WEBVTT - Where to Be in a Pandemic 0:00:01.120 --> 0:00:05.520 Welcome to Prognosis. I'm Laura Carlson. It's day two hundred 0:00:05.519 --> 0:00:09.520 and fifty six since coronavirus was declared a global pandemic. 0:00:10.560 --> 0:00:15.320 Today we have a special edition of the show. Everyone 0:00:15.440 --> 0:00:19.799 is fighting the same coronavirus, but nearly a year into 0:00:19.840 --> 0:00:23.680 the pandemic, quality of life and control of the pathogens 0:00:23.760 --> 0:00:29.400 spread look vastly different across the world. Bloomberg's new COVID 0:00:29.440 --> 0:00:34.000 Resilience Ranking scores the largest fifty three economies on their 0:00:34.040 --> 0:00:38.479 success at containing the virus with the least amount of 0:00:38.600 --> 0:00:44.680 social or economic disruption. I spoke to Bloomberg's Rachel Chang, 0:00:44.920 --> 0:00:48.600 who worked on the Resilience ranking project, about the data 0:00:48.840 --> 0:00:52.920 and the analysis that went into determining the best places 0:00:53.120 --> 0:00:57.680 for weathering the pandemic. The findings on the relative strength 0:00:57.720 --> 0:01:01.280 of health care systems around the globe and how they've 0:01:01.320 --> 0:01:06.440 succeeded or failed to manage the pandemic may surprise you. 0:01:11.360 --> 0:01:14.720 I was wondering if you might start off just explaining 0:01:15.319 --> 0:01:19.200 what this new COVID Resilience ranking does and and who 0:01:19.240 --> 0:01:23.200 it's for. So our idea is to be able to 0:01:23.240 --> 0:01:28.000 give an accurate view, based on data of what's going 0:01:28.000 --> 0:01:30.560 on in the world right now, because what we've seen 0:01:30.600 --> 0:01:33.920 of COVID nineteen, it's it's pretty much the biggest public 0:01:33.920 --> 0:01:38.360 health crisis of a generation. And not only that, everything 0:01:38.400 --> 0:01:40.520 that we thought we knew about the world and how 0:01:40.560 --> 0:01:43.680 different countries would handle and a pandemic of this scale 0:01:43.840 --> 0:01:47.920 has actually been proven wrong. There were many pandemic preparedness 0:01:47.960 --> 0:01:53.040 and healthcare adequacy type of rankings before the COVID nineteen pandemic, 0:01:53.400 --> 0:01:55.920 and you had countries like the US and the UK 0:01:56.520 --> 0:01:59.320 top all of those rankings, which clearly have turned out 0:01:59.480 --> 0:02:02.480 to be wrong. At the same time, this year, we've 0:02:02.520 --> 0:02:05.960 seen a lot of quite surprising success stories. We've seen 0:02:06.360 --> 0:02:09.960 developing countries really come out with unique strategies. Some of 0:02:10.000 --> 0:02:13.560 them have eliminated the entire virus from their local communities. 0:02:14.600 --> 0:02:17.800 And so the starting point was really that COVID nineteen 0:02:17.880 --> 0:02:21.800 is going to transform has transformed the world, and Rachel, 0:02:21.960 --> 0:02:26.600 you know this, this tool has a wealth of data, 0:02:26.919 --> 0:02:30.320 um but of course we've seen a lot of questions, 0:02:30.720 --> 0:02:34.760 a lot of interrogation about whether or not COVID nineteen 0:02:34.840 --> 0:02:36.840 data can be trusted. And I was wondering if you 0:02:36.919 --> 0:02:41.520 might go into that as it relates to the resilience ranking, right. 0:02:41.560 --> 0:02:44.640 I mean, the starting point really was that we needed 0:02:44.639 --> 0:02:48.760 to have daily figures for cases and deaths, and a 0:02:48.760 --> 0:02:51.959 lot of places have collated that. The ones where the 0:02:52.320 --> 0:02:55.760 database we're relying on is by the Johns Hopkins University. 0:02:55.800 --> 0:03:01.640 Of course, we know that cases and fatalities underreported across 0:03:01.639 --> 0:03:06.440 the board. That's just um a reality for every country. 0:03:06.600 --> 0:03:09.720 It's not something that is limited just to developing countries 0:03:09.760 --> 0:03:14.040 with porous data. It's something that we've seen repeatedly in 0:03:14.200 --> 0:03:17.400 advanced economies as well. A big fact is just that 0:03:17.680 --> 0:03:21.080 testing was extremely inadequate in many major countries, and so 0:03:21.200 --> 0:03:22.720 there were a lot of people and I'm sure you 0:03:22.720 --> 0:03:25.480 know some who have felt that they probably were sick 0:03:25.520 --> 0:03:27.680 with COVID, but we're never able to get a test 0:03:27.680 --> 0:03:30.560 to confirm that. In terms of fatalities, a lot of 0:03:30.560 --> 0:03:33.680 people as well have died at home before being diagnosed. 0:03:34.040 --> 0:03:37.560 That's certain countries like Russia where if somebody has a 0:03:37.560 --> 0:03:41.720 core morbidity, has another disease and then dies after contracting 0:03:41.760 --> 0:03:45.880 COVID nineteen, sometimes they mark that down as a fatality 0:03:45.920 --> 0:03:48.360 not due to COVID nineteen. So from what we know 0:03:48.440 --> 0:03:52.520 from experts, all of that data is under reported, underdetected 0:03:52.640 --> 0:03:54.880 across the board. One of the things we're looking at 0:03:55.080 --> 0:03:57.920 UM in the future, although it's not available yet, is 0:03:57.960 --> 0:04:01.960 something called access mortality, that country's record for the whole year. 0:04:02.720 --> 0:04:06.080 So we can see in countries with pretty good overall 0:04:06.120 --> 0:04:10.720 death data by comparing what the number is to say 0:04:10.800 --> 0:04:14.760 nineteen or the average between twenty and you can see 0:04:14.760 --> 0:04:17.760 that access that will be due to COVID nineteen, and 0:04:17.839 --> 0:04:20.359 sometimes that is way more than what the official COVID 0:04:20.440 --> 0:04:23.720 nineteen fatality is. But having said all that, I think 0:04:23.760 --> 0:04:26.320 we have to go into this project with an understanding 0:04:26.360 --> 0:04:29.560 that the data is inadequate, that it probably won't be 0:04:29.600 --> 0:04:32.320 adequate for a long, long period of time. But at 0:04:32.320 --> 0:04:34.719 the same time, it's still a valuable way for us 0:04:34.800 --> 0:04:36.640 to have a picture of what's going on right now. 0:04:37.680 --> 0:04:40.000 And I was wondering if maybe we could break down 0:04:40.320 --> 0:04:44.320 some of the data UM that you do mention and 0:04:44.400 --> 0:04:47.960 include in the resilience ranking. And one is, of course, 0:04:48.320 --> 0:04:50.720 and this is a term we've heard used a lot, 0:04:51.320 --> 0:04:54.920 is the positive test rate. Why is this particular factor 0:04:55.080 --> 0:04:57.960 important when considering and and why did you choose to 0:04:58.000 --> 0:05:01.160 include it in the resilience ranking. So the positive test 0:05:01.279 --> 0:05:04.640 rate is something that experts do look at um to 0:05:04.680 --> 0:05:06.760 look at the situation in a country and how much 0:05:06.839 --> 0:05:10.560 undetected infection is in the community. So a very high 0:05:10.600 --> 0:05:14.600 positive test rate basically means that doctors are only testing 0:05:14.800 --> 0:05:17.479 the sickest people, people who have become so sick that 0:05:17.520 --> 0:05:20.120 they have to go to hospital very often, they are 0:05:20.200 --> 0:05:23.880 quite close to a very terrible deterioration in their disease um. 0:05:23.960 --> 0:05:26.040 And what that means is that there is just so 0:05:26.080 --> 0:05:28.919 many cases out there in your community that haven't been detected. 0:05:29.040 --> 0:05:32.719 These are people probably moving around and infecting other people. 0:05:33.160 --> 0:05:36.719 So it's a way to tell how contain or how 0:05:36.800 --> 0:05:40.400 in control the doctors and the officials are of a 0:05:40.560 --> 0:05:43.760 situation on the ground. So what we see, for example, 0:05:44.040 --> 0:05:49.080 is that when the infection the positive test rate falls 0:05:49.120 --> 0:05:52.359 below five percent for fourteen days, that is when the 0:05:52.520 --> 0:05:56.440 WHO says that governments should think about relaxing relaxing the 0:05:56.480 --> 0:06:00.280 lockdown restrictions. Prior to that, there's a dangerous amount of 0:06:00.320 --> 0:06:04.240 infection in the community. Now, speaking of lockdowns, actually that 0:06:04.400 --> 0:06:08.200 is another indicator you have on the ranking, the lockdown 0:06:08.360 --> 0:06:11.160 strictness indicator. And I was wondering if you might go 0:06:11.200 --> 0:06:14.680 into what that is and and maybe continuing on from 0:06:14.720 --> 0:06:17.640 your previous discussion, why is this so important for us 0:06:17.640 --> 0:06:20.520 to understand almost from a global level. Yeah, this is 0:06:20.520 --> 0:06:23.640 a very interesting indicator because I think it's something that's 0:06:23.640 --> 0:06:26.720 really evolved over the course of the crisis. So it's 0:06:26.720 --> 0:06:30.080 an indicator that's produced by Oxford University. They have a 0:06:30.080 --> 0:06:33.800 team of researchers which is monitoring the number and the 0:06:33.839 --> 0:06:37.040 strictness of lockdown policies that every government in the world 0:06:37.160 --> 0:06:40.720 is imposing. So and the initial phase of the crisis, 0:06:40.839 --> 0:06:44.599 what we did see is that countries that impose very 0:06:44.640 --> 0:06:47.720 strict measures very early on, so what we call that 0:06:47.880 --> 0:06:52.680 swift and up strong and early action, were very successful 0:06:52.839 --> 0:06:55.840 at containing the virus. So the economies that are ranked 0:06:56.000 --> 0:07:00.240 in our top ten, for example New Zealand, Taiwan as well, 0:07:00.600 --> 0:07:04.040 these were places that did have a really stringent reaction 0:07:04.080 --> 0:07:08.880 early on. But what we've actually seen as the pandemic 0:07:08.920 --> 0:07:12.360 has gone on is that if a government currently has 0:07:12.400 --> 0:07:16.880 the need to impose again stract policies of lockdown, that 0:07:16.960 --> 0:07:19.920 points to actually a failure of containing the coronavirus. The 0:07:20.040 --> 0:07:23.920 points to a failure of maintaining the gains from previous lockdowns, 0:07:24.320 --> 0:07:27.840 and so in the in our ranking, we've taken stringency 0:07:28.080 --> 0:07:31.400 as a negative thing. So the more stringent your current 0:07:31.440 --> 0:07:35.200 situation is, the lower your score in this indicator. Because 0:07:35.200 --> 0:07:37.200 I think what we've seen almost a year ender the 0:07:37.240 --> 0:07:40.920 pandemic is that that sort of disruption that lockdown's brain 0:07:41.200 --> 0:07:45.560 has been extremely economically costly, has been socially very costly 0:07:45.600 --> 0:07:49.000 to a lot of people. That's been a huge mental 0:07:49.000 --> 0:07:52.800 health toll from isolation and disruption, and we see it 0:07:52.800 --> 0:07:54.640 as a negative to people's lives, and that's what we 0:07:54.680 --> 0:07:58.560 wanted to reflect. Now that indicator does seem to have 0:07:58.640 --> 0:08:01.240 a lot to do with with something else on the ranking, 0:08:01.240 --> 0:08:03.960 which is community mobility. But I was wondering if you 0:08:04.040 --> 0:08:08.560 might go into how how that differs how the ranking 0:08:08.640 --> 0:08:13.320 for community mobility is slightly different from the lockdown indicator. Yeah, 0:08:13.320 --> 0:08:17.160 so the lockdown the stringency indicated from Oxford University UM 0:08:17.480 --> 0:08:22.560 is the number and strictness of government policies, and so 0:08:22.640 --> 0:08:24.840 you know, it captures the letter of what governments are 0:08:24.840 --> 0:08:27.880 trying to do, but it does not capture whether or 0:08:27.920 --> 0:08:32.400 not there is enforcement and compliance on the ground. And 0:08:32.440 --> 0:08:34.120 what we're seeing is that you know, there are a 0:08:34.160 --> 0:08:37.280 lot of places where governments are imposing all of these 0:08:37.320 --> 0:08:40.360 intense rules, but there's no enforcement, people are not following 0:08:40.360 --> 0:08:44.120 it um. And then there are also places where governments 0:08:44.160 --> 0:08:47.360 don't have to really impose any kind of rules, but 0:08:47.840 --> 0:08:50.600 because of a high level of social compliance and high 0:08:50.679 --> 0:08:55.719 level of population ownership of the problem, people kind of 0:08:55.880 --> 0:08:57.679 decide for themselves that they don't want to be as 0:08:57.720 --> 0:09:00.240 mobile as before and they stay home or when here 0:09:00.280 --> 0:09:03.640 that they are more cases. So that's two sides of 0:09:03.720 --> 0:09:07.760 the same coin of disruption. And so at this point 0:09:07.800 --> 0:09:11.880 we look at mobility as the higher mobility is to 0:09:12.000 --> 0:09:16.480 the pre pandemic baseline, the better situation on economy is 0:09:16.480 --> 0:09:31.880 in right now. One indicator that you do include on 0:09:31.920 --> 0:09:36.439 this ranking is going to be more and more relevant 0:09:36.559 --> 0:09:38.960 as we go forward in time, and certainly with the 0:09:38.960 --> 0:09:42.160 news from say Visor and bioin tech, something that we're 0:09:42.160 --> 0:09:44.960 all very optimistic about, and that is of course the 0:09:45.080 --> 0:09:48.720 vaccine access indicator. I was wondering if you might maybe 0:09:48.800 --> 0:09:52.040 unpack a little bit about what people can understand from 0:09:52.040 --> 0:09:54.800 from this data point. Yeah, this is a really exciting 0:09:54.960 --> 0:09:57.920 indicator and one that we put a lot of effort 0:09:57.960 --> 0:10:01.960 into piecing together. Going off on a database that was 0:10:02.000 --> 0:10:05.200 originally put together by some deep researchers. But you know, 0:10:05.240 --> 0:10:08.920 this is such a shifting thing. Countries are announcing new 0:10:08.960 --> 0:10:12.480 agreements every day, vaccines themselves are making so much progress 0:10:12.480 --> 0:10:14.200 every day, So it's something we've really had to keep 0:10:14.240 --> 0:10:16.920 on top of. But we think it's a really valuable 0:10:16.960 --> 0:10:20.200 way of uh, you know, not just revealing something that's, 0:10:20.400 --> 0:10:22.080 as you said, is is the most important thing that 0:10:22.080 --> 0:10:24.200 everybody is thinking about right now, but it's also a 0:10:24.240 --> 0:10:27.520 way to take that ranking and kind of pivoted towards 0:10:27.600 --> 0:10:32.040 the future because the biggest beneficiary of this indicator being 0:10:32.160 --> 0:10:36.760 included countries where in the US is the number one 0:10:36.800 --> 0:10:40.719 example of this, have really lost control of the epidemic, 0:10:40.960 --> 0:10:45.400 and the US well, the administration of the outgoing President 0:10:45.440 --> 0:10:48.240 Donald Trump has said openly that they don't want to 0:10:48.240 --> 0:10:52.760 contain the coronavirus. They want to use treatments and vaccines 0:10:53.280 --> 0:10:56.280 to solve the crisis. And we've seen them. We've seen 0:10:56.280 --> 0:10:59.400 the US poll almost twenty billion dollars into funding some 0:10:59.480 --> 0:11:02.240 of this res such and indeed, it's now in a 0:11:02.320 --> 0:11:07.360 situation where it has five separate vaccine agreements with five 0:11:07.360 --> 0:11:11.520 different Phase three candidates, and as we know vaccines like 0:11:11.720 --> 0:11:16.400 the FISO one has proven extraordinarily effective, and we know 0:11:16.520 --> 0:11:18.240 that that approval is going to come just in a 0:11:18.280 --> 0:11:20.160 couple of weeks, So it could very much be a 0:11:20.240 --> 0:11:23.920 game changer for countries who otherwise have lost control of 0:11:24.040 --> 0:11:28.080 their situations. I was wondering if you might just go 0:11:28.200 --> 0:11:31.320 through some of the other variables that are measured in 0:11:31.640 --> 0:11:34.960 the resilience ranking and and perhaps just very briefly the 0:11:35.080 --> 0:11:39.120 rationale and including some of these variables. So some of 0:11:39.160 --> 0:11:43.120 the other things that we've included pre pandemic measures, like, 0:11:43.520 --> 0:11:47.679 for example, the Universal Healthcare Coverage Indicator, which looks at 0:11:47.880 --> 0:11:52.200 twenty three different aspects of in the economies healthcare system, 0:11:52.320 --> 0:11:55.440 ranging from very basic stuff like basic childhood vaccines to 0:11:55.679 --> 0:11:59.040 something like cancer care. And what that indicator was shown, 0:11:59.040 --> 0:12:02.000 although it was the atabase was put together before COVID nineteen, 0:12:02.559 --> 0:12:03.960 was that it was really give an idea of the 0:12:03.960 --> 0:12:06.920 strength of the country's healthcare system, which we think makes 0:12:06.920 --> 0:12:10.680 a big difference in how patients are helped. The other 0:12:10.760 --> 0:12:12.880 thing that that does reflect is the ability of a 0:12:12.960 --> 0:12:17.360 place to continue providing non COVID nineteen healthcare even through 0:12:17.400 --> 0:12:20.200 the pandemic. And we've seen that that's quite an important 0:12:20.200 --> 0:12:23.800 facet for maintaining a normal life for a lot of people. 0:12:24.440 --> 0:12:27.360 Um another thing as well, We've included the United Nations 0:12:27.440 --> 0:12:31.360 Human Development Index, which is quite widely known and widely 0:12:31.480 --> 0:12:36.560 used as a measure of a country's well being. It's 0:12:36.559 --> 0:12:39.800 made up of three components. One of that is life expectancy, 0:12:40.320 --> 0:12:43.120 the second one is wealth per capita, and the third 0:12:43.160 --> 0:12:46.640 one is expected years of schooling, which we think can 0:12:46.679 --> 0:12:50.280 act as a proxy for populations trust in science, which 0:12:50.320 --> 0:12:52.880 has really emerged as something that makes a difference in 0:12:52.960 --> 0:12:57.880 terms of whether people are following public health guidance like 0:12:57.920 --> 0:13:01.040 mask wearing, handwashing. These times, small things can really make 0:13:01.080 --> 0:13:04.560 a big difference. How are you hoping a user of 0:13:04.640 --> 0:13:08.640 this tool can can apply this information? What can they 0:13:08.679 --> 0:13:11.560 take away from this resilience ranking? I think I think 0:13:11.600 --> 0:13:14.880 the main thing that people can take away, first of all, 0:13:15.080 --> 0:13:19.359 is that the coronavirus is not something that cannot be controlled. 0:13:19.679 --> 0:13:22.200 The economies that have placed really high on the ranking, 0:13:22.840 --> 0:13:25.800 a lot of the people in these places are living 0:13:25.880 --> 0:13:29.480 lives pretty much the pre pandemic life, you know, before 0:13:29.520 --> 0:13:33.880 COVID nineteen was even a thing. Decisive and United action 0:13:33.960 --> 0:13:37.319 has really helped some of these places control the coronavirus. 0:13:37.360 --> 0:13:39.319 I mean, Taiwan has gone two d days without a 0:13:39.360 --> 0:13:43.640 local case. Uh. You know, there's live music, social events, 0:13:43.760 --> 0:13:46.800 mass social events in New Zealand. What the ranking really 0:13:46.840 --> 0:13:49.720 provides is um an idea of where the look for 0:13:49.760 --> 0:13:52.040 some of these strategies. Right some of these countries have 0:13:52.200 --> 0:13:56.040 pioneered some of the best strategies to fight something like this. Secondly, 0:13:56.080 --> 0:13:58.960 I think what the virus really helps to do is 0:13:59.040 --> 0:14:02.040 to put things in past active for people, because I 0:14:02.040 --> 0:14:03.920 think it's pretty much a once in a lifetime thing 0:14:03.960 --> 0:14:07.120 where there is a single event that has affected people 0:14:07.160 --> 0:14:11.120 around the world in the same magnitude. And I think 0:14:11.160 --> 0:14:14.080 it's very important to have a perspective on, you know, 0:14:14.160 --> 0:14:16.959 a situation for example, like in Japan, which now is 0:14:17.080 --> 0:14:20.800 entering a winter wave and the capital of Tokyo just 0:14:21.000 --> 0:14:24.240 raised its alert to the highest level last week. But 0:14:24.320 --> 0:14:27.160 Japan is in a situation where there are thirty eight 0:14:27.240 --> 0:14:31.120 people in serious condition from COVID nineteen right now, which 0:14:32.040 --> 0:14:36.680 is an extraordinarily low amount by the standards of other places. 0:14:36.800 --> 0:14:40.560 And finally, I think it is a ranking that aims 0:14:40.640 --> 0:14:44.080 to kind of dispel some of the myths that people 0:14:44.120 --> 0:14:47.280 have to kind of change people's minds and show them 0:14:47.320 --> 0:14:50.560 that you know, the world is not that's not um 0:14:50.640 --> 0:14:52.800 exists accounting to some of these old ideas that we 0:14:52.880 --> 0:14:55.680 had that kind of ruled the world for so many years. Right, Like, 0:14:55.720 --> 0:14:58.320 the best healthcare systems are not necessarily where we think 0:14:58.320 --> 0:15:02.720 they are, the strongest scions let leadership, and not necessarily 0:15:02.720 --> 0:15:04.880 in the places that we think they are. And I 0:15:04.880 --> 0:15:07.120 think one of things that emerged that has emerged is 0:15:07.120 --> 0:15:11.720 that Asia as a region has been extremely effective at 0:15:11.720 --> 0:15:16.200 controlling a coronavirus because of very strong public health systems, 0:15:16.240 --> 0:15:19.200 because of contact traces on the ground, because of publicly 0:15:19.320 --> 0:15:23.800 funded nurses, because of free health coverage, and these are 0:15:23.800 --> 0:15:27.040 all things that we want to show people are very 0:15:27.080 --> 0:15:36.000 important in the coronavirus era. That was Rachel Chang and 0:15:36.080 --> 0:15:38.560 that's it for our show. To day. For coverage of 0:15:38.600 --> 0:15:41.920 the outbreak from one twenty bureaus around the world, visit 0:15:41.960 --> 0:15:46.800 Bloomberg dot com slash coronavirus and if you like the show, 0:15:47.240 --> 0:15:49.840 please leave us a review and a rating on Apple 0:15:49.880 --> 0:15:53.280 Podcasts or Spotify. It's the best way to help more 0:15:53.360 --> 0:15:57.840 listeners find our global reporting. The Prognosis Daily edition is 0:15:57.840 --> 0:16:02.640 produced by Tophor foreheads in Gaspore, Magnus Hendrickson, and Nie 0:16:03.000 --> 0:16:07.440 Laura Carlson. Today's main story was reported by Rachel Chang 0:16:07.560 --> 0:16:12.000 with help from Emma O'Brien. Original music by Leo Sidrin. 0:16:12.480 --> 0:16:16.680 Our editors are Rick Shine and Francesco Levi. Francesco Levi 0:16:17.000 --> 0:16:20.640 is Bloomberg's head of podcasts. Thanks for listening.