TED2009
Hans Rosling: Insights on HIV, in stunning data visuals
Hans Rosling 論HIV：新的事實與驚奇的視覺數據
Filmed:
Readability: 3.9
1,174,291 views
Hans Rosling 使用嶄新視覺效果去剖析世上其中一種最致命（亦最被人誤解）疾病的危險因素：愛滋病。他認為要結束這世紀流行病，關鍵在於預防傳染而非靠藥物治療。
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. Full bio
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.
00:12
(Applause)
0
0
5000
(掌聲)
00:18
AIDS was discovered 1981; the virus, 1983.
1
6000
5000
愛滋病是在1981年被發現的，而HIV病毒是在1983年
00:23
These Gapminder bubbles show you
2
11000
2000
這張 Gapminder 氣泡圖會顯示
00:25
how the spread of the virus was in 1983 in the world,
3
13000
4000
於1983年病毒在世界各地擴散的情況
00:29
or how we estimate that it was.
4
17000
2000
或者說是我們對它的估計
00:31
What we are showing here is --
5
19000
2000
今天我們要展示的是
00:33
on this axis here, I'm showing percent of infected adults.
6
21000
7000
這條（Y）軸，是被感染的成年人比例
00:40
And on this axis, I'm showing dollars per person in income.
7
28000
5000
而這條（X）軸，是人均收入（美元）
00:45
And the size of these bubbles, the size of the bubbles here,
8
33000
4000
而這些氣泡的大小
00:49
that shows how many are infected in each country,
9
37000
3000
代表每個國家被感染的人數
00:52
and the color is the continent.
10
40000
2000
而顏色代表不同洲分
00:54
Now, you can see United States, in 1983,
11
42000
2000
現在來看看1983年的美國
00:56
had a very low percentage infected,
12
44000
3000
當時的感染率還非常低
00:59
but due to the big population, still a sizable bubble.
13
47000
4000
但因為人口基數大，這個氣泡還是很大
01:03
There were quite many people infected in the United States.
14
51000
3000
也就是說在美國有很多人被感染
01:06
And, up there, you see Uganda.
15
54000
2000
在上面是烏干達
01:08
They had almost five percent infected,
16
56000
3000
感染率接近百分之五
01:11
and quite a big bubble in spite of being a small country, then.
17
59000
3000
雖然國家不大，但氣泡也不小
01:14
And they were probably the most infected country in the world.
18
62000
5000
他們可能是全世界感染率最高的國家
01:19
Now, what has happened?
19
67000
2000
為什麼會這樣？
01:21
Now you have understood the graph
20
69000
2000
我想大家現在都能看明白這個圖表了
01:23
and now, in the next 60 seconds,
21
71000
3000
在接下來的60秒裏
01:26
we will play the HIV epidemic in the world.
22
74000
3000
我們會展示愛滋病疫情在世界各地蔓延的過程
01:29
But first, I have a new invention here.
23
77000
3000
但在這之前，我要先拿出我的新發明
01:34
(Laughter)
24
82000
3000
(笑聲)
01:39
I have solidified the beam of the laser pointer.
25
87000
4000
我把鐳射筆的光線變成固體了
01:43
(Laughter)
26
91000
3000
(笑聲)
01:46
(Applause)
27
94000
3000
(掌聲)
01:52
So, ready, steady, go!
28
100000
4000
好，準備，坐穩了，開始！
01:56
First, we have the fast rise in Uganda and Zimbabwe.
29
104000
4000
最開始是烏干達和辛巴威的感染率飆升
02:00
They went upwards like this.
30
108000
2000
像這樣一直上升
02:02
In Asia, the first country to be heavily infected was Thailand --
31
110000
4000
在亞洲，第一個受嚴重感染的國家是泰國
02:06
they reached one to two percent.
32
114000
2000
感染率達到百分之一至二
02:08
Then, Uganda started to turn back,
33
116000
2000
然後烏干達開始回落
02:10
whereas Zimbabwe skyrocketed,
34
118000
2000
而辛巴威一飛沖天
02:12
and some years later South Africa had a terrible rise of HIV frequency.
35
120000
4000
幾年後南非的HIV感染率急劇上升
02:16
Look, India got many infected,
36
124000
2000
看這裏，印度也有很多人被感染
02:18
but had a low level.
37
126000
2000
但整體比率還很低
02:20
And almost the same happens here.
38
128000
2000
這裏也一樣
02:22
See, Uganda coming down, Zimbabwe coming down,
39
130000
3000
看，烏干達下降了，辛巴威下降了
02:25
Russia went to one percent.
40
133000
2000
俄羅斯上升到百分之一
02:27
In the last two to three years,
41
135000
3000
在過去的兩三年裏
02:30
we have reached a steady state of HIV epidemic in the world.
42
138000
4000
世界HIV疫情進入了穩定期
02:34
25 years it took.
43
142000
3000
這個穩定期需時25年
02:37
But, steady state doesn't mean that things are getting better,
44
145000
3000
但穩定並不意味著情況開始好轉
02:40
it's just that they have stopped getting worse.
45
148000
3000
只是不再惡化而已
02:43
And it has -- the steady state is, more or less,
46
151000
4000
穩定情況就是說
02:47
one percent of the adult world population is HIV-infected.
47
155000
4000
世界成年人口的百分之一感染了HIV病毒
02:51
It means 30 to 40 million people,
48
159000
3000
也就是說大約3000萬到4000萬人
02:54
the whole of California -- every person,
49
162000
2000
相當於加利福尼亞州的所有人口
02:56
that's more or less what we have today in the world.
50
164000
2000
這就是現在全世界愛滋病患者的大概數量
02:58
Now, let me make a fast replay of Botswana.
51
166000
5000
現在我們再快速看一下波札那的情況
03:03
Botswana -- upper middle-income country in southern Africa,
52
171000
4000
波札那是為於非洲南部中上收入國家
03:07
democratic government, good economy,
53
175000
3000
民主政府，經濟也不俗
03:10
and this is what happened there.
54
178000
2000
來看看這裏的情況
03:12
They started low, they skyrocketed,
55
180000
2000
他們的感染率一開始很低，然後火箭般竄升
03:14
they peaked up there in 2003,
56
182000
3000
在2003年達到頂峰
03:17
and now they are down.
57
185000
2000
現在有所下降
03:19
But they are falling only slowly,
58
187000
2000
但下降的速度很慢
03:21
because in Botswana, with good economy and governance,
59
189000
2000
因為波札那的經濟政治環境不錯
03:23
they can manage to treat people.
60
191000
3000
可以治療愛滋病患者
03:26
And if people who are infected are treated, they don't die of AIDS.
61
194000
3000
感染者只要接受治療就不會輕易死於愛滋病
03:29
These percentages won't come down
62
197000
3000
所以這個比例不會下降
03:32
because people can survive 10 to 20 years.
63
200000
2000
因為病毒帶菌者可以繼續活上10年到20年
03:34
So there's some problem with these metrics now.
64
202000
3000
所以這個計算方法現在有點問題
03:37
But the poorer countries in Africa, the low-income countries down here,
65
205000
4000
但一些非洲的窮國，像下面的這些低收入國家
03:41
there the rates fall faster, of the percentage infected,
66
209000
6000
感染比例下降得很快
03:47
because people still die.
67
215000
2000
因為感染者在不斷死亡
03:49
In spite of PEPFAR, the generous PEPFAR,
68
217000
3000
儘管有慷慨的"總統愛滋病緊急防治救援計畫"（PEPFAR）
03:52
all people are not reached by treatment,
69
220000
3000
卻不是所有人都能得到治療
03:55
and of those who are reached by treatment in the poor countries,
70
223000
2000
在這些貧窮國家中，即使是受到治療的那些病人
03:57
only 60 percent are left on treatment after two years.
71
225000
3000
兩年後也只剩下60%的人還在治療計畫中
04:00
It's not realistic with lifelong treatment
72
228000
4000
對窮國中的每一個患者
04:04
for everyone in the poorest countries.
73
232000
2000
進行終身治療是不切實際的
04:06
But it's very good that what is done is being done.
74
234000
3000
但畢竟這些工作已經很好
04:09
But focus now is back on prevention.
75
237000
4000
但現在的關注點已經回到了防預工作上
04:13
It is only by stopping the transmission
76
241000
3000
只有阻止傳播
04:16
that the world will be able to deal with it.
77
244000
3000
我們的世界才會有機會對抗愛滋病
04:19
Drugs is too costly -- had we had the vaccine,
78
247000
2000
藥物太貴了 -- 要是有疫苗就好了
04:21
or when we will get the vaccine, that's something more effective --
79
249000
3000
或者知道什麼時候會有疫苗，這樣會有效得多
04:24
but the drugs are very costly for the poor.
80
252000
2000
但藥物對窮人來說太貴了
04:26
Not the drug in itself, but the treatment
81
254000
2000
並不是藥物本身貴，而是整個治療過程
04:28
and the care which is needed around it.
82
256000
2000
以及所需的看護很貴
04:32
So, when we look at the pattern,
83
260000
3000
所以，我們看看整個圖表
04:35
one thing comes out very clearly:
84
263000
2000
有一件事非常清楚：
04:37
you see the blue bubbles
85
265000
2000
你看那些藍色的氣泡
04:39
and people say HIV is very high in Africa.
86
267000
2000
人們會說非洲的HIV比率很高
04:41
I would say, HIV is very different in Africa.
87
269000
3000
我必須說，HIV在非洲也是非常不同的
04:44
You'll find the highest HIV rate in the world
88
272000
4000
你們會發現世界上最高的HIV感染率
04:48
in African countries,
89
276000
2000
是在非洲國家
04:50
and yet you'll find Senegal, down here --
90
278000
2000
但這裏也有塞內加爾，在下面
04:52
the same rate as United States.
91
280000
2000
感染率和美國一樣
04:54
And you'll find Madagascar,
92
282000
2000
也有馬達加斯加
04:56
and you'll find a lot of African countries
93
284000
2000
而其他很多非洲國家
04:58
about as low as the rest of the world.
94
286000
3000
和世界其他地方的感染率一樣低
05:01
It's this terrible simplification that there's one Africa
95
289000
4000
所以認為非洲的所有事情都是一個樣
05:05
and things go on in one way in Africa.
96
293000
2000
將非洲簡單地同一化是很可怕的
05:07
We have to stop that.
97
295000
2000
我們不能再這麼想
05:09
It's not respectful, and it's not very clever
98
297000
3000
這麼想很不尊重他們
05:12
to think that way.
99
300000
2000
也很不明智
05:14
(Applause)
100
302000
4000
(掌聲)
05:18
I had the fortune to live and work for a time in the United States.
101
306000
3000
我有幸在美國生活和工作過一段時間
05:21
I found out that Salt Lake City and San Francisco were different.
102
309000
4000
我發現鹽湖城和舊金山就很不一樣
05:25
(Laughter)
103
313000
2000
(笑聲)
05:27
And so it is in Africa -- it's a lot of difference.
104
315000
3000
非洲也是一樣 -- 各地有很多不同
05:30
So, why is it so high? Is it war?
105
318000
2000
那，為什麼比率會這麼高呢？是因為戰爭的關係？
05:32
No, it's not. Look here.
106
320000
2000
不是的。看這裏
05:34
War-torn Congo is down there -- two, three, four percent.
107
322000
3000
飽經戰火的剛果在下面 -- 百分之二、三、四的樣子
05:37
And this is peaceful Zambia, neighboring country -- 15 percent.
108
325000
4000
而和平的鄰國赞比亚 -- 百分之十五
05:41
And there's good studies of the refugees coming out of Congo --
109
329000
3000
有人研究過剛果難民的感染率
05:44
they have two, three percent infected,
110
332000
2000
也在百分之二到三之間
05:46
and peaceful Zambia -- much higher.
111
334000
2000
而和平的赞比亚要高得多
05:48
There are now studies clearly showing
112
336000
2000
現在有研究明確岀指出
05:50
that the wars are terrible, that rapes are terrible,
113
338000
3000
雖然有很多戰爭，很多強暴事件發生
05:53
but this is not the driving force for the high levels in Africa.
114
341000
3000
但這並不是非洲HIV病毒高比率的主要原因
05:56
So, is it poverty?
115
344000
2000
所以，是因為貧窮嗎？
05:58
Well if you look at the macro level,
116
346000
2000
如果我們從宏觀角度看看
06:00
it seems more money, more HIV.
117
348000
2000
好像錢越多，HIV就越多
06:02
But that's very simplistic,
118
350000
3000
但這過於簡單化了
06:05
so let's go down and look at Tanzania.
119
353000
2000
我們來仔細看看坦桑尼亞的情況
06:07
I will split Tanzania in five income groups,
120
355000
4000
我把坦桑尼亞人按收入分成五組
06:11
from the highest income to the lowest income,
121
359000
2000
從最高收入到最低收入
06:13
and here we go.
122
361000
2000
我們來看看
06:15
The ones with the highest income, the better off -- I wouldn't say rich --
123
363000
3000
收入最高的人，處境較好的人，我不會叫他們富人
06:18
they have higher HIV.
124
366000
2000
他們的HIV感染率更高
06:20
The difference goes from 11 percent down to four percent,
125
368000
3000
感染率最高有百分之十一，最低的到百分之四
06:23
and it is even bigger among women.
126
371000
2000
婦女中這個差距更大
06:25
There's a lot of things that we thought, that now, good research,
127
373000
4000
許多我們以前的想法，被現在許多由
06:29
done by African institutions and researchers
128
377000
3000
非洲及國際機構和研究人員所做的研究
06:32
together with the international researchers, show that that's not the case.
129
380000
3000
證實是錯誤的
06:35
So, this is the difference within Tanzania.
130
383000
2000
這是坦桑尼亞的例子
06:37
And, I can't avoid showing Kenya.
131
385000
2000
我必須再舉一下肯亞的例子
06:39
Look here at Kenya.
132
387000
2000
來看看肯亞
06:41
I've split Kenya in its provinces.
133
389000
2000
我按省份劃分肯亞
06:43
Here it goes.
134
391000
2000
來看看
06:45
See the difference within one African country --
135
393000
3000
在同一個非洲國家裏的差別
06:48
it goes from very low level to very high level,
136
396000
3000
從很低的水平到很高的水平
06:51
and most of the provinces in Kenya is quite modest.
137
399000
3000
而肯亞大部分的省份感染率並不高
06:54
So, what is it then?
138
402000
2000
那到底是什麼原因呢？
06:56
Why do we see this extremely high levels in some countries?
139
404000
4000
為什麼有些國家的感染率那麼高？
07:00
Well, it is more common with multiple partners,
140
408000
3000
其中因素包括有多個性伴侶，
07:03
there is less condom use,
141
411000
3000
或不愛用避孕套
07:06
and there is age-disparate sex --
142
414000
3000
或有年齡差異大的性愛因素
07:09
that is, older men tend to have sex with younger women.
143
417000
3000
就是大年紀男人喜歡跟年輕女人做愛
07:12
We see higher rates in younger women than younger men
144
420000
3000
所以我們發現在很多感染率較高的國家裏
07:15
in many of these highly affected countries.
145
423000
2000
年輕女性的感染率要高於年輕男性
07:17
But where are they situated?
146
425000
2000
那地理上的分佈又是怎麼樣呢？
07:19
I will swap the bubbles to a map.
147
427000
2000
我把氣泡轉移到地圖上
07:21
Look, the highly infected are four percent of all population
148
429000
4000
看，感染率高的國家佔世界人口的百分之四
07:25
and they hold 50 percent of the HIV-infected.
149
433000
3000
但卻有全球百分之五十的HIV感染者
07:28
HIV exists all over the world.
150
436000
3000
HIV在世界各地都存在
07:31
Look, you have bubbles all over the world here.
151
439000
2000
看，氣泡分佈在所有地方
07:33
Brazil has many HIV-infected.
152
441000
3000
巴西有很多HIV感染者
07:36
Arab countries not so much, but Iran is quite high.
153
444000
3000
阿拉伯國家不多，但伊朗很高
07:39
They have heroin addiction and also prostitution in Iran.
154
447000
4000
伊朗的問題是海洛因和賣淫
07:43
India has many because they are many.
155
451000
2000
印度有很多因為它本身人口多
07:45
Southeast Asia, and so on.
156
453000
2000
以及東南亞等等
07:47
But, there is one part of Africa --
157
455000
2000
但非洲有一部分 --
07:49
and the difficult thing is, at the same time,
158
457000
2000
同時要注意的是
07:51
not to make a uniform statement about Africa,
159
459000
4000
不要說到非洲就想到整個非洲
07:55
not to come to simple ideas of why it is like this, on one hand.
160
463000
4000
一方面不要認為出現現在的情況是因為單一的原因
07:59
On the other hand, try to say that this is not the case,
161
467000
3000
另一方面要承認現在的情況很嚴重
08:02
because there is a scientific consensus about this pattern now.
162
470000
4000
現在科學界已經對這個分佈圖達成了共識
08:06
UNAIDS have done good data available, finally,
163
474000
3000
UNAIDS終於提供了HIV傳播的
08:09
about the spread of HIV.
164
477000
3000
詳細數據
08:12
It could be concurrency.
165
480000
3000
可能是由於多重性伴
08:15
It could be some virus types.
166
483000
3000
也可能是某些病毒種類
08:18
It could be that there is other things
167
486000
4000
也可能是有別的原因
08:22
which makes transmission occur in a higher frequency.
168
490000
3000
使病毒傳播到這樣高的比例
08:25
After all, if you are completely healthy and you have heterosexual sex,
169
493000
3000
不管怎樣，如果你完全健康並且是異性戀
08:28
the risk of infection in one intercourse is one in 1,000.
170
496000
5000
每次性交被感染的機會是千分之一
08:33
Don't jump to conclusions now on how to
171
501000
2000
但別輕易得出結論
08:35
behave tonight and so on.
172
503000
2000
今晚就去胡混
08:37
(Laughter)
173
505000
2000
(笑聲)
08:39
But -- and if you are in an unfavorable situation,
174
507000
3000
但是，如果你處於不利情況
08:42
more sexually transmitted diseases, it can be one in 100.
175
510000
3000
通過性傳染的疾病機會可以達到百分之一
08:45
But what we think is that it could be concurrency.
176
513000
3000
但我們認為多個性伴可能是主要原因
08:48
And what is concurrency?
177
516000
2000
什麼是多重性伴侶？
08:50
In Sweden, we have no concurrency.
178
518000
2000
在瑞典我們沒有多重性伴侶
08:52
We have serial monogamy.
179
520000
2000
我們是連續的單一性伴侶
08:54
Vodka, New Year's Eve -- new partner for the spring.
180
522000
2000
喝伏特加，除夕夜 -- 春天有新性伴了
08:56
Vodka, Midsummer's Eve -- new partner for the fall.
181
524000
2000
喝伏特加，仲夏夜 -- 秋天有新性伴了
08:58
Vodka -- and it goes on like this, you know?
182
526000
2000
喝伏特加 -- 繼續這樣子，你們明白了嗎？
09:00
And you collect a big number of exes.
183
528000
3000
這樣你會有很多“前”男、女朋友
09:03
And we have a terrible chlamydia epidemic --
184
531000
2000
有一種可怕的衣原體傳染病
09:05
terrible chlamydia epidemic which sticks around for many years.
185
533000
4000
這種可怕的衣原體傳染病持續多年
09:09
HIV has a peak three to six weeks after infection
186
537000
3000
而HIV是在感染後的三到六周有一個活動高峰
09:12
and therefore, having more than one partner in the same month
187
540000
3000
因此，在一個月裏有多個性夥伴
09:15
is much more dangerous for HIV than others.
188
543000
3000
對HIV傳播是特別危險的
09:18
Probably, it's a combination of this.
189
546000
2000
很可能，這是原因之一
09:20
And what makes me so happy is that we are moving now
190
548000
3000
還有令我高興的是,當我們在考慮這些因素的時候
09:23
towards fact when we look at this.
191
551000
2000
我們也不斷地向真相邁步
09:25
You can get this chart, free.
192
553000
2000
大家可以免費取得這份圖表
09:27
We have uploaded UNAIDS data on the Gapminder site.
193
555000
3000
我們把UNAIDS的資料上傳到Gapminder.org
09:30
And we hope that when we act on global problems in the future
194
558000
4000
並且希望將來在解決全球性問題時
09:34
we will not only have the heart,
195
562000
3000
我們不僅帶著一顆心
09:37
we will not only have the money,
196
565000
2000
不僅帶著錢
09:39
but we will also use the brain.
197
567000
3000
也多用腦子
09:42
Thank you very much.
198
570000
2000
謝謝大家
09:44
(Applause)
199
572000
6000
(掌聲)
ABOUT THE SPEAKER
Hans Rosling - Global health expert; data visionaryIn 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.
Hans Rosling | Speaker | TED.com