1 00:00:15,396 --> 00:00:22,756 Speaker 1: Pushkin from Pushkin Industries. This is Deep Background, the show 2 00:00:22,796 --> 00:00:25,956 Speaker 1: where we explore the stories behind the stories in the news. 3 00:00:26,476 --> 00:00:31,756 Speaker 1: I'm Noah Feldman. Research into the novel Coronavirus is happening 4 00:00:32,276 --> 00:00:37,436 Speaker 1: and being published or sometimes just press released at breakneck speed. 5 00:00:38,116 --> 00:00:41,796 Speaker 1: Every few weeks, we hear about a possible new breakthrough 6 00:00:41,916 --> 00:00:45,516 Speaker 1: or a potentially interesting avenue of research. But often that 7 00:00:45,556 --> 00:00:47,836 Speaker 1: breakthrough it turns out to be too good to be true, 8 00:00:48,316 --> 00:00:50,836 Speaker 1: or to have less effect than we might have imagined. 9 00:00:51,476 --> 00:00:54,156 Speaker 1: To help us make sense of the latest about the 10 00:00:54,196 --> 00:00:57,596 Speaker 1: novel coronavirus, which studies to watch, which studies are too 11 00:00:57,596 --> 00:01:00,236 Speaker 1: soon to interpret, and where we are in the progress 12 00:01:00,276 --> 00:01:04,996 Speaker 1: towards a vaccine, We're joined by doctor Sad Omer. Doctor 13 00:01:04,996 --> 00:01:09,436 Speaker 1: Omer is a professor of infectious disease and epidemiology at 14 00:01:09,436 --> 00:01:12,116 Speaker 1: the Yale School of Medicine and at the Yale School 15 00:01:12,116 --> 00:01:15,836 Speaker 1: of Public Health. He's also director of the Yale Institute 16 00:01:15,916 --> 00:01:19,476 Speaker 1: for Global Health. In short, he's perfectly qualified to talk 17 00:01:19,476 --> 00:01:25,356 Speaker 1: about these questions. So thank you so much for joining me. 18 00:01:25,396 --> 00:01:28,276 Speaker 1: I'm very grateful. I wonder if we could begin with 19 00:01:28,356 --> 00:01:32,836 Speaker 1: some of the latest publicized developments in therapy. There's a 20 00:01:32,916 --> 00:01:36,036 Speaker 1: large randomized study out of the UK, which we only 21 00:01:36,076 --> 00:01:38,316 Speaker 1: see in so far in press release form, although we're 22 00:01:38,316 --> 00:01:41,996 Speaker 1: getting used to that, involving the use of the steroid dexamethasone. 23 00:01:42,676 --> 00:01:45,316 Speaker 1: What is your takeaway from that study. It's a very 24 00:01:45,556 --> 00:01:50,276 Speaker 1: encouraging study for several reasons. First of all, from the protocol, 25 00:01:50,756 --> 00:01:54,436 Speaker 1: it seems that it was a well conducted study. They 26 00:01:54,556 --> 00:01:58,556 Speaker 1: showed an impact on mortality, not on everyone, but those 27 00:01:58,596 --> 00:02:01,636 Speaker 1: who were on vents. The third thing is that it's 28 00:02:01,676 --> 00:02:04,956 Speaker 1: a widely available drug. So whenever you are dealing with 29 00:02:04,996 --> 00:02:10,196 Speaker 1: these public health emergencies, one concern, one major n is equity. 30 00:02:10,876 --> 00:02:13,876 Speaker 1: At least in the initial few months after a drug 31 00:02:13,956 --> 00:02:18,196 Speaker 1: is evaluated successfully or it comes out, etc. You're really 32 00:02:18,236 --> 00:02:22,596 Speaker 1: concerned about getting that to the most vulnerable. Since this 33 00:02:22,716 --> 00:02:28,316 Speaker 1: is a widely used drug already, we have broader availability. 34 00:02:28,356 --> 00:02:32,356 Speaker 1: So that's the good news. The caveat, as you pointed out, 35 00:02:32,676 --> 00:02:35,036 Speaker 1: is that all we know at this point is a 36 00:02:35,076 --> 00:02:39,156 Speaker 1: press release, a press release from a credible group. But look, 37 00:02:39,196 --> 00:02:43,396 Speaker 1: I would like to see at least data, maybe not 38 00:02:44,076 --> 00:02:46,956 Speaker 1: a full flash paper, but they worst probably somewhere some 39 00:02:47,116 --> 00:02:50,756 Speaker 1: discussion at their data Safety Monitoring board or somewhere where 40 00:02:50,796 --> 00:02:54,396 Speaker 1: they presented those slides. At least share those slides. Now. 41 00:02:54,476 --> 00:02:58,116 Speaker 1: I understand that there's a lot of time pressure on investigators, 42 00:02:58,116 --> 00:03:00,476 Speaker 1: but if the data are good enough to be shared 43 00:03:00,476 --> 00:03:03,116 Speaker 1: publicly in a press release, they should be good enough 44 00:03:03,156 --> 00:03:07,156 Speaker 1: to be shared more broadly. The effect on mortality on 45 00:03:07,276 --> 00:03:11,276 Speaker 1: deaths reported in a press lease was a one third 46 00:03:11,356 --> 00:03:13,636 Speaker 1: reduction for those people who were so sick that they 47 00:03:13,636 --> 00:03:16,716 Speaker 1: were on ventilators, and I believe a one in five 48 00:03:16,916 --> 00:03:19,956 Speaker 1: reduction in deaths for those who were sick enough to 49 00:03:19,996 --> 00:03:23,476 Speaker 1: be on oxygen but not oxygen delivered via a ventilator. 50 00:03:24,116 --> 00:03:25,876 Speaker 1: And then for those who were very sick and in 51 00:03:25,916 --> 00:03:30,476 Speaker 1: the hospital but we're not on oxygen, they reported no effect. Obviously, 52 00:03:30,516 --> 00:03:32,676 Speaker 1: I'm asking you to reconstruct something that's not so simple 53 00:03:32,676 --> 00:03:36,196 Speaker 1: to reconstruct. But why would one have expected those sorts 54 00:03:36,236 --> 00:03:41,876 Speaker 1: of results specifically from this treatment. Yeah. So, look, we 55 00:03:42,036 --> 00:03:45,836 Speaker 1: are learning about the disease as we go along, and 56 00:03:45,916 --> 00:03:50,396 Speaker 1: sometimes what works in terms of treatment tells you as 57 00:03:50,476 --> 00:03:52,276 Speaker 1: much about the disease as it tells you about the 58 00:03:52,316 --> 00:03:56,036 Speaker 1: intervention itself. But in this case, and you know, these 59 00:03:56,076 --> 00:04:01,716 Speaker 1: results combined with our previous current understanding of what's happening 60 00:04:02,076 --> 00:04:05,036 Speaker 1: with the patient with the individual after you get the disease, 61 00:04:05,996 --> 00:04:12,356 Speaker 1: is that there is this maladaptation and then this exaggerated 62 00:04:12,476 --> 00:04:17,036 Speaker 1: response of the immune system. And so the contrast is 63 00:04:17,156 --> 00:04:20,276 Speaker 1: higher when you have an intervention that is attacking the 64 00:04:20,396 --> 00:04:26,396 Speaker 1: condition by dampening broadly the immune response at a stage 65 00:04:26,396 --> 00:04:31,356 Speaker 1: when it's exaggerated. So that contrast would be highlighted in 66 00:04:31,516 --> 00:04:35,436 Speaker 1: more severe patients because, for example, the cytokine storm is 67 00:04:35,476 --> 00:04:38,036 Speaker 1: happening in more severe patients, So if you're attacking that, 68 00:04:38,036 --> 00:04:40,276 Speaker 1: that's where the contrast is. So that would be in 69 00:04:40,476 --> 00:04:45,756 Speaker 1: line with these results, and that's because steroids are broadly 70 00:04:45,796 --> 00:04:50,436 Speaker 1: speaking anti inflammatory, but maybe going on in these most 71 00:04:50,476 --> 00:04:54,596 Speaker 1: sick patients is some kind of the cytokinde storm, which 72 00:04:54,636 --> 00:05:00,276 Speaker 1: is a kind of exaggerated immune reaction, exaggerated maladaptive. So 73 00:05:00,356 --> 00:05:03,396 Speaker 1: it's not just the quantity of the immune response, but 74 00:05:03,476 --> 00:05:07,876 Speaker 1: the type of immune response. But but essentially focusing on 75 00:05:07,916 --> 00:05:11,076 Speaker 1: the type of response and the quantity of response and 76 00:05:11,156 --> 00:05:15,036 Speaker 1: sometimes dampening it broadly speaking can have these benefits. So 77 00:05:15,116 --> 00:05:17,876 Speaker 1: that would explain it. So if I just to make 78 00:05:17,876 --> 00:05:21,956 Speaker 1: sure I'm understanding you correctly, because the sicker patients actually 79 00:05:21,996 --> 00:05:27,876 Speaker 1: benefited proportionally more from the steroidal intervention that provides some 80 00:05:27,916 --> 00:05:30,436 Speaker 1: indication that at least in those very very sick patients, 81 00:05:30,756 --> 00:05:32,596 Speaker 1: what's going on is the kind of thing that might 82 00:05:32,596 --> 00:05:37,156 Speaker 1: be responsive to steroids and therefore fits the theory argued 83 00:05:37,156 --> 00:05:39,476 Speaker 1: for by some of your colleagues at Yale and others 84 00:05:39,956 --> 00:05:43,916 Speaker 1: of the cytokind storm. Yeah, exactly. Let me ask you 85 00:05:43,956 --> 00:05:49,156 Speaker 1: about this large genome wide association study that's being reported 86 00:05:49,236 --> 00:05:51,516 Speaker 1: on in Europe. Again, I think we don't have the 87 00:05:51,596 --> 00:05:55,636 Speaker 1: full final paper yet in which an argument is being 88 00:05:55,676 --> 00:06:01,276 Speaker 1: made for an association of blood type, surprisingly enough with 89 00:06:01,476 --> 00:06:05,276 Speaker 1: probability of suffering from COVID, not exposure to the virus, 90 00:06:05,276 --> 00:06:07,956 Speaker 1: but suffering from the disease if you are exposed to 91 00:06:07,956 --> 00:06:10,516 Speaker 1: the virus. And then there's it's not the blood type itself, 92 00:06:10,596 --> 00:06:13,116 Speaker 1: according to the theory, at least, it's a some set 93 00:06:13,116 --> 00:06:16,796 Speaker 1: of genes that are associated with the same gene area 94 00:06:16,956 --> 00:06:19,476 Speaker 1: as the blood type. If I'm getting it right, say 95 00:06:19,476 --> 00:06:22,356 Speaker 1: a word about that place. From my perspective, it's too 96 00:06:22,436 --> 00:06:27,996 Speaker 1: early to say anything definitive about this. It's a signal generation. 97 00:06:28,116 --> 00:06:30,036 Speaker 1: I think there needs to be a lot more work 98 00:06:30,556 --> 00:06:33,076 Speaker 1: to look at. First of all, if the signal is 99 00:06:33,116 --> 00:06:35,516 Speaker 1: credible because a lot of times when you do these 100 00:06:35,516 --> 00:06:41,116 Speaker 1: observational studies in sick patients, you're not able to match 101 00:06:41,396 --> 00:06:45,716 Speaker 1: appropriately you control for underlying confounding and so therefore that's 102 00:06:45,756 --> 00:06:47,596 Speaker 1: one of the reasons we would like to see more 103 00:06:47,636 --> 00:06:51,076 Speaker 1: detailed data, etc. To figure that out. I think this 104 00:06:51,116 --> 00:06:54,316 Speaker 1: one is too early to say anything definitively. I think 105 00:06:54,316 --> 00:06:57,756 Speaker 1: it's certainly something that needs to be followed up that 106 00:06:57,876 --> 00:07:01,676 Speaker 1: could have further implications. So I would put it in 107 00:07:01,716 --> 00:07:05,596 Speaker 1: the bucket of signal generation more than or hypothesis generation 108 00:07:05,716 --> 00:07:08,836 Speaker 1: more than anything beyond that. It was fascinating to me 109 00:07:08,876 --> 00:07:11,076 Speaker 1: because it reminded me of some of the other high 110 00:07:11,156 --> 00:07:15,356 Speaker 1: profile GA genome white association studies, where you know, the 111 00:07:15,436 --> 00:07:18,756 Speaker 1: researchers look potentially at hundreds of thousands in some cases 112 00:07:19,156 --> 00:07:22,356 Speaker 1: of people with some condition and then they just literally 113 00:07:22,436 --> 00:07:24,916 Speaker 1: mind the data, which is what scientists we're supposed to 114 00:07:24,956 --> 00:07:26,636 Speaker 1: not do in the bad old days or maybe the 115 00:07:26,636 --> 00:07:28,916 Speaker 1: good old days, and they say, well, we're minding the data, 116 00:07:28,956 --> 00:07:30,756 Speaker 1: and here's what we see. You know, these are these 117 00:07:30,796 --> 00:07:33,396 Speaker 1: associations that we find in the data, and therefore they 118 00:07:33,476 --> 00:07:35,596 Speaker 1: must have some effect, and now let's try to figure 119 00:07:35,596 --> 00:07:38,156 Speaker 1: out what that effect is it's sort of the opposite 120 00:07:38,196 --> 00:07:39,676 Speaker 1: of what we were all taught. The scientific method is 121 00:07:39,716 --> 00:07:42,716 Speaker 1: supposed to be, and yet it has caught on as 122 00:07:42,716 --> 00:07:46,636 Speaker 1: a real methodology, and it often yields fascinating things. But 123 00:07:46,636 --> 00:07:48,756 Speaker 1: of course there's some statistical reason to think that some 124 00:07:48,876 --> 00:07:52,316 Speaker 1: things should be yielded anyway. Yeah. No, So here's the 125 00:07:52,556 --> 00:07:58,596 Speaker 1: interesting thing DWAs. And big data techniques, whether applied directly 126 00:07:58,596 --> 00:08:02,236 Speaker 1: to biology, to or to other sources of data, give 127 00:08:02,236 --> 00:08:06,316 Speaker 1: you great power and for a lack of bettle example, 128 00:08:06,516 --> 00:08:10,956 Speaker 1: you know, i'd quote spider Man, power comes great responsibility. 129 00:08:11,196 --> 00:08:14,476 Speaker 1: Actually Voltaire said it before, but you know, you know 130 00:08:14,556 --> 00:08:17,276 Speaker 1: spider Man, or actually his uncle Ben said it with 131 00:08:17,436 --> 00:08:20,676 Speaker 1: more flair. So with this kind of these kinds of tools, 132 00:08:20,836 --> 00:08:26,116 Speaker 1: it's okay, it's reasonable to apply these tools, but a 133 00:08:26,156 --> 00:08:29,676 Speaker 1: lot of it is in what you do when you 134 00:08:29,796 --> 00:08:33,116 Speaker 1: find something. So if it's taken as a signal hypothesis 135 00:08:33,156 --> 00:08:37,316 Speaker 1: generation exercise to then do a sort of a hypothesis 136 00:08:37,356 --> 00:08:40,276 Speaker 1: testing set of studies, this kind of an approach can 137 00:08:40,316 --> 00:08:45,476 Speaker 1: add value. But if it is taken as hypothesis testing exercise, 138 00:08:46,076 --> 00:08:48,516 Speaker 1: then you get into some of those other issues that 139 00:08:48,596 --> 00:08:52,556 Speaker 1: you mentioned a little bit earlier. Two vaccines are getting 140 00:08:52,676 --> 00:08:56,236 Speaker 1: very close to trials that are going to tell us 141 00:08:56,236 --> 00:09:00,556 Speaker 1: probably whether they work or not. The Maderna vaccine RNA 142 00:09:00,636 --> 00:09:03,716 Speaker 1: based vaccine, and then the Oxford vaccine, which is a 143 00:09:03,796 --> 00:09:08,116 Speaker 1: trojan horse vaccine. These are both brand new techniques, neither 144 00:09:08,156 --> 00:09:10,436 Speaker 1: of which, according to guests I've had here before, has 145 00:09:10,436 --> 00:09:14,276 Speaker 1: ever generated a successful vaccine that went to market. Yet nevertheless, 146 00:09:14,316 --> 00:09:18,716 Speaker 1: we're all extremely excited and eagerly anticipating the results. Everyone 147 00:09:18,756 --> 00:09:21,196 Speaker 1: has some instinct about this. You're in a position to 148 00:09:21,236 --> 00:09:24,716 Speaker 1: actually have an intelligent instinct. What is your instinct about 149 00:09:24,716 --> 00:09:27,636 Speaker 1: these possible vaccines? So first of all, I add in 150 00:09:27,676 --> 00:09:30,436 Speaker 1: a little bit of nuance to these are two Western 151 00:09:30,556 --> 00:09:34,716 Speaker 1: vaccines that are two of the more prominent ones. There 152 00:09:34,756 --> 00:09:37,676 Speaker 1: are a couple of Chinese vaccines that we should keep 153 00:09:37,716 --> 00:09:40,956 Speaker 1: an eye out for and we should track. So one 154 00:09:41,076 --> 00:09:44,836 Speaker 1: is produced by the company's Signo vac and then the 155 00:09:44,956 --> 00:09:48,436 Speaker 1: other one is can sign on. But coming to these vaccines, 156 00:09:48,916 --> 00:09:52,556 Speaker 1: the Modern vaccine and the Oxford vaccine are some of 157 00:09:52,596 --> 00:09:56,236 Speaker 1: the earliest vaccines that are being evaluated or likely to 158 00:09:56,276 --> 00:09:59,596 Speaker 1: be evaluated in large trials. The Oxford vaccine has an 159 00:09:59,716 --> 00:10:02,996 Speaker 1: innovative trial design where they had a rolling Phase two 160 00:10:03,196 --> 00:10:08,556 Speaker 1: three trial where they have already enrolled a bunch of people, 161 00:10:09,356 --> 00:10:13,196 Speaker 1: not they're not close to their final sample size. And 162 00:10:13,556 --> 00:10:15,716 Speaker 1: one of the complications, one of the nuance that has 163 00:10:15,756 --> 00:10:19,236 Speaker 1: been added is that some of the earlier projections of 164 00:10:19,276 --> 00:10:22,836 Speaker 1: their timeline, as I understand, was based on the incidence 165 00:10:23,516 --> 00:10:28,156 Speaker 1: in the UK because that's where the main core of 166 00:10:28,196 --> 00:10:32,476 Speaker 1: the investigators is located. So that the disease incidence going 167 00:10:32,516 --> 00:10:35,636 Speaker 1: down seems to have complicated things a little bit. And 168 00:10:35,676 --> 00:10:38,436 Speaker 1: they are going to Brazil now to recruit, which is 169 00:10:39,036 --> 00:10:42,716 Speaker 1: very reasonable and this is how it should be done 170 00:10:43,236 --> 00:10:48,796 Speaker 1: in a pandemic. But the reason I'm highlighting this is, look, 171 00:10:49,396 --> 00:10:51,796 Speaker 1: this is one of the reasons why we should stay 172 00:10:51,796 --> 00:10:56,876 Speaker 1: away from predicting that the vaccine will be available in 173 00:10:57,036 --> 00:11:00,596 Speaker 1: three months. You can say that it will be available 174 00:11:00,916 --> 00:11:04,996 Speaker 1: in the near future or the prospects look good, because 175 00:11:04,996 --> 00:11:06,956 Speaker 1: there are a lot of things that can slow down 176 00:11:07,036 --> 00:11:10,636 Speaker 1: your development process. But coming back to your original questions, 177 00:11:10,636 --> 00:11:13,836 Speaker 1: so the main question that these are a new approaches, 178 00:11:14,676 --> 00:11:18,756 Speaker 1: I think they're based on pretty sound biology. Then there 179 00:11:18,836 --> 00:11:22,716 Speaker 1: should be in the front line of things where the 180 00:11:22,716 --> 00:11:28,236 Speaker 1: global community and national programs invest Having said that things 181 00:11:28,316 --> 00:11:33,236 Speaker 1: can go sideways you can have unexpected things. So what 182 00:11:33,276 --> 00:11:35,196 Speaker 1: do we do about that? A First of all, have 183 00:11:35,756 --> 00:11:40,676 Speaker 1: realistic expectations about the timelines. If they go early, that's great, 184 00:11:40,756 --> 00:11:43,276 Speaker 1: but we should all have a little bit of humility 185 00:11:43,316 --> 00:11:47,156 Speaker 1: about our projections, especially for new products. The other thing 186 00:11:47,436 --> 00:11:50,436 Speaker 1: is we should all hedge our bets. So it's a 187 00:11:50,476 --> 00:11:55,396 Speaker 1: good approach to have a diversity of technologies, some new, 188 00:11:54,996 --> 00:11:59,276 Speaker 1: some old. So having a couple of live attenuated products 189 00:11:59,356 --> 00:12:03,356 Speaker 1: in the mix, having a couple of recombinant vaccines in 190 00:12:03,396 --> 00:12:08,036 Speaker 1: the mix helps us even out that risk. And so 191 00:12:08,236 --> 00:12:13,276 Speaker 1: these are the few implications of having a vaccine program 192 00:12:13,836 --> 00:12:17,716 Speaker 1: or a vaccine development program that has a few new, novel, 193 00:12:17,836 --> 00:12:21,276 Speaker 1: innovative products. Can you say something about the two Chinese 194 00:12:21,356 --> 00:12:23,276 Speaker 1: vaccines that you mentioned, because those have not gotten the 195 00:12:23,276 --> 00:12:25,356 Speaker 1: same amount of coverage in the US media. But my 196 00:12:25,436 --> 00:12:28,836 Speaker 1: understanding is one of them is a live attenuated vaccine, 197 00:12:28,836 --> 00:12:32,156 Speaker 1: good old fashioned vaccine. Yeah, exactly. You take the virus 198 00:12:32,276 --> 00:12:37,596 Speaker 1: and you primarily through serial passage through culture, take away 199 00:12:37,916 --> 00:12:42,116 Speaker 1: the disease potential, but ideally maintain the replication potentials. So 200 00:12:42,156 --> 00:12:45,956 Speaker 1: that's the live attenuated vaccine. There's another vector vaccine that 201 00:12:46,116 --> 00:12:48,396 Speaker 1: is also in more advanced stages. So these are the 202 00:12:48,436 --> 00:12:52,436 Speaker 1: two vaccines that are ahead of the pack in China. 203 00:12:52,556 --> 00:12:56,516 Speaker 1: They also seem to have issues in terms of Phase 204 00:12:56,596 --> 00:13:00,316 Speaker 1: three trials because of the successful control they have achieved 205 00:13:00,796 --> 00:13:04,596 Speaker 1: in reducing the incidence of the virus in their own population. 206 00:13:05,436 --> 00:13:07,116 Speaker 1: One of the most important things I think that you 207 00:13:07,196 --> 00:13:10,636 Speaker 1: just said is that we need to realize that even 208 00:13:10,756 --> 00:13:14,476 Speaker 1: just running the trials can take longer than one expects. 209 00:13:14,516 --> 00:13:17,796 Speaker 1: Even if these are great, the durational issue isn't easily 210 00:13:17,836 --> 00:13:20,596 Speaker 1: manageable because these aren't challenge trials. No one is being 211 00:13:20,716 --> 00:13:25,076 Speaker 1: at this point intentionally exposed to stars Covy two virus. 212 00:13:25,356 --> 00:13:27,916 Speaker 1: There have been people who've talked about the value of 213 00:13:27,956 --> 00:13:30,956 Speaker 1: doing that. Under the circumstances, I have actually been opened. 214 00:13:30,956 --> 00:13:33,316 Speaker 1: I understand ethical challenges. I've been sort of opened to 215 00:13:33,356 --> 00:13:36,796 Speaker 1: the ethical argument that when many people are dying and 216 00:13:36,876 --> 00:13:39,156 Speaker 1: the economic effects are as great as they are, if 217 00:13:39,196 --> 00:13:41,996 Speaker 1: there's ever a time for challenge trials where people are 218 00:13:41,996 --> 00:13:44,596 Speaker 1: intentionally exposed, this is it. It sounds as though you're 219 00:13:44,636 --> 00:13:48,876 Speaker 1: not convinced, well, I'm actually I haven't made up my 220 00:13:48,956 --> 00:13:52,356 Speaker 1: mind in terms of specific challenge trials, And here's the 221 00:13:52,396 --> 00:13:56,036 Speaker 1: reason why I think they're a legitimate policy option that 222 00:13:56,116 --> 00:14:00,116 Speaker 1: should be explored. But in order to going forward with 223 00:14:00,276 --> 00:14:03,356 Speaker 1: an actual challenge trial, I think we need a few 224 00:14:03,396 --> 00:14:06,836 Speaker 1: more things, and I like the WHO approach, so they 225 00:14:07,036 --> 00:14:09,836 Speaker 1: issued ethical guidance about if to do it, this is 226 00:14:09,836 --> 00:14:14,476 Speaker 1: how you do it. It's not straightforward to do a 227 00:14:14,596 --> 00:14:17,756 Speaker 1: challenge studies because you have to have a standardized challenge 228 00:14:17,796 --> 00:14:21,796 Speaker 1: doors for humans, you have to have a more rigorous 229 00:14:22,036 --> 00:14:25,436 Speaker 1: set of protocols facilities. The ability to do that and 230 00:14:25,516 --> 00:14:29,076 Speaker 1: the ability to conduct challenge trials is actually way more 231 00:14:29,196 --> 00:14:33,356 Speaker 1: limited than to do efficacy trials throughout the world. So 232 00:14:33,396 --> 00:14:36,036 Speaker 1: there are fewer centers in the world that have done 233 00:14:36,116 --> 00:14:39,596 Speaker 1: human challenge studies. So obviously animal challenge studies are different. 234 00:14:40,156 --> 00:14:44,156 Speaker 1: And so one of the thinking that that is there, 235 00:14:44,356 --> 00:14:47,716 Speaker 1: which is not discussed too much in the public discourse 236 00:14:47,796 --> 00:14:52,756 Speaker 1: or discussion, is what is the added time gain if 237 00:14:52,836 --> 00:14:57,236 Speaker 1: you have to take these several steps that require you know, 238 00:14:57,316 --> 00:15:00,756 Speaker 1: some time to iron out. Having said that, you know, 239 00:15:00,876 --> 00:15:03,716 Speaker 1: developing it as a parallel policy option is very reasonable, 240 00:15:04,116 --> 00:15:07,356 Speaker 1: but it should be done with not just policy discussion, 241 00:15:07,796 --> 00:15:11,316 Speaker 1: but detailed call discussion. I want to ask you about 242 00:15:11,516 --> 00:15:15,876 Speaker 1: asymptomatic transmission as sort of our last topic of conversation. 243 00:15:16,356 --> 00:15:18,436 Speaker 1: I guess the question that I'm really interested in is 244 00:15:18,836 --> 00:15:23,596 Speaker 1: we all understand that there's droplet transmission from coughing sneezing. 245 00:15:24,076 --> 00:15:26,796 Speaker 1: We also understand that there is presumably some sort of 246 00:15:26,836 --> 00:15:32,516 Speaker 1: aerosolization transmission where the droplets are much much, much much tinier. 247 00:15:33,476 --> 00:15:35,116 Speaker 1: I think a lot of people are trying to figure 248 00:15:35,116 --> 00:15:38,636 Speaker 1: out how they should think about those two aspects of 249 00:15:38,636 --> 00:15:42,316 Speaker 1: transmission and what it means for masks. So within the 250 00:15:42,436 --> 00:15:46,196 Speaker 1: symptomatic they can be sort of different modes of transmission. 251 00:15:46,236 --> 00:15:49,076 Speaker 1: It could be from surfaces or full mites, mediums, large 252 00:15:49,076 --> 00:15:54,196 Speaker 1: sized droplets as well as small sort of aerosols. Although 253 00:15:54,196 --> 00:15:58,396 Speaker 1: that the data are being generated, there's a few things 254 00:15:58,436 --> 00:16:01,756 Speaker 1: to keep in mind. First of all, the classifying the 255 00:16:01,756 --> 00:16:06,236 Speaker 1: type of the size of droplet and the probability of 256 00:16:06,356 --> 00:16:10,796 Speaker 1: something being aerosolized versus not so. Hanging out in the 257 00:16:10,876 --> 00:16:13,716 Speaker 1: air for some periods and sort of transmitting through air 258 00:16:13,796 --> 00:16:16,916 Speaker 1: is different from aerosualization, which stays much longer in the air. 259 00:16:17,476 --> 00:16:20,996 Speaker 1: We do know that the risk of aerosolization is way 260 00:16:21,076 --> 00:16:25,716 Speaker 1: higher in some higher risk procedures such as intubation, enduring 261 00:16:25,796 --> 00:16:30,196 Speaker 1: medical procedures, and even you know specimen taking is likely 262 00:16:30,236 --> 00:16:32,876 Speaker 1: to be especially in Nize with angel swabs, etc. So 263 00:16:32,916 --> 00:16:36,636 Speaker 1: therefore healthcare workers need to have PPE for some of 264 00:16:36,636 --> 00:16:39,876 Speaker 1: that stuff. The good news is if you have good 265 00:16:39,916 --> 00:16:45,196 Speaker 1: personal protective equipment in healthcare settings, even with aerosolization, we 266 00:16:45,316 --> 00:16:49,756 Speaker 1: seem to have fairly low transmission wherever PPE was available, 267 00:16:49,916 --> 00:16:52,756 Speaker 1: So that's setting that aside. So now for mass transmission, 268 00:16:53,156 --> 00:16:58,716 Speaker 1: what you're dealing with is a surface paced versus you know, 269 00:16:58,756 --> 00:17:02,276 Speaker 1: these droplet transmission, which is not quite a rasalized but 270 00:17:02,356 --> 00:17:06,516 Speaker 1: these droplets can travel, you know, reasonably far beyond six 271 00:17:06,516 --> 00:17:11,836 Speaker 1: feet sometimes, and those droplets there is evidence, or again 272 00:17:11,876 --> 00:17:14,996 Speaker 1: it's not definitive evidence, that you decrease the probability of 273 00:17:15,036 --> 00:17:18,996 Speaker 1: that spread if you are wearing masks, but the effect 274 00:17:19,076 --> 00:17:22,836 Speaker 1: size on an individual level is relatively modest. So the 275 00:17:22,956 --> 00:17:26,996 Speaker 1: thinking is because it's not a very intrusive intervention, if 276 00:17:27,036 --> 00:17:31,796 Speaker 1: you have masks compliance with mask wearing, you decrease the 277 00:17:31,876 --> 00:17:34,876 Speaker 1: probability to an extent that you can see a substantial 278 00:17:34,916 --> 00:17:39,876 Speaker 1: population impact. That last point is fascinating and one that 279 00:17:40,316 --> 00:17:43,036 Speaker 1: has not I think been fully stated, partly maybe because 280 00:17:43,036 --> 00:17:45,596 Speaker 1: people in the public health space don't want to state 281 00:17:45,636 --> 00:17:47,436 Speaker 1: it as explicitly as you just did. So let's just 282 00:17:47,476 --> 00:17:49,916 Speaker 1: go over it for clarity. What I hear you to 283 00:17:49,956 --> 00:17:54,436 Speaker 1: be saying is that although the data on masks, not 284 00:17:54,516 --> 00:17:57,396 Speaker 1: in the hospital context but in the public context, are 285 00:17:57,436 --> 00:18:01,636 Speaker 1: not necessarily that definitive, and although the effects actually might 286 00:18:01,676 --> 00:18:04,836 Speaker 1: be relatively small, there's a kind of public health judgment 287 00:18:04,916 --> 00:18:07,476 Speaker 1: that says, well, it's very low cost for everybody to 288 00:18:07,476 --> 00:18:11,756 Speaker 1: wear masks, and let's insist that people wear them, in fact, 289 00:18:11,796 --> 00:18:15,116 Speaker 1: regulated by law in many places, including where I live 290 00:18:15,116 --> 00:18:20,476 Speaker 1: in Massachusetts. And then we think that cumulatively, that is 291 00:18:20,556 --> 00:18:24,156 Speaker 1: likely to have a harm reducing effect, and the theory 292 00:18:24,236 --> 00:18:27,596 Speaker 1: is sort of that there's not that much downside. If 293 00:18:27,636 --> 00:18:30,516 Speaker 1: that's the case. I do think there's a little bit 294 00:18:30,516 --> 00:18:33,076 Speaker 1: of subtlety there, because it involves a value judgment about 295 00:18:33,116 --> 00:18:35,596 Speaker 1: how low cost it is to wear a mask, and 296 00:18:35,676 --> 00:18:38,316 Speaker 1: I think that may vary from person to person, and 297 00:18:39,076 --> 00:18:41,556 Speaker 1: there are regional variations and how people feel about it, 298 00:18:41,716 --> 00:18:45,596 Speaker 1: There are cultural differences in different places. So I'm wondering 299 00:18:45,596 --> 00:18:48,156 Speaker 1: if you could just say a little bit more on that. Yeah, no, 300 00:18:48,356 --> 00:18:50,116 Speaker 1: I agree, And so that's one of the reasons why 301 00:18:50,476 --> 00:18:53,356 Speaker 1: public health agencies have gone back and forth on this issue. 302 00:18:53,356 --> 00:18:55,796 Speaker 1: It's not a clear good issue. So there's a nice 303 00:18:55,876 --> 00:19:00,916 Speaker 1: review by Oxford that try to incorporate all of these things, 304 00:19:01,036 --> 00:19:05,076 Speaker 1: and they did show that at really high compliance numbers 305 00:19:05,596 --> 00:19:10,596 Speaker 1: you can have a pretty substantial population level impact. What 306 00:19:10,796 --> 00:19:13,636 Speaker 1: level of impact is there? So, based on the fact 307 00:19:13,636 --> 00:19:16,596 Speaker 1: that a lot of these are assessments from studies that 308 00:19:16,636 --> 00:19:19,476 Speaker 1: are sort of still evolving in terms of the evidence 309 00:19:19,516 --> 00:19:23,276 Speaker 1: is still evolving. Because of that, I don't think we 310 00:19:23,316 --> 00:19:26,476 Speaker 1: can say what is the amount of impact, but there's 311 00:19:26,516 --> 00:19:29,436 Speaker 1: likely to be some population level impact. But I think 312 00:19:29,436 --> 00:19:31,836 Speaker 1: you're right, we need to have some nuance in the messaging. 313 00:19:32,436 --> 00:19:34,756 Speaker 1: Thank you very much. I really appreciate your time, my pleasure, 314 00:19:34,756 --> 00:19:44,916 Speaker 1: and these were great questions. Sud's analysis is crisp, clear 315 00:19:45,316 --> 00:19:49,156 Speaker 1: and helpful. First, and most importantly, we should not assume 316 00:19:49,556 --> 00:19:52,916 Speaker 1: any specific time when we will know if the existing 317 00:19:52,996 --> 00:19:56,676 Speaker 1: vaccines that are being tested work. Challenges to the testing 318 00:19:56,716 --> 00:19:59,676 Speaker 1: process are endemic at a time when the virus is 319 00:19:59,716 --> 00:20:03,116 Speaker 1: itself being controlled in many places in the world, and 320 00:20:03,276 --> 00:20:06,476 Speaker 1: resetting up a protocol in a place where the disease 321 00:20:06,556 --> 00:20:10,276 Speaker 1: is spreading faster is actually time consuming in its own right. 322 00:20:10,756 --> 00:20:12,956 Speaker 1: So the fact that it is possible to get trial 323 00:20:12,996 --> 00:20:16,516 Speaker 1: results sometime in twenty twenty does not at all mean 324 00:20:16,556 --> 00:20:20,476 Speaker 1: that we will get those results in twenty twenty. Next, 325 00:20:20,516 --> 00:20:23,396 Speaker 1: when it comes to new therapies, we need to see 326 00:20:23,596 --> 00:20:27,516 Speaker 1: more data. It's very promising that the steroidal treatment of 327 00:20:27,676 --> 00:20:31,836 Speaker 1: dexamethasone is helping to reduce deaths. This is the first 328 00:20:31,876 --> 00:20:35,996 Speaker 1: therapy we've seen that actually specifically does reduce deaths, because 329 00:20:36,036 --> 00:20:39,356 Speaker 1: the rim desvere therapy reduced time in the hospital but 330 00:20:39,476 --> 00:20:43,396 Speaker 1: was not shown statistically to reduce deaths. So that's promising. 331 00:20:43,516 --> 00:20:46,516 Speaker 1: But we still do not have publicly released data. What 332 00:20:46,636 --> 00:20:49,916 Speaker 1: we have rather is a press release from a reputable group, 333 00:20:50,116 --> 00:20:53,236 Speaker 1: Sad says. Sad also reminds us to keep an eye 334 00:20:53,316 --> 00:20:55,876 Speaker 1: on the vaccines that are coming out of China, including 335 00:20:55,876 --> 00:20:59,916 Speaker 1: a traditional style vaccine with an attenuated form of the virus, 336 00:20:59,956 --> 00:21:04,036 Speaker 1: a topic to which we may return in a future episode. Last, 337 00:21:04,076 --> 00:21:07,036 Speaker 1: but not least, when it comes to masks again, Soad 338 00:21:07,156 --> 00:21:11,476 Speaker 1: calls for nuance. He points out that some studies suggest 339 00:21:11,956 --> 00:21:15,356 Speaker 1: mild benefits of mask wearing, which can be magnified through 340 00:21:15,356 --> 00:21:19,476 Speaker 1: the population if there's very very broad compliance, and that 341 00:21:19,556 --> 00:21:22,756 Speaker 1: public health officials think that is worth doing, in part 342 00:21:22,836 --> 00:21:25,276 Speaker 1: because they judge that the wearing of masks is not, 343 00:21:25,556 --> 00:21:29,956 Speaker 1: in fact a high cost public intervention that raises fascinating 344 00:21:29,956 --> 00:21:33,396 Speaker 1: issues about the costs versus the benefits of mask wearing. 345 00:21:33,716 --> 00:21:36,196 Speaker 1: I guarantee you we will return to that issue in 346 00:21:36,236 --> 00:21:39,396 Speaker 1: the near future as well. We'll be back in a moment. 347 00:21:49,516 --> 00:21:51,676 Speaker 1: During the intense last couple of months, we've been so 348 00:21:51,756 --> 00:21:55,076 Speaker 1: focused on getting you COVID stories that we temporarily paused 349 00:21:55,116 --> 00:21:56,756 Speaker 1: a segment that we used to have on the show 350 00:21:56,956 --> 00:21:59,676 Speaker 1: called Playback, where I choose a moment in the news 351 00:21:59,876 --> 00:22:03,716 Speaker 1: and play it back to you for further discussion. This week, 352 00:22:03,756 --> 00:22:07,116 Speaker 1: we're bringing playback back, and in particular, we're going to 353 00:22:07,196 --> 00:22:09,716 Speaker 1: turn our attention where it always goes at the end 354 00:22:09,756 --> 00:22:18,356 Speaker 1: of June, to the Supreme Court of the United States. 355 00:22:20,916 --> 00:22:22,916 Speaker 1: That's the sound of people celebrating in front of the 356 00:22:22,956 --> 00:22:26,796 Speaker 1: Supreme Court last Thursday, after the Supreme Court ruled that 357 00:22:26,836 --> 00:22:30,236 Speaker 1: the Trump administration had acted unlawfully when it tried to 358 00:22:30,276 --> 00:22:35,316 Speaker 1: rescind DHAKA, the Deferred Action for Childhood Arrival's program designed 359 00:22:35,316 --> 00:22:39,836 Speaker 1: to protect people known as dreamers. From a moral standpoint, 360 00:22:40,036 --> 00:22:44,116 Speaker 1: this is a tremendously gratifying decision. Dreamers are about the 361 00:22:44,156 --> 00:22:47,476 Speaker 1: most sympathetic people you could imagine, And the fact that 362 00:22:47,476 --> 00:22:51,876 Speaker 1: the Trump administration sought their deportation was again, from a 363 00:22:51,916 --> 00:22:56,556 Speaker 1: moral standpoint, horrendous. That said, the Supreme Court's decision was 364 00:22:56,636 --> 00:23:00,116 Speaker 1: itself surprising on the law. The decision was written by 365 00:23:00,196 --> 00:23:04,276 Speaker 1: Chief Justice John Roberts, who is ordinarily a staunch conservative, 366 00:23:04,836 --> 00:23:06,356 Speaker 1: and as the fact that it was a five to 367 00:23:06,356 --> 00:23:10,356 Speaker 1: four decision shows, there were grounds that a conservative justice 368 00:23:10,396 --> 00:23:13,876 Speaker 1: like Roberts could have used had he wanted to decide 369 00:23:14,116 --> 00:23:17,716 Speaker 1: that what Barack Obama put in place, namely the DOCCA program, 370 00:23:18,036 --> 00:23:22,156 Speaker 1: Donald Trump could remove. Indeed, Roberts typically has a rather 371 00:23:22,316 --> 00:23:26,076 Speaker 1: expansive conception of executive power. And although we can know 372 00:23:26,116 --> 00:23:28,716 Speaker 1: with one hundred percent certainty, I would say there's ninety 373 00:23:28,756 --> 00:23:32,116 Speaker 1: nine percent probability that several years ago Roberts was one 374 00:23:32,116 --> 00:23:35,636 Speaker 1: of the justices who voted to strike down an Obama 375 00:23:35,676 --> 00:23:39,036 Speaker 1: program that was similar to DOCA but aimed at parents. 376 00:23:39,596 --> 00:23:42,396 Speaker 1: So what was going on here? Why did Chief Justice 377 00:23:42,436 --> 00:23:46,116 Speaker 1: John Roberts choose to leave his conservative allies and join 378 00:23:46,196 --> 00:23:50,996 Speaker 1: the liberals to keep DOCCA in place. Sometimes when Roberts 379 00:23:50,996 --> 00:23:53,876 Speaker 1: issues an apparently liberal decision, it's clear that what he's 380 00:23:53,916 --> 00:23:56,636 Speaker 1: doing is trying to preserve the appearance of legitimacy of 381 00:23:56,636 --> 00:23:59,716 Speaker 1: the Supreme Court by avoiding a scenario where the public 382 00:23:59,796 --> 00:24:04,476 Speaker 1: would think of the justices as basically partisan. Roberts understands 383 00:24:04,516 --> 00:24:06,596 Speaker 1: that the public knows that the Supreme Court justices have 384 00:24:06,636 --> 00:24:09,836 Speaker 1: different ideologies. What he doesn't want is for the public 385 00:24:09,876 --> 00:24:12,596 Speaker 1: to think that the justices vote based on the party 386 00:24:12,596 --> 00:24:16,436 Speaker 1: of the person who appointed them. That may explain Roberts's 387 00:24:16,516 --> 00:24:20,556 Speaker 1: vote not to entirely strike down Obamacare, the Affordable Care 388 00:24:20,596 --> 00:24:24,836 Speaker 1: Act some years ago. In the DACA case, however, Roberts's 389 00:24:24,916 --> 00:24:28,396 Speaker 1: motivation seems to have been somewhat different. What seems to 390 00:24:28,396 --> 00:24:31,836 Speaker 1: be motivating Roberts is a kind of disrespect for the 391 00:24:31,876 --> 00:24:36,476 Speaker 1: Donald Trump administration's unwillingness to cross its tees, dot its eyes, 392 00:24:36,516 --> 00:24:38,836 Speaker 1: and follow the rule of law when it comes to 393 00:24:38,916 --> 00:24:43,076 Speaker 1: issuing important governmental decisions. We saw this a year ago 394 00:24:43,396 --> 00:24:47,316 Speaker 1: when Roberts also provided the decisive fifth vote to reverse 395 00:24:47,316 --> 00:24:50,756 Speaker 1: the Trump administration's plan to put a citizenship question on 396 00:24:50,796 --> 00:24:54,036 Speaker 1: the twenty twenty census. In that case, as in the 397 00:24:54,116 --> 00:24:57,556 Speaker 1: DACA case, Roberts relied on a law called the Administrative 398 00:24:57,596 --> 00:25:00,196 Speaker 1: Procedure Act, which is the law that gives the federal 399 00:25:00,276 --> 00:25:04,716 Speaker 1: courts the authority to oversee and review decisions of administrative 400 00:25:04,756 --> 00:25:08,476 Speaker 1: bodies in order to determine whether they complied with the 401 00:25:08,596 --> 00:25:13,276 Speaker 1: pre jurors that the law demands. In particular, the Administrative 402 00:25:13,276 --> 00:25:17,356 Speaker 1: Procedure Act requires that the government give clear, honest, and 403 00:25:17,556 --> 00:25:21,316 Speaker 1: accurate justifications and reasons for why it's doing what it's doing, 404 00:25:21,676 --> 00:25:24,876 Speaker 1: and both the Census case and the DACA case, Roberts 405 00:25:24,956 --> 00:25:28,636 Speaker 1: ruled that the government had failed to provide those justifications. 406 00:25:29,236 --> 00:25:32,756 Speaker 1: In essence, Roberts was saying, taking the action in question 407 00:25:33,076 --> 00:25:36,956 Speaker 1: was within the general authority of the executive branch, but 408 00:25:37,156 --> 00:25:40,116 Speaker 1: the executive branch didn't do a good enough job of 409 00:25:40,156 --> 00:25:44,156 Speaker 1: explaining why it did what it did. This kind of 410 00:25:44,236 --> 00:25:47,876 Speaker 1: judicial supervision of governmental action is crucial to preserving the 411 00:25:47,956 --> 00:25:50,956 Speaker 1: rule of law, and it's pretty clear that John Roberts 412 00:25:51,156 --> 00:25:54,356 Speaker 1: no longer trusts the Trump administration to do that. To 413 00:25:54,436 --> 00:25:57,356 Speaker 1: be sure, at the beginning of the Trump administration, Roberts 414 00:25:57,676 --> 00:25:59,956 Speaker 1: was willing to give Trump the benefit of the doubt. 415 00:26:00,596 --> 00:26:03,396 Speaker 1: He after all, wrote the opinion in the Trump against 416 00:26:03,396 --> 00:26:06,836 Speaker 1: Hawaii case, the one involving the Muslim travel ban, in 417 00:26:06,876 --> 00:26:10,476 Speaker 1: which he upheld the president's authority to issue the version 418 00:26:10,516 --> 00:26:12,436 Speaker 1: of the travel band that was in play at the time. 419 00:26:13,076 --> 00:26:15,436 Speaker 1: What seems to have happened subsequently is that as Roberts 420 00:26:15,436 --> 00:26:18,156 Speaker 1: has gotten a closer and closer look at Trump's disrespect 421 00:26:18,196 --> 00:26:20,796 Speaker 1: for the courts and his disrespect for the rule of law, 422 00:26:21,356 --> 00:26:24,356 Speaker 1: He's decided to take on the role of defending the judiciary, 423 00:26:24,636 --> 00:26:27,796 Speaker 1: defending the rule of law, and of him making Trump comply. 424 00:26:28,556 --> 00:26:30,796 Speaker 1: And it may not be irrelevant that Roberts also had 425 00:26:30,836 --> 00:26:33,516 Speaker 1: to spend a good chunk of his January sitting in 426 00:26:33,516 --> 00:26:37,836 Speaker 1: the Senate listening to the Impeachment Manager's condemnation of Donald Trump, 427 00:26:37,996 --> 00:26:42,356 Speaker 1: precisely for his disrespect for the rule of law. So 428 00:26:42,396 --> 00:26:45,036 Speaker 1: if you're wondering whether John Roberts has suddenly become a liberal, 429 00:26:45,356 --> 00:26:48,076 Speaker 1: take it from me. He has not. I expect more 430 00:26:48,116 --> 00:26:52,116 Speaker 1: conservative decisions from him, possibly even this week or next. 431 00:26:52,636 --> 00:26:55,676 Speaker 1: But John Roberts has taken up the responsibility of the 432 00:26:55,756 --> 00:27:00,476 Speaker 1: judiciary to keep an eye on this president, and for 433 00:27:00,556 --> 00:27:04,956 Speaker 1: that I think everybody liberal or conservative should be profoundly grateful. 434 00:27:07,036 --> 00:27:08,996 Speaker 1: Next week, we'll be taking a break for July fourth, 435 00:27:09,196 --> 00:27:11,676 Speaker 1: but we will see you the week after, and until then, 436 00:27:12,116 --> 00:27:16,196 Speaker 1: be careful, be safe, and be well. Deep Background is 437 00:27:16,236 --> 00:27:19,316 Speaker 1: brought to you by Pushkin Industries. Our producer is Lydia 438 00:27:19,396 --> 00:27:23,156 Speaker 1: Jane Cott, with mastering by Jason Gambrell and Martin Gonzalez. 439 00:27:23,476 --> 00:27:26,996 Speaker 1: Our showrunner is Sophia mckibbon. Our theme music is composed 440 00:27:26,996 --> 00:27:30,876 Speaker 1: by Luis GERA special thanks to the Pushkin Brass, Malcolm Gladwell, 441 00:27:30,996 --> 00:27:35,036 Speaker 1: Jacob Weissberg, and Mia Lovell. I'm Noah Feldman. I also 442 00:27:35,036 --> 00:27:37,716 Speaker 1: write a regular column for Bloomberg Opinion, which you can 443 00:27:37,756 --> 00:27:42,356 Speaker 1: find at Bloomberg dot com slash Feldman. To discover Bloomberg's 444 00:27:42,356 --> 00:27:46,956 Speaker 1: original slate of podcasts, go to Bloomberg dot com slash Podcasts. 445 00:27:48,036 --> 00:27:50,356 Speaker 1: And one last thing. I just wrote a book called 446 00:27:50,436 --> 00:27:53,396 Speaker 1: The Arab Winter, a Tragedy. I would be delighted if 447 00:27:53,396 --> 00:27:56,316 Speaker 1: you checked it out. If you liked what you heard today, 448 00:27:56,316 --> 00:27:59,316 Speaker 1: please write a review or tell a friend. You can 449 00:27:59,316 --> 00:28:01,316 Speaker 1: always let me know what you think on Twitter. My 450 00:28:01,396 --> 00:28:05,796 Speaker 1: handle is Noah R. Feldman. This is Deep Background.