1 00:00:05,200 --> 00:00:08,600 Speaker 1: It's ninety degrees out and I'm covered in bug spray, 2 00:00:08,960 --> 00:00:10,880 Speaker 1: lying on the dirt floor of a hut with a 3 00:00:10,960 --> 00:00:14,320 Speaker 1: roof made of palms. A woman is pressing hard on 4 00:00:14,400 --> 00:00:24,480 Speaker 1: my stomach. She's telling me something is wrong. Look here, hey, 5 00:00:23,720 --> 00:00:30,400 Speaker 1: hap happy? The woman forcefully massaging my belly is She's 6 00:00:30,400 --> 00:00:34,320 Speaker 1: a a kind of traditional healer in the Yucatan region 7 00:00:34,360 --> 00:00:37,680 Speaker 1: of Mexico. Pregnant women come to her from nearby to 8 00:00:37,720 --> 00:00:41,280 Speaker 1: make sure that the whole childbirth experience is safe, kind 9 00:00:41,320 --> 00:00:44,800 Speaker 1: of like a duela. The massage she's giving me is 10 00:00:44,840 --> 00:00:47,760 Speaker 1: one of the sort of services she performs for her clients. 11 00:00:48,600 --> 00:00:51,479 Speaker 1: It does a bunch of things, including putting the baby 12 00:00:51,479 --> 00:00:54,400 Speaker 1: in a head down position for labor or calming the 13 00:00:54,440 --> 00:01:03,720 Speaker 1: client's nerves. Okay, that this massage, though it did not 14 00:01:03,880 --> 00:01:09,560 Speaker 1: exactly call my nerves while massaging me, tells me that 15 00:01:09,720 --> 00:01:14,600 Speaker 1: something of mine called isn't where it should be. This 16 00:01:14,760 --> 00:01:17,800 Speaker 1: probably isn't a body part you've ever heard of, but 17 00:01:17,920 --> 00:01:21,959 Speaker 1: in my own culture, here is an organ believed to 18 00:01:22,000 --> 00:01:25,320 Speaker 1: be found in your mid section. After you have a baby, 19 00:01:25,680 --> 00:01:28,960 Speaker 1: a time where your organs are really shifted around. You're 20 00:01:28,959 --> 00:01:31,920 Speaker 1: supposed to come back twelve days after delivery to get 21 00:01:31,959 --> 00:01:36,800 Speaker 1: a massage from someone like During that she makes sure 22 00:01:36,840 --> 00:01:39,520 Speaker 1: that your sto is where it should be and massages 23 00:01:39,520 --> 00:01:42,480 Speaker 1: it back into place if it isn't. The belief here, 24 00:01:42,959 --> 00:01:45,880 Speaker 1: though it isn't backed up by modern medicine, is that 25 00:01:45,920 --> 00:01:48,680 Speaker 1: with it out of place, you can experience back pain, 26 00:01:49,080 --> 00:01:53,200 Speaker 1: stomach issues, and anxiety. They believe you can pass along 27 00:01:53,280 --> 00:01:55,800 Speaker 1: some of those issues to your baby if you breastfeed too. 28 00:01:56,840 --> 00:02:00,400 Speaker 1: I'm way past that twelve day mark. How to baby 29 00:02:00,440 --> 00:02:10,320 Speaker 1: a year ago? So why am I hair exactly? I'm 30 00:02:10,400 --> 00:02:14,880 Speaker 1: Kelsey Butler, a reporter on Bloomberg's A Quality Team. When 31 00:02:14,880 --> 00:02:17,240 Speaker 1: I got pregnant in the middle of the pandemic, I 32 00:02:17,280 --> 00:02:19,760 Speaker 1: was living in New Jersey. The state was one of 33 00:02:19,800 --> 00:02:23,560 Speaker 1: the highest maternal mortality rates in the US, and the 34 00:02:23,600 --> 00:02:26,680 Speaker 1: numbers were the worst for women like me, who are black. 35 00:02:27,480 --> 00:02:29,919 Speaker 1: The death rate was made even scarier by the prospect 36 00:02:29,919 --> 00:02:32,760 Speaker 1: of getting COVID, which I knew made the chances of 37 00:02:32,800 --> 00:02:36,960 Speaker 1: complications for both me and my baby even higher. I 38 00:02:37,160 --> 00:02:41,079 Speaker 1: thankfully had a mostly complication free birth. My son turned 39 00:02:41,120 --> 00:02:44,280 Speaker 1: one last month, but it got me thinking about maternal health, 40 00:02:45,080 --> 00:02:47,080 Speaker 1: and when I started looking into it, I found an 41 00:02:47,080 --> 00:02:51,600 Speaker 1: even more shocking statistic, just a little bit south. For years, 42 00:02:51,720 --> 00:02:56,000 Speaker 1: maternal mortality had been improving in Mexico. Then the pandemic 43 00:02:56,080 --> 00:02:59,160 Speaker 1: hit and the rate for maternal deaths climbed over sixty. 44 00:03:00,360 --> 00:03:03,320 Speaker 1: So I jumped on a plane to Mexico to find 45 00:03:03,360 --> 00:03:09,119 Speaker 1: out what happened. Jobless claims coming in, I mean really 46 00:03:09,200 --> 00:03:12,880 Speaker 1: jumping from the week before, pretty brutal. Three point to 47 00:03:13,280 --> 00:03:16,800 Speaker 1: a million records. Six point six million Americans filed for 48 00:03:16,840 --> 00:03:21,480 Speaker 1: unemployment last week. Indian working women were the worst impacted 49 00:03:21,560 --> 00:03:27,359 Speaker 1: by the pandemic. If so divid like Umia, Well, now 50 00:03:27,440 --> 00:03:31,480 Speaker 1: to the billionaire boom. According to Bloomberg's super yacht charters 51 00:03:31,840 --> 00:03:36,040 Speaker 1: are up over three hut and a billionaire was created 52 00:03:36,200 --> 00:03:40,160 Speaker 1: every twenty six hours during this pandemic. It is time 53 00:03:40,360 --> 00:03:49,320 Speaker 1: for a wealth tax in America. Welcome back to the paycheck. 54 00:03:49,920 --> 00:03:53,840 Speaker 1: I'm Rebecca Greenfield. Among the many things that have determined 55 00:03:53,880 --> 00:03:57,360 Speaker 1: how a country has fared economically during the pandemic is 56 00:03:57,400 --> 00:04:01,280 Speaker 1: how government's decided to manage the virus that's off. Some 57 00:04:01,400 --> 00:04:05,680 Speaker 1: places opted for a COVID zero strategy, going to extreme 58 00:04:05,760 --> 00:04:09,400 Speaker 1: lengths to keep the virus out of their borders. Others 59 00:04:09,480 --> 00:04:12,920 Speaker 1: had more of a letter rip strategy, keeping the economy 60 00:04:13,000 --> 00:04:16,480 Speaker 1: and businesses open with little regard for the virus itself, 61 00:04:17,000 --> 00:04:21,480 Speaker 1: and many places where somewhere in between. Each approach comes 62 00:04:21,480 --> 00:04:26,520 Speaker 1: with costs, though some are much higher than others. Mexico 63 00:04:26,680 --> 00:04:29,919 Speaker 1: is a country that chose its economy over everything else. 64 00:04:30,839 --> 00:04:33,880 Speaker 1: A few months into the pandemic, the government slowly started 65 00:04:33,920 --> 00:04:38,359 Speaker 1: lifting restrictions. That's my colleague Andrea Navarro. She's a reporter 66 00:04:38,480 --> 00:04:41,080 Speaker 1: in Mexico City. We were one of the few places 67 00:04:41,120 --> 00:04:43,720 Speaker 1: in the world where we never really had any travel 68 00:04:43,800 --> 00:04:47,080 Speaker 1: restrictions of any kind. So things went back to normal 69 00:04:47,320 --> 00:04:52,240 Speaker 1: relatively quickly. Here Andrea usually covers Mexico's economy, but for 70 00:04:52,279 --> 00:04:55,000 Speaker 1: the last two and a half years she's been covering COVID. 71 00:04:55,520 --> 00:05:00,159 Speaker 1: She told me as early as before vaccines, Mexico is 72 00:05:00,200 --> 00:05:04,359 Speaker 1: open for business. To understand this approach, Andrea says, you 73 00:05:04,400 --> 00:05:09,400 Speaker 1: have to understand Mexico's president. Andrea's Manuel Lopez Obrador, who's 74 00:05:09,440 --> 00:05:14,000 Speaker 1: known more colloquially as Amlo. Amlo can be described as 75 00:05:14,000 --> 00:05:17,320 Speaker 1: a populist, and what that means is that he will 76 00:05:17,360 --> 00:05:20,840 Speaker 1: basically say and do anything that he says will be 77 00:05:20,880 --> 00:05:24,320 Speaker 1: popular with his base, which is very big. Am Lo 78 00:05:24,440 --> 00:05:28,200 Speaker 1: caters to Mexico's poorest people, many who work in the 79 00:05:28,240 --> 00:05:31,800 Speaker 1: informal and service economies, the people who run things like 80 00:05:31,839 --> 00:05:35,080 Speaker 1: street cards, and if they aren't allowed to operate or 81 00:05:35,200 --> 00:05:38,440 Speaker 1: all their customers are stuck in quarantine, they can't earn 82 00:05:38,440 --> 00:05:42,479 Speaker 1: a living, and unlike richer countries, Mexico didn't have the 83 00:05:42,520 --> 00:05:46,000 Speaker 1: money to just pay people to stay home. Plus, am 84 00:05:46,080 --> 00:05:49,479 Speaker 1: Low hates debt, so he basically let COVID run free 85 00:05:49,520 --> 00:05:53,279 Speaker 1: and the hopes that the economy would survive. Andrea says 86 00:05:53,480 --> 00:05:57,279 Speaker 1: the strategy allowed Mexico to keep a balanced budget. The 87 00:05:57,279 --> 00:06:01,400 Speaker 1: paso has also remained relatively stable, and there are no 88 00:06:01,480 --> 00:06:04,919 Speaker 1: worries about the country defaulting on its debt. But it 89 00:06:05,000 --> 00:06:08,760 Speaker 1: also had some nasty knock on effects, particularly on Mexico's 90 00:06:08,800 --> 00:06:11,920 Speaker 1: health care system. It's safe to say that the healthcare 91 00:06:12,000 --> 00:06:17,360 Speaker 1: system collapsed, Andrea says. During the worst wave, ambulances would 92 00:06:17,360 --> 00:06:21,640 Speaker 1: circle all night looking for empty hospital beds. So far, 93 00:06:21,839 --> 00:06:26,560 Speaker 1: Mexico has lost three people to COVID, which is high 94 00:06:26,680 --> 00:06:30,040 Speaker 1: enough on its own, but it lost another five hundred 95 00:06:30,080 --> 00:06:33,760 Speaker 1: thousand people to what are known as excess deaths, people 96 00:06:33,800 --> 00:06:36,280 Speaker 1: who shouldn't have died but couldn't get the care they 97 00:06:36,320 --> 00:06:40,680 Speaker 1: needed due to COVID, and among those were many pregnant 98 00:06:40,760 --> 00:06:46,080 Speaker 1: and childbearing women. Before the pandemic, Mexico's maternal mortality rate, 99 00:06:46,440 --> 00:06:49,400 Speaker 1: while still high, had been moving in the right direction. 100 00:06:50,040 --> 00:06:53,839 Speaker 1: Over two decades, it had dropped by half. The pandemic 101 00:06:53,839 --> 00:06:57,560 Speaker 1: erased most of those games. About two thousand women have 102 00:06:57,720 --> 00:07:01,359 Speaker 1: died in childbirth or soon after Mexico since the start 103 00:07:01,360 --> 00:07:04,599 Speaker 1: of the pandemic. My colleague Kelsey went down to Mexico 104 00:07:04,720 --> 00:07:14,280 Speaker 1: to investigate back to her for the story. I ended 105 00:07:14,320 --> 00:07:16,720 Speaker 1: up in Mexico after I heard the story of getting 106 00:07:16,840 --> 00:07:21,760 Speaker 1: Viejo Costito in January getting checked into a hospital in 107 00:07:21,880 --> 00:07:25,800 Speaker 1: Baja California to have her second baby. She was a healthy, 108 00:07:25,880 --> 00:07:29,000 Speaker 1: thirty one year old woman getting had a c section. 109 00:07:30,160 --> 00:07:34,040 Speaker 1: They're common generally speaking, but they're especially popular in Mexico, 110 00:07:34,320 --> 00:07:36,400 Speaker 1: which has one of the highest c section rates in 111 00:07:36,480 --> 00:07:40,120 Speaker 1: the world, and during the pandemic, the c section rate 112 00:07:40,520 --> 00:07:44,360 Speaker 1: jumped even higher. Hospitals were too maxed out and short 113 00:07:44,440 --> 00:07:47,520 Speaker 1: on time to let labor happen on its own. The 114 00:07:47,680 --> 00:07:49,920 Speaker 1: rates in the first year of the pandemic were more 115 00:07:50,000 --> 00:07:55,200 Speaker 1: than three times what the World Health Organization recommends. Because 116 00:07:55,280 --> 00:07:58,880 Speaker 1: c sections, though life saving and necessary in some cases, 117 00:07:59,280 --> 00:08:03,480 Speaker 1: carry greater risk of complications like infections or blood cloths 118 00:08:03,840 --> 00:08:07,000 Speaker 1: then giving birth the old fashioned way. It's also major 119 00:08:07,080 --> 00:08:10,920 Speaker 1: surgery and recovery is tougher to Just after gett in 120 00:08:11,000 --> 00:08:13,640 Speaker 1: c section, her family was sent home and told to 121 00:08:13,680 --> 00:08:18,840 Speaker 1: come back later. Everything seemed fine. They were told she 122 00:08:19,040 --> 00:08:23,720 Speaker 1: just needed some rust. But when Gatton's family returned, she 123 00:08:23,960 --> 00:08:29,480 Speaker 1: was dead. Her sister, Anna Maria Vaejo found her in 124 00:08:29,560 --> 00:08:35,480 Speaker 1: her hospital room. I talked to Anna on the phone 125 00:08:35,480 --> 00:08:40,079 Speaker 1: about this, which she described was heartbreaking. Anna says that 126 00:08:40,160 --> 00:08:43,480 Speaker 1: when she went to touch her sister, Gaydon was freezing. 127 00:08:44,120 --> 00:08:47,319 Speaker 1: Her arms dropped to her side, completely limp. It was 128 00:08:47,400 --> 00:08:53,079 Speaker 1: as if she had been dead for hours. The official 129 00:08:53,160 --> 00:08:56,319 Speaker 1: cause of death was listed as a hemorrhage or excessive bleeding, 130 00:08:56,960 --> 00:08:59,520 Speaker 1: one of the top causes from maternal death in Mexico 131 00:08:59,640 --> 00:09:03,760 Speaker 1: right now, just ahead of COVID. But Getton's family didn't 132 00:09:03,800 --> 00:09:10,760 Speaker 1: understand how things went so wrong. So quickly Anna told 133 00:09:10,840 --> 00:09:13,560 Speaker 1: me she asked the doctors how in the world that happened. 134 00:09:14,320 --> 00:09:17,760 Speaker 1: The family filed an official complaint, which triggered an autopsy, 135 00:09:18,400 --> 00:09:20,840 Speaker 1: but when her body was delivered to the medical examiner, 136 00:09:21,400 --> 00:09:23,199 Speaker 1: they were told they wouldn't be able to give the 137 00:09:23,240 --> 00:09:27,280 Speaker 1: family any answers because her organs were already removed from 138 00:09:27,320 --> 00:09:32,120 Speaker 1: her body. That's really odd. An official at the Medical 139 00:09:32,160 --> 00:09:34,960 Speaker 1: Examiner's office said it was the first time he had 140 00:09:35,000 --> 00:09:39,160 Speaker 1: seen something like that. The hospital, meanwhile, said it followed 141 00:09:39,200 --> 00:09:44,120 Speaker 1: protocol and removing Giddon's organs during its own autopsy. The 142 00:09:44,240 --> 00:09:47,440 Speaker 1: family wonders if doctors were trying to cover something up. 143 00:09:49,000 --> 00:10:00,040 Speaker 1: News outlets started picking up the story getting by that 144 00:10:00,480 --> 00:10:07,319 Speaker 1: is Eli. The story went viral locally. The pictures of 145 00:10:07,400 --> 00:10:10,040 Speaker 1: getting from her social media accounts put a face to 146 00:10:10,120 --> 00:10:15,959 Speaker 1: the brutal details. Women shared their own stories of mised appointments, negligence, 147 00:10:16,320 --> 00:10:21,319 Speaker 1: and bad treatment during their pregnancies. In February, people protested 148 00:10:21,320 --> 00:10:33,880 Speaker 1: in the streets. So that's almost gidding. We are all gidding. 149 00:10:50,360 --> 00:10:54,280 Speaker 1: Maternal mortality was already high in Mexico, but a perfect 150 00:10:54,360 --> 00:10:56,959 Speaker 1: storm of bad decisions made by the government during the 151 00:10:57,040 --> 00:11:02,320 Speaker 1: pandemic created a nightmare scenario for giving birth. The problem 152 00:11:02,440 --> 00:11:07,360 Speaker 1: started in the months before the pandemic. Mexico's President m 153 00:11:07,480 --> 00:11:11,520 Speaker 1: Low decided to overhaul the country's healthcare system to eventually 154 00:11:11,600 --> 00:11:24,160 Speaker 1: make it entirely free for everyone. Plar. The move couldn't 155 00:11:24,160 --> 00:11:26,720 Speaker 1: have come at a worse time. The news system wasn't 156 00:11:26,800 --> 00:11:30,720 Speaker 1: up and running, were fully funded. When the pandemic overwhelmed 157 00:11:30,840 --> 00:11:36,000 Speaker 1: Mexican hospitals, chaos ensued. There were drug shortages and not 158 00:11:36,240 --> 00:11:39,800 Speaker 1: enough hospital beds, and then one really bad decision made 159 00:11:39,840 --> 00:11:44,199 Speaker 1: it all worse. So when the pandemic started, there was 160 00:11:44,360 --> 00:11:49,040 Speaker 1: something called reconversion, hospital re conversion, and I think it 161 00:11:49,280 --> 00:11:53,599 Speaker 1: was not the best idea. That's Mina Mendez Dominguez, a 162 00:11:53,720 --> 00:11:58,079 Speaker 1: physician and researcher who studies maternal health in Mexico. She's 163 00:11:58,120 --> 00:12:01,360 Speaker 1: based in Mediva, a city of one point two million 164 00:12:01,440 --> 00:12:05,240 Speaker 1: people on Mexico's You've Got Them Peninsula. But I first 165 00:12:05,320 --> 00:12:07,640 Speaker 1: met her at a conference in New York in April. 166 00:12:08,240 --> 00:12:11,440 Speaker 1: Nina told me to deal with the influx of COVID patients, 167 00:12:12,040 --> 00:12:15,360 Speaker 1: the government decided to convert many big hospitals around the 168 00:12:15,440 --> 00:12:20,240 Speaker 1: country into COVID only facilities, meaning no one could be 169 00:12:20,360 --> 00:12:24,959 Speaker 1: treated for anything else, not heart attacks, not gunshot wounds, 170 00:12:25,720 --> 00:12:29,480 Speaker 1: not even childbirth. It was Nina and her colleagues research 171 00:12:29,559 --> 00:12:33,240 Speaker 1: that uncovered that first statistic that really shocked me, that 172 00:12:33,360 --> 00:12:36,160 Speaker 1: there had been a sixty jump in the maternal mortality 173 00:12:36,240 --> 00:12:40,440 Speaker 1: rate in Mexico during the pandemic. Other countries in Latin America, 174 00:12:40,840 --> 00:12:45,160 Speaker 1: like Brazil and Peru also had big jumps. Those COVID 175 00:12:45,200 --> 00:12:48,000 Speaker 1: only hospital conversions played a big part in the deaths. 176 00:12:48,160 --> 00:12:52,120 Speaker 1: She told me. What happened was that non essential medical 177 00:12:52,200 --> 00:12:57,960 Speaker 1: consultations were not available, but also nurses and oldest staff 178 00:12:58,200 --> 00:13:03,480 Speaker 1: were moved from certain hospitals to other hospitals. In other words, 179 00:13:04,000 --> 00:13:06,600 Speaker 1: even the hospitals that would see pregnant women were short 180 00:13:06,679 --> 00:13:09,520 Speaker 1: staffed because their staff had been sent to deal with COVID. 181 00:13:10,200 --> 00:13:12,240 Speaker 1: This led to a lot of problems for people with 182 00:13:12,360 --> 00:13:16,320 Speaker 1: all kinds of health emergencies, but it was particularly dangerous 183 00:13:16,520 --> 00:13:19,880 Speaker 1: for pregnant women, especially pregnant women who lived far away 184 00:13:19,920 --> 00:13:23,560 Speaker 1: from a hospital. Outside of the big cities, the only 185 00:13:23,640 --> 00:13:27,200 Speaker 1: nearby hospital or health clinic was reserved just for COVID patients. 186 00:13:27,760 --> 00:13:29,760 Speaker 1: In the remote region of you got done. Where I 187 00:13:29,840 --> 00:13:33,840 Speaker 1: saw someone in labor could be hours from the nearest 188 00:13:33,880 --> 00:13:36,840 Speaker 1: place that could deliver a baby or even do standard 189 00:13:37,000 --> 00:13:41,120 Speaker 1: pre and postnatal care. The first contact in rural areas 190 00:13:41,200 --> 00:13:46,000 Speaker 1: were not priority because they treat very small amount of people, 191 00:13:46,160 --> 00:13:53,640 Speaker 1: so then they stopped all the maternal consultations, and women 192 00:13:54,160 --> 00:13:58,400 Speaker 1: feared to travel to the urban areas and then go 193 00:13:58,559 --> 00:14:01,280 Speaker 1: to the hospital because they knew there were patients that 194 00:14:01,480 --> 00:14:05,720 Speaker 1: were sick over there already. Basically, pregnant women who already 195 00:14:05,760 --> 00:14:08,960 Speaker 1: lived far from medical care might now be even further 196 00:14:09,200 --> 00:14:11,760 Speaker 1: from somewhere that would treat them, and they also might 197 00:14:11,800 --> 00:14:14,240 Speaker 1: be scared to go there because there was more risk 198 00:14:14,320 --> 00:14:18,280 Speaker 1: of catching COVID. Henny Carrillo, a professor at Texas A 199 00:14:18,280 --> 00:14:21,040 Speaker 1: and M University who worked with Nina on the research, 200 00:14:21,200 --> 00:14:24,960 Speaker 1: put it bluntly, so what happened pregnant women did not 201 00:14:25,160 --> 00:14:28,280 Speaker 1: attend the routine checobs. All these decisions had a repel 202 00:14:28,320 --> 00:14:32,040 Speaker 1: effect henn He says not all paternal dates in Mexico 203 00:14:32,120 --> 00:14:36,880 Speaker 1: were directly related to COVID inflation, but rather to uncontrolled 204 00:14:36,960 --> 00:14:42,400 Speaker 1: conditions during pregnancy due to the limited hay care availability 205 00:14:42,920 --> 00:14:46,240 Speaker 1: that these women had to face. Nina told me about 206 00:14:46,320 --> 00:14:48,720 Speaker 1: one case while doing her research that's stuck with her. 207 00:14:49,720 --> 00:14:51,520 Speaker 1: She told me about a young woman who showed upbout 208 00:14:51,520 --> 00:14:55,440 Speaker 1: a remote hospital with a rare, life threatening pregnancy complication 209 00:14:55,680 --> 00:14:59,280 Speaker 1: called help syndrome. The first facility she went to didn't 210 00:14:59,320 --> 00:15:01,600 Speaker 1: catch it. By the time she got to the next 211 00:15:01,960 --> 00:15:05,840 Speaker 1: it was too late. She started bleeding internally and was 212 00:15:05,920 --> 00:15:10,960 Speaker 1: taken to surgery. The end result was tragic. She just 213 00:15:11,080 --> 00:15:14,600 Speaker 1: passed away, and it was so sad because her family 214 00:15:14,880 --> 00:15:18,000 Speaker 1: came after and she was already gone. It's these kinds 215 00:15:18,000 --> 00:15:20,160 Speaker 1: of cases that stick with Nina because they're part of 216 00:15:20,240 --> 00:15:23,880 Speaker 1: a common pattern unnecessary roadblocks that make it hard for 217 00:15:24,000 --> 00:15:29,120 Speaker 1: people to safely have babies. Emergencies were especially dangerous for 218 00:15:29,200 --> 00:15:31,400 Speaker 1: women in the thick of COVID because it took so 219 00:15:31,680 --> 00:15:34,240 Speaker 1: long for them to get to treatment and be seen 220 00:15:34,320 --> 00:15:38,440 Speaker 1: by doctors. It became so difficult for a woman, for 221 00:15:38,560 --> 00:15:43,600 Speaker 1: a pregnant woman to move from her house to find 222 00:15:44,040 --> 00:15:48,040 Speaker 1: medical attention that it ended up so bad. You get 223 00:15:48,080 --> 00:15:51,160 Speaker 1: done where Nina is based, so the highest level of 224 00:15:51,280 --> 00:15:55,680 Speaker 1: maternal deaths and more than a decade, it's a problem 225 00:15:55,760 --> 00:15:58,960 Speaker 1: that is leaving too many women behind. She says, pregnancy 226 00:15:59,320 --> 00:16:05,160 Speaker 1: should be a very positive experience. Bringing children to life 227 00:16:05,440 --> 00:16:09,880 Speaker 1: should be such an important event that we should all 228 00:16:10,240 --> 00:16:15,160 Speaker 1: enjoy this process and it should be equal for all 229 00:16:15,240 --> 00:16:19,040 Speaker 1: women in all the world. But at a virtual event 230 00:16:19,160 --> 00:16:24,480 Speaker 1: in February, Zoe Lejano, head of the Mexican Institute of 231 00:16:24,560 --> 00:16:29,560 Speaker 1: Social Security, said the country. Strategy had been quote very 232 00:16:29,800 --> 00:16:35,320 Speaker 1: very focused on hospital reconversion unquote, so that doctors wouldn't 233 00:16:35,360 --> 00:16:40,160 Speaker 1: be forced to decide which COVID patients lived and which died. 234 00:16:41,160 --> 00:16:45,400 Speaker 1: He went on to say, quote Mexico's model was growing 235 00:16:45,480 --> 00:16:50,320 Speaker 1: the capacity for care, so there were zero rejections unquote, 236 00:16:53,280 --> 00:16:56,880 Speaker 1: and barras or midwives are stepping in to fill some 237 00:16:57,000 --> 00:16:59,480 Speaker 1: of these gaps in a health care system they say 238 00:16:59,600 --> 00:17:04,200 Speaker 1: isn't working for women, but they can't fix everything. I 239 00:17:04,280 --> 00:17:07,080 Speaker 1: called one of these women who has been delivering babies 240 00:17:07,200 --> 00:17:12,240 Speaker 1: for over thirty years. Her name is Guada up She's 241 00:17:12,280 --> 00:17:16,640 Speaker 1: the president of the Association of Professional Midwives in Mexico City. Joe, 242 00:17:22,240 --> 00:17:24,920 Speaker 1: I have been delivering babies for more than thirty years 243 00:17:25,040 --> 00:17:29,360 Speaker 1: outside of hospital settings, in homes or in birthing centers, 244 00:17:29,880 --> 00:17:34,600 Speaker 1: under very strict protocols to ensure the security and safety 245 00:17:34,960 --> 00:17:39,480 Speaker 1: of both mother and baby. Told me she was afraid 246 00:17:39,520 --> 00:17:42,840 Speaker 1: to treat women early in the pandemic, leaving another gap 247 00:17:42,920 --> 00:17:46,160 Speaker 1: in the system for rural women. That wasn't the case 248 00:17:46,200 --> 00:17:49,520 Speaker 1: for Guada Lupe, who, during the height of COVID saw 249 00:17:49,840 --> 00:17:53,040 Speaker 1: double or triple the number of women she normally does. 250 00:17:53,880 --> 00:17:57,399 Speaker 1: That's because people either couldn't get care or we're scared 251 00:17:57,440 --> 00:18:03,040 Speaker 1: to go to traditional care facilities. See, so it was 252 00:18:03,200 --> 00:18:07,960 Speaker 1: very difficult imagine the situation running out of options and 253 00:18:08,320 --> 00:18:15,679 Speaker 1: filling on certain women began calling professional meadwifes. Now, she says, fortunately, 254 00:18:16,080 --> 00:18:19,240 Speaker 1: the maternal mortality numbers are in a much better place. 255 00:18:19,800 --> 00:18:22,920 Speaker 1: The latest government figures show the rate of maternal deaths 256 00:18:23,359 --> 00:18:26,879 Speaker 1: is at about thirty one for every one hundred thousand 257 00:18:26,960 --> 00:18:31,040 Speaker 1: babies born. That's down from fifty three deaths for every 258 00:18:31,119 --> 00:18:33,840 Speaker 1: one hundred thousand berths at the end of last year. 259 00:18:34,320 --> 00:18:36,800 Speaker 1: That's in large part because the chaos of the earliest 260 00:18:36,840 --> 00:18:40,440 Speaker 1: days of the pandemic and those hospital conversions are in 261 00:18:40,520 --> 00:18:43,680 Speaker 1: the past for now, but there's still work to do. 262 00:18:44,240 --> 00:18:47,600 Speaker 1: In two thousand, the country committed to decreasing the maternal 263 00:18:47,720 --> 00:18:51,680 Speaker 1: mortality rate to twenty two deaths for every one hundred 264 00:18:51,760 --> 00:18:55,440 Speaker 1: thousand live births. That's higher than many developed countries, but 265 00:18:55,600 --> 00:18:59,440 Speaker 1: lower than the United States rate right now. One way 266 00:18:59,520 --> 00:19:02,000 Speaker 1: to achieve eve that, Guada Lupe says, would be to 267 00:19:02,119 --> 00:19:09,320 Speaker 1: integrate midwives like herself into the health care system in Mexico. 268 00:19:11,480 --> 00:19:15,880 Speaker 1: We think that's what should happen here in Mexico. For starters, 269 00:19:16,320 --> 00:19:20,920 Speaker 1: they should insert professional midwives in the multidisciplinary team with 270 00:19:21,080 --> 00:19:24,240 Speaker 1: a budget to pay them well to stop treating them 271 00:19:24,560 --> 00:19:28,359 Speaker 1: in a denigrading way. There's evidence to back that up. 272 00:19:28,840 --> 00:19:32,280 Speaker 1: Researchers say addressing a shortage of global midwives would prevent 273 00:19:32,400 --> 00:19:36,960 Speaker 1: two and eighty thousand deaths per year by and the 274 00:19:37,040 --> 00:19:41,840 Speaker 1: World Health Organization recommends increasing education for midwives to reduce 275 00:19:41,960 --> 00:19:45,440 Speaker 1: maternal and infant deaths. Gualla Lupe says that there should 276 00:19:45,440 --> 00:19:48,720 Speaker 1: be more education for women about options outside the traditional 277 00:19:48,800 --> 00:19:52,080 Speaker 1: health care system to a system that is overwhelmed just 278 00:19:52,280 --> 00:19:54,840 Speaker 1: can't provide care to pregnant women the way they deserve. 279 00:19:57,480 --> 00:19:59,800 Speaker 1: Prenatal visit with an O B G y N that 280 00:20:00,040 --> 00:20:03,400 Speaker 1: has eighty women to see in a date, you can't 281 00:20:03,440 --> 00:20:06,320 Speaker 1: ask for quality of care, not even to give proper 282 00:20:06,400 --> 00:20:09,359 Speaker 1: advice or guidance. It's not that they don't want to, 283 00:20:09,720 --> 00:20:15,160 Speaker 1: it's that they can't. Right now, one thousand pregnant women 284 00:20:15,240 --> 00:20:20,159 Speaker 1: die each year in Mexico. Zoom out, and there are 285 00:20:20,280 --> 00:20:31,119 Speaker 1: three hundred thousand more around the world. One of the 286 00:20:31,240 --> 00:20:34,080 Speaker 1: lessons of the season for me has been that there's 287 00:20:34,200 --> 00:20:37,920 Speaker 1: no escaping the pain of the last two years. Some 288 00:20:38,080 --> 00:20:40,560 Speaker 1: places have felt that pain more than others, and in 289 00:20:40,640 --> 00:20:45,840 Speaker 1: more traumatic ways through unimaginable death tolls. But even countries 290 00:20:45,920 --> 00:20:49,560 Speaker 1: that manage the virus well couldn't fully insulate themselves from 291 00:20:49,600 --> 00:20:54,600 Speaker 1: the global shock of COVID. Next week, on The Paycheck, 292 00:20:54,840 --> 00:20:56,800 Speaker 1: we had to a place with one of the lowest 293 00:20:57,000 --> 00:20:59,840 Speaker 1: death rates in the world, where more and more people 294 00:21:00,280 --> 00:21:05,479 Speaker 1: are feeling economic pain. It strikes against the singaple pledge. Right. 295 00:21:05,520 --> 00:21:09,680 Speaker 1: We pledge ourselves to developer justin equal society. If we 296 00:21:09,880 --> 00:21:14,040 Speaker 1: don't hold that, then there's something problematic. Thanks for listening 297 00:21:14,080 --> 00:21:16,920 Speaker 1: to The Paycheck. If you like our show, please head 298 00:21:16,920 --> 00:21:19,280 Speaker 1: on over to Apple Podcasts or wherever you listen to 299 00:21:19,359 --> 00:21:23,480 Speaker 1: podcasts to rate, review and subscribe. This episode was hosted 300 00:21:23,560 --> 00:21:27,359 Speaker 1: by Me Rebecca Greenfield and reported by Kelsey Butler. It 301 00:21:27,480 --> 00:21:31,040 Speaker 1: was edited by Kristin V. Brown with help from Francesca Leavy, 302 00:21:31,280 --> 00:21:35,320 Speaker 1: Janet Paskin, Rocksheeta Sluja, and Me. We also had editing 303 00:21:35,359 --> 00:21:39,560 Speaker 1: help from Daniel Balby, Shelley Banjo, Gilda to Carly, Nicole Flato, 304 00:21:39,840 --> 00:21:43,959 Speaker 1: Elissa McDonald, and Kai Schultz. This episode was produced by 305 00:21:44,000 --> 00:21:48,120 Speaker 1: Gildada Carly and sound engineered by Matt kim Our original 306 00:21:48,200 --> 00:21:52,520 Speaker 1: music is by Leo Sidron. Special thanks to Magnus Hendrickson, McKinnon, 307 00:21:52,560 --> 00:21:57,040 Speaker 1: Da Kuyper, Margaret Sutherland, and Stacy Wong. The voice actor 308 00:21:57,160 --> 00:22:01,240 Speaker 1: you heard was Veronica Colloe. Francesca O Leevie is Bloomberg's 309 00:22:01,280 --> 00:22:06,560 Speaker 1: head of podcasts. See you next week. H