1 00:00:04,440 --> 00:00:09,800 Speaker 1: Welcome to Prognosis. I'm Laura Carlson. It's day one and 2 00:00:09,920 --> 00:00:15,600 Speaker 1: fifty four since coronavirus was declared a global pandemic. Today's 3 00:00:15,640 --> 00:00:20,880 Speaker 1: main story. Despite the fact that COVID nineteen has disproportionately 4 00:00:20,880 --> 00:00:27,040 Speaker 1: affected black, Latino and Indigenous Americans in major drug trials, 5 00:00:27,520 --> 00:00:34,919 Speaker 1: the participants are overwhelmingly white. But first, here's what happened 6 00:00:34,960 --> 00:00:51,960 Speaker 1: in virus news today. Russia rushed aside international concerns about 7 00:00:51,960 --> 00:00:57,040 Speaker 1: the safety of the world's first COVID nineteen vaccine. The 8 00:00:57,120 --> 00:01:02,160 Speaker 1: country will start mass inoculation this month before clinical testing 9 00:01:02,440 --> 00:01:07,360 Speaker 1: is completed. According to Russian Minister of Health Mikhail Murashko, 10 00:01:07,760 --> 00:01:11,759 Speaker 1: authorities planned to start inoculating medical workers and other risk 11 00:01:11,800 --> 00:01:16,240 Speaker 1: groups within two weeks on a voluntary basis. The vaccine 12 00:01:16,280 --> 00:01:21,360 Speaker 1: will be available to the wider population from October. President 13 00:01:21,480 --> 00:01:25,440 Speaker 1: Vladimir Putin's announcement on Tuesday that Russia has cleared the 14 00:01:25,520 --> 00:01:29,160 Speaker 1: vaccine for use was a propaganda coup for the Kremlin, 15 00:01:30,200 --> 00:01:33,679 Speaker 1: but many questions remain in the West about this vaccine's 16 00:01:33,880 --> 00:01:39,039 Speaker 1: safety and efficacy given the scant details about its development. 17 00:01:41,720 --> 00:01:45,160 Speaker 1: New Jersey is the latest US state to retreat from 18 00:01:45,200 --> 00:01:50,120 Speaker 1: plans to send kids back to classrooms. Governor Phil Murphy 19 00:01:50,120 --> 00:01:53,240 Speaker 1: will now give public schools the option of all remote 20 00:01:53,280 --> 00:01:59,919 Speaker 1: teaching when classes resume in September. Earlier, Murphy had required 21 00:02:00,160 --> 00:02:04,000 Speaker 1: that all districts offer some level of in person instruction 22 00:02:04,520 --> 00:02:09,640 Speaker 1: with safety precautions in place. On Tuesday, the state's largest 23 00:02:09,680 --> 00:02:14,240 Speaker 1: teachers union issued a joint statement with groups representing administrators 24 00:02:14,880 --> 00:02:21,320 Speaker 1: saying classroom instruction quote is not safe yet. Finally, the 25 00:02:21,320 --> 00:02:25,600 Speaker 1: pandemic will likely make the gender pay gap worse after 26 00:02:25,680 --> 00:02:31,559 Speaker 1: the US economy recovers, but it could ultimately improve opportunities 27 00:02:31,560 --> 00:02:35,200 Speaker 1: for women. A paper from the National Bureau of Economic 28 00:02:35,280 --> 00:02:39,000 Speaker 1: Research said that in a regular recession, the pay gap 29 00:02:39,080 --> 00:02:43,640 Speaker 1: between men and women shrinks by two percentage points because 30 00:02:43,680 --> 00:02:48,079 Speaker 1: men tend to get hit harder by job losses. But 31 00:02:48,280 --> 00:02:51,920 Speaker 1: according to the report, in a pandemic recession like the 32 00:02:51,960 --> 00:02:57,960 Speaker 1: one we're in now, that gap increases by five percentage points. 33 00:03:04,760 --> 00:03:08,480 Speaker 1: And now, for today's main story, in the rush to 34 00:03:08,560 --> 00:03:13,000 Speaker 1: develop a vaccine or treatment for COVID, nineteen drug companies 35 00:03:13,040 --> 00:03:17,640 Speaker 1: are fast tracking clinical trials, but those trials have a 36 00:03:17,760 --> 00:03:22,680 Speaker 1: major diversity problem. Participants in major drug trials range from 37 00:03:22,720 --> 00:03:29,200 Speaker 1: seven to eighty nine white. This is a big problem 38 00:03:29,240 --> 00:03:33,880 Speaker 1: considering it's a disease that disproportionately affects people of color. 39 00:03:35,280 --> 00:03:38,800 Speaker 1: Kristin V. Brown reports that failing to account for minority 40 00:03:38,840 --> 00:03:43,280 Speaker 1: groups could potentially impact how well a drug eventually works 41 00:03:43,640 --> 00:03:52,800 Speaker 1: for those that the virus has harmed the most. COVID 42 00:03:52,880 --> 00:03:58,120 Speaker 1: nineteen is not an equal opportunity threat. Over the past 43 00:03:58,160 --> 00:04:02,080 Speaker 1: six months, black little you know, and Indigenous Americans have 44 00:04:02,160 --> 00:04:06,640 Speaker 1: suffered more from the virus than anyone else. The statistics 45 00:04:06,720 --> 00:04:11,120 Speaker 1: here can be shocking. For example, in cases where race 46 00:04:11,200 --> 00:04:15,000 Speaker 1: is known, black lives have accounted for more than of 47 00:04:15,040 --> 00:04:18,160 Speaker 1: the national death toll, even though they make up about 48 00:04:18,680 --> 00:04:22,599 Speaker 1: of the population. So I was surprised when I took 49 00:04:22,600 --> 00:04:25,719 Speaker 1: a look at who has participated in clinical trials for 50 00:04:25,800 --> 00:04:30,000 Speaker 1: COVID nineteen vaccines and treatments. It turns out that, at 51 00:04:30,080 --> 00:04:34,800 Speaker 1: least so far, most of them have been white. You 52 00:04:34,880 --> 00:04:39,680 Speaker 1: might wonder why this matters, after all, race is not biological. 53 00:04:40,320 --> 00:04:44,599 Speaker 1: It's a social construct. But the more we understand about 54 00:04:44,640 --> 00:04:48,520 Speaker 1: human biology, the clearer it is that a person's individual 55 00:04:48,560 --> 00:04:52,640 Speaker 1: biology can influence certain things, like whether they are more 56 00:04:52,680 --> 00:04:57,520 Speaker 1: susceptible to certain diseases, or if certain drugs work for them. 57 00:04:57,560 --> 00:05:00,720 Speaker 1: This can be connected to genetics or environment you grew 58 00:05:00,800 --> 00:05:03,359 Speaker 1: up in, and both of those things can be connected 59 00:05:03,400 --> 00:05:07,400 Speaker 1: to race. So if you know that a disease especially 60 00:05:07,440 --> 00:05:12,320 Speaker 1: impacts minority populations, it's really important to make sure that 61 00:05:12,360 --> 00:05:19,960 Speaker 1: those populations are represented in clinical trials. I talked about 62 00:05:20,000 --> 00:05:23,479 Speaker 1: this with John Bagel, a researcher at the National Institute 63 00:05:23,560 --> 00:05:27,560 Speaker 1: of Allergy and Infectious Diseases who has worked on multiple 64 00:05:27,640 --> 00:05:31,040 Speaker 1: or lea stage clinical trials for COVID nineteen. The way 65 00:05:31,040 --> 00:05:34,800 Speaker 1: I would frame it is that the diversity should match 66 00:05:34,880 --> 00:05:42,200 Speaker 1: the scientific objective. If the objective is determining efficacy and 67 00:05:42,800 --> 00:05:48,680 Speaker 1: understanding how the vaccine prevents disease in different populations and 68 00:05:48,720 --> 00:05:53,479 Speaker 1: how effective it is in different populations, then that diversity 69 00:05:53,880 --> 00:05:59,080 Speaker 1: is very critical. Uh. The last thing that you would 70 00:05:59,080 --> 00:06:02,280 Speaker 1: want to do is roll out a public health intervention 71 00:06:02,320 --> 00:06:05,880 Speaker 1: and not understand the impact that it had for the 72 00:06:05,960 --> 00:06:10,039 Speaker 1: different populations that you're trying to cover. Now it should 73 00:06:10,040 --> 00:06:13,560 Speaker 1: be clear race is not the only variable that could 74 00:06:13,560 --> 00:06:16,360 Speaker 1: be connected to why a person responds to a vaccine 75 00:06:16,600 --> 00:06:20,840 Speaker 1: and another one doesn't. Age can also matter, so can 76 00:06:20,839 --> 00:06:24,599 Speaker 1: other underlying medical conditions. You could also give the exact 77 00:06:24,720 --> 00:06:27,680 Speaker 1: same vaccine to two different white men in their fifties, 78 00:06:27,800 --> 00:06:29,680 Speaker 1: and the vaccine might work for one of them but 79 00:06:29,839 --> 00:06:33,880 Speaker 1: not the other. Biology can just be mysterious. Sometimes there 80 00:06:34,000 --> 00:06:37,120 Speaker 1: is still so much we don't know, but we do 81 00:06:37,360 --> 00:06:41,200 Speaker 1: have clear examples of where race is a factor. The 82 00:06:41,320 --> 00:06:45,720 Speaker 1: classic examples would be for hypertensive where that in the 83 00:06:45,800 --> 00:06:49,880 Speaker 1: hypertension guidelines there are clear recommendations based on race because 84 00:06:49,920 --> 00:06:52,720 Speaker 1: we know that as a class, even though there is 85 00:06:52,800 --> 00:06:57,480 Speaker 1: individual variation that as as a class of drugs, UH, 86 00:06:57,760 --> 00:07:02,160 Speaker 1: they will have different effects on different populations. Another example 87 00:07:02,200 --> 00:07:05,960 Speaker 1: that comes to mind is asthma. Black and Latino children 88 00:07:06,000 --> 00:07:09,279 Speaker 1: are known to not respond as well to abutyroll, which 89 00:07:09,320 --> 00:07:11,960 Speaker 1: is the most popular medication on the market to treat 90 00:07:11,960 --> 00:07:15,800 Speaker 1: asthma attacks. There's been some compelling research to suggest that 91 00:07:15,840 --> 00:07:20,080 Speaker 1: a genetic variant maybe what's responsible here, and knowing someone 92 00:07:20,160 --> 00:07:23,240 Speaker 1: might have that variant because save their life since abutyrol 93 00:07:23,280 --> 00:07:26,160 Speaker 1: is the medication that most emergency rooms keep on hand 94 00:07:26,200 --> 00:07:29,560 Speaker 1: to treat severe attacks. But much of this we have 95 00:07:29,760 --> 00:07:33,360 Speaker 1: really only started to understand over the last decade or so. 96 00:07:34,480 --> 00:07:40,920 Speaker 1: It is an increasingly recognized phenomenon and the whole field 97 00:07:41,040 --> 00:07:47,760 Speaker 1: of personalized medicine is revolving around this idea that there 98 00:07:47,800 --> 00:07:55,160 Speaker 1: are subtle variations in our immune response, subtle variations in 99 00:07:55,400 --> 00:08:00,160 Speaker 1: multiple genes that might not be a parent but but 100 00:08:00,880 --> 00:08:05,080 Speaker 1: will affect our ability to respond to different medications. Now, 101 00:08:05,360 --> 00:08:08,040 Speaker 1: one thing that John mentioned is that it's important for 102 00:08:08,080 --> 00:08:12,400 Speaker 1: a trial's patient population to match the scientific objectives of 103 00:08:12,400 --> 00:08:16,640 Speaker 1: that trial. So he said it's less critical that early 104 00:08:16,680 --> 00:08:20,160 Speaker 1: stage trials be diverse because the main objective is to 105 00:08:20,240 --> 00:08:22,960 Speaker 1: test a small number of people and make sure that 106 00:08:23,040 --> 00:08:26,640 Speaker 1: drug or vaccine is safe. I looked at the data 107 00:08:26,720 --> 00:08:30,160 Speaker 1: for six trials that had published results, and only one 108 00:08:30,200 --> 00:08:33,480 Speaker 1: of them, elite stage trial for the drug Room Disapvere, 109 00:08:34,200 --> 00:08:38,560 Speaker 1: had anything approaching diversity. But most of those trials were 110 00:08:38,600 --> 00:08:42,360 Speaker 1: early stage. It's in phase three trials, which seek to 111 00:08:42,360 --> 00:08:45,600 Speaker 1: test how well a drug or vaccine actually works, that 112 00:08:45,720 --> 00:09:01,199 Speaker 1: diversity is absolutely critical. Congress actually passed legislation acquiring publicly 113 00:09:01,280 --> 00:09:05,800 Speaker 1: funded medical studies to include more women and minorities. The 114 00:09:05,880 --> 00:09:10,160 Speaker 1: f d A also encourages the inclusion of diverse populations 115 00:09:10,559 --> 00:09:14,520 Speaker 1: and its guidelines for developing COVID nineteen treatments and vaccines. 116 00:09:15,520 --> 00:09:17,560 Speaker 1: Part of the problem is that can be hard to 117 00:09:17,600 --> 00:09:21,319 Speaker 1: recruit minority populations to participate in a trial. There is 118 00:09:21,360 --> 00:09:25,080 Speaker 1: a lot of mistrust in our healthcare system among them, 119 00:09:25,160 --> 00:09:29,240 Speaker 1: but in the past drugmakers also haven't necessarily tried hard 120 00:09:29,440 --> 00:09:35,680 Speaker 1: enough to recruit them. That may be changing. Every single 121 00:09:35,760 --> 00:09:38,240 Speaker 1: drugmaker I talked to for the story told me that 122 00:09:38,280 --> 00:09:40,640 Speaker 1: they had plans in place to make sure that there 123 00:09:40,679 --> 00:09:45,360 Speaker 1: are more diverse participants in later stage vaccine trials. Plans 124 00:09:45,520 --> 00:09:50,440 Speaker 1: like working with community organizations to help recruit participants. I 125 00:09:50,559 --> 00:09:53,440 Speaker 1: noticed these efforts in place when the NIH launched its 126 00:09:53,440 --> 00:09:57,600 Speaker 1: Phase three trial for a vaccine produced by Maderna. They 127 00:09:57,600 --> 00:09:59,719 Speaker 1: hosted a Facebook live Q and A in which the 128 00:09:59,760 --> 00:10:03,040 Speaker 1: heads of Maderna, the NIH, and the n I A 129 00:10:03,160 --> 00:10:06,319 Speaker 1: I d All fielded questions from a participant in the 130 00:10:06,360 --> 00:10:10,679 Speaker 1: phase one trials. That participant was a black woman named Robin, 131 00:10:11,320 --> 00:10:14,080 Speaker 1: and she got right to the tough questions about race. 132 00:10:14,400 --> 00:10:16,520 Speaker 1: I have to say that when I told my friends 133 00:10:16,520 --> 00:10:20,240 Speaker 1: and relatives that I was going to participate, they were 134 00:10:20,320 --> 00:10:24,760 Speaker 1: absolutely adamant that it was a bad idea. They tried 135 00:10:24,800 --> 00:10:28,480 Speaker 1: to discourage me because they were concerned about my health 136 00:10:29,120 --> 00:10:32,200 Speaker 1: and about my safety. And the reason for that was 137 00:10:32,360 --> 00:10:36,200 Speaker 1: because in the African American community, we are all familiar 138 00:10:36,679 --> 00:10:43,280 Speaker 1: with the Tuskegee experiments. The Tuskegee experiments are often cited 139 00:10:43,320 --> 00:10:45,640 Speaker 1: as one of the reasons there is mistrust of our 140 00:10:45,679 --> 00:10:49,840 Speaker 1: healthcare system in the black community. Beginning in the thirties, 141 00:10:50,000 --> 00:10:54,120 Speaker 1: public health researchers conducted an experiment which they sought to 142 00:10:54,160 --> 00:10:58,839 Speaker 1: observe untreated syphilis in black men, but lied to participants 143 00:10:58,960 --> 00:11:01,760 Speaker 1: and told them they were eaving a treatment for bad blood. 144 00:11:02,760 --> 00:11:06,160 Speaker 1: Even after a cure for syphilis was discovered, most of 145 00:11:06,200 --> 00:11:10,520 Speaker 1: them did not receive it. And so many people are 146 00:11:10,840 --> 00:11:14,480 Speaker 1: in the African American community are familiar with it, and 147 00:11:14,679 --> 00:11:18,600 Speaker 1: when you asked them about participating in clinical trials, they'll 148 00:11:18,640 --> 00:11:26,360 Speaker 1: give you two words, Tuskegee and no. I was curious, though, 149 00:11:26,559 --> 00:11:29,320 Speaker 1: just how Maderna had recruited Robin and others for the 150 00:11:29,360 --> 00:11:35,040 Speaker 1: early stage trials. According to Maderna, of those trial participants 151 00:11:35,040 --> 00:11:38,760 Speaker 1: were white. I talked with Ian Hayden, a twenty nine 152 00:11:38,840 --> 00:11:42,520 Speaker 1: year old Seattle resident who participated in the trials. He 153 00:11:42,600 --> 00:11:44,600 Speaker 1: was actually one of just a few people who had 154 00:11:44,600 --> 00:11:48,360 Speaker 1: a bad reaction to the vaccine. Ian is white, by 155 00:11:48,400 --> 00:11:51,000 Speaker 1: the way. I first learned about the study from a 156 00:11:51,080 --> 00:11:54,320 Speaker 1: co worker who posted about it in slack Um he 157 00:11:54,400 --> 00:11:57,920 Speaker 1: shared a form basically where people who are interested could 158 00:11:57,960 --> 00:12:01,960 Speaker 1: could express their interest. Um that was the first that 159 00:12:02,040 --> 00:12:04,520 Speaker 1: I learned that the trial was taking place here in Seattle, 160 00:12:04,559 --> 00:12:06,760 Speaker 1: where I live, and that they were recruiting in the 161 00:12:06,840 --> 00:12:12,320 Speaker 1: Seattle area looking for healthy people under fifty five like me. Um. So, 162 00:12:12,360 --> 00:12:16,439 Speaker 1: I filled out that form really without much forethought, because 163 00:12:16,480 --> 00:12:18,840 Speaker 1: I didn't expect to hear back. To be honest, I 164 00:12:18,920 --> 00:12:20,800 Speaker 1: just figured I'd throw my hat in the ring and 165 00:12:21,160 --> 00:12:23,600 Speaker 1: we'll see what happens. A couple of days later, I 166 00:12:23,600 --> 00:12:25,400 Speaker 1: did get a call back from the clinic asking me 167 00:12:25,440 --> 00:12:28,560 Speaker 1: to come in for a screening visit. Ian works in 168 00:12:28,600 --> 00:12:31,760 Speaker 1: the world of vaccine development as a science communicator at 169 00:12:31,800 --> 00:12:35,520 Speaker 1: the University of Washington. In other words, he heard about 170 00:12:35,559 --> 00:12:38,160 Speaker 1: the trial because it's in his field of work. He 171 00:12:38,280 --> 00:12:41,320 Speaker 1: also said that he was comfortable volunteering in part because 172 00:12:41,320 --> 00:12:43,960 Speaker 1: he works in this world and knows what to expect. 173 00:12:45,440 --> 00:12:47,280 Speaker 1: You know, it seems clear to me that we need 174 00:12:47,320 --> 00:12:50,080 Speaker 1: a coronavirus vaccine. I think that's clear to a lot 175 00:12:50,120 --> 00:12:52,240 Speaker 1: of people now. It's it's how we're going to put 176 00:12:52,240 --> 00:12:54,520 Speaker 1: this all behind us at the end of the day, 177 00:12:54,760 --> 00:12:58,360 Speaker 1: and we're not going to get a vaccine without clinical trials, 178 00:12:58,400 --> 00:13:01,480 Speaker 1: and clinical trials need volunteer. You know, I came in, 179 00:13:01,559 --> 00:13:04,320 Speaker 1: I guess with uh, I don't know on on the 180 00:13:04,360 --> 00:13:06,880 Speaker 1: side of science, you could say, and of course with 181 00:13:06,960 --> 00:13:09,040 Speaker 1: a lot of trust in that system, something that I 182 00:13:09,080 --> 00:13:13,280 Speaker 1: was familiar with. I'm somebody who happens to know scientists. 183 00:13:13,360 --> 00:13:16,360 Speaker 1: I know people who work on vaccine design, and undoubtedly 184 00:13:17,040 --> 00:13:19,559 Speaker 1: that color is my thinking to this. This whole process 185 00:13:19,640 --> 00:13:22,160 Speaker 1: is probably going to look very different to someone who 186 00:13:22,400 --> 00:13:24,520 Speaker 1: who doesn't know a scientist, and you know, you only 187 00:13:24,600 --> 00:13:27,560 Speaker 1: hear about these things through the news. For her part 188 00:13:28,000 --> 00:13:30,960 Speaker 1: in that Q and A, Robin said she decided to 189 00:13:31,000 --> 00:13:34,640 Speaker 1: participate because she wanted to help her community. I felt 190 00:13:34,800 --> 00:13:40,320 Speaker 1: that if those people who conducted the Tuskegee experiments were 191 00:13:40,360 --> 00:13:43,640 Speaker 1: allowed to succeed, not only because of what they did, 192 00:13:44,240 --> 00:13:48,400 Speaker 1: but because future generations of African Americans were still too 193 00:13:48,440 --> 00:13:53,880 Speaker 1: afraid to participate in trials that would benefit us, then 194 00:13:53,920 --> 00:13:57,480 Speaker 1: those people would really have one twice and I was 195 00:13:57,520 --> 00:14:03,480 Speaker 1: not going to let that happen. With so many vaccines 196 00:14:03,520 --> 00:14:07,000 Speaker 1: in progress now it does seem promising that one of 197 00:14:07,040 --> 00:14:10,080 Speaker 1: them will work, and eventually we will be able to 198 00:14:10,080 --> 00:14:14,800 Speaker 1: put this terrible year behind us. But it will take 199 00:14:14,880 --> 00:14:19,520 Speaker 1: significant effort to achieve the diversity necessary to make sure 200 00:14:19,640 --> 00:14:37,520 Speaker 1: that vaccine works for everyone. That was Kristin V. Brown 201 00:14:38,080 --> 00:14:40,720 Speaker 1: and that's it for our show today. For coverage of 202 00:14:40,720 --> 00:14:44,680 Speaker 1: the outbreak from one bureaus around the world, visit Bloomberg 203 00:14:44,840 --> 00:14:49,160 Speaker 1: dot com slash coronavirus and if you like the show, 204 00:14:49,600 --> 00:14:52,320 Speaker 1: please leave us a review and a rating on Apple 205 00:14:52,400 --> 00:14:56,080 Speaker 1: Podcasts or Spotify. It's the best way to help more 206 00:14:56,160 --> 00:15:00,560 Speaker 1: listeners find our global reporting. The product No sis Dale 207 00:15:00,760 --> 00:15:05,640 Speaker 1: Edition is produced by Topher foreheads Jordan Gospore, Magnus Hendrickson 208 00:15:05,800 --> 00:15:10,400 Speaker 1: and me Laura Carlson. Today's main story was reported by 209 00:15:10,480 --> 00:15:16,000 Speaker 1: Kristin V. Brown. Original music by Leo Sidrin. Our editors 210 00:15:16,040 --> 00:15:20,960 Speaker 1: are Francesco Levi and Rick Shine. Francesco Levi is Bloomberg's 211 00:15:20,960 --> 00:15:23,440 Speaker 1: head of Podcasts. Thanks for listening.