1 00:00:00,040 --> 00:00:02,880 Speaker 1: Welcome to our three of the Clay Travis and Buck 2 00:00:02,920 --> 00:00:06,800 Speaker 1: Sexton Show. I'm Buck here in studio in NYC with 3 00:00:06,880 --> 00:00:09,840 Speaker 1: Clay and we have been looking forward to this deep 4 00:00:09,960 --> 00:00:14,200 Speaker 1: dive conversation and to COVID everything going on right now 5 00:00:14,240 --> 00:00:18,040 Speaker 1: with the vaccines, the mandates, the masks, what works, what doesn't, 6 00:00:18,079 --> 00:00:20,480 Speaker 1: What does the data tell us? With the one and 7 00:00:20,600 --> 00:00:23,760 Speaker 1: only Alex Barrenson. You've probably seen him on Fox and 8 00:00:23,800 --> 00:00:27,440 Speaker 1: you maybe have gotten Unreported Truth downloaded. I recommend you 9 00:00:27,480 --> 00:00:30,240 Speaker 1: do so on Amazon before they decide you can't. You 10 00:00:30,280 --> 00:00:33,400 Speaker 1: can also follow him on sub stack. Alex Barrenson on substack. 11 00:00:33,479 --> 00:00:36,720 Speaker 1: He is just a journalist who who's been asking questions 12 00:00:36,720 --> 00:00:39,120 Speaker 1: and gone against the consensus when the data told him too. 13 00:00:39,159 --> 00:00:42,199 Speaker 1: And he is here with us now in studio in 14 00:00:42,240 --> 00:00:44,280 Speaker 1: New York. Alex, great to see you. It's the pleasure. 15 00:00:44,560 --> 00:00:46,440 Speaker 1: We're too. Clay and I have both been talking to 16 00:00:46,479 --> 00:00:49,240 Speaker 1: you now about this issue for about eighteen months and 17 00:00:49,479 --> 00:00:52,519 Speaker 1: we're going on a long time. Can we can we 18 00:00:52,560 --> 00:00:54,440 Speaker 1: start with with this? Actually, because we have so much 19 00:00:54,440 --> 00:00:56,000 Speaker 1: we're gonna we're gonna keep you. Like I said, a 20 00:00:56,080 --> 00:00:58,320 Speaker 1: deep dives, you can actually have time. It's not a 21 00:00:58,320 --> 00:01:02,280 Speaker 1: four minute TV hit such as it is. Um masks, 22 00:01:02,920 --> 00:01:04,720 Speaker 1: you got a lot of heat in the beginning. It 23 00:01:04,800 --> 00:01:07,760 Speaker 1: seems like now fondly people understand that this is almost 24 00:01:07,800 --> 00:01:10,400 Speaker 1: like a religious symbol for most folks. Is there what 25 00:01:10,840 --> 00:01:12,679 Speaker 1: is the data clear on this one? Before we get 26 00:01:12,680 --> 00:01:14,920 Speaker 1: into vaccines? Can we just get into if they had 27 00:01:14,959 --> 00:01:17,880 Speaker 1: good mass data, wouldn't we know about it? Has anybody 28 00:01:18,040 --> 00:01:20,320 Speaker 1: been alive in the last eighteen months? Didn't we all 29 00:01:20,360 --> 00:01:23,520 Speaker 1: mask up for about twelve of those months? And the 30 00:01:23,640 --> 00:01:25,840 Speaker 1: virus came and went and came and went and came 31 00:01:25,880 --> 00:01:29,399 Speaker 1: and went. Masks are useless. They are useless. Uh. They're 32 00:01:29,440 --> 00:01:34,120 Speaker 1: certainly useless to keep you from getting sick. Uh. And 33 00:01:34,280 --> 00:01:37,640 Speaker 1: they are and they are almost as certainly useless to 34 00:01:37,640 --> 00:01:40,200 Speaker 1: to you know, prevent you from transmitting the virus to 35 00:01:40,240 --> 00:01:42,320 Speaker 1: other people. Ugies that you know. Can I just ask 36 00:01:42,360 --> 00:01:44,200 Speaker 1: who are now willing to say that, at least to 37 00:01:44,280 --> 00:01:48,360 Speaker 1: you offline? Yeah? I mean absolutely. And by the way 38 00:01:48,440 --> 00:01:50,760 Speaker 1: we are we're not talking about what they call respirators again, 39 00:01:50,800 --> 00:01:53,600 Speaker 1: and ninety five and ninety five maybe marginally useful. I'm 40 00:01:53,640 --> 00:01:55,880 Speaker 1: not willing to, you know, be as definitive about that. 41 00:01:56,280 --> 00:02:00,360 Speaker 1: But when you when you asked the CDC to present 42 00:02:00,440 --> 00:02:04,080 Speaker 1: studies showing that masks work, that cloth or surgical masks 43 00:02:04,120 --> 00:02:06,800 Speaker 1: work to you know, protect their wearers from COVID. They 44 00:02:06,840 --> 00:02:09,840 Speaker 1: don't have any because those studies don't exist. Okay, this 45 00:02:09,919 --> 00:02:12,000 Speaker 1: is important, I think because so many kids are going 46 00:02:12,040 --> 00:02:14,200 Speaker 1: back to school. My kids go back to school tomorrow. Alex, 47 00:02:14,200 --> 00:02:17,320 Speaker 1: thanks for being in here in studio with us. Does 48 00:02:17,320 --> 00:02:20,399 Speaker 1: it make any sense at all for kids in particular 49 00:02:20,520 --> 00:02:23,160 Speaker 1: to be wearing masks in school? Or is it madness? No, 50 00:02:23,240 --> 00:02:26,600 Speaker 1: it's madness. Okay, it's madness. First of all, they don't work. 51 00:02:26,840 --> 00:02:29,280 Speaker 1: Second of all, kids are dirty little creatures who are 52 00:02:29,280 --> 00:02:31,720 Speaker 1: like constantly touching them and taking them off and switching 53 00:02:31,720 --> 00:02:34,440 Speaker 1: them with each other. And third, when kids get COVID, 54 00:02:35,440 --> 00:02:39,919 Speaker 1: I mean unless they're you know, lightning strike unlike unlucky, 55 00:02:40,160 --> 00:02:43,359 Speaker 1: or they're really sick, they don't. I mean, I mean 56 00:02:43,480 --> 00:02:47,280 Speaker 1: pre existing like leukemia or some terrible condition, they don't 57 00:02:47,280 --> 00:02:49,240 Speaker 1: get sick from COVID. Okay, And most they you know, 58 00:02:49,240 --> 00:02:50,760 Speaker 1: they get a fever for a couple of days, they 59 00:02:50,800 --> 00:02:53,280 Speaker 1: don't get sick. And I want to say this, I'm 60 00:02:53,280 --> 00:02:55,440 Speaker 1: a parent. I've got three young kids. You have how 61 00:02:55,440 --> 00:03:00,000 Speaker 1: many kids? Three kids Okay, So for people out there, 62 00:02:59,800 --> 00:03:02,799 Speaker 1: you shared some data before Twitter banned you, which were 63 00:03:03,080 --> 00:03:05,120 Speaker 1: ver suspended you, I guess I should say for seven days, 64 00:03:05,160 --> 00:03:06,639 Speaker 1: which we'll get too in a minute. But we're talking 65 00:03:06,639 --> 00:03:11,000 Speaker 1: to Alex Barnson. You shared some data from England about 66 00:03:11,080 --> 00:03:15,079 Speaker 1: kids in particular and the impact that this great British 67 00:03:15,080 --> 00:03:18,679 Speaker 1: study had shown COVID has on them, and the numbers 68 00:03:18,760 --> 00:03:21,840 Speaker 1: were truly staggering, right, Yeah, No, So, I mean there 69 00:03:22,160 --> 00:03:24,400 Speaker 1: are two actually that were that Lance had published over 70 00:03:24,440 --> 00:03:27,120 Speaker 1: the last year. One was from I believe last summer 71 00:03:27,240 --> 00:03:29,240 Speaker 1: or fall, and they looked at you know, they found 72 00:03:29,240 --> 00:03:33,040 Speaker 1: six children who died in Britain from COVID. Three of 73 00:03:33,080 --> 00:03:37,000 Speaker 1: the six were neonates with severe genetic abnormalities, and there's 74 00:03:37,080 --> 00:03:39,880 Speaker 1: you know, like babies born just too sick to live, 75 00:03:40,160 --> 00:03:42,760 Speaker 1: and I think the other three head terminal illness. And 76 00:03:42,800 --> 00:03:48,840 Speaker 1: then there's an updated study from a month or two 77 00:03:48,880 --> 00:03:52,880 Speaker 1: ago where there were sixty one I believe it was 78 00:03:53,920 --> 00:03:57,160 Speaker 1: updated people under eighteens, so children and teens who died 79 00:03:57,200 --> 00:03:59,560 Speaker 1: in Britain thirty six of them. I think you could 80 00:03:59,560 --> 00:04:02,160 Speaker 1: just say we're totally wrong and they're homicide or suicide 81 00:04:02,200 --> 00:04:05,000 Speaker 1: or stuff like that, and then of the others, there 82 00:04:05,000 --> 00:04:08,320 Speaker 1: are only six who didn't have you know, triesames or 83 00:04:08,360 --> 00:04:11,400 Speaker 1: other really severe genetic conditions, who you know, who'd be 84 00:04:11,400 --> 00:04:14,520 Speaker 1: classified as healthy and you know, so that's six out 85 00:04:14,560 --> 00:04:17,520 Speaker 1: of twelve million in Britain. I think that's just significant 86 00:04:17,520 --> 00:04:20,400 Speaker 1: because so many parents are out there as it pertains 87 00:04:20,440 --> 00:04:22,640 Speaker 1: to kids and COVID. That's a great study out of 88 00:04:22,680 --> 00:04:25,800 Speaker 1: England that I don't think got enough attention. Also when 89 00:04:25,800 --> 00:04:28,320 Speaker 1: I ask you about the vaccine situation here because right 90 00:04:28,360 --> 00:04:30,320 Speaker 1: now with masks, I have more and more people on 91 00:04:30,360 --> 00:04:34,120 Speaker 1: the left who are saying things like masks are really 92 00:04:34,160 --> 00:04:36,320 Speaker 1: now just they are a symbols. When we used to 93 00:04:36,360 --> 00:04:38,400 Speaker 1: say they were a symbol, it was shut up at science. 94 00:04:38,760 --> 00:04:41,200 Speaker 1: Now people will tell you. I've had leftists that are 95 00:04:41,279 --> 00:04:43,520 Speaker 1: people I know or work with, will say, it's really 96 00:04:43,520 --> 00:04:46,840 Speaker 1: just about reminding everybody about all the things we have 97 00:04:46,920 --> 00:04:49,640 Speaker 1: to do. It's reminding everybody that we all need to 98 00:04:49,640 --> 00:04:51,360 Speaker 1: get vaxed, all that kind of stuff. Right, So they've 99 00:04:51,520 --> 00:04:54,000 Speaker 1: they've transitioned, because otherwise, if you look at the data, 100 00:04:54,000 --> 00:04:56,680 Speaker 1: it doesn't. Okay, so we'll put masks aside for a second. 101 00:04:56,800 --> 00:04:59,880 Speaker 1: But even though the amount of ferocity directed to people 102 00:04:59,880 --> 00:05:03,320 Speaker 1: like you, me Clay for even questioning it to me 103 00:05:03,600 --> 00:05:07,160 Speaker 1: was like a mass mental illness on display. But vaccines, 104 00:05:07,720 --> 00:05:12,279 Speaker 1: what is going on right now? People look at the numbers, 105 00:05:12,279 --> 00:05:15,159 Speaker 1: they look at the data come to very different conclusions. 106 00:05:15,440 --> 00:05:17,720 Speaker 1: And even people that I know, Alex, who have been 107 00:05:17,760 --> 00:05:19,839 Speaker 1: really supportive of a lot of the work you've done, 108 00:05:20,240 --> 00:05:22,480 Speaker 1: have complained to me and wanted me to ask you 109 00:05:22,960 --> 00:05:27,599 Speaker 1: he's too critical. He does not show enough of the 110 00:05:27,720 --> 00:05:31,919 Speaker 1: upside of the vaccines. How do you respond to that? Okay, 111 00:05:32,000 --> 00:05:36,120 Speaker 1: So vaccines are supposed to be permanent, right, that's sort 112 00:05:36,120 --> 00:05:39,320 Speaker 1: of inherent in the name. They're supposed to last ten years, 113 00:05:39,440 --> 00:05:44,000 Speaker 1: twenty years, a lifetime. It is abundantly clear these vaccines 114 00:05:44,200 --> 00:05:48,080 Speaker 1: don't meet that definition. Okay, they don't work like traditional vaccines. 115 00:05:48,240 --> 00:05:50,240 Speaker 1: I'm talking about the mRNA and the J and J 116 00:05:50,400 --> 00:05:55,280 Speaker 1: which works differently but as well, which but is essentially 117 00:05:55,279 --> 00:05:58,360 Speaker 1: the same idea as the mr anda vaccine. They don't 118 00:05:58,400 --> 00:06:03,080 Speaker 1: work like traditional vaccines. They also, and we have now 119 00:06:03,120 --> 00:06:05,520 Speaker 1: pretty good data on this, the first couple of weeks 120 00:06:05,520 --> 00:06:07,880 Speaker 1: after you get the first dose, you're actually more likely 121 00:06:07,920 --> 00:06:11,479 Speaker 1: to get infected. It looks like the clinical trial data 122 00:06:11,520 --> 00:06:14,200 Speaker 1: didn't show that it showed that there was no protective effect, 123 00:06:14,200 --> 00:06:17,560 Speaker 1: but the real world data shows there's some increase in infectivity. Okay, 124 00:06:17,880 --> 00:06:20,080 Speaker 1: then it takes a couple more weeks, then you get 125 00:06:20,080 --> 00:06:23,040 Speaker 1: the second dose. After the second dose, it looks like 126 00:06:23,120 --> 00:06:26,720 Speaker 1: you have this sort of happy valley. Okay, you get it. 127 00:06:26,800 --> 00:06:29,800 Speaker 1: There's there's a there's a couple of months where this 128 00:06:29,880 --> 00:06:32,720 Speaker 1: thing really does seem to work and it provides protection. 129 00:06:32,760 --> 00:06:34,360 Speaker 1: And you saw that in Israel, you saw it in 130 00:06:34,440 --> 00:06:37,080 Speaker 1: the UK, you saw it sort of in American nursing 131 00:06:37,120 --> 00:06:40,920 Speaker 1: home data. It's pretty clear. Okay. The problem is it 132 00:06:40,960 --> 00:06:44,440 Speaker 1: doesn't last and the last month in Israel, that data 133 00:06:44,560 --> 00:06:47,040 Speaker 1: is horrific. Yeah, tell us about this because people believe 134 00:06:47,120 --> 00:06:49,680 Speaker 1: that the thing we hear, right, and we're Clay and 135 00:06:49,720 --> 00:06:51,680 Speaker 1: I are looking at this stuff every day. From the 136 00:06:51,720 --> 00:06:55,919 Speaker 1: news cycle perspective, you hear it's good at least six 137 00:06:56,040 --> 00:06:58,400 Speaker 1: to eight months, is what they've been saying. That's what 138 00:06:58,480 --> 00:07:00,680 Speaker 1: that's what you know, the narrative has been. Okay, So 139 00:07:01,000 --> 00:07:03,039 Speaker 1: first of all, let's say it's good six to eight months. 140 00:07:03,480 --> 00:07:05,560 Speaker 1: How did that become something that we all have to 141 00:07:05,560 --> 00:07:07,360 Speaker 1: take for the rest of our lives? A great question 142 00:07:07,360 --> 00:07:10,080 Speaker 1: and your point. Sorry, before we get to Israel. Your point, 143 00:07:10,080 --> 00:07:13,000 Speaker 1: based on the data that you are seeing, would suggest 144 00:07:13,160 --> 00:07:17,040 Speaker 1: that instead of being a traditional vaccine like measles, mumps, 145 00:07:17,080 --> 00:07:20,680 Speaker 1: and rebella, what you're effectively saying is this is more 146 00:07:20,720 --> 00:07:22,920 Speaker 1: akin to a flu shot, where you're gonna have to 147 00:07:22,920 --> 00:07:26,520 Speaker 1: get it every year forever, and it provides some measure 148 00:07:26,560 --> 00:07:29,640 Speaker 1: of protection, but it's not the equivalent of hey, you're 149 00:07:29,680 --> 00:07:32,000 Speaker 1: never gonna get chicken pox for instance. That's right, but 150 00:07:32,040 --> 00:07:34,320 Speaker 1: it's also much more dangerous than a flu shot. I mean, 151 00:07:34,720 --> 00:07:37,760 Speaker 1: I anybody who looks at the data is going to 152 00:07:37,800 --> 00:07:39,760 Speaker 1: agree to that. Okay, the side effects are off the 153 00:07:39,840 --> 00:07:42,480 Speaker 1: charts compared to the flu shot. Even even if you 154 00:07:42,640 --> 00:07:47,360 Speaker 1: only talk about the myocarditis risk and the venous sinus 155 00:07:47,360 --> 00:07:50,440 Speaker 1: thrombosis risk with the J and J vaccines, nobody, no 156 00:07:50,840 --> 00:07:55,800 Speaker 1: nineteen year old drop dead of venus sinus thrombosis after 157 00:07:55,840 --> 00:07:58,880 Speaker 1: getting a flu shot. It does not happen. Okay, So 158 00:07:59,080 --> 00:08:03,080 Speaker 1: these are has happened. When you talk about myocardietus minor number, 159 00:08:03,160 --> 00:08:05,040 Speaker 1: what kind of numbers are we talking about? Because they'll 160 00:08:05,040 --> 00:08:07,800 Speaker 1: say one hundred and sixty million have gotten the shot 161 00:08:07,840 --> 00:08:10,920 Speaker 1: in this country. I mean, if fifty people got myocardietus, 162 00:08:10,920 --> 00:08:13,880 Speaker 1: they'll just you know, it's not like that. So again, 163 00:08:14,040 --> 00:08:17,960 Speaker 1: we have better data out of Israel. Explain let's sorry 164 00:08:17,960 --> 00:08:20,040 Speaker 1: to cut you up, but explain that Israel data. For 165 00:08:20,080 --> 00:08:22,800 Speaker 1: people out there, what are you seeing because Israel's ahead 166 00:08:22,800 --> 00:08:25,040 Speaker 1: of us in terms of vaccinating their people. For those 167 00:08:25,160 --> 00:08:28,120 Speaker 1: listeners out there who may not be aware, what are 168 00:08:28,120 --> 00:08:30,360 Speaker 1: you seeing from that data? So the two countries that 169 00:08:30,360 --> 00:08:33,120 Speaker 1: were more aggressive than the US significantly more were Israel 170 00:08:33,120 --> 00:08:35,360 Speaker 1: in the UK, and the data is cleaner out of 171 00:08:35,440 --> 00:08:37,120 Speaker 1: Israel for a couple of reasons. First of all, the 172 00:08:37,200 --> 00:08:39,400 Speaker 1: UK used a lot of astras anica, which we don't 173 00:08:39,480 --> 00:08:42,439 Speaker 1: use here. The UK also did this weird thing where 174 00:08:42,480 --> 00:08:46,280 Speaker 1: they didn't go with the regular vaccine schedule and others. 175 00:08:46,280 --> 00:08:48,280 Speaker 1: In the clinical trials it was one dose and then 176 00:08:48,320 --> 00:08:50,200 Speaker 1: a second to is you know, three weeks later for 177 00:08:50,240 --> 00:08:53,360 Speaker 1: fis or four weeks later for maderna. The UK didn't 178 00:08:53,400 --> 00:08:55,760 Speaker 1: do that. They serve they wanted to get as many 179 00:08:55,760 --> 00:08:58,600 Speaker 1: people to have one dose as possible. In Israel, they 180 00:08:58,600 --> 00:09:01,640 Speaker 1: only used fiser, which is mRNA vaccine, you know, which 181 00:09:01,679 --> 00:09:04,640 Speaker 1: more people in the US have gotten. And they did 182 00:09:04,679 --> 00:09:07,560 Speaker 1: it on the you know, we'll say correct. They did 183 00:09:07,600 --> 00:09:10,520 Speaker 1: on the correct schedule, so the data is more comparable 184 00:09:10,600 --> 00:09:14,240 Speaker 1: to the US data. Second of all, Israel is relatively small, 185 00:09:14,640 --> 00:09:17,480 Speaker 1: and they've been collecting data on a daily basis and 186 00:09:17,559 --> 00:09:21,400 Speaker 1: releasing it, you know, since before the vaccines started. Okay, 187 00:09:21,600 --> 00:09:24,559 Speaker 1: and they do it in a pretty transparent way. It's 188 00:09:24,600 --> 00:09:27,800 Speaker 1: not as transparent as I would like, but it's pretty transparent. 189 00:09:27,840 --> 00:09:30,839 Speaker 1: It is far far more transparent and honest than the 190 00:09:30,920 --> 00:09:34,360 Speaker 1: data we get in the US. So, So when SO 191 00:09:35,400 --> 00:09:37,000 Speaker 1: and they're in front of US, as I said, they 192 00:09:37,040 --> 00:09:40,280 Speaker 1: started before US. So, Israel actually was saying that young 193 00:09:40,320 --> 00:09:45,000 Speaker 1: men who are at the highest risk for myracharditis appear 194 00:09:45,040 --> 00:09:47,080 Speaker 1: to have about a one in three thousand to one 195 00:09:47,120 --> 00:09:50,360 Speaker 1: in six thousand risk of clinically significant miocharditis. Now that 196 00:09:50,360 --> 00:09:53,640 Speaker 1: may not sound like that much, but those young men 197 00:09:53,760 --> 00:09:56,840 Speaker 1: have essentially zero risk if they're healthy from COVID. And 198 00:09:56,880 --> 00:09:58,480 Speaker 1: there's a second point. There's a point that does not 199 00:09:58,520 --> 00:10:02,680 Speaker 1: get understood here. Okay, it's not likely that one in 200 00:10:02,760 --> 00:10:05,560 Speaker 1: three thousand people is having myocardite is bad enough to 201 00:10:05,559 --> 00:10:07,520 Speaker 1: go to the hospital, and the other twenty nine ninety 202 00:10:07,559 --> 00:10:10,400 Speaker 1: nine are having nothing happened to them. Okay, it is 203 00:10:10,480 --> 00:10:14,320 Speaker 1: likely that a significant number of people are having changes 204 00:10:14,360 --> 00:10:17,960 Speaker 1: in their heart function that are real but are not 205 00:10:18,120 --> 00:10:20,400 Speaker 1: bad enough to send you to the hospital. And we 206 00:10:20,480 --> 00:10:22,800 Speaker 1: don't know how many people that might be because the 207 00:10:22,880 --> 00:10:25,680 Speaker 1: companies didn't do any work in the clinical trials that 208 00:10:25,800 --> 00:10:27,720 Speaker 1: might help us with that. Alex, we want to return 209 00:10:27,760 --> 00:10:29,400 Speaker 1: to this with you in a second. And also I 210 00:10:29,400 --> 00:10:31,559 Speaker 1: want to pose to you and for everyone listening, just 211 00:10:32,240 --> 00:10:35,520 Speaker 1: the narrative right now from the Biden administration on down 212 00:10:36,000 --> 00:10:38,920 Speaker 1: is get the shot, You're fine, it's over. If you 213 00:10:38,960 --> 00:10:41,880 Speaker 1: don't get the shot, you're a barbarian who basically you know, 214 00:10:42,080 --> 00:10:43,680 Speaker 1: you get what you deserve. I mean, it's very clear 215 00:10:43,720 --> 00:10:46,319 Speaker 1: that's what they're saying. I want to have you respond 216 00:10:46,360 --> 00:10:48,760 Speaker 1: to that based on the data in just a moment, 217 00:10:48,760 --> 00:10:50,280 Speaker 1: when we come back and look at the truth of 218 00:10:50,400 --> 00:10:54,240 Speaker 1: where we are in this fight against COVID. But I mean, 219 00:10:54,520 --> 00:10:58,120 Speaker 1: Mike Lendell just stands athwart cancel culture in a way 220 00:10:58,120 --> 00:11:00,760 Speaker 1: that is honestly inspiring. This guy will not back down 221 00:11:00,840 --> 00:11:03,080 Speaker 1: from anybody, doesn't matter who comes at him from the left. 222 00:11:03,200 --> 00:11:05,559 Speaker 1: And you know why. One, he's a patriot, he loves 223 00:11:05,559 --> 00:11:08,440 Speaker 1: this country. But also he's got a fantastic company with 224 00:11:08,480 --> 00:11:12,160 Speaker 1: amazing products that I use every single day. 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We have 244 00:12:19,280 --> 00:12:21,720 Speaker 1: maybe the most dangerous man on Twitter in the studio 245 00:12:21,760 --> 00:12:24,760 Speaker 1: with us right now, Alex Berenson. And by the way, 246 00:12:25,040 --> 00:12:28,040 Speaker 1: the phone lines have been lit ever since Alex came in. 247 00:12:28,080 --> 00:12:30,120 Speaker 1: We appreciate all the people who want to talk and 248 00:12:30,360 --> 00:12:32,120 Speaker 1: get on with him. But here here's what I'm going 249 00:12:32,160 --> 00:12:33,720 Speaker 1: to ask you to do so that we can be 250 00:12:33,760 --> 00:12:36,480 Speaker 1: as efficient with Alex's time and your time as possible. 251 00:12:36,920 --> 00:12:40,679 Speaker 1: If you want to tag Buck Sexton or me at 252 00:12:40,800 --> 00:12:44,120 Speaker 1: Clay Travis at buck Sexton right now on Twitter with 253 00:12:44,160 --> 00:12:47,640 Speaker 1: any questions, we'll scroll through and make sure that we 254 00:12:47,679 --> 00:12:49,839 Speaker 1: are trying to hit the things that you guys care 255 00:12:49,840 --> 00:12:51,679 Speaker 1: about the most. I think there's gonna be a lot 256 00:12:51,679 --> 00:12:54,520 Speaker 1: of overlap in what Buck and I would ask that 257 00:12:54,559 --> 00:12:57,240 Speaker 1: you guys would also be interested in, but we'll check 258 00:12:57,360 --> 00:13:00,439 Speaker 1: Twitter rather than take any calls. Okay, I want to 259 00:13:00,440 --> 00:13:03,160 Speaker 1: ask you this question. Right now, we are being told 260 00:13:03,720 --> 00:13:07,360 Speaker 1: that if every single person in the entire United States 261 00:13:07,520 --> 00:13:10,760 Speaker 1: got the COVID vaccine, that COVID would be over. That 262 00:13:11,000 --> 00:13:14,080 Speaker 1: the people who are unvaccinated are the only reason why 263 00:13:14,120 --> 00:13:16,960 Speaker 1: COVID still exists. Based on the data that you see 264 00:13:16,960 --> 00:13:20,240 Speaker 1: in Israel and in England. Is that true? And if not, 265 00:13:20,679 --> 00:13:23,400 Speaker 1: what does the future look like right now? No? I 266 00:13:23,480 --> 00:13:26,600 Speaker 1: mean that's demonstrably untrue. So in Israel, ninety five percent 267 00:13:26,640 --> 00:13:29,360 Speaker 1: of people over eighty or vaccinated, ninety plus percent of 268 00:13:29,400 --> 00:13:32,600 Speaker 1: people over sixtier vaccinated, and eighty five percent of people 269 00:13:32,640 --> 00:13:35,960 Speaker 1: over thirty or vaccinated fully vaccinated, two doses, two weeks 270 00:13:35,960 --> 00:13:39,199 Speaker 1: fully vaccinate. Okay, that is above the levels that we 271 00:13:39,200 --> 00:13:42,280 Speaker 1: were told would need her immunity. It is, I mean, 272 00:13:42,360 --> 00:13:44,240 Speaker 1: it is as close to full vaccination as you can 273 00:13:44,320 --> 00:13:49,040 Speaker 1: reasonably hope for. The number of infections in Israel has 274 00:13:49,360 --> 00:13:53,160 Speaker 1: increased more than tenfold in the last month. Is there 275 00:13:53,400 --> 00:13:54,960 Speaker 1: are three to four thousand a day. This is a 276 00:13:54,960 --> 00:13:56,640 Speaker 1: country of nine million people, Okay, so you've got to 277 00:13:56,679 --> 00:14:00,480 Speaker 1: multiply that by thirty plus to get to a numbers 278 00:14:00,480 --> 00:14:02,400 Speaker 1: that's over one hundred thousand infections a day the last 279 00:14:02,440 --> 00:14:06,960 Speaker 1: few days. The equivalent more concerning even than that is 280 00:14:07,280 --> 00:14:10,160 Speaker 1: the number of people who are in critical care seriously 281 00:14:10,200 --> 00:14:14,280 Speaker 1: ill in Israel has increased tenfold in the last month 282 00:14:14,960 --> 00:14:17,600 Speaker 1: to two hundred and fifty. It was so again Israel 283 00:14:17,720 --> 00:14:21,640 Speaker 1: had this period late April through mid June when basically, 284 00:14:21,680 --> 00:14:24,120 Speaker 1: it looked like the epidemic was over there, looked like 285 00:14:24,120 --> 00:14:27,360 Speaker 1: the vaccines were flawlessly and it was gonna vanish. That 286 00:14:27,480 --> 00:14:30,280 Speaker 1: is right. They dropped all the restrictions there were. You 287 00:14:30,320 --> 00:14:32,240 Speaker 1: can find all the articles from all the people who 288 00:14:32,280 --> 00:14:36,520 Speaker 1: criticize me talking about how great the situation was in Israel, 289 00:14:36,840 --> 00:14:39,720 Speaker 1: how this was the future if you got everyone vaccinated, 290 00:14:40,200 --> 00:14:45,400 Speaker 1: the vaccines don't last. It is just abundantly clear. The 291 00:14:45,480 --> 00:14:48,240 Speaker 1: data in the UK is the same, although I mean, 292 00:14:48,360 --> 00:14:50,680 Speaker 1: you know it doesn't repeat itself at it rise, but 293 00:14:50,720 --> 00:14:53,480 Speaker 1: it's roughly the same. So in this country right now, 294 00:14:53,520 --> 00:14:55,800 Speaker 1: going back to the narrative that's all being jammed down 295 00:14:55,800 --> 00:14:58,240 Speaker 1: our throats all the time by the generally democratic line 296 00:14:58,280 --> 00:15:02,200 Speaker 1: corporate media, is that the only reason we still have 297 00:15:02,280 --> 00:15:06,960 Speaker 1: COVID really is because of DELTA being more efficient yet 298 00:15:07,040 --> 00:15:10,960 Speaker 1: spread and unvaccinated people. Sounds like you're telling us that 299 00:15:11,320 --> 00:15:15,280 Speaker 1: even if they didn't have those bad unvaccinated talking to 300 00:15:15,280 --> 00:15:17,880 Speaker 1: two of them right now, those unvaccinated people out there 301 00:15:18,200 --> 00:15:21,160 Speaker 1: there would still be COVID. But is it then the 302 00:15:21,200 --> 00:15:23,480 Speaker 1: situation that they don't want to be honest about that 303 00:15:23,520 --> 00:15:25,880 Speaker 1: with the public because they want to get to one 304 00:15:25,960 --> 00:15:29,120 Speaker 1: hundred percent vaccination and then tell us they'll be boosters. 305 00:15:29,200 --> 00:15:32,000 Speaker 1: Is that what we're heading for? I mean, I can't 306 00:15:32,080 --> 00:15:35,160 Speaker 1: guess at the motives. And I'll say this, Okay, when 307 00:15:35,160 --> 00:15:36,920 Speaker 1: you look at the Asraeli data, there is one thing 308 00:15:36,920 --> 00:15:39,240 Speaker 1: that they're sort of clinging to, this idea that vaccines 309 00:15:39,280 --> 00:15:42,520 Speaker 1: still present prevent or lower the risk of severe illness 310 00:15:42,520 --> 00:15:45,800 Speaker 1: and death. Okay, And it is clear actually right now 311 00:15:45,880 --> 00:15:48,880 Speaker 1: from the Israeli data that people who haven't been vaccinated 312 00:15:49,120 --> 00:15:52,880 Speaker 1: are at higher risk of severe illness and death than 313 00:15:53,040 --> 00:15:55,400 Speaker 1: those people who are vaccinated. Even though vaccinated people make 314 00:15:55,480 --> 00:15:58,840 Speaker 1: up far more of the overall number who are severely ill, 315 00:15:59,120 --> 00:16:03,120 Speaker 1: because that pool is so small of unvaccinated people, those 316 00:16:03,160 --> 00:16:05,480 Speaker 1: people do appear to be at higher risk. But now 317 00:16:05,520 --> 00:16:08,400 Speaker 1: I gotta take it down one more level. The people 318 00:16:08,400 --> 00:16:11,920 Speaker 1: who are unvaccinated in Israel, especially older people, are probably 319 00:16:11,920 --> 00:16:13,680 Speaker 1: people who are Many of them are people who are 320 00:16:13,720 --> 00:16:16,040 Speaker 1: too sick to be vaccinated to begin with. Right, So, 321 00:16:16,080 --> 00:16:19,040 Speaker 1: if you're vaccinating ninety five percent of people over eighty, 322 00:16:19,320 --> 00:16:21,320 Speaker 1: it's not like some eighty eight year old saying I 323 00:16:21,520 --> 00:16:23,240 Speaker 1: want you know, I don't want this thing. No, they're 324 00:16:23,240 --> 00:16:25,960 Speaker 1: probably just too sick to get it. And that means 325 00:16:26,040 --> 00:16:29,720 Speaker 1: that's probably why they seem to be at higher risk, 326 00:16:29,800 --> 00:16:31,520 Speaker 1: or at least part of the reason. What I'm saying 327 00:16:32,000 --> 00:16:35,200 Speaker 1: you add it all up. Okay, the country that did 328 00:16:35,240 --> 00:16:38,240 Speaker 1: the best job with the mr Anda vaccines has a 329 00:16:38,280 --> 00:16:41,040 Speaker 1: serious crisis on a hand on its hands right now 330 00:16:41,280 --> 00:16:43,560 Speaker 1: and is talking about going back into lockdown for the 331 00:16:43,600 --> 00:16:46,800 Speaker 1: Jewish holidays in September. Okay, that is the fact. And 332 00:16:47,080 --> 00:16:50,160 Speaker 1: however much they want to scream about Mississippi and Florida, 333 00:16:50,200 --> 00:16:52,920 Speaker 1: which has a national average vaccination rate by the way, 334 00:16:52,920 --> 00:16:54,880 Speaker 1: how much they want to scream about people like me, 335 00:16:55,200 --> 00:16:59,200 Speaker 1: they can't get around that fact. It's never going away, right, 336 00:16:59,240 --> 00:17:02,160 Speaker 1: that's the big take. You never think it's significant, and 337 00:17:02,200 --> 00:17:05,520 Speaker 1: so this is going to be endemic for years and 338 00:17:05,720 --> 00:17:08,600 Speaker 1: years to come. Right. That that's what people need to prepare. 339 00:17:09,040 --> 00:17:11,280 Speaker 1: Let me tell you one thing. It doesn't. It looks 340 00:17:11,359 --> 00:17:13,919 Speaker 1: like if you get it and you recover from it, 341 00:17:13,920 --> 00:17:15,960 Speaker 1: which Bucket Eye both did by the way, you are 342 00:17:16,200 --> 00:17:19,440 Speaker 1: very unlikely to get it again. That's a shining light 343 00:17:19,560 --> 00:17:22,960 Speaker 1: in terms of natural immunity. That's right. Natural immunity appears 344 00:17:23,000 --> 00:17:27,000 Speaker 1: significantly superior to vaccine generating immunity, and there's good biological 345 00:17:27,040 --> 00:17:30,040 Speaker 1: reasons to think that's the case, because your body reacts 346 00:17:30,040 --> 00:17:33,720 Speaker 1: to the whole coronavirus. The vaccine only tells you about 347 00:17:33,760 --> 00:17:36,600 Speaker 1: one small part of it, and if the virus changes 348 00:17:36,680 --> 00:17:40,280 Speaker 1: in that part, your body's not going to recognize it. Alex, 349 00:17:40,320 --> 00:17:41,680 Speaker 1: We're going to come back in here in a second 350 00:17:41,720 --> 00:17:43,600 Speaker 1: because I want to talk to you about T cell immunity. 351 00:17:43,640 --> 00:17:46,719 Speaker 1: But also we're here in New York City and there 352 00:17:46,760 --> 00:17:49,560 Speaker 1: are vaccine mandates that they're about to put into effect. 353 00:17:49,600 --> 00:17:52,639 Speaker 1: This is the tip of the spear of tyranny. Unfortunately. 354 00:17:52,680 --> 00:17:53,960 Speaker 1: Want to talk to you about what you think that's 355 00:17:53,960 --> 00:17:55,640 Speaker 1: going to look like and where we go from here 356 00:17:56,160 --> 00:17:59,480 Speaker 1: in just a moment. But who's watching your money these days? 357 00:17:59,480 --> 00:18:01,760 Speaker 1: I mean it's not your financial advisor. You know, he's 358 00:18:01,800 --> 00:18:04,440 Speaker 1: on the beach having a my tie hanging out because 359 00:18:04,480 --> 00:18:06,960 Speaker 1: he doesn't really care your investments tank. He's still got 360 00:18:06,960 --> 00:18:10,840 Speaker 1: plenty in the bank. Wall Street insiders predict that a 361 00:18:10,840 --> 00:18:13,359 Speaker 1: correction could be just ahead. So it's your choice. I mean, 362 00:18:13,400 --> 00:18:16,080 Speaker 1: you can listen to the same old excuses from your advisor, 363 00:18:16,640 --> 00:18:20,280 Speaker 1: or you can take action today subscribe to Carnivore Trading. 364 00:18:20,320 --> 00:18:22,439 Speaker 1: That's what I do, and see why their picks have 365 00:18:22,560 --> 00:18:26,280 Speaker 1: become legendary. These guys are crushing it. 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That's get our Trades dot Com 375 00:18:57,160 --> 00:19:01,320 Speaker 1: Promo Code USA. Carnival Trading, real trade, real trading, real time, 376 00:19:01,480 --> 00:19:04,399 Speaker 1: past performance. No guarantee of future earning. See website for 377 00:19:04,480 --> 00:19:16,560 Speaker 1: guarantee terms and conditions. Fund the EIB Network. Welcome back 378 00:19:16,560 --> 00:19:19,240 Speaker 1: to the Clay Travis and Buck Sexton show. Buck here 379 00:19:19,280 --> 00:19:23,160 Speaker 1: with Clay in NYC in our studio mittown, Manhattan, and 380 00:19:23,280 --> 00:19:27,600 Speaker 1: we promise you a deep dive with Alex Barrinson, who 381 00:19:27,640 --> 00:19:30,080 Speaker 1: some would say is the most controversial man out there 382 00:19:30,119 --> 00:19:32,600 Speaker 1: when it comes to COVID, just because he doesn't go 383 00:19:32,640 --> 00:19:35,879 Speaker 1: along with the so called Fouchiite consensus, and Clay and 384 00:19:35,920 --> 00:19:37,600 Speaker 1: I have been following his work and talking to him 385 00:19:37,600 --> 00:19:39,880 Speaker 1: now for eighteen months. I'm going on quite a long time. 386 00:19:41,320 --> 00:19:44,320 Speaker 1: Clay wants to establish a few things about how you're 387 00:19:44,359 --> 00:19:46,320 Speaker 1: not anti vaccine, and I want to get that. Can 388 00:19:46,359 --> 00:19:49,280 Speaker 1: I just ask you, though, the people who say on 389 00:19:49,320 --> 00:19:53,199 Speaker 1: the vaccines that you're wrong, what do they say and 390 00:19:53,400 --> 00:19:56,000 Speaker 1: why are they wrong? I mean, get to the criticisms first, 391 00:19:56,000 --> 00:19:58,000 Speaker 1: because right now, as you know, there are people who 392 00:19:58,080 --> 00:20:01,280 Speaker 1: just know they're supposed to oppose. That's all they think about. 393 00:20:01,800 --> 00:20:04,439 Speaker 1: So you know, a couple months ago, they had an 394 00:20:04,440 --> 00:20:06,240 Speaker 1: easier case, right it was sort of like, well, look 395 00:20:06,280 --> 00:20:08,120 Speaker 1: look at Israel, there's no cases. Look at the UK, 396 00:20:08,200 --> 00:20:12,040 Speaker 1: there's no cases. So you know, back then, the argument's 397 00:20:12,040 --> 00:20:13,840 Speaker 1: sort of about, look, there's all these side effects, which, 398 00:20:13,840 --> 00:20:16,360 Speaker 1: by the way, we're not even talking about side effects anymore. 399 00:20:16,400 --> 00:20:19,399 Speaker 1: We're just talking about whether this thing works at all. Okay. 400 00:20:19,760 --> 00:20:23,040 Speaker 1: So so that idea that the vaccines are going to 401 00:20:23,280 --> 00:20:26,160 Speaker 1: end the epidemic, that they are going to return life 402 00:20:26,160 --> 00:20:30,240 Speaker 1: to normal by themselves, that that that's gone. I think 403 00:20:30,359 --> 00:20:33,800 Speaker 1: delta has ended that. Now, that doesn't mean we can't 404 00:20:33,800 --> 00:20:36,320 Speaker 1: get back to normal. We can get back to normal 405 00:20:36,560 --> 00:20:40,280 Speaker 1: whenever we want. There is no evidence that this thing 406 00:20:40,440 --> 00:20:43,000 Speaker 1: is going to cause that any that COVID or any 407 00:20:43,000 --> 00:20:45,680 Speaker 1: of the variants is going to cause health system collapse. 408 00:20:46,000 --> 00:20:49,960 Speaker 1: That was the whole point eighteen months ago, fifteen days 409 00:20:49,960 --> 00:20:52,399 Speaker 1: to flatten the curve, fifteen days so that if you 410 00:20:52,480 --> 00:20:54,960 Speaker 1: got in a car accident you would be there'd be 411 00:20:55,000 --> 00:20:58,560 Speaker 1: a hospital bed for you. Okay. The day the hospital 412 00:20:58,600 --> 00:21:02,680 Speaker 1: ships left New York's City, New York Harbor in April, 413 00:21:02,840 --> 00:21:04,280 Speaker 1: you know, late March or not. I guess it was 414 00:21:04,359 --> 00:21:07,439 Speaker 1: late April of last year. That argument should have ended. 415 00:21:07,880 --> 00:21:10,320 Speaker 1: New York was the worst hit city basically major city 416 00:21:10,359 --> 00:21:12,879 Speaker 1: in the world, and it was, you know, a terrible time, 417 00:21:13,160 --> 00:21:15,640 Speaker 1: and Cuomo made bad decisions, and you know, it got 418 00:21:15,640 --> 00:21:17,440 Speaker 1: worse because of the nursing homes. It got worse because 419 00:21:17,480 --> 00:21:21,520 Speaker 1: they overventilated people. Nonetheless, the hospital system in New York 420 00:21:21,560 --> 00:21:25,240 Speaker 1: City did not collapse those there there were no mass graves, 421 00:21:25,400 --> 00:21:28,440 Speaker 1: there were no you know, people being cared for intense 422 00:21:28,520 --> 00:21:31,439 Speaker 1: in Central Park. It didn't happen. This thing is not 423 00:21:31,640 --> 00:21:34,720 Speaker 1: bad enough to destroy our society. Only we can do 424 00:21:34,760 --> 00:21:39,760 Speaker 1: that to ourselves, Okay, And so this ends. When we 425 00:21:39,840 --> 00:21:42,119 Speaker 1: say it ends, it doesn't end because of vaccines and 426 00:21:42,200 --> 00:21:44,120 Speaker 1: the problem and we were talking about this a little 427 00:21:44,119 --> 00:21:46,640 Speaker 1: bit during the break is there are so many people 428 00:21:46,680 --> 00:21:49,040 Speaker 1: who've been so frightened because all they did is watch CNN. 429 00:21:49,160 --> 00:21:51,439 Speaker 1: They have no idea who really gets very sick from this, 430 00:21:51,520 --> 00:21:53,119 Speaker 1: They have no idea who really dies from it. They 431 00:21:53,119 --> 00:21:55,000 Speaker 1: have no idea what the numbers really are. They've been 432 00:21:55,040 --> 00:21:57,640 Speaker 1: lied to for eighteen months. They were told the vaccines 433 00:21:57,640 --> 00:22:00,159 Speaker 1: were going to save them and you know, get us 434 00:22:00,200 --> 00:22:02,920 Speaker 1: all back to the hot vacts summer. Now that's been 435 00:22:02,960 --> 00:22:05,480 Speaker 1: taken from him, and they are looking to blame somebody. 436 00:22:05,640 --> 00:22:08,800 Speaker 1: They're looking to blame me. They should be blaming the 437 00:22:08,840 --> 00:22:10,960 Speaker 1: people who told them the vaccines were the way out 438 00:22:10,960 --> 00:22:13,239 Speaker 1: of this when that was never true. Okay, I think 439 00:22:13,280 --> 00:22:15,440 Speaker 1: this is significant, and thank you for talking to Alex 440 00:22:15,480 --> 00:22:18,800 Speaker 1: Barnson in studio. Clay Travis buck Saxton, you are not 441 00:22:19,160 --> 00:22:21,200 Speaker 1: anti vaccine, and I want to make that. I want 442 00:22:21,200 --> 00:22:23,760 Speaker 1: to make this clear because there is this idea that 443 00:22:23,800 --> 00:22:27,440 Speaker 1: if you ask questions about the COVID vaccine, it means 444 00:22:27,480 --> 00:22:30,639 Speaker 1: you question the legitimacy of all vaccines. That's different. You 445 00:22:30,640 --> 00:22:33,840 Speaker 1: have young children, you just took your kids to go 446 00:22:33,880 --> 00:22:36,399 Speaker 1: get their vaccine. That's right. Well, and you know I 447 00:22:36,400 --> 00:22:38,119 Speaker 1: said this on Tiger last week, and I wasn't clear that. 448 00:22:38,160 --> 00:22:41,320 Speaker 1: People said you got your daughter vaccine against COVID. No, 449 00:22:41,480 --> 00:22:44,520 Speaker 1: I got a vaccinate against MMR. And you know, deed 450 00:22:44,560 --> 00:22:46,840 Speaker 1: tap that was her two year well child visit. She 451 00:22:46,880 --> 00:22:48,159 Speaker 1: got the shots. Let me tell you she didn't like 452 00:22:48,200 --> 00:22:50,080 Speaker 1: the shots. She got the shots and now she doesn't 453 00:22:50,080 --> 00:22:52,960 Speaker 1: have to worry about those things ever again, basically ever again. 454 00:22:53,040 --> 00:22:55,880 Speaker 1: And one of these people say, oh, measles vaccine fails. Yeah, 455 00:22:55,880 --> 00:22:59,199 Speaker 1: after twenty five years, if you're exposed to somebody with 456 00:22:59,280 --> 00:23:01,040 Speaker 1: measles and you know you're in the same room with 457 00:23:01,080 --> 00:23:04,080 Speaker 1: them for an hour, Okay, that's if. If the COVID 458 00:23:04,119 --> 00:23:08,040 Speaker 1: vaccine did that, sign me up. Okay, Unfortunately it doesn't 459 00:23:08,080 --> 00:23:10,760 Speaker 1: do that. We went at warp speed, and I you know, 460 00:23:10,760 --> 00:23:12,560 Speaker 1: I've said this on Twitter. Now I can't say anything 461 00:23:12,560 --> 00:23:15,080 Speaker 1: on Twitter because I'm bad. You want it bad, you 462 00:23:15,160 --> 00:23:17,640 Speaker 1: get it bad. We wanted this bad and we got 463 00:23:17,680 --> 00:23:20,359 Speaker 1: something that doesn't really work as promises. How can we 464 00:23:20,440 --> 00:23:23,600 Speaker 1: not know if boosters are I mean that this is 465 00:23:23,600 --> 00:23:25,760 Speaker 1: a we hear there'll be a news story they'll say, 466 00:23:26,000 --> 00:23:30,560 Speaker 1: booster get an approval, booster here, booster there. Well, shouldn't 467 00:23:30,600 --> 00:23:32,320 Speaker 1: that be a part if we have a strategy to 468 00:23:32,440 --> 00:23:34,159 Speaker 1: end this thing, or if we have a strategy to 469 00:23:34,520 --> 00:23:37,120 Speaker 1: handle this The Biden administrations doing such a great job, 470 00:23:37,160 --> 00:23:39,840 Speaker 1: which is what we were told, shouldn't we already know, 471 00:23:40,119 --> 00:23:43,399 Speaker 1: Alex if you're gonna need a booster shot for this? 472 00:23:43,720 --> 00:23:45,800 Speaker 1: Do they kind of already know? But they just don't 473 00:23:45,800 --> 00:23:47,679 Speaker 1: want to talk about it. What's going on with them? 474 00:23:47,720 --> 00:23:49,800 Speaker 1: So that's a fascinating question. If you look back at 475 00:23:49,880 --> 00:23:52,920 Speaker 1: Maderna and the companies have played this so brilliantly. They 476 00:23:52,920 --> 00:23:55,760 Speaker 1: were talking about boosters back in January. So the companies, 477 00:23:55,880 --> 00:23:58,359 Speaker 1: the companies were much much smarter. I mean, they are smarter, 478 00:23:58,440 --> 00:24:01,080 Speaker 1: they have more money, if much smarter the public health authorities. 479 00:24:01,480 --> 00:24:03,880 Speaker 1: They have let the public health authorities do the hard 480 00:24:03,920 --> 00:24:07,560 Speaker 1: work for them the whole time. And so and so, 481 00:24:07,600 --> 00:24:10,199 Speaker 1: I mean, if you told people, yeah, guess what, you're 482 00:24:10,240 --> 00:24:12,040 Speaker 1: going to be on a treadmill with this vaccine for 483 00:24:12,080 --> 00:24:14,240 Speaker 1: the rest of your life. And by the way, we 484 00:24:14,320 --> 00:24:17,119 Speaker 1: don't know what the side effects for a third, fourth, fifth, sixth, 485 00:24:17,200 --> 00:24:19,320 Speaker 1: or seventh dose are going to look like. And by 486 00:24:19,320 --> 00:24:21,719 Speaker 1: the way, we don't know how long immunity is going 487 00:24:21,760 --> 00:24:24,520 Speaker 1: to last. Will it get shorter with each bister, will 488 00:24:24,600 --> 00:24:28,159 Speaker 1: get longer with each bister? Who knows? And by the way, 489 00:24:28,960 --> 00:24:34,840 Speaker 1: we don't even know that these vaccines actually reduce deaths. Okay, 490 00:24:34,920 --> 00:24:37,159 Speaker 1: we's never been proven in a clinical trial. You can 491 00:24:37,200 --> 00:24:38,920 Speaker 1: look at the real world data and say, yeah, it 492 00:24:38,920 --> 00:24:41,480 Speaker 1: looks like they reduced death for a time again for 493 00:24:41,560 --> 00:24:44,560 Speaker 1: a time, but it has not been proven in a 494 00:24:44,560 --> 00:24:47,320 Speaker 1: clinical trial that these reduced deaths. How certain are we 495 00:24:47,359 --> 00:24:52,720 Speaker 1: in the question of delta variant versus vaccine failure as 496 00:24:52,760 --> 00:24:56,320 Speaker 1: the cause of the surge right now? Is it just 497 00:24:56,520 --> 00:25:00,320 Speaker 1: the unvaccinator getting whacked with delta all over the place? No, again, my, 498 00:25:00,560 --> 00:25:02,720 Speaker 1: and and this is a really complicated this is there's 499 00:25:02,760 --> 00:25:05,840 Speaker 1: like immunology in this question. There's a very complicated technical 500 00:25:05,920 --> 00:25:08,960 Speaker 1: questions here that are sort of above my paygrade. But my, 501 00:25:09,720 --> 00:25:12,439 Speaker 1: but smart people I talked to say, it looks to 502 00:25:12,480 --> 00:25:15,679 Speaker 1: them like it's not that the delta variant is so 503 00:25:15,760 --> 00:25:17,480 Speaker 1: much worse, it's that the vaccine has just happened to 504 00:25:17,480 --> 00:25:22,000 Speaker 1: be failing now the timing of it, that's that's right. Okay, 505 00:25:22,040 --> 00:25:26,800 Speaker 1: So you are right now suspended from Twitter for seven days. 506 00:25:27,040 --> 00:25:29,199 Speaker 1: This is the first time you've been suspended during the 507 00:25:29,240 --> 00:25:31,840 Speaker 1: eighteen months. No, I was so so since the Biden 508 00:25:31,880 --> 00:25:35,080 Speaker 1: administration had that press conference, since jem Posaki, you know, 509 00:25:35,200 --> 00:25:37,640 Speaker 1: put the list of twelve names. You mentioned that list, 510 00:25:37,680 --> 00:25:41,119 Speaker 1: which I don't think I was on, But since she 511 00:25:41,240 --> 00:25:44,879 Speaker 1: said that, Twitter has been much much harsher to me. 512 00:25:45,160 --> 00:25:48,000 Speaker 1: So Twitter suspending me for twelve hours is spending me 513 00:25:48,040 --> 00:25:50,360 Speaker 1: for twelve hours again. And then last week they suspended 514 00:25:50,400 --> 00:25:52,320 Speaker 1: me for a week, and they suspended me for a 515 00:25:52,359 --> 00:25:56,080 Speaker 1: week for a tweet that did nothing but report the 516 00:25:56,160 --> 00:26:00,399 Speaker 1: results of Adviser's pivotal clinical trial about the vaccine. I 517 00:26:00,440 --> 00:26:03,679 Speaker 1: pointed out correctly. No one has said my information is 518 00:26:03,680 --> 00:26:07,320 Speaker 1: wrong because it's not that fifteen people who received the 519 00:26:07,400 --> 00:26:11,760 Speaker 1: vaccine died and fourteen people who received placebo died in 520 00:26:11,800 --> 00:26:15,240 Speaker 1: that clinical trial, not of COVID, of all causes, right, Okay, 521 00:26:15,320 --> 00:26:19,720 Speaker 1: So if you're hoping that the vaccine reduces all cause mortality, 522 00:26:19,760 --> 00:26:22,200 Speaker 1: that it actually prevents death, which is a whole point 523 00:26:22,240 --> 00:26:25,000 Speaker 1: of all of this. I thought you cannot find that 524 00:26:25,119 --> 00:26:27,960 Speaker 1: data in that clinical trial, and that is the trial 525 00:26:28,080 --> 00:26:31,320 Speaker 1: that is the reason these vaccines got the emergency, youth oppostion, 526 00:26:31,600 --> 00:26:34,280 Speaker 1: what happens? Do you think that Twitter is going to banu? 527 00:26:34,480 --> 00:26:36,760 Speaker 1: And if they do, how would you tell people? Obviously 528 00:26:36,800 --> 00:26:38,639 Speaker 1: they're listening to you on the radio show right now, 529 00:26:38,640 --> 00:26:40,359 Speaker 1: but how would people how would you tell people to 530 00:26:40,440 --> 00:26:42,280 Speaker 1: be able to consume what you put out? So the 531 00:26:42,280 --> 00:26:44,240 Speaker 1: best way to find me right now is on substack. 532 00:26:44,320 --> 00:26:46,800 Speaker 1: So again this is it's sort of a new platform. 533 00:26:47,080 --> 00:26:51,040 Speaker 1: It's called substack. Sub st a c K. You just 534 00:26:51,080 --> 00:26:53,520 Speaker 1: put my name in ole experience in and you know 535 00:26:53,560 --> 00:26:56,639 Speaker 1: you'll find me alexperience in dot substack dot com. You 536 00:26:56,680 --> 00:26:59,160 Speaker 1: can sign up for free. You know, almost one hundred 537 00:26:59,160 --> 00:27:01,159 Speaker 1: thousand people have now signed up, mostly just in the 538 00:27:01,240 --> 00:27:03,880 Speaker 1: last couple of weeks. People are clearly aware that I'm 539 00:27:03,960 --> 00:27:07,680 Speaker 1: on very finnice on Twitter. You can also pay. Basically 540 00:27:07,720 --> 00:27:09,480 Speaker 1: you're going to get the same content if you pay 541 00:27:09,600 --> 00:27:11,679 Speaker 1: or if you don't. In fact, I've been frankly shocked 542 00:27:11,720 --> 00:27:14,720 Speaker 1: how many people are willing to pay. Uh. They clearly, 543 00:27:15,000 --> 00:27:17,160 Speaker 1: you know, they think that what I'm doing has some value, 544 00:27:17,440 --> 00:27:19,719 Speaker 1: and so they're paying for what they can get mostly 545 00:27:19,800 --> 00:27:22,320 Speaker 1: for free. Um, which is which is but you know 546 00:27:22,320 --> 00:27:28,199 Speaker 1: which is support your work yourself? There you go, well, 547 00:27:28,240 --> 00:27:31,920 Speaker 1: thank you, thank you buck. Um so so so. Assuming 548 00:27:31,920 --> 00:27:35,560 Speaker 1: Twitter lets me back on tomorrow, Um, you know, I 549 00:27:35,600 --> 00:27:38,200 Speaker 1: am going to figure out what my options are because 550 00:27:38,280 --> 00:27:41,639 Speaker 1: I I'm not going to tweet with a sword, you know, 551 00:27:41,680 --> 00:27:44,159 Speaker 1: hanging over my head. I'm gonna I'm gonna tweet what 552 00:27:44,240 --> 00:27:46,480 Speaker 1: I want to tweet, and I need to make sure 553 00:27:46,600 --> 00:27:49,239 Speaker 1: that Twitter is aware of that. And you know, if 554 00:27:49,240 --> 00:27:50,879 Speaker 1: they're not okay with that, then I guess I'll have 555 00:27:50,880 --> 00:27:53,560 Speaker 1: to consider my legal options. Another thing that we are told, 556 00:27:53,760 --> 00:27:56,720 Speaker 1: and it's one of these it's like, you know, the 557 00:27:56,840 --> 00:27:59,600 Speaker 1: hamster hitting the pedal to get the little pellet, you 558 00:27:59,600 --> 00:28:01,800 Speaker 1: know what I mean. It's it's just this is your response. 559 00:28:01,800 --> 00:28:05,040 Speaker 1: It's supposed to be you. If you get the shot, 560 00:28:05,440 --> 00:28:09,560 Speaker 1: you're going to basically just be fine, you know, even 561 00:28:09,600 --> 00:28:11,920 Speaker 1: if you show up. Because originally they did say that 562 00:28:11,960 --> 00:28:14,440 Speaker 1: it was going to prevent transmission, and now they've gone 563 00:28:14,440 --> 00:28:16,760 Speaker 1: back on that. That That is a fact that as a reality, 564 00:28:17,040 --> 00:28:19,240 Speaker 1: this data out of what was it to cape cod 565 00:28:19,520 --> 00:28:22,560 Speaker 1: the big party and the Delta variant and now okay, 566 00:28:22,600 --> 00:28:24,600 Speaker 1: well now you can get it. And in fact, there 567 00:28:24,600 --> 00:28:27,280 Speaker 1: were headlines a few days ago saying that if you 568 00:28:27,359 --> 00:28:31,200 Speaker 1: have a breakthrough, infection you're actually as likely to transmit 569 00:28:31,240 --> 00:28:34,040 Speaker 1: it as somebody, which again seems like a complete moving 570 00:28:34,040 --> 00:28:36,520 Speaker 1: of the goal post on this, But it sounds like 571 00:28:36,520 --> 00:28:40,920 Speaker 1: what you're telling us is that it's just not really provable. 572 00:28:41,240 --> 00:28:43,040 Speaker 1: I mean, do you do you believe that it's not 573 00:28:43,120 --> 00:28:46,600 Speaker 1: the case that for somebody that that if you get 574 00:28:46,640 --> 00:28:49,320 Speaker 1: the shot, whoever you are, whoever you may be, you're 575 00:28:49,440 --> 00:28:51,920 Speaker 1: much less likely to end up in the hospital and 576 00:28:52,160 --> 00:28:54,520 Speaker 1: or die from this from COVID. Is that really is 577 00:28:54,520 --> 00:28:57,000 Speaker 1: that where we are now pretty definitively based on the data. 578 00:28:57,680 --> 00:28:59,240 Speaker 1: That's a little bit of a that's too much. So 579 00:28:59,240 --> 00:29:01,840 Speaker 1: it sounds where so so the smart, the really smart 580 00:29:02,000 --> 00:29:04,680 Speaker 1: people who you know, who are who are not you know, fauci, 581 00:29:04,680 --> 00:29:06,880 Speaker 1: who are not sort of like you have to get 582 00:29:06,920 --> 00:29:08,840 Speaker 1: the vaccine tomorrow, who look at the data where they 583 00:29:08,880 --> 00:29:12,240 Speaker 1: disagree with me is they would say it still looks 584 00:29:12,280 --> 00:29:16,400 Speaker 1: like there's decent efficacy here against severe illness and death 585 00:29:16,840 --> 00:29:18,880 Speaker 1: and um and so. And if you look at the 586 00:29:18,880 --> 00:29:21,320 Speaker 1: clinical trial, what the clinical rail did show is that 587 00:29:21,400 --> 00:29:24,160 Speaker 1: in this group of people, this group of relatively healthy 588 00:29:24,160 --> 00:29:27,080 Speaker 1: people who they tested the vaccine on, there were fewer 589 00:29:27,120 --> 00:29:30,520 Speaker 1: cases of what they called severe illness, which wasn't actually 590 00:29:30,560 --> 00:29:33,840 Speaker 1: that severe. It was basically for most people having low oxygen. 591 00:29:34,080 --> 00:29:38,360 Speaker 1: But okay, that's actually that's good. There's two problems with that. 592 00:29:39,000 --> 00:29:41,400 Speaker 1: One is, again it's this problem of how long does 593 00:29:41,400 --> 00:29:43,800 Speaker 1: it last? So you do have this period where you 594 00:29:43,840 --> 00:29:46,720 Speaker 1: get some protection, protection against the affection and everybody, that's 595 00:29:46,720 --> 00:29:49,200 Speaker 1: what I meant is if the vaccine fails, that's that 596 00:29:49,280 --> 00:29:51,800 Speaker 1: then are you know? I mean, it's right. So my 597 00:29:52,560 --> 00:29:54,440 Speaker 1: position on this, and what I said to them, to 598 00:29:54,800 --> 00:29:58,160 Speaker 1: these smart people I talked to, is you're assuming that 599 00:29:58,200 --> 00:30:01,320 Speaker 1: you can have partial failure and I have protection, and 600 00:30:01,560 --> 00:30:04,760 Speaker 1: I don't see great evidence for that in the real 601 00:30:04,800 --> 00:30:08,200 Speaker 1: world data. What I yes, So we'll come back and Clay, 602 00:30:08,200 --> 00:30:10,040 Speaker 1: do you have something real quick? No, No No, I'm gonna say, 603 00:30:10,040 --> 00:30:12,160 Speaker 1: we're gonna come back. We're gonna finish off the show. 604 00:30:12,200 --> 00:30:14,440 Speaker 1: If you're just in your car, if you're just listening 605 00:30:14,560 --> 00:30:17,240 Speaker 1: right now, encourage you to go listen to this entire discussion. 606 00:30:17,240 --> 00:30:19,680 Speaker 1: In the meantime, we got to save you some money. Absolutely, 607 00:30:19,680 --> 00:30:21,800 Speaker 1: a lot of homeowners don't understand the impact that a 608 00:30:21,840 --> 00:30:25,120 Speaker 1: refinance can actually have on their lives. I mean, just 609 00:30:25,160 --> 00:30:27,680 Speaker 1: think about this for a second. When you refinance. Using 610 00:30:27,720 --> 00:30:31,280 Speaker 1: American Financing, you could save up to a thousand dollars 611 00:30:31,440 --> 00:30:34,000 Speaker 1: a month. I mean, that's twelve thousand dollars a year. 612 00:30:34,160 --> 00:30:35,720 Speaker 1: Think about what you could do with that money the 613 00:30:35,800 --> 00:30:37,960 Speaker 1: credit card debt, you could pay down, you know, the 614 00:30:38,280 --> 00:30:41,080 Speaker 1: down payment on a car, a boat, or just pay down. 615 00:30:41,160 --> 00:30:43,880 Speaker 1: I mean, it's so important to save money these days, 616 00:30:43,960 --> 00:30:46,600 Speaker 1: especially given the uncertainty in the economy. And you can 617 00:30:46,640 --> 00:30:50,720 Speaker 1: do this just by using the right REFI with American 618 00:30:50,800 --> 00:30:53,480 Speaker 1: Financing I mean Clay, They'll lock you into a low rate, 619 00:30:53,520 --> 00:30:56,000 Speaker 1: could save you up to twelve grand a year. Twelve 620 00:30:56,080 --> 00:30:58,480 Speaker 1: grand a year. Think about how much difference a thousand 621 00:30:58,480 --> 00:31:01,920 Speaker 1: dollars extra month for you could be. It's an incredible 622 00:31:01,960 --> 00:31:04,320 Speaker 1: low rate, some of the lowest in the history of 623 00:31:04,360 --> 00:31:06,480 Speaker 1: this country. You need to find out if you're making 624 00:31:06,480 --> 00:31:09,320 Speaker 1: the smart decision for you and your family. Call right now, 625 00:31:09,360 --> 00:31:13,520 Speaker 1: pull out your phone eight hundred seven seven seven eighty 626 00:31:13,600 --> 00:31:18,000 Speaker 1: one oh nine. That's eight hundred seven seven seven eighty 627 00:31:18,080 --> 00:31:22,160 Speaker 1: one oh nine, Or visit American Financing dot net, American 628 00:31:22,240 --> 00:31:26,640 Speaker 1: Financing MLS one eight two three three four www dot mls, 629 00:31:26,760 --> 00:31:31,479 Speaker 1: Consumer access dot org. How sorry driving? Call and let 630 00:31:31,600 --> 00:31:34,560 Speaker 1: us know At one eight hundred two eight two two 631 00:31:34,640 --> 00:31:39,600 Speaker 1: eight eight two Clay Travison, buck Sexton, Fundy EIB Network 632 00:31:48,120 --> 00:31:51,080 Speaker 1: walcome back in Clay Travis buck Sexton Show. Alex Berenson's 633 00:31:51,080 --> 00:31:53,680 Speaker 1: been in studio with us, great discussion. If you're just 634 00:31:53,720 --> 00:31:56,280 Speaker 1: hearing this part right now, encourage you to go listen 635 00:31:56,320 --> 00:31:57,840 Speaker 1: to the entire thing. You can check it out at 636 00:31:57,880 --> 00:32:02,360 Speaker 1: Clay and Buck dot com. Bucket, I Alex have been saying, hey, 637 00:32:02,440 --> 00:32:04,560 Speaker 1: to our parents, you should go get the vaccine if 638 00:32:04,600 --> 00:32:06,800 Speaker 1: you're over sixty five years old. You look at the data, 639 00:32:06,840 --> 00:32:10,760 Speaker 1: the mortality is much higher for older people. Even with 640 00:32:11,200 --> 00:32:14,200 Speaker 1: concerns about the vaccine, would you tell people sixty five 641 00:32:14,240 --> 00:32:16,360 Speaker 1: and over to get it? Yeah? Absolutely, I mean I've 642 00:32:16,360 --> 00:32:18,560 Speaker 1: said that all along, and you know, I think and 643 00:32:18,640 --> 00:32:20,640 Speaker 1: my mother, you know, months ago, asked me if she 644 00:32:20,840 --> 00:32:22,240 Speaker 1: or I mean, she told me she's gonna get and 645 00:32:22,280 --> 00:32:24,480 Speaker 1: say that that's good, go get it. You know you're seventy. 646 00:32:24,760 --> 00:32:27,480 Speaker 1: I'm not gonna say hell old you, but um, but yeah, 647 00:32:27,560 --> 00:32:29,440 Speaker 1: she she doesn't look a day over fifty, by the 648 00:32:29,600 --> 00:32:37,000 Speaker 1: yantastic exactly. So anyway, yes, and even now with this, 649 00:32:37,120 --> 00:32:39,240 Speaker 1: you know, is sort of the somewhat depressing data out 650 00:32:39,240 --> 00:32:41,640 Speaker 1: of Israel. It still looks like the vaccines are a 651 00:32:41,680 --> 00:32:44,120 Speaker 1: better bet than not for older people. And you know, 652 00:32:44,200 --> 00:32:45,840 Speaker 1: I've never been in this camp. You know there's people 653 00:32:45,840 --> 00:32:48,320 Speaker 1: five G and graphine and oxide and this is a 654 00:32:48,400 --> 00:32:52,040 Speaker 1: depopulation campaign. One of the reasons these the Fauciites and 655 00:32:52,240 --> 00:32:54,440 Speaker 1: you know, my old employer, you know at the Times 656 00:32:54,440 --> 00:32:56,600 Speaker 1: and all these people hate me so much is you 657 00:32:56,640 --> 00:32:59,040 Speaker 1: can't dismiss me as a conspiracy nut because I'm not 658 00:32:59,080 --> 00:33:01,520 Speaker 1: a conspiracy don't look at the data that's allowing it 659 00:33:01,560 --> 00:33:03,840 Speaker 1: to tell a story. That's that's right. One more question 660 00:33:03,880 --> 00:33:05,400 Speaker 1: on the data here. We got a lot of this 661 00:33:05,520 --> 00:33:08,160 Speaker 1: people reaching out. Do we why do we not know 662 00:33:08,200 --> 00:33:10,560 Speaker 1: how many people have natural immunity? Because there's a positive 663 00:33:10,560 --> 00:33:12,960 Speaker 1: side here, which is natural immunity like Buck and iye 664 00:33:12,960 --> 00:33:16,080 Speaker 1: have because we both got COVID seems to provide the 665 00:33:16,080 --> 00:33:19,280 Speaker 1: best possible immunity going forward. Yet we don't know how 666 00:33:19,280 --> 00:33:21,640 Speaker 1: many people actually have had COVID in the United States. 667 00:33:21,720 --> 00:33:24,160 Speaker 1: That's four studies. That's a great question. You know in 668 00:33:24,480 --> 00:33:27,000 Speaker 1: other countries they know even in India, Okay, in India 669 00:33:27,040 --> 00:33:29,920 Speaker 1: they've done four thirds basically of Indians have had COVID. 670 00:33:29,920 --> 00:33:32,320 Speaker 1: Now that's right, and that's up from you know, like 671 00:33:32,360 --> 00:33:36,040 Speaker 1: ten percent at this time two in England have either 672 00:33:36,080 --> 00:33:38,760 Speaker 1: had COVID or they've had the vaccine. We don't know 673 00:33:38,760 --> 00:33:40,800 Speaker 1: those numbers in the unity. That's right. And you know, 674 00:33:41,200 --> 00:33:43,480 Speaker 1: again I'm not a conspiracy theorist, but that's one of 675 00:33:43,520 --> 00:33:45,840 Speaker 1: those questions that doesn't have a good answer, like why 676 00:33:46,280 --> 00:33:48,640 Speaker 1: haven't they told us how many people have gotten this 677 00:33:48,680 --> 00:33:51,280 Speaker 1: and recovered? We should have been doing those studies. I mean, 678 00:33:51,320 --> 00:33:52,920 Speaker 1: you can find tweets from me saying we need to 679 00:33:52,960 --> 00:33:57,920 Speaker 1: do it's called the Urology Study eighteen again seventeen now 680 00:33:57,960 --> 00:34:01,240 Speaker 1: months ago, back in April twelve, twenty twenty, and why 681 00:34:01,280 --> 00:34:04,160 Speaker 1: we haven't done that New York back when they did 682 00:34:04,160 --> 00:34:05,640 Speaker 1: it in June, I think it was a twenty twenty 683 00:34:05,720 --> 00:34:08,319 Speaker 1: said that was twenty percent and that was now well 684 00:34:08,360 --> 00:34:10,560 Speaker 1: over a year ago, and that was before the huge 685 00:34:10,560 --> 00:34:12,440 Speaker 1: wave we had through the winter. We had the all 686 00:34:12,480 --> 00:34:15,560 Speaker 1: time records hitting. So clearly there's there should be a 687 00:34:15,600 --> 00:34:17,560 Speaker 1: greater interest in that. But but I want to know 688 00:34:17,640 --> 00:34:20,080 Speaker 1: what you think now. I mean, let's say we could 689 00:34:20,120 --> 00:34:23,680 Speaker 1: get Alex Barnson to walk into the Biden oval office 690 00:34:23,800 --> 00:34:27,040 Speaker 1: right now and they would have to listen. They would 691 00:34:27,120 --> 00:34:30,359 Speaker 1: have to hear you out. What do you think they 692 00:34:30,400 --> 00:34:33,120 Speaker 1: should do right now? I mean, it's completely clear what 693 00:34:33,160 --> 00:34:35,080 Speaker 1: they should do. They should encourage the you know, there's 694 00:34:35,120 --> 00:34:37,640 Speaker 1: the sort of rump of people who are at high 695 00:34:37,719 --> 00:34:40,120 Speaker 1: risk and haven't been vaccinated to be vaccinating. That's you know, 696 00:34:40,160 --> 00:34:43,080 Speaker 1: that's some older people, and it's you know, listen, if 697 00:34:43,120 --> 00:34:46,320 Speaker 1: you're four hundred pounds probably you know, although obesity is 698 00:34:46,320 --> 00:34:48,480 Speaker 1: a big oh, it's a huge factor and it hasn't 699 00:34:48,480 --> 00:34:51,000 Speaker 1: been talked about that more. Yes, that's exactly right. So 700 00:34:51,000 --> 00:34:53,360 Speaker 1: so you know, listen fout she was around for HIV 701 00:34:53,640 --> 00:34:57,719 Speaker 1: and in the eighties, the the infectiousness. These specialists lied. 702 00:34:57,960 --> 00:34:59,759 Speaker 1: They said, you know, you can get this if you're 703 00:34:59,760 --> 00:35:01,640 Speaker 1: a or a sexual woman and you have sex with 704 00:35:01,719 --> 00:35:03,920 Speaker 1: the wrong guy one time, you know, you can get this. 705 00:35:04,000 --> 00:35:06,560 Speaker 1: It was they knew they were lying. They were afraid 706 00:35:06,600 --> 00:35:09,080 Speaker 1: the disease would be stigmatized, and something like that is 707 00:35:09,120 --> 00:35:12,959 Speaker 1: happening on a much broader level with much bigger consequences 708 00:35:13,080 --> 00:35:15,560 Speaker 1: right now. So there's there's several things we should do. 709 00:35:16,000 --> 00:35:18,799 Speaker 1: We should encourage those people who are not vaccinated to 710 00:35:18,880 --> 00:35:24,000 Speaker 1: be vaccinated. That's right, that's right on the we should 711 00:35:24,040 --> 00:35:27,759 Speaker 1: figure out what multiple doses mean and what they look like, 712 00:35:27,800 --> 00:35:30,239 Speaker 1: because those people it looks like are gonna need to 713 00:35:30,280 --> 00:35:35,120 Speaker 1: be vaccinated a third time. And why would you assume 714 00:35:35,200 --> 00:35:37,600 Speaker 1: that the third dose is the one that fixes everything 715 00:35:37,680 --> 00:35:40,400 Speaker 1: for them? Okay, the second thing they need to do 716 00:35:40,600 --> 00:35:43,719 Speaker 1: is just turned down the fear. Drop the masks. They 717 00:35:43,760 --> 00:35:48,480 Speaker 1: don't work, they don't do anything. Just let everybody live, Okay. 718 00:35:48,840 --> 00:35:52,000 Speaker 1: Fifteen years ago a really good paper about this by 719 00:35:52,000 --> 00:35:54,560 Speaker 1: the guy who did more to eradicate smallpox than anyone 720 00:35:54,560 --> 00:35:58,440 Speaker 1: else in the world said, get back to normal. Communities 721 00:35:58,520 --> 00:36:02,120 Speaker 1: function better for a normal when people have normal life. 722 00:36:02,120 --> 00:36:08,800 Speaker 1: And three, get the schools open normally. No mask, no nothing. 723 00:36:08,880 --> 00:36:12,840 Speaker 1: We have punished our kids enough. It's craziness. Alex uh 724 00:36:12,920 --> 00:36:16,480 Speaker 1: your substack people, just go find it. Alex Barrenson on substack. 725 00:36:16,840 --> 00:36:18,759 Speaker 1: I got a substack dot com Stack dot com put 726 00:36:18,800 --> 00:36:22,160 Speaker 1: my name in and hopefully Twitter won't ban me if 727 00:36:22,200 --> 00:36:25,319 Speaker 1: they do. You know what if in the end you 728 00:36:25,400 --> 00:36:28,960 Speaker 1: come hang hang out with us there. It's a few 729 00:36:28,960 --> 00:36:31,000 Speaker 1: million of our best friends there. You go hang out 730 00:36:31,040 --> 00:36:33,399 Speaker 1: with us anytime, appreciating you so much. Spending an hour 731 00:36:33,480 --> 00:36:36,040 Speaker 1: here with us in a deep dive and I like that, Clay. 732 00:36:36,040 --> 00:36:38,080 Speaker 1: I mean, let's we're gonna get through it. We're gonna 733 00:36:38,080 --> 00:36:39,960 Speaker 1: be all right, it's gonna be okay, everybody. You know, 734 00:36:40,000 --> 00:36:41,640 Speaker 1: we're gonna get We're gonna have to fight some of 735 00:36:41,640 --> 00:36:43,520 Speaker 1: the crazies on some of this stuff. We will get 736 00:36:43,520 --> 00:36:45,880 Speaker 1: back to NORMA have to get back to normalcy, and 737 00:36:45,960 --> 00:36:48,560 Speaker 1: we have to let the data drive us. And I 738 00:36:48,560 --> 00:36:50,640 Speaker 1: appreciate Alex coming in and talking to all of us. 739 00:36:50,719 --> 00:36:52,359 Speaker 1: This is one reason you and I wanted to take 740 00:36:52,400 --> 00:36:55,719 Speaker 1: a show like this, because there's so few places where 741 00:36:55,719 --> 00:36:58,920 Speaker 1: you can get honest discussion and truth in the world 742 00:36:58,960 --> 00:37:01,040 Speaker 1: that we live in today. And I think again, if 743 00:37:01,040 --> 00:37:02,640 Speaker 1: you just heard part of that, I'd encourage you to 744 00:37:02,680 --> 00:37:04,799 Speaker 1: go listen to all of it from Alex. We're gonna 745 00:37:04,920 --> 00:37:08,400 Speaker 1: keep giving people facts and letting them make rational decisions. 746 00:37:08,400 --> 00:37:10,280 Speaker 1: I know it's wild. I know it's great show already 747 00:37:10,280 --> 00:37:13,400 Speaker 1: Tomorrow sendat to Marsha Blackburn of Clay's home state of Tennessee, 748 00:37:13,400 --> 00:37:15,399 Speaker 1: will be with us. We'll talk the border, we'll talk 749 00:37:15,440 --> 00:37:22,080 Speaker 1: COVID and more with you all. Then you're listening to Clay, 750 00:37:22,160 --> 00:37:25,640 Speaker 1: Travis and Buck Sexton on the EIB Network