1 00:00:01,120 --> 00:00:03,400 Speaker 1: Welcome to Stuff. You should know a production of My 2 00:00:03,600 --> 00:00:12,760 Speaker 1: Heart Radios How Stuff Works. Hey, and welcome to the podcast. 3 00:00:12,800 --> 00:00:15,800 Speaker 1: I'm Josh Clark. There's Charles W Chuck Bryan over there, 4 00:00:16,720 --> 00:00:19,239 Speaker 1: and uh, it's just the two of us again. But 5 00:00:19,600 --> 00:00:23,079 Speaker 1: I'm getting used to it. How about you? I am. 6 00:00:23,120 --> 00:00:27,120 Speaker 1: I am sweating in our studio by myself, Like you're 7 00:00:27,160 --> 00:00:32,600 Speaker 1: nervous now. I'm hot because the studio is hot and 8 00:00:32,960 --> 00:00:35,000 Speaker 1: you know, I know we've been buzz marketing enough, but 9 00:00:35,880 --> 00:00:38,960 Speaker 1: the internet is only working in our studio for some reason. 10 00:00:40,280 --> 00:00:43,640 Speaker 1: And uh, I ate some of that spicy beef ramen 11 00:00:43,960 --> 00:00:49,680 Speaker 1: in this hot room. Yeah, that's a dangerous combo. I 12 00:00:49,680 --> 00:00:51,319 Speaker 1: didn't think to open the door, So I'm just like 13 00:00:51,440 --> 00:00:54,680 Speaker 1: sitting here pouring sweat out everywhere. Well here's the thing. 14 00:00:55,480 --> 00:00:58,240 Speaker 1: You could go totally dong out like Spartacus if you 15 00:00:58,280 --> 00:01:01,480 Speaker 1: wanted to, because you're the only one there. People have 16 00:01:01,520 --> 00:01:04,400 Speaker 1: been talking about dong out lately. To the movie crush page. Yeah, 17 00:01:04,440 --> 00:01:07,839 Speaker 1: well it's a pretty hilarious term. But just please put down, 18 00:01:07,880 --> 00:01:11,120 Speaker 1: like some newspaper or something on the chair before you 19 00:01:11,160 --> 00:01:14,399 Speaker 1: sit on the bare bottomed Okay. Oh, and by the way, 20 00:01:14,400 --> 00:01:18,080 Speaker 1: speaking of movie crush, you. I think this is going 21 00:01:18,120 --> 00:01:21,200 Speaker 1: to come out the day after your movie Crush Mini 22 00:01:21,200 --> 00:01:24,880 Speaker 1: Crush appearance next week. Yeah, I'm excited about it. Man, 23 00:01:25,000 --> 00:01:27,640 Speaker 1: I'm a little nervous. So No, it's gonna be great. 24 00:01:27,640 --> 00:01:29,479 Speaker 1: People are gonna love it. So if you don't listen 25 00:01:29,520 --> 00:01:32,840 Speaker 1: to the show, maybe listen to this one episode and 26 00:01:32,840 --> 00:01:37,080 Speaker 1: then forget about the show again. If you want always 27 00:01:37,080 --> 00:01:40,440 Speaker 1: stick around, maybe boost the numbers a tad. But it 28 00:01:40,560 --> 00:01:42,680 Speaker 1: was a lot of fun, and I think I think 29 00:01:43,160 --> 00:01:45,880 Speaker 1: people would want to hear your appearances. What I really 30 00:01:45,920 --> 00:01:49,120 Speaker 1: appreciated you having me on it was it was a 31 00:01:49,160 --> 00:01:53,840 Speaker 1: lot of fun. It was fun professional at hosting. Hey, 32 00:01:53,960 --> 00:01:56,040 Speaker 1: we turns out we know what we're doing here, don't 33 00:01:56,040 --> 00:02:01,440 Speaker 1: we don't? Uh? Speaking of which, I think we should 34 00:02:01,440 --> 00:02:03,600 Speaker 1: frontload this episode with a little bit of a c 35 00:02:03,800 --> 00:02:08,400 Speaker 1: o A Um. If you are a pretty hard line 36 00:02:08,440 --> 00:02:13,320 Speaker 1: anti vaxer, or if you believe in things like planned 37 00:02:13,320 --> 00:02:18,639 Speaker 1: demmi or that Bill Gates created the coronavirus for population control, 38 00:02:19,760 --> 00:02:21,400 Speaker 1: you may not want to listen to this because we're 39 00:02:21,440 --> 00:02:26,440 Speaker 1: gonna bring you hard and leaned facts, lean and mean, 40 00:02:26,919 --> 00:02:28,920 Speaker 1: depending on your point of view. I think that's a 41 00:02:28,960 --> 00:02:31,040 Speaker 1: good It's a good c O a. I think that 42 00:02:31,120 --> 00:02:35,000 Speaker 1: maybe you got rid of two of the hate mail 43 00:02:35,000 --> 00:02:38,560 Speaker 1: we're gonna get, so thank you for that. Yeah, we'll see. 44 00:02:38,639 --> 00:02:42,840 Speaker 1: I mean I think, uh, it just bears saying, just why, why, 45 00:02:42,880 --> 00:02:46,960 Speaker 1: why rile yourself all up? Just let's listen to your 46 00:02:46,960 --> 00:02:50,720 Speaker 1: echo chamber podcasts that validate what you think maybe or 47 00:02:50,880 --> 00:02:55,400 Speaker 1: or or or or calm down and just hear us 48 00:02:55,440 --> 00:02:58,120 Speaker 1: out and see what you think. Well, that's always a 49 00:02:58,680 --> 00:03:02,399 Speaker 1: you know, it's always an option. You know. So we're 50 00:03:02,440 --> 00:03:08,000 Speaker 1: not even talking necessarily just about vaccines or anti vaccines. Um, 51 00:03:08,040 --> 00:03:11,480 Speaker 1: it's almost like a side thing to this whole thing, 52 00:03:11,880 --> 00:03:16,960 Speaker 1: but it's definitely still, um, very much intertwined with it. Um, 53 00:03:17,040 --> 00:03:21,280 Speaker 1: we're talking about her can't or you can't not talk 54 00:03:21,360 --> 00:03:23,640 Speaker 1: about vaccines if you're going to talk about her immunity 55 00:03:24,120 --> 00:03:28,320 Speaker 1: right now, because with with her immunity, especially in the 56 00:03:28,320 --> 00:03:31,120 Speaker 1: twenty one century, there's basically two ways of getting there, 57 00:03:31,520 --> 00:03:36,880 Speaker 1: and one of them is a robust vaccination program. That's right. 58 00:03:37,040 --> 00:03:40,720 Speaker 1: And if you don't know what her immunity is, then um, 59 00:03:40,840 --> 00:03:42,800 Speaker 1: then you're probably just fine. You've been living under a 60 00:03:42,880 --> 00:03:45,040 Speaker 1: rock and you're not near any other humans or the internet. 61 00:03:45,200 --> 00:03:48,680 Speaker 1: You're still protected though that's right. Herd immunity those the 62 00:03:48,720 --> 00:03:52,280 Speaker 1: principle uh, sort of in its simplest form of safety 63 00:03:52,280 --> 00:03:54,720 Speaker 1: and numbers and if you have a lot of people 64 00:03:55,480 --> 00:03:58,560 Speaker 1: or enough people, because there's actual math involved to figuring 65 00:03:58,600 --> 00:04:00,800 Speaker 1: that out. It's not just a guess. If you have 66 00:04:00,920 --> 00:04:04,600 Speaker 1: enough people that are immune to a virus. Uh. And 67 00:04:04,600 --> 00:04:07,120 Speaker 1: it can be like you said, through vaccination or through 68 00:04:07,520 --> 00:04:11,200 Speaker 1: having lived through the disease and then having antibodies, then 69 00:04:11,480 --> 00:04:17,000 Speaker 1: the population is protected from that disease even if they 70 00:04:17,000 --> 00:04:20,040 Speaker 1: are an immune. That's that's the idea that so many 71 00:04:20,080 --> 00:04:23,559 Speaker 1: a certain threshold of people are immune that even people 72 00:04:23,640 --> 00:04:28,320 Speaker 1: that choose not to vaccinate can hop on that wagon, right. Um. 73 00:04:28,440 --> 00:04:30,839 Speaker 1: And it's not even like you hop on the wagon, 74 00:04:30,960 --> 00:04:33,960 Speaker 1: like you are on the wagon just by vulture being 75 00:04:34,000 --> 00:04:36,919 Speaker 1: alive in the society or culture. Right. So that's a 76 00:04:36,920 --> 00:04:39,480 Speaker 1: good point. Um. There's a really easy way of understanding 77 00:04:39,560 --> 00:04:44,159 Speaker 1: it that Molly Edmonds used in Um the House Stuff 78 00:04:44,160 --> 00:04:47,520 Speaker 1: Works episode Unheard Immunity that if you pretend you're at 79 00:04:47,520 --> 00:04:50,160 Speaker 1: a bowling alley and each person has their own lane, 80 00:04:50,200 --> 00:04:53,160 Speaker 1: and this is basically that bowling alley lane is like 81 00:04:53,520 --> 00:04:57,040 Speaker 1: there their bubble that they live in, their work their 82 00:04:57,040 --> 00:05:00,360 Speaker 1: home and everything, and they don't encounter anybody else. That's 83 00:05:00,400 --> 00:05:03,719 Speaker 1: kind of like Wally, But with bowling. If the first 84 00:05:03,760 --> 00:05:08,880 Speaker 1: person on lane one comes down with say the flu um, 85 00:05:08,960 --> 00:05:11,279 Speaker 1: he can very easily pass it on to the woman 86 00:05:11,320 --> 00:05:14,159 Speaker 1: in lane two. If she's not immune to the flu, 87 00:05:14,360 --> 00:05:16,800 Speaker 1: she will contract it and pass it on to the 88 00:05:16,800 --> 00:05:18,760 Speaker 1: person in lane three, and so on and so forth, 89 00:05:18,800 --> 00:05:22,760 Speaker 1: and it'll just keep going and eventually people will develop anybodies. 90 00:05:23,040 --> 00:05:26,200 Speaker 1: Some of those people will die, most will survive, uh, 91 00:05:26,240 --> 00:05:28,760 Speaker 1: and the flu will have a hard time getting through 92 00:05:28,760 --> 00:05:33,240 Speaker 1: that population a second time around. But if the woman 93 00:05:33,279 --> 00:05:37,200 Speaker 1: in lane two is already immunized to that flu strain, 94 00:05:37,400 --> 00:05:40,920 Speaker 1: say through like a vaccine or something, then it's not 95 00:05:40,960 --> 00:05:44,120 Speaker 1: going to transmit from the first guy in lane one 96 00:05:44,400 --> 00:05:47,360 Speaker 1: to her, or it's certainly not going to transmit beyond her. 97 00:05:47,680 --> 00:05:51,520 Speaker 1: So she's protected everybody in lanes three through ten just 98 00:05:51,560 --> 00:05:55,000 Speaker 1: by virtue of having been immune to that flu virus. 99 00:05:55,160 --> 00:05:59,400 Speaker 1: It's stopped with her, and that's the point of her immunity. 100 00:05:59,440 --> 00:06:02,960 Speaker 1: That's the whole that's the basis of the whole thing. Yeah, 101 00:06:03,040 --> 00:06:05,080 Speaker 1: And if we want to stick with bowling parlance, then 102 00:06:05,120 --> 00:06:07,599 Speaker 1: that means that that lady is bowling strikes. She's throwing 103 00:06:07,680 --> 00:06:11,159 Speaker 1: strikes strikes, not even seven ten splits, which she could 104 00:06:11,200 --> 00:06:14,039 Speaker 1: if she wanted to. That's how she is. Yeah, the 105 00:06:14,080 --> 00:06:18,200 Speaker 1: perfect game, right. I remember that dumb joke when I 106 00:06:18,240 --> 00:06:20,640 Speaker 1: was a little about You know, you learn the stupidest 107 00:06:20,680 --> 00:06:22,760 Speaker 1: jokes when you're a kid because they have to be 108 00:06:22,760 --> 00:06:24,599 Speaker 1: so dumb. A kid can understand him, I think, I 109 00:06:24,640 --> 00:06:27,159 Speaker 1: think so. But about the the guy who bowled a 110 00:06:27,160 --> 00:06:29,960 Speaker 1: three hundred and one and you're like, you can't bowl 111 00:06:29,960 --> 00:06:32,240 Speaker 1: a three d and one, Well, you can't bowl a 112 00:06:32,279 --> 00:06:38,080 Speaker 1: three hundred and lose, man. I know. That's how bad 113 00:06:38,120 --> 00:06:39,560 Speaker 1: it was, and that's how much it stuck with me. 114 00:06:39,640 --> 00:06:43,400 Speaker 1: Did you get that from highlights? I don't know where 115 00:06:43,440 --> 00:06:45,320 Speaker 1: I got that. It's pretty bad. It sounds like a 116 00:06:45,320 --> 00:06:48,640 Speaker 1: playground joke. I think so. But I think you beat 117 00:06:48,720 --> 00:06:51,919 Speaker 1: up in the playground even with that one. Yeah. So 118 00:06:52,400 --> 00:06:55,400 Speaker 1: let's talk about her community some more. We talked about 119 00:06:55,440 --> 00:07:00,160 Speaker 1: the two ways natural exposure and vaccinations, and if we're 120 00:07:00,200 --> 00:07:04,080 Speaker 1: going back pre vaccination and talking about human history. Um, 121 00:07:04,160 --> 00:07:06,800 Speaker 1: the hurt there was hert immunity, and it was I 122 00:07:06,800 --> 00:07:09,320 Speaker 1: guess the way to describe it as herd immunity. The 123 00:07:09,360 --> 00:07:13,160 Speaker 1: hard way. Um, people being exposed to the virus or 124 00:07:13,200 --> 00:07:17,400 Speaker 1: the bacteria developing that immune response and enough, you know, 125 00:07:17,440 --> 00:07:19,480 Speaker 1: they reached that tipping point where enough people have it 126 00:07:19,880 --> 00:07:22,280 Speaker 1: to where everyone's immune. But they lost a lot of 127 00:07:22,320 --> 00:07:24,400 Speaker 1: people along the way. Yeah, that's part of the problem 128 00:07:24,480 --> 00:07:26,880 Speaker 1: is is if you look at it on an individual level, 129 00:07:26,920 --> 00:07:30,160 Speaker 1: if you are exposed to a virus or a bacterium 130 00:07:30,200 --> 00:07:33,080 Speaker 1: and it runs rampant and infects you when you come 131 00:07:33,120 --> 00:07:37,760 Speaker 1: down with an illness from it, you there's basically two outcomes. 132 00:07:38,160 --> 00:07:40,920 Speaker 1: You can put it up, put up an immune response 133 00:07:41,000 --> 00:07:44,480 Speaker 1: and win, or you can lose and die. But if 134 00:07:44,560 --> 00:07:48,440 Speaker 1: you survive and win, you've become immunized. And that's just 135 00:07:48,480 --> 00:07:52,800 Speaker 1: the natural course of viruses or bacteria when they encounter humans. 136 00:07:52,840 --> 00:07:56,360 Speaker 1: It's at least contagious ones infectious ones, right, um. And 137 00:07:56,360 --> 00:07:59,560 Speaker 1: and we didn't have any recourse other than that. So 138 00:07:59,560 --> 00:08:01,640 Speaker 1: it's actually kind of good that we do have this 139 00:08:02,160 --> 00:08:06,400 Speaker 1: natural immune response to I mean, we just wouldn't be 140 00:08:06,440 --> 00:08:08,480 Speaker 1: around anymore if we didn't have. Its. Part and parcel 141 00:08:08,520 --> 00:08:11,640 Speaker 1: with human survival or any biological survival is to be 142 00:08:11,680 --> 00:08:14,960 Speaker 1: able to mount in immune response, build antibodies so that 143 00:08:15,000 --> 00:08:17,000 Speaker 1: if you do encounter this thing again. You don't have 144 00:08:17,080 --> 00:08:19,520 Speaker 1: to go through the illness all over again for the 145 00:08:19,560 --> 00:08:24,320 Speaker 1: most part. But like, we didn't have any other tools 146 00:08:24,400 --> 00:08:28,480 Speaker 1: besides that until the nineteen forties when we were able 147 00:08:28,520 --> 00:08:32,080 Speaker 1: to mass manufacture vaccines, and now all of a sudden, 148 00:08:32,160 --> 00:08:36,720 Speaker 1: we could say, create herd immunity without anybody ever having 149 00:08:36,760 --> 00:08:41,520 Speaker 1: to get sick or almost anybody, um, just through vaccination 150 00:08:42,120 --> 00:08:47,160 Speaker 1: vaccination programs. Yeah, and here's the deal to uh. In 151 00:08:47,520 --> 00:08:50,880 Speaker 1: you know, pre vaccination, they could build up an immunity, 152 00:08:50,960 --> 00:08:52,480 Speaker 1: lose a lot of people on the way, and it 153 00:08:52,520 --> 00:08:55,440 Speaker 1: wasn't like, all right, now we're fully set forever. Uh. 154 00:08:55,520 --> 00:08:59,280 Speaker 1: Sometimes there would be like another swell of exposure, whether 155 00:08:59,400 --> 00:09:01,600 Speaker 1: or not it's like a bunch of people moving into 156 00:09:01,600 --> 00:09:04,280 Speaker 1: the country or a bunch of people being born, but 157 00:09:04,360 --> 00:09:08,720 Speaker 1: basically non immune people kind of flooding the system. And 158 00:09:08,720 --> 00:09:10,920 Speaker 1: then that percentage point that we're going to talk about 159 00:09:11,000 --> 00:09:13,640 Speaker 1: dips below that number, and then you kind of you 160 00:09:13,640 --> 00:09:16,079 Speaker 1: don't have to restart the whole process, but it kind 161 00:09:16,080 --> 00:09:18,960 Speaker 1: of that hamster wheel gets going again until that herd 162 00:09:18,960 --> 00:09:22,000 Speaker 1: immunity is then reached again. Yeah. That's I think that's 163 00:09:22,120 --> 00:09:25,760 Speaker 1: um what's called an endemic disease where it's still they're 164 00:09:25,840 --> 00:09:28,440 Speaker 1: just hanging in the background. But for the most part, 165 00:09:28,480 --> 00:09:31,040 Speaker 1: people are immune to it. And then when you have 166 00:09:31,160 --> 00:09:33,600 Speaker 1: like an influx of births or an influx of immigrants, 167 00:09:33,640 --> 00:09:36,280 Speaker 1: that can flare up again. But then those people get 168 00:09:36,640 --> 00:09:40,160 Speaker 1: um kind of taken into the immunized herd, become part 169 00:09:40,160 --> 00:09:42,440 Speaker 1: of the immunized herd as well. And and the deal 170 00:09:42,559 --> 00:09:44,760 Speaker 1: is is that natural herd immunity is all we had 171 00:09:44,840 --> 00:09:48,319 Speaker 1: until we developed kind of the ability to make massive 172 00:09:48,400 --> 00:09:51,880 Speaker 1: quantities of vaccines, right I think of the starting in 173 00:09:51,880 --> 00:09:54,840 Speaker 1: the nineteen forties. Yeah, I mean there were a few 174 00:09:54,840 --> 00:09:58,120 Speaker 1: researchers along the way who really brought this along. There 175 00:09:58,200 --> 00:10:00,600 Speaker 1: was a couple of people, name a couple of dudes 176 00:10:00,679 --> 00:10:05,360 Speaker 1: named W. W. C. Topley and G. S. Wilson who 177 00:10:05,400 --> 00:10:09,880 Speaker 1: actually coined the term um herd immunity. But in ninety three. 178 00:10:10,280 --> 00:10:15,360 Speaker 1: That was an UH epidemiologist named A. W. Hydrick who 179 00:10:15,400 --> 00:10:19,480 Speaker 1: studied measles between ninety one and he's the one that 180 00:10:19,520 --> 00:10:22,880 Speaker 1: actually kind of quantified this and said, I've done the math. 181 00:10:23,360 --> 00:10:26,679 Speaker 1: If sixty percent of kids fifteen or younger were immune 182 00:10:26,679 --> 00:10:29,040 Speaker 1: to measles, then we're not going to have a big outbreak, 183 00:10:29,040 --> 00:10:31,440 Speaker 1: and he wrote a very famous paper about it, and 184 00:10:31,480 --> 00:10:35,280 Speaker 1: that's where the term really took off. Yeah, and so, um, 185 00:10:35,480 --> 00:10:42,840 Speaker 1: herd immunity is basically an epidemiological concept. It gets um sometimes, 186 00:10:42,840 --> 00:10:46,240 Speaker 1: I think in the in the popular press especially, it 187 00:10:46,320 --> 00:10:48,240 Speaker 1: gets kind of leaned on as if it's like a 188 00:10:48,480 --> 00:10:52,600 Speaker 1: natural universal law or something like that. It's basically an observation, 189 00:10:53,200 --> 00:10:56,080 Speaker 1: but one that has seems to be consistently held up 190 00:10:56,440 --> 00:11:00,360 Speaker 1: by the success of vaccination programs that we've cre aided 191 00:11:00,600 --> 00:11:04,720 Speaker 1: to generate artificial herd immunity. And that's the point. That's 192 00:11:04,760 --> 00:11:10,199 Speaker 1: the point of vaccine programs is to say, okay, for 193 00:11:10,200 --> 00:11:13,200 Speaker 1: for basically all of human history, all we had was 194 00:11:13,679 --> 00:11:16,000 Speaker 1: that natural herd immunity, whether we liked it or not. 195 00:11:16,120 --> 00:11:18,920 Speaker 1: But now that we have vaccines, we can create vaccine 196 00:11:18,960 --> 00:11:23,199 Speaker 1: programs where if we vaccinate enough people, we can force 197 00:11:23,320 --> 00:11:28,280 Speaker 1: this herd immunity without almost anybody getting sick. Like you 198 00:11:28,360 --> 00:11:31,000 Speaker 1: might have a slight reaction to the vaccine for a 199 00:11:31,040 --> 00:11:34,520 Speaker 1: small number of people, usually somewhere around like say three 200 00:11:34,520 --> 00:11:37,640 Speaker 1: to ten percent, the vaccine is not going to protect you. 201 00:11:37,920 --> 00:11:40,920 Speaker 1: But if enough people out there get this vaccine, they're 202 00:11:40,920 --> 00:11:44,640 Speaker 1: going to be vaccinated. Immunized against the disease without ever 203 00:11:44,760 --> 00:11:48,120 Speaker 1: having gotten it. And if enough people are vaccinated, we 204 00:11:48,160 --> 00:11:51,320 Speaker 1: will have this herd immunity without having to undergo some 205 00:11:51,400 --> 00:11:56,000 Speaker 1: disastrous epidemic that kills off some ungodly number of people 206 00:11:56,400 --> 00:11:59,720 Speaker 1: and makes an even larger number of people sick. That's 207 00:11:59,760 --> 00:12:03,960 Speaker 1: the basis of vaccines in the vaccination program. And I 208 00:12:04,000 --> 00:12:07,840 Speaker 1: mean countless tens of millions of lives have been saved 209 00:12:08,320 --> 00:12:10,599 Speaker 1: just from the fact that they have existed since the 210 00:12:10,679 --> 00:12:14,320 Speaker 1: nineteen forties. Yeah, I mean that's when they came into 211 00:12:14,360 --> 00:12:18,960 Speaker 1: mass production in se is, when we first started as humans. 212 00:12:19,000 --> 00:12:21,880 Speaker 1: To kind of understand this concept, there was a man 213 00:12:21,960 --> 00:12:25,480 Speaker 1: named Edward Jenner who inoculated a little kid, a little boy, 214 00:12:25,480 --> 00:12:28,800 Speaker 1: against smallpox. And this is kind of gross sounding, but 215 00:12:28,840 --> 00:12:32,800 Speaker 1: he infected him with the plus from a blister of 216 00:12:32,960 --> 00:12:36,520 Speaker 1: cow cow pox, which is less deadly, and he was like, Hey, 217 00:12:36,559 --> 00:12:40,360 Speaker 1: I think I'm onto something here, and in uh, two 218 00:12:40,480 --> 00:12:43,319 Speaker 1: hundred and or I guess a hundred and forty something years, 219 00:12:44,559 --> 00:12:46,680 Speaker 1: we're really going to be on the ball with this stuff, right. 220 00:12:46,960 --> 00:12:50,280 Speaker 1: And there were others like vaccines along the way, but um, 221 00:12:50,320 --> 00:12:53,320 Speaker 1: and I think they were all just kind of small batch. 222 00:12:53,800 --> 00:12:58,080 Speaker 1: You know, like artisan vaccines that were created, um, but 223 00:12:58,320 --> 00:13:01,360 Speaker 1: the uh, the it was like the forties where this 224 00:13:01,480 --> 00:13:04,920 Speaker 1: on this mass industrial scale that that they were produced. 225 00:13:04,920 --> 00:13:07,880 Speaker 1: And only under those circumstances can you actually get to 226 00:13:08,040 --> 00:13:11,800 Speaker 1: herd immunity for like a large population like a state 227 00:13:11,920 --> 00:13:17,000 Speaker 1: or a nation or a world. Basically, Yeah, and you know, 228 00:13:17,120 --> 00:13:18,960 Speaker 1: I think we've said this will kind of keep beating 229 00:13:18,960 --> 00:13:21,680 Speaker 1: this drum and repeating this, but the whole concept is 230 00:13:21,720 --> 00:13:26,479 Speaker 1: to protect people who haven't even been vaccinated. Just sometimes 231 00:13:27,000 --> 00:13:29,440 Speaker 1: you're too young to get vaccinated, Sometimes you have a 232 00:13:29,440 --> 00:13:32,600 Speaker 1: condition as a child where you literally can't be vaccinated, 233 00:13:33,360 --> 00:13:36,920 Speaker 1: or maybe you're elderly and you had been vaccinated. But 234 00:13:37,400 --> 00:13:40,319 Speaker 1: you know, they always talk about, especially with COVID nineteen 235 00:13:40,360 --> 00:13:43,280 Speaker 1: and and the flu, the elderly population is at risk 236 00:13:43,360 --> 00:13:48,400 Speaker 1: because they're way more likely to develop complications like uh, 237 00:13:48,559 --> 00:13:51,000 Speaker 1: pneumonia as a big one for what's going around now, 238 00:13:51,440 --> 00:13:54,640 Speaker 1: but as far as even something like chicken pox, encephalitis 239 00:13:54,679 --> 00:13:58,400 Speaker 1: or hepatitis. And we don't really know the deal with 240 00:13:58,720 --> 00:14:02,560 Speaker 1: children and adults their immune system and exactly how they 241 00:14:02,600 --> 00:14:05,679 Speaker 1: work and what the differences are, but it looks like 242 00:14:05,800 --> 00:14:10,760 Speaker 1: kids are either more robust and against something like chicken pox, 243 00:14:11,080 --> 00:14:12,400 Speaker 1: like when you have it as a kid is usually 244 00:14:12,440 --> 00:14:14,200 Speaker 1: not such a big deal. When you have it as 245 00:14:14,200 --> 00:14:16,360 Speaker 1: an adult, it is a big deal because it may 246 00:14:16,400 --> 00:14:19,640 Speaker 1: be your adult system just going into overdrive saying you 247 00:14:19,640 --> 00:14:22,200 Speaker 1: should have had this when you were six, Right, what 248 00:14:22,400 --> 00:14:25,040 Speaker 1: is wrong with you? Didn't you have any friends? Did 249 00:14:25,120 --> 00:14:27,520 Speaker 1: you have chicken pox? Probably didn't you? I did? I 250 00:14:27,560 --> 00:14:30,840 Speaker 1: did here. Yeah, my sister always had. She had a 251 00:14:30,880 --> 00:14:33,560 Speaker 1: pox scar like on her temple that I always admired, 252 00:14:33,600 --> 00:14:35,600 Speaker 1: so I made sure to like pick one on my temple. 253 00:14:37,200 --> 00:14:40,000 Speaker 1: I don't think Emily got it for some reason. I'm 254 00:14:40,040 --> 00:14:42,360 Speaker 1: that is in my brain. Oh my is she? Does 255 00:14:42,360 --> 00:14:45,760 Speaker 1: she have the vaccine against it? I think so? Okay, 256 00:14:45,800 --> 00:14:48,040 Speaker 1: because since the mid nineties they came out with a 257 00:14:48,200 --> 00:14:51,000 Speaker 1: vaccine against ari selah, which is the virus that causes 258 00:14:51,080 --> 00:14:53,720 Speaker 1: chicken pox, And now it's like you don't have to 259 00:14:53,760 --> 00:14:56,280 Speaker 1: get it as a kid any anymore. I'm pretty sure 260 00:14:56,440 --> 00:14:58,840 Speaker 1: somebody I know didn't get it and did get the vaccine, 261 00:14:58,840 --> 00:15:05,240 Speaker 1: and I'm pretty sure it's right, so pretty well so 262 00:15:05,400 --> 00:15:08,520 Speaker 1: um so with chicken pox, that's a good example of 263 00:15:08,560 --> 00:15:10,520 Speaker 1: how like you know, if you haven't when you're a kid, 264 00:15:10,560 --> 00:15:12,640 Speaker 1: it's I mean, it's still life threatening. You can get 265 00:15:12,640 --> 00:15:16,080 Speaker 1: all those same things like encephalitis or pneumonia, but you're 266 00:15:16,120 --> 00:15:18,560 Speaker 1: just way likelier to get it as an adult. Same 267 00:15:18,640 --> 00:15:21,880 Speaker 1: thing with the flu, Like the flu can be very 268 00:15:21,920 --> 00:15:25,920 Speaker 1: deadly depending on how old you are. UM, I think 269 00:15:26,000 --> 00:15:30,560 Speaker 1: something like it says ninety percent of flu related deaths 270 00:15:30,640 --> 00:15:34,280 Speaker 1: and fifty to seventy percent of hospitalizations for the flu 271 00:15:34,400 --> 00:15:38,040 Speaker 1: are for people over age sixty five. I mean, so 272 00:15:38,280 --> 00:15:41,000 Speaker 1: for the same exact strain of a bug that, like 273 00:15:41,240 --> 00:15:43,760 Speaker 1: you know, has a kid at home watching prices right 274 00:15:44,160 --> 00:15:48,960 Speaker 1: for one day, maybe two, UM, it lands an older 275 00:15:49,000 --> 00:15:51,360 Speaker 1: person over age sixty five in the hospital on the 276 00:15:51,400 --> 00:15:54,040 Speaker 1: brink of death. You know, it's just different. And so 277 00:15:54,280 --> 00:15:58,000 Speaker 1: because that there is that difference, it makes sense to 278 00:15:58,080 --> 00:16:02,200 Speaker 1: immunize the young, inoculate the young, to protect the elderly. 279 00:16:02,480 --> 00:16:04,960 Speaker 1: And let's not forget, even if you couldn't care less 280 00:16:05,000 --> 00:16:08,120 Speaker 1: about the elderly, you hate the elderly because some old 281 00:16:08,120 --> 00:16:10,840 Speaker 1: man yelled at you once when you threw a football 282 00:16:10,840 --> 00:16:13,360 Speaker 1: in his yard, and you've hated all old people ever since. 283 00:16:13,400 --> 00:16:17,520 Speaker 1: Then do you hate babies because there are there are 284 00:16:17,560 --> 00:16:20,520 Speaker 1: babies who are too young to be inoculated? And then 285 00:16:20,520 --> 00:16:23,360 Speaker 1: there's also those people, like you said, who don't have 286 00:16:23,680 --> 00:16:27,360 Speaker 1: um healthy enough immune systems to get a vaccine, and 287 00:16:27,400 --> 00:16:31,360 Speaker 1: so they rely on the everybody else the herd to 288 00:16:31,440 --> 00:16:35,200 Speaker 1: be vaccinated to provide this immunity for them. So there 289 00:16:35,200 --> 00:16:38,640 Speaker 1: are really good reasons to be vaccinated in addition to 290 00:16:39,280 --> 00:16:44,680 Speaker 1: you yourself being immunized against these things. Yeah, and you know, 291 00:16:45,360 --> 00:16:48,920 Speaker 1: these things work better in a homogeneous population. And every 292 00:16:48,920 --> 00:16:50,920 Speaker 1: time I see that word, I want to say homogeneous 293 00:16:51,280 --> 00:16:53,960 Speaker 1: for some reason, that's the British way of saying. Do 294 00:16:54,040 --> 00:16:56,160 Speaker 1: they say that way? They probably do, probably just to 295 00:16:56,200 --> 00:17:03,080 Speaker 1: be contrarian or contrary Indian. Uh, they work better and 296 00:17:03,240 --> 00:17:05,880 Speaker 1: homogeneous populations, which there are not a lot of those 297 00:17:06,119 --> 00:17:09,760 Speaker 1: uh still these days, um, thanks to you know, people 298 00:17:09,840 --> 00:17:13,200 Speaker 1: integrating with one another. So when they do these calculations 299 00:17:13,200 --> 00:17:15,119 Speaker 1: that we're about to talk about, they take all of 300 00:17:15,160 --> 00:17:20,520 Speaker 1: that into account, races, ethnicities, mixed races, stuff like that. 301 00:17:21,000 --> 00:17:23,320 Speaker 1: And so you know, we've been talking about the modeling 302 00:17:23,520 --> 00:17:27,040 Speaker 1: and the math involved. It can get complicated, but it's 303 00:17:27,080 --> 00:17:31,000 Speaker 1: really kind of simple that it's base form, don't you think, yes, 304 00:17:31,119 --> 00:17:34,520 Speaker 1: especially if you're a mathematical genius in a statistical whiz, 305 00:17:34,920 --> 00:17:38,120 Speaker 1: which I am not okay, But in the broad strokes, yeah, 306 00:17:38,200 --> 00:17:39,920 Speaker 1: you you can make a pretty good case that it's 307 00:17:39,960 --> 00:17:43,080 Speaker 1: understandable for sure that it's it's all based on the 308 00:17:43,160 --> 00:17:49,600 Speaker 1: reproduction number in relation to the size of the population. Basically, yeah, 309 00:17:49,600 --> 00:17:52,920 Speaker 1: and that reproduction number they in the in the biz, 310 00:17:53,680 --> 00:17:56,760 Speaker 1: it's pronounced are not. It's are with a. I guess 311 00:17:56,600 --> 00:17:59,919 Speaker 1: that's a zero. Huh, yeah, I'd to say our zero 312 00:18:00,000 --> 00:18:04,399 Speaker 1: any day. Are not though, for an infection, is a 313 00:18:04,480 --> 00:18:08,400 Speaker 1: number of people expected to contract that illness after coming 314 00:18:08,400 --> 00:18:12,359 Speaker 1: into contact with an infected person under the right conditions 315 00:18:13,000 --> 00:18:16,920 Speaker 1: that they can contract it. So a less confusing way 316 00:18:16,960 --> 00:18:19,080 Speaker 1: of saying that is the are not number is the 317 00:18:19,119 --> 00:18:22,199 Speaker 1: expected number of people that a contagious person is going 318 00:18:22,240 --> 00:18:26,080 Speaker 1: to infect. Right, So if you understand this about a disease, 319 00:18:26,119 --> 00:18:30,120 Speaker 1: if you know um, for example, with the MOMPS that's 320 00:18:30,240 --> 00:18:33,640 Speaker 1: extremely contagious, which means that it has a high are 321 00:18:33,760 --> 00:18:37,439 Speaker 1: not because the average person walking around infected with the 322 00:18:37,480 --> 00:18:39,920 Speaker 1: MOMPS and contagious with the MOMPS is going to get 323 00:18:40,000 --> 00:18:44,040 Speaker 1: something between ten and twelve other people infected with the 324 00:18:44,119 --> 00:18:46,760 Speaker 1: MOMPS and then they themselves will be contagious. So that 325 00:18:46,800 --> 00:18:49,320 Speaker 1: means that the MOMPS has a relatively high are not 326 00:18:49,760 --> 00:18:53,200 Speaker 1: or reproduction number. So if you understand that about the moms, 327 00:18:53,480 --> 00:18:57,439 Speaker 1: you can calculate how many people in a population have 328 00:18:57,680 --> 00:19:01,879 Speaker 1: to be immunized against the momps to to prevent it 329 00:19:02,000 --> 00:19:05,400 Speaker 1: from transmitting within that population. And, like we said, there's 330 00:19:05,440 --> 00:19:08,320 Speaker 1: a lot more math to it than that, but ultimately, 331 00:19:08,440 --> 00:19:14,080 Speaker 1: for the months in today's modern heterogeneous populations, is that 332 00:19:14,160 --> 00:19:17,600 Speaker 1: the right way of saying. I don't know. Nobody says heterogeneous, 333 00:19:17,600 --> 00:19:21,199 Speaker 1: do they. That sounds way too close to erotic. It 334 00:19:21,240 --> 00:19:25,119 Speaker 1: sounds like something I would say, so um uh, in 335 00:19:25,160 --> 00:19:28,919 Speaker 1: today's modern society, We'll just put it like that, you 336 00:19:29,000 --> 00:19:34,840 Speaker 1: need to have about of any given population immunized against 337 00:19:34,960 --> 00:19:39,679 Speaker 1: momps to reach what's called the herd immunity threshold. That 338 00:19:39,720 --> 00:19:42,320 Speaker 1: herd immunity threshold is basically what I just said. It's 339 00:19:42,359 --> 00:19:45,160 Speaker 1: the percentage of the population that has to be immunized 340 00:19:45,400 --> 00:19:49,800 Speaker 1: for her immunity to kick in to cover everybody else. Yeah, 341 00:19:49,840 --> 00:19:52,320 Speaker 1: and I know that everyone's going, what about COVID, What 342 00:19:52,320 --> 00:19:55,760 Speaker 1: about COVID? What about COVID? Oh? Do you want to 343 00:19:55,800 --> 00:19:58,080 Speaker 1: not even say yet? You want to wait? Okay, I 344 00:19:58,160 --> 00:20:01,280 Speaker 1: mean that's fine, that's fine. We'll how about this let's 345 00:20:01,320 --> 00:20:03,919 Speaker 1: take a break. Oh my god, this is just and 346 00:20:03,920 --> 00:20:07,920 Speaker 1: then right after the break, we'll we'll dive into this 347 00:20:07,920 --> 00:20:09,679 Speaker 1: stuff later, but right after the break, we'll give you 348 00:20:09,720 --> 00:20:11,959 Speaker 1: sort of what they're thinking as of today when we 349 00:20:12,000 --> 00:20:41,280 Speaker 1: record right after this shosh and shock. All right, So 350 00:20:41,320 --> 00:20:45,920 Speaker 1: that was an unfair cliffhanger, uh, And keep in mind, 351 00:20:46,000 --> 00:20:47,879 Speaker 1: like we kind of learned and we knew this was 352 00:20:47,880 --> 00:20:50,000 Speaker 1: going to happen with our COVID nineteen podcast, it was 353 00:20:50,040 --> 00:20:52,639 Speaker 1: out of date like days later, and this will be 354 00:20:52,640 --> 00:20:54,520 Speaker 1: out of date because there's just so much we don't 355 00:20:54,560 --> 00:20:56,399 Speaker 1: know yet and we're learning so much every day and 356 00:20:56,440 --> 00:21:02,000 Speaker 1: every week. But I've seen the range from six is 357 00:21:02,000 --> 00:21:05,119 Speaker 1: what they think the immunity threshold needs to be for 358 00:21:05,480 --> 00:21:10,640 Speaker 1: UH to have a pretty successful herd immunity, Right, that's 359 00:21:10,680 --> 00:21:12,880 Speaker 1: the current thinking that I saw as well, that they 360 00:21:12,920 --> 00:21:15,920 Speaker 1: think the reproduction number is somewhere between two and three. 361 00:21:16,320 --> 00:21:18,199 Speaker 1: I think that's a two point eight is like the 362 00:21:18,240 --> 00:21:23,840 Speaker 1: most widely touted for COVID nineteen, thankfully. I mean, can 363 00:21:23,880 --> 00:21:27,800 Speaker 1: you imagine if it was like a month's level, right, Yeah, No, 364 00:21:27,920 --> 00:21:30,080 Speaker 1: that's especially with the fact that there's such a thing 365 00:21:30,119 --> 00:21:33,000 Speaker 1: as asymptomatic carriers who can walk around in fating people. 366 00:21:33,040 --> 00:21:36,200 Speaker 1: If that was that much more contagious, it would be, Yeah, 367 00:21:36,280 --> 00:21:38,439 Speaker 1: it would be pretty rotten. Like it as bad as 368 00:21:38,520 --> 00:21:43,040 Speaker 1: it is, it could conceivably be worse epidemiologically speaking. Yeah, 369 00:21:43,080 --> 00:21:45,480 Speaker 1: And here's where we should also point out that, just 370 00:21:45,720 --> 00:21:47,880 Speaker 1: like we're talking about her immunity, but if we reach 371 00:21:47,960 --> 00:21:51,960 Speaker 1: her immunity, that doesn't mean like everything is solved. Um, 372 00:21:52,000 --> 00:21:54,119 Speaker 1: if we come up with a vaccine, which we will, 373 00:21:54,720 --> 00:22:00,640 Speaker 1: vaccines aren't effective against every single human, so things can 374 00:22:00,720 --> 00:22:04,600 Speaker 1: still happen. Um, And then sometimes you get an immunization 375 00:22:05,080 --> 00:22:08,280 Speaker 1: that's effective for a short time, for a few years. Maybe. Yeah, 376 00:22:08,440 --> 00:22:12,879 Speaker 1: there's an outbreak of diphtheria in Russia. I mean, like 377 00:22:12,920 --> 00:22:15,760 Speaker 1: tens of thousands of people fell ill with diphtheria, and 378 00:22:15,800 --> 00:22:18,600 Speaker 1: they were almost all adults. And they went back and 379 00:22:18,600 --> 00:22:21,480 Speaker 1: figured out the reason why this happened was because, um, 380 00:22:21,520 --> 00:22:24,840 Speaker 1: those adults hadn't been given a booster shot for their 381 00:22:24,840 --> 00:22:30,679 Speaker 1: diphtheria um inoculation and so so they're they're immune response. 382 00:22:30,720 --> 00:22:33,240 Speaker 1: They're antibodies that they built up when they were children 383 00:22:33,560 --> 00:22:38,520 Speaker 1: having been given this diphtheria vaccine had waned, and they 384 00:22:38,600 --> 00:22:41,480 Speaker 1: it waned enough that diphtheria was able to kind of 385 00:22:41,520 --> 00:22:44,360 Speaker 1: take over and and cause this outbreak. And so when 386 00:22:44,359 --> 00:22:46,480 Speaker 1: you look at it like that, that's almost a really 387 00:22:46,480 --> 00:22:52,600 Speaker 1: good analogy to herd immunity. It's like over time, the 388 00:22:52,600 --> 00:22:56,480 Speaker 1: the the that threshold can be can be can decline 389 00:22:56,600 --> 00:22:59,199 Speaker 1: so that the virus or the bacteria can get in 390 00:22:59,320 --> 00:23:01,600 Speaker 1: the same thing. The individual level, if you don't get 391 00:23:01,640 --> 00:23:04,880 Speaker 1: a booster shot if you need it. For some vaccines, 392 00:23:04,920 --> 00:23:07,480 Speaker 1: you don't need it. I think measles, moms, and rubella 393 00:23:07,600 --> 00:23:11,720 Speaker 1: are all considered UM to confer lifetime immunity if it 394 00:23:11,760 --> 00:23:14,120 Speaker 1: does work on you, and I think those are nine 395 00:23:14,359 --> 00:23:17,199 Speaker 1: seven percent effective. So for nine seven out of a 396 00:23:17,240 --> 00:23:20,679 Speaker 1: hundred people, when you get an mm ARE vaccine as 397 00:23:20,720 --> 00:23:22,800 Speaker 1: a kid, you don't need any kind of booster and 398 00:23:22,840 --> 00:23:25,720 Speaker 1: you're gonna be immune to it for life, right, which 399 00:23:25,760 --> 00:23:29,960 Speaker 1: is great. It is UM. That's the point of accedence. Yeah, 400 00:23:30,000 --> 00:23:31,520 Speaker 1: and this is where we need to dip our toe 401 00:23:31,560 --> 00:23:36,240 Speaker 1: into something UM. That's called vaccine hesitancy. That's that's what 402 00:23:36,400 --> 00:23:39,480 Speaker 1: the official name for it is UH. And this is 403 00:23:39,520 --> 00:23:43,120 Speaker 1: a situation we have UM. I'm not sure about other 404 00:23:43,160 --> 00:23:46,000 Speaker 1: countries because I didn't do a lot of research into that. 405 00:23:46,080 --> 00:23:48,920 Speaker 1: But here in the United States, especially certain parts of 406 00:23:48,920 --> 00:23:54,040 Speaker 1: the United States, there are vaccinine vaccine exemptions in place, 407 00:23:54,600 --> 00:24:00,520 Speaker 1: granted for philosophical purposes, religious purposes, personal reasons. UM. It 408 00:24:00,640 --> 00:24:04,360 Speaker 1: is important to point out here that personal reasons get 409 00:24:04,400 --> 00:24:07,800 Speaker 1: all the press. UM, like when you see articles about 410 00:24:07,840 --> 00:24:10,760 Speaker 1: anti vaxxer's as people that choose not to get their 411 00:24:10,840 --> 00:24:15,440 Speaker 1: child vaccinated for certain reasons. But the the largest percentage 412 00:24:15,440 --> 00:24:18,560 Speaker 1: of people who don't get vaccinated very sadly. UM. It 413 00:24:18,640 --> 00:24:22,960 Speaker 1: has to do with UH finances and poverty, right. I mean, 414 00:24:23,000 --> 00:24:26,360 Speaker 1: like it's it's if you want to vaccinate your kid, 415 00:24:26,520 --> 00:24:29,359 Speaker 1: but you can't because you don't have the money or 416 00:24:29,400 --> 00:24:32,080 Speaker 1: they're not available to you. I think kids in rural 417 00:24:32,119 --> 00:24:36,840 Speaker 1: areas have much lower vaccine rates than kids in urban areas. UM. 418 00:24:36,880 --> 00:24:39,360 Speaker 1: That is really sad, and I think that's something that 419 00:24:39,800 --> 00:24:44,679 Speaker 1: because it's such a public health success, UM, it should 420 00:24:44,720 --> 00:24:47,560 Speaker 1: be something that's much more widely available than anybody who 421 00:24:47,560 --> 00:24:51,200 Speaker 1: wants it. Yeah, here's some numbers on that. There was 422 00:24:51,240 --> 00:24:56,280 Speaker 1: a study by the CDC in that noted the percentage 423 00:24:56,280 --> 00:24:59,880 Speaker 1: of children without any vaccines had risen to about one 424 00:25:00,000 --> 00:25:02,640 Speaker 1: point three percent. And these are kids that were born 425 00:25:02,760 --> 00:25:06,440 Speaker 1: in the year two thousand fifteen, and then they compared 426 00:25:06,480 --> 00:25:09,240 Speaker 1: that with the two thousand one survey. They found it 427 00:25:09,280 --> 00:25:12,160 Speaker 1: was just point three percent of children between the ages 428 00:25:12,200 --> 00:25:16,000 Speaker 1: of nineteen to thirty five months. So basically they looked 429 00:25:16,040 --> 00:25:18,080 Speaker 1: at the numbers and they found that the children who 430 00:25:18,080 --> 00:25:21,320 Speaker 1: are uninsured or who live in rural areas like you said, 431 00:25:21,400 --> 00:25:26,040 Speaker 1: or maybe had Medicaid insurance. Seventeen point two percent of 432 00:25:26,040 --> 00:25:29,080 Speaker 1: the unvaccinated kids were uninsured compared to two point eight 433 00:25:29,119 --> 00:25:32,679 Speaker 1: percent of overall kids. There's a big deaf It is 434 00:25:32,880 --> 00:25:35,480 Speaker 1: a huge diff for sure, UM. And then there are, 435 00:25:35,520 --> 00:25:38,919 Speaker 1: like you said, there's parents who forego vaccinations, uh, for 436 00:25:39,040 --> 00:25:43,320 Speaker 1: personal reasons or religious reasons, UM, or philosophical reasons, although 437 00:25:43,320 --> 00:25:46,840 Speaker 1: I don't understand what the differences between philosophical and personal. Yeah, 438 00:25:46,880 --> 00:25:50,120 Speaker 1: I agree, UM, and I'd be interested to find that out. 439 00:25:50,160 --> 00:25:56,040 Speaker 1: But the people who don't vaccinate their kids for whatever reason, 440 00:25:56,840 --> 00:26:00,880 Speaker 1: who make a conscious decision not to are UM tend 441 00:26:00,880 --> 00:26:03,480 Speaker 1: to be viewed as freeloaders. And that's not just us 442 00:26:03,520 --> 00:26:06,399 Speaker 1: like throw in shade, that's like the term that that 443 00:26:06,560 --> 00:26:09,879 Speaker 1: is used as freeloaders. They're freeloading on the larger herd. 444 00:26:10,320 --> 00:26:15,520 Speaker 1: To UM, prevent from being exposed to this disease or 445 00:26:15,520 --> 00:26:21,360 Speaker 1: these diseases or viruses or bacteria, UM, because they're depending 446 00:26:21,400 --> 00:26:26,359 Speaker 1: on other people to immunize their kids through vaccinations instead. 447 00:26:27,680 --> 00:26:31,080 Speaker 1: That's right. Uh. And there's another weird phenomenon that's happened 448 00:26:31,080 --> 00:26:35,040 Speaker 1: here in the US that where a vaccine program is 449 00:26:35,119 --> 00:26:39,760 Speaker 1: so successful that generations will go by without any of 450 00:26:39,800 --> 00:26:43,240 Speaker 1: this disease. So you're not even familiar with it. So 451 00:26:43,840 --> 00:26:47,560 Speaker 1: it's sort of absurd in this way that it's been flipped. 452 00:26:48,160 --> 00:26:51,359 Speaker 1: But one of the reasons sometimes you will hear uh 453 00:26:51,400 --> 00:26:54,720 Speaker 1: to to not vaccinate. It's like, well, that old disease 454 00:26:54,760 --> 00:26:56,600 Speaker 1: that haven't you know that, we haven't seen that in 455 00:26:56,640 --> 00:26:59,720 Speaker 1: two hundred years, And I'm gonna put that vaccine in 456 00:26:59,760 --> 00:27:04,160 Speaker 1: Mike Kid and a cycle. Yeah, because the vaccine worked, right, 457 00:27:04,200 --> 00:27:07,040 Speaker 1: It's a victim of its own success. The vast vaccination 458 00:27:07,080 --> 00:27:09,320 Speaker 1: program is. And I think from what I can tell, 459 00:27:09,440 --> 00:27:14,359 Speaker 1: that's how UM public health officials typically explain uh anti 460 00:27:14,440 --> 00:27:19,240 Speaker 1: vaccine or declines in vaccine rates among people who consciously 461 00:27:19,320 --> 00:27:22,240 Speaker 1: choose not to that basically, they just haven't seen how 462 00:27:22,280 --> 00:27:25,440 Speaker 1: bad a disease is, Like you haven't seen what polio 463 00:27:25,560 --> 00:27:27,800 Speaker 1: can do. To somebody because you were born into a 464 00:27:27,840 --> 00:27:33,200 Speaker 1: world war. For all intents and purposes, polio just didn't exist, right, 465 00:27:33,359 --> 00:27:38,000 Speaker 1: And so you lose that incentive that somebody who is 466 00:27:38,080 --> 00:27:41,639 Speaker 1: aware of what polio can do, um the incentive that 467 00:27:41,640 --> 00:27:44,680 Speaker 1: that person has to vaccinate their kid. And then when 468 00:27:44,680 --> 00:27:49,359 Speaker 1: you couple that with um questions about a vaccine or 469 00:27:49,480 --> 00:27:52,880 Speaker 1: fears that there are some um negative side effects from 470 00:27:52,880 --> 00:27:56,960 Speaker 1: a vaccine, that disincentive or that lack of incentive becomes 471 00:27:56,960 --> 00:28:00,840 Speaker 1: a disincentive to get that. And so there's this ironic 472 00:28:00,920 --> 00:28:05,080 Speaker 1: circle that develops where those vaccination rates go down, we 473 00:28:05,320 --> 00:28:09,000 Speaker 1: dip below the herd immunity level, there's an outbreak of 474 00:28:09,040 --> 00:28:12,879 Speaker 1: that disease, and then the very people who lead to 475 00:28:12,960 --> 00:28:16,440 Speaker 1: that decline in vaccination levels point to that outbreak as 476 00:28:16,520 --> 00:28:20,679 Speaker 1: evidence that vaccines don't work or herd immunity doesn't work, 477 00:28:21,200 --> 00:28:24,000 Speaker 1: and it's it's um. It's hard to wrap your head around. 478 00:28:24,040 --> 00:28:26,120 Speaker 1: It is very hard to wrap your head around, especially 479 00:28:26,200 --> 00:28:30,320 Speaker 1: if you are fully on board the vaccine and UM 480 00:28:30,560 --> 00:28:33,960 Speaker 1: herd immunity through vaccine trains. It can be fairly galling, 481 00:28:34,080 --> 00:28:37,119 Speaker 1: I believe. Yeah. And there's a couple of things, A 482 00:28:37,119 --> 00:28:40,000 Speaker 1: couple of big challenges to herd immunity and whether or 483 00:28:40,040 --> 00:28:42,520 Speaker 1: not it can work today. And one of them is 484 00:28:42,600 --> 00:28:46,240 Speaker 1: that we can get on an airplane with our family 485 00:28:47,120 --> 00:28:50,000 Speaker 1: and we can fly great, great distances and get places 486 00:28:50,040 --> 00:28:53,240 Speaker 1: really fast and then come home again really fast. And 487 00:28:53,360 --> 00:28:57,240 Speaker 1: this happened in two thousand eight with the outbreak in 488 00:28:57,440 --> 00:29:00,000 Speaker 1: San Diego. That was a family that went to Switzerland 489 00:29:00,000 --> 00:29:04,280 Speaker 1: in um the this little boy picked up the virus 490 00:29:04,960 --> 00:29:07,360 Speaker 1: of the measles while he was in Switzerland. Such a 491 00:29:07,400 --> 00:29:14,160 Speaker 1: bad little boy he was. He was he he was unvaccinated, 492 00:29:14,520 --> 00:29:16,960 Speaker 1: He got sick. When he got home, he infected eleven 493 00:29:17,000 --> 00:29:19,960 Speaker 1: other people, including one who was an infant that was 494 00:29:19,960 --> 00:29:22,800 Speaker 1: too young to be vaccinated. Just if you were like 495 00:29:22,880 --> 00:29:28,240 Speaker 1: ambivalent about this through that that little detailing. Yeah, And 496 00:29:28,360 --> 00:29:30,200 Speaker 1: at first they were like, what is going on here 497 00:29:30,200 --> 00:29:34,360 Speaker 1: with this weird outbreak because we have a minimum threshold 498 00:29:34,360 --> 00:29:38,480 Speaker 1: here in San Diego against the measles for her community, 499 00:29:38,680 --> 00:29:42,320 Speaker 1: and in two thousand it was declared eliminated basically all 500 00:29:42,360 --> 00:29:44,760 Speaker 1: over the country. And so they started to kind of 501 00:29:44,760 --> 00:29:47,360 Speaker 1: poke around this case and they said, all right, San 502 00:29:47,360 --> 00:29:50,480 Speaker 1: Diego is doing great, but this kid actually goes to 503 00:29:50,480 --> 00:29:55,040 Speaker 1: a school and his localized social group is about seventeen 504 00:29:55,480 --> 00:29:59,360 Speaker 1: of them uh at this school don't vaccinate. So while 505 00:29:59,440 --> 00:30:02,920 Speaker 1: the city was doing fine, his little localized community had 506 00:30:02,920 --> 00:30:08,120 Speaker 1: a pretty high percentage of unvaccinated kids, and so that 507 00:30:08,200 --> 00:30:10,920 Speaker 1: allowed it to spread, right, It allowed it to spread. 508 00:30:11,240 --> 00:30:14,280 Speaker 1: Those kids became immunized, they became ill, but then they 509 00:30:14,320 --> 00:30:18,120 Speaker 1: became immunized to the measles naturally from being exposed to 510 00:30:18,120 --> 00:30:21,840 Speaker 1: it and having fallen ill um. But the big problem is, 511 00:30:21,960 --> 00:30:23,920 Speaker 1: in addition to the fact that it just kind of 512 00:30:24,040 --> 00:30:29,800 Speaker 1: ravaged this hyperlocal social group, there are other pockets within 513 00:30:29,840 --> 00:30:33,840 Speaker 1: the herd that probably bear a striking resemblance to that 514 00:30:34,000 --> 00:30:37,080 Speaker 1: social group. And those social groups come in contact with 515 00:30:37,080 --> 00:30:39,640 Speaker 1: the other social group that's been infected, you can have 516 00:30:39,720 --> 00:30:44,400 Speaker 1: an epidemic within the larger immunized herd, which you don't want. 517 00:30:44,680 --> 00:30:48,120 Speaker 1: You want those people to be protected. But the decline 518 00:30:48,160 --> 00:30:51,360 Speaker 1: in vaccine rates and the fact that we can travel, 519 00:30:51,440 --> 00:30:53,760 Speaker 1: like you were saying so easily, not only does it 520 00:30:53,800 --> 00:30:56,600 Speaker 1: mean that like a virus or bacteria can travel just 521 00:30:56,680 --> 00:31:00,719 Speaker 1: as fast on on board a human who's on a plane, um, 522 00:31:00,760 --> 00:31:05,840 Speaker 1: it also means that there's constant fluctuations to the percentage 523 00:31:06,120 --> 00:31:10,360 Speaker 1: that herd immunity threshold because of the influx and outflux 524 00:31:10,360 --> 00:31:14,440 Speaker 1: of people who are vaccinated or not vaccinated. Right, And 525 00:31:14,440 --> 00:31:17,960 Speaker 1: this is why those vaccination vaccination rates being high is 526 00:31:18,000 --> 00:31:22,400 Speaker 1: really important, um, because it's it's protecting everybody. Yes, you 527 00:31:22,440 --> 00:31:26,760 Speaker 1: want a large public buy in to the concept of vaccinations, 528 00:31:26,800 --> 00:31:29,640 Speaker 1: and when there is not a large public buying, then 529 00:31:29,760 --> 00:31:32,480 Speaker 1: your herd immunity is under threat and everybody who is 530 00:31:32,520 --> 00:31:38,520 Speaker 1: bought in is is um at risk. Because again you 531 00:31:38,600 --> 00:31:41,480 Speaker 1: might say, well, who cares if you if you've inoculated 532 00:31:41,520 --> 00:31:44,760 Speaker 1: your kids, if they're immunized against measles, what do you 533 00:31:44,800 --> 00:31:48,440 Speaker 1: care if somebody else's kid isn't because they have personal 534 00:31:48,520 --> 00:31:52,560 Speaker 1: reasons against it. Um, your kids find they're inoculated, don't 535 00:31:52,560 --> 00:31:55,600 Speaker 1: forget that. With the measles vaccine, I think it's like 536 00:31:56,400 --> 00:32:00,280 Speaker 1: pcent effective and that that means that if there's a 537 00:32:00,320 --> 00:32:03,760 Speaker 1: hundred hundred kids in a room and one of them 538 00:32:03,800 --> 00:32:07,160 Speaker 1: has full on contagious measles, which again is very contagious 539 00:32:07,240 --> 00:32:10,640 Speaker 1: like the mumps in its contagiousness, three of those kids 540 00:32:10,640 --> 00:32:15,000 Speaker 1: who have been vaccinated are possibly going to get the 541 00:32:15,080 --> 00:32:18,280 Speaker 1: measles from that kid even though they were vaccinated, because 542 00:32:18,320 --> 00:32:21,760 Speaker 1: their body just didn't form the right immune response or 543 00:32:21,880 --> 00:32:24,800 Speaker 1: enough of an immune response that they be protected if 544 00:32:24,840 --> 00:32:27,080 Speaker 1: they were exposed to that kid. So it is a 545 00:32:27,120 --> 00:32:31,440 Speaker 1: problem for even people who have been vaccinated against diseases 546 00:32:31,760 --> 00:32:34,640 Speaker 1: to have a decline and herd immunity. And then also, 547 00:32:34,720 --> 00:32:38,240 Speaker 1: don't forget the people who don't have uh an immune 548 00:32:38,240 --> 00:32:41,680 Speaker 1: system that can allow for them to be inoculated or vaccinated, 549 00:32:41,960 --> 00:32:46,120 Speaker 1: and the elderly who are just by virtue of being older, 550 00:32:46,640 --> 00:32:50,160 Speaker 1: more susceptible to a really hard about with whatever disease 551 00:32:50,160 --> 00:32:53,360 Speaker 1: it is they're being exposed to. Yeah, I've been running 552 00:32:53,400 --> 00:32:57,360 Speaker 1: up against that, that frustrating sort of circular um non 553 00:32:57,440 --> 00:33:01,200 Speaker 1: logic about COVID Night Team. I'm a member of a 554 00:33:01,200 --> 00:33:06,120 Speaker 1: Facebook page of a an area and more rural Georgia. 555 00:33:06,200 --> 00:33:08,560 Speaker 1: That's all I'll say. You could have just stopped at 556 00:33:08,600 --> 00:33:12,760 Speaker 1: a Facebook page. And there's been a lot of that 557 00:33:12,880 --> 00:33:17,600 Speaker 1: same sort of um circular logic of well, all these 558 00:33:17,640 --> 00:33:20,240 Speaker 1: models are turning out to be wrong. They weigh overstated 559 00:33:20,280 --> 00:33:23,400 Speaker 1: everything because look at the numbers falling. It's like that's 560 00:33:23,440 --> 00:33:27,240 Speaker 1: because we social distance and because we did all this 561 00:33:27,280 --> 00:33:30,880 Speaker 1: stuff and like it worked, that's how modeling works. Like 562 00:33:30,920 --> 00:33:35,160 Speaker 1: the initial numbers were really high because that was just 563 00:33:35,240 --> 00:33:38,040 Speaker 1: sort of the starting point, that was the input data 564 00:33:38,400 --> 00:33:39,920 Speaker 1: was here we are at the beginning, and this can 565 00:33:40,000 --> 00:33:43,840 Speaker 1: happen this way, and Americans got together by and large 566 00:33:43,960 --> 00:33:46,560 Speaker 1: at first at least and did the right thing, and 567 00:33:46,560 --> 00:33:49,880 Speaker 1: so those numbers went way down and it worked. And 568 00:33:49,920 --> 00:33:52,240 Speaker 1: then they're using that as proof of like we'll see 569 00:33:52,320 --> 00:33:56,360 Speaker 1: the modelings just off. They're just guessing. Yeah that a 570 00:33:56,480 --> 00:34:02,280 Speaker 1: mile away of course. Just yeah, yeah, everything is political, 571 00:34:02,440 --> 00:34:04,600 Speaker 1: huh yeah, And I'm just you know, I've tried to 572 00:34:05,400 --> 00:34:07,760 Speaker 1: I've tried to avoid it, but I have also commented 573 00:34:07,800 --> 00:34:11,680 Speaker 1: at times like modeling is not guessing. It is there. 574 00:34:11,800 --> 00:34:15,040 Speaker 1: There's real research and math that goes into it, and 575 00:34:15,040 --> 00:34:17,400 Speaker 1: and that math changes based on the input data. Like 576 00:34:17,480 --> 00:34:19,960 Speaker 1: in a month, there will probably be different numbers. And 577 00:34:20,000 --> 00:34:25,120 Speaker 1: it's not because they're just guessing and they're wrong, right right, Yeah, 578 00:34:25,280 --> 00:34:30,560 Speaker 1: it's um it's that distrust and expertise that has really 579 00:34:30,640 --> 00:34:34,359 Speaker 1: kind of wrecked things quite a bit. Yeah, all right, 580 00:34:34,640 --> 00:34:37,319 Speaker 1: let's talk about what's going on right now and how 581 00:34:37,360 --> 00:34:42,879 Speaker 1: this applies to our situation today with the novel coronavirus 582 00:34:42,960 --> 00:34:46,120 Speaker 1: COVID nineteen call it whatever you want, Well, wait a minute, 583 00:34:46,160 --> 00:34:48,920 Speaker 1: I think we should institute a tradition in this episode 584 00:34:48,920 --> 00:34:51,400 Speaker 1: where every time we're about to talk about COVID, we 585 00:34:51,560 --> 00:34:54,520 Speaker 1: make it a cliffhanger and take a break. Okay, all right, 586 00:34:54,560 --> 00:34:56,120 Speaker 1: we'll take a break and we'll talk about all that 587 00:34:56,200 --> 00:35:24,799 Speaker 1: right after this a shosh and shock. Alright, Chuck, thanks 588 00:35:24,840 --> 00:35:27,440 Speaker 1: for playing along with me. We're gonna have like fifty 589 00:35:28,280 --> 00:35:31,040 Speaker 1: ad breaks in here because we're gonna stop every time 590 00:35:31,120 --> 00:35:34,759 Speaker 1: right before we talk about COVID. Yeah. So, what we're 591 00:35:34,800 --> 00:35:38,440 Speaker 1: dealing with now in the most recent days, in a 592 00:35:38,480 --> 00:35:43,439 Speaker 1: couple of weeks, is a new sort of divide has emerged. Um. 593 00:35:43,480 --> 00:35:46,160 Speaker 1: Everyone got together at first, it seemed like and there 594 00:35:46,160 --> 00:35:49,439 Speaker 1: was a lot of unity for five minutes, and then 595 00:35:50,719 --> 00:35:53,520 Speaker 1: a dividing line has now formed. Um in the United 596 00:35:53,520 --> 00:35:55,319 Speaker 1: States and kind of in the world, depending on what 597 00:35:55,440 --> 00:35:58,160 Speaker 1: your view is on how to best handle this, and 598 00:35:58,400 --> 00:36:02,600 Speaker 1: the two sort of route are and we'll talk about 599 00:36:02,640 --> 00:36:05,879 Speaker 1: specific example examples of different countries and what they're doing. 600 00:36:05,920 --> 00:36:11,800 Speaker 1: But there's elimination and then there's herd immunity and vaccinations 601 00:36:12,080 --> 00:36:15,399 Speaker 1: and not by not pooping, you don't mean pooping. By elimination, 602 00:36:16,560 --> 00:36:19,440 Speaker 1: I mean getting rid of it, of the of the virus. 603 00:36:19,600 --> 00:36:22,960 Speaker 1: But not by pooping, no, not by pooping. But we're 604 00:36:23,000 --> 00:36:25,919 Speaker 1: talking about a few countries in particular. Everyone's talking about 605 00:36:25,920 --> 00:36:30,880 Speaker 1: Sweden right now because Sweden, compared to the rest of 606 00:36:30,920 --> 00:36:32,920 Speaker 1: the Nordic countries, the rest of Europe and most of 607 00:36:32,920 --> 00:36:35,680 Speaker 1: the rest of the world, was one country that was like, 608 00:36:35,719 --> 00:36:39,080 Speaker 1: you know what we are gonna say, if you feel sick, 609 00:36:39,120 --> 00:36:41,960 Speaker 1: stay at home. If you're at risk, maybe stay at home, 610 00:36:42,920 --> 00:36:46,920 Speaker 1: try and uh keep a safe distance from people. But 611 00:36:47,040 --> 00:36:50,400 Speaker 1: bars are open, restaurants are open. Um, no big concerts 612 00:36:50,440 --> 00:36:52,960 Speaker 1: or anything like that, and let's try and get that 613 00:36:53,080 --> 00:36:58,440 Speaker 1: herd immunity going instead of shutting everything down. Right. So 614 00:36:58,520 --> 00:37:04,120 Speaker 1: they're they're pursuing mixture of like social distancing guidelines, but 615 00:37:04,320 --> 00:37:08,960 Speaker 1: nothing that's being super enforced aside from you know, those gatherings, 616 00:37:08,960 --> 00:37:13,560 Speaker 1: like you said. But ultimately they're pursuing basically a strategy 617 00:37:13,560 --> 00:37:17,319 Speaker 1: of herd immunity while trying their best to keep the 618 00:37:17,440 --> 00:37:22,640 Speaker 1: curve flattened, right, And I think we're pushing this one 619 00:37:22,640 --> 00:37:24,520 Speaker 1: out sooner, So this will just be out like four 620 00:37:24,600 --> 00:37:27,480 Speaker 1: or five days from now, and all these numbers are 621 00:37:27,480 --> 00:37:29,719 Speaker 1: going to be changing. But the jury is kind of 622 00:37:29,719 --> 00:37:32,759 Speaker 1: still out on whether or not that's working in Sweden. UM, 623 00:37:32,800 --> 00:37:35,640 Speaker 1: as of a couple of days ago, they have a 624 00:37:35,680 --> 00:37:41,080 Speaker 1: far higher infection rate than their Nordic neighbors. UM not, 625 00:37:41,280 --> 00:37:43,800 Speaker 1: I mean it's a little lower than some other countries 626 00:37:43,840 --> 00:37:47,680 Speaker 1: to the south. So we just don't really know yet 627 00:37:47,760 --> 00:37:49,799 Speaker 1: because the jury is still out. We don't know what 628 00:37:50,320 --> 00:37:53,239 Speaker 1: our our percentage needs to be right now. Like I said, 629 00:37:53,239 --> 00:37:55,480 Speaker 1: it could be as high as eight percent, So we 630 00:37:55,560 --> 00:37:57,520 Speaker 1: just don't know. As these numbers come in over the 631 00:37:57,520 --> 00:38:00,760 Speaker 1: next month or two, it's gonna be really telling. UM. 632 00:38:00,800 --> 00:38:03,600 Speaker 1: I think kind of either way you slice it, it's 633 00:38:03,640 --> 00:38:06,720 Speaker 1: not right to say, all right, we'll look at Sweden 634 00:38:07,160 --> 00:38:09,719 Speaker 1: and if if it works there, that means it's gonna 635 00:38:09,719 --> 00:38:12,200 Speaker 1: work everywhere, because that's just not the case. No be 636 00:38:12,400 --> 00:38:15,479 Speaker 1: in Sweden has like consistently beat this drum. They're like, look, 637 00:38:15,560 --> 00:38:17,399 Speaker 1: we're not even sure this is gonna work for us, 638 00:38:17,400 --> 00:38:20,080 Speaker 1: but we're willing to try it. But we're far likelier 639 00:38:20,120 --> 00:38:23,359 Speaker 1: to be successful at something like this because our UM 640 00:38:23,600 --> 00:38:28,080 Speaker 1: population maybe is a little more collectivists than some other populations. 641 00:38:28,760 --> 00:38:31,919 Speaker 1: They're healthier, They are healthier, they have a big deal 642 00:38:32,080 --> 00:38:36,400 Speaker 1: a much stronger um and more responsive health care system. 643 00:38:36,560 --> 00:38:39,719 Speaker 1: They have a more homogeneous population don't forget, which may 644 00:38:39,760 --> 00:38:42,799 Speaker 1: mean that they could reach HERD immunity more quickly than 645 00:38:42,840 --> 00:38:46,279 Speaker 1: some other countries that have less homogeneous populations. Sweden is 646 00:38:46,280 --> 00:38:50,000 Speaker 1: more homogeneous. They also get this. They also they don't 647 00:38:50,040 --> 00:38:53,240 Speaker 1: have like huge mega grocery stores where there's a thousand 648 00:38:53,360 --> 00:38:56,360 Speaker 1: or undred people milling around all at the same time. 649 00:38:56,800 --> 00:39:01,440 Speaker 1: They have like smaller shops and markets serve like a 650 00:39:01,520 --> 00:39:04,759 Speaker 1: particular like corner in the neighborhood, and they have them 651 00:39:04,800 --> 00:39:07,720 Speaker 1: like every few corners, so there's not tons of people 652 00:39:07,760 --> 00:39:10,400 Speaker 1: in the market at every given at any given moment. 653 00:39:10,719 --> 00:39:15,120 Speaker 1: There's just a lot of differences between Swedish culture and 654 00:39:15,160 --> 00:39:19,480 Speaker 1: say American culture. That's that is giving the Swedes the 655 00:39:19,520 --> 00:39:22,640 Speaker 1: confidence to try this. But even still, there are people 656 00:39:22,640 --> 00:39:26,560 Speaker 1: in Sweden that are like, this is indefensibly reckless. We 657 00:39:26,640 --> 00:39:28,800 Speaker 1: can't do this, we can't try this is a stupid 658 00:39:29,080 --> 00:39:32,359 Speaker 1: and like you said, there are some early signs that 659 00:39:32,440 --> 00:39:37,320 Speaker 1: it is not going so well because compared to um Norway, Denmark, 660 00:39:37,400 --> 00:39:42,520 Speaker 1: and Finland, their death rate adjusted for um UH population 661 00:39:42,600 --> 00:39:45,520 Speaker 1: size is between three and six times the death rate 662 00:39:45,600 --> 00:39:50,520 Speaker 1: of those nations, and those nations tried elimination. Yeah, and 663 00:39:50,560 --> 00:39:53,000 Speaker 1: I saw that the UM. I don't. I don't think 664 00:39:53,000 --> 00:39:55,640 Speaker 1: it was like the I think it might have been 665 00:39:55,680 --> 00:39:58,520 Speaker 1: the head of whatever their CDC is said that they 666 00:39:58,520 --> 00:40:03,759 Speaker 1: were surprised by the death toll. Yeah, yeah, and not 667 00:40:03,840 --> 00:40:06,200 Speaker 1: in a way like they seem like really good people, 668 00:40:06,239 --> 00:40:08,520 Speaker 1: so it's not like, oh, we never thought of this, 669 00:40:08,640 --> 00:40:11,640 Speaker 1: but I think they were surprised. It is as high 670 00:40:11,719 --> 00:40:15,200 Speaker 1: as it's been right UM. And so Sweden is not 671 00:40:15,239 --> 00:40:17,760 Speaker 1: the only one trying this. India is trying it as well, 672 00:40:18,320 --> 00:40:20,759 Speaker 1: and they're doing something very similar to Sweden. They have 673 00:40:20,880 --> 00:40:23,680 Speaker 1: a lot of social distancing guidelines, but are also kind 674 00:40:23,719 --> 00:40:28,120 Speaker 1: of hoping for natural herd immunity to kick in UM. 675 00:40:28,360 --> 00:40:33,200 Speaker 1: And they don't have much of a choice there. They 676 00:40:33,239 --> 00:40:36,840 Speaker 1: have like point five five hospital beds, so a little 677 00:40:36,880 --> 00:40:41,240 Speaker 1: over half of a hospital bed per one thousand people 678 00:40:41,719 --> 00:40:46,040 Speaker 1: in the country, and forty four thousand ventilators UM. But 679 00:40:46,120 --> 00:40:49,720 Speaker 1: that both Sweden and India are taking a strategy of saying, 680 00:40:49,760 --> 00:40:53,239 Speaker 1: if you're older, if you're elderly, if you are in 681 00:40:53,280 --> 00:40:57,480 Speaker 1: this high risk group for suffering complications from COVID nineteen, 682 00:40:57,880 --> 00:41:00,920 Speaker 1: you stay home too, and we'll let the younger population 683 00:41:00,960 --> 00:41:03,440 Speaker 1: go out and get sick because they can handle it 684 00:41:03,480 --> 00:41:05,640 Speaker 1: better and maybe less of a strain on the health 685 00:41:05,640 --> 00:41:10,759 Speaker 1: care system. Um, and they'll be the immunized herd for 686 00:41:10,800 --> 00:41:13,080 Speaker 1: the rest of the population. I don't know if those 687 00:41:13,080 --> 00:41:15,759 Speaker 1: strategies are going to work or not, um, but that's 688 00:41:15,840 --> 00:41:19,200 Speaker 1: kind of like the mentality behind them. Yeah. And there 689 00:41:19,200 --> 00:41:22,960 Speaker 1: are other countries. I think in England they originally we're 690 00:41:22,960 --> 00:41:25,760 Speaker 1: going to kind of follow that model, and then everyone 691 00:41:25,880 --> 00:41:30,600 Speaker 1: said no way, bollocks to that, and so they have, 692 00:41:30,920 --> 00:41:34,479 Speaker 1: um got some stricter measures going. Belarus is the one 693 00:41:35,000 --> 00:41:38,239 Speaker 1: place that's really that. The president there, who's been in 694 00:41:38,320 --> 00:41:42,800 Speaker 1: office i think since, has called the stricter responses around 695 00:41:42,800 --> 00:41:45,880 Speaker 1: the world mass psychosis, and he's basically like, I mean 696 00:41:45,880 --> 00:41:50,600 Speaker 1: they're having a full on military parade this weekend and saying, 697 00:41:51,040 --> 00:41:54,440 Speaker 1: screw all this. Uh. And Belarus has one of Europe's 698 00:41:54,480 --> 00:41:58,280 Speaker 1: highest per capita infection rates. Yeah, it's like, have any 699 00:41:58,320 --> 00:42:05,400 Speaker 1: of you even seen there ownavirus and yourself I haven't. Yeah, jeez. 700 00:42:05,520 --> 00:42:07,160 Speaker 1: There was a guy on one of this that same 701 00:42:07,200 --> 00:42:10,760 Speaker 1: Facebook page that said I don't even know a single 702 00:42:10,800 --> 00:42:14,080 Speaker 1: person who's had it l O L. And I was like, well, 703 00:42:14,120 --> 00:42:16,480 Speaker 1: you're you're lucky, sir. You should be thankful for that, 704 00:42:16,920 --> 00:42:20,120 Speaker 1: and he's like, hmm, it's not luck could be something 705 00:42:20,160 --> 00:42:23,400 Speaker 1: else dot dot dot, and it's just like, I'm stepping 706 00:42:23,400 --> 00:42:27,479 Speaker 1: out of this immediately. Man, I don't know if I 707 00:42:27,480 --> 00:42:30,200 Speaker 1: I say hats off to you for being on that 708 00:42:30,239 --> 00:42:33,200 Speaker 1: Facebook group or just deeply pity you for being on 709 00:42:33,200 --> 00:42:35,960 Speaker 1: that Facebook group. Well I sort of have to be 710 00:42:35,960 --> 00:42:37,960 Speaker 1: because I have to keep up with some things. Uh. 711 00:42:38,000 --> 00:42:40,440 Speaker 1: This is a another part of Georgia where on a 712 00:42:40,480 --> 00:42:43,279 Speaker 1: little little tract of land. Oh gotch, So you need 713 00:42:43,320 --> 00:42:49,600 Speaker 1: to like nobody's squatting on it. Yeah, I'm the only squatter. So. 714 00:42:49,800 --> 00:42:54,080 Speaker 1: Um So, this whole herd immunity thing, there's herd immunity 715 00:42:54,120 --> 00:42:59,279 Speaker 1: itself has been controversial, uh since before the COVID nineteen pandemic. Right, 716 00:42:59,440 --> 00:43:04,000 Speaker 1: those same but who questioned vaccines also questioned the concept 717 00:43:04,080 --> 00:43:09,400 Speaker 1: of reaching herd immunity through vaccinations. There's like suspicion that, um, 718 00:43:09,880 --> 00:43:14,200 Speaker 1: you're artificially suppressing the vaccine and you're actually weakening the 719 00:43:14,239 --> 00:43:16,200 Speaker 1: immune system, and that it's going to set us up 720 00:43:16,239 --> 00:43:19,200 Speaker 1: for this horrible problem down the road. None of that 721 00:43:19,280 --> 00:43:25,040 Speaker 1: bears scrutiny under logic. Um, but today herd immunity has 722 00:43:25,120 --> 00:43:28,320 Speaker 1: kind of reached this controversial inflection point for a totally 723 00:43:28,320 --> 00:43:31,839 Speaker 1: different reason, and that the people who are saying, well, 724 00:43:31,920 --> 00:43:35,000 Speaker 1: we're going to opt for to try for her immunity 725 00:43:35,080 --> 00:43:37,759 Speaker 1: now rather than later so that we can get our 726 00:43:37,800 --> 00:43:40,879 Speaker 1: economy going again, what they're talking about is her community 727 00:43:40,920 --> 00:43:46,000 Speaker 1: without a vaccine. Big, big, big difference, huge difference, because 728 00:43:46,040 --> 00:43:49,600 Speaker 1: what they're talking about is basically reverting back to the 729 00:43:49,640 --> 00:43:52,400 Speaker 1: pre vaccine thing where it was just like, Okay, I 730 00:43:52,440 --> 00:43:54,440 Speaker 1: hope we get to herd immunity sooner than later, and 731 00:43:54,480 --> 00:43:56,800 Speaker 1: a lot of people are going to die along the way. 732 00:43:56,880 --> 00:43:59,360 Speaker 1: And that's one of the big flaws of this argument 733 00:43:59,560 --> 00:44:03,280 Speaker 1: of going for her immunity right now, which is there's 734 00:44:03,320 --> 00:44:06,080 Speaker 1: going to be a lot of people who die as 735 00:44:06,120 --> 00:44:10,640 Speaker 1: a result before we get to her immunity because we 736 00:44:10,680 --> 00:44:12,799 Speaker 1: don't have a vaccine there. We're going to have to 737 00:44:12,840 --> 00:44:17,640 Speaker 1: reach her community through just exposure to this virus, just 738 00:44:17,719 --> 00:44:20,000 Speaker 1: like in the old timey days. Yeah, I was about 739 00:44:20,000 --> 00:44:22,360 Speaker 1: to say, it's as if we were living in ancient 740 00:44:22,440 --> 00:44:27,879 Speaker 1: times and just sort of crossing our fingers. So lots 741 00:44:27,920 --> 00:44:31,560 Speaker 1: of death is a big flaw against it. Um If 742 00:44:31,640 --> 00:44:35,880 Speaker 1: if the reproduction number for stars Cove two is three, 743 00:44:37,120 --> 00:44:40,560 Speaker 1: that's confusing. But if it has, If if COVID nineteen 744 00:44:40,600 --> 00:44:44,400 Speaker 1: has a reproduction number of three, let's say um, and 745 00:44:44,440 --> 00:44:46,840 Speaker 1: that that means that the herd immunity threshold is about 746 00:44:46,880 --> 00:44:49,560 Speaker 1: se That's about the high end that anybody's saying is 747 00:44:49,840 --> 00:44:55,120 Speaker 1: seventy should stop the virus from spreading anymore. Right, So 748 00:44:55,280 --> 00:44:57,960 Speaker 1: if that's the case, then that means seventy of a 749 00:44:58,040 --> 00:45:02,920 Speaker 1: population would be sick. And I think a half to 750 00:45:03,080 --> 00:45:05,960 Speaker 1: one percent of a fatality rate would mean that of 751 00:45:06,040 --> 00:45:10,320 Speaker 1: the larger population, point three five to point seven percent 752 00:45:10,680 --> 00:45:14,239 Speaker 1: of the population will die. So if you know that, 753 00:45:15,000 --> 00:45:17,239 Speaker 1: and you can take just the populations of some of 754 00:45:17,280 --> 00:45:20,880 Speaker 1: these countries that are trying this and say, well, before 755 00:45:20,880 --> 00:45:24,759 Speaker 1: you reach her community, um Sweden, out of your population 756 00:45:24,800 --> 00:45:27,959 Speaker 1: of ten point to five million people, about thirty six 757 00:45:28,000 --> 00:45:31,960 Speaker 1: thousand to seventy two thousand are going to die along 758 00:45:32,000 --> 00:45:35,160 Speaker 1: the way. Statistically speaking, that's the number that you can 759 00:45:35,200 --> 00:45:38,960 Speaker 1: bet on, Yeah, between one point to five and about 760 00:45:39,000 --> 00:45:40,920 Speaker 1: two and a half a million in the US. And 761 00:45:41,880 --> 00:45:45,000 Speaker 1: if you're going to look at the world population, we're 762 00:45:45,040 --> 00:45:48,239 Speaker 1: talking numbers higher than the Spanish flu twenty seven to 763 00:45:48,320 --> 00:45:52,799 Speaker 1: about fifty four million people dead. And that's if you know, 764 00:45:52,840 --> 00:45:54,879 Speaker 1: we're not saying like that's gonna happen. We're saying that's 765 00:45:54,880 --> 00:45:57,680 Speaker 1: if the whole world took the approach of just all right, 766 00:45:57,800 --> 00:46:01,160 Speaker 1: let's just see how we do, you know, right, And 767 00:46:01,160 --> 00:46:07,680 Speaker 1: and I mean like this, that's we're a virgin population humanity, 768 00:46:07,719 --> 00:46:10,239 Speaker 1: not just the US, not just Canada, not just the UK, 769 00:46:10,440 --> 00:46:14,719 Speaker 1: not just Sweden. The world is a virgin population to 770 00:46:14,800 --> 00:46:18,600 Speaker 1: this virus because it's a novel coronavirus. We've never no 771 00:46:18,719 --> 00:46:21,880 Speaker 1: one on Earth has ever been exposed to this particular 772 00:46:21,960 --> 00:46:25,160 Speaker 1: virus before, so there isn't any pre built in immunity 773 00:46:25,360 --> 00:46:27,520 Speaker 1: like there would be if it makes another round a 774 00:46:27,600 --> 00:46:31,360 Speaker 1: year from now, right, So it just burns. Viruses and 775 00:46:31,400 --> 00:46:35,080 Speaker 1: bacteria burn their way through populations like that. So you 776 00:46:35,120 --> 00:46:39,040 Speaker 1: can imagine it would spread, uh, pretty effectively. And if 777 00:46:39,040 --> 00:46:41,440 Speaker 1: the fatality rate really is a half to one percent, 778 00:46:41,680 --> 00:46:44,960 Speaker 1: those numbers could be pretty real depending on what what 779 00:46:45,040 --> 00:46:47,560 Speaker 1: measures we take to mitigate those, Like you were saying, 780 00:46:47,719 --> 00:46:51,240 Speaker 1: so death that's a big, big problem, um. And also 781 00:46:51,320 --> 00:46:55,120 Speaker 1: along the way, we would be doing the opposite of 782 00:46:55,160 --> 00:46:57,960 Speaker 1: flattening the curve by just letting people go out and 783 00:46:58,000 --> 00:47:01,160 Speaker 1: getting sick to get things over with. Yeah. I mean, 784 00:47:01,160 --> 00:47:03,600 Speaker 1: we we've worked so hard to flatten the curve and 785 00:47:03,760 --> 00:47:07,440 Speaker 1: it worked in most of the most of the United States, 786 00:47:07,520 --> 00:47:11,280 Speaker 1: except you know, these weird outbreaks in in smaller towns 787 00:47:11,320 --> 00:47:13,920 Speaker 1: that didn't have enough beds and then laters and that's 788 00:47:13,920 --> 00:47:16,480 Speaker 1: all been really really sad to see happen. But by 789 00:47:16,560 --> 00:47:18,240 Speaker 1: and large, we did the right thing for a while 790 00:47:18,280 --> 00:47:21,120 Speaker 1: and it flattened the curve pretty well. But this would 791 00:47:21,120 --> 00:47:23,880 Speaker 1: fatten that curve right back up. Uh, and we'd be 792 00:47:23,920 --> 00:47:27,799 Speaker 1: in that same like in a worse situation than we 793 00:47:27,800 --> 00:47:31,960 Speaker 1: were going in, right. So, um, that's another big one. 794 00:47:32,000 --> 00:47:35,920 Speaker 1: And then also took reinfection is another huge flaw in this. 795 00:47:36,480 --> 00:47:42,880 Speaker 1: We don't know if stars cove two, which causes COVID nineteen, um, 796 00:47:42,920 --> 00:47:47,120 Speaker 1: how fast it's mutating. If it's like other coronaviruses or 797 00:47:47,120 --> 00:47:50,439 Speaker 1: other flu viruses, it probably has a lot of what's 798 00:47:50,440 --> 00:47:54,400 Speaker 1: called antigenic drift, where it mutates really rapidly and creates 799 00:47:54,400 --> 00:47:58,239 Speaker 1: new strains that the antibodies that have built up this 800 00:47:58,320 --> 00:48:03,200 Speaker 1: immune defense against one variety are useless to fight this 801 00:48:03,239 --> 00:48:07,360 Speaker 1: new variety. Right. Yeah, some diseases don't do that, like polio. 802 00:48:07,800 --> 00:48:11,279 Speaker 1: The reason our polio vaccine has been so successful is 803 00:48:11,320 --> 00:48:13,640 Speaker 1: because it doesn't mutate very much, it doesn't call it, 804 00:48:13,719 --> 00:48:17,479 Speaker 1: it doesn't create new strains. With coronavirus is they tend 805 00:48:17,480 --> 00:48:19,520 Speaker 1: to do that a lot, so there's a real chance 806 00:48:19,719 --> 00:48:22,920 Speaker 1: for reinfection. So this herd immunity will just be like 807 00:48:22,960 --> 00:48:25,440 Speaker 1: this ongoing thing until we can come up with the 808 00:48:25,560 --> 00:48:30,240 Speaker 1: viable vaccine that can that can protect us from basically 809 00:48:30,760 --> 00:48:36,400 Speaker 1: any mutated variety of this coronavirus. That's right, an antigenic drift. 810 00:48:37,080 --> 00:48:41,200 Speaker 1: Do I need to say it? No? You don't, great? Great? 811 00:48:43,239 --> 00:48:47,959 Speaker 1: Oh yeah, Chuck, I think he's for sure that that 812 00:48:48,440 --> 00:48:52,040 Speaker 1: muted trumpet thing that they got going on. What's that 813 00:48:52,120 --> 00:48:54,560 Speaker 1: thing called on the trumpet that they make that sound with. 814 00:48:55,480 --> 00:49:01,600 Speaker 1: Oh yeah, the plunger plunger head muffler, the thing. I 815 00:49:01,600 --> 00:49:06,000 Speaker 1: don't know. Yeah, you're on the trolley. So. Uh. The 816 00:49:06,040 --> 00:49:08,680 Speaker 1: other thing that we need to consider, and that is 817 00:49:08,800 --> 00:49:10,680 Speaker 1: the other sort of way that you can go about 818 00:49:10,719 --> 00:49:15,680 Speaker 1: this is elimination. Elimination that we were talking about, and 819 00:49:16,280 --> 00:49:19,000 Speaker 1: not pooping, and that is the opposite tactic, and that's 820 00:49:19,000 --> 00:49:21,560 Speaker 1: what most of the world has done, including the u S, 821 00:49:21,600 --> 00:49:25,560 Speaker 1: which is self quarantining, isolating, trying to contain the virus, 822 00:49:26,360 --> 00:49:31,319 Speaker 1: closing borders, mass gloves, all that stuff. Um, we have 823 00:49:31,360 --> 00:49:34,360 Speaker 1: flattened the curve for the most part. Other countries have 824 00:49:34,560 --> 00:49:37,719 Speaker 1: come close to elimination. New Zealand is getting a lot 825 00:49:37,719 --> 00:49:40,759 Speaker 1: of press because they and you know, they got a 826 00:49:40,800 --> 00:49:43,000 Speaker 1: lot of Again, you can't say, like, well, the same 827 00:49:43,040 --> 00:49:45,200 Speaker 1: thing could happen here in the US because New Zealand 828 00:49:45,239 --> 00:49:48,719 Speaker 1: is a very isolated place and it's a smaller population 829 00:49:48,840 --> 00:49:52,680 Speaker 1: and they have super smart elected officials and smart people 830 00:49:52,719 --> 00:49:58,359 Speaker 1: who listen to those elected officials. Good to get no, man, 831 00:49:58,960 --> 00:50:01,600 Speaker 1: someone come at me news. England's Prime minister is amazing. 832 00:50:01,719 --> 00:50:04,360 Speaker 1: She's she's like one of the best. Yeah. I remember 833 00:50:04,360 --> 00:50:06,560 Speaker 1: when we were there. Um, we got a cabra, do 834 00:50:06,600 --> 00:50:08,799 Speaker 1: you me? And I did to the airport and this 835 00:50:09,080 --> 00:50:11,000 Speaker 1: this guy, I think it was an immigrant from Sri 836 00:50:11,080 --> 00:50:14,520 Speaker 1: Lanka and he just could not stop boasting about how 837 00:50:14,560 --> 00:50:18,640 Speaker 1: great the New Zealand government was, about how taking care 838 00:50:18,719 --> 00:50:21,480 Speaker 1: of their population was, how like how much of a 839 00:50:21,520 --> 00:50:24,320 Speaker 1: sense of community the whole country had, and it was 840 00:50:24,400 --> 00:50:29,399 Speaker 1: just really refreshing to experience. Yeah it is, Uh, maybe 841 00:50:29,440 --> 00:50:32,719 Speaker 1: we should move there anyway. So the thing about New Zealand, Yeah, 842 00:50:32,760 --> 00:50:34,879 Speaker 1: I'm sure there's some people listening like yeah, why don't 843 00:50:34,880 --> 00:50:37,480 Speaker 1: you move there if you love it so much? And 844 00:50:37,520 --> 00:50:40,200 Speaker 1: there's there's also Kiwis that are going come on over, 845 00:50:40,320 --> 00:50:43,120 Speaker 1: We'd love to have you. And then there's also probably 846 00:50:43,160 --> 00:50:46,560 Speaker 1: some there like please don't. We've had enough of you too. 847 00:50:47,239 --> 00:50:50,239 Speaker 1: So why it worked there though, was because, like I said, 848 00:50:50,280 --> 00:50:53,520 Speaker 1: they have you have to have everyone on board, and 849 00:50:53,560 --> 00:50:56,680 Speaker 1: it seemed like most everyone on board or got on 850 00:50:56,719 --> 00:50:59,000 Speaker 1: board in New Zealand, and that's just not happened here. 851 00:50:59,239 --> 00:51:01,480 Speaker 1: So yeah, and I mean, it really has worked for 852 00:51:01,480 --> 00:51:06,480 Speaker 1: New Zealand, but they've taken serious restrictions, like you you 853 00:51:06,560 --> 00:51:10,480 Speaker 1: can't fly if you want to domestically, they shut down 854 00:51:10,480 --> 00:51:12,760 Speaker 1: their reports. If you want to fly to New Zealand, 855 00:51:13,000 --> 00:51:15,359 Speaker 1: t s for you, you're not gonna get anywhere near 856 00:51:15,360 --> 00:51:17,399 Speaker 1: the country. But in addition that, if you're a New 857 00:51:17,480 --> 00:51:21,120 Speaker 1: Zealand citizen, you can't fly from one place to another 858 00:51:21,160 --> 00:51:22,960 Speaker 1: if you want to just for the heck of it. Right, 859 00:51:23,320 --> 00:51:27,200 Speaker 1: There's so they've really insted instituted some draconian measures, but 860 00:51:27,320 --> 00:51:30,000 Speaker 1: it seems to have worked. Like there was a report 861 00:51:30,040 --> 00:51:32,520 Speaker 1: that came out two days ago on May fourth, that 862 00:51:32,640 --> 00:51:37,160 Speaker 1: says that the models originally used to project how many cases. 863 00:51:37,200 --> 00:51:39,200 Speaker 1: New Zealand was going to have said that they were 864 00:51:39,239 --> 00:51:41,520 Speaker 1: going to get something like a thousand cases a day 865 00:51:41,640 --> 00:51:45,399 Speaker 1: if they did nothing like no lockdown measures. All they've 866 00:51:45,400 --> 00:51:49,960 Speaker 1: had since March is fourteen hundred and eighty seven cases, 867 00:51:50,480 --> 00:51:54,799 Speaker 1: not a thousand a day, seven cases total, and they've 868 00:51:54,800 --> 00:51:58,360 Speaker 1: only had twenty deaths. So it seems like elimination can work. 869 00:51:58,719 --> 00:52:01,040 Speaker 1: And for that reason, and a lot of people are 870 00:52:01,160 --> 00:52:02,879 Speaker 1: a lot of countries have said this is what we're 871 00:52:02,880 --> 00:52:06,839 Speaker 1: gonna try, and elimination just amounts to hiding out from 872 00:52:06,880 --> 00:52:10,480 Speaker 1: the virus until a vaccine can be developed. The problem 873 00:52:10,560 --> 00:52:14,600 Speaker 1: is there are serious flaws to that too, depending on 874 00:52:14,960 --> 00:52:17,920 Speaker 1: what kind of what kind of government and culture that 875 00:52:18,000 --> 00:52:21,040 Speaker 1: you have. But even without that, depending on that, it 876 00:52:21,120 --> 00:52:27,400 Speaker 1: requires that everybody act basically perfectly and avoid everybody else 877 00:52:28,080 --> 00:52:31,640 Speaker 1: and give up your job, give up your economy and 878 00:52:31,800 --> 00:52:34,279 Speaker 1: wait until somebody comes up with a vaccine. And that 879 00:52:34,320 --> 00:52:39,400 Speaker 1: can be a really pricey, costly measure. Yeah, which is 880 00:52:39,440 --> 00:52:41,640 Speaker 1: why a lot of people are like this, this we 881 00:52:41,719 --> 00:52:44,640 Speaker 1: got to find some other way, Yeah, And they've looked 882 00:52:44,680 --> 00:52:47,040 Speaker 1: at um there are like ways you can look at 883 00:52:47,040 --> 00:52:49,120 Speaker 1: the countries and decide whether or not people are going 884 00:52:49,160 --> 00:52:54,280 Speaker 1: to comply or not. Um, there was uh some cultural data. 885 00:52:54,600 --> 00:52:59,719 Speaker 1: There was a company called half Steata Insights, and they 886 00:52:59,719 --> 00:53:04,319 Speaker 1: look it things like individualism of a population, basically like 887 00:53:04,400 --> 00:53:06,680 Speaker 1: whether or not people are gonna all go along or 888 00:53:06,680 --> 00:53:09,840 Speaker 1: if people are like heck no, man, I want my freedoms. 889 00:53:10,080 --> 00:53:13,279 Speaker 1: I'm an individual, I'm an American and you can't tell 890 00:53:13,280 --> 00:53:16,239 Speaker 1: me what to do, right. And you might not be 891 00:53:16,320 --> 00:53:19,120 Speaker 1: surprised to learn that in Sweden, Uh they have a 892 00:53:19,239 --> 00:53:24,240 Speaker 1: rank of seventy one out of one hundred as on individualism. 893 00:53:24,680 --> 00:53:27,000 Speaker 1: Uh the U scores ninety one out of a hundred, 894 00:53:27,480 --> 00:53:32,640 Speaker 1: so basically out of a hundred would be uh difficult 895 00:53:32,680 --> 00:53:35,960 Speaker 1: to maintain. You know, these kind of restrictions for too long. 896 00:53:36,640 --> 00:53:39,120 Speaker 1: I mean, if you look at it like that, it's remarkable, 897 00:53:39,239 --> 00:53:44,800 Speaker 1: how it's remarkable, in heartening, how much people have given 898 00:53:44,880 --> 00:53:48,040 Speaker 1: up individual liberties for the greater good in this pandemic 899 00:53:48,040 --> 00:53:50,520 Speaker 1: in the United States. Then, like I hadn't looked at 900 00:53:50,520 --> 00:53:53,040 Speaker 1: it that way. I just kind of saw like one 901 00:53:53,120 --> 00:53:56,080 Speaker 1: and thought, okay, you know that's that's that's a that's 902 00:53:56,120 --> 00:53:58,719 Speaker 1: a high score. There's a lot of individualism in the 903 00:53:58,800 --> 00:54:02,080 Speaker 1: United States. We gotta into visual streak like nobody's business, right, 904 00:54:02,600 --> 00:54:04,440 Speaker 1: But if you look at it almost like it's a 905 00:54:04,560 --> 00:54:08,160 Speaker 1: it's a percentage of the population that will listen in 906 00:54:08,320 --> 00:54:10,520 Speaker 1: situations like this, then it really does kind of go 907 00:54:10,560 --> 00:54:13,280 Speaker 1: to show you how how much of a sacrifice people 908 00:54:13,280 --> 00:54:15,279 Speaker 1: have made, not just Americans. I don't want to just 909 00:54:15,320 --> 00:54:17,600 Speaker 1: say it like that, Like if you're in a collective 910 00:54:17,600 --> 00:54:21,879 Speaker 1: of society, you're still sacrificing for the greater good. It's 911 00:54:21,920 --> 00:54:25,719 Speaker 1: just possibly a little more culturally ingrained in you that 912 00:54:25,800 --> 00:54:28,680 Speaker 1: this is the thing to do. But either way, the 913 00:54:28,719 --> 00:54:33,000 Speaker 1: idea of people people sacrificing for others is is it's heartening. 914 00:54:33,360 --> 00:54:36,440 Speaker 1: The problem is is people can only sacrifice for so 915 00:54:36,520 --> 00:54:42,719 Speaker 1: long until you have just massive economic drawbacks. And and 916 00:54:43,480 --> 00:54:46,959 Speaker 1: that's the thing. So if you follow the forced herd 917 00:54:47,000 --> 00:54:52,120 Speaker 1: immunity natural herd immunity strategy towards COVID nineteen, you will 918 00:54:52,680 --> 00:54:55,239 Speaker 1: it will result in a lot of deaths. If you 919 00:54:55,320 --> 00:55:00,080 Speaker 1: follow the elimination strategy, it results in a trem in 920 00:55:00,080 --> 00:55:02,839 Speaker 1: this amount of economic hardship. And it's easy to say, 921 00:55:03,320 --> 00:55:07,480 Speaker 1: chuck like, well, lives lost tops economic hardship any day 922 00:55:07,480 --> 00:55:10,879 Speaker 1: of the week, And ultimately, yes it does. But it's 923 00:55:11,440 --> 00:55:19,040 Speaker 1: you really should not um understate the toll in human 924 00:55:19,080 --> 00:55:23,200 Speaker 1: misery of economic hardships and how bad this has gotten 925 00:55:23,239 --> 00:55:27,399 Speaker 1: for some people and how quickly. Yeah, And the other 926 00:55:27,440 --> 00:55:29,839 Speaker 1: thing I'll say too, is one of the arguments I've 927 00:55:29,880 --> 00:55:32,200 Speaker 1: heard is that, you know, there are going to be 928 00:55:32,239 --> 00:55:35,680 Speaker 1: so many deaths from people who are who are depressed 929 00:55:35,760 --> 00:55:39,960 Speaker 1: because they can't go out, and people dying by suicide 930 00:55:40,000 --> 00:55:42,080 Speaker 1: and stuff like that, which you know, I don't want 931 00:55:42,080 --> 00:55:44,120 Speaker 1: to minimize that because that that for sure has an 932 00:55:44,160 --> 00:55:47,600 Speaker 1: impact on people. But I saw a tweet from a 933 00:55:47,600 --> 00:55:50,680 Speaker 1: guy that was talking about can we just stop pretending 934 00:55:50,719 --> 00:55:54,000 Speaker 1: that our former world of like working fifty hours a 935 00:55:54,000 --> 00:55:58,160 Speaker 1: week and commuting in a stressful environment and hectic crowds 936 00:55:58,200 --> 00:56:02,040 Speaker 1: and mask consu umerism and pollution and everything else was 937 00:56:02,080 --> 00:56:05,960 Speaker 1: like a mental health utopia. So it's you know, you've 938 00:56:05,960 --> 00:56:07,719 Speaker 1: got to kind of look at the big picture and 939 00:56:07,760 --> 00:56:10,960 Speaker 1: not just pick and choose what you're going to highlight 940 00:56:11,080 --> 00:56:13,480 Speaker 1: because it fits your narrative. You know. Yeah, I think 941 00:56:13,520 --> 00:56:17,080 Speaker 1: one of the like the few good outcomes so far 942 00:56:17,160 --> 00:56:19,759 Speaker 1: of this has been like a huge down shift in 943 00:56:20,600 --> 00:56:26,719 Speaker 1: that um manic productivity that drives most Americans, you know. Yeah, 944 00:56:26,840 --> 00:56:28,600 Speaker 1: And you know, here's The thing is, we don't know. 945 00:56:29,600 --> 00:56:31,319 Speaker 1: Everything is so new. We're not gonna sit here and 946 00:56:31,360 --> 00:56:34,960 Speaker 1: pretend like there is only one right way, like, we 947 00:56:35,000 --> 00:56:37,360 Speaker 1: don't know. So there's so much that we don't know 948 00:56:37,400 --> 00:56:40,319 Speaker 1: about this is we don't know the exact right path 949 00:56:40,400 --> 00:56:44,120 Speaker 1: forward yet as a population, and the medical community doesn't 950 00:56:44,120 --> 00:56:46,840 Speaker 1: know the exact right path forward. We're all trying to 951 00:56:46,840 --> 00:56:50,600 Speaker 1: figure this out in real time and build the road 952 00:56:50,640 --> 00:56:53,120 Speaker 1: as we're driving on it or whatever that expression is. 953 00:56:54,520 --> 00:56:58,600 Speaker 1: And you know, I have my money on uh, staying 954 00:56:58,600 --> 00:57:02,440 Speaker 1: at home, slowing this thing down and elimination. Other people 955 00:57:02,480 --> 00:57:05,200 Speaker 1: might feel a different way, But it seems like that 956 00:57:05,239 --> 00:57:09,040 Speaker 1: way is working better. Yeah it is. But again, if 957 00:57:09,080 --> 00:57:12,279 Speaker 1: you it's still early and the data is still coming in. 958 00:57:12,320 --> 00:57:14,960 Speaker 1: There was a report this week of a hundred New 959 00:57:15,040 --> 00:57:17,720 Speaker 1: York hospitals. They found that six or six percent of 960 00:57:17,760 --> 00:57:20,400 Speaker 1: new cases where among people who had stayed at home 961 00:57:20,440 --> 00:57:25,040 Speaker 1: and mostly followed the elimination strategy. So this one guy, 962 00:57:25,160 --> 00:57:27,880 Speaker 1: this doctor who wrote an article that I read, Dr 963 00:57:28,200 --> 00:57:32,520 Speaker 1: Stephen Phillips. He said, look, man, like, in addition to 964 00:57:32,560 --> 00:57:34,520 Speaker 1: all the stuff that we need to be doing to 965 00:57:34,680 --> 00:57:39,440 Speaker 1: handle this pandemic, let's also create like a really robust 966 00:57:39,520 --> 00:57:44,840 Speaker 1: data sharing um arrangement, so that we can look back 967 00:57:45,160 --> 00:57:47,960 Speaker 1: a year or a few years from now and study 968 00:57:48,000 --> 00:57:51,600 Speaker 1: this and say, oh, actually, these countries followed elimination mixed 969 00:57:51,600 --> 00:57:56,080 Speaker 1: with the social distancing guidelines, or they followed herd uh 970 00:57:56,120 --> 00:57:59,520 Speaker 1: immunity pursuit um and they actually came out on top. 971 00:57:59,760 --> 00:58:02,240 Speaker 1: So that we will know the next time which one 972 00:58:02,360 --> 00:58:06,280 Speaker 1: actually does work. Taking everything into account the cost in lives, 973 00:58:06,280 --> 00:58:09,480 Speaker 1: the economic cost, the cost and personal liberty, and find 974 00:58:09,560 --> 00:58:12,280 Speaker 1: the best way forward. And it probably won't be a 975 00:58:12,360 --> 00:58:16,400 Speaker 1: panacea where everything works like one thing works for every country, 976 00:58:16,600 --> 00:58:20,640 Speaker 1: but we'll have a pretty good model hopefully that can 977 00:58:20,680 --> 00:58:25,240 Speaker 1: be adjusted to suit the individual country that's adopting it. Hopefully. 978 00:58:25,520 --> 00:58:27,680 Speaker 1: That's if we can get past all of the arguing 979 00:58:27,960 --> 00:58:32,760 Speaker 1: over whether this is even real or not. Yeah, and 980 00:58:32,800 --> 00:58:35,960 Speaker 1: I know it's hard right now, but I think that 981 00:58:36,040 --> 00:58:38,440 Speaker 1: the most dangerous thing right now is to have the 982 00:58:38,480 --> 00:58:42,040 Speaker 1: mindset of, well, you know what, I'm pretty kg and 983 00:58:42,040 --> 00:58:45,200 Speaker 1: the weather is nice, and I don't know anyone personally 984 00:58:45,200 --> 00:58:47,320 Speaker 1: who's gotten it, so I'm just sort of going to 985 00:58:47,440 --> 00:58:51,800 Speaker 1: ease back into normality here. I think that's that's when 986 00:58:52,440 --> 00:58:56,880 Speaker 1: the second wave comes and things get worse and it's tough, uh, 987 00:58:56,880 --> 00:59:00,360 Speaker 1: and everyone is anti and KG myself include did you 988 00:59:00,360 --> 00:59:03,680 Speaker 1: know I find myself wanting to do things. Um, and 989 00:59:03,720 --> 00:59:07,400 Speaker 1: it's tough on on kids especially, But I think it's 990 00:59:07,440 --> 00:59:10,720 Speaker 1: more important now than ever to keep up what's what 991 00:59:10,720 --> 00:59:14,200 Speaker 1: we're doing. Yeah, we haven't just magically wished the pandemic away. 992 00:59:14,280 --> 00:59:18,520 Speaker 1: It didn't work. No, and lovely weather. Um, you know 993 00:59:18,880 --> 00:59:21,720 Speaker 1: to take your walks, get outside, do it safely, but 994 00:59:21,840 --> 00:59:23,680 Speaker 1: that it is not a reason to be like, well 995 00:59:24,240 --> 00:59:26,560 Speaker 1: that's old news. Now we can just go back to normal, 996 00:59:26,880 --> 00:59:30,160 Speaker 1: right right. I saw a post to button it up. 997 00:59:30,160 --> 00:59:32,520 Speaker 1: I'm sorry we keep going back back and forth on this, 998 00:59:32,600 --> 00:59:35,600 Speaker 1: but I saw a post that said, um, easing of 999 00:59:36,440 --> 00:59:39,440 Speaker 1: lockdown doesn't mean that the pandemic has gone away. It 1000 00:59:39,480 --> 00:59:41,520 Speaker 1: means that they have a hospital bed for you now, 1001 00:59:42,080 --> 00:59:46,240 Speaker 1: right exactly? You got anything else? I got nothing else? Man? 1002 00:59:46,400 --> 00:59:48,960 Speaker 1: All right, Well that's it for her community. Hopefully you 1003 00:59:48,960 --> 00:59:52,160 Speaker 1: guys learned something I definitely did from researching all this, 1004 00:59:52,480 --> 00:59:55,280 Speaker 1: and we hope everyone out there is staying safe, insane 1005 00:59:55,760 --> 00:59:59,720 Speaker 1: and uh, hanging in there. That's right. Uh. Since I 1006 00:59:59,720 --> 01:00:02,439 Speaker 1: said hanging in there, it's time chuck for listener mail. 1007 01:00:05,000 --> 01:00:08,480 Speaker 1: I'm gonna call this thanks from England and a little 1008 01:00:08,520 --> 01:00:11,400 Speaker 1: shout out. Hey, guys, I wanted to say thank you, 1009 01:00:12,560 --> 01:00:15,160 Speaker 1: thank you for your ongoing efforts with Stuff you Should Know. 1010 01:00:15,200 --> 01:00:17,960 Speaker 1: It's been a welcome distraction at work. I, along with 1011 01:00:18,000 --> 01:00:20,040 Speaker 1: so many feel like we know you guys so well 1012 01:00:20,680 --> 01:00:22,840 Speaker 1: with Stuff you Should Know and Chuck's movie Crush and 1013 01:00:22,920 --> 01:00:25,880 Speaker 1: Josh's Into the World podcasts. I hope your families remain 1014 01:00:25,960 --> 01:00:29,040 Speaker 1: safe and from my son Dexter and I we wish 1015 01:00:29,040 --> 01:00:31,480 Speaker 1: you all the best for yourselves in the future of 1016 01:00:31,480 --> 01:00:34,800 Speaker 1: the podcast. Sorry to ramble on, which, by the way, Ben, 1017 01:00:34,920 --> 01:00:37,760 Speaker 1: that was not rambling on. That was concise and beautiful. 1018 01:00:38,080 --> 01:00:41,160 Speaker 1: But you're from England, so you're very kind. Uh. Sorry 1019 01:00:41,160 --> 01:00:42,720 Speaker 1: to ramble On, but I was wondering if you would 1020 01:00:42,720 --> 01:00:45,560 Speaker 1: be kind enough to shout out all the UK NHS 1021 01:00:45,600 --> 01:00:48,520 Speaker 1: staff that are helping us over here. I have friends 1022 01:00:48,560 --> 01:00:51,080 Speaker 1: and family that work for the NHS services and this 1023 01:00:51,160 --> 01:00:53,360 Speaker 1: is the only way I know how to say thank you, 1024 01:00:53,880 --> 01:00:57,040 Speaker 1: So for sure, Ben, thank you to not only them, 1025 01:00:57,080 --> 01:01:00,760 Speaker 1: but to medical providers all over the world who are 1026 01:01:00,920 --> 01:01:05,120 Speaker 1: working hard risking their own lives UM, often with UM 1027 01:01:05,320 --> 01:01:09,200 Speaker 1: equipment that's being reused when it shouldn't be and uh, 1028 01:01:09,280 --> 01:01:12,000 Speaker 1: I'm not going to wade into those waters. But you 1029 01:01:12,040 --> 01:01:13,840 Speaker 1: don't have all that you need to do your job 1030 01:01:13,920 --> 01:01:16,320 Speaker 1: right now and that's terrible and we should not be 1031 01:01:16,360 --> 01:01:19,160 Speaker 1: in this position. But we are so thank you. Uh. 1032 01:01:19,280 --> 01:01:25,120 Speaker 1: He also says ps Torquay. We heard from a bunch 1033 01:01:25,120 --> 01:01:27,160 Speaker 1: of people on this uh you mentioned the other week 1034 01:01:27,200 --> 01:01:29,960 Speaker 1: and I think that Agatha Christie segment we would pronounce 1035 01:01:30,000 --> 01:01:33,800 Speaker 1: it tour as in tour bus and key Torquay. It's 1036 01:01:33,800 --> 01:01:36,400 Speaker 1: always fun to hear how everyone pronounces these bloody silly 1037 01:01:36,400 --> 01:01:40,520 Speaker 1: towns over here. Kind regards. That is from Ben Cleaver 1038 01:01:41,200 --> 01:01:48,400 Speaker 1: and Harrowgates, England. Hirogaty Ben. That was such a good 1039 01:01:48,440 --> 01:01:52,280 Speaker 1: email that we are now friends. That's right, thank you 1040 01:01:52,360 --> 01:01:55,560 Speaker 1: for that. That was much needed man Um, thanks a 1041 01:01:55,600 --> 01:01:57,919 Speaker 1: lot for that, and we will very happily shout out 1042 01:01:58,000 --> 01:02:02,160 Speaker 1: the entire NHS, especially all of the people who are 1043 01:02:02,200 --> 01:02:04,440 Speaker 1: out there on the front lines working to save people's 1044 01:02:04,480 --> 01:02:07,840 Speaker 1: lives against COVID nineteen or anything that happens to it 1045 01:02:07,920 --> 01:02:11,640 Speaker 1: befallen them. That's right, Um, Thanks again, Ben, And if 1046 01:02:11,680 --> 01:02:13,160 Speaker 1: you want to be like Ben and get in touch 1047 01:02:13,200 --> 01:02:14,960 Speaker 1: with us, whether you want to tell us to stop 1048 01:02:15,000 --> 01:02:17,280 Speaker 1: being so political, or you want to tell us that 1049 01:02:17,320 --> 01:02:19,400 Speaker 1: you think we're great. It doesn't matter. We want to 1050 01:02:19,440 --> 01:02:22,760 Speaker 1: hear from you. Either way, You can email us by 1051 01:02:22,840 --> 01:02:30,120 Speaker 1: sending one to Stuff podcast at iHeart radio dot com. 1052 01:02:30,200 --> 01:02:32,360 Speaker 1: Stuff you Should Know is a production of iHeart Radio's 1053 01:02:32,360 --> 01:02:34,919 Speaker 1: How Stuff Works. For more podcasts for my heart Radio, 1054 01:02:35,000 --> 01:02:37,640 Speaker 1: visit the iHeart Radio app, Apple Podcasts, or wherever you 1055 01:02:37,720 --> 01:02:38,880 Speaker 1: listen to your favorite shows.