43,839 Speaker 1: some folks get mixed up. Again, many of our listeners 133 00:06:43,839 --> 00:06:46,320 Speaker 1: probably already know this, but it is something that comes 134 00:06:46,360 --> 00:06:49,320 Speaker 1: up time and again people not understanding it is. And 135 00:06:49,360 --> 00:06:51,680 Speaker 1: that's that the flu is not transferred through the skin. 136 00:06:51,800 --> 00:06:53,760 Speaker 1: So you're not going to get sick by just touching 137 00:06:53,760 --> 00:06:56,800 Speaker 1: a contaminated door knob or shaking hands with somebody who 138 00:06:56,839 --> 00:06:59,279 Speaker 1: has the flu. So I mean we should talk about 139 00:06:59,360 --> 00:07:01,520 Speaker 1: why it's to keep washing your hands during the flu 140 00:07:01,600 --> 00:07:04,240 Speaker 1: season though, well, because with the fluid goes back to 141 00:07:04,279 --> 00:07:06,239 Speaker 1: the nose and the mouth, so if you touch something 142 00:07:06,320 --> 00:07:08,479 Speaker 1: coated with the virus and then you touch your nose 143 00:07:08,560 --> 00:07:11,679 Speaker 1: or mouth, that's when the infection occurs. And of course 144 00:07:11,720 --> 00:07:13,800 Speaker 1: this is why you definitely don't want to share dishes 145 00:07:13,920 --> 00:07:17,120 Speaker 1: or utensils with somebody who has the flu either. I mean, 146 00:07:17,360 --> 00:07:19,200 Speaker 1: I don't want to share those things with anyone period. 147 00:07:19,240 --> 00:07:22,680 Speaker 1: But that's definitely good advice. So one crazy statistic I 148 00:07:22,680 --> 00:07:25,760 Speaker 1: found while researching is that approximately one third of families 149 00:07:25,760 --> 00:07:29,120 Speaker 1: with schoolish children are actually infected with the flu each year. 150 00:07:29,640 --> 00:07:32,400 Speaker 1: A third. I mean, that's insane, And I think one 151 00:07:32,440 --> 00:07:34,640 Speaker 1: reason that's the case is that spreading the flu might 152 00:07:34,640 --> 00:07:37,800 Speaker 1: be even easier than we think. And how's that. Well, 153 00:07:37,840 --> 00:07:40,120 Speaker 1: according to a new study from the University of Maryland, 154 00:07:40,200 --> 00:07:42,800 Speaker 1: breathing alone is enough to spread the flu virus, never 155 00:07:42,840 --> 00:07:46,800 Speaker 1: mind sneezing or coughing. So what happened was researchers gathered 156 00:07:46,840 --> 00:07:49,600 Speaker 1: bread samples from a hundred forty two people who were 157 00:07:49,600 --> 00:07:52,920 Speaker 1: confirmed to have the flu, and after testing those samples, 158 00:07:53,040 --> 00:07:55,240 Speaker 1: it was found that nearly half of the fine aerosol 159 00:07:55,360 --> 00:08:00,360 Speaker 1: droplets collected during normal breathing contained viral r n A. Alright, 160 00:08:00,360 --> 00:08:03,679 Speaker 1: so so just exhaling can cause the virus to spread. 161 00:08:03,720 --> 00:08:06,200 Speaker 1: You know, it's still something like sneezing. It seems like 162 00:08:06,240 --> 00:08:08,640 Speaker 1: that has to be way worse, right, Like, I think 163 00:08:08,640 --> 00:08:10,400 Speaker 1: a lot more of the what did you call them, 164 00:08:10,440 --> 00:08:13,920 Speaker 1: the aerosol droplets, It seems like more of those would 165 00:08:13,920 --> 00:08:17,440 Speaker 1: be pushed out with a sneeze than just your normal breathing, right, Yeah, 166 00:08:17,440 --> 00:08:19,720 Speaker 1: I mean you think so. But sneezing happens a lot 167 00:08:19,840 --> 00:08:22,400 Speaker 1: less often than breathing, so it isn't as big a 168 00:08:22,440 --> 00:08:25,679 Speaker 1: contributor as you guess. In fact, when participants in UMD 169 00:08:25,800 --> 00:08:29,120 Speaker 1: study provided sneeze samples, there wasn't much viral RNA and 170 00:08:29,120 --> 00:08:33,360 Speaker 1: those aerosol droplets, So really, sneezing isn't the big factor 171 00:08:33,400 --> 00:08:35,320 Speaker 1: as big a factor in spreading the flu virus as 172 00:08:35,400 --> 00:08:38,360 Speaker 1: coughing or even just breathing normally. All right, So I 173 00:08:38,400 --> 00:08:40,160 Speaker 1: think we need to pause just to figure out whether 174 00:08:40,200 --> 00:08:42,560 Speaker 1: there's an upside to this research or is this really 175 00:08:42,600 --> 00:08:45,200 Speaker 1: only good for making me even more paranoid about being 176 00:08:45,200 --> 00:08:48,400 Speaker 1: around people with the flu? Well, I mean, it's suggests 177 00:08:48,440 --> 00:08:50,320 Speaker 1: a new ways to help fight the spread of the flu, 178 00:08:50,520 --> 00:08:54,120 Speaker 1: such as improving ventilation in schools or offices or even 179 00:08:54,160 --> 00:08:57,199 Speaker 1: subway cars. But probably the biggest upside is that the 180 00:08:57,240 --> 00:09:00,400 Speaker 1: fine things might actually make public health initiatives more accurate 181 00:09:00,400 --> 00:09:03,640 Speaker 1: at tracking the risk of flu epidemics and also controlling 182 00:09:03,640 --> 00:09:06,400 Speaker 1: the outbreaks. So having a better sense of how the 183 00:09:06,480 --> 00:09:08,600 Speaker 1: virus spreads through the air will go a long way 184 00:09:08,640 --> 00:09:10,959 Speaker 1: towards improving the computer models we used for that kind 185 00:09:11,000 --> 00:09:12,920 Speaker 1: of work. Yeah, you know, and I'm glad you mentioned 186 00:09:12,960 --> 00:09:16,040 Speaker 1: the effort to track these and predict the flu outbreaks, 187 00:09:16,080 --> 00:09:18,200 Speaker 1: because there's a new model for this that I do 188 00:09:18,280 --> 00:09:21,120 Speaker 1: want to talk about. So back in two thousand thirteen, 189 00:09:21,160 --> 00:09:24,120 Speaker 1: the CDC kicked off this official it was called the 190 00:09:24,200 --> 00:09:28,440 Speaker 1: Predict the Influence the Season Challenge on the exciting but 191 00:09:28,840 --> 00:09:31,240 Speaker 1: you know, it was this way of encouraging researchers to 192 00:09:31,280 --> 00:09:34,400 Speaker 1: find ways of using social media to predict and track 193 00:09:34,520 --> 00:09:37,719 Speaker 1: the flu. And so you had researchers from all over 194 00:09:37,760 --> 00:09:39,920 Speaker 1: the country competing in this kind of thing, and even 195 00:09:39,920 --> 00:09:42,840 Speaker 1: companies like Google getting involved. But one of the most 196 00:09:42,920 --> 00:09:46,720 Speaker 1: interesting results of the challenge came from Northeastern University in Boston. 197 00:09:47,360 --> 00:09:50,280 Speaker 1: So last year, a team they're collected location data from 198 00:09:50,280 --> 00:09:54,040 Speaker 1: over fifty million tweets. And we've talked a little bit 199 00:09:54,080 --> 00:09:57,040 Speaker 1: before about the use of like mass data in order 200 00:09:57,080 --> 00:10:00,200 Speaker 1: to try to predict certain things, but they were just 201 00:10:00,240 --> 00:10:03,800 Speaker 1: grabbing content willy nilly. Instead, they restricted their research to 202 00:10:03,920 --> 00:10:08,040 Speaker 1: messages that contain flu related words like coughing and vomiting, 203 00:10:08,080 --> 00:10:10,880 Speaker 1: and then all this data help them form this picture 204 00:10:10,880 --> 00:10:14,120 Speaker 1: of early flu activity all over the country. And they 205 00:10:14,160 --> 00:10:16,640 Speaker 1: did this like a full six weeks before the flu 206 00:10:16,720 --> 00:10:19,720 Speaker 1: season officially began, which is kind of amazing, right, six 207 00:10:19,720 --> 00:10:22,840 Speaker 1: weeks before the season. But what's the practical application for 208 00:10:23,000 --> 00:10:25,360 Speaker 1: like that kind of mapping, Well, it helps these health 209 00:10:25,440 --> 00:10:29,120 Speaker 1: organizations predict the amount of flu cases to expect that season, 210 00:10:29,360 --> 00:10:31,400 Speaker 1: you know, as well as how the virus might peak 211 00:10:31,480 --> 00:10:33,880 Speaker 1: and when it might peak, and whether it may be 212 00:10:33,960 --> 00:10:37,480 Speaker 1: more or less contagious than previous years. And it heads 213 00:10:37,520 --> 00:10:38,960 Speaker 1: up of this kind of stuff can help when the 214 00:10:39,000 --> 00:10:42,480 Speaker 1: illness hits in full force. In any given years, somewhere 215 00:10:42,480 --> 00:10:45,920 Speaker 1: between five and of the US population comes down with 216 00:10:46,000 --> 00:10:48,640 Speaker 1: the flu, So knowing where we might fall on that 217 00:10:48,720 --> 00:10:52,120 Speaker 1: scale definitely helps with preparations and helps to make sure 218 00:10:52,120 --> 00:10:54,560 Speaker 1: there are enough flu vaccines available to meet the demand 219 00:10:54,679 --> 00:10:57,040 Speaker 1: for the year, which makes sense, right, Like a little 220 00:10:57,080 --> 00:10:59,040 Speaker 1: four warning counts for a lot when you're dealing with 221 00:10:59,080 --> 00:11:01,160 Speaker 1: a matter of life and death and the flu is 222 00:11:01,240 --> 00:11:04,120 Speaker 1: most certainly that. In fact, according to the World Health 223 00:11:04,160 --> 00:11:07,200 Speaker 1: the Organization and the CDC, the flu is responsible for 224 00:11:07,640 --> 00:11:10,480 Speaker 1: somewhere between three hundred thousand and seven hundred thousand deaths 225 00:11:10,520 --> 00:11:13,800 Speaker 1: worldwide each year, and between two thousand and two thousand 226 00:11:13,840 --> 00:11:16,560 Speaker 1: sixteen flu related deaths in the U. S branch from 227 00:11:16,600 --> 00:11:20,320 Speaker 1: about ten thousand to sixty annually. Wow. I mean, that's 228 00:11:20,400 --> 00:11:22,599 Speaker 1: that's a lot of people, and it's pretty frightening to 229 00:11:22,640 --> 00:11:25,320 Speaker 1: think about that. But you know, I've I've always wondered, like, 230 00:11:25,440 --> 00:11:29,480 Speaker 1: what is a flu related death? I mean, obviously understand 231 00:11:29,480 --> 00:11:32,360 Speaker 1: the basic concept, but but how exactly does the flu 232 00:11:32,559 --> 00:11:35,120 Speaker 1: kill somebody? Yeah, I was curious about that too, so 233 00:11:35,200 --> 00:11:37,360 Speaker 1: I looked into it, and there are actually a few 234 00:11:37,400 --> 00:11:39,960 Speaker 1: ways the flu can take us out. So first, it 235 00:11:40,000 --> 00:11:42,440 Speaker 1: helps to know that once the flu virus enters your body, 236 00:11:42,800 --> 00:11:46,040 Speaker 1: it immediately sets to work. It hijacks human cells in 237 00:11:46,080 --> 00:11:49,240 Speaker 1: the nose and throat and converts them into copies of itself. 238 00:11:49,720 --> 00:11:52,839 Speaker 1: And this sudden influx of viral cells it triggers the 239 00:11:52,880 --> 00:11:56,200 Speaker 1: immune system, which immediately responds by sending an army of 240 00:11:56,200 --> 00:11:59,880 Speaker 1: white blood cells and antibodies to fight back the horde. Now, 241 00:12:00,200 --> 00:12:02,480 Speaker 1: the good guy cells are victorious. In most cases, they 242 00:12:02,559 --> 00:12:05,480 Speaker 1: destroyed the virus laden tissue and you start to feel 243 00:12:05,559 --> 00:12:08,080 Speaker 1: better as a result within a few days or weeks. 244 00:12:08,120 --> 00:12:10,760 Speaker 1: But every now and then the immune system gets a 245 00:12:10,800 --> 00:12:14,600 Speaker 1: little over eager with its defense efforts, and in these cases, 246 00:12:15,040 --> 00:12:17,320 Speaker 1: so much tissue is destroyed that the lungs can no 247 00:12:17,360 --> 00:12:20,679 Speaker 1: longer provide the blood with the amount of oxygen it needs, 248 00:12:20,720 --> 00:12:24,520 Speaker 1: and this results in this deficiency of oxygen called hypoxia, 249 00:12:24,600 --> 00:12:27,440 Speaker 1: which can be terminal. Another way the flu can be 250 00:12:27,440 --> 00:12:31,080 Speaker 1: deadly is through those secondary bacterial infections that I mentioned earlier. 251 00:12:31,280 --> 00:12:34,160 Speaker 1: The immune system can exhaust itself fighting the flu, which 252 00:12:34,480 --> 00:12:37,160 Speaker 1: leaves it open to attack by bacterial infections, which can 253 00:12:37,160 --> 00:12:40,040 Speaker 1: then cause organ damage or even death. Wow, and and 254 00:12:40,080 --> 00:12:42,800 Speaker 1: so which of these is actually more of a problem. 255 00:12:42,960 --> 00:12:45,280 Speaker 1: Are there more flu related deaths due to the virus 256 00:12:45,320 --> 00:12:48,160 Speaker 1: itself and what it does to the immune system, or 257 00:12:48,360 --> 00:12:52,040 Speaker 1: you know, maybe to the bacterial infections that overwhelmness system. Yeah, 258 00:12:52,280 --> 00:12:55,120 Speaker 1: it really varies. So the viral strains that cause the 259 00:12:55,160 --> 00:12:57,880 Speaker 1: flu are always changing from season to season, and it's 260 00:12:57,920 --> 00:13:01,040 Speaker 1: typically the most virulent ones that collapse the immune system 261 00:13:01,080 --> 00:13:03,920 Speaker 1: on their own. The bacterial related flu debts are more 262 00:13:03,960 --> 00:13:06,439 Speaker 1: the result of a lack of cleanliness and the facilities 263 00:13:06,440 --> 00:13:09,559 Speaker 1: where flu patients are housed. For example, some researchers think 264 00:13:09,600 --> 00:13:13,800 Speaker 1: that during the infamous global flu pandemic of when cities 265 00:13:13,840 --> 00:13:16,320 Speaker 1: were at their least hygienic, the majority of debts were 266 00:13:16,400 --> 00:13:20,000 Speaker 1: due to bacterial infections. Well, I know, there definitely is 267 00:13:20,000 --> 00:13:22,960 Speaker 1: a lot more to say about the pandemic, and not 268 00:13:23,040 --> 00:13:24,960 Speaker 1: all of that is going to be pretty So before 269 00:13:25,000 --> 00:13:40,400 Speaker 1: we get into that, let's take a quick break. You're 270 00:13:40,400 --> 00:13:42,240 Speaker 1: listening to part time Genius and we're talking about the 271 00:13:42,280 --> 00:13:45,520 Speaker 1: ins and outs of influence, all right, so we definitely 272 00:13:45,520 --> 00:13:49,000 Speaker 1: should talk a little bit about pandemics. But before we 273 00:13:49,040 --> 00:13:51,200 Speaker 1: do that, just a quick note on the terms. There 274 00:13:51,280 --> 00:13:53,600 Speaker 1: so two words that crop up a lot when we 275 00:13:53,640 --> 00:13:58,560 Speaker 1: discuss contagious diseases and illnesses, in these words epidemic and pandemic. 276 00:13:59,000 --> 00:14:01,760 Speaker 1: So just to set the record straight, a flu epidemic 277 00:14:01,840 --> 00:14:04,720 Speaker 1: is a sudden outbreak of the virus that spreads rapidly 278 00:14:04,920 --> 00:14:07,319 Speaker 1: and of course affects a lot of people at once. 279 00:14:07,920 --> 00:14:10,760 Speaker 1: In other words, flu epidemics happen every year and aren't 280 00:14:10,840 --> 00:14:13,880 Speaker 1: much of a cause for alarm on their own. Many 281 00:14:13,880 --> 00:14:16,480 Speaker 1: of the cases that make up an epidemic are pretty mild, 282 00:14:16,559 --> 00:14:18,920 Speaker 1: though of course there are always some that proved to 283 00:14:18,960 --> 00:14:22,800 Speaker 1: be lethal, something that's unfortunately especially true for both very 284 00:14:22,840 --> 00:14:26,160 Speaker 1: young and the elderly, who sadly account for the highest 285 00:14:26,200 --> 00:14:30,080 Speaker 1: hospitalization rates during most flu seasons. On the other hand, 286 00:14:30,080 --> 00:14:33,360 Speaker 1: a pandemic has caused for very much alarm, and there 287 00:14:33,400 --> 00:14:36,440 Speaker 1: are two characteristics of pandemics that kind of explain why 288 00:14:36,480 --> 00:14:39,480 Speaker 1: this is. And the first is that the virus involved 289 00:14:39,480 --> 00:14:42,880 Speaker 1: in the pandemic is always a new strain that's one 290 00:14:42,920 --> 00:14:45,160 Speaker 1: that few people or or maybe even none at all 291 00:14:45,240 --> 00:14:48,440 Speaker 1: have any kind of resistance too. And then the second 292 00:14:48,480 --> 00:14:50,800 Speaker 1: is that a pandemic involves a virus that spread to 293 00:14:50,960 --> 00:14:53,760 Speaker 1: more than one continent, and that basically means that this 294 00:14:53,840 --> 00:14:56,880 Speaker 1: strain is gaining strength and claiming victims with no clear 295 00:14:56,960 --> 00:14:59,840 Speaker 1: sign of slowing down. Yeah, flu pandemics have been re 296 00:15:00,040 --> 00:15:02,080 Speaker 1: can havo pretty much since the illness came on the 297 00:15:02,120 --> 00:15:04,720 Speaker 1: scene in the late fifteen hundreds. That's when the first 298 00:15:04,760 --> 00:15:07,720 Speaker 1: major flu pandemic on records swept through Asia and Europe 299 00:15:07,720 --> 00:15:10,880 Speaker 1: and wiped out roughly ten percent of Rome's population in 300 00:15:10,960 --> 00:15:14,560 Speaker 1: just one week's time. It's crazy, right, And since then 301 00:15:14,600 --> 00:15:17,280 Speaker 1: there have been more than a dozen confirmed flu pandemics, 302 00:15:17,280 --> 00:15:20,120 Speaker 1: but the worst in modern history is undoubtedly the one 303 00:15:20,160 --> 00:15:22,720 Speaker 1: from Well and this is the one that most people 304 00:15:22,800 --> 00:15:25,680 Speaker 1: refer to as the Spanish Flu, right yeah, which really 305 00:15:25,720 --> 00:15:28,200 Speaker 1: has been one of the most unfair misnomers in history, 306 00:15:28,280 --> 00:15:31,240 Speaker 1: because the Spanish Flu definitely didn't come from Spain or 307 00:15:31,280 --> 00:15:34,040 Speaker 1: the Spaniards. You know, I remember hearing that that was 308 00:15:34,040 --> 00:15:36,680 Speaker 1: the case, but I can't remember why this nickname came 309 00:15:36,720 --> 00:15:38,640 Speaker 1: about in the first place. That do you know why 310 00:15:38,680 --> 00:15:41,840 Speaker 1: this is? Well? World War One was nearing its end 311 00:15:41,880 --> 00:15:44,560 Speaker 1: by the time the pandemic rolled around, and most countries 312 00:15:44,560 --> 00:15:47,000 Speaker 1: involved were wary of letting their enemies know how badly 313 00:15:47,040 --> 00:15:49,360 Speaker 1: they had been hit by the flu. So in places 314 00:15:49,480 --> 00:15:54,080 Speaker 1: like Germany, France, Austria, UK US, even like all the 315 00:15:54,120 --> 00:15:56,920 Speaker 1: major players, news outlets weren't allowed to report on the 316 00:15:56,920 --> 00:16:00,040 Speaker 1: true extent of the crisis. But Spain, if you'll remember it, 317 00:16:00,160 --> 00:16:02,720 Speaker 1: was neutral, like, they had no reason to hide the 318 00:16:02,720 --> 00:16:06,440 Speaker 1: flues impact. So when Spanish papers became the first report 319 00:16:06,480 --> 00:16:08,800 Speaker 1: on the millions of flu related deaths in the country, 320 00:16:09,200 --> 00:16:11,560 Speaker 1: many people got to fase impression that the country was 321 00:16:11,640 --> 00:16:14,640 Speaker 1: disproportionately affected by the illness and that it must have 322 00:16:14,720 --> 00:16:18,080 Speaker 1: also originated there. I would say, that's pretty much the 323 00:16:18,080 --> 00:16:20,640 Speaker 1: definition of a bum round. But all right, so if 324 00:16:20,720 --> 00:16:24,280 Speaker 1: Spain definitely wasn't the originator, who was. I mean, it's 325 00:16:24,320 --> 00:16:27,200 Speaker 1: still a matter of debate. Actually, some researchers think it 326 00:16:27,280 --> 00:16:31,000 Speaker 1: originated in East Asia, some think it's in Europe, but 327 00:16:31,440 --> 00:16:34,240 Speaker 1: others claim it started in Kansas, where U. S. Soldiers 328 00:16:34,240 --> 00:16:37,240 Speaker 1: occupied this unsanitary military base before shipping off for the 329 00:16:37,280 --> 00:16:41,640 Speaker 1: fighting Europe. But no matter where the pandemic virus began geographically, 330 00:16:42,000 --> 00:16:44,800 Speaker 1: we now know that it adapted from an avian virus strain, 331 00:16:45,000 --> 00:16:48,040 Speaker 1: so the bird flu exactly we should be pointing our 332 00:16:48,080 --> 00:16:51,560 Speaker 1: fingers at birds. But you mentioned earlier that pandemics are 333 00:16:51,640 --> 00:16:54,440 Speaker 1: a result of new, unknown flu strains. Well, in the 334 00:16:54,440 --> 00:16:57,280 Speaker 1: case of the nineteen eighteen pandemic, the new strain came 335 00:16:57,320 --> 00:16:59,960 Speaker 1: from a bird based illness that mutated until the next 336 00:17:00,000 --> 00:17:03,280 Speaker 1: scesary features to be transmitted to humans. And this was 337 00:17:03,320 --> 00:17:06,520 Speaker 1: something that wasn't confirmed until many years later, But even 338 00:17:06,560 --> 00:17:08,800 Speaker 1: at the time, there was talk that birds might be 339 00:17:08,840 --> 00:17:11,680 Speaker 1: to blame for the outbreak. In fact, these suspicions even 340 00:17:11,680 --> 00:17:15,000 Speaker 1: inspired a creepy schoolyard rhyme kind of like the Pocket 341 00:17:15,000 --> 00:17:17,400 Speaker 1: Full of Poses one that's supposedly based on the plague. 342 00:17:17,560 --> 00:17:21,280 Speaker 1: All right, and I'm assuming you know how Yeah. Well, 343 00:17:21,359 --> 00:17:23,160 Speaker 1: I'm not gonna sing it because I have a terrible 344 00:17:23,160 --> 00:17:25,879 Speaker 1: singing voice, but supposedly it has the same tune as 345 00:17:25,960 --> 00:17:29,360 Speaker 1: Ring around the Rosy. But the lyrics go, I had 346 00:17:29,400 --> 00:17:32,760 Speaker 1: a little bird and its name was Enza. I opened 347 00:17:32,760 --> 00:17:38,280 Speaker 1: the window and Influenza. You just made that? Is that real? Yeah? 348 00:17:38,440 --> 00:17:40,440 Speaker 1: I mean it's a little punnier than the plague grind, 349 00:17:40,440 --> 00:17:42,639 Speaker 1: but I guess I can imagine jumping rope to it. 350 00:17:42,680 --> 00:17:44,760 Speaker 1: But you know, kids rhymes aside, It sounds like this 351 00:17:44,800 --> 00:17:47,360 Speaker 1: was a super dangerous time to be alive. I mean, 352 00:17:47,400 --> 00:17:50,439 Speaker 1: it's called the Great Pandemic for a reason. Absolutely the 353 00:17:50,520 --> 00:17:53,200 Speaker 1: virus flared up all around the world, and every time 354 00:17:53,200 --> 00:17:56,199 Speaker 1: it did more people died. In fact, it's estimated that 355 00:17:56,200 --> 00:17:59,080 Speaker 1: as many as fifty million to a hundred million people 356 00:17:59,119 --> 00:18:02,200 Speaker 1: died worldwide in the event, which was roughly five percent 357 00:18:02,240 --> 00:18:05,680 Speaker 1: of the world's population. It's just insane to think about. 358 00:18:05,720 --> 00:18:07,840 Speaker 1: I mean, that's more than the number of people who 359 00:18:07,880 --> 00:18:10,840 Speaker 1: died from actual combat during World War One. Wow. And 360 00:18:10,840 --> 00:18:13,760 Speaker 1: I'm guessing that just about everybody who contracted the flu 361 00:18:13,920 --> 00:18:16,280 Speaker 1: that year that actually died from it or is this 362 00:18:16,359 --> 00:18:18,360 Speaker 1: not right? That's what I thought too, But but that's 363 00:18:18,400 --> 00:18:20,760 Speaker 1: not the case. So, according to research from the CDC, 364 00:18:21,240 --> 00:18:23,439 Speaker 1: about half a billion people who were infected with the 365 00:18:23,440 --> 00:18:27,080 Speaker 1: flu in nineteen eighteen, but an overwhelming majority of them 366 00:18:27,080 --> 00:18:29,880 Speaker 1: managed to survive it. In fact, the national death rates 367 00:18:29,920 --> 00:18:33,760 Speaker 1: for those infected really rose above But that said, the 368 00:18:33,760 --> 00:18:36,760 Speaker 1: typical flu outbreak kills less than one percent of those affected, 369 00:18:36,800 --> 00:18:40,679 Speaker 1: So a percent rate is off the charts. Yeah, no kidding. 370 00:18:40,680 --> 00:18:42,480 Speaker 1: And you know one thing I don't understand. That was 371 00:18:42,520 --> 00:18:45,600 Speaker 1: why the nineteen eighteen pandemic was so much more severe 372 00:18:45,680 --> 00:18:47,920 Speaker 1: than the ones before it or since then. I mean, 373 00:18:47,920 --> 00:18:51,800 Speaker 1: what made that one so destructive? Well, we already mentioned 374 00:18:51,800 --> 00:18:54,280 Speaker 1: the emergence of a brand new avian virus that most 375 00:18:54,320 --> 00:18:56,439 Speaker 1: of the world just wasn't equipped to fight off. But 376 00:18:56,920 --> 00:18:59,920 Speaker 1: another key factor was the unhygienic conditions of the time, 377 00:19:00,440 --> 00:19:03,679 Speaker 1: especially among urban residents, and the millions of troops engaged 378 00:19:03,720 --> 00:19:06,359 Speaker 1: in trench warfare around the globe. And as writer as 379 00:19:06,480 --> 00:19:09,879 Speaker 1: Katherine Paul's and Anthony Fauci put in their recent article 380 00:19:10,000 --> 00:19:15,000 Speaker 1: for Scientific American quote, crowding and poor sanitation allowed for 381 00:19:15,119 --> 00:19:19,120 Speaker 1: rampant disease transmission, especially in areas where access to healthcare 382 00:19:19,160 --> 00:19:22,800 Speaker 1: was limited. Anti virals to treat influenza were not available 383 00:19:22,840 --> 00:19:26,399 Speaker 1: in nineteen eighteen, and infections often were complicated by fatal 384 00:19:26,400 --> 00:19:30,440 Speaker 1: bacterial pneumonias, for which there were no effective antibodies. Further, 385 00:19:30,600 --> 00:19:34,960 Speaker 1: protective vaccines, the cornerstone of modern influenza prevention, were still 386 00:19:35,080 --> 00:19:37,400 Speaker 1: decades in the future. Yeah, I read up on how 387 00:19:37,400 --> 00:19:40,080 Speaker 1: the flu vaccine eventually came about, and it really wasn't 388 00:19:40,160 --> 00:19:42,800 Speaker 1: rolled out to the public until the mid nineteen forties, 389 00:19:43,280 --> 00:19:45,159 Speaker 1: And it may seem like a late edition, but you 390 00:19:45,200 --> 00:19:47,360 Speaker 1: do have to consider that it wasn't until the nineteen 391 00:19:47,480 --> 00:19:50,199 Speaker 1: thirties that scientists even figure this out. You know, that 392 00:19:50,240 --> 00:19:53,800 Speaker 1: this was a virus causing this widespread illness, and that 393 00:19:53,880 --> 00:19:57,840 Speaker 1: breakthrough came compliments of an American researcher named Dr Francis Jr. 394 00:19:58,280 --> 00:20:00,359 Speaker 1: And you know what he used. He actually used erets 395 00:20:00,400 --> 00:20:03,879 Speaker 1: to prove that the flu was purely a viral illness. Wait, 396 00:20:04,040 --> 00:20:08,440 Speaker 1: why ferrets? Well, strangely enough, ferrets are the model organism 397 00:20:08,520 --> 00:20:12,159 Speaker 1: for influenza research. Apparently, most animals can produce two kinds 398 00:20:12,160 --> 00:20:15,080 Speaker 1: of ceolic acid, and that's the sugar that's crucial for 399 00:20:15,119 --> 00:20:19,200 Speaker 1: certain metabolic processes. But ferrets, much like humans, they can 400 00:20:19,240 --> 00:20:22,919 Speaker 1: actually only make one kind. So what exactly does that 401 00:20:22,960 --> 00:20:25,480 Speaker 1: have to do with the flu Well, flu strains bind 402 00:20:25,560 --> 00:20:28,600 Speaker 1: to the ceolic acid and that causes the infection, But 403 00:20:28,960 --> 00:20:32,400 Speaker 1: different strains have different preferences for which kind they actually 404 00:20:32,440 --> 00:20:35,200 Speaker 1: adhere to. And since ferrets can only make the same 405 00:20:35,200 --> 00:20:38,080 Speaker 1: type of sugar as humans, they're naturally susceptible to the 406 00:20:38,160 --> 00:20:41,600 Speaker 1: humanized strains of influenza. I mean, that's a raw deal 407 00:20:41,680 --> 00:20:44,160 Speaker 1: for farrets, it might be, but it kind of gives 408 00:20:44,200 --> 00:20:47,000 Speaker 1: the lab rates a break for the seriously, I mean, 409 00:20:47,080 --> 00:20:50,639 Speaker 1: this year marks the anniversary of what's widely considered to 410 00:20:50,680 --> 00:20:53,840 Speaker 1: be the most disastrous outbreak of an infectious illness in 411 00:20:53,960 --> 00:20:56,879 Speaker 1: known history, And of course, the question that brings to 412 00:20:56,960 --> 00:20:59,800 Speaker 1: mind for me is how much progress have we made since? 413 00:21:00,440 --> 00:21:02,520 Speaker 1: Or to put it another way, how likely is it 414 00:21:02,560 --> 00:21:04,800 Speaker 1: that we'll have to deal with a nightmare like that 415 00:21:05,000 --> 00:21:08,560 Speaker 1: sometime again? Well, I know the flu vaccine has lessened 416 00:21:08,560 --> 00:21:11,600 Speaker 1: the sting of influenza and obviously saved countless lives in 417 00:21:11,640 --> 00:21:14,720 Speaker 1: the process, But I also know that vaccines don't always work. 418 00:21:14,840 --> 00:21:18,160 Speaker 1: Particularly with new pandemic strains, and it's possible that we're 419 00:21:18,200 --> 00:21:20,800 Speaker 1: still pretty vulnerable. Well that's what I was afraid of. 420 00:21:20,880 --> 00:21:22,919 Speaker 1: And we should talk a little bit more about how 421 00:21:23,000 --> 00:21:26,119 Speaker 1: vaccines work and how the fight against the flu is 422 00:21:26,160 --> 00:21:28,359 Speaker 1: going today. But before we do that, let's take a 423 00:21:28,440 --> 00:21:44,879 Speaker 1: quick break. Okay, Well, so let's do our part to 424 00:21:44,920 --> 00:21:48,479 Speaker 1: help at another global health crisis. Tell me everything you 425 00:21:48,520 --> 00:21:52,800 Speaker 1: know about the flu vaccine and flatter do you think 426 00:21:52,840 --> 00:21:55,560 Speaker 1: might take might help prevent a help crisis. But you 427 00:21:55,640 --> 00:21:58,320 Speaker 1: might be overstating how much I know by just a bit. 428 00:21:58,760 --> 00:22:00,879 Speaker 1: But I did do some research and and one of 429 00:22:00,920 --> 00:22:03,240 Speaker 1: the things that struck me was just how much work 430 00:22:03,280 --> 00:22:07,359 Speaker 1: goes into developing these flu vaccines. And it is vaccines plural, 431 00:22:07,400 --> 00:22:10,160 Speaker 1: because every year we have to develop a new one. 432 00:22:10,440 --> 00:22:13,840 Speaker 1: So why is that? Because flu viruses are constantly changing 433 00:22:13,840 --> 00:22:17,320 Speaker 1: in these subtle ways. So they evolved through continuous genetic 434 00:22:17,400 --> 00:22:21,520 Speaker 1: mutations or sometimes by swapping jeans with other flu strains, 435 00:22:21,560 --> 00:22:23,879 Speaker 1: so by the time the next flu season rolls around, 436 00:22:24,160 --> 00:22:26,840 Speaker 1: actually dealing with a slightly different kind of threat than 437 00:22:26,880 --> 00:22:29,360 Speaker 1: the one you faced in the year prior. Now, our 438 00:22:29,400 --> 00:22:32,320 Speaker 1: current solution to this problem is to develop new vaccines 439 00:22:32,400 --> 00:22:35,040 Speaker 1: each year, and this allows us to better target the 440 00:22:35,080 --> 00:22:37,800 Speaker 1: specific viruses that are predicted to be active in the 441 00:22:37,920 --> 00:22:41,760 Speaker 1: upcoming season. But unfortunately, even with these annual updates to 442 00:22:41,840 --> 00:22:45,320 Speaker 1: flu vaccines, they're usually only about forty two sixty percent 443 00:22:45,440 --> 00:22:48,919 Speaker 1: effective at best, and in some years, vaccine effectiveness is 444 00:22:48,960 --> 00:22:51,159 Speaker 1: even lower than that. And I think that's what I've 445 00:22:51,160 --> 00:22:53,160 Speaker 1: been reading about is the case this year? But why 446 00:22:53,200 --> 00:22:56,000 Speaker 1: is it lower than I thought? Vaccination was our best 447 00:22:56,080 --> 00:22:58,240 Speaker 1: chance for ducting the flu? Well, it definitely is. But 448 00:22:58,359 --> 00:23:01,399 Speaker 1: you know, sometimes new viral it's emerge in between the 449 00:23:01,400 --> 00:23:04,560 Speaker 1: development and the deployment of a new vaccine. You know, 450 00:23:04,600 --> 00:23:07,280 Speaker 1: so scientists could be prepping this year's new vaccine based 451 00:23:07,320 --> 00:23:09,680 Speaker 1: on all the data they have from the current crop 452 00:23:09,720 --> 00:23:12,400 Speaker 1: of viruses, and then you know, bam, suddenly a new 453 00:23:12,480 --> 00:23:15,200 Speaker 1: strain comes out of nowhere and kind of blindsides them. 454 00:23:15,320 --> 00:23:17,760 Speaker 1: I know, this idea that your vaccine can't protect against 455 00:23:17,760 --> 00:23:20,360 Speaker 1: this new virus that comes out. It's kind of tricky. Yeah, 456 00:23:20,400 --> 00:23:22,200 Speaker 1: it is. And and in a case like that, it's 457 00:23:22,240 --> 00:23:24,880 Speaker 1: still better to roll out the new vaccine than none 458 00:23:24,880 --> 00:23:27,480 Speaker 1: at all. But you know, the vaccine's effectiveness will be 459 00:23:27,600 --> 00:23:30,400 Speaker 1: much lower because it won't fully match the viruses it's 460 00:23:30,440 --> 00:23:33,720 Speaker 1: up against, which always sounds like we need a new system. Yeah, 461 00:23:33,760 --> 00:23:36,160 Speaker 1: and there are a lot of these national health organizations 462 00:23:36,200 --> 00:23:38,040 Speaker 1: that would agree with you on this, and and there 463 00:23:38,080 --> 00:23:40,280 Speaker 1: are a lot of conversations going on around this. So 464 00:23:40,440 --> 00:23:42,520 Speaker 1: just last year a few of them met with leading 465 00:23:42,520 --> 00:23:46,200 Speaker 1: flu experts to discuss better ideas for you know, improved 466 00:23:46,200 --> 00:23:49,040 Speaker 1: flu vaccines. Of course, the dream is to do away 467 00:23:49,040 --> 00:23:51,679 Speaker 1: with all the guesswork that makes us need new vaccines 468 00:23:51,680 --> 00:23:55,639 Speaker 1: and just have this one universal flu shot instead. So, 469 00:23:55,680 --> 00:23:58,040 Speaker 1: for example, one idea is the design of vaccine that 470 00:23:58,119 --> 00:24:00,280 Speaker 1: targets the parts of the virus that are common among 471 00:24:00,440 --> 00:24:03,520 Speaker 1: all flu strains, in other parts that don't easily change 472 00:24:03,560 --> 00:24:07,520 Speaker 1: through mutation, which sounds promising. And this kind of just 473 00:24:07,560 --> 00:24:10,320 Speaker 1: popped into my head, but it might sound a little random. 474 00:24:10,440 --> 00:24:13,239 Speaker 1: What exactly is in a flu vaccine? Like, is it 475 00:24:13,280 --> 00:24:16,000 Speaker 1: like with allergy shots where they inject you with whatever 476 00:24:16,040 --> 00:24:18,040 Speaker 1: you're allergic to? Yeah, that's pretty much it. I mean, 477 00:24:18,080 --> 00:24:21,040 Speaker 1: flu vaccines are made of dead viruses, and when they're 478 00:24:21,080 --> 00:24:24,240 Speaker 1: injected in the body, they trigger this defensive response from 479 00:24:24,280 --> 00:24:26,720 Speaker 1: your immune system, and that kind of serves as a 480 00:24:26,800 --> 00:24:29,680 Speaker 1: training for when the body is faced with the live viruses. 481 00:24:30,160 --> 00:24:32,760 Speaker 1: So then wait, can't we make a universal vaccine by 482 00:24:32,880 --> 00:24:35,440 Speaker 1: just sticking corpses of all the known viral strains into 483 00:24:35,480 --> 00:24:37,840 Speaker 1: one injection, and that way the body would be primed 484 00:24:37,840 --> 00:24:39,840 Speaker 1: to take on all the new viruses. Well, it's a 485 00:24:39,920 --> 00:24:42,720 Speaker 1: nice theory, and I appreciate your trying to solve all 486 00:24:42,800 --> 00:24:45,879 Speaker 1: of this issue with just one big vaccine, But the 487 00:24:45,920 --> 00:24:48,439 Speaker 1: reality is that the human immune system doesn't really have 488 00:24:48,520 --> 00:24:52,720 Speaker 1: the capacity to effectively fight that many viruses at one time, 489 00:24:53,359 --> 00:24:55,720 Speaker 1: and so the vaccine would just wind up making you sick. 490 00:24:56,200 --> 00:24:58,600 Speaker 1: But you know, I was reading about some new research 491 00:24:58,640 --> 00:25:01,359 Speaker 1: from a joint team of US and Chinese scientists who 492 00:25:01,560 --> 00:25:04,680 Speaker 1: think they may have found a workaround, and their solution 493 00:25:04,760 --> 00:25:07,040 Speaker 1: is to boost the immune systems ability to deal with 494 00:25:07,080 --> 00:25:10,040 Speaker 1: a variety of viruses by making a vaccine that elicits 495 00:25:10,040 --> 00:25:13,880 Speaker 1: a strong response from the body's T cells. And those 496 00:25:13,920 --> 00:25:16,680 Speaker 1: are the white blood cells that fight diseases. But don't 497 00:25:16,720 --> 00:25:19,920 Speaker 1: current vaccines stimulate those already? Well that's the thing, I mean, 498 00:25:19,920 --> 00:25:23,360 Speaker 1: the current vaccines don't elicit a strong T cell response 499 00:25:23,400 --> 00:25:27,040 Speaker 1: because they're made from dead viruses. Instead, they only trigger 500 00:25:27,080 --> 00:25:30,119 Speaker 1: the development of anybodies, which are helpful in their own, right, 501 00:25:30,160 --> 00:25:32,640 Speaker 1: I mean they bind to intruding flu cells and help 502 00:25:32,680 --> 00:25:35,639 Speaker 1: prevent infection, but not as much as when they're working 503 00:25:35,640 --> 00:25:38,680 Speaker 1: with T cells. Alright, So well, I think you're biases 504 00:25:38,680 --> 00:25:41,800 Speaker 1: showing what's so great about T cells. Well, in this case, 505 00:25:41,840 --> 00:25:43,840 Speaker 1: the advantage of T cells is that they would be 506 00:25:43,880 --> 00:25:46,679 Speaker 1: on alert for different features of the flu virus. You know, 507 00:25:46,680 --> 00:25:49,679 Speaker 1: anybody's would be mostly keeping watch for the shape of 508 00:25:49,680 --> 00:25:53,000 Speaker 1: the specific strain. So by using a live virus in 509 00:25:53,040 --> 00:25:56,040 Speaker 1: the vaccine, you've got patients that would have both anybodies 510 00:25:56,240 --> 00:25:58,800 Speaker 1: and T cells working on their side from the start, 511 00:25:59,160 --> 00:26:01,080 Speaker 1: you know, rather than way for T cells to show 512 00:26:01,160 --> 00:26:04,840 Speaker 1: up only after you already have the flu. So Kathleen 513 00:26:04,880 --> 00:26:08,320 Speaker 1: Sullivan are director at the Children's Hospital Philadelphia. She describes 514 00:26:08,359 --> 00:26:11,000 Speaker 1: the benefit this way. She says, it has the magic 515 00:26:11,040 --> 00:26:13,679 Speaker 1: of both great and a body response and inducing a 516 00:26:13,800 --> 00:26:16,760 Speaker 1: strong T cell response that will be a safety net. 517 00:26:17,200 --> 00:26:19,600 Speaker 1: So if a virus breaks through the first line of defense, 518 00:26:19,640 --> 00:26:21,720 Speaker 1: you'll have T cells to make sure you don't get 519 00:26:21,840 --> 00:26:25,720 Speaker 1: very sick. Which is pretty cool, But still injecting yourself 520 00:26:25,720 --> 00:26:28,640 Speaker 1: with a live flu virus seems kind of dicey. I mean, 521 00:26:28,800 --> 00:26:30,840 Speaker 1: does this work with just any vital strain that happens 522 00:26:30,840 --> 00:26:32,720 Speaker 1: to be lying around, well not exactly. I mean, see, 523 00:26:32,720 --> 00:26:35,320 Speaker 1: the scientists basically took a part of flu virus in 524 00:26:35,359 --> 00:26:37,800 Speaker 1: their lab, figured out what made it tick, and they 525 00:26:37,840 --> 00:26:41,000 Speaker 1: kind of frankenstein a mutant flu strain that was perfectly 526 00:26:41,040 --> 00:26:44,680 Speaker 1: suited for this new kind of vaccination. And what exactly 527 00:26:44,720 --> 00:26:46,639 Speaker 1: makes it so suitable to be injected live into my 528 00:26:46,680 --> 00:26:49,600 Speaker 1: body because I have to tell you I've avoided Tristan's 529 00:26:49,800 --> 00:26:52,320 Speaker 1: injections here and I'm pretty picky about this kind of thing. 530 00:26:53,600 --> 00:26:55,520 Speaker 1: Well that what they did was they created a strain 531 00:26:55,600 --> 00:26:58,960 Speaker 1: that was strong enough to replicate efficiently, but actually weak 532 00:26:59,040 --> 00:27:01,800 Speaker 1: enough so that our immune systems can easily control them. 533 00:27:02,240 --> 00:27:04,960 Speaker 1: So once the mutant virus is injected into the vaccine, 534 00:27:04,960 --> 00:27:08,600 Speaker 1: it triggers both in anybody response and a T cell response, 535 00:27:08,960 --> 00:27:11,080 Speaker 1: you know, all while never posing that much of an 536 00:27:11,119 --> 00:27:14,080 Speaker 1: actual threat to the body. And not only that, but 537 00:27:14,119 --> 00:27:17,359 Speaker 1: because T cell responses tend to provide longer term immunity, 538 00:27:17,640 --> 00:27:19,639 Speaker 1: a vaccine like this could actually do away with the 539 00:27:19,720 --> 00:27:23,400 Speaker 1: need for annual flu vaccinations. Well, I'm sure there's still 540 00:27:23,440 --> 00:27:25,560 Speaker 1: a ways to go before a universal vaccine like that 541 00:27:25,600 --> 00:27:28,600 Speaker 1: can go public, but I'll admit the prospect of not 542 00:27:28,680 --> 00:27:31,040 Speaker 1: having to get a flu shot anymore is pretty appealing. 543 00:27:31,480 --> 00:27:34,679 Speaker 1: And in the meantime, though, annual vaccinations are still the 544 00:27:34,720 --> 00:27:37,560 Speaker 1: best chance to stay healthy, and not just for ourselves 545 00:27:37,560 --> 00:27:40,160 Speaker 1: but for all of society. I was bringing this article 546 00:27:40,160 --> 00:27:43,600 Speaker 1: in Quanta magazine that pointed out how people who talk 547 00:27:43,680 --> 00:27:46,160 Speaker 1: themselves out of getting flu shots because you know, they 548 00:27:46,240 --> 00:27:48,720 Speaker 1: never get the flu, are sort of missing the point. 549 00:27:48,880 --> 00:27:52,240 Speaker 1: And how's that. Well? The idea is that vaccination campaigns, 550 00:27:52,280 --> 00:27:54,800 Speaker 1: whether for the flu or anything else, aren't merely a 551 00:27:54,800 --> 00:27:57,679 Speaker 1: way of keeping yourself from getting sick. They're also a 552 00:27:57,680 --> 00:28:00,879 Speaker 1: way to boost our collective resistance. There's an idea that 553 00:28:00,920 --> 00:28:04,640 Speaker 1: health experts throw around called herd immunity, which is basically 554 00:28:04,720 --> 00:28:06,880 Speaker 1: the level of immunity that a population needs in order 555 00:28:06,880 --> 00:28:09,720 Speaker 1: to prevent an outbreak of a disease. So when her 556 00:28:09,800 --> 00:28:13,480 Speaker 1: immunity dips below a certain level, which varies from disease disease, 557 00:28:13,880 --> 00:28:17,560 Speaker 1: that's when our epidemics occur. Yeah, that's definitely true, but 558 00:28:17,600 --> 00:28:20,480 Speaker 1: I mean it's kind of painting this vaccinations as the 559 00:28:20,640 --> 00:28:23,359 Speaker 1: be all, end all to the flu protection. So we 560 00:28:23,440 --> 00:28:26,640 Speaker 1: definitely need to think about the other preventative measures out there, 561 00:28:26,840 --> 00:28:29,919 Speaker 1: like avoiding public spaces during flu season, or washing our 562 00:28:30,000 --> 00:28:32,760 Speaker 1: hands more often, and you know all the analysis and 563 00:28:32,840 --> 00:28:36,080 Speaker 1: predictive tracking that goes into planning for a flu season. 564 00:28:36,119 --> 00:28:39,120 Speaker 1: So I mean all of this has to count for something, right, Yeah, 565 00:28:39,120 --> 00:28:41,240 Speaker 1: it does, And every little bit helps when you're up 566 00:28:41,280 --> 00:28:46,360 Speaker 1: against like an ageless, invisible enemy who's constantly changing his tactics. 567 00:28:46,360 --> 00:28:49,280 Speaker 1: But no matter how much you hate getting shots or 568 00:28:49,360 --> 00:28:51,960 Speaker 1: how much you love washing your hands, it doesn't change 569 00:28:51,960 --> 00:28:55,000 Speaker 1: the fact that vaccinations are any society's best option for 570 00:28:55,160 --> 00:28:58,640 Speaker 1: keeping epidemics at bay. So, as Tara Smith put it 571 00:28:58,640 --> 00:29:02,240 Speaker 1: in her article for Quanta, knowing the factors that contribute 572 00:29:02,240 --> 00:29:04,920 Speaker 1: to these outbreaks can AIDA's and stopping epidemics in their 573 00:29:04,920 --> 00:29:07,800 Speaker 1: early stages, but to prevent them from happening in the 574 00:29:07,800 --> 00:29:10,800 Speaker 1: first place, a population with a high level of immunity 575 00:29:10,840 --> 00:29:14,120 Speaker 1: is mathematically our best bet for keeping disease at bay. 576 00:29:14,280 --> 00:29:16,600 Speaker 1: All right, I think you sold me, so Tristan, get 577 00:29:16,640 --> 00:29:18,480 Speaker 1: over here, buddy. I think I finally worked up the 578 00:29:18,520 --> 00:29:21,280 Speaker 1: nerve for the shut Okay, but before I have to 579 00:29:21,280 --> 00:29:22,840 Speaker 1: take you to the e R, why don't we do 580 00:29:22,840 --> 00:29:32,520 Speaker 1: our fact off? All right? That's probably a better idea anyway, 581 00:29:34,360 --> 00:29:36,720 Speaker 1: So we talked a little earlier about the terrible Flu. 582 00:29:38,240 --> 00:29:40,640 Speaker 1: Did you know that if Walt Disney himself hadn't gotten 583 00:29:40,680 --> 00:29:42,960 Speaker 1: the flu during the pandemic, we might have missed out 584 00:29:42,960 --> 00:29:46,360 Speaker 1: on the birth of Mickey Mouse entirely. So, towards the 585 00:29:46,480 --> 00:29:48,800 Speaker 1: end of World War One, Disney was signed up to 586 00:29:48,800 --> 00:29:51,280 Speaker 1: work for the Red Cross Ambulance Corps. He was only 587 00:29:51,320 --> 00:29:53,520 Speaker 1: sixteen at the time, and that might seem a little young, 588 00:29:53,640 --> 00:29:57,000 Speaker 1: but it's because Disney lied about his age. But before 589 00:29:57,080 --> 00:29:59,479 Speaker 1: heading out he actually got the flu, and by the 590 00:29:59,480 --> 00:30:01,720 Speaker 1: time he was well and able to go, the war 591 00:30:01,880 --> 00:30:04,480 Speaker 1: was over alright. Well, one day we may be getting 592 00:30:04,480 --> 00:30:07,200 Speaker 1: our flu shots with a bit of frog slime in them, 593 00:30:07,480 --> 00:30:09,560 Speaker 1: or at least scientists are trying to figure out why. 594 00:30:09,600 --> 00:30:12,760 Speaker 1: It appears that the slime from an Indian fungoid frog 595 00:30:12,800 --> 00:30:16,000 Speaker 1: appears to have multiple peptides that are capable of killing 596 00:30:16,040 --> 00:30:19,200 Speaker 1: the H one flu virus. So they tested the most 597 00:30:19,200 --> 00:30:21,960 Speaker 1: effective of these peptides and this concoction that they gave 598 00:30:22,000 --> 00:30:24,720 Speaker 1: to mice, and sure enough, it actually kept them from 599 00:30:24,760 --> 00:30:27,960 Speaker 1: getting the flu and it seemed to produce no side effects. 600 00:30:28,240 --> 00:30:30,120 Speaker 1: So the next step, of course, is figuring out whether 601 00:30:30,160 --> 00:30:34,240 Speaker 1: this can be tested in people. Another interesting possible treatment estrogen. 602 00:30:34,680 --> 00:30:37,320 Speaker 1: So we've actually known for some time that estrogen seems 603 00:30:37,360 --> 00:30:41,480 Speaker 1: to have some antiviral effect on ebola and hepatitis and HIV, 604 00:30:41,760 --> 00:30:44,600 Speaker 1: so there have recently been more studies on its effects 605 00:30:44,640 --> 00:30:47,720 Speaker 1: on the flu, and through a few studies they found 606 00:30:47,800 --> 00:30:50,800 Speaker 1: that estrogen did in fact significantly slow the replication of 607 00:30:50,800 --> 00:30:53,640 Speaker 1: the flu virus. It'll be interesting to see where this 608 00:30:53,680 --> 00:30:56,400 Speaker 1: goes in terms of developing treatment. But I just thought 609 00:30:56,400 --> 00:30:59,440 Speaker 1: I was fascinating. Yeah, that is pretty interesting. Well, in 610 00:30:59,560 --> 00:31:01,640 Speaker 1: terms of ways to prevent the spread of the flu 611 00:31:01,760 --> 00:31:04,960 Speaker 1: beyond vaccines. The Wall Street Journal reported on a study 612 00:31:05,000 --> 00:31:08,160 Speaker 1: from the National Bureau of Economic Research, and it showed 613 00:31:08,160 --> 00:31:11,080 Speaker 1: that paid sick days for employees would reduce the spread 614 00:31:11,160 --> 00:31:13,440 Speaker 1: of the flu. And maybe that's not a huge surprise, 615 00:31:13,480 --> 00:31:16,240 Speaker 1: but the numbers are pretty surprising. I mean, for those 616 00:31:16,240 --> 00:31:18,160 Speaker 1: who did not get paid sick time, you know, they're 617 00:31:18,160 --> 00:31:20,400 Speaker 1: of course more likely to go to work sick and 618 00:31:20,680 --> 00:31:23,440 Speaker 1: are therefore more likely to spread their illness. And of 619 00:31:23,440 --> 00:31:25,680 Speaker 1: course this is something that can be abused to some extent, 620 00:31:25,720 --> 00:31:28,320 Speaker 1: but when you consider the estimate that paid leave would 621 00:31:28,360 --> 00:31:31,600 Speaker 1: reduce flu cases by six percent, it might just be 622 00:31:31,640 --> 00:31:34,040 Speaker 1: worth it. You know, Mago, I gotta hand it to you. 623 00:31:34,080 --> 00:31:36,400 Speaker 1: We've been talking about something which is not always the 624 00:31:36,440 --> 00:31:39,840 Speaker 1: happiest topic, but you found something positive out of it. 625 00:31:39,880 --> 00:31:42,760 Speaker 1: We have Mickey Mouse because of the flu, so I'm 626 00:31:42,760 --> 00:31:46,040 Speaker 1: gonna have to give you this week's fact Off Trophy. Congratulations. 627 00:31:46,080 --> 00:31:49,200 Speaker 1: Thanks very much. Alright, listeners, if we forgot any facts 628 00:31:49,240 --> 00:31:50,960 Speaker 1: you feel like we should know about, we'd love to 629 00:31:51,040 --> 00:31:53,080 Speaker 1: hear from you. It's part Time Genius at how stuff 630 00:31:53,120 --> 00:31:56,200 Speaker 1: Works dot com. You can also call our seven fact 631 00:31:56,240 --> 00:31:59,280 Speaker 1: hotline that's one eight four four pt Genius, or hit 632 00:31:59,360 --> 00:32:02,320 Speaker 1: us up on book and Twitter. We love hearing from you, 633 00:32:02,400 --> 00:32:18,800 Speaker 1: and thanks so much for listening. Thanks again for listening. 634 00:32:18,920 --> 00:32:21,080 Speaker 1: Part Time Genius is a production of How Stuff Works 635 00:32:21,080 --> 00:32:23,680 Speaker 1: and wouldn't be possible without several brilliant people who do 636 00:32:23,720 --> 00:32:26,840 Speaker 1: the important things we couldn't even begin to understand. 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