ABOUT THE SPEAKER
Hans Rosling - Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus.

Why you should listen

Even the most worldly and well-traveled among us have had their perspectives shifted by Hans Rosling. A professor of global health at Sweden's Karolinska Institute, his work focused on dispelling common myths about the so-called developing world, which (as he pointed out) is no longer worlds away from the West. In fact, most of the Third World is on the same trajectory toward health and prosperity, and many countries are moving twice as fast as the west did.

What set Rosling apart wasn't just his apt observations of broad social and economic trends, but the stunning way he presented them. Guaranteed: You've never seen data presented like this. A presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling's hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.

Rosling's presentations were grounded in solid statistics (often drawn from United Nations and World Bank data), illustrated by the visualization software he developed. The animations transform development statistics into moving bubbles and flowing curves that make global trends clear, intuitive and even playful. During his legendary presentations, Rosling took this one step farther, narrating the animations with a sportscaster's flair.

Rosling developed the breakthrough software behind his visualizations through his nonprofit Gapminder, founded with his son and daughter-in-law. The free software — which can be loaded with any data — was purchased by Google in March 2007. (Rosling met the Google founders at TED.)

Rosling began his wide-ranging career as a physician, spending many years in rural Africa tracking a rare paralytic disease (which he named konzo) and discovering its cause: hunger and badly processed cassava. He co-founded Médecins sans Frontièrs (Doctors without Borders) Sweden, wrote a textbook on global health, and as a professor at the Karolinska Institut in Stockholm initiated key international research collaborations. He's also personally argued with many heads of state, including Fidel Castro.

Hans Rosling passed away in February 2017. He is greatly missed.


More profile about the speaker
Hans Rosling | Speaker | TED.com
TED@State

Hans Rosling: Let my dataset change your mindset

Filmed:
1,816,065 views

Talking at the US State Department this summer, Hans Rosling uses his fascinating data-bubble software to burst myths about the developing world. Look for new analysis on China and the post-bailout world, mixed with classic data shows.
- Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus. Full bio

Double-click the English transcript below to play the video.

00:16
I'm going to talk about your mindset.
0
0
4000
00:20
Does your mindset correspond to my dataset?
1
4000
4000
00:24
(Laughter)
2
8000
1000
00:25
If not, one or the other needs upgrading, isn't it?
3
9000
3000
00:28
When I talk to my students about global issues,
4
12000
4000
00:32
and I listen to them in the coffee break,
5
16000
2000
00:34
they always talk about "we" and "them."
6
18000
3000
00:37
And when they come back into the lecture room
7
21000
3000
00:40
I ask them, "What do you mean with "we" and "them"?
8
24000
2000
00:42
"Oh, it's very easy. It's the western world and it's the developing world," they say.
9
26000
3000
00:45
"We learned it in college."
10
29000
2000
00:47
And what is the definition then? "The definition?
11
31000
2000
00:49
Everyone knows," they say.
12
33000
2000
00:51
But then you know, I press them like this.
13
35000
2000
00:53
So one girl said, very cleverly, "It's very easy.
14
37000
2000
00:55
Western world is a long life in a small family.
15
39000
3000
00:58
Developing world is a short life in a large family."
16
42000
3000
01:01
And I like that definition, because it enabled me
17
45000
3000
01:04
to transfer their mindset
18
48000
2000
01:06
into the dataset.
19
50000
2000
01:08
And here you have the dataset.
20
52000
2000
01:10
So, you can see that what we have on this axis here
21
54000
2000
01:12
is size of family. One, two, three, four, five
22
56000
3000
01:15
children per woman on this axis.
23
59000
2000
01:17
And here, length of life, life expectancy,
24
61000
2000
01:19
30, 40, 50.
25
63000
2000
01:21
Exactly what the students said was their concept about the world.
26
65000
4000
01:25
And really this is about the bedroom.
27
69000
2000
01:27
Whether the man and woman decide to have small family,
28
71000
4000
01:31
and take care of their kids, and how long they will live.
29
75000
3000
01:34
It's about the bathroom and the kitchen. If you have soap, water and food, you know,
30
78000
4000
01:38
you can live long.
31
82000
2000
01:40
And the students were right. It wasn't that the world consisted --
32
84000
2000
01:42
the world consisted here, of one set of countries over here,
33
86000
4000
01:46
which had large families and short life. Developing world.
34
90000
4000
01:50
And we had one set of countries up there
35
94000
3000
01:53
which was the western world.
36
97000
2000
01:55
They had small families and long life.
37
99000
3000
01:58
And you are going to see here
38
102000
2000
02:00
the amazing thing that has happened in the world during my lifetime.
39
104000
4000
02:04
Then the developing countries applied
40
108000
2000
02:06
soap and water, vaccination.
41
110000
2000
02:08
And all the developing world started to apply family planning.
42
112000
3000
02:11
And partly to USA who help to provide
43
115000
2000
02:13
technical advice and investment.
44
117000
3000
02:16
And you see all the world moves over to a two child family,
45
120000
4000
02:20
and a life with 60 to 70 years.
46
124000
3000
02:23
But some countries remain back in this area here.
47
127000
3000
02:26
And you can see we still have Afghanistan down here.
48
130000
3000
02:29
We have Liberia. We have Congo.
49
133000
3000
02:32
So we have countries living there.
50
136000
2000
02:34
So the problem I had
51
138000
2000
02:36
is that the worldview that my students had
52
140000
4000
02:40
corresponds to reality in the world
53
144000
2000
02:42
the year their teachers were born.
54
146000
3000
02:45
(Laughter)
55
149000
3000
02:48
(Applause)
56
152000
3000
02:51
And we, in fact, when we have played this over the world.
57
155000
3000
02:54
I was at the Global Health Conference here in Washington last week,
58
158000
3000
02:57
and I could see the wrong concept
59
161000
3000
03:00
even active people in United States had,
60
164000
3000
03:03
that they didn't realize the improvement
61
167000
3000
03:06
of Mexico there, and China, in relation to United States.
62
170000
5000
03:11
Look here when I move them forward.
63
175000
2000
03:13
Here we go.
64
177000
7000
03:20
They catch up. There's Mexico.
65
184000
3000
03:23
It's on par with United States in these two social dimensions.
66
187000
3000
03:26
There was less than five percent
67
190000
2000
03:28
of the specialists in Global Health that was aware of this.
68
192000
3000
03:31
This great nation, Mexico,
69
195000
2000
03:33
has the problem that arms are coming from North,
70
197000
3000
03:36
across the borders, so they had to stop that,
71
200000
2000
03:38
because they have this strange relationship to the United States, you know.
72
202000
4000
03:42
But if I would change this axis here,
73
206000
4000
03:46
I would instead put income per person.
74
210000
3000
03:49
Income per person. I can put that here.
75
213000
3000
03:52
And we will then see
76
216000
2000
03:54
a completely different picture.
77
218000
2000
03:56
By the way, I'm teaching you
78
220000
2000
03:58
how to use our website, Gapminder World,
79
222000
2000
04:00
while I'm correcting this,
80
224000
2000
04:02
because this is a free utility on the net.
81
226000
3000
04:05
And when I now finally got it right,
82
229000
3000
04:08
I can go back 200 years in history.
83
232000
4000
04:12
And I can find United States up there.
84
236000
4000
04:16
And I can let the other countries be shown.
85
240000
3000
04:19
And now I have income per person on this axis.
86
243000
3000
04:22
And United States only had some, one, two thousand dollars at that time.
87
246000
3000
04:25
And the life expectancy was 35 to 40 years,
88
249000
4000
04:29
on par with Afghanistan today.
89
253000
2000
04:31
And what has happened in the world, I will show now.
90
255000
5000
04:36
This is instead of studying history
91
260000
2000
04:38
for one year at university.
92
262000
2000
04:40
You can watch me for one minute now and you'll see the whole thing.
93
264000
3000
04:43
(Laughter)
94
267000
2000
04:45
You can see how the brown bubbles, which is west Europe,
95
269000
5000
04:50
and the yellow one, which is the United States,
96
274000
3000
04:53
they get richer and richer and also
97
277000
2000
04:55
start to get healthier and healthier.
98
279000
2000
04:57
And this is now 100 years ago,
99
281000
2000
04:59
where the rest of the world remains behind.
100
283000
3000
05:02
Here we come. And that was the influenza.
101
286000
5000
05:07
That's why we are so scared about flu, isn't it?
102
291000
3000
05:10
It's still remembered. The fall of life expectancy.
103
294000
3000
05:13
And then we come up. Not until
104
297000
3000
05:16
independence started.
105
300000
2000
05:18
Look here You have China over there,
106
302000
2000
05:20
you have India over there,
107
304000
2000
05:22
and this is what has happened.
108
306000
8000
05:30
Did you note there, that we have Mexico up there?
109
314000
3000
05:33
Mexico is not at all on par with the United States,
110
317000
2000
05:35
but they are quite close.
111
319000
2000
05:37
And especially, it's interesting to see
112
321000
2000
05:39
China and the United States
113
323000
2000
05:41
during 200 years,
114
325000
3000
05:44
because I have my oldest son now working for Google,
115
328000
2000
05:46
after Google acquired this software.
116
330000
3000
05:49
Because in fact, this is child labor. My son and his wife sat in a closet
117
333000
3000
05:52
for many years and developed this.
118
336000
2000
05:54
And my youngest son, who studied Chinese in Beijing.
119
338000
4000
05:58
So they come in with the two perspectives I have, you know?
120
342000
4000
06:02
And my son, youngest son who studied in Beijing,
121
346000
2000
06:04
in China, he got a long-term perspective.
122
348000
4000
06:08
Whereas when my oldest son, who works for Google,
123
352000
2000
06:10
he should develop by quarter, or by half-year.
124
354000
4000
06:14
Or Google is quite generous, so he can have one or two years to go.
125
358000
3000
06:17
But in China they look generation after generation
126
361000
2000
06:19
because they remember
127
363000
3000
06:22
the very embarrassing period, for 100 years,
128
366000
2000
06:24
when they went backwards.
129
368000
2000
06:26
And then they would remember the first part
130
370000
3000
06:29
of last century, which was really bad,
131
373000
3000
06:32
and we could go by this so-called Great Leap Forward.
132
376000
3000
06:35
But this was 1963.
133
379000
2000
06:37
Mao Tse-Tung eventually brought health to China,
134
381000
4000
06:41
and then he died, and then Deng Xiaoping started
135
385000
2000
06:43
this amazing move forward.
136
387000
2000
06:45
Isn't it strange to see that the United States
137
389000
2000
06:47
first grew the economy, and then gradually got rich?
138
391000
4000
06:51
Whereas China could get healthy much earlier,
139
395000
3000
06:54
because they applied the knowledge of education, nutrition,
140
398000
4000
06:58
and then also benefits of penicillin
141
402000
3000
07:01
and vaccines and family planning.
142
405000
2000
07:03
And Asia could have social development
143
407000
3000
07:06
before they got the economic development.
144
410000
3000
07:09
So to me, as a public health professor,
145
413000
2000
07:11
it's not strange that all these countries grow so fast now.
146
415000
4000
07:15
Because what you see here, what you see here
147
419000
2000
07:17
is the flat world of Thomas Friedman,
148
421000
3000
07:20
isn't it.
149
424000
2000
07:22
It's not really, really flat.
150
426000
2000
07:24
But the middle income countries --
151
428000
2000
07:26
and this is where I suggest to my students,
152
430000
2000
07:28
stop using the concept "developing world."
153
432000
3000
07:31
Because after all, talking about the developing world
154
435000
3000
07:34
is like having two chapters in the history of the United States.
155
438000
4000
07:38
The last chapter is about present, and president Obama,
156
442000
4000
07:42
and the other is about the past,
157
446000
2000
07:44
where you cover everything from Washington
158
448000
2000
07:46
to Eisenhower.
159
450000
2000
07:48
Because Washington to Eisenhower,
160
452000
2000
07:50
that is what we find in the developing world.
161
454000
2000
07:52
We could actually go to Mayflower
162
456000
2000
07:54
to Eisenhower,
163
458000
2000
07:56
and that would be put together into a developing world,
164
460000
3000
07:59
which is rightly growing its cities in a very amazing way,
165
463000
3000
08:02
which have great entrepreneurs,
166
466000
2000
08:04
but also have the collapsing countries.
167
468000
3000
08:07
So, how could we make better sense about this?
168
471000
3000
08:10
Well, one way of trying is to see whether we could
169
474000
3000
08:13
look at income distribution.
170
477000
2000
08:15
This is the income distribution of peoples in the world,
171
479000
3000
08:18
from $1. This is where you have food to eat.
172
482000
3000
08:21
These people go to bed hungry.
173
485000
2000
08:23
And this is the number of people.
174
487000
2000
08:25
This is $10, whether you have a public or a private
175
489000
2000
08:27
health service system. This is where you can
176
491000
2000
08:29
provide health service for your family and school for your children,
177
493000
3000
08:32
and this is OECD countries:
178
496000
2000
08:34
Green, Latin America, East Europe.
179
498000
2000
08:36
This is East Asia, and the light blue there is South Asia.
180
500000
4000
08:40
And this is how the world changed.
181
504000
3000
08:43
It changed like this.
182
507000
2000
08:45
Can you see how it's growing? And how hundreds of millions
183
509000
3000
08:48
and billions is coming out of poverty in Asia?
184
512000
3000
08:51
And it goes over here?
185
515000
2000
08:53
And I come now, into projections,
186
517000
2000
08:55
but I have to stop at the door of Lehman Brothers there, you know, because --
187
519000
3000
08:58
(Laughter)
188
522000
3000
09:01
that's where the projections are not valid any longer.
189
525000
2000
09:03
Probably the world will do this.
190
527000
2000
09:05
and then it will continue forward like this.
191
529000
3000
09:08
But more or less, this is what will happen,
192
532000
2000
09:10
and we have a world which cannot be looked upon as divided.
193
534000
5000
09:15
We have the high income countries here,
194
539000
2000
09:17
with the United States as a leading power;
195
541000
3000
09:20
we have the emerging economies in the middle,
196
544000
3000
09:23
which provide a lot of the funding for the bailout;
197
547000
2000
09:25
and we have the low income countries here.
198
549000
3000
09:28
Yeah, this is a fact that from where the money comes,
199
552000
3000
09:31
they have been saving, you know, over the last decade.
200
555000
2000
09:33
And here we have the low income countries
201
557000
2000
09:35
where entrepreneurs are.
202
559000
2000
09:37
And here we have the countries in collapse and war,
203
561000
3000
09:40
like Afghanistan, Somalia, parts of Congo, Darfur.
204
564000
5000
09:45
We have all this at the same time.
205
569000
2000
09:47
That's why it's so problematic to describe what has happened
206
571000
2000
09:49
in the developing world.
207
573000
2000
09:51
Because it's so different, what has happened there.
208
575000
2000
09:53
And that's why I suggest
209
577000
2000
09:55
a slightly different approach of what you would call it.
210
579000
3000
09:58
And you have huge differences within countries also.
211
582000
4000
10:02
I heard that your departments here were by regions.
212
586000
3000
10:05
Here you have Sub-Saharan Africa, South Asia,
213
589000
3000
10:08
East Asia, Arab states,
214
592000
2000
10:10
East Europe, Latin America, and OECD.
215
594000
2000
10:12
And on this axis, GDP.
216
596000
2000
10:14
And on this, heath, child survival,
217
598000
2000
10:16
and it doesn't come as a surprise
218
600000
2000
10:18
that Africa south of Sahara is at the bottom.
219
602000
3000
10:21
But when I split it, when I split it
220
605000
2000
10:23
into country bubbles,
221
607000
2000
10:25
the size of the bubbles here is the population.
222
609000
3000
10:28
Then you see Sierra Leone and Mauritius, completely different.
223
612000
3000
10:31
There is such a difference within Sub-Saharan Africa.
224
615000
2000
10:33
And I can split the others. Here is the South Asian,
225
617000
3000
10:36
Arab world.
226
620000
2000
10:38
Now all your different departments.
227
622000
2000
10:40
East Europe, Latin America, and OECD countries.
228
624000
3000
10:43
And here were are. We have a continuum in the world.
229
627000
3000
10:46
We cannot put it into two parts.
230
630000
2000
10:48
It is Mayflower down here. It is Washington here,
231
632000
3000
10:51
building, building countries.
232
635000
2000
10:53
It's Lincoln here, advancing them.
233
637000
4000
10:57
It's Eisenhower bringing modernity into the countries.
234
641000
3000
11:00
And then it's United States today, up here.
235
644000
2000
11:02
And we have countries all this way.
236
646000
2000
11:04
Now, this is the important thing
237
648000
3000
11:07
of understanding how the world has changed.
238
651000
4000
11:11
At this point I decided to make a pause.
239
655000
4000
11:15
(Laughter)
240
659000
2000
11:17
And it is my task, on behalf of the rest of the world,
241
661000
3000
11:20
to convey a thanks to the U.S. taxpayers,
242
664000
4000
11:24
for Demographic Health Survey.
243
668000
2000
11:26
Many are not aware of -- no, this is not a joke.
244
670000
3000
11:29
This is very serious.
245
673000
2000
11:31
It is due to USA's continuous sponsoring
246
675000
4000
11:35
during 25 years of the very good methodology
247
679000
3000
11:38
for measuring child mortality
248
682000
2000
11:40
that we have a grasp of what's happening in the world.
249
684000
3000
11:43
(Applause)
250
687000
7000
11:50
And it is U.S. government at its best,
251
694000
3000
11:53
without advocacy, providing facts,
252
697000
3000
11:56
that it's useful for the society.
253
700000
2000
11:58
And providing data free of charge
254
702000
3000
12:01
on the internet, for the world to use. Thank you very much.
255
705000
3000
12:04
Quite the opposite of the World Bank,
256
708000
2000
12:06
who compiled data with government money,
257
710000
3000
12:09
tax money, and then they sell it to add a little profit,
258
713000
3000
12:12
in a very inefficient, Gutenberg way.
259
716000
3000
12:15
(Applause)
260
719000
6000
12:21
But the people doing that at the World Bank
261
725000
2000
12:23
are among the best in the world.
262
727000
2000
12:25
And they are highly skilled professionals.
263
729000
2000
12:27
It's just that we would like to upgrade our international agencies
264
731000
4000
12:31
to deal with the world in the modern way, as we do.
265
735000
3000
12:34
And when it comes to free data and transparency,
266
738000
3000
12:37
United States of America is one of the best.
267
741000
3000
12:40
And that doesn't come easy from the mouth of a Swedish public health professor.
268
744000
3000
12:43
(Laughter)
269
747000
3000
12:46
And I'm not paid to come here, no.
270
750000
3000
12:49
I would like to show you what happens with the data,
271
753000
2000
12:51
what we can show with this data.
272
755000
2000
12:53
Look here. This is the world.
273
757000
2000
12:55
With income down there and child mortality.
274
759000
2000
12:57
And what has happened in the world?
275
761000
2000
12:59
Since 1950, during the last 50 years
276
763000
3000
13:02
we have had a fall in child mortality.
277
766000
3000
13:05
And it is the DHS that makes it possible to know this.
278
769000
2000
13:07
And we had an increase in income.
279
771000
2000
13:09
And the blue former developing countries
280
773000
2000
13:11
are mixing up with the former industrialized western world.
281
775000
5000
13:16
We have a continuum. But we still have, of course,
282
780000
3000
13:19
Congo, up there. We still have as poor countries
283
783000
3000
13:22
as we have had, always, in history.
284
786000
4000
13:26
And that's the bottom billion, where we've heard today
285
790000
3000
13:29
about a completely new approach to do it.
286
793000
3000
13:32
And how fast has this happened?
287
796000
3000
13:35
Well, MDG 4.
288
799000
2000
13:37
The United States has not been so eager
289
801000
2000
13:39
to use MDG 4.
290
803000
3000
13:42
But you have been the main sponsor that has enabled us to measure it,
291
806000
3000
13:45
because it's the only child mortality that we can measure.
292
809000
3000
13:48
And we used to say that it should fall four percent per year.
293
812000
3000
13:51
Let's see what Sweden has done.
294
815000
2000
13:53
We used to boast about fast social progress.
295
817000
3000
13:56
That's where we were, 1900.
296
820000
2000
13:58
1900, Sweden was there.
297
822000
2000
14:00
Same child mortality as Bangladesh had, 1990,
298
824000
2000
14:02
though they had lower income.
299
826000
2000
14:04
They started very well. They used the aid well.
300
828000
3000
14:07
They vaccinated the kids. They get better water.
301
831000
2000
14:09
And they reduced child mortality,
302
833000
2000
14:11
with an amazing 4.7 percent per year. They beat Sweden.
303
835000
3000
14:14
I run Sweden the same 16 year period.
304
838000
4000
14:18
Second round, it's Sweden, 1916,
305
842000
2000
14:20
against Egypt, 1990.
306
844000
2000
14:22
Here we go. Once again the USA is part of the reason here.
307
846000
3000
14:25
They get safe water, they get food for the poor,
308
849000
4000
14:29
and they get malaria eradicated.
309
853000
2000
14:31
5.5 percent. They are faster than the millennium development goal.
310
855000
3000
14:34
And third chance for Sweden, against Brazil here.
311
858000
3000
14:37
Brazil here has amazing social improvement
312
861000
4000
14:41
over the last 16 years,
313
865000
2000
14:43
and they go faster than Sweden.
314
867000
2000
14:45
This means that the world is converging.
315
869000
2000
14:47
The middle income countries,
316
871000
2000
14:49
the emerging economy, they are catching up.
317
873000
2000
14:51
They are moving to cities,
318
875000
2000
14:53
where they also get better assistance for that.
319
877000
2000
14:55
Well the Swedish students protest at this point.
320
879000
3000
14:58
They say, "This is not fair,
321
882000
2000
15:00
because these countries had vaccines and antibiotics
322
884000
2000
15:02
that were not available for Sweden.
323
886000
2000
15:04
We have to do real-time competition."
324
888000
2000
15:06
Okay. I give you Singapore, the year I was born.
325
890000
3000
15:09
Singapore had twice the child mortality of Sweden.
326
893000
2000
15:11
It's the most tropical country in the world,
327
895000
2000
15:13
a marshland on the equator.
328
897000
2000
15:15
And here we go. It took a little time for them to get independent.
329
899000
3000
15:18
But then they started to grow their economy.
330
902000
2000
15:20
And they made the social investment. They got away malaria.
331
904000
2000
15:22
They got a magnificent health system
332
906000
2000
15:24
that beat both the U.S. and Sweden.
333
908000
2000
15:26
We never thought it would happen that they would win over Sweden!
334
910000
3000
15:29
(Applause)
335
913000
8000
15:37
All these green countries are achieving millennium development goals.
336
921000
3000
15:40
These yellow are just about to be doing this.
337
924000
2000
15:42
These red are the countries that doesn't do it, and the policy has to be improved.
338
926000
3000
15:45
Not simplistic extrapolation.
339
929000
3000
15:48
We have to really find a way
340
932000
2000
15:50
of supporting those countries in a better way.
341
934000
2000
15:52
We have to respect the middle income countries
342
936000
3000
15:55
on what they are doing.
343
939000
2000
15:57
And we have to fact-base the whole way we look at the world.
344
941000
3000
16:00
This is dollar per person. This is HIV in the countries.
345
944000
3000
16:03
The blue is Africa.
346
947000
2000
16:05
The size of the bubbles is how many are HIV affected.
347
949000
3000
16:08
You see the tragedy in South Africa there.
348
952000
2000
16:10
About 20 percent of the adult population are infected.
349
954000
3000
16:13
And in spite of them having quite a high income,
350
957000
3000
16:16
they have a huge number of HIV infected.
351
960000
3000
16:19
But you also see that there are African countries down here.
352
963000
3000
16:22
There is no such thing as an HIV epidemic in Africa.
353
966000
4000
16:26
There's a number, five to 10 countries in Africa
354
970000
3000
16:29
that has the same level as Sweden and United States.
355
973000
3000
16:32
And there are others who are extremely high.
356
976000
2000
16:34
And I will show you that what has happened
357
978000
3000
16:37
in one of the best countries, with the most vibrant economy
358
981000
4000
16:41
in Africa and a good governance, Botswana.
359
985000
3000
16:44
They have a very high level. It's coming down.
360
988000
2000
16:46
But now it's not falling,
361
990000
2000
16:48
because there, with help from PEPFAR,
362
992000
2000
16:50
it's working with treatment. And people are not dying.
363
994000
3000
16:53
And you can see it's not that easy,
364
997000
3000
16:56
that it is war which caused this.
365
1000000
3000
16:59
Because here, in Congo, there is war.
366
1003000
2000
17:01
And here, in Zambia, there is peace.
367
1005000
3000
17:04
And it's not the economy. Richer country has a little higher.
368
1008000
3000
17:07
If I split Tanzania in its income,
369
1011000
2000
17:09
the richer 20 percent in Tanzania
370
1013000
2000
17:11
has more HIV than the poorest one.
371
1015000
2000
17:13
And it's really different within each country.
372
1017000
3000
17:16
Look at the provinces of Kenya. They are very different.
373
1020000
2000
17:18
And this is the situation you see.
374
1022000
3000
17:21
It's not deep poverty. It's the special situation,
375
1025000
3000
17:24
probably of concurrent sexual partnership
376
1028000
3000
17:27
among part of the heterosexual population
377
1031000
3000
17:30
in some countries, or some parts of countries,
378
1034000
2000
17:32
in south and eastern Africa.
379
1036000
2000
17:34
Don't make it Africa. Don't make it a race issue.
380
1038000
3000
17:37
Make it a local issue. And do prevention at each place,
381
1041000
4000
17:41
in the way it can be done there.
382
1045000
2000
17:43
So to just end up,
383
1047000
3000
17:46
there are things of suffering
384
1050000
3000
17:49
in the one billion poorest, which we don't know.
385
1053000
3000
17:52
Those who live beyond the cellphone,
386
1056000
2000
17:54
those who have yet to see a computer,
387
1058000
2000
17:56
those who have no electricity at home.
388
1060000
3000
17:59
This is the disease, Konzo, I spent 20 years
389
1063000
2000
18:01
elucidating in Africa.
390
1065000
2000
18:03
It's caused by fast processing of toxic cassava root in famine situation.
391
1067000
5000
18:08
It's similar to the pellagra epidemic in Mississippi in the '30s.
392
1072000
4000
18:12
It's similar to other nutritional diseases.
393
1076000
3000
18:15
It will never affect a rich person.
394
1079000
2000
18:17
We have seen it here in Mozambique.
395
1081000
3000
18:20
This is the epidemic in Mozambique. This is an epidemic in northern Tanzania.
396
1084000
3000
18:23
You never heard about the disease.
397
1087000
2000
18:25
But it's much more than Ebola
398
1089000
2000
18:27
that has been affected by this disease.
399
1091000
2000
18:29
Cause crippling throughout the world.
400
1093000
2000
18:31
And over the last two years,
401
1095000
2000
18:33
2,000 people has been crippled
402
1097000
2000
18:35
in the southern tip of Bandundu region.
403
1099000
2000
18:37
That used to be the illegal diamond trade,
404
1101000
2000
18:39
from the UNITA-dominated area in Angola.
405
1103000
3000
18:42
That has now disappeared,
406
1106000
2000
18:44
and they are now in great economic problem.
407
1108000
2000
18:46
And one week ago, for the first time,
408
1110000
3000
18:49
there were four lines on the Internet.
409
1113000
3000
18:52
Don't get confused of the progress of the emerging economies
410
1116000
3000
18:55
and the great capacity
411
1119000
3000
18:58
of people in the middle income countries
412
1122000
2000
19:00
and in peaceful low income countries.
413
1124000
2000
19:02
There is still mystery in one billion.
414
1126000
2000
19:04
And we have to have more concepts
415
1128000
2000
19:06
than just developing countries and developing world.
416
1130000
3000
19:09
We need a new mindset. The world is converging,
417
1133000
3000
19:12
but -- but -- but not the bottom billion.
418
1136000
3000
19:15
They are still as poor as they've ever been.
419
1139000
3000
19:18
It's not sustainable, and it will not happen around one superpower.
420
1142000
5000
19:23
But you will remain
421
1147000
2000
19:25
one of the most important superpowers,
422
1149000
3000
19:28
and the most hopeful superpower, for the time to be.
423
1152000
3000
19:31
And this institution
424
1155000
2000
19:33
will have a very crucial role,
425
1157000
2000
19:35
not for United States, but for the world.
426
1159000
2000
19:37
So you have a very bad name,
427
1161000
3000
19:40
State Department. This is not the State Department.
428
1164000
2000
19:42
It's the World Department.
429
1166000
2000
19:44
And we have a high hope in you. Thank you very much.
430
1168000
2000
19:46
(Applause)
431
1170000
5000

▲Back to top

ABOUT THE SPEAKER
Hans Rosling - Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus.

Why you should listen

Even the most worldly and well-traveled among us have had their perspectives shifted by Hans Rosling. A professor of global health at Sweden's Karolinska Institute, his work focused on dispelling common myths about the so-called developing world, which (as he pointed out) is no longer worlds away from the West. In fact, most of the Third World is on the same trajectory toward health and prosperity, and many countries are moving twice as fast as the west did.

What set Rosling apart wasn't just his apt observations of broad social and economic trends, but the stunning way he presented them. Guaranteed: You've never seen data presented like this. A presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling's hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.

Rosling's presentations were grounded in solid statistics (often drawn from United Nations and World Bank data), illustrated by the visualization software he developed. The animations transform development statistics into moving bubbles and flowing curves that make global trends clear, intuitive and even playful. During his legendary presentations, Rosling took this one step farther, narrating the animations with a sportscaster's flair.

Rosling developed the breakthrough software behind his visualizations through his nonprofit Gapminder, founded with his son and daughter-in-law. The free software — which can be loaded with any data — was purchased by Google in March 2007. (Rosling met the Google founders at TED.)

Rosling began his wide-ranging career as a physician, spending many years in rural Africa tracking a rare paralytic disease (which he named konzo) and discovering its cause: hunger and badly processed cassava. He co-founded Médecins sans Frontièrs (Doctors without Borders) Sweden, wrote a textbook on global health, and as a professor at the Karolinska Institut in Stockholm initiated key international research collaborations. He's also personally argued with many heads of state, including Fidel Castro.

Hans Rosling passed away in February 2017. He is greatly missed.


More profile about the speaker
Hans Rosling | Speaker | TED.com