WEBVTT 00:00:00.000 --> 00:00:05.000 (Applause) 00:00:06.000 --> 00:00:11.000 AIDS was discovered 1981; the virus, 1983. 00:00:11.000 --> 00:00:13.000 These Gapminder bubbles show you 00:00:13.000 --> 00:00:17.000 how the spread of the virus was in 1983 in the world, 00:00:17.000 --> 00:00:19.000 or how we estimate that it was. 00:00:19.000 --> 00:00:21.000 What we are showing here is -- 00:00:21.000 --> 00:00:28.000 on this axis here, I'm showing percent of infected adults. 00:00:28.000 --> 00:00:33.000 And on this axis, I'm showing dollars per person in income. 00:00:33.000 --> 00:00:37.000 And the size of these bubbles, the size of the bubbles here, 00:00:37.000 --> 00:00:40.000 that shows how many are infected in each country, 00:00:40.000 --> 00:00:42.000 and the color is the continent. NOTE Paragraph 00:00:42.000 --> 00:00:44.000 Now, you can see United States, in 1983, 00:00:44.000 --> 00:00:47.000 had a very low percentage infected, 00:00:47.000 --> 00:00:51.000 but due to the big population, still a sizable bubble. 00:00:51.000 --> 00:00:54.000 There were quite many people infected in the United States. 00:00:54.000 --> 00:00:56.000 And, up there, you see Uganda. 00:00:56.000 --> 00:00:59.000 They had almost five percent infected, 00:00:59.000 --> 00:01:02.000 and quite a big bubble in spite of being a small country, then. 00:01:02.000 --> 00:01:07.000 And they were probably the most infected country in the world. 00:01:07.000 --> 00:01:09.000 Now, what has happened? 00:01:09.000 --> 00:01:11.000 Now you have understood the graph 00:01:11.000 --> 00:01:14.000 and now, in the next 60 seconds, 00:01:14.000 --> 00:01:17.000 we will play the HIV epidemic in the world. NOTE Paragraph 00:01:17.000 --> 00:01:20.000 But first, I have a new invention here. 00:01:22.000 --> 00:01:25.000 (Laughter) 00:01:27.000 --> 00:01:31.000 I have solidified the beam of the laser pointer. NOTE Paragraph 00:01:31.000 --> 00:01:34.000 (Laughter) NOTE Paragraph 00:01:34.000 --> 00:01:37.000 (Applause) NOTE Paragraph 00:01:40.000 --> 00:01:44.000 So, ready, steady, go! 00:01:44.000 --> 00:01:48.000 First, we have the fast rise in Uganda and Zimbabwe. 00:01:48.000 --> 00:01:50.000 They went upwards like this. 00:01:50.000 --> 00:01:54.000 In Asia, the first country to be heavily infected was Thailand -- 00:01:54.000 --> 00:01:56.000 they reached one to two percent. 00:01:56.000 --> 00:01:58.000 Then, Uganda started to turn back, 00:01:58.000 --> 00:02:00.000 whereas Zimbabwe skyrocketed, 00:02:00.000 --> 00:02:04.000 and some years later South Africa had a terrible rise of HIV frequency. 00:02:04.000 --> 00:02:06.000 Look, India got many infected, 00:02:06.000 --> 00:02:08.000 but had a low level. 00:02:08.000 --> 00:02:10.000 And almost the same happens here. 00:02:10.000 --> 00:02:13.000 See, Uganda coming down, Zimbabwe coming down, 00:02:13.000 --> 00:02:15.000 Russia went to one percent. NOTE Paragraph 00:02:15.000 --> 00:02:18.000 In the last two to three years, 00:02:18.000 --> 00:02:22.000 we have reached a steady state of HIV epidemic in the world. 00:02:22.000 --> 00:02:25.000 25 years it took. 00:02:25.000 --> 00:02:28.000 But, steady state doesn't mean that things are getting better, 00:02:28.000 --> 00:02:31.000 it's just that they have stopped getting worse. 00:02:31.000 --> 00:02:35.000 And it has -- the steady state is, more or less, 00:02:35.000 --> 00:02:39.000 one percent of the adult world population is HIV-infected. 00:02:39.000 --> 00:02:42.000 It means 30 to 40 million people, 00:02:42.000 --> 00:02:44.000 the whole of California -- every person, 00:02:44.000 --> 00:02:46.000 that's more or less what we have today in the world. NOTE Paragraph 00:02:46.000 --> 00:02:51.000 Now, let me make a fast replay of Botswana. 00:02:51.000 --> 00:02:55.000 Botswana -- upper middle-income country in southern Africa, 00:02:55.000 --> 00:02:58.000 democratic government, good economy, 00:02:58.000 --> 00:03:00.000 and this is what happened there. 00:03:00.000 --> 00:03:02.000 They started low, they skyrocketed, 00:03:02.000 --> 00:03:05.000 they peaked up there in 2003, 00:03:05.000 --> 00:03:07.000 and now they are down. 00:03:07.000 --> 00:03:09.000 But they are falling only slowly, 00:03:09.000 --> 00:03:11.000 because in Botswana, with good economy and governance, 00:03:11.000 --> 00:03:14.000 they can manage to treat people. 00:03:14.000 --> 00:03:17.000 And if people who are infected are treated, they don't die of AIDS. 00:03:17.000 --> 00:03:20.000 These percentages won't come down 00:03:20.000 --> 00:03:22.000 because people can survive 10 to 20 years. 00:03:22.000 --> 00:03:25.000 So there's some problem with these metrics now. 00:03:25.000 --> 00:03:29.000 But the poorer countries in Africa, the low-income countries down here, 00:03:29.000 --> 00:03:35.000 there the rates fall faster, of the percentage infected, 00:03:35.000 --> 00:03:37.000 because people still die. 00:03:37.000 --> 00:03:40.000 In spite of PEPFAR, the generous PEPFAR, 00:03:40.000 --> 00:03:43.000 all people are not reached by treatment, 00:03:43.000 --> 00:03:45.000 and of those who are reached by treatment in the poor countries, 00:03:45.000 --> 00:03:48.000 only 60 percent are left on treatment after two years. 00:03:48.000 --> 00:03:52.000 It's not realistic with lifelong treatment 00:03:52.000 --> 00:03:54.000 for everyone in the poorest countries. 00:03:54.000 --> 00:03:57.000 But it's very good that what is done is being done. NOTE Paragraph 00:03:57.000 --> 00:04:01.000 But focus now is back on prevention. 00:04:01.000 --> 00:04:04.000 It is only by stopping the transmission 00:04:04.000 --> 00:04:07.000 that the world will be able to deal with it. 00:04:07.000 --> 00:04:09.000 Drugs is too costly -- had we had the vaccine, 00:04:09.000 --> 00:04:12.000 or when we will get the vaccine, that's something more effective -- 00:04:12.000 --> 00:04:14.000 but the drugs are very costly for the poor. 00:04:14.000 --> 00:04:16.000 Not the drug in itself, but the treatment 00:04:16.000 --> 00:04:18.000 and the care which is needed around it. 00:04:20.000 --> 00:04:23.000 So, when we look at the pattern, 00:04:23.000 --> 00:04:25.000 one thing comes out very clearly: 00:04:25.000 --> 00:04:27.000 you see the blue bubbles 00:04:27.000 --> 00:04:29.000 and people say HIV is very high in Africa. 00:04:29.000 --> 00:04:32.000 I would say, HIV is very different in Africa. 00:04:32.000 --> 00:04:36.000 You'll find the highest HIV rate in the world 00:04:36.000 --> 00:04:38.000 in African countries, 00:04:38.000 --> 00:04:40.000 and yet you'll find Senegal, down here -- 00:04:40.000 --> 00:04:42.000 the same rate as United States. 00:04:42.000 --> 00:04:44.000 And you'll find Madagascar, 00:04:44.000 --> 00:04:46.000 and you'll find a lot of African countries 00:04:46.000 --> 00:04:49.000 about as low as the rest of the world. 00:04:49.000 --> 00:04:53.000 It's this terrible simplification that there's one Africa 00:04:53.000 --> 00:04:55.000 and things go on in one way in Africa. 00:04:55.000 --> 00:04:57.000 We have to stop that. 00:04:57.000 --> 00:05:00.000 It's not respectful, and it's not very clever 00:05:00.000 --> 00:05:02.000 to think that way. NOTE Paragraph 00:05:02.000 --> 00:05:06.000 (Applause) NOTE Paragraph 00:05:06.000 --> 00:05:09.000 I had the fortune to live and work for a time in the United States. 00:05:09.000 --> 00:05:13.000 I found out that Salt Lake City and San Francisco were different. 00:05:13.000 --> 00:05:15.000 (Laughter) 00:05:15.000 --> 00:05:18.000 And so it is in Africa -- it's a lot of difference. 00:05:18.000 --> 00:05:20.000 So, why is it so high? Is it war? 00:05:20.000 --> 00:05:22.000 No, it's not. Look here. 00:05:22.000 --> 00:05:25.000 War-torn Congo is down there -- two, three, four percent. 00:05:25.000 --> 00:05:29.000 And this is peaceful Zambia, neighboring country -- 15 percent. 00:05:29.000 --> 00:05:32.000 And there's good studies of the refugees coming out of Congo -- 00:05:32.000 --> 00:05:34.000 they have two, three percent infected, 00:05:34.000 --> 00:05:36.000 and peaceful Zambia -- much higher. 00:05:36.000 --> 00:05:38.000 There are now studies clearly showing 00:05:38.000 --> 00:05:41.000 that the wars are terrible, that rapes are terrible, 00:05:41.000 --> 00:05:44.000 but this is not the driving force for the high levels in Africa. NOTE Paragraph 00:05:44.000 --> 00:05:46.000 So, is it poverty? 00:05:46.000 --> 00:05:48.000 Well if you look at the macro level, 00:05:48.000 --> 00:05:50.000 it seems more money, more HIV. 00:05:50.000 --> 00:05:53.000 But that's very simplistic, 00:05:53.000 --> 00:05:55.000 so let's go down and look at Tanzania. 00:05:55.000 --> 00:05:59.000 I will split Tanzania in five income groups, 00:05:59.000 --> 00:06:01.000 from the highest income to the lowest income, 00:06:01.000 --> 00:06:03.000 and here we go. 00:06:03.000 --> 00:06:06.000 The ones with the highest income, the better off -- I wouldn't say rich -- 00:06:06.000 --> 00:06:08.000 they have higher HIV. 00:06:08.000 --> 00:06:11.000 The difference goes from 11 percent down to four percent, 00:06:11.000 --> 00:06:13.000 and it is even bigger among women. 00:06:13.000 --> 00:06:17.000 There's a lot of things that we thought, that now, good research, 00:06:17.000 --> 00:06:20.000 done by African institutions and researchers 00:06:20.000 --> 00:06:23.000 together with the international researchers, show that that's not the case. 00:06:23.000 --> 00:06:25.000 So, this is the difference within Tanzania. NOTE Paragraph 00:06:25.000 --> 00:06:27.000 And, I can't avoid showing Kenya. 00:06:27.000 --> 00:06:29.000 Look here at Kenya. 00:06:29.000 --> 00:06:31.000 I've split Kenya in its provinces. 00:06:31.000 --> 00:06:33.000 Here it goes. 00:06:33.000 --> 00:06:36.000 See the difference within one African country -- 00:06:36.000 --> 00:06:39.000 it goes from very low level to very high level, 00:06:39.000 --> 00:06:42.000 and most of the provinces in Kenya is quite modest. NOTE Paragraph 00:06:42.000 --> 00:06:44.000 So, what is it then? 00:06:44.000 --> 00:06:48.000 Why do we see this extremely high levels in some countries? 00:06:48.000 --> 00:06:51.000 Well, it is more common with multiple partners, 00:06:51.000 --> 00:06:54.000 there is less condom use, 00:06:54.000 --> 00:06:57.000 and there is age-disparate sex -- 00:06:57.000 --> 00:07:00.000 that is, older men tend to have sex with younger women. 00:07:00.000 --> 00:07:03.000 We see higher rates in younger women than younger men 00:07:03.000 --> 00:07:05.000 in many of these highly affected countries. NOTE Paragraph 00:07:05.000 --> 00:07:07.000 But where are they situated? 00:07:07.000 --> 00:07:09.000 I will swap the bubbles to a map. 00:07:09.000 --> 00:07:13.000 Look, the highly infected are four percent of all population 00:07:13.000 --> 00:07:16.000 and they hold 50 percent of the HIV-infected. 00:07:16.000 --> 00:07:19.000 HIV exists all over the world. 00:07:19.000 --> 00:07:21.000 Look, you have bubbles all over the world here. 00:07:21.000 --> 00:07:24.000 Brazil has many HIV-infected. 00:07:24.000 --> 00:07:27.000 Arab countries not so much, but Iran is quite high. 00:07:27.000 --> 00:07:31.000 They have heroin addiction and also prostitution in Iran. 00:07:31.000 --> 00:07:33.000 India has many because they are many. 00:07:33.000 --> 00:07:35.000 Southeast Asia, and so on. 00:07:35.000 --> 00:07:37.000 But, there is one part of Africa -- 00:07:37.000 --> 00:07:39.000 and the difficult thing is, at the same time, 00:07:39.000 --> 00:07:43.000 not to make a uniform statement about Africa, 00:07:43.000 --> 00:07:47.000 not to come to simple ideas of why it is like this, on one hand. NOTE Paragraph 00:07:47.000 --> 00:07:50.000 On the other hand, try to say that this is not the case, 00:07:50.000 --> 00:07:54.000 because there is a scientific consensus about this pattern now. 00:07:54.000 --> 00:07:57.000 UNAIDS have done good data available, finally, 00:07:57.000 --> 00:08:00.000 about the spread of HIV. 00:08:00.000 --> 00:08:03.000 It could be concurrency. 00:08:03.000 --> 00:08:06.000 It could be some virus types. 00:08:06.000 --> 00:08:10.000 It could be that there is other things 00:08:10.000 --> 00:08:13.000 which makes transmission occur in a higher frequency. 00:08:13.000 --> 00:08:16.000 After all, if you are completely healthy and you have heterosexual sex, 00:08:16.000 --> 00:08:21.000 the risk of infection in one intercourse is one in 1,000. 00:08:21.000 --> 00:08:23.000 Don't jump to conclusions now on how to 00:08:23.000 --> 00:08:25.000 behave tonight and so on. 00:08:25.000 --> 00:08:27.000 (Laughter) 00:08:27.000 --> 00:08:30.000 But -- and if you are in an unfavorable situation, 00:08:30.000 --> 00:08:33.000 more sexually transmitted diseases, it can be one in 100. NOTE Paragraph 00:08:33.000 --> 00:08:36.000 But what we think is that it could be concurrency. 00:08:36.000 --> 00:08:38.000 And what is concurrency? 00:08:38.000 --> 00:08:40.000 In Sweden, we have no concurrency. 00:08:40.000 --> 00:08:42.000 We have serial monogamy. 00:08:42.000 --> 00:08:44.000 Vodka, New Year's Eve -- new partner for the spring. 00:08:44.000 --> 00:08:46.000 Vodka, Midsummer's Eve -- new partner for the fall. 00:08:46.000 --> 00:08:48.000 Vodka -- and it goes on like this, you know? 00:08:48.000 --> 00:08:51.000 And you collect a big number of exes. 00:08:51.000 --> 00:08:53.000 And we have a terrible chlamydia epidemic -- 00:08:53.000 --> 00:08:57.000 terrible chlamydia epidemic which sticks around for many years. 00:08:57.000 --> 00:09:00.000 HIV has a peak three to six weeks after infection 00:09:00.000 --> 00:09:03.000 and therefore, having more than one partner in the same month 00:09:03.000 --> 00:09:06.000 is much more dangerous for HIV than others. 00:09:06.000 --> 00:09:08.000 Probably, it's a combination of this. NOTE Paragraph 00:09:08.000 --> 00:09:11.000 And what makes me so happy is that we are moving now 00:09:11.000 --> 00:09:13.000 towards fact when we look at this. 00:09:13.000 --> 00:09:15.000 You can get this chart, free. 00:09:15.000 --> 00:09:18.000 We have uploaded UNAIDS data on the Gapminder site. 00:09:18.000 --> 00:09:22.000 And we hope that when we act on global problems in the future 00:09:22.000 --> 00:09:25.000 we will not only have the heart, 00:09:25.000 --> 00:09:27.000 we will not only have the money, 00:09:27.000 --> 00:09:30.000 but we will also use the brain. NOTE Paragraph 00:09:30.000 --> 00:09:32.000 Thank you very much. NOTE Paragraph 00:09:32.000 --> 00:09:38.000 (Applause)