1 00:00:04,040 --> 00:00:09,680 Speaker 1: Welcome the prognosis. I'm Laura Carlson. It's day two since 2 00:00:09,760 --> 00:00:15,080 Speaker 1: coronavirus was declared a global pandemic. Our main story. Dogs 3 00:00:15,480 --> 00:00:17,799 Speaker 1: may hold a key to one raveling some of the 4 00:00:17,840 --> 00:00:22,920 Speaker 1: mysteries about the virus. The reason lies in their noses. 5 00:00:24,280 --> 00:00:36,160 Speaker 1: But first, here's what happened today. For the first time 6 00:00:36,240 --> 00:00:39,879 Speaker 1: in months, the most important story in the US is 7 00:00:39,960 --> 00:00:44,559 Speaker 1: not the vicious spread of COVID nineteen through the population. Instead, 8 00:00:45,200 --> 00:00:48,880 Speaker 1: days of protests have rocked the country and some cities 9 00:00:48,920 --> 00:00:54,720 Speaker 1: around the world in response to the death of George Floyd. 10 00:00:55,720 --> 00:00:58,480 Speaker 1: Floyd's is the latest in a series of killings of 11 00:00:58,520 --> 00:01:02,400 Speaker 1: black men and women at the hands of police. While 12 00:01:02,440 --> 00:01:06,279 Speaker 1: the protests have been mostly peaceful, some participants have broken 13 00:01:06,280 --> 00:01:09,920 Speaker 1: store windows and set buildings and cars on fire. The 14 00:01:10,000 --> 00:01:13,759 Speaker 1: police in many cities have also acted with force, driving 15 00:01:13,840 --> 00:01:19,080 Speaker 1: vehicles into crowds, firing rubber bullets at protesters, and arresting journalists. 16 00:01:26,640 --> 00:01:29,600 Speaker 1: The virus may not have been the spark for the protests, 17 00:01:30,160 --> 00:01:33,120 Speaker 1: but it has helped create the conditions that have made 18 00:01:33,120 --> 00:01:38,120 Speaker 1: them so volatile. Unemployment has reached levels not seen since 19 00:01:38,120 --> 00:01:42,240 Speaker 1: the Great Depression. The disease caused by the virus has 20 00:01:42,280 --> 00:01:47,040 Speaker 1: killed over one hundred thousand and disproportionately affected the black community, 21 00:01:48,480 --> 00:01:52,360 Speaker 1: and as the country limps towards reopening, fears about getting 22 00:01:52,400 --> 00:01:58,480 Speaker 1: sick and economic insecurity hang in the air to make 23 00:01:58,520 --> 00:02:02,200 Speaker 1: things worse. Health experts are worried that the large gatherings 24 00:02:02,200 --> 00:02:06,040 Speaker 1: could cause a spike of new infections. Silent carriers of 25 00:02:06,040 --> 00:02:10,400 Speaker 1: the virus could unwittingly infect others as protesters crammed together, 26 00:02:10,960 --> 00:02:15,360 Speaker 1: some without masks. Police in many cities have fired tear 27 00:02:15,400 --> 00:02:20,200 Speaker 1: gas of protesters, which causes widespread coughing. The virus is 28 00:02:20,280 --> 00:02:26,000 Speaker 1: dispersed by microscopic droplets in the air when people cough, sneeze, sing, 29 00:02:26,560 --> 00:02:38,280 Speaker 1: or talk. And now our main story. Dogs have long 30 00:02:38,360 --> 00:02:41,880 Speaker 1: had a positive link with human health. Science has shown 31 00:02:41,919 --> 00:02:45,120 Speaker 1: that the benefits of dog ownership extend from reducing the 32 00:02:45,240 --> 00:02:50,320 Speaker 1: risk of schizophrenia to improving cardiovascular health. But in the 33 00:02:50,400 --> 00:02:55,400 Speaker 1: era of coronavirus, they have other, as yet untapped powers 34 00:02:55,639 --> 00:02:59,519 Speaker 1: to help stop the spread of the virus. Bloomberg Senior 35 00:02:59,639 --> 00:03:11,640 Speaker 1: editor Jason Gale has more. This is Merlin. He's a 36 00:03:11,680 --> 00:03:14,120 Speaker 1: six year old Labrador who trained to be a guide dog, 37 00:03:14,400 --> 00:03:17,320 Speaker 1: but he didn't make the cut. He got distracted by 38 00:03:17,360 --> 00:03:21,240 Speaker 1: his powerful sense of smell, mostly of edible things. Stopping 39 00:03:21,280 --> 00:03:24,359 Speaker 1: Merlin stealing food is a full time job for my kids. 40 00:03:24,880 --> 00:03:26,960 Speaker 1: But what if there was a way of channeling that 41 00:03:27,000 --> 00:03:29,480 Speaker 1: potent sense of smell to get dogs to sniff out 42 00:03:29,520 --> 00:03:35,000 Speaker 1: the coronavirus. Turns out there is. Researchers in Helsinki and 43 00:03:35,040 --> 00:03:38,520 Speaker 1: London are separately training dogs to detect the coronavirus, and 44 00:03:38,560 --> 00:03:40,800 Speaker 1: when you think about it, it's not such a stretch. 45 00:03:41,320 --> 00:03:44,080 Speaker 1: For years, dogs have been routinely used in airports to 46 00:03:44,160 --> 00:03:47,960 Speaker 1: sniff out explosives, drugs and clandestine food. They have also 47 00:03:48,040 --> 00:03:50,960 Speaker 1: been used to detect cancer and toxic mold. At the 48 00:03:50,960 --> 00:03:54,160 Speaker 1: London School of Hygiene and Tropical Medicine, Professor James Logan 49 00:03:54,200 --> 00:04:01,520 Speaker 1: has worked with dogs to find malaria. When you have 50 00:04:01,560 --> 00:04:05,360 Speaker 1: an infection and your body order, the smells coming from 51 00:04:05,400 --> 00:04:10,000 Speaker 1: your body change, which is detectable by mosquitoes. So mosquitoes 52 00:04:10,040 --> 00:04:13,600 Speaker 1: find you more attractive when you have a malaria infection, 53 00:04:14,040 --> 00:04:16,200 Speaker 1: and we wondered whether dogs could do the same. So 54 00:04:16,320 --> 00:04:19,719 Speaker 1: we did a study to see whether dogs were able 55 00:04:19,760 --> 00:04:22,480 Speaker 1: to pick up on this smell. And the amazing thing 56 00:04:22,480 --> 00:04:25,160 Speaker 1: about dogs is they've got an incredible sense of smell. 57 00:04:25,200 --> 00:04:28,720 Speaker 1: We've got a very very sensitive nose, but they are 58 00:04:28,760 --> 00:04:33,240 Speaker 1: also able to learn and they can learn smells. James says, 59 00:04:33,320 --> 00:04:36,719 Speaker 1: the dogs are highly effective at identifying people with malaria, 60 00:04:37,000 --> 00:04:40,400 Speaker 1: even those people who aren't displaying any signs of the disease. 61 00:04:41,000 --> 00:04:44,320 Speaker 1: It's opened up a new line of research investigating the 62 00:04:44,360 --> 00:04:49,560 Speaker 1: potential to train cardres of corona catching canines. So we 63 00:04:49,640 --> 00:04:54,400 Speaker 1: know that diseases have orders. We know this. We know 64 00:04:54,520 --> 00:04:58,560 Speaker 1: that respiratory type diseases like influenza, for example, also have 65 00:04:58,800 --> 00:05:02,800 Speaker 1: orders and they're quite things. So um, there is a 66 00:05:02,920 --> 00:05:07,000 Speaker 1: very very good chance that COVID ninety also has a 67 00:05:07,080 --> 00:05:12,480 Speaker 1: distinctive order. And if it does, then I am really 68 00:05:12,520 --> 00:05:15,680 Speaker 1: confident that the dogs would be able to learn that 69 00:05:15,760 --> 00:05:19,960 Speaker 1: smell and detected. In Finland and doctor Anna hum Yorkman 70 00:05:20,080 --> 00:05:22,919 Speaker 1: is a senior researcher in the Department of Equine and 71 00:05:23,040 --> 00:05:26,800 Speaker 1: Small Animal Medicine at the University of Helsinki. She's worked 72 00:05:26,839 --> 00:05:30,159 Speaker 1: with dogs for years and when the pandemic started, it's 73 00:05:30,160 --> 00:05:34,240 Speaker 1: saying natural to test out their smelling pross and we 74 00:05:34,240 --> 00:05:38,000 Speaker 1: were fortunate or unfortunate to have a lot of people 75 00:05:38,040 --> 00:05:42,920 Speaker 1: who had corona in in kind of of our near 76 00:05:43,160 --> 00:05:45,960 Speaker 1: family and friends, so we got a lot of samples 77 00:05:46,920 --> 00:05:50,280 Speaker 1: that we were able to pilot with, and in this 78 00:05:50,400 --> 00:05:55,719 Speaker 1: pilot we could see that the dogs actually had no 79 00:05:55,960 --> 00:06:01,440 Speaker 1: trouble at all uh finding the virus, so they were 80 00:06:02,920 --> 00:06:05,720 Speaker 1: I thought it was actually kind of a an easy 81 00:06:05,760 --> 00:06:10,520 Speaker 1: smell compared to to the different type of cancer as 82 00:06:10,560 --> 00:06:18,559 Speaker 1: they've been smelling before. To be clear, Anna wasn't using 83 00:06:18,640 --> 00:06:21,680 Speaker 1: any old MutS for this experiment. The two dogs she 84 00:06:21,800 --> 00:06:24,920 Speaker 1: put to the test were professional sniffers with proven all 85 00:06:25,000 --> 00:06:29,000 Speaker 1: factory skills. But there's another trait that Anna looks for 86 00:06:29,040 --> 00:06:35,560 Speaker 1: in a detected dog, a good appetite. The thing that 87 00:06:35,640 --> 00:06:39,200 Speaker 1: you you train them with is treats, and if they're 88 00:06:39,240 --> 00:06:43,160 Speaker 1: not very interested in food treats or other like play 89 00:06:43,320 --> 00:06:45,920 Speaker 1: or something like that, it's very hard to get them 90 00:06:45,920 --> 00:06:50,400 Speaker 1: to learn anything. So they don't actually have to be 91 00:06:50,480 --> 00:06:54,040 Speaker 1: a certain breed or a certain age or a certain sex. 92 00:06:54,640 --> 00:06:57,839 Speaker 1: It's mostly these two things that are important. When the 93 00:06:57,880 --> 00:07:00,240 Speaker 1: dogs were put to the test, they detect did the 94 00:07:00,240 --> 00:07:03,600 Speaker 1: coronavirus in two people who had tested negative for COVID, 95 00:07:04,120 --> 00:07:06,159 Speaker 1: and it says she wondered whether it was too big 96 00:07:06,160 --> 00:07:08,640 Speaker 1: a challenge for the poachers, but she gave them the 97 00:07:08,640 --> 00:07:12,880 Speaker 1: benefit of the town. We first thought that, okay, that 98 00:07:13,080 --> 00:07:15,640 Speaker 1: this is maybe not so so easy for the dogs 99 00:07:15,680 --> 00:07:19,840 Speaker 1: because they kind of were not on the They didn't 100 00:07:20,000 --> 00:07:23,480 Speaker 1: have the same opinion about the samples as did the 101 00:07:23,520 --> 00:07:29,360 Speaker 1: tests that had been taken. And since we've been working 102 00:07:29,360 --> 00:07:33,400 Speaker 1: with dogs for for five years, just with biological samples, 103 00:07:33,440 --> 00:07:36,440 Speaker 1: we know that mostly they're rights and we're wrong. So 104 00:07:36,560 --> 00:07:39,600 Speaker 1: An and the colleagues asked those two people to get retested, 105 00:07:40,440 --> 00:07:43,440 Speaker 1: and actually both of them had developed the corona as 106 00:07:43,440 --> 00:07:46,640 Speaker 1: a disease in the meanwhile. So one of them was 107 00:07:46,760 --> 00:07:51,880 Speaker 1: four days tested before and one of them was five 108 00:07:52,000 --> 00:07:55,760 Speaker 1: days tested before, and the dog could smell them then 109 00:07:55,920 --> 00:07:59,800 Speaker 1: already before before kind of the clinical disease erupted in 110 00:07:59,840 --> 00:08:03,400 Speaker 1: the people. Anna is doing more research to verify and 111 00:08:03,520 --> 00:08:07,360 Speaker 1: validate these initial findings. She says more work is needed 112 00:08:07,400 --> 00:08:10,640 Speaker 1: to clarify what the dogs are identifying in patient samples 113 00:08:11,080 --> 00:08:14,280 Speaker 1: and how long the smell stays after the infection has passed, 114 00:08:14,800 --> 00:08:17,640 Speaker 1: but she's hoping to publish the results in a scientific journal, 115 00:08:18,120 --> 00:08:21,440 Speaker 1: and like James Logan in London, she's optimistic about what 116 00:08:21,520 --> 00:08:24,680 Speaker 1: dogs could bring to the COVID screening table given their 117 00:08:24,800 --> 00:08:30,280 Speaker 1: proven utility across the number of areas. We have about 118 00:08:30,440 --> 00:08:35,440 Speaker 1: thirty different kind of professions that dogs do. We have 119 00:08:35,559 --> 00:08:43,120 Speaker 1: dogs that are are alarming for for cancer, for epilepsy, 120 00:08:43,400 --> 00:08:50,120 Speaker 1: for chronic pain, for diabetes patients. We've got dogs that 121 00:08:50,200 --> 00:08:54,640 Speaker 1: are are trained to look for explosives and drugs and 122 00:08:54,720 --> 00:08:59,840 Speaker 1: money and whatnot. So so it's actually not far fetched 123 00:09:00,160 --> 00:09:04,000 Speaker 1: dogs can can do this. So just having a dog 124 00:09:04,120 --> 00:09:09,640 Speaker 1: standing by the customs when when people come into countries, 125 00:09:09,679 --> 00:09:13,840 Speaker 1: for example, they can scan up to one human beings 126 00:09:13,880 --> 00:09:19,640 Speaker 1: an hour. So that's a totally other scale of potential 127 00:09:19,920 --> 00:09:24,600 Speaker 1: that that we're we're seeing in kind of testing people. 128 00:09:24,640 --> 00:09:28,640 Speaker 1: And also it's it's instantly with additional funding, and it 129 00:09:28,720 --> 00:09:31,080 Speaker 1: says it might be possible to train fifty dogs in 130 00:09:31,080 --> 00:09:34,120 Speaker 1: Finland to scout for people carrying the coronavirus, ready for 131 00:09:34,160 --> 00:09:37,320 Speaker 1: when cooler weather later in the year risks bringing a 132 00:09:37,360 --> 00:09:41,280 Speaker 1: new wave of infections. James Logan says it takes about 133 00:09:41,480 --> 00:09:43,439 Speaker 1: four to six weeks to train a dog to seek 134 00:09:43,440 --> 00:09:46,319 Speaker 1: out a new smell. He's hoping to have dogs ready 135 00:09:46,320 --> 00:09:49,360 Speaker 1: to deploy in two to three months for the cost 136 00:09:49,360 --> 00:09:52,440 Speaker 1: of a treat. Recruiting man's best friend to help screen 137 00:09:52,520 --> 00:09:56,080 Speaker 1: for COVID makes a lot of sense, and anyone who 138 00:09:56,200 --> 00:09:59,360 Speaker 1: suffered the indignity of an eye watering swab way up 139 00:09:59,400 --> 00:10:03,160 Speaker 1: the nose can tell you being screened by a dog 140 00:10:03,320 --> 00:10:15,640 Speaker 1: can only be an improvement. That was Jason Gayle in Melbourne, 141 00:10:16,200 --> 00:10:19,080 Speaker 1: And that's our show today. For coverage of the outbreak 142 00:10:19,160 --> 00:10:22,559 Speaker 1: from one and twenty bureaus around the world, visit bloomberg 143 00:10:22,600 --> 00:10:26,920 Speaker 1: dot com Flash Coronavirus and if you like the show, 144 00:10:27,559 --> 00:10:30,040 Speaker 1: please leave us a review and a rating on Apple 145 00:10:30,120 --> 00:10:33,679 Speaker 1: Podcasts or Spotify. It's the best way to help more 146 00:10:33,720 --> 00:10:38,520 Speaker 1: listeners find our global reporting. The Prognosis Daily edition is 147 00:10:38,520 --> 00:10:43,559 Speaker 1: produced by tophor Forehaz, Jordan Gospore, Magnus Hendrickson and me 148 00:10:44,200 --> 00:10:49,079 Speaker 1: Laura Carlson. Today's main story was reported by Jason Gaal, 149 00:10:49,520 --> 00:10:54,720 Speaker 1: Francis Schwartzkoff and fergos O Sullivan. Special thanks to Arabella Gayle, 150 00:10:55,200 --> 00:11:00,000 Speaker 1: Georgie Gayle and their great pup Merlin. Original music by 151 00:11:00,120 --> 00:11:04,240 Speaker 1: Leo Sidron. Our editors are Francesco Levi and Rick Shawn. 152 00:11:04,960 --> 00:11:09,440 Speaker 1: Francesco Levi is Bloomberg's head of Podcasts. Thanks for listening.